Freeze drying produced lighter potato flour (L* = 92.86) compared to the other methods. Boiling and blanching at 95 °C followed by oven drying recorded a low angle of repose and compressibility index, indicating better flow characteristics. The smallest particle size (56.5 µm) was recorded for the freeze-drying treatment, while boiling followed by oven drying had the largest particle size (307.5 µm). Microstructural results indicate that boiling and blanching at 95 °C, followed by oven drying resulted in damaged starch granules, while freeze-drying and low-temperature blanching (60 °C) maintained the native starch granule. Particle size and the solubility index of potato flour showed strong positive correlation. This study revealed that the pretreatments and drying methods affected potato flour’s physical and microstructural parameters differently, resulting in changes in their functionality.This study evaluated the effects of pretreatments (blanching (60 and 95 °C) and boiling) and drying methods (freeze-drying and oven drying) on the quality characteristics of potato flour derived from three potato varieties, namely, Shangi, Unica, and Dutch Robjin. The percentage flour yield, color, particle size distribution, flow characteristics, microstructural and functional properties of the potato flour were determined. Unica recorded the least peeling loss, while the Dutch Robjin variety had the highest. Color parameters were significantly affected ( Solanum tuberosum L.) is considered to be an important food crop after rice, wheat, and maize [The potato  grown in Kenya, namely, Shangi, Unica, and Dutch Robjin, were procured locally from Nyandarua county. These varieties are the most commonly consumed and used in diverse applications in industries [Three popular potato varieties  .(1)AmouOne kilogram of each of the three potato varieties was washed and manually peeled with a sharp stainless-steel knife. The peeled potatoes were cut into thin slices and then kept in water containing 0.5% sodium metabisulfite (SMB) for 5 min to prevent enzymatic darkening . The thiBlanched potato flours were prepared according to the methods described by , with a Boiled potato flour was prepared using a method as previously described . Washed This was conducted as described by , with slOne kilogram of each potato variety was washed and manually peeled with a sharp stainless-steel knife. After peeling, potatoes underwent pretreatments to produce flour, as explained in Potato flour color was measured using a HunterLab’s ColorFLex EZ spectrophotometer. The instrument was first calibrated by using white and black tiles as the standards. Next, potato flour was tightly packed in an optically transparent glass cup and covered with another opaque cover, used as a light trap to prevent the external light from interfering with the sample cup. The clear glass containing the flour was then placed on the port. Light from the spectrophotometer was flashed on the sample, and the color intensity was recorded. The potato flour color was reported in terms of 3-dimensional color values on the following rating scale: Lightness L* ranges from (black (0) to light (100)), a* from red (60) to green (−60), and b* ranges from yellow (60) to blue (−60). Measurements were conducted in triplicate. a* and b* values were used to calcite values for hue angle (H*) and chroma (C*) (Equations (3) and (4)), two parameters that are used for describing the visual color appearance .H* = ta7H8) was used instead water because it is absorbed by flour to a lesser extent. Approximately 1 g of potato flour was filled in a measuring cylinder containing toluene. The rise in toluene level was measured twice. True density was calculated as indicated in Equation (5):True density was calculated according to . TolueneT). Bulk and tapped density were calculated as shown in Equations (6) and (7):The bulk and tapped density of potato flour were determined according to the method described by . Potato The compressibility index of potato flour was determined on the basis of bulk density and tapped density as described by   was determined by using the method described by . A funneParticle size distribution was determined as described by . A laserThe potato flour was observed using a polarized optical microscope , Italy) equipped with a camera (Optikam HDMI Pro Camera). A thin layer of potato flour was placed on a microscope slide and dispersed using a drop of distilled water. All images were observed and photographed at 20× magnification under an X-LED white illumination.Flour micrographs were taken using a scanning electron microscope ). Potato flour was suspended on an aluminum stub using double-sided adhesive tape. Accelerating potential of 15 kV and magnification of 300× were used during micrography.The solubility index of potato flour was determined following the method of , with slAll analyses were carried out in triplicate and expressed as means of standard errors. Data were subjected to statistical analysis using R-Console software. Results were analyzed using a one-way analysis of variance (ANOVA). In addition, the least-significance test (LSD) set at the 5% probability level was applied.The Dutch Robjin variety recorded the highest percentage peel loss (25%), while Unica showed the least (8%) . This diPotato flour yields from the different potato varieties as affected by pretreatments and drying methods are shown in There was a significant difference in the yield of potato flour obtained from the different processing methods. Boiling followed by oven drying resulted in the lowest flour yield in all the three varieties. This might have been associated with the leaching of starch during boiling. On the other hand, the Dutch Robjin resulted in the highest flour yield in all the processing conditions. This might be attributed to its high specific gravity and dry matter compared to the other varieties ,36,45. TThe color parameters of the potato flour varied greatly depending on the different pretreatments and drying methods . Only reFreeze-dried flour recorded the highest value of L* (92.86) and the lowest a* (−0.65) value. A higher L* value indicates white flour and a lower browning index . Flours p < 0.05) in the bulk density of the potato flour prepared under different conditions  influenced the true density of potato flour. The true density of the flours varied from 1.46 g/mL to 1.65 g/mL. Freeze-dried flour had the lowest true density compared to other treatments. This could be attributed to the ice sublimation during freeze-drying which creates more pores within the samples [Tapped density is determined to correct the fluctuation of the total volume of interparticle voids during transportation, drying, and packing processes. It is the maximal packing produced under the impact of an externally applied force. It indicates the volume of a mass of the sample after tapping the container to cause a closer packing of particles. Consequently, freeze-dried potato flour was more porous, since it had the lowest tapped density. This is because freeze-dried powder granules have small particles that can agglomerate to form a clumpy powder, thus producing more voids between them . The con samples .The effects of different pretreatments and drying methods on compressibility index and angle of repose of potato flour are shown in The compressibility index ranged from 13.48% to 31.56% for boiling, followed by oven drying and freeze-drying, respectively. Boiling and blanching at high temperature (95°C) showed a minor compressibility index meaning that the flour has good flowability characteristics. Conversely, oven drying and freeze-drying had the highest compressibility indexes indicating poor flow behavior (cohesiveness). Flours with good flow behavior are suitable for easier mixing, transport, and other manufacturing manipulations .p < 0.05) influenced by the pretreatments and drying methods, thus affecting the flow behavior. The angle of repose measures the flour resistance to the flow under gravity due to frictional forces resulting from the surface of the granules [The highest angle of repose was recorded for freeze-drying treatment while boiling and blanching at high temperature showed the lowest angle of repose. The angle of repose was significantly  indicates good sample homogeneity and less interference . On the LM and SEM images of the potato flours prepared under different pretreatments and drying methods are shown in The solubility index of potato flour as influenced by different treatments and drying methods is presented in 2 > 0.98). The highest solubility index was observed for high-temperature processed samples (boiling and blanching at 95 °C) compared to freeze-dried and low-temperature blanching flour. These results agree with Kim and Kim [The solubility of the flour increased with increasing temperature for all the samples. There was a strong positive correlation for solubility with increasing temperature . Boiling and blanching at 95 °C treatments resulted in a low angle of repose and Carr’s index, meaning that they had good flow characteristics, suitable for easier mixing, transport, and further handling. Particle size, temperature, and the solubility index of potato flour were strongly correlated. Potato flour derived from different processing methods depicted various physical and morphological properties, indicating significant variations in the application window in the food and pharmaceutical industries.


The aim of the present study was to evaluate the relative attenuation of VIS, UV and NIR solar radiation through a large pond skylight into the interior of the l’Almoina Archaeological Museum , and to determine how relative attenuation varied throughout the year and time of day. Measurements were taken at 9:00 a.m., 12:00 p.m. and 3:00 p.m. during July 2019 and January 2020. Relative attenuation values were obtained from the measurement of spectral irradiance in the exterior and at different points in the interior by means of two Ocean Optics spectrometers: HR4000CG-UV-NIR for VIS (400–700 nm) and NIR (700–1000 nm) bands, and FLAME-S-UV-VIS for UV-A (280–315 nm) and UV-A (315–400 nm) bands. The central points of the skylight had relative attenuation at 520 nm, reaching a value of 50% in summer at noon and 38% in the afternoon. At noon in winter, there were two relative attenuation peaks above 33% at 520 nm and at 900 nm. For mean relative attenuation, in the UVB range, the highest relative attenuation (20%) was inside the ruins in the morning in both summer and winter, and the UVA band relative attenuation was quite constant throughout the museum, but lower than that of the UVB band, in the range 0–3%. The preventive conservation and maintenance of archaeological sites is one of the requirements of the main international charters on the protection of archaeological heritage ,2,3,4. PIndeed, prolonged exposure to visible light (VIS) is known to cause pigment discoloration, and UV causes yellowing and disintegration of certain materials, while the infrared band (IR) causes warming of the surface of objects that can eventually lead to thermal deterioration .The case study described here is within an archaeological site in Valencia (Spain) containing the remains of different historical epochs, the oldest of which dates back to the foundation of the city in the Roman Republic period ,8. The sThis decision made it possible to capture intense solar lighting throughout the day and, at the same time, an effect of transparency that attracts the curiosity of the passers-by and suggests, from the inside, the presence of an open space. The skylight consists of a three-leaf laminar glass plate covered by a thin sheet of water, producing a quivering effect of the projected light . The intAlthough the museum and the public space generated have received a good reception from the public, the truth is that the presence of the skylight is causing significant practical problems. In addition to the extensive maintenance required by the need for cleaning and the appearance of leaks, other problems are no less serious, such as the thermal oscillation, the generation of condensation or the drying effect that favors the formation of efflorescence . On the These setbacks caused a reaction in public decision makers, who proposed replacing the pond with a pyramidal skylight in the style of the Louvre in Paris , or alteThe scientific literature provides several analyses on the conservation of archaeological sites exposed to solar radiation. Funda Yaka  considerAl-Obaidi et al.  warned oThe type and thickness of the glass used in the skylight have a significant influence on the UV spectrum. Several authors ,23,24,25Tuchinda et al.  analyzedLi et al.  studied Serrano and Moreno  studied In the previous works cited ,27 and iThe present study aimed to evaluate the relative attenuation of solar radiation in the interior of the l’Almoina through the water-covered skylight, for VIS, UV and NIR, and to determine how relative attenuation varies over time, throughout the day and the year; how it is distributed in space; and to what extent it is affected by the presence of the sheet of water over the glass, all this taking into account that the l’Almoina is a museum and the skylight was designed mainly for lighting and visual relationships, but not for the ideal environmental conditions for the conservation of the archaeological remains. In this regard, the study joins other studies already published that analyzed temperature and humidity variables such as those mentioned above.This study took place in the Museo de l’Almoina, in the historic center of Valencia , on the Spanish east coast. The element on which the research was based is a large skylight composed of a laminated glass consisting of 3 sheets of 10 mm-thick glass joined together by sheets of polyvinyl butyral (PVB) . This maRelative attenuation values were obtained from the measurement of spectral irradiance in the exterior and at different points in the interior by means of two Ocean Optics spectrometers : HR4000CThe operation of both devices is similar , althougBoth spectrometers were calibrated in July 2017 from 250 to 1000 nm and from 250 to 400 nm for HR4000CG-UV-NIR and FLAME-S-UV-VIS, respectively, by Ocean Optics, with a measurement uncertainty of approximately 10% across the entire measurement spectrum.The capture and reception management of the information provided by the two spectrometers was performed on a conventional PC using the applications OOIBase32 (for HR4000CG-UV-NIR) and SpectraSuite (for FLAME-S-UV-VIS), both by Ocean Optics.The sensor was first directed towards the maximum light intensity point that coincides with the solar position to record normal solar irradiance, and immediately afterwards, the measurement was taken in the same way at a total of 17 points just below or around the skylight projection . Two sucThis procedure was repeated on different days of the year: two in summer (25 and 30 July 2019) and one in winter (14 January 2020). In the case of 25 July, the skylight did not have the water sheet on its upper surface, while on 30 July, it did, which is the usual situation except during maintenance and cleaning operations. On 14 January, the skylight was filled with water. The procedure was also repeated at different times of the day: 9.00 a.m., 12.00 p.m. and 15.00 p.m. (solar time). The three days when the spectral values were taken were clear. The solar zenith angle on the data collection days is shown in As the UVB radiation values below 300 nm with FLAME-S had a lot of background noise, they were discarded from the calculations. Wavelengths above 1000 nm were also disregarded for the same reason, meaning that the total range covered was from 300 to 1000 nm. This range was organized into UVB, UVA, VIS and NIR bands, according to their physical properties and their environmental effects .When light reaches a semi-transparent surface, part of it is reflected, part of it is absorbed and part of it is transmitted through the object . This phImax) by the incident maximum ray intensity .Optical relative attenuation, as the main magnitude on which this entire study pivots, defines a relative—dimensionless—quantity that measures the fraction of incident light passing through a sample (2), in this case, the glass of the skylight. It is expressed by the result of dividing the transmitted light maximum intensity .The calculations for obtaining the relative attenuation values were based on the data provided by the spectrometers  according to the following expression:-To evaluate the influence of irradiance due to the different sun inclinations throughout the year, the relative attenuation data of a summer and a winter day were compared for the same hours  and the same points;-To evaluate the influence of irradiance due to the different orientations and inclinations of the sun throughout the day, the relative attenuation calculations were compared at different times  for the same season and same points;-To compare the relative attenuation of the skylight with and without water in the different frequency bands, we worked with the same sampling period—summer—with data from two days close together when the skylight was dry for maintenance (25 July 2019) or with the water sheet (30 July 2019);-To take into account the spatial variations in relative attenuation inside the museum, the spectral values of all the points recorded by the UV and VIR-NIR bands were considered for the same season, the same time and the same skylight situation (clear days without clouds).According to the objectives set when planning the study, data management was specific in each case:The selected data were arranged in tables and presented in graphs using Microsoft Office Excel for a clear visualization of the results.Regarding the precision of the measurements, the calibration uncertainty of 10% is the same as that with which other authors have worked ,27,29,30In this work, we measured the relative attenuation that does not correspond to the accepted definition of transmittance . TransmiThe measurement performed in this work is the minimum attenuation at a point, since it is the relationship between the maximum incident intensity of the upper part and the maximum at a lower point.This coincides with the norm  for the The methodology proposed in this work is useful in museums with natural lighting since, as in this case overhead, the maximum intensity at a point depends on many architectural factors, and the only way to know it is to precisely measure it.According to the standard  for a stThe spectral relative attenuation of the UV band was calculated according to Equation (2) for the chosen sites and two seasons of the year and is represented graphically in These higher relative attenuations at 300 nm reach their highest values in winter in all the locations. In this season, at 300 nm, the relative attenuation value observed at all locations was over 80%  in the mIn summer, the general trend was also similar in all locations. At 300 nm, the relative attenuation was also at its maximum in the morning, around 60% in location D and about 40–45% at the rest of the locations , rangingIt is observed for the UV band that the relative attenuations are lower at noon  than at It is also observed in each of For the VIS and NIR bands, the same procedure was followed as for the UV band using Equation (2) see .The winter morning and noon relative attenuations reveal wide variability, as shown in NIR relative attenuation at locations A and B is significant in winter in the morning and at noon , with a In the NIR band, locations A and B presented a similar tendency to the rest of the studied periods, with a relative attenuation below 15%.In the VIS band, locations A and B had a similar tendency during all the studied periods, with a relative attenuation value below 5%, except for location A in summer afternoons (25%).Exceptionally, at location C, there was a greater transmission in winter at midday, exceeding 100% at 670 nm. In this location at the VIS band in summer, the relative attenuation values reached 70% and 50% in the morning and noon, respectively . In the As seen in In the two seasons of the year studied, the shape of the relative attenuation curve is similar for all the locations studied, as it can be seen in In the morning and at solar noon, the highest relative attenuation  occurred at 300 nm at locations C, D and E in winter, as shown in At solar noon, as shown in In the winter in the afternoon, as it can be seen in The trend found in winter in the morning regarding the increasing relative attenuation from 400 to 1000 nm at all the locations studied can be seen in At 9 solar hours, in the NIR band in summer, the relative attenuation dropped from 50 to 5–10%, as shown in At solar noon see , there wAt 15 solar hours, the relative attenuation was quite small in the two seasons studied at all locations, as it can be seen in The relative attenuation of the UVB and UVA bands was calculated using Equation (3) and is shown in In the UVB range, the highest relative attenuation (20%) is inside the ruins (locations D and E) in the morning in both seasons, as shown in As it can be seen in The relative attenuations obtained following the same procedure as for the UV band (Equation (3)) are shown in In summer in the VIS and NIR bands, the relative attenuation was very small at all times on the walkway (locations A and B), except in the afternoon in the VIS range, which reached 22% in location A, as it can be seen in In winter, on the walkway (A and B), the relative attenuation is very small at all times in the VIS range and in the afternoon in the NIR range. In both ranges, the highest relative attenuation reached the maximum value (85%) at noon within the ruins (location C).In the morning, the relative attenuation was higher in the NIR range than the VIS range (30% vs. 10%), presenting little variation throughout the entire museum.In the afternoon, in both ranges, the relative attenuation was less than 1% at all of the studied locations.Analyzing This fact can also be verified in The spectral relative attenuation was calculated according to Equation (2) for the locations studied and the UV band see . The intAt 9 solar hours and solar noon, the relative attenuation was generally higher when the skylight was without water (day 25-7), except for location E at noon. At locations C, D and E, in the afternoon, relative attenuation was higher from 380 nm when the skylight had no water.This study of the relative attenuation of the UVB band from 300 nm and the UVA, VIS and NIR bands through the skylight indicates that the highest relative attenuation occurs in the VIS band (range 70–80%) in both seasons and in the NIR band (80%) in winter. Our results are in agreement with those of Tuchinda et al. , who fouIn the UV range, the skylight relative attenuation is higher in the UVB band than in the UVA band (20% vs. 5%). These results do not agree with the conclusions reached in other studies, such as Tuchinda et al. , Li et aThe observed results of a lower relative attenuation at higher temperatures, as happens at noon, could also be due to the fact that when the temperature increases, the thermal conductivity decreases, which leads to a greater thermal inertia. In conclusion, this would lead to a lower relative attenuation.Summarizing, we found that summer relative attenuations were higher at 9 h solar than at solar noon and were similar to those in winter. This could be due to the higher summer thermal level at solar noon that could cause the network of elastomers to rotate and vibrate, intercepting most of the solar radiation incident photons. Additionally, the mechanical properties of the materials could produce this, considering that thermal diffusivity is higher at lower temperatures and thus relative attenuation is increased. When the temperature is higher, diffusivity is reduced , and theThe sequence of this study was as follows: measurements were made at specific points of the museum of UV, VIS and NIR bands at certain times, and a maximum at 300 nm and a minimum at 370 nm were detected as a common result.The VIS and NIR bands around location D  showed greater relative attenuation at 520 nm, reaching a value of 50% in summer at noon  and 38% At location E , the highest relative attenuations occurred in the morning, reaching 70% at 520 nm in summer and 50% at 1000 nm in winter. At midday, in winter, they reached 40% at 600 nm .For the VIS band, the maximum relative attenuation (70%) was reached at 525 nm in summer at locations C (south point) and E .Hourly study of the spectral relative attenuation of UV highlighted the fact that in the afternoon, location C (southern point of the skylight) presented higher values in winter (50%) at 300 nm.Relative attenuation was higher in the UV range in the morning in winter at locations within the ruins, with the lowest values at noon. Within the UV range, from 320 to 370 nm, the relative attenuation was very low at all times and locations. In the UVB range, the highest mean UVB and UVA band relative attenuation (20%) was within the ruins (locations D and E) in the morning in both seasons. The relative attenuation of the UVA band was quite constant throughout the museum in both seasons but lower than that of the UVB band, since it is in the range of 0–3%. The highest mean relative attenuation of the VIS and NIR bands also occurred within the ruins (locations C and D) and decreased from morning to afternoon, but with lower relative attenuation values than VIS in the NIR range (morning 35% and afternoon 15%) (morning 50–65% and afternoon 30%).The comparison of UV spectral relative attenuation for the skylight with and without the water sheet showed that at the 9:00 a.m. solar hour and solar noon, the relative attenuation was generally higher through the empty skylight (day 25-7), except for location E at noon and in the afternoon for locations D and E, since relative attenuation was higher from 380 nm when the skylight was covered by the water sheet.Measurement of relative attenuation has been found to be a useful tool in the preventive conservation of cultural heritage since this measure is affected by the entire specific architectural and decorative structure of the museum. Architecturally, the water layer that covers the skylight increases the relative attenuation of the solar rays that affect the skylight. Work in progress is currently applying statistical comparison methods to reinforce the results.


In this research, two common apple seed cultivars Viz: ‘Golden Delicious’ (GD) and ‘Red Delicious’ (RD) of Northern Himalayan region were characterized for physical, techno-functional, microstructure, thermal, and rheological properties. Seeds showed a significant difference in width, arithmetic, and geometric mean diameters, volume, and surface area. Proximate analysis results revealed that seed flours have high oil content (> 20%) and are potentially rich sources of protein (> 40%). Color analysis of flours indicated their satisfactory whiter color with higher brightness values (L* ˃ 75), resulting from the reduced particle size which allows greater light penetration and relatively lower a* (< 1.5) and b* (< 11) values. Techno-functional attributes including water/oil absorption capacity, emulsifying capacity, and emulsion stability were significantly higher in RD than GD flour. There was also a significant difference in the average particle size of seed flours. Flour micrographs indicated the presence of oval/spherical-shaped starch granules embedded in dense protein matrix while, Differential Scanning calorimeter (DSC) revealed exothermic transition enthalpies for seed flours. Additionally, seed flours depicted high elastic modulus (G′), suggesting their suitability for modifying food texture. It was concluded that apple seeds exhibit significant potential for use in formulating protein-enriched foods while contributing to reducing industrial wastage. Malus domestica) is one of the most important fruit crops cultivated throughout the temperate regions of the world. The fruit is consumed fresh or processed into juice, concentrate, jam, cider, canned products. Processing, however, generates a huge quantum of pomace which accounts for up to 20–35% share of fresh fruit weight and consists of a mixture of skin/ pulp tissue (94.5%), with a significant amount of seeds (4.1%) and stems (1.1%)2. Apple seeds are reported to be an excellent source of proteins (38.85–49.55%) and lipids (20.69–24.32%) with linoleic and oleic acids as predominant amino acids3. They also contain a considerably high amount of polyphenolics mainly dihydrochalcones (phloridzin), hydroxycinnamic acid, flavan-3-ol, and flavonols which are effective in many aspects of human health, including reducing the risk of obesity and diabetes mellitus6, help prevent bone loss, inhibit cancer cell growth, enhance memory and life span5. Manzano and Williamson7 reported that phloridzin, a chalcone derivative, has an antidiabetic effect by inhibiting sodium-linked glucose transporters. Additionally, apple seeds have good commercial potential as promising antioxidants and can inhibit lipid peroxidation and protects the food from unstable reactive oxygen species6. Currently, apple seeds are gaining more interest in food formulations and as potential delivery vehicles for the administration of bioactive compounds5. The incorporation of defatted apple seed flour in various food systems has been extensively studied. Puric et al.2 examined the effect of adding defatted apple seed cake (DASC) in bread making and observed that bread supplemented with 20% DASC exhibited better nutritive value primarily due to increased protein (15.99%) and insoluble dietary fiber (7.21%) content. Also, a relatively higher total phenolic content, best antioxidant activity, and lowest change in freshness were found in bread supplemented with 20% DASC. In another study, Sudha et al.8 reported cake making from apple pomace and wheat flour blend at 0–30% to enrich it with total dietary fiber and polyphenols which have antioxidant activity.Apple  seeds9, melon (Cucumis melo L.) seeds11, sunflower (Helianthus annuus) seeds12, Akee apple (Bilphia sapida) seed13, oats (Avena sativa L.)10, finger millet (Eleusine coracana)14, no such study has been carried out for apple seeds. Besides, there is no study on the thermal, morphological, and rheological properties of apple seed flours. Due to the lack of such studies, apple seeds are rarely used at the commercial level and they generally go to waste. The work was, therefore, focused to determine the basic geometrical, morphological, thermal, techno-functional, and rheological properties of underutilized apple seeds collected from two common varieties ‘Red Delicious’ and ‘Golden Delicious’  compared to RD seeds (29.08 mm3). Similarly, sphericity ranged from 48.18% (RD) to 51.72% (GD) indicating a higher resemblance of GD seeds towards a sphere. This can be attributed to the higher moisture content of GD seeds compared to RD seeds. The increase in sphericity with increased moisture content was reported by Malik & Saini12 in sunflower seeds. Besides, sphericity and length are inversely related, with round grains resembling more to a sphere than a cylinder. Similar relations were depicted in our study with more spherical grains having the lowest length. However, both varieties depicted non-significant variation in aspect ratio, which indicates the tendency of seeds to roll on a flat surface. Also, the thousand-grain weight, which usually indicates the endosperm content in the seeds, was found to be 44.83 g (GD) and 45.32 g (RD) with no significant difference noticed between cultivars. All such variations could be attributed to the genetic makeup of the seed cultivars and will play an important role in the machine and other post-harvest equipment designing for efficient handling, processing, and storage of materials.Physical dimensions measured in terms of length, width, thickness, arithmetic, and geometric mean diameter, and shape provide valuable information for differentiating between varieties and/or other grains and in designing material handling and processing machinery. Results of the physical characterization of flour samples are presented in Table 14. The results for moisture content were found to be 8.17% for RD seed flour and 8.57% for GD seed flour with no significant variation observed among cultivars. These results were agreeable to that reported for Akee apple seed flour (8.05%)13. It was also found that RD flour contained significantly high (p ≤ 0.05) crude protein and fat content. The crude protein content was found to be 41.31% (GD) and 47.98% (RD) and was higher compared to other fruit seeds such as kiwi fruit flour (4.75–8.74%)15, quinoa flour (13.46%)16, watermelon, guava, orange, apricot, paprika and prickly-pear17 and also protein-rich flours, such as chickpea (20–24.3%)18, cowpea (24.1%) and horse gram flour (22.5%)19. This high protein content might be substantial enough to have a decisive effect for supplementing composite flours for the development of nutrient-enriched food products. Regarding protein quality, apple seeds are reported to be rich in sulfur-containing amino acids and appear to be reasonably balanced, with most of the essential amino acids above the FAO/WHO pattern . Concerning lipid content, a significantly highest percentage was found in RD seed flour (25.31%) than GD seed flour (21.47%). These results are comparable to that reported for L. acidissima (Wood apple) seed flour (24.9%)20 but superior to that reported for quinoa seed flour which has only 5.47% oil16. However, total ash content, which is related to minerals, was not found to vary significantly and ranged from 4.35% (RD) to 4.67% (GD). These results were found to be higher than in C.lanatus (2.75%) and L. acidissima (2.84%) seed flour20. Overall, both seed varieties presented a good nutritional value that can contribute to the formulation of protein-enriched functional foods to combat malnutrition.Table 14 was recorded to be 0.38 g/mL and 0.60 g/mL for RD and GD cultivars  might be attributed to its high proteins, lipids, and fiber content that gets degraded at high temperature23. Further, a significant (p ≤ 0.05) difference in the gelatinization enthalpy was also recorded among the two cultivars with RD seed flour having a generally lower ΔH value (9.78 ± 1.33 J/g) compared to GD seed flour (18.41 ± 0.63 J/g) which indicates its low energy requirement for crystallite melting. It may be due to a greater number of double-helical regions within GD granules which require more energy for breaking hydrogen bonds between glucan chains for complete starch gelatinization. Ren24, reported that particle size also affects ∆H value suggesting that flour with small particles results in complete protein denaturation and starch gelatinization which is consistent with the SEM results of this study.The thermal characteristics of the two seed flours as determined by DSC differed significantly (p ≤ 0.05). The gelatinization transition temperatures  and enthalpy of gelatinization (∆ H) of two seed flour samples were determined by DSC. The values obtained for ‘Golden Delicious’ and ‘Red Delicious’ seed flours were Tp = 98.37, 102.17 °C, To = 78.95, 89.07 °C, Tc = 108.71, 117.53 °C and ∆H = 18.41, 9.78 J/g respectively  higher water holding capacity (WHC) of RD seed flour (327.65 g/100 g) compared to GD seed flour (312.58 g/100 g). Earlier, El-safy et al.17 reported comparable results for the Egyptian variety of apple seed flour (3.58 g/g), whereas lower values were found for watermelon, guava, orange, apricot, paprika, and prickly-pear. The existence of higher protein content in flour samples (Table 19.Water holding capacity determines the ability of a product to hold water depending on the presence of polar/ hydrophilic proteins and polysaccharides327.65 g/00 g comp17. This variation in fat absorption among two cultivars can be attributed to variation in protein concentration and hydrophobicity of proteins which in turn determine its degree of interaction with oil and water26.Regarding oil absorption capacity (OHC), the values 92.97 g/100 g and 86.76 g/100 g observed in the present work for RD and GD seed flour, respectively are low compared to values given for the Egyptian variety of apple seeds flour19 was found to have a higher value for RD seed flour (51.81%) than GD seed flour 46.56% after 60 min  characterizes the capacity of flour samples to form stable emulsion via the interaction of polar and non-polar proteins with oil droplets at the oil–water interface. Therefore, more is protein content more will be adsorption ability towards oil. The EA was recorded to be 79.61% for RD seed flour and 72.01% for GD seed flour with a significant (p ≤ 0.05) difference observed among cultivars. Also, emulsification stability (ES), which indicates if the globular proteins present in the flour sample can prevent deformation of the emulsion system under shear stress conditions26 reported a similar trend of dynamic moduli of pearl millet used in their studies. Moreover, RD seed flour exhibited a pronounced increase in visco-elastic behavior compared to the GD variety. This could be due to the higher protein percentage in RD seed flour which favours protein aggregations resulting from increased disulfide linkage and enhanced interaction of gluten network within the matrix favouring visco-elasticity of the continuous phase. The effect of protein in increasing the G′ and G″ was reported by Marco and Rosell27. The results were also consistent with the proximate composition wherein RD and GD seed flours showed higher protein concentrations.The difference in rheological behaviour (visco-elastic properties) of the two flour samples was expressed in terms of loss moduli G′′ and storage moduli G′. Variation curves of G′′ and G′ as a function of oscillatory frequency are depicted in Fig. The study provided a basic understanding of various geometrical, physiochemical, functional, morphological, thermal, and rheological properties of two underutilized apple seed cultivars. The experimental results revealed that apple seeds differ considerably in their dimensional properties which will enable their sorting in different fractions for post-harvest operations. A considerable good amount of protein and lipid content was observed in seed flours which suggest their use in the development of protein-enriched food products with different end uses. Further, flour prepared from RD seeds depicted smaller particle size distribution with high stability to thermal degradation, mostly suitable for various food processing operations. Likewise, a significant difference was observed in techno-functional properties with RD seed flour having significantly higher water/oil holding capacity, emulsification capacity, and emulsification stability than GD seed flour. Moreover, rheological results revealed predominant visco-elastic behaviour of seed flour which could help modify the texture of various foods. Therefore, the exploitation of apple seeds can be a boon for food security while minimizing industrial food wastage and as well contribute to the development of protein-enriched foods to combat malnutrition.Apple seeds (‘Golden Delicious’ and ‘Red Delicious’) were procured from the Juice processing industry . The collection of seed samples was in compliance with the institutional guidelines. The samples were cleaned, dried, dehulled, and then stored at 4 °C in airtight containers. All chemicals and reagents used were of analytical grade and purchased from High media Laboratories Pvt Ltd and Sigma Aldrich (USA).6.The seed flours were prepared following the method described in our previous workThe three principal axial dimensions (mm) including length (L), width (W), and thickness (T) of 100 randomly selected seeds of each variety were measured by digital vernier caliper reading to an accuracy of 0.01 mm.10.Geometric mean diameter, Dg (mm), and arithmetic mean diameter, Da (mm) of seeds were calculated using Eqs.  and 2)  2) as de14.The shape of seeds can be determined in terms of sphericity (φ), which is an index of roundness and was calculated by the formula used by Ramashia et al.a) was calculated by the equation used by Shah et al.10 as:The aspect ratio (R3), and surface area S, (mm2) was calculated from geometric mean diameter by the following equation:Sample volume, V  of 0.001 g accuracy. The value was then multiplied by 20 to get the weight of 1000 seeds.28.The moisture (925.10), fat (920.85), ash (923.03), and protein (920.87) contents were determined by the official AOAC method29. The tapped density was determined by the same procedure, but the sample in the measuring cylinder was tapped on the bench very carefully until a constant flour volume was observed.Bulk density was measured according to the method described by Gani et al.30.ρb is flour bulk density and ρt is flour tapered density.The Compressibility index (CI) and Hausner ratio (HR) were calculated as per the formula given by CarrThe particle size distribution of flour samples was measured using a Litesizer 500 laser light scattering instrument . 0.01% flour samples were suspended in Milli-Q water  and sonicated at 40 kHz (15–30 min) for complete dispersion of flour fractions. The measurements were performed at 20 °C at neutral pH.The color of the flour samples was determined by Color Flex Spectrocolorimeter  which was calibrated using a white reference tile. The results were expressed in terms of L* (lightness/brightness), a* (redness/greenness), and b* (yellowness/blueness) values.The microscopic structure of flour samples was analyzed by scanning electron microscope  under a high vacuum. The samples were mounted on a circular aluminium specimen stub using double-sided adhesive carbon tape. After coating vertically with gold–palladium, the samples were photographed at an accelerator potential of 10.00 kV.e System. Samples (3.5 mg) were weighed into aluminum pans and mixed with Milli Q water (8 μL). The pans were sealed hermetically and allowed to equilibrate for 1 h before analysis. The heat rate was 10 °C/min over a temperature range of 20 to 180 °C in a nitrogen atmosphere. An empty platinum pan was used as the reference. From the curve, enthalpy of gelatinization (ΔH), the onset (To), peak (Tp), and end (Tc) temperatures were obtained using the data processing software supplied with the DSC instrument.The thermal characteristics of flour samples were studied using Mettler Toledo DSC-1 STARThe samples (1 g) were poured in a pre-weighed centrifuge tube and mixed with 10 mL of water/oil. The tubes were vortexed for 5 min and then allowed to stand for 20 min at room temperature. Thereafter tubes were centrifuged  at 3000 rpm for 30 min and supernatant (distilled water/oil) decanted and wet residue weighed for determination WAC and OAC.25. Flour samples (0.5 g) were mixed with 5 mL distilled water in centrifuge tubes and vortexed for 30 s. 5 mL oil was added to the suspension, homogenized, and then centrifuged at 1100×g for 5 min . The emulsification activity expressed in percentage was calculated as:2 is the height of the emulsified layer in the tube and H1 is the height of total contents before centrifugation.Emulsion capacity (EC) and stability (ES) were determined according to the method described by Hussain et al.g for 5 min and expressed as:t is the height of the emulsified layer after heating and H2 is the height of the emulsified layer before heating.The emulsification stability was estimated by further heating the emulsion for 30 min at 80 °C and centrifuged at 1100×The rheological analysis was carried out using MCR 102 rheometer . The flour suspensions (1% w/v) were prepared with Milli-Q water. The suspensions were homogenized at 1000 × g for 20 min and thereafter equilibrated at room temperature for 5 min. The homogenized samples were subjected to frequency sweep testing from 0.1 to 100 rad/s performed at 25 °C for determining the changes in storage modulus (Gʹ) and loss modulus (Gʹʹ) occurring during the test.t-test. The statistical difference was determined with p ≤ 0.05.All experiments have been carried out in triplicates and data was expressed as mean ± standard deviation. The results obtained were statistically analyzed by paired student


The physicochemical properties, swelling power, solubility, and digestibility of flour from four rice varieties  were analyzed. The results showed that the black and brown rice had high‐amylose percentage (21.8% and 20.5%), a relatively low percentage of starch content (68.1% and 79.1%), and lower swelling power (6.6% and 7.6%) and solubility (13.5% and 15.7%), respectively. Waxy rice flour attributed to lower gelatinization temperatures and higher enthalpy values. Meanwhile, the brown, black, and white rice showed higher gelatinization temperature and lower enthalpy value. The black and brown rice flour exhibited lower pasting and viscosity values as compared to waxy rice flour. The results showed that all rice flour had an A‐type X‐ray diffraction pattern, and after cooking all rice flour showed V‐type polymorphs except waxy rice flour. Brown and black rice flour after cooking have lower digestion rate than white rice and waxy rice flour, probably due to its lower expansion and solubility rates, and higher gelatinization temperature. Rosa Roxburghii seed oil was of high quality in terms of its high amount of unsaturated fatty acids. Heat treatment of R. roxburghii seed oil showed an increase in the relative percentage of linoleic acid and linolenic acid isomers with increasing temperature and time. The formation of linoleic acid and linolenic acid isomers followed a zero order reaction. As rice flour is gluten‐free, therefore, it is recommended to make gluten‐free food products   were selected to investigate its solubility, swelling power, and thermal and enzymatic hydrolysis properties.22.1Four commercial brand rice varieties were purchased from the local market of Guangzhou, China. Black rice and brown rice were from Posh Brand, and white rice was from the Xiguyuanji brand, whereas, white waxy rice was from the Blue wheel brand. Megazyme assay kits were used to analyze total starch content . All chemicals used for analysis were of analytical grade.2.2All samples were ground into a powder with a hammer mill (Miller 6850). Then, the samples were passed through a sieve (100‐mesh). Samples were stored in a plastic bag before analysis.2.3The iodine colorimetric method was used to determine the amylose portion of ground samples with minor modifications  was used (Rigaku). All samples of flour taken for analysis were cooked at a temperature of 90°C for 30 min. Then, the cooked samples were placed in the freeze‐dryer for drying and further ground. Both the freeze‐dried and raw samples were tightly packed in a glass cell of rectangular shape and placed for scanning ranged between 4 and 35° 2θ angle at a rate of 2°/min  operating with Cu Kα radiation (2.5Tp), onset (To), enthalpy of gelatinization (∆H), and conclusion (Tc) were taken with the help of software provided with the DSC instrument .Sample of rice flour  with 70%, w/w deionized water was scanned with the help of a differential scanning calorimeter  at the temperature of 30 to 150°C at 10°C/min rate in a pan made up of stainless steel , each sample of flour  was put up with deionized water; then, a sample of accurate weight was analyzed by Brabender Viso‐ amylograph at 95°C (1.5°C/min) heat and after this was cooled to 50°C (1.5°C/min). Final viscosity (FV), peak viscosity (PV), and hot paste viscosity (HPV) were obtained from Brabender profiles. Breakdown (BD) and set back (SBV) viscosity were measured by software supplied with the instrument.2.7g) for 15 min. The supernatant was gradually poured into a tube, and the resulted residue was measured to determine swelling power. The supernatant was shifted to glass and boiled for evaporation. Afterward, a sample was dried to a constant weight at 105°C temperature and weighed. Swelling power (SP) and solubility (S) were assessed by using the following equations.Wt: the weight of wet sediment; Wr: the weight of dried supernatant; W: the weight of a sample.Swelling power (SP) and solubility (S) were examined according to previous procedure with slight modifications  to stop unwanted reactions and centrifuged  for 5 min to remove an undigested portion of starch. Maltose equivalent level was determined by using PAHBAH assay (Para‐hydroxybenzoic acid hydrazide)   analysis . The plot of ln (dC/dt) against digestion time t is intellectually linear with a slope of −k, and the C can be calculated from the intercept of the equation and slope k.In this equation, digestion time in minutes was represented by 2.9Significance difference and mean value were analyzed by using the least significant difference (LSD) with the help of SPSS 18.0 statistical software . The significance level was .05.33.1The protein, fat, amylose, and total starch contents of rice flour are shown in Table 3.2The native rice flour exhibited a clear A‐type diffraction pattern with a strong reflection peak at 2θ = 15.0° and 23.0° and an unresolved doublet at ca. 17.0° and 18.2° 2θ Figure . The resFigure 3.3To), peak (Tp), and conclusion (Tc) gelatinization temperatures and gelatinization enthalpy (∆H) varied significantly. The gelatinization temperatures of all rice flour were varied from 69.4 to 73.0°C for onset temperature; 76.0 to 81.4°C for peak temperature; and from 80.9 to 88.7°C for conclusion temperature. Brown rice flour displayed a higher onset temperature (To = 73.0°C) than black and white rice flours . It is evident from data that To peak increases with the increase in amylose content. Also, waxy rice flour displayed lower To temperature as compared to nonwaxy rice flours. The lower gelatinization temperature in waxy rice flour as compared to nonwaxy one was attributed to the more crystalline region and lower gelatinization temperature  of waxy rice flour (9.9 J/g) was higher than brown, black, and white rice flours . It is due to the lower gelatinization temperature, and enthalpy value increased with decreasing amylose content  of all rice flour was ranged from 6.6 to 13.9 g/g, which is in line with previous findings  value (22.6%) as compared to the black, brown, and white rice flours . The solubility value was found lower in rice with high‐amylose content than waxy rice flour due to its noneasily rupturing and more compact structure  of enzyme concentration and type(s) of an enzyme are responsible factors to speed up the rate of starch digestion (Warren et al., As the first‐order fit of digestion progress curves shown in Figure k values and released more reducing sugars than brown, black, and white rice flours samples, representing that waxy rice showed fast digestion as compared to nonwaxy rice. This is probably related to their higher swelling power, solubility (Table Brown rice and black rice flour showed a relatively low enzymatic digestion rate Figure  as compaty Table , and higty Table  of waxy 4To and Tc and lower ∆H that may be due to higher amylose content than waxy rice flour. All rice flour exhibited an A‐type X‐ray diffraction pattern. Black and brown rice showed significantly lower digestibility than white and waxy rice flour. This study revealed that brown and black rice flour could be an effective alternative in different food formulations due to their low starch digestibility, low swelling power and solubility, high‐amylose content, and higher amount of nonstarch components.Differences were found in the chemical composition, physicochemical and functional properties, and digestibility of four rice varieties. The research indicated that black rice had higher amylose, protein, and fat content along with lower starch content as compared to the brown, white, and waxy rice flour. Brown, black, and white rice had higher All authors declare that they have no conflict of interest.


This phenomenon is driven by the interplay of bulk, elastic and electrostatic energies of coexisting modulated phases with strong and weak spontaneous polarizations. We demonstrate reversable and tip-voltage magnitude/time-dependent donut-like domain morphology evolution towards continuously and reversibly modulated high-density nonvolatile ferroelectric memories.Multitudinous topological configurations spawn oases of many physical properties and phenomena in condensed-matter physics. Nano-sized ferroelectric bubble domains with various polar topologies  achieved in ferroelectric films present great potential for valuable physical properties. However, experimentally manipulating bubble domains has remained elusive especially in the bulk form. Here, in any bulk material, we achieve self-confined bubble domains with multiple polar topologies in bulk Bi Experimentally manipulating bubble domains remains elusive especially in the bulk form of ferroelectrics. Here, the authors achieve self-confined bubble domains with multiple polar topologies in bulk Bi0.5Na0.5TiO3 ferroelectrics, demonstrating reversible and donut-like domain morphology evolution. Separated by domain walls, normally, different orientations of ordering vectors are expected in adjacent different domains, while they are constant within the same domain6. However, this conventional notion of ferroic domain microstructure is not the only way in which ordering vectors can be arranged spatially10. Nano-sized ferroelectric bubble domains, presenting polar topologies , were recently achieved in thin-film superlattices of (PbTiO3)n/(SrTiO3)n5. However, such domain structures have not so far been achieved in a bulk material. If it were possible to stabilize these structures, we could achieve multi-conformational domain structures with multitudinous physical properties, e.g., chirality, ultrahigh memory density (exceeding tens of Tb in−2), low-power consumption, and colossal electromechanical activity12, in economical bulk materials for practical applications. In ferromagnetic materials, the Dzyaloshinskii−Moriya interaction can be used as the driving force for stabilizing and eventually manipulating these bubble domains, but is not available in ferroelectrics. To trigger the continuous rotation of electrical dipoles in ferroelectric materials, alternative driving forces must be found, which have been forecasted by several researchers and are becoming a major endeavor in recent years14. Thin films allow better control over the ferroelectricity and depolarization field, and by varying the epitaxial constraint between the ferroelectric and paraelectric layers, polar bubble domains with various polar topologies have been observed in high-quality multilayer thin films5. Nevertheless, no such effective epitaxial constraint is applicable to bulk materials, which narrows the experimental options for triggering and further utilizing these topological configurations in bulk ferroelectrics.For ferroic materials, spatial variations in the orientation of order parameters  are accommodated through the formation of discrete domains15. Relaxor ferroelectrics, with decoupled dipoles (of multiple symmetries) naturally coexisting in local regions16, may just satisfy the requirement of this kinetic constraint. In their free energy expansion, the high-order gradient terms could provide a negative wall energy, which could drive modulations of polarization vectors as well as domain configurations15. Regulated by this constraint, labyrinthine and stripe domain structures can be achieved in thin-film or bulk relaxor ferroelectrics, but not yet for bubble domains19. Determined by a critical balance among elastic, electrostatic, and gradient energy terms, bubble domains might be stable only within a very narrow range of boundary conditions. It leads to the long-standing challenge of capturing such special domain structure in relaxor ferroelectrics19, especially for bulk ferroelectrics that lack the epitaxial constraint of multilayer thin films.Theoretical and experimental findings suggest that kinetic constraint possibly exists in systems that exhibit two or more distinct modulated phases, and therefore should also apply to bulk materials0.5Na0.5TiO3-based relaxor ferroelectrics possess concomitantly modulated short-range-ordered crystal symmetries (mainly R3c and P4bm), based on which, we have manipulated the domain conformations through modifying the local structural heterogeneity. Labyrinthine, stripe, bubble, and even polar-skyrmion domains are demonstrated using a combination of Z-contrast imaging and phase-field modeling. We experimentally validate the possibility of triggering the bubble domains in bulk ferroelectrics, achieving multiple polar topologies, especially polar skyrmions. The total free energy of bulk ferroelectrics is mainly affected by the competition of bulk, elastic, and electrostatic energy terms of coexisting modulated phases, which determines the observed bubble domains, especially for vortices or skyrmions. Not only do we demonstrate the possibility of triggering the bubble domains in bulk ferroelectrics, but also our results demonstrate that Bi0.5Na0.5TiO3-based relaxor ferroelectrics represent a material family exhibiting polar skyrmions. It opens up a direction to understand the puzzles on topologies  and design functionalities previously inaccessible in bulk materials. Here, we propose one possibility, manipulating the reversible and tip-voltage magnitude/time-dependent donut-like domain morphologies, which holds potential for designing high-density nonvolatile ferroelectric memories that can be continuously and reversibly modulated. In addition to the prerequisite requirement for applications, reversibility, the ability for continuous modulation, holds promise for creating a series of memory states, superior to the conventional “0” and “1” states.Bi21. For easy description, we abbreviate the chemical formulas for different compositions, and the details are provided in the “Methods” section. By doping appropriate elements, the domain pattern can be regulated from large-size labyrinthine domains , to refined stripe domains , then to ultrafine stripe domains , and finally to bubble domains . Moreover, these bubble domains , the composition-induced domain evolution is demonstrated by the induced phase change Fig. , which t0.5Na0.5TiO3-based materials, the displacement of the center Ti4+ cation with respect to the corner Bi3+/Na+ cations (δTi-Bi/Na) or the center of its nearest O2- neighbors (δTi-O) can be used to represent the local polarization state  reflections, respectively23. Selected-area electron diffraction (SAED) patterns along three basic zone axes  reveal the increased intensity of ½{ooe}-type reflections with a decreased intensity of ½{ooe}-type reflections from BNT-labyrinthine to BNT-stripe and then to BNT-bubble samples, as shown in Fig. 3ooe}-type or ½{ooo}-type diffraction spots indicates the increasing ratio of the shorter-range-correlated P4bm symmetry, which is consistent with the high-resolution X-ray diffraction Rietveld refinement analysis  favor the polarization modulation between the coexisting symmetries. Therefore, P4bm symmetry plays a crucial role in restraining the domain boundary, as the depolarization field does, while R3c determines the main body of the bubble domains. The increasing ratio of P4bm is expected to segment the large-sized domains. If R3c/P4bm symmetries coexist in a critical ratio range, bubble domains or even polar skyrmions can be realized in Bi0.5Na0.5TiO3-based bulk ferroelectrics. As revealed by the macro and local structural analysis, the domain morphology evolution is tightly correlated with the ferroelectric−ferrielectric symmetry transition.The observed polarization behaviors raise fundamental questions on their physical origin. According to phenomenological theory, relaxor ferroelectrics with coexisting symmetries have higher-order gradient terms in their free-energy expansionion Fig. . Slightl001]pc, 1pc, [111]Below, we combine phase-field modeling and theoretical rationalization to reveal the physical origin of the above-mentioned observations, including (1) composition-induced domain evolution, (2) microscopic features of the bubble domains, and (3) the skyrmion-like topological conformations.With phase-field modeling, we reproduce the composition-regulated evolution of domain patterns, from the large-sized labyrinthine-like domains to the refined stripe-like domains and finally to the distinctive bubble-like domains with polar topologies  that determine the energy terms, it is found that the doping concentration c greatly influences the number of vortices and the background dielectric permittivity εbr 8. Due to the E-field-induced polarization rotation from the IP to OP directions, such metastable and short-range correlated bubble-like topological patterns are expected to experience an E-field-induced conformational transition, leading to the enhanced piezoelectric responses during the voltage-loading process8. To test the local piezoelectric response and conformational transition during the polarization rotation process, switching spectroscopic PFM (SSPFM) hysteresis behavior was investigated on the bubble domains  voltage was then applied to the bubble regions to manipulate the domain morphologies. A preprocessing −40-V voltage was first scanned over a 1 μm*1 μm bubble region for the initial poling. Then, a unidirectional voltage is applied to one point. Controlling the duration and magnitude of the applied voltage induces peculiar donut-like antiphase domains around this point Fig. −22. The The observed multifarious peculiar domain morphologies present at least three important features to note, including: (1) continuously varying ferroelectric domain morphologies can be easily manipulated by the duration and magnitude of the applied tip voltage, (2) the donut-like anti-phase domains are spatially stable and experimentally recoverable, and (3) two groups of the donut-like domain morphologies induced by opposite tip voltages exhibit mirrored patterns. These results, therefore, demonstrate the concept of a continuously and reversibly modulated high-density nonvolatile ferroelectric memories, whose operation is linked to the above reversible tip-voltage magnitude/time-dependent domain morphology evolution.0.5Na0.5TiO3-based ferroelectrics. This is the first observation of the elusive polar skyrmions, composed of a series of diversely oriented Néel- and Bloch-like conformations, in any bulk ferroic material. The coexisting R3c/P4bm symmetries significantly affect the interfacial energies, and R3c determines the main body of the bubble domains, while P4bm restrains the domain boundary. Driven by the interplay of bulk, elastic, and electrostatic energies of coexisting modulated phases, such peculiar topological structures clearly differentiate from the ordinary 2D skyrmions observed in magnetic systems, as well as the 3D skyrmions observed in multilayer thin films. By controlling the duration and magnitude of the applied tip voltage, these polar topologies exhibit donut-like domain morphologies that open up the concept for potential applications: beyond reversibility, necessary for the conventional “0” and “1” states, the possibility for non-conventional and high-density nonvolatile ferroelectric memories is based on sequential modulation through a series of memory states.In summary, we report the direct observation of polar bubble domains including polar skyrmions in bulk BiSupplementary Information


As a crucial task in surveillance and security, person re-identification (re-ID) aims to identify the targeted pedestrians across multiple images captured by non-overlapping cameras. However, existing person re-ID solutions have two main challenges: the lack of pedestrian identification labels in the captured images, and domain shift issue between different domains. A generative adversarial networks (GAN)-based self-training framework with progressive augmentation (SPA) is proposed to obtain the robust features of the unlabeled data from the target domain, according to the preknowledge of the labeled data from the source domain. Specifically, the proposed framework consists of two stages: the style transfer stage (STrans), and self-training stage (STrain). First, the targeted data is complemented by a camera style transfer algorithm in the STrans stage, in which CycleGAN and Siamese Network are integrated to preserve the unsupervised self-similarity (the similarity of the same image between before and after transformation) and domain dissimilarity (the dissimilarity between a transferred source image and the targeted image). Second, clustering and classification are alternately applied to enhance the model performance progressively in the STrain stage, in which both global and local features of the target-domain images are obtained. Compared with the state-of-the-art methods, the proposed method achieves the competitive accuracy on two existing datasets. Person re-identification (re-ID) as a crucial task in surveillance and security strives to retrieve the same people across multiple images captured by non-overlapping cameras or across multi-scene images captured by the same camera. Despite the great success in person re-ID, some limitations still exist in practical applications, such as the acquisition of high-quality feature representation, the domain shift between training and testing data, and the difficulty of model migration from source domain to target domain.Although existing person re-ID methods achieve high recognition rates on different types of single dataset, the great disparity exists between these person re-ID methods and practical applications, which is usually caused by the difference between the training and testing datasets ,6,7,8,9.The domain adaptive person re-ID was proposed to alleviate the domain shift issue between the labeled source domain and target domain. Some existing domain adaptive solutions achieve good performance in person re-ID. Existing domain adaptive person re-ID solutions can be roughly categorized into cross domain person re-ID  and sharThis paper proposes a GAN-based self-training framework with progressive augmentation (SPA) to solve the aforementioned two main challenges: the lack of labeled data and domain shift. This proposal expands the target-domain dataset by analyzing the consistency of each person identity in the labeled data and gains the pedestrian scale features in different learning strategies. Specifically, clustering and classification are applied to obtain the global and local features of each person respectively. The proposed SPA consists of style transfer stage and self-training stage, which act on the expanding and training processes respectively.Style transfer stage (STrans): As a widely used style transfer solution in image processing, the proposed solution uses CycleGAN to achieve the transformation of the labeled image from source domain to target domain. Therefore, the generated training samples retain the style of target domain, such as resolution and light conditions. Specifically, Siamese network is applied to preserve the identities of pedestrians in the transformed images by using adversarial loss and contrastive loss. Besides, circle loss is used to mitigate the inflexibility and sensitivity of the proposed solution to image quality.Self-training stage (STrain): Clustering and classification are integrated to learn the robust features of the unlabeled target domain. Therefore, the learned global and local features are semantically complementary. As the progressive augmentation learning, both global and local features of the target-domain data are gradually enhanced by alternate clustering and classification. Since clustering and classification can promote and supervise each other, the self-training process can be completed without external intervention.The proposed solution applies a two-stage (STrans and STrain) method to data expanding and training. Source images are first transformed without distorting semantic contents, and then credible pseudo labels are generated. Therefore, the proposed solution can achieve good prediction performance. According to the comparative results, the proposed solution outperforms other state-of-the-art unsupervised domain adaptive person re-ID solutions on two benchmark datasets Market-1501  and DukeA two-stage (STrans and STrain) framework is proposed for unsupervised domain adaptive person re-ID, which can achieve good performance on both image style transformation and self-training.A progressive augmentation learning strategy integrates clustering and classification to obtain both global and local features of the target-domain data, and generates credible pseudo labels without any interventions.The rest of this paper is organized as follows. As a critical task in intelligent monitoring, person re-ID that was first proposed by Gandhi in 2006  has attrSupervised person re-ID: Supervised person re-ID methods conduct supervised training and testing on the same datasets [datasets ,7,8,9,13datasets  exploreddatasets  integratAlthough existing supervised person re-ID methods can achieve good performance in the source domain, the lack of labeled samples and domain shift as two main issues still exist. Due to the difference of feature distribution between source and target domains, their recognition performance is often unsatisfactory in the target domain. Therefore, unsupervised domain adaptive (UDA) learning was proposed and applied to person re-ID to address the domain shift issue, which can be roughly categorized into cross domain learning and shared domain learning.Cross domain person re-ID: Cross domain models can improve the object recognition accuracy, which are usually based on the supervised learning in the labeled source domain and applied to the unlabeled target domain by migration learning [learning ,23,24,25learning  proposedShared domain person re-ID: Shared domain-based person re-ID methods mainly focus on migrating the images in both source and target domains to a shared feature space [re space ,28,29,30GAN-based person re-ID: The acquisition and learning of valid datasets are two main steps of recognition. GAN [ion. GAN  adopts tion. GAN  maintainion. GAN ) to targion. GAN  achievesion. GAN  introducThe robustness of UDA person re-ID methods is determined by the differentiated information from different domains. Due to the varying degrees of domain shift, the overall recognition performance of cross- and shared-domain person re-ID methods is not stable. Therefore, this paper explores how the labels, feature representation, and metric learning affect the performance of person re-ID and proposes an effective GAN-based self-training framework.As shown in In Strans, both CycleGAN and Siamese Network are integrated to ensure the self-similarity (the same identity in an image is remained) and inter-domain difference  before and after transformation. When any part of STrans is changed, the corresponding parameters of CycleGAN and Siamese Network are updated accordingly.In Strans, the global and local structures of target-domain data are obtained in the two-stage self-training process of the progressive augmentation framework. In particular, the global and local features of each person are obtained by clustering and classification, respectively. Two stages process alternately in the self-training process until reaching the goal. Similarly, the corresponding parameters are updated according to any change of STrain.Similar to SPGAN , CycleGAG and F by capturing the fine information of the labeled source-domain dataset G and D. CycleGAN is formalized as follows.G(F), As shown in the lower part of In addition to adversarial losses and cycle-consistency loss, style retain function is designed to ensure that the color composition between the input and output is preserved and the generator is prevented from outputting unreal results. In particular, when the generator transfers an image, it needs to preserve the identity information of source images. Therefore, a unit matrix is formed to ensure the identity mapping as follows.d is the Euclidean distance between the pair, m controls the margin of decision boundary.L and K represent the number of Euclidean distances corresponding to positive and negative input pairs respectively, It is necessary to ensure the identity consistency and domain dissimilarity of pedestrian after transformation. During the training process, Siamese network is optimized by minimizing the sum of contrastive loss and circle loss  on the dIn Equations  and 4),,4), lossThe overall objective function of style transfer stage can be formalized as follows.The extended target domain dataset Due to the dramatic appearance changes and identity dissimilarity between different domains, it is expensive and impractical to label data in the unsupervised and domain adaptation settings. To alleviate the above limitations, a two-step self-training process is proposed, which takes advantage of classification and clustering.Since the extended target domain dataset ne (PCB) . Subsequne (PCB) ,38 LCTLEquation , and forConventionally, according to the difference of objective loss function, person re-ID consists of representation learning and metric learning corresponding to classification and clustering respectively. Most existing methods use one way to train the network and the two learning methods are applied to further improve the network performance. Theoretically, due to PCK-Means clustering, the network focuses on the local structure of data distribution and may ignore the global information in semi-supervised learning. Therefore, the model is easy to fall into a sub-optimal local minimum.C denotes the cluster number of the updated training set W is the initialized classifier weight.As an optimization way, clustering and classification are used alternately. In this way, a fully connected layer is added to the end of the model as a classification layer, which is initialized by the current Two large-scale person re-ID datasets as shown in Market-1501  is a datDukeMTMC-ReID  is a larn gallery samples in turn, and then sorts the obtained distances to check whether the same identity samples are located in the top-k, and finally the CMC curve is obtained by statistics. Specifically, it is a floating-point number in an interval. In convenience, it usually takes the form of percentage and only compares three-digits accuracy rates.Cumulative matching feature (CMC) is the most widely used in person re-ID, which can be regarded as the accuracy rate in the related papers. For each pedestrian in the query set, it calculates the distance to As an index widely used in reflecting the recall rate of the model, mean average precision (mAP) is the mean value of average accuracy (AP) of all query samples ,41,42,43CycleGAN and Siamese network are adopted in the style transfer stage. Adam optimizer  is also m in Equations ,,m in EquEquation  are empim is set to 2 which is consistent with Equations (The two-step learning rate can improve the learning performance of the progressive self-monitoring learning framework, rather than using the same learning rate directly in both self-monitoring stage and classification stage. Therefore, the false label guidance can be avoided. Specifically, in the semi-supervised learning, the learning rate of the backbone network is initialized to quations .SPA proposed in this paper is compared with the state-of-the-art style transfer learning and UDA learning solutions on Market1501  and DukeAs shown in As shown in It is useful to use the expanded labeled data to train the model in the last two rows of The impact of the each component of the proposed algorithm. As mentioned in introduction, the accuracy of person re-ID in UDA setting replies on the generation quality and identity recognition accuracy. Four components of the proposed GAN-based self-training network are evaluated as follows.GAN-based transformation network: According to the SPGAN model, the performance of the proposed GAN-based transformation network is significantly improved, which benefits from the adoption of both novel training data construction and circle loss methods.Progressive self-training framework: The semi-supervised clustering and classification learning are combined to learn the robust features of the unlabeled target domain effectively.Semi-supervised learning: k-reciprocal encoding and PCK-Means are used when a ranking score matrix is constructed and the initial images are clustered.Classification: It is identical to general softmax classification but needs to initialize the classification layer.As show in The impact of the hyperparameters. The generalization properties of a loss function are governed by a small number of hyper-parameters. The hyperparameter values are determined in the process of model selection. In Equation (Equation , λ is usSubsequently, three hyperparameters in Equation  of STranThis paper proposes a GAN-based self-training framework for UDA person Re-ID, which focuses on solving the lack of pedestrian identification labels in the captured images and domain shift issue between different domains.In the proposed SPA, the a priori knowledge from the labeled source domain is used to obtain the robust features of target domain. In style transfer stage, CycleGAN and Siamese Network are combined to ensure the self-similarity and inter-domain difference of person identification. Besides the widely used adversarial loss and contrastive loss, which are inflexible and sensitive to the quality of pair, circle loss is used to optimize the model with a targeted convergence. The self-training stage captures the global and local structure of target-domain data in the progressive augmentation framework, which takes advantage of clustering and classification on person re-ID. The comparative experimental results confirm the proposed solution achieves better performance than the state-of-the-art unsupervised cross-domain re-ID solutions in person re-ID. In future, the proposed method will be extended to other unsupervised cross-domain applications.


It could also be easily adapted to study other skewed sequence populations used in the analysis of B cell receptor populations, for instance, k-mers and V gene usage. These analysis types should allow for inter and intra-repertoire comparisons of diversity, which could revolutionize the way we understand repertoire changes and diversity.The B cell population is highly diverse and very skewed. It is divided into clones (B cells with a common mother cell). It is thought that each clone represents an initial B cell receptor specificity. A few clones are very abundant, comprised of hundreds or thousands of B cells while the majority have only a few cells per clone. We suggest a novel method - domain-based latent personal analysis (LPA), a method for spectral exploration of entities in a domain, which can be used to find the spectral spread of sub repertoires within a person. LPA defines a domain-based spectral signature for each sub repertoire. LPA signatures consist of the elements, in our case - the clones, that most differentiate the sub repertoire from the person’s abundance of clones. They include both positive elements, which describe overabundant clones, and negative elements that describe missing clones. The signatures can also be used to compare the sub repertoires they represent to each other. Applying LPA to compare the repertoires found in different tissues, we reiterated previous findings that showed that gut and blood tissues have separate repertoires. We further identify a third branch of clonal patterns typical of the lymphatic organs  separated from the other two categories. We developed a python version of LPA analysis that can easily be applied to compare clonal distributions -  The extremely high diversity of B cell and T cell receptors in the immune repertoire is key for immune function and protection from disease . Clear lWhen comparing these distributions that are long-tailed and far from normally distributed, we still tend to use tools that depend on normalcy and focus on the most abundant members of the distribution. Moreover, in most cases, it is hard to quantify a negative difference  when comparing distributions. We suggest a novel method, domain-based Latent Personal Analysis (LPA), recently developed to analyze texts , which cdiffers most from the domain’s vocabulary . If one negatively assumes no personal differences, then a personal vocabulary could be considered a random sample from the domain vocabulary. This would yield a minimal information loss when measured by a relative entropy distance, e.g., a Kullback-Leibler Divergence  observed in a specific tissue match or differ from the overall distribution of clones observed in a person. Here, the n entity Figure 1https://github.com/ScanLab-ossi/LPA, and how to identify cases when under-sampling of populations makes them untenable in the immune and other domains.In the research below, we show how applying LPA to the B cell populations of six individuals scanned across eight different tissues allows us to observe both known relationships between repertoires found in gut and blood tissues  and new - clone size source data). The size of the clone in unique instances is the number of unique sequences a clone has per sample . The distance is calculated as the sum of the distances between the relative weights of the same elements (clones) in the two vectors – the domain and the entity. Clones that are prominent in the entity but not in the person, and clones that are prominent in the person but not in the entity, contribute to the entity’s distance. For distance calculation, LPA uses KLDϵ, a variant of Kullback-Leibler Divergence with a back-off model, defined by Bigi  .To decide on the adequate value of ε, we required ε to be less than the frequency of a single clone in the entire individual and still large enough so that KLD gives results in the range . We, therefore, chose 1/ . We defisamples) . After t1-norm distance between the sign-corrected signatures. Having calculated for each tissue sample, and set of tissue samples in a single tissue, their sign corrected signature distance from the individual’s clone frequency distribution, we next calculated the L1 distances of every signature-pair to compare the tissue samples and tissues directly.The signature, consisting of the K clone-elements that most differentiate the tissue sample or tissue from the individual, is a vector of tuples. Each tuple in the signature consists of an element name (a unique clone ID in this case), its distance from the domain , and a sign, indicating whether, in the entity, it is a locally missing clone or a locally over-abundant clone. To determine the similarity between entities and see how different entities are from each other, we calculate the distance between the entities’ signatures. Recall that the signatures are vectors of tuples: <element, element-KLD> with the element-KLD denoting the KLD distance between the element’s global domain weight and its local-entity weight. The element-KLD is a value in the range  and has a negative value when the element is locally missing or rare. Clearly, when two signatures have the same elements with opposite element-KLD signs, i.e., in one entity, the element is more frequent than in the domain, and in the other, it is absent, their relative distance needs to increase. To that end, positive element-KLD values are incremented by one, while negative element-KLD values are decremented by minus one. These changed signatures are termed the sign-corrected signatures. The similarity is then determined by calculating the Lhttps://github.com/ScanLab-ossi/LPA.LPA computes KLD distances between vectors on a per-element basis, performing simple arithmetic operations and logarithms. The computation is therefore the order of the number of elements in the domain, n. The signatures are of size K<<n. Given there are q entities, calculating the distance between all entities requires O(K*q^2). Hence, as detailed in , LPA is - by tissue entity distance tables). As expected in D207, which was sampled sufficiently to observe all expanded clones (- by tissue distance heatmaps and networks). This is not surprising given that none of the other individuals were sufficiently sampled to describe even the expanded clone diversity in their B cell receptor populations (Methods) that was similar to that in D207 .As a first step, we wished to see if our new method could identify tissues from samples and differentiated between the tissues in the gut and the other “blood” tissues as we had observed before . Combinid clones , we found clones Figure 2ulations  and only- by sample entity distance tables). A PCA of these distances accounted for more than 95% of the variance in its first 3 dimensions. We now see much more clearly for both D207 and D181 that the blood tissues diverge from the gut tissues. In addition, we find that the central lymphatic tissues  diverge from the lung and blood, each of which have their own cluster in the PCA (- figures of 2D PCA1_PCA2_PCA3 comparison based on sample distances and - 3d interactive figures of PCA based on sample distances). Interestingly if the test signature is calibrated correctly (see Methods) even the under sampled individuals  show similar if less precise patterns of gut tissues and lymphatic tissues (see - 3d interactive figures of PCA based on sample distances).To identify the differences between tissues more clearly, we drilled down into our data and treated each sampling experiment as an entity. The tissue categories are in some sense arbitrary/circular as they depend on our nomenclature. The only real individual entity is the experimental sample. On the other hand, each sample is clearly under-sampling the clone diversity of the repertoire as a whole. We therefore wanted to test to what extent the method would identify and differentiate individual tissues when we do not combine all the samples into a single tissue entity but rather the samples are the entities. We created a distance matrix table of all samples (Methods) the PCA of the between sample differences in D207 and D181 the 1st 3 dimensions of the PCA account for ~ 95% of the variance in the differences. At the same time in the other, less sampled, individuals the variance accounted for is between 38% and 64% (see - signature/variance). An additional phenomenon that could indicate the lack of sampling is that we very rapidly reach a plateau of similarities in the under-sampled individuals. The domain is more easily described by the few entities from which it is made. It is tempting then to lengthen the signature to the size of the entire repertoire as it seems feasible to do so. However, we find that this additional information has harmful effects. It is true that when we lengthen the signature in D145, D149, D168, and D182 the first three dimensions of the calculated PCAs account for a greater portion of the variance (about 87% - see - long signature interactive 3d PCA). We therefore conclude that by lengthening the signatures beyond the 0.5 cutoff (see Methods) added very little new information and instead added noise to our analysis of the under sampled repertoires.Although we can see some indication of the patterns described above, D145,D149, D168 and D182  appear tAnother way to consider differences between entities is to ask how different each entity is from the domain. In this case, we measured how different each tissue sample was from the individual. When we did this, we found again an indication of the consistent role of the lymphatics. Across all six individuals we found that the spleen samples were the most similar to the individual, followed by the bone marrow samples. In contrast, the blood samples were the most distant from the individual . Within the lymphatics, the spleen clearly encompasses the closest picture of the entire repertoire  and (2) low variance explained when performing a PCA off of the signature differences (Methods) are set correctly, some differences can still be observed. In general, and especially in such cases, it is very important to set a correct signature length as otherwise we found that noise is added to our comparisons and the clarity of our results degrades.In terms of its effectiveness of use with existing means of experimental B cell receptor sequence sampling, we showed that LPA works even if each specific sampling experiment under-samples the diversity of the domain. What is important is that sampling overall  is sufficient. Lack of sampling can clearly be seen by: (1) speedy plateauing of % distance  distributions are mostly shared between individuals and could potentially allow us to then create both inter and intra personal comparisons of repertoires, and also to ask questions about motifs and their abundance and effects on population size. To aid with the analysis of different kinds of B cell receptor sequence and B cell clone distributions we have created a python-based version of LPA here: The original contributions presented in the study are included in the article/UA ran the analysis and created the python version of LPA. OM designed LPA and its testing methods. UH designed the analysis and comparison of B cell populations and modified LPA to be used with immune cell repertoires. UA, OM and UH wrote the manuscript. All authors contributed to the article and approved the submitted version.This research was funded by NIH P01 AI106697 and the European Union’s Horizon 2020 research and innovation program, under grant agreement No 825821.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


In a car body, there exist thousands of resistance spot welds, which may induce large deformation during the manufacturing process. Therefore, it is expected that automotive industries will develop a method and a computing system for the fast and simple prediction of its deformation. Although the inherent strain method has been used for the fast prediction of arc welding deformation, it has not been applied to resistance spot welding so far. Additionally, the electrical-thermal-mechanical coupling analysis for the deformation induced by resistance spot welding is complicated and much more time-consuming. Therefore, in this study, a nugget model of the resistance spot weld has been developed, and the inherent strain method is extended for use in the fast prediction of resistance spot welding deformation. In addition, the deformation of a vehicle part with 23 resistance spot welds was efficiently predicted within around 90 min using the inherent strain method, displaying good accuracy compared with the measurement. Resistance spot welding (RSW) is the primary joining method in the automotive manufacturing process due to its high productivity and low cost . A typicRSW is a complicated process that involves mechanical, thermal, electrical, and metallurgical phenomena . The priBesides the coupling analysis method, the inherent strain method has been successfully applied to predict arc-welding induced deformation ,20,21,22However, as of yet, the inherent strain method has not been applied for RSW. Therefore, it is necessary to extend the inherent strain method to RSW and to develop an analytical system of RSW deformation for practical applications.There are two main steps in the RSW process, the electrode pressure step and the welding step. It is necessary to classify the inherent deformation modes induced by the electrode pressure step and welding step so that spot weld deformation induced by complicated phenomena can be expressed using a simple methodology as opposed to the conventionally inherent strain method .In this paper, the inherent deformation modes that exist in a resistance-spot weld are specified and their corresponding magnitude parameters are defined. The inherent deformation parameters are identified by measuring the deformation of a single spot weld specimen. In addition, the deformation of a vehicle part with 23 resistance spot welds was predicted using the inherent strain method and analysis system.Initial geometrical imperfection of work-piece;Gap between work-pieces before welding;Electrode pressure ;Inherent strain due to welding thermal cycle.In the automotive industry, high accuracy is always expected in assembling automotive parts. Since the phenomena in the RSW process are complicated, many factors influence on the welding quality. From the perspective of the deformation generation mechanism, the following four influencing factors have to be considered and numerically modeled.First, the initial geometrical imperfection of the work-piece, depending on accuracy of the stamping process, can be considered in FE modeling, based on the deformed geometry after stamping.Second, work-pieces with a gap that has been induced in previous manufacturing processes, such as stamping, are generally closed as a result of electrode pressure, as shown in The third and fourth items are both related to the creation of the weld nugget and can be modeled by extending the inherent deformation concept for RSW.The inherent strain method, which was first proposed by Ueda et.al , is the The inherent deformation analysis  is widelTo study the basic behavior of the nugget generation of RSW, an electrical-thermal-mechanical coupling analysis was performed using Ansys LS-DYNA. From the results of the previous section, deformation induced by the spot welding process is found to be concentrated inside the weld nugget. As in an conventional inherent deformation analysis, by classifying the inherent deformation from the strain distribution of the weld nugget, it is possible to predict the overall deformation of the welding process by considering the inherent deformation as the initial strain to the elements in the weld nugget area.To reproduce deformations induced by the RSW process, three types of inherent deformation modes, shown in Here, The three deformation modes exist in RSW, and their magnitudes can be described via inherent strain for a simple and fast prediction of the deformation. Here, the nugget model was implemented at the nugget area as shown in jth column of , respectively, which are typical values of a steel plate at room temperature because only elastic analysis is performed. Geometrical nonlinearity is taken into account. Part-to-part and part-to-clamp contact is also taken into account, resulting in static and dynamic friction coefficients of 0.3 and 0.1, respectively. Clamps were placed with a margin of about 3 mm from the position specified by the CAD.To develop the finite element model, the geometry of vehicle parts was measured by a 3D geometric scanner before welding. A finite element model consisting of shell elements was developed based on the scanned geometry, with initial geometrical imperfection induced by the stamping process. The model is shown in The nugget model is defined based on the initially designed geometry, so the nugget model may be distorted due to the welding assembling operations. The mechanism of the nugget-model distortion is shown in From the result of predicted deformation shown in (1)Based on the deformation generation mechanism in resistance spot welding, three types of inherent deformation modes, in-plane shrinkage, out-of-plane shrinkage, and out-of-plane bending were classified, and their magnitude is expressed by corresponding parameters.(2)The octagon nugget model was developed and meshed by 8 shell elements positioned with a pitch of 45 degrees along the circumferential direction.(3)The deformation that occurs in assembling the vehicle model with 23 resistance spot welds was calculated efficiently by the proposed method and validated by experiments. The calculated weld deformation agreed well with the measured deformation.(4)By updating the nugget mesh to avoid the extreme distortion of the nugget, the predicted results were found to be much closer to the measured results. Future studies should explore ways in which to avoid issues caused by a distortion of the nugget model.In this study, the concept of the conventional inherent deformation analysis was extended to predict the assembly deformation of spot welds. The main conclusions are summarized as follows: