Lottia gigantea, were analyzed by electronic spectroscopy and mass spectrometry. Both MT proteins, as well as their γ domains, exhibit a strong binding specificity for Cd(II), but not for Zn(II) or Cu(I). The LgiMTs’ γ domain renders an MII4(SCys)10 cluster with an increased Cd stoichiometry (binding 4 instead of 3 Cd2+ ions), representing a novel structural element in the world of MTs, probably featuring an adamantane 3D structure. This cluster significantly improves the Cd(II)-binding performance of the full length proteins and thus contributes to the particularly high Cd coping capacity observed in free-living limpets.Metallothioneins (MTs) constitute an important family of metal binding proteins. Mollusk MTs, in particular, have been used as model systems to better understand the evolution of their metal binding features and functional adaptation. In the present study two recombinantly produced MTs, LgiMT1 and LgiMT2, and their de novo evolved γ domain, of the marine limpet  Interestingly, in a same organism, MT isoforms might have different metal preferences or be expressed in different tissues or in response to different stimuli, supporting that MTs perform diverse physiological functions4, many of them still unknown. After 65 years from their discovery and identification in 19575, MTs still remain enigmatic7, and a hot topic of research in many scientific areas, from Biology through Chemistry to Environmental Sciences, but also Physics, Medicine, Toxicology and Pharmacology.Interactions between metals and organisms are intrinsic to life, whereby metals constitute ubiquitous and essential components of the biological systems. Some metallic trace elements such as iron (Fe), zinc (Zn) or copper (Cu) are essential micronutrients and trace elements required for the functionalization of numerous enzymes and proteins. Other metals such as lead (Pb), cadmium (Cd) or mercury (Hg) are highly reactive and, even at low concentrations, might displace essential metals from their active binding sites, resulting in very harmful effects. All living beings require, therefore, mechanisms to control the homeostasis of the essential metals as well as to counteract the harmful effects of the non-essential ones. One of these mechanisms is based on the activity of metallothioneins (MTs), a heterogeneous family of metal-binding proteins that have been involved in the physiological control of metals operating as ion reservoirs, metal transporters and/or metal deliverers to target metalloproteins, but also in radical scavenging, oxidative stress protection and anti-apoptotic defense , MTs lack a defined secondary and tertiary structure, meaning that they only exhibit a well-folded structure in association with metal ions10. Moreover, the same MT can be folded in distinct ways depending on the type and the number of metal ions that the peptide is coordinating11. Historically, MTs were natively found associated with Zn(II) and/or Cd(II)12, but when new MTs were discovered, Cu(I) was also found to be natively bound to some of them14, already revealing that not all MTs show the same abilities to bind Zn(II), Cd(II) or Cu(I) ions16. The number of Cys and their position in the amino acid sequence, together with the nature of some non-coordinating amino acids, determine the metal-binding preference as well as the metal-binding capacity of the MTs19. These structural features define whether an MT will natively bind divalent -Zn(II) and/or Cd(II)- or monovalent -Cu(I)- metal ions, and the number of ions that it can load4.MTs are characterized by their low molecular weight and their high percentage of cysteines (Cys) in their amino acid sequences20. To date, two types of metal clusters have been described in mammalian MTs binding Zn(II) or Cd(II), the MII3(SCys)9 clusters for the β domains, and the MII4(SCys)11 clusters for the α domains22. Both types of metal-Cys aggregates are characteristic of vertebrate MTs23 but have also been found in species of other animal phyla. In invertebrates, most three-dimensional structures solved by NMR are from gastropod MTs24, which mostly are bidominial proteins made of a β3 domain (CxnCxn[CxC]xn[CxC]xn[CxC]xnC) at the N-terminal region, and a β1 domain ([CxC]xn[CxC]xnCxn[CxC]xn[CxC]) at the C-terminal end (i.e. β3/β1-MTs)25. These gastropod domains can independently bind 3 divalent metal ions forming MII3(SCys)9 clusters. We have recently identified two new gastropod MTs in Lottia gigantea, a marine mollusk of the Patellogastropoda clade25. Surprisingly, L. gigantea MTs (LgiMT1 and LgiMT2) exhibited a domain organization diverging from the prototypical gastropod β3/β1-MT, since their N-terminal domains were different from any other MT domain hitherto known and thus representing an evolutionary innovation. The novel N-terminal domain, which was named γ domain, comprises ten Cys arranged in five CC duplets. Hence, the structure of L. gigantea MTs is of γ/β1 domains. In the present work, the metal-binding abilities of both L. gigantea MTs and of the new γ domain were thoroughly characterized after their recombinant production in the presence of Zn(II), Cd(II) and Cu(II) metal ions. Purified metal-protein complexes have been characterized by UV–Vis and circular dichroism spectroscopies and mass spectrometry, revealing the metal-binding features of the analyzed proteins, as well as the functional autonomy and structural independence of the γ domain. Interestingly, the present results show that the γ domain forms an MII4(SCys)10 cluster probably with an adamantane 3D structure, which represents a new structural motif in the world of MTs. Nevertheless, the novel γ-domain of MTs from L. gigantea represents an evolutionary step forward by improving the Cd-binding performance of these proteins and thus the Cd detoxification capacity of this common limpet species.Sequence analyses have revealed that in MTs, Cys residues are arranged in distinctive motifs  whose number and distribution define the MT domains: α domains with 11–12 Cys, and β domains with 9 Cys. In this modular structure, each domain is able to independently form different kinds of metallic clusters depending on the number and disposition of their Cys residues25. Our methodological approach was based on compelling evidence that heterologous productions of MTs yield metal-MT complexes structurally and functionally equivalent to those isolated from native sources28. In brief, synthetic cDNAs codifying LgiMT1, LgiMT2 and the γ domain of LgiMT2 (from Met1 to Gln45) were provided by Synbiotech  and cloned in the pGEX-4 T-1 expression vector  in order to produce GST-MT fusion proteins. Recombinant metal-MT complexes were produced in E. coli BL21 cells transformed with the corresponding recombinant plasmids, grown in Luria–Bertani (LB) medium with 100 μg/mL ampicillin, and induced with 100 μM isopropyl-β-D-thiogalactopyranoside for 3 h. After the first 30 min of induction, cultures were supplemented with ZnCl2 (300 μM), CdCl2 (300 μM), or CuSO4 (500 μM) in order to generate metal-MT complexes. Recombinant GST-MT fusion proteins were purified from soluble protein extracts with glutathione sepharose beads  and digested with thrombin , thus enabling separation of the metal-MT complexes from the GST that remained bound to the sepharose matrix. Here, it should be noticed that recombinant MTs produced in this way contain two additional amino acids (GS) at their N-term after purification. It has been demonstrated that these additional amino acids do not alter the metal-binding abilities of the recombinant MTs29. The eluted metal-MT preparations were concentrated with a 3-kDa Centripep Low Concentrator  and fractionated on a Superdex-75 FPLC column . The protein-containing fractions, identified by their absorbance at 254 nm, were pooled and stored at − 80 °C until use.Production and purification of recombinant metal-MT complexes were performed as described elsewhere3 1% (v/v). Their S, Cu, Zn and Cd content was determined by means of inductively coupled plasma-atomic emission spectrometry (ICP-AES). A Perkin-Elmer Optima 4300DV  spectrometer performed the element quantification  of the samples at the correct wavelength  under conventional conditions30. Protein concentration was calculated based on the S concentration obtained by ICP-AES, assuming that all the sulfur measured comes from peptides’ Cys and methionine (Met) residues.Solutions containing the metal-MT complexes purified from the bacterial production were diluted with HNO31. The assay conditions were as follows: 20 µL of sample injected at 30–50 µL·min-1 at 3.5–5.0 kV capillary-counter voltage, 90–110 °C of desolvation temperature, and dry gas at 6 L·min-1. Spectra were recorded between a m/z range from 800 to 3000. The liquid carrier for native conditions was a 90:10 mixture of 15 mM ammonium acetate and acetonitrile at pH 7.0, while acidic conditions was a 95:5 mixture of formic acid and acetonitrile at pH 2.4.Positive ion electrospray ionization time-of-flight mass spectrometry (ESI-TOF MS) was performed on the samples obtained from the purification process, previously equilibrated with 20 mM Tris–HCl at pH 7. A Micro Tof-Q Instrument , calibrated with ESI-L Low Concentration Tuning Mix  and interfaced to a Series 1100 HPLC pump (Agilent Technologies) was used to determine the molecular weight of the metal-MT species. This process was performed under physiologic (pH 7) and acidic (pH 2.4) conditions. Under acidic conditions, Zn- and Cd-loaded forms exchange the metal by protons and apo-form’s molecular weight is determinedUV–Vis spectrometry was performed to the samples by means of a HP-8453 diode array UV–visible spectrophotometer  to assess their absorption features. Moreover, to investigate charge-transfer transitions of the metal-LgiMT1, -LgiMT2 and -γLgiMT2 complexes, CD determinations were performed in the UV–Vis range (200–500 nm) using a Jasco spectropolarimeter  interfaced to a computer (J700 software). Raw data obtained from these experiments was processed with GRAMS32 software .L. gigantea25. Both MTs were 74 amino acid long with 19 Cys (25.7%), only differing at positions 6, 20, and 49: Pro, Lys, and Pro residues in LgiMT1, and Ala, Ser, and Ser in LgiMT2 , which was connected by a linker of six amino acids to an archetypal 9-Cys β1 domain ([CxC]x3[CxC]x3Cx5[CxC]x3[CxC]) at the C-terminal region  and LgiMT2 (accession number QHN12718), had been identified in the marine gastropod L. gigantea MTs as well as of the γ domain, we studied the formation of metal–MT complexes by ESI–MS analyses. LgiMT1, LgiMT2 and the γ domain of LgiMT2  were heterologously expressed in E. coli grown in media supplemented with Cu(II), Cd(II) or Zn(II) salts. The election of the γ domain of LgiMT2 relied on the fact that it was more conserved than that of LgiMT1 when compared across the γ domains of other Patellogastropoda MTs -enriched productions of additional peaks in the ESI–MS spectra at acidic and physiologic pHs 4 chromophores, seemed to appear (confirming a high structuration degree of the chromophores), even if the negative band of the exciton coupling has disappeared by the very high intensity of the band related with the secondary sequence of the protein and the peptide bonds (up to 240 nm). These spectroscopic fingerprints also contrasted with those obtained for the Zn-preparations , confirming the Cd-thionein character of both LgiMTs  -or Zn(II)- ions bound, but these are not their preferred ones.Finally, the productions of LgiMTs in Cu(II) surplus conditions also sustained their Cd-specificity. ‘Genuine’ Cu-thioneins render single homometallic species when synthesized under Cu surplus but yield a mixture of species when produced in Cd(II)- or Zn(II)-enriched culturesMTs Fig. . SpectroMTs Fig. D. As obs4-γLgiMT2 species when synthesized under Cd(II) surplus 10 clusters, as no intermediate species were detected. Similar results, although less intense, were observed in Zn(II) surplus productions. Zn4-LgiMT2 and Zn4-γLgiMT2 peaks were still present at pH 2.4 10 metal cluster is spectroscopically dominant over the other half of the entire protein.The most conspicuous feature of LgiMTs was their γ domain, a novel MT domain that seems to be exclusive of the Patellogastropoda clade. We characterized the biochemical properties and metal-binding features of this domain from the LgiMT2 isoform. The γLgiMT2 domain rendered a unique Cdlus Fig. C, which 2.4 Fig. C, and pH2.4 Fig. D. Additi3(SCys)9 cluster with poor contribution to the final CD envelope, and that easily exchanges metal ions. Our data also suggest that the strong Cd-thionein character of the γ domain is transferred to the full-length LgiMTs proteins. Based on its stoichiometry and a comparison with stoichiometries and structures of three-metal and four-metal clusters from other MTs (Table II4(SCys)10 cluster of the γ domain adopts an “adamantane” cage structure that contrasts with the cyclohexane-like ring structure in the MII3(SCys)9 cluster of the “conventional” gastropod β1 domains  and other limpets, some of them still thriving in marine realms dominated by Cd emanations through volcanic and hydrothermal activities49, or in habitats contaminated by anthropogenic Cd emissions50.All limpet MTs so far known show in their primary structure the typical sequence features as described for the two MTs of tea Fig. . It can tea Fig. D and 3D.tea Fig. . The higII4(SCys)10 cluster, and on its affinity constants for divalent metal ions such as Zn(II) and Cd(II).The discovery of the new γ domain in limpet MTs will pave the way for further investigations focusing, among others, on the 3D structure of this novel domain with its M


Deformation instability is a macroscopic and microscopic phenomenon of non-uniformity and unstable deformation of materials under stress loading conditions, and it is affected by the intrinsic characteristics of materials, the structural geometry of materials, stress state and environmental conditions. Whether deformation instability is positive and constructive or negative and destructive, it objectively affects daily life at all times and the deformation instability based on metal-bearing analysis in engineering design has always been the focus of attention. Currently, the literature on deformation instability in review papers mainly focuses on the theoretical analysis of deformation instability (instability criteria). However, there are a limited number of papers that comprehensively classify and review the subject from the perspectives of material characteristic response, geometric structure response, analysis method and engineering application. Therefore, this paper aims to provide a comprehensive review of the existing literature on metal deformation instability, covering its fundamental principles, analytical methods, and engineering practices. The phenomenon and definition of deformation instability, the principle and viewpoint of deformation instability, the theoretical analysis, experimental research and simulation calculation of deformation instability, and the engineering application and prospect of deformation instability are described. This will provide a reference for metal bearing analysis and deformation instability design according to material deformation instability, structural deformation instability and localization conditions of deformation instability, etc. From the perspective of practical engineering applications, regarding the key problems in researching deformation instability, using reverse thinking to deduce and analyze the characteristics of deformation instability is the main trend of future research. In the majority of engineering application fields, such as aerospace, automobile, coastal power station, etc., the deformation and stability failure of materials is one of the key issues. From the perspective of macrophysics, instability is a phenomenon in which a structure changes from one equilibrium state to another equilibrium state, or to an unstable state. In essence, instability is a change in energy. The deformation instability of materials not only has macroscopic instability, but also has microscopic instability . GeneralTherefore, deformation instability is a process based on energy change and guided by shearing deformation, and the deformation instability process of metal materials is a complex process with multi-factor coupling. That is, it is mainly related to multiple factors, such as material intrinsic properties, material macro/microstructure, geometric structure, ambient temperature, and loading conditions ,14,15,16At present, many scholars have adopted theoretical analysis ,17, numeUp until now, there have been many review papers on deformation instability, most of which only focused on the theoretical analysis of deformation instability (instability criteria); there have been very few papers that classify and review based on material characteristic response, geometric structure response, analysis methods and engineering applications. Therefore, from the above four aspects, this paper comprehensively analyzes, summaries and reviews the latest discoveries and achievements in the study of the deformation instability of metal materials. The purpose is to help more researchers quickly extract the latest research results in this field, and compare the value and significance of their own topics with predecessors, so as to propose more innovative research content.Since deformation instability is closely related to the intrinsic characteristics of materials, macro/microstructure, forming temperature, stress loading conditions and other factors, many scholars have clearly defined deformation instability for different materials and different forming conditions. At the same time, relevant theoretical criteria are established to predict, analyze and control the deformation instability of materials.Based on the problem of elastic compression rods, Euler proposed the definition of compression rod instability first; that is, the minimum load which causes the compression rod to bend is the critical load of compression rod instability. It was concluded that critical load is inversely proportional to the square of rod length (as show in Equation (1)), also known as the “engineering beam theory”. Since then, people have had an understanding of deformation instability. Felippa et al.  further When the majority of metal materials undergo plastic deformation, the essence is also a change of energy. When the increment of strain energy is less than the increment of work performed by an external force, plastic instability will occur. From the perspective of stress and loading force, plastic instability refers to the phenomenon that when the load on the material reaches a certain critical value, even if the load decreases, the plastic deformation will continue. Plastic deformation instability includes load instability and deformation instability. For general metal materials, load instability is accompanied by geometric deformation instability; the material will be unstable when there are significant extreme points on the tensile curve. In a deformation process dominated by tensile stress, deformation instability is mainly manifested in the form of shear deformation and local necking, which is called tensile instability . On the A is instantaneous cross-sectional area, and dA is the value of the change in cross-sectional area.Tensile instability includes dispersion instability and concentration instability. After the material undergoes stable and uniform deformation under tensile stress, there is a metastable flow in a relatively wide area, which is called dispersion instability. When the tensile necking reaches a certain extent, the unstable flow will be confined to a narrow area, which is called local instability or concentration instability. Swift proposed  that, foIn the complex stress state, the stress intensity K and n are material constants.If the stress–strain relationship of materials follows the power function form y, the direction perpendicular to it is x, and the angle between maximum principal stress x is Hill proposed the definition of concentration instability in 1952, firstly , which rThe direction of local necking line is:Marciniak and Kuczynski jointly proposed the famous M–K groove theory . Accordiirection . Figure In recent years, numerous researchers have modified the classic M–K instability theory for different materials, allowing for the prediction of deformation instability and sheet forming limits under different forming conditions. A summary of the research results can be found in m is normal vector of the yield surface and h is the hardening rate.Storen and Rice  were ablThis research shows that, compared with the classic M–K model, the Storen–Rice model predicts forming limit diagrams for an aluminum alloy sheet in biaxial tension; it is closer to the experimental results ,51.Bressan and Williams  studied Semiatin et al. ,54 analyP ≤ 0. Geometric instability is the process of materials’ non-uniform deformation; that is, when the uniform strain is greater than the strain hardening exponent, the strain hardening effect cannot offset the increase in stress caused by the contraction of cross-section, and geometric instability occurs at this time. Typically, in the plastic instability process, load instability and geometric instability usually occur simultaneously. In the case of superplastic materials, necking does not occur after load instability, and it can re-establish a prolonged and nearly stable deformation process after geometric instability [Many scholars have given corresponding definitions of deformation instability according to different materials’ formability. For example, Song et al. ,56 studitability . In additability ,59 found(1)Hart’s instability criterion Based on the above definitions of deformation instability, in order to more accurately analyze and predict the deformation instability behavior of materials, a variety of deformation instability criteria have been used for judgment and prediction. Among them, several common criteria are as follows:Under uniaxial tension, the material appears to have deformation instability when the following conditions are met:m is the strain rate sensitivity parameter:(2)Jona’s instability criterion Under uniaxial compression, the localized flow criterion is as follows:According to the above criterion, flow localization increases with the increment of material strain rate sensitivity. Taking into account the localization of strain rate, an additional criterion given for flow localization in uniaxial compression is as follows:(3)Semiatin’s instability criterion Semiatin and Lahoti proposed a phenomenological criterion for predicting flow localization in the hot forging of titanium alloys. According to this criterion, shear banding may occur when the ratio of dimensionless flow softening rate to strain rate sensitivity parameter exceeds 5. The instability condition for uniaxial compression can be expressed as:(4)Dynamic Material Model (DMM) criterion D is the dissipation function that characterizes the flow behavior of the material, and G and J, D can be replaced by J, this is called power co-content.The DMM is based on the principle of irreversible thermodynamics proposed by Ziegler, which is suitable for large deformation processes of metallic materials. When the entropy rate produced by the material deformation does not match the entropy rate imposed on the material, flow localization or instability will occur. Therefore, the flow instability criterion is:Therefore, the instability criterion also can be expressed as follows:J into the instability criterion, the following expression can be obtained:Substituting the expression of According to the continuity criterion, when the parameter −1. Zheng et al. [(5)Gegel’s and Alexander’s instability criterion m is the strain rate sensitivity, s is the entropy, and T is temperature. Meanwhile, considering the Lyaponov function LMetallurgical instability criterion Therefore, the metallurgical instability condition is In summary, the definition and criteria of deformation instability under specific conditions are given according to the deformation instability characteristics of different materials, different structures, and different deformation conditions. Deformation instability is a process based on energy change and guided by shearing deformation. Deformation instability will promote or inhibit the effective forming of materials, which is very critical for engineering applications.Deformation instability is related to material characteristics; whether it is the inherent characteristics of materials or the new characteristics induced by the change of external conditions, the deformation instability characteristics will be different. Therefore, this section mainly reviews the deformation instability characteristics induced by inherent properties of materials, and the deformation instability characteristics of new properties, which are induced by changes in the forming conditions.Different materials have different inherent characteristics. It is well known that super-plasticity is the inherent characteristic of superplastic materials, and the super-plasticity of materials can also be a new characteristic induced by high temperature, multi-pass processing and other external conditions. In general, super-plasticity is an underlying property of materials with lattice structures. From the perspective of bearing capacity, superplastic materials do not show geometric instability after load instability, and there will be a similar stable deformation process after geometric instability . Microscm and strain hardening exponent n are the main mechanical parameters which affect the deformation instability of superplastic material; the deformation instability mode is mainly represented by necking at high strain rate. Sheinerman [m, strain hardening exponent n, and hardening coefficient. They put forward the criterion of tensile load instability and geometric instability under constant temperature; that is:(1)Load instability criterion are as follows:Zhang et al.  establiseinerman  proposedeinerman ,56 analyAccording to the load instability criterion, the load instability point of superplastic materials appears earlier than plastic materials.(2)The geometric instability criterion is as follows:Stress instability is manifested at this point because material necks occur when the materials have geometric instability.In addition, a majority of metal materials will also exhibit superplastic deformation behavior under the action of high temperature, fine-grain strengthening, or other special conditions. Jafarian et al. ,76 studii et al.  conductem) and hardening exponent (n). Nazeer et al. [m, low n, and thermal stability are necessary to achieve super-plasticity. It was found that the elongation of the WE54 Mg alloy reached 726% at 400 °C. If this temperature is exceeded, the thermal stability of the material will decrease, the super-plasticity will deteriorate, and deformation instability and cracks will even be generated, thus limiting the further extension of the material and eventually leading to deformation failure. Recent studies by some scholars on the characteristics of the superplastic deformation instability of other alloy materials are summarized in Malik et al.  studied r et al.  also sugIn order to meet the requirements of lightweight materials, and better performance in aerospace, automotive and other industrial fields, research and development of various new materials are increasing gradually; they are made of various materials. Due to the different functions of various materials, functionally gradient metal materials (FGMM) have been formed ,85. FGMMUnder thermoforming conditions, the plastic deformation instability of material is characterized by flow instability, and the material flow occurs before local necking. From the analysis of external forming conditions, conditions such as tensile load, friction conditions, temperature gradients or local softening of materials may cause flow instability of materials ,90. From−1), flow instability occurs in both thermal and warm deformation regions. At low strain rates (0.01 s−1), flow instability occurs only in lower temperature ranges (700~900 °C). The reason for this is that low strain rates can cause microcracks or micro-void nucleation, leading to instability, while high strain rates can result in the formation of adiabatic shear bands within high temperature regions, ultimately causing shear instability within the materials.Ji et al.  investig−1. The TC4 alloy is unstable in a range of 800~850 °C and 0.01~1.0 s−1. Macroscopic fracture morphology is shown in Zheng et al. ,100 and Except for the above contents, the latest research on deformation instability in hot forming by some scholars is summarized in The deformation instability characteristics of materials are closely related to their macro/micro structures. Many scholars have studied the influence of macro geometric configurations such as sheet metal, tubes, and beam-column structures on deformation instability behaviors. They have good engineering application orientations and provide references for practical applications. Therefore, this section reviews the latest research results on deformation instability characteristics according to different geometric structures of materials.The deformation behavior in sheet metal forming processes is relatively complex. In sheet metal stretch forming, deformation instability is mainly in the form of shearing; in the extrusion or stamping forming, the deformation instability is mainly in the form of wrinkling. Shear instability and wrinkling can both cause many problems, such as easy corrosion, easy damage, and difficult assembly . TherefoIn order to study the local deformation instability characteristics caused by local uneven plastic deformation during the plastic forming process of thin-walled metal sheets, Li R. et al.  and Li FChen et al. ,122 inveWrinkling is the main form of instability in the tube forming process, and includes bending, compression or liquid expansion. This wrinkling instability generally tends to be localized, and can possibly lead to catastrophic failure such as collapse or rupture ,127; wriJia et al. ,133 studLi et al. ,141,142 In addition to the rotary draw bending method, there are also other forming methods for the bending tube, such as push bending, free bending, etc. The deformation instability during the forming process is summarized in The deformation instability of beams is characterized mainly by buckling instability, which is generally considered to be a critical failure mechanism that needs to be prevented from occurring in most cases. During the buckling process, there may be multiple modes in the buckling response due to differences in loading forces, temperatures, etc. ,153,154.Salem et al.  and YangAccording to the review of the previous four sections, the research methods of material deformation instability mainly include the establishment of theoretical instability criteria, the use of numerical simulation predictions and experimental verification. Therefore, this section elaborates and summarizes the latest research methods of deformation instability.As we all know, theory serves as the premise for various studies and provides the basis for further investigations. Theoretical analysis of deformation instability research is very important, and is the guarantee for the feasibility of follow-up research results. Therefore, this section mainly elaborates on and summarizes the latest research on deformation instability criteria and instability prediction.Chawla et al. ,165 usedPozorski et al. ,167 studLi et al. ,174, basFor the study of material deformation instability, theoretical analysis alone is not enough. It must be combined with finite element numerical simulation, experimental research and other comprehensive analysis methods to obtain the best research results quickly and accurately. Therefore, many scholars use finite element simulation, experimental research or a combination of the two methods to analyze the causes of deformation instability, to predict the conditions of deformation instability, or control the behavior of deformation instability.Malik et al. ,177,178 However, in order to analyze and predict the deformation instability of materials more accurately, most studies take the method of combining finite element simulation and experimental research. Huang et al.  analyzedIn engineering applications, the deformation instability of materials may bring potential danger to the service of parts, or directly cause catastrophic accidents; there are also some parts that may take advantage of the deformation instability characteristics of materials to achieve special functions, which can play a key role in special occasions. Therefore, this section summarizes applications in engineering in terms of utilizing and avoiding deformation instability.In industrial fields such as aerospace, automobile engines, and coastal power stations, axial multilayer compression tubes and variable-diameter tubes play a main role in engine exhaust, fuel transportation and oil transportation because they have the advantages of changing fluid direction and easy installation. The controllable formation of deformation instabilities is essential; however, it is imperative to prevent the occurrence of failures . VariablIn addition, plastic hinges can realize unidirectional or multidirectional rotation and transmit bending moments in practical engineering applications. The deformation instability of the internal structure of the plastic hinge is used to dissipate energy, increasing the safety reserve and multi-degree of freedom energy release of the actual support structure. Therefore, plastic hinges are widely used in practical engineering, such as in building anti-shock design, automobile anti-collision design and aviation anti-collision design ,198,199.However, in the structural parts and collision parts of aerospace and automotive industries, most of the high-strength and light-weight parts are in the forming process of stamping, spinning, rolling, forging, etc., and deformation instability must be avoided ,212. Li In conclusion, the deformation instability of materials is extremely critical in engineering applications. According to the specific forming conditions and forming requirements, catastrophic failure must be avoided and deformation instability should be used reasonably for process forming.The study of deformation instability is very important in engineering applications, and it has always been the focus of the stability of material forming. Previous research has achieved relatively perfect results in terms of theoretical analysis solutions and other research methods on metal deformation instability. This paper comprehensively analyzes, summarizes and reviews the latest theoretical methods, discoveries and achievements in the study of the deformation instability of metal materials, helping more researchers to quickly extract the latest research results in this field, and proposing more innovative research content. This work has a high reference significance. Additionally, the conclusions are as follows: (1) Based on the classical instability theory, more modified deformation instability criteria have been proposed and deduced. They can be used to accurately predict and control deformation instability, and to achieve the purpose of improving the precision of metal forming. (2) Inherent characteristics of materials or new properties caused by changes in forming conditions all produce different deformation instability characteristics. Notably, instability characteristics caused by the latter are typically more complex. (3) The deformation instability characteristics of materials are closely related to their macro-micro structures, manifesting primarily in the form of wrinkling, buckling, etc. (4) The main methods of deformation instability research include theoretical analysis and FE simulation and experiment, and most studies combine two or three methods to obtain feasible conclusions to improve the forming accuracy. (5) Deformation instability of materials plays a crucial role in engineering applications. Depending on the specific forming conditions and forming requirements, it is essential to avoid catastrophic failure and utilize deformation instability in a reasonable manner for process forming.However, there are still many key problems in the study of deformation instability. In practical engineering applications, there are many factors affecting deformation instability, and the forming conditions and forming environments of materials are very complex. In previous studies, some conditions have been idealized and the modal technology for deformation instability analysis was not accurate enough; there is also a lack of detailed research on different proportion superposition analyses of various deformation instability modes. The related research is all about finding the critical load to predict instability, but the proportion of the impact of load on the different instability states is unknown. When the applied external conditions change, it can be difficult to predict the location of instability using the existing analysis method. Similarly, if, in the complex environment of engineering accidents, it is known that the parts have several instability states, it can be difficult to know how to quickly obtain the critical load at that time, which requires new theoretical analysis and analytical solution. With the rapid development of informatization and industrialization, new materials are continuously being developed and used. Whether the previous related research is applicable to the deformation instability analysis of these new materials still needs to be debated and verified.Therefore, research on the deformation instability of metal materials should mainly focus on the complex forming conditions of practical engineering applications and the forming analysis of new materials. Additionally, using reverse thinking to solve practical engineering problems, proposing universal instability criteria, broadening the application of instability criteria, and conducting correlation analysis with deformation damage, instability fracture, and service life changes caused by deformation, are the inevitable trends of future development.


This study aimed to subject the albino peach palm to cooking and drying processes and characterize the raw pulp (RP), cooked pulp (CP), raw pulp flour (RPF), and cooked pulp flour (CPF). The product’s chemical composition, bioactive compounds, and physicochemical, color, thermal, morphological, and functional–technological properties were evaluated. The proximate composition showed that carbohydrates were the main constituents of all the products (69.59–72.08 g/100 g). The cooking process decreased the lipids (10.21 to 8.63 g/100 g), dietary fiber (13.64 to 12.81 g/100 g), and total sugar content (59.18 to 49.10 g/100 g) of the CP. The colorimetric parameters indicated a significant browning of the CP and CPF, which can be attributed to the Maillard reaction and lipid oxidation. After cooking, the total phenolic compound and ascorbic acid content decreased in the pulp. The RPF and CPF displayed different thermogravimetric behaviors. The spectral patterns in the infrared region showed the characteristic bands of organic compounds that are present in the structure of starches. The scanning electron microscopy showed amyloplast and fiber bundles with starches in the RP and gelatinized starch granules in the CP and CPF. The RPF presented small and heterogeneous starch granules with isolated amyloplast. The RPF and CPF showed different granulometric patterns and technological indices. The results suggest that the pulp and flour from the pulp of albino peach palms can be exploited by the food, pharmaceutical, and biotechnological industries. Bactris gasipaes), açaí (Euterpe oleracea), bacaba (Oenocarpus bacaba), and buriti (Mauritia flexuosa). These species can be used by directly consuming its fruits and obtaining products and byproducts, such as drinks, creams, flour, and oils [The Amazon region is rich in native fruits of various species, which are of great importance for the local population’s culture, food, economy, and health . These fand oils ,6.The peach palm fruit is known worldwide as “pupunha” (in Brazil), “pejibaye” (in Costa Rica), and “chontaduro” (in Colombia) ,7,8. ThiThe peach palm fruit needs to be cooked in water before consumption to inhibit anti-nutritional factors , eliminate oxalate crystals present in the peel ,11, and The cooking process required for fruit consumption and the drying to obtain flour could lead to significant changes. These processes promote changes in food’s physical and chemical characteristics, such as browning and protein denaturation, nutritional composition, and cellular structure. In addition, these processes affect food products’ sensory and color characteristics ,22. DespTherefore, this work aimed to evaluate the chemical composition, bioactive compounds, and physicochemical, color, thermal, morphological, and functional–technological properties of albino peach palms before and after the cooking and drying processes. To the best of our knowledge, this work comprises the first report on the influence of the cooking and drying of albino peach palms.Five bunches (~20 kg each) of albino peach palm (~100 kg of fruits) were acquired at a fair located in the metropolitan region of Belém, the state of Pará, Brazil , and which were harvested during the period September to December 2020. This research was registered with access activity in the National System for the Management of Genetic Heritage and Associated Traditional Knowledge . The voucher specimen was identified and deposited in the Herbarium “HF Professora Normélia Vasconcelos” at the Federal University of Pará  and notified under register 4070.At this stage, half of the fruits (with peel) were cooked in water in a pressure cooker for 15 min, according to the traditional procedure performed in Northern Brazil. The other half of the fruits were separated without cooking. Both fruit samples (raw and cooked) were peeled, and the pulp was separated from the seed using a stainless steel knife. The edible portion of peach palm (raw and cooked pulps) was crushed separately in a multiprocessor  and then placed in plastic bags and packed in a vacuum sealer . The samples were stored at −20 °C and wrapped in aluminum foil for protection against light until the analysis. To obtain raw and cooked peach palm flour, a part of the samples of their respective pulps was subjected to drying at 55 °C  in an ovw) was determined with a direct measure on a water activity analyzer .The analyses of moisture, ash, total proteins , lipids, total titratable acidity , hydrogen potential, and total and reducing sugars were performed according to the Association of Official Analytical Chemists . DietaryL* for luminosity, a* for red color intensity, b* for yellow color intensity). The chromaticity (C*) and the Hue angle (h°) were calculated according to McLellan et al. [The instrumental color parameters were analyzed in a digital colorimeter , using the CIELAB system to assess the chromaticity coordinates  and digested with 5.0 mL of HNO3 25% (v/v) and 5.0 mL of H2O2 30% (w/w) in a microwave oven. The heating program consisted of the following three steps: 800 W, 180 °C for 10 min; 800 W, 180 °C for 15 min; and ventilation for 50 min. After digestion, the digested part and the residue (silicate compounds that were not digested) were quantitatively transferred to a 14 mL volumetric flask, and 10 mL of ultrapure water was added. The same procedure was used to prepare the analytical blank, without adding the sample. For the analysis of Al, As, Ba, Ca, Cd, Cr, Cu, Fe, Mg, Mn, P, Se, and Zn, an inductively coupled plasma optical emission spectrometer  was used. All solutions and dilutions were prepared with ultrapure water (resistivity 18.2 MΩ cm) obtained from a water purification system . Nitric acid  was used at 65% v/v, previously purified by a distillation system .This analysis was performed according to Alves et al. . A mass The titrimetric method quantified the ascorbic acid content with the reagent 2,6-dichlorophenolindophenol (DCFI) . The totA digital electromagnetic stirrer  was used, with a constant stirring speed and frequency of 50/60 HZ. Each flour was sieved in a set of 9-, 20-, 28-, 60-, 80-, and 100-mesh sieves , and a pan, for 10 min . The samThermogravimetric analyses of the raw and cooked pulps and flour were performed with a thermobalance  under the following conditions: airflow of 60 mL/min, a heating ramp of 10 °C/min, in the temperature range of 20 to 800 °C, in an alumina crucible with a mass of 5 mg (±0.5).−1. The sample was incorporated into potassium bromide pellets, with Scan 100 and a resolution of 4 cm−1. All bands were analyzed by the software Origin 8.0.In the infrared region, the absorption spectroscopy was carried out using the same samples with a spectrometer  with records in the spectral frequency range of absorption from 4000 to 500 cmThe micrographs were obtained using an electron microscope  with an electron gun-type FEG (field emission gun). The samples were metalized with Au for 2.5 min for the deposition of a film on the sample, with a 10 to 15 nm thickness. The images were generated by detecting secondary electrons, using a voltage acceleration between 5 and 10 kV and working distances between 10 and 15 mm.The functional technological properties: water solubility index (WSI), water absorption index (WAI), and oil absorption capacity (OAC), were performed and calculated according to Anderson et al. , with sop ≤ 0.05) using the software the version number for software Statistica 10.0 .All analyses were performed in triplicate, and the results were expressed as mean ± standard deviation. Data were submitted for analysis of variance (ANOVA) and Tukey’s complementary test for means comparison  between the pulps, indicating that cooking caused significant changes in this component. The ash contents found in both flour (2.12–2.21 g/100 g dm) allowed for the classification of these samples as having a low ash content (2–6 g/100 g) [For the ash content, a significant difference was observed (g/100 g) . The resg/100 g)  for peacg/100 g)  for cookp ≤ 0.05). This behavior can be attributed to the decrease in other flour constituents, such as total sugars. The protein content found in both albino peach palm flour (RPF and CPF) was higher than that found (8.64 g/100 g dm) for a peach palm by-product (stem portion) [Regarding proteins, the content observed in both flour was higher than in the respective pulps (portion) . From a portion) . Thus, pportion) ,42,43.p > 0.05), which suggests that neither cooking nor drying caused the loss of this constituent. However, a tendency towards a reduction in the lipid content was observed in the CP and CPF, compared to the values of the RP and RPF, respectively, which can be attributed to a small loss of lipids due to leaching during cooking. The lipid values in the RP and CP (10.21 and 8.63 g/100 g dm) were within the range observed by Melo et al. [The lipid contents were statistically equal for the four samples  , indicating that neither cooking nor drying caused the loss of this macronutrient. In turn, the total dietary fiber content was not statistically different (p > 0.05) between pulps, but the values were statistically different (p ≤ 0.05) between flours. For the total and insoluble fibers, a decreasing trend in the CP and CPF values was observed concerning the RP and RPF, which can be attributed to the leaching of these constituents. The insoluble dietary fiber represented 68.2%, 57.1%, 87.1%, and 73.6% of the total dietary fiber in the RP, CP, RPF, and CPF, respectively. These results corroborated those Pires et al. [The carbohydrates were the major macronutrient in the pulps (RP and CP) and flour (RPF and CPF), and the values were not statistically different . Similar behavior was observed for reducing and non-reducing sugar fractions. These results indicated that during cooking, the dissolution and leaching of sugars occurred, as the same was found by Giombelli et al. [A lower content of total sugars was observed in the CP and CPF compared with the respective RP and RPF , while, for the RPF and CPF, the TEV was statistically equal  (p > 0.05). The TEV observed in both flour was higher than the values reported for wheat  and oat  flour [A higher total energetic value (TEV) was observed for the RP  than for the CP  (g) flour , which ig) flour .w values (aw < 0.25), capable of guaranteeing the microbiological stability of the products (aw < 0.6). On the other hand, the aw values in the RP and CP (0.98) were highly favorable to the activity of microorganisms, chemical and enzymatic reactions, and physical changes in the products [The data showed that the reduction in the moisture promoted by drying ensured the obtainment of flour with low aproducts ,24,25. Tproducts , such asproducts .p ≤ 0.05). On the other hand, the RP and RPF, as well as the CP and CPF, in general, showed the same colorimetric pattern (p > 0.05). Cooking caused a decrease in the brightness (L*) and whiteness index (WI) and an increase in the parameters b* (yellow color) and C* (chromaticity) of the pulp. The L* and WI values decreased significantly during cooking (p ≤ 0.05), but, during drying, no reduction in these parameters was observed (p > 0.05). Therefore, there occurred a browning of the pulp during cooking  and in the RPF (b* = +16.0), which was confirmed by the values of the C* and h° that were attributed to the light yellow color of the RP (C* = 18.57 and h° = 91.35°) and RPF (C* = 15.17 and h° = 94.92°) [C* values indicated an increase in the intensity of the yellow color of the CP (C* = 25.93) and CPF (C* = 24.93).The increase in the P and CP  and visuP and CP , the b*  94.92°) . In turnjambo (Syzygium jambos) (5.71 mg/kg for Cu), mangosteen (Garcinia mangostana) (5.71 mg/kg for Cu and 23.3 mg/kg for Fe), muruci (Byrsonima scrispa) (1.8 mg/kg for Cu and <0.2 mg/kg for Zn), ajuru  , and umari (Andira spinulosa)  [ for Zn) .The minerals found in the pulps and flours of albino peach palm are essential for human body metabolism. Generally, the macro minerals are related to nerve cell functions, and the micro minerals are associated with the formation of erythrocyte cells . Mg, thep ≤ 0.05). Regarding the cooking, the reduction observed can be attributed to the leaching of these compounds by the cooking water and the cooking temperature (~100 °C). During drying, in turn, the degradation can be attributed to the process temperature as well as the exposure time of the samples.The contents of TPC, total flavonoids, ascorbic acid, and total carotenoids in the samples are shown in Rojas-Garbanzo et al.  were thep > 0.05) was observed for the content of total flavonoids between the RPF and CPF, but the drying process degraded 87.7% of the flavonoids from the RP, while the CP just lost 78.8% of these compounds. These results showed that drying the peach palm pulp at 55 °C caused a greater degradation of the flavonoids in the RP than in the CP, indicating that cooking increased the thermostability of this class of compounds.Flavonoids, compounds included in the group of phenolic compounds, showed similar results in the TPC during cooking, but the degradation of the TPC was 18.6%, while for total flavonoids, it was 47.3%. No significant difference  when exposed to different processes such as storage, cooking, and heating .p > 0.05). AA was shown to be susceptible to reduction at high temperatures and, as it is a water-soluble compound, it may have been leached from the pulp during cooking. However, the AA contents in the flour were approximately ten times lower than those observed in the respective pulps, which allows us to state that drying at 55 °C caused a highly significant reduction in the AA content of the raw and cooked pulps (p ≤ 0.05). In this way, it could be seen that the temperature and duration of drying had a much greater impact on the degradation of AA than cooking.Ascorbic acid (AA) showed the same behavior observed for the flavonoids during cooking. The CP showed a 19.9% reduction in the AA content compared to the RP. The AA contents in the RPF and CPF were statistically the same , although there was a 6% reduction in the total carotenoid content after cooking. Regarding the flour, it was observed that the CPF had a total carotenoid content 26% higher than that observed in the RPF. This result indicated a greater fixation of the carotenoids in the CP during the drying at 55 °C. On the other hand, the results found after cooking the albino peach palm were contrary to those of some authors [The RP and CP did not show carotenoid contents statistically different , two exothermic peaks were observed for all products (pulps and flours), the first at approximately 350 °C and the second at approximately 500 °C. These peaks are related to the release of energy in the same region of the main mass decays of the TG/DTG curves. The first peak showed a low intensity for the RP A and RPFThe exothermic peaks observed for the RP were related to the release of energy resulting from successive degradations and oxidations of organic-based macronutrients  and inorganic macro- and microminerals. On the other hand, for the CP, RPF, and CPF, the increase in the intensity, mainly of the second peak, was attributed to the release of energy from the carbonization process, since these products were submitted to thermal processes (cooking and/or drying), which can promote starch gelatinization, protein denaturation, and lipid oxidation .The exothermic peak at approximately 500 °C paralleled a mass decay observed in the TG curve, representing the final mass loss. Finally, the thermal behavior presented by the RP and CP indicated that the hydrothermal treatment to which the fruits were submitted (cooking with water at high temperature and pressure) and drying at 55 °C, used to obtain the flour, interfered with the differential thermogravimetry profiles of the products.−1 for the RP .The spectra of the RP A and CP  the RPF C showed  species , like pe−1, which was practically suppressed in the CP and CPF. This peak is characteristic of the presence of primary amide bonds (primary elongation C=O). For secondary amides, the characteristic band occurred at 1155 cm−1, which is present in proteins [The RP and RPF showed a strong absorption peak at 1637 cmproteins ,74. Thes−1, which correspond to the stretching of alkanes (–CH3) and the stretching of the bonds of the C–O glycosidic groups, related to the bonds of the starch-forming units (D-glucose molecules) [The four samples showed medium and low absorption peaks between 2926 and 2853 cmlecules) ,75. Peaklecules) .−1 for the CP  of the starch-forming units (D-glucose units) can cause changes in the linear (amylose) and branched (amylopectin) chains of starch. These alterations can promote structural and functional changes in starch, attributed to gelation, paste formation, and retrogradation ,76.Scanning electron microscopy (SEM) was used to evaluate whether the hydrothermal process (cooking in water under high temperature and pressure) applied to peach palm and if drying the RP and CP at 55 °C promoted morphological structure changes in the CP, RPF, and CPF. The micrographs are shown in The micrographs showed that the CP’s morphological structure had undergone more modifications compared to the RP. During the hydrothermal process, heat in the presence of water promoted the rupture of amyloplasts, with the consequent release of some starch granules C. This dThe micrographs of the RPF  showed tIn general, the morphological aspects of the CPF  were simThe results of the particle size distribution for both the RPF and CPF  showed tAs the conditions used in drying the RP and CP and in grinding the dry products were the same, the granulometric profiles of the flour allow us to state that the hydrothermal process used in cooking the peach palm caused the weakening of the molecular structures of the albino peach palm pulp, making the CPF less resistant to milling than the RPF. The observed behavior can be attributed to the disruption of the amyloplast membranes during the hydrothermal process, evidenced in the micrographs of the CP  and CPF p ≤ 0.05). These results indicated that the hydrothermal process (cooking) caused changes in the main technological functional properties of the albino peach palm flour. Zhou et al. [The values of the technological functional properties analyzed in the RPF and CPF are shown in u et al.  reportedu et al. , cookingp ≤ 0.05). Additionally, the highest WAI value for the CPF indicated that during the hydrothermal process, starch molecules might have been converted into lower-molecular-weight molecules , which have more affinity for water molecules [Regarding the WAI, according to Silva , flour wolecules ,84.The results showed that during the hydrothermal process, there was a greater increase in the hydrophilic constituents than in the hydrophobic constituents in the pulp, which justifies a lower OAC and a higher WAI in the CPF. The OAC value is directly related to the protein content in the food; therefore, the lower the protein content, the lower the food’s ability to absorb oil . The OACFinally, the RPF showed foaming capacity (FC), which indicates that the applied cooking eliminated the foaming compounds from the pulp. Likewise, proteins also influence the foaming capacity of the flour due to their amphiphilic properties and because they are surfactants . The abiThis study comprises the first report on the chemical composition, bioactive compounds, and physicochemical, functional–technological, color, thermal, and morphological properties of the raw pulp (RP), cooked pulp (CP), raw pulp flour (RPF), and cooked pulp flour (CPF) of albino peach palm. The results showed that the hydrothermal treatment (cooking) decreased the contents of lipids, total dietary fiber, and sugars of the albino peach palm pulp, while drying at 55 °C caused the concentration of these nutrients in the flour (except for carbohydrates and sugar). Cooking and drying, in turn, caused the browning of the CP and CPF. The RP turned out to be an excellent source of calcium, magnesium, and phosphorus, contributing to the requirements for human health, even though this latter mineral was decreased by cooking. The contents of phenolic compounds, flavonoids, ascorbic acid, and carotenoids were negatively impacted by cooking. The thermal analysis showed that the cooking and drying processes modified the thermogravimetric profile of the products, while the FTIR showed that there were little changes in the functional groups of the chemical structures of the pulp after cooking, which was more representative in the dry pulp (flour). The morphological aspects proved the existence of fibrous structures, including those linked to starch granules in the albino peach palm pulp, and evidence of the starch gelatinization caused by cooking. The CPF had smaller particle sizes than the RPF, showing that cooking caused the softening of the more resistant structures of the albino peach palm pulp. On the other hand, the RPF had a higher water solubility index, oil absorption capacity, and foam stability, and lower water absorption index than the CPF. The results of this research should encourage studies on the other components of the albino peach palm, as well as the technological and functional application of albino peach palm flour to enrich foods, especially in dietary fibers, calcium, magnesium, and phosphorus. In addition, it is also important to better explore the bioactive potential of extracts from this peach palm variety in biological assays.


Merah Sederhana is a type of red-pigmented rice that is indigenous to Sarawak, Malaysia. This research investigates the nutritional, texture, and sensory properties of gluten-free rice bread produced from a composite of BMS rice flour and potato starch, producing samples referred to as F1 (100:0), F2 (90:10), F3 (80:20), and F4 (70:30). The gluten-free rice bread formulations demonstrated higher ash and crude fibre content and lower carbohydrate content than wheat bread. However, the crude protein content of the bread decreased significantly (p < 0.05) with a decreased amount of rice flour, owing to wheat flour containing greater protein. The crumb of rice bread appeared to be darker due to the red pigment of rice flour; in contrast, the crust was lighter than the control sample, possibly due to a lower Maillard reaction. Among rice bread formulations, F4 demonstrated the lowest hardness in dough and bread, as well as the highest stickiness and springiness in dough and bread, respectively. The wheat bread received the highest rating (p < 0.05) in the sensory test; nonetheless, among the rice breads, F4 was considered to be an acceptable formulation owing to its high score in colour (7.03), flavour (5.73), texture (6.03), and overall acceptability (6.18). BMS has potential in gluten-free rice breads; the formulation of 70% rice flour combined with 30% potato starch was indicated to be acceptable.Current gluten-free food development trends tend to favour pigmented rice flour. Bario  Triticum aestivum L.) flour, which is notable for its viscoelasticity, allowing the bread to create air bubbles and produce a porous structure [Bread is one of the most widely consumed bakery products worldwide. The market for bakery goods is anticipated to increase from USD 416.36 billion in 2021 to USD 590.54 billion in 2028 [tructure . HoweverIn general, gluten-related disorders have been associated with celiac disease (CD), nonceliac gluten sensitivity (NCGS), and an allergy to wheat or grains . Celiac Oryza sativa L.) flour is one of the most commonly utilised flours in commercial gluten-free loaves [In recent years, research into gluten-free bread production has increased significantly . Rice , a red-pigmented rice, as the main ingredient in gluten-free bread. BMS is one of the Bario rice varieties, an indigenous crop in Malaysia. The local ethnic community in the Bario highland of Sarawak cultivates these varieties through traditional techniques and prevents the application of inorganic fertiliser [This study focuses on utilising Bario rtiliser ,25. A rertiliser  reportedrtiliser . Besidesrtiliser . In recertiliser ,30,31, ertiliser ,33.At present, the application of rice flour in gluten-free products is expected. However, the current trend of rice flour use in gluten-free food is more focused on utilising pigmented rice flour rather than nonpigmented rice flour. The reason is that pigmented rice flour has been shown to improve gluten-free food’s nutritional profiles. Hence, this research supports the trend by utilising the red-pigmented rice flour BMS, a locally grown crop from Sarawak, Malaysia, in gluten-free bread. On the other hand, this study encourages the utilisation of locally cultivated crops as ingredients in food products and helps to extend the applications of pigmented rice flour in product development. Therefore, this work aims to provide information on the potential application of BMS supplemented with potato starch in gluten-free bread in the aspect of nutritional profiles, texture properties, and sensory profiles.Solanum tuberosum L.) starch, xanthan gum, soy (Glycine max (L.) Merr.) protein isolate, and bread improver. The rice flour was prepared by drying the rice grains, which were ground to a fine powder for 80 s in a Waring blender . The grinding procedure was repeated until finely ground rice flour could pass through a 250-micron sifter . A laboratory sieve shaker  was used to sift the rice flour. The fine rice flour was sealed in airtight bags and kept at 4 °C until further utilisation.BMS, a primary ingredient, was purchased from Zulkifli Suli Enterprise in Kuching, Sarawak, Malaysia. Castor sugar, salt, low-fat dairy milk, and wheat flour (Cap Sauh) were all acquired from 99 Speedmart in Kota Kinabalu, Sabah, Malaysia. The following ingredients were purchased from Bake With Yen Kolombong, Kian Yap, Lot 126, 127, Lorong Durian 5, Kota Kinabalu, Sabah, Malaysia: shortening, dry yeast, potato  were determined according to the procedure described by Raman et al. . The colTexture profile analysis was performed on both dough and bread products. Parameters analysed on dough samples were hardness, springiness, cohesiveness, and stickiness, whereas bread products were investigated in terms of their hardness, springiness, cohesiveness, and chewiness.DoughTexture analysis of dough regarding hardness, stickiness, springiness, and cohesiveness was determined using a texture profile analyser  as described by Mamat and Hill , with slOn the other hand, stickiness (or adhesiveness) is the work or force necessary to overcome the attraction forces between the product’s surface and the material surface it contacts . The sti2.BreadBread texture analysis was conducted according to the method described by Wu et al. , with apA sensory evaluation test was conducted using the nine-point hedonic scale in the sensory laboratory in the Faculty of Food Science and Nutrition (FSMP). In general, the hedonic test is the most straightforward test in which panellists evaluate a few products to determine the best among them . A totalp < 0.05. The sensory evaluation data were analysed by using the Friedman test, and the Wilcoxon signed-rank test was applied as a multiple comparison test to examine whether there was a statistically significant difference between gluten-free bread formulations made with different ratios of rice flour to potato starch. Statistical significance was determined at p < 0.05.Statistical Packages for the Social Sciences (SPSS) version 26.0 was used to analyse all experimental data in a completely randomised study design. All experimental values were expressed as mean ± standard deviation. In general, one-way analysis of variance (ANOVA) was used for all studies to determine the statistically significant differences in data between experimental units. In addition, Tukey’s HSD test was used for multiple comparisons. Statistical significance was declared at The proximate analysis of wheat bread (control sample) and gluten-free rice bread, measuring moisture, ash, crude protein, crude fat, crude fibre, and carbohydrate content, is shown in p < 0.05) from wheat bread, except for F3. The moisture content of F3 (36.81%) demonstrated no significant difference (p > 0.05) with wheat bread (34.90%). Since F3 contained the lowest moisture content of other rice bread formulations, the possible reason for moisture loss might be due to the result of baking-related evaporation, drying out during the storage period, and the equilibration of moisture between crust and crumb [The moisture content of all bread ranged from 34.90% to 41.22% . Overallnd crumb . Previound crumb  and 31.5nd crumb . Accordind crumb , the pernd crumb , the moip > 0.05) to F4. Overall, gluten-free rice bread possessed greater ash content than control bread. This is due to the rice flour produced from BMS, unpolished rice covered with red-pigmented bran. This was consistent with the findings of prior research, which found that the incorporation of rice bran into bread formulation led to a progressive increase in ash content. [The ash content ranged from 1.16% to 1.70%. The highest was shown by F1 bread with 100% rice flour. The wheat bread exhibited the lowest ash content, 1.16%; nevertheless, it showed no significant difference  crude protein content was wheat bread (11.43%). The crude protein content for gluten-free rice bread (F1 to F4) ranged from 8.10% to 10.50%, which statistically showed significant differences (p < 0.05) from each other. Starch is the most abundant constituent of wheat flour, followed by proteins. An estimated 80% of protein is composed of gluten-forming protein, a complex mixture of gliadins and glutenins [The most significant highest . According to FoodData Central Search Results [Based on  Results , convent Results  reported Results ,66. Varip < 0.05) among formulations. On the other hand, the crude fibre content of gluten-free rice bread demonstrated a gradual downward trend starting from F1 (0.89%), F2 (0.76%), F3 (0.70%), and F4 (0.64%). The percentage usage of rice flour in the formulations affected the downward trend. This is due to the external layer of the rice kernels, which can enhance the crude protein, ash, crude fiber, and crude fat content within baked products [The crude fibre content of all formulations ranged from 0.40% to 0.89%. The wheat bread showed the lowest crude fibre content and was significantly different , F3 0.%, and F4products .p < 0.05) from gluten-free rice bread formulations. On the other hand, the lowest carbohydrate content was observed in F1 (42.18%); this formulation utilises 100% rice flour in the bread. Higher carbohydrate content in wheat bread is due to the lower value in other proximate parameters such as moisture, ash, crude protein, crude fat, and crude fibre. For instance, as shown in p < 0.05) lower than that of gluten-free bread (0.64% to 0.89%). For this reason, the carbohydrate content of wheat bread was the highest among all samples. On the contrary, F1 exhibited the lowest carbohydrate content, because almost all proximate components of F1 were greater than those of other formulations. In addition, the results in The carbohydrate content of wheat and gluten-free rice bread ranges from 42.18% to 48.38%. Wheat bread shows the highest carbohydrate content, with 48.38%, significantly different . The lightness of the bread crumb was more pronounced in wheat bread because it is colourless compared to the BMS, which includes bran that produces darker flour and crumbs within the final product. Another factor that could shift the colour of red rice products is a process known as “colour-deepening”, which involves the creation of intramolecular bonds in proanthocyanidin as a result of oxidation. In most cases, the heating process causes monomeric anthocyanins to break down into chalcones, which then can be degraded further to a brown colour throughout the heating process [p > 0.05) between the L* value of gluten-free rice bread, indicating that the fluctuation amount of BMS did not substantially affect the bread’s lightness. However, a modest increase in F3 and F4′s lightness was still observed. This may have occurred due to the reduction in BMS rice flour while increasing the percentage of potato starch, causing an increase in the bread crumb’s lightness .The L* value of the wheat and gluten-free rice crumb indicated a statistical difference ( process . Meanwhip < 0.05). Overall, gluten-free rice bread showed a high a* value due to the application of rice flour produced from the red-pigmented rice kernels BMS. Based on p < 0.05) from other gluten-free formulations. The reason is that F4 only contains 70% rice flour, which somehow reduces the bread’s redness value (a*).On the other hand, the a* value of the bread’s crumb was more prominent in gluten-free rice formulations. Statistically, wheat and gluten-free rice bread formulation exhibited a significant difference (p < 0.05), which was more yellow compared to the gluten-free bread formulation. This was because wheat grain contains a variety of carotenoids, such as lutein, carotene, zeaxanthin, antheraxanthin, triticoxanthin, and flavoxanthin [p > 0.05) from each other, there was a downtrend in the b* value with a decrease in the amount of rice flour. This is due to the reduction of the yellow hue contributed by the red rice flour.For the b* value, the crumb of wheat bread showed a significant difference (oxanthin . Lutein oxanthin . On the p < 0.05) between the L* value of wheat and gluten-free rice bread. In contrast to the crumb, the lightness of the bread crust was more prominent in gluten-free rice bread. Several past studies have discovered similar outcomes [There was a statistical difference  from each other. In general, the a* value of the bread crust demonstrated a proportional relationship with the percentage of rice flour. This might be due to the red hue being influenced by the pigmentation of the red rice flour; hence, a reduced amount of rice flour would diminish the a* value of the crust. On the other hand, the redness (a*) of the crust of the wheat bread was higher than that of the gluten-free rice bread, even though it was produced from red rice flour. Gülcan et al. [The a* value of the bread crust was more noticeable in the wheat bread. All gluten-free rice breads showed no significant difference  compared to the gluten-free bread formulation. This indicates that the crust of wheat bread possessed a greater yellow hue. The high b* value of wheat bread crust indicated a yellower crust, which also resulted from the Maillard browning reaction of reducing sugar and protein in wheat flour [The b* value of the wheat bread crust was significantly higher , springiness, cohesiveness, and stickiness. The gluten-free rice bread was analysed for its hardness (g), springiness, cohesiveness, and chewiness. The result is presented in p < 0.05) between each sample. Similarly, the highest bread hardness value was indicated by F1 (2846.52 g) and the lowest was by the control (849.13 g). Generally, there was an increase in hardness corresponding to a decrease in rice flour and increase in potato starch. Alam et al. [Hardness is measured by the amount of force needed to change the shape of a material. Based on d by F1 26.52 g anm et al. ,85. Potam et al. , subsequm et al. . As can p > 0.05) between the springiness value of gluten-free rice bread, there was a notable increase in springiness with a decrease in rice flour. Likewise, the bread springiness value was significantly greater (p < 0.05) in wheat bread, 1.01. The springiness value of bread is directly related to its elasticity . Based op < 0.05) cohesive compared to gluten-free dough due to the presence of gluten protein, which promotes the cohesiveness and elasticity of wheat dough [p < 0.05) and highest cohesiveness was shown by wheat bread (0.78), and there were no significant differences (p > 0.05) between F1 (0.31), F2(0.35), F3 (0.31), and F4 (0.33); this indicates that gluten-free rice bread was more susceptible to rupture than wheat bread.Wheat dough is significantly  in the wheat dough (40.12) due to the presence of gluten protein that promoted the elasticity and adhesive properties within the dough. The dough made from 100% rice flour exhibited the lowest stickiness value (12.70), while the highest stickiness was shown in F4 (17.45). The results indicated an inversely proportional relationship between the percentage of rice flour and the stickiness of the dough. Gluten-free rice dough made from 100% rice flour showed the lowest stickiness value. It is highly likely that the stickiness value was influenced by the usage of potato starch. In general, potato starch has a higher water absorption capacity due to its great swelling power [The stickiness of the dough was significantly higher  value, of 669.10, among all samples. On the other hand, no significant differences (p > 0.05) were shown among the gluten-free rice bread samples. The chewiness value generally indicated a positive correlation to the percentage of rice flour, which the chewiness of the bread enhances with the increment of the amount of rice flour. On the contrary, the chewiness value of gluten-free rice bread decreased with an increased amount of potato starch. Several previous studies found that the addition of starch to the dough can reduce bread’s chewiness. [Chewiness is measured as the time needed to chew a sample at a consistent rate of force before it acquires the optimum consistency for swallowing . The cheewiness. ,97. On tewiness.  reportedA hedonic test was carried out to determine the acceptability of each sample. This study implemented a nine-level hedonic test scale to obtain the best formulation for baking gluten-free bread made from BMS rice flour. All formulations were assessed based on colour, flavour, aroma, texture, and overall acceptability. A total of 40 semi-trained panellists comprising undergraduate students (second year and above), postgraduate students, and staff, generally aged between 21 and 37 years old, were involved in this test. The outcome of the sensory evaluation is recorded in Based on the scores presented in p-value more than 0.05 (p > 0.05) against the control. The score of F4, 5.73, is associated with “neither like nor dislike” and “like slightly”. Nonetheless, F1, F2, and F3 generally scored lower, ranging between 5.20 and 5.38, conveying a meaning of “neither like nor dislike”. Based on the result obtained, gluten-free breads containing 80% rice flour or more were less preferred by the panellists. The reason is that higher rice flour concentrations might sharpen the final product’s flavour. Filipini et al. [Regarding its flavour, wheat bread received the highest score (6.88), a result between “like slightly” and “like moderately”. F4 was the second-highest (5.73) for flavour, after the control, and significantly differed, with a i et al.  revealedp < 0.05). In addition, the lowest score among all was received by F3 (5.65), equivalent to “neither like nor dislike” and “like slightly”. Gluten-free rice bread, in comparison to wheat bread, has a more pronounced yeast aroma [The highest rate was acquired by wheat bread with a score of 6.68, corresponding to “like slightly” and “like moderately”. Interestingly, F2 was rated as the second-highest formulation, with a score of 6.08, conveying “like slightly”. However, both were significantly different (st aroma . This map < 0.05) score (6.80), conveying to a response of “like slightly” and “like moderately”. F4 received the second-highest rating, with 6.03, corresponding to “like slightly”, and the lowest score was obtained by F2, with a score of 4.83. The majority of panellists rated F2 between “dislike slightly” and “neither like nor dislike”. These results align with the outcome of the texture profile analyser (TPA) for bread in Based on the results shown in Most panellists are not consumers of gluten-free bread, and only 5% of the panellists had experienced the consumption of gluten-free bread. Hence, it is undeniable that the highest rating was obtained by the control sample (wheat bread). However, F4 received the highest scores for colour, flavour, texture, and overall acceptability among gluten-free rice breads. Therefore, for the panellists, overall, F4 was the most consumer-acceptable formulation of gluten-free rice bread.The potential application of Bario rice flour in gluten-free rice bread was demonstrated. BMS flour is generally capable to improve the nutritional profiles of gluten-free rice bread. The increase in the ash content showed that the compositions related to ash constituents, such as vitamins and minerals, were improved by the utilisation of BMS flour. Moreover, BMS flour increased the crude fibre and lowered the carbohydrate content compared to that of wheat bread. Based on the final products, the crumb colour of wheat bread was lighter than gluten-free rice bread; this is due to red rice flour including a bran layer which, unfortunately, darkens the bread’s crumb. In contrast, the crust of gluten-free bread was lighter than wheat bread due to the low Maillard reaction. Among all gluten-free rice formulations, the F4 dough showed the least hardness and highest stickiness and cohesiveness. This was due to the addition of 30% potato starch, which increased the hydration capacity of the rice dough. The lowest hardness and the increased stickiness in the F4 dough produced the least hardness and high springiness in the final F4 bread. This may demonstrate that low dough hardness and increased stickiness can produce bread with low hardness as well as good springiness. Wheat bread exhibited outstanding texture characteristics compared to gluten-free bread. It was expected that the highest rating would be received by wheat bread. F4 was determined to be the most acceptable formulation among gluten-free breads owing to its colour, flavour, texture, and overall acceptability. To summarise, the application of BMS has potential in gluten-free bread; especially the formulation of 70% rice flour mixed with 30% potato starch. However, several improvements can be implemented in future studies, especially to improve the texture of gluten-free rice bread, making it more comparable with wheat bread. In addition, choosing panellists that were not familiar with gluten-free bread may have increased the panellists’ preference for the control sample.


Grammar is a key input in grammar-based genetic programming. Grammar design not only influences performance, but also program size. However, grammar design and the choice of productions often require expert input as no automatic approach exists. This research work discusses our approach to automatically reduce a bloated grammar. By utilizing a simple Production Ranking mechanism, we identify productions which are less useful and dynamically prune those to channel evolutionary search towards better  solutions. Our objective in this work was program size reduction without compromising generalization performance. We tested our approach on 13 standard symbolic regression datasets with Grammatical Evolution. Using a grammar embodying a well-defined function set as a baseline, we compare effective genome length and test performance with our approach. Dynamic grammar pruning achieved significantly better genome lengths for all datasets, while significantly improving generalization performance on three datasets, although it worsened in five datasets. When we utilized linear scaling during the production ranking stages (the first 20 generations) the results dramatically improved. Not only were the programs smaller in all datasets, but generalization scores were also significantly better than the baseline in 6 out of 13 datasets, and comparable in the rest. When the baseline was also linearly scaled as well, the program size was still smaller with the Production Ranking approach, while generalization scores dropped in only three datasets without any significant compromise in the rest. Grammatical Evolution (GE) is a grammar-based Genetic Programming (GP) approach which has found wide acceptance in the research communities , 2. It iGrammar is a key input to grammatical evolution and it has been known that the performance of GE is significantly influenced by the design and structure of the grammar . Howeverextended grammar. It has been reported in earlier efforts , interval between two successive pruning stages in the set , and the acceptable performance drop in the population in the set . The parameter values least affecting the generalization performance were chosen, and are shown in Table We ran all experiments on the libGE system,mixed-arity grammar structure was found to be producing minimum effective genome lengths, we utilize the same structure in this work. In terms of the function set embodied in the grammar, we defined extended version of the grammar and a baseline grammar to compare it with.Since this work is an extension of the work presented in  where thNicolau and Agapitos  defined In the above grammar, the <expr> rule is the start rule. The <var> rule carries as many alternative terminal productions as there is the number of input features in a given dataset. The <arith-op> rule models arithmetic operators. Note that in <arith-op>, we model the division operator as an unprotected division (UPD). Although in GP literature, the use of protected division is common, it has been found to be problematic due to the presence of asymptote  Keijzer  proposed Keijzer . Ni et a Keijzer  proposedAgapitos , which iextended function set which contained all mathematical functions commonly used in symbolic regression. It included arithmetic operators, trigonometric functions, exponential, and power functions. Besides commonly used functions and operators, we also included some divergent exponential functions such as extended grammar abbreviated as grE in this work. The grammar is similar to the baseline grammar defined in  “In our earlier work , 8, we dx) and exponential function , which is a non-parametric test, with the null hypothesis that, for the randomly drawn samples X and Y from two independent populations, the probability of X being greater than Y is equal to the probability of Y being greater than X. Since the assumption of normality and dependence, as required by parametric tests, does not hold in general in experimental results of evolutionary computing approaches, non-parametric tests are the right choice [p-value is below 0.05, we conclude, with 95% confidence, that the compared samples are drawn from different distributions.We performed tests of statistical significance to compare the output using baseline, extended and pruned grammar. All comparisons were made with respect to the chosen baseline. We used the Mann–Whitney t choice . All resbetter than the baseline, while in the case of a grey-filled cell, the results are statistically worse.In Tables Table Our earlier research has revealed the positive impact of grammar pruning on program size reduction , 8. In tAs evident from Tables ch works . At the ividuals . To veriWe applied dynamic grammar pruning in both sets of experiments on all datasets. In the first set of experiments, when comparing the results of dynamic pruning (column grP) with the baseline , cos(<expr>), log(abs(<expr>)), and tanh(<expr>), which are generally expected to be useful productions and commonly used in GE for symbolic regression. A similar pattern was exhibited in the case of cooling, tower, and dowchem. It turned out, for these datasets, there was not enough variation in the population, when evolving for just five generations, to better exploit potentially useful productions. Increasing the number of ranking generations before pruning did not help maintain generalization performance since it reduced the number of post-pruning generations.expression whose shape is most similar to that of the target function” [We encountered a similar problem in our earlier work  when we unction” . We hypoAt the end of the first set of experiments, we trialled LS-enabled grammar pruning, i.e. LS enabled only during ranking and pruning (first 20 generations). This dramatically improved results. Not only was the effective genome length in all datasets significantly better, test performance significantly improved for six datasets, while it was comparable in the other seven datasetsAnother important observation in LS-enabled pruning trials was that the fitness and test performance achieved in the first 20 generations could rarely be surpassed by regular evolution in the later 80 generations.Apart from the results and discussion above, it is important to present an analysis of which productions were pruned and how much computational overheads were incurred in the process. Below, we outline those details.The grammar pruning strategy utilized in this research is dynamic pruning , and 115.9 in the case of regular pruning;There is a clear contrast between frequently pruned productions when pruning with and without LS. The top four heavily pruned productions in case of regular pruning are: sin(<expr>), cos(<expr>), (1/<expr>), log(abs(<expr>)). The top four productions pruned in case of LS-enabled pruning are: pow, exp(<expr>), cos(<expr>), pow.There are a couple of questions which demand a more detailed examination: Are there any patterns in the choice, order, and rank of pruned productions which negatively affect generalization performance? With the current ranking scheme, how can we improve the pruning suggestion mechanism? How does static pruning compare with dynamic pruning? Studies are being planned to investigate and answer these questions.Both production ranking and grammar pruning introduce some overhead in computation. These overheads include both time and space complexity costs. Below, we present an analysis of costs in terms of execution times. Memory overhead analysis is one of the future tasks in our research. However, we did put considerable effort into our implementation to reduce spatial complexity and reclaim additional memory allocations once the ranking and pruning iterations were over.p-value of 0.00188. Therefore, we conclude that our approach carries not only negligible overheads but also provides significant gains in execution times.Before we delve into a more detailed discussion about the cost of ranking, pruning and linear scaling, we present an overall comparison. The bar plot shown in Fig. In our system, production ranking is implemented as a plugin feature. Once enabled, ranking starts accumulating production ranks  during ranking computations.A single data structure (2-D array) keeps track of the data  to generate an improved ranking profile. When comparing LS-enabled dynamic pruning with linearly scaled baseline, the program size outcomes persisted. At the same time, the generalization scores dropped in only three datasets without any significant compromise in the rest of the 10 datasets. These results led us to conclude that dynamic grammar pruning is a promising approach which can not only be applied for program size reduction but primitive set identification as well.The current work can be extended with both function and feature selection in a parallel pruning fashion to exercise high-dimensional problems. Although we have used a few relatively high-dimensional regression datasets, we intend to exercise much higher levels of dimensionality (500+ features).Besides, classification problems can be exercised with the grammar pruning approach. For high-dimensional classification problems, we can utilise our grammar-based feature selection approach . On the Recommend function in dynamic pruning. The current production ranking mechanism is efficient but fairly simple and unintelligent. Utilizing an ML approach to better predict which production to prune will be an interesting study;We want to improve Another improvement to the production ranking scheme can be to employ more opportunistic production ranks to assess marginal contributions of each production in the solution using approaches such as variants of Shapely-Value , withoutIt would be interesting to explore how DynPRP would perform with other variants of GE or grammar-based GP approaches.We also intend to explore other problem domains, for instance program synthesis and Boolean logic.There are several possible extensions to our work; a few are already in process, while others are being planned. Some of the ideas are mentioned below: