Acute coronary syndrome (ACS) is a life-threatening condition that requires a prompt diagnosis and therapeutic intervention. Although serum troponin T and creatinine kinase-MB (CK-MB) are established biomarkers for ACS, it may take several hours to reach diagnostic values for ACS. In this study, we attempted to explore novel biomarkers for ACS with higher sensitivity than that of troponin T and CK-MB. The metabolomic profiles of 18 patients with ACS upon hospital arrival and those of the age-matched control (HC) group consisted of 24 healthy volunteers were analyzed using liquid chromatography-time-of-flight mass spectrometry. Volcano plots showed 24 metabolites whose concentrations differed significantly between the ACS and HC groups. Using these data, we developed a multiple logistic regression model for the ACS diagnosis, in which lysine, isocitrate, and tryptophan were selected as minimum-independent metabolites. The area under the receiver operating characteristic curve value for discriminating ACS from HC was 1.00 (95% confidence interval [CI]: 1.00-1.00). In contrast, those for troponin T and CK-MB were 0.917 (95% confidence interval [CI]: 0.812-1.00) and 0.988 (95% CI: 0.966-1.00), respectively. This study showed the potential of combining three plasma metabolites to discriminate ACS from HC with a higher sensitivity than that of troponin T and CK-MB.

Oligodendrocyte progenitor cells (OPCs) represent a subtype of glia giving rise to oligodendrocytes, the myelin forming cells in the central nervous system (CNS). While OPCs are highly proliferating during development, they become relatively quiescent during adulthood, when their fate is strictly influenced by the extracellular context. In traumatic injuries and chronic neurodegenerative conditions including those of autoimmune origin, oligodendrocytes undergo apoptosis, and demyelination starts. Adult OPCs become immediately activated, they migrate at the lesion site and proliferate to replenish the damaged area, but their efficiency is hampered by the presence of a glial scar, a barrier mainly formed by reactive astrocytes, microglia, and the deposition of inhibitory extracellular matrix components. If, on one hand, glial scar limits the lesion spreading, it also blocks tissue regeneration. Therapeutic strategies aimed at reducing astrocyte or microglia activation and shifting them toward a neuroprotective phenotype have been proposed, whereas the role of OPCs has been largely overlooked. In this review, we have considered glial scar from the perspective of OPCs, analysing their behaviour when lesions originate and exploring the potential therapies aimed at sustaining OPCs to efficiently differentiate and promote remyelination.

This study presents a detailed computational investigation aimed at identifying and evaluating potential small organic molecular scaffolds as inhibitors targeting the Pks13 protein, a critical enzyme in tuberculosis (TB) drug discovery. Our approach integrates multiple computational techniques, including quantitative structure-activity relationship (QSAR) modelling, compound library generation, molecular docking, biological activity prediction, re-evaluation of screened compounds, molecular dynamics (MD) analysis, and binding free energy estimation using the MM-GBSA approach. We developed a robust QSAR model using multiple linear regression (MLR) techniques, specifically tailored to predict the minimum inhibitory concentration (MIC) values of potential anti-TB agents. This model demonstrated excellent predictive performance, validated through rigorous internal and external validation procedures. Through molecular docking simulations, we identified five promising inhibitors Ethyl (R,Z)-2-(2-((2-chlorobenzyl) oxy)benzylidene)-5-(4-chlorophenyl)-7-methyl-3-oxo-2,3-dihydro-5H-thiazolo [3,2-a] pyrimidine-6-carboxylate (PKD1), (7R,9aR)-7-(2-hydroxyphenyl)-4-(2-methoxyphenyl)-3-methyl-7,8,9,9a-tetrahydroisoxazolo[5,4-b]quinolin-5(6H)-one (PKD2), (7-(4-methoxy phenyl)-2-methyl-3-phenylpyrazolo[1,5-a]pyrimidin-5-yl)(4-(3-(trifluoromethyl)phenyl) piperazin-1-yl)methanone (PKD3), (8S,10S)-10-(((2R,4S,5S,6S)-4-amino-5-hydroxy-6-methyl tetrahydro-2H-pyran-2-yl)oxy)-6,8,11-trihydroxy-8-(2-hydroxyacetyl)-1-methoxy-7,8,9,10-tetra-hydrotetracene-5,12-dione (PKD4), 3-(3,4-dimethylphenyl)-5-((2-(4-fluorophenyl)-2-oxoethyl) thio)-6-phenyl-2-thioxo-2,3,5,7a-tetrahydrothiazolo[4,5-d]pyrimidin-7(6H)-one (PKD5)with high binding affinities, prioritizing them based on their binding energies. These selected compounds were further assessed for their biological activity predictions, guiding the selection of candidates for experimental validation. Subsequent re-evaluation using absolute binding free energy estimation and MD simulations provided insights into the stability and dynamics of the protein-ligand complexes over time. Our findings highlighted the potential of identified compounds as stable binders within the Pks13-TE domain binding pocket, underscoring their viability as drug candidates. Additionally, binding free energy analysis using MM-GBSA reaffirmed the strong affinity of the proposed compounds towards Pks13. Our integrated computational approach offers a systematic and detailed framework for the identification and characterization of potential Pks13 inhibitors with specific relevance to TB drug discovery.

Over the past decade and a half, dynamic functional imaging has revolutionized the neuroimaging field. Since 2009, it has revealed low dimensional brain connectivity measures, has identified potential common human spatial connectivity states, has tracked the transition patterns of these states, and has demonstrated meaningful alterations in these transition and spatial patterns in neurological disorders, psychiatric disorders, and over the course of development. Recently, researchers have begun to analyze this data from the perspective of dynamic system and information theory in the hopes of understanding how these dynamics support less easily quantified processes, such as information processing, cortical hierarchy, and consciousness. Consciousness, in particular, appears to be strongly linked to entropy production in the brain. Little attention has been paid to the effects of psychiatric disease on entropy production in the human brain, however. Even disorders characterized by substantial changes in conscious experience have not been widely analyzed from this perspective. We begin to rectify this by examining the complexity of subject trajectories in state space through the lens of information theory. Specifically, we identify a basis for the dynamic functional connectivity state space and track subject trajectories through this space over the course of the scan. The dynamic complexity of these trajectories is assessed along each dimension of the proposed basis space. Using these estimates, we demonstrate that schizophrenia patients display substantially simpler trajectories than demographically matched healthy controls, and that this drop in complexity concentrates along specific dimensions. We also demonstrate that entropy generation in at least one of these dimensions is linked to cognitive performance. Overall, results suggest great value in applying dynamic systems theory to problems of neuroimaging and reveal a substantial drop in the complexity of schizophrenia patients’ brain function.

An increased demand for natural products nowadays most specifically probiotics (PRO) is evident since it comes in conjunction with beneficial health effects for the consumers. In this regard, it is well known that encapsulation could affect positively the PRO's viability throughout food manufacturing and long-term storage. This paper aims to analyze and review various multilayer strategies for encapsulation of PRO. Double-layer encapsulation of PRO by electro-hydrodynamic atomization or electrospray technology has been reported along with layer-by-layer assembly and water-in-oil-in-water (W1/O/W2) double emulsions to produce multilayer PRO-loaded carriers. Finally, their applications in food products are presented. The resistance (cover material) and viability of (PRO) to mechanical damage, during gastrointestinal transit and shelf life of these trapping systems are also described. The PRO encapsulation in double and multiple-layer coatings combined with other technologies can be examined to increase the opportunities for new functional products with amended functionalities opening a novel horizon in food technology.

Objective: The goal of this review is to provide a succinct, yet comprehensive, guide to the an-tepartum management of multiple gestations. Methods: This narrative review on twins and multiple gestation provides a concise guide for providers with this ever-growing patient population. PubMED was utilized for literature search. Each reference was evaluated and graded for quality of evidence by US Preventative Services Task Force and Cochrane Review guidelines. Screening, surveillance, and management strategies are delineated succinctly and organized by type of multiple gestation being managed from the lowest risk dichorionic twin pair to the increasingly escalating risks of twins and higher order multiples sharing a placenta and/or amniotic sac. Results: The incidence of twin pregnancies has grown over the past several years, due in large part to delayed reproductive timing and surge in assisted reproductive technologies. Twin pregnancies are associated with higher morbidity for both gravidas and offspring, warranting evidence-based approach in counseling and management. Conclusions: We note the important differences among multiples in chorionicity and amnionicity, in the importance of close surveillance and early delivery. Graded clinical pearls and evi-dence-based recommendations are presented to guide obstetric providers.

Undernutrition and micronutrient deficiencies such as anemia are considered significant public health challenges in Bangladesh, which enhancing fish consumption is a well-established food-based intervention to address these. This paper documents the establishment of community-based fish chutney production and reports the impact of its consumption on mid-upper arm circumference (MUAC) and hemoglobin (Hb) levels among targeted 150 pregnant and lactating women (PLW) in rural Bangladesh. A fish chutney was developed using locally available ingredients followed by a series of laboratory tests, including nutrient composition, shelf-life and food safety. A community-based fish chutney production process was designed to: 1) supply locally available ingredients for processing; 2) establish two fish drying sites; 3) initiate a community-based production site, and 4) distribute fish chutney to PLW by six women nutrition field facilitators for one year. Then a pre- and post-intervention study was designed for a selected 150 PLW to receive 30g of fish chutney daily for 12 months. Differences in mean mid-upper arm circumference (MUAC) and hemoglobin (Hb) levels pre- and post-consumption were analyzed using one-way analysis of variance. Consumption of 30g of fish-chutney resulted in significant increases of the mean values of Hb levels and MUAC among the targeted PLW.

Background/Purpose: Multimorbidity of malaria, anaemia, and malnutrition (MAMM) is a condition in which an individual cohabits with two or more of these health outcomes and is becoming an emergent public health concern in sub-Saharan African countries. The independent associations of a child’s demographic variables and socioeconomic disparities with a child’s health outcomes have been established in literature. However, the effects of the intersection of these factors on MAMM, while accounting for other covariates have not been studied. Therefore, this study aimed to determine how children’s sex, age and socioeconomic status interact to explain the variations in MAMM among children aged 6-59 months in Nigeria. Methods: Data from the 2018 Nigeria Demographic and Health Survey and the 2018 National Human Development Report (NHDR) were used. The study includes weighted samples of 10,184 children aged 6-59 months in Nigeria. A three-level multilevel mixed effect ordinal logistic regression model such that individual characteristics at level 1 are nested in communities at level 2 and nested in states at level 3 was used. Subsequently, predictive probability charts and average adjusted probability tables were used to interpret the intersectional effects. Five models were created in this scenario. Model 1 is the interaction between the child's sex and wealth status; model 2, child's sex and age; model 3 is between child's age and wealth status; model 4 has the three 2-way interactions of child's sex, age, and household wealth status, and model 5 includes model 4 and the 3-way interactions between a child's sex, age, and wealth quintiles. Results: The prevalence of children with ‘none of the three diseases’ outcomes was 17.3% (1767/10,184), while, 34.4% (3499/10,184) had ‘only one of the diseases’, and 48.3% (4,918/10,184) cohabit with ‘two or more’ of MAMM. However, in the multivariate analyses, model 3 was the best fit compared with other models, so, that the two-way interaction effects of a child's age and wealth status are significant predictors in the model. Children aged 36-47 months living in the poorest households have the probability of 0.11, 0.18, and 0.32 of contracting MAMM above the probability of children of the same age and live in the middle, more prosperous and richest households, respectively, while all other covariates are held constant. Thus, the variation in MAMM over a child's age differs depending on the household wealth quintile. In other words, as the children grow older, variations in MAMM become more evident between the rich and the poor household. Conclusion: Therefore, it is recommended that policies that are geared toward economic redistribution will help bridged the disparities observed in multiple diseases among children aged 6-59 months in Nigeria

Gender has been a rarely addressed aspect in digital game-based learning (DGBL). Likewise, mixed results have been presented regarding the effects according to gender and the conditions that generate these effects. The present work studies the effects of a drill-and-practice mathe-matical game on primary students. The study focused on an analysis by gender, measuring learning performance, and motivation in the practice activity. Also, two instructional mechanics were considered regarding the question answering, a multiple-try (MTF) and a single-try (STF) condition, to search for possible differences. A total of 81 students from 4 courses and 2 schools participated in the experiment. The study's main findings were that: (a) the girls outperformed boys in terms of students' learning gains, (b) girls presented lower levels of competence and autonomy than boys, (c) in the MTF, girls presented lower levels of autonomy but no differences in competence contrasted to boys, (d) in the STF, girls presented lower levels of competence but no differences in autonomy against boys, and (e) no differences existed in interest, effort and value among gender overall o per instructional condition. This study enhances the knowledge of gender differences under diverse instructional settings, in particular providing insights into possible differences by gender when varying the number of attempts provided to students.

By repeated unloading and loading of the excavation dynamic and static loads, repeated train dynamic and static loads of multi-factors, the underpass tunnel, cross tunnel engineering influence area rock layer, the existing tunnel structure of the three constitutes a multifaceted structure, multi-factor interaction system. Existing tunnels into the prediction theory model of the new tunnel excavation process of dynamic and static loads, dynamic and static loads of existing tunnels are mostly analyzed individually, the results of synergistic analysis needs to be improved. Based on the theory of the current layer method, the paper comprehensively considers the stiffness of the existing tunnel, the stiffness of the new tunnel, the excavation method load and the existing tunnel load, coupled with Peck's empirical formula, the theoretical model of deformation prediction for excavation of a two-lane highway tunnel under the tunnel through the existing railroad is proposed, and verified and optimized by numerical calculations and monitoring data, which proves the applicability and reliability of the theoretical model in the similar strata and the project promotion.

MicroRNAs (miRNAs), particularly miR-16 and miR-21, play a crucial role in mul-tiple myeloma (MM) pathogenesis by regulating gene expression. This study evalu-ated the prognostic significance of circulating miR-16 and miR-21 expression levels in 48 patients with MM at diagnosis treated with lenalidomide/dexamethasone (LD) compared with 15 healthy individuals (HI). All patients were treated with LD, 13 at first line and 35 at relapse, of whom 21 were tested twice at diagnosis and before LD initiation. The results revealed significantly lower levels of miR-16 and miR-21 in patients than in HIs, both at diagnosis and relapse, with decreased miR-16 levels at diagnosis, indicating improved overall survival (OS) (p value 0.024). Furthermore, miR-16 and miR-21 levels were associated with disease markers, while both corre-lated with the depth of response and mir-16 with sustained response to LD treatment. The ratios of both miR-16 and miR-21 expression levels (prior to LD treat-ment/diagnosis) below 2 predicted a shorter time to response (P = 0.027) and a longer time to next treatment (P = 0.042), respectively. These findings suggested a prognostic value for serum miR-16 and miR-21 levels in MM, as their expression levels corre-lated with disease variables and treatment outcomes.

Understanding the optimal strategy for a real estate investment and how performance changes based on characteristics is crucial for optimising the achievable return. This is prominent in tourist areas such as Paphos where there is no clear distinction as to whether short or long-term approaches are optimal. The study aimed to develop a model for predicting the optimal rental strategy whilst assessing which model performed best and which property attributes impacted its return the greatest. Short-term data was collected from AirDNA and long-term data was manually collected from real estate agents websites. Furthermore, Random Forest, K-Nearest Neighbour and Multiple Linear Regression models were created to predict the highest and best use for each property. Model accuracy varied between data sets with the best performing model for short-term properties being Random Forest (R-Squared: 0.843), and Distance-Based Multiple Linear Regression for long-term approach (R-Squared: 0.843). The study demonstrated that accurate models could be created to predict the optimal rental strategy with the number of bedrooms being the main driver for rental income, followed by luxury finishes and the presence of a pool. It found that locational characteristics didn’t impact the returns significantly assuming that the property was located within a tourist area.

Deep Neural Network (DNN) inference demands substantial computing power, resulting in significant energy consumption. A large number of negative output activations in convolution layers are rendered zero due to the invocation of the ReLU activation function. This results in a substantial number of unnecessary computations that consume significant amounts of energy. This paper presents ECHO: Energy-efficient Computation Harnessing Onilne Arithmetic - A MSDF-based accelerator for DNN inference, designed for computation pruning, utilizing an unconventional arithmetic paradigm known as online/ most-significant digit first (MSDF) arithmetic which performs computations in a digit-serial manner. The MSDF digital serial computation of online arithmetic enables overlapped computation of successive operations leading to substantial performance improvements. The online arithmetic, coupled with a negative output detection scheme, facilitates early and precise recognition of negative outputs. This, in turn, allows for the timely termination of unnecessary computations, resulting in a reduction of energy consumption. The implemented design has been realized on the Xilinx Virtex-7 VU3P FPGA and subjected to a comprehensive evaluation through a rigorous comparative analysis involving widely used performance metrics. Experimental results demonstrate promising power and throughput improvements compared to contemporary methods. In particular, the proposed design achieved an average improvement in power consumption of up to 81%, 82.9%, and 40.6% for VGG-16, ResNet-18, and ResNet-50 workloads compared to the conventional bit-serial design, respectively. Furthermore, significant average speedups of 2.39×, 2.6×, and 2.42 were observed when comparing the proposed design to conventional bit-serial designs for VGG-16, ResNet-18, and ResNet-50 models respectively.

Transition from basic to higher education is regarded as a ‘juggle of many balls’ because students ought to balance between theoretical and clinical requirements, including social life. As a result, a significant number of undergraduate first-year nursing students succumb to these challenges due to lack of coping mechanisms emanating from poor resilience. As a result, the aim of this study was to determine the factors that influence resilience among undergraduate first-year nursing students at a South African university. A quantitative cross-sectional descriptive research design was followed. Data was collected using an adapted self-administered online questionnaire. Principal component analysis extraction method and Varimax rotation were used to analyse data. A total of 123 participants completed the questionnaire. The eigenvalues showed that the first factor explained 23.9% of the variance, the second factor 11.2%, a third factor 7.5% while the fourth factor explained 5.9% of the variance. The fifth until the eight factor had eigenvalues greater than 1 but less than 2. This study showed that resilience can be dependent on various factors such as lecture support, parental support, academic achievement, peer and mentor support, optimism about the future and being self-determined.

This work presents the mathematical framework of the Second-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems (abbreviated as “2nd-CASAM-L”), which enables the most efficient computation of exactly obtained mathematical expressions of first- and second-order sensitivities of a generic system response with respect to functions (“features”) of model parameters. Subsequently, the first- and second-order sensitivities with respect to the model’s uncertain parameters, boundaries, and internal interfaces are obtained analytically and exactly, without needing large-scale computations. Within the 2nd-FASAM-L methodology, the number of large-scale computations is proportional to the number of model features (defined as functions of model parameters), as opposed to being proportional to the number of model parameters, which are considerably more than the number of features, being incomparably more efficient and more accurate than any other methods (statistical, finite differences, etc.) for computing exact expressions of response sensitivities (of any order) with respect to the model’s features and/or primary uncertain parameters, boundaries, and internal interfaces. The application of the 2nd-CASAM-L methodology is illustrated using a simplified energy-dependent neutron transport model of fundamental significance in nuclear reactor physics.

Multiple sclerosis is an autoinflammatory condition that results in damage of myelinated neurons in affected patients. While disease-modifying treatments have been successful in slowing the progression of relapsing remittent disease, most patients still progress to secondary progressive disease that is largely unresponsive to disease-modifying treatments. Similarly, there is currently no effective treatment for patients with primary progressive MS. Innate and adaptive immune cells in the CNS play a critical role in initiating an autoimmune attack and in maintaining the chronic inflammation that drives disease progression. In this review, we will focus on recent insights into the role of T cells with regulatory function in suppressing the progression of MS, and, more importantly, in promoting the remyelination and repair of MS lesions in the CNS. We will discuss the exciting opportunity to genetically reprogram regulatory T cells to achieve immune suppression and enhance repair locally at sites of tissue damage, while retaining a fully competent immune system outside the CNS. In the future, reprogramed regulatory T cells with defined specificity and function may provide life medicines that can persist in patients and achieve lasting disease suppression after one cycle of treatment.

Multiple myeloma (MM) accounts for about 10 to 15% of all diagnosed hematologic malignancies and about 1-2% of all cancer cases. Approximately 80-90% of MM patients develop bone disease and the changes rarely regress. It is only possible to stop or slow their progression. A major role in bone destruction in MM is attributed to the Wnt signaling pathway, and its action can be modified by various types of interventions including training and diet. Therefore, the aim of this project was to evaluate the effects of a Nordic Walking (NW) training cycle and intermittent fasting (IF) on the levels of selected bone turnover markers associated with the Wnt pathway in patients with MM. Results from 35 patients divided into training (NW and IF NW) and non-training (IF and control) groups were included in the analysis. A 6-week training cycle involving 60-minute workouts 3 times a week was conducted. Body mass and composition and the levels of: vitamin D, calcium and phosphorus, beta2-microglobulin and albumin were examined before and after completion of training cycle. Markers of bone turnover were also determined: sclerostin (SOST), Dickkopf-related protein 1 (DKK-1), osteoprotegrin (OPG), osteopontin (OPN) and Tartrate-resistant acid phos-phatase 5b (TRACP 5b). There was no negative effect of IF or combined training and fasting on the nutritional status of the patients (the level of albumines was unchanged). Both training groups showed an increase in serum concentrations of the active metabolite of vitamin D (IF NW and NW: p=0.001 and p=0.022, re-spectively). The change in the concentration of this vitamin negatively correlated with the con-centration of TRACP 5b (r=-0.413, p=0.014). Evaluating the concentrations of markers related to bone turnover, a reduction in the concentrations of SOST (time: p=0.026, time vs. group: p=0.033) and TRACP 5b (time: p

Estimating parameters for multiple datasets can be time consuming, especially when the number of datasets is large. One solution is to sample from multiple datasets simultaneously using Bayesian methods such as adaptive multiple importance sampling (AMIS). Here we use the AMIS approach to fit a von Misses distribution to multiple datasets for wind trajectories derived from a Lagrangian Particle Dispersion Model driven from a 3D meteorological data. The primary objective is to characterise the uncertainties in wind trajectories in a form that can be used as inputs for predictive models of wind-dispersed insect pests and pathogens of agricultural crops for use in evaluating risk and in planning mitigation actions. Our results show that AMIS can significantly improve the efficiency of parameter inference for multiple datasets.

The development of multiple drug resistant (MDR) cancer all too often signals the need for alternative toxic therapy or palliative care. Our recent in vivo and in vitro studies using canine MDR lymphoma cancer cells demonstrated that the Anaphase Promoting Complex (APC) is impaired in MDR cells compared to normal canine control and drug sensitive cancer cells. Here, we sought to establish whether this phenomena is a generalizable mechanism independent of species, malignancy type or chemotherapy regime. To test the association of blunted APC activity with MDR cancer behavior, we used matched parental and MDR MCF7 human breast cancer cells, and a patient derived xenograft (PDX) model of human breast cancer. We show that APC activating mechanisms, such as APC subunit 1 (APC1) phosphorylation and CDC27/CDC20 protein associations, are reduced in MCF7 MDR cells when compared to chemosensitive matched cell lines. Consistent with impaired APC function in MDR cells, APC substrate proteins failed to be effectively degraded. Similar to our previous observations in canine MDR lymphoma cells, chemical activation of the APC using Mad2 Inhibitor-1 (M2I-1) in MCF7 MDR cells enhanced APC substrate degradation and resensitized MDR cells in vitro to the cytotoxic effects of the alkylating chemotherapeutic agent, Doxorubicin (DOX). Using cell cycle arrest/release experiments we show that chemo-sensitive and -resistant MCF7 cells progress through the cell cycle at similar rates, but mitosis is delayed in MDR cells with elevated substrate levels. When treated with M2I-1, MDR cells progress through mitosis at a faster rate that coincides with reduced levels of APC substrates. In our PDX model, mice growing a clinically-MDR human breast cancer tumor show significantly reduced tumor growth when treated with M2I-1, with evidence of increased DNA damage and apoptosis. Thus, our results strongly support the hypothesis that APC impairment is a driver of aggressive tumor development and that targeting the APC for activation has the potential for meaningful clinical benefits in treating recurrent cases of MDR malignancy.

The goal was to model the irrigated (IBY) and rainfed (RBY) bean yields, as a function of essential climatic variables (ECVs), in the center (Culiacán) and south (Rosario) from Sinaloa. In Sinaloa, and for the period 1982–2013 (October–March), the following were calculated: a) temperatures. b) average degree days for the bean, c) cumulative potential evapotranspiration and d) cumulative effective precipitation. For ECVs, from the European Space Agency, e) daily soil moisture. f) IBY and RBY, from the Agrifood and Fisheries Information Service. Multiple linear regressions were applied, which modeled IBY–RBY (dependent variables), as a function of ECVs (independent variables). Then, to establish each Pearson correlation (PC) as significantly different from zero, a hypothesis test was applied: PC vs Pearson's critical correlation (CPC). The four models obtained were significantly predictive: IBY–Culiacán (PC = 0.590 > CPC = |0.349|), RBY–Culiacán (PC = 0.734 > CPC = |0.349|), IBY–Rosario (PC = 0.621 > CPC = |0.355|) and RBY–Rosario (PC = 0.532 > CPC = |0.349|). This study is the first in Sinaloa to predict IBY and RBY based on ECVs, contributing to the production of sustainable food.

Maize is an important staple food crop in sub-Saharan Africa (SSA). However, the average grain yield on farmers’ fields falls considerably short of the demand of the region’s population. In addition, the normal endosperm maize widely consumed in SSA is deficient in vitamin A. Drought, a consequence of climate change, is a major constraint to maize production, resulting in seasonal low grain yield in farmers’ fields. The objectives of this study were to assess the performance of newly developed extra-early maturing provitamin A hybrids under managed drought and well-watered conditions, compare the outcomes of multiple trait base-index and multi-trait genotype-ideotype distance index selection procedures, and identify drought-tolerant hybrids with stable performance across contrasting environments for commercialization in SSA. One hundred and ninety provitamin A hybrids and six checks were evaluated under managed drought and well-watered conditions at Ikenne for two seasons between 2021 and 2023. A 14*14-lattice design was used for the field evaluations under both research conditions. Drought stress was achieved by the complete withdrawal of irrigation water 25 days after planting. Results revealed significant differences among the hybrids under drought and well-watered conditions. Grain yield, ears per plant, and plant aspect under managed drought were correlated to the same traits under well-watered conditions suggesting that the expression of these traits is governed by common genetic factors. Twenty-nine hybrids were identified as top-performing drought-tolerant hybrids by the multiple trait base index and multiple-trait genotype–ideotype distance index. Of the selected outstanding 29 hybrids, 34% were derived from crosses involving the tester TZEEIOR 197, demonstrating the outstanding genetic potential of this inbred line. Further analysis of the 29 selected hybrids revealed TZEEIOR 509 × TZEEIOR 197 as the hybrid that combined the most drought-tolerant adaptive traits. However, the hybrids TZEEIOR 526 × TZEEIOR 97, TZEEIOR 384 × TZEEIOR 30, TZEEIOR 515 × TZEEIOR 249, TZEEIOR 510 × TZEEIOR 197, TZEEIOR 479 × TZEEIOR 197, and TZEEIOR 458 × TZEEIOR 197 were identified as the most stable hybrids across drought and well-watered conditions. These hybrids should be extensively tested in multi-location trials for deployment and commercialization in SSA.

In this paper, we propose a method to find all efficient solutions of an interval multiple objective linear programming (IMOLP) problem with interval coefficients in the objective functions, the constraint matrix and the right-hand side vector. The set of all efficient solutions of an IMOLP problem can completely supply information to the decision makers in finding their most preferred solutions but, up to now, not all solutions of an IMOLP problem can be found by known methods. A numerical example is given to illustrate the working of the proposed method.

Background: Several studies recently confirmed the emergence of resistance to antimalarial drugs in sub-Saharan Africa. Multiple first-line treatment (MFT) is one of the measures envisaged to respond to the emergence and spread of this resistance. The aim of this study was to identify perceived advantages and disadvantages of several MFT deployment strategies and to better understand potential implementation drivers and barriers. Methods: A qualitative survey was conducted in seven sub-Saharan countries amongst key opinion-leaders, national decision-makers, and end users. A total of 200 individual interviews were conducted and findings were analyzed following a thematic inductive approach. Results: From a policy perspective, the new MFT intervention would require endorsement at the global, national, and regional levels to ensure its inclusion in guidelines. Funding of the MFT intervention could be a bottleneck due to costs associated with additional training of healthcare workers, adaptation of drug delivery mechanisms, and higher costs of drugs. Concerning the MFT deployment strategies, a slight preference for the segmentation strategy was expressed over the rotation and geographic approaches, due to the perception that a segmentation approach is already in place at country level. Conclusions: The findings highlighted the need for a collective approach to MFT deployment through the engagement of stakeholders at all levels of malaria management.

Significant changes to the new National College Entrance Examination (NCEE) and the implementation of the “Double First-Class” (DFC) initiative in China are coincidentally in the national spotlight and fall within the same policy window. However, few studies have investigated the effects of the new NCEE on the quality of students in DFC universities. By leveraging the 2018-2022 college admission data from Shandong Province, these effects are examined via the interrupted time-series technique. Weighted rankings for liberal arts and science disciplines and the admission ranking coefficient are adopted to ensure comparability before and after the reform. The findings reveal that after the reform, the quality of students in both world-class universities and first-class discipline universities improved, with greater improvements seen in world-class universities. Focusing on urban differences, the quality of students in DFC universities located in second-tier cities is found to have experienced a higher increase as compared with students in the first-tier and new first-tier cities. In addition, the reform has had different impacts on the quality of students in different majors. Furthermore, when selecting postsecondary institutions, high-scoring students prioritize the quality of universities and majors over urban factors. Finally, the implications of the new NCEE in relation to a sustainable development of DFC universities for research, policy, and practice are further discussed.

German noise action plans aim to reduce negative health outcomes from noise exposure and identify quiet areas free of noise pollution. Quiet area identification in German noise action plans is based primarily on noise mapping and spatial analysis and not empirical or qualitative data about acoustic environments, thus leaving a gap in the understanding of the quality of formally recognized quiet areas in noise action plans. This work presents a comparative empirical case study in Dortmund, Germany, with the aim to describe the diurnal dB(A) and biophonic properties of quiet areas versus noise 'hot spots'. Sound observations were collected (n=282,764) in five different natural or recreational land use patch types larger than four acres within 33 proposed quiet areas in Dortmund (n=70) and 23 noise hot spots between April 27^th, 2022 and March 2^nd, 2023. We find that quiet areas are on average more than 20 dB(A) quieter than noise hot spots almost every hour of the day. Forests, managed tree stands, cemeteries, and agriculture diel patterns are dominated by dawn dusk chorus in spring and summer, whereas sport and recreation as well as noise hot spots are dominated by traffic and human noise. A novel composite biophony mapping procedure is presented that finds distinct temporal distribution of biophony in forested and agriculture peri-urban locations positively associated with patch size, distance away from LDEN > 55, proximity to water, and the number of vegetation layers in the plant community. Anthrophony distribution dominates urban land uses in all hours of the day, but expands during day and evening and contracts at night and in dusk hours. The procedures presented here illustrate how qualitative information regarding quiet areas can be integrated into German noise action planning.

As the adoption of renewable energy sources grows, ensuring a stable power balance across various time frames has become a central challenge for modern power systems. In line with the "dual carbon" objectives and the seamless integration of renewable energy sources, harnessing the advantages of various energy storage resources and coordinating the operation of long-term and short-term storage have become pivotal directions for future energy storage deployment. To address the complexities arising from the coupling of different time scales in optimizing energy storage capacity, this paper proposes a method for energy storage planning that accounts for power imbalance risks across multiple time scales. Initially, the Seasonal and Trend decomposition using the Loess (STL) decomposition method is utilized to temporally decouple actual operational data. Subsequently, power balance computations are performed based on the obtained data at various time scales to optimize the allocation of different types of energy storage capacities and assess the associated imbalance risks. Finally, the effectiveness of the proposed approach is validated through hourly applications using real-world data from a province in China over recent years.

The structural, elastic, and electronic properties of orthorhombic Cd2SiO4 and Hg2GeO4 were examined under varying pressure conditions using first-principles calculations based on densi-ty-functional theory employing the projector augmented wave method. The obtained cell pa-rameters at 0 GPa were found to align well with existing experimental data. We delved into the pressure-dependence of normalized lattice parameters and elastic constants. In Cd2SiO4, all lat-tice constants decreased as pressure increased, whereas in Hg2GeO4, parameters a and b de-creased while parameter c increased under pressure. Employing the Hill average method, we calculated the elastic moduli and Poisson’s ratio up to 10 GPa, noting an increase with pressure. Evaluation of ductility/brittleness under pressure indicated both compounds remained ductile throughout. We also estimated elastic anisotropy and Debye temperature under varying pres-sures. Cd2SiO4 and Hg2GeO4 were identified as indirect band gap insulators, with estimated band gaps of 3.34 eV and 2.09 eV, respectively. Interestingly, Cd2SiO4 exhibited a significant increase in band gap with increasing pressure, whereas the band gap of Hg2GeO4 decreased under pres-sure, revealing distinct structural and electronic responses despite their similar structures.

In Spain, the National Health System, of a public nature, provides care to Spaniards and other residents in Spain. It is a system adapted to the State of Autonomies, decentralized. Each Auton-omous Community has legislative capacity in its organization and management. We studied the agreement of private hospitals by the public system in La Rioja, an Autonomous Community of Spain located in the North of the Iberian Peninsula. Documentary sources from the General archives of La Rioja, the Institute of Riojan Studies, municipal funds (Logroño, Haro, Calahorra), and in-formation from catalogs and censuses of hospitals from the Ministry of Health, National Institute of Statistics, and Institute of Statistics of La Rioja have been reviewed. The hospital model of La Rioja is characterized by a predominance of public beds over private ones, although there is a growing trend in the number of private beds from 2013 onwards, due to the incorporation of two conva-lescent socio-health hospitals. A characteristic element of La Rioja has been the promotion of pub-lic-private collaboration, conceived as a strategic alliance. Regarding agreements, in La Rioja there has been a specialization in the socio-health space, whose formulas have been the management service contract and the concession of work. The development of the Health System in La Rioja, 1986-2019, has been determined by the presence of a mixed public-private hospital system and a progressively lower dependence on specialized hospitals from other Autonomous Communities.

: Controlling the distribution of water and wastewater between industrial processes is very vital in rationalizing water and preserving the environment. In this paper, a mathematical technique is proposed to optimize water-wastewater networks; a nonlinear program is introduced to minimize the consumption of freshwater, and consequently, the flowrate of the wastewater dis-charge will be also minimized. A general mathematical model, able to handle industrial plants containing up to eight sources and eight sinks, is developed using LINGO optimization software to facilitate dealing with complex case studies. The introduced model can handle single contam-inant networks as well as multiple contaminants cases. The optimal water network is synthe-sized through two steps; the first step is to introduce the case study data to the developed mathematical model. The second step considers using the optimal solution produced after run-ning the developed LINGO model as feed data for a pre-designed Excel sheet able to deal with these results and simultaneously draw the optimal water-wastewater network. The proposed mathematical model is applied to two case studies; The first case study includes actual data from four fertilizer plants located in Egypt; the water resources and requirements are simultaneously integrated to obtain a sensible cutting in both freshwater consumption (lowered by 52.2%) and wastewater discharge (zero wastewater discharge). The second case study is for a Brazilian pet-rochemical plant; the obtained results showed noticeable reductions in freshwater consumption for the second case study by 12.3 % while the reduction percentage of wastewater discharge is 4.5%.

The existence of low-cost and accurate tools that can equip the First Responders (FRs) to detect trapped victims and provide insights about their health condition in the aftermath of a disaster, is imperative. To address the problem of detecting trapped victims behind walls or debris, we have developed a tool that exploits an Ultra-Wide Band (UWB) radar sensor for data collection and Machine Learning (ML) algorithms for data analysis. To evaluate the efficacy of our approach, we collected data from nine humans, both in standing and lying down positions. Next, we applied various ML algorithms to the collected dataset for two discrete sub-tasks that are of interest from an FR’s perspective. The first task is the detection of the victim’s presence, where the algorithms attained more than 95% accuracy and F1-Score. The second task is the estimation of the distance between the radar sensor and the victim, where the tool showed an average error of less than 40 cm.

In the modern power grid, characterized by the increased penetration of power electronics and extensive utilization of renewable energy, inverters-based power plants play a pivotal role as the principal interface of renewable energy sources (RESs) and the grid. Considering the stability characteristics of grid-following (GFL) inverters when the grid is relatively weak, the application of grid-forming (GFM) controls becomes imperative to enhance the stability of the entire power plant. Thus, there is an urgent need for suitable and effective models to study the interaction and stability of the paralleled inverters employing GFL and GFM controls. Thus, the small-signal modeling with full-order state space model and eigenvalues analysis is presented in this paper. First, the small-signal state-space model of the individual GFL and GFM inverters is obtained considering the control loop, interaction, reference frame, transmissions, and time delays. Then, the models of the individual inverter are extended to the hybrid inverters to study the effects of the GFM inverters on the small- signal stability of the entire system. And, the impacts of the inertia and damping are analyzed by the eigenvalues of the state-transition matrix. Case comprising three parallel GFL inverters and two GFL inverters with one GFM inverter, respectively, are studied to examine the effectiveness and accuracy of the model. Finally, the stability margin obtained from the eigenvalue analysis of the entire system is verified by time-domain simulations.

It has been theorized that black holes are surrounded by firewalls, although there is not universal agreement concerning this. We first review basic concepts pertaining to Schwarzschild black holes and Hawking radiation. Then we discuss the anticipation of Hawking radiation—albeit from non-black holes—initially by R. C. Tolman and shortly thereafter with P. Ehrenfest. We compare evaporation into a vacuum at absolute zero (0 K) of black holes with that of non-black holes, and show that not only black holes but also non-black holes evaporate within a finite time. The times required for evaporation of black holes and non-black holes are compared. Next, we show that (i) if firewalls exist, they can originate via Hawking radiation at the minimum possible ruler distance (the Planck length) beyond the Schwarzschild horizon, where it has not suffered any gravitational redshift, or, alternatively, suffered maximal gravitational blueshift and (ii) the firewall temperature is on the order of the Planck temperature, independently of the mass and hence also of the Schwarzschild radius of a Schwarzschild black hole. We then explain the exponential nature of the gravitational frequency shift as a function of the gravitational potential. Next, we consider the firewall-mass problem, and provide an at least prima facie tentative resolution thereto based on: (i) the mass of a firewall being canceled by the negative gravitational mass = (negative gravitational energy)/c² accompanying its formation, (ii) the unchanged observations of a distant observer upon formation of a firewall, and (iii) Birkhoff's Theorem (actually first discovered by Jørg Tofte Jebsen). We then consider one aspect of thermodynamics in gravitational fields, showing that equilibrium relativistic gravitational temperature gradients cannot be exploited to violate the Second Law of Thermodynamics.

In patients with schizophrenia, metabolic syndrome is associated with cognitive impairments. We carried out a second analysis of data from a longitudinal trial to examine the relationship between weight gain and cognitive function in patients with first-episode schizophrenia (FES) over the first 6-month antipsychotic treatment. Baseline and 6-month endpoint measurements were taken for both cognitive function and body weight. Linear and logistic regression analyses were applied to investigate the bidirectional relationship between weight gain and cognitive function. Clinically relevant weight gain (CRW) was defined as an increase in body weight ex-ceeding 7%. The final analysis included 337 participants. Lower baseline scores in processing speed (OR=0.837, p=0.007), working memory and attention (OR=0.889, p=0.043), and executive function (OR=0.863, p=0.006) domains were significantly associated with CRW at the 6-month endpoint. After adjusting for confounders, CRW was found to be associated with improvement in the Brief Visuospatial Memory Test (p=0.036). The findings suggest that patients with lower baseline cognitive performance experienced more substantial weight gain. Conversely, weight gain was correlated with cognitive improvements, particularly in the domain of visual learning and memory. This suggested a potential bidirectional relationship between weight gain and cog-nitive function in patients with first-episode schizophrenia.

Cognitive impairment affects 34-65% of People with Multiple Sclerosis (PwMS), significantly impacting their quality of life. Clinicians routinely address cognitive deficits with in-clinic neuro-behavioural interventions, but accessibility issues exist. Telerehabilitation is a promising solution that utilises digital tools for home-based cognitive remediation. This narrative review assessed the feasibility and efficacy of cognitive telerehabilitation in PwMS, identifying 13 relevant studies. Regarding the feasibility of cognitive telerehabilitation, evidence shows adherence rates are generally good, although, surprisingly, not all studies reported a measure of compliance with the cognitive training explored. Considering the efficacy of different rehabilitative techniques on cognitive performance of PwMS, findings are generally inconsistent, with only one study reporting consistently positive results. A range of methodological limitations are reported as potential factors contributing to the variability of results. Overcoming some of these issues will be key. Upcoming research is necessary to determine optimal intervention approaches, long-term effects of rehabilitation, and how to best integrate the use of telerehabilitation into routine clinical practice. By exploiting digital tools in the best way and addressing methodological concerns, home-based rehabilitation holds the potential for improving cognitive functions and enhancing the quality of life in PwMS.

Euler sums are alternating (or level two) extension of multiple zeta values (MZVs). Kaneko and Tsumura initiated the study of multiple T-values (MTVs), another level two generalization, by restricting the summation indices in the definition of MZVs to a fixed parity pattern. In this paper, we shall study finite MTVs and their alternating versions which are level two and level four variations of finite MZVs, respectively. We conjecture that all finite MZVs are in the Q-span of finite MTVs which in turn apparently lie in the span of finite Euler sums, and the inclusions are both proper. We shall first provide some structural results for Euler sums of small weights, guided by the author's previous conjecture that the finite Euler sum space of weight w is isomorphic to a quotient Euler sum space of weight w. Then, by utilizing some well-known properties of the classical alternating MTVs, we shall derive a few important Q-linear relations among the finite alternating MTVs, including the reversal, linear shuffle and sum relations. We then compute the upper bound for the dimension of the Q-span of weight w finite (alternating) MTVs for w<9, both rigorously using the newly discovered relations and numerically aided by computers.

Human endogenous retroviruses (HERV) are remnants of ancient retroviral infections that, over millions of years, became integrated into the human genome. While normally inactive, environmental stimuli such as infections have contributed to the transcriptional reactivation of HERV promoting pathological conditions including the development of autoimmunity, neurodegenerative disease and cancer. What infections then trigger HERV activation? Mycobacterium avium subspecies paratuberculosis (MAP) is a pluripotent driver of human disease. Aside from granulomatous diseases Crohn’s, sarcoidosis and Blau syndrome, MAP is associated with autoimmune disease: type one diabetes (T1D), multiple sclerosis (MS), rheumatoid arthritis and autoimmune thyroiditis. MAP is also associated with Parkinson’s disease. Autoimmune diabetes, multiple sclerosis and rheumatoid arthritis are the diseases with the strongest MAP/HERV association. There are several other diseases associated with HERV activation including diseases whose epidemiology and/or pathology would prompt speculation for a causal role of MAP. These include non-solar uveal melanoma, colon cancer, glioblastoma and amyotrophic lateral sclerosis (ALS). This article further points to MAP infection as a contributor to autoimmunity, neurodegenerative disease and cancer via unsilencing of HERV. We examine the link between the ever-increasing number of MAP- associated diseases, the MAP/HERV intersection with these diverse medical conditions and propose treatment opportunities based upon this association.

Pediatric onset multiple sclerosis (POMS), characterized by the onset of multiple sclerosis before the age of 18, is gaining increased recognition. Approximately 5 percent of MS cases manifest before the age of 18, with less than 1 percent occurring before the age of 10. Despite its rarity, pediatric MS exhibits distinct characteristics, with an association between younger age at onset and a comparatively slower disease progression. Despite this slower progression, individuals with POMS historically reach disability milestones at earlier ages than those with adult-onset multiple sclerosis. While various immunomodulatory agents demonstrate significant benefits in MS treatment, such as reduced relapse rates and slower accumulation of brain lesions on magnetic resonance imaging (MRI), the majority of disease-modifying therapies (DMTs) commonly used in adult MS lack evaluation through pediatric clinical trials. Current evidence is predominantly derived from observational studies. This comprehensive review aims to consolidate existing knowledge on the mechanisms of action, efficacy, safety profiles, and recommended dosages of available DMTs specifically in the context of pediatric MS. Furthermore, the review outlines recent advancements and explores potential medications still in developmental stages, providing a thorough overview of the current landscape and future prospects for treating POMS.

Commuting is a vital travel channel for college students throughout their higher education career; nevertheless, excessive commute time negatively impacts students’ school satisfaction, academic achievement, health, and quality of life. Meanwhile, few studies have explored students’ commute time, covering a large population and scope. Therefore, this study analyzes the dwelling type that influences college and graduate students’ school commute times in the Seoul Metropolitan Area, using data from the 2016 Household Travel Diary Survey. This study uses spatial data on housing development to classify five dwelling types (i.e., new town, housing site development, Seoul, Incheon, and Gyeonggi-do). A multiple linear regression model empirically analyses students’ household and personal characteristics. The results reveal that dwelling type significantly affects students’ commute time. Specifically, Students living in Seoul have a shorter commute to school than those living in new towns. Socioeconomic characteristics have less effect on college and graduate students' school commute time. This study discusses the problem of excessive commuting of college and graduate students in new towns.

Neurodegeneration is a major problem in neuroscience and medicine as it causes and worsens many neurological and psychiatric disorders. It involves gradual loss of neurons at different levels of the brain, affecting cognition, emotion, behavior, consciousness, and attention. Understanding the causes and consequences of neurodegeneration is crucial for identifying the risk factors, biomarkers, and treatments. However, the current therapies are mostly symptomatic and ineffective. Therefore, new and innovative methods, such as noninvasive brain stimulation (NIBS), are needed to modulate brain activity and plasticity in a safe and reversible manner. This field is rapidly developing, with a focus on exploring new clinical applications, mechanisms, and combinations of NIBS and drugs. This special issue covers the latest progress and challenges in the study of neurodegeneration in cognitive impairment and mood disorders from the experimental, clinical, and translational perspectives. It addresses the complexity and diversity of these conditions, the lack of disease-modifying treatments, the ethical and practical issues of conducting research in vulnerable and diverse populations, the integration and interpretation of data from multiple sources and modalities, and the development and validation of novel methods such as NIBS, artificial intelligence, and drug repurposing. Collaborative efforts among various stakeholders are needed to improve our knowledge and treatment of neurodegeneration underlying cognitive impairment and mood disorders.

Background:Caregiving for individuals with neurological disease involves providing physical, emotional, and social support, which can be a challenging and stressful experience. This study aims to compare the caregivers' burden, including the impact on mental and physical health, social support, and quality of life, in different neurodegenerative disorders. Methods:Fifty-five primary caregivers (F=41;mean age=53.07±12.29) of patients with Parkinson's Disease (PD=26), Multiple System Atrophy (MSA=16), and Amyotrophic Lateral Sclerosis (ALS=13), took part in the study. Standardized screening scales for the quality of life (EQ-5D/EQ-VAS and PQoL), levels of the caregiving burden (CBI and FSQ), and the assessment of the anxiety-depressive axis (HADS) were administered. Results: The mean CBI score was higher for caregivers of MSA patients (28.81±21.90) and ALS (25.15±16.23) than for caregivers of PD patients (16.08±10.34; p=0.036). Critical burden (cut-off>36) was present in the caregivers of MSA (31.3%), ALS (23.1%), and PD (19.2%) patients. Caregivers of patients with ALS had a worse perception of quality of life (EQ-5D total score) than caregivers of patients with MSA and PD (p

The performance of the presurgical test (preSurg) for temporal lobe epilepsy (TLE) was evaluated via video-electroencephalography (VEEG), electroencephalography (EEG), 99mTc-HmPAO single-photon emission tomography (SPECT) and 1.5 T magnetic resonance imaging (MRI) in a group of 112 men (37.0 ± 1.1 years) and 106 women (39.7 ± 1.1 years) operated on for TLE. The epileptic zone (EZ) was adequately identified to determine whether the patient reached an Engel I grade (EI) at least one year postop. Accuracy was evaluated by the coefficient α, ranging from 3 (when result = EZ) to 2 (result in the same hemisphere as the EZ), 1 (noninformative result) or 0 (EZ in the contralateral hemisphere). The simplicity of diagnosis was defined as the number of preSurg surgeries needed to identify the EZ. EI was obtained in 85.8% of patients even though 42.2% of patients had noninformative MRI results. For preSurg α was (mean ± SEM) = VEEG (2.83 ± 0.04) &gt; MRI (2.14 ± 0.08) &gt; EEG (1.87 ± 0.09) &gt; SPECT (1.71 ± 0.09). The accuracy (combination of sensitivity and specificity) was calculated as follows: VEEG (0.797) &gt; MRI (0.518) &gt; EEG (0.446) &gt; SPECT (0.360). The likelihood positive ratio was greater, and the likelihood negative ratio was lower for VEEG. The most relevant factor for the regression model was VEEG (3.106) &gt; MRI (2.558) &gt; EEG (1.905), and the factors were not significantly related to SPECT. EZs in EI patients with low simplicity were identified mainly by VEEG. A very good postoperative outcome can be obtained even in TLE patients with no lesions on MRI. The VEEG is the most reliable preSurg test and may be the only reliable test for patients with very low simplicity (i.e., difficult).single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

In this study, we evaluated the antibacterial effect against Staphylococcus aureus and Salmonella Typhimurium in fried fish paste using floating electrode-dielectric barrier discharge (FE-DBD) plasma (1.1 kV, 43 kHz, N2 1.5 m/s, 1-60 min). In addition, quality evaluation (pH, VBN) of fried fish paste was conducted after FE-DBD plasma treatment. When FE-DBD plasma was treated for 1, 5, 10, 20, 30 and 60 min, S. aureus decreased by 0.16-1.13 log10 CFU/g, and S. Typhimurium decreased 0.25-1.13 log10 CFU/g. Both decreased &gt; log10 CFU/g at 60 min. The D-value was 58.92 and R2 was 0.97 for S. aureus using first-order kinetics, and the D-value was 43.60 and R2 was 0.97 for S. Typhimurium using the Weibull model. There was no significant difference in pH after FE-DBD plasma treatment (p &gt; 0.05). However, volatile basic nitrogen (VBN) significantly decreased as the treatment time increased (p &lt; 0.05), and it was the lowest at 60 min to 3.46. Therefore, FE-DBD plasma treatment could be considered as a technology for preserving the quality of processed foods.

Film cooling technology is of great significance to enhance the performance of aero-engines and extend service life. With the increasing requirements for film cooling efficiency, researchers and engineers have carried out a lot of work on the precision and digital measurement of cooling holes. Based on the above, this paper outlines the importance and principles of film cooling technology, reviews the evolution of cooling holes. Also, this paper details the traditional measurement methods of the cooling hole used in current engineering scenarios with their limitations and categorizes digital measurement methods into five main types, including probing measurement technology, optical measurement technology, infrared imaging technology, computer tomography(CT) scanning technology, and composite measurement technology. The five types of methods and integrated automated measurement platforms are also analyzed. Finally, through a generalize and analysis of cooling hole measurement methods, this paper points out technical challenges and future trends, providing a reference and guidance for forward researches.

Building energy demand impacts a myriad of interconnected economic, societal, and environmental aspects. As a result, Buildings Energy Models (BEM) play an important role in the process of urban design and planning. While previous studies have investigated the effects of building interventions on energy efficiency, their applicability may be limited due to the BEM’s high computational complexity. This limits their ability to systematically study important aspects of energy demand on a large scale. The development of Machine Learning Models (MLM) allows to design the required detailed analysis and solutions, while reducing the computational burden, making MLM attractive for urban designers. The capability of MLM to generalize well for multiple contexts (in our case, multiple buildings) is a crucial contributor to their applicability. However, the validation process in a wider context is often overlooked, therefore its generalization capabilities are not quantified. In this paper, we present a framework to train and validate a surrogate model derived from a physics-based BEM. Our method employs a Multiple Linear Regression model to predict Energy Use Intensity (EUI) for office buildings in Singapore using 36 input parameters (covariates), based on a training dataset of 23,000 samples. Model validation is performed by comparing the results of the Surrogate Model (SM) to a widely used BEM for a sample of 120 buildings. Our results indicate that the SM has an accuracy of NRMSE of 13%, NMBE of −3.56%, and R2 of 0.92, which suggests it can effectively and accurately predict building EUI. We also conduct a sensitivity analysis, which indicates that the parameters associated with internal loads and internal space usage are the most influential. Additionally, we present a reduced order model trained with only the 11 most influential parameters, which exhibits negligible loss in accuracy compared to the full SM while providing reduced complexity. Finally, we demonstrate an application of our SM to evaluate energy efficiency under uncertainty scenarios. The analytically derived results indicate a potential reduction of EUI of offices in Singapore from 227kWh/m2 to 99kWh/m2 by altering the building parameters that were identified as most influential.

Safety limits application has always been a traditional approach to ensure the safe operation of electro-mechanical systems within many industries including automated vehicles, robotics, aerospace, traditional automotive, railways, manufacturing, etc. In all of these applications, control and safety limits are usually hard-coded into the production firmware and are fixed throughout the entire product life cycle. Currently, due to the evolving needs of automated systems like automated vehicles and robots, this traditional approach does not address all the use cases and scenarios to ensure safe operation. Especially for data-driven machine learning applications that constantly evolve and learn over time, it is important to be able to adjust the safety limits application strategy to be more flexible and adaptable based on different Operational Design Domains (ODDs) and scenarios. Our ITSC conference paper ~\cite{4} introduced the concept of a new safety limits application strategy called the Dynamic Control Limits Application (DCLA) strategy that supports the flexible application of diverse limits profiles based on the parameters involved within the dynamic scenario at different layers of the Autonomy software stack.This paper extends the DCLA strategy to derive the complete methodology for safety limits application based on ODD elements, scenario identification and scenario classification using Decision Making Engines. It leverages the layered architecture introduced in the ITSC conference paper to implement the Decision Making (DM) algorithms. Another important extension is the use of cloud infrastructure that is based on the Vehicle-to-Infrastructure (V2I) technology to store the scenarios and the limits mapping to serve as a ground truth and/or a backup mechanism in case of errors or failures associated with the main Decision Making (DM) Engine. There is also a focus on providing a more comprehensive list of scenarios and a custom built experimental dataset to cover the maximum ODD elements, and multiple tables of safety limits to be chosen from, which eventually helps in creating different safety limits application profiles. These distinct safety limits application profiles are based on the scenario parameters that are perceived by the system upon which the Decision Making algorithms are applied or trained. This systematic approach can be used within the industry for any of the future automated vehicles and systems until Level 5 Autonomy.

Background: Neuromuscular electrical stimulation (NMES) has beneficial effects on physical functions in Multiple Sclerosis (MS) patients. However, the neurophysiological mechanisms underlying these functional improvements are still unclear. This study aims at comparing acute responses in spinal excitability, as measured by soleus Hoffmann reflex (H-reflex), between MS patients and healthy individuals, following three experimental conditions involving the ankle planta flexor muscles: 1) passive NMES (pNMES); 2) NMES superimposed to isometric voluntary contraction (NMES+); and 3) isometric voluntary contraction (ISO). Methods: 20 MS patients (MSp) and 20 healthy individuals as control group (CG) took part in a single experimental session. During each condition, participants performed 15 repetitions of 6 seconds at 20% of maximal voluntary isometric contraction, with 6 seconds of recovery between repetitions. Before and after each condition, H-reflex amplitudes were recorded. Results: In MSp, H-reflex amplitude did not change following any experimental condition (ISO: p = 0.506; pNMES: p = 0.068; NMES+: p = 0.126). In CG, H-reflex amplitude significantly increased following NMES+ (p = 0.01), decreased after pNMES (p = 0.000) and was unaltered following ISO (p = 0.829). Conclusion: the different H-reflex responses between MS and CG might reflect a reduced ability of MS patients in modulating spinal excitability.

In the discussion on environmental policies, the notion of eco-efficiency is often used. Eco-efficiency is defined as the delivery of products and services with competitive values, while reducing the ecological impacts and satisfying human needs. In an environment of great competitiveness in which the companies operate, the improvements in the productive process is one of the differentiating factors for guaranteeing a strong competition. Also it is essential rationalizing energy consumption and natural resources. For this it is necessary to understand the main operations and dynamics of the company. This work presents an empirical study of a Portuguese company in the industrial sector. The problematic here presented is based on the company’s growing concern to reduce the amount of scrap produced. From the literature research that was performed, a strong dependence relation between the different variables in the extrusion process was found. The main objective of this work is to model the aluminium extrusion process, with the aim of minimizing the production of scrap. For this several variables involved in the process are taking into account. Using statistical techniques, in particular multiple linear regressions, it was possible to identify the importance of the variables under study for the scrap production.

In the evolving landscape of vibration analysis, the integration of machine learning technologies for semi-automated analytical processes presents challenges in establishing clear cause-and-effect relationships in decision-making formulas. This research addresses this gap by exploring analytical diagnosis through residual signals, enabling the identification of anomalies and underperformance in machinery. Vibration signature analysis, focusing on distinctive vibration patterns, proves instrumental in detecting bearing defects and optimizing maintenance for enhanced operational efficiency and safety. Mathematical modeling, particularly worst-case analysis, provides a structured framework for decision-making under uncertainty. The research employs descriptive methods to analyze bearing wear data, transforming it into quantitative data for multiple regression equations. The derived equations reveal the dominance of harmonics in determining bearing wear stages, with PeakVue and overall vibration further indicating damage progression. The findings emphasize the significance of harmonic detection and high-frequency vibration analysis in predicting bearing health, offering a comprehensive approach to enhance machinery reliability. The study concludes with practical recommendations for bearing damage diagnosis based on the developed mathematical models, providing valuable insights for predictive maintenance strategies.

Using the h-index to assess individual researchers is not only unethical and unfair but also inaccurate and misleading. This index fails to offer a reliable measure of a researcher's impact based on their citation scores. Beyond statistical and conceptual considerations, authorship practices, especially in the case of multi-authored publications, give rise to significant problems that often go unnoticed. While some modifications of the h-index have been proposed to mitigate these weaknesses, the fundamental deficiencies persist. Most of these flaws have been effectively addressed by the c-score, a composite citation index. The c-score excludes self-citations, normalizes the number of citations by considering the number of authors in each paper, and takes into account first, single, and last authorship. This approach provides a more realistic measure of the impact of each individual researcher based on raw citations.

It has been more than a century since Erlang published his paper in 1909. The classical queueing system for the M/D/c queue has been investigated by many authors. The key is to find the roots of an equation using explicit or numerical methods. We present an alternate form of explicit solution(s) of this/these root(s) using the Lambert-W function in this paper. In addition, the unsaturated probabilities of the number of customers in the system is derived explicitly in terms of this/these root(s). Finally, the mean number of customers in the system and the mean queueing delay are obtained from these probabilities. The exact queueing delay formula for the M/D/c queue is expressed in closed-form in terms of the root(s). Numerical results show that they are in excellent agreement with the numerical results published by Seelen, Tijms and Van Hoorn.

The overwhelming evidence supports the assertion that the climate is undergoing change. Understanding the perception of locals of the magnitude of climate change and its influence on non-timber forest products (NTFPs) challenge at a global scale. Although studies on climate change, value addition, and the multiple uses of NTFPs and their impact on local livelihoods have been conducted, locals' perceptions of these factors have not been fully explored. This study aims to assess various social factors, including education, gender, and religion, and their influence on locals' perceptions of the abovementioned factors. The research focused on five regions where NTFPs are prevalent in Ghana (Western North, Bono, Ahafo, Ashanti, and Eastern regions). To investigate the impact of social factors on local perceptions of climate change, value addition, and the multiple values of NTFPs within rural communities, a total of 732 interviews with a team of interviewers across these five regions in Ghana were carried out. We applied a logistic regression model to assess the social factors and their influencing locals’ perceptions of the mentioned variables. It was revealed that age, gender, education, and occupation did not significantly influence locals' perceptions of climate change. However, religion was found to influence locals' perceptions of climate change. Furthermore, the results demonstrated that gender (P<0.000328) and education (P<0.00426) strongly influenced locals' perceptions of value addition to NTFPs. In contrast, religion and constraints (related to time, finance, and skills) did not significantly influence locals' perceptions. Additionally, it was observed that gender (0.00132), education (0.00692), and religion (8.12e-05) significantly influenced how locals perceive and use NTFPs. In conclusion, this study provides valuable insights into the intricate interplay among local perceptions, climate change, value addition, multiple uses of NTFPs, and the capacity of NTFPs to enhance the well-being of forest fringe communities. These findings underscore the importance of comprehensive, tailor-made interventions that consider local perspectives and adhere to sustainable approaches, with the aim of optimising the positive impacts of NTFPs in poverty alleviation and overall community development.

Multiple imputation with chained equations (MICE) is a widespread approach to account for missing data in empirical research. Combining MICE with bootstrapping, that is, repeatedly resampling with replacement from the data to estimate variances and confidence intervals of statistics of interest, is not straightforward. The current document provides an overview of how to use bootstrapping with imputed data in Stata. Two main approaches (impute first and then bootstrap or vice-versa) are discussed and shortly compared. Code is provided for Stata.

Primary failure of eruption (PFE) is a rare non-syndromic condition involving total or partial non-eruption of posterior teeth, in the absence of mechanical obstruction. This paper presents the case of a healthy girl referred at age 4 years for asymmetry of upper arch. Clinical examination confirmed a slight shift of the upper midline to the left, with no erupted teeth distal to the upper left canine and left posterior open bite. Panoramic X-ray showed delayed intra-osseous development of lateral left upper teeth compared to the right side. Clinic and radiographic follow-up during the next 9 years showed that 26 has not erupted by almost 13 years of age, 27 has delayed development and an unusual shape and there is agenesis of 24, 25. Genetic analysis using the PTH1R single gene sequencing did not detect any known disease-causing or rare pathogenic variants that could explain the patient's phenotype. Even when detected early, PFE rises difficult problems with regard to diagnosis and ortho-surgical treatment planning due to the impossibility to accurately predict the evolution. Tooth agenesis on the same arch worsens the prognosis and adds challenges to planning the treatment. Close long-term follow-up and timely adjustment of treatment plan in accordance to the evolution of the case are needed.

Tularemia is a zoonotic disease caused by {\it Francisella tularensis} bacteria, a gram-negative coccobacillus-shaped bacterium. There are multiple transmission routes of the infection to humans such as consumption of contaminated food or water, handling of infected animals or bites from {\it haematophagous} arthropods (such as ticks, deer flies, or mosquitoes). In this study we focus on transmission via the bites of ticks and developed a deterministic model of ordinary and impulsive differential equations to gain insight in the differential effect of prescribed fire on {\it Demacenta variablis} and {\it Amblyomma americanum} ticks and the prevalence of tularemina. We found that prescribed fire differentially reduce the number of the two ticks with {\it A. americanum} reduced the least compare to {\it D. variablis} subsequently leading to differential increase of tularemia new infected cases in humans and rodents. Our result further indicates that the spatial arrangement of burn against unburn areas may not matter as either arrangement led to fewer ticks and reduction in tularemia transmission when prescribed fire was implemented. The results of this study provide important new understandings of the intricate effect of prescribed fire on tick species, and the dynamics of the tick-borne disease, tularemia disease in this study.

Resistance to therapy and disease progression are the main causes of mortality in most cancers. In particular, the development of resistance is an important limitation affecting the efficacy of therapeutic alternatives for cancer, including chemotherapy, radiotherapy, and immunotherapy. Signaling pathways are largely responsible for the mechanisms of resistance to cancer treatment and progression, and multiple myeloma is no exception. p38 mitogen-activated protein kinase (p38) is downstream of several signaling pathways specific to treatment resistance and progression. Therefore, in recent years, developing therapeutic alternatives directed at p38 MAPK has been of great interest, in order to reverse chemotherapy resistance and prevent progression. In this review, we discuss recent findings on the role of p38, including recent advances in our understanding of its expression and activity as well as its isoforms, and its possible clinical role based on the mechanisms of resistance and progression in multiple myeloma.

New insights into the causes and mechanisms of congenital heart disease (CHD) have been gained through the use of next-generation sequencing. Examination of the whole exome sequence detects detrimental gene variations modifying single or contiguous nucleotides, that are characterised as pathogenicity based on statistical assessments of families. and correlates with congenital heart disease, elevated expression during heart development, and reduction of harmful protein-coding mutations in the general population. Patients with CHD and extracardiac abnormalities enriched for gene classes meeting these criteria. CHDs and extracardiac defects, supporting a common set of pathways in the organogenesis of CHDs. Single-cell transcriptomics data reveal the expression of genes associated with CHD in specific cell lineages, and emerging evidence suggests that genetic variants disrupt multicellular genes essential for cardiogenesis. Metrics and units are being tracked in whole genome sequence studies.

(1) Background: Since fullerene C60 is insoluble in water and is toxic, it is not applicable in biomedicine and cosmetics. For this reason, the first derivative FD-C60 (fullerenol) was synthesized, which solved the problem of solubility in water and partially reduced toxicity. In order to maximally reduce toxicity and increase biomedical efficiency, the second derivative SD-C60 (3HFWC- Hyper-Harmonized-Hydroxylated Fullerene Water Complex), was created. (2) Methods: In order to obtain the most reliable data, several different methods are applicable in the characterization of FD-C60 and SD-C60 with water layers (NIR, FTIR, 13C-NMR,  1H-NMR, TGA/DTA, XRD, AFM/MFM etc.). (3) Results: FD-C60 as an individual structure is about 1.3 nm in size, while SD-C60 as an individual structure is 1030 nm in size. The aforementioned methods showed that SD-C60 contains water layers, which explains the difference between those two structures in the physicochemical properties, and their effects on biomolecules. (4) Conclusions: Based on the above methods and techniques, FD-C60 and SD-C60 are two different substances in terms of size, structure, and physicochemical properties; FD-C60 at 100C has endothermic characteristics and SD-C60 at 133C has exothermic characteristics, FD-C60 possesses water molecules only from humidity, while SD-C60 has water molecules from both humidity and extra water molecules in layers, the zeta potential of FD-C60 is -25.85 mV, while it is -43.29 mV for SD-C60.

Fermatean fuzzy sets (FFSs) are a versatile tool for handling uncertain problems and have shown great effectiveness in practical applications. However, many existing Fermatean fuzzy similarity measures exhibit counter-intuitive situations, making it challenging to accurately measure the similarity or difference between FFSs. To address this issue, several similarity and distance measures for FFSs are proposed, inspired by the Tanimoto similarity measure. The properties of the proposed measures are also explored, along with several comparative examples with existing measures for FFSs, which illustrate their superior performance in processing fuzzy information from FFSs. The proposed measures have effectively overcome the counter-intuitive challenges posed by many existing measures and significantly outperforms existing measures in differentiating different FFSs. Furthermore, we demonstrate the practical applicability of the proposed measures in solving pattern recognition, medical diagnosis and multiple-attribute decision-making problems.

23-Hydroxy ursolic acid (23-OH UA) is a potent atheroprotective and anti-obesogenic phytochemical, with anti-inflammatory and inflammation resolving properties. In this study, we examined whether dietary 23-OH UA protects mice against the acute onset and progression of experimental autoimmune encephalomyelitis (EAE), a mouse model of multiple sclerosis (MS). Female C57BL/6 mice were fed either a defined low-calorie maintenance diet (MD) or an MD supplemented with 0.2 % wgt/wgt 23-OH UA for 5 weeks prior to actively inducing EAE and during the 30 days post-immunization. We observed no difference in the onset of EAE between both groups of mice, but ataxia and EAE disease severity were suppressed by 52% and 48%, respectively, and disease incidence was reduced by over 49% in mice that received 23-OH UA in their diet. Furthermore, disease-associated weight loss was strikingly ameliorated in 23-OH UA-fed mice. ELISPOT analysis showed no significant differences in frequencies of T cells producing IL-17 or IFN- between 23-OH UA fed mice and control mice, suggesting that 23-OH UA does not appear to regulate peripheral T-cell responses. In summary, our findings demonstrate that dietary 23-OH UA may represent an effective oral adjunct therapy for the prevention and treatment of relapsing-remitting MS.

This paper investigates the reconfigurable intelligent surface (RIS)-aided uplink multicell massive multiple-input multiple-output (mMIMO) communication system with transceiver hardware impairments (THWIs), and the practical and feasible two-timescale scheme is used to design the phase shifts of RIS. We consider the Rician channel model and use maximal-ratio combining (MRC) technology to process the received signal at BS. The expression of the uplink achievable rate is derived and analyzed. Besides, genetic algorithm (GA) is used to optimize the phase shifts of RIS to maximize the data rate. Finally, the accuracy of the derived results is verified. The simulation results show that appropriately increasing the number of RIS’s reflecting elements can compensate for the performance loss caused by inter-cell interference and THWIs, and reduce the demand for the number of BS antennas, which can significantly reduce the hardware costs at the BS.

Stochastic modelling of geometrically imperfect steel frame structures requires inputs of statistical values of the imperfection parameters, in some cases also with suitably selected mutual correlations between these input parameters. The paper presents a verification study of two stochastic methods to directly model the initial global geometrical imperfections of the steel frame structures. The stochastic input values of geometrical imperfections are derived from the tolerance criteria of the corresponding European Standard. Two advanced stochastic methods have been developed, referred as #RSS (random story sway) and #RSP (random story position). These methods are verified using random sampling simulations. This study provides useful provisions for the advanced numerical analyses of multi-story steel frames of various geometries. The proposed methods are verified for equidistant story heights and for structures of up to 24 stories, hence might be used for the most types of the standard steel frame structures.

Sphingosine 1-phosphate (S1P) is a signaling lipid molecule involved in various cellular processes. It is important to develop a quantitative method for S1P to determine endogenous levels and to investigate its functions. Especially since S1P is a tiny lipid component of most biological samples, highly sensitive analysis by LC-MS/MS is required. The main challenge in S1P analysis by chromatography is peak broadening due to the presence of a polar phosphate and zwitterion formation in S1P. In this study, we used hydrogen fluoride (HF) to efficiently remove a phosphate and then analyzed the surrogate, sphingosine, as a sharp peak by LC-ESI-MS/MS. We optimized the dephosphorylation reaction in terms of reaction time, temperature, and HF concentration. Multiple reaction monitoring (MRM) for dephosphorylated form of S1P and C17-S1P as internal standard at m/z transition 300.4&gt;282.4 (quantification ion), 300.4&gt;262.4 (qualification ion), 286.3&gt;268.2 (internal standard). This method was validated by essential parameters such as specificity, linearity, range, LOQ, LOD, accuracy, precision, and repeatability. To confirm this new method, we quantified S1P levels in various serum products (100.02 ~ 284.38 nM). To apply the method in vivo, we analyzed S1P in plasma and kidney tissues obtained from a chronic kidney disease (CKD) mouse model. S1P levels were increased only in CKD kidney tissue but not in plasma. In conclusion, by applying the dephosphorylation step with HF, we established a new sensitive LC-MS/MS quantitative method for S1P that can be applied to biological samples.

In a Water-Cooled Lithium-Lead (WCLL) Breeding Blanket (BB), the heat generated by the plasma thermal radiation and nuclear reactions is removed mainly by two components; namely, the First Wall (FW) and the Breeding Zone (BZ). The FW faces the neutrons and charged particles fluxes generated by the fusion reactions and the thermal radiation coming from the plasma. The present work takes into account the FW cooling system inspired by the WCLL BB 2018 design of DEMO 2017 baseline. Unlike the baseline where a Pressurized-Water Reactor (PWR) setup is used for the coolant, various setup between the Boiling Water Reactor (BWR) and the High-Pressure (HP) BWR are studied in the present work operating in the Two-Phase Flow (TPF) regime. The 3D model of the FW in the WCLL BB 2018 design is simplified into a 1D model and a steady state analysis is carried out to optimize the mass flow rate of the water and the number of parallel channels at the BB cells at different poloidal locations of the reactor, which helps not only in reducing the used coolant but also in improving the Tritium Breeding Ratio (TBR). The present work takes into account forced convection in the liquid only region, the subcooled boiling region, and the saturated boiling region using suitable empirical or semi-empirical models from the literature. The results are validated against the existing results in the literature. In the end, related conclusions are made regarding the pros and cons of the studied operating conditions.

We present the case of a 28-year-old male with a history of alcohol dependency and smoking, who presented with chest pain, shortness of breath, and altered sensorium. He exhibited severe metabolic acidosis, low platelet count, and acute kidney injury. Alcoholic ketoacidosis (AKA) was suspected due to ketonuria, metabolic acidosis, and ketonemia, compounded by electrolyte abnormalities and radiographic findings of pneumonia.Prompt intervention included electrolyte correction, thiamine supplementation, broad-spectrum antibiotics, and diuretics. Thiamine played a pivotal role in the patient's recovery, with significant improvement in consciousness observed within a day. After six days, the patient was discharged in stable condition, showing normal renal and hepatic function during follow-up.This case emphasizes the need for early recognition and comprehensive management in AKA, highlighting thiamine's crucial role in treatment success.

Abstract: Placenta accreta spectrum (PAS) is a severe complication of pregnancy associated with excessive invasion of cytotrophoblast cells at the sites of the endometrial-myometrial interface and the myometrium itself in cases of adherent (creta) and invasive (increta and percreta) forms, respectively. Despite advancements in ultrasound protocols and found associations of alpha-fetoprotein, PAPP-A, hCG, PLGF, sFlt-1, IL-8, and IL-33 peripheral blood levels with PAS, the condition remains undiagnosed before delivery because of the lacking clear evaluation criteria for each of the three grades of PAS. This leads to a high risk of massive blood loss, maternal hysterectomy, and preterm birth. While using deep sequencing, miRNA signatures of placental tissue, myometrium, and blood plasma from women with PAS in the third trimester of pregnancy, as well as miRNA profile in exosomes from the blood serum of women in the first trimester with physiologically progressing pregnancy, complicated by PAS or preeclampsia, were obtained. Two logistic regression models were constructed, both featuring statistically significant parameters related to the levels of miR-26a-5p, miR-17-5p, and miR-101-3p quantified by real-time PCR in native blood serum. These models demonstrated 100% sensitivity in detecting PAS during the first pregnancy screening. These miRNAs were identified as specific markers for PAS, showing significant differences in their blood serum levels during the first trimester in the PAS group compared to those in physiological pregnancies, early- or late-onset preeclampsia groups. Furthermore, these miRNAs exhibited differential expression in the PAS placenta and/or myometrium in the third trimester and, according to literature data, control angiogenesis. Significant correlations were found between extracellular hsa-miR-101-3p and nuchal translucency thickness, hsa-miR-17-5p and uterine artery pulsatility index, and hsa-miR-26a-5p and hsa-miR-17-5p with PLGF. The developed test system for early non-invasive PAS diagnosis based on the blood serum level of extracellular miR-26a-5p, miR-17-5p, and miR-101-3p can serve as an auxiliary method for 1st trimester screening pregnant women, subject to validation on independent test samples.

Training has a significative effect on physiology of blood coagulation both in humans and in horses. Several hemostatic changes have been reported after exercise in the horse but data available are inconclusive. The aim of this study was to investigate the platelet activation and primary platelet-related hemostasis modifications in young untrained Thoroughbred racehorses in the first 4-month timeframe incremental training period in order to improve knowledge on this topic. Twenty-nine clinically healthy, untrained, 2-year-old Thoroughbred racehorses. Never trained Thoroughbreds were followed during their incremental 4-month sprint exercise schedule. Blood collection was performed once a month (T-30, T0, T30, T60, and T90). Platelet aggregation was measured by light transmission aggregometer in response to various agonists: adenosine diphosphate (ADP), collagen and calcium ionophore A23187. Platelet function was evaluated using the Platelet Function Analyzer (PFA-100®) using collagen/ADP and collagen/adrenaline cartridges. Nitrite-nitrate (NOx) plasma concentrations were measured by a colorimetric assay to assess in vivo nitric oxide bioavailability. Platelet activation was investigated also through gene expression analyses (selectin P-SELP, ectonucleotidase CD39-ENTPD1, prostaglandin I2 synthase-PTGIS, endothelial nitric oxide synthase 3-NOS3). Differences among the time points were analyzed and mean±SEM were calculated. Significant modifications were identified compared with T-30 with increase of platelet aggregation (collagen:32.6±4.8 vs 21.6±4.9%; ADP: 35.5±2.0 vs 24.5±3.1%; A23187: 30±4.7 vs 23.8±4%) and a shorter closure time of C-ADP cartridges (75.6±4.4 vs 87.7±3.4 sec) that tended to return to baseline value at T90. NOx concentrations in plasma significantly increased after 30 days of training program compared with baseline. The first long-term training period induce platelet hyperactivity already after 30 days in untrained Thoroughbreds. Regular physical training blunts the negative effects of acute efforts on platelets activation.

This paper considers the direction of arrival (DOA) estimation problem of phase ambiguity for unfolded coprime linear array (UCLA). The existing most common stacking subarray-based method can tackle the phase ambiguity problem. However, the method is not always true. For a given DOA, it has its corresponding steering vector, but if there are two DOAs which have the same steering vectors with the given DOA for different subarrays, the phase ambiguity problem still arises. A modified method, which defines a decision variable and uses the classic beamforming technique to estimate the DOAs is proposed. However, this method needs additional algorithm to distinguish the true DOAs besides multiple signal classification (MUSIC) spectrum. And sometimes this method is not reliable if the decision variable is not chosen appropriately. Therefore, based on the UCLA, we reconstruct the array to design an improved UCLA called IUCLA. With moving the reference element, the linear relationship among the directional vectors can be broken. In this way, we can directly utilize the MUSIC algorithm to estimate with no additional algorithm. The proposed method can solve the phase ambiguity problem and it does not demand other technique to decrease the complexity. Moreover, the Cramer-Rao Bound (CRB), as the lower bound of the unbiased estimation, is provided and numerical simulations are given to demonstrate the effectiveness and superiority of the proposed method.

Gradual disability worsening in Multiple Sclerosis (MS) is indicative of confirmed progression that mostly involves progression independent of relapse activity (PIRA) and is associated with neurodegeneration. Insights from pathology reveal grey matter involvement (neocortex, hippocampus, spinal cord, and deep grey matter structures) and microglia activation in early stages of MS. Cortical lesions result in thinning and atrophy and are considered accurate predictors of disability progression and cognitive decline.Neuroimaging biomarkers, such as high-resolution 7T MR images and TSPO-PET, have been examined for the detection of cortical pathology linked to cognitive deficits and thus progression, but are limited in clinical practice due to availability, time constraints, and cost.Electroencephalography (EEG) emerges as a non-invasive, cost-effective tool that reflects cortical activity in MS. Its potential in monitoring cognitive impairment is explored by focusing on nonlinear EEG analysis. The MuST PREDICT^TM project aims to extract linear and nonlinear EEG features, investigating their role in predicting disease progression and optimizing treatment. The study employs retrospective, cross-sectional, and prospective designs, utilizing EEGs from various MS forms, cognitive assessments, serum/cerebrospinal fluid biomarkers and neuroimaging. The methodology involves time-based and spectral feature extraction, employing artificial intelligence classifiers and brain criticality-based approaches.The conceptual framework of an innovative modality is herein presented, that would EEG for early MS progression detection. Standardization of the methodology could lead to the creation of a digital tool for better prognostication and treatment strategy optimization.

Flowering in cassava is crucial for generation of botanical seed for breeding. However, most farmer preferred genotypes are poor at flowering, exhibit great disparity in time and amount of flowering or never flower. To elucidate the genetic basis of such a flowering behaviour, 293 diverse cassava accessions were evaluated for flowering traits under two locations and seasons in Uganda. Genotyping by the Diversity Array Technology Pty Ltd. (DArTseq) platform identified 24,040 single-nucleotide polymorphisms (SNPs) distributed on the 18 cassava chromosomes. Population structure analysis using principal components (PC) and kinships showed clustering, the first five PCs accounted for 49.2% of the observed genetic variation. Linkage disequilibrium (LD) estimation was averagely 0.32 at a distance of ~2850kb (kilo base pairs). Polymorphism information content (PIC) and minor allele frequency (MAF) were 0.25 and 0.23, respectively. Genome-wide association study (GWAS) analysis uncovered 53 significant marker-trait associations (MTA) with flowering traits involving 27 loci. Two loci, SNPs S5_29309724 and S15_11747301 were associated with all the flowering traits. Using five of the 27 SNPs with Phenotype_Variance_Explained (PVE) ≥ 5%, 37 candidate genes were identified in the peak SNP sites located within 50kb upstream or downstream, most were associated with branching traits. Eight of the genes, orthologous to Arabidopsis and other plant species, had known functional annotations related to flowering, e.g. eukaryotic translation initiation factor and myb family transcription factor. This study identified genomic regions associated with flowering in cassava, the identified SNPs could be useful in marker-assisted selection to overcome hybridization challenges like unsynchronized flowering, and candidate gene validation.

Steroid hormones have diverse roles in pregnancy; some, such as progesterone and its metabolites, help stabilise pregnancy and can very likely influence the stability of pregnancy and the onset of labour. Changes and disorders in steroidogenesis may be involved in several pregnancy pathologies, such as premature delivery, preeclampsia, and intrahepatic cholestasis. To date, only a few studies have performed steroid analysis in multiple pregnancies. However, these studies offered a limited analysis of the steroidome in children and mothers with multiple pregnancies. Our team and a team from the Department of Steroids and Proteofactors of the Institute of Endocrinology in Prague investigated multiple pregnancies regarding the biosynthesis, transport, and effects of steroids. We recruited two groups of patients: pregnant women with multiple pregnancies as the study group and singleton pregnancies as the control group. Blood samples were drawn from the participants and analysed. Information about the mother, foetus, delivery, and newborn was extracted from medical records. The data were then analysed. The gestational age of twin pregnancies during delivery ranged from 35+3 to 39+3 weeks, while it was 38+1 to 41+1 weeks for the controls. Our findings provide answers to questions regarding the steroidome in multiple pregnancies.

We introduce the Transformation Flower Approach (TFA), a Theory of Change that attends to multiple value creation and institutional change as a dual design challenge. We highlight how the TFA integrates social scientific theories and models relevant for transformative change (in particular focusing on pathways, leverage points, governance, power, and values) and demonstrate its practical value by an application to the ongoing transformation of the Dutch food system. By providing a holistic, transdisciplinary and practically relevant approach that aims to support new social contract formation, the TFA goes beyond other transformative change approaches. Based on the notion of pathways, it offers a toolbox that aids in working towards desired futures, involving both incumbents and challengers in an effort to harness untapped yet proximal potentials in a forward-looking way. By embracing an innovation approach, it not only promises to circumvent resistance to change, but also serves as a step-by-step approach to identify options for multiple value creation and effective cooperation. We demonstrate the analytical and practical value of the TFA by discussing action perspectives at various levels and scales in the context of the Dutch food system transition, including (1) area-oriented approaches, (2) acceleration agendas for specific transformation pathways, and (3) actor-specific transformation flowers. In developing these, we emphasize the importance of interdependencies between leverage points. Our approach helps to identify opportunities to link transformative options (the what), actors (the who) and levers (the how) in dynamic interaction to embark on transformative pathways.

Background: Injury is an important cause of mortality and morbidity.(1). FA is the immediate assistance provided to a suddenly injured or sick person until professional help arrives or that person has recovered.(2), could be a potential factor differentiating between life and death in RTA . Many lives would be saved if proper first aid is provided early. (3) In the middle east, there are limited studies that explore knowledge and practices towards first aid needed during RTA. Objective: The main aim of this study is to investigate the knowledge and attitude towards first aid among drivers in Sharjah. Methodology: A cross-sectional study was conducted through a self-administered questionnaire written in Arabic and English languages. Participants were 18 years or older holding a driving license in the city of Sharjah. Paramedics and certified participants with a certification from authorized organizations were excluded . A non-proportional convenient sampling method was used. A total of 343 participants have completed the questionnaires. Data was entered and analysed using SPSS. Results: Majority of the study participants were less than 40 years old and (56.76%) were males. Most participants(94.2%) indicated that they know the term ‘First Aid’. However, (49.73%) of the participants knew the ambulance number and (52.43%) of the participants indicated that the victim should be moved to the hospital without the ambulance. With regards to attitude, 34.86% were not willing to provide first aid in the case of RTA. The main reason was lack of knowledge followed by fear of legal consequences. Most participants (83,78%) were willing to participate in first aid classes to improve their knowledge and attitude. Conclusion: Most participants are aware of the basic term of first aid; however, they are not willing to provide first aid in cases of RTA due to lack of knowledge and fear of legal consequences. Based on these findings we recommend providing first aid classes for new drivers and to obtain certification. References: 1 and 3. Midani, O., Tillawi, T., Saqer, A., Hammami, M., Taifour, H. and Mohammad, H., 2020. Knowledge And Attitude Toward First Aid: A Cross-Sectional Study In The United Arab Emirates. 2.Van de Velde S, Heselmans A, Roex A, Vandekerckhove P, Ramaekers D, Aertgeerts B. Effectiveness of nonresuscitative first aid training in laypersons:A systematic review. Ann Emerg Med 2009;54:447-57, 457e1-5.

Banana (Musa spp.) is an important crop to the economies of many developing countries. In the north of Argentina, a sub-tropical region, banana plants grow in a suboptimal environment that limits yield because only one harvest per year is achieved. The objective of this work was to characterize the agroecological aptitude of Formosa, Argentina, for banana production, through the behavior of three varieties of international use: Willians, Jafa and Gran Enano, evaluated during five consecutive campaigns. The three-way data analysis technique called Multiple Factor Analysis (MFA) was used for evaluating varieties’ performances across cycles of production. The results allowed inferring the existence of genotype x environment (GEI) interaction, corroborated by two-way factorial ANOVA. In order to determine how this suboptimal environment affects the development of each genotype of this perennial crop, Dual Multiple Factor Analysis (DMFA) was applied to jointly analyze the correlation structure among traits contributing to the performance of each variety at each campaign. The correlation structures between variables were different in each population and varied among campaigns. All traits showed a great variation across years and genotypes, the fruit peel thickness being the most discrepant throughout the campaigns. However, Formosa appeared as a promising subtropical agroecological environment to produce banana because varieties’ performances were acceptable for large scale production systems. In addition to evaluating the adequate aptitude for cultivating banana in Formosa considering the significant effect of GEI, this research makes a methodological contribution by proposing the use of three-way data analysis MFA and DMFA in Agronomy Science.

Background: Therapeutic climbing (TC) has emerged as a prospective rehabilitation approach for individuals with Multiple Sclerosis (MS). Existing literature primarily focuses on the physical and psychological benefits of TC across diverse populations but is limited concerning its application and efficacy for patients with MS. Objectives: This study aimed to delineate the experiences, effects, and perceptions of both individuals with MS and therapists regarding TC, highlighting the potential benefits and challenges of this therapeutic approach. Methods: Using a qualitative design, structured interviews were conducted with patients living with MS (N=5) and therapists (N=7) involved in TC sessions at a rehabilitation facility. The interviews were recorded, transcribed verbatim, and subjected to thematic qualitative text analysis. Results: Our analysis resulted in the identification of five main categories: (1) motivational factors, (2) training conditions, (3) training content, (4) observed effects, and (5) safety protocols. Findings primarily centred around the motivational aspects of TC. Participants consistently reported experiencing feelings of accomplishment, success, enjoyment, and increased self-confidence. Furthermore, TC was often perceived as a comprehensive intervention, addressing endurance, strength, flexibility, neuromotor functions, cognition, and mental health while having a low-risk profile. However, due to the demanding nature of TC, careful fatigue management is crucial. This entails personalized intensity adjustments during sessions and coordinating TC with other physically demanding therapies when implementing TC within a rehabilitation environment. Conclusions: TC shows promise within MS rehabilitation and can be considered safe under certain framework conditions. This research sheds light on its potential benefits, facilitators and barriers and provides insights for practical integration into rehabilitation programmes.

Neisseria meningitidis (N. meningitidis) serogroup B (MenB) is the leading cause of invasive meningococcal disease worldwide. The pathogen has a wide range of virulence factors, which are potential vaccine components. Studying the genetic variability of antigens within a population, especially their long-term persistence, is necessary to develop new vaccines and predict the effectiveness of existing ones. The multicomponent 4CMenB vaccine (Bexsero), used since 2014, contains three major genome-derived recombinant proteins: factor H-binding protein (fHbp), Neisserial Heparin-Binding Antigen (NHBA) and Neisserial adhesin A (NadA). Here, we assessed the prevalence and sequence variations of these vaccine antigens in a panel of 5667 meningococcal isolates collected worldwide over the past 10 years and deposited in the PubMLST database. Using multiple amino acid sequence alignments and machine learning methods, we estimated the potential strain coverage by fHbp and NHBA vaccine variants (51 and about 30%, respectively); the NadA antigen sequence was found in only 17.8% of MenB genomes analyzed, but cross-reactive variants were present in less than 1% of isolates. Based on our findings, we proposed various strategies to improve the 4CMenB vaccine and broaden coverage of N. meningitidis strains.

Undergraduate learning is a multifaceted concept that many researchers have investigated to promote student engagement, academic performance, etc. Exploring factors promoting learning among undergraduates in FYW programs, which are required for undergraduates might potentially contribute to sustainable, cross-disciplinary undergraduate education. This study used the 10-year longitudinal grade and survey data at San José State University (SJSU) and the data was collected from Academic Years (AYs) 2015 to 2020, and five student surveys constituted the sample size of 18,101 students. In 2016, SJSU changed the remedial writing course to college writing courses. Since then, students need to complete an online module course before placing themselves into a one-semester or two-semester writing course. The previous study showed that students with higher writing comfort and confidence tend to place themselves into a semester-long class. Regression analysis was applied to examine the relationships among factors promoting learning among those students. University admitted students from various diversity and backgrounds, the results of this study suggested that what students chose and persisted in were more important in advancing their academic success rather than prior learning experience or psychological factors before the class.

Telemonitoring and telerehabilitation have shown promise in delivering individualized healthcare remotely. We introduce STASISM, a Sensor-Based Telerehabilitation and Telemonitoring System, in this work. This platform has been created to facilitate individualized telerehabilitation and telemonitoring for those who need rehabilitation or ongoing monitoring. To gather and analyze pertinent and validated physiological, kinematic, and environmental data, the system combines a variety of sensors and data analytic methodologies. The platform facilitates customized rehabilitation activities based on individual needs, allows for remote monitoring of patients' progress, and offers real-time feedback. To protect the security of patient data and to safeguard patient privacy, STASISM also provides secure data transmission and storage. The platform has the potential to significantly improve the accessibility and efficacy of telerehabilitation and telemonitoring programs, enhancing patients' quality of life and allowing healthcare professionals to provide individualized care outside of traditional clinical settings/

Multiple Sclerosis (MS) is a neurodegenerative disease that mainly affects young adults. The high prevalence of the disease and its impact on patients' quality of life led to priority being given to the etiopathogenesis of the disease to identify possible modifiable factors and consequent effective intervention strategies. Recent hypotheses suggest that the etiopathogenesis of MS is multifactorial and includes factors related to the immune system, neuroinflammation and neuro-degeneration. In this scenario, sleep has a close - although indirect - relationship with MS, through its relationship with each of those factors. In particular, the role of cytokines in immune system impairment and neuroinflammation, mitochondrial dysfunction and oxidative stress in neurodegeneration all are associated with sleep in different forms. Furthermore, melatonin in relation with vitamin D has a potential therapeutic effect in MS sleep-related problems. Given the growing interest of research in the mechanisms underlying MS and therapies able to alleviate MS-related symptoms at all stages of the disease, a more in-depth study of the role of sleep disturbances and the factors intrinsically related to sleep and MS could be useful both to investigate the etiopathogenetic factors of MS and to develop potential non-invasive intervention strategies for MS treatment.

(1) Background: Prevention of acute cardiovascular events in patients with cardiovascular diseases (CVDs) requires promoting health-protective behaviors (e.g., physical activity) and preventing health-compromising behaviors (sitting). Digital health interventions provide much potential. Based on multiple behavioral change theory, an intervention (reCardial app) was evaluated, and the following hypotheses were tested: H1: Health behaviors (physical activity, sitting) and disease self-management (self-care maintenance, self-care confidence) are closely interrelated. H2: Change in health behaviors and disease self-management indicators over time is more pronounced in reCardial app-users. H3: In the intervention group, changes in systolic and diastolic blood pressure indicate a positive trajectory. (2) Methods: A study with the design of a randomized controlled trial over 12 weeks was conducted. 40 CVD-patients were randomized equally to the Intervention Group (35% women; Mage=60.6years) and Control Group (45% women; Mage=61.5years). (3) Results: Findings support H1 with significant correlations between health behaviors (r=0.45-0.63**), and disease self-management (r=-0.32-0.54**), H2 with Eta²=0.21 (not statistically significant) and H3 partially with d=0.101 for systolic blood pressure but not regarding diastolic blood pressure. (4) Conclusions: Replications are needed with larger samples and more objective measures. The app can help prevent and manage CVD by means of promoting health-protective behaviors and preventing health-compromising behaviors. Taking different behaviors into account can increase intervention effects and with that support of users.

Haematopoietic stem cell transplantation (HSCT) is a curative approach for blood cancers, yet its efficacy is undermined by a range of acute and chronic complications. In light of mounting evidence to suggest that these complications are linked to a dysbiotic gut microbiome, we aimed to evaluate the feasibility of faecal microbiota transplantation (FMT) delivered during the acute phase after HSCT. Of note, this trial opted for FMT prepared using the individual’s own stool (autologous FMT) to mitigate risks of disease transmission from donor stool. Adults (>18 years) with multiple myeloma were recruited from a single centre. Stool was collected prior to starting first-line therapy. Patients that progressed to HSCT were offered FMT via 3 x re-tention enemas before day +5 (HSCT = day 0). Feasibility was determined by recruitment rate, number and volume of enemas administered, and retention time. Longitudinally collected stool samples were also col-lected to explore the influence of auto-FMT using 16S rRNA gene sequencing. N=4 (2F:2M) participants received auto-FMT in 12 months. Participants received an average of 2.25(1-3) enemas (43.67(25-50)mL total, retained for an average of 60.78(10-145)minutes). No AEs, attributed to the FMT, were identified. Although minimum requirements were met for the volume and retention of auto-FMT, recruitment was significantly impacted by the logistical challenges of pre-therapy stool collection. This ultimately under-mined the feasibility of this trial and suggests that third party (donor) FMT should be prioritised.

Background. The purpose of the study was to evaluate the intensity and frequency of low back pain (LBP) in people with multiple sclerosis (PwMS) and the patient's knowledge of physiotherapeutic methods of combating. Methods. In this study, patients with confirmed multiple sclerosis were selected. The study was carried out using an original survey questionnaire and a numerical pain intensity scale (Visual Analogue Scale). PwMS were divided into 3 age groups: 18-30 years, 31-50 years, and over 50 years. Results. Ninety PwMS (68 women and 22 men) aged 18 to 60 years were included in the study. The mean duration of the disease was 9.5±4.9 years, and the mean EDSS was 3.5±1.6. Most of the patients had a relapse-remitting form. 68.9% of PwMS felt lower back pain (n = 62). The relationship tested was statistically significant (p=0.0000012), and the strength of the relationship was high (rc=0.695). The average level of low back pain among PwMS was 4.7 out of 10 on the VAS scale. The prevalence of LBP was higher in female patients (p<0.001), with a secondary progressive form (p<0.001) and with a longer duration of the disease (p=0.023). The most widely used methods of LBP therapy were kinesitherapy and manual therapy. Conclusions. LBP is common in multiple sclerosis. A female sex, a secondary progressive form of MS, and a longer duration of the disease increased the risk of LBP. It is important to implement properly planned physiotherapy activities and educate patients on how to combat LBP.

Object detection is important in many applications, such as autonomous driving. While 2D images are lack of depth information and are sensitive to environmental conditions, 3D point cloud can provide accurate depth information and a more descriptive environment. However, sparsity is always a challenge in single-frame point cloud object detection. This paper introduces a two-stage proposal-based feature fusion method for object detection using multiple frames. The proposed method, called proposal features fusion (PFF), utilizes a cosine-similarity approach to associate proposals from multiple frames and employs an attention weighted fusion module to merge features from these proposals. It allows for feature fusion specific to individual objects and offers lower computational complexity while achieving higher precision. The experimental results on the nuScenes dataset demonstrate the effectiveness of our approach, achieving a mAP of 46.7%, which is 1.3% higher than the state-of-the-art 3D object detection method.

Post-stroke depressive disorders (PSD) and post-stroke cognitive impairments (PCI) are frequent consequences of ischemic stroke (IS). The study was focused on exploring possible associations between relative volumes of cortical and limbic brain structures during the acute period of IS, and changes in biochemical indices of hypothalamic-pituitary-adrenal, sympathoadrenal medullary and inflammatory systems, with the development of PSD or PCI after mild or moderate IS. Patients developing PSD later on had significantly smaller relative volumes of the hippocampus, entorhinal cortex, and temporal pole versus patients without depressive symptoms. PCI development was associated with significantly smaller volumes of temporal pole and supramarginal gyrus versus patients without cognitive changes. Multiple logistic regression analysis showed higher likelihood of developing PSD in patients with smaller temporal pole volume (β0=10.9; β=-4.27; p=0.04) and increased salivary α-amylase activity (β0=-3.55; β=2.68e-05; p=0.02,). PCI likelihood was higher in patients with smaller supramarginal gyrus volume (β0=3.41; β=-0.99; p=0.047), smaller temporal pole volume (β0=3.41; β=-3.12; p=0. 06), and increased hair cortisol concentration at admission (index of accumulated stress load within a month before IS; β0=3.41; β=-0.05; p=0.08). The data support the hypothesis suggesting predisposition to PSD and PCI and multi hit scenarios of their pathogenesis with IS providing a final hit.

Based on the multiple coordination framework of “promising government-effective market-ordered society”, this paper takes 68 cases of adding elevators to old buildings as samples, and selects six conditional variables: approval optimization, financial subsidies, financing innovation, technological innovation, capable people leading and neighborhood committee guidance. Using Crisp-Set Qualitative Comparative Analysis (csQCA), this paper discusses the combination of conditions that affect the success or failure. It is found that: approval optimization and neighborhood committee guidance are sufficient conditions for the success; successful cases can be divided into three types: “political and social dual-drive type”, “market and social dual-drive type” and “ternary co-drive type”; lack of approval optimization, lack of financing innovation, and the existence of capable people leading are necessary conditions for the failure. The failure cases can be divided into “government and market double failure type” and “market failure type”.

As renewable energy generation prediction systems have been introduced into the energy trading market, accurate prediction of solar photovoltaic (PV) energy generation has become a crucial challenge for ensuring stable trade of variable energy. Therefore, it is essential to quantitatively investigate and analyze current prediction technology and develop more advanced prediction systems. In this study, three models for predicting PV energy generation were investigated. Multiple regression, random forest, and gradient boosting machine (GBM) models were con-structed for 15 utility-scale power plants throughout South Korea. Model performance was evaluated in terms of root mean square error (RMSE) and mean absolute error (MAE). The multiple regression-based model had an RMSE of 12.00% and MAE of 9.06%. The random forest model had an RMSE of 11.69% and MAE of 8.61%. The GBM model had an RMSE of 11.34% and MAE of 8.18%, indicating its superior accuracy among the three models in predicting PV energy generation. These findings provide valuable insights that may contribute to the development of advanced PV energy generation models and their application in grid operations.

Machine learning (ML) systems that use sensors obtain observations from sensors and use them to recognize and interpret the current situation. These systems are susceptible to sensor-based adversarial example attacks (AEs); if some sensors are vulnerable and can be compromised by an attacker, the attacker can change the output of the system by changing the values of the sensors. The detection of compromised sensors is important to defend the system against sensor-based AEs, because we can check the sensors and replace them by detecting the sensors used by the attacker. In this paper, we propose a method to detect the sensors used in sensor-based AEs by utilizing the features of the attack that cannot be avoided. In this method, we introduced a model called the feature-removable model (FRM), which allows us to select the features used as inputs into the model. Our method detects the sensors used in sensor-based AEs by finding the inconsistencies between the outputs of the FRM obtained by changing the selected features. We evaluated our method using a human activity recognition model with sensors attached to the user’s chest, wrist, and ankle. We demonstrate that our method can accurately detect sensors used by the attacker and achieves an average Recall of Detection of 0.92, and the average Precision of Detection is 0.72.

The persistence of geographic inequities in vaccination coverage often evidences the presence of zero-dose and missed communities and vulnerabilities to vaccine-preventable diseases. These inequities were exacerbated in many places during the COVID-19 pandemic, due to severe disruptions to vaccination services. Understanding changes in zero-dose prevalence and associated risk factors in the context of the COVID-19 pandemic is, therefore, critical to designing effective strategies to reach vulnerable populations. Using data from nationally representative household surveys conducted before the COVID-19 pandemic in 2018 and during the pandemic in 2021 in Nigeria, we fitted Bayesian geostatistical models to map the distribution of three vaccination coverage indicators: receipt of DTP1, MCV1 and any of the four basic vaccines (BCG, OPV0, DTP1 and MCV1), and corresponding zero-dose estimates independently at 1x1 km resolution and the district level during both time periods. We also explored changes in the factors associated with non-vaccination at the national and regional levels using multilevel logistic regression models. Our results revealed no increases in zero-dose prevalence due to the pandemic at the national level, although considerable increases were observed in a few districts. We found substantial subnational heterogeneities in vaccination coverage and zero-dose prevalence both before and during the pandemic, showing broadly similar patterns in both time periods. Areas with relatively higher zero-dose prevalence occurred mostly in the north and a few places in the south in both time periods. We also found consistent areas of low coverage and high zero-dose prevalence using all three zero-dose indicators, revealing areas in greatest need. At the national level, risk factors related to socioeconomic/ demographic status (e.g., maternal education), maternal access to and utilization of health services and remoteness were strongly associated with the odds of zero dose in both time periods, while those related to communication were mostly relevant before the pandemic. These associations were also supported at the regional level, but we additionally identified risk factors specific to zero dose in each region; for example, communication and cross-border migration in the northwest. Our findings can help guide tailored strategies to reduce zero-dose prevalence and boost coverage levels in Nigeria.

The commonly quoted bistable Higgs potential is not a proper description of the Higgs field because, among other technical reasons, one of its stable states acquires a negative expectation value in vacuum. We rely on formal catastrophe theory to derive the form of the Higgs potential that admits only one positive mean value in vacuum. No symmetry is broken during the ensuing phase transition that assigns mass to the Higgs field; only gauge redundancy is “broken” by the appearance of phase in the massive state, but this redundancy is not a true symmetry of the massless field. Furthermore, a secondary, certainly amusing conclusion is that, in its high-energy state, the field oscillates about its potential minimum between positive and negative masses; but it is doubtful that such evanescent states can survive below the critical temperature of 159.5 GeV, where the known particles were actually created.

The classical joint economic lot-sizing (JELS) policy in a single-vendor single-buyer system generates an equal production quantity in all cycles, where the input parameters remain static indefinitely. In this paper, a new two-echelon supply chain inventory model is developed involving a hybrid production system that simultaneously focuses on green and regular production methods with optimal allocation fraction of green and regular productions. Unlike the classical mathematical formulation, each cycle is independent from the previous one, and consequently, the input parameters can be adjusted to be responsive to the dynamic nature of demand rate and price fluctuation. A rigorous heuristic approach is used to derive a global optimal solution for a joint hybrid production system. The model accounts for carbon emissions from production and storage activities related to green and regular produced items along with transportation activity under a multi-level emission-taxing scheme. The results emphasize the significant impact of green production on emissions. That is, the higher the allocation fraction of green production the lower the total amount of emissions generated by the system, i.e., the system becoming more sustainable. Adopting a hybrid production method not only decreases the greenhouse gas (GHG) emissions dramatically, but also reduces the per unit time total cost when compared with regular production. One of the main findings is that the total system cost generated by the base closed-form formula of the proposed model is considerably lower than that of the existing literature i.e., 33.59% (16.13%) lower in the first cycle (subsequent cycles) when the regular production method is assumed. Moreover, the optimal production rate generated by the proposed model is the one that minimizes the emissions production function. Illustrative examples and special cases that reflect different realistic situations are compared to outline managerial insights.

Balo’s concentric sclerosis is a rare disease and a subtype of multiple sclerosis. A 38-year-old male patient presented to the hospital with the complaint of numbness in the left-sided upper and lower limb, slurring of speech and left-sided headache for 15 days. Further investigation was done and in ECG ‘Delta wave’ was identified along with tachycardia. Diagnosis of Wolff Parkinson White syndrome was made. The patient’s MRI Brain has shown a non-enhancing intra-axial altered signal intensity lesion at the callose-septal interface adjacent to both lateral ventricles, which was identified as Balo’s concentric sclerosis.

There are no theorems (proven theories) in the biological sciences. We propose that the 3 31 nt minihelix tRNA evolution theorem be universally accepted as one. The 3 31 nt minihelix theorem completely describes evolution of type I and type II tRNAs from ordered precursors (RNA repeats and inverted repeats). Despite diversification of tRNAome sequences, statistical tests overwhelmingly support the theorem. Furthermore, the theorem relates the dominant pathway for the origin of life on Earth, specifically, how tRNAomes and the genetic code may have coevolved. Alternate models for tRNA evolution (i.e., 2 minihelix, convergent and accretion models) are falsified. In the context of the pre-life world, tRNA was a molecule that via mutation could modify anticodon sequences and teach itself to code. We relate the clearest history to date of the chemical evolution of life on Earth. From analysis of tRNA evolution, ribozyme-mediated RNA ligation was a primary driving force in evolution of complexity during the pre-life to life transition on Earth.

Art organizations are increasingly focusing on enhancing the visitor experience to attract a wider audience. The aim objective of this study was to explore the key factors that influence the visitor experience of offline art exhibitions and to use a mixed methods to data collection and analysis. The research process was divided into three stages. In the first stage, we conducted semi-structured interviews with 12 respondents by dividing the exhibition experience into three time periods: pre, during, and post-visit. We extracted seven factors affecting visitor experience through qualitative content analysis including marketing, motivation, physical environment, exhibit quality, participation, technology and service facilities; in the second stage, we developed an assessment scale and pretested it; in the third stage, we collected 725 questionnaires to validate the factors of visitor experience in art exhibitions. The results of linear regression analyses showed that all seven key factors had a significant impact on visitor experience. This study constructed a scale to assess the factors of art exhibition experience, which provides theoretical sup-port for in-depth study of art exhibition experience and useful guidance for planning and design-ing art exhibitions to improve the quality of visitors' experience of art exhibitions.

Revealing the underlying pathomechanisms of neurological and psychiatric disorders, searching for new biomarkers, and developing novel therapeutics all require translational research. In vivo and in vitro disease models have been instrumental in casting light on complex polygenic, multifactorial, and heterogeneous disease mechanisms. In the most recent years, advanced preclinical models have revealed the intriguing interaction of sex/gender and aging with the pathogenesis and clinical manifestations of psychiatric and neurological diseases. However, despite these advancements, there is still a great deal of work to be done to fully comprehend the underlying mechanisms of these diseases and to develop treatments that can significantly improve the lives of those who suffer from them. The current challenge in the field of neurological and psychiatric diseases is to develop disease-modifying, effective treatments for these complex and long-lasting debilitating conditions with a high burden of disease.The first edition of the research topic ‘Emerging Translational Research in Neurological and Psychiatric Diseases: From In Vitro to In Vivo Models’ reinforces translational research playing a critical role in bridging the gap between basic research and clinical applications. Also, it provides a platform for researchers to share their findings and advancements in translational research in this field. This new collection gathers 25 papers offering insights into the latest advancements in translational research and potential new avenues for treatments. These papers cover various topics, including the development of new preclinical models, the use of in vitro and in vivo methods, and the application of qualitative and quantitative research methods.

This paper presents a novel approach for the recognition of multiple sclerosis (MS) using wavelet entropy and a Particle Swarm Optimization (PSO)-based neural network. MS is a complex neurological disorder with diverse clinical manifestations, often challenging to diagnose accurately. In this study, we leverage wavelet entropy (WE) as a feature extraction method to capture intricate patterns within brain imaging data. These extracted features are then employed to train a neural network model optimized through PSO to enhance classification accuracy. Experimental results on a dataset comprising MS and healthy control subjects demonstrate the effectiveness of our proposed approach, viz., WE-PSONN, which achieves a sensitivity of 91.95±1.15, a specificity of 92.36±0.88, a precision of 92.28±0.88, an accuracy of 92.16±0.90. The combination of advanced signal processing techniques and machine learning optimization holds promise for improving the early diagnosis and management of MS, offering potential benefits to both patients and healthcare providers.

We introduce linear probing hashing schemes that construct a hash table of size $n$, with constant load factor $\alpha$, on which the worst-case unsuccessful search time is asymptotically almost surely $O(\log \log n)$. The schemes employ two linear probe sequences to find empty cells for the keys. Matching lower bounds on the maximum cluster size produced by any algorithm that uses two linear probe sequences are obtained as well.

Influenza virus can cause several complications during pregnancy. Therefore, we aimed to inves-tigate the effects of influenza on the development of congenital abnormalities (CAs) by analyzing the database of the Hungarian Case-Control Surveillance of Congenital Abnormalities (HCCS-CA). In our multicenter, case-control, population-based study, we processed clinician-reported outcomes and diagnoses collected in the HCCSCA. The case group included newborns with dif-ferent non-chromosomal birth defects, while controls were newborns without CAs. Maternal in-fluenza, as a risk factor for CAs, was analyzed by using a logistic regression model and odds ra-tios with 95% confidence intervals (CIs). Our results showed that maternal influenza in the first trimester was associated with increased odds of developing non-chromosomal CAs (OR: 1.41, CI: 1.28–1.55). There were increased odds of neural tube defects (OR: 2.22, CI: 1.78–2.76), orofacial clefts (OR: 2.28, CI: 1.87–2.78) and congenital heart defects (OR: 1.28, CI: 1.10–1.49) after influenza infection. In all cases, we found a protective effect of folic acid supplementation in the first tri-mester. The odds of non-chromosomal birth defects are higher after maternal influenza in the first -trimester. Folic acid or pregnancy vitamin supplementation and antipyretic therapy may reduce the effect of maternal influenza during the first trimester.

The electronic, optical, and magnetic properties of Nd-doped ZnO systems were calculated using the DFT/GGA+U method. According to the results, the Nd dopant causes lattice parameter expansion, negative formation energy, and bandgap narrowing, resulting in the formation of an n-type degenerate semiconductor. Overlapping of the generated impurity and Fermi levels results in a significant trap effect that prevents electron-hole recombination. The absorption spectrum demonstrates a redshift in the visible region and improved intensity, leading to enhanced photocatalytic performance. The Nd-doped ZnO system displays ferromagnetic, with FM coupling due to strong spd-f hybridization through magnetic exchange interaction between the Nd-4f state and O-2p, Zn-4s, and Zn-3p states. These findings imply that Nd-doped ZnO may be a promising material for DMS spintronic devices.

Dielectric elastomer actuators (DEAs) offer robust, high energy density solutions for soft robotics. The proposed end effector consists of three spring roll configuration DEAs, each acting as a robotic finger, using a 3M VHB-F9473PC adhesive membrane. The lateral force, bending angle and response time of the actuator are measured experimentally and compared with the predictions of an analytical model. The cylindrical actuator measures 70 mm in length and 15 mm in diameter and achieved a lateral force of 30 mN, a bending angle of 6.8 ° and a response time of ≈ 1 s. Spring roll configuration DEAs are shown to reduce the effects of viscoelasticity seen in the membrane, making the actuator more controllable at higher voltages. The dielectric constant of the membrane is shown to be a limiting factor of actuation, with a decrease in dielectric constant resulting in larger actuation. The end effector successfully gripped numerous light objects for extended periods, showing the applicability of spring roll DEAs for soft end effectors.

Growing incidence of myopia worldwide justifies the search for efficient methods of myopia prevention. Numerous pharmacological, optical, and lifestyle measures have already been utilized, but there remains a need to explore more practical and predictable methods for myopia control. This paper presents a review of the latest literature on preventing the progression of myopia using Defocus Incorporated Multiple Segments Spectacle Lenses (DIMSsl), Repeated Low-level Red-Light Therapy (RLRL), and the combination of low-dose atropine (0.01%) with orthokeratology lenses.

By making periodic thru-holes in a suspended film, the phonon system can be modified. Motivated by the BCS theory, the technique -- so-called phonon engineering -- was applied to a metallic niobium sheet. It was found that its electrical resistance dropped to zero at 175 K, and the zero-resistance state persisted up to 290 K in the subsequent warming process. Despite the initial motivation, neither these high transition temperatures nor the phase transition with thermal hysteresis can be accounted for by the BCS theory. Therefore, we abandon the BCS theory. Instead, it turns out that the metallic holey sheet is partly oxidized to form a niobium-oxygen square lattice, which has points of resemblance to a copper-oxygen plane, the fundamental component of cuprate high-T_c superconductors. Therefore, the pairing mechanism underlying this study should be related to that of cuprate high-T_c superconductors, which we may not yet understand. In addition to the electrical results of zero resistance, the holey sheet exhibited a decrease in magnetization upon cooling, i.e., the Meissner effect. Moreover, the remnant magnetization was clearly detected at 300 K, which can only be attributed to persistent currents flowing in a superconducting sample. Thus, this study meets the established criteria for a conclusive demonstration of true superconductivity. Finally, the superconducting transition with the unambiguous thermal hysteresis is discussed. According to Halperin, Lubensky, and Ma, or HLM for short, any superconducting transition must always be first order with thermal hysteresis because of the intrinsic fluctuating magnetic field. The HLM theory is very compatible with the highly oriented system harboring two-dimensional superconductivity.