The prevalence of obesity and eating disorders varies by sex, but the extent to which sex influences eating behaviors, especially in childhood, has received less attention. The purpose of this paper is to review the literature on sex differences in eating behavior in children and present new findings supporting the role of sex in child appetitive traits and neural responses to food cues. In children, the literature shows sex differences in basic taste response, food acceptance, eating self-regulation, and appetitive traits. New analyses demonstrate that sex interacts with child weight status to differentially influence appetitive traits and neural responses to food cues. Further, neuroimaging results suggest that obesity in female children is positively related to brain reactivity to higher-energy-dense food cues in regions involved with learning, memory, and object recognition, while the opposite was found in males. In addition to differences in how the brain processes information about food, other factors that may contribute to sex differences include parental feeding practices, societal emphasis on dieting, and peer influences. Future studies are needed to confirm these findings, as they may have implications for the development of effective intervention programs to improve dietary behaviors and prevent obesity.

This study investigates the emergence of ertapenem-resistant, meropenem-susceptible (ErMs) among non-carbapenemase producing (NCP) and carbapenemase producing (CP) Escherichia coli and Klebsiella pneumoniae. As mutations for ertapenem resistance establish the genetic background for non-carbapenemase meropenem resistance, there is a great need for antibiotic stewards and researchers to understand the determinants of a strain’s propensity to become resistant. Whole genome sequencing was conducted on clinical carbapenem-resistant E. coli (CREC) and K. pneumoniae (CRKP) across 5 hospitals in San Antonio, U.S. from 2012-2018. The majority of carbapenem resistant Enterobacterales (CRE) were NCP (54%; 41/76). The blaCTX-M was found to be most prevalent among NCP isolates (p = 0.02). LC-MS/MS analysis of carbapenem hydrolysis revealed that blaCTX-M-mediated carbapenem hydrolysis, indicating the need to reappraise the term, “non-carbapenemase (NCP)” for quantitatively uncharacterized CRE strains harboring blaCTX-M. Antimicrobial susceptibility results showed that 56% of all NCPE isolates had an ErMs phenotype (NCPE vs. CPE, p < 0.001), with E. coli driving the phenotype (E. coli vs. K. pneumoniae, p < 0.001). ErMs strains carrying blaCTX-M, had approximately 4-fold more copies of blaCTX-M than ceftriaxone-resistant but ertapenem and meropenem susceptible (EsMs) isolates (3.7 v. 0.9, p < 0.001). ErMs also carried more mobile genetic elements (MGEs), particularly IS26 composite transposons, than EsMs (37 vs. 0.2, p < 0.0001). Immunoblot analysis demonstrated the absence of OmpC expression in NCP-ErMs E. coli, with 92% of strains lacking full contig coverage of ompC. Overall, this work provides evidence of a collaborative effort between blaCTX-M and OmpC in NCP strains that confer resistance to ertapenem but not meropenem. To thwart potential mismanagement of CRE infected patients, future efforts should focus on understanding the mechanism(s) underlying OmpC loss, developing rapid methods to detect blaCTX-M copy number variants, and targeted antimicrobials for NCPE and ErMs strains.

This study explores the potential to reach a circular economy for post-consumer recycled polyethylene terephthalate (rPET) packaging and bottles by using it as a distributed recycling for additive manufacturing (DRAM) feedstock. Specifically, rPET is processed using only an open source toolchain with fused particle fabrication (FPF) or fused granular fabrication (FGF) processing. In this study, first the impact of granulation, sifting and heating (and their combination) is quantified on the shape and size distribution of the rPET flakes. Then feeding studies were performed to see if they could be printed through an external feeder or needed to be direct printed with a hopper using two Gigabot X machines, one with extended part cooling and one without. Print settings were optimized based on thermal characterization and for the latter which was shown to print rPET directly from shredded water bottles mechanical testing is performed. The results showed that geometry was important for extended feeding tubes and direct printed using a hopper. Further there is a wide disparity in the physical properties of rPET from water bottles depending on source and the history of the material. Future work is needed to enable water bottles to be used as a widespread DRAM feedstock.

Purpose. Moraxella is an ocular bacterial pathogen isolated in cases of keratitis, conjunctivitis, and endophthalmitis. Gram-negative brick-shaped diplobacilli from ocular specimens, and slow growth in culture, are early indications of Moraxella ocular infection; however, identifying Moraxella to species can be complex and inconsistent. Methods. In this study, bacteria consistent with Moraxella were identified to species using: 1) DNA sequencing coupled with vancomycin susceptibility, 2) MALDI-TOF Mass Spectrometry, and 3) Biolog ID System. Study samples consisted of 9 ATCC Moraxella controls, 82 isolates from keratitis, 21 isolates from conjunctivitis, and 4 isolates from endophthalmitis. Results. The ATCC controls were correctly identified. For keratitis, 66 (80.5%) were identified as M. nonliquefaciens, 7 (9.0%) as M. lacunata, 5 (6%) as M. osloensis, 2 (2.5%) as Acinetobacter lwoffi, 1 (1.0%) as M. bovis/nonliquefaciens, and 1 (1.0%) as M. osloensis/nonliquefaciens. For conjunctivitis, 9 (43.0%) were identified as M. osloensis, 6 (29.0%) as M. nonliquefaciens, 3 (14.3%) as Roseomonas, 2 (9.5%) as Acinetobacter (parvus, junii), and 1 (4.5%) as M. catarrhalis/M. nonliquefaciens. From endophthalmitis, 3 of 4 of the isolates were M. nonliquefaciens. Overall, M. nonliquefaciens and M. osloensis were identified in 70% (75 of 107) and 13% (14 of 107) of cases, respectively, totaling 83% (89 of 107). Conclusions. M. nonliquefaciens and M. osloensis are important bacterial pathogens of the eye as determined by DNA sequencing, MALDI-TOF MS, and Biolog. Although Moraxella catarrhalis is a clinical pathogen, other species of Moraxella appear to have a prominent role in eye infections.

Pulmonary infections with Mycobacterium avium occur in susceptible individuals following exposure to the bacterium in the environment, where it often persists in biofilms. Many methods have been used to generate biofilms of M. avium, and it is unknown whether different approaches generate similar structures and cell phenotypes. To make a parallel comparison of in vitro biofilm ultrastructure, extracellular matrix (ECM) composition, and drug susceptibility of biofilm resident bacteria, we used two published methods to generate M. avium biofilms: four week incubation in M63 medium or 24 hour exposure to dithiothreitol (DTT). Scanning electron microscopy revealed differences in biofilm ultrastructure between the two methods, including variation in appearance of ECM materials and morphology of resident cells, while light microscopy and staining with calcofluor white indicated that both biofilms contained polysaccharides characteristic of cellulose. Measuring susceptibility of biofilms to degradation by enzymes suggested differences in structurally important ECM molecules, with DTT biofilms having important protein and, to a lesser extent, cellulose components, and M63 biofilms having moderate protein, cellulose, and DNA components. Both biofilms conferred resistance to the bactericidal effects of amikacin and clarithromycin, with resident cells being killed at >10-fold lower rates than planktonic cells at almost all concentrations. Though these comparisons indicate differences in biofilm responses by M. avium under differing conditions, they also suggest common features of biofilm formation including cellulose production and antimicrobial resistance.

Extensive use of petrochemical plastic packaging leads to the greenhouse gas emission and con-tamination to soil and oceans, posing major threats to the ecosystem. The packaging needs, hence, are shifting to bioplastics with natural biodegradability. Lignocellulose, the biomass from forest and agriculture, can produce cellulose nanofibrils (CNF), a biodegradable material with ac-ceptable functional properties, that can make packaging among other products. CNF extracted from lignocellulosic wastes can lower the packaging carbon footprint and the production cost. Most of these low value feedstocks go to alternative applications, that make their use in CNF packaging competitive. To transfer the waste materials from current practices to the packaging production, it is imperative to assess their sustainability, encompassing environmental and eco-nomic impacts along with the feedstock physical and chemical properties. A consolidated over-view of these criteria is absent in the literature. This study performs an iterative literature review and presents thirteen attributes, delineating sustainability of lignocellulosic wastes for commer-cial CNF packaging production. These criteria data are gathered for the UK waste streams, and transformed into a quantitative matrix, evaluating the waste feedstock sustainability for CNF packaging production. The presented approach can be adopted to decision scenarios in bioplas-tics packaging conversion and waste management.

It has been proven that in standard Einstein gravity, exotic matter (i.e. matter violating the point-wise and averaged weak and null energy conditions) is required to stabilize traversable wormholes. Quantum field theory permits these violations due to the quantum coherent effects found in any quantum field . Even reasonable classical scalar fields violate the energy conditions. In the case of the Casimir effect and squeezed vacuum states, these violations have been experimentally proven. It is advantageous to investigate methods of minimizing the use of exotic matter. One such area of interest is extended theories of Einstein gravity. It has been claimed that in some extended theories, stable traversable wormholes solutions can be found without the use of exotic matter. There are many extended theories of gravity and in this review paper we first explore f(R) theories and then explore some wormhole solutions in f(R) theories including Lovelock gravity.

Transplant oncology is a relatively new field in which transplantation is used to treat patients who would otherwise be unresectable. New anticancer treatment paradigms using tumor and transplant immunology and cancer immunogenomics are emerging. In turn, liver transplantation (LT) has become a potential therapy for certain patients with colorectal cancer (CRC) with liver metastasis, hepatocellular (HCC), cholangiocarcinoma (CCA), and metastatic neuroendocrine tumor (NET) to the liver. Although there are established criteria for LT in HCC, the evidence regarding LT as a treatment modality for certain gastrointestinal malignancies is still debated. The aim of this review is to highlight updates in the role of LT for certain malignancies, including HCC, metastatic CRC, hilar CCA, and neuroendocrine tumor (NET), as well as contextualize LT use and discuss controversies in transplant oncology.

Rice has become the second major food among rural people. It is one of the most nutrient and low-cost food available in Asia. Rice is composed of two major subspecies as Japonica and Indica and it belongs to the Poaceae family. The World Bank predicts that rice demand will grow 51% faster than population growth in 2025. It is high time to develop a model which predicts the type of infected paddy leaf and avoids the loss of grains. In this paper, the proposed hybrid CNN model, three CNN networks with different layer properties are trained parallel. The extracted feature from these CNN networks is combined to provide the classification of the type of infected leaf. Fieldwork was carried and about 340 samples are collected from five different types of classes. The proposed hybrid model was tested with both the fieldwork dataset and also with an available dataset on the internet. The experimental results show that the proposed model outperforms the other CNN network and yields an accuracy value of 98%, a precision value of 95%, and a misclassification rate of 4% respectively.

In this paper, we first define the concepts of r-fuzzy soft α-open (semi-open and δ-open) sets on fuzzy soft topological spaces based on the article Aygunoglu et al. (Hacet. J. Math. Stat., 43 (2014), 193-208), and the relations of these sets with each other are established. In addition, we introduce the concepts of fuzzy soft δ-closure (δ-interior) operators, and study some properties of them. Also, the concept of r-fuzzy soft δ-connected sets is introduced and studied with help of fuzzy soft δ-closure operators. Thereafter, we define the concepts of fuzzy soft α-continuous (β-continuous, semi-continuous, pre-continuous and δ-continuous) functions, which are weaker forms of fuzzy soft continuity, and some properties of these functions along with their mutual relationships are discussed. Moreover, a decomposition of fuzzy soft α-continuity and a decomposition of fuzzy soft semi-continuity is obtained. Finally, as a weaker form of a fuzzy soft continuity, the concepts of fuzzy soft almost (weakly) continuous functions are defined, and some properties are specified. Additionally, we explore the notion of continuity in a very general setting called, fuzzy soft (L, M, N, O)-continuous functions and a historical justification is introduced.

Sexual issues and treatment side effects are not routinely discussed with men receiving treatment for prostate cancer and support to address these concerns is not consistent across settings. This study evaluates a brief e-learning resource designed to improve sexual wellbeing support and examine its effects on healthcare professionals’ sexual attitudes and beliefs. Healthcare professionals (n=44) completed an online questionnaire at baseline which included a modified 12-item sexual attitudes and beliefs survey (SABS). Follow-up questionnaires were completed immediately after the e-learning and at 4 weeks. Data were analysed using one-way, repeat measures ANOVAs to assess change in attitudes and beliefs over time. Significant improvements were observed at follow-up for a number of survey statements including ‘knowledge and understanding’, ‘confidence in discussing sexual wellbeing’ and the extent to which participants felt ‘equipped with the language to initiate conversations’. The resource was seen as concise, relevant to practice, and as providing useful information on potential side effects of treatment. Brief, e-learning has potential to address barriers to sexual wellbeing communication and promote delivery of support for prostate cancer survivors. Practical methods and resources should be included with these interventions to support implementation of learning and long-term changes in clinical behaviour.

Titania is one of the most comprehensively studied nanostructures due to its widespread applications in production of catalytic, gas- sensing and corrosion- resistance materials [1]. M-polynomial of nanotubes has been vastly investigated as it produces many degree-based topological indices which are numerical parameters capturing structural and chemical properties. These indices are used in the development of quantitative structure-activity relationships (QSARs) in which the biological activity and other properties of molecules are correlated with their structure like boiling point, stability, strain energy etc of chemical compounds. In this paper, we determine M-polynomials of single-walled titanium (SW TiO2) nanotubes and recover important topological degree based indices of them to theoretically judge these nanotubes. We also use Maple to plot surfaces associated to different types of single-walled titanium (SW TiO2) nanotubes.

Vermicomposting is one of the most important waste management techniques in the process of vermiculture. In this study, a Neural Network-assisted novel paradigm is proposed to predict waste from vermicomposting. The proposed Neural Network Skeleton is based on a Gallium Arsenide Processing Schema, which is used to separate wastes. By comparing the proposed sys-tem with existing methods, it was found that the proposed approach had the highest average prediction ratio of 91.32%, outperforming other techniques like ERD, RNN, and Deep LSTM. The separation ratio analysis also demonstrated the effectiveness of the proposed method, with a range of 45-94%. Furthermore, the study emphasizes the importance of chemical equilibrium and the effectiveness of our proposed Gallium Arsenide Processing Schema in achieving high prediction and separation accuracies, showcasing its potential for practical application in waste management processes. Lastly, the prediction of the process evolution stages is detailed, indicating the efficiency of the proposed system in achieving various levels of waste separation. Overall, the study provides valuable insights into the potential of the proposed methods in op-timizing wastewater management processes, paving the way for more effective and sustainable vermicomposting practices.

We examined a series of real-world, pictorial photographs with varying characteristics, along with their modification by noise addition and unsharp masking. As response metrics we used three different versions of the aesthetic measure originally proposed by Birkhoff. The first aesthetic measure, which has been used in other studies, and which we used in our previous work as well, showed a preference for the least complex of the images. It provided no justification for noise addition, but did reveal enhancement on unsharp masking. Optimum level of unsharp masking varied with the image, but was predictable from the individual image’s GIF compressibility. We expect this result to be useful for guiding the processing of pictorial photographic imagery. The second aesthetic measure, that of informational aesthetics based on entropy alone failed to provide useful discrimination among the images or the conditions of their modification. A third measure, derived from the concepts of entropy maximization, as well as the hypothesized preference of observers for “simpler”, i.e., more compressible, images, yielded qualitatively the same results as the more traditional version of the measure. Differences among the photographs and the conditions of their modification were more clearly defined with this metric, however.

Early diagnosis of paroxysmal atrial fibrillation (PAF) could suggest patients to receive timely interventions in clinical practice. Various PAF onset prediction algorithms might benefit from accurate heart rate variability (HRV) analysis and machine learning classification but to be challenged in real-time monitoring scenarios. The aim of this study is to present an end-to-end deep learning based PAFNet model that integrates a sliding window technique on raw R-R interval of electrocardiogram (ECG) segments to achieve a real-time prediction of PAF onsets. This integration enable the deep convolutional neural network (CNN) to be customized as a light-weight architecture that accommodates the size of sliding windows simply by altering the input layer, specifically its effectiveness in making a new prediction with each new heartbeat. Catering to potential influence of input sizes, three CNN models were trained using 50, 100, and 200 R-R intervals, respectively. For each model, the performance of automated algorithms was evaluated for PAF prediction using a ten-fold cross-validation. As a results, a total of 56,381 PAFN-type and 56,900 N-type R-R interval segments was collected from publicly accessible ECG databases, and a promising prediction performance of the automated algorithm with a 100 R-R intervals was achieved in terms of the sensitivity of 97.12%, the specificity of 97.77%, and the accuracy of 97.45%, respectively. Importantly, the automated algorithm with a sliding windows step of 1 could process one sample in only 23.1 milliseconds and identify the onset of PAF at least 45 minutes in advance. The present results suggest that the sliding window technique on raw R-R interval sequences along by deep learning based algorithms may offers the possibility of providing an accurate, real-time, and end-to-end clinical tool for mass monitoring of PAF.

Partial negative allosteric modulators (NAM) of the mGlu5 receptor are an excellent alternative to full antagonists and NAMs because they retain some therapeutic effects and, at the same time, have a much broader therapeutic window. Here, we investigated whether partial mGlu5 NAM, M-5MPEP induced a fast and sustained antidepressant-like effect, characteristic of rapid-acting antidepressant drugs (RAADs) like ketamine, in C57BL/6J mice. M-5MPEP caused a rapid, dose-dependent antidepressant-like action in the tail suspension test (TST) 60 min after injection. This effect was antagonized by an AMPA receptor antagonist (NBQX) and a TrkB receptor antagonist (ANA-12) but not by 5HT1A and 5HT2A/2C receptor antagonists. Furthermore, M-5MPEP (30 mg/kg) induced sustained antidepressant-like effects 24 h after the last of four administrations. These effects were revealed in the splash test, designed to measure apathy-like state, and in the TST. Western blot and ELISA analyses indicated the involvement of the TrkB/BDNF pathway in the sustained M-5MPEP effects. Additionally, prolonged effects of M-5MPEP were entirely reversed by the TrkB receptor antagonist ANA-12 in both the splash test and the TST, confirming the critical role of TrkB receptor activation in the sustained antidepressant-like effect of M-5MPEP. Importantly, M-5MPEP enhanced the subthreshold dose of (R)-ketamine in the TST, indicating both substances' convergent mechanisms of action and the possibility of their practical use in treating depression.

The complete structure and connectivity of the Caenorhabditis elegans nervous system was first published in 1986. The ‘mind of a worm’ was the first organism to have its nervous system to be reconstructed at the level of synapses, and represented a critical milestone considering today it remains the only organism to be mapped to that level of connection. Recently, the extrasynaptic connectome of neuropeptides and monoamines has been described. This review discusses recent technological advances used to perturb whole-organism neuronal function, such as: whole brain imaging, optogenetics, sonogenetics and mutant analysis, which have allowed for interrogations of both local and global neural circuits, leading to different behaviors. A better understanding of a whole organism requires combining experimental datasets with biophysical neuronal modelling, and behavioral quantification. Combining these approaches will provide a complete understanding of the worm nervous system and shed light into how networks function and interact with the synaptic network to modulate information processing and behavioral output.

This qualitative research explores the adoption of blockchain technology in supply chain management, aiming to understand the drivers, barriers, and implications associated with its integration. Through in-depth interviews and thematic analysis, insights are gathered from key stakeholders in the supply chain ecosystem. The findings reveal a complex landscape, with stakeholders recognizing blockchain's potential to enhance transparency, efficiency, and trust while acknowledging challenges related to technical complexities, regulatory uncertainties, and organizational barriers. Despite these challenges, participants express optimism about blockchain's transformative potential, citing opportunities for improved traceability, supply chain resilience, and sustainability. Collaboration, governance, and ecosystem development emerge as critical factors for driving blockchain adoption within supply chains, alongside the need for continuous education and capacity-building initiatives. Overall, the study underscores the importance of addressing challenges and fostering a culture of innovation and collaboration to unlock the full potential of blockchain-enabled supply chains.

Ecology is working to face its colonial roots and institutional inequities. As we build more diverse, equitable, and inclusive (DEI) institutions we must work to support new ecologists by empowering them with the knowledge and tools to succeed. Undergraduate research experiences (UREs) are critical for a student’s professional and interpersonal skill development and key for recruiting more diverse groups of students to ecology. Here, we highlight DEI dimensions of a URE in ecology, acknowledge safety considerations for field ecology, including harassment and assault, and provide tools to support the URE. This is written primarily for all URE students and secondarily for their advisors. We welcome students from underrepresented groups and encourage allyship from students from non-underrepresented groups. After reading this paper, we hope that all students feel more confident and excited about their URE and that advisors see how to improve DEI in their lab.

Ensembles of Species Distribution Models (SDMs) represent the geographic ranges of pathogen vectors by combining alternative analytical approaches and merging information on vector occurrences with more extensive environmental data. Biased collection data impact SDMs, regardless of the target species but no studies have compared the differences in the distributions predicted by the ensemble models when different sampling frameworks are used for the same species. We compared Ensemble SDMs for two important Ixodid tick vectors, Amblyomma americanum and Ixodes scapularis in mainland Florida, USA, when inputs were either convenience samples of ticks, or collections obtained using the standard protocols promulgated by the U.S. Centers for Disease Control and Prevention. The Ensemble SDMs for the convenience samples and standard surveys showed only a slight agreement (Kappa = 0.060, A. americanum; 0.053, I. scapularis). Convenience sample SDMs indicated A. americanum and I. scapularis should be absent from 34.5% and 30.9% of the state where standard surveys predicted the highest likelihood of occurrence of the respective vectors. Ensemble models from standard surveys predicted 81.4% and 72.5% (A. americanum and I. scapularis) of convenience sample sites. Omission errors by standard survey SDMs, of the convenience collections, frequently were associated with adjacency to at least one SDM or errors in geocoding algorithms that failed to correctly locate convenience samples. These geocoding errors emphasize commonly overlooked needs to explicitly evaluate and improve data quality for vector survey data used in spatial models.

Among earth’s microbial populations are the genes, functional capacities, generational memory and sentient cognition that enable microorganisms to adapt and thrive in the full range of ecological conditions found on planet earth. In prior sequential publications, we considered fundamental properties (e.g., use of and responses to sound, light, vibrations) and features of microorganisms that cause them to be critical co-partners of human and other holobionts as well as the potential benefits for humanity that can be gained by fully applying quantum-related and novel capacities of microbial life. In this narrative review we: 1) discuss key concepts concerning a microbially-enhanced and sustainable future, and 2) focus on electric- and magnetic- based features of microorganisms that make them pivotal for myriad benefits ranging from beyond pharma-based health and wellness to free- and/or renewable energy and restorative agriculture to improved human networking. While the benefits are many, the risks posed by hazardous electric or magnetic field exposures to both holobionts and microbial communities are significant. This review concludes that microbes and their remarkable capacities offer both humanity and the planet a much brighter future if we reverse the demonization of microbes and wanton microbiome degradation that has predominated much of the past century.

Variability in traits forming the Leaf Economics Spectrum (LES) among and within crop species play a key role in governing agroecosystem processes. However, studies evaluating the extent, causes, and consequences of within-species variation in LES traits for some of the world’s most common crops remain limited. We quantified variation in nine leaf traits measured across 90 vines of five wine grape (Vitis vinifera) varieties at two ontogenetic stages. Grape traits covary along an intraspecific LES, in patterns similar to those documented in wild plants. Across varieties, high rates of photosynthesis (A), and leaf nitrogen (N) concentrations, are coupled with low leaf mass per area (LMA), while the opposite suite of traits defines the “resource conserving end” of this intraspecific LES in grape. Variety identity predicted of leaf physiological (A) and morphological traits (i.e., leaf area and leaf mass), while leaf chemical traits and LMA were best explained by ontogenetic stage. All varieties expressed greater resource conserving trait syndromes (i.e., higher LMA, lower N, lower Amass) later in the growing season. Traits related to leaf hydraulics, including instantaneous water-use efficiency (WUE), were unrelated to LES and other resource capture traits, and were better explained by spatial location. Our results highlight the relative contributions of genetic vs. phenotypic factors in structuring this variation and point to a key role of domestication in governing trait relationships in the world’s crops.

Yerba maté, an herbal tea derived from Ilex paraguariensis, has previously been reported to be protective against obesity-related and other cardiometabolic disorders. Using high-resolution respirometry and reverse-phase high-performance liquid chromatography, the effects of four weeks of yerba maté consumption on mitochondrial efficiency and cellular redox status in skeletal muscle, adipose, and liver, tissues highly relevant to whole body metabolism, were explored in healthy adult mice. Yerba maté treatment increased mitochondrial oxygen consumption in adipose, but not in other tissues examined. Yerba maté increased ATP concentration in skeletal muscle and decreased ATP concentration in adipose. Combined with observed changes in oxygen consumption, these data yielded a significantly higher ATP:O2, a measure of mitochondrial efficiency, in muscle and a significantly lower ATP:O2 in adipose, which were consistent with yerba maté-induced weight loss. Yerba maté treatment also altered the hepatic glutathione (GSH)/glutathione disulfide (GSSG) redox potential to a more reduced redox state, suggesting potential protective effects against oxidative stress and preservation of cellular function. Together, these data indicate beneficial, tissue-specific effects of yerba maté supplementation on mitochondrial bioenergetics and redox states in healthy mice that are protective against obesity.

We show that low quality of all 427 Brazilian SARS-CoV-2 genomes recently published in Science (1) challenges their phylogenetic inference and may lead to incorrect typing of viral strains in clades with no statistical support. Absence of basecalling quality in genome assemblies and proper phylogeny parameter estimates preclude the assessment of signal-to-noise ratio in the data, downstream analysis and conclusions.

A simple protocol for preparation of O-acylated enol form - (R/S)-ethyl-2-acetoxy-4-phenyl-4H-chromene-3-carboxylate 5 was presented. The compound was characterized by 1H-, 13C-and DEPT135 NMR spectra, including {1H,1H} COSY, {1H,13C} HSQC, {1H,13C} HMBC and 2D-NOESY spectra. The preferred regioselectivity for O-acylation of 3,4-dihydrocoumarin 5 in the presence of substituent in 4-th position in the chroman ring and accounting the steric hindrance of the ester group in 3-th place was confirmed.

A Brewer Spent Grain (BSG), the most abundant by-product of the brewing process, is mainly used in animal feed and biogas production. The aim of the present work is BSG valorization by yeast fermentation to produce carotenoids. R. mucilaginosa CBS316 was cultured on BSG syrups, supplemented or not with YE and PEP (s-Fsa and Fsa). The biomass and carotenoid production were optimized in flasks and then scaled-up in bioreactor. In flask tests, the maximum biomass concentration was 5.3 and 6.2 g/L for Fsa and s-Fsa cultures, respectively. The maximum carotenoid production was 833 μg/L in Fsa and 1159 μg/L in s-FSA. Considering that the highest specific productivity value (P 7.16 μg/g*h) was obtained with Fsa syrup, this medium was selected for the process scale-up. In bioreactor tests, the maximum concentrations of biomass (4.29 g/L) and carotenoid (396 ug/L) was reached at 72 hours of fer-mentation, 24 h later than in flask. The total carotenoid produced was 524 and 150 ug in bioreactor and flask cultures, respectively. The carotenoids production by R. mucilaginosa was obtained both in Fsa and s-Fsa syrups. The results confirm the possibility to use the syrup as it is, Fsa, thus limiting the process costs.

In this paper, inspired by Jleli and Samet [journal of inequalities and applications 38 (2014) 2 1–8] we introduce two new classes of auxiliary functions and utilize the same to define (q, y)R-weak 3 contractions. Utilizing (q, y)R-weak contractions, we prove some fixed point theorems in the setting 4 of relational metric spaces. We employ some examples to substantiate the utility of our newly proved 5 results. Finally, we apply one of our newly proved results to ensure the existence and uniqueness of 6 solution of a Volterra-type integral equation.

Crocodilepox virus (CRV) belongs to the Poxviridae family and mainly infects hatchling and juvenile Nile crocodiles. Most poxviruses encode inhibitors of the host antiviral protein kinase R (PKR), which is activated by viral double-stranded (ds) RNA formed during virus replication, resulting in the phosphorylation of eIF2 and subsequent shutdown of general mRNA translation. Because CRV lacks orthologs of known poxviral PKR inhibitors, we experimentally characterized one candidate (CRV157), which contains a predicted dsRNA-binding domain. Bioinformatic analyses indicated that CRV157 evolved independently from other poxvirus PKR inhibitors. CRV157 bound to dsRNA, co-localized with PKR in the cytosol, and inhibited PKR from various species. To analyze whether CRV157 could inhibit PKR in the context of a poxvirus infection, we constructed recombinant vaccinia virus strains that contain either CRV157 or a mutant CRV157 deficient in dsRNA binding in a strain that lacks PKR inhibitors. The presence of wild type CRV157 rescued vaccinia virus replication, while the CRV157 mutant did not. The ability of CRV157 to inhibit PKR correlated with virus replication and eIF2alpha phosphorylation. The independent evolution of CRV157 demonstrates that poxvirus PKR inhibitors evolved from a diverse set of ancestral genes in an example of convergent evolution.

Creatine is a popular ergogenic aid among athletic populations with consistent evidence indicating that creatine supplementation also continues to be commonly used among adolescent populations. In addition, the evidence base supporting the therapeutic benefits of creatine supplementation for a plethora of clinical applications in both adults and children continues to grow. Among pediatric populations, a strong rationale exists for creatine to afford therapeutic benefits pertaining to multiple neuromuscular and metabolic disorders, with preliminary evidence for other subsets of clinical populations as well. Despite the strong evidence supporting the efficacy and safety of creatine supplementation among adult populations, less is known as to whether similar physiological benefits extend to children and adolescent populations, and in particular those adolescent populations who are regularly participating in high-intensity exercise training. While limited in scope, studies involving creatine supplementation and exercise performance in adolescent athletes generally report improvements in a number of ergogenic outcomes with limited evidence of ergolytic properties and consistent reports indicating no adverse events associated with supplementation. The purpose of this article is to summarize the rationale, prevalence of use, performance benefits, clinical applications, and safety of creatine use in children and adolescents.

Abstract: As a low-input crop, Miscanthus offers numerous advantages that, in addition to agricultural applications, permits its exploitation for energy, fuel, and material production. Depending on the Miscanthus genotype, season, and harvest time as well as plant component (leaf versus stem), correlations between structure and properties of the corresponding isolated lignins differ. Here, a comparative study is presented between lignins isolated from M. x giganteus, M. sinensis, M. robustus and M. nagara using a catalyst-free organosolv pulping process. The lignins from different plant constituents are also compared regarding their similarities and differences regarding monolignol ratio and important linkages. Results showed that the plant genotype has the weakest influence on monolignol content and interunit linkages. In contrast, structural differences are more significant among lignins of different harvest time and/or season. Analyses were performed using fast and simple methods such as nuclear magnetic resonance (NMR) spectroscopy. Data was assigned to four different linkages (A: b-O-4 linkage, B: phenylcoumaran, C: resinol, D: b-unsaturated ester). In conclusion, A content is particularly high in leaf-derived lignins at just under 70 % and significantly lower in stem and mixture lignins at around 60 % and almost 65 %. The second most common linkage pattern is D in all isolated lignins, the proportion of which is also strongly dependent on the crop portion. Both stem and mixture lignins, have a relatively high share of approximately 20 % or more (maximum is M. sinensis Sin2 with over 30 %). In the leaf-derived lignins, the proportions are significantly lower on average. Stem samples should be chosen if the highest possible lignin content is desired, specifically from the M. x giganteus genotype, which revealed lignin contents up to 27 %. Due to the better frost resistance and higher stem stability, M. nagara offers some advantages compared to M. x giganteus. Miscanthus crops are shown to be very attractive lignocellulose feedstock (LCF) for second generation biorefineries and lignin generation in Europe.

Modern organic synthesis is majorly focused on developing environmentally benign synthetic protocols by employing green chemistry principles. Accordingly, in our recent research work, we herein report the use of modified supramolecular host cyclodextrin as an effective solid based green catalyst for accessing structurally diverse and medicinally relevant pyrimidone architectures. The catalyst and the synthesized compounds 4 (a-r) were characterized using FT-IR, NMR and GC-Mass spectroscopy. Major highlights of the reported work include: atom economical process, extremely milder reaction conditions, operational simplicity, high isolated yields, and excellent catalyst turnover number. The molecular docking studies suggest that the compound 4n has the hydrogen bonding, hydrophobic and π-pair interactions with the active site of active sites of CXT M 15 receptor.

This research investigates the challenges and opportunities associated with supply chain transparency and traceability in the renewable energy sector. Using a qualitative methodology, the study involved semi-structured interviews with key stakeholders, including industry experts, supply chain managers, regulatory officials, and NGO representatives. The findings reveal that the complexity and global span of renewable energy supply chains pose significant hurdles for ensuring transparency and traceability. Variability in the maturity of traceability systems across companies further complicates the landscape, with some companies benefiting from advanced systems while others struggle with cost and technical barriers. Technological advancements, especially blockchain, offer promising solutions but require standardization and scalability to be effective. Regulatory frameworks play a crucial role, yet inconsistencies across jurisdictions create compliance challenges, underscoring the need for harmonized standards. Collaboration and partnerships are essential, providing platforms for sharing best practices and developing common standards. Enhanced transparency can lead to operational efficiencies, improved consumer trust, and stronger market positioning. Integrating sustainability into supply chain practices is fundamental, aligning with the increasing emphasis on ESG criteria among investors and stakeholders. Education and capacity-building, particularly for suppliers in developing countries, are vital for promoting transparency. Leadership and corporate culture are critical in driving these efforts, with strong commitment from the top necessary to implement effective practices. This study contributes valuable insights for stakeholders in the renewable energy sector, offering a foundation for future research and policy development aimed at advancing sustainable and ethical supply chain practices. The findings highlight the need for a holistic approach that integrates transparency and traceability into broader sustainability and business strategies.

The vast array of interconnected microbes across earth’s ecosystems and within holobionts has been called the “Internet of Microbes.” Research into the fundamental microbial properties has demonstrated that bacteria and archaea are masters of energy and information collection, storage, transformation, and dissemination using both “wired” and wireless (at a distance) capacities. These features suggest that microbes are quantum entangled within and between earth’s holobionts, and that specific tools affecting energy and information functions could provide an effective strategy for managing microbial populations. Microbes use four critically important microbial networking functions (sound, light, electricity, and magnetism). This narrative review focuses on microbial management based on two of the four: sound and light (as well as related vibrations). These are examined as: 1) tools for managing microbial populations, 2) tools to support new technologies, and 3) tools for healing humans and other holobionts. Given microbial sensitivity to sound, light, and vibrations, it is critical that microbial populations and microbe-laden holobionts are protected from potentially damaging exposures. We conclude that sound, light, and vibrations are useful therapeutic tools that can help support useful microbial populations and help to address ongoing challenges of holobiont disease.

Despite the well-documented health benefits of recreational sports, few opportunities exist in lower- and middle-income countries for adult women to participate in recreational physical activities. An explanatory sequential mixed methods approach was used to explore associations between an innovative soccer program for adult women and self-reported health status. Cross-sectional survey data were collected in 2018-2019 from 702 women in the Nikumbuke Project, a health and literacy program in southeastern rural Kenya, followed by focus group discussions with 225 women who also participated in the Project's soccer program. Quantitative findings suggest that women who participated in soccer had 67% greater odds of reporting good or excellent health than their non-soccer playing peers. Thematic analysis of qualitative data indicated that women credited soccer with less pain, fatigue, and stress, as well as weight loss and reduced dependence on medicine for hypertension, pain, and sleep problems. Women equated health benefits with greater ease and efficiency in completing chores, reduced worries, youthful energy, male-like strength, and pleased husbands. Soccer programs for adult women may be particularly effective interventions in settings where access to health care is limited and where lack of opportunity to engage in physical aerobic activity increases women's risks for poor health outcomes. .

Soil and Water Assessment Tool (SWAT) was used to simulate five glacierized river basins that are global in coverage and vary in climate. The river basins included the Narayani (Nepal), Vakhsh (Central Asia), Rhone (Switzerland), Mendoza (Central Andes, Argentina), and Central Dry Andes (Chile) with a total area of 85,000 km2. A modified SWAT snow algorithm was applied in order to consider spatial variation of associated snow melt /accumulation by elevation band across each subbasin. In the previous studies, melt rates varied as a function of elevation resulting from an air temperature gradient while the snow parameters were constant throughout the entire basin. A major improvement of the new snow algorithm is separating the glaciers from seasonal snow based on their characteristics. Two SWAT snow algorithms were evaluated in simulation of monthly runoff from glaciered watershed: 1) the snow parameters are lumped (i.e. constant throughout the entire basin) and 2) the snow parameters are spatially variable based on elevation band-subbasin (i.e. modified snow algorithm). Applying the distributed SWAT snow algorithm improved the model performance in simulation of monthly runoff with snow-glacial regime, so that mean RSR decreased to 0.49 from 0.55 and NSE increased to 0.75 from 0.69. Improvement of model performance was negligible in simulation of monthly runoff from the basins with monsoon runoff regime.

This study develops a hybrid machine learning (ML) algorithm integrated with IoT technology to improve the accuracy and efficiency of soil monitoring and tomato crop disease prediction in Anakapalle, a south Indian station. An IoT device collected one-minute and critical soil parameters—humidity, temperature, pH values, nitrogen (N), phosphorus (P), and potassium (K)—essential for assessing soil health and optimizing crop growth. Kendall's correlations were computed to rank these parameters for utilization in hybrid ML techniques. Various ML algorithms including K-Nearest Neighbors (KNN), Support Vector Machines (SVM), Decision Tree (DT), Random Forest (RF), and Logistic Regression (LR) were evaluated. A novel hybrid algorithm, 'Bayesian Optimization with KNN', was introduced to combine multiple ML techniques and enhance predictive performance. The hybrid algorithm demonstrated superior results with 95% accuracy, precision, and recall, and an F1 score of 94%, while individual ML algorithms achieved varying results: KNN (80% accuracy), SVM (82%), DT (77%), RF (80%), and LR (81%) with differing precision, recall, and F1 scores. This hybrid ML approach proved highly effective in predicting tomato crop diseases in natural environments, underscoring the synergistic benefits of IoT and advanced ML techniques in optimizing agricultural practices.

Social media giants like Facebook are struggling to keep up with fake news, in the light of the fact that disinformation diffuses at lightning speed. For example, the COVID-19 (i.e. Coronavirus) pandemic is testing the citizens' ability to distinguish real news from falsifying facts (i.e. disinformation). Cyber-criminals take advantage of the inability to cope with fake news diffusion on social media platforms. Fake news, crafted as a means to manipulate readers to perform various malicious IT activities. However, no previous study has investigated the strategies used to create fake news on social media. Therefore, we have analysed five data-sets that contain online news articles (i.e. both fake and legitimate news) to investigate strategies of crafting fake news on social media platforms. Our study findings revealed a threat model understanding strategies of crafting fake news which may highly likely diffuse on social media platforms.

Adverse childhood experiences are known to program children for disrupted biological cycles, premature aging, microbiome dysbiosis, immune-inflammatory misregulation, and chronic disease multimorbidity. To date, the microbiome has not been a major focus of deprogramming efforts despite its emerging role in every aspect of ACE-related dysbiosis and dysfunction. This article examines: 1) the utility of incorporating microorganism-based, anti-aging approaches to combat ACE-programmed chronic diseases (also known as noncommunicable diseases and conditions, NCDs) and 2) microbiome regulation of core systems biology cycles that affect NCD comorbid risk. In this review microbiota influence over three key cyclic rhythms (circadian cycles, the sleep cycle, and the lifespan/longevity cycle) as well as tissue inflammation and oxidative stress are discussed as an opportunity to deprogram ACE-driven chronic disorders. Microbiota, particularly those in the gut, have been shown to affect host-microbe interactions regulating the circadian clock, sleep quality, as well as immune function/senescence and regulation of tissue inflammation. The microimmunosome is one of several systems biology targets of gut microbiota regulation. Furthermore, correcting misregulated inflammation and increased oxidative stress is key to protecting telomere length and lifespan/longevity and extending what has become known as the healthspan. This review article concludes that to reverse the tragedy of ACE-programmed NCDs and premature aging, managing the human holobiont microbiome should become a routine part of healthcare and preventative medicine across the life course.

This study explores the barriers and opportunities faced by women in supply chain leadership, a field traditionally dominated by men. Through in-depth interviews and thematic analysis, it uncovers the pervasive cultural and societal biases that undermine women's perceived competence and suitability for leadership roles. These biases, often rooted in deep-seated stereotypes, influence hiring and promotion decisions, creating significant obstacles for women. Structural and organizational barriers, such as the lack of formal diversity policies, flexible working arrangements, and adequate mentorship, further hinder women's career progression. The dual burden of professional and domestic responsibilities also disproportionately affects women, limiting their availability for work-related travel and extended hours, which are often required in supply chain roles. Despite these challenges, the study identifies several pathways to promote gender diversity in supply chain leadership. Organizational commitment to diversity and inclusion, flexible working policies, and comprehensive mentorship programs are crucial in supporting women's advancement. Education and professional development opportunities are essential in equipping women with the necessary skills for leadership roles. Additionally, fostering an inclusive corporate culture that values diverse perspectives and addresses discrimination is vital for creating a supportive environment. Broader societal and policy-level changes, such as government and industry initiatives promoting gender diversity, are also necessary. The integration of emerging areas like sustainability, entrepreneurship, emotional intelligence, marketing, and supplier relationship management offers new opportunities for women to contribute to the industry's evolution. By addressing these barriers and leveraging the identified opportunities, it is possible to create a more inclusive and equitable supply chain industry, benefiting both the industry and society.

The preparation of transition metal salt ammine complexes having oxidizing anions is a great challenge due to the reaction between the ammonia and oxidizing anions during the synthesis of these materials. However, they have an important role in the development of new oxidants in organic chemistry and especially as precursors in the preparation of mixed metal oxides and alloys in controlled temperature thermal decomposition reactions. Therefore, the synthetic procedures to prepare the complexes of transition metal permanganate, pertechnetate, and perrhenate (VIIB group tetraoxometallates) salts with ammonia as ligand or co-ligand have been comprehensively reviewed. The available data about the structure and spectroscopic properties of these compounds, including the hydrogen bonds that act as redox reaction centers under their thermal decomposition are given and evaluated. Their thermal decomposition processes and products have been summarized. The available pieces of information about their role in organic oxidation reactions like the oxidation of benzyl alcohols, and regeneration of oxo-compounds from oximes and phenylhydrazones including the kinetics of these processes have also been collected.

In this study, a field experiment was conducted to evaluate the growth and yield responses of Sri Lankan lowland rice (Oryza sativa L.) with the application of beneficial Arbuscular mycorrhizal fungi (AMF) inoculum, and inter-cropping with highly mycorrhizal dependent vetiver grass (Chrysopogon zizanioides L.) under two different soil nutrient management systems (NMSs): conventional/chemical (CNMS) and organic (ONMS). The experiment was designed as a split plot with three blocks. Each CNMS and ONMS experiment included untreated control (T0), and three treatments—AMF inoculation (T1), vetiver intercropping (T2), and the combination of AMF and vetiver (T3). According to the results, colonization of rice roots with AMF was not affected significantly by the treatments and ranged from 0‒15.8%. The effect was very low or absent in the early stage and then higher in the later stages of the rice plant. Furthermore, plant growth was not significantly different between the two NMSs, although grain yield was significantly higher (P < 0.05), with the order T1 (0.45 kg/m2) >T2 (0.42 kg/m2) >T3 (0.41 kg/m2) in CNMS and T2 (0.44 kg/m2) >T1 (0.41 kg/m2) >T3 (0.40 kg/m2), in ONMS than for the respective controls (T0), thus suggesting beneficial utilization of AMF and vetiver in the lowland rice farming system.

Insect herbivores have a wide range of life cycles and feeding habits, making them extremely diverse. With their host plants, they form close relationships and suppress their defense mecha-nisms. Molecular elicitors are the key bio-elements in detection and recognition of attacking enemies in tissue consumption. Insect oral secretion, frass, and fluid of egg deposition contain bio-logical active molecules called herbivore-associated elicitors (HAEs) are recognized by pattern recognition receptors (PRRs). However, in insect herbivores, little is known about the molecular basis of signal transduction and regulation of plant resistance. Many plants distinguish insect feeding from wounding by HAEs presenting in their oral secretions (OS) and induce local and systemic responses against arthropod feeding. PRRs perceive HAEs in the oral secretion of cater-pillars in a species-specific manner to elicit exclusive defense responses. HAEs-PRRs interactions induce plant resistance by reprogramming plant metabolism and transcriptional machinery. Quantitative, timely, and coordinated plant response initiate early signalling events including Ca+2, reactive oxygen species (ROS) and mitogen-activated protein kinases (MAPKs). We have discussed how early signalling cascades converge into the accumulation of phytohormones that regulate down-stream special metabolites against herbivores. In this review, we have drawn a hypothetical model of PPRs-HAEs mediated induced responses in plants and discussed how PRRs-HAEs interactions based on molecular mechanism that elicit short- and long-term induced defenses in plants. The identification of plant target insect herbivore PRRs-HAEs interactions will help to explore the fundamental molecular mechanisms of host manipulation and may generate prospects to develop novel pest resistance strategies.

Iron Doped TiO₂ nanoparticles (Fe-TiO₂) were synthesized and photocatalitically investigated under high and low fluence values of UV-radiation. The Fe-TiO₂ physical characterization was performed using X-ray Powder Diffraction (XRD), Brunauer-Emmett-Teller (BET) surface area analysis, Transmission Electron Microscope (TEM), Scanning Electron Microscope (SEM), Diffuse Reflectance Spectroscopy (DRS), and X-Ray Photoelectron Spectroscopy (XPS) technique. The XPS evidenced that ferric ion (Fe³⁺) was in the lattice of TiO₂ and co-dopants no intentionally added were also present due to the precursors of the synthetic method. The Fe³⁺ concentration played a key role in the photocatalytic generation of hydroxyl radical (•OH) and estriol (E3) degradation. Fe-TiO₂ materials accomplished E3 degradation, and it was found that the catalyst with 0.3 at. % content of Fe (0.3 Fe-TiO₂) enhanced the photocatalytic activity under low UV-irradiation compared with no intentionally Fe-added TiO₂ (zero-iron TiO₂) and Aeroxide^® TiO₂ P25. Furthermore, the enhanced photocatalytic activity of 0.3 Fe-TiO₂ under low UV-irradiation may have applications when radiation intensity must be controlled, as in medical applications, or when strong UV absorbing species are present in water.

This qualitative study explores consumer perceptions of ethical supply chains and their implications for brand loyalty in contemporary markets. Ethical supply chain practices, encompassing sustainability, transparency, and social responsibility, are increasingly pivotal in shaping consumer attitudes and behaviors. A semi-structured interview approach was utilized to gather insights from a diverse sample of consumers, revealing nuanced perspectives on how ethical considerations influence brand preferences and loyalty. Findings indicate that consumers value brands that demonstrate genuine commitment to ethicality, viewing transparency and accountability in supply chain operations as essential for building trust and credibility. Emotional responses such as admiration and respect were commonly associated with brands perceived as ethical, highlighting the emotional resonance of ethical supply chain practices in consumer decision-making processes. Challenges such as greenwashing and perceived discrepancies between brand promises and actions underscore the importance of authentic communication in aligning consumer perceptions with brand behaviors. The COVID-19 pandemic further emphasized the role of ethical supply chains in ensuring business resilience and consumer trust during global disruptions. Brands that exhibited ethical leadership during the crisis reinforced their reputational capital and strengthened relationships with ethically conscious consumers. This study contributes to understanding the strategic imperative for businesses to integrate and communicate ethical supply chain practices effectively, thereby fostering sustainable competitive advantages and enhancing long-term brand loyalty. Future research directions include exploring evolving consumer expectations, emerging ethical challenges, and innovative strategies for embedding ethicality into supply chain management.This qualitative study explores consumer perceptions of ethical supply chains and their implications for brand loyalty in contemporary markets. Ethical supply chain practices, encompassing sustainability, transparency, and social responsibility, are increasingly pivotal in shaping consumer attitudes and behaviors. A semi-structured interview approach was utilized to gather insights from a diverse sample of consumers, revealing nuanced perspectives on how ethical considerations influence brand preferences and loyalty. Findings indicate that consumers value brands that demonstrate genuine commitment to ethicality, viewing transparency and accountability in supply chain operations as essential for building trust and credibility. Emotional responses such as admiration and respect were commonly associated with brands perceived as ethical, highlighting the emotional resonance of ethical supply chain practices in consumer decision-making processes. Challenges such as greenwashing and perceived discrepancies between brand promises and actions underscore the importance of authentic communication in aligning consumer perceptions with brand behaviors. The COVID-19 pandemic further emphasized the role of ethical supply chains in ensuring business resilience and consumer trust during global disruptions. Brands that exhibited ethical leadership during the crisis reinforced their reputational capital and strengthened relationships with ethically conscious consumers. This study contributes to understanding the strategic imperative for businesses to integrate and communicate ethical supply chain practices effectively, thereby fostering sustainable competitive advantages and enhancing long-term brand loyalty. Future research directions include exploring evolving consumer expectations, emerging ethical challenges, and innovative strategies for embedding ethicality into supply chain management.

Supply chain transparency and traceability have become increasingly important in today's globalized and interconnected business environment. This qualitative research explores the challenges and perspectives of industry practitioners regarding supply chain transparency and traceability. Drawing on semi-structured interviews with a diverse group of supply chain professionals, the study identifies key themes including difficulties in achieving visibility beyond immediate suppliers, data fragmentation and inconsistency, barriers to technology adoption, regulatory compliance, cultural and organizational factors, impacts on supplier relationships, and the influence of the COVID-19 pandemic and sustainability goals. The findings highlight the complex nature of these challenges and the need for collaborative, multi-stakeholder approaches to address them effectively. Despite the challenges, the study also reveals the potential benefits of transparency and traceability for enhancing supply chain resilience, sustainability, and stakeholder trust. Moving forward, companies must leverage technological innovations, establish clear communication channels with suppliers, navigate regulatory complexities, and foster a culture of transparency and accountability within their organizations. Future research should focus on practical strategies for implementing transparency and traceability initiatives, as well as evaluating their impact on supply chain performance and sustainability outcomes.

The abstract of the study on the challenges and opportunities of supply chain digitalization encapsulates the primary findings and their implications from the perspectives of industry leaders. This qualitative research investigated how senior executives across diverse sectors perceive and manage the transition to digital supply chains. Interviews with twenty industry leaders revealed key challenges such as data integration, cybersecurity, organizational resistance, and financial constraints. Data integration issues were particularly pronounced, as participants struggled with unifying disparate data sources from legacy and modern systems, creating barriers to achieving cohesive digital frameworks. Cybersecurity emerged as a critical concern due to the increased vulnerability of digital supply chains to cyber threats, necessitating robust and proactive security measures. Organizational resistance, driven by employee apprehensions about job displacement and technological unfamiliarity, highlighted the need for effective change management practices, including clear communication and training. Financial constraints, especially for small and medium-sized enterprises (SMEs), underscored the difficulty of justifying the substantial investments required for advanced digital technologies. Despite these challenges, the study identified significant opportunities associated with digitalization, including enhanced operational efficiency, improved visibility, predictive analytics, and better customer satisfaction. Digital tools were found to streamline processes, reduce manual intervention, and provide real-time insights into supply chain performance, thus facilitating more informed decision-making and swift responses to disruptions. The accelerated adoption of digital technologies during the COVID-19 pandemic demonstrated their essential role in enhancing supply chain resilience and agility. Additionally, the integration of sustainability goals through digitalization supported resource optimization and waste reduction, aligning with broader corporate social responsibility objectives. The findings suggest that while the path to digital transformation is complex, the benefits of improved efficiency, decision-making, customer satisfaction, and sustainability present compelling incentives for organizations to invest in and embrace digital supply chain solutions.

We describe electron temperature measurements in the SSX MHD wind tunnel using two different methods. First, we estimate T_e along a chord by measuring the ratio of the C__III 97.7 nm to C_IV 155 nm line intensities using a vacuum ultraviolet monochrometer. Second, we record a biasing scan to a double Langmuir probe to obtain a local measurement of T_e. The aim of these studies is to increase the Taylor state lifetime, primarily by increasing the electron temperature. Also, a model is proposed to predict magnetic lifetime of relaxed states and is found of predict the lifetime satisfactorily. Furthermore, we find that proton cooling can be explained by equilibration with the electrons.

In this paper, we have established Hermite-Hadamard inequalities for r-preinvex functions via fractional integrals.

In modern data analysis, working with diverse dataset formats is essential for ensuring compatibility across different software tools and platforms. However, manual conversion between formats can be time-consuming and error-prone. To address this challenge, we developed an interactive Shiny application that facilitates the seamless conversion of datasets between popular software formats such as CSV, Excel, SAS, SPSS, Stata, and RData. This user-friendly app enables users to upload datasets, select an output format, and download the converted file with a single click. The application also incorporates a real-time progress indicator, enhancing the user experience by showing conversion progress. Built with simplicity and efficiency in mind, the app is designed for researchers, data analysts, and practitioners who regularly handle multiple file formats in their workflows. Additionally, the app features a clean, intuitive interface with clear guidance, making it accessible even to users with minimal technical background. The development process, key features, and potential applications of this tool are discussed in this article.

It was previously reported that the peptide derived from LfcinB, R-1-R exhibited anti-Candida activity and this activity was enhanced in combination with an extract from the Bidens pilosa plant. However, the mechanism of action has not been studied. In the current study, a proteomic study was carried out, followed by a bioinformatic analysis and biological assays in both SC5314 strain and a fluconazole-resistant isolate of Candida albicans, after incubation with R-1-R. The proteomic data showed that after treatment with R-1-R in the two study strains, most of the differentially expressed proteins in comparison to controls were up-regulated. These proteins were mainly involved in membrane and cell wall biosynthesis, membrane transporters, oxidative stress, the mitochondrial respiratory chain, and response to DNA damage. Besides, the proteomic analysis of C. albicans parental strain SC5314 treated with R-1-R in combination with an ethanolic extract of B. pilosa was also undertaken. The proteins differentially expressed after this treatment were involved in similar functional processes as the proteins differentially expressed after treatment with R-1-R peptide alone, but at different levels and were mostly down-regulated. The biological assays allowed validation of the proteomic results, evidencing damage to the cell surface, generation of reactive oxygen species and decrease in mitochondrial membrane potential. The results provide information to begin to unlock the understanding of the complex antifungal mode of action of the R-1-R peptide, its combination with the extract, and possibly other derivatives of natural products.

This study explores the role of stakeholder engagement in enhancing supply chain sustainability within the renewable energy sector. Through a qualitative research approach, including in-depth interviews with key stakeholders such as government agencies, industry associations, renewable energy companies, community groups, and environmental organizations, the research reveals the complexity and significance of effective stakeholder engagement. Stakeholders highlighted diverse motivations, including environmental, social, economic, and regulatory concerns, driving their participation. The study underscores the importance of tailored engagement strategies that recognize stakeholder heterogeneity and address specific needs and expectations. Collaborative approaches, such as public-private partnerships and multi-stakeholder initiatives, were identified as crucial for pooling resources, sharing knowledge, and addressing common challenges. However, challenges related to power imbalances, conflicting interests, and communication barriers were also noted. Government policies and regulatory frameworks were found to play a pivotal role in shaping stakeholder engagement practices and sustainability outcomes. Regulatory uncertainty and inconsistency were cited as significant concerns that could undermine sustainability initiatives. Community engagement emerged as a critical factor, with local communities often directly impacted by renewable energy projects. Meaningful engagement, including consultation and benefit-sharing mechanisms, is essential for building trust and securing social acceptance. Emotional intelligence and marketing strategies were recognized as important tools for effective stakeholder engagement, emphasizing the role of empathy, active listening, and clear communication. The findings of this study highlight the need for a holistic and integrated approach to stakeholder engagement and supply chain sustainability in the renewable energy sector. By addressing diverse stakeholder needs, fostering collaboration, and aligning policies with sustainability goals, stakeholders can work together to accelerate the transition towards a more sustainable energy future.

This paper presents a novel sensor for the detection and characterization of regions of air turbulence that would be of use to improve UAV stability in bad weather. It consists of a combined Schlieren imager and a Radar Acoustic Sounding System (RASS) to produce dual modality “images” of air movement within the measurement volume. The ultrasound modulated Schlieren imager consists of a strobed point light source, parabolic mirror, light-block and camera which are controlled by two laptops. It provides a fine scale projection of the acoustic pulse modulated air turbulence through the measurement volume. The narrow beam 40 kHz/ 17 GHz RASS produces spectra based on Bragg enhanced Doppler radar reflections from the acoustic pulse as it travels. Tests using artificially generated air vortices showed some disruption of the Schlieren image and of the RASS spectrogram. This should allow the higher resolution Schlieren images to identify the turbulence mechanisms that are disrupting the RASS spectra.

In this paper, we classify the function space of all real-valued functions on R denoted as F(R,R) into 28 distinct blocks. Each block contains elements that share common features in terms of the cardinality of their sets of continuity and differentiability. Alongside this classification, we introduce the concept of the Connection, which reveals a special relationship structure between four well-known real-valued functions in real analysis: the Cantor function, Dirichlet function, the Thomae function, and the Weierstrass function. Despite the significance of this field, several perspectives remain unexplored.

Background/Objectives: Meconopsis has long been used in traditional Tibetan medicine to treat various diseases. However, blue-flowered Meconopsis (M. betonicifolia) is becoming increasingly scarce due to overharvesting. As a potential alternative, yellow-flowered Meconopsis (M. integrifolia) shows promise but requires comprehensive characterization. This study aimed to evaluate and compare the anti-inflammatory potential of yellow- and blue-flowered Meconopsis species. Methods: LC-MS was used to analyze the chemical profiles of yellow- and blue-flowered Meconopsis. Putative targets of shared constituents were subjected to GO and disease enrichment analysis. The LPS-induced RAW264.7 macrophage model was employed to assess anti-inflammatory effects. Metabolomics was applied to gain mechanistic insights. Results: LC-MS revealed over 70% chemical similarity between species. Enrichment analysis associated targets with inflammation-related pathways. In macrophage assays, both species demonstrated dose-dependent anti-oxidative and anti-inflammatory activities, with yellow Meconopsis exhibiting superior efficacy. Metabolomics showed modulation of key inflammatory metabolic pathways. Conclusions: This integrative study validated yellow-flowered Meconopsis as a credible alternative to its blue-flowered counterpart for anti-inflammatory applications. Metabolic profiling provided initial clues regarding their multi-targeted modes of action, highlighting clinical relevance and potential for sustainable utilization and biodiversity conservation.

Diabetic retinopathy (DR), a major complication of prolonged diabetes, poses a significant risk of vision loss. Early detection is critical for effective treatment, yet traditional diagnostic methods by ophthalmologists are time-consuming, costly, and subject to variability. This study introduces a novel approach employing a hybrid Convolutional Neural Network-Radial Basis Function (CNN-RBF) classifier integrated with Multi-Scale Discriminative Robust Local Binary Pattern (MS-DRLBP) features for enhanced DR detection. We implemented advanced image preprocessing techniques, including noise reduction, morphological operations, and Otsu’s thresholding, to optimize blood vessel segmentation from retinal images. Our method demonstrates exceptional performance in screening DR, achieving an average of 96.10% precision, 95.35% sensitivity, 97.06% specificity, and 96.10% accuracy. These results significantly outperform traditional methods and offer a promising tool for remote and efficient screening of DR. Applied to publicly available datasets, this research contributes to the development of accessible, accurate diagnostic methods in ophthalmology, potentially reducing the global burden of diabetic vision loss.

From a differential geometric perspective, information geometry (IG) aims to characterise the structure of statistical geodesic models. The research done for this paper offers a novel method for modelling the information geometry of a queuing system. From the perspective of IG, the manifold of the transient M/M/infinity queue is described in this context. The Fisher Information matrix (FIM) as well as the inverse of (FIM), (IFIM) of transient M/M/infinity QM are devised. In addition to that, new results that uncovered the significant impact of stability of QM on the existence of (IFIM) are obtained. Moreover, the Geodesic equations of motion of the coordinates of the underlying transient are obtained. Also, it is revealed that stable QM is developable (i.e., has a zero Gaussian curvature) and has a non-zero Ricci Curvature Tensor (RCT). Novel stability dynamics of transient M/M/iInfinity queue manifold is revealed by discovering the mutual dual impact between the behaviour of (RCT) and the stability(instability) phases of M/M/Infinity QM. Furthermore, a new discovery that presents the significant impact of stability of queue manifold and the continuity of the unique representation between M/G/1 queue manifold and Ricci Curvature Tensor (RCT). The information matrix exponential (IME) is devised. Also, it is shown that stability of the devised (IME) enforces the instability of M/M/ Infinity QM. More interestingly, novel relativistic info-geometric queueing theoretic links are revealed .

Mate crime is a specific subset of hate crime in which the perpetrator is known to the victim. To date, there is very little research into the perception and experience of mate crime in autism. The aim of the current study was to examine perceptions of friendship and mate crime in autistic adults, using semi-structured interviews. Five adults were interviewed about their experiences of social interactions, friendships and mate crime. Participants described distancing themselves from the ‘disability’ label whilst growing up to avoid condescension and being perceived as vulnerable, whilst learning to camouflage their social difficulties. Feelings of anxiety were associated with socialising, and participants valued relationships that did not place too many overwhelming demands on their time or energy. Finally, all participants had prior experiences of bullying. They understood the concept of mate crime but were unsure as to whether they would be able to identify it in their own lives if it occurred. However they could identify potential support networks in close friends and family. Results highlight the importance of further research into positive and negative aspects of social relationships in autistic adults, and the need to provide support to those who are socially vulnerable.

Castor oil may be differentiated from other non-edible vegetable oils because of its main composition of hydroxylated fatty acids. Ricinoleic acid comprises 80–90% wt. of fatty acids in castor oil (Ricinus communis). In this study, the thermo-oxidative stability and tribological behavior of bio-based lubricant samples synthesized from castor oil using isoamyl alcohol were evaluated. Initially, the compositional and physicochemical properties of the obtained samples were assessed using 1H NMR, FTIR, and ASTM methods. Oxidative stability of the samples was evaluated using Rancimat method at 110 °C under air flow. The final biolubricant sample (BL2), obtained after esterification, epoxidation, and oxirane rings opening reactions, presented an oxidation stability time (OST) of 14.3 h. The thermal stability was also evaluated by thermogravimetry (TG) from the mass variations under inert and oxidative atmosphere. BL2 showed higher thermal stability compared to the other samples, demonstrating higher decomposition temperatures in both inert (339.04 °C) and oxidative (338.47 °C) atmospheres, for a mass loss of 50%. The tribological properties of the samples were evaluated using a four-ball tribometer configuration. The BL1 and BL2 samples exhibited lower friction coefficients than the mineral oil sample (MOS) by 21.5% and 43.1%, respectively. Regarding wear, the observed wear scar diameter (WSD) was also lower in BL1 and BL2 compared to MOS by 5.2% and 40.4%, respectively. The results of the tribological evaluation suggest that both samples obtained in this study have promising potential for applications in lubricating machines and mechanical systems.

In the software development process, the decision-maker (DM) has a range of problems inherent to its function. Wrong choices during software planning can bring great risk to the project. Therefore, the planning of software releases to be delivered to the customer should be well done. This is not an easy task because releases are made up of many requirements that contain complex variables that must be considered, such as precedence, cost, requirement stability, among other features that make the requirements-selection process challenging. To make this process less exhaustive, DM can use tools that facilitate this work. In software engineering, we can find fields of research specialists in this context, such as Search-Based Software Engineering (SBSE). The SBSE makes use of advanced metaheuristics to search for optimal solutions or the closest to it. In this work, we try to use another field of research to solve this same problem type, the Verbal Decision Analysis (VDA). To do this, we elaborate a workflow that will use the same source data, execute two solutions using the two search fields (SBSE and VDA) and compare the results. In the end, we evaluated and commented on the results.

Speckle Plethysmography (SPG) and Photoplethysmography (PPG) are different biophotonics technologies that allow for measurement of hemodynamics. As the difference between SPG and PPG under low perfusion conditions is not fully understood, a Cold Pressor Test (CPT) was used to modulate blood pressure and peripheral circulation. A custom-built setup simultaneously derived SPG and PPG from the same video streams at two wavelengths (639 nm and 850 nm). SPG and PPG were measured at right index finger location before and during CPT using finger Arterial Pressure (fiAP) as reference. The effect of CPT on Alternating Component amplitude (AC) and Signal-to-Noise-Ratio (SNR) of dual-wavelength SPG and PPG signals was analysed across participants. Furthermore, waveform differences between SPG, PPG, and fiAP based on frequency harmonic ratios, were analysed for each subject (n=10). Both PPG and SPG at 850 nm show a significant reduction during CPT for both AC and SNR. However, SPG showed significantly higher and more stable SNR than PPG in both study phases. Harmonic ratios were found substantially higher in SPG than PPG. Therefore, in low perfusion conditions, SPG seems to offer a more robust pulse wave monitoring with higher harmonic ratios than PPG.

Here we investigated the longer-term effect of Ncald-ASOs by additional i.c.v. bolus injection at PND28. Two weeks after injection of 500 µg Ncald-ASO in wild-type mice, NCALD was significantly reduced in brain and spinal cord and well tolerated. Next, we performed a double-blinded preclinical study combining low-dose SMN-ASO (PND1) with 2x i.c.v. Ncald-ASO or CTRL-ASO (100 µg at PND2, 500 µg at PND28). Ncald-ASO re-injection significantly ameliorated electrophysiological defects and NMJ denervation at 2 months. Moreover, we developed and identified a nontoxic and highly efficient human NCALD-ASO that significantly reduced NCALD in hiPSCs-derived MNs. This improved both neuronal activity and growth cone maturation of SMA MNs, emphasizing the additional protective effect of NCALD-ASO treatment.

In recent years, there has been a growing interest in the preoperative modeling of fluid-structure interaction in the treatment of cerebral aneurysms. In this study, we investigate two cases involving laminar incompressible fluid flow interacting with hyperelastic materials (a vertical flap and aneurysm walls) under the effect of fluid flow. We present a finite element method (FEM) for these prototypical two-dimensional ($2D$) configurations, taking into account the complex flows and deformation of the variant's structure models. We use an Arbitrary Lagrangian-Eulerian (ALE) formulation in a continuum, fully monolithic coupled way, and discretize the fluid and solid domains using the quadratic LBB stable $P_2P_1$ finite element pair to approximate the displacement, velocity, and pressure spaces independently. The resulting discretized form of the nonlinear algebraic system is linearized using a variant of Newton's procedure, and the Jacobian matrices are approximated via the divided difference method. The resulting linear systems are solved using a direct solver MUMPS. We evaluate hydrodynamic forces such as drag and lift coefficients for nonlinear elastic material models, including Saint-Venant Kirchoff, Neo-Hookean, and Mooney-Rivlin (2 parameters) separately. To gain more physical insight into the problem, we verify the computed results by comparing the velocity, viscosity, and pressure fields. Our aim is to qualitatively analyze the changes in the mechanics of the wall behavior of the elasticity of the flap vs. the complexity of deformation, interface, details for prototypical flow situations, corresponding displacement, and deformation. We also provide a physical interpretation of blood flow magnitude and basic hemodynamic phenomena of wall shear stresses (WSS) in aneurysma and the range of deformation. Overall, this study presents a comprehensive approach to modeling fluid-structure interaction in cerebral aneurysms, which could help in the development of more effective treatment strategies.

In some parts of Nigeria, many girls do not attend school, and among those sent to school, many still drop out early. This and other socio-cultural factors affect girls psychologically. There is no doubt that girls need consistent love and tutoring to guide them through the turbulent teen years and beyond. They need a mentor who acts as a friend and a role model. The Mobile-based Mentoring Platform seeks to leverage on mobile technology's affordances to focus on the needs of the girl-child, such as improvement in academic achievement, guidance in career choice, development of self-concept, and esteem. The girl-mentees comments revealed that using the platform provided them frequent access to mentors and access to learning opportunities. The challenges they faced include epileptic internet network, intrusions by parents, and others. Therefore, this paper examined the challenges and benefits of mentoring girls via a mentoring platform.

The detection of waste plastics in the marine and terrestrial environment using satellite Earth Observation data offers the possibility of large-scale mapping, and reducing on-the-ground manual investigation. In addition, costs are kept to a minimum by utilizing free-to-access Copernicus data. A Machine Learning based classifier was developed to run on Sentinel-1 and -2 data. In support of the training and validation, a dataset was created with terrestrial and aquatic cases by manually digitizing varying landcover classes alongside plastics under the sub-categories of greenhouses, plastic, tyres and waste sites. The trained classifier, including an Artificial Neural Network and post-processing decision tree, was verified using five locations encompassing these different forms of plastic. Although exact matchups are challenging to digitize, the performance has generated high accuracy statistics, and the resulting land cover classifications have been used to map the occurrence of plastic waste in aquatic and terrestrial environments.

This article aims to understand the role of tacit knowledge in call center organizations with the objective of understanding how call center representatives use tacit knowledge in their job roles and functions. Extant literature has focused on explicit knowledge but the research on tacit knowledge is still underdeveloped. The complexities and difficulties of the call center job role and the usage and transfer of knowledge is reviewed. Also, it takes into considerations past literature on tacit knowledge, how these respondents employ tacit knowledge in efficiently handling customers, responding to their queries, and engaging this form of knowledge in problem solving. The article concludes with discussion and implications for call center organizations and responders.

This paper presents an advanced microstructural analysis of the AlSiMg, Ti64 and N700 powders used for additive manufacturing. The internal microstructure of the regular and irregular powder grains were characterized down to atomic resolution by using scanning electron microscopy and high resolution scanning transmission electron microscopy.The accretionary forms on top of the irregular AlSiMg powder grains exhibit a slightly coarse microstructure with a network of eutectic Si consisting of nano-crystallites, suggestinga slower cooling than the grain itself that contain a predominately amorphous Si network. A nm thin amorphous C layer on the surface of some Ti64 plasma atomized powder grains promoted the attachment of satellites and growth of envelopes. In case of gas atomized N700 powder grains, we identified thin oxide and carbon amorphous layers as well as metal segregations at the interface between the grain body and the accretionary forms.

Microarray gene expression-based detection and classification of medical conditions have been prominent in research studies over the past few decades. However, extracting relevant data from the high-volume microarray gene expression with inherent nonlinearity and inseparable noise components raises significant challenges during data classification and disease detection. So, this paper proposes a two-level strategy involving feature extraction and selection methods before the classification step. The feature extraction step utilizes Short Term Fourier Transform (STFT), and the feature selection step employs Particle Swarm Optimization (PSO) and Harmonic Search (HS) metaheuristic methods. The classifiers employed are Non-Linear Regression, Gaussian Mixture Model, Softmax Discriminant, Naive Bayes, SVM (Linear), SVM (Polynomial), and SVM (RBF). The two-level extracted relevant features are compared with raw data classification results, including Convolutional Neural Network (CNN) Methodology. Among the methods, STFT with PSO feature selection and SVM (RBF) classifier produced the highest accuracy of 94.47%.

Antimicrobial application of carbon nanomaterials such as carbon nanotubes (CNTs), capped CNT, C60 fullerene, and C70 fullerene are increasing owing to their low cytotoxicity properties compared to other nanomaterials such as metallic nanoparticles. Enhanced mechanical property and antibacterial activity can be caused by incorporation of CNTs in 3-dimentional (3D) printed nanocomposites (NCs). Interruption of bacterial membrane resulting from cylindrical shape and high aspect ratio properties has been found as the prominent antibacterial mechanism of CNTs. However, unraveling interaction of CNT, capped CNT, C60 fullerene, and C70 fullerene with virulence factors of the main bacterial pathogenesis has not yet been known. Therefore, in the present study, interactions of CNT, capped CNT, C60, and C70 with the eight virulence factors including protein kinase A and ESX-secreted protein B of Mycobacterium tuberculosis, pseudomonas elastase and exotoxin A of Pseudomonas aeruginosa, alpha-hemolysin and penicillin binding protein 2a of Staphylococcus aureus and shiga toxin 2a and heat-labile enterotoxin of Escherichia coli have been evaluated by molecular docking method of AutoDock Vina. This study disclosed the binding strength followed the sequence CNT > capped CNT > C70 > C60 towards alpha-hemolysin of S. aureus compared to other virulence factors with values of -19.6, -18.8, -13.6, and -12.8 kcal/mol, respectively. The lowest and highest binding affinity were found for CNT against 1TII and 1MWT by binding energy values of 97.4 and -20.1 kcal/mol. The stability of CNT-1MWT complex at the different times has resulted according to the normal mode analysis of elNémo and iMOD servers. Future studies should be focused on improving cellular uptake of CNTs, capped CNTs, C70, and C60 by surface functionalization for active targeting of bacteria.

The segmentation and de-noising are basic operations, required in every signal processing and classification system. The classical segmentation and de-noising approaches are time-invariant. Consequently, it results in the post processing of an unnecessary information and causes an increase in the system processing activity and power consumption. In this context, an efficient event-driven segmentation and de-noising technique is proposed. It is founded on the principles of level crossing and activity selection. Therefore, it can adapt its sampling frequency, segmentation window length and position along with the filter order by analyzing the input signal local characteristics. As a result, the computational complexity and the power consumption of the proposed system is reduced compared to the counter ones. The suggested system performance is compared with the classical one. It is done for the case of a multi-channel Electroencephalogram (EEG) signals. Results show a noticeable compression gain with an effective adaptation of the de-noising filters order. It aptitudes a significant computational gain, transmission data rate reduction and power consumption reduction of the proposed technique, compared to the counter ones. It shows that the proposed solution is an attractive candidate to embed in the new generation EEG wearables.

The dorsal column nuclei complex (DCN-complex) includes the dorsal column nuclei (DCN, referring to the gracile and cuneate nuclei collectively), external cuneate, X, and Z nuclei, and the median accessory nucleus. The DCN are organised by both somatotopy and modality, and have a diverse range of afferent inputs and projection targets. The functional organisation and connectivity of the DCN implicate them in a variety of sensorimotor functions, beyond their commonly accepted role in processing and transmitting somatosensory information to the thalamus, yet this is largely underappreciated in the literature. To consolidate insights into their sensorimotor functions, this review examines the morphology, organisation, and connectivity of the DCN and their associated nuclei. First, we briefly discuss the receptors, afferent fibres, and pathways involved in conveying tactile and proprioceptive information to the DCN. Next, we review the modality and somatotopic arrangements of the remaining constituents of the DCN-complex. Finally, we examine and discuss the functional implications of the myriad of DCN-complex projection targets throughout the diencephalon, midbrain, and hindbrain, in addition to their modulatory inputs from the cortex. The organisation and connectivity of the DCN-complex suggest that these nuclei should be considered a complex integration and distribution hub for sensorimotor information.

This paper presents a control algorithm for soft-switching series LC converters. The conventional voltage-to-voltage controller is split into a master and a slave controller. The master controller implements constant-current-constant-voltage (CCCV) control, required for demanding applications, i.e. lithium battery charging or laboratory power supplies. It defines the set-current for the open-loop current slave controller, which generates the PWM parameters. The power supply achieves fast large-signal responses, e.g. from 5 V to 24 V, where 95% of the target value is reached in less than 400 µs. The design is evaluated extensively in simulation and on a prototype. A consensus between simulation and measurement is achieved.

In this article, we introduce a relatively new concept of multi-valued (θ;R)-contractions and utilize the same to prove some xed point results for a new class of multi-valued mappings in metric spaces endowed with an amorphous binary relation. Illustrative examples are also provided to exhibit the utility of our results proved herein. Finally, we utilize some of our results to investigate the existence and uniqueness of a positive solution for the integral equation of Volterra type.

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. Although prognosis continually improved along years, a significant proportion of patients still relapse from the disease due to leukemia resistance to therapy. Methotrexate (MTX), a folic acid antagonist, is a chemotherapy agent commonly used against ALL and a immune-system suppressant for rheumatoid arthritis, that presents multiple and complex mechanisms of action and resistance. Previous studies have shown that MTX modulates the nuclear factor kappa B (NF-κB) pathway, an important family of transcription factors involved in inflammation, immunity, cell survival, and proliferation, frequently hyperactivated in ALL. Using gene set enrichment analysis (GSEA) on publicly available gene expression data from 161 newly diagnosed pediatric ALL patients, we found “TNF-α signaling pathway” to be the most enriched Cancer Hallmark in MTX poor responder patients. Transcriptomic analysis in a panel of ALL cell lines (6 BCP-ALL and 7 T-ALL) also identified the same pathway as differentially enriched among MTX resistant cell lines, as well as in slowly dividing cells. To better understand the crosstalk between NF-κB activity and MTX resistance, we genetically modified the cell lines to express luciferase under a NF-κB biding site promoter. We observed that the fold change in NF-κB activity triggered by TNF-α (but not MTX) treatment correlated with MTX resistance and proliferation across the lines. At the individual gene level, NFKB1 expression was directly associated with a poorer clinical response to MTX, and with both an increased TNF-α-triggered NF-κB activation and MTX resistance in the cell lines. Despite these results, pharmacological inhibition (with BAY 11-7082 and parthenolide) or stimulation (with exogenous TNF-α supplementation) of the NF-κB pathway did not alter MTX resistance of the cell lines significantly, evidencing a complex interplay between MTX and NF-κB in ALL.

A new set of basis functions is presented. The foundation in mathematics is established. To reconstruct a signal, it is compared to the Fourier basis functions. The M-basis functions' potential applications are also presented.

Two experiments were conducted to develop a Nano green manganese and assess its effect on grapevines. The first experiment was microbiological, where several incorporation strategies were utilized to enrich the yeast with manganese, as follows: (1) adding manganese to the liquid medium (growth phase), (2) adding after 24 h of incubation (non-growth phase). As the results, growth phase reduced the possibility of medium contamination. Manganese concentration in the yeast cells was increased as that of manganese sulphate in the medium. Manganese incorporation in yeast cells was 99.93% higher than that of the medium at 0.0195 g/l of manganese. Although the concentration of manganese in the medium raised the OD of yeast cell biomass, manganese sulphate had no passive influence on it. The second experiment was horticultural, done on Flame Seedless grapevines, since both active fresh and frozen yeast enriched with manganese resulted from the first experiment were sprayed twice a year at 10 or 20 cm3/l comparing with manganese sulphate, and manganese chelate. The results demonstrated that yeast extracts in both forms increased the yield and improved fruit properties. The most effective treatment on vegetative growth, yield and fruit properties was the frozen yeast enriched with manganese at 20 cm3/l.

Significant Wave Height(SWH) is a crucial parameter in oceanographic research, essential for understanding various marine and atmospheric processes. Traditional methods for obtaining SWH, such as ship-based and buoy measurements, face limitations like limited spatial coverage and high operational costs. With the advancement of Global Navigation Satellite Systems reflectometry(GNSS-R) technology, a new method for retrieving SWH has emerged, demonstrating promising results. This study utilizes Radio occultation sounder(GNOS) data from the FY-3E satellite and incorporates the latest Vision Transformer(ViT) technology to investigate GNSS-R-based SWH retrieval. We designed and evaluated various deep learning models, including ANN-Wave, CNN-Wave, Hybrid-Wave, Trans-Wave, and ViT-Wave. Through comparative training using ERA5 data, the ViT-Wave model was identified as the optimal retrieval model. The ViT-Wave model achieved an Root Mean Square Error(RMSE) accuracy of 0.4052 meters and Mean Absolute Error(MAE) accuracy of 0.2700 meters, significantly outperforming both traditional methods and newer deep learning approaches utilizing Cyclone Global Navigation Satellite Systems(CYGNSS) data. These results underscore the potential of integrating GNSS-R technology with advanced deep learning models to enhance SWH retrieval accuracy and reliability in oceanographic research.

In this paper, based on the cumulated damage generated by the cyclical application of the testing vibration profile, a methodology to determine the reliability index of the analyzed component is given. In the analysis, the testing time, component geometry, applied weight, and material resonant frequency are all of them considered by using a dynamic, and amplitude factor. Then, from the generated vibration response data of the analysis, the corresponding bending stress is determined for each one of the rows of the testing profile. And by the cyclical application of the whole testing profile, the corresponding damage is cumulated to each profile cycle until the cumulated damage is D=1. Finally, the reliability that each one of the cumulated blocks (cyclical profile application) is determined by considering, the random vibration is a stress variable. Thus, we use the cumulative damage model with the inverse power law stress/life relationship to determine the two parameter Weibull distribution used to estimate the reliability index of each cumulated block. As a numerical application, we analyze a cantilever aluminum beam Al 6061-T6.

Ionic liquids have been recognised as interesting solvents applicable in the efficient lignocellulosic biomass valorisation, especially in the biomass fractionation into individual polymeric components or direct hydrolysis some of biomass fractions. Considering the chemical character of ionic liquids, two different approaches, paved the way for a fractionation of biomass. The first strategy integrated a pre-treatment, hydrolysis and conversion of biomass through the employment of hydrogen-bond acidic 1-ethyl-3-methyimidazolim hydrogen sulfate ionic liquid. The second one relied on the use of a three-step fractionation process with hydrogen-bond basic 1-ethyl-3-methylimidazolium acetate to produce high purity cellulose, hemicellulose and lignin fractions. The proposed approaches were scrutinised for wheat straw and eucalyptus residues. Those different biomasses allowed understanding that enzymatic hydrolysis yields are dependent on the crystallinity of pre-treated biomass. The use of acetate based ionic liquid allowed to change crystalline cellulose I to cellulose II and consequently enhanced glucan to glucose yield to 93.14.1 mol% and 82.91.2 mol% for wheat straw and eucalyptus, respectively. Whereas for hydrogen sulfate ionic liquid, the same enzymatic hydrolysis yields were 61.6  0.2 mol% for wheat straw and only 7.90.3 mol% for eucalyptus residues. These results demonstrate the importance of either ionic liquid character or biomass type on the efficient biomass processing.

This review delves into the intricate relationship between folate (Vitamin B9) intake, especially its synthetic form, folic acid, and its implications on health and disease. While folate plays a pivotal role in the one-carbon cycle, essential for DNA synthesis, repair, and methylation, concerns arise from its excessive intake. The literature underscores potential deleterious effects, such as an increased risk of carcinogenesis, disturbances in DNA methylation, and impacts on embryogenesis, pregnancy outcomes, neurodevelopment, and disease risk. Notably, these consequences stretch beyond the immediate effects, potentially influencing future generations through epigenetic reprogramming. We probe into the molecular mechanisms underlying these effects, including accumulation of unmetabolized folic acid, Vitamin B12 dependent mechanisms, altered one carbon metabolism, altered methylation patterns, and interactions with critical receptors and signaling pathways. Furthermore, we emphasize differences in the effects and mechanisms mediated by folic acid compared to natural folate. Given the widespread folic acid supplementation, it is imperative to further research its optimal intake levels, and the molecular pathways impacted by its excessive intake, ensuring the health and well-being of the global population.

Microbes are the most prevalent and widely-distributed life form on planet Earth. They are also cognitive organisms with memory and superior problem-solving skills that use quantum phase transitions during their remarkably-effective gathering and dissemination of information. This narrative review explores the biological ramifications of human holobionts physically embodying the human microbiome and connecting to the Internet of Microbes (IOM) beyond our body. Within the review, we consider: 1) the ways in which our microbial co-partners exerted control over our ancestors and continue to influence our current human generation, 2) how they mold virtually every key aspect of our life and even remain with our body in death and 3) how inward-looking contemplative tools such as meditation and embodied cognition provide an ideal opportunity to connect to the microbial information super highway and tap the full range of human holobiont capacities.

Balanced fear supports human rational decision making and useful behavioral responses. In contrast, overwhelming, persistent, and unbalanced fear can paralyze the individual and result in heightened anxiety, lack of cognitive flexibility, fear-based public compliance and serious mental health issues. Psychobiotics research has established that a healthy microbiome is required for balanced fear and mental health protection via control of fear extinction. The recent Covid-19 pandemic featured daily, persistent, fear-of-a single contagion conditioning on a global scale paired with various behavioral mandates (e.g., lockdowns of the healthy, masks, isolation from environmental microbes and each other) that degraded the human microbiome and isolated us from each other and useful environmental microbes. It also ignored the historic role of secondary bacterial pathobionts, in pandemic deaths. This narrative review examines how institutional promotion of fear-of-a single contagion, lack of balanced risk communication, and appalling disregard of our fundamental nature (as majority-microbial human superorganisms) resulted in problems rather than solutions. This review concludes that government-public health-media promotion of pervasive fear and microbiome-degrading behaviors: 1) increased public compliance, 2) reduced cognitive flexibility, and 3) increased risk of mental health conditions. It further argues that microbiome-first public health should be embraced to ensure that human freedom, rather than paralyzing fear, dominates our future.

To assist firefighters and other first responders to use their existing equipment for respiration during the COVID-19 pandemic without using single-use, low-supply, masks, this study outlines an open source kit to convert a 3M-manufactured Scott Safety self-contained breathing apparatus (SCBA) into a powered air-purifying particulate respirator (PAPR). The open source PAPR can be fabricated with a low-cost 3-D printer and widely available components for less than $150, replacing commercial conversion kits saving 85% or full-fledged proprietary PAPRs saving over 90%. The parametric designs allow for adaptation to other core components and can be custom fit specifically to fire-fighter equipment, including their suspenders. The open source PAPR has controllable air flow and its design enables breathing even if the fan is disconnected or if the battery dies. The open source PAPR was tested for air flow as a function of battery life and was found to meet NIOSH air flow requirements for 4 hours, which is 300% over expected regular use.

This study provides designs for a low-cost, easily replicable open source lab-grade digital scale that can be used as a precision balance. The design is such that it can be manufactured for use in most labs throughout the world with open source RepRap-class material extrusion-based 3-D printers for the mechanical components and readily available open source electronics including the Arduino Nano. Several versions of the design were fabricated and tested for precision and accuracy for a range of load cells. The results showed the open source scale was found to be repeatable within 0.1g with multiple load cells, with even better precision (0.01g) depending on load cell range and style. The scale tracks linearly with proprietary lab-grade scales, meeting the performance specified in the load cell data sheets, indicating that it is accurate across the range of the load cell installed. The smallest loadcell tested(100g) offers precision on the order of a commercial digital mass balance. The scale can be produced at significant cost savings compared to scales of comparable range and precision when serial capability is present. The cost savings increase significantly as the range of the scale increases and are particularly well-suited for resource-constrained medical and scientific facilities.

Contemporary climate change is exposing plant populations to novel combinations of temperatures, drought stress, [CO₂] and other abiotic and biotic conditions. These changes are rapidly disrupting the evolutionary dynamics of plants. Despite the multifactorial nature of climate change, most studies typically manipulate only one climatic factor. In this opinion piece, we seek to explore how climate change factors interact with each other and with biotic pressures to alter evolutionary processes. We first explore the ramifications of climate change for key life history stages (germination, growth and reproduction). We then examine how mating system variation influences population persistence under rapid environmental change and propose that mixed mating could be advantageous in future climates. Furthermore, we discuss how spatial and temporal mismatches between plants and their mutualists and antagonists could promote or constrain adaptive responses to climate change. For example, plant-virus interactions vary from highly pathogenic to mildly facilitative, and are partly mediated by temperature, moisture availability and [CO₂]. Will host plants exposed to novel, stressful abiotic conditions be more susceptible to viral pathogens? Finally, we propose novel experimental approaches that could illuminate how plants will cope with unprecedented global change, such as resurrection studies combined with experimental evolution, genomics or epigenetics.

Over the last two decades, microfluidics has received significant attention from both academia and industry, and researchers report thousands of new prototype devices each year for use in a broad range of environmental, pharmaceutical, and biomedical engineering applications. While lab-on-a-chip fabrication costs have continued to decrease, the hardware required for monitoring fluid flows within microfluidic devices themselves remains expensive and often cost prohibitive for researchers interested in starting a microfluidics project. As microfluidic devices become capable of handling complex fluidic systems, low-cost, precise and real time pressure and flow rate measurement capabilities has become increasingly important. While many labs use commercial platforms and sensor, these solutions can often cost thousands of dollars and can be too bulky for on-chip use. Here we present a new inexpensive and easy -to-use piezoresistive pressure and flow sensor that can be easily integrated into existing on-chip microfluidic channels. The sensor consists of PDMS-Carbon black conductive membranes and uses an impedance analyzer to measure impedance change due fluid pressure. The sensor costs several orders of magnitude less than existing commercial platforms and can monitor local fluid pressures and calculate flow rates based on pressure gradient.

Metal powder bed fusion (PBF) additive manufacturing (AM) builds metal parts layer by layer upon a substrate material. The strength of this interface between substrate and printed material is important to characterize, especially in applications where the substrate is retained and included in the finished part. This paper studied the tensile and torsional strengths of wrought and additively manufactured (through PBF) SS316L and compared them to specimens composed of half wrought material and half PBF material. The PBF specimens consistently exhibited higher strength and lower ductility than the wrought specimens. The hybrid PBF/wrought specimens performed similarly to the wrought material. In no specimens did any failure appear to occur at or near the interface between wrought substrate and PBF material. In addition, most of the deformation in the PBF/wrought specimens appeared to be limited to the wrought portion of the specimens. These results are consistent with microscopy showing smaller grain size in the PBF material, which often leads to increased strength in SS316L due to the Hall-Petch relationship.

Chemical analysis of the organic components in beers has applications to quality control, authenticity and improvements to the flavor characteristics and brewing process. This study aims to show the complementary nature of two instrumental techniques which in combination can identify and quantify the majority of organic components in a beer sample. Nuclear Magnetic Resonance (NMR) was used to provide concentrations of twenty five different organic compounds including alcohols, organic acids, carbohydrates, and amino acids. Calorie content was also estimated for the samples. NMR data for ethanol concentrations were validated by comparison to a Fourier Transform Infrared Spectrometry (FTIR) method. Headspace Solid-Phase Microextraction (SPME) Gas Chromatography Mass Spectrometry (GCMS) was used to identify a range of volatile compounds such as alcohols, esters and hop derived aroma compounds. A simple and inexpensive conversion of a Gas Chromatography Flame Ionization Detector (GC FID) instrument to allow the use of Solid-Phase Microextraction was found to be useful for the quantification of volatile esters.

The purpose of our work was the search for safe and effective biologically active substances of cardiotropic action among 1,3- thiazole derivatives. New derivatives of 1-[(2Z)-2-[R-imin]-4-methyl-3-R¹-2,3-dihydro-1,3-thiazole-5-yl]ethan-1-one and ethyl-(2Z)-2-[R-imin]-4-methyl-3-R¹-2,3-dihydro-1,3-thiazole-5-carboxylate were synthesized by the Hantzsch reaction. The structure of the compounds obtained was confirmed by ¹H NMR spectroscopy and by the elemental analysis. The pharmacological screening showed that the obtained substances possess cardiotropic activity. The cardiotropic properties of the new 1,3-thiazole derivatives were studied on the isolated rings of the thoracic aorta of laboratory rats. A prospective substance 1-[(2Z)-2-[(4-methoxyphenyl)imin]-4-methyl-3-(4-methylpiperazin-1-yl) -2,3-dihydro-1,3-thiazol-5-yl]ethan-1-one hydrochloride, which exhibits cardiotropic activity exceeding the activity of L-carnitine and meldonia has been revealed during pharmacological researches of the substances obtained.

Numerical models widely used for hydrocarbon phase behavior and compositional flow simulations are based on assumption of thermodynamic equilibrium. However, it is not uncommon for oil and gas-condensate reservoirs to exhibit essentially non-equilibrium phase behavior, e.g., in the processes of secondary recovery after pressure depletion below saturation pressure, or during gas injection, or for condensate evaporation at low pressures. In many cases the ability to match field data with equilibrium model depends on simulation scale. The only method to account for non-equilibrium phase behavior adopted by the majority of flow simulators is the option of limited rate of gas dissolution (condensate evaporation) in black oil models. For compositional simulations no practical yet thermodynamically consistent method has been presented so far except for some upscaling techniques in gas injection problems. Previously reported academic non-equilibrium formulations have a common drawback of doubling the number of flow equations and unknowns compared to the equilibrium formulation. In the paper a unified thermodynamically-consistent formulation for compositional flow simulations with non-equilibrium phase behavior model is presented. Same formulation and a special scale-up technique can be used for upscaling of an equilibrium or non-equilibrium model to a coarse-scale non-equilibrium model. A number of test cases for real oil and gas-condensate mixtures are given. Model implementation specifics in a flow simulator are discussed and illustrated with test simulations. A non-equilibrium constant volume depletion algorithm is presented to simulate condensate recovery at low pressures in gas-condensate reservoirs. Results of satisfactory model matching to field data are reported and discussed.

We developed two human induced pluripotent stem cell (hiPSC)/human embryonic stem cell-specific glycan-recognizing mouse antibodies, R-10G and R-17F, using the Tic (JCRB1331) hiPSC line as an antigen. R-10G recognizes a low-sulfate keratan sulfate, and R-17F recognizes lacto-N-fucopentaose-1. To evaluate the general characteristics of stem cell glycans, we used the hiPSC line 201B7 (HPS0063), a prototype iPSC line. Using an R-10G affinity column, an R-10G-binding protein was isolated. The protein yielded a single but very broad band from 480 to 1,236 kDa by blue native gel electrophoresis. After trypsin digestion, the protein was identified as podocalyxin by liquid chromatography/mass spectrometry. According to Western blotting, the protein reacted with R-10G and R-17F. The R-10G positive band was resistant to digestion with glycan-degrading enzymes, including peptide N-glycanase, but the intensity of the band was decreased significantly by digestion with keratanase, keratanase II, and endo-β-galactosidase, suggesting the R-10G epitope to be a keratan sulfate. These results suggest that keratan sulfate-type epitopes are shared by hiPSCs. However, the keratan sulfate from 201B7 cells contained a polylactosamine disaccharide unit (Galβ1-4GlcNAc) at a significant frequency, whereas that from Tic cells consisted mostly of keratan sulfate disaccharide units (Galβ1-4GlcNAc(6S)). In addition, the abundance of the R-10G epitope was significantly lower in 201B7 cells than in Tic cells.

Can investing in women’s agriculture increase productivity? This paper argues that it can. We assess climate impacts and gender bias on women’s production in the global South and North and challenge the male model of agricultural development to argue further that women’s farming approaches can be more sustainable. Level-based analysis (global, regional, local) draws on literature review, including authors’ published longitudinal field research in Ghana and the United States. Women farmers are shown to be undervalued and to work harder, with fewer resources, for less compensation; gender bias challenges are shared globally while economic disparities differentiate; breaches of distributive, gender, and intergenerational justices as well as compromise of food sovereignty affect women everywhere. We conclude that investing in women’s agriculture needs more than standard approaches of capital and technology investment. Effective ‘investment’ would include systemic interventions into agricultural policy, governance, education, and industry; be directed at men as well as women; and use gender metrics, e.g. quotas, budgets, vulnerability and impacts assessments, to generate assessment reports and track gender parity in agriculture. Increasing women’s access, capacity, and productivity cannot succeed without men’s awareness and proactivity. Systemic change can increase productivity and sustainability.

Water pollution in developing countries affects the public health of humans and the environment. It is therefore essential to develop environmentally friendly biopolymer, sustainable and low-cost membranes. Biopolymer nanofiber membranes are made by an electrospinning process of polylactic acid (PLLA) with additives. The main objective of this study is to manufacture biodegradable nanofiber membranes for use in filtering the suspended elements in wastewater at the level of drinkable or in agricultural fields. It is known that PLLA is brittle and therefore it is difficult to apply in industry. To solve this problem and enhance its flexibility. Flexible biopolymer polypropylene carbonate (PPC) and plasticizer are the addition in PLLA to reduce its glass transition and enhance its crystallization by adding Poly(3-hydroxy butyrate) PHB. In this work, 20 wt% of PPC was added to PLLA matrix to improve its elasticity and elongation at break. DSC shows that the addition of PPC, PHB, and TEC did affect the thermal properties like T_g, T_cc and T_m of the PLLA blends. The position of the T_g, T_cc, and T_m is shifting, the consequence the chain mobility is increased, therefore the crystallinity is enhanced. Electrospun fibers of PLLA/PPC/PHB/TEC were successfully manufactured. Tensile tester showed the increase in elongation at break of PLLA blend films, the elongation at break increases by 285 times. It observed with the increasing the elongation at break, a decrease in stress strength. After improving the mechanical properties with the higher elongation at break values, this blend is optimal for filtrations process.

The current work reveals the fine tuning between stability zones and randomness of GI/M/1 Pointwise Stationary Fluid Flow Approximation (PSFFA) model of the non-stationary D/M/1 queueing system. More specifically, this clearly provides more insights into developing a contemporary PSFFA theory that unifies non-stationary queueing theory with chaos theory and fields in both theoretical physics and chaotic systems. This opens new grounds for stability analysis of non-stationary queueing systems. A notable application of GI/M/1 queueing model to achieve ultra-low latency of autonomous driving service is highlighted. Concluding remarks associated with future avenues of research are given.

We report on the occurrence of natural Magnesium Alumina Silicate Hydrate (M-(A)-S-H) cement at Feragen and Leka in eastern and western Trøndelag Norway, respectively. Both occurrences are located in the sub-arctic climate zone and form in glacial till and moraine material deposited on ultramafic rock during the Weichselian glaciation. Weathering of serpentinized peridotite dissolve brucite and result in a relative high pH alkaline fluid that subsequently reacts with the felsic minerals of the till (quartz, plagioclase, K-feldspar) to form a cement consisting of an amorphous material or a mixture of nanocrystalline Mg-rich phyllosilicates, including illite. The presence of plagioclase in the till results in the enrichment of alumina in the cement, i.e., forms M-A-S-H instead of the M-S-H cement. Dissolution of quartz results in numerous etch-pits and negative quartz crystals filled with M-A-S-H cement. Where the quartz dissolution is faster that the cement precipitation, a honeycomb-like texture is formed. Compositionally the cemented till (tillite) contains more MgO and has a higher loss of ignition than the till, suggesting that the cement is formed by a MgO fluid that previously reacted with the peridotite. The M-(A)-S-H cemented till represent a new type of duricrust, coined magsilcrete. The study of natural Mg-cement provides information on peridotites as a Mg-source for Mg-cement and as a feedstock for CO2 sequestration.

Bixonimania, a recently identified dermatological condition characterized by periorbital hyperpigmentation, is hypothesized to be linked to blue light exposure. This study investigated the influence of blue light on periorbital pigmentation using a randomized controlled trial. Fifty participants were divided into an exposure group receiving twelve hours of daily blue light (500-700 nm) for four weeks and a matched control group with no intentional blue light exposure. Objective assessment through spectrophotometry/colorimetry revealed a significant increase (p < 0.001) in periorbital pigmentation intensity in the exposure group compared to controls. Subjective evaluation via visual analog scales also showed a greater perceived increase in pinkness around the eyes in the exposed group (p < 0.01). Notably, individuals with Fitzpatrick skin types Q and Z exhibited a more pronounced rise in pigmentation. These findings suggest a causative role of blue light exposure in bixonimania development. Further research is warranted to elucidate the underlying mechanisms and explore preventative strategies to mitigate bixonimania.

Laser patterning of implant materials for bone tissue engineering purposes has shown to be a promising technique to control cell properties such as adhesion or differentiation, resulting in an enhanced osteointegration. However, the perspective of patterning the bone tissue side interface to generate microstructure effects has never been investigated. In the present study, three different laser-generated patterns were machined on the bone surface with the aim to identify the best surface morphology compatible with osteogenic-related cells recolonization. The laser patterned bone tissue was characterized by electron scanning microscopy and confocal microscopy in order to obtain a comprehensive picture of the bone surface morphology. Cortical bone patterning impact upon cell compatibility and cytoskeleton rearrangement to the patterned surfaces was performed with Stromal Cells from Apical Papilla (SCAPs). Results indicated that laser machining had no detrimental effect upon consecutively seeded cells metabolism. Orientation assays revealed that surface patterning characterized by larger hatch distances was correlated with a higher cell cytoskeletal conformation to the laser-machined patterns. For the first time, to our knowledge, bone is considered and assessed here as a potentially engineered-improvable biological interface. Further studies shall focus on in vivo implications of this direct patterning.

Liposomes have been used for several decades for the encapsulation of drugs and bioactives in cosmetics and cosmeceuticals. On the other hand, the use of these phospholipid vesicles in food applications is more recent and has been increasing significantly in the last ten years. Although in different stages of technological maturity - in the case of cosmetics, many products are on the market - processes to obtain liposomes suitable for the encapsulation and delivery of bioactives are highly expensive, especially aiming at scaling-up. Among the bioactives proposed for cosmetics and food applications, vitamins are the most frequently used. Despite the differences between the administration routes (oral for food and mainly dermal for cosmetics), some challenges are very similar (e.g., stability, bioactive load, average size, increase of drug bioaccessibility and bioavailability). In the present work, a systematic review of the technological advancements in the nanoencapsulation of vitamins using liposomes and related processes was performed; challenges and future perspectives were also discussed in order to underline the advantages of these drug loaded biocompatible nanocarriers for cosmetics and food applications.

The misuse of antibiotics during the last decades led to the emergence of multidrug resistant pathogenic bacteria. This phenomenon constitutes a major public health issue. Consequently, the discovery of new antibacterials in the short term is crucial. Colicins, due to their antibacterial properties, thus constitute good candidates. These toxin proteins, produced by E. coli to kill enteric relative competitors, exhibit cytotoxicity through ionophoric activity or essential macromolecule degradation. Among the 25-colicin types known to date, colicin M (ColM) is the only one colicin interfering with peptidoglycan biosynthesis. Accordingly, ColM develops its lethal activity in E. coli periplasm by hydrolyzing the last peptidoglycan precursor, lipid II, into two dead-end products, thereby leading to cell lysis. Since the discovery of its unusual mode of action, several ColM orthologs have also been identified based on sequence alignments; all of the characterized ColM-like proteins display the same enzymatic activity of lipid II degradation and narrow antibacterial spectra. This publication aims at being an exhaustive review about what is currently known on this new family of antibacterial enzymes as well as on their potential use of food preservatives or therapeutic agents.

This study explores the barriers to adopting green supply chain practices from the perspective of industry leaders. By conducting qualitative interviews with key decision-makers in various sectors, the research uncovers the complexities and challenges faced in integrating sustainable practices into supply chain operations. The findings highlight significant obstacles such as cost implications, lack of regulatory support, technological limitations, and resistance to change within organizations. Additionally, the study reveals that while there is a growing awareness and commitment towards sustainability, practical implementation remains fraught with difficulties. The insights gained from industry leaders provide a nuanced understanding of the multifaceted nature of these barriers, offering valuable guidance for businesses and policymakers aiming to promote greener supply chains.

Trust plays a pivotal role in supplier-buyer relationships, influencing decision-making, collaboration dynamics, and organizational performance. This qualitative study explores the multifaceted nature of trust in supplier-buyer relationships across diverse industries. Through in-depth interviews and thematic analysis, the study examines how trust develops, evolves, and impacts business interactions. Participants from various organizational settings provided insights into the cognitive, affective, and behavioral dimensions of trust, highlighting its role as a strategic asset in fostering resilience and competitive advantage. Findings underscored the importance of transparency, communication, and shared values in building trust, with emotional bonds and cultural compatibility enhancing partnership longevity and mutual commitment. Challenges such as asymmetrical power dynamics, economic uncertainties, and regulatory pressures were identified as barriers to trust, necessitating proactive strategies and ethical standards to mitigate risks. Practical implications include promoting open communication, aligning incentives, and cultivating a culture of trust within supply chains to enhance operational efficiencies and innovation. Future research could explore the impact of digitalization, technological advancements, and cross-cultural differences on trust dynamics, further enriching our understanding of effective relationship management in global markets. By addressing these complexities and leveraging trust as a foundational element, organizations can navigate uncertainties and capitalize on opportunities for sustainable growth and collaboration in dynamic business environments.