We propose a novel optimization approach for determining the envelopes of thin-film transmittance spectra. This method can be coupled with the Swanepoel algorithm to determine the optical properties of the thin films.

The main goal of optimization is to find factors values that bring minimum feedstock consumption or maximum final product or services of the production process. In a production process, the factors that make up the model that describes it are usually the properties of the final product. In the case of biodiesel, which is the final product of the process that is the object of study, among the various properties, the glycerol content is among the most important. The present study aims to maximize the model yield that defines glycerol content on the biodiesel composition. This optimization was executed by a hybrid metaheuristic algorithm (SAGAC),and its experimental results are compared with other optimization techniques named by RSM (Response Surface Methodology). After run the experimental assays, SAGAC algorithm has find the follow values of model factors: molar ratio = 3(mol/mol), catalyst content = 0.52 (wt%), reaction temperature = 49(^oC), Time = 45 (min) generating model yield of 14.46 that, match with EN 14105 standard value of 0.33 (wt%). Comparing results between SAGAC and RSM methodologies, SAGAC has presented an improvement of 31%.

Theories about consciousness—what it is/is not; who does/does not possess it; included/excluded functional modes; how/when it appears to be operational—are regularly published in books and articles. This essay opines that while many, if not most, of those speculations contain elements properly subsumed within a comprehensive doctrine, none satisfactorily fulfills its subject’s immense scope. Consciousness = Metaphysics + Physics + Biology is intended to rectify the situation by providing omitted components. As the title states, this is a wide-ranging approach neglecting many relevant details found in cited references, but also including ideas not found elsewhere in the easily accessible literature.

This review explores the crucial role of glycosphingolipids (GSLs) in the context of cardiovascular diseases (CVD), focusing on their biosynthesis, metabolic pathways, and implications for clinical outcomes. GSLs are pivotal in regulating a myriad of cellular functions that are essential for heart health and disease progression. Highlighting findings from both human cohorts and animal models, this review emphasizes the potential of GSLs as biomarkers and therapeutic targets. We advocate for more detailed mechanistic studies to deepen our understanding of GSL functions in cardiovascular health, which could lead to innovative strategies for diagnosis, treatment, and personalized medicine in cardiovascular care.

Adaptive hyperactivity, characterized by increased activity levels and novelty-seeking traits without mood disorders, is prevalent among older adults in Sardinia's "blue zone," an area with high longevity. This study aims to evaluate the adaptive nature of hyperac-tivity concerning quality of life, social rhythms, and mood symptoms in individuals from this region, particularly among older adults over 80. Methods: This observational cross-sectional study included adults and older adults over 80 years from Sardinia's blue zone, recruited from the dermatology clinic at the University Hospital of Cagliari. Partici-pants underwent psychiatric interviews and completed the Mood Disorder Questionnaire (MDQ), Patient Health Questionnaire (PHQ-9), SF-12, and Brief Social Rhythm Scale (BSRS). Data were compared with national and regional normative data. Results: Older adults in the blue zone demonstrated higher MDQ positivity (22.58%) compared to na-tional averages (0.87%), without corresponding increases in dysregulated rhythms, de-pressive symptoms, or reduced quality of life. Younger elders (65-79 years) showed in-creased rhythm dysregulation (BSRS score: 20.64±7.02) compared to adults (17.40±6.09, p=0.040), but this trend was not observed in older elders (80+ years). No significant differ-ences were found in CH3SH and (CH3)2S levels between groups. Conclusions: Hyperactiv-ity observed in older adults from Sardinia's blue zone appears adaptive, not linked to so-cial rhythm dysregulation, depressive symptoms, or diminished quality of life, suggesting resilience factors that may contribute to longevity. These findings support the potential classification of such hyperactivity as beneficial rather than pathological, warranting fur-ther research into biomarkers and psychoeducational interventions to prevent the onset of bipolar disorders in predisposed individuals.

Currently, the Bangladeshi financial sector is undergoing significant transformations. With the expansion of the infrastructure and the increasing prevalence of digital banking services, it is essential to take measures to prevent cyberattacks. These threats can be effectively mitigated through the utilization of deep learning and machine learning techniques. Through the analysis of massive amounts of banking data in real-time, these methods make it possible to detect and prevent malicious software, fraud, and security breaches that are proactive. Because the government is actively pushing for financial inclusion and digitalization, strong cybersecurity measures are more important than they have ever been. It is the purpose of this study to investigate the application of deep learning and machine learning to improve the cybersecurity environment of Bangladesh’s banking sector in light of the country’s rapidly expanding digital economy.

In relativity, the Newtonian concepts of velocity and acceleration are observer-dependent quantities that vary with the chosen frame of reference. It is well established that in the comoving frame, cosmic expansion is currently accelerating; however, in the rest frame, this expansion is actually decelerating. In this paper, we explore the implications of this distinction. The traditional measure of cosmic acceleration, denoted by q, is derived from the comoving frame and describes the acceleration of the scale factor a for a 3D space-like homogeneous sphere. We introduce a new parameter q_E representing the acceleration experienced between observers within the light cone. By comparing q_E to the traditional q using observational data from Type Ia supernovae (SN) and the radial clustering of galaxies and quasars (BAO)—including the latest results from DESI2024—our analysis demonstrates that q_E aligns more closely with these data. The core argument of the paper is that Λ—regardless of its origin—creates an event horizon that divides the manifold into two causally disconnected regions analogous to conditions inside a black hole’s interior, thereby allowing for a rest-frame perspective q_E in which cosmic expansion appears to be decelerating and the horizon acts like a friction term. Such a horizon suggests that the universe cannot maintain homogeneity outside. The observed cosmological constant Λ can then be interpreted not as a driver of new dark energy or a modification of gravity but as a boundary term exerting an attractive force, akin to a rubber band, resisting further expansion and preventing event horizon crossings. This interpretation calls for a reconsideration of current cosmological models and the assumptions underlying them.

Abstract Introduction and Objectives Multimorbidity, defined as the coexistence of two or more chronic conditions, poses significant challenges in healthcare by affecting patient outcomes and increasing costs. This study aimed to evaluate multimorbidity's impact on patients with genitourinary cancer (GUC) in Chile, focusing on prevalent comorbidities, their combinations, and their association with hospitalization severity. Materials and Methods A retrospective, population-based study was conducted using data from the Fondo Nacional de Salud (FONASA) in Chile, including patients with bladder, prostate, kidney, and testicular cancer between 2019 and 2021. Diagnosis-related group (DRG) data were used to analyze comorbidity prevalence, hospitalization type (elective vs. emergency), severity (moderate/major vs. minor/none), length of stay, and associated costs. Results Among 4,028,597 hospital events, 11.6% were related to GUC, involving 18,792 patients. Multimorbidity was present in 67.3% of patients, with hypertension and diabetes being the most common comorbidities. These patients accounted for 69.1% of total GUC care costs. Hospital mortality was higher in multimorbid patients (7.5% vs. 3.7%; P

Turmeric starch (TS) has gained significant attention due to its potential health benefits, this study intended to investigate the dose-dependent effects of TS on colonic fermentation in rats. Four experimental diets containing different levels of TS (5%, 10%, and 20% w/w) were formulated and fed to male Fischer 344 rats for two weeks and compared with rats fed 0% TS diet (TS0). The results showed that increasing doses of TS resulted in reduced body weight gain and lower visceral tissue weights compared to the TS0 group. These effects may be attributed to the high content of resistant starch in TS, which contributed to lower caloric intake. Colonic fermentation analysis revealed that higher doses of TS resulted in increased short chain fatty acids (SCFA) production, specifically increased cecal acetate content and decreased cecal pH dose-dependently. Notably, beneficial bacteria from the family Oscillospiraceae, genus Lachnospiraceae NK4A136 group, and Ruminococcus spp. were enriched in the TS-fed groups, further supporting its beneficial effects on gut microbiota and SCFA production. Furthermore, these results suggest that TS may have beneficial effects on colonic fermentation in rats.

Introduction and importance: Congenital bicuspid aortic valve (BAV) is a common cardiac malformation predisposing individuals to aortic stenosis, regurgitation, and aortopathy. This risk persists even after aortic valve replacement (AVR). Case presentation: We report a case of a male in his 60s with a history of BAV who underwent bioprosthetic aortic valve replacement (BVR) and ascending aorta/root repair in 2014. The patient was noncompliant with follow-up and presented nine years later with severe bioprosthetic aortic stenosis and an 8.0 cm ascending aortic aneurysm with no symptoms. Emergent redo BVR and aneurysm repair were successful. Clinical discussion: It should be emphasized that successful outcomes for BAV patients require a lifelong commitment to surveillance, even after surgical intervention. Noncompliance can lead to life-threatening consequences like bioprosthetic valve deterioration or progressive aortic dilation. Conclusion: This case highlights the importance of early BAV diagnosis for ongoing monitoring, accessible follow-up care after complex cardiac procedures, and addressing patient barriers to treatment adherence.

Nocardia cyriacigeorgica causes bovine mastitis, reduces milk quantity and quality, and is often re-sistant to antimicrobials. Selenomethionine (SeMet) is a form of selenium, an essential trace el-ement. Although SeMet reduced ROS-mediated apoptosis and intramammary infections. How-ever, protective effects of SeMet on N. cyriacigeorgica-infected bovine mammary epithelial cells (bMECs) are unclear. The objective was to evaluate whether SeMet mitigated N. cyriacigeorgi-ca-induced inflammatory injury, oxidative damage and apoptosis in bMECs. Cells were cultured with or without being pretreated 40 µM of SeMet for 12 h, then challenged N. cyriacigeorgica (MOI=5:1) for 6 h. Although N. cyriacigeorgica was resistant to lincomycin, erythromycin, en-rofloxacin, penicillin, amoxicillin, cephalonium, cephalexin, and ceftriaxone, 40 μM SeMet in-creased cell viability and inhibited LDH release in infected bMECs. Furthermore, N. cyriacigeor-gica significantly induced mRNA production and protein expression of TNF-α, IL-1β, IL-6, and IL-8 at 6 h. Cell membrane rupture, cristae degeneration and mitochondria swelling were evi-dent with transmission electron microscopy. SOD and GSH-px activities were down regulated after 3, 6 or 12 h, whereas MDA and ROS contents were significantly upregulated, with cell damage and apoptosis rapidly evident (the latter increased significantly in a time-dependent manner). In contrast, bMECs pretreated with 40 μM SeMet before infection, SOD and GSH-px ac-tivities were upregulated (P < 0.05), MDA and ROS concentrations were downregulated (P < 0.05), and apoptosis was reduced (P < 0.05). In conclusion, 40 μM SeMet alleviated inflammation, oxi-dative stress and apoptosis induced by N. cyriacigeorgica in bMECs cultured in vitro.

The objective of this study was to develop and evaluate artificial intelligence (AI) models for the detection and instance segmentation of vertebrae and spinal metastases in computer tomography (CT) scans. The models were trained on datasets consisting of patients with polytrauma and relatively undamaged spines, as well as patients diagnosed with spinal metastases. Our results indicate that the models achieved high performance in vertebra segmentation, with F-beta scores ranging from 0.88 to 0.96 across all vertebra classes. For spinal metastases, the model attained F-beta scores of 0.68 for lytic type and 0.57 for sclerotic type metastases. Additionally, the models demonstrated the capability to detect isolated metastatic nodes in other bones, highlighting their robustness and potential for broader clinical application. Despite these promising results, the study faced limitations including a relatively small and homogeneous dataset, variability in segmentation mask quality, and the need for real-world clinical validation. Future clinical trials are necessary to evaluate the practical utility and effectiveness of these AI models in improving patient outcomes. Our study emphasizes the potential of AI-assisted detection and segmentation models in enhancing diagnostic accuracy and efficiency in clinical practice.

Introduction: Situated within the broad spectrum of lymphoproliferative diseases, Hodgkin (HL) and non-Hodgkin lymphomas (NHL) are neoplasms renowned for their complexity and heterogeneity, insidious onset, and frequent detectability at advanced, even terminal, stages worldwide.Objectives: The study aimed to compile conclusive statistics, identify genetic factors, and establish correlations with environmental carcinogens, while simultaneously highlighting the importance of developing preventive informational programs for the population.Materials and Methods: The retrospective study encompassed individuals admitted to the Hematology Clinic of "Sfântul Spiridon" Hospital in Iași between January 1, 2010 and December 31, 2019. Out of 1916 patients hospitalized with hematologic neoplasms, 392 were diagnosed with lymphoma. Eighty-four cases exhibiting genetic predisposition (21.42%) were selected, among which 20 displayed a heightened genetic burden (5.1%). These cases were thoroughly analyzed based on medical records.Results and discussion: The study underscores/highlights/emphasizes the significant position of malignant lymphomas among hematologic neoplasms (20.45%). Although the majority do not present malignant heredocolateral antecedents(78.58%), with an estimated empirical recurrence risk(2-4%), predisposing diseases, along with exposure to environmental carcinogens, as well as the region of residence, play fundamental roles in the determinism. It is observed that older individuals from urban agglomerations, especially males (54-70%), have a higher probability of developing these conditions and are therefore recommended to undergo regular check-ups.Conclusion: Unequivocally characterized by a vast etiology, multifactorial diseases result from the bilateral interaction between environmental and hereditary factors.

The integration of genetic technologies into neurological diagnostics has significantly enhanced our ability to understand and manage neurological disorders. This article discusses the functional analysis of key genetic tests, including microarray analysis, variant sequencing, exome sequencing, RNA sequencing, and whole genome sequencing. Each of these technologies offers unique advantages and challenges, providing a comprehensive toolkit for diagnosing and understanding the genetic basis of neurological conditions. The functional insights gained from these tests not only detect genetic abnormalities but also elucidate their functional consequences, aiding in the diagnosis, prognosis, and management of neurological disorders. As these technologies continue to evolve, they are expected to play an increasingly important role in the field of neurological diagnostics, paving the way for personalized medicine and improved patient outcomes.

Distributed Denial of Service (DDoS) is among the commonly used type of network attacks, particularly aimed at the IoT devices in the emerging future wireless services specially for strictly latency-limited applications. DDoS attacks pose serious threats for many entrepreneurial businesses as they can prevent legitimate customers from accessing network resources of corporate websites, demanding intelligent analytics prior to entertaining a service request. DDoS involves exploiting the vulnerability of IoT devices by launching distributed multi-point attacks to generate high traffic by flooding the network of victims. The consequences of DDoS attacks could be worst in any Software-Defined Networking (SDN) than in traditional networks because SDN is configured as centralised architecture, failing to address the weaknesses current paradigm. However, SDN can play a crucial role in mitigating the effects of DDoS attacks as it bears the features of easy programmability, manageability, flexibility, and scalability. In this manuscript preliminary framework to detect DDoS attacks by mitigating their threats in an SDN architecture is presented. The authors propose a defense mechanism that uses OpenFlow and sFlow to mitigate the effects of DDoS attacks. The initial results show that the proposed model can minimize efficiently the consequences of DDoS attacks in an SDN type of architectural paradigm.

Knee joint injuries, including those affecting the anterior cruciate ligament (ACL), meniscus, and cartilage, present complex challenges in sports medicine and orthopedics due to the intricate cellular and molecular mechanisms involved in tissue damage and repair. Understanding the molecular biology underpinning these processes is crucial for developing effective therapeutic and rehabilitation strategies. This systematic review investigates the impact of mechanical loading on the cellular responses during knee joint injury repair, with a particular focus on the molecular pathways involved in tissue regeneration. Mechanical loading plays a dual role, where controlled early loading can promote tissue repair, while excessive or inappropriate loading can exacerbate tissue damage. Fibroblasts, chondrocytes, and mesenchymal stem cells (MSCs) are central to the repair process, and their activation, proliferation, and differentiation are regulated by key molecular pathways. Upon injury, mechanotransduction pathways such as the integrin/FAK signaling axis are activated, which convert mechanical signals into biochemical responses that regulate cell adhesion, migration, and extracellular matrix (ECM) synthesis. Additionally, mechanosensitive ion channels like Piezo1 and TRPV4 modulate intracellular calcium levels, triggering downstream signaling cascades such as calmodulin/CaMKII, which regulate gene transcription and cellular responses to mechanical stress. The YAP/TAZ pathway, a critical component of the Hippo signaling pathway, responds to mechanical stimuli and regulates cell proliferation and ECM production in fibroblasts and chondrocytes. YAP/TAZ translocate to the nucleus in response to mechanical loading, where they interact with transcription factors such as TEAD, promoting the expression of genes involved in collagen synthesis and tissue repair. In parallel, growth factors like transforming growth factor-beta (TGF-β) and fibroblast growth factor (FGF) activate the TGF-β/Smad and PI3K/Akt signaling pathways, driving MSC differentiation into fibroblasts and chondrocytes, essential for ligament and cartilage repair. Mechanical loading also influences the inflammatory response at the injury site by modulating immune cell activity. Early mechanical loading can shift macrophages from a pro-inflammatory M1 phenotype to an anti-inflammatory M2 phenotype, mediated by growth factors such as TGF-β and interleukin-10 (IL-10). This phenotypic switch promotes tissue regeneration by enhancing ECM synthesis and resolving inflammation, which is crucial for long-term joint health. Matrix metalloproteinases (MMPs), regulated by NF-κB and MAPK pathways, play a role in ECM remodeling, where an imbalance between MMPs and their inhibitors (TIMPs) can lead to excessive matrix degradation, impeding tissue repair. Furthermore, Wnt/β-catenin signaling is activated in response to moderate mechanical loading, promoting chondrocyte proliferation and enhancing cartilage repair by upregulating type II collagen and aggrecan synthesis. However, dysregulation of Wnt signaling under excessive mechanical stress can lead to chondrocyte hypertrophy and cartilage degradation, contributing to osteoarthritis development. This review also explores emerging therapeutic strategies that leverage the molecular biology of knee joint repair, including biologics like platelet-rich plasma (PRP) and MSC-derived exosomes, which deliver bioactive molecules that activate critical regenerative pathways such as TGF-β/Smad and PI3K/Akt. Gene therapies targeting Wnt signaling or YAP/TAZ offer potential for enhancing tissue regeneration by modulating mechanotransduction and repair processes at the molecular level. In conclusion, the molecular biology of cellular responses to mechanical loading is central to knee joint repair following injuries. By understanding these processes and targeting specific molecular pathways, clinicians can optimize rehabilitation protocols and develop novel therapeutic approaches that enhance tissue regeneration, prevent chronic degeneration, and restore joint function. This comprehensive synthesis highlights the importance of integrating molecular insights into treatment strategies for ACL, meniscal, and cartilage injuries to improve patient outcomes.

Structural biology has a strong interest in ion channels, a diverse group of membrane proteins. This group has long remained difficult to study, but much progress has been made in recent decades with improvements in biochemical methods and computational procedures. Voltage-gated ion channels undergo conformational changes upon functioning, and multiple models of activation mechanisms were proposed based on experimental data. This review focuses on the structural studies of the functioning of voltage-gated ion channels, which are accompanied by conformational changes in proteins, and the methodological advances that allow their observation. Modern experimental methods that allow obtaining ion channel proteins in specific functional states are discussed, including cryoelectron microscopy and cryoelectron tomography. Finally, new algorithms for studying the conformational mobility of proteins have been developed, which help to better understand the mechanisms of ion channel domain movements.

In the face of increasing environmental protection requirements, modeling emissions from older vehicles presents a significant challenge. This paper introduces an innovative methodology for developing emission models for older vehicles by employing advanced AI and machine learning techniques. The study utilized algorithms, including gradient boosting, to analyze data from road tests and the OBDII diagnostic interface, allowing the creation of precise models for CO₂, CO, THC and NOx emissions. A key achievement is the implementation of input data clustering, which significantly enhances the accuracy of emission forecasts. Model validation demonstrated high precision, with notable R² coefficients and mean squared errors. The developed models serve as a crucial tool for analyzing and managing emissions in the context of an aging vehicle fleet, providing new opportunities to shape transportation policy and strategies for pollution reduction.

The textile industry plays a vital role in the global economy and faces increasing pressures related to sustainability and efficiency. Given the industry's significant environmental impact and the need for improved operational strategies, our review addresses the critical intersection of decision-making methodologies and sustainable practices. Specifically, This review aims to explore the applications of Multi-Criteria Decision-Making (MCDM) techniques within the textile supply chain to enhance operational performance and decision-making processes. Utilizing a systematic literature review method, we analyzed articles from Scopus, Web of Science, and Google Scholar, focusing on those that address MCDM applications in the textile supply chain. The findings reveal a strong emphasis on supplier selection and evaluation as determinants of competitive advantage, with significant trends toward integrating fuzzy set theory and advanced MCDM methodologies to address uncertainties. Additionally, Sustainability emerges as a core theme, emphasizing the necessity for firms to incorporate green practices into decision frameworks. The insights suggest that by adopting innovative analytical techniques, organizations can improve supplier relationships and operational efficiency.

Organisations need dynamic capabilities in the ongoing digital transformation to reconfigure knowledge and learning. There is a need to define new concepts and explain mechanisms of relevant factors to build dynamic capabilities. Especially organisations acting in healthcare are caught in a dilemmatic situation. New, digital processes and business models are promising benefits for cost-containment measures and improved patient-centric care, offering digital services. However, investments are needed to benefit. The important question is: how can individual actors in healthcare be motivated to engage in this transformational process to build and reconfigure relevant competences and establish new learning routines? Founded on the essence of existing literature, we assume sustained learning as a relevant dynamic capability to seize and sense competences and reconfigure human capital. This paper answers the call for deeper investigations into the mechanisms in new digitally transformed environments and sectors with less focus on performance and competitive advantages, like public administration or the healthcare sector. Based on previous research, validated in qualitative interviews and quantitative testing, we define the new construct of sustained learning with its subdimensions. By providing measures, we build the ground for further quantitative research.

Embryo’s Implantation is a question that we are not in the position to answer in full details. We know that it depends on embryo’s quality and uterine receptivity. It is possible to access uterine cavity before in vitro fertilisation by a variety of tools, however hysteroscopy is the gold standard in evaluation of uterine cavity and potential pathology. The frequencies of unrecognised uterine pathology revealed by hysteroscopy are 18-50% and 40-43% in patients undergoing in vitro fertilisation or after recurrent implantation failure respectively. Data is inconclusive regarding the role of hysteroscopy on pregnancy outcome after in vitro fertilisation. This review aims to evaluate the validity of office hysteroscopy in subfertile population before or after IVF treatment

Infection-related cardiovascular diseases (CVDs) represent a significant health challenge, necessitating novel therapeutic strategies targeting key receptors involved in inflammation and infection. Antimicrobial peptides (AMPs) offer a promising approach, potentially disrupting pathogenic processes. This study aimed to investigate the efficacy of AMPs as therapeutic agents by examining their interactions with critical CVD-related receptors. A comprehensive computational approach was utilized to assess the interactions between AMPs and receptors associated with CVDs. Molecular docking studies were conducted to evaluate AMP binding to target receptors: ACE2, CRP, MMP9, NLRP3, and TLR4. The top-performing AMPs were further analyzed through 100 ns molecular dynamics (MD) simulations, and their binding affinities were quantified using MM/PBSA calculations. The analysis revealed that Tachystatin, Pleurocidin, and Subtilisin A exhibit strong binding affinities to key CVD-related receptors, including ACE2, CRP, and MMP9. These AMPs demonstrated the potential for disrupting receptor-peptide interactions critical to infection and inflammation. MD simulations confirmed the stability of AMP-receptor complexes, with MM/PBSA calculations showing significant binding energies. Future directions include conducting in vitro and in vivo studies to validate the therapeutic efficacy and safety of these AMPs in clinical settings.

Wide bandgap (WBG) power semiconductor devices are increasingly replacing silicon IGBTs in high-power and high-voltage power electronics applications. However, there is a significant gap in the literature regarding efficient testing methodologies for high-power and high-voltage converters under constrained laboratory resources. This paper addresses this gap by presenting comprehensive, hardware-focused testing methodologies for high-power and high-voltage WBG power semiconductor based converters, preceding the control evaluation phase. The proposed methods enable thorough evaluation and evaluation of converter hardware, including device switching characteristics, driving circuit functionality, thermal management performance, insulation integrity, and sustained operation at full power. We utilize the double pulse test (DPT) to characterize switching performance in a two-level phase leg configuration, extract circuit parasitics, and validate magnetic components. The DPT is further applied to optimize gate driving circuits, validate overcurrent protection mechanisms, and measure device on-resistance. Additionally, a multicycle test is introduced to rapidly assess steady-state converter performance and estimate efficiency. Recognizing the critical role of thermal management in high-power converters, our methodologies extend to the experimental extraction of key thermal parameters—such as junction-to-ambient thermal resistance and thermal capacitance—via a heat loss injection method. A correlation method between temperature sensor measurements and junction temperature is presented to enhance the accuracy of device temperature monitoring during tests. To ensure reliability and safety, dielectric withstand tests and partial discharge measurements are conducted at both component and converter levels under conventional 60 Hz sinusoidal and high-frequency PWM waveforms. Finally, we highlight the importance of testing converters under full voltage, current, and thermal conditions through power circulating tests with minimal power consumption, applicable to both non-isolated and isolated high-power converters. Practical examples are provided to demonstrate the effectiveness and applicability of these hardware testing methodologies.

Background: Due to the importance of Avicenna in the history of philosophy and his special views and ideas, the views of this philosopher have always been examined by scholars and researchers. This is why many researchers have been published in connection with Avicenna's philosophy. Thereby, the comprehensive study in relation to the review of previous studies about philosophy of Avicenna is important. Methods: The Web of Science Core Collection has been used to review documents, and the data has been analyzed in VOSviewer. Results: Based on the findings in the WoS and also the maps made by VOSviewer, Types of documents, languages, documents per year, countries, journals, authors, citations, and keywords were analyzed, and based on these data and analysis the limitations of studies are realized.

Migraine is a neurological disorder characterized by severe disabling headaches with a substantial global burden and elevated morbidity rates. Extensive research has established a clear association between migraine and sex/gender, with a notably higher incidence reported in females, reaching up to 18%, which is three times greater compared to males. Additionally, women commonly experience more intense pain and greater frequency of migraine symptoms, both with and without aura, highlighting the differential impact of sex/gender on migraine presentation. This review comprehensively examines the pathophysiology of migraine, with a particular focus on the effects of sex hormones in migraine pathophysiology and the central nervous system. Furthermore, we explore various treatment modalities tailored to gender differences, including pharmacological interventions and emerging therapeutic approaches. Furthermore, we explored alternative treatment strategies such as nutraceuticals and behavioural techniques, including mindfulness and cognitive behavioural therapy. This review aims to provide a comprehensive overview of the multifaceted nature of migraine and the diverse therapeutic approaches available for their management.

In light of the accelerated pace of economic growth and urbanisation, the transformation of green buildings has emerged as a prominent area of re-search. A considerable number of existing buildings have been constructed and are still in use. However, the energy consumption and environmental impact throughout the entire life cycle of these buildings are not adequately considered in the renovation design. This results in high energy consumption and poor indoor comfort. In this work, we include improving the thermal insulation of buildings, such as thickening the insulation of external walls and replacing energy-efficient windows to reduce energy losses caused by temperature differences between in-door and outdoor buildings; Adopt energy-efficient HVAC systems to reduce en-ergy consumption and improve indoor air quality by upgrading equipment effi-ciency, optimizing duct design, and intelligent control systems; At the same time, we will introduce renewable energy sources such as solar energy, and we will not only install solar photovoltaic panels to generate electricity, but also use solar thermal collector systems to provide hot water and heating, so as to achieve di-versified and sustainable use of energy. Combined, these measures can effec-tively reduce the overall energy consumption of the building, reduce carbon emissions, and improve the comfort and health of the indoor environment. During the experimental analysis, the energy consumption and indoor comfort before and after the renovation were evaluated, and the results showed that the energy consumption was significantly reduced and living comfort was improved.

Artificial neural networks are highly efficient tools for numerous kinds of tasks, which include forecasting, regression, and recognizing patterns in classification and pattern recognition. An artificial neural network is a model for processing information using essential components called artificial neurons that are inspired by the human brain. Two significant aspects of delayed neural networks dynamic activity are their stability and the synchronization phenomenon. This work presents a bidirectional associative memory (BAM) incommensurate fractional-order delay neural network model. The incommensurate fractional orders are calculated within the stability region through the corresponding eigenvalues and their points of equilibrium. The involved neuron states are synchronized with each other for the calculated incommensurate stable fractional orders. The reduction of the time delay will give more relaxation time for the state variable $w_4(t)$ to be stable as compared to the state variable $w_3(t)$ due to the induction of extra activation functions. The theoretical findings of this research have significance for providing guidance and controlling the dynamic behavior of artificial neural networks.

Nonlinear single unit activity (SUA) characteristics are the useful measures to reveal the information processing and transfer features associated with Parkinson’s disease (PD) in the basal ganglia. Most of the state-of-the-art approaches to compute such parameters in continuous and discrete forms are strongly dependent on SUA recording length, noise level and input parameters. Due to the specificity of SUA data collection (mainly short recordings with relatively low signal-to-noise ratio) new techniques to evaluate neuronal nonlinear properties are needed. We have developed an encoding technique based on a mean interspike interval (ISI) value to calculate spike train discrete nonlinear features. The approach to compute mutual information (MI) of isolated neurons with its unstructured activity was also proposed. The proposed technique of SUA nonlinear features evaluation slightly depends on spike train length, has low correlations with other SUA characteristics (firing rate, coefficient of ISI variance and asymmetry index). The derived entropy measure in the subthalamic nucleus has significant positive correlation with PD severity. The proposed approach provides nonlinear features that are slightly dependent on investigated sample size and independent on input parameters. Also, the developed mean ISI based measures reflect the more complex nature of oscillatory activity in the basal ganglia, than it was thought previously. Moreover, MI, unlike entropy, takes into account the position of the spike train elements, which allows us to investigate the amount of information retained after the occurrence of temporary failures. The developed approach may be useful in describing nonlinear features of basal ganglia activity contributing to PD pathophysiology probably associated with impaired information transfer in movement disorders.

Sustainability in construction has emerged as a critical focus in response to growing environmental challenges. This article review explores the intersection of LEED (Leadership in Energy and Environmental Design) certification and design-build construction, highlighting how these two frameworks enhance sustainability in the built environment. By examining the findings of a selected article, the review emphasizes the advantages of LEED certification in promoting energy efficiency, reducing waste, and improving overall environmental performance. The design-build method, with its integrated and collaborative approach, complements LEED’s objectives by ensuring that sustainability is prioritized from the initial planning stages. This review also critically analyzes the strengths and limitations of the article, including its coverage of cost-related challenges and the applicability of LEED in diverse project scales. Ultimately, the review underscores the significant role that LEED certification plays in advancing sustainable construction practices, particularly within the design-build model.

Cutaneous metastatic melanoma (CMM) is the most aggressive form of skin cancer with a poor prognosis. Drugs-induced secondary tumorigenesis and the emergency of drug resistance worsen the already worrying scenario, thus rendering urgent the development of new treatments, not dealing with mutable cellular processes. Triphenyl phosphonium salts (TPPSs), in addiction to act as cytoplasmic membrane disruptors, are reported to be mitochondria-targeting compounds, exerting anticancer effects mainly by damaging their membranes and causing depolarization, impairing mitochondria functions and their DNA, triggering oxidative stress (OS), and priming primarily apoptotic cell death. TPP-based bola-amphiphiles are capable to self-form nanoparticles (NPs) with enhanced biological properties, as commonly observed for nanomaterials. Already employed in several other biomedical applications, only recently the per se selective potent antibacterial effects of a TPP bola-amphiphile has been demonstrated on 50 multidrug resistant (MDR) clinical superbugs, as well as its exceptional and selective anticancer properties, on sensitive and MDR neuroblastoma cells. Here, aiming at finding new molecules possibly developable as new treatments for counteracting CMM, the effects of this TPP-based bola-amphiphile (BPPB) have been investigated against two BRAF mutants CMM cell lines (MeOV and MeTRAV) with excellent results (even IC50 = 49 nM on MeOV after 72 h treatment). Upon these findings and considered the low cytotoxicity of BPPB against different mammalian not tumoral cell lines and red blood cells (RBCs, selectivity indexes up to 299 on MeOV after 72 h treatment), the possible future development of BPPB as topical treatment for CMM lesions was presumed. In this sight, a biodegradable hyaluronic acid (HA)-based hydrogel formulation (HA-BPPB-HG) was prepared without using any potentially toxic crosslinking agents, but simply dispersing suitable amounts of the two ingredients in water and sonicating under gentle heating. HA-BPPB-HA was completely characterized with promising outcomes, such as high swelling capability, high porosity and viscous elastic rheological behavior.

In the paper, we suggest a method for calculating optimal time intervals in the queue analysis. The suggested method processes partitioning of the time interval and utilizes the epsilon-entropy and epsilon-capacity of the partition for finding an optimal partition. Optimality of the partition is specified based on its epsilon-information. The suggested method is illustrated by defining the intervals for histograms of differently distributed samples and demonstrated its effectiveness in comparison with the existing methods.

This article investigates robust optimality and duality for a class of nonsmooth multiobjective programming problems with vanishing constraints under data uncertainty (in short, UNMPVC) via convexificators. Using the properties of convexificators, we introduce generalized standard Abadie constraint qualification (in short, GS-ACQ) for the considered problem UNMPVC. Moreover, we introduce generalized robust version of nonsmooth stationary conditions, namely, weakly stationary point (in short, RW-Stationary), T-stationary point (in short, RT-Stationary), M-stationary point (in short, RM-Stationary) and S-stationary point (in short, RS-Stationary) for UNMPVC. By employing GS-ACQ, we establish that the RS-Stationary is the necessary first-order optimality condition for a local Pareto solution of UNMPVC. Moreover, under generalized convexity assumptions, we establish sufficient optimality criteria for UNMPVC. Furthermore, we formulate the Wolfe-type (in short, WRD) and Mond-Weir-type (in short, MWRD) robust dual models corresponding to the primal problem UNMPVC.

The emerging wireless energy transfer technology enables sensor nodes to maintain perpetual operation. However, maximizing the network performance while preserving short charging delay is a great challenge. In this work, a Wireless Mobile Charger (WMC) and a Directional Charger (DC) are deployed to transmit wireless energy to the sensor node to improve the network's throughput. To the best of our knowledge, this is the first work to optimize the data sensing rate and charging delay by joint scheduling of MC and DC. We prove we can transmit maximum energy to each sensor node to obtain our optimization objective. In our proposed work, a DC selects a total horizon of equipped with DCs, which selects the horizon of each specific area with based on its antenna orientation. DC's orientation is scheduled for each time slot. Furthermore, multiple MCs are used to transmit energy for sensor nodes which cannot be covered by DCs. We divided the Rechargeable Wireless Sensor Network into several zones via the Voronoi diagram. We deployed a static DC and one MC charging location in each zone to provide wireless charging service jointly. We obtain the optimal charging location of MCs in each zone by solving Mix Integral Programming for energy transmission. The optimization objective of our proposed research is to sense maximum data from each sensor node with the help of maximum energy. The lifetime of each sensor network can increase, and the end delay can be maximized with joint energy transmission. Extensive simulation results demonstrate that our RWSNs are designed significantly to improve network lifetime over the baseline method.

This is a methodological contribution to reference mode development in system dynamics model conceptualization. Existing behavior mode taxonomies-developed for various modeling phases-provide no comprehensive method for mode classification based on an exhaustive set of mutually exclusive modes, and derivation of questions the simulation model should answer. Novice modelers need such guidance. The article proposes a conceptual framework for systemic behavior with a hierarchical taxonomy of elementary, composite, and overlaid modes. A structured method identifies the intervals of each respective mode, orders them into episodes and then condenses the variables’ episodes to systemic episodes. Each transition then gives rise to a fundamental question for the model under development. Three classical cases illustrate the application and contrast the proposed taxonomy to others in the extant literature. The article then discusses some validation criteria referring to reference modes and their link to the dynamic hypothesis, current limitations, and questions for further research.

In this paper, we reviewed 42 studies on applied Life Cycle Analysis (LCA) in dairy products published since 2015. Such a systematic review of the literature contributes to addressing the gap regarding the usefulness of the LCA methodology and the need for additional research due to limited studies, data, variables, and the magnitude of environmental impact. We analyzed various environmental impacts generated in the environment, compared methods and results, and highlighted emerging issues affecting society, the economy, and the environment, warranting further investigation. Additionally, we statistically analyzed the effects that the choice of functional unit and allocation rule could have on the results. LCA is a key tool for assessing the environmental sustainability of the agri-food sector. This review aims to summarize case study research on LCA in dairy processing, disseminating potential environmental impacts and providing specific examples of research in dairy processing demonstrating how the representative end product is associated with environmental impacts on air, water, and land.

Due to its flexibility, cloud computing has become essential in modern operational schemes. However, the effective management of cloud resources to ensure cost-effectiveness and maintain high performance presents significant challenges. The pay-as-you-go pricing model, while convenient, can lead to escalated expenses and hinder long-term planning. Consequently, FinOps advocates proactive management strategies, with resource usage prediction emerging as a crucial optimization category. In this research, we introduce the multi-time series forecasting system (MSFS), a novel approach for data-driven resource optimization alongside the hybrid ensemble anomaly detection algorithm (HEADA). Our method prioritizes the concept-centric approach, focusing on factors such as prediction uncertainty, interpretability and domain-specific measures. Furthermore, we introduce the similarity-based time-series grouping (STG) method as a core component of MSFS for optimizing multi-time series forecasting, ensuring its scalability with the rapid growth of the cloud environment. The experiments performed demonstrate that our group-specific forecasting model (GSFM) approach enabled MSFS to achieve a significant cost

It is a fact, that the varying definitions and perspectives on thinking among scientists, emphasizing the influence of theoretical foundations and practical experiences on individual mental processes, would equally highligh the importance of mathematics in developing thinking skills by fostering connections between ideas, organizing information, and encouraging students to record problem-solving strategies. The professional development of mathematics teachers aims to enhance students' thinking abilities by focusing on skills such as problem-solving, abstraction, generalization, and divergent thinking. The use of puzzles and games in education to enhance students' mathematical thinking and problem-solving skills, as a significant indicator on how puzzles and games can engage students in critical thinking, logical reasoning, and creative problem-solving, leading to a deeper understanding of mathematical concepts. By incorporating educational games into teaching, educators can create a fun and interactive learning environment that promotes cognitive, emotional, and psychomotor development in students. On a different note, the potential negative behaviors that can arise from games, such as fraud and deception, when the focus shifts away from educational goals, could be prevented to ensure that games are not solely recreational, do not overly emphasize winning or losing, align with social values, and are understood by students as purposeful educational activities. Additionally, fostering self-efficacy beliefs among students can enhance their persistence and success in achieving goals, as demonstrated in studies using game-based learning environments to improve mathematical skills and motivation. The current exposition showcases the significance of employing puzzles to revolutionize both theory and practice of teaching mathematics. Most potentially, some emerging open problems are provided. The paper ends with some concluding remarks combined with futuristic research pathways.

We introduce derangetropy, a novel functional measure designed to characterize the dynamics of information within probability distributions. Unlike scalar measures such as Shannon entropy, derangetropy offers a functional representation that captures the dispersion of information across the entire support of a distribution. By incorporating self-referential and periodic properties, it provides deeper insights into information dynamics governed by differential equations and equilibrium states. Through combinatorial justifications and empirical analysis, we demonstrate the utility of derangetropy in depicting distribution behavior and evolution, providing a new tool for analyzing complex and hierarchical systems in information theory.

In the recent years, with the advent of Artificial Intelligence (AI) traditional methods have seen a significant transformation in the agriculture sector, especially in soil management. Soil management involves practices that maintains and improves the physical, chemical as well as the biological properties of the soil. Soil health management is essential for both the environmental conservation and sustainable agriculture production, ensuring the soil productivity and functional aspects associated with the ecosystem. Soil health management is one of the most important aspects of agriculture and food production, hence preserving and enhancing the soil health is an essential factor for supporting agriculture. Integration of Artificial Intelligence (AI) technologies with soil health management offers the potential to enhance agricultural sustainability, productivity, adapt to the climatic changes and resource constraints. The study of AI tools that can help improve soil health management by providing more accurate and efficient monitoring, analysis and decision-making capabilities. This paper studies the potential AI technologies including machine learning, robotics, and remote sensing in enhancing soil health, raising crop yields, and lowering environmental concerns by examining previous research and case studies.

Dry Fish is a rich source of proteins and nutrients and can be eaten in many forms. Oman is one of the important fish producers in the world and having high demand in neighboring countries for Oman’s fish. Fishery sector is considered as one of the important economic development sector in sultanate of Oman. In the fishery sector, use of technology is not up to the mark because of less awareness of technology application among Omani fishermen. Also, there is a demand for a greater number of cold storages in different regions to store fresh fishes which is not materialized yet. Similarly, there is a demand of perfect and cheap technology in Oman to dry fishes to improve the profit to the fishermen. Solar energy is abundantly available in Oman and there are high possibilities in Oman to use solar energy in domestic and industrial applications. Since the sunlight is available throughout the year, it is possible to convert in to thermal energy or electrical energy. Electricity can be produced from photovoltaic principle (PV) or indirectly with concentrated solar power. Similarly, we can use solar concentrators for many thermal applications. The solar dryer is a device which is used to dry fruits, vegetables, leaves, clothes etc. If any of the items are dried with the help of solar energy, then we can save lot of non-renewable source of energy and can help to improve economy of the country. The sun can, at least seasonally at Oman’s latitudes, provide a substantial part of the energy needed for various applications. In this work, we used solar dryer to make dry fish with high quality. Use of parabolic type concentrator to dry the fish is an effective solution which is an innovative idea to the fishermen. The temperature variation in dryer is directly proportional to the intensity of solar. The tracking mechanism is a combination of electronic and mechanical design which tracks the sun automatically. In this work, a parabolic concentrator with automatic tracking mechanism was designed and the performance analysis have been done. In the design, copper tubes are used for heat transfer and then the hot fluid is circulated in the box which is used to dry the fishes. As per the experiment, fish drying efficiency obtained from solar dryer is 77.9% and it took 3 days to dry king fish of 20kg. There are many advantages in parabolic type solar concentrators relate to the quality of dryness in the fishes and time taken to dry the fishes which are elaborately discussed in this paper. This solar dryer technology will improve green environment and also will save non-renewable sources of sultanate of Oman for longer period of time.

Control of oxidation/antioxidation homeostasis is important for cellular protective functions, and disruption of the antioxidation balance by exogenous and endogenous ligands can lead to profound pathological consequences of cancerous commitment within cells. Although cancers are sensitive to antioxidation drugs, these drugs are sometimes associated with problems including tumor resistance or dose-limiting toxicity in host animals and patients. These problems are often caused by the imbalance between the levels of oxidative stress induced reactive oxygen species (ROS) and the redox efficacy of antioxidants. Increased ROS levels, because of abnormal function, including metabolic abnormality and signaling aberrations, can promote tumorigenesis and the progression of malignancy, which are generated by genome mutations and activation of pro-oncogene signaling. This hypothesis is supported by various experiments to show that the balance of oxidative stress and redox control is important for cancer therapy. Although many antioxidant drugs exhibit therapeutic potential, there is a heterogeneity of antioxidation functions, including cell growth, cell survival, invasion abilities, and tumor formation, as well as the expression of marker genes including tumor suppressor proteins, cell cycle regulators, nuclear factor erythroid 2-related factor 2, and Jun dimerization protein 2; and their effectiveness in cancer remains unproven. Here, we summarize the rationale for the use of antioxidative drugs in preclinical and clinical antioxidant therapy of cancer, and recent advances in this area using cancer cells and their organoids, including the targeting of ROS homeostasis.

In this study, we developed a lightweight shoe sensor system equipped with four high-capacity, compact triaxial force sensors and an inertial measurement unit. Remarkably, this system enabled measurements of localized three-directional ground reaction forces (GRFs) at each sensor position (heel, first and fifth metatarsal heads, and toe) and estimations of stride length and toe clearance during walking. Compared to conventional optical motion analysis systems, the developed sensor system provided relatively accurate results for stride length and minimum toe clearance. To test the performance of the system, 15 older and eight young adults were instructed to walk along a straight-line while wearing the system. The results revealed that compared to the young adults, older adults exhibited lower localized GRF contributions from the heel and greater localized GRF contribution from the toe and fifth metatarsal locations. Furthermore, the older adults exhibited greater variability in their stride length and smaller toe clearance with greater variability compared to the young adults. These results underscore the effectiveness of the proposed gait analysis system in distinguishing the gait characteristics of young and older adults, potentially replacing traditional motion capture systems and force plates in gait analysis.

This work presents a novel compact CMOS potentiostat designed circuit for electrochemical cell. The proposed topology functions as a circuit interface, controlling the polarization of voltage signals at the sensor electrodes and facilitating current measurement during the oxidation-reduction process of a analyzed solution. The potentiostat, designed for CMOS technology, comprises a two-stage amplifier, two current mirror blocks coupled to this amplifier, and a CMOS push-pull output stage. It employs the electrochemical method of cyclic voltammetry, operating within voltage range of ±0.8 V and scan rates of 10mV/s, 25mV/s, 100mV/s and 250 mV/s. The circuit is capable of reading currents ranging from 10 µA to 500 µA. Experimental results were obtained using a potassium ferrocyanide (K3(FeCN)6) redox solution with concentrations of 10, 15 and 20 mmol/L, and their corresponding voltammograms were evaluated. The experimental results from a discrete circuit demonstrate that the proposed potentiostat topology produces outcomes consistent with those of classical topologies presented in the literature and industrial equipment.

Multiple lines of research have led to the hypothesis that antimicrobial peptides (AMPs) are an important component of the innate immune response, playing a vital role in the defense against a wide range of infectious diseases. In this review we explore the occurrence and availability of antimicrobial proteins and peptides across various species, highlighting their natural abundance and evolutionary significance. The design of AMPs has been driven by the identification of key structural and functional features, which are essential for optimizing their antimicrobial activity and reducing toxicity to host cells. We discuss various approaches, including rational design, high-throughput screening, and computational modeling, that have been employed to develop novel AMPs with enhanced efficacy. A particular focus is given to the identification and characterization of peptide fragments derived from naturally occurring host defense proteins, which offer a promising avenue for the discovery of new AMPs. The incorporation of artificial intelligence (AI) and machine learning (ML) tools into AMP research has further accelerated the identification, optimization, and application of these peptides. This review also discusses the current status and therapeutic potential of AMPs, emphasizing their role in addressing the growing issue of antibiotic resistance. The conclusion highlights the importance of continued research and innovation in AMP development to fully harness their potential as next-generation antimicrobial agents.

HIGHLIGHTS This paper is presenting an experiment based on Ehrenfest's paradox where an effect of special relativity was expected but not observed. The validity of special relativity in our macro world will be questioned and an alternative will be offered. Indeed, special relativity has been successful in describing the behaviour of particles (Rossi & Hall, 1941), but since particles obey quantum rules, there is no observation of special relativity in our everyday world. On the contrary, there are at least two paradoxes based on special relativity: the twin paradox (Langevin, 1911) and Ehrenfest's paradox (1909). ABSTRACT After presenting the history of special relativity, the non-simultaneity of special relativity is questioned in our macro world. In addition, some issues between light clocks and the application of Lorentz transformation are presented. All this indicates that special relativity appears to be correct only for particles and would be invalid in our macro world. A new hypothesis is presented based on an adaptation of special relativity; this new hypothesis solves the anomalies and could be a solution to the twin paradox. This new hypothesis has a prediction in disagreement with special relativity. To test that prediction, a new experiment has been carried out and the preliminary results support the new hypothesis. Previously, a lack of special relativistic effects has been observed in the universe (Davis et al., 2004); that second observation is also explained with the new hypothesis.

Purpose of review: In this review, we discuss the importance of digital health equity and how social determinants of health (and intersectionality with race, ethnicity, and gender) affect cardiovascular health-related outcomes in digital health trials. We propose strategies to improve digital health equity as we move to a digitally-connected world for healthcare applications and beyond.Recent findings: Digital health has immense promise to improve population health by reaching individuals in their homes, at their preferred times. However, initial data demonstrate decreased patient engagement and worse cardiovascular outcomes for racial and ethnic minorities, leading to unequal uptake of digital health technologies. In addition, while women generally have higher uptake of technology, they are less likely to be referred by clinicians for digital health interventions. We highlight several exemplar trials and analyze their methodology for replication in future digital health research.Summary: The promise of digital health equity has not been reached due to exclusionary practices. Specific focus must be placed on societal/governmental policies that enable digital inclusion, particularly of racial and ethnic minority populations and women, to ensure that the expansion of digital health technologies does not exacerbate existing health disparities.

Bangladesh faces significant wheat grain deficiency compared to its demand due to the lengthy process (10-12 years) required to release a variety through a conventional breeding approach. Traditional breeding methods involve several years of various types of crosses between male and female parents and/or progenies, along with recurrent selection-crossing to obtain a homozygous line (F₁ to F₆ generations) with desired traits within almost 10 years. The double haploid (DH) method is also a time-saving, easier, and more reliable technique to achieve the desired traits in homozygous lines within 2-3 years. DH lines were produced by crossing two F₁ hybrids of spring wheat with maize. 0.1% solution of colchicine was applied to produce DH of F₂ progeny of wheat in the study. 80.8% (340) of the 421 pollinated florets from the two F₁ wheat hybrids were produced as green parthenocarpic caryopses (GPCs) (F₂). 35 of the 70 rescued embryos (or 20.6% of the GPCs) germinated. The germinated embryos regenerated 10 haploid green plants (14.3% of total embryos). After being applied colchicine, 8 of the regenerated haploid (H₁) plants made it. Out of the 8 plants that made it through, only one developed homozygous double haploid seed (DH₁ seed). These seeds were multiplied to produce DH₂, used in the preliminary yield in the next year. The results demonstrated the potential of this method to produce a homozygous line within a short period (2-3 years) by doubling the haploid line generated through pollination of spring bread wheat F₁ with maize.

During the COVID-19 pandemic, wastewater surveillance was used to monitor community transmission of SARS-CoV-2. As new genetic variants emerged, the need for timely identification of these variants in wastewater became an important focus. In response to increased reports of Omicron transmission across the United States, the Oklahoma Wastewater Surveillance team utilized allele-specific RT-qPCR assays to detect and differentiate variants, such as Omicron, from other variants found in wastewater in Oklahoma. The PCR assays showed presence of the Omicron variant in Oklahoma on average two weeks before official reports, which was confirmed through genomic sequencing of selected wastewater samples. Through continued surveillance from November 2021 to January 2022, we also demonstrated the transition from prevalence of the Delta variant to prevalence of the Omicron variant in local communities. We further assessed how this transition correlated with certain demographic factors characterizing each community. Our results highlight RT-qPCR assays as a rapid, simple and cost-effective method for monitoring community spread of SARS-CoV-2 genetic variants in wastewater. Additionally, they demonstrate that specific demographic factors such as ethnic composition and household income can correlate with the timing of SARS-CoV-2 variant introduction and spread.

Aflatoxins (AF), secondary metabolites produced by fungi, pose significant health risks, especially to children and adults. In developing countries like Nepal, the tropical climate promotes fungal growth, leading to high levels of AF in animal feed and milk. In this study, we investigated the incidence of aflatoxin M1 (AFM1) contamination in 84 milk samples collected from the Kathmandu district using the competitive enzyme-linked immunosorbent assay (c-ELISA) technique. We also interviewed farmers to gather information on feeding and storage practices. . All the collected milk samples were contaminated with AFM1, with 97.6% of the samples exceeding the European Union (EU) maximum permissible limit of 50 ppt. The majority (98.5%) of the farms included paddy straw, and all farms (100%) included concentrate in their feed regimen. Only half (52%) of the farms had proper storage facilities. Straw was mostly stored in sacks outdoors or left open in a shed, while concentrates were stored in a closed room or shed. The study reports very high contamination levels of AFM1 in the milk samples, presenting a serious public health issue, and recommends comprehensive surveillance and further investigation across the country, especially given the limited research and literature available.

Winter rapeseed (Brassica rapa) has good chilling and freezing tolerance. INDUCER OF CBF EXPRESSION1 (ICE) plays a crucial role in cold signaling in plant; however, its role in B. rapa remains unclear. In this study, we identified 41 ICE1 homologous genes from 6 widely cultivated Brassica species. These genes exhibited high conservation, with evolutionary complexity between diploid and allotetraploid species. Cold stress induced ICE1 homolog expression, with differences between strong and weak cold-tolerant varieties. Two novel ICE1 paralogs, BrICE1 and BrICE2 were cloned from B. rapa Longyou 6. Subcellular localization assays showed that they localized to the nucleus, and low temperature did not affect their nuclear localization. Overexpression of BrICE1 and BrICE2 increased cold tolerance in transgenic Arabidopsis, and enhanced reactive oxygen species (ROS) scavenging ability. Furthermore, our data demonstrate that overexpression of BrICE1 and BrICE2 inhibited root growth in Arabidopsis, and low temperatures could induce the degradation of BrICE1 and BrICE2 via the 26S-proteasome pathway. In summary, ICE1 ho-mologous genes exhibit complex evolutionary relationships in Brassica species, and are involved in the CBF pathway, and ROS scavenging mechanism in response to cold stress; these regulating mechanisms might be also responsible for balancing the development and cold defense of B. rapa.

The small dimensions of microfluidic channels allow for fast diffusive or passive mixing, which is beneficial for time-sensitive applications such as chemical reactions, biological assays, and the transport of to-be-detected species to sensors. In microfluidics, the need for fast mixing within milliseconds arises primarily because these devices are often used in fields where rapid and efficient mixing significantly impacts the performance and outcome of the processes. Active mixing with acoustics in microfluidic devices involves using acoustic waves to enhance the mixing of fluids within microchannels. Using sharp corners and wall patterns in acoustofluidic devices significantly enhances mixing by acoustic streaming around these features. The streaming patterns around sharp edges are particularly effective for mixing because they can produce strong lateral flows that rapidly homogenize liquids. This work presents extensive characterizations of the effect of sharp-edged structures on acoustic mixing in bulk acoustic wave (BAW) mode in a silicon microdevice. The effect of side wall patterns in different angles and shapes, their position, the type of piezoelectric transducer, and its amplitude and frequency have been studied. Following the patterning of the channel walls, a mixing time of 25 times faster was reached, compared to channels with smooth sidewalls exhibiting conventional BAW behavior. The average locally determined acoustic streaming velocity inside the channel becomes 14 times faster if sharp corners of 10° are added to the wall.

Aim: This study aims to analyze the structure and impact of research collaborations in colonoscopy from 2000 to 2023 by examining co-authorship networks. The goal is to understand the evolution of these networks, identify key contributors, and assess how collaborative relationships influence the field. Method: I conducted a comprehensive network analysis of co-authorship patterns using data from the Web of Science (WoS) Core Collection database. The analysis included 41,213 articles related to colonoscopy published between 2000 and 2023. Using Python (Version 3.10.5) and PyCharm (Software Version 2022.1.3), we evaluated the networks through macro-level indicators (network density, clustering coefficient, number of components, average distance) and micro-level indicators (degree centrality, closeness centrality, betweenness centrality).Result: The analysis revealed a network with increasing but still fragmented collaboration over the years. The network density showed low proportions of realized connections relative to potential ones, with a high clustering coefficient indicating tight-knit groups when collaborations occurred. The number of components remained high, reflecting a fragmented structure. Prominent researchers such as Hassan, Cesare (Italy) and Dekker, Evelien (Netherlands) consistently emerged as central figures across different periods, demonstrating significant roles in facilitating connections between various research clusters.Conclusion: The study highlights a growing but fragmented collaborative landscape in colonoscopy research. Key researchers have played central roles in connecting different parts of the network, yet there remains substantial room for further integration. Strengthening collaborations across isolated groups could enhance the cohesiveness and impact of research in this field.

Keywords: Dihydroxybenzenes; Acetic acid; Ethyl acetate; Microelectrode; Voltammetry

In this note, we suggest a one-sample version of the recently proposed two-sample test for comparison of the means of multivariate samples. The test checks a hypothesis that the mean of multivariate sample is equal to a certain value with the alternative hypothesis that the mean does not equal to this value. The suggested test is illustrated by analysis of real-world and simulated data.

Poor perinatal mental health can have significant and lasting impacts on a woman’s overall health and the well-being of her children and family. From conception, a baby's behavior, appearance, aversions, and interests can be influenced by the prenatal environment. Thus, the quality of prenatal care is crucial. Factors such as maternal stress, environmental conditions, cravings, mood swings, hormonal changes, and emotional experiences during pregnancy can profoundly affect the baby’s behavior once born. The baby's interaction with the external world begins from conception, not just at birth. For instance, maternal depression can negatively affect both the mental and physical health of the infant. Therefore, fostering a supportive environment for expectant mothers is essential for their health and that of their unborn child. Promoting the mother’s well-being through happiness and comfort is critical.This review paper aims to synthesize current research on maternal-fetal attachment during pregnancy, its evolution, and its postpartum effects on the mother-infant relationship. It will explore how these dynamics change over time, both during pregnancy and after delivery, to provide a comprehensive understanding of the factors influencing attachment and related outcomes. As Alan Soufre, a famous developmental psychologist would state, "Attachment would begin before birth. The mother’s emotional state can shape the child’s development trajectory long before the child is born."

Zinc Oxide nanoparticles functionalized with APTES were obtained to evaluate their CH4 and CO2 adsorption and separation behavior. First, ZnO nanoparticles were obtained by a precipitation method and subsequently coated with (3-aminopropyl)-triethoxysilane (APTES). The nanoparticles sample was characterized by UV-Vis, FT-IR spectroscopy, TGA, XRD, TEM/EDX, XPS and N2 adsorption at 77 K. CH4 and CO2 adsorption experiments were carried out at 298 K in a range between 0-10 bar. It was observed that the amount of gas adsorbed on the surface of the nanostructure is very small in comparison with other materials traditionally used for this purpose but slightly higher than those obtained in naked nanoparticles evaluated in previous studies.

(R)-2-Amino-1-hydroxyethylphosphonic acid 2 was prepared by hydrolytic kinetic resolution of rac-diethyl oxiran-2-ylphosphonate followed by reaction with benzylamine, acid hydrolysis, catalytic hydrogenolysis and anion exchange chromatography. Recrystallization from water-ethanol gave 2, which was characterized by IR, 1H NMR, 13C NMR, 31P NMR, polarimetry, elemental microanalysis, high-resolution mass spectrometry and single-crystal X-ray diffraction. The acid 2 crystallized in the orthorhombic chiral space group P212121 with cell constants a = 6.303(2) Å, b = 7.104(2) Å, c = 11.627(3) Å. The X-ray crystal structure confirmed the (R)-configuration of 2 and revealed that 2 is zwitterionic in the solid state, with extensive intermolecular hydrogen bonding between the hydroxyl, ammonium cation and phosphonate anion groups.

This paper delves into the intricate nature of the different essence interactions that shape our perceived reality, leveraging a blend of existing empirical data and original experiments. Through a multidisciplinary approach encompassing quantum mechanics, general physics, metaphysics, philosophy, and spiritualism, it seeks to elucidate the fundamental interplays governing phenomena such as gravity, mass, electromagnetism, force, motion, and quantum mechanics. This exploration promises a reexamination and unification of these principles, offering novel perspectives on the extraordinary phenomena that underpin our reality. By comprehending and manipulating these interactions, the potential arises to orchestrate reality towards desired ends. This study not only unveils compelling avenues for scientific advancement but also proposes transformative technologies and concepts, including light-speed transportation, remote viewing, communication with the deceased, alchemy, and the realization of what is commonly perceived as magic. These visionary notions not only push the boundaries of current understanding but also provide a captivating glimpse into the future possibilities that may await humanity.

The objective of this research project was to evaluate the effects of the addition of inorganic fillers into PEBA at various loading levels on the processing, mechanical, thermal and physical properties of the polymer. The composites investigated in this study were Pebax® 6333 SA01 MED (PEBA100) with 10 wt.%, 20 wt.% and 30 wt.% Barium Sulphate (PEBA/BaSO4) and Bismuth Oxychloride (PEBA/BiOCl) respectively. Composites were prepared using twin screw extrusion and injection moulding. Post-processing, composite samples were analysed for their mechanical properties (via tensile, impact and flexural analysis), thermal properties (via differential scanning calorimetry), rheological performance (via melt flow index) and physical properties (via density analysis and ash content testing). The results of which reveal how filler type and concentration influence PEBA composites. The results of the study suggest that BiOCl filler enhances the aesthetic properties, increases the stiffness, while maintaining some level of flexibility with minimal adverse effects on the tensile and impact strength. When comparing BiOCl to BaSO4 filled composites, it was clear that depending on the application of the polymer composite, BiOCl may provide more desirable properties. The study highlights the importance of optimising filler concentration and processing conditions to achieve desired composite properties for specific medical applications.

Background - Compared to the da Vinci platform, there is limited experience with the Hugo RAS platform for colorectal surgery in Europe. This difference is especially notable when considering a single complex procedure, such as total colectomy. Aim - To demonstrate the feasibility and safety of using the Hugo RAS for assisted total colectomy. Clinical case- Female patient: eighteen-year-old with Familial Adenomatous Polyposis (FAP). Her IBM was 19. She underwent a total colectomy with ileorectal anastomosis using the Hugo RAS platform. The procedure took 230 minutes and had no complications. The postoperative period was uneventful. She was discharged from the hospital on the third postoperative day. Conclusion - The Hugo RAS platform is one of the emergent minimally invasive robotic platforms that can be used even in total colectomy if the proper patient selection is made. The placement choice of arms and trocars was crucial to obtain a similar operative time of the single laparoscopic approach. The certification of Hugo’s new instruments, such as energy devices and staplers, will make this platform even more competitive.

Hyper-spectral imaging provides the possibility of describing specific characteristics of materials in air, land and water depending on reflections of each material in a specific zone of the electromagnetic spectrum. Hyper-spectral sensors capture images in continuous and narrow spectral bands in the visible, near-infrared, and mid-infrared spectral regions. These sensors look at objects using a large part of the electromagnetic spectrum. Some objects have unique characteristics in certain electromagnetic spectrums. These spectral signatures, known as "spectral signatures," help to identify materials in images. But the main problem with these sensors is that the images they get in bad weather conditions and in the presence of dust or rain or snow are of very poor quality. Therefore, we go to SAR images, which are able to form a high-resolution image even in bad weather conditions. The method proposed in this paper is to obtain the final elements of hyper-spectral images using the decomposition method into a multilayer negative matrix. The reason for using this method is that, unlike the high-spectral images that form the image in a number of high-traffic zones, we can create the image in 8 different frequencies, so the most important thing is to get all the hidden information at those frequencies. And also, we compare between the RDA, SENMAV, OMP, ISMA and ADMM algorithms.

Eco-labelling plays a crucial role in encouraging sustainable consumer behaviour by giving clear information about a product's environmental impact. This study looks at how eco-labelling affects the buying decisions of young consumers in Enugu State, Nigeria. Using a cross-sectional survey approach, 430 undergraduate students from five universities participated in an online questionnaire. The research focused on understanding how aware young consumers are of eco-labels, how these labels influence their buying decisions, and whether they are willing to pay more for eco-labelled products. The data were analysed through descriptive statistics, including average scores and variations. The results showed that young consumers have a moderate to high level of awareness of different eco-labels, with the NAFDAC Green Dot being the most recognised (average score = 4.12, variation = 0.96). Eco-labelling was found to have a significant influence on their purchasing decisions, especially in building trust in the products (average score = 4.31, variation = 0.71) and their willingness to pay a higher price (average score = 4.21, variation = 0.83). Overall, the study shows that eco-labelling has a positive impact on young consumers’ buying choices and could be a valuable tool for promoting more sustainable consumption in Nigeria. The study recommends increasing awareness through educational campaigns, building consumer trust in eco-labelling, and using effective marketing strategies to boost recognition and adoption of eco-labelled products.

This review explores the transformative role of artificial intelligence (AI) in the entire winemaking process, from viticulture to bottling, with a particular focus on enhancing food safety and traceability. It discusses AI’s applications in optimizing grape cultivation, fermentation, bottling, and quality control, while emphasizing its critical role in managing microbiological risks such as mycotoxins. The review aims to show how AI technologies not only refine operational efficiencies but also raise safety standards and ensure traceability from vineyard to consumer. Challenges in AI implementation and future directions for integrating more advanced AI solutions into the winemaking industry will also be discussed, providing a comprehensive overview of AI's potential to revolutionize traditional practices.

Background: Bronchopulmonary dysplasia (BPD) is the most common respiratory disease in pre-term and is still associated with increased mortality and morbidity. The great interest lies in iden-tifying early biomarkers that can predict the development of BPD. Objectives: This pilot study explores the potential of e-nose for early identification of BPD risk in premature infants by analyzing volatile organic compounds (VOCs) in the exhaled breath con-densate (EBC). Materials and Methods: Fourteen mechanically ventilated very preterm infants were included in the study. Clinical parameters and EBC were collected within the first 24 hours of life. The dis-criminative ability of breath-prints between preterms who did and did not develop BPD was in-vestigated by pattern recognition, machine learning algorithm, and standard statistical methods. Results: We found that e-nose probes can significantly predict the outcome of “no-BPD” vs “BPD”. Specifically, a subset of probes (S18, S24, S14, and S6) were found to be significantly predictive, with an AUC of 0.87, 0.89, 0.82, 0.8 and p=0.019, 0.009, 0.043, 0.047, respectively. Conclusion: The E-nose is an easy-to-use, handheld, non-invasive electronic device that quickly samples breath. Our preliminary study has shown that it has the potential for early prediction of BPD in preterms.

Burnout is a factor that affects organizational performance. Researchers agree that the emotional stability provided by an ethical climate and adequate work autonomy often has a buffering effect on chronic stress. However, despite the abundant literature analyzing the relationship between work autonomy and burnout, whether work autonomy acts as a stress-reducing resource or a stress-increasing demand is not sufficiently well established. It is also unknown to what extent work autonomy contributes to explaining the relationship between ethical climate and burnout. Therefore, the main objective of this study is to examine the relationship between an ethical climate of principles and norms on burnout, using the moderating effect of work autonomy. A multivariate moderation analysis was used to address the issue. The sample consists of 448 employees in the Colombian electric sector. The results show that an ethical climate of principles and work autonomy relate positively to burnout. However, when a rule-demanding work environment is related to a high perception of work autonomy, the relationship with burnout syndrome changes from positive to negative. In conclusion, when employees have significant control over their usual tasks, they develop a behavior pattern that includes both the organization's internal standards and the principles that shape individual morale. In this case, employees are able to balance the workload with the high psychological demands of an ethical climate of principles, without it representing a disturbance to their emotional well-being.

As the penetration of renewable energies increases, their acceptance of the power grid system is becoming an important issue. In the case of South Korea, a 22.9kV transformer is frequently utilized to reduce the power loss of the generated renewable energy transmission, so the power quality at the point of common connection (PCC) is inevitably influenced by the nonlinearity of the transformer and the uncertainty of the inductance and resistance of the transmission line. In this paper, we present a point of common connection voltage-modulated direct power control (PCCVM-DPC) system that enhances power quality at the PCC. First, we present the mathematical dynamics of active and reactive power at the PCC side, which contains the step-up transformer’s nonlinearity, the grid voltage harmonics, and the parameter uncertainties. By analyzing the disturbance terms of the PCCVM-DPC system, we present the disturbance observer (DOB) for the PCCVM-DPC system. To assess the efficacy of our approach, we perform comparative studies of the PCCVM-DPC without DOB and PCCVM-DPC with DOB by constructing the simulation environment based on the commercial step-up transformer and ESS inverter datasheet. We have validated that the active and reactive power control performance of the PCCVM-DPC with DOB outperforms the PCCVM-DPC without DOB from the observation that the current total harmonic distortion reduced by more than 40% compared to the PCCVM-DPC without the DOB.

The expression of the oncogene zinc-finger protein 217 (ZNF217) has been reported to play a central role in cancer development, resistance, and recurrence. Therefore, targeting ZNF217 has been proposed as a possible strategy to fight cancer, making necessary to discover novel com-pounds. The present work aims to characterize the chemopreventive properties of cucurbitacin D , a compound with a broad range of anticancer effectsin relation to the ZNF217 expression. Different cucurbitacins were isolated from the Vietnamese plant Elaeocarpus hainanensis. The purified compounds were tested on nucleophosmin-mutated acute myeloid leukemia and other hematology cancer to study their effects on viability, apoptosis, cell cycle and on the expression of ZNF217. Cucurbitacin D reduced the number of acute myeloid leukemia cells by increasing apoptosis and blocking cell cycle progression. It also significantly decreased ZNF217 expression but only in the OCI-AML3 Nucleophosmin-mutated cell line, but not in other hematologic cancers. The reduction in ZNF217 expression contributed significantly to the blocking of cell cycle progression but not to apoptosis as established by the silencing of the same gene. The obtained results suggest Cucurbitacin D as a promising molecule to target the mutated Nu-cleophosmin or its pathway in acute myeloid leukemia cells, although further studies are needed for in depth investigatiion of its specificity.

Medical laboratories are perhaps the largest measurement industry in the world. The metrology terminology is relevant for effective and efficient communication, particularly where metrology activities are carried out by operators with different metrology skills. WASPaLM and SIPMeL have had some opportunities to propose changes to the documents in preparation to CLSI and ISO in order to harmonise the terminology with the Metrology Vocabulary (VIM). Many proposals have been accepted. Here we summarise some particularly critical points for metrological terms. The main terms discussed are: Measuring, measuring range, examination, pre-examination, post-examination, manufacturer, measuring instrument, quantitative, qualitative, semi-quantitative, processing, easurement error, maximum permissible error of measurement, total error of measurement, monitoring, variability, performance, reliability, influence, interference, selectivity, sensitivity, detection limit, reliability, pomparability, compatibility, control material. Despite all efforts to coordinate terminologies, it is inevitable that overlapping and inconsistent terminologies will continue to be used because documents and policies are produced in different contexts. In some ISO and CLSI documents, phenomena of magnetic attraction towards common words (such as “analysis” and derivatives), without any consideration of the true metrological meaning, are noted. The ISO and CLSI working groups show, alongside moments of openness, phenomena of true self-referential conservatism.

Background: Surgery for Chiari I malformation (CMI) is indicated when typical clinic-radiological features (syringomyelia, exertional headaches, sleep apnea syndrome, tetraparesis) are present. Sometimes patients have atypical complaints suggestive of otolaryngological (ENT) involvement, and it is sometimes difficult for the neurosurgeon to determine if these complaints are related to the CMI. Our aim was to describe postural control pattern in children with CMI using Computerized Dynamic Posturography. To our knowledge, this is the first study addressing postural instability in paediatric CMI patients. Methods: twenty-eight children aged 6 to 17 years with both radiologically confirmed CMI and clinical ENT complaints were included. Children were separated into 2 groups: operated and non-operated patients, basing on neurosurgical indication. Epidemiologic and posturographic results (CDP - Equitest®) were compared between both groups, as well as pre and post operatively in the group 2. Results: in Group 2 patients, significant improvement of global SOT was found after intervention. When the three sensorial aspects of postural control calculated by the system were independently assessed, the greatest improvement was in the vestibular ratio. We also observed an altered CoG pattern (“lateral deviation”) in the Group 2 patients, which significantly differed from Group 1. Lateral deviation was significantly reduced postoperatively in Group 2 patients. A correspondence between preoperative MRI and side of lateralisation on posturography was found in 4 children, but this cannot be regarded as significant due to the low number of patients. Conclusions: postural control seems to improve after surgery for CMI in children, mostly due to improvement in vestibular function. There is a correspondence between the side of lateral deviation and the side of greatest tonsillar descent on MRI and perioperatively. Further studies are needed to support these results and to confirm utility of CDP in CMI patients.

The information about the BCoV receptors, co/receptors that might be involved in the BCoV entry to the host cells is inconceivable. In addition to that, the roles of other host cell proteases, such as Furin and TMPRSS2, have not yet been well studied during BCoV replication. The current study’s main objectives are to identify some novel BCoV receptors and host cell proteases that might fine-tune the BCoV replication, tissue tropism, and molecular pathogenesis. We used a combination of some in silico prediction, molecular docking, and gene expression profile tools to predict some new BCoV receptors out of some known other coronavirus receptors and some host cell enzymes that are potentially involved in BCoV replication. To achieve these goals, we applied the in-silico prediction tools to check the potential interactions between eh BCoV/S glycoprotein and some known coronaviruses receptors (ACE2, APN1, NPR1, CECAM-1, AXL, and DPP4). We also established some potential models for the interaction between the BCoV/S and some common host cell proteases proved to play important roles in other coronavirus replication cycle (Furin, TMPRRS2, and Cathepsin-L). To confirm our prediction models, we assessed the gene expression profiles of these potential receptors and proteases in some bovine cell lines infected with BCoV using the next generation sequencing and the qRT-PCR assay. Our results show that the NPR1, AXL1 and the ACE2 have the strongest and firm binding affinities to the BCoV-S protein. Our prediction models and gene expression profiles show the potential bindings of the Furin and TMPRSS2 to the BCoV-S polybasic cleavage site (RRSRR|A). Notably, high expression of the host cell Furin was observed in response to both BCoV/Ent and BCoV/Resp infection, whereas TMPRSS2 expression was upregulated in the case of the BCoV/Ent infection, positioning Furin as a common receptor for different BCoV isolates. Further research is needed to study the roles of these top-ranked receptors and host cell proteases in molecular pathogenesis, and tissue tropism.

The global prevalence of cancer is on the rise, and while targeted therapies, early diagnosis, im-munotherapies, and conventional personalized chemotherapy have significantly upgraded out-comes for cancer patients, there is still a significant likelihood that cancer cannot be fully eradi-cated. Cancer stem-like cells (CSCs) and Epithelial-mesenchymal transition (EMT) exhibit pivotal roles in cancer cell metastasis, tumor recurrence, chemotherapy resistance, and cancer cell death, among other processes. This review aims to elucidate the molecular mechanisms underlying EMT and CSCs, their interplay, associated signaling pathways, and regulation of the EMT process and the initiation of CSCs. EMT induction confers mesenchymal properties and the potential of cancer cells to adopt the CSC state. These processes are intricately associated with the regulation of Notch and Wnt signaling pathways, transforming growth factor-β (TGF-β), as well as the expres-sion of miRNAs. Further exploring the relationship between EMT and CSCs is essential for the development of new chemotherapeutic strategies and the identification of novel therapeutic tar-gets, and hence, the development of therapeutic strategies targeting EMT, or CSCs holds promise for improving cancer therapy.

In this work, we study a boundary control problem for the evolutionary Stokes equations, under mixed boundary conditions, in two and three dimensions. The Stokes equation is a valuable tool in cardiovascular biomechanics, especially for modeling blood flow in low-velocity and high-viscosity conditions. Its application in the microvasculature, the design of medical devices, and the study of cardiovascular diseases helps improve the understanding and treatment of various pathological conditions. We provide a comprehensive theoretical framework to address the analysis and the derivation of a system of first-order optimality conditions that characterizes the solution of the control problem. Finally, solution-finding algorithm is proposed and illustrated with some simulations.

A Co–doped porous carbon was successfully fabricated by a facile carbonizing procedure using coal hydrogasification semi-coke (SC) as the carbon and cobalt nitrate as the magnetic precursors, respectively. The microwave absorption (MA) performances were regulated by adjusting the mass ratio of the precursors. The dielectric loss from the carbon framework, the magnetic loss from nano–sized Co particles coupled with multiple scattering from the residual pores synergistically contribute to the favorable MA capabilities. When the initial mass ratio of cobalt nitrate and SC was 1:1, the Co/C composite showed the lowest reflection loss of -33.45 dB at the thickness of 4.0 mm. The effective absorbing bandwidth (EAB) could achieve 3.5 GHz at 2 mm in thickness. This work not only exploits a new avenue for the structural design and facile fabrication of dielectric and magnetic loss combinations, but also opens up another way for the high value–added utilization of SC.

Accordingly, a lot of dry direct seeding rice would be dense planted, that the initial seedling quantity could approach or even exceed the targeted effective panicle number. While limit information is available to evaluate the effects of involved novel nitrogen application methods, that total nitrogen once applied at a determined leaf age stage, on the yield formation traits of such dense planted dry direct seeding rice. The two-year experiments with total 180 kg ha-1 nitrogen once applied time treatments at sixth (L6), seventh (L7), eighth (L8), ninth (L9) and tenth (L10) leaf age stages were carried out. Results showed that the above-ground dry matter weight at maturity and grain yield of L8 was 2.1% ~ 11.8% and 4.0% ~ 9.9% higher than those of other treatments. Compared to other treatments, the higher above-ground dry matter weight after heading stage, bigger mean leaf area index with higher leaf area index at heading stage, increased leaf area duration, crop growth rate and net assimilation rate from jointing to heading period were important traits of higher grain yield formation of L8. In addition, the L8 had relative higher grain-leaf ratio traits than other treatments. Overall, a total 180 kg ha-1 nitrogen with mixed urea and compound fertilizer once applied at eighth leaf age stage would be suggest a useful high yield cultivation method for dense planted dry direct seeding rice in rice-wheat rotation system.

Physical activity (PA) benefits are well-established, yet many US adults fail to meet PA guidelines. This is especially true for minorities facing social inequities. This study explored barriers and facilitators to PA among urban Midwestern minorities using a mixed-methods approach framed on the socio-ecological model. A cross-sectional survey was conducted among community-dwelling minorities. Participants were grouped as completing low (LLPA) or high (HLPA) weekly leisure-time PA for comparison. Quantitative analysis included MANOVA, follow-up ANOVAs, and calculation of effect sizes. Qualitative data were assessed using inductive thematic analysis. Twenty-nine adults (44.83% Black, 41.37% Latino) participated in the study. The HLPA group (n = 18) reported higher leisure-time PA (p = 0.001, d = 2.21) and total PA (p = 0.02, d = 1.00) compared to the LLPA group (n = 11). LLPA participants faced more personal barriers to PA (p = 0.02, d = -0.92). Common barriers identified in the interviews included a lack of time and financial costs. Facilitators included social support and available PA facilities. Both groups achieved USPA guidelines through different PA domains. Increasing social support and lowering PA-related costs could enhance participation. Addressing barriers and leveraging existing facilitators are crucial to increasing PA among minorities.

In the digital age, social media platforms have become a significant source of both information and misinformation, presenting challenges and opportunities for threat intelligence. Natural Language Processing (NLP) has emerged as a powerful tool for extracting actionable insights from the vast amounts of unstructured text generated on these platforms. This paper explores the application of NLP techniques to enhance social media threat intelligence, focusing on methodologies for detecting and analyzing threats such as disinformation, cyberbullying, and extremist content. We examine various NLP approaches, including sentiment analysis, topic modeling, and entity recognition, and their effectiveness in identifying and mitigating potential risks. The paper also addresses the challenges associated with processing social media data, such as dealing with slang, context, and multilingual content. By leveraging NLP, organizations can improve their ability to monitor and respond to emerging threats in real-time, ultimately enhancing their overall security posture. The findings suggest that while NLP offers significant benefits, it must be complemented by human expertise and ethical considerations to ensure accurate and responsible threat assessment.

This study aimed to explore the genetic information about the yield traits in perennial Chinese rice "Shendao3^#" and provide a series of theoretical bases for the innovative utilization of perennial Chinese rice germplasm. The F₂ population derived from the cross between perennial Chinese rice "Shendao3^#" and one annual rice "XiqingzaoB" was developed to identify QTLs’ underlying yield-related traits. Fifteen yield traits including plant height, panicle plant^-1, and thousand-grain weight were measured for the QTL mapping. The software packages Excel 2010, GraphpadPrism 5.0, and QTLIciMapping 4.10 were used to perform the phenotypic data analysis, construction of molecular map, and QTL mapping, respectively. Results indicated 15 yield-related traits displaying normal distribution and belonging to quantitative trait inheritance. A total of 25 QTLs associated with the yield-related traits and 26 epistatic QTLs were detected on the whole genome except for the 6th and 12th chromosomes. This finding explained phenotypic variance with ranging from 4.21% to 27.30% and 1.15% to 19.30%, respectively. Six pleiotropic QTL (chromosomal regions) underlying two or more yield-related traits were detected on the 1st , 4th, 7th, 8th, and 11th chromosomes, respectively. Among 25 QTLs underlying a single yield-related trait, 11 were primarily identified in the perennial Chinese rice "Shendao3^#". All QTLs underlying 15 yield-related traits followed the genetic model of additive, dominant, and digenic epistatic of additive by additive, additive by dominant, dominant by additive, and dominant by dominant. This work can serve as a good foundation for yield-related gene mining and its utilization in breeding the perennial Chinese rice "Shendao3^#".

The Internet of Things (IoT) has revolutionized various industries, but the increased dependence on all kinds of IoT devices and the sensitive nature of the data accumulated by them pose a formidable threat to privacy and security. While traditional Intrusion Detection Systems (IDSs) have been effective in securing critical infrastructures, the centralized nature of these systems raises serious data privacy concerns, as sensitive information is sent to a central server for analysis. This research paper introduces a Federated Learning (FL) approach designed for detecting intrusions in diverse IoT networks that addresses the issue of data privacy by ensuring that sensitive information is kept in the individual IoT devices during model training. Our framework utilizes the Federated Averaging (FedAvg) algorithm, which aggregates model weights from distributed devices to refine the global model iteratively. The proposed model manages to achieve above 90\% accuracy across various metrics, including precision, recall, and f1-score, while maintaining low computational demands. The results show that the proposed system successfully identifies various types of cyber attacks, including DoS, DDoS, Data Injection, Ransomware, and several others showcasing its robustness. This research makes a great advancement to the intrusion detection systems by providing an efficient and reliable solution that is more scalable and privacy friendly than any of the existing models.

Multiple sclerosis (MS) is an immune-mediated disease characterized by inflammation, demyelination, and neurodegeneration within the central nervous system. Brain plasticity, the brain's ability to adapt its structure and function, plays a crucial role in mitigating MS's impact. This paper explores the potential benefits of lifestyle changes and nutraceuticals on brain plasticity in MS population. Lifestyle modifications, including physical activity and dietary adjustments, can enhance brain plasticity by upregulating neurotrophic factors, promoting synaptogenesis, and reducing oxidative stress. Nutraceuticals, such as vitamin D, omega-3 fatty acids, and antioxidants like alpha-lipoic acid, have shown promise in supporting brain health through anti-inflammatory and neuroprotective mechanisms. Regular physical activity has been linked to increased levels of brain-derived neurotrophic factor and improved cognitive function. Dietary interventions, including caloric restriction and the intake of polyphenols, can also positively influence brain plasticity. Integrating these lifestyle changes and nutraceuticals into the management of MS could provide a complementary approach to traditional therapies, potentially improving neurological outcomes and enhancing the quality of life for MS population.

Background and Objectives: Most of the research of the BRCA1 inactivation is focused on monoallelic germline alterations and loss of heterozygosity in tumour. The aim of this study was to identify characteristic transcriptomic pattern of monoallelic somatic BRCA1 inactivation and estimate its impact to the event-free breast cancer survival prognosis. Materials and Methods: We conducted global transcriptome sequencing of breast cancer tissue samples to identify differentially expressed genes and signalling pathways associated with monoallelic somatic BRCA1 inactivation. The study group involved 36 patient samples categorized based on BRCA1 inactivation status. Subsequently, the differential gene expression and Kaplan-Meier analyses in the groups with and without monoallelic somatic BRCA1 inactivation were performed. Results: Kaplan-Meier analysis showed tendency for longer event-free survival in patients with monoallelic somatic BRCA1 inactivation, suggesting somatic BRCA1 inactivation is favourable prognostic. Differential gene expression analysis followed by the STRING tool enrichment analysis showed significant enrichment of proteins in the extracellular region and extracellular space. Conclusion: In this study we identified transcriptomic profile of differentially expressed genes TPSD1, FABP4, CARTPT and MMP9 as indicative for homologous recombination impaired tumours with tendency for better therapy results.

Candida albicans, a prominent constituent of the human microbiota, poses a significant health threat due to its opportunistic pathogenicity and adept biofilm-forming capabilities. This research delves into the antifungal attributes and biofilm inhibition potential of Tea Tree Oil (Melaleuca alternifolia) cultivated in Vietnam. Renowned for its bioactive compounds, including terpinen-4-ol, 1,8-cineole, and terpinolene, the essential oil of Melaleuca alternifolia, commonly referred to as tea tree oil (TTO), is scrutinized for its impact on Candida albicans. The study meticulously determines the Minimum Inhibitory Concentration (MIC) and Minimum Fungicidal Concentration (MFC) of TTO against Candida albicans in both planktonic and biofilm states. Additionally, it assesses the biofilm-forming capacity of Candida albicans and establishes the Minimum Biofilm Inhibitory Concentration (MBIC) and Minimum Biofilm Eradication Concentration (MBEC) of TTO. Employing a liquid culture dilution method within a defined concentration range of 0.1 μL/mL to 10 μL/mL, the experimental approach adheres to established protocols. The outcomes reveal a noteworthy MIC and MIC₈₀ of 0.1 μL/mL and 2 μL/mL, respectively, and an MFC of 10 μL/mL for TTO against Candida albicans. Furthermore, TTO exhibits an MBIC of 2 μL/mL, showcasing its efficacy in inhibiting biofilm formation. However, the MBEC of TTO remains uncertain, possibly due to insufficient concentration tested, which may not effectively disrupt over 50% of the pre-formed biofilm mass within 24 hours. These results underscore the promising potential of TTO as a potent antifungal agent and biofilm inhibitor against Candida albicans, offering valuable insights for the innovation of novel therapeutic strategies in the realm of fungal infections.

High-wind structures were identified in the Cross-Calibrated Multi-Platform (CCMP) ocean wind vector reanalysis for comparison with winds measured by satellite radiometers and synthetical aperture radar (SAR) instruments from February to October 2023. The comparison aims to evaluate bias, uncertainty, and spatial correlations with the goal of enhancing the accuracy of ocean wind datasets during tropical cyclones (TCs). In 10°longitude×10°latitude blocks, each containing a TC, Soil Moisture Active Passive (SMAP) and Advanced Microwave Scanning Radiometer 2 (AMSR2) winds are 6.5% and 4.8% higher than CCMP, while Advanced Scatterometer (ASCATB) is 0.8% lower. For extratropical cyclones, AMSR2 and SMAP also show stronger winds with a 5% difference, and ASCATB is about 0.3% weaker compared to CCMP. The comparison between SAR and CCMP for TC winds, sampled at the locations and time frames of SAR tiles, indicates that SAR winds around TCs are about 9% higher than CCMP winds. Using empirically defined TC structural indices, we find that the TCs observed by CCMP are shifted in locations and lack a compact core region. A Random Forest (RF) regressor was applied to TCs in CCMP with corresponding SAR observations, nearly correcting the full magnitude of low bias in CCMP statistically, with a 15m/s correction in the core region. The hierarchy of importance among the predictors is as follows: CCMP wind speed (62%), distance of SAR pixels to the eye region (21%) and eye center (7%), and distance of CCMP pixels to the eye region (5%) and eye center.

This study investigates the synthesis and characterization of zirconium oxide (ZrO₂)-based metal-composites doped with cerium (Ce) and yttrium (Y), using chromium (Cr) and nickel (Ni) as base metals. These constituents were selected for their superior mechanical properties and compatibility with the ceramic phase. High-purity powders were homogenized via high-energy ball milling, followed by cold isostatic pressing (CIP) and sintering in a controlled atmosphere. The sintering process was conducted at various temperatures (850°C to 1350°C) to examine densification, grain growth, and microstructure evolution. Scanning Electron Microscopy (SEM) revealed a homogeneous distribution of phases, with distinct microstructural features attributed to each element at different sintering temperatures. Density measurements using the water immersion method and theoretical calculations demonstrated increased density and reduced porosity with higher sintering temperatures. Vickers hardness testing indicated that hardness improved with increased sintering temperature, peaking around 1150°C due to cerium and yttrium reinforcement within the matrix. Flexural strength tests showed the highest value at 1350°C, with a significant drop in porosity, suggesting enhanced mechanical properties due to efficient doping and phase transformations. Overall, the incorporation of cerium and yttrium significantly improved the mechanical behavior and phase stability of the ZrO₂-Cr-Ni composites, highlighting their potential for advanced engineering applications.

Poland suffered an epidemic of louse-borne typhus from 1916-1923, with 400,000 cases and more than 130,000 deaths. The causative factors were depressed economic conditions and a refugee crisis that engulfed Poland after World War I. The recognition of the epidemic in 1919 stimulated the creation of the League of Red Cross Societies (LRCS). However, the LCRS had limited resources and the Poles requested help from other governments and the League of Nations (LoN). The United States sent the American-Polish Relief Expedition to conduct delousing. However, the Polish-Soviet War of 1920 disrupted typhus control and exacerbated the refugee situation. The LoN belatedly organized an underfunded Epidemic Commission. The LCRS sent a research team that did ground-breaking work on the pathology of typhus. Into 1921, the epidemic continued, driven by refugees from typhus-stricken Russia. By 1924, typhus cases were finally approaching pre-World War I levels. Multiple factors lead to the amelioration of the epidemic. The repatriation of prisoners of war and displaced civilians had concluded by 1923. Also, there had been a steady influx of sanitary, food, economic, and medical aid from various organizations into Poland since 1919. Administratively, within Poland, the anti-typhus campaign was also conducted more effectively by the Extraordinary Epidemic Commissariat.

The fundamental divergence in foundation of modern physics lies in the incompatibility between quantum theory and relativity. This study created a relative continuum, found a mathematical tool for the cosmic continuum; proposed dark particle hypothesis, filled gap on minimum existence quantity particle; discovered new equivalence principle, bridged differences in foundation of physics; and established an ideal model, revealed deep essence of cosmic and material structure. In this model, any cosmic system is a continuum composed of existence continuum relative to the wavelength of bosons energy waves and its dimension continuum. This model provides new perspectives on the fundamental problems of physics and cosmology. Firstly, it elucidated the physical mechanism of bosons in fundamental interactions. Secondly, it reconstructed the understanding of the basic unit of the cosmic and material structure. Thirdly, it updated the inherent concepts about the existence form and existence dimension. Fourthly, it restored the causality truth of wave function collapse in quantum mechanics.

The use of natural health products (NHP) is constantly increasing worldwide. Among the most NHP consumed are the resins of Commiphora myrrha (C. myrrha) tree. Consumption of C. myrrha may result in herb-drug interactions that can lead to serious health consequences. This study aims to determine the herb-drug interactions based on the induction of drug-metabolizing enzyme cytochrome P-450 (CYP) 2C9 by a non-toxic boiled aqueous extract of C. myrrha and to unveil the potential involvement of xenobiotic-sensing nuclear receptors such as Pregnane X Receptor (PXR), a well-known CYP 2C9 transcription factor. Tested at low concentrations (0.01-10 g/mL) devoid of anti-proliferative effects, boiled C. myrrha resin aqueous extract upregulated CYP 2C9 gene and protein expressions in a dose-dependent manner, reaching a mean expression level exceeding 3.0-fold change in Hep G2 cells, compared with the basal level expressed in untreated cells. Furthermore, chemical analysis using mass spectrometry and computational molecular docking using in silico studies revealed that few C. myrrha resin-derived metabolites are strongly bound to PXR. In particular, the identified metabolite named diayangambin exhibited a predicted molecular docking score close to that of a native PXR ligand. The use of the nuclear receptor binding assays confirmed the binding between C. myrrha metabolite(s) and PXR, while no binding to the other xenobiotic-sensing nuclear receptor, the constitutive androstane receptor (CAR), was observed, suggesting that C. myrrha metabolite(s) are potential PXR agonists. In conclusion, although in vivo studies are needed, this study cautions patients, healthcare providers, and governmental regulators against the consumption of C. myrrha and diayangambin-rich preparations with a high potential for herb-drug interactions through drug-metabolizing CYP 2C9 enzyme induction, which could affect drug efficacy.

Estrogen exerts its action via estrogen receptors (ERs), including ERα and ERβ, and has effects on immunomodulation during pregnancy. It is known that there is a remodeling in maternal immunology during pregnancy. However, it is not clear if early pregnancy has effects on the expression of ERα and ERβ in the maternal thymus, lymph nodes, spleen, and liver. In this study, these maternal immune organs were harvested at day 16 of the estrous cycle, and at days 13, 16, and 25 of pregnancy. The mRNA and protein expression of ERα and ERβ was analyzed. The results revealed that mRNA and protein expression of both ERα and ERβ was upregulated in the maternal spleen, and expression of ERα and ERβ in the thymus, lymph nodes, and liver was modulated during early pregnancy. In conclusion, early pregnancy modulates the expression of ERα and ERβ in the maternal thymus, lymph nodes, spleen, and liver in a tissue-specific manner, which is related to the regulation of maternal immune function during early pregnancy.

Background/Objectives: The Perilla frutescens plant has historically been used to protect against inflammation and redox stress. This has been attributed in part to the high content of various polyphenols. Despite this, the complement of polyphenolic components in Perilla extract is not yet fully defined. The aim of this study was to characterise the polyphenolic composition in Perilla extract, and its effect on the transcription factor nuclear factor erythroid 2-related factor 2 (Nrf2), which during inflammation and oxidative stress binds to the antioxidant response element (ARE) found on the promoter of phase II antioxidant enzymes. Methods: Following extraction using four solvents of different properties, the total phenolic, flavonoid and ortho-diphenolic content of Perilla extract were determined. Individual phenolic compounds were identified and quantified by RP-HPLC. Dual Luciferase assay using a reporter plasmid containing a human NQO1 ARE-luciferase fusion was employed to determine the potential protective effect of the Perilla fractions against redox stress. Results: HPLC analysis revealed that the highest phenolic content was present in the polar extracts. A total of 35 distinct polyphenolic compounds were identified, with rosmarinic acid being the major constituent. On cells in vitro, the methanol Perilla fraction showed protection against redox stress, with the luciferase assay displaying up to 1.5 fold increase in the induction of the human NQO1 ARE-luciferase reporter. Conclusions: While Perilla extract seems to be mainly protecting against inflammation and redox stress through the action of rosmarinic acid, further work is required on the synergystic effects between different polyphenols.

Recent advancements in semantic communication (SC) have shown the potential to surpass the limitations of the Shannon theorem, by leveraging an understanding of the meaning of data instead of the data itself. In networks, data-aided sensing (DAS) presents a powerful tool that can significantly reduce communication overhead, aligning perfectly with the goals of SC by providing more powerful semantic messages. This survey explores the synergy between DAS and SC and investigates how their convergence can lead to more efficient and effective communication.

Ternary ZnS/ZnO/graphitic carbon nitride (gCN) photocatalysts were prepared by coupling gCN sheets with ZnO nanorods under solvothermal conditions followed by sulfurization using Na2S. SEM and TEM analyses show that small-sized ZnS particles (ca. 7.2 nm) deposit homo-geneously on the surface of ZnO/gCN nanohybrids. Photoluminescence and electrochemical impedance spectroscopy show that ZnS allows an enhanced charge separation efficiency as well as prolonged lifetime of photogenerated charge carriers, leading to improved hydrogen photo-production under UV light irradiation compared to ZnO/gCN. Moreover, the deposition of ZnS nanoparticles improves the photostability of the ZnS/ZnO/gCN catalyst for hydrogen produc-tion. A double Z-scheme mechanism is proposed for hydrogen photoproduction using the ZnS/ZnO/gCN heterojunction.

The COVID-19 pandemic has profoundly disrupted small businesses, exacerbating financial vulnerabilities and operational challenges. As these enterprises play a crucial role in economic stability and growth, identifying effective recovery strategies is imperative. This study investigates the legal and management solutions necessary for small businesses to recover and thrive post-pandemic. The research aims to examine the economic impact of the COVID-19 pandemic on small businesses, evaluate the effectiveness of existing legal and governmental support measures, and propose management strategies that enhance resilience and drive recovery. A mixed-methods approach was adopted, comprising both quantitative and qualitative analyses. A survey was conducted with 500 small businesses across various sectors to collect data on financial performance, operational disruptions, and the utilization of government support programs. Additionally, 30 in-depth interviews with small business owners provided qualitative insights into adaptive strategies and challenges faced. A review of relevant legal documents and policy frameworks was also performed to assess the support mechanisms in place. The study revealed that 68% of small businesses experienced substantial revenue losses, with 50% encountering severe liquidity crises. Government support measures, such as grants and low-interest loans, were pivotal but often marred by accessibility issues and delays. Successful management strategies identified included accelerating digital transformation, diversifying revenue streams, and optimizing supply chain management. Legal measures that temporarily eased regulatory requirements and offered tax relief significantly aided in alleviating immediate pressures. The economic recovery of small businesses post-COVID-19 hinges on comprehensive legal and management solutions. Enhancing the effectiveness and reach of government support programs is crucial, as is the adoption of agile and innovative management practices by small businesses. Policymakers and business leaders must work collaboratively to create an environment that fosters resilience and sustainable growth, ensuring small businesses can navigate future economic uncertainties.

Cytokines play a substantial role in the pathophysiology of infectious diseases. Consequently, genetic polymorphisms in cytokine genes can have profound effect on the susceptibility to or protection from infections and also influence the clinical manifestations, disease severity as well as outcome. The objective of this brief narrative review is to provide an update on the recent research findings on the role of genetic polymorphisms of IL-18, a recently discovered cytokine on certain infectious diseases of public health relevance. The current review suggests there is a significant impact of IL-18 polymorphisms on different infectious diseases. The presence of G and T alleles at position -656 is suggested to have a probable protective effect against VL. The −137G/−607C (GC) and −137C/−607C (CC) haplotypes in the promoter region are associated with increased susceptibility to severe malarial anemia. SNPs rs544354 and rs574429 (GC) are linked to a higher risk of P. falciparum infection and increased parasitemia. The -137 C/C genotype and -137 G allele (with G/G genotype) are associated with faster progression to AIDS. In contrast, the IL-18 genotype does not seem to affect overall HIV susceptibility but influences disease progression. The G and GG genotypes at position -137 and allele A at position -607 are likely associated with protection against HBV infection. Conversely, the C allele at position -137 is linked to increased susceptibility to HBV infections. The GG genotype of IL-18 -137 G > C variant is associated with increased susceptibility to pulmonary tuberculosis (PTB). The AC genotype of IL-18 -607A>C has been linked to PTB susceptibility, particularly in patients with co-morbid diabetes mellitus. SNPs −137G/C, 113T/G, and +127C/T are associated with susceptibility to H. pylori infection, indicating that these genetic variants may influence the risk of H. pylori-related diseases. There are conflicting results in studies conducted in different populations (e.g., genetic polymorphism, studies conducted in India and China against HBV infection) highlighting the need for further research with larger sample sizes to resolve discrepancies. Due to the variability in findings, extensive studies in diverse populations are needed to better understand the impact of IL-18 polymorphisms.

This study evaluates the effectiveness of an integrated vestibular rehabilitation program in improving balance, motor control, and proprioceptive function in patients diagnosed with Benign Paroxysmal Positional Vertigo (BPPV). The prospective observational study involved 107 participants who underwent a tailored rehabilitation regimen, including the Epley maneuver, Brandt-Daroff exercises, and balance and proprioceptive training. The program was designed to address the vestibular and proprioceptive deficits caused by BPPV, with the goal of restoring normal function and reducing the risk of symptom recurrence. Dynamic Gait Index (DGI) and Balance Beam Test were used to assess progress, showing significant improvements in balance stability and dynamic motor function. The findings support the integration of vestibular rehabilitation into standard care for BPPV patients, highlighting the program's potential to enhance patient outcomes and reduce recovery time. However, the study also notes limitations such as the lack of a control group and the need for further research to explore the long-term effects of such interventions.

The zinc oxide (ZnO) arrester is positioned on locomotive roof preventing other onboard electrical equipment from the harm caused by external and internal overvoltages. A number of locomotive arrester burnout and explosion accidents occur during traction supply network harmonic resonance causing train stoppages and power outages in the network. This study firstly carries out high-frequency tests to investigate the wide frequency band electrical characteristics of the locomotive arrester, explaining that the arrester is prone to fault during resonance. Consequently, a prognostics and health management (PHM) for locomotive arrester is proposed providing on online monitoring, fault warning and health assessment solutions, which is beneficial to the operation and maintenance of arresters in the future. The testing method and PHM scheme presented in this paper can be not only applied to the arrester, also readily expanded to other high-voltage electrical equipment on the electric locomotive.

Background: Whole-body computed tomography (WBCT) is commonly employed for primary screening in pediatric patients experiencing out-of-hospital cardiac arrest (OHCA) without prehospital return of spontaneous circulation (ROSC). This study aimed to evaluate the cause of OHCA on WBCT and compare WBCT findings between ROSC and non-ROSC groups in non-traumatic pediatric OHCA cases in an emergency department (ED) setting. Methods: A retrospective analysis was conducted on 27 pediatric patients (mean age: 32.4 months; median age: 10 months) who experienced non-traumatic OHCA without prehospital ROSC and were transported to our tertiary care hospital between January 2013 and December 2023. WBCT scans were performed to investigate the cause of OHCA, with recorded findings in the head, chest, abdomen, and subcutaneous tissues. Results: In all cases, the direct causes of OHCA were undetermined, and WBCT identified no fatal findings. Statistical comparisons of CT findings between the ROSC and non-ROSC groups revealed significant differences. The non-ROSC group had a higher incidence of brain swelling, loss of cerebral gray-white matter differentiation, symmetrical lung consolidation/ground-glass opacity, cardiomegaly, hyperdense aortic walls, narrowed aorta, gas in the mediastinum, and hepatomegaly compared to the ROSC group. Conclusions: Although WBCT did not provide the direct cause of OHCA, it clarified several indicative findings for non-ROSC. These imaging findings could support clinical decision-making, offering objective criteria for discontinuing resuscitation in pediatric OHCA cases where prehospital ROSC is absent.

Vehicle logo detection plays a crucial role in various computer vision applications, such as vehicle classification and detection. In this research, we propose an improved vehicle logo detection method leveraging the MAMBA structure. The MAMBA structure integrates multiple attention mechanisms and bidirectional feature aggregation to enhance the discriminative power of the detection model. Specifically, we introduce the Multi-Head Attention for Multi-Scale Feature Fusion (MHAMFF) module to capture multi-scale contextual information effectively. Moreover, we incorporate the Bidirectional Aggregation Mechanism (BAM) to facilitate information exchange between different layers of the detection network. Experimental results on a benchmark dataset (VLD-45 dataset) demonstrate that our proposed method outperforms baseline models in terms of both detection accuracy and efficiency. Furthermore, extensive ablation studies validate the effectiveness of each component in the MAMBA structure. Overall, the proposed MAMBA-based vehicle logo detection approach shows promising potential for real-world applications in intelligent transportation systems.

The paper considers two models of queuing with a varying structure based on the introduction of additional transient intensities into known models or their combinations, which create stationary distributions convenient for calculation. In the first model, it is a probabilistic mixture of known stationary distributions with given weights. In the second model, this uniform distribution is repeatedly used in physical statistics. Both models are based on the selection of states, between which additional transient intensities are introduced. The algorithms used in the paper for introducing new transient intensities are closely related to the concept of flow in a deterministic transport network. The introduced controls are selected so that the marginal distribution of the combined system is a mixture of the marginal distributions of the combined systems with different weights determined by the introduced transient intensities. As a result, the process of functioning of the combined system is obtained by switching processes corresponding to different combined systems at certain points in time.

Clinical trials are essential in the development of new medical treatments, offering crucial data on their safety and effectiveness. This study provides a comprehensive analysis of clinical trials registered on ClinicalTrials.gov, examining trends, challenges, and innovations that have shaped the field over the past century. Data were extracted on July 15, 2024, and analyzed to identify patterns in trial design, sponsorship, participant demographics, and geographical distribution. The analysis reveals a significant increase in clinical trial registrations, peaking in 2021, driven by the COVID-19 pandemic. Most trials focus on cancer, reflecting its global burden, and are predominantly interventional, with randomized controlled trials (RCTs) being the most common study design. However, challenges persist, including underrepresentation of certain demographics, limited global distribution, and insufficient reporting of trial results. Additionally, the underrepresentation of pediatric, elderly, and minority populations in trials limits the generalizability of findings. The analysis underscores the need for more inclusive and globally distributed research to address disparities in health outcomes.

Background The metabolic syndrome increases the risk of developing various systemic cancers. The prevalence of the metabolic syndrome in newly diagnosed glioblastoma patients is unknown. Further, there have been contradictory reports about how the metabolic syndrome affects clinical outcomes. Therefore, the purpose of this study is to test the hypothesis that the metabolic syndrome is associ-ated with increased prevalence of glioblastoma and worsened survival outcomes. Methods This retrospective cohort study examines seventy-three patients with isocitrate dehydrogenase (IDH)-wild type glioblastoma as it provides for a relatively homogeneous population to examine. Patient characteristics, vital signs, lab results, tumor molecular markers, and overall survival were analyzed. Patients with the metabolic syndrome and individual risk factors were identified and survival outcomes were examined. Results Our results demonstrate that there is a higher prevalence of the metabolic syndrome in our cohort of patients with glioblastoma than the general population (41% vs 33%). We also demonstrate that after correction for confounding variables, the metabolic syndrome is not significantly asso-ciated with overall survival (p = 0.1). When analyzing individual metabolic risk factors, we demonstrate that there is a significant association between the accumulation of metabolic risk factors and decreased survival (p = 0.03), and hyperglycemia emerges as a significant independent risk factor for decreased survival (p = 0.05). Conclusion These results suggest that metabolic risk factors can affect survival in patients with glioblastoma, which can have significant implications for clinical practice. These findings need to be further ex-plored through further clinical and mechanistic studies.

The authors propose a novel approach for a comprehensive evaluation of neuroprotective effects using both in vitro and in vivo methods. This approach allows for the initial screening of numerous newly synthesized chemical compounds and substances from plant and animal sources while preserving animal life. In vitro techniques, including mitochondrial suspensions and neuronal cell cultures, enable assessment of neuroprotective activity, which can be challenging in intact organisms. The preliminary methods help outline the neuroprotection mechanism depending on the neurodestruction agent. The authors have validated a model of acute cerebrovascular accident, which simulates key cerebrovascular phenomena such as reduced cerebral blood flow, energy deficit, glutamate-calcium excitotoxicity, oxidative stress, and early gene expression. A significant advantage of this model is its ability to reproduce the clinical picture of cerebral ischemia: impaired motor activity, signs of neurological deficits (paresis, paralysis, etc.), as well as disturbances in attention, learning, and memory. Crucial to this approach is the selection of biochemical, molecular, and cellular markers to evaluate nerve tissue damage and characterize potential neuroprotective agents. Additionally, a comprehensive set of molecular, biochemical, histological, and immunohistochemical methods is proposed for evaluating neuroprotective effects and underlying mechanisms of potential pharmaceutical compounds.