Concrete is one of the most widespread materials in the civil engineering field due to its versatility for both structural and non-structural applications depending on the density range, competitiveness in terms of durability and manufacturing costs, as well as ease in finding raw constituent elements. For this reason, the mechanical behavior of concrete and, even more, reinforced concrete (RC) has been a research theme tackled by many researchers through different approaches for years. Although the relevant literature is full of papers on this topic, ranging from experimental works to theoretical contributions, an accurate and comprehensive description of the actual mechanical behavior exhibited by concrete and reinforced concrete at service and ultimate conditions still remains a challenge in the field of structural engineering. This is due to several intricate and interconnected phenomena involved, such as tensile cracking, compression crushing, strain softening, interaction between aggregates and matrix, interaction between concrete and reinforcement, stiffness degradation, energy dissipation, and ductility exhibited under cycling loading.Following these research motivations, this Special Issue collects 15 papers focused on the mechanical behavior of concrete materials and structures, including both experimental findings and numerical analyses using both conventional and advanced methodologies. In the Editors’ opinion, each article contains clear scientific novelty from various standpoints , thus representing a major contribution to the understanding of the mechanical behavior of concrete materials and structures. The Editors hope that this article collection can somehow contribute, even if modestly, to the continuous research for a more thorough and reliable understanding of the mechanical behavior of ordinary and prestressed concretes, as well as special concretes, including high-strength, recycled, and fiber-reinforced concretes, for both structural and non-structural applications, and for the development of related numerical/analytical predictive models.Among the experimental contributions, Ni et al.  presenteThree contributions were focused on recycled concretes, from either an experimental or numerical perspective. Garbaya et al.  incorporThe mechanical behavior of concrete was analyzed not only under static loading. The dynamic characteristics of concrete were experimentally investigated by Sun et al.  through Another aspect playing a key role in structural serviceability analyses of RC structures is the concrete shrinkage. Dey et al.  presenteThe influence of multi-walled and single-walled carbon nanotubes (CNTs) on the carbonation, compressive and flexural strength, electrical resistance, and porosity of special mortars was experimentally analyzed by Lee et al. . Based oAn increasing number of researchers have recently advanced the use of machine learning methodologies for predicting the mechanical characteristics of concrete based on training sets of data. For estimating the compressive strength of ultra-high-strength concrete (UHSC), Shen et al.  used sofBernardo et al.  addresseThe deflection behavior of horizontal structural members was the object of the investigation of D’Antino and Pisani . The recOne of the most complex phenomena to simulate in concrete structures is fracture behavior, due to the heterogeneous microstructure and interaction between aggregates and matrix. In this context, Tawfik et al.  employedIt is well known that durability of existing concrete structures was not always regarded as a crucial performance requirement in the past, and periodical maintenance plans have not been performed over the years. As a consequence, many damage phenomena have been recently observed in existing concrete structures dated from around 50 years ago; in some extreme cases, these damage mechanisms have led to complete structural collapse, as recently observed for bridges. One of the most serious factors negatively affecting the durability of concrete structures is the corrosion of steel reinforcement. In this context, De Domenico et al.  developeFinally, the review paper by Dong et al.  illustra


A 66-year-old North-East Indian male presented with bilateral eyelid swelling, ptosis, and bilateral submandibular gland enlargement. Dry skin on both arms was another peculiar complaint. Contrast enhanced CT scans revealed homogenously enhancing, diffusely enlarged lacrimal glands and blood investigations showed raised serum IgG4 levels. Histopathology from lacrimal gland biopsy showed lymphoplasmacytic infiltrates in storiform pattern. Immunohistochemistry showed 35% plasma cells positive for IgG4. A diagnosis of IgG4-related disease was made, due to supportive histopathology, immunohistochemistry, and serum IgG4 levels. The patient showed excellent response to systemic immunomodulators.Abbreviations: IgG4-RD = IgG4-related disease, CECT = Contrast-enhanced computed tomography, ACE = Angiotensin converting enzyme, IHC = Immunohistochemistry, HPF = high power field, IgG4-ROD = IgG4-related ophthalmic disease, ACR/ EULAR = American College of Rheumatology/ European League Against Rheumatism  Ophthalmic presentations of IgG4-RD in various forms of orbital and adnexal inflammation have been described in literature [2]. A unique case of intraocular inflammation in IgG4-RD, which presented as a masquerade of ciliary body melanoma has previously been reported from North-East India [3].IgG4-related disease (IgG4-RD) is a multi-system inflammatory disorder that has gained acknowledgement in recent years and is characterized by high serum IgG4 levels along with plasma cells positive for IgG4 on histopathology . IgG4-RD with systemic involvement occurs mostly in middle to old age (median age: 58 to 67 years), while a slightly younger average age (56.7 years) has been noted in men with IgG4-ROD [1].IgG4-RD was described for the first time nearly two decades ago and since then has been known to cause fibroinflammatory mass lesions in almost any body organ [6]. The enlargement of these glands has been described to be painless and progressive with elastic consistency, similar to what was seen in our case. In IgG4-RD involving head and neck, submandibular gland enlargement is more commonly noted, in contrast to predominant parotid enlargement in Sjogren’s syndrome [6].Involvement of submandibular and lacrimal glands is common in the head and neck region [7]. A multi-disciplinary team of specialists has laid down 3-step criteria, the first step being the demonstration of a possible IgG4-RD involvement in one of the possible 11 organs, the second step being the screening through 32 exclusion criteria and the third step involving 8 weighted domains that have the inclusion criteria. Lastly, a sum of all inclusion criteria points was done. The validation cohort of this study showed that a score of 20 carried 99.2% specificity for IgG4-RD diagnosis. In our case, the total of the inclusion criteria points came out to be 29. The American College of Rheumatology/ European League Against Rheumatism (ACR/ EULAR) committee has recently proposed new criteria for classification of IgG4-RD . Immunomodulators can be used in conjunction with a tapering dose of steroids or as steroid-sparing agents.Response to systemic steroids in IgG4-RD is high initially but it has been suggested that only a limited time period exists for efficiency [8-10]. IgG4-RD may rarely convert into a low-grade lymphoma; thus, these patients require a close follow-up and monitoring.Previous literature has shown that IgG4-ROD is a close mimicker of malignancy, particularly lymphoma [IgG4-related disease can present with swelling of glands of the head and neck. Diagnosis requires a high degree of clinical suspicion. Clinicians must be aware of this clinical entity and its various presentations, to diagnose it early and tackle it effectively.Conflict of Interest StatementThe authors state no conflict of interest. Informed Consent and Human and Animal Rights statementAny information that could contribute to identify the patients, including the patients’ names, initials or hospital numbers have not been published in written descriptions or photographs. The manuscript was shown to the patient before submission to the journal and an explicit informed consent was obtained for the purpose of publication. Authorization for the use of human subjectsEthical approval: The research related to human use complies with all the relevant national regulations, institutional policies, it is in accordance with the tenets of the Helsinki Declaration and has been approved by the review board of Department of Ocular Pathology and Department of Oculoplasty and Oncology, Sri Sankaradeva Nethralaya, India. AcknowledgementNone. Sources of FundingNil. DisclosuresNone. Commercial relationshipsNil.Competing interestsNone.


The Yellow River is difficult to control. Little water and a large amount of sediment results in sediment accumulation in its lower reaches as sediment inflow exceeds transport capacity. Reducing this sediment deposition is essential for harnessing the Yellow River. Included in this process is the rational use of the sediment. Many researchers have investigated usage of Yellow River sediment as an aggregate material for concrete production, but there are still some problems . To make up the deficiency in the existing research, this study proposes two methods of sediment utilization. One is to use Yellow River sediment to build embankments, and the other is to use ultra-fine Yellow River sand to prepare ultra-high-performance concrete (UHPC). Test results reveal that the prepared high-strength concrete performs well in each test, including: fluidity, mechanical properties, pore structure, ecological evaluation, microscopic measurement of the interface transition zone, and economic analysis. The Yellow River is one of the most difficult rivers to harness worldwide, as it is characterized by complicated hydrological and sediment conditions . Since tThus, this study proposes two sediment resource utilization methods to address the current shortcomings: using the deposited sediment in the reservoir area to construct an embankment to improve the storage capacity, and using the ultra-fine sand of the Yellow River to prepare ultra-high-performance concrete (UHPC). The particle size of ultra-fine Yellow River sand in the Zhengzhou section is similar to that of small quartz sand (0.18~0.6 mm), and the particle size of cement (<0.075 mm) is similar to that of Yellow River silt in the Puyang section. Therefore, it is feasible to use mixed sand composed of Yellow River ultrafine sand (0~0.6 mm) and river sand instead of quartz sand as the fine aggregate in high-performance concrete, and to use Yellow River silt (0~0.072 mm) instead of cement to prepare high-performance concrete. This provides a new source for concrete building materials and allows resource utilization of the sediment of the Yellow River, which will bring good economic and ecological benefits to the lower reaches of the Yellow River.From flood diversion, desilting, mechanical desilting, and embankment consolidation since the last century, to sediment brickmaking and soil improvement over the past few years, decades of exploration has resulted in great progress in the utilization technology of sediment in the Yellow River. Sediment used for land rectification can be divided into flood diversion and desilting, and sediment filling of collapsed mining areas ,5. To be(1)Flood diversion and desilting: The silted Yellow River sediment is adopted to fill dike ditches and cascade ditches on the beach surface to improve the impermeability of the dike and to prevent the river from rushing directly into the dike along the cascade ditch. Based on silting treatment, the probability of flood discharge along the embankment and the occurrence of cross river, oblique river, and rolling river decreases, thus ensuring flood-control safety of the Yellow River embankment to a certain extent. First, the sediment of the Yellow River can consume the sediment deposited by the Yellow River. Further, the construction of village platforms and centralized resettlement can save considerable land resources and improve the carrying capacity of land resources for economic and social development.(2)Sediment filling of collapsed mining areas: There are a considerable number of coal mines in the Yellow River Basin . Out of (3)Farmland improvement: Using the sediment of the Yellow River to improve farmland  can signSediment use in the construction industry includes making bricks and ceramsite ,12,13.(1)Sand brickmaking. With China’s increasing attention to the ecological environment, sources of building materials that have an impact on the environment, such as mountain quarries, are limited, and Yellow River sediment brickmaking and flood control stone materials have progressively aroused the attention of society. Boxing County  of ShandWhile meeting national environmental protection requirements, sediment brick also shows several advantages, including fire resistance, weight reduction, earthquake resistance, shear resistance, and energy savings. Preparation of flood-control stones from the sediment of the Yellow River can alleviate the flood-control pressure in its lower reaches while satisfying economic development needs along the river and facilitating the development and progress of sediment resource utilization technology and equipment.(2)Sand ceramsite: Yellow River sediment can be excavated, naturally dried, pelletized, preheated, roasted, and cooled into ceramsite. As a result, sediment resource utilization has been achieved. Using the sediment of the Yellow River to replace clay to make pottery  reduces In order to alleviate the shortage of medium-coarse sand , Yellow Test results show that the mechanical properties of the samples are related to the curing conditions . The mecThe concrete mix proportions of different strength grades are obtained through testing . Ultra-fIn order to study the influence of different contents of Yellow River sand on different grades of concrete , concretBy changing the ratio of superfine Yellow River sand to river sand , as wellTaking Yellow River sediment as a raw material, flood control stone is prepared by alkali activation , and theRegarding sediment control in the Yellow River, the above sediment resource utilization scheme has studied sediment utilization of the Yellow River from different perspectives and has achieved certain results . However, there have also been the following deficiencies: (1) After decades of sediment resource utilization, it has played a certain role in reducing river sedimentation. At present, however, the exploited sediment only accounts for a small part of the deposited sediment, and the sediment utilization rate is small. (2) Although different researchers have tried to optimize temperature, pressure, and dosage to for Yellow River sand concrete, the strength of the concrete is generally not high.Thus, to solve the first shortcoming, this study proposes sediment-based embankment building on the Yellow River, which transports the sediment from the bottom of the reservoir to the water’s surface and uses the transported sediment to build the embankment; this will consume considerable sediment and improve the sediment utilization rate. In view of the second deficiency, we propose preparing high-strength concrete to solve the low strength of Yellow River sand concrete.Sediment-based embankment building is the transportation of sediment from low to high. The target is the considerable amount of sediment deposited in the Sanmenxia Reservoir area. The cleared sediment is treated on-site and built into a dike at the elevation line of 330 m on both banks of the reservoir area.In 1960, Sanmenxia Reservoir ,23,24,253/S in the flood season; otherwise, it is limited to 305 m.The period since November 1973 has consisted of storing clear water and discharging muddy water. In the non-flood season, the highest operating water level of the reservoir has decreased yearly, and the duration of the high water level has also decreased yearly. From 1974 to 1979, the reservoir water level was higher than 322 m an average of 74 days annually. From 1979 to 1985, the reservoir water level exceeded 322 m for an average of 57 days. From 1986 to 1992, the reservoir water level reached over 322 m an average of 39 days annually. From 1993 to 2001, the reservoir water level exceeded 322 m for an average of 3 days. In 2003, “318” was put into operation , and theAs revealed by the above data, the historical pool level of the Sanmenxia Reservoir area is more than 330 m part of the time and more than 322 m for a large proportion of time. Accordingly, it is feasible to build an embankment on the 330 m elevation line on both banks to restore the water level in the reservoir area to 330 m.An elevation line of 330 m is drawn from Tongguan to the dam in the reservoir area , the sedUnder the restraint that the living conditions of residents remain unchanged, we take the bottom of the embankment as a horizontal line and extend it 10–20 m to the outside Sediment extraction cost: The total cost of sand excavation consists of sand dredger rental, power, labor, and oil. Dredger rental would cost from 80 million yuan to 120 million yuan, which is equivalent to the purchase price. The salary of the personnel over the total building period would be nearly 60–70 million yuan plus other expenses . The sediment extraction cost would be about 200–300 million yuan.(2)Building of embankment and relocation cost: The cost of dump trucks and excavators would be about 160 million yuan. Oil, electricity, and other related expenses are expected to cost between 20–30 million yuan. The total transportation cost ranges from 200 to 300 million yuan. The cost of concrete would be approximately 80–90 million yuan. The labor cost and the excavator cost would reach nearly 130 million yuan. Compensation for resident relocation is based on a population of approximately 50 thousand people in the Sanmenxia Reservoir area, and the cost would range from 4 to 4.5 billion yuan.(1)Dredging: Building sediment revetments significantly reduces the amount of sediment deposition in the reservoir area, enhances the water storage performance of the reservoir, and utilizes rather than wastes the cleared sediment.(2)Swan protection: Swans are second-class protected animals. Tens of thousands of white swans migrate from Siberia to Sanmenxia for winter every October. The construction of Swan Lake wetland community will provide tens of thousands of mu of habitat for swans.(3)After the water surface in the Sanmenxia Reservoir is raised, alkali pressing can be achieved, and farming conditions, soil fertility and quality, and crop yield can be improved, increasing agricultural income.Sediment-based embankment building achieves on-site utilization of sediment while bringing the following benefits:The materials selected for the preparation of ultra-high-performance concrete (UHPC) consist of ordinary Portland cement, green high-performance polycarboxylic acid superplasticizer , first-class fly ash, silica fume, and fine aggregates, which consist of large-size river sand (0.6~1.18 mm), quartz sand (0.18~1 mm), and ultra-fine Yellow River sand (0~0.6 mm). High-strength concrete benefits from its dense skeleton stacking structure. A dense internal structure gives mechanical properties and pore microstructure density several times that of ordinary concrete . Thus, tBased on the modified A&A model, the mix proportion of concrete can be designed. The proportion of various materials in concrete is of great significance, as it determines the density of the stacking structure of the prepared concrete. Because our research is on ultra-high-performance and high-strength concretes, only fine aggregate is used. The content of fine aggregate is dependent on the distribution modulus, which is fixed at 0.23 in this study. Next, the mass proportion of various materials in the concrete mortar is regulated using the least-square method (LSM) as seen in Equation (2). .2 (Equation (3)). . R2 provides a correlation value between all the fitted particle size curves and the particle size curve of the target mixture.The fitting quality of the obtained complete particle-size distribution curve is determined and assessed by the coefficient RThe particle sizes of the quartz sand used in this test are 0.18~0.6 mm and 0.6~1 mm, while the highest particle size of the ultra-fine Yellow River sand is 0.6 mm. AccordiFirst, all the required materials—P · O 52.5 cement , silica fume, fly ash, natural river sand, and other materials—are introduced into a mixing pot and then mixed at 140 + 5 r/min for 2 min. Then 70% of the water and all of the polycarboxylate superplasticizer are added, and mixing continues at 140 + 5 r/min for 2 min. Finally, the remaining water is added to mixing pot, and mixing continues at 280 + 10 r/min for 2 min to obtain the mixture slurry. Then, the slurry is poured into a mold and cures for 24 h at ambient temperature. The sample is then demolded and transferred to a standard curing box for the corresponding curing period. The curing conditions of the curing box are: temperature 20 ± 1 °C and humidity 95%.The GBT2419-2005 standard is used to test the fluidity of concrete mixtures. The instrument used is an NLD-3 cement mortar fluidity tester. The specific test method is as follows: put the mixed mortar into the test mold twice, and tamp it with a tamping rod. After tamping, scrape the excess (the part higher than the test mold) with a knife, start the jumping table, jump 25 times, then lift the cone test mold vertically, and the mixture flows freely. Measure the two mutually perpendicular diameters and calculate their average value (unit: mm), which is the fluidity of the mixture .When the mixture of river sand and ultra-fine sand of the Yellow River is employed to replace quartz sand at substitution rates of 20%, 40%, 60%, 80%, and 100%, the fluidity is reduced by 0%, 3%, 6%, 12%, and 17%, respectively. This trend is also identified in the V-shaped funnel test. Increased mixed sand content progressively prolongs the time taken to pass through a V-shaped funnel. Replacement rates of 20%, 40%, 60%, 80%, and 100% prolongs the time to pass through a V-shaped funnel by 0.04 s, 0.55 s, 1.26 s, 6.72 s, and 7.20 s, respectively.Nevertheless, even when the replacement rate is 100%, the mixing flow mobility is still 248.5 mm , meetingThe compressive and flexural strength of the sample is determined in accordance with the standard cement mortar strength test (ISO method) (GB/T 17671-2020), and the instrument used is the fully automatic flexural and compressive testing machine TYA-300B. The specific operations are as follows: first wipe the moisture from the surface of the test block. Then, put the flat side of the test block upward into the bending test machine and start the machine. The loading speed of the bending test is 50 N/s ± 10 N/s until the test block breaks. Average the bending strength results of three samples from each group. The test block for compressive strength is the fractured test block after the bending test. The specific test steps are as follows: put the flat side of the test block upward into the fixture for the compression test. Before the test, ensure that there are no impurities or sand particles on the compression surface or the bottom surface of the fixture, and then start the machine. The loading speed of the compression test is 2400 N/s ± 200 N/s until the test block is crushed. The results are the average compressive strength of six blocks from each group .The trend of flexural strength is similar to that of compressive strength, where the strength increases significantly with the increase in the curing period. When the replacement rates of mixed sand reach 20, 40, 60, 80, and 100%, after 7 days of curing, the flexural strengths are 10.80, 8.67, 8.60, 8.13, 6.83, and 5.83 MPa, respectively. Curing for 28 days enhances flexural strength by 43.5, 73.0, 96.5, 104.2, 121.1, and 117.8%, respectively. This shows that increasing the curing period significantly improves flexural strength. When the replacement rates of mixed sand reach 20, 40, 60, 80, and 100%, the flexural strength at 28 days of curing is 15.5, 15.0, 16.9, 16.6, 15.1, and 12.7 MPa, respectively. Further, the flexural strength does not exhibit a strong regularity, as the general strength is greater than 12 MPa, and the average flexural strength is 15.3 MPa. Notably, with the increase in the replacement rate of mixed sand, the compressive strength and flexural strength do not tend to decrease significantly. The reason for this is that the particle size of Yellow River sand is smaller than that of quartz sand, thus making it more conducive to filling the pores between particles and forming a dense skeleton structure in the concrete.The scanning electron microscope used in this test is an emission scanning electron microscope (SU8020) produced by Hitachi company in Tokyo, Japan. Before the test, we put the test block in a vacuum coater and spray a gold film using sputtering to ensure good conductivity .The interface transition zone is the connection between aggregate and slurry in concrete and is the weakest part of the internal structure. Detailed observation and analysis of the interface transition zone can reveal the overall strength of the sample. The mixed sand comprises 0~0.6 mm ultra-fine Yellow River sand and 0.6~1.18 mm river sand, so the sizes of the aggregates are different. However, in the interface transition zone, the aggregate and slurry are closely connected, and no cracks or pores are found, indicating that the addition of mixed sand will not weaken the interface transition zone of the sample. This again proves that the addition of mixed sand does not seriously reduce compressive strength.Pore structure is tested using a micro mercury porosimeter  produced in the produced in Norcross, GA, USA. The specific operation steps are as follows: first, immerse the sample to be tested in isopropanol for 7 d, terminate hydration, vacuum dry for 48 h, and then test.At 7 days, the cumulative void ratio of all samples mixed with a variety of sands is higher than that of samples without mixed sand. This is due to the relatively small particle size of the ultra-fine sand of the Yellow River, which leads to relatively low fineness and high specific surface area. Thus, it absorbs more free water in the early hydration process ,33, resuThe pore development of samples cured for 7 days and 28 days is compared. The results suggests that with the increase in the curing period, the proportion of cumulative pores is smaller  and the 3 as revealed by the ecological evaluation of the primary energy consumed by UHPC, as presented in We carried out a lifecycle ecological evaluation of Yellow River ultra-fine sand UHPC using primary energy consumption in accordance with the EN ISO 14040 standard. The ultra-fine sand of the Yellow River is natural ultra-fine sand that meets the requirements for ultra-high-performance concrete fine aggregate, while quartz sand needs to be crushed and processed, which not only wastes energy but can easily create polluting dust in the crushing process. We use production technology 1 mThe economic analysis of this test uses the normalized cost index (NCI)—that is, the cost of raw materials per cubic meter of concrete. The cost declines to a certain extent with the use of mixed sand instead of quartz sand to prepare ultra-high-performance concrete. The standardized cost indexes of different replacement rates of quartz sand are determined by the algorithm of the normalized cost index. During the economic analysis, the concrete strength is also comparatively analyzed, as presented in Mixing superfine Yellow River sand and river sand has a negative impact on the flow performance of high-performance concrete. When the substitution rate is 20~100%, the fluidity of the corresponding mixture decreases by 0~17% and the time for the mixture to pass through a V-shaped funnel is 0.04 s~7.20 s longer than for the control group. This is because the ultra-fine sand of the Yellow River is relatively fine and has a larger specific surface area than quartz sand. These fine particles more easily absorb the water in the slurry, resulting in thickening of the slurry and decreased fluidity. However, even when the replacement rate is as high as 100%, the mixture still has high fluidity (248.5 mm).Replacing quartz sand with mixed sand as aggregate does not have a serious negative impact on the compressive strength of the sample. This conclusion is also supported by the microstructure of the interface transition zone. When the replacement rate of mixed sand increases from 20, 40, 60, 80, or 100%, the compressive strength after 28 days of curing is 100.3, 96.7, 95.9, 93.5, 104.3, and 95.6 MPa, respectively, which has no obvious regularity, but the average compressive strength is 97.2 MPa. This is because the particle size distribution of mixed sand is uniform and continuous, and the ultra-fine Yellow River sand is smaller than quartz sand, which is more conducive to filling the pores between aggregates. At the same time, thanks to the modified Andreasen and Andersen model, the internal particles are densely stacked and the structural framework is dense.The addition of mixed sand increases the early shrinkage of the sample. The early shrinkage of samples with 0%, 60%, and 100% replacement rates of mixed sand is 759, 815, and 861 ppm, respectively. This is because the ultra-fine sand of the Yellow River absorbs more water during the mixing process due to its small particle size and large specific surface area. In this way, the water–binder ratio and internal humidity of the sample are reduced at the same time, increasing early shrinkage of the sample.Replacing quartz sand with mixed sand has an adverse effect on the pore structure of early samples. However, with increased curing time, this adverse effect is offset as the pores between large particles are filled with ultra-fine Yellow River sand and with the secondary hydration reaction of cement. It is worth noting that with increased curing time and a replacement rate of mixed sand of 100%, the pore diameter is mainly distributed at 3 nm. The addition of mixed sand continuously refines the pore diameter and optimizes the pore structure. When the replacement rate of mixed sand is 100%, the cost of high-performance concrete decreases by 45% and primary energy consumption drops by 7% with no significant decrease in 28 d compressive strength.In this study, the resource utilization of the sediment of the Yellow River is investigated. To reduce the limitations of existing sediment utilization schemes, we propose using sediment to build embankments and to prepare ultra-high-performance concrete (UHPC) from the ultra-fine sand of the Yellow River, and the performance of the prepared concrete is examined. The major conclusions are drawn below:(1)Since sediment resources have been underutilized, this study proposes sediment-based embankment building, i.e., transporting sediment from the bottom of the reservoir to the shore and building an embankment at the 330 m elevation line on both sides of the reservoir. This would be consume considerable sediment and increase the water storage capacity of the reservoir area.(2)To solve the low strength of Yellow River sand concrete, we propose a method for utilizing the ultra-fine Yellow River sand to make high-strength concrete, i.e., mixing of the ultra-fine Yellow River sand and river sand negatively affects the fluidity of ultra-high-performance concrete; however, even with a replacement rate as high as 100%, the mixture still exhibits high fluidity (248.5 mm). The addition of mixed sand does not seriously reduce the compressive strength. At a 100% replacement rate, pore diameter is primarily distributed at 3 nm. At the 100% replacement rate, UHPC cost can be reduced by 45% and primary energy consumption by 7% with no significant decrease in compressive strength.


Correction: J Exp Clin Cancer Res 33, 24 (2014)https://doi.org/10.1186/1756-9966-33-24Figure Following publication of the original article , the autFurthermore, the sentence ‘Colony formation was absent in HCT-116 and MSTO-211, while yields of HFF and Met-5A colonies were not affected.’ under CF reduces the clonogenic survival of MSTO-211 and HCT-116 cell lines of Results section should be updated to ‘Colony formation was reduced in HCT-116 and MSTO-211, while yields of HFF and Met-5A colonies were not affected.’This correction does not change the result, interpretation, and conclusions of the study.


Good hygiene, in both health care and the community, is central to containing the rise of antibiotic resistance, as well as to infection control more generally. But despite the well-known importance, the ecological mechanisms by which hygiene (or other transmission control measures) affect the evolution of resistance remain to be elucidated. Using metacommunity ecology theory, we here propose that hygiene attenuates the effect of antibiotic selection pressure. Specifically, we predict that hygiene limits the scope for antibiotics to induce competitive release of resistant bacteria within treated hosts, and that this is due to an effect of hygiene on the distribution of resistant and sensitive strains in the host population. We show this in a mathematical model of bacterial metacommunity dynamics, and test the results against data on antibiotic resistance, antibiotic treatment, and the use of alcohol-based hand rub in long-term care facilities. The data are consistent with hand rub use attenuating the resistance promoting effect of antibiotic treatment. Our results underscore the importance of hygiene, and point to a concrete way to weaken the link between antibiotic use and increasing resistance. Hygiene and antibiotic use are important levers in the work to limit resistance evolution. We study how they interact, and find that hygiene can attenuate the effect of antibiotic pressure on the rate of evolution. Antibiotics have revolutionized modern medicine, but they also drive the evolution of resistance, and thereby contribute to their own demise , 2. To mIn addition to the role of antibiotic use, there is within the medical profession a firm appreciation of the importance of hygiene in the management of antibiotic resistance. Measures of hygiene, such as hand disinfection, are fundamental to good medical practice after the discoveries of Semmelweis Ignác Fülöp in the mid 1800s , and forIt is thus recognized that antibiotic use and hygiene are key factors in the evolution of resistance, and that this evolution often takes place in a microbial community—but these insights have yet to be put together. This is the task of the present investigation: to study the joint effects of hygiene and antibiotic use on the rate of increase of resistant bacteria in microbial communities, where these communities are commensal, and the antibiotic exposure is collateral. It requires that we integrate the within-host ecological effects of antibiotics with the between-host process of bacterial dispersal, where the latter is affected by hygiene, and possibly other factors, such as population density or cultural habits. This sits most naturally within the theoretical framework of metacommunity ecology , 11, andThe aim of this paper is to introduce the hypothesis that hygiene attenuates the effect of antibiotic pressure on resistance evolution, and address its plausibility. The paper has three parts. First, we informally explain how metacommunity theory predicts that hygiene should limit the within-host ecological response to antibiotic treatment. Second, we develop a mathematical model of resistance dynamics in a metacommunity context and show that this prediction obtains in the model. Third, we test the prediction against antibiotic resistance data from the European Centre for Disease Prevention and Control (ECDC) and find that it is consistent with the data.Bacteria form local communities within individual hosts, and they transmit between host individuals. In ecological terms, bacteria thus form metacommunities, that is, networks of local communities interconnected by dispersal . Within However, the drug dose is only part of the picture. Competitive release of resistant bacteria requires that both sensitive and resistant strains are simultaneously present in the bacterial community within the treated host individual. And if they are, the magnitude of the release depends on the extent to which resistant strains are limited by competition from sensitive strains (see ). If resAs a consequence, the scope for competitive release is maximized when resistant strains are present in a large proportion of host individuals, and have a low abundance in the local communities in which they are present. Hence, for a given total abundance of resistant bacteria in the metacommunity, the competitive release will be larger when the resistant bacteria are more uniformly distributed across the host population.The distribution of organisms in metacommunities is a focus of research in metacommunity ecology, and a picture has emerged that, perhaps unsurprisingly, dispersal of organisms among habitat patches tends to spread them across these patches, making them more uniformly distributed . ConversIn the context of humans carrying resistant and sensitive bacteria, measures of hygiene are precisely such interventions. They should therefore make the distribution of resistant strains less uniform, leaving them abundant in some individuals and absent from others, and thus decrease the scope for competitive release.This leads to our prediction: Increasing the level of hygiene should decrease the effect of antibiotic pressure on the competitive release of resistant bacteria. That is to say that, whilst the magnitude of competitive release increases with antibiotic pressure, this increase is less steep when the level of hygiene is higher. We focus on hygiene, because it is readily actionable and its importance is well-established, but the prediction applies to any factor that limits bacterial dispersal among host individuals.In the previous section, we informally explained why metacommunity ecology theory predicts that hygiene should attenuate competitive release, in the commensal bacterial community collaterally exposed to antibiotics. We used a metacommunity framing, because it provides an intuitive and conceptually straight forward way to represent the biology involved, naturally integrating, as it is, the within- and between host levels of the system. Unfortunately, however, intuition, useful as it may be in generating hypotheses, is not a reliable guide to logical validity. Next, we therefore test this validity by subjecting the argument to formal modelling. In the main text, we use a metacommunity model, and in Supplementary A, we complement the analysis with an epidemiological compartmental model.There are several reasons for this choice. Firstly, we wish to keep the formal analysis close to the informal argument. Secondly, we think that, at least to some extent, the benefits of the metacommunity framework for informal reasoning, such as the within- and between host level integration, translate to the formal modelling as well. Thirdly, despite the frankly obvious fact that our microbiomes form metacommunities, metacommunity theory has not yet found its way into our field. We think this is a missed opportunity, and wish to introduce this tool to the tool box of antibiotic resistance research. But promising as the metacommunity approach may be, as with other approaches, there may be peculiarities to it that affect the results, casting doubt over them. To alleviate this problem, we test our argument against a compartmental model as well. The weakness of this type of model is that its representation of the within host level is crude, but the strengths are that it is well established in the field and that it is very different from the metacommunity model, and therefore unlikely to share unfortunate peculiarities with it. We thus think that this combination is a good choice for the task at hand.J for the number of bacteria in each host and N for the number of host individuals. The constant community size means that the resistant and sensitive types compete with each other, and a decrease in one entails an equal increase in the other, representing competitive release.Our model of bacterial metacommunity dynamics is an extension of Hubbell’s neutral model of biogeography and relative species abundance , 20. TheThe model tracks the proportion of bacterial cells that are resistant in the metacommunity, as time, step by step, unfolds. In each time step bacterial cells die. In the absence of antibiotics, one cell dies in each host individual, and the resistance status of a cell does not affect its probability of dying. With increasing antibiotic pressure, however, more cells can die in each time step, and the death process becomes increasingly biased towards sensitive cells (see Supplementary A for details). We expand on this below.Rj(t) be the number of resistant bacteria at a given time t in host j. Since we are only looking at the transition between two adjacent time steps, we will drop the index t and only write Rj.Once those cells have died, they are replaced by new cells by division. These cells may originate from within the same host or from different host individuals. The probability that a new cell comes from a different host depends on the level of hygiene – the better the hygiene, the lower the probability that a bacterium transmits from another host. If the new cell originates from a different host, the probability that it is resistant is equal to the proportion of cells that are resistant in the metacommunity as a whole, and if it originates from within the focal host, the probability of resistance equals the proportion of cells that are resistant in that host. Let us compute the probabilities more precisely. Let Rj number of resistant bacteria in an individual, the probability that a resistant bacterium dies isEach time step has two phases. In the first phase one or several bacteria are lost, and in the second phase these bacteria are replaced. In the first phase, given a ≥ 1 is the antibiotic pressure, represented as the differential survival of resistant and sensitive cells. Hence, a = 1 means that no antibiotics are present, and the probability that it is a resistant (or a sensitive) cell that dies is simply proportional to their number, whereas a > 1 means that antibiotic treatment makes the death process biased towards sensitive cells.where The probability that sensitive bacteria are lost isρ that depends on the antibiotic pressure a and the abundance R = Rj of resistant bacteria in host j . However, in the computations (see Supplementary A), we consider ρ to be a continuous function that is differentiable in the a-direction. Moreover, we require that it is a decreasing function of R, meaning that more sensitive bacteria die if there are many such bacteria . We then take the integer part of this function to go back to the integer valued ρ. Let us denote by µ the number of bacteria lost in this first phase  = 1 or µ = ρ).The number of sensitive bacteria lost is an integer function R number of resistant bacteria, the probability that one resistant or one sensitive bacterium reappears is, respectively,In the second phase, given wherem ∈   is the probability that a bacterium is chosen from the metacommunity as a whole, rather than the focal individual. The hygiene parameter h = 1 − m, so that good hygiene means high h-values and low m-values (and vice versa). This procedure is performed precisely µ times to replace all bacteria lost in the first phase.and µ/J is very small, although the number µ can be large (in particular much larger than 1). This means that we can replace R/) by R/J with a very small error. With this simplification, which is of minor importance (see Supplementary A), the new probabilities Qr and Qs then becomeThe time steps can be made very small in the mathematical model, and therefore we assume that the portion rj = Rj/J is the portion of resistant bacteria in host individual j, and rj, i.e.,where Z = Z, which is a function of a and h. We prove thatWe compute the expected change of the total number of resistant bacteria in the metacommunity in one time step. This expectation is denoted by a ≥ 1, with strict inequality if a > 1.if Hence, the effect of antibiotic pressure on the rate of increase of resistance (∂Z/∂a) decreases with improving hygiene.Rj across host individuals.We also show that this is due to the effect of hygiene on the β-diversity of the metacommunity (see Supplementary A for details). The β-diversity is the standard deviation of the number of resistant bacteria In the preceding sections, we saw, first, that informal theory predicts that hygiene attenuates the effect of antibiotics on the competitive release—and thus the rate of increase—of resistant bacteria, and, second, that formal modelling supports the validity of that argument. Now, we test this prediction empirically. To do so, we restate it in statistical form.a) and a measure of hygiene (h) in that setting, there should be an interaction (a · h), and this should be negative. The reason is that the interaction term represents the effect that the value of one variable (e.g. h) has on the effect of the other variable (e.g. a), a negative term meaning attenuation.The prediction is as follows: If a measure of the increase of resistant bacteria in a given setting is regressed upon a measure of antibiotic pressure (E. coli), the use of β-lactam antibiotics, and the use of alcohol-based hand rub in long-term care facilities in different European countries, reported by the European Centre for Disease Prevention and Control (ECDC). The merit of this data set is that it pertains to facilities where individuals stay for an extended period of time and contains information on antibiotic resistance, antibiotic use, and a quantitative measure of hygiene. The principal shortcoming is that it is cross sectional, and thus only provides the level of resistance at a given time, not the rate of increase. We therefore modelled the increase in resistance as the enrichment of resistant strains in the long-term care facilities in each country as compared with resistance in E. coli in the general society in that country, the rationale being that this enrichment should be a proxy for the average rate of change in resistance in the individuals in the facilities after they arrived there .We tested this prediction against data on resistance to third generation cephalosporins (a type of β-lactam antibiotics) in Enterobacteriaceae  The data and the regression model are shown in Fig. 2B.The data were analysed by logistic regression . In accHere we have employed metacommunity ecology theory to study what are arguably the two most important levers available to limit the rise of resistance—the amount of antibiotics used and the level of hygiene. We found that informal theory, formal modelling, and data from the ECDC all yield the same conclusion: Improvements in hygiene weaken the link between antibiotic use and increasing resistance. The mechanism is that hygiene limits bacterial dispersal, and thereby alters the diversity that is the substrate for antibiotic induced competitive release. Since a quantitative assessment of this effect in the mathematical model requires biological information that is currently unavailable, we assessed the effect size directly with the ECDC resistance data, and found that it was quite striking  It is important to keep in mind, however, that both our models are designed specifically to test the validity of the informal argument, and as such, are far from comprehensive models of resistance evolution. For example, we do not include costs of resistance and related matters of potential equilibria of resistant-sensitive coexistence. We also ignored de novo mutation. From the perspective of a focal host, mutation is analogous to transmission in that it is an arrival process, whereby resistant cells are introduced to the local population and made available for competitive release. We therefore expect that it should interact with antibiotic pressure in a similar way, and that very high levels of resistance mutation would limit the scope for hygiene to inhibit resistance evolution.E. coli and Enterococci in the faeces of healthy volunteers living in cities with different population densities, and found that it correlated poorly with the antibiotic pressure per individual, but well with the antibiotic pressure per land area. Assuming that bacterial dispersal among individuals is facilitated by a high population density, this fits well with a modulating effect of dispersal, since the antibiotic pressure per land area is the product of the pressure per individual and the population density, and thus corresponds to the interaction term, a · h, in the statistical model above.In addition to our analyses, there are previous empirical results that are suggestive of a role for bacterial dispersal in modulating the effect of antibiotic pressure. Bruinsma et al.  investigWhilst decreasing the population density may not be a viable route to limiting antibiotic resistance, improving health care hygiene is. Proper hand hygiene in clinical work is a cornerstone of patient safety , but morIn conclusion, we have here introduced metacommunity ecology theory to the study of antibiotic resistance, and found that interventions to limit microbial dispersal may provide a means to attenuate the effect of antibiotic selection pressure on the rise of resistance.eoac038_suppl_Supplementary_MaterialClick here for additional data file.


Increasing awareness of antimicrobial resistance (AMR) has raised concerns surrounding antimicrobial use (AMU) in food-producing animals and has focused attention towards livestock production free from antibiotic use. As antibiotic-free livestock production proliferates in the UK, there is an increasing need to implement a system, such as the use of a QR code, to provide consumers with reliable antibiotic information while ensuring that animal welfare standards are upheld. Subsequently, this study aims to explore UK consumers’ perceptions and purchase intention towards QR code labelled pork, and to identify determinants of its purchase, incorporating various theoretical constructs from the Theory of Planned Behaviour. Based on results, consumers’ perceptions, perceived control, and attitudes towards QR code labelled pork are the main determinants of purchase intention. QR code labelled pork may offer a suitable alternative to antibiotic-free labelling as it provides consumers with antibiotic information without inadvertently communicating that conventionally produced pork is unsafe. Crises such as the Bovine Spongiform Encephalopathy (BSE) in cows, avian influenza, the melamine milk incident in China, and the horse meat in beef scandal, have negatively impacted consumers’ confidence in the food chain and increased worldwide concern over food safety4. In response to such crises, a food traceability system was established to provide consumers with unambiguous information about the origin and authenticity of the product5. Traceability systems have been broadly utilised in the food industries8 to reduce food safety concerns and to improve marketplace reputation. Food producers have made great efforts to track the flow of food1 with many showing motivation to go beyond mandatory traceability requirements4, for example, the British pork industry has been at the forefront of developing a DNA/RFID traceability solution incorporating blockchain technology, delivering both knowledge and authenticity assurances to consumers9. Despite these advances, various aspects of food production remain under public scrutiny.Over the years, consumer concern over food quality and safety has risen due to a number of food scandals and accidents10. Despite the 2006 EU ban on antibiotics for growth promotion, the dispute surrounding the extent of AMU in livestock production remains unsettled. Such issues are often exacerbated by the media, as a 2015 article from the Guardian, a British national newspaper, reported the discovery of MRSA in pork products sold in supermarkets11. Not only was this article about food contamination, but notably it highlighted antibiotic use in pig farming as the root cause of MRSA, and the implications for human health11. Subsequently, recent reports of ‘pig-MRSA’ in the media suggest that familiar concerns encompassing biosecurity in agriculture  are converging with those around AMU11.Most recently, antimicrobial use (AMU) in food producing animals is one of the most criticised issues in modern pig production12, AMU in livestock production is still perceived as one of the primary causes for the increase in antimicrobial resistance (AMR)13, with many concerns surrounding the transfer of resistant bacteria from animals to humans via the food chain. As a result, there have been proposals to partially or even completely eliminate antibiotic use in agriculture14. Completely eliminating antibiotic usage is not only detrimental to animal welfare but the use of ‘antibiotic-free’ or ‘raised without antibiotics’ food labels could give consumers the impression that, by default, conventionally produced foods are unsafe.Although the most recent UK One Health Report has revealed that the majority of antibiotics consumed in 2017 were prescribed for human use , compared to only 204 tonnes (26%) for use in food-producing animals15, quantified antibiotic usage at farm level and specific data surrounding the quantity and patterns of use are not available17. Additionally, collecting such information presents a variety of challenges including variations in study objectives as investigators may only measure therapeutic use, only non-therapeutic use, or a combination of both17. Furthermore, it is unrealistic for farmers to record antibiotic usage for each individual animal, especially those operating at a large scale. To the best of the authors’ knowledge, there is currently no operational system to collect and disseminate antibiotic usage information to consumers at the point of purchase, presenting a unique opportunity for the development of a new system similar to that of a traceability system.While antibiotic use in UK pork production has decreased considerably from 278 mg/population correction unit (PCU) in 2015 to 105 mg/PCU in 202019. Scanning the QR code on a smartphone enables easy access to information specific to that product19, a concept employed globally and accepted by consumers18. QR code usage is estimated to reach 10.1 million in Europe by 202020 and the food traceability market is expected to reach $18,528 million by 2023 with a compound annual growth rate of 9.1%21. As such, sector wide research into the application of QR codes is vast, with more research emerging relating to food traceability23. Research has highlighted the success gained by food traceability systems, as consumers generally link traceability with safety and quality attributes25, instilling trust in both a certain food product and also in the food system as a whole26. Specifically, an estimated 92% of consumers revealed a desire to access transparent information on product’s labelling, validating the need for QR codes on food packaging21. As a result, several well-known brands such as Nestle, have recently added QR codes onto their best-selling products such as the instant Maggi noodles27.Quick Response (QR) codes are one of the most popular traceability systems having been introduced into the food industry as a two-dimensional barcode28 to explain the antecedents of behaviour32. The TPB has been successfully applied in health and food choice research as intention to perform a behaviour typically precedes, and thereby predicts, the actual behaviour33. The TPB postulates that behavioural intention is determined by an individual’s attitude, subjective norm, and perceived behavioural control (PBC)28. In addition to theoretical research, various studies have focused on consumers’ willingness-to-pay (WTP) for products that have been produced with increased concern for animal welfare37, particularly as research conducted into consumer preference illustrates that concerns for the wellbeing of livestock is of great interest to them39. Indeed, Kehlbacher et al.35 found that each month, consumers were willing to increase meat expenditure by 26 and 32% for meat produced with ‘enhanced’ and ‘excellent’ welfare standards, respectively.Substantial research surrounding consumer food choice, typically applies a conceptual framework, such as the Theory of Planned Behaviour (TPB)42. However, since the introduction of ‘antibiotic-free’ and associated labels, contradictory findings have emerged. According to Karavolias et al.43, when purchasing ‘antibiotic-free’ labelled poultry, consumers believe this label perpetuates high levels of animal welfare. Of consumers who purchase meat products raised without antibiotics, 70% believe that animal health is significantly improved44 and that they are promoting good livestock production practices43. This is consistent with findings by Goddard et al.13 suggesting that consumers are unaware of the negative ramifications that a ban on antibiotic use in livestock production may have on animal welfare. These findings suggest that such labels may be misleading consumers, resulting in further confusion. In addition, it highlights an information gap among consumers in relation to understanding their food labels.In addition, research specific to pig welfare has commonly found that consumers have a positive attitude towards increased welfare standards for pigs43.As the use of ‘antibiotic-free’ labelling proliferates, there is an increasing need to implement a system similar to that of a food traceability system to enable consumers access to reliable antibiotic information, providing both quality and safety assurances about the food product, but also ensuring that animal welfare standards are upheld. While providing consumers with the choice to purchase QR code pork, this does not guarantee that all consumers will choose to do so. Food choice is often contingent upon values, food attributes they consider important, and their motivation to use available information45. Pork was selected as the test food as the UK pig industry is recognised to be the highest user of antibiotics, believed to use more pro rata than any other livestock production sector46. In addition, safety concerns and negative media representation have led to feelings of uncertainty and mistrust among consumers surrounding pork safety45.Therefore, it is necessary to explore consumers’ perceptions and purchase intentions towards QR code pork to characterise consumers response to information as an integral aspect in the development of food marketing and communication strategiesThe objectives of the research were (1) to determine consumers’ purchase intention of QR code labelled pork and the exploratory factors that influence purchase, (2) to identify if the TPB constructs’ ‘attitude’, ‘PBC’, and ‘trust’, influence purchase intention of QR code labelled pork, and (3) to understand consumers’ perceptions of QR code labelled pork. The study will offer insights into how QR code labelled pork influences consumer perceptions and attitude to pork, and how the label influences consumer purchasing decisions.In total, 1000 participants aged 18–92 years old  completed the survey ; indicating that they do not consider domestic animals to act as a reservoir or spread resistant bacteria.In both QR code sub-groups, participants showed a moderately high level of PBC (QR1: 4.76 and QR2: 4.82) stating they were able to find and understand the antibiotic-related information embedded in the QR code. However, they strongly indicated (QR1: 5.26 and QR2: 5.18) that they preferred a rating system or colour coding to indicate if antibiotic use is high rather than a figure in ml . Participants perceived personal risk and consideration towards animal welfare standards to be high . Participants thought that too many antibiotics from the doctor can cause AMR and that AMR will interfere with disease treatment. In addition, adherence to animal welfare standards and ensuring animals do not experience pain were considered important. Contrastingly, participants were neutral in their acceptance of AMU in livestock production (QR1: 4.20 and QR2: 4.30) and held negative perceptions towards domestic pets acting as a potential source of AMR transfer  towards QR code labelled pork and showed a general high level of knowledge towards EU regulations . However, awareness of AMR was limited; while the majority had heard of AMR (52%), only 38% of respondents knew what AMR is.Participants in both sub-groups were neutral in their intention to buy QR code labelled pork (QR1: 4.20 and QR2: 4.29); with no significant differences between antibiotic usage and farm assurance labelled pork. Conversely, when examining the willingness to purchase antibiotic usage labelled pork; 34.8% of the sample were not willing to pay more, and of the 65.2% who were willing to pay extra, on average they were willing to pay ~10% more. For farm assurance labelled pork, 35.2% of the sample were unwilling to pay a price premium and of the 64.8% of those who would pay; on average they were willing to pay ~15% more.All exploratory constructs except knowledge of EU regulations and awareness of AMR, correlated significantly with intention to purchase QR code labelled pork in both sub-groups (see Table 2adj) of the variance in intention to purchase pork labelled with antibiotic use and 77% of the variance in intention to purchase farm assured labelled pork , PBC (both sub-groups), perception of QR codes (both sub-groups), personal concern perceptions (farm assurance label sub-group), perceptions towards animal AMU acceptance (antibiotic usage label sub-group), perceptions towards animal welfare standards (antibiotic usage label sub-group), knowledge of EU regulations (farm assurance label sub-group), and awareness of AMR (antibiotic usage label sub-group). Together these exploratory variables account for 73% , a higher PBC for finding and understanding the antibiotic information , and having more favourable perceptions towards the QR code , were associated with a greater intention to purchase it. Additionally, having an increased level of personal concern towards AMU (ß = 0.06) was associated with a greater intention to buy farm assurance labelled pork; while, having favourable perceptions towards animal welfare standards (ß = 0.06) was associated with an increased intention to buy antibiotic usage labelled pork. While perceptions towards animal AMU acceptance (ß = −0.08 for the antibiotic usage label sub-group), awareness of AMR (ß = −0.06 for the antibiotic use label sub-group), and knowledge of EU regulations (ß = −0.05 for the farm assurance label sub-group) were also determinants of purchase intention, they had a negative influence on intention to purchase QR code labelled pork. Therefore, having less favourable perceptions towards the acceptance of AMU in animals, lacking awareness towards AMR, and lacking knowledge towards EU regulations, were associated with a greater intention to purchase QR code pork.2adj) in intention to purchase labelled pork remained constant at 73% for the antibiotic usage label sub-group (p < 0.001) and 77% for the farm assurance label sub-group (p < 0.001). That is, when the model was extended with age, gender, education, and socioeconomic status (SES), socio-demographic characteristics explained little variance in the prediction of purchase intention. Attitude (ß = 0.25), PBC (ß = 0.07), perception of QR code (ß = 0.64), acceptance of animal AMU (ß = −0.08), perceptions towards animal welfare standards (ß = 0.07), and awareness of AMR (ß = −0.07) remained significant determinants of intention to purchase antibiotic usage labelled pork  of the variance in attitude towards antibiotic usage labelled pork and 40% of the variance in attitude towards farm assurance labelled pork  and animal welfare (farm assurance label sub-group) influence consumer attitude towards labelled pork. Together these exploratory variables account for 37%  and constructs from the TPB on intention to purchase QR code labelled pork in a representative sample of adults in the UK.48. This study shows that the exploratory models account for 73% (based on R2adj) of the variance in intention to purchase pork labelled with antibiotic usage information and 77% of the variance in intention to purchase farm assured labelled pork.Overall, the exploratory models showed that psychological contributors to intention to buy QR code pork are somewhat different between each sub-group (antibiotic usage and farm assurance labels). Based on the literature it was expected that the presence of a QR code would influence consumer purchase intention as food packaging with less information is more attractive and considered to be a product of higher quality49 which showed that older participants perceived more risks in food safety than younger participants; possibly explaining why the younger sample population viewed purchasing QR code pork as more beneficial and thus, as something that makes them feel good and pleased. As a construct of the TPB, attitude is often identified as a determinant of purchase intention32. Specifically, Spence et al.4 found that attitude had the strongest relationship and was the main determinant of intention to buy both traceable beef steak and mince steak, while McCarthy and colleagues50 established that consumers’ attitudes towards pork consumption influenced their intention to consume pork. The TPB postulates that behavioural beliefs influence attitude29, and the present study shows that, with the exception of the belief that QR code pork will likely be more expensive, beliefs surrounding product quality (both labelling sub-groups) and animal welfare (farm assurance label sub-group) contribute 37% of the variance in attitude towards intention to buy antibiotic usage labelled pork and 40% towards the purchase intention of farm assurance labelled pork. As attitude is one of the main predictors of intention across both labelling sub-groups, behavioural beliefs should be incorporated into marketing campaigns, with a particular focus on product quality.Respondents’ attitude and PBC towards QR code pork were strong positive determinants of purchase intention across both labelling sub-groups. Generally, respondents reported a slightly favourable attitude towards QR code pork, with younger participants presenting significantly more positive attitudes towards traceable pork. This finding is in line with Veeman and Li51; thus, this finding can be used for marketing purposes to ensure that information transfer is both desirable and user friendly. Additionally, as PBC is positively associated with intention to buy QR code pork, increasing consumers usability should further increase their PBC and thus, their intention to purchase QR code pork.In correspondence with their attitude, respondents also reported moderately positive PBC, perceiving themselves to have the ability to find and use the QR code and understand the antibiotic-related information presented. Despite this, respondents in both label sub-groups strongly indicated that they would prefer a rating or colour coded system related to antibiotic usage, similar to that of the traffic light system, rather than usage figures and data. It is possible that this implies a lack of consumer understanding of usage data, however, the traffic light system is an effective tool for conveying complex information3 identified that consumers’ perceptions had a significant influence on choosing antibiotic-free chicken, and Schleenbecker and Hamm52 uncovered that perception has an important role in purchasing organic foods. However, based on the finding that consumers’ perceptions of QR code pork are only moderately positive, it is clear that there is considerable scope for improving UK consumers’ perceptions; thus, the introduction of marketing communications may be a useful strategy to provide consumers with the benefits of QR codes for accessing traceability information and thereby promote its use.While participants conveyed neutral perceptions towards QR code pork, perception was the main determinant of purchase intention in each sub-group. This result corroborates with other studies, as Rahnama and colleaguesAn interesting finding from this study is that respondents’ perceptions towards AMU practices vary and therefore, while they were found to influence purchase intention, certain perceptions had a positive influence while others had a negative association with purchase intention. Moreover, the perceptions that were found to influence purchase intention additionally varied between each label sub-group. Respondents personal risk concerns surrounding AMU and their consideration towards animal welfare were high. Livestock production free from pain and adherence to animal welfare standards when purchasing meat was important to respondents; however, at the same time, they reported a high level of concern towards contracting AMR, particularly in relation to antibiotics prescribed by a doctor. Overall, in the exploratory model for the antibiotic usage label sub-group, having favourable perceptions towards animal welfare standards was associated with an increased purchase intention, whereas, in the farm assurance label sub-group respondents personal concern towards AMU was associated with a greater purchase intention. It is possible that the former finding suggests that consumers who are more considerate of high animal welfare standards have a greater interest in the antibiotic usage label and accessing exact AMU data instead of the farm assurance label, as it was not a predictor within the farm assurance label sub-group. In comparison to respondents more favourable views, perceptions surrounding the acceptance of animal AMU were moderate and this was reflected in the model for the antibiotic usage label sub-group as it was found to have a negative influence on intention. Consequently, possessing less favourable perceptions towards the acceptance of AMU in animals is associated with a greater intention to purchase. This result was surprising as while perceptions towards animal AMU were more neutral, respondents indicated that they were, nonetheless, positively accepting of AMU in livestock. This finding suggests that more research is required to supplement this preliminary result before a definitive conclusion is reached as to the potential role of this construct in the model of purchase intention towards QR code pork.54 and antibiotic-free chicken3; however, dissimilar to this study, awareness was found to have a positive influence on intention. The present study determined that respondents generally lack awareness of AMR as just over one third of consumers know what AMR is, yet, as previously discussed, respondents perceive high personal risks associated with AMR. Similarly, research conducted by Public Health England55 revealed that misunderstandings about antibiotics persists in the minds of a significant proportion (44%) of the general public, with respondents showing uncertainty around concepts such as carriage of resistant bacteria and whether resistance is caused by taking antibiotics. Although consumers do not fully understand the concept of AMR, it can be speculated that once they were exposed to the QR code product in our study, due to unfamiliarity, they may equate it with increased qualities and automatically assume it is a superior product. Therefore, this may explain why a lack of awareness towards AMR is associated with a greater intention to buy QR code pork. While this finding can be used in the development of consumer campaigns to increase AMR awareness, it must be considered that this rationale is speculation and thus, merits further research.Additionally, the exploratory models identified respondent’s awareness of AMR as a determinant of intention to purchase antibiotic usage labelled pork, and knowledge of EU regulations as a determinant of intention to buy farm assurance labelled pork; again, uncovering a negative influence in both sub-groups on intention to buy QR code pork. Previous research has also shown that consumers’ awareness is one of the most important factors in choosing healthy food productsp < 0.001) and 76% for the farm assurance label sub-group (p < 0.001). Various studies have uncovered a link between socio-demographic characteristics and purchase intention, as Pelletier and colleagues56 identified that gender has a positive impact on buying organic food, and Zhang et al.1 also observed that females had a higher likelihood of purchasing traceable pork and oil, than males. Additionally, previous studies have shown that age has a significant influence on purchasing healthy food products56 whereby younger consumers are more likely to purchase traceable food products than other age groups1 and are also more likely to pay extra for meat with reduced antibiotics13. By contrast in this study the socio-demographics factors such as gender, age, education, and SES had no significant influence on intention to purchase QR code labelled pork.When extended with socio-demographic characteristics, the predictive power of the exploratory model remained constant at 73% for the antibiotic usage label sub-group , by exploring the trust placed in various stakeholders and organisations, it will be possible to identify the most effective manner in which to gain consumer trust and thus, advocate QR code labelled pork.In the final model, perception was the main determinant of intention to purchase each QR code product, followed by attitude. As a construct of the TPB, attitude has been identified in various studies as a strong precedent of behaviour intention, often identified as the main determinant influencing purchase intention60; however, in recent years we have seen the emergence of a “raised without antibiotics” (RWA) label on the UK market. Despite this, the impact that RWA livestock production has on welfare parameters has not yet been quantified, and thus, it is possible that the elimination of antibiotics from production can have detrimental influence on animal welfare; particularly if sick animals are denied treatment in order to comply with marketing standards. Hence, there is a gap in the UK market for a product that provides valuable and useful antibiotic-related information while preserving animal welfare. QR code labelled pork may offer an alternative solution to RWA labelling, providing consumers with the necessary information without inadvertently communicating that conventionally produced ‘unlabelled’ pork is harmful or unsafe. QR codes can be used as a means of access to information via food packaging and therefore, any information can be added or removed to provide consumers with the exact information they require, highlighting that QR codes are an effective and adaptable platform of information dissemination. For instance, the present study has identified that consumers have a high level of consideration for animal welfare standards, subsequently, information could be added to the QR code output to provide additional animal welfare data ; and this may be worth exploring in the future. Additionally, by providing this information on food labels, it may also encourage producers to reassess their AMU practices and influence positive reform through the application of improved farm management and prevention strategies.The use of antibiotic credence labelling such as “antibiotic-free”, “no antibiotics ever”, and “raised without antibiotics” has been used in abundance on food labels in countries such as the United StatesOverall, based on the findings presented in this study, the use of QR codes as a means of access to antibiotic information may be considered as a suitable and useful alternative to RWA and other associated ‘antibiotic-free’ labelling. This finding assists to inform marketers, retailers, and policymakers to aid the development of effective strategies to further engage consumers and to successfully identify a position for this product in the UK market. Whilst we have outlined the practicality of QR code labelled pork, it is, however, imperative for these stakeholders to conduct cost-benefit analysis prior to the launch of any such product. Additionally, having uncovered a lack of consumer knowledge surrounding agricultural AMU practices, it is necessary to develop targeted communication materials to address consumer concern and misinformation, educating the consumer on the positive role of access to antibiotics in upholding animal welfare standards.10. Additionally, there is also the possibility that consumers may not notice or choose not to scan the QR code. Despite this, research suggests that nearly 60% of shoppers use their mobile phones to search for coupons, and more than half of shoppers use apps when grocery shopping, suggesting that many consumers feel confident using their mobile phone to seek product information while shopping61. Nevertheless, it must be considered that consumers are faced with various other types of information, labels, and logos when shopping which influences their purchase intention, and this is something that this research has not addressed. It is therefore recommended that future studies investigate the in-store purchase of QR code labelled pork, for instance, through the application of an experimental auction. Conducting in-store research, using real money and real goods will thereby assure researchers that consumer responses are more closely linked to their actual purchasing behaviour. Additionally, various design aspects should be considered before a QR code is added to product packaging. For instance, ensuring the QR code is the correct size for the food product and that it can be easily seen by consumers, and providing a call-to-action text  and brief instructions for scanning food QR codes as not all consumers are familiar with doing so20. Lastly, as this research was the first of its kind to investigate consumers’ perceptions and intention to buy a hypothetical QR code labelled pork product, the results presented are preliminary and future studies should seek to replicate these findings to ensure that the QR code output presented to consumers is of utmost success.Notwithstanding the contributions of this research, certain limitations remain that future research should seek to overcome. Firstly, behavioural intention is reported in this study rather than actual behaviour; however, intention does not necessarily translate into purchasing behaviourOverall, this study demonstrates that consumers have somewhat favourable perceptions and attitudes towards QR code pork as an antibiotic traceability system, and that these are the main determinants having a positive influence on their purchase intention. QR code labelled pork may be a suitable and useful alternative to RWA labelling however, more research is needed to directly compare QR code labelled pork and antibiotic-free labelled products before marketers can develop strategies to promote this traceable product. In addition, communication practitioners should place an emphasis on developing communications to increase consumer knowledge and awareness of agricultural AMU and address any misinformation.Using an online survey (see Supplementary Table n = 495) answering questions related to QR code one (antibiotic usage labelled pork), and the other half (n = 505) answering questions related to QR code two (farm assurance labelled pork). To ensure no missing data, a forced response option was used for all items. The questionnaire took approximately 20 min to complete. Ethical approval for the study was obtained by the School of Medicine, Dentistry, and Biomedical Sciences Faculty Research Ethics Committee, Queen’s University Belfast (Faculty REC Reference Number: MHLS 20_23) and conducted in accordance with guidelines specified in the Declaration of Helsinki. Participants were told that by agreeing to take part in the survey they were providing consent and no written consent was obtained. The data was collected by a research agency, Dynata. An overview of participants socio-demographic characteristics is described in Table Respondents were randomly assigned to a survey with approximately half of the respondents . Firstly, pork consumption, purchase frequency, and the importance of selected attributes in purchase decisions, were measured. Socio-demographic characteristics were then sought to ensure nationally representative quotas were obtained. Then, consumer knowledge of EU regulations, awareness of AMR, and AMU practices within both humans and animals, were measured. Following this, participants were presented with an example of a hypothetical QR code labelled pork product before completing items measuring attitude, PBC, trust, behavioural beliefs, perceptions of QR code, and purchase intention. Lastly, WTP, generalised trust, and remaining socio-demographics  were recorded.The questionnaire contained close-ended questions pertaining to various theoretical constructs from the TPBn = 495) were shown QR code 1 (antibiotic usage labelled pork), and the other half (n = 505) were shown QR code 2 (farm assurance labelled pork).Respondents were shown an example of a pork product with a QR code facilitating access to antibiotic-related information. The pictorial highlighted the difference to traditional pork widely available in stores due to the unique information made available to consumers by scanning the QR code on the pack via a smartphone. A visual aid showing QR code labelled pork was shown to respondents as illustrated in Fig. The basis of each QR code option was the same. It enabled consumers to gain information about the region of origin, the farmer, the rearing conditions of the pork , the breed of pig, and an assurance that the product is compliant with UK law, appropriate withdrawal periods, and RSPCA animal welfare standards. In addition, QR code 1 (referred to as the ‘antibiotic usage label’) provided quantified antibiotic usage data from the farm in mg/kg, while QR code 2 (referred to as the ‘farm assurance label’) said that the product is Red Tractor assured.4 unless otherwise indicated.All items were scored on a 7-point Likert-type scale . All items were adapted from Spence et al.Attitude towards purchasing QR code pork in comparison to traditional pork currently available in supermarkets was measured with four items on seven-point semantic differential scale. Participants were asked to indicate how purchasing pork labelled with antibiotic information would make them feel  and beliefs towards purchase .Respondent’s perceived ability to find and understand the antibiotic information embedded in the QR code label was assessed by eight items.Trust in the QR code antibiotic information was evaluated with three items: “I trust that QR code labelled pork can provide accurate and reliable information surrounding antibiotic use during production”, “I trust that the information about adherence to the withdrawal period is reliable on QR code labelled pork” and “I trust that QR code labelled pork will provide an assurance that antibiotics have been used on the animal responsibly”.To measure behavioural beliefs, eight statements that compared QR code labelled pork to traditional pork currently available in supermarkets were measured .Respondent’s perceptions towards QR code pork were measured with seven items (constructed by the author): “I believe this QR code would be useful”, “I would like to see this QR code on pork products”, “seeing this QR code on foods will assure me that antibiotics have been used on the animal responsibly”, “I would eat meat from animals which had antibiotics knowing that the animal hasn’t suffered”, “buying products with this QR code will reduce my risk of consuming antibiotics”, “buying products with this QR code will reduce my chances of getting AMR” and “buying products with this QR code will help me not worry as much about AMR”.To measure intention to purchase QR code labelled pork, participants responded to four statements: “if pork products with this QR code become available…”, “I intend to buy them”, “I will look for them”, “it will be important for me to buy them” and “I will buy them to find out more about animal welfare standards”.Respondents rated the extent to which they trust others with four items (unpublished): “most people are basically honest”, “most people are trustworthy”, “most people are basically good and kind” and “most people are trustful of others”.11); three relating to human practices and eight in relation to animal practices.Perceptions towards human and animal AMU practices were assessed by eleven items .Respondents indicated how much more (in pence) they would pay for QR code labelled pork directly through the question: “suppose the price of pork currently available in the supermarket is £2 for 500 g. The price of pork labelled with a QR code embedded with unique antibiotic information will be higher but is not determined yet. How much more would you be willing to pay to purchase 500 g of labelled pork?” Participants chose between the following options: 10p, 20p, 30p, 40p, 50p, 60p, 70p, 80p, 90p, £1, £1.10, £1.20, £1.30, £1.40, £1.50 + , “I would not be willing to pay any extra” and “I would not be willing to buy pork labelled with a QR code”. The price of the traditional pork was based upon the market price of a product sold in September 2019 by one leading UK supermarket.Respondent’s knowledge of EU regulated pork was evaluated by five items (constructed by the author) and measured using a dichotomous scale .11): “have you heard of antibiotic or antimicrobial resistance?” and “do you know what AMR is?”Awareness towards AMR was assessed by two dichotomous scale (yes/no) items , with a p-value 62. The items within each construct were then averaged by computing a mean of the loading items and scales were constructed. Scores of each scale ranged from a minimum of 1 to a maximum of 7, with higher values signifying stronger levels of the construct. Finally, resulting scales were labelled based upon their content and Pearson correlations were computed to measure the strength of the relationship between constructs within the model.Each of the 62 Likert-type questionnaire items were entered into a maximum likelihood factor analysis with Direct Oblimin rotation, supressing factor loadings < 0.3, to identify a measurement model. The item loadings were then examined to ensure that a clean solution was attained and Cronbach’s α coefficient was calculated to investigate the internal reliability of each construct (Table Descriptive statistics (mean and SD) were used to explore the data within each sub-group Table .Hierarchical multiple regression analyses were used to examine the association between predictor variables and intention to purchase QR code labelled pork across both sub-groups. In step 1, exploratory predictor variables were entered while socio-demographic characteristics were entered in step 2. In addition, to examine the unique contribution of behavioural beliefs scores and attitude, a standard multiple regression analysis was performed. Regression assumptions regarding normality, linearity, and homoscedasticity were met and multicollinearity was not a concern .Quality, α = 0.88), group two consisted of three attributes relating to animal welfare practices involved in the production of QR code labelled pork . Perceptions of AMU practices contained four factors, identified as Personal concern (α = 0.65), Animal welfare standards (p = 0.75), Animal AMU acceptance (α = 0.71), and Animal concern (α = 0.55). Due to unacceptable internal reliability, the factor Animal concern was removed from the analysis. Although the internal reliability of Personal concern was also < 0.7 (α = 0.65), it was deemed acceptable for analysis as recommended by Ursachi et al.63 as the α is within the range of 0.6–0.7. All factor items and internal reliability values are presented in Table Perceptions of QR code α = 0.92), intention (α = 0.95), attitude (α = 0.93), trust (α = 0.94), perceived behavioural control (α = 0.93), and generalised trust (α = 0.93) were all unifactorial. Behavioural beliefs also yielded a one-factor solution however, for structure and practicality, beliefs were separated into three groups. Group one consisted of four attributes relating to the quality of QR code labelled pork (and was therefore labelled , intentiConsumer surveyPublished paper sharing data