Physical Attributes Research Articles

Deep learning-assisted local resonance strategy for accurate internal damage imaging in composites

In this paper, we propose a deep neural network-assisted strategy to accurately and efficiently identify local defect resonance (LDR) modes and accurately image the internal damage in composites. A two-dimensional convolutional neural network (2D-CNN) model was constructed to identify LDR modes. The frequency-domain contour maps were used as input data, given that the LDR phenomenon exhibits discernible physical attributes in the frequency domain that are conducive to deep neural network assimilation. The obtained results demonstrate effective training outcomes and transferability, even with a limited number of samples. The LDR modes are efficiently extracted by the developed 2D-CNN model and used to obtain the accurate imaging of internal damages in composites.

Sugarcane bagasse derived biochar potential to improve soil structure and water availability in texturally different soils

Low organic matter content is one of the main constraints in arid and semiarid regions. This constraint and its negative influences on soils and plant growth may be alleviated by biochar (BC). Furthermore, improving soil physical and hydraulic attributes by application of biochar has received increased attention. Therefore, in the present study, the effects of sugarcane bagasse-derived biochar on the structural stability, water availability, and pore-size distribution (PSD) of three texturally different calcareous soils collected from different agro-climatologically regions were examined during a long-term experiment. Low and high-temperature biochars, produced in a muffle furnace by the traditional slow pyrolysis method at 300 °C (BC300) and 600 °C (BC600) were evaluated. Pots (15 kg) were filled with three different silty-clay Inceptisols (SCInc), silty-clay-loam Alfisols (SCLAlf), and loam Aridisols (LArid) soils mixed with 0 (control), 1, 2, and 3 w/w% of BC300 and BC600 during 540 days of incubation. The high energy moisture characteristic (HEMC) data was modeled using a modified van Genuchten function to quantify aggregate stability through stability ratio (SR) and structural stability index (SSI). The plant available water (PAW), least limiting water range (LLWR), and integral water capacity (IWC) were calculated with two matric suctions (h) of 330 cm for field capacity (FC) and 15,000 cm for permanent wilting point (PWP). Then the integral energy (EI) values were calculated (EIIWC). Results indicated that the incorporation of 3 w/w% biochar significantly (p < 0.01) increased SR (35 to 100%) and SSI (21 to 28%) indices in all three soils. Biochar significantly increased modal suction (MS) in LArid soils (5 to 158%); whereas, decreased MS of the other soils (3 to 43%). MS, SR, and SSI of BC300 and BC600-treated soils were not significantly different. PAW, LLWR, and IWC significantly decreased in the SCInc (18 to 61%, 8 to 44%, and 6 to 35%) and SCLAlf (8 to 44%, 18 to 35%, and 20 to 47%) soils and increased in LArid (4 to 54%, 3 to 61%, and 24 to 111%) soil with increasing biochar doses. There were no changes in EIIWC in biochar-treated LArid soil where PAW, LLWR, and IWC increased. Biochar increased EIIWC across the studied soil from 1% to 3.38 folds, thereby increasing the gradient of water potential to absorb the available water. Soil and soil-biochar mixtures exhibited heterogeneous and multimodal pore-size distribution (PSD). Biochar promoted the PSD peaks related to water-transmitting pores in SCInc and SCLAlf soils while decreased in LArid soil. In conclusion, results indicated that among the applied levels of biochar, the application of 3 w/w% biochar is suggested as a suitable way to improve soil physical behavior and structural stability.

Evaluation of Morphological, Physical and Functional Attributes of Agathi (Sesbania grandiflora) Leaves and Flowers

The study aimed to characterize the morphological, physical, and functional properties of agathi (Sesbania grandiflora) leaf and flower powders, highlighting their potential for food applications. Morphological assessments revealed that agathi leaves have an edible index of 76.20 ± 0.42 % and a waste index of 23.75 ± 0.65 %, while flowers showed an edible index of 63.79 ± 0.46% and a waste index of 36.21 ± 0.54 %. Physical properties showed that leaf powder had a higher bulk density (0.36 ± 0.02 g/cm³) and tapped density (0.59 ± 0.02 g/cm³) compared to flower powder (0.29 ± 0.03 g/cm³ and 0.48 ± 0.01 g/cm³, respectively). The flowability (Carr index) was slightly better for flower powder (40.24 ± 0.01 %) than for leaf powder (39.2 ± 0.01 %). Functional properties indicated that flower powder had significantly higher water absorption capacity (597.28 ± 1.22 %) and oil absorption capacity (224.21 ± 1.56%) compared to leaf powder (315.30 ± 1.28 % and 183.16 ± 1.34 %, respectively). Flower powder also exhibited greater solubility (28.77 ± 2.66 %) versus leaf powder (12.92 ± 1.59 %). These results suggest that both agathi powders are valuable ingredients for food formulations, providing functional and nutritional benefits, and are suitable for use in developing, handling, and packaging functional food products.

Optimizing Cookie Formulation Using a Composite Flour Blend of Soybean, Beetroot, and Wheat: Effects on Physicochemical and Phytonutrient Characteristics

This study aimed to optimize cookie formulation using a composite flour blend of soybean (SF), beetroot (BF), and wheat (WF). Four blends were formulated: 50% WF:45% SF:5% BF (T1), 50% WF:35% SF:15% BF (T2), 50% WF:25% SF:25% BF (T3), and 100% WF (Control) (T4) for cookie preparation. The inclusion of SF and BF had significant effects on the physical, chemical, and phytonutrient attributes of the cookies. Results showed an increase in diameter and height with the addition of beetroot and soy flour. T2 had the highest weight (9.57g), diameter (5.42cm), and spread ratio (6.46) among the blends, while T3 had the highest total color difference. T1 cookies had higher levels of protein, crude fiber, total phenolic content, and total antioxidant activity compared to the control. Statistical analysis indicated that the sensory characteristics of the cookies were not significantly affected by the addition of soy and beetroot flours. This study suggests that composite flour cookies enriched with nutritional and antioxidant properties can be developed by incorporating varying levels of beetroot and soy flour alongside wheat flour.

Impact of corn shredlage and crabtree-negative yeast on silage quality and rumen fermentation characteristics

The physical attributes of corn silage are enhanced by shredlage (SHR), while there is a rising interest in boosting its biological performance. This study aimed to assess and compare the impact of both the chopping method and different yeast strains on ensilage quality including the in vitro evaluation of corn silage. Both types of corn, including chopped and shredded, were harvested on the same day from the same field where the same corn hybrid (Suwan 5) was grown. Subsequently, whole-corn plants were fermented with additives. A 2 × 5 Factorial completely randomized design was employed, where factor A represents corn chopped (CON) and corn shredded (SHR), and factor B represents the additives: no additives, molasses + urea (M + U), M + U + Candida tropicalis KKU20, M + U + Pichia kudriavzevii KKU20, and M + U + saccharomyces cerevisiae. The results demonstrated that SHR fermentation with M + U and yeast significantly increased in vitro dry matter degradability (IVDMD) and organic matter degradability (IVOMD). Specifically, at 4 h post-incubation, the addition of Crabtree-negative yeast led to a 5.8% increase in total volatile fatty acids (TVFA) compared to the Crabtree-positive yeast group (P < 0.01). The C2 (acetic acid) + C4 (normal butyric acid and isobutyric acid): C3 (propionic acid) ratio showed a significant decrease without additives, but P. kudriavzevii KKU20 led to the highest ratio and methane production (P < 0.01). Based on this study, it could be concluded that SHR harvesting led to higher digestion efficiency in the rumen. The use of M + U + yeast also demonstrated uncertain effects on rumen fermentation efficiency, and the inclusion of P. kudriazevii KKU20 may potentially reduce rumen fermentation efficiency when used with corn silage.

Modeling Nonspherical Hailstones

Abstract Hail research and forecasting models necessarily involve explicit or implicit—and uncertain—physical assumptions regarding hailstones’ shape, tumbling behavior, fall speed, and thermal energy transfer. Whereas most models assume spherical hailstones, we relax this assumption by using hailstone shape data from field observations to establish empirical size–shape relationships with reasonable degrees of randomness considering hailstones’ natural shape variability, capturing the observed distribution of triaxial ellipsoidal shapes. We also incorporate explicit, random tumbling of individual hailstones during their growth to simulate their free-falling behavior and the resultant changes in cross-sectional area (which affects growth by hydrometeor collection). These physical attributes are incorporated in calculating hailstones’ fall speeds, using either empirical relationships or analytical relationships based on each hailstone’s Best and Reynolds numbers. Options for drag coefficient modification are added to emulate hailstones’ rough surfaces (lobes), which then modifies their thermal energy and vapor exchange with the environment. We investigate how applying these physical assumptions about nonspherical hail to the Penn State hail growth trajectory model, coupled with Cloud Model 1 supercell simulations, impacts hail production and examine the reasons behind the resulting variability in hail statistics. The choice of hailstone size–mass relation and fall speed scheme have the strongest influence on hail sizes. Using nonspherical, tumbling hailstones reduces the number of large hailstones produced. Applying shape-specific thermal energy transfer coefficients subtly increases sizes; the effects of lobes vary depending on the fall speed scheme used. These physical assumptions, although adding complexity to modeling, can be parameterized efficiently and potentially used in microphysics schemes. Significance Statement In numerical modeling of hailstorms, we usually consider hailstones to be spherical to simplify calculations, but in nature, hailstones generally are not spheres and can be rather lumpy and have spikes. The purpose of this study is to examine how the model result would change when nonspherical hailstone shape is implemented. We examine the relationship between hailstone shape and physical processes during hail growth in effort to explain why these changes occur and offer insights on how nonspherical hailstone shape may be parameterized in bulk microphysics schemes.

Ігрові амплуа в баскетболі: функції та вимоги до гравців

In modern basketball, effective team play requires players in different positions to perform specialized functions that match their physical, technical and psychological attributes. Understanding these functions is crucial to the success of the team. Identifying the functions and requirements of players at different positions is key to the success of any basketball team. This allows you to create an effective strategy where each player can maximize his or her potential. Purpose of the study: to consider the functions of basketball players playing in certain positions and to determine the requirements for players of different playing roles in basketball. Research methods: theoretical analysis and generalization of scientific and methodological literature. Results of the study. The functions of basketball players playing at certain positions are characterized. The requirements for players of different playing roles in basketball are revealed: point guard, attacking guard, light forward, heavy forward, center. Conclusions. The functions of basketball players playing in different positions are determined by their roles and responsibilities on the court. The distribution of players by function is an important aspect of organizing team play in basketball. This distribution allows to achieve an organized and purposeful game, taking into account the individual capabilities of each player. The distribution of playing roles among players depends on their physical and psychological characteristics. The anthropometric data and skills of a player are taken into account when determining his role. However, it is also important to take into account the psychological characteristics of the player and his ability to cooperate with his teammates. It is necessary to clearly assign roles in the team in order to achieve success. Intragroup rivalry can have a negative impact on teamwork, so it is important that each player understands his own capabilities and has the ability to assess the capabilities of his partners. The requirements for players of different playing roles in basketball are their understanding of roles and responsibilities, ability to cooperate with partners, individual skill and ability to assess the situation on the court. This helps to effectively build a team that can succeed.

Design and assessment of an adapted absorber solar air collector tailored for sustainable drying applications

The design of a relevant solar air collector (SAC) is imperative to make the drying industries self-reliant and sustainable in terms of energy. However, the literature doesn’t describe the coherent design assessment of SAC, and its viability for a drying system provided the scale-up opportunity for commercial applications. Hence, the present work was devoted to estimating the heat load for a particular drying condition, a methodological understanding of SAC design, and an investigation of the performance of the newly developed solar collector. The essential design criteria were the moisture content of fresh and intended dried items, physical attributes of items, dryer capacity, preferred drying temperature, projected drying duration, required air speed (based on dryer type), and local climate (solar radiation, ambient temperature and relative humidity). The regular semi-hexagonal shape aluminium (Al) sheet was chosen to introduce air turbulence while maximizing the surface area available for heat transfer. The regular semi-hexagonal absorber was outfitted with helical springs to generate air turbulence and augment heat transfer. A double glazing (polycarbonate) of 5 mm apart was mounted to impede radiation heat loss. Three successive days of the experimental study showed that the average temperature increases of air passing through SAC were 36.02 °C, 37 °C, and 39.2 °C. The optimal tilt angle with the horizontal surface was found to be 35° in a south-facing direction for the month of January. The highest energy efficiency was found to be 40.5 %, while the lowest was found to be 24.73 %. The sustainability index of the SAC was found to be 1.02. The experimental results clearly demonstrate that the designed SAC was capable of supplying adequate heat energy (at the minimum of 155.86 W/hr.) to meet the necessary heat load (125.82 W/hr.) for agro-products drying at the designed capacity.

A finite mixture distribution to model genetic architecture of image‐based oat grain morphology

AbstractThe multi‐floral oat (Avena sativa L.) inflorescence influences grain size and shape distributions, affecting the physical attributes of grain quality such as plumpness, size, and uniformity. While the grain size and shape distribution has been characterized as multi‐modal, very little is known about the genetic determinants of those distributions and their properties. The goal of this study was to model grain size and shape distribution using a finite mixture distribution approach and propose new distributional traits (i.e., emerging distributional traits) to characterize genotypes. We evaluated 47 oat genotypes in four highly replicated field experiments. Grains of three panicles per plot were individually threshed and scanned. Grain area, length, width, and roundness were obtained from each grain‐based image, while emerging distributional traits were evaluated using a finite mixture distribution approach. Finally, grain size distributions from hand‐threshed panicles (representing the full biological distribution) were compared with the grain size distributions of grains harvested with a combine harvester representing commercial harvest where small grains may be blown out. The heritability of all grain traits was high (0.89–0.94), and trait distributions differed among genotypes. Grain area and length show bi‐ and trimodal distributions, while grain width and roundness are uni‐ and bimodal. Although the full biological distribution of grains differed from the combine‐harvested grains, their genetic correlations were high, suggesting the combine‐harvested distributions can be used as a proxy for full biological distributions. This study proposes a straightforward methodological approach to model grain attributes that can aid in quality evaluations for genetic studies, breeding decisions, and industry characterization.

Enhancing Streamflow Prediction in Ungauged Basins Using a Nonlinear Knowledge‐Based Framework and Deep Learning

AbstractIn hydrology, a fundamental task involves enhancing the predictive power of a model in ungagged basins by transferring information on physical attributes and hydroclimate dynamics from gauged basins. Introducing an integrated nonlinear clustering framework, this study aims to develop a comprehensive framework that augments predictive performance in basins where direct measurements are sparse or absent. In this framework, uniform manifold approximation and projection (UMAP) is used as a nonlinear method to extract the essential features embedded in hydro‐climatological attributes and physical properties. Then, the Growing Neural Gas (GNG) clustering model is used to find the basins that potentially share similar hydro‐climatological behaviors. Besides UMAP‐GNG, the integration of Principal Component Analysis (PCA) as a linear method to reduce dimensionality with common clustering methods are also assessed to serve as benchmarks. The results reveal that the combination of clustering algorithms with the PCA method may lead to loss of information while the nonlinear method (UMAP) can extract more informative features. The efficacy of the proposed framework is assessed across the Contiguous United States (CONUS) by training a single Base Model using long short‐term memory (LSTM) for the centroids of all clusters and then, fine‐tuning the model on the centroids of each cluster separately to create a regional model. The results indicate that using the information extracted by the UMAP‐GNG method to guide a Base Model can significantly improve the accuracy in most of the clusters and enhance the median prediction accuracy within different clusters from 0.04 to 0.37 of KGE in ungauged basins.

Physical Training Methods to Improve the Physical Condition Components of Elite Taekwondo Athletes in The Kyorugi Category: A Systematic Review

Objectives. The study aimed to provide a systematic review of physical training methods to improve the physical condition components of elite taekwondo athletes in the kyorugi category. Materials and methods. An extensive literature assessment of earlier research was carried out. The objective was to examine articles published between 2020 and 2024 that describe strategies for improving the physical condition component of taekwondo athletes. The electronic search was conducted using Google Scholar, PubMed, Web of Science, and Scopus. The articles that addressed methods for enhancing physical condition through exercise were compiled. Results. Sixty publications used training approaches to enhance the physical condition component of elite taekwondo athletes in the kyorugi category. Based on the physical state that is assessed and improved, items are categorized. Among the physical training methods that can be applied in the Taekwondo category of kyorugi are plyometric training, circuit training methods, speed, agility, and quickness (SAQ) training; strength training, endurance training, flexibility training, reaction training, power training, coordination training, balance training, resistance training, and functional training. Conclusions. After thorough analysis, several training techniques have been shown to be effective in enhancing the physical attributes of elite taekwondo athletes in the kyorugi category. These attributes include flexibility, response, strength, power, coordination, agility, speed, balance, and VO₂max.

1D/2D Heterostructures: Synthesis and Application in Photodetectors and Sensors

Two-dimensional (2D) semiconductor components have excellent physical attributes, such as excellent mechanical ductility, high mobility, low dielectric constant, and tunable bandgap, which have attracted much attention to the fields of flexible devices, optoelectronic conversion, and microelectronic devices. Additionally, one-dimensional (1D) semiconductor materials with unique physical attributes, such as high surface area and mechanical potency, show great potential in many applications. However, isolated 1D and 2D materials often do not meet the demand for multifunctionality. Therefore, more functionality is achieved by reconstructing new composite structures from 1D and 2D materials, and according to the current study, it has been demonstrated that hybrid dimensional integration yields a significant enhancement in performance and functionality, which is widely promising in the field of constructing novel electronic and optoelectronic nanodevices. In this review, we first briefly introduce the preparation methods of 1D materials, 2D materials, and 1D/2D heterostructures, as well as their advantages and limitations. The applications of 1D/2D heterostructures in photodetectors, gas sensors, pressure and strain sensors, as well as photoelectrical synapses and biosensors are then discussed, along with the opportunities and challenges of their current applications. Finally, the outlook of the emerging field of 1D/2D heterojunction structures is given.

A Computational Model for Water Quality Analysis and Assessment in Tanzania

Research on water quality has received much attention in both developing and developed countries. This is because of the fact that, the effects of poor quality of water are detrimental to human beings, animals and the environment. This study is about a computational model for water quality analysis and assessment in Tanzania. Water quality can be understood as the measure of suitability of water based on physical, chemical and biological attributes. Water quality analysis and assessment face several challenges due to population growth, urban land use, agricultural activities, and industrialization. Besides, attempts have been made by the scholars to address the challenges. However, the tools used like titrimetric, electrometric, pH-meter, thermometer and turbidity meter are yet to come up with effective solutions. Because of these, the researcher was compelled to adopt computational model which uses Statistical Analysis System (SAS) software in order to come up with effective solutions concerning water quality analysis and assessment. In this study therefore, the secondary data were collected from Lake Victoria littoral stations under the auspices of the Ministry of Water in Tanzania with the objective to get sufficient information concerning water quality analysis and assessment. Additionally, the collected data were coded in SAS software to analyse independent and dependent variables. SAS software therefore, was employed to obtain central tendency and dispersion as benchmarks in determining quality of water. Also, the Multivariate Linear Regression Model was run to obtain coefficients of estimation, 95% confident limits and p-value. Statistical findings from central tendency and dispersion indicate that, the mean for potential of Hydrogen (pH) was 8.165; for total suspended solids was 3.065 mg/l; chloride displayed a mean of 6.494 mg/l; calcium displayed a mean of 6.421 mg/l; iron had a mean of 0.188 mg/l; magnesium displayed a mean of 3.331 mg/l and sulphate had mean of 2.326 mg/l. Looking closely at all of the above-mentioned water quality parameters, they all align with a Tanzania Bureau of Standards (TBS) and World Health Organization (WHO) as shown on table 1. Findings from the Multivariate linear regression model shows that: First, iron had a p-value of 0.0153, magnesium 0.0347 and total hardness had a p-value of 0.001. All of these were statistically significant in the analysis and assessment of water quality as shown on table 2. The study concludes that, the water quality in Lake Victoria complies with both TBS and WHO standards as explained above.

Adolescent well-being in time of crisis: The role of social and residential contexts

Abstract Background It is unknown whether social or residential context during the COVID-19 lockdowns may impact mental well-being. We identified classes of each of social and residential context during the lockdown and examined their associations with mental well-being among French adolescents one-year after the first lockdown. Methods We used data collected in a cross-sectional study design in 2021 from 387 adolescents ages 12 to 15 years enrolled in the school-based pilot study for EXIST. Participants reported social and residential characteristics during the lockdown retrospectively, and current mental well-being in self-report questionnaires. We used latent class analysis to identify classes of social and residential contexts, and linear regression models to study their association with mental well-being. Results Four social context classes were identified: class 1 ‘Low opportunities for social contacts at home’, class 2 ‘Moderate opportunities for social contact at home”, class 3 ‘High opportunities for social contact at home’, and class 4 ‘Very high opportunities for social contact at home’. Compared to class 4, lower levels of mental well-being were observed among adolescents in class 1 (b= -4.08, 95% CI [-8.06; -0.10]) one year after the lockdown. We identified four residential context classes, with differences across classes in proximity to nature, type of residence (e.g., apartment, house), and level of neighborhood deprivation. No association was found between residential context during the lockdown and adolescent mental well-being one year later. Conclusions An unsupportive social environment during the lockdown may have long-term effects on mental well-being among adolescents. Given the observed disparities in social support, future intervention should aim to strengthen social support for adolescents living in unsupportive environments (e.g., remote homework assistance, support for isolated parents, provision of virtual chat rooms for adolescents). Key messages • Mental well-being was challenged among youth with lower levels of social connectedness and support during lockdown, residential context was not associated with adolescent well-being after one year. • During crisis, a critical need among adolescents does not pertain to the physical attributes of their living environment, but rather to social support from friends or family within and outside home.

Unsaturated Strength of a Compacted Latosol Considering Physical and Dielectric Attributes

Unsaturated Strength of a Compacted Latosol Considering Physical and Dielectric Attributes

Technosols Made from Iron Mine Tailings and Construction and Demolition Waste as an Alternative for Sustainable Solid Waste Management

ABSTRACTBrazil faces urgent environmental challenges due to large waste production from mining and construction activities particularly regarding the disposal and management of the solid waste generated by these activities. The extraction of iron ore and the storage of tailings in dams, most of which are at imminent risk of rupture, represent foretold environmental disasters. Additionally, the disposal of construction waste raises environmental concerns due to the decreasing vailability of inert landfill space. To address these challenges, we evaluated the potential of Technosols made from construction and demolition waste (CDW) and iron mining tailing (IMT) in different proportions (60:40, 70:30, 80:20, and 100% of IMT and CDW, respectively) to support grass development. The Technosols were compared to a natural soil (Haplic Ferralsol). The soils were cultivated with Urochloa brizantha cv. Marandu in a field experiment conducted for 120 days. At the end of experiment, soil samples were collected and analyzed their chemical, physical, and mineralogical attributes, while plants were analyzed for dry biomass. Plants cultivated in Technosols exhibited dry biomass production 3.3‐fold (825 ± 270 g) greater than those cultivated in the natural soil (251 ± 77 g). Higher biomass production in the Technosols, especially in the TEC70:30, was associated with the favorable chemical conditions of these soils, such as slightly neutral pH (~7.5), higher cation exchange capacity (68.1 ± 12.4 mmol dm−3) and nutrient availability, especially Ca and P (57.8 ± 0.8 and 28.2 ± 0.4 mmol dm−3, respectively). These results aim to provide insights for the effective use of different Technosols in mitigating environmental impacts and promoting sustainable land and waste management practices, primarily to prevent future environmental disasters.

Visible-Photo-Assisted Phase Switching of Antiferroelectric-to-Ferroelectric Orders in an I3 --Intercalated 2D Perovskite.

Antiferroelectric (AFE) has emerged as a promising branch of electroactive materials, due to intriguing physical attributes stemming from the electric field-induced antipolar-to-polar phase transformation. However, the requirement of extremely high electric field strength to switch adjacent sublattice polarization poses great challenges for exploiting new molecular AFE system. Although photoirradiation is striking as a noncontact and nondestructive manipulation tool to optimize physical properties, optical control of antiferroelectricity still remains unexplored. Here, by adopting light-sensitive I3 - anion into 2D perovskite family, we design a new I3 --intercalated molecular AFE of (t-ACH)2EA2Pb3I10(I3)0.5 ⋅ ((H3O)(H2O))0.5 (1, t-ACH=trans-4-aminomethyl-1-cyclohexanecarboxylate, EA=ethylammonium). The I3 --intercalating gives an ultra-narrow band gap of 1.65 eV with strong absorption. In term of AFE structure, the anti-parallel alignment of electric dipoles results in a large spontaneous polarization of 4.3 μC/cm2. Strikingly, 1 merely shows AFE behaviour in the dark even under ultrahigh voltage, while the field-induced ferroelectric state can be facilely obtained upon visible illumination. Such unprecedented visible-photo-assisted phase switching ascribes to the incorporation of photoactive I3 - anions that reduces AFE-to-ferroelectric switching barrier. This pioneering work on the photo-assisting transformation of ferroic orders paves a way to develop future photoactive materials with potential applications.

Visible‐Photo‐Assisted Phase Switching of Antiferroelectric‐to‐Ferroelectric Orders in an I3−‐Intercalated 2D Perovskite

AbstractAntiferroelectric (AFE) has emerged as a promising branch of electroactive materials, due to intriguing physical attributes stemming from the electric field‐induced antipolar‐to‐polar phase transformation. However, the requirement of extremely high electric field strength to switch adjacent sublattice polarization poses great challenges for exploiting new molecular AFE system. Although photoirradiation is striking as a noncontact and nondestructive manipulation tool to optimize physical properties, optical control of antiferroelectricity still remains unexplored. Here, by adopting light‐sensitive I3− anion into 2D perovskite family, we design a new I3−‐intercalated molecular AFE of (t‐ACH)2EA2Pb3I10(I3)0.5 ⋅ ((H3O)(H2O))0.5 (1, t‐ACH=trans‐4‐aminomethyl‐1‐cyclohexanecarboxylate, EA=ethylammonium). The I3−‐intercalating gives an ultra‐narrow band gap of 1.65 eV with strong absorption. In term of AFE structure, the anti‐parallel alignment of electric dipoles results in a large spontaneous polarization of 4.3 μC/cm2. Strikingly, 1 merely shows AFE behaviour in the dark even under ultrahigh voltage, while the field‐induced ferroelectric state can be facilely obtained upon visible illumination. Such unprecedented visible‐photo‐assisted phase switching ascribes to the incorporation of photoactive I3− anions that reduces AFE‐to‐ferroelectric switching barrier. This pioneering work on the photo‐assisting transformation of ferroic orders paves a way to develop future photoactive materials with potential applications.

Metallic nanoparticles: a promising novel therapeutic tool against antimicrobial resistance and spread of superbugs.

In recent years, antimicrobial resistance (AMR) has become an alarming threat to global health as notable increase in morbidity and mortality has been ascribed to the emergence of superbugs. The increase in microbial resistance because of harboured or inherited resistomes has been complicated by the lack of new and effective antimicrobial agents, as well as misuse and failure of existing ones. These problems have generated severe and growing public health concern, due to high burden of bacterial infections resulting from scarce financial resources and poor functioning health systems, among others. It is therefore, highly pressing to search for novel and more efficacious alternatives for combating the action of these super bacteria and their infection. The application of metallic nanoparticles (MNPs) with their distinctive physical and chemical attributes appears as promising tools in fighting off these deadly superbugs. The simple, inexpensive and eco-friendly model for enhanced biologically inspired MNPs with exceptional antimicrobial effect and diverse mechanisms of action againsts multiple cell components seems to offer the most promising option and said to have enticed many researchers who now show tremendous interest. This synopsis offers critical discussion on application of MNPs as the foremost intervening strategy to curb the menace posed by the spread of superbugs. As such, this review explores how antimicrobial properties of the metallic nanoparticles which demonstrated considerable efficacy against several multi-drugs resistant bacteria, could be adopted as promising approach in subduing the threat of AMR and harvoc resulting from the spread of superbugs.

Assessment of Whole Grain Ancient Wheat Sourdough in Lyophilised and Native Forms for Cookie Formulation

This study explored the potential of two forms of sourdough—native and lyophilised—obtained through the spontaneous fermentation of whole grain flours from ancient wheat varieties, for cookie production. The research involved evaluated the dough’s rheological properties through creep and recovery measurements and Mixolab analysis, assessing proximate composition, physical attributes, texture, colour, and sensory characteristics using the Rate-all-that-apply (RATA) method. The rheological analysis revealed that native sourdough significantly impacted dough behaviour, making it more challenging to process. Although differences were observed in the proximate composition, colour, and texture, these factors did not influence the samples as much as the rheological parameters. Sensory evaluation identified Khorasan lyophilised sourdough, along with its control sample, as the most promising, while modern wheat, spelt, and emmer exhibited potentially undesirable attributes. Based on these findings, it was concluded that lyophilised Khorasan sourdough was very favourable for cookie production and should be considered for further in-depth research and development. This suggests that the lyophilised forms of ancient wheats could offer valuable alternatives for cookie formulation, with implications for both the processing and sensory attributes of the final product.