bluuebunny/crossref_metadata_2025 huggingface dataset:
Revisiting decade-old questions in proanthocyanidin biosynthesis: current understanding and new challenges
Authors: Lu Nan
Published: March 2024

Proanthocyanidins (PAs), one of the most abundant natural polymers found in plants, are gaining increasing attention because of their beneficial effects for agriculture and human health. The study of PA biosynthesis has been active for decades, and progress has been drastically accelerated since the discovery of key enzymes such as Anthocyanidin Reductase (ANR), Leucoanthocyanidin Reductase (LAR), and key transcription factors such as Transparent Testa 2 (TT2) and Transparent Testa 8 (TT8) in the early 2000s. Scientists raised some compelling questions regarding PA biosynthesis about two decades ago in the hope that addressing these questions would lead to an enhanced understanding of PA biosynthesis in plants. These questions focus on the nature of starter and extension units for PA biosynthesis, the stereochemistry of PA monomers and intermediates, and how and where the polymerization or condensation steps work subcellularly. Here, I revisit these long-standing questions and provide an update on progress made toward answering them. Because of advanced technologies in genomics, bioinformatics and metabolomics, we now have a much-improved understanding of functionalities of key enzymes and identities of key intermediates in the PA biosynthesis and polymerization pathway. Still, several questions, particularly the ones related to intracellular PA transportation and deposition, as well as enzyme subcellular localization, largely remain to be explored. Our increasing understanding of PA biosynthesis in various plant species has led to a new set of compelling open questions, suggesting future research directions to gain a more comprehensive understanding of PA biosynthesis.
Social representation of masculine and feminine sports among Saudi adolescents
Authors: Alsamih Munirah
Published: March 2024

Introduction

This study examined how certain sports are represented as masculine or feminine in Saudi adolescents, namely, which sports adolescents associate with males and which sports they associate with females. Previous research aligned with this concern was conducted within Western culture; however, there is a need to shed light on how the issues of social representation of masculine and feminine sports affect other cultures such as Middle Eastern cultures.

Methods

A survey was completed by 280 Saudi adolescents, aged between 12 and 17 (M = 13.5, SD = 1.3). The survey contained open-ended recall questions that asked participants to name three masculine, feminine, and natural sports.

Results

Most participants were familiar with using feminine and masculine terminology to describe sports, and nearly half had personally used gendered terms to describe sports. Overall, the participants generated 2,195 names of various sports, with the majority classified as natural (appropriate for both men and women), many masculine, and the fewest feminine.

Discussion

The connection between specific sports and masculinity or femininity can restrict the activities of adolescents who do not conform to traditional gender roles. Also, adolescents who are interested in sports that are not typically associated with their gender may experience social stigma or exclusion, which can discourage their participation. Therefore, it is important to establish inclusive environments in sports, regardless of the gender.
Exploring a practitioner-athlete relationship and facilitated learning throughout a psychological skills training program
Authors: Zhang Xiao , Rogers Morgan , Werthner Penny
Published: March 2024

Psychological skills training (PST) programs have been consistently reported as an important part of preparation for optimal performance in high performance sport. However, there is much less research about the quality and characteristics of the working relationship between a sport psychology practitioner (SPP) and an athlete and, importantly, how that relationship facilitates learning. Therefore, the purpose of the present paper was to explore the working relationship between a SPP and a volleyball player and how that working relationship facilitated the learning processes utilized by this player, as she prepared for the demands of her sport and life. An instrumental case study methodology with a qualitative description approach was employed to illustrate different aspects of the evolving relationship and the athlete’s experiences. The results of this case reflect an approach that combined features of both a directive approach in teaching specific psychological skills and a less directive and more collaborative approach, which, in turn, allowed an athlete to begin to learn how to guide their own learning.
Developing a scale to explore self-regulatory approaches to assessment and feedback with academics in higher education
Authors: Evans Carol , Kay William , Amici-Dargan Sheila , González Rafael De Miguel , Donert Karl , Rutherford Stephen
Published: March 2024

Introduction

Students need to acquire high level self-regulatory skills if they are to be successful within higher education, and academics need support in facilitating this. In this article we explore how the current research gap between knowledge of self-regulatory assessment and feedback (SRAF) practices, and academics’ professional training in it can be bridged.

Methods

SRAF tools were used with academics to explore their understandings of and training needs in SRAF; central to this work was the development of a SRAF scale. We consider the value of such tools in supporting academics’ professional development needs in SRAF. The reliability and validity of the SRAF scale was tested using exploratory factor analyses (EFA).

Results

Iterative EFA resulted in a 17 item support required SRAF scale (SR). Two underpinning factors:Creating the Conditions for SRAF, andSupporting Students’ SRAF Skills Developmentwere identified. The reliability of the instrument supported its primary use as a tool to facilitate academics’ professional development in fostering students’ self-regulatory skills.

Discussion

Our findings highlight the importance of supporting academics in developing strategies to maximize students’ metacognitive skills and motivation in assessment and feedback, contingent on effective assessment design. Such professional development needs to be mindful of individual and contextual factors impacting academics’ access to, and confidence and competence in, using SRAF in practice. This research is important in highlighting potential disconnects between where academics’ focus their attention in assessment, and what is known to have most impact on student learning success. The SRAF tools have considerable potential in supporting translation of theory into practice as part of sustained professional development for academics in higher education.
Investigating machine learning and natural language processing techniques applied for detecting eating disorders: a systematic literature review
Authors: Merhbene Ghofrane , Puttick Alexandre , Kurpicz-Briki Mascha
Published: March 2024

Recent developments in the fields of natural language processing (NLP) and machine learning (ML) have shown significant improvements in automatic text processing. At the same time, the expression of human language plays a central role in the detection of mental health problems. Whereas spoken language is implicitly assessed during interviews with patients, written language can also provide interesting insights to clinical professionals. Existing work in the field often investigates mental health problems such as depression or anxiety. However, there is also work investigating how the diagnostics of eating disorders can benefit from these novel technologies. In this paper, we present a systematic overview of the latest research in this field. Our investigation encompasses four key areas: (a) an analysis of the metadata from published papers, (b) an examination of the sizes and specific topics of the datasets employed, (c) a review of the application of machine learning techniques in detecting eating disorders from text, and finally (d) an evaluation of the models used, focusing on their performance, limitations, and the potential risks associated with current methodologies.
Depression and hepatobiliary diseases: a bidirectional Mendelian randomization study
Authors: Kong Yu , Yao Zhongcai , Ren Lingli , Zhou Liqin , Zhao Jinkai , Qian Yuanyuan , Lou Dayong
Published: March 2024

Background

More and more evidence suggests a close association between depression and hepatobiliary diseases, but its causal relationship is not yet clear.

Method

Using genome-wide association studies (GWAS) to summarize data, independent genetic variations associated with depression were selected as instrumental variables. Firstly, we designed a univariate Mendelian randomization (UVMR) analysis with two samples and simultaneously conducted reverse validation to evaluate the potential bidirectional causal relationship between depression and various hepatobiliary diseases. Secondly, we conducted a multivariate Mendelian randomization (MVMR) analysis on diseases closely related to depression, exploring the mediating effects of waist to hip ratio, hypertension, and daytime nap. The mediating effects were obtained through MVMR. For UVMR and MVMR, inverse variance weighted method (IVW) is considered the most important analytical method. Sensitivity analysis was conducted using Cochran’Q, MR Egger, and Leave-one-out methods.

Results

UVMR analysis showed that depression may increase the risk of non-alcoholic fatty liver disease (OR, 1.22; 95% CI, 1.03-1.46; p=0.0248) in liver diseases, while depression does not increase the risk of other liver diseases; In biliary and pancreatic related diseases, depression may increase the risk of cholelithiasis (OR, 1.26; 95% CI, 1.05-1.50; p=0.0120), chronic pancreatitis (OR, 1.61; 95% CI, 1.10-2.35; p=0.0140), and cholecystitis (OR, 1.23; 95% CI, 1.03-1.48; p=0.0250). In addition, through reverse validation, we found that non-alcoholic fatty liver disease, cholelithiasis, chronic pancreatitis, cholecystitis, or the inability to increase the risk of depression (p>0.05). The waist to hip ratio, hypertension, and daytime nap play a certain role in the process of depression leading to non-alcoholic fatty liver disease, with a mediating effect of 35.8%.

Conclusion

Depression is a susceptibility factor for non-alcoholic fatty liver disease, and the causal effect of genetic susceptibility to depression on non-alcoholic fatty liver disease is mediated by waist-hip ratio, hypertension, and daytime nap.
Is there evidence for factorial invariance of the COVID Stress Scales? an analysis of North American and cross-cultural populations
Authors: Boehme Blake A. E. , Kinsman Laura , Taylor Steven , Asmundson Gordon J. G.
Published: March 2024

The COVID-19 pandemic impacted the mental health of more citizens globally than any previous modern viral outbreak. In response to the psychological challenges associated with COVID-19, the COVID Stress Scales (CSS) were developed to assess the presence and severity of COVID-related distress. The initial North American validation study of the CSS identified that the scale comprised five factors: danger and contamination fears, fear of socioeconomic consequences, xenophobia, checking and reassurance seeking, and traumatic stress symptoms. The CSS have since been validated across a multitude of international populations. However, findings support a five- and six-factor model. Methodological issues make interpreting most studies supporting a five-factor model challenging. The purpose of this study was to re-evaluate the factor structure of the CSS using data from North American samples, to assess for potential factorial invariance, and compare these results to cross-cultural findings. Multiple confirmatory factor analyses (mCFA) were conducted across 28 different groups (e.g., age, ethnicity/race, sex) from two large independent North American samples from 2020 (n = 6827) and 2021 (n = 5787), assessing the fit indices of the five-, six-, and alternative-factor model of the CSS. The current results provide evidence for factorial invariance of the six-factor model of the CSS across different North American demographics and highlight potential challenges in interpreting the results of studies that have supported a five-factor model of the CSS.
Single and combined association between brominated flame retardants and cardiovascular disease: a large-scale cross-sectional study
Authors: Yin Wenhao , Xu Rui , Zou Jiyu , Wang Yaqin , Zhang Yan
Published: March 2024

Introduction

The single and combined association between brominated flame retardants (BFRs) and cardiovascular diseases (CVD) has remained unelucidated. This research aimed at exploring the associations between mixture of BFRs and CVD.

Methods

This research encompassed adult participants from the National Health and Nutrition Examination Survey in 2005–2016. The weighted quantile sum (WQS) model and quantile g-computation (QGC) model were applied to examine the combined effects of BFRs mixture on CVD.

Results

In this research, overall 7,032 individuals were included. In comparison with the lowest quartile, the highest quartile of PBB153 showed a positive association with CVD, with odds ratio (OR) values and 95% confidence intervals (CI) of 19.2 (10.9, 34.0). Furthermore, the acquired data indicated that PBB153 (OR: 1.23; 95% CI: 1.02, 1.49), PBB99 (OR: 1.29; 95% CI: 1.06, 1.58), and PBB154 (OR: 1.29; 95% CI: 1.02, 1.63) were linked to congestive heart failure. PBB153 was also related to coronary heart disease (OR: 1.29; 95% CI: 1.06, 1.56). Additionally, a positive correlation between the BFRs mixture and CVD (positive model: OR: 1.23; 95% CI: 1.03, 1.47) was observed in the weighted quantile sum (WQS) model and the quantile g-computation (QGC) model.

Discussion

Therefore, exposure to BFRs has been observed to heighten the risk of cardiovascular disease in US adults, particularly in the case of PBB153. Further investigation is warranted through a large-scale cohort study to validate and strengthen these findings.
Modeling sediment concentrations and loads for two small agricultural watersheds in Prince-Edward-Island (Canada): present conditions and a future scenario
Authors: Bée Simon , St-Hilaire André , van den Heuvel Michael
Published: March 2024

The degradation of soils and its detrimental consequences on aquatic environments is an important research topic in agricultural regions such as Prince Edward Island (PEI, Canada). Enhanced information related to suspended sediments in watercourses can serve as an effective decision-making tool in agricultural land management. This study aims to compare flow, suspended sediment concentrations (SSC), and loads using the Soil and Water Assessment Tool (SWAT) in two watersheds in Prince Edward Island (PEI). The final investigations will focus on the potential variations in hydrological and sedimentary values in the future using a relatively pessimistic climate change scenario. Finally, the projected sediment concentrations and loads will be analyzed, considering their potential impacts on ecosystems. Water level and turbidity were recorded using two water level loggers and two optical backscatter sensors (OBS) deployed in the Tuplin Creek and Spring Valley watersheds. These instruments continuously recorded suspended sediments and flow data from June 2021 to September 2022. The data were used to manually calibrate the hydrological and suspended sediment models. The understanding of sediment loads and the benefits of proposed changes to agricultural practices can be tested with the SWAT model, as it incorporates a land use index that varies spatially and temporally. Calibration and validation of both the hydrological and sediment models were satisfactory, with Kling-Gupta Efficiency coefficients varying between 0.51 and 0.73 and Nash-Sutcliffe coefficients varying between 0.61 and 0.73 respectively, indicating successful simulation of both variables in an agricultural context in spite of relatively short calibration and validation periods. Under the selected climate change scenario (RCP 8.5), daily flows and suspended sediment concentrations were simulated until 2,100, showing a slight increase in the average suspended sediment concentration (CSS). For Tuplin Creek, extremely high sediment peaks (>1,500 mg/L) could become significantly more frequent, potentially causing more frequent and severe ecosystem disturbances according to the simulations.
Changes in the mechanical properties of the thigh and lower leg muscle-tendon units during the early follicular and early luteal phases
Authors: Saito Rina , Shagawa Mayuu , Sugimoto Yuzuka , Hirai Tomoki , Kato Koyo , Sekine Chie , Yokota Hirotake , Hirabayashi Ryo , Ishigaki Tomonobu , Akuzawa Hiroshi , Togashi Ryoya , Yamada Yuki , Osanami Haruki , Edama Mutsuaki
Published: March 2024

Background

This study aimed to determine changes in the muscle and tendon stiffness of the thigh and lower leg muscle-tendon units during the early follicular and early luteal phases, and check for possible relations between muscle and tendon stiffness in each phase.

Methods

The sample consisted of 15 female university students with regular menstrual cycles. The basal body temperature method, ovulation kit, and salivary estradiol concentration measurement were used to estimate the early follicular and early luteal phases. A portable digital palpation device measured muscle-tendon stiffness in the early follicular and early luteal phases. The measurement sites were the rectus femoris (RF), vastus medialis (VM), patellar tendon (PT), medial head of gastrocnemius muscle, soleus muscle, and Achilles tendon.

Results

No statistically significant differences in the thigh and lower leg muscle-tendon unit stiffness were seen between the early follicular and early luteal phases. Significant positive correlations were found between the stiffness of the RF and PT (r = 0.608, p = 0.016) and between the VM and PT (r = 0.737, p = 0.002) during the early luteal phase.

Conclusion

The present results suggest that the stiffness of leg muscle-tendon units of the anterior thigh and posterior lower leg do not change between the early follicular and early luteal phases and that tendons may be stiffer in those women who have stiffer anterior thigh muscles during the early luteal phase.
Millet production, challenges, and opportunities in the Asia-pacific region: a comprehensive review
Authors: Harish M. S. , Bhuker Axay , Chauhan Bhagirath Singh
Published: March 2024

Global warming, water scarcity, population growth, rising food prices, urbanization, and other socio-economic factors pose significant threats to agriculture and food security in the 21st century. This situation is particularly grave for low-income individuals in the Asia-Pacific region. To tackle this challenge and eradicate hunger and poverty, it is imperative for scientists to explore alternative food sources, covering all stages from production through processing to consumption. Cereal grains serve as a crucial food source and hold substantial importance in human diets. Therefore, revamping the food system becomes crucial to achieve food and nutritional security. A pragmatic approach toward reaching this goal involves ensuring universal access to affordable, wholesome, and nourishing food through the utilization of millets—nutrient-dense grains (often referred to as Nutri-cereals) that offer a rich array of vital macronutrients, micronutrients, carbohydrates, protein, dietary fiber, lipids, and phytochemicals. Leveraging these grains holds the potential to significantly alleviate the challenges of food insecurity and malnutrition. Millet, a drought-resistant grain, constitutes a primary source of carbohydrates and proteins for populations residing in semi-arid regions of Africa and Asia. Given its crucial contribution to national food security and potential health advantages, there is a growing focus among food scientists. Additionally, the United Nations designated 2023 as the International Year of Millet, underscoring its importance. This article delves into various methods of production and processing, highlighting opportunities to enhance the production and nutritional qualities of millet. We attribute millets to inadequate rainfall distribution, poor crop management high prices of farm inputs such as fertilizer and pesticides and low adoption of improved varieties by the farmers. It also outlines the constraints, challenges, and future prospects associated with promoting millet as a viable food source for the burgeoning population. Despite the promise that millets hold, they have not received adequate research attention. Therefore, increased research efforts on integrating genomics in genome-wide marker-trait association are imperative, encompassing germplasm collection, protection, evaluation, consumption patterns, development of high-yielding cultivars, processing techniques, and policy interventions. Such initiatives are necessary to bolster the cultivation of millets and harness their potential to address the escalating global food challenge.
Building an adverse outcome pathway network for estrogen-, androgen- and steroidogenesis-mediated reproductive toxicity
Authors: Zilliacus Johanna , Draskau Monica K. , Johansson Hanna K. L. , Svingen Terje , Beronius Anna
Published: March 2024

Introduction: Adverse Outcome Pathways (AOPs) can support both testing and assessment of endocrine disruptors (EDs). There is, however, a need for further development of the AOP framework to improve its applicability in a regulatory context. Here we have inventoried the AOP-wiki to identify all existing AOPs related to mammalian reproductive toxicity arising from disruption to the estrogen, androgen, and steroidogenesis modalities. Core key events (KEs) shared between relevant AOPs were also identified to aid in further AOP network (AOPN) development.

Methods: A systematic approach using two different methods was applied to screen and search the entire AOP-wiki library. An AOPN was visualized using Cytoscape. Manual refinement was performed to remove AOPS devoid of any KEs and/or KERs.

Results: Fifty-eight AOPs relevant for mammalian reproductive toxicity were originally identified, with 42 AOPs included in the final AOPN. Several of the KEs and KE relationships (KERs) described similar events and were thus merged to optimize AOPN construction. Sixteen sub-networks related to effects on hormone levels or hormone activity, cancer outcomes, male and female reproductive systems, and overall effects on fertility and reproduction were identified within the AOPN. Twenty-six KEs and 11 KERs were identified as core blocks of knowledge in the AOPN, of which 19 core KEs are already included as parameters in current OECD and US EPA test guidelines.

Discussion: The AOPN highlights knowledge gaps that can be targeted for further development of a more complete AOPN that can support the identification and assessment of EDs.
Fuzzy Modeling Framework Using Sector Non-Linearity Techniques for Fixed-Wing Aircrafts
Authors: Brusola Pablo , Garcia-Nieto Sergio , Salcedo Jose Vicente , Martinez Miguel , Bishop Robert H.
Published: March 2024

This paper presents a mathematical modeling approach utilizing a fuzzy modeling framework for fixed-wing aircraft systems with the goal of creating a highly desirable mathematical representation for model-based control design applications. The starting point is a mathematical model comprising fifteen non-linear ordinary differential equations representing the dynamic and kinematic behavior applicable to a wide range of fixed-wing aircraft systems. Here, the proposed mathematical modeling framework is applied to the AIRBUS A310 model developed by ONERA. The proposed fuzzy modeling framework takes advantage of sector non-linearity red techniques to recast all the non-linear terms from the original model to a set of combined fuzzy rules. The result of this fuzzification is a more suitable mathematical description from the control system design point of view. Therefore, the combination of this fuzzy model and the wide range of control techniques available in the literature for such kind of models, like parallel and non-parallel distributed compensation control laws using linear matrix inequality optimization, enables the development of control algorithms that guarantee stability conditions for a wide range of operations points, avoiding the classical gain scheduling schemes, where the stability issues can be extremely challenging.
Using a Hybrid Convolutional Neural Network with a Transformer Model for Tomato Leaf Disease Detection
Authors: Chen Zhichao , Wang Guoqiang , Lv Tao , Zhang Xu
Published: March 2024

Diseases of tomato leaves can seriously damage crop yield and financial rewards. The timely and accurate detection of tomato diseases is a major challenge in agriculture. Hence, the early and accurate diagnosis of tomato diseases is crucial. The emergence of deep learning has dramatically helped in plant disease detection. However, the accuracy of deep learning models largely depends on the quantity and quality of training data. To solve the inter-class imbalance problem and improve the generalization ability of the classification model, this paper proposes a cycle-consistent generative-adversarial-network-based Transformer model to generate diseased tomato leaf images for data augmentation. In addition, this paper uses a Transformer model and densely connected CNN architecture to extract multilevel local features. The Transformer module is utilized to capture global dependencies and contextual information accurately to expand the sensory field of the model. Experiments show that the proposed model achieved 99.45% accuracy on the PlantVillage dataset. The 2018 Artificial Intelligence Challenger dataset and the private dataset attained accuracies of 98.30% and 95.4%, and the proposed classification model achieved a higher accuracy and smaller model size compared to previous deep learning models. The classification model is generalizable and robust and can provide a stable theoretical framework for crop disease prevention and control.
Deciphering the Genomic Characterization of the GGP Gene Family and Expression Verification of CmGGP1 Modulating Ascorbic Acid Biosynthesis in Melon Plants
Authors: Yang Tiantian , Amanullah Sikandar , Li Shenglong , Gao Peng , Bai Junyu , Li Chang , Ma Jie , Luan Feishi , Wang Xuezheng
Published: March 2024

Ascorbic acid (AsA), also known as vitamin C, is a well-known antioxidant found in living entities that plays an essential role in growth and development, as well as in defensive mechanisms. GDP-L-galactose phosphorylase (GGP) is a candidate gene regulating AsA biosynthesis at the translational and transcriptional levels in plants. In the current study, we conducted genome-wide bioinformatic analysis and pinpointed a single AsA synthesis rate-limiting enzyme gene in melon (CmGGP1). The protein prediction analysis depicted that the CmGGP1 protein does not have a signaling peptide or transmembrane structure and mainly functions in the chloroplast or nucleus. The constructed phylogenetic tree analysis in multispecies showed that the CmGGP1 protein has a highly conserved motif in cucurbit crops. The structural variation analysis of the CmGGP1 gene in different domesticated melon germplasms showed a single non-synonymous type-base mutation and indicated that this gene was selected by domestication during evolution. Wild-type (WT) and landrace (LDR) germplasms of melon depicted close relationships to each other, and improved-type (IMP) varieties showed modern domestication selection. The endogenous quantification of AsA content in both the young and old leaves of nine melon varieties exhibited the major differentiations for AsA synthesis and metabolism. The real-time quantitative polymerase chain reaction (qRT-PCR) analysis of gene co-expression showed that AsA biosynthesis in leaves was greater than AsA metabolic consumption, and four putative interactive genes (MELO3C025552.2, MELO3C007440.2, MELO3C023324.2, and MELO3C018576.2) associated with the CmGGP1 gene were revealed. Meanwhile, the CmGGP1 gene expression pattern was noticed to be up-regulated to varying degrees in different acclimated melons. We believe that the obtained results would provide useful insights for an in-depth genetic understanding of the AsA biosynthesis mechanism, aimed at the development of improving crop plants for melon.
Effects of Mechanical Vibration in Equine Osteoarthritis: A Pilot Study
Authors: Rinnovati Riccardo , Meistro Federica , Ralletti Maria Virginia , Marzari Francesca , Saragoni Giuditta , Gottarelli Roberto , Pasquotto Anna , Spadari Alessandro
Published: March 2024

The use of therapeutic ultrasounds (TUs) is widespread in both human and veterinary medicine. In fact, mechanical vibration is the simplest and purest form of vibratory energy that is applied either in physical therapies or in rehabilitation medicine. In particular, the use of low-frequency TUs to treat equine conditions is a new and evolving field. In the equine industry, osteoarthritis (OA) is one of the most challenging causes of lameness. Despite its prevalence and the advancements in its treatment, there is still no therapy whose results are completely decisive. Little is described in the literature about the use of TUs in horses’ joints, particularly regarding its use to treat OA. For these reasons, the aim of this study was to preliminarily assess the efficacy of low-frequency ultrasound in two horses with metacarpo/metatarso-phalangeal joint OA. The reduction in lameness was significant in both treated cases, pointing to the effective therapeutic action of TUs. However, to better evaluate the long-term effects in athlete horses, it is necessary to include in the research a greater number of cases and a control group.
Cascade-Forward, Multi-Parameter Artificial Neural Networks for Predicting the Energy Efficiency of Photovoltaic Modules in Temperate Climate
Authors: Postawa Karol , Czarnecki Michał , Wrzesińska-Jędrusiak Edyta , Łyskawiński Wieslaw , Kułażyński Marek
Published: March 2024

Solar energy is a promising and efficient source of electricity in countries with stable and high sunshine duration. However, in less favorable conditions, for example in continental, temperate climates, the process requires optimization to be cost-effective. This cannot be done without the support of appropriate mathematical and numerical methods. This work presents a procedure for the construction and optimization of an artificial neural network (ANN), along with an example of its practical application under the conditions mentioned above. In the study, data gathered from a photovoltaic system in 457 consecutive days were utilized. The data includes measurements of generated power, as well as meteorological records. The cascade-forward ANN was trained with a resilient backpropagation procedure and sum squared error as a performance function. The final ANN has two hidden layers with nine and six nodes. This resulted in a relative error of 10.78% and R2 of 0.92–0.97 depending on the data sample. The case study was used to present an example of the potential application of the tool. This approach proved the real benefits of the optimization of energy consumption.
Surface Roughness Evaluation of Pre- Versus Post-Crystallization Polish of Two High-Strength Silicate Ceramics for Chairside CAD/CAM Technology
Authors: Rea Felipe Tarosso , Valcanaia Andre , Herrera-Fierro Pilar , Verma Manish , Neiva Gisele de Faria
Published: March 2024

This in vitro study evaluated the surface roughness (Sa) of two high-strength silicate ceramics, lithium disilicate IPS e.max CAD, Ivoclar Vivadent (LDS group), and zirconia-reinforced lithium silicate Vita Suprinity, VITA Zahnfabrik (ZLS group). The surface roughness was investigated before and after milling using different polishing systems and timings relative to the final crystallization of the ceramics. Forty-eight samples per group were polished by a single calibrated operator using two polishing systems: Dialite LD (Brasseler) and Lithium Silicate Polishers (Meisinger) for the LDS group and Dialite LD (Brasseler) and Vita Suprinity Polishing Set Technical (VITA Zahnfabrik) for the ZLS group, both pre- and post-crystallization. Surface roughness was measured using a confocal laser microscope (OLS4000 LEXT/Olympus), with scanning electron microscopy (SEM) used to evaluate surface morphological changes. Significant differences in Sa values were found between baseline groups, with ZLS exhibiting lower values. All polishing methods significantly reduced surface roughness compared to baseline (p ≤ 0.05). No significant differences were found in LDS samples when polishing pre- or post-crystallization (p = 0.129), while for ZLS samples, post-crystallization polishing achieved significantly smoother surfaces (p < 0.001). The study concluded that the choice of polishing system and timing did not significantly affect surface roughness for LDS. However, it is recommended that post-crystallization polishing be performed for the optimal smoothness of ZLS. This study aimed to evaluate the post-milling polishing procedures of CAD/CAM high-strength restorations, emphasizing the importance of an optimal surface roughness to prevent issues such as increased risk of abrasion on opposing teeth, enhanced plaque adhesion, and mechanical failures. Investigating these polishing techniques enables clinicians to optimize clinical performance, thereby improving the quality and longevity of high-strength silicate ceramics.
Transient Analysis of a Selective Partial-Update LMS Algorithm
Authors: Siqueira Newton N. , Resende Leonardo C. , Andrade Fabio A. A. , Pimenta Rodrigo M. S. , Haddad Diego B. , Petraglia Mariane R.
Published: March 2024

In applications where large-order filters are needed, the computational load of adaptive filtering algorithms can become prohibitively expensive. In this paper, a comprehensive analysis of a selective partial-update least mean squares, named SPU-LMS-M-min, is developed. By employing the partial-update strategy for a non-normalized adaptive scheme, the designer can choose an appropriate number of update blocks considering a trade-off between convergence rate and computational complexity, which can result in a more than 40% reduction in the number of multiplications in some configurations compared to the traditional LMS algorithm. Based on the principle of minimum distortion, a selection criterion is proposed that is based on the input signal’s blocks with the lowest energy, whereas typical Selective Partial Update (SPU) algorithms use a selection criterion based on blocks with highest energy. Stochastic models are developed for the mean weights and mean and mean squared behaviour of the proposed algorithm, which are further extended to accommodate scenarios involving time-varying dynamics and suboptimal filter lengths. Simulation results show that the theoretical predictions are in good agreement with the experimental outcomes. Furthermore, it is demonstrated that the proposed selection criterion can be easily extended to active noise cancellation algorithms as well as algorithms utilizing variable filter length. This allows for the reduction of computational costs for these algorithms without compromising their asymptotic performance.
Polyphenol-Rich Extracts and Essential Oil from Egyptian Grapefruit Peel as Potential Antioxidant, Antimicrobial, and Anti-Inflammatory Food Additives
Authors: Ibrahim Faten Mohamed , Abdelsalam Eman , Mohammed Reda Sayed , Ashour Wedian El Sayed , Vilas-Boas Ana A. , Pintado Manuela , El Habbasha El Sayed
Published: March 2024

Grapefruit (GF) processing generates significant nutrient and economic losses due to the production of 50% by-products, primarily peels. GF peels are a rich and sustainable source of bioactive compounds (BCs), such as essential oils (EOs) and phenolic compounds. Thus, finding value-added solutions based on a circular economy is paramount. This research aims to assess the antioxidant, anti-inflammatory, and antimicrobial properties of a hydroethanolic polyphenol-rich extract from crude GF peels (GF-CE), essential oil (GF-EO), and polyphenol-rich extract from GF peels after essential oil extraction (GF-PE). The GF-CE and GF-PE showed high concentrations of naringenin (7.71 and 48.60 mg/g dry extract (DE)), narirutin (15.03 and 28.73 mg/g DE), and hesperidin (0.67 and 0.29 mg/mL), respectively. Extracting firstly EOs from GF improved the release of phenolic acids (p-coumaric, ferulic, and chlorogenic acid). The GF-CE exhibited stronger free radical scavenging activity mainly in DPPH (IC50 = 75.69 ± 0.81 µg/mL) than GF-EO (1271 ± 0.85 µg/mL) and GF-PE (113.45 ± 0.85 µg/mL). The GF-EO demonstrated moderate antimicrobial activity against Gram-positive bacteria compared to the reference standard (amoxicillin) and strong activity against the yeast Candida albicans (inhibition zone of 16 mm). The major compounds in the GF-EO included D-limonene (25%), nootkatone (24%), and β-pinene (8%). Both polyphenol-rich extracts showed promising activities as COX1 and COX2 inhibitors with IC50 values of 25 ± 0.1 and 0.28 ± 0.00 µg/mL (compared to celecoxib (97.5 ± 0.1 and 0.31 ± 0.01 µg/mL) and indomethacin (6.25 ± 0.00 and 0.52 ± 0.01 µg/mL) as the standards), respectively. The study concludes that GF peels are a valuable source of BCs with significant bioactivities, offering a sustainable multi-cascade approach to recovering value-added compounds from GF peels in alignment with circular economy principles and open opportunities as functional ingredients for food applications.
Performance Evaluation of Reconfiguration Policy in Reconfigurable Manufacturing Systems including Multi-Spindle Machines: An Assessment by Simulation
Authors: Renna Paolo
Published: March 2024

Reconfigurable manufacturing systems (RMSs) are extensively studied and employed to address demand uncertainties. RMS machines are designed to be modular and adaptable to changing requirements. A recent innovation is the introduction of multi-spindle reconfigurable machines (MRMTs). This study evaluates the impact of MRMTs’ introduction into an RMS, considering factors such as the number of MRMT machines and reconfiguration policies. A simulation model incorporating failures, process time variability, and part inter-arrival supports the analysis. The numerical results aid decision makers in determining the optimal RMS configuration with MRMTs. The simulation outcomes indicate that a balanced number of multi-spindle machines can significantly enhance performance compared with an unbalanced distribution.
Sparsity-Robust Feature Fusion for Vulnerable Road-User Detection with 4D Radar
Authors: Ruddat Leon , Reichardt Laurenz , Ebert Nikolas , Wasenmüller Oliver
Published: March 2024

Detecting vulnerable road users is a major challenge for autonomous vehicles due to their small size. Various sensor modalities have been investigated, including mono or stereo cameras and 3D LiDAR sensors, which are limited by environmental conditions and hardware costs. Radar sensors are a low-cost and robust option, with high-resolution 4D radar sensors being suitable for advanced detection tasks. However, they involve challenges such as few and irregularly distributed measurement points and disturbing artifacts. Learning-based approaches utilizing pillar-based networks show potential in overcoming these challenges. However, the severe sparsity of radar data makes detecting small objects with only a few points difficult. We extend a pillar network with our novel Sparsity-Robust Feature Fusion (SRFF) neck, which combines high- and low-level multi-resolution features through a lightweight attention mechanism. While low-level features aid in better localization, high-level features allow for better classification. As sparse input data are propagated through a network, the increasing effective receptive field leads to feature maps of different sparsities. The combination of features with different sparsities improves the robustness of the network for classes with few points.
Vegetation and Evapotranspiration Responses to Increased Atmospheric Vapor Pressure Deficit across the Global Forest
Authors: Wen Rihong , Qin Meiou , Jiang Peng , Yang Feiyun , Liu Bin , Zhu Mengyuan , Fang Yuan , Tian Yichen , Shang Bo
Published: March 2024

A forest is vulnerable to drought and plays important roles in the regulation of carbon and water cycling in a terrestrial ecosystem. Atmospheric vapor pressure deficit (VPD) has been identified as an increasingly major factor in plant functioning and has been established as a main contributor to recent drought-induced plant mortality, independent of other drivers associated with climate change. However, most previous studies have focused on the effects of climate warming and CO2 enrichment on vegetation growth, without considering the effects of an increased VPD on vegetation growth and evapotranspiration (ET) in forest ecosystems. This could lead to a large uncertainty in estimating the variability in forest carbon sinks. Based on the long-term satellite data, we investigated the response of the leaf area index (LAI) and ET to the VPD via a partial correlation analysis in this study. We also examined the temporal variability in the partial coefficients within a ten-year moving window. The results showed that over 50% of the region displayed a negative partial correlation between the LAI, ET, and VPD, and those pixels were mainly concentrated in North America and the plains of Eastern Europe. Regions with a negative trend of partial correlation in both the LAI and ET are mostly located in the plains of Eastern Europe and the Siberian Plain of western Russia, while the positive trend is mainly in South America. The plains of Eastern Europe are becoming drier, which was proved by the interannual trend of the Standardized Precipitation Evapotranspiration Index (SPEI) and soil water content (SWC). Additionally, the LAI and ET in those areas exhibited a significant positive correlation with the SWC based on the moving window average. This study suggests that the role of the VPD on vegetation will become increasingly prominent in the context of future climate change for the forest ecosystem.
Swollen Feet: Considering the Paradoxical Roles of Interleukins in Nephrotic Syndrome
Authors: Kovalik Maria E. , Dacanay Monique A. , Crowley Steven D. , Hall Gentzon
Published: March 2024

Interleukins are a family of 40 bioactive peptides that act through cell surface receptors to induce a variety of intracellular responses. While interleukins are most commonly associated with destructive, pro-inflammatory signaling in cells, some also play a role in promoting cellular resilience and survival. This review will highlight recent evidence of the cytoprotective actions of the interleukin 1 receptor (IL-1R)- and common gamma chain receptor (IL-Rγc)-signaling cytokines in nephrotic syndrome (NS). NS results from the injury or loss of glomerular visceral epithelial cells (i.e., podocytes). Although the causes of podocyte dysfunction vary, it is clear that pro-inflammatory cytokines play a significant role in regulating the propagation, duration and severity of disease. Pro-inflammatory cytokines signaling through IL-1R and IL-Rγc have been shown to exert anti-apoptotic effects in podocytes through the phosphoinositol-3-kinase (PI-3K)/AKT pathway, highlighting the potential utility of IL-1R- and IL-Rγc-signaling interleukins for the treatment of podocytopathy in NS. The paradoxical role of interleukins as drivers and mitigators of podocyte injury is complex and ill-defined. Emerging evidence of the cytoprotective role of some interleukins in NS highlights the urgent need for a nuanced understanding of their pro-survival benefits and reveals their potential as podocyte-sparing therapeutics for NS.
The Bidirectional Relationship between Weight Gain and Cognitive Function in First-Episode Schizophrenia: A Longitudinal Study in China
Authors: Ma Ke , Zhou Tianhang , Pu Chengcheng , Cheng Zhang , Han Xue , Yang Lei , Yu Xin
Published: March 2024

Patients with schizophrenia often encounter notable weight gain during their illness, heightening the risk of metabolic diseases. While previous studies have noted a correlation between obesity and cognitive impairment in schizophrenia, many were cross-sectional, posing challenges in establishing a causal relationship between weight gain and cognitive function. The aim of this longitudinal study is to examine the relationship between weight gain and cognitive function in patients with first-episode schizophrenia (FES) during the initial 6-month antipsychotic treatments. Employing linear and logistic regression analyses, the study involved 337 participants. Significantly, baseline scores in processing speed (OR = 0.834, p = 0.007), working memory and attention (OR = 0.889, p = 0.043), and executive function (OR = 0.862, p = 0.006) were associated with clinically relevant weight gain (CRW, defined as an increase in body weight > 7%) at the 6-month endpoint. On the other hand, CRW correlated with improvements in the Brief Visuospatial Memory Test (p = 0.037). These findings suggest that patients with lower baseline cognitive performance undergo more substantial weight gain. Conversely, weight gain was correlated with cognitive improvements, particularly in the domain of visual learning and memory. This suggested a potential bidirectional relationship between weight gain and cognitive function in first-episode schizophrenia patients.
Influence of Stress Severity on Contextual Fear Extinction and Avoidance in a Posttraumatic-like Mouse Model
Authors: Eyraud Noémie , Bloch Solal , Brizard Bruno , Pena Laurane , Tharsis Antoine , Surget Alexandre , El-Hage Wissam , Belzung Catherine
Published: March 2024

Posttraumatic stress disorder (PTSD) is a widespread fear-related psychiatric affection associated with fear extinction impairments and important avoidance behaviors. Trauma-related exposure therapy is the current first-hand treatment for PTSD, yet it needs to be improved to shorten the time necessary to reach remission and increase responsiveness. Additional studies to decipher the neurobiological bases of extinction and effects on PTSD-like symptoms could therefore be of use. However, a PTSD-like animal model exhibiting pronounced PTSD-related phenotypes even after an extinction training directly linked to the fearful event is necessary. Thus, using a contextual fear conditioning model of PTSD, we increased the severity of stress during conditioning to search for effects on extinction acquisition and on pre- and post-extinction behaviors. During conditioning, mice received either two or four electrical shocks while a control group was constituted of mice only exposed to the context. Stressed mice exhibited important fear generalization, high fear reaction to the context and selective avoidance of a contextual reminder even after the extinction protocol. Increasing the number of footshocks did not induce major changes on these behaviors.