The purpose of this research article was to study the physicochemical characteristics of semi-wild Jhar honey grown in Western Georgia. Jara honey is produced in the alpine and sub-alpine forest zone of high mountain Adjara,  which is distinguished by the variety of honey plants [1]. The physicochemical characteristics were examined concerning the Alimemtarius Code and EU regulations: moisture content, total carbohydrate, free acidity, pH , electrical conductivity, microelements (Li, Na, K, Mg, Ca), color, total phenols, total phenolic acids, total flavonoids, proline, diastase activity, protein and microscopic study of pollens. Using the UPLC-MSB method, grayanotoxin-III was identified in the semi-wild Jara honey samples. The findings demonstrated that honey has significant concentrations of phenols, phenolic acids, and flavonoids. A directly proportional relationship was established between the quantitative content of phenolic compounds and the antioxidant activity of honey. This article is the first study of the characteristics of Jara honey produced in Western Georgia.

As the global overprovisioning of electronic devices continues to rise, the management of electronic waste (e-waste) has developed as a significant challenge. E-waste is comprised of hazardous materials; moreover, the toxic constituents in them can impact the environment and public health through improper disposal. On the beneficial side, this e-waste also contains some valuable materials. If the valuable materials are recovered, they can reduce the dependence on new, raw materials. Conventional linear models of production and consumption have led to a momentous buildup of e-waste, posing environmental and economic risks. This paper examines how the adoption of a circular economy approach can improve e-waste recycling in Nairobi by evaluating its economic recovery potential and e-waste residuals. It introduces metrics to assess the development of circular economy practices to help in the handling of e-waste residuals and examines the economic consequences associated with the adoption of circular strategies.

Multiple Sclerosis (MS) is a chronic autoimmune disorder characterized by the demyelination of neural fibers in the central nervous system. Understanding the impact of demyelination on neural network efficiency is crucial for elucidating the pathophysiological mechanisms underlying MS. This study aims to model the effects of demyelination on neural network efficiency, specifically focusing on how increased resistance and path lengths due to demyelination correlate with the clinical symptoms of MS. We employed a graph-theoretical approach to simulate neural networks, introducing varying degrees of demyelination. The demyelination was represented by increasing the resistance (weights) of selected edges within the network, affecting both random and clustered distributions of network connections. The primary metric analyzed was the average shortest path length, indicative of network efficiency. The models demonstrated a significant increase in the average shortest path length in demyelinated networks compared to intact ones. Specifically, networks with clustered demyelination exhibited localized inefficiencies, correlating with the focal nature of MS lesions. The increase in path length was associated with reduced signal transmission efficiency, providing insights into a range of MS symptoms including motor and sensory impairments, cognitive dysfunction, visual disturbances, and fatigue. The graph-theoretical model of neural network demyelination offers a novel perspective on how structural changes in the brain's connectivity due to MS can lead to diverse clinical manifestations. While the model simplifies the complexity of neural networks, it underscores the potential of computational approaches in understanding and predicting the course of neurological disorders like MS.

This qualitative study explores consumer responses to sustainable supply chains and green marketing strategies, aiming to uncover insights into consumer behavior, perceptions, and attitudes towards sustainability in the marketplace. Through semi-structured interviews and focus group discussions with 30 participants, the study examines key factors influencing consumer trust in green marketing claims, barriers to adopting sustainable products, generational differences in attitudes towards sustainability, and the impact of social media on consumer perceptions. Findings reveal that consumers value transparency and credibility in green claims, preferring products certified by trusted third parties and companies that demonstrate transparent supply chain practices. Higher pricing, concerns about product effectiveness, and limited availability emerged as significant barriers to consumer adoption of sustainable products, highlighting the need for cost competitiveness and increased market accessibility. Generational cohorts, particularly Millennials and Generation Z, exhibit strong inclinations towards sustainability-driven behaviors, shaping market trends towards ethical consumption practices. Social media plays a pivotal role in influencing consumer perceptions, disseminating information about sustainability, and fostering engagement with environmental issues. The study underscores the importance of clear communication, consumer education, and supportive regulatory frameworks in promoting sustainable consumption behaviors. Practical implications include recommendations for businesses to enhance transparency, innovate sustainable products, align with consumer values, leverage social media platforms, and advocate for regulatory measures that uphold environmental standards. By addressing these insights, businesses and policymakers can effectively meet consumer expectations and contribute to sustainable development goals in the global marketplace.

The current green development in the context of public policy and industrial economy is difficult to fully match the new infrastructure process driven by massive data. Its connotation and exten-sion and the level of rule of law need to be deepened to ensure that data production, processing, circulation, elimination and other activities can get high-quality and sustainable development in the collaborative construction of hard facilities and soft environment in the new era. Based on the practical needs of data industry green development in key areas, we can resolve the legal risk of data industry green development from three aspects: improving the legal level of green public policy, clarifying the green legal benchmark of data industry development, and improving the green legal system of digital society. Then, it considers the design of environmental protection system based on hardware facilities and the structural and readable clean data system innova-tion of soft data industry development framework mode, so as to clarify the legalization scheme of data industry green development under the new infrastructure. Overall, achieving the green development of the data industry requires not only active attempts by China but also joint efforts by China and other countries.

The production of nanoparticles has recently surged due to their varied applications in biomedical, pharmaceutical, textile, and electronic sectors. However, this rapid increase in nanoparticle manufacturing has raised concerns about environmental pollution, particularly due to their potential adverse effects on human health. Among the various concerns, inhalation exposure to nanoparticles poses significant risks, especially affecting the respiratory system. Airway epithelial cells play a crucial role as the primary defense against inhaled particulate matter and pathogens. Studies have shown that nanoparticles can disrupt the airway epithelial barrier, triggering inflammatory responses, generating reactive oxygen species, and compromising cell viability. However, our understanding of how different types of nanoparticles specifically impact the airway epithelial barrier remains limited. To investigate nanoparticle-induced cellular responses and barrier dysfunction, both in vitro cell culture models and in vivo murine models are commonly utilized. In this review, we discuss the methodologies frequently employed to assess nanoparticle toxicity and barrier disruption. Furthermore, we analyze and compare the distinct effects of various nanoparticle types on the airway epithelial barrier. By elucidating the diverse responses elicited by different nanoparticles, we aim to provide insights that can guide future research endeavors in assessing and mitigating the potential risks associated with nanoparticle exposure.

We report the detection of live Escherichia coli (E. coli) in liquid samples using a biosensor based on a field effect transistor (FET) biosensor with B/N co-coped graphene oxide (GO) gel (BN-GO) as the transducer material. The FET was functionalized with antibodies to detect E. coli K12 O-antigens in phosphate-buffered saline (PBS). The biosensor detected the presence of planktonic E. coli bacterial cells within a mere 2 minutes. The biosensor exhibited a limit of detection (LOD) of 10 cells per sample, which can be extrapolated to a limit of detection at the level of a single cell per sample and a detection range of at least 10– 108 CFU/mL. The selectivity of the biosensor for E. coli was demonstrated using Bacillus thuringiensis (B. thuringiensis) as a sample contaminant. We also present a comparison of our functionalized BN-GO FET biosensor with established detection methods of E. coli k12 bacteria, as well as with state-of-the-art detection mechanisms.

The practice of stormwater management has evolved from a singular focus on drainage to a multifaceted approach to support integrated urban development. By contributing to healthy, livable, ecological, and water sensitive cities, it is a key tool to promote Sustainable Development Goal 11 from neighborhood to metropolitan scales. A review of the knowledge base for stormwater management shows several attributes that favor an integrative approach to achieve co-benefits across several sectors. Functional areas of its contributions include drainage, flood control, flood plain management, water quality control, urban ecology, recreation, and city beautification. Legacy path dependance affects the potential to reform land use practices, while stormwater management practice is being affected by climate change, sea level rise, urbanization, inequality, and poor governance. Technical methods for stormwater management are well advanced, but integrative frameworks to address social, ecological and infrastructure needs are more challenging. The sensitivity of ecological issues is most evident in cities in coastal zones. Organizational initiatives are needed to counter neglect of essential maintenance and sustain flood risk reduction in cities. Stormwater management is related to other integrative tools, including IWRM, One Water, One Health, and integrated flood management, as well as the broader concept of urban planning. Stormwater capture and rainfall harvesting offer major opportunities to augment scarce water supplies. Nature-based solutions like low-impact development and the Sponge City concept show promise to transform cities. Major cities face challenges to sustain conveyance corridors for major flows and to store and treat combined sewer runoff. The neighborhood focus of stormwater management elevates the importance of participation and inclusion to advance environmental justice and strengthen social capital. Integrating organizational initiatives from local to city scale and funding improvements to stormwater systems are major challenges that require leadership from higher governance levels, although governments face resistance to change toward integration, especially in countries with poor land use and public works management systems. Finding solutions to neighborhood issues and the connectivity of water systems at larger scales requires complex approaches to urban planning and represent an important agenda for urban and water governance going forward.

Lahpet-ye-hsain, known as a “tea shop” or teahouse, is where the people of Myanmar conduct their daily social activities besides its economic orientation. They are private establishments and informal gathering places serving tea and food at different times of the day for various clients. They can be small snacks, large open-aired, or covered restaurants with extensive menus. Patrons sit around small square tables on footstools. A diverse range of characters goes to tea shops. They have a reputation for welcoming people from all backgrounds and walks of life, but the role of women is hardly seen and unclear. They provide a space for men to share a cup of tea and food and exchange ideas, opinions, problems, hopes, and aspirations. They provide not only space but also to get ‘good taste and cheap food.’ A cup of tea at a tea shop is an opportunity to share knowledge amongst old and new friends. Such shops are abundant over the country. This paper examines the social, political, and economic role of these ubiquitous features of Myanmar society. The barriers to women's participation and inroads in some locales are discussed.

Hirschsprung disease (HSCR, incidence 1/5000 live births) is caused by failure of neural crest-derived precursors to migrate, survive, proliferate or differentiate during the embryonic development of the Enteric Nervous System (ENS), which could be disrupted by many factors, in-cluding inflammatory processes. The NF-κB family controls several biological processes includ-ing inflammation, neurogenesis and cell migration. With the aim of studying the potential role of NF-κB in HSCR, we have analyzed the expression of the NF-κB main subunits and other NF-κB-related genes by RT-qPCR in HSCR tissue samples (sub-divided in ganglionic and agan-glionic segments). We found a decreased gene expression of the NF-κB main subunit RelA/p65, but also of IkBα, TNF-α, TFGBR2 and ERBB3 in the pathologic distal aganglionic segments com-pared to the proximal ganglionic segments. Moreover, we could also confirm the lower protein expression of RelA/p65 in the aganglionic distal segments by immunofluorescence staining. Fur-ther, we show that the expression of RelA/p65 in the proximal segments concurs with lymphocyte infiltration in the bowel tissue, indicating a pro-inflammatory activation of p65 in the proximal ganglionic HSCR tissue in the patients analyzed. In all, our findings suggest that the modulation of NF-κB signaling in the neuro-enteric system does obviously contribute to the pathological ef-fects in HSCR.

This qualitative study explores consumer perceptions of supply chain sustainability and its impact on buying decisions. Through in-depth interviews and focus groups, the research investigates the multifaceted factors influencing consumer behaviors towards sustainable products. Findings reveal that environmental impact, social responsibility, transparency, economic considerations, and cultural influences are pivotal in shaping consumer attitudes. While consumers express strong motivations to support sustainability, practical barriers such as higher costs and limited availability often hinder consistent adoption of sustainable practices. Effective communication strategies, including transparency reports and sustainability certifications, emerge as crucial in bridging the gap between consumer intentions and actions. The study underscores the importance of aligning corporate sustainability initiatives with consumer expectations to build trust and foster sustainable consumption patterns. Insights suggest a need for targeted interventions and policy measures to address barriers and promote broader adoption of sustainable behaviors. By understanding and responding to consumer concerns, businesses can enhance their sustainability strategies and contribute to a more environmentally and socially responsible marketplace.

This study explores the intriguing phenomenon of action potentials reverberating and propagating in high-resistance tissues, such as gliosis, leading to the emergence of short circuits within the brain. Gliosis, characterized by increased tissue resistance, presents a unique environment for electrical signals. My research investigates the possible mechanisms behind these reverberations and their role in the creation of self-empowering short circuits that can potentially affect the entire brain's functionality. Understanding these processes may have significant implications for the treatment and management of neurological disorders associated with gliosis and abnormal electrical activity in the brain.

A single paragraph of about 200 words maximum. For research articles, abstracts should give a Ultra-high performance concrete (UHPC) has gained worldwide popularity because of its notable mechanical response. This research studied the compressive strength, modulus of elasticity, and flexural tensile strength of UHPC. Batches were made with the addition of steel and PVA fibers using a standard procedure defined in the research. The experimental data from the compressive strength test was analyzed in the Statistica 10 software to investigate the fibers' influence on UHPC's mechanical properties. An analysis of the elastic modulus prediction was carried out according to international standards. It was found that the normalized equations for the elastic modulus are not adequate for its estimation. The statistical analysis indicated that the range of fiber quantities analyzed did not significantly affect the compressive strength and the elastic modulus. Regarding the optimized mix, its flexural tensile strength indicates that the fiber content must be higher for UHPC to be suitable for structural use.

Polymyalgia rheumatica (PMR) is an inflammatory disease common in people aged 50 years and older. This condition is characterized by the presence of pain and stiffness involving mainly the shoulder and pelvic girdle. Besides the frequent association with giant cell arteritis (GCA), several conditions may mimic PMR or present with PMR features. Since the diagnosis is basically clinical, an adequate diagnosis of this condition is usually required. Positron emission tomography-computed tomography (PET-CT) has proved to be a useful tool for the diagnosis of PMR. The use of 18F-FDG-PET imaging appears promising as it provides detailed information on inflammatory activity that may not be evident with traditional methods. However, since PET-CT is not strictly necessary for the diagnosis of PMR, clinicians should consider several situations in which this imaging technique can be used in patients with suspected PMR.

Understanding and preventing the “great obstetrical syndromes” has been the focus of pregnancy research for decades. The combined global impact from these syndromes on maternal and perinatal morbidity and mortality is compounded by increased long-term risk of adverse health effects following pregnancy. Accumulating evidence indicates that conditions such as pre-eclampsia, fetal growth restriction, spontaneous preterm labour, and stillbirth, are syndromes with etiologic heterogeneity that share common pathophysiologic pathways involving placental dysfunction. Recently, the importance of the interaction between fetal and maternal genomes has been extended to include the epigenetic impact of pre-existing maternal pathophysiology on placental development and highlights the importance of nutritional and environmental factors in altered placentation. Validated first-trimester screening algorithms for preeclampsia can identify high-risk women and prophylactic treatment with low-dose aspirin can be initiated. High-risk women can be monitored during the second trimester using clinical assessment, ultrasound, and biochemical markers, that are able to predict complications prior to the development of clinical signs and symptoms. The integration of lifestyle interventions, pregnancy screening, and medical management represents a conceptual advance in pregnancy care. This approach has the potential to significantly reduce pregnancy complications, maternal and perinatal morbidity and mortality, adverse health outcomes later in life, and health-care costs.

Functional copy number alterations (fCNAs) are DNA copy number changes with concordant differential gene expression. These are less likely to be bystander genetic lesions and could serve as robust and reproducible tumor biomarkers. To identify candidate fCNAs in neuroendocrine tumors (NETs), we integrated chromosomal microarray (CMA) and RNA-seq differential gene expression data from 31 pancreatic (pNET) and 33 small bowel neuroendocrine tumors (sbNET). Tumors were resected from 47 early disease progression (24 months) patients. Candidate fCNAs that accurately differentiated these groups in this discovery cohort were then replicated using fluorescence in situ hybridization (FISH) on formalin-fixed, paraffin-embedded (FFPE) tissues in a larger validation cohort of 60 pNETs and 82 sbNETs (52 early and 65 late disease progression samples). Logistic regression analysis determined the predictive ability of these biomarkers as well as the assay performance metrics of sensitivity, specificity, and area under the curve. Our results indicate that copy number changes at chromosomal loci 4p16.3, 7q31.2, 9p21.3, 17q12, 18q21.2, and 19q12 may be used as diagnostic and prognostic NET biomarkers. This involves a rapid, cost-effective approach to determine primary tumor site for patients with metastatic liver NETs and to guide risk stratified therapeutic decisions.

3D reality capturing has demonstrated increased efficiency and consistently accurate outcomes in architectural digitisation. Nevertheless, despite advancements in data collecting, 3D reality capturing still lacks full automation, especially in the post-processing and modelling phase. Artificial intelligence (AI) has been a significant focus, especially in computer vision, and tasks such as image classification and object recognition might be beneficial to the digitisation process and its subsequent utilisation. This article aims to examine the potential outcomes of integrating AI technology into the field of 3D reality-capturing, with a particular focus on its use in architectural scenarios. The main methods used for data collection are laser scanning (static or mobile) and photogrammetry. As a result, image data including RGB-D data (files containing both RGB colours and Depth information) and point clouds have become the most common raw datasets available for object mapping. The study comprehensively analyses the current use of 2D and 3D deep learning techniques in documentation tasks, particularly downstream applications. It also highlights the ongoing research efforts in developing real-time applications with the ultimate objective of achieving generalisation and improved accuracy.

Gradients of smooth functions with non-independent variables are relevant for exploring complex models and for the optimization of functions subjected to constraints. In this paper, we investigate new and simple approximations and computations of such gradients by making use of independent, central and symmetric variables. Such approximations are well-suited for applications in which the computations of the gradients are too expansive or impossible. The derived upper-bounds of the biases of our approximations do not suffer from the curse of dimensionality for any $2$-smooth function, and theoretically improve the known results. Also, our estimators of such gradients reach the optimal (mean squared error) rate of convergence (i.e., $\mathcal{O}(N^{-1})$) for the same class of functions. Numerical comparisons based on a test case and a high-dimensional PDE model show the efficiency of our approach.

Prostate cancer is the most common non-cutaneous malignancy in men, with the majority of newly diagnosed patients eligible for active surveillance. Despite definitive treatment, a considerable percentage of men will experience biochemical recurrence and even regional and distant metastatic recurrence after radiation therapy or radical prostatectomy. Salvage prostatectomy, while oncologically effective, poses significant morbidity with poor functional outcomes. Salvage cryotherapy has emerged as a promising alternative for localized recurrence, demonstrating safety and efficacy. This review examines the oncologic and functional outcomes of whole-gland and focal salvage cryotherapy, including disease-free survival, cancer-specific survival, and overall survival. The crucial role of multiparametric prostate MRI and evolving role of next-generation PSMA-targeted PET imaging is also examined. Comparison of outcomes of cryotherapy to other salvage ablation modalities, such as high-intensity focused ultrasound (HIFU) is also explored.

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

A novel means of applying radiotherapy in cancer treatment is the application of the radiation dose at a very high intensity for a very short time, FLASH radiotherapy (FLASH-RT). This technique involves exposure of tumors to >40 Gy/s, usually for less than one second. Studies conducted in cell and preclinical models suggest that FLASH-RT seems less damaging to normal tissues from adverse effects, relative to the same overall dose of radiation administered in conventional therapy (CONV-RT) which involves administration of lower levels of radiation repeated intermittently over a protracted period. In contrast, the susceptibility of tumor tissues to FLASH-RT is not diminished relative to CONV-RT. Within solid tumors both modes of dispensation of radiation produce an equivalent degree of cell damage. This differential between normal and malignant material has been found in isolated tissues, animal studies, and more recently in clinical trials. However, the classical radiation concept is that high energy linear transfer radiation (LET) is more damaging than the equivalent total dose of low LET. Thus, the susceptibility of cells should be greater to short-term exposure to high LET. This article discusses the potential reasons that may account for this discrepancy. While the relative protection given to untransformed tissues by FLASH-RT relative to tumor tissue is a major step forward in radiation therapy of cancer, the processes that lie behind this phenomenon are incompletely understood and are considered here.

Obsessive-Compulsive Disorder (OCD) is a mental health condition marked by recurrent intrusive thoughts or sensations that compel individuals to perform repetitive behaviors or mental acts. Obsessions and compulsions significantly disrupt daily life and cause considerable distress. Early identification and intervention improve long-term outcomes. This study aimed to evaluate the ability of four advanced artificial intelligence models (ChatGPT-3.5, ChatGPT-4, Claude, and Bard) to accurately recognize OCD compared to human professionals and to assess recommended therapies and stigma attributions. This study was conducted during March 2024 utilizing 12 vi-gnettes. Each vignette depicted a client, either a young adult or a middle-aged male or female, attending an initial therapy session. Each vignette was evaluated ten times, resulting in 480 evaluations. The results were compared with those of a human sample of 514 psychotherapists, as reported by Canavan. Significant differences were found. AI models demonstrated higher OCD recognition rates and confidence levels than human professionals and showed 100% confidence in recognition, compared to 87% among psychotherapists. AI models also recommended evi-dence-based interventions more frequently, with ChatGPT-3.5 and Claude at 100%, ChatGPT-4 at 90%, and Bard at 60%, compared to 61.9% among psychotherapists. Additionally, AI models ex-hibited significantly lower stigma and danger estimations, though both AI and psychotherapists demonstrated high willingness to treat the described cases. The findings suggest that AI models surpass human professionals in recognizing OCD and recommending evidence-based treatments while also demonstrating lower stigma. These results highlight the potential of AI tools to enhance OCD diagnosis and treatment in clinical settings.

Topology optimization has become a very popular design tool when an optimum design with a concrete objective and subjected to several restrictions is searched. However, the resultant shape of the optimization process isn’t usually easy to manufacture with a typical manufacturing method as machining, being necessary an interpretation and validation of the result; besides, some parameters can be chosen, and the final shape is directly dependent on them. In this paper, a sensitivity analysis of the main parameters involved in 3D topology optimization, the penalization and the filter radius, is carried out for the concrete case of the density-based method, analyzing how manufacturable the results are for 3 axis machining. Also, a new filter and method is proposed for obtaining highly manufacturable and low interpretable parts. The main aim of the study is to help designers to choose the more appropriate parameters and showing what they must have into account for obtaining the desired optimized shapes. Note that the density-based topology optimization method has been chosen due to its popularity in commercial packages, so the conclusions may have direct applications in designers’ work. Finally, the results of the study are verified through different cases for checking the validity of the conclusions.

The impact of propeller effects and power contribution on the aerodynamics of small aircraft is indispensable. The aerodynamic analysis of wings in flight varies from rigid wing analysis due to wing deflection caused by transferred aerodynamic loads. This paper investigates the intertwined influence of propeller effects and elasticity on the aerodynamics of small propeller-driven aircraft. Through a detailed methodology, a twin-engine propeller-driven aircraft is analyzed as a case study, providing insights into the proposed approach. Two critical analyses are presented: an examination of propeller effects in rigid aircraft and the incorporation of elastic wing properties. The former establishes a foundational understanding of aerodynamic behaviour, while the latter explores the impact of wing elasticity on performance. Validation is achieved through comparative analysis with wind tunnel test results from a similar rigid structure aircraft. Utilizing NASTRAN software, aerodynamic analysis of the elastic aircraft is conducted, complemented by semi-empirical insights. The results highlight the importance of these factors across different angles of attack. Furthermore, deviations from the rigid aircraft configuration emphasize the considerable influence of static aeroelasticity analysis, notably increasing longitudinal characteristics by approximately 20%, while showing a lower impact of 5% in lateral-directional characteristics. This study contributes to enhanced design and operational considerations for small propeller-driven aircraft, with implications for future research and innovation, particularly for the purpose of efficient concepts in advanced air mobility.

Huntington’s disease (HD) is a rare but progressive and devastating neurodegenerative disease characterized by involuntary movements, cognitive decline, executive dysfunction, and neuropsychiatric conditions such as anxiety and depression. It follows an autosomal dominant inheritance pattern. Thus, a child who has a parent with the mutated huntingtin (mHTT) gene has a 50% chance of developing the disease. Since HTT protein is involved in many critical cellular processes including neurogenesis, brain development, energy metabolism, transcriptional regulation, synaptic activity, vesicle trafficking, cell signaling, and autophagy, its aberrant aggregates lead to disruption of numerous cellular pathways and neurodegeneration. Essential heavy metals are vital at low concentrations, however, at higher concentrations, can exacerbate HD by disrupting the glial-neuronal communication, and/or causing dysbiosis (disturbance in the gut microbiota, GM), both of which can lead to neuroinflammation and further neurodegeneration. Here, we discuss in detail the interactions of iron, manganese and copper with glial-neuron communication and GM and indicate how this knowledge may pave the way for development of a new generation of disease-modifying therapies in HD.

The construction industry, a vital sector of the global economy, is projected to grow significantly over the next 15 years. Despite its importance, this industry struggles with inefficiency, high costs, prolonged timelines, and substantial ecological impacts. These challenges have led governments to advocate for Building Information Modeling (BIM) to enhance Efficiency and sustainability through comprehensive digital representations of physical and functional characteristics. The effective integration of BIM technology hinges on the active participation of industry providers, raising the question of how these providers can positively contribute to improving BIM dimen-sions. This study investigates the potential of coopetition networks within the Portuguese Orna-mental Stone industries (OS-PT) to address this challenge. Coopetition networks, which blend competition and cooperation, foster collaborative networks among companies to enhance their re-sponse to digital supply chains. The research employs an Experimental Pilot Network facilitated by an Industrial Internet of Things (IIoT) artefact to assess the benefits of coopetition networks. The findings demonstrate that transitioning from current practices (CB.P) to coopetition network practices (CN.P) significantly improves operational Efficiency, labour productivity, and sustaina-bility. Specifically, the transition resulted in a 15.6% increase in on-time delivery performance, a 27.38% improvement in labour productivity, and a 21.8% reduction in CO₂ emissions per part produced. These improvements align with Sustainable Development Goals (SDGs) 8, 9, 11, and 13, highlighting the strategic value of coopetition in driving innovation and sustainability in the construction industry. Future research should explore the scalability of these findings across different sectors and further refine methodologies to maximize the benefits of coopetition net-works.

Utilizing lignocellulosic biosourced platforms, we synthesized novel cyanostilbene (CS) deriva-tives featuring the 3,4-dimethoxyphenyl moiety. These derivatives were investigated for their emission properties in both solution and solid states. The two simple CS derivatives exhibit very weak luminescence in solution but significant luminescence in the solid state, indicating distinct Aggregation-Induced Emission (AIE) characteristic. Furthermore, combining these two CS units, without conjugation and with quasi perpendicular orientation, results in Dual-State Emission (DSE) fluorophore showing luminescence both in solution and solid states. X-ray crys-tallography studies on the solid-state compounds reveal a structure-emission relationship, demonstrating that the colour emission correlates with the conformations adopted by the mol-ecules in the solid state, which influence the type of stacking.

The use of sustainable energy sources is a feasible alternative for fossil fuel products, which can represent a positive factor to alleviate many current environmental issues. In that sense, not only the sustainable industrial development is important, but also sustainable practices at local level, including households. Specifically, heating and cooking are one of the most important activities that require energy in households, where the role of biomass could be interesting, as it can provide an energy source with lower environmental impact. However, there is room for improvement in biomass stoves, whose adaptability to specific wastes, as well as their improvement in efficiency, should be accomplished. The aim of this work was to assess the improvement of combustion performance of a domestic stove by the implementation of a programmable logic converter for a better adaptation to different biomass samples (holm oak, pear tree, poplar and sugarcane bagasse pellets). Thus, the working regime of the stove was controlled, especially concerning the screw conveyor (to regulate pellet feeding) and flue gas fan (to change oxygen supply). As a result, better combustion performances were obtained, heat capacities from 5.66 to 8.67 kW for the selected samples. On the other hand, different improvements of the combustion stove to avoid blockages, for instance, are proposed as further steps.

Data integrity and security are among the most essential things in this digital era performance. Digital certificates can be one solution to this problem. This research will develop the architecture of digital certificate verification and validation using blockchain. The blockchain concept for digital certificates uses three stages: requirements planning, workshop design, and implementation. Digital certificate files will be tested based on a scenario in which there could be any changes to those files, such as compressing files, changing data of files, inserting images in the file, and rotating files. This system architecture will detect any changes that could occur to the digital certificate file by using a digital signature, Keccak256 hash algorithm, and blockchain. This research shows that change detection accuracy for digital certificate files is 100%. However, there is a digital signature nature that could reduce the accuracy of change detection, and several solutions can be resolved. The average time to generate a signature using blockchain technology is 2.11 seconds, faster than 3.23 seconds when it does not use blockchain. The average time to validate a signature is 2.11 seconds without using blockchain, which is reduced to 0.22 seconds using blockchain technology. This research concludes that the architecture for digital certificate verification and validation using blockchain technology has successfully improved the security of digital certificates. Testing showed that even minor changes to a digital certificate could affect the signature, ensuring the certificate's integrity. For further research, evaluating the performance of various hash algorithms within the blockchain network is recommended.

Wound healing is a complex, dynamic process involving the coordinated interaction of diverse cell types, growth factors, cytokines, and extracellular matrix components. Despite emerging evidence highlighting their importance, dermal sheath cells remain a largely overlooked aspect of wound healing research. This review explores the multifunctional roles of dermal sheath cells in various phases of wound healing, including modulating inflammation, aiding in proliferation, and contributing to extracellular matrix remodeling. Special attention is devoted to the paracrine effects of dermal sheath cells and their role in fibrosis, highlighting their potential in improving healing outcomes, especially in differentiating between hairy and non-hairy skin sites. By drawing connections between dermal sheath cells activity and wound healing outcomes, this work proposes new insights into the mechanisms of tissue regeneration and repair, marking a step forward in our understanding of wound healing processes.

Using the limits of a specific watershed (river basin) to establish boundaries of precise rural and urban intervention strategies, can conduce to a better understanding of the dynamics between natural hydro-morphology of a hydrological region, water infrastructures (damns, canals, reservoirs) and urban and rural fabric. To perform watershed-based planning approaches with valuable indicators is necessary to generate hybrid cartographies combining urban, architectural, agricultural and hydrological boundaries. In some countries, the necessary information to produce these cartographies is not available; however, is possible to create fundamental layers using GIS software and national geospatial information and subsequently perform algorithmic calculations in the same software. Once these cartographies are developed and analyzed for a determined basin is possible to observe scenarios where rural and urban planning are better suited for precise hydric-urban restoration. In the following article a series of hybrid cartographies are presented. These types of maps are useful for interpretation of water usage flow in rural communities and their agricultural productive surfaces, and ultimately for analytical purposes in dealing with hydrological alterations of the water cycle. The diagnostic results can be used to develop specific rural interventions for fluvial restoration in territorial contexts, and improvement on hydrological infrastructure and the hydrological region water network.

The proposed method deals with the problem of data privacy and sharing when processing personal mobility tracking data. Previous methods concentrate on producing highly detailed data on short-term and restricted areas, e.g. for autonomous driving scenarios. Another possibility consists of city-wide scales and beyond, that are used to predict general traffic flows. The presented approach takes the tracked mobility behavior of individuals to create coherent new mobility data that reflects the long-term mobility behavior of the person, guaranteeing location persistency and sound embedding within the point-of-interest structure of the observed area. After an analysis and clustering step with the original data, the area is distributed into a geospatial grid structure (H3 is used here), and the neighborhood relationships between the grids are interpreted as a graph. A feed-forward-autoencoder and a graph encoding-decoding network generate a latent space representation of the area. The original clustered data is associated with their respective H3 grids. With a greedy algorithm approach and concerning privacy strategies, new combinations of grids are top-level patterns for individual mobility behavior. Concrete locations are found and connected within the grids based on the original data. The described method is then applied to a study with 1000 participants from the city of Munich in Germany, and the results are described, showing the application of the approach in generating synthetic data, enabling further research on individual mobility behavior and patterns. The result is a sharable dataset on the same abstraction level as the input data, which makes it interesting, particularly for machine learning applications.

Antibiotic-loaded bone cement (ALBC) plays a pivotal role in infection prevention and treatment related to musculoskeletal surgery. The release efficacy of antibiotics from ALBC is closely tied to its surface area, yet little is known about the effective release depth. To investigate the relationship between surface area, volume, and antibiotic elution, spheric ALBC specimens with consistent outer diameters but different internal metal sphere diameters were prepared. Two vancomycin doses were utilized in ALBC specimens with an outer diameter of 35 mm: high (4 g) and low (1 g). Each dosage group included five specimens containing embedded metal spheres with diameters of 15, 25, 29, 32, or 33 mm. The resulting shell-like ALBC specimens had thicknesses of 10 mm, 5 mm, 3 mm, 1.5 mm, or 1 mm, respectively. The specimens were immersed in sterile phosphate buffer solution, and antibiotic elution was measured at designated sampling times (1, 3, 6, 10, 24, 48, 72, and 168 hours). Methylene blue was employed to visualize penetration depth. Vancomycin elution did not display statistically significant differences between high- and low-dose groups. In both groups, specimens with 1 mm thickness exhibited a higher vancomycin release efficiency (high-dose group: 18560±5474 μg, 6.7%; low-dose group: 2017±419 μg, 2.6%), decreasing sharply in thicker ALBC specimens. Methylene blue penetration depth showed no apparent difference between high-dose and low-dose groups. ALBC thickness does not significantly impact antibiotic elution, while surface area and antibiotic dose exert notable effects. These in vitro findings offer potential applications in clinical treatments for musculoskeletal infections.

Expression of the breast cancer resistance protein (BCRP/ ABCG2) transporter is downregulated in placentas from women with preeclampsia (PE) and in an immunological rat model of PE, which closely resembles human PE. While many drugs are substrates of this important efflux transporter, the impact of BCRP downregulation on maternal and fetal drug exposure has not been investigated. Using the PE rat model, we performed a pharmacokinetic study with rosuvastatin (RSV), a BCRP substrate, to investigate this impact. PE was induced in rats during gestational days (GD) 13 to 16 with daily low-dose endotoxin. On GD18, RSV (3 mg/kg) was administrated intravenously, and rats were sacrificed at time intervals between 0.5-6 hours. Placental expression of Bcrp and Oatp2b1 significantly decreased in PE rats. A corresponding increase in RSV levels was seen in fetal tissues and amniotic fluid of the PE group (p<0.05), while maternal plasma concentrations remained unchanged. An increase in Bcrp expression and decreased RSV concentration, was seen in the livers of PE dams. This suggests that PE-mediated transporter dysregulation leads to significant changes in the maternal and fetal RSV disposition. Overall, our findings demonstrate that altered placental expression of transporters in PE can increase fetal accumulation of their substrates.

The extraction of cell cultures from fresh tissue is a process that requires significant computa-tional resources and is associated with substantial overheads. The objective of our research is to de-vise a rapid, straightforward, and efficient technique for the cultivation of neuronal cells derived from frozen biological material. We utilized freshly isolated hippocampus and cerebral cortex tissue from rats, in addition to whole brain tissue. This tissue underwent digestion and processing to yield a cellular suspension. This suspension was subsequently cryopreserved using a variety of cryopro-tectants: CTS™ Synth-a-Freeze™, SpermFreeze®, and a medium supplemented with 10% DMSO. CTS™ Synth-a-Freeze™ is a commercially available cryoprotectant typically employed in the preservation of cellular cultures, while the addition of 10% DMSO to the medium is a conventional technique for the cryopreservation of cells to mitigate damage. The innovative aspect of our meth-odology is the application of SpermFreeze®, a product used for the cryopreservation of sperm in in vitro clinics. We postulated that SpermFreeze® might enhance the viability and quality of the cryo-preserved neuronal cells, given the delicate and energetically demanding nature of both sperm and neuronal cells. The ultimate objective was to ascertain whether a cryoprotectant formulated for sperm could augment the post-thawing efficacy of our nervous system cells. This investigation intro-duces an innovative methodology for the optimization of neuronal cell isolation and cryopreserva-tion from animal-derived tissues.

A model of space-time is presented, whose origin is set before the appearance of any universe. It uses concepts of previous work, a central one being that the information about the laws of nature is stored locally everywhere in space such that all physical processes obey them. Since information storage is bound to matter or energy, space is assumed to consist of dark energy (DE), which thus assumes an importance far beyond its function as a stopgap for an energy deficit in our universe ( U ). The primordial state (PS) is a timeless and relatively large space of 3 dimensions described by a Wheeler DeWitt (WDW) equation, whose solution is interpreted as an arrangement of very many space quanta and possesses properties that remind of the time-honored concept of the unmoved mover. The comparison of WDW solutions belonging to different mass densities of the DE favors one in which the space quanta are mini black holes. This allows the space quanta to be imagined as mass points which are kept at a distance compatible with the quantum volume by the Pauli principle or something equivalent. Triggered by a dramatic increase in probability, the PS is followed by a time-controlled sequence of quantized expansion states (ES i ). The concomitant emergence of time occurs in a lightning huge crash, consuming almost all DE of the PS. The subsequent quantized ES i emerge from a WDW equation, novelly derived from a solution of the modified cosmic momentum equation, which classically describes an exponential space expansion (CS). The huge volme of the ES i is also used as size of the PS. Information is assumed to be geometrically stored in arrangements of space quanta similar to how genetic information is stored in DNA molecules. During the CS information must be transferred from already existing "information quanta" to new ones. This requires time, slows down the expansion and is taken into account by a friction term in the cosmological momentum equation thus modified. Since the Friedmann-Lemaître (FL) equation remains fully valid, the model is widely based on recognized equations, so that some results may be understood as interpretations.

To explore the effect of lily polysaccharide (LP) on immune function and intestinal flora in immunosuppressive mice.The immunosuppressive model was established by intraperitoneal injection of cyclophosphamide (CTX) in mice, and the immunological indexes were measured. The cecal contents of mice were taken, and the DNA of intestinal flora was extracted for 16S DNA sequence analysis.Compared with CTX group, the body weight and thymus index of mice in each treatment group increased significantly, the liver index decreased significantly,the hepatocyte morphology, liver plate and hepatic sinus arrangement of mice in high and low concentration LP groups were relieved in varying degrees, and the contents of IgA and IgG in serum of mice in low concentration LP group and positive control group increased significantly; The contents of TNF-α and IL-6 in colon decreased, while the contents of IL-10 increased significantly. The contents of AST, ALT and MDA in liver decreased significantly, while the content of SOD increased significantly. Compared with the blank group, LP can improve the intestinal flora of immunosuppressive mice , mainly by increasing the abundance of beneficial bacteria such as s24-7, Bacteroides and butyrimionas and reducing the abundance of harmful bacteria such as Prevotella, dorea and adlercreutzia.

A pathway frequently altered in cancer is glutaminolysis where glutaminase (GA) catalyses the main step: the deamidation of glutamine to form glutamate and ammonium. There are two types of GA isozymes, named GLS and GLS2, which differ considerably in their expression patterns and can even perform opposing roles in cancer. GLS correlates with tumor growth and proliferation, while GLS2 may function as a context-dependent tumor suppressor. However, both isoenzymes have been described as essential molecules handling oxidant stress because of their involvement in glutathione production. We have reviewed the literature to highlight the critical roles of GLS and GLS2 to restrain ROS and regulate both cellular signaling and metabolic stress due to their function as indirect antioxidant enzymes and also by modulating both reductive carboxylation and ferroptosis. Blocking GA activity appears to be a potential strategy to dual activate ferroptosis and inhibit cancer cell growth in a ROS-mediated mechanism.

This work presents a historical-epistemological analysis of the foundations of quantum mechanics. From a philosophical point of view, the relationships between quantum mechanics and scientific realism are highlighted, as well as the influence of the neo-positivist philosophy of the first decades of the 20th century. The great significance of measurement in the context of quantum mechanics is underlined, as an essential element in providing a coherent description of reality moving from the microcosm to the macrocosm, as well as the role that the measurement apparatus and the consciousness of the observer assume during the act of measurement, the ontological problem, the problem of the objectification of the wave function and the problem of the definition of discernibility. This is followed by an overview of the most important alternative proposals to the standard interpretation (Copenhagen interpretation), with particular reference to hidden variable theories, and other alternatives to standard quantum mechanics that profoundly modify the vision of reality, such as the Everett’s many-worlds theory, the QBism, the unified holistic approach.

Aiming at the problem of small size of some spots on apple leaves and the difficulty of accurate detection of spot targets brought by the complex background of the orchard, this paper takes the alternaria leaf spot, rust, brown spot, grey spot and frog eye leaf spot on apple leaves as the research object, and proposes a high-accuracy detection model YOLOv5-Res and lightweight detection model YOLOv5-Res4 are proposed. Firstly, a multiscale feature extraction module ResBlock is designed by combining the Inception multi-branch structure and ResNet residual idea. Secondly, a lightweight feature fusion module C4 is designed to reduce the number of model parameters while improving the detection ability of small targets. Finally, a parameter streamlining strategy based on optimized model architecture is proposed. The experimental results show that the performance of YOLOv5-Res model and YOLOv5-Res4 model is significantly improved, the [email protected] value is improved by 2.8% and 2.2% compared with YOLOv5s model and YOLOv5n model, respectively, and the size of YOLOv5-Res model and YOLOv5-Res4 model is only 10.8MB and 2.4MB, and the number of model parameters is reduced compared with YOLOv5s model and YOLOv5n model. counts are reduced by 22% and 38.3% compared to the YOLOv5s model and YOLOv5n model.

Abstract Background: Atrazine, a widely used herbicide, is recognized for its potential endocrine-disrupting effects, though its direct link to diabetes has not been extensively studied. Objectives: This study investigates the relationship between atrazine exposure and diabetes incidence, especially in agricultural settings, and examines how socioeconomic factors like income and education levels influence diabetes risk. Methods: A retrospective cohort study was conducted using data from 67 counties in Pennsylvania from 2011 to 2019. Atrazine exposure was measured in local water sources and correlated with diabetes data from the Pennsylvania Behavioral Risk Factor Surveillance System (BRFSS). Socioeconomic data were sourced from U.S. Census Bureau records, with logistic regression used to adjust for confounders such as age, race, and lifestyle. Results: Findings showed a significant association between high atrazine exposure and increased diabetes incidence, even after adjusting for confounders. Discussion and Conclusion: The study highlights a significant health risk posed by atrazine, particularly for socioeconomically disadvantaged groups. It underscores the need for stricter atrazine regulation and public health interventions to mitigate its impact. Further research is crucial to understand how atrazine affects glucose metabolism and diabetes development. Implementing stricter environmental controls and educational initiatives could reduce the diabetes burden in impacted communities.

From an industrial point of view, the milling of 2.5D cavities is a frequent operation, 1 consuming time and presenting optimization potential, especially through a judicious choice of 2 the tool trajectory. Among the different types of trajectories, some have a general spiral-like aspect 3 and can potentially offer a reduced machining time. They are called curvilinear trajectories and are 4 obtained by interpolation between structure curves which are the numerical solutions of a partial 5 differential equation. In this case, the machine tool will connect points and the trajectory will be made 6 up of small segments. Even if, macroscopically, these trajectories have all the qualities to allow the 7 tool to move quickly, on a small scale, the discontinuities in tangency, inherent in the discretization, 8 significantly increase machining time. This article suggests to enhancing the continuity level of the 9 toolpath by rebuilding structure curves with a set of Hermite quartic spline patches connected in 10 tangency and curvature. Thanks to this, the tool will machine at an average feedrate closer to the 11 programmed one and will, de facto, reduce traveling time. 12 This article shows that the proposed method increases, on the two tested cavities, toolpath quality 13 indicators, reduces milling time from 10% to 18% for a curvilinear method without a filter and make 14 it possible to generalize the Bieterman and Sandström method for all non convex pockets.

This study, serving as Part-2 of the research titled "Comparative Analysis of Length Deformation in Classical and Relativistic Mechanics," investigates the behaviour of matter within gravitationally bound systems. Through meticulous examination of projected length alterations, the research highlights differences between classical and relativistic mechanics frameworks, emphasizing the necessity of considering relativistic effects beyond velocity alone. Additionally, the study underscores the crucial role of gravitational effects on the effective mass of moving objects, which emerges as a critical factor in predicting length deformation across scientific disciplines. The incomplete treatment of relativistic effects within Relativistic Mechanics, including acceleration and material stiffness, emphasizes the importance of comprehensively understanding gravitational influences on effective mass. This is evident in gravitational equations, where the gravitational force depends not only on the object's mass but also on its effective mass, influenced by kinetic energy. Thus, incorporating the gravitational effect on effective mass enhances the understanding of length deformation phenomena within gravitationally bound systems, enriching scientific discourse.

The genus Strophantus belongs to the Apocynaceae family of flowering plants which grows primarily in tropical Africa. The plants are widely used in traditional herbal medicine. S. sarmentosus, in particular, is used for the treatment of, e.g., joint pain and rheumatoid arthritis, wound infections, head lice, diarrhoea, snake bite, and eye conditions. Despite the widespread use, dedicated research characterizing bioactive plant components is scarce. Investigations focussed mainly on the cardenolides, because of their cardioactivity and historical use as cardiotonic. There are also studies concerning the antibacterial, antioxidant and anti-inflammatory activity of plant extracts. This review summarizes the present knowledge about the biochemical and analytical reserach on Strophantus, in general, and S. sarmentosus, in particular, and describes the current state-of-the-field based on the available sientific literature.

Background: Localization of acute appendicitis in a hernia sac is a rare phenomenon with a frequency of around 0.08 - 1 %. Even fewer cases of postoperative hernias with a vermiform appendix in the hernia sac have been described. We selected 23 cases in the English literature describing this phenomenon and analyzed diagnostic and treatment options. Case presentation: We present a 72-year-old woman who was complaining of a painful, rigid mass in the anterior abdomen wall for two days. After performing an ultrasound, incarcerated ventral hernia was diagnosed and emergency surgery was performed. During the surgery, gangrenous appendicitis was found in the hernia sac. It was decided to do an appendectomy and primal hernioplasty. Postoperative period was uneventful. Conclusion: Appendicitis within incisional hernia is an extremely rare phenomenon. Diagnosis may be challenging because of dominating incarcerated hernia symptoms. However, computed tomography might play a crucial role, by differentiating causes of acute abdomen. Appendectomy is the standard option for appendicitis treatment, however, there is no consensus on how abdominal wall integrity should be restored.

Wellbeing is a multifaceted concept that involves various facets of human condition and experience, including individual and communal spiritual, emotional, intellectual, physical, and social dimensions. To explore the complex facets of sustainable wellbeing, this study utilized an interpretive qualitative research approach, looking at round table (focus group) discussion data obtained from a diverse group of public and private sector representatives, including education, government, non-governmental organizations, and businesses in Qatar. The purpose of this study was to gain a contextualized understanding of how participants perceive and experience wellbeing. A purposive sampling technique was employed to recruit participants representing different sectors of society. To elicit participants’ perspectives on wellbeing, thematic analysis was used to identify recurring themes and patterns that emerged from the focus groups, viewed through the lens of Bronfenbrenner’ Ecological Systems Theory. Findings reveal that wellbeing is a very personal and subjective experience. Key themes extracted from the data include challenges to sustainable wellbeing in Qatar, including technological disruptions and socio-cultural influences. These challenges require proactive measures that reflect educational priorities, promote cultural preservation, and foster resilient communities while emphasizing individual and collective sustainable wellbeing. This research also identified opportunities for enhancing sustainable wellbeing in Qatar.

This article is an early draft on a proposed alternative to the current Marxist mode of thought; one that seeks to reject the generally ill-conceived and dogmatic proposals formulated by Marx in favour of another predicated on the more unwavering emotional ideals of the philosophy that preceded it. It eliminates that dogmatic mode in favour of a wholly social society, one that is founded upon the Marxist superstructure and intends hence to capture that humanity and re-form particularly economic principles that are used to construct the utopia into what is instead an entirely socially idealised frame of living.

Reducing waiting times is crucial for ports to be efficient and competitive. Important causes of waiting times are cascading interactions between realistic hydrodynamics, accessibility policies, vessel-priority rules, and detailed berth availability. The main challenges are determining the cause of waiting and finding rational solutions to reduce waiting time. In this study, we focus on the role of the design depth of a channel on the waiting times. We quantify the performance of channel depth for a representative fleet rather than the common approach of a single normative design vessel. It relies on a mesoscale agent-based discrete-event model that can take processed Automatic Identification System and hydrodynamic data as its main input. The presented method’s validity is assessed by hindcasting one year of observed anchorage area laytimes for a liquid bulk terminal in the Port of Rotterdam. The hindcast demonstrates that the method predicts the causes of 73.4% of the non-excessive laytimes of vessels, thereby correctly modelling 60.7% of the vessels-of-call. Following a recent deepening of the access channel, cascading waiting times due to tidal restrictions were found to be limited. Nonetheless, the importance of our approach is demonstrated by testing alternative maintained bed level designs, revealing the method’s potential to support rational decision-making in coastal zones.

Background: In the landscape of thoracic surgery, innovation continually drives progress, offering novel approaches to address complex pathologies while prioritizing patient well-being. Dual-portal robotic-assisted thoracic surgery DRATS represents the next frontier in this evolution. In this report we describe our experience with the DRATS approach for segmentectomy with the indocyanine green intersegmental plane identification. Methods: We presented the case of a patient who underwent a DRATS lingulectomy and lymphadenectomy stations 5, 6, 7, and 10 using the daVinci Surgical System. Results: The patient's postoperative course was uneventful with chest tube was removed in second post operative day. The final pathological analysis confirmed a low-grade malignant potential adenocarcinoma, with main diameter of 1.1 cm, at 3 cm from lung margins. 12 nodes were removed, from station 5,6,7,10,11, all of the free of metastases. Conclusions: Our initial observations suggest that Dual-Portal Robotic-Assisted Tho-racic Surgery (DRATS) demonstrates notable feasibility.

Cold chains are essential in providing us humans with food and medicine across the globe. However, cold transportation, like all transportation, has massive negative impacts on the environment and human well-being, which especially culminate in cities. Thus, it is important to research the ways to reduce these impacts and reinvent urban logistics infrastructure. In this article, we articulate the massive problems the road-based transportation sector imposes on the environment and on the health of humans, especially in cities. We present algorithms that show promise in optimizing the whole road transportation sector as well as some innovations and alternative ways to model cities and the whole urban transportation infrastructure. We approach the issues discussed specifically from the point of view of refrigerated transportation, but many of the solutions can be applied to all the transportation sector in general.

This study aims to analyze various types of pellet fuels used as energy sources in Bulgaria, focusing on their energy characteristics and the consumer preferences. Both standard and specialized methods such as thermogravimetry (TG) and differential scanning calorimetry (DSC) are used for the analyses. The results from TG and DSC indicate that during the drying of the samples, moisture is evaporated from their surface, along with the release of volatile substances. The processes during the analysis are accompanied by energy absorption, with the main stage being combustion, where the primary amount of heat is generated. Standard analysis methods show that wood pellets usually contain about 7.31% moisture, 0.72% ash and have a calorific value of 18.33 kJ/kg, while sunflower pellets contain about 7.62% moisture, 2.42% ash and have a calorific value of 19.63 kJ/kg. Mixed pellets contain about 7.07% moisture, up to 0.69% ash and have a calorific value of 18.05 kJ/kg. A specialized marketing research was conducted to investigate consumer attitudes and preferences toward purchasing different types of solid biomass fuels on Bulgarian market. This study provides information on the quality of pellets as fuel by offering a detailed analysis of their fuel properties and ensuring their effective utilization as an energy source.

Due to the rapid growth of the Internet of Things (IoT), securing communications between a huge number of devices has become very difficult. Access controls and authentication secure the connection between IoT devices and protect sensitive data from unauthorized users or malicious attackers. In this paper, we provide a comprehensive review to emphasize the critical role of authentication and access control in securing IoT environments. This paper explores different types of access controls, like Attribute-Based Access Control and Role-Based Access Control. Furthermore, it demonstrates different authentication techniques, like passwords and biometrics. Based on the previous mechanisms, we discuss different IoT security challenges regarding authentication and access control mechanisms and highlight future directions. In addition, this paper investigates the integration between access control and authentication to safeguard IoT communications.

(1) Background: Since microplastics in the aquatic environment are difficult to prevent and can cause adverse physiological and biochemical reactions to various organisms, we aimed to analyze the effectiveness of an eco-friendly removal method using aquatic plants with high ornamental value and excellent water purification ability. (2) Methods: Iris pseudacorus and Lythrum anceps were planted in tap water contaminated with microplastics to analyze the removal rate and root adsorption of microplastics. (3) Results: The amount of microplastics in the planting boxes of Iris pseudacorus and Lythrum anceps was significantly reduced, and the adsorption of microplastics on the roots was confirmed. (4) Conclusions: It was found that the removal of microplastics in water by aquatic plants is effective and that microplastic pollution does not significantly affect plant growth. However, the removal of microplastics by adsorption on plant roots may be affected by various environmental factors, so it is necessary to consider various limitations.

Providing user confidence in Mobile Government Services (MGS) is essential for the success of mobile government. This study aimed to test the moderating role of techno-skepticism in the impact of crisis management on mobile government. Some scholars have stated that government investment in mobile government services for public administration during the financial crisis is a critical issue for crisis management. In the constantly evolving and changing world, the rapid advancement of technology in modern societies has prompted an acceleration in investments in information and communication technologies. However, due to several inadequacies, citizens seem to respond negatively to the use of certain public technological services, leading them to develop a perspective of techno-skepticism. This issue has been cited in numerous scholarly studies as a critical subject for the effective implementation of technological innovations. The effectiveness of digital technology in the procurement of public services is highly dependent on the perceptions and behaviors of users. In this context, this study measured the attitudes of the participants and the connections between techno-skepticism, mobile government use, and crisis management among Northern Cyprus residents over 18 years old. The study employed a quantitative approach. A 5-point Likert scale was used to collect data by modifying the survey questions to fit the scope of the study. The study participants were selected using the random sampling method to acquire data from a total of 402 citizens. The study findings revealed that techno-skepticism mediates the impact of crisis management on mobile government. As a result, techno-skepticism is a critical and decisive factor in citizens’ mobile government use, affecting its utilization frequency. Techno-skepticism was also found to play a vital role in mobile government use. The current study represents a pioneering effort in testing the moderating role of techno-skepticism in the impact of crisis management on mobile government. It also provides various contributions to theory and practice, particularly in the fields of mobile government and the use of digital technologies.

Receptor-interacting protein kinase 1 (RIPK1) plays a crucial role in controlling inflammation and cell death. Its function is tightly controlled through post-translational modifications, enabling its dynamic switch between promoting cell survival and triggering cell death. Phosphorylation of RIPK1 at various sites serves as a critical mechanism for regulating its activity, exerting either activating or inhibitory effects. Perturbations in RIPK1 phosphorylation status have profound implications for the development of severe inflammatory diseases in humans. This review explores the intricate regulation of RIPK1 phosphorylation and dephosphorylation and highlights the potential of targeting RIPK1 phosphorylation as a promising therapeutic strategy for mitigating human diseases.

In a constantly changing environment brought about by the climate crisis and escalated anthropogenic perturbations driven by the growing population, harmful algal bloom dynamics and their impacts are expected to shift, necessitating adaptive management strategies and comprehensive research efforts. Similar to primary productivity, HABs have been thought to be driven primarily by major nutrients such as N, P, and Si. However, recent investigations on the role and importance of micronutrients as limiting factors in aquatic environments have been highlighted. This paper provides a review of metal and phytoplankton interactions, with a specific emphasis on pertinent information on the influence of trace nutrients on growth, toxin production, and other underlying mechanisms related to the dynamics of HABs. Low to near-depleted levels of essential nutrients including Fe, Cu, Zn, Se, Mn, Co, and Mo, negatively impact cell growth and proliferation of various marine and freshwater HAB species. However, evidence shows that at elevated levels, these trace elements along with other non-essential ones, could still cause toxic effects to certain HAB species manifested by decreased photosynthetic activities, oxidative stress, ultrastructure damage, and cyst formation. Interestingly, while elevated levels of these metals mostly result in increased toxin production, Co (i.e., yessotoxins, gymnodimine, and palytoxins) and Mn (i.e., isodomoic acid, okadaic and diol esters) enrichments revealed otherwise. In addition to toxin production, releasing dissolved organic matter (DOM) including dissolved organic carbon (DOC) and humic substances was observed as an adaptation strategy, since these organic compounds have been proven to chelate metals in the water column, thereby reducing metal-induced toxicity. Whilst current research center on free metal toxicity of specific essential elements such as in Cu and Zn, a comprehensive account of how trace metals contribute to the growth, toxin production, and other metabolic processes under conditions reflective of in-situ scenarios of HAB-prone areas, would yield new perspectives on the roles of trace metals in HABs. With the growing demands of the global population for food security and sustainability, substantial pressure is exerted on the agriculture and aquaculture sector, highlighting the need for effective communication of information regarding the interactions of macro- and micronutrients with HABs to improve existing policies and practices.

Autism has been described as a gastrointestinal and neurological condition that is represented by impairments in language and social situations. Recently reported increases in the occurrence of Autism Spectrum Disorder (ASD) have resulted in increased research into the environmental differences between areas with a high occurrence, as in the “Western” diet populations, and a more locally derived diet population, wherein the rate appears to be significantly less. Thirty autistic children (USA) ages 6 to 21, were sampled at three different intervals: prior to any intervention, post-xylitol intervention, and post-probiotic intervention. The sampling consisted of buccal swabs for MITOSWAB testing, and saliva for metatranscriptomics to determine the entire range of microorganisms and the metabolome. In addition, a “Blue Zone” subject component that included 30 Colombian children, ages 6-16, and who were healthy and within normal behavior standards, also had buccal swabbing and salivary sampling performed for comparison along with 30 healthy (no history medications, illnesses, or behavior issues) USA children matched for age and gender. Saliva samples were analyzed metatranscriptomically and artificial intelligence was utilized to discern important differences in the microbiome that included bacteria, archaea, fungi, and viruses, and microbial functions. Significant differences were noted, and seen in the temporal data, demonstrating shifts that may have been precipitated by the interventions, with both the probiotics and the polyols. Particular bacterial strains were significantly more prevalent in the autism subject group including a strain that reduces neurotransmitters by enzymatic degradation. This provided supporting evidence to the hypothesis that the occurrence of autism may also be influenced by low Gamma Amino Butyric Acid (GABA) levels during development. Also, of interest was the un-expected finding that verbal skills dramatically increased in 6 of the 30 ASD subjects following xylitol supplementation.

Heterodimeric approach has emerged as a promising method for simultaneously targeting multiple receptors on tumor cells using a single molecule. Simultaneous targeting of the prostate-specific membrane antigen (PSMA) and the gastrin-releasing peptide receptor (GRPr) holds the potential to improve the accuracy of prostate cancer diagnosis. This study aimed to develop and compare six alternative routes for stereoselective synthesis of heterobivalent conjugates designed to deliver the chelating agent DOTA to PSMA/GRPr receptors. The comparison of these alternative synthetic approach, considered such factors as efficiency, complexity, synthesis and purification characteristics, as well as yields of the target compounds has been made. Optimal conditions for the stereoselective synthesis of heterobivalent ligands to PSMA and GRP, which could serve as molecular platforms for the targeted delivery of therapeutic and/or diagnostic agents to these receptors, were determined. For synthesized heterobivalent ligand 26^x and heterobivalent conjugate with DOTA 27 complete signal assignment in ¹H, ¹³C, and ¹⁵N NMR spectra was achieved using 2D NMR techniques. Based on these data, comprehensive signal assignments were provided for all final compounds in their NMR spectra.

A beverage made from a combination of Agave sap (AS) and prickly pear juice (PPJ) was ana-lyzed for its nutrients, bioactive and potentially health-promoting compounds. The beverage was evaluated for its ability to act as an antioxidant, regulate glycemic properties, and undergo gut bacterial fermentation in vitro. The major mono- and oligosaccharides present in the beverage were galacturonic acid (217.74±13.46 mg/100 mL), rhamnose (227.00±1.58 mg/100 mL), and fructose (158.16±8.86 mg/mL). The main phenolic compounds identified were protocatechuic acid (440.31±3.06 mg/100 mL) and catechin (359.72±7.56 mg/100 mL). It was observed that the beverage had a low glycemic index (

Background: Galectins are innate immune system regulators, associated with disease progression in cancer. This paper aims to investigate the correlation between mutated cancer-critical genes and galectin levels in breast cancer patients to determine whether galectins and genetic profiles can be used as biomarkers for disease and potential therapy targets. Materials and Methodology: Prisma Health Cancer Institute’s Biorepository provided seventy-one breast cancer patient samples, including all four stages as well as major molecular subtypes and histologies of breast cancer. Hotspot mutation statuses of cancer-critical genes were determined using multiplex PCR in tumor samples from the same patients by Precision Genetics and the University of South Carolina Functional Genomics Core Facility. The galectin levels of patients’ sera were analyzed using enzyme-linked immunosorbent assay (ELISA) to measure the concentrations of galectins-1, -3, and -9. Analysis was performed using JMP software to compare mean and median serum galectin levels between samples with and without specific cancer-critical genes including pooled t-test, Wilcoxon test, ANOVA, Tukey’s range test, and Steel Dwass Method (α=0.05). Results: Our analysis indicates that KIT mutations correlate with elevated serum levels of galectin-1 and -9 in patients with breast cancer. In patients with Luminal A subtype, FLT3 mutation correlates with lower serum galectin-1 and -9 levels and TP53 mutations correlate with higher serum galectin-3 levels. Patients with invasive ductal carcinoma had significantly higher serum galectin-3 levels than patients with ductal carcinoma in situ. Patients with both TP53 and PIK3CA mutations exhibit elevated serum galectin-3 levels, while patients with one or neither mutation show no significant difference in serum galectin-3 levels. In addition, metastatic breast cancer samples were more likely to have KIT or PIK3CA mutation compared to primary breast cancer samples. Conclusion: The relationship between genetic mutations and galectin levels has the potential to identify appropriate candidates for combined therapy, targeting genetic mutations and galectins. Further understanding of the effect of genetic mutations and galectin levels on cancer progression and metastasis could aid in the search for biomarkers for breast cancer diagnosis, disease progression, and prognosis.

In general, during emergencies, healthcare is provided by tents and temporary structures that do not consider the environmental and social impact of the structure as a first term, in favor of swift response. The resultant construction intended as a temporary solution often persists long-term. This paper aims to analyze an alternative and innovative modular structure designed as a transitory solution in emergency and everyday life. In the first part of the paper, the conceptual framework, and the preliminary design for the new approach to basic non-conventional sanitary spaces are described, by investigating the benefits of a safe space as a generator space for care services and community. In the second part, the technological requirements of the system, its energy efficiency, and environmental impact are analyzed.

This proposal advocates using energy states as fundamental units for quantum computer programming. Each programming unit is conceptualized as an energy state, manifested as an essence-unit. The essence-unit, defined as the minimal form encapsulating complete uniqueness or specificity, serves as the cornerstone of this paradigm. This approach allows recording various forms of matter on quantum computers in essence-units representing their energy states. Recording energy states is achieved through the creation of four distinct coherent potentials facilitated by quantum dots or crystals. It is crucial to note that these energy states, embodied in essence-units, cannot be subdivided. The study examines the intricate relationship between similarity, fractals, and uniqueness in quantum dot operations, elucidating their profound implications for information transfer efficiency. Normalized entropy quantifies the charge localization in quantum dot impurities in systems exhibiting distortions. Utilizing N-level recording and entropy-fractal dimension equivalence enables this paper to elucidate the potential of quantum dots in reducing transmission time and modeling complex systems. The proposed methodology represents a significant departure from the current state of quantum computing, offering unprecedented potential for overcoming previously intractable challenges.

Air pollution is a situation that negatively affects the health of humans and all living things in nature and causes financial damage to the environment. In the case of air pollution, harmful and foreign substances in the air reach an amount and density above normal values. Air pollution also causes climate change, which affects global warming. Particulate matter is a harmful substance that harms the health of humans and other living things, causes air pollution, increases radiation, and negatively affects cloud formation. Particulate matter is extremely small solid particles and liquid droplets suspended in the air. PM10, which is less than 10 microns in diameter, is defined as small particles that can remain in the air for a long time and settle in the respiratory tract, damaging the lungs. Many criteria affect PM10 density and changes in density. The main criteria are vehicle traffic and fuel consumption, industrialization, coal, fuel oil and wood-burning heaters, greenhouse gas impact, and unregulated urbanization. It is important to identify the underlying causes of air pollution caused by PM10. In this context, these criteria need to be evaluated to minimize the negative effects of PM10. In the study, monthly average PM10 data between 2019 and 2023 obtained from the Air Monitoring Station in Kocaeli, Türkiye are used. After determining the criteria affecting PM10, the criteria are prioritized with the Intuitionistic Fuzzy AHP (IF-AHP) method by taking expert decision-maker opinions. The proposed decision-making model aims to guide obtaining the important causes of PM10 emission in terms of danger and focusing on these causes. Additionally, PM10 data is analyzed in the context of Covid-19 and a statistical analysis is made. One-way ANOVA is used to evaluate whether there is a significant difference in the average monthly data over the years. Games-Howell test, one of the post-hoc tests, is used for differences between groups (years). The study is important in that it provides a focus on the criteria affecting PM10 with an intuitive fuzzy perspective, along with statistical analysis.

In the realm of educational technology, Data Analytics (DA) is reshaping teaching and learning. This paper investigates the impact of DA on education, specifically comparing Student Information Systems (SIS) and Learning Management Systems (LMS). Data-driven insights from SIS and LMS platforms enable educators to tailor instructional strategies to individual student needs effectively. While SIS manages student data for administrative tasks, LMS offers tools for content delivery and collaboration. Using the strengths of SIS and LMS, educators can optimise teaching and learning experiences, tracking student progress, and fostering collaboration. The comparison emphasises their distinct roles: SIS manages administrative tasks, while LMS focusses on content delivery and collaboration. Using both systems, educators improve the teaching and learning experience, leveraging DA for continuous improvement. In summary, this paper underscores the transformative role of DA in education, framed within the context of comparing the SIS and LMS functionalities. By examining the intersection of data-driven decision making and educational technology, educators are equipped with the tools and knowledge to harness the power of data for meaningful and impactful teaching and learning.

Chlorella vulgaris has considerable promise as a raw material for biofuel production since it has a high productivity per unit area, has a minimum influence on the environment, and does not significantly affect food security. Nevertheless, the low fatty content of their biomass poses a considerable economic obstacle for commercialization. Increasing the amount of biomass and lipids produced by these algae is essential for improving the economic feasibility of using them as biofuel sources. This review highlights the significance of identifying appropriate algal strains, namely those found in local environments, and utilising mutagenesis and genetic engineering techniques to create 'platform strains'. Prior endeavours have primarily concentrated on altering environmental and dietary parameters to enhance the production of biomass and lipids. Here, we review a scientific literature that examines biotechnological approaches and develops methodologies designed to increase lipid production, emphasising the importance of aligning engineering efforts with breakthroughs in DNA manipulation tools. In addition, the review research evaluates the present economic and commercial situation of algal biorefineries, including any related disadvantages. In summary, this thorough research highlights the importance of using creative methods to tackle the intricacies of lipogenesis and enhance the economic viability of producing biofuels from algae.

Evidence is emerging on the role of maternal diet, gut microbiota, and other lifestyle factors in establishing lifelong health and disease, which are determined by trans-generationally inherited epigenetic modifications. Understanding epigenetic mechanisms may help identify novel biomarkers for pregnancy-related exposure, burden, or disease risk. Such biomarkers are essential for developing tools for the early detection of risk factors and exposure levels. It is necessary to establish the exposure threshold to the fetus due to nutrient deficiencies or other environmental factors that can lead to clinically relevant epigenetic changes that modulate disease risks. This narrative review summarizes the latest updates on the roles of maternal nutrients (n-3 fatty acids, polyphenols, vitamins) and gut microbiota on the placental epigenome and its impacts on fetal brain development.

The dynamic nature of international business necessitates a strategic approach to achieve sustainable value creation. This paper supports the hypothesis that understanding institutional constraints and leveraging organizational resources provides the foundation for sustainable value creation during international expansion. These elements provide a solid foundation for firms seeking to expand internationally by enabling them to effectively navigate the complexities of foreign markets. Using the context supplied by Peng (2023), the subsequent sections and subsections delve into critical facets of international expansion, including market integration, the role of entrepreneurial firms, entry strategies, supply chain establishment, multinational strategies, and the impact of global trade and foreign direct investment (FDI).

The work provides insights on the effect of fire on soil processes in Mediterranean-type ecosystems of Cyprus. Soil samples from mountainous sites that were subjected to a summer wildfire and adjacent control samples were collected. Incubations were used to estimate basal respiration and isolate soil CO2 release of heterotrophic microorganisms from autotrophic root respiration and heterotrophic respiration from litter decomposition. Physicochemical properties changes, bacteria community changes using DNA extraction and 16S rRNA gene analysis, and the effects of ash and fresh litter addition were studied to reveal the microbial composition and the post-fire soil function. Laboratory incubation showed that burned soils constantly showed higher microbial respiration rates compared with control unburned areas, even six months after fire. Adding ash to unburned samples increased microbial respiration, suggesting that increased nutrient availability positively corelates with increased release of CO2 from fire-affected soil. Elevated temperatures due to the wildfire exerted significant effects on the composition of soil bacterial community. Nevertheless, the wildfire did not affect the alpha-diversity of soil bacteria. New communities of microorganisms are still able to decompose fresh plant material after fire, but at a slower rate than natural pre-fire populations.

Varicella (chickenpox) is one of the most common infectious diseases in preschool children and can be prevented by immunization. While immunization program promotes higher vaccine coverage, there are still challenges with implementing vaccination programs particularly in low-income countries. Economic barriers can increase inequality in vaccination, which highlights the importance of distributing cost-effective varicella vaccines. Varicella vaccines have been developed with two main Varicella-Zoster Virus (VZV) strains globally: MAV/06 and Oka strains. Most of the vaccines are based on the Oka strain, while MAV/06 strain vaccines were exclusively developed by GC Biopharma. Although more than 30 million doses of MAV/06 vaccines as cost-effective vaccines have been distributed internationally, there is no comprehensive review on safety, immunogenicity, and effectiveness of MAV/06 vaccines in the literature. This paper aims to summarize and present more than 30 years of accumulated evidence from research on safety, immunogenicity, and effectiveness of MAV/06 vaccines. We expect that MAV/06 vaccines as cost-effective varicella vaccines make a significant contribution to improving global public health and health equality in children.

The study of biologically active substances from natural sources shows the prospect of obtaining a new type of antimicrobial agents, highly effective against pathogenic microorganisms and non-toxic to humans. Our study reveals for the first time that Cornu aspersum mucus has the potential to act as a source of antibacterial agents against bacterial pathogens such as Bacillus cereus 1085, Propionibacterium acnes 1897, Salmonella enterica 8691, Enterococcus faecalis 3915, and Enterococcus faecium 8754. Both mucus fractions with MW<20 kDa and MW>20 kDa showed antimicrobial activity and antioxidant properties that’s why they can be turned into an alternative agent to expensive synthetic antibacterial compounds. Using de novo sequencing 16 novel peptides with potential antibacterial activity were identified by in a fraction with MW<20 kDa. The results of electrophoretic and proteomic analysis of mucus fraction with MW >20 kDa presented proteins with potential antibacterial activity highly homologous to hemocyanins, mucus protein Aspernin, lectins, L-amino acid oxidase-like protein, and mucins (mucin-5AC, mucin-5B, mucin-2 and mucin-17). Thanks to the synergistic action of the bioactive components, the mucus fraction with MW > 20 kDa in low concentrations per 8–2 µg/mL showed promising antimicrobial activity against the tested bacteria, comparable to Vancomycin and without unwanted cytotoxic effects against non-target cells. Additionally, C. aspersum mucus fractions were found to have a positive effect on eukaryotic organisms by reducing the levels of intracellular oxidative damage and increasing the antioxidant capacity of the cell. These findings could serve as a basis for the development of a potent non-cytotoxic antibacterial agent to replace conventional antibiotics and avoid the development of antibiotic resistance.

Based on big data and artificial intelligence technology, the judicial big data intelligent service platform provides users with efficient and accurate legal consulting services. It has many functions such as intelligent question and answer, case analysis, and law inquiry. It also analyzes the application value of the intelligent legal consulting service platform in the field of judicial big data. By building an intelligent service platform, the rapid processing and analysis of massive judicial data has been realized, and the efficiency and quality of judicial work have been significantly improved. In addition, it emphasizes the importance of data management and quality control in the application of judicial big data, and puts forward specific measures to strengthen data management and quality control. With the continuous advancement of technology and the expansion of application fields, the platform is expected to achieve deep integration with other legal services, expand new application fields, and provide users with more comprehensive and efficient legal services. At the same time, it points out the problems that need to be paid attention to in the future development, such as data security, privacy protection and so on. Through in-depth analysis and research on judicial big data, the platform can provide strong support for judicial decision-making and promote the improvement of judicial justice and efficiency.

Recent advancements in gut microbiome research have highlighted the complex interplay between gut microbiota and various physiological and pathological processes, showing that gut microbiota plays a vital role in human health and disease. Imbalances in the gut microbiota, known as dysbiosis, have been associated with a range of health conditions, including gastrointestinal disorders, metabolic diseases, etc. In response to these findings, probiotics, prebiotics, synbiotics, and postbiotics have emerged as a promising therapeutic strategy to modulate gut microbiota composition and functionality. This review paper explores the latest research on how gut microbiota impacts host physiology, immune responses, and overall well-being. Furthermore, the paper delves into the therapeutic potential of probiotics, postbiotics, prebiotics, and synbiotics in therapeutic applications and curing various diseases. The paper also addresses the challenges and opportunities in the field, highlighting the need for personalized approaches to probiotic therapy and the importance of considering factors such as strain specificity, dosing, and safety.Overall, this review aims to provide a comprehensive overview of the evolving landscape of gut microbiota and probiotics, prebiotics, synbiotics, and postbiotics as novel therapeutic agents. It underscores the potential of harnessing the gut microbiome to improve health, prevent diseases, and complement traditional medical interventions. As research in this field continues to expand, a deeper understanding of the gut microbiota and probiotics, prebiotics, synbiotics, and postbiotics promises new avenues for preventive and therapeutic healthcare strategies.

The approach to the personal experience and previous ideas about Physical Education of future Primary Education teachers is a starting point of great interest for the teaching of the subject of Didactics of Physical Education. The study aims to investigate these prior beliefs and to verify to what extent this initial perception changes after taking the course on “Didactics of Physical Education”. A concurrent mixed-methods study was conducted, which included two data collection procedures: (1) a pre-experimental design with a single group featuring pre-test and post-test; (2) the analysis of students' autobiographical accounts of their school experience with physical education. The participants were students enrolled in the Bachelor’s degree program in Primary Education at the University of Santiago de Compostela (USC) who undertook the course last year. The results obtained reveal that after taking the subject of Didactics of Physical Education, students give greater value to more positive concepts of learning, socializing, participating, and playing, among others. Similarly, in the post-test, the assessment of concepts such as competitiveness and physical fatigue diminished. In their autobiographical memories, students associate good memories with relationships with classmates and the playful and socializing nature of the subject; and among the bad memories, they highlight the content related to physical performance, competitiveness, and lack of attention to the diversity of students and their individual characteristics.

This paper investigates the influence of sample size and layer height on the elastic modulus of samples 3D printed by fused filament fabrication (FFF). Cubic samples of different sizes from either a stiff thermoplastic polymer (polycarbonate (PC)) or a soft polymer (thermoplastic polyurethane (TPU)) were printed at three different layer heights: 0.1 mm, 0.2 mm, and 0.4 mm. The samples were imaged using micro-computed tomography to visualize porosity and tested under compression. The results indicate that the elastic modulus of TPU varied with sample size, demonstrating size effects due to high porosity. In contrast, PC samples had a low void volume fraction and did not demonstrate statistically significant size effects on the elastic modulus. The variations in elastic modulus due to layer height were statistically significant for both materials. The highest elastic modulus was observed at 0.2 mm layer height for both materials across different sample sizes, which can be attributed to low void volume fractions. The study develops process-structure-property relations for PC and TPU samples manufactured by FFF. It provides new insights into the design guidelines for FFF based on the size effects. The results indicate that variations in mechanical properties due to size effects must be considered during the design stage for TPU to accurately predict the material’s behavior. Additionally, the locations of the printed parts that are subjected to higher loads should be printed closer to the heated print bed due to the lower void volume fraction observed in the section of the samples printed adjacent to the heated print bed.

New multilayer 3D nanocomposite wear-resistant ion-plasma hard and superhard coatings Avinit [(TiN-AlN)(Mo-Cr-V-Si)]_n have been developed.The introduction of additional alloying elements (Mo, Cr, V, Si) into the Ti-Al-N coating composition, which have a high affinity for nitrogen and are capable of forming strong nitride nanoparticles in the Ti-N and Al-N layers.This makes it possible to obtain hard and superhard hardening coatings.The metallographic and tribological studies carried out indicate the prospects of the developed multicomponent multilayer nano- and microstructured Avinit coatings for increasing wear resistance and reducing friction coefficients.This paper is devoted to the development and implementation of Avinit vacuum plasma technologies for strengthening cutting and forming tools to improve tool performance.Production tests of cutting tools with Avinit's developed multilayer wear-resistant ion-plasma coatings in production conditions at many large machine-building enterprises have shown their high efficiency.In serial production, the wear resistance of tools increases by 3 to 30 times, stamps by 5 to 100 times, and parts rubbing against abrasive materials by 10 to 100 times.Avinit's vacuum plasma technologies have been successfully implemented in production in the aggregate and engine building, transport engineering, and power engineering industries.Positive experience in applying multicomponent coatings has been gained not only when applying hardening coatings to manufactured cutting tools, but also after regrinding to regrindable carbide cutting tools from domestic and foreign manufacturers.

Refractive index measurements have been an important task for a long time because that index plays an essential role in describing the optical properties of a material. Many methods have been developed to perform that task. Some of them use interferometry to achieve high precision, however these configurations are complicated. Some measure the critical angle using simple structures, but the accuracy is not satisfactory because it is difficult to judge the exact critical angle with intensity variations. Here we propose several new schemes based on measuring the polarization change in the total internal reflection. The proposed method has the merits of simple structure and easy incident angle determination that gives the maximum phase change. Additionally, it is possible to find the material dispersion by measuring the wavelength dependence of the polarization ellipticity. Some useful formulas relating the refractive index with the maximum phase change are obtained. This work can provide valuable alternatives for index measurement.

Emotion detection holds significant importance in facilitating human-computer interaction, enhancing the depth of engagement. By integrating this capability, we pave the way for forthcoming AI technologies to possess a blend of cognitive and emotional understanding, bridging the divide between machine functionality and human emotional complexity. This progress has the potential to reshape how machines perceive and respond to human emotions, ushering in an era of empathetic and intuitive artificial systems. This paper introduces a novel approach to multimodal emotion recognition, seamlessly integrating speech and text modalities to accurately infer emotional states. Employing CNNs, we meticulously analyze speech using Mel spectrograms, while a BERT-based model processes the textual component, leveraging its bidirectional layers for profound semantic comprehension. The outputs from both modalities are combined using an attention-based fusion mechanism that optimally weighs their contributions. The proposed method undergoes meticulous testing on two distinct datasets: Carnegie Mellon University’s Multimodal Opinion Sentiment and Emotion Intensity (CMU-MOSEI) dataset and the Multimodal Emotion Lines Dataset (MELD). The results demonstrate superior efficacy compared to existing frameworks, achieving an accuracy of 88.4% and an F1-score of 87.9% on the CMU-MOSEI dataset, and a notable weighted accuracy (WA) of 67.81% and a weighted F1 (WF1) score of 66.32% on the MELD dataset. This comprehensive system offers precise emotion detection and introduces several significant advancements in the field.

Diabetic foot is a serious complication that poses significant risks for diabetic people. The resulting reduction in protective sensitivity in the plantar region requires early detection to prevent the imminent ulceration and amputation. The primary method employed for evaluating this sensitivity loss is the 10 g f Semmes-Weinstein monofilament test, commonly used as a first-line procedure. However, the lack of calibration in existing devices often introduces decision errors due to unreliable feedback. In this paper, a new equipment designed to address these limitations and enhance the assessment of the sensitivity loss using the 10 g f monofilament is introduced. The proposed system automates metrological verification and evaluation processes, ensuring accurate and reliable results. Furthermore, it simulates the practitioner’s procedure, serving both as a valuable training tool and a means to provide force-feedback information. An analytical model of the monofilament buckling and deflection is also presented. The obtained results showed that the tested monofilaments had a very high error compared to the 10 g f declared by the manufacturers. It is aimed, by introducing this advanced equipment, to improve the precision and reliability of assessing the sensitivity loss. The integration of automated verification, simulation capabilities, and precise measurements shows great promise for diabetic patients, reducing the likelihood of adverse outcomes such as ulceration and amputation.

The growing demand in industrial and biotechnological settings for more efficient enzymes with enhanced biochemical features, particularly thermostability and thermotolerance, necessitates a timely response. Renowned for their versatility, thermostable enzymes, offer significant promise across a range of applications, including agricultural, medicinal, and biotechnological domains. This comprehensive review summarizes the structural attributes, catalytic mechanisms, and the relationships between structure and function of two major classes of thermostable enzymes: α-amylases and laccases. These enzymes serve as valuable models for understanding the structural basis of protein thermostability. Commercial significance of these enzymes and researchers' interest in further optimization and innovation, this article can greatly contribute to ongoing research on thermostable enzymes and aiding industries in optimizing production processes. It also give insights to the exploration of suitable strategies and factors for enhancing thermostability, resulting in heightened multipronged stability and notable enhancements in the enzymes’ industrial applicability.

The purpose of this paper is to propose a novel transfer learning regularization method based on knowledge distillation. Recently, transfer learning methods have been used in various fields. However, the problems such as knowledge loss still occur during the process of transfer learning to a new target dataset. To solve these problems, there are various regularization methods based on knowledge distillation techniques. In this paper, we propose a transfer learning regularization method based on feature map alignment used in the field of knowledge distillation. The proposed method is composed of two attention based submodules: self-pixel attention (SPA) and global channel attention (GCA). The self-pixel attention submodule utilizes both the feature maps of the source and target models, so that it provides an opportunity to jointly consider the features of the target and the knowledge of the source. The global channel attention submodule determines the importance of channels through all layers, unlike the existing methods that calculate these only within a single layer. Accordingly, transfer learning regularization is performed by considering both the internal of each single layer and the depth of the entire layer. Consequently, the proposed method using both of these submodules showed overall improved classification accuracy than the existing methods in classification experiments on commonly used dataset.

Mild traumatic brain injuries (mTBIs) are highly prevalent and can lead to chronic behavioral and cognitive deficits, often associated with the development of neurodegenerative diseases. The formation of reactive oxygen species (ROS) and oxidative stress have been implicated in mTBI-mediated axonal injury and pathogenesis. However, the underlying mechanisms and contributing factors are not completely understood. In this study, utilizing a murine model of repetitive mTBI (r-mTBI) involving five closed-skull concussions in young adult C57BL/6J mice, we observed a significant elevation of Na+/H+ exchanger protein (NHE1) expression in GFAP+ reactive astrocytes, IBA1+ microglia, and OLIG2+ oligodendrocytes across various brain regions (including the cerebral cortex, corpus callosum, and hippocampus). This elevation was accompanied by astrogliosis, microgliosis and the accumulation of amyloid precursor protein (APP). Concurrently, r-mTBI mice displayed impaired motor learning and spatial memory deficits. However, post-r-mTBI administration of a potent NHE1 inhibitor, HOE642, attenuated locomotor and cognitive functional deficits as well as gliosis, oxidative stress, axonal damage, and white matter damage. These findings underscore the role of NHE1 upregulation in r-mTBI-induced oxidative stress, axonal damage, and gliosis, suggesting NHE1 as a promising therapeutic target to alleviate mTBI-induced injuries and restore neurological function.

Based on the traditional Chinese cultural belief of "male breadwinner, female homemaker," as well as the systemic and interactive characteristics of families, this study aims to explore the influence of maternal gatekeeping behavior on the quality and quantity of paternal parenting, as well as adolescent aggressive behavior. A total of 483 seventh-grade students completed questionnaires on maternal gatekeeping behavior, paternal involvement, parenting styles and aggressive behavior. Latent profile analysis identified four parenting combinations: positive, negative, mixed, and neglectful. Adolescents under negative parenting exhibited the highest aggression, while those under positive and neglectful parenting showed the least aggression. Maternal gatekeeping behavior correlated with paternal negative parenting and adolescent aggression. Paternal negative parenting mediated the relationship between maternal gatekeeping and aggression, while paternal involvement moderated this relationship. These findings highlight the role of parental interaction in adolescent behavior and support family-based interventions.

The COVID-19 pandemic remains a serious public health problem globally. During winter flu seasons, more aggressive SARS-CoV-2 infections with fatalities have been documented, indicating that influenza co-infections may significantly impact the disease outcome of COVID-19. Both influenza and SARS-CoV-2 viruses share many similarities in their transmission and cellular tropism for their replication in the human respiratory tract. However, it is still unclear how the two pathogens interplay to ensure their survival in the same lung microenvironment. In addition, clinical studies on influenza co-infections in COVID-19 patients do not provide conclusive evidence on how influenza co-infection mechanistically modifies the disease outcome in COVID-19. This mini-review discusses various viral as well as host factors that potentially influence the survival or synergism of these two respiratory pathogens in the infected lung microenvironment.

Under the background that the international technological innovation environment VUCA has been intensifying and the innovation situation of Chinese manufacturing enterprises has been impacted, the innovation dilemma faced by enterprises has attracted increasing attention, while the innovation dilemma is also one of the important factors affecting the operation efficiency of enterprises. Based on the micro-data of China’s A-share manufacturing listed enterprises, this paper empirically analyzes the impact of innovation dilemmas faced by enterprises on operational efficiency (innovation dilemmas are measured by the difference when actual innovation performance is lower than expected innovation performance). The results show that the innovation dilemma of manufacturing enterprises significantly inhibits the operational efficiency of manufacturing enterprises by reducing their risk tolerance, development ability expectation and profitability. After using a series of tests, such as instrumental variable method, propensity score matching method, DID (Differences-in-Differences) and changing variable measure method, the conclusion is still robust. In addition, the inhibitory effect of innovation dilemma on enterprise operation efficiency is more obvious for private enterprises, small and medium-sized enterprises, enterprises in the ascend or decline phase, high-tech enterprises and enterprises in the eastern region. Therefore, the government should strengthen the policy support for the manufacturing enterprises in the innovation dilemma, help the enterprises to overcome the innovation bottleneck. Manufacturing enterprises themselves should enhance their innovation capabilities and strive to get rid of the innovation dilemma in order to maintain a stable footing in the fierce market competition and improve the high-quality development of China’s manufacturing industry.

The tailoring of the surface properties of cellulose nanocrystals (CNCs) to meet various requirements in environmental, food, and material areas has always been of great interest. In this study, the surface chemistry of CNCs was noncovalently modified by cetyltrimethylammonium bromide (CTAB), followed by characterizations and an application as a coating material for interfacial interaction investigation over various substrates. Due to the CTAB modification, the surface charge of the CNCs was neutralized, resulting in an increased size of each nanocrystal at the aqueous status and the aggregated microfibers when dried up. The CTAB modification not only decreased the crystallinity of the samples from 48.57% to 9.12% but also hydrophobized the CNCs and decreased their total surface energy. Finally, the adsorption behavior of the CNCs and CTAB-CNCs over nonionic, anionic, and cationic polymers was investigated by ellipsometry. Based on the thickness of the CNC and CTAB-CNC layers over 2-Hydroxyethyl cellulose (HEC), carboxymethyl cellulose (CMC), and polyethyleneimine (PEI), we proposed that the adsorption behavior was overall influenced by electrostatic interaction, hydrogen bonding, and van der Waals forces and the thickness of the adsorbed layers could be impacted by both the surface charge and the size of the crystals.

Background: Progression of metabolic dysfunction associated steatotic liver disease (MASLD) to steatohepatitis (MASH) is driven by stress-inducing lipids that promote liver inflammation and fibrosis. MASH can lead to cirrhosis and hepatocellular carcinoma. We showed coordinated defenses regulated by transcription factors, nuclear factor erythroid 2 related factor-1 (Nrf1) and -2 (Nrf2), protect against hepatic lipid stress. Here, we investigated protective effects of hepatocyte Nrf1 and Nrf2 against MASLD-induced liver fibrosis and tumorigenesis. Methods: Using mice fed MASH diet for 24-52 weeks, we examined MASLD in mice with hepatocyte specific Nrf1, Nrf2, or combined deletion, and compared this to control. In a separate study, mice received weekly injections of carbon tetrachloride to induce liver fibrosis. From week 16-24, mice were treated with Nrf2 activating drug bardoxolone, hepatocyte overexpression of human NRF1 (hNRF1), or both, and groups were compared to control. Results: Hepatocyte Nrf2 deficiency had no effect. Hepatocyte Nrf1 and combined deficiency caused MASH but only hepatocyte Nrf1 deficiency in male mice increased tumor number. Bardoxolone reduced liver steatosis, fibrosis, inflammation, and proliferation, and this effect when combined with hNRF1 was greater than bardoxolone alone. Conclusion: Physiologic Nrf1 delays MASLD progression, Nrf2-induction alleviates MASH, and combined enhancement synergistically protects against steatosis.

Background/Objectives: Population aging is rapidly increasing, and the importance of preventive medicine has been stressed. Health checkup, diet, and exercise are of paramount importance. This study aimed to evaluate the effectiveness of a personalized dual-task intervention that combined exercise with cognitive tasks in improving physical and cognitive functions among independently living elderly individuals. Methods: Participants were aged &gt;65 years who were mostly independent in their activities of daily living, divided into 2 groups. The group receiving the 20-min robot-assisted session was compared to the group receiving traditional functional restoration training. This randomized trial assessed the impact of this intervention on the 30-s chair stand test score and Montreal Cognitive Assessment-Japanese version score of the participants. Results: Both scores significantly improved in the intervention group, indicating enhanced lower-limb function and cognitive capabilities. Conclusions: These findings suggest that integrating cognitive tasks with physical exercise can be a potent strategy to improve overall well-being in the elderly, offering valuable insights for designing comprehensive preventive health programs tailored to this demographic.

Raman spectra of [TeX6](Y2) (X, Y - Cl, Br, I) were recorded in the temperature range 5-300 K. The vibration frequency of molecular halogens as function on temperature and the type of halogen X- in the [TeX6]2- complex was obtained. The vibration frequency of the molecular halogen Y2 depends on the type of halogen X- complex [TeX6]2- The temperature dependence of the Y2 frequency is anomalous compared to what was expected for a conventional anharmonic oscillator. It is shown that the interpretation of the experimental results based on the concept of traditional chemical bonding is quite satisfactory in all cases. The study was motivated by the need to consider the mechanism of interaction in the X-Y2 contacts.

Intense rainfall events frequently occur in Brazil, often leading to rapid flooding. Despite their recurrence, there is a notable lack of sub-daily studies in the country. This research aims to assess patterns related to the structure and microphysics of clouds driving intense rainfall in Brazil, resulting in high accumulations within 1 hour. Employing a 40 mm/h threshold and validation criteria, 83 events were selected for study, observed by both single and dual-polarization radars. Contoured Frequency by Altitude Diagrams (CFADs) of reflectivity, Vertical Integrated Liquid (VIL), and Vertical Integrated Ice (VII) are employed to scrutinize the vertical cloud characteristics in each region. To address limitations arising from the absence of polarimetric coverage in some events, three case studies focusing on polarimetric variables are included. A fourth case study enhances the overall understanding of these events, emphasizing the underexplored nature of short-term intense rainfall studies in Brazil. Results reveal that the generating system significantly influences the rainfall pattern, especially in the Southern, Southeastern, and Central-Western regions. Regional CFADs unveil primary convective columns with 40-50 dBZ reflectivity, extending to approximately 6 km. The microphysical analysis highlights the rapid structural intensification, challenging the event predictability and the issuance of timely specific warnings.

Intellecta dataset emerges as an innovative synthetic dataset, engineered to enhance the cognitive processing capabilities of contemporary language models. With a composition of 11.53 billion tokens, integrating 8.01 billion tokens of synthetic data with 3.52 billion tokens of rich textbook data, Intellecta is crafted to foster advanced reasoning and comprehensive educational narrative generation. Leveraging the Mixtral-8x7B-Instruct-v0.1 model, the dataset facilitates the generation of complex thought processes and detailed, textbook-style explanations, thus enabling language models to engage in both critical thinking and profound educational discourse. This hybrid dataset stands as a testament to the potential of synthetic data in pushing the boundaries of AI, offering a repository that is not only vast and varied but also refined to align with ethical standards and intellectual rigor.

This manuscript presents a novel approach to estimating the potential within Schrödinger equations, with a particular focus on applications to the Navier-Stokes problem in fluid dynamics. By establishing new theoretical estimates, we delve into the intricate dynamics of fluid flow, aiming to unveil previously obscured aspects of the Navier-Stokes equations. Through a rigorous mathematical framework, we explore how these new potential estimates can provide a fresh perspective on fluid mechanics, contributing to the ongoing quest to solve some of its most persistent challenges.

Additive manufacturing, commonly referred to as 3D printing, is an exciting and versatile manufacturing technology that is gaining traction and interest in both academic and industrial settings. Polymeric materials are essential components in a majority of the “inks” used across the various 3D printing technologies. As the environmental ramifications of sole or primary reliance on petrochemicals as a resource for industrial polymers continue to manifest themselves at a global scale, a transition to more sustainable bioderived alternatives could offer solutions. In particular, cellulose is promising due to its global abundance, biodegradability, excellent thermal and mechanical properties, and ability to be chemically modified to suit various applications. Thus far, cellulose has typically been incorporated in additive manufacturing applications as a substrate, filler, or reinforcement for other materials. However, due to its versatility and desirable properties, the exploration of all-cellulose 3D printing materials and associated methodologies is increasing. This review will discuss the progress and status of all-cellulose 3D printing approaches, associated challenges, and their potential as a key player in a more sustainable industrial future.

Brain-Computer Interface (BCI) systems can assist physically challenged people to interact with their surroundings and improve the quality of their lives. Decoding human thoughts is a powerful technique that can assist paralyzed people who have lost their speech production ability. Speaking is a combined process involving synchronizing the brain and the oral articulators. This paper proposed a high-accuracy brain wave pattern recognition based on inner speech using a novel feature extraction method. Only eight EEG electrodes were used in this study, and they were set on selected spots on the scalp. Support Vector Machine (SVM) was employed to decode the recorded EEG dataset into four internally spoken words which are: Up, Down, Left, and Right. The proposed approach achieved overall classification accuracy that ranges between 96.20% to 97.5%. In addition, more performance evaluation metrics were estimated to test the reliability of classifying the EEG-based inner speech data, and we obtained 97.61%, 97.50%, and 97.73% for F1-score, recall, and precision respectively. Furthermore, the Area Under Curve of the Receiver Operating Characteristic (AUC-ROC) proved the strength of the proposed approach for classifying the specified inner speech commands by achieving a macro-average amount of 99.32%. The inner speech classification method using electroencephalography proposed in this work can clinically help improve communication for patients with problems including speech disorder, mutism, cognitive development, executive function, and psychopathology.

1,3,5-Tris-(α-naphthyl)benzene is an organic non-electrolyte with notable stability of an amorphous phase. Its glassy and supercooled liquid states were previously studied by spectroscopic and calorimetric methods. However, the thermodynamic parameters of phase transitions available from the literature are inconsistent. In this work, the heat capacities of crystalline and liquid phases, the temperature dependence of the saturated vapor pressures, fusion and vaporization enthalpies were determined using differential and fast scanning calorimetry and verified using the estimates based on solution calorimetry. The structural features of 1,3,5-tris-(α-naphthyl)benzene are discussed based on the computations performed and the data on the molecular refractivity. The consistency between the values obtained by independent techniques was demonstrated. The deviations in the previously published data were attributed to possible polymorphism.

Aiming to improve medical diagnosis and treatment, artificial intelligence (AI) has emerged as a transformational force in the healthcare industry. In this article, we examine how AI is increasingly being used to improve healthcare, with an emphasis on how it is changing medical diagnosis and treatment. We explore the opportunities, threats, and ethical concerns of incorporating AI into healthcare practice. In addition, we feature important AI applications in radiology, pathology, cardiology, and cancer. AI has great potential to improve patient outcomes, diagnostic accuracy, and the ability to provide individualized treatment plans in the future if it is used and refined with care.

The brown pelican (Pelecanus occidentalis) is a species often affected by natural and man-made disasters such as hurricanes and oil spills as well as general human activities; that subsequently receives medical care and rehabilitation. During rehabilitation, blood may be collected for various testing to help with diagnosis, treatment, and monitoring. Reference intervals for this species are limited, dated, and typically from small sample sizes. Seventy one presumed healthy brown pelicans were sampled as a part of their pre-release examination from rehabilitation at the Wildlife Center of Texas after a large volume stranding in December 2014 to January 2015, and various venous analytes were measured to establish updated reference intervals for Brown Pelicans. Fibrinogen was measured via heat precipitation and the Abaxis VSPro equine Fibrinogen cartridge to determine reference intervals, and in an attempt to validate the VSPro for use in avian species. Abaxis VS2 Avian/Reptile Chemistry panel, iSTAT CG4+, and iSTAT Chem8+ results in addition to body condition score, spun PCV, cloacal temperature and fibrinogen were measured. Proposed reference intervals for brown pelicans are presented. Fibrinogen results were not comparable between the gold standard method and the VSPro, indicating that the VSPro is not appropriate for use in brown pelicans.

Adamantinomatous Craniopharyngioma (ACP) is a rare epithelial tumor located in the craniopharyngeal duct, often associated with high morbidity and a high long-term recurrence rate. ACP is predominantly diagnosed in children below the age of 15 and accounts for a majority of Craniopharyngioma cases in the United States. It is most commonly caused by a mutation in exon 3 of the CTNNB1 gene, which promotes overaccumulation of β-Catenin in the WNT pathway. As β-Catenin accumulates, it over-activates the transcription factor, causing an over-transcription of WNT proteins and uncontrolled cell growth. Current methods of treatment for ACP are centered around surgical intervention and radiotherapy, including gross-total resection (GTR), subtotal resection (STR), and a combination of subtotal resection and adjuvant radiotherapy (STR+XTR). These methods of treatment are associated with high risk due to the proximity of ACP to critical structures near the craniopharyngeal duct. High recurrence rates and morbidity are closely associated with current methods of treatment and other methods have yet to be attempted in craniopharyngioma. This review will explore two possible methods of non-surgical and non-radiological therapeutic interventions. The use of RNAi therapy and CRISPR may provide insight and be a potential way to treat ACP with increased quality of life and decreased recurrence rates.

This study delves into the Schrödinger equation's new invariants, shedding light on their crucial implications for theoretical physics and beyond. Specifically, it explores the behavior of scattering amplitudes and bound states concerning the choice of coordinate systems. The research unveils that while the energy of bound states remains invariant under coordinate transformations, the phase of scattering amplitudes undergoes variations, underscoring its pivotal role in theories reliant on phase normalization. Moreover, these findings have played a pivotal role in constructing estimates for three-dimensional Navier-Stokes equations, enhancing our ability to model complex fluid dynamics with greater precision and reliability. Additionally, in seismic exploration, tomography, and ultrasound imaging, these properties allow researchers to optimize phase selection, facilitating the most effective interpretation of measurement results. This strategic phase manipulation ensures clearer insights into subsurface structures, tissue composition, and fluid dynamics, with the flexibility to seamlessly transition back to the original coordinate system post-interpretation. This interdisciplinary synergy underscores the profound impact of fundamental theoretical research on advancing practical applications across diverse scientific domains.

In recent years, thanks to continuous technological development, temperature data loggers have been used to collect data from the breeding progress of birds, which can be used, e.g. to obtain information on the length of incubation breaks, to detect the start of incubation or to record unsuccessful breeding. Temperature data loggers have been used in various types of bird nests, but not in a „closed“ nests such as a burrow or cavity. The study presents the results of using a temperature data loggers in natural nest holes of the common kingfisher (Alcedo atthis). Their nests, which lack substantial insulating structures, are primarily influenced by the relatively stable soil temperature. The temperature of the space inside a nest chamber was measured on a continuous basis with an interval of 1 minute between measurements. The measurement was carried out from egg laying/incubation to a successful leave of the nest chamber/death of chicks (5 nests on 3 different streams in 3 breeding seasons). The temperature curves showed the laying of the eggs, the start of incubation, the successful flight out of the nest chamber or the death of the chicks in the nest chamber. It was not always possible to determine exactly when the chicks hatched from the temperature data.

With the emergence of autonomous functions in road vehicles, there has been an increased use of Advanced Driver Assistance Systems comprising various sensors to perform automated tasks. Light Detection and Ranging (LiDAR) is one of the most important types of optical sensor that detects the positions of obstacles, representing them as clusters of points in 3-dimensional space. LiDAR performance degrades significantly when driving in rain as raindrops adhere to the outer surface of the sensor assembly. The performance degradation behaviors include missing points and reduced reflectivity of the points. It was found that the extent of degradations is highly dependent on the interface material properties, which subsequently affects the shapes of the adherent droplets, causing different perturbations to the optical rays. A fundamental investigation is performed on the protective polycarbonate cover of the LiDAR assembly coated with four classes of materials – hydrophilic, almost-hydrophobic, hydrophobic, and superhydrophobic. Water droplets are controllably dispensed onto the cover to quantify the signal alteration due to each droplet of various sizes and shapes. To further understand the effects of droplet motion on LiDAR signals, sliding droplet conditions are simulated using numerical analysis and validated with physical optical tests using a 905 nm laser source and receiver to mimic the LiDAR detection mechanism. Comprehensive explanations are presented on LiDAR performance degradation in rain from both material and optical perspectives. These can aid component selection and the development of signal enhancing strategies for integrating LiDARs in vehicle designs to minimize the impact of rain.