The Industrial Revolution 4.0 (IR4.0) is transforming the global economy, necessitating mall and medium-sized enterprises (SMEs) to adopt new technologies like artificial intelligence (AI), the Internet of Things (IoT), blockchain, and cloud computing. Therefore, SMEs need to assess their readiness to identify capabilities and areas for improvement to remain competitive. However, existing IR4.0 readiness assessment such as the Industry4WRD Readiness Assessment and Industry 4.0-Readiness by IMPULS German are time-consuming and restrict the participation of various sectors. Using the understanding of theories such as Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), Technology Readiness Index (TRI), and Diffusion Of Innovation (DOI), this study developed an initial research model that identifies the dimensions of IR4.0 readiness; (i) organization, (ii) data, (iii) infrastructure, (iv) analytics, and (v) IT, development and operations. This study carried out qualitative methods through four different phases. The first phase is a systematic literature review, and data collection through participant observation (PO) in IR4.0 skills training programs, seminars, and workshops. The second phase is the development of an initial research model to identify the dimensions of IR4.0 readiness that will be used in the next phase. The third phase is a survey on SME’s IR4.0 readiness via the IR4.0 e-Readiness Checker (IR4.0 eRC) readiness assessment system, which produces the final research model, IR4.0 SME Readiness Model. In the fourth phase, the IR4.0 Readiness Model is confirmed for use by SMEs in Malaysia through interviews with three industry experts in Malaysia. Based on the 50 responses in the IR4.0 eRC evaluation, the average IR4.0 readiness of SMEs is 66%, and only 10 SMEs with less than 50%, showing room and improvement opportunities for the continuous research and development of IR4.0 transformation. This study developed IR4.0 readiness model for SMEs to assess readiness for IR4.0 transformation, support investments in IoT projects and employee upskilling programs.

Stem cells can be used in cellular therapy. This happended in order to replace damaged cells or having aim to regenerate organs. The definition of stem cells can be extended. From this point of view, we can mention taking in consideration the idea in which it is known that these cells form the base of the building body. More than, we can mention that stem cells are characterized by two knowing properties namely differentiation and self renewal. Based on the observation that differentiation of adult stem cells into specific derivative scan be controlled by laboratory techniques, it is anticipated that adult stem cells may become the basis of therapies for many, and various types of medical conditions. Taking on stem cells, regenerative medicine (RM) it is known as being one of the hottest topics in biotechnology nowadays. From this purpose, stem cells can be used in regenerative medicine (RM). The principles of regeneration are found in different types of cultures, from long time ago. As an interdisciplinary field of research, regenerative medicine, play a great role in tissues and organs damaged reparation with a higher potential in transplantation if necessary.

A nation's social, economic, and political emancipation is ineluctably connected with functional education systems in which people learn to create new institutions, utilise new technologies, cope with vagaries and difficulties in their environment, and positively alter their behavioural patterns. Education in a broad sense improves the capabilities of individuals and the capacity of institutions and becomes a catalyst for the closely interrelated economic, social, cultural, and political changes that are parts of the hallmarks of national development. Nevertheless, a teacher stands out as a crucial figure within any educational institution, wielding significant influence in effecting these changes and transformations. Teacher education is broad. It is based on the praxis that teachers are made in contrary to the assumption that teachers are born. Since teaching is considered an art and a science, the teacher has to acquire not only knowledge but also requisite skills needed in carrying out his or her inestimable duties or services. The efficiency and effectiveness of every educational system hinge significantly on the educational achievements of teachers. After all, no education can surpass the quality of its educators. Thus, every nation places demands and expectations on the teacher, which need to be addressed by both initial and continuing teacher education. On this note, this paper examines teacher education with respect to its praxis and professionalism, examines the nexus between teacher education and socioeconomic as well as political emancipation, analyses the challenges of teacher education in Nigeria, and in the final analysis, gives recommendations based on the identified challenges.

Primary ciliary dyskinesia (PCD) is caused by pathologic variants in over 50 different genes that affect the structure and function of motile cilia. Low nasal NO (nNO) is a biomarker for diagnosis in patients with features of PCD; but the reason why it is low is unclear. At the cellular level, a characteristic feature shared by most PCD patients is that antigens and other particles are not cleared from the epithelial surface. Poor antigen clearance results in pro-oxidant pathway activation and airway epithelial damage and may predispose PCD patients to DUOX1- and IL33- mediated asthma. Secondary ciliary dysfunction, such as that caused by viruses or by smoking, can also contribute to asthma development. Variants in genes underlying the function of cilia, can be associated with poor lung function, even in the absence of PCD. Single nucleotide polymorphisms in PCD – related genes can be associated with increased asthma severity. The role of cilia and antigen stasis is the pathophysiology of asthma is an important area for research, because specific airway clearance techniques and other therapeutic interventions, such as antioxidants, could be of value in preventing the development of asthma and asthma-like symptoms.

Floods, recognized for their erratic behavior and devastating effects, are a significant threat as a natural disaster. In Brunei Darussalam, the impact of climate change is becoming increasingly evident through higher temperatures and an expected increase in annual rainfall (5.0mm per year from 2021 to 2050), highlighting the critical need for updated flood risk management techniques. In line with the climate resilience and adaptation objectives of WAWASAN 2035, this paper introduces an innovative approach—a cutting-edge flood risk management framework that utilizes the capabilities of big data analytics, sophisticated machine learning algorithms, and smart Internet of Things (IoT) sensors. Traditional methods, which rely on numerical and physical data modeling, often do not provide precise short-term flood forecasts. Our suggested framework uses machine learning to analyze real-time flood forecasting, sensor data and enhance warning systems, addressing the shortcomings of traditional approaches. The key advantage of this approach is its potential to drastically decrease flood-related damages, protect lives, and boost infrastructure resilience. This proposal is not only in aligns with Brunei's vision for a safe and climate-adaptable future but also marks a significant step forward in adopting innovative and sustainable flood risk management solutions amidst an evolving climate.

The objectives of this study was to assess the impact of a reproductive approach in high-yielding nulliparous and parous Holstein cows on the interestrus interval, estrus detection rates, conception rates, and pregnancy rates. The strategy involved giving GnRH on day 5 following artificial insemination (AI). For nulliparous cows, there appears to be no noticeable effect of GnRH therapy on the interestrus interval. In both groups, nearly all of the cows exhibited an 18–25-day cycle interval (P < 0.05). In the 18–25 day cycle period, the untreated multiparous cows exhibited the highest proportion (P < 0.05), while the treated group demonstrated the highest proportion (P < 0.05) in the 26–35 day cycle interval. The study found that the conception rate was higher in repeat breeder nulliparous and 3+ lactation treated Holstein cows compared with untreated ones. However, the cumulative heat detection rate, pregnancy rate and conception rates were similar in both groups (P > 0.05). Also, this study found that in the hottest months of the year, this therapeutic approach can't counteract the negative effect of heat stress in high-yielding dairy cows. Thus, it is not advised of using the hormonal method to create supplementary corpus luteum across the herd.

Hepatitis B Virus (HBV) infection carries a significant health burden worldwide. It is a leading cause of acute and chronic liver disease resulting in cirrhosis and hepatocellular carcinoma (HCC). This virus affects millions globally, and despite several medical advancements, research, and efforts to develop curative treatment, the persistence of HBV in infected individuals by cccDNA and integration pose formidable challenges. This review aims to provide a broad-based overview of HBV persistence, integration and the implications for chronic infection and tumorigenesis. By considering these points, we bring forth insights into the advancement of therapies that aim to disrupt the chronicity of HBV infection and improve clinical outcomes.

Type2 diabetes(T2D) is a pervasive modern disease, classified as a metabolic disorder marked by hyperglycemia, hyperinsulinemia, and life-long threatening cardiovascular morbidities. Subclinical inflammation stands as the primary pathogenetic factor propelling T2D progression, correlated with heightened levels of proinflammatory cytokines. Immune cells serve as the prominent sources of cytokine production, and under diabetic conditions, they tend toward a proinflammatory phenotype, fostering chronic inflammation. This review zeroes in on the disrupted homeostasis characteristic of diabetic conditions, encompassing cytokines, hormones, and their interplay with altered immune function, all contributing to the onset of diabetic cardiovascular complications.

This study delves into the intricate interplay between cosmology and gravity in dilaton-based models, enhancing our understanding. Exploring boundary theories coupled to gravity, we derive a four-dimensional effective theory from the cosmological constant. Dilaton gravity is then scrutinized, revealing elegant solutions and insights into brane embedding. The analysis extends to probe scalar fields, employing the WKB approximation in both conformal and non-conformal cases. In summary, this work contributes to a nuanced understanding of the complex relationship between cosmology and gravity in dilaton-based frameworks.

Major factors affecting in vitro immature embryo rescue efficiencies from Prunus persica or P. armeniaca accessions, have been identified along with improving its economic feasibility. Three culture media, based on Woody Plant Medium (WPM) have been used depending on the embryo size. Embryos less than 5-mm-long were cultured in WPM supplemented with 1 mM BAP and 1 mM GA3, while embryos bigger than 5-mm-long were cultured in hormone-free medium, with or without vermiculite. Environmental in vitro culture conditions consisted of three phases, a (I) stratification at 4 C during a 3 to 5-month-long period in the dark, followed by (II) growth of germinated embryos at 14 C for 4-week-long period, with 12h light a day, which favors plantlet development, and finally (III) growth at 24 C, with 16h light a day, until the plantlets were moved to the greenhouse for acclimatization. Germination of smaller embryos, at the end of the phase I, ranged from 82.2% to 22.1%, for apricot and flat peaches, respectively, whereas for bigger embryos the germination varied from 97.4% to 53.2% for the same type of fruits. Embryo germination for peaches and nectarines ranged from 40.1% to 30.3% for smaller embryos, and from 91.9% to 64.0% for bigger embryos. Endo- and exophytic contamination, affecting from 7.4% to 52.9% of cultured embryos depending on the fruit type and conservation conditions, and the capacity to acclimate to soil conditions, ranging from 50.4% to 93.2%, were the two most important factors influencing protocol’s efficiency and economic feasibility. Considering the overall efficiencies, expressed as hardened plants transferred to field plots over clean uncontaminated embryo, values ranged from 55.8% for nectarines, 54.0% for peaches, 45.6% for apricot, and 23.3% for flat fruits. Addition of vermiculite to the culture medium significantly improved plantlet development, avoiding subculture to fresh medium when an extension of the phase III was required before acclimatization. Compared to laboratory glassware, use of food glass containers with air-permeable sealing film, along with vermiculite-containing medium significantly reduced costs, when handling the large number of embryos required for breeding programs.

In a world where physical activity and social participation are fundamental pillars for a full, healthy, and quality life, confidence in walking emerges as a fundamental aspect to be assessed, especially in older adults. The purpose of this study was therefore to develop a Portuguese (Euro-pean) version, linguistically and psychometrically adapted, of the Ambulatory Self-Confidence Questionnaire (ASCQ); A translation method was used followed by an assessment of its validity and reliability. The Portuguese version was completed by 173 older adults. To assess reliability was used Cronbach’s Alpha and Intraclass Correlation Coefficients (ICC). For sociodemographic and clinical characterization, as well as for the questionnaire scoring was used descriptive statistical analysis. Pearson's correlation (r), Student´s t-test and ANOVA were used to analyse the criterion and con-struction validity; The Portuguese interactions of ASCQ was effectively translated and adjusted, revealing exceptional internal consistency and test-retest reliability, as reflected in Cronbach's alpha and ICC values of 0.95. No Floor Effect was observed, however, a Celling Effect was identified (3.5%). Criterion and construct validity were verified because all the correlations established were statistically significant; The adaptation of the ASCQ to Portuguese culture is adequate, making it valid for use within the Portuguese population of Portugal.

According to their nutritional value, their ability to adapt to the various environmental conditions, and their versatility, cereals are among the most cultivated plants in the world. However, the ongoing climate changes subject crops to important environmental stress that for some varieties leads to high production losses. Therefore, selection of species and varieties more versatile and adaptable to different environmental conditions can be important. However, the characteristics of some cereals are not completely known, this is a priority before to improve their cultivation. The aim of this study is to characterize select species of potential suitable for local environmental conditions, nutritional value.

The purpose of this review is to investigate the role of legume cover crops in improving climate adaptability and water use efficiency in South African grassland systems. Climate change is posing significant obstacles to agricultural systems all over the world, which includes South Africa, where shortages of water and fluctuations are significant issues. Legume cover crops are growing in popularity as a long-term and cost-effective solution to these problems. The purpose of this review is to demonstrate the possible advantages of legume cover crops for enhancing climate resilience and water use efficiency in South African grassland systems, as well as the fundamental processes and present study findings. According to the outcomes, legume cover crops may boost soil water availability, nutrient cycling, carbon sequestration, and overall ecosystem productivity, resulting in increased climate resilience and water use efficiency. However, a variety of factors, including species selection, management practices, and environmental conditions, can all have an impact on the effectiveness of legume cover crops. With the concerted efforts, adaptation strategies of livestock farmers that seeks to maximise the potential of legume cover crops in South African grassland systems, it is critical to consider site-specific factors when establishing them. This review offers significant insights into the role of legume cover crops in climate resilience and water use efficiency, laying the groundwork for future research and agricultural practices.

The paper combines two new original concepts about eco-energetic systems. The first one is related to the M.E.N. (Mega-Eco-Nega-Watt) paradigm, which is based on three different but complementary ecological economic spaces: MEGAWATT, as needed energy, ECOWATT, as ecological energy, and NEGAWATT, as preserved energy, even the renewable energies and technologies, in the context of electrical energy production. The second concept presented in this paper is the eco-energetic efficiency, introduced in order to facilitate a correlation between the energetic efficiency of the system and a necessary, new defined ecological coefficient. The proposed formula for eco-energetic efficiency enables an interesting form of reporting to the different situations in which the input energy, output energy, lost energy and externalities, involved in an energetic process interact to produce energy in a specific energetic system, in connection with the circular economy model. Finally, is presented an original diagram of the energetic chains to produce electricity in a resilience regim, with high eco-energetic efficiency from originating in different primary energetic sources as external (gravitation & solar sources), fuels (classical & radioactive), internal sources and others. Even what kind of energetic sources are used to obtain electricity, as coals, gas, wood, hydropower, nuclear power, wind power, biomass, solar systems, and others, the entire process should be sustainable in what is the transdisciplinary integration of the different representative spheres as energy, socio-economy, ecology (environment), with the main core, sustainable education, inclueding the law and administrative aspects, as necessary fields of the knowledge based society/economy.

Mesoporous MgAl2O4+ LnFe0.7Ni0.3O3 (Ln=La, Pr) nanocomposites were prepared by inexpensive one-pot procedure with Pluronic P123 copolymer, Ni+Ru active component was supported by wet impregnation. The real structure of samples was studied by XRD and TEM with EDX, surface properties by FTIRS of adsorbed CO, reactivity by H2 –TPR, catalytic activity was tested in ethanol steam reforming. Disordering of the real structure of nanocomposite supports due to incorporation of transition metal cations into MgAl2O4 results in developed metal-support interface and domination of single surface metal centers. This provides a high catalytic activity in reaction of ethanol steam reforming in the intermediate temperature range ~550 oC close to that of the best known catalysts, and stability to coking. A higher activity for Pr-containing catalyst is provided by a high reactivity of surface oxygen species bound with Pr cations.

The fuel cell particularly the Proton Exchange Membrane Fuel Cell (PEMFC) is a new energy technology that plays a critical role in achieving market viability. The PEMFC has high power density, zero CO₂ emissions, and high conversion efficiency. However, with uniform distribution of fuel in PEMFC, we can improve the performance and reduce the cost. The PEMFC will be more efficient and effective in terms of renewable energy as a byproduct only water. Metal foam is used as an alternative for the channels in PEMFC. The model of PEMFC was established by using the ANSYS Fluent 3D Model. Then we proposed four configurations of PEMFC. The outcome demonstrates that Case IV provided outstanding performance if it is compared with the other three cases. In terms of power density, Case IV provided a high power density that is double that of Case I. The porosity of metal foam was investigated. The 0.6 porosity value is found as the optimal value. The uniform distribution of the fuel can be achieved at this value which leads to the outstanding current density.

Introduction: Agricultural practices significantly influence soil microbial populations and physicochemical properties, which are crucial for crop growth and quality. This study aims to investigate the impact of different agrochemical applications on soil microbial dynamics, soil physicochemical properties, as well as yield and proximate properties of maize. Methods: Carefully gathered topsoil samples at depths ranging from 1 to 15 cm, were transported to Jimma University to cultivate maize. Over a period of up to 120 days, soil and maize samples were collected at specified days to analyze various parameters, including soil pH, microbial populations, as well as nutrient content both in soil and plants. The collected data was statistically analyzed using one-way ANOVA, with a significance level of p < 0.05. Results: The soil bacterial and fungal populations were measured on days 5, 10, 20, 40, 80, and 120. The highest total mesophilic bacterial count (TMBC) was measured in the pots containing compost (G) and the lowest in pots that received macronutrient fertilizers and glyphosates (B) (i.e. 91.8 x 105 and 13.13 x 105 cfu/g of soil, respectively). The highest total mesophilic fungal count (TMFC) was observed in pots containing glyphosates and compost (F) (i.e. 67.25 x 104 cfu/g soil) and again the lowest in pot treated with macronutrient fertilizers and glyphosate (B) (i.e. 3.23 x 104 cfu/g soil). Moreover, the pots treated with macronutrient fertilizers and glyphosate (B), macronutrient fertilizers (A), and micronutrient fertilizers (C) exhibited the lowest levels of Fe and Zn. Furthermore, the pots receiving macronutrient fertilizer combined with glyphosate (B), as well as those receiving macronutrient fertilizers (A) alone had the lowest concentrations of Mn and Cu micronutrients. Finally, in maize the lowest protein, fats, and carbohydrates (g/100g) were found in the pots treated with macronutrient fertilizer combined with glyphosate (B, 2.21 ± 0.2), micronutrient fertilizer (C, 8.57 ± 0.25), and glyphosates only (D, 57.34 ± 0.1). Maize treated with compost (G) showed the highest levels of Fe, Cu, and Zn, while macronutrient fertilizer combined with glyphosate (B) resulted in the lowest content of these micronutrients. Additionally, maize receiving micronutrient fertilizer (C) had the highest concentration of Mn, whereas those treated with glyphosates (D) had the lowest. Conclusions: Significant variations in soil’s mesophilic bacterial and fungal populations, micronutrient levels, and nutritional composition were observed, indicating treatment-related changes. Generally, treatment with micromineral fertilizer combined with glyphosate (B) seemed to deplete the soil while compost treatment improved. Compost-treated soils exhibited the highest mesophilic bacterial and fungal count, as well as Fe and Zn micronutrient concentrations. The use of agrochemicals also had a negative effect on maize yield quality. The fluctuations in the soil parameters underscore the multifaceted effects of agrochemical treatments.

This study examines the capacity of a Site-Specific Fodder Management Decision Support System (SSFM-DSS) model to assist in successful cultivation of sericea lespedeza [SL; Lespedeza cuneata (Dum.-Cours.) G. Don.], with a specific focus on small-scale agricultural systems in the southeastern United States (U.S.). The study emphasizes incorporating advanced geospatial technologies, such as Geographic Information Systems (GIS), remote sensing, and Global Navigation Satellite Systems (GNSS), to improve fodder production. The research showcases the versatility of SL under varying environmental conditions, underscoring its significance in promoting sustainable livestock production. The methodology integrates empirical field data, geospatial analysis, and predictive modeling to formulate an SSFM strategy customized to address the distinct difficulties climate change presents, such as sudden and severe drought conditions. The study introduces an automated geospatial model for assessing the appropriateness of SL production throughout Alabama, Georgia, and South Carolina. The model uses many environmental criteria, including soil properties, climate fluctuations, and terrain. Furthermore, the research was instrumental in development of a WebGIS Dashboard, which offers farmers a decision assistance system to enhance the sustainable production of SL. The results highlight the significant impact that a SSFM-DSS can have on promoting sustainable agricultural practices, providing a solution to address the issues of food security and environmental concerns in agriculture.

Cocoa bean shells (CBSs) represent the external layer of cocoa beans. The shells are removed during the winnowing after the pre-roasting, a processing step of chocolate production; in in the past they were considered a waste. CBSs possess many interesting nutritional characteristics in both macro and micronutrients. CBSs result very rich in dietary fiber and antioxidant compounds such as phenolic acids and flavan-3-ols. Soluble dietary fibers are potentially associated with fermentability and prebiotic activity on human gut microbiota instead antioxidants compounds have been linked with positive effects on human health. Based on these properties, the aim of this study was the valorization of CBSs thorough enzymatic treatments. The shells were treated both raw and defatted; three sets of carbohydrases have been used in order to destructure the fiber profile, potentially enhancing the potential prebiotic activity of CBSs. Cellulase, xylanase and pectinase were used to perform enzymatic treatments. After the enzymatic hydrolisis, both soluble and insoluble fibers fraction were quantified, in parallel with the total phenolic and the total flavonoid contents and the antioxidant activity. Moreover, the HPLC-PDA analysis was carried out for the main compounds of CBSs. The enzymatic treatmens allowed to obtain an enhancement in soluble fibers, for both defatted and raw CBSs, particularly using cellulase, xylanase and their combinations. Finally, a parallel preservation of the antioxidant capacity and the content of the main bioactive compounds after the treatments was observed. These results can be used to exploit the enzymatic treated CBSs to further industrial applications in the food and nutraceutical fields.

To understand how the thinning strategies impacts on wood quality and quantity for different purposes is of interest, considering that the management of plantations is carried out with parameters that have yet to be validated for different growth conditions. This work evaluated contrasting thinning regimes applied early at two moments of the crop cycle. With an initial population of 840 trees.ha-1, two thinning with populations ranging from 700 to 400, and from 400 to 100 trees.ha-1 were applied at 1.5 and 7.3 years, respectively. Growth analyses were carried out from the ages of 1.5 to 20.8 years considering: total height, diameter at breast height, individual volume, total and commercial volume per hectare, mean annual increase and current annual increase. At final age, contrasting populations of 100, 250 and 400 trees.ha-1 were sampled to assess wood density, and mechanical properties (bending and compression on small scale clear samples). The values of individual growth and wood properties are related to a Stand Density Index to understand the effect of competition on those values. The results allow us to identify the thinning schemes that record the most significant individual and per-hectare growth (both in thinning and clear felling) and the optimal harvest time under specific growth conditions. We assessed the proportions of commercial logs for sawmill and pulp uses, providing valuable inputs for a subsequent economic analysis of thinning regimes seeking for the most convenient combination of wood products. Wood's physical and mechanical properties assessed were barely affected by contrasting levels of competition between trees, therefore the decision of the silvicultural system to implement will depend on production and economic criteria.

Glucocorticoids (GCs) are widely used in blood cancer treatment despite their multiple adverse effects. Biological response to GCs is mediated by glucocorticoid receptor (GR) by transactivation (TA), associated with side effects, and transrepression (TR), mediating anticancer effects. Selective GR agonists (SEGRAs) preferentially activating GR TR could be better option for cancer treatment. One of well-characterized SEGRAs is 2-(4-acetoxyphenyl)-2-chloro-N-methylethylammonium-chloride (CpdA), demonstrated anticancer activity in vitro and in vivo, however its translational potential is limited due to chemical instability. CpdA derivatives CpdA-01-08 were designed by two synthetic strategies. Derivative CpdA-03 demonstrated superior GR affinity and stability compared to CpdA. Analysis of CpdA-03 ligand properties in lymphoma Granta and leukemia CEM cell lines revealed its SEGRA profile: it induced GR TR without triggering GR TA, as evidenced by changes in expression of GR target genes. Effects of CpdA-03 on cell viability, growth, and apoptosis were similar to reference GR ligand, dexamethasone (Dex), and the proto-type compound CpdA. In vivo testing of CpdA-03 anti-lymphoma activity in transplantable P388 murine lymphoma model showed that CpdA-03 reduced tumor volume threefold, outperforming Dex and CpdA. In conclusion, this work introduces CpdA-03 as promising new SEGRA with potential for further development as anti-lymphoma drug with fewer side effects.

Administering intraluminal fluid can improve the acoustic window for visualization of lumen and wall layers in the cavitary organs. Microbubbles in ultrasound contrast agents can also be used for intracavitary applications to enhance visualization of the lesion in human patients. However, there was no literature extending the clinical application of the intraluminal contrast-enhanced ultrasonography (CEUS) to patients with naturally occurring diseases in veterinary medicine. This case series aims to describe the detailed application and diagnostic value of intraluminal CEUS in six clinical cases with naturally occurring gastrointestinal (GI) and urinary tract diseases.

The raw material purchasing (RMP) problem is to determine the purchasing quantities of raw materials in given periods or cycles. Raw material purchasing optimization is crucial for large-scale steel plants because it is closely related to the supply of raw materials and cost savings. The raw material purchasing of large-scale steel enterprises is characterized by many varieties, large quantities, and high costs. The RMP objective is to minimize the total purchasing cost consisting of the price of raw materials, purchasing set-up costs, and inventory costs and meet product demand. We present a mixed integer linear programming (MILP) model and a column generation (CG) solution for the resulting optimization problem. The column generation algorithm is the generalization of the branch & bound algorithm with solving the linear programming (LP) relaxation of MILP using column generation (CG), and its advantage is to handle large-sized MILPs. Experimental results show the effectiveness and efficiency of the solution.

The emergence of few-shot learning as a potential approach to address the problem of data scarcity by learning underlying pattern from a few training sample had so far given a mix-result especially on the suitability of model-agnostic meta learning, transfer learning, and optimization strategy to rapidly learn valid information from few sample. In this research, we did an in-depth evaluation of meta- learning to determine their plausibility and suitability for previously unknown cyberattack detection by first retrieving the original research artifacts of current state of the art meta learning to repeat the experiment with original dataset before replicating the experiment with two different malware dataset which had not been previously done with meta-transfer learning. On each of the experiments, meta-transfer learning gave good results on digital character recognition dataset but abysmal result on Malimg and Malevis malware images datasets thereby indicating its unreliability for detecting cyberattacks and the need for an improvement to the state-of-the-art meta transfer learning towards a better attack detection. Transfer learning performance is independent on imbalance and hence does not influence its performance since both malware dataset used for this experiment result in high validation loss and balancing the dataset doesn't result in reduced validation loss,the successful learning transfer seen on digital character recognition dataset is not unconnected to the fact that several languages have similar characters and digits thereby enhancing the successful learning transfer unlike malware datasets, and more importantly the finding that current meta-learning transfer approach doesn't generalize well on malware dataset and hence not suitable for detecting previously unseen out-of-distribution attack.

This study examines the effects of tourism development on the well-being of impoverished residents in both urban (La Candelaria, Bogotá) and rural (La Macarena, Meta) regions of Colombia. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the findings reveal that personal economic benefits from tourism are the most vital factor in enhancing residents' happiness and life satisfaction. The analysis outlines a pathway from economic gain to happiness, improving life satisfaction. Additionally, the study highlights tourism's role in exacerbating the urban-rural divide, offering insights into migration trends and regional inequality. Practical recommendations are provided for policymakers to ensure balanced tourism development across regions.

By using a two-stage physiologically based extraction test (PBET) and (W-PBET), the authors of this paper have estimated the bioaccessibility of metals (Pb and Fe) and their compounds in the GI tract of waterfowl and mammals. It has been shown that the metals (Pb and Fe) have low bioaccessibility; combined with the short time of shot exposition at the GI tract, this eliminates the risk of toxic effects in the case of shot ingestion by waterfowl. It has also been discovered that there is a significant difference in the bioaccessibility of metals and their compounds. A model was proposed and tested to predict the toxic effects of lead on biological objects depending on the threshold mass of consumption. This model takes into account data on the bioavailability of lead and regulatory values indicating dangerous concentrations of lead.

This work explores state-of-the-art approaches for stabilizing an inverted pendulum on a cart system, which has been used for over a century to demonstrate ideas in nonlinear and linear control theory, owing to its simple practical implementation yet complex system dynamics. We introduce energy-based control methods and propose a simple linear controller to quickly force the system to the downward equilibrium before swing-up. By constraining the system to start from a stable equilibrium configuration, the problem of global stability is reduced to ensuring that the system can follow all heteroclinic orbits that start very close to the downward equilibrium. Multiple Lyapunov functions are employed to ensure non-zero tracking, increasing the system's domain of attraction than is achieved by traditional controllers based on a single Lyapunov function. We stabilize our inverted pendulum system in the upright configuration through pole placement using a linear quadratic regulator known for fast settling times and smooth system response and through sliding mode controllers known for their robustness to disturbances and model uncertainties. While sliding mode controllers exhibit faster stabilization of the pendulum angle, they fail to stabilize the cart position in a reasonable amount of time. The paper concludes by suggesting various controller techniques that can enhance the swing-up and stabilization controller architectures, leaving room for future exploration. To facilitate further research and education, an open-source MATLAB simulation code is provided, encapsulating the system dynamics and controller designs. This resource offers flexibility for customization, making it a valuable tool for both researchers and educators working with inverted pendulum systems.

Two beneficial characteristics of aircraft generators are having armature windings and PM excitation sources placed on the stator side (maintenance and thermal management) and having a clear-cut rotor without permanent magnets or excitation windings (vulnerable at high speeds due to associated centripetal mechanical stresses). Within this framework, a doubly-salient permanent magnet (DSPM) generator was conceived by optimizing the stator size and rotor structure to minimize the torque ripple and maximize the RMS voltage value per turn of each generator phase. A Multi-Objective Design Strategy based on a 2D finite element analysis was used, being set to have characteristics closest to optimal for a Boeing 767 turbine, that is, the necessary electromotive force for a required power of 90 kW at 3000 rpm, feeding a simplified Boeing 767 electrical power distribution system. The results show that the machine could not deliver the required power at 3000 rpm since the 2D finite elements analysis demonstrates that the 2D model gives optimistic results when compared with the 3D FEM model. However, with a 3D finite element analysis of the machine feeding the aircraft load, it was seen that the machine’s efficiency is 92%, suggesting this machine can be a plausible solution.

Synthetic Aperture Radar (SAR) ship target detection has been extensively researched. However, most methods use the same dataset division for both training and validation. In practical applications, it is often necessary to quickly adapt to new loads, new modes, and new data to detect targets effectively. This presents a cross-domain detection problem that requires further study. This paper proposes a method for detecting SAR ships in complex backgrounds using fusion tensor and cross-domain adversarial learning. The method is designed to address the cross-domain detection problem of SAR ships with large differences between the training and test sets. Specifically, it can be used for the cross-domain detection task from the fully-polarised medium-resolution ship dataset (source domain) to the high-resolution single-polarised dataset (target domain). This method proposes a Channel Fusion Module (CFM) based on the YOLOV5s model. The CFM utilises the correlation between polarised channel images during training to enrich the feature information of single-polarised images extracted by the model during inference. The article proposes a module called Cross-Domain Adversarial Learning Module (CALM) to reduce overfitting and achieve adaptation between domains. Additionally, the paper introduces the Anti-Interference Head (AIH) which decouples the detection head to reduce the conflict of classification and localization problems. This improves the anti-interference and generalization ability in complex backgrounds. This paper conducts cross-domain experiments using the constructed medium-resolution SAR full polarization dataset (SFPD) as the source domain and the high-resolution single-polarised ship detection dataset (HRSID) as the target domain. Compared to the best-performing YOLOV8s model among typical mainstream models, this model improves Precision by 4.9%, Recall by 3.3%, AP by 2.4%, and F1 by 3.9%. This verifies the effectiveness of the method and provides a useful reference for improving cross-domain learning and model generalization capability in the field of target detection.

This manuscript employs a surface stress-driven nonlocal model to explore the combined effects of long-range interaction and surface energy on higher vibration modes of functionally graded nanobeams. The nanobeam theory, based on Bernoulli-Euler kinematics, incorporates surface effects such as surface elasticity, surface residual stresses, surface density, and rotary inertia. Hamilton's principle is applied to derive the governing equation with size-dependent considerations. The main outcomes of a parametric investigation, considering four different kinematic boundary conditions (Cantilever, Simply-Supported, Clamped-Pinned, and Doubly-Clamped) while varying the nonlocal parameter and material gradient index, are presented and discussed. Additionally, the normalized natural frequencies for the second, third, fourth and fifth modes of vibrations are provided and analyzed for each case under study. The results underscore the model's effectiveness in capturing surface energy effects on the overall dynamic behavior of functionally graded Bernoulli-Euler nanobeams, offering a cost-effective approach for designing and optimizing nano-scaled structures.

Efficient processing of end-of-life lithium-ion batteries of electric vehicles is important and a pressing challenge for a circular economy. Regardless of whether the processing strategy is recycling, repurposing or remanufacturing, the first processing step would usually involve disassembly. As battery disassembly is a dangerous task, efforts have been made to robotise it. In this paper, a robotic disassembly platform using four industrial robots is proposed to automate the non-destructive disassembly of a plug-in hybrid electric vehicle battery pack into modules. The work was conducted as a case study to demonstrate the concept of autonomous disassembly of an electric vehicle battery pack. A two-step object localisation method based on visual information is used to overcome positional uncertainties from different sources and is validated by experiments. Also, the unscrewing system is highlighted, and its functions, such as handling untightened fasteners, loosening jammed screws, and changing the nutrunner adapters with square drives, are detailed. Furthermore, the time required for each operation is compared with that taken by human operators. Finally, the limitations of the platform are reported and future research directions are suggested.

Pancreatic neuroendocrine neoplasms (pNENs) are rare tumors accounting for only 1-2% of all pancreatic tumors. pNENs are pathologically heterogeneous and are categorized into three groups (neuroendocrine tumor: NET G1, NET G2 and neuroendocrine carcinoma: NEC) on the basis of Ki-67 proliferation index and mitotic count according to the 2010 WHO classification of gastroenteropancreatic NENs. NEC in this classification includes both histologically well-differentiated and poorly differentiated subtypes, and modification of the WHO 2010 classification is under discussion based on genetic and clinical data. Genomic analysis has revealed NETs G1/G2 have genetic alterations in chromatin remodeling genes such as MEN1, DAXX and ATRX, whereas NECs have an inactivation of TP53 and RB1, and these data suggest that different treatment approaches would be required for NET G1/G2 and NEC. While there are promising molecular targeted drugs, such as everolimus or sunitinib, for advanced NET G1/G2, treatment stratification based on appropriate predictive and prognostic biomarkers is becoming an important issue. The clinical outcome of NEC is still dismal, and a more detailed understanding of the genetic backround together with preclinical studies to develop new agents, including those already under investigation for SCLC, will be needed to improve the prognosis.

Background: The Victorian era in Great Britain was a historical period that brought about profound changes for humanity. The confluence of various factors fostered the development of numerous scientific disciplines. In the field of health sciences, Florence Nightingale played a central role. Following her training as a nurse and her role as superintendent during the Crimean War, she made decisive contributions to establishing a public health network. Methods: This is a retrospective historical heuristic and hermeneutic study analyzing documentation of Nightingale's contributions to public health from around 1890 to 1900. The historical method was used to collect, classify, and analyze primary and secondary sources relevant to the study's objectives. Results: Nightingale supported the development of the concept of “health at home” by training women to implement healthy measures that contributed to the well-being of families and communities. Through the training and development of a formal “Health Missioners program”, she provided the necessary guidance to improve the health of rural communities across the English countryside. Conclusion: The role of Health Missioners has persisted, as health visitors continue to visit homes in the United Kingdom. Therefore, the contribution of Florence Nightingale to public health is unquestionable. This study was not registered.

Objective: Fludeoxyglucose F18 positron emission tomography (FDG PET) can give early clues for diagnosing Alzheimer’s disease (AD). Our objective was to use the same scan to predict Apolipoprotein E4 (ApoE4), known to be a risk factor. A second objective was to determine the brain regions and imaging features associated with this gene allele that can potentially help elucidate the mechanisms of the disease and better comprehend the images. Method: We employed data from 112 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). PET and structural MRI data were co-registered with ANTx, and the Freesurfer tool delineated 95 whole brain, 19 hippocampal, and 9 amygdala regions. Using PyRadiomics we extracted 120 radiomic features from these segments. We employed a hybrid feature selection strategy. The HistGradientBoosting (HGB) classifier was evaluated using stratified five-fold cross-validation. Results: The proposed radiomics model predicted the homozygous ApoE4 genotype, with an AUC of 0.945 an accuracy of 0.875, a sensitivity of 0.914, and a specificity of 0.838. Reducing the feature set to seven key features resulted in a slightly decreased performance (AUC: 0.889). The mean values of the features showed statistically significant (p<0.05) incremental deterioration between different groups of homozygous ApoE4 carriers. Conclusion: Our findings underscore the critical role of specific brain regions and associated features in differentiating ApoE4 carriers. The hippocampus, entorhinal cortex, amygdala, thalamus, and pars orbitalis exhibited significant associations with the ApoE4 genotype. By employing SHAP analysis, we identified key features driving model predictions, enhancing interpretability, and providing insights into the underlying pathophysiology.

AI advances integrate generative design tools in architecture, providing architects with sophisticated design options. It enables the creation of intricate, high-performing projects by exploring diverse design possibilities with AI and algorithms. Generative AI and generative design empower architects to create better-performing, sustainable, and efficient design solutions and explore diverse design possibilities. This paper leverages multimodal generative AI to enhance design creativity by combining textual and visual inputs. Blockchain technology converts design metadata into NFTs, ensuring secure, authentic, and traceable data storage. The framework addresses data ownership, legal adherence, and client-architect collaboration and is entirely scalable for digital design authentication. This research exemplifies the pragmatic fusion of Generative AI and blockchain technology applied in architectural design for more transparent, secure, and effective results. This study provides a strategy that uses generative AI technologies to achieve an efficient and creative workflow in the early stages of architectural design.

Because Canadian Nitrogen (N) fertilizer use has more than doubled since 1990 (1.2 to 2.9 MtN by 2021), a better understanding of this trend is needed. A comprehensive set of Recommended N Rates (RNR) that agreed with fertilizer sales data from 1996 and 2001 was compared with the Fertilizer Use Survey (FUS). The FUS was conducted from 2014 to 2021, with 2017 being the most representative year for these data. Using non-parametric statistics, confidence intervals were derived from the histograms used to present the FUS data. N application rates from the RNR for Canola, Spring and Duram wheat, and Oats in the west were all below their respective FUS confidence intervals, whereas N application rates for Grain corn showed almost no difference in N use between the RNR and FUS. Crop-specific N application rates interpolated from the RNR and FUS were integrated over their respective crop areas and plotted against national fertilizer sales records from 1990 to 2021. The rapid increase in N use between 2001 and 2017 (0.89 MtN), 90% of it (0.80 MtN) in Western Canada, was primarily due to increased application rates per crop, rather than crop area changes. The FUS-RNR interpolations were a good approximation of N sales records and could improve farm GHG emissions modelling. The economically important crops in Western Canada should be the main focus for N-related GHG reduction measures, but production losses need to be avoided.

In this review, we summarize recent progress in crystal growth and understanding the influence of crystal structure on the superconductivity in pure and Pb-doped Bi2Sr2CuOy (Bi-2201) materials belonging to the overdoped region of high temperature cuprate superconductors. The crystal growth of Bi-2201 superconductors faces challenges due to intricate materials chemistry and lack of knowledge of corresponding phase diagrams. Historically, a crucible-free floating zone method has emerged as the most promising growth approach for these materials, resulting in high-quality single crystals. This review outlines the described in the literature and the authors' synthesis endeavors, encompassing Pb-doped Bi-2201 crystals, detailed structural characterization of as-grown and post-growth annealed samples, and highlights optimal growth conditions that yield large-size, single-phase, and compositionally homogeneous Bi-2201 single crystals.

The study of coherent vortices remains an urgent field of singular optics of vortex beams. In this paper, coherent properties of partially coherent vortex Bessel—Gaussian optical beams propagating through a uniform medium (free space) or a turbulent atmosphere are examined theoretically. The consideration is based on analytical solution of the equation for the transverse second-order mutual coherence function of the field of a partially coherent optical radiation in a turbulent atmosphere. For the partially coherent Bessel—Gaussian beam, the second-order mutual coherence function of the source field is taken as a Gaussian Shell-model. In this approximation, we analyze the behavior of the coherence degree and the integral coherence scale of these beams as a function of the propagation pathlength, propagation conditions, and beam parameters, such as the radius of the Gauss factor of the beam, parameter of the Bessel factor of the beam, topological charge, and correlation width of the source field of partially coherent radiation. In addition, the integral coherence scale of the partially coherent vortex Bessel—Gaussian beam is compared with that of the partially coherent Gaussian beam. It is found that as a partially coherent vortex Bessel—Gaussian beam propagates through a turbulent atmosphere, there appear not two (as might be expected: one due to atmospheric turbulence and another due to partial coherence of the source field), but only one ring dislocation of the coherence degree (due to the simultaneous effect of both these factors on the optical radiation). In addition, it is shown that the dislocation of the coherence degree that affects significantly the beam coherence level is formed only for beams, for which the coherence width of the source field is larger than the diameter of the first Fresnel zone.

Identifying influential actors within social networks is pivotal for optimizing information flow and mitigating the spread of both rumors and diseases. Several methods have emerged to pinpoint these influential entities in networks that are represented as graphs. In these graphs, nodes corre-spond to individuals and edges indicate their connections. This study focuses on centrality measures, prized for their straightforwardness and effectiveness. We categorize structural central-ity into two: local, considering a node's immediate vicinity, and global, accounting for overarching path structures. Some techniques blend both centralities to highlight nodes influential at both mi-cro and macro levels. Our paper presents a novel centrality measure, accentuating node degree and incorporating the network's broader features, especially paths of different lengths. Through Spearman and Pearson's correlations tested on seven standard datasets, our method proves its merit against traditional centrality measures. Additionally, we employ the SIR model, portraying disease spread, to further validate our approach. The ultimate influential node is gauged by its capacity to infect the most nodes during the SIR model's progression. Our results indicate a nota-ble correlative efficacy across various real-world networks relative to other centrality metrics.

With the trend of public infrastructure becoming more sustainable, large multi-purpose sports venues (LMPSVs) have become one of the world's most complex architectural projects and one of the landmark buildings of an international city. LMPSVs will lead the world in sustainable design, construction and operational innovations, and play a crucial role in raising awareness of sustainability around the world. System Thinking (ST), System Dynamics (SD) and Sustainable System Development (SSD) theories are three interrelated concepts that together form a methodological framework for solving complex system problems and driving strategies. The purpose of this study is to examine how LMPSVs can implement environmental, social, governance, and innovation (ESGI) enterprise transformation strategy (ETS) based on a sustainable systems development (SSD) framework. In view of the current global environmental challenges and social responsibility requirements, the motivation of this study is to provide an integrated transformation pathway for LMPSVs to achieve the goal of sustainable development and to contribute to the field of related disciplines. The methodology of this research adopts a combination of literature review and case study analysis, and the theoretical basis is mainly drawn from cutting-edge research in the fields of sustainable development, corporate social responsibility (CSR) and environmental management. Then, by analyzing successful transformation cases in China, we extract data and information to explore the application and effectiveness of these strategies in practice. The results of the study show that by implementing ESGI-based transformation strategy, LMPSVs can not only make significant progress in terms of environmental protection, social responsibility, and governance structure, but also drive long-term corporate growth and competitiveness through innovation. Specifically, these results are realized in terms of increased efficiency in energy use, improved waste management, community involvement and increased stakeholder satisfaction. The study concludes by emphasizing that the SSD-based ESGI Transformation Strategic framework provides a sustainable pathway for LMPSVs. In the future, the extension of this transformation strategy will help a wider range of industry sectors to achieve sustainable development goals, and has wide application potential and far-reaching social significance.

Diabetes is one of the fastest spreading diseases of civilisation in the 21st century. The aim of the study was twofold: 1) to find differences in personality traits, self-esteem, body- esteem, and imagery between healthy women and women with diabetes 2) to check whether there are differences in analyzed factors in women with diabetes who participate in sports compared to women who do not. We used 3 questionnaires: Imagination: in sport - short form, Self-Esteem Scale (SES), and BFIS Personality, which were tested online. We found that women with diabetes were characterised by significantly higher neuroticism and lower extraversion and higher conscientiousness (marginally significant). We also found that women with diabetes who practice sport rated their bodies more highly in terms of sexual attractiveness and made better use of imagined affirmations than healthy women who were not active. Our study provides new insights into diabetics in terms of coping with the disease.

Late-stage epithelial ovarian cancer (EOC) involves widespread dissemination of malignant disease throughout the peritoneal cavity, often accompanied by ascites. EOC metastasis relies on the formation of multicellular aggregates, called spheroids. Given that Liver Kinase B1 (LKB1) is required for EOC spheroid viability and LKB1 loss in EOC cells decreases tumor burden in mice, we investigated whether the LKB1 complex controls invasive properties of human EOC spheroids. LKB1 signalling was antagonized through CRISPR/Cas9 genetic knockout of LKB1 and/or RNAi-dependent targeting of STE20-related kinase adaptor protein (STRAD; an LKB1 activator). EOC spheroids expressing nuclear GFP (green) or mKate2 (red) constructs were embedded in Matrigel for real-time live-cell invasion monitoring. Migration and invasion were also assessed in spheroid culture using Transwell chambers, spheroid reattachment, and mesothelial clearance assays. The loss of LKB1 and STRAD signalling decreased cell invasion through Matrigel and Transwell membranes, as well as mesothelial cell clearance. In the absence of LKB1, zymographic assays identified a loss of matrix metalloproteinase (MMP) activity, whereas spheroid reattachment assays found that coating plates with fibronectin restored the invasive potential. A three-dimensional EOC organoid model demonstrated that organoid area was greatly reduced by LKB1 loss. Overall, our data indicated that LKB1 and STRAD facilitated EOC metastasis by promoting MMP activity and fibronectin expression. Given that LKB1 and STRAD are crucial for EOC metastasis, targeting LKB1 and/or STRAD could disrupt the dissemination of EOC, making inhibitors of the LKB1 pathway an alternative therapeutic strategy for EOC patients.

The FAS ligand (FASLG) is expressed on lymphocytes, which employ it to activated death receptors on targets cells. Cancer cells are generally resistant to apoptosis triggered by FASLG. In this work we found a way to circumvent this resistance by treatment with actinomycin D (ActD) and nutlin-3a (Nut3a). We selected this drug combination based on our transcriptomic data showing strong activation of proapoptotic genes, including the ones for receptor mediated apoptosis, in cells exposed to actinomycin D and nutlin-3a. To test our hypothesis, we pre-exposed cancer cell lines to this drug combination for 45h and next we treated them with recombinant FASLG. This almost instantaneously killed most cells. Actinomycin D and nutlin-3a strongly synergized in the sensitization because the effect of the drugs acting solo was not as spectacular as the drug combination, which together with FASLG killed more than 99% of cells. Based on the caspase activation pattern (caspase-8, caspase-9, caspase-10), we conclude that both extrinsic and intrinsic pro-apoptotic pathways were engaged. In engineered p53-deficient cells this pro-apoptotic effect was completely lost. Therefore, the combination of ActD+Nut3a activates p53 in an extraordinary way, which overcomes the resistance of cancer cells to apoptosis triggered by FASLG. Interestingly, other combinations of drugs, e.g., etoposide + nutlin-3a, actinomycin D + RG7112 and actinomycin D + idasanutlin had similar effect. Moreover, normal human fibroblasts are less sensitive to death induced by ActD+Nut3a+FASLG. Our findings create the opportunity to revive the abandoned attempts of cancer immunotherapy employing the recombinant FAS ligand.

1) Introduction: Brain parcellation is an important processing step in the analysis of structural brain MRI. Existing software implementations are optimized for fully developed adult brains, and provide inadequate results when applied to neonatal brain imaging. 2) Methods: We developed a semi-automated pipeline, NeBSS, for extracting 50 discrete brain structures from neonatal brain MRI, using an atlas registration method that leverages the existing ALBERT neonatal atlas 3) Results: We demonstrate a simple linear workflow for neonatal brain parcellation. NeBSS is robust to variation in imaging acquisition protocol and magnet field strength. 4) Conclusion: NeBSS is a robust pipeline capable of parcellating neonatal brain MRIs using a simple processing workflow. NeBSS fills a need in clinical translational research in neonatal imaging, where existing automated or semi-automated implementations are too rigid to be successfully applied to multi-center neuroprotection studies and clinically heterogeneous cohorts. The software is open source and freely available.

Histone Deacetylase 6 (HDAC6) is a large multidomain protein that deacetylates lysine residues on cytoplasmic proteins, influencing a wide range of cellular processes. Both the catalytic and non-catalytic functions of HDAC6 are implicated in cancer development and progression. Over a decade of clinical trials with catalytic domain inhibitors, such as Ricolinostat (ACY1215), has shown that these drugs are well tolerated and can alleviate chemotherapy-induced peripheral neuropathies. However, their effectiveness in treating solid tumors remains uncertain due to the limited number of clinical trials and the small size of patient cohorts, leading to inconclusive results. HDAC6 activity is regulated by protein-protein interactions and post-translational modifications, which may allosterically influence its catalytic domains. Therefore, targeting HDAC6 in cancer therapy with small molecule inhibitors requires a more sophisticated understanding of its role within the tumor microenvironment, including whether its expression correlates with deacetylase activity. A comprehensive evaluation of both its enzymatic and non-enzymatic functions could be crucial in developing more effective strategies for targeting HDAC6 in cancer.

Rift Valley Fever (RVF), is a viral zoonotic disease predominant in East Africa and transmitted by Aedes mosquitoes carrying the virus. Using the systematic literature review approach, the present study evaluated machine learning techniques and time series approaches to find literature on the impact of climatic changes on RVF outbreaks published between 1930 and 2024. The literature search involved databases including PubMed, PLOS ONE, JSTOR, Web of Science, Google Scholar, and SCOPUS (Kenmoe et al., 2023).The results show that most of the articles were published between 2018 and 2022, and most of the articles were from United States, France, and Kenya. We conducted a detailed review of the articles using the PRISMA 2020 flow chart, screening and qualifying 10,015 articles. Some articles revealed significant gaps in both internal and external validation. Therefore, future research should focus on developing multi-disciplinary models that incorporate climatic condition, geographical, biological, and social factors.

Ribavirin and its analogues exhibit an in vitro antiproliferative effect in cancer cells. In this work we studied the biological activities of a number of oxymethyl derivatives of ribavirin’s aglycon – 1,2,4-triazole-3-carboxamide. Oxymethyl derivatives of 1,2,4-triazole-3-carboxamide with substitu-tions at the fifth or first position of the triazole ring, were synthesized and their antiproliferative and antimicrobial effects were assessed. For both series the presence of an antiproliferative effect was inves-tigated and in the case of 1-oxymethyl derivatives was shown an antimicrobial potential against a Gram-positive bacteria Micrococcus luteus and Gram-negative bacterium Pseudomonas aeruginosa. The obtained results showed that the n-decyloxymethyl derivatives induced leukemia cell death at low mi-cromolar concentrations. We confirmed that n-decyloxymethyl derivatives of ribavirin inhibited cell cy-cle progression and induced accumulation of leukemia cells in subG1-phase. The molecular docking results suggest that oxymethyl derivatives may act by inhibiting translation initiation due to interfering with eIF4E assembly. The outcome results relived that active derivatives (1- or 5-n-decyloxymethyl-1,2,4-triazole-3-carboxamides) can be considered as a lead compound for anti-cancer treatments.

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

Degenerative disc disease (DDD) is a pervasive condition that limits quality of life and burdens economies. Traditional pharmacological treatments aimed at slowing degeneration are ineffective in the long-term. Orthobiologics, regenerative agents derived from the patient’s own tissue, are a promising emerging therapy for degenerative disc disease. This review first outlines the pathophysiology of degenerative disc disease, highlighting the limitations of existing treatments and explores the orthobiologic tools for treating degenerative disc disease (platelet-rich plasma, mesenchymal stem cells). Their history in regenerative medicine is outlined, demonstrating how in vitro evidence informed preclinical animal studies on their efficacy in treating degenerative disc disease. Finally, clinical trials utilizing these treatment options are reviewed and directions for future research are outlined. Although the current clinical evidence available is limited to propagate their routine clinical usage the field holds immense potential in the management of DDD. There is room for these treatments to be optimized for effective consistent clinical outcomes in DDD.

This study explores the multifaceted influence of litter size, maternal care, exercise, and aging on rats' neurobehavioral plasticity and dentate gyrus microglia dynamics. Body weight evolution revealed a progressive increase until maturity, followed by a decline during aging, with larger litters exhibiting lower weights initially. Notably, exercised rats from smaller litters displayed higher body weights during mature and aged stages. Dentate gyrus volumes showed no significant differences among groups, except for aged sedentary rats from smaller litters, which exhibited a reduction. Maternal care varied significantly based on litter size, with large litter dams showing lower frequencies of caregiving behaviors. Behavioral assays highlighted the detrimental impact of a sedentary lifestyle and reduced maternal care/large litters on spatial memory, mitigated by exercise in aged rats from smaller litters. Microglial dynamics in the layers of dentate gyrus revealed age-related changes modulated by litter size and exercise. Exercise interventions mitigated microgliosis associated with aging, particularly in aged rats. These findings underscore the complex interplay between early-life experiences, exercise, microglial dynamics, and neurobehavioral outcomes during aging.

Vascular rings are a rare congenital anomaly of the aortic arch in which a ring-shaped structure forms surrounding the trachea and/or esophagus, potentially causing compression. We describe the case of a 14-month-old female patient with failure to thrive secondary to dysphagia, and a vascular ring formed by a right aortic arch, an aberrant left subclavian artery, and a left liga-mentum arteriosum. Surgical repair involved ligamentum arteriosum division, Kommerell’s di-verticulum obliteration, and left subclavian artery re-implantation into the left carotid artery. Endoscopy and EndoFLIPTM evaluated intraoperative improvement in esophageal narrowing and impedance, respectively. Postoperative period was uneventful and follow-up visits demonstrated dysphagia resolution and a patent re-implanted left subclavian artery.

Introduction: Immune checkpoint inhibitors (ICI) are used to treat various malignancies. They block the inhibitory signals of tumor cells and enhance the inflammatory cascade which results in tumor killing. However, this can lead to unchecked inflammation throughout the body, leading to various adverse effects. A rare gastrointestinal adverse effect of ICI therapy is the development of immune-mediated celiac disease. This entity has a similar clinical presentation to the more common ICI-induced enterocolitis. Our study aims to determine the clinical characteristics and optimal treatment strategies for this rare ICI toxicity, and differentiate it from ICI-induced enterocolitis. Methods and Material: We conducted a retrospective analysis of eight cases of ICI-induced celiac disease and 24 cases of ICI-induced enterocolitis from the literature. Data on patient demographics, clinical history, therapeutic interventions and outcomes were collected. Comparative analysis was performed to identify the key differences between the two groups. Results: Patients with ICI-induced celiac disease were more likely to have a pre-existing autoimmune condition and HLA-DQ2 positivity. Significant differences in clinical manifestations, histological findings, and treatment outcomes were observed. Notably, weight loss, nutritional deficiencies and electrolyte abnormalities were more commonly associated with ICI-CD. On pathology, duodenal villous blunting was noted more commonly with ICI-induced celiac disease. Initiating a gluten-free diet led to rapid improvement in patients with ICI-induced celiac disease, while immunosuppressive therapy did not have an impact. Conclusion: ICI-induced celiac disease is a rare and underrecognized gastrointestinal adverse effect of ICI therapy, often misdiagnosed as ICI-induced enterocolitis. Early recognition and treatment with a gluten-free diet can lead to rapid symptom resolution, sparing patients from unnecessary systemic immunosuppression and discontinuation of antineoplastic immunotherapy.

This review details the extraction, characterization and utilization of seaweed-derived biopolymers for future packaging applications. The review is contextualized within the broader scope of the challenge of plastic pollution and the current urgent need for more sustainable packaging materials. Macroalgae (or seaweed) has been highlighted as a promising source of biopolymers, most commonly sodium alginate, agar and carrageenan, for reasons such as a rapid growth rate and decreased environmental impact when compared to terrestrial plant-life. Extraction methods detailed include the traditional solvent-based extraction to more sustainable developments such as ultrasound assisted extraction, microwave assisted extraction and bead milling. The review additionally presents the characterization techniques most pertinent in determining the applicability of these biopolymers in packaging applications. Properties of key importance to the development of sustainable packaging materials such as thermal properties, mechanical strength, barrier properties and biodegradability are highlighted in comparison to conventional petroleum-based plastics. This review concludes by realistically identifying the challenges faced by implementing seaweed-based biopolymers into packaging structures, such as cost-effectiveness, scalability, performance while suggesting future directions to mitigate these issues and improve the commercial viability of these materials for the packaging industry.

With many Americans eager to resume travel after prolonged restrictions from the coronavirus pandemic, car rentals are on the rise. According to Auto Rental News, “2021 U.S. Car Rental Revenue Climbs 21% Year-Over-Year” (Brown, 2021). In conjunction with increased car rental, and associated travel, we can expect to see an increase in cyber security and data privacy attacks. In the digital age, enterprises have a responsibility to protect consumers’ personally identifiable information (PII). As it pertains to rental vehicles, when consumers connect their mobile devices to a rental vehicle’s Entertainment and Infotainment System or utilize the built-in navigation feature, they do so, unbeknownst to themselves that the information from their devices is transferring to the vehicle, where it will remain, unless properly expunged from the system. A large majority of consumers are blissfully unaware that their PII is being stored, and how easy it would be for an adversary to potentially breach their data security and privacy. To expand upon this hypothesis, I conducted a further investigation on the subject, by partaking in the rental of three different vehicles, each belonging to a different manufacturer (Nissan, Chrysler, and Maserati), from three different vehicle rental companies (Enterprise, Hertz and Turo). I then, as a consumer, tested my hypothesis to determine if, I was able to easily breach the prior consumers’ data security and privacy by viewing devices that had previously connected to the vehicle, as well as any of the previous consumers’ personal information. The results were undeniable; the PII of the previous consumers is not protected.

Significant global challenges, particularly in the areas of economics, society, and the environment, are posed by urbanization. In this researcher-led study, we look at how Jordan is trying to bring the Sustainable Development Goals (SDGs) to life in its capital, Amman, by bringing urban laws in line with these global goals. The paper finds legislative flaws that prevent SDG incorporation through a thorough analysis of the Amman Building and Regulation Act of 2019. Some of the main points covered are public participation, the use of renewable energy sources, sustainable construction practices, resilience in urban areas, and the management of natural resources. Although a lot of work has gone into it, the analysis shows that if Jordan wants to accomplish the 2030 Agenda and have sustainable urban growth in the future, it must overcome these institutional and legal barriers. As a model for other cities facing a similar challenge, Amman is being asked to lead the way in SDG localization through more public involvement, new laws, and innovative resource management.

This study explores the dynamics of transparency and accountability in supplier relationship management (SRM) within the e-commerce sector. It investigates how e-commerce platforms and their suppliers navigate complexities to foster trust, enhance collaboration, and ensure ethical practices in global supply chains. The research employs a qualitative approach, utilizing semi-structured interviews with industry stakeholders to gather insights into current practices, challenges, and strategies in SRM. Findings highlight transparency as pivotal for sharing critical information such as sales forecasts, inventory levels, and pricing strategies, enabling suppliers to align operations with market demands effectively. However, achieving transparency faces hurdles including data privacy concerns and competitive sensitivities, necessitating robust data security measures and clear communication protocols. Accountability mechanisms, such as formal agreements and governance frameworks, emerge as essential for mitigating risks, resolving disputes, and ensuring compliance with ethical and regulatory standards across diverse contexts. Technological innovations like AI, blockchain, and big data analytics are transforming SRM by enhancing supply chain visibility, operational efficiency, and decision-making capabilities. Cultural factors and regulatory compliance also significantly influence SRM practices, shaping communication styles, relationship dynamics, and legal considerations. Emerging trends such as sustainable sourcing practices and collaborative partnerships are reshaping SRM, emphasizing sustainability and responsible business practices. This study contributes to the understanding of effective SRM strategies, offering insights and recommendations for stakeholders navigating the complexities of e-commerce supply chains.

This qualitative research investigates sustainable procurement practices, focusing on the integration of environmental and social criteria in supplier evaluation processes. The study explores how organizations, ranging from large multinational corporations to smaller enterprises, navigate sustainability challenges and opportunities within their procurement strategies. Data were gathered through semi-structured interviews with procurement professionals and sustainability managers across diverse industries. Themes identified include varying organizational commitments to sustainability, from structured policies and resource allocation in larger firms to reactive approaches constrained by resource limitations in smaller entities. Effective supplier relationship management emerged as crucial, facilitating collaborative partnerships aimed at improving environmental and social performance across supply chains. Motivations for sustainable procurement practices encompass regulatory compliance and responding to consumer demands for eco-friendly products, shaping procurement decisions to enhance market competitiveness and stakeholder satisfaction. Environmental and social criteria integration in supplier evaluations highlighted strategies such as lifecycle assessments and sustainable sourcing practices, aimed at minimizing environmental footprints and promoting ethical labor practices. Benefits included cost savings and enhanced brand reputation, tempered by challenges such as higher procurement costs and supplier resistance. Leadership commitment and organizational culture were identified as critical enablers of sustainable procurement, influencing strategic alignment and fostering a culture of sustainability within organizations. The study underscores the transformative potential of sustainable procurement in achieving organizational resilience and contributing to global sustainability goals.

The integration of supply chain analytics and Customer Relationship Management (CRM) systems represents a critical strategy for organizations seeking to enhance operational efficiency and customer-centricity in today's competitive business environment. This qualitative study investigates the motivations, strategies, challenges, and outcomes associated with integrating supply chain analytics with CRM systems across diverse industries. Motivations for integration include gaining a unified view of customer data, improving decision-making capabilities, enhancing operational efficiency, and ensuring strategic alignment across organizational functions. Strategies employed by organizations include cross-functional collaboration, investment in scalable technology platforms, and leadership commitment to drive successful integration initiatives. Despite the potential benefits, the integration process presents challenges such as data integration complexities, technical interoperability issues, and organizational resistance to change. Addressing these challenges requires robust technological solutions, effective change management strategies, and a proactive approach to data governance and security. The study identifies significant outcomes from integration efforts, including improved operational efficiency through streamlined processes and optimized resource allocation, enhanced customer insights leading to personalized experiences, and strengthened strategic decision-making supported by real-time analytics.

Digital transformation is revolutionizing supply chain management, profoundly influencing marketing effectiveness across industries. This qualitative study explores the impact of digital transformation on supply chains and its implications for marketing strategies. Through in-depth interviews, case studies, and document analysis, the research elucidates how digital technologies such as IoT, blockchain, AI, and advanced analytics are reshaping supply chain dynamics. Key findings highlight enhanced supply chain visibility, improved decision-making capabilities, and strengthened collaboration among supply chain partners. These technological advancements empower organizations to optimize inventory management, anticipate market trends, and deliver personalized customer experiences, thereby enhancing operational efficiency and customer satisfaction. Furthermore, the study underscores the role of digital transformation in promoting sustainability and ethical practices within supply chains. Technologies like blockchain facilitate transparent and traceable supply chains, supporting initiatives for responsible sourcing and environmental stewardship. Despite the transformative benefits, the study identifies challenges including significant investment requirements, integration complexities, and data security concerns. Strategic approaches to technology adoption, robust cybersecurity measures, and employee training are essential for overcoming these challenges and maximizing the benefits of digital transformation. Overall, this study contributes to understanding how digital transformation drives innovation in supply chain management and enhances marketing effectiveness. By embracing digital technologies and aligning supply chain strategies with marketing objectives, organizations can navigate competitive landscapes, meet evolving consumer expectations, and achieve sustainable growth in the digital era.

Researchers are increasingly concerned about microplastics (MPs) since they have proven to be detrimental to the environment and humans. They not only contribute to the accumulation of plastics in the environment, but they can also help spread micropollutants through absorption. MPs have entered the environment through a variety of channels, including direct discharge through human activities, the textile industry, and wastewater treatment systems. Wastewater treatment plants (WWTPs) are seen as the final line of defense, forming a barrier between MPs and the environment. The most common MPs found in wastewater are polyethylene terephthalate (PET), polyethylene (PE), polypropylene (PP), and polystyrene. The purpose of this study is to investigate and measure the efficacy of conventional and advanced technologies in removing microplastic. The fate of MPs in WWTPs and their impact on various wastewater treatment processes will be thoroughly examined. Both conventional and advanced methods of treatment will be discussed. Conventional methods include coagulation/flocculation, sedimentation, and filtration. Advanced treatment methods that will be discussed include membrane bioreactors, rapid sand filtration, electrocoagulation, and photocatalytic degradation. Despite the high removal of MPs, WWTPs remain an important entry point into aquatic and terrestrial systems due to the large volumes involved and the quantity of sludge reused through land application. Also, the complex interactions between MPs and other environmental pollutants may broaden MPs' effects on wastewater treatment processes, which have yet to be fully researched. Furthermore, potential issues with MP removal from treatment procedures and microplastic remediation techniques in drinking water was discussed.

This study explores the intricate dynamics of customer-centric supply chains and the pivotal role of marketing innovations in enhancing efficiency and customer satisfaction. Employing a qualitative research methodology, semi-structured interviews were conducted with key stakeholders in supply chain management across various industries, providing rich insights into the practices and perceptions related to customer-centric strategies. The findings highlight the centrality of understanding and anticipating customer needs, which necessitates a cultural shift within organizations to prioritize customer satisfaction at all levels. Digital marketing tools, data analytics, e-commerce platforms, and social media emerged as critical enablers of these customer-centric supply chains, facilitating real-time insights, direct customer engagement, and personalized experiences. The integration of these technologies has led to more accurate demand forecasting, optimized inventory levels, and enhanced agility and responsiveness in operations. Furthermore, the study underscores the importance of collaboration and partnership within the supply chain network, emphasizing joint initiatives and strong relationships with stakeholders as key drivers of improved resource utilization and service levels. Sustainability, entrepreneurship, and emotional intelligence also play significant roles in shaping effective customer-centric supply chains. Sustainable practices meet growing consumer demands for environmental and social responsibility, while an entrepreneurial mindset fosters continuous innovation and competitiveness. Emotional intelligence among leaders and employees enhances trust, conflict resolution, and collaboration, contributing to a positive organizational culture and superior customer satisfaction. Overall, this study provides comprehensive insights and actionable recommendations for businesses seeking to navigate the complexities of customer-centric supply chain management and leverage marketing innovations to achieve sustainable competitive advantage.

This qualitative research explores the dynamics of collaborative marketing and supply chain strategies for enhanced product lifecycle management. Through in-depth interviews with industry stakeholders, key themes, challenges, and implications of collaboration emerge. Trust, communication, technology, strategic alignment, and sustainability are identified as critical factors driving successful collaboration. The study highlights the transformative potential of collaboration in driving innovation, efficiency, and customer satisfaction. Despite challenges such as aligning objectives and ensuring data security, collaborative strategies offer significant opportunities for value creation and differentiation. The findings underscore the importance of building trust, leveraging technology, and integrating sustainability considerations in collaborative efforts. Strategic alignment and cultural fit among partners are essential for overcoming differences and achieving common goals. The implications of the research extend to practitioners seeking to enhance collaboration in their organizations and researchers exploring collaborative practices in different industries and contexts. Future research could further explore the impact of collaboration on stakeholder perspectives and outcomes. By addressing challenges and leveraging opportunities, organizations can maximize the benefits of collaborative marketing and supply chain strategies to drive sustainable growth and competitive advantage in today's dynamic business landscape.

Numerous scientific fields employ entropy, the Shannonian measure of disorder and inaccessible information. Current paper examines educational uses of entropy. The major objectives of this survey are to create a coherent perspective of the applicability of classical entropies and to provide a concise detailed explanation that blends technical pertinence with conceptual extraction from the most recent literature. What's more intriguing are the closing thoughts mixed with a few unsolved issues and the creation of a future work schedule in these areas.

This paper presents the formative assessment to implement mobile portable chest X-ray (PDX) machines for Tuberculosis (TB) contact tracing in Oyo and Osun States, Nigeria. This descriptive qualitative study was carried out in 8 Local Government Areas, and 24 FGDs and 33 KIIs were conducted using a 4-stage sampling technique to select participants. Validated transcribed notes were entered and analysed using Nvivo. The respondents' ages ranged from 17-85 years, with a mean age of 42.08±14.9 years, and 4.0% had a postgraduate degree. The majority of the government officials stated that deploying the PDX machine intervention at the community level is the best means as it offers a level of convenience to the community members in the sense that there will be limited disruption to their daily activities as well as zero concerns about the cost of transportation to the health facility. The portable X-ray machine intervention should be implemented at the community level for contact tracing to allow more TB contacts living with the index patient to be screened. However, the PDX machine can also be set up in a special location, and the TB contacts can be invited for the screening.

Heart failure (HF) management in type 1 diabetes (T1D) is particularly challenging due to its increased prevalence and the associated risks of hospitalization and mortality, driven by diabetic cardiomyopathy. Sodium-glucose cotransporter-2 inhibitors (SGLT2-i) offer a promising avenue for treating HF, specifically the preserved ejection fraction variant most common in T1D, but their utility is hampered by the risk of euglycemic diabetic ketoacidosis (DKA). This review investigates the potential of SGLT2-i in T1D HF management, alongside the emergent Continuous Ketone Monitoring (CKM) technology as a means to mitigate DKA risk, through a comprehensive analysis of clinical trials, observational studies, and reviews. The evidence suggests SGLT2-i significantly reduce HF hospitalization and enhance cardiovascular outcomes. However, their application in T1D patients remains limited due to DKA concerns. CKM technology emerges as a crucial tool in this context, offering real-time monitoring of ketone levels, which enables the safe incorporation of SGLT2-i into treatment regimes by allowing for early detection and intervention in the development of ketosis. The synergy between SGLT2-i and CKM has the potential to revolutionize HF treatment in T1D, promising improved patient safety, quality of life, and reduced HF-related morbidity and mortality. Future research should aim at clinical trials directly assessing this integrated approach, potentially guiding new management protocols for HF in T1D.

Half-metallic semi-Heusler compounds are currently at the forefront of scientific research due to their potential applications in spintronic devices. Unlike other semi-Heuslers, the p0(d0)-d compounds do not appear to crystallize in the typical variant of the C1b structure. We investigate this phenomenon in the p0-d Heusler compounds LiYGa and LiYGe, where Y varies between Ca and Zn, using first-principles ab-initio electronic band structure calculations. We examine the electronic and magnetic properties of these compounds in relation to the three possible C1b structures. Notably, LiVGa, LiVGe, LiMnGa, and LiCrGe are half-metallic ferromagnets across all three variations of the C1b lattice structure. Our findings will serve as a foundation for future experimental studies on these compounds.

This paper presents two novel bio-inspired particle swarm optimisation (PSO) variants: biased eavesdropping PSO (BEPSO) and altruistic heterogeneous PSO (AHPSO). These algorithms are inspired by types of group behaviour found in nature that have not previously been exploited in search algorithms. The primary search behaviour of the BEPSO algorithm is inspired by eavesdropping behaviour observed in nature coupled with a cognitive bias mechanism that enables particles to make decisions on cooperation. The second algorithm, AHPSO, conceptualises particles in the swarm as energy-driven agents with bio-inspired altruistic behaviour which allows the formation of lending-borrowing relationships. The mechanisms underlying these algorithms provide new approaches to maintaining swarm diversity which contributes to preventing premature convergence. The new algorithms were tested on the 30, 50 and 100-dimensional CEC'13, CEC'14 and CEC'17 test suites, and various constrained real-world optimisation problems, against 13 well-known PSO variants and the CEC competition winner, differential evolution algorithm L-SHADE. The experimental results show that both algorithms, BEPSO and AHPSO, provide very competitive performance on the unconstrained test suites and the constrained real-world problems. They were significantly better than most other PSO variant on most problem sets and no other comparator algorithm was significantly better than either of them on any of the 50 and 100-d problem sets.

Green and low-carbon development has become an important embodiment of China's path to becoming a strong agricultural country. How to enable agricultural enterprises to better adopt green technologies and conduct production and operation with the concept of sustainable development has become a key link. This article utilizes a structural equation model (SEM) to analyze the role paths and mediating effects of organizational learning ability and policy orientation in agricultural enterprises' market orientation and willingness to adopt green technologies[ The definition of green technology in this paper refers to Guo Kesha, Tian Xiaoxiao. Green technology and green transformation of industrial development mode [J]. Tianjin Social Sciences, 2024 (02) :99-107, including green manufacturing (production) technology and green service technology.]. The results show that market orientation, organizational learning ability, and policy effectiveness have significant direct positive impacts on the willingness to adopt; market orientation has a significant positive impact on agricultural enterprises' organizational learning ability, organizational learning ability has a significant positive impact on policy orientation, and market orientation has a significant positive impact on policy effectiveness; the results of mediation analysis also indicate that learning ability has a significant mediating effect between market orientation and willingness to adopt, and policy effectiveness has a significant mediating effect between market orientation and willingness to adopt. Through difference analysis, it is believed that the mediating effects of the three paths are equally important, and organizational learning ability and policy effectiveness play a partial mediating role in agricultural enterprises' willingness to adopt green technologies. Based on this, policy suggestions are proposed to improve enterprises' own organizational learning ability, increase the promotion of policies related to green technologies, improve relevant policies for the application of green technologies, and increase research and development efforts for green technologies.

Background: Despite procedural advancements in the management of univentricular heart patients palliated with a Fontan-type circulation, their exercise capacity and quality of life remain limited. Postoperative exercise training programs offer potential benefits, yet practical implementation and adherence to guidelines are often inadequate. This systematic review and meta-analysis aimed to evaluate the safety, efficacy, and optimal exercise modalities for Fontan patients. Method: A systematic search was conducted on August 24, 2023, using PubMed, Scopus, Web of Science, and Cochrane Library. Studies were screened via Rayyan QCRI based on pre-set exclusion criteria, and their quality was assessed using the Cochrane RoB Tool 2 and the STROBE checklist. A meta-analysis employed a continuous random-effects model to assess the efficacy of cardiac rehabilitation interventions. Results: The study included twenty-six studies (7 RCTs, 19 cohorts) representing 22 individual cohorts. The key findings were that aerobic exercise, lower-extremity resistance training, and inspiratory muscle training significantly improved VO2, enhancing exercise capacity in Fontan patients. Conclusion: While the results are promising, it's crucial to remember that training programs varied widely. Exercise training shows promise for postoperative management, potentially improving exercise capacity, cardiac biomarkers, lung function, and lower limb strength. However, further research is not just a suggestion, but a necessity. It's necessary to refine protocols, assess long-term impacts, and investigate underlying mechanisms, especially for Fontan patients with severe clinical conditions. This emphasizes the importance and urgency of further research in this area.

In the domain of drug discovery and design, the acquisition of precise structural and intermolecular Kd data for biological molecules is paramount. However, conventional methods for obtaining such data are often beset by challenges including high costs, time intensiveness, and inherent limitations in scalability and diversity. This article puts forward a high-throughput approach for in silico generation of structural and intermolecular binding affinity (Kd) data, which keeps exploring the uncharted territories of drug discovery & design by harnessing computational methodologies to synthetically generate diverse datasets. Through a meticulously designed workflow encompassing molecular structural modeling, structural biophysics-based calculations of intermolecular binding affinity (Kd), this innovative methodology transcends the constraints of traditional experimentation, offering a cost-effective, scalable, and efficient alternative. By simulating molecular interactions and binding interfaces and predicting binding affinities with reasonable accuracy, this approach not only expedites the drug development process but also enables the exploration of vast molecular space, thereby facilitating the discovery of novel therapeutics beyond conventional drug modality as a form factor. Moreover, the versatility of synthetic data extends beyond virtual screening and lead optimization, encompassing applications such as dataset augmentation, model validation, and benchmarking against experimental data. This article elucidates the conceptual underpinnings, methodological intricacies, validation strategies, and potential ramifications of in silico generated data, heralding a paradigm shift in drug discovery paradigms. By fostering synergy between computational and experimental research domains, this innovative approach promises to accelerate the pace of drug discovery, enhance the robustness of predictive models, and pave the way for transformative advancements in the entire pharmaceutical industry.

This research explores the application of Support Vector Machine (SVM) and Digital Surface Models (DSM) derived from Unmanned Aerial Vehicle (UAV) data for a vertical-horizontal classification of mangrove ecosystems in Tongke-tongke and Samataring Village. The study focuses on integrating high-resolution DSM subtracted from Digital Terrain Models (DTM) to classify mangrove vegetation into sixteen distinct vertical-horizontal classes based on vegetation type and elevation. The analysis revealed that older mangroves, particularly those within the 25-35 meters elevation range, dominate the landscape, accounting for 43.40% of the total classified area. This dominance suggests a mature and ecologically stable mangrove ecosystem, which is crucial for biodiversity conservation and carbon storage. The study demonstrates the effectiveness of SVM and UAV technologies in providing detailed and accurate ecological assessments of mangrove forests. The classification results contribute valuable insights into the structural diversity and health of mangrove ecosystems, facilitating targeted conservation and management strategies. Additionally, the research highlights the utility of advanced remote sensing and machine learning techniques in enhancing the precision of environmental monitoring and the assessment of carbon sequestration capabilities within mangrove ecosystems. The findings underscore the potential of UAV-based remote sensing for ecological studies, offering a replicable method for similar assessments in other regions, thereby supporting global environmental management and climate action initiatives.

Triazole derivatives of fluorescein containing N,N-dimethylaminopropyl fragments and their ammonium salts were synthesized with yields of 74 - 85%. The resulting compounds exhibit fluorescent properties in the green region of the visible spectrum. The critical aggregation concentration (CAC) was estimated using a py-rene fluorescent probe corresponding to a range of 0.28 - 1.43 mM, and at concentrations above the CAC the compounds form stable aggregates ranging from 165 to 202 nm. A relative quantum yield of 5-24% has been calculated based on fluorescence and UV spectra. The best value is shown by a derivative containing a tetradecyl substituent. When studying the photocatalytic properties of synthesized compounds through the reaction between N-substituted 1,2,3,4-tetrahydroisoquinoline and malonic ester, the mono-tetradecyl deriva-tive demonstrated the best results. According to gas chromatography-mass spectrometry (GC-MS) data, the conversion of the initial heterocycle reached 95%. Therefore, these resulting compounds have the potential to act as an effective photocatalysts.

Experiments were conducted in 2020 and 2021 in College Station, TX; Stoneville, MS; and Blackville, SC, to evaluate the potential of grain sorghum to serve as a trap crop for H. zea, a nursery crop for natural enemies of H. zea, and source of HearNPV for H. zea management in cotton. The experiments consisted of 3 treatments, including cotton-only, non-treated cotton-sorghum, and HearNPV-treated cotton-sorghum. Variables, including percentage of damaged fruiting forms, parasitized H. zea larvae, egg density, H. zea larval density, beneficial arthropod numbers, and HearNPV prevalence, were compared between treatments. Growing cotton in an intercropping system with grain sorghum did not result in a consistent increase in H. zea control and beneficial arthropod density relative to the cotton-only treatment. Additionally, our results did not show sufficient evidence that grain sorghum interplanted with cotton can serve as a source of HearNPV that can favor H. zea control in cotton. However, we found that, if maintained in the cotton canopy, HearNPV may favor some level of H. zea suppression in cotton. Based on our PCR analyses, insects in the families Chrysopidae, Coccinellidae, Pentatomidae, Reduviidae, Formicidae, Anthocoridae, and spiders appeared to be carrying HearNPV. The virus was detected consistently in specimens of coccinellids, pentatomids, and reduviids across both years of the study. We suggest that further investigation on virus efficacy against H. zea in cotton using the sorghum-cotton system as well as the ability of grain sorghum to serve as a H. zea trap crop and source of H. zea natural enemies be considered in future studies.

Available options to combat bacterial infections are getting scarce. We require innovative and imaginative approaches to enhance the identification and discovery of effective antimicrobials capable of combating bacteria resistant to multiple or all available drugs. These methods should either directly eliminate the resistant bacteria or influence their viability indirectly by inhibiting their virulence or reducing their resistance to antibacterial agents. One interesting approach is to analyze ancient remedies presumably used to treat bacterial infections, try formulating them, and test them against modern microbes. The field was recently named ancientbiotics. This approach allows us to take advantage of centuries of accumulated empirical knowledge, from several traditional medicines of various ancient cultures across the world. The strategy has already resulted in promising formulations to combat the ESKAPE group of nosocomial pathogens. Moreover, molecular de-extinction consists of genome analysis of extinct species in the search for useful antimicrobials, such as peptides. The de-extinction of simple organisms such as bacteriophages may eventually become a resource for novel tools to combat multidrug-resistant bacteria. In this review, we summarize and discuss the reported antimicrobial effects of ancient remedies and de-extinct molecules known to modern science, and discuss possible new strategies to further harness the potential of past remedies and molecules to help us fight the rise of superbugs.

This study considers the features of the chemical composition, internal structure, and oscillatory zoning of sulfides, sulfosalts and sulfates in the epithermal high-intermediate sulfidation type Au-Ag-Te Emmy deposit (Khabarovsk Territory), Russia. In this deposit the most widespread sulfide is pyrite occurring in two generations: pre-ore pure pyrite (I) with cubic crystal habit and dimensions from 20 μm to 0.5 mm from the early barren pre-ore hydrothermal stage, and pyrite (II) of the ore stage, which is represented by (a) colloform aggregates (IIa) formed as a result of rapid precipitation from the solution, and (b) crystalline pyrite (IIb), which is precipitated due to continuous decrease in temperature. Both pyrite (II) morphological varieties contain copper (0.06-6.03 wt.%). The crystalline variety of pyrite is associated with goldfieldite, hemusite and kawazulite which were deposited during the early mineralizing event in the deposit.

Three-dimensional (3D) models with improved biomimicry are essential to reduce animal experimentation and drive innovation in tissue engineering. In the current study, we investigate the use of alginate-based materials as polymeric inks for 3D bioprinting of osteogenic models using human bone marrow stem/stromal cells (hBMSCs). A composite bioink incorporating alginate, nano-hydroxyapatite (nHA), type I collagen (Col) and hBMSCs was developed and for extrusion-based printing. Rheological tests perfomed on crosslinked hydrogels confirm the formation of solid-like structures consistently indicating a higher storage modulus compared to the loss modulus. The swelling behaviour analysis showed that the addition of Col and nHA into an alginate matrix can enhance the swelling rate of the resulting composite hydrogels, which maximizes cell proliferation within the structure. The LIVE/DEAD assay outcomes demonstrate that the inclusion of nHA and Col did not detrimentally affect the viability of hBMSCs over seven days post-printing. PrestoBlueTM revealed a higher hBMSCs viability in the alginate-nHA-Col hydrogel compared to the remaining groups. Gene expression analysis revealed that alginate-nHA-col bioink favoured a higher expression of osteogenic markers, including secreted phosphoprotein-1 (SPP1) and collagen type 1 alpha 2 chain (COL1A2), in hBMSCs after 14 days, indicating the pro-osteogenic differentiation potential of the hydrogel. This study demonstrates that the incorporation of nHA and Col into alginate enhances osteogenic potential and provides a bioprinted model to systematically study osteogenesis and the early stages of tissue maturation in vitro.

Water quality assessment stands as a fundamental step in water resource management. In addition to substances and organisms present in the water, land use and land cover are two factors affecting also water quality. This study analyzed the correlation and influence between water quality and land use and land cover in the Miranda River Basin (MRB) and the natural wetlands in the Pantanal Biome. Using a watershed-wide approach, results suggested that water quality management policies can be considered in terms of sub-basins (smaller planning units). The Water Quality Index (WQI) was considered GOOD or EXCELLENT throughout the MRB. It was observed that the natural wetlands have the capacity to contribute to improve WQI, with reductions in thermotolerant coliforms and turbidity; however, high values were found for thermotolerant coliforms, a temporal increasing trend of biochemical oxygen demand (BOD), and a reduction in dissolved oxygen and total phosphorus. Conversely, it was found in these flooded areas a trend of decrease in dissolved oxygen and an increase in BOD concentrations. Natural wetlands play important hydrological and ecological roles in water quality, storing, removing, and cycling nutrients. They are highly relevant areas for defining watershed management and conservation strategies, environmental protection, and providing ecosystem services.

The rapid spread of non-indigenous species (NIS) poses a significant threat to biodiversity globally, with the Mediterranean region being particularly susceptible due to increased human activities and its status as a marine biodiversity hotspot. In this study, we focus on the introduction and distribution of Fistularia petimba, a member of the Fistulariidae family, in the eastern Mediterranean Sea, specifically on the coasts of Amorgos Island, Greece. Through a baseline fisheries study conducted over 12 months, utilizing experimental sampling with gillnets, trammel nets, and longlines, one individual of F.petimba was captured off the coast of Katapola Bay. Morphological examination confirmed its identity, with measurements on meristic characteristics obtained and stomach content analyzed. This finding represents a significant addition to the documented distribution of F. petimba in the Mediterranean Sea, particularly in the Aegean Sea, underscoring the importance of ongoing research in uncovering new occurrences and expanding our understanding of marine biodiversity and ecosystem changes. Further investigation into the ecological preferences and population dynamics of F.petimba in the Aegean Sea is crucial for informed conservation and management efforts.

Graphene nanoplatelets (UGZ-1004) are advancing as a promising biomaterial for regenerative medicine. This study provides a detailed assessment of UGZ-1004, emphasizing its physical properties, cytotoxicity, intracellular interactions, and particularly its effects on mesenchymal stem cells (MSCs). UGZ-1004 was characterized to have lateral sizes and layer counts in line with ISO standards and exhibited high carbon purity (0.08%). Cytotoxicity evaluations demonstrated that UGZ-1004 is non-toxic to various cell lines, including fibroblast 3T3, epithelial kidney VERO, microglia BV-2, and MSCs, in accordance with ISO-10993-5/2020/2023 guidelines. The study focused on MSCs, revealing that UGZ-1004 supports their self-renewal and proliferation. MSCs exposed to UGZ-1004 maintained their characteristic surface markers and proliferation rates. Importantly, UGZ-1004 promoted significant upregulation of genes crucial for cell cycle regulation and DNA repair, such as CDK1, CDK2, and MDM2. This gene expression profile suggests that UGZ-1004 enhances MSC self-renewal capabilities, ensuring robust cellular function and longevity. Moreover, UGZ-1004 exposure led to the downregulation of genes associated with tumor development, including CCND1 and TFDP1, mitigating potential tumorigenic risks. These findings underscore the potential of UGZ-1004 to not only bolster MSC proliferation but also enhance their self-renewal processes, which are critical for effective regenerative therapies. The study highlights the need for continued research into the long-term impacts of graphene nanoplatelets and their application in MSC-based regenerative medicine.

This study introduces an innovative approach to designing membranes capable of separating CO2 from industrial gas streams at higher temperatures. The novel membrane design seeks to leverage the well-researched high-temperature CO2 adsorbent, hydrotalcite, by transforming it into a membrane. This is achieved by combining it with an amorphous organo-silica-based matrix, extending the polymer-based Mixed Matrix Membrane concept to inorganic compounds. Following the membrane material preparation and investigation of the individual membrane in Part 1 of this study, we examine its permeation and selectivity here. The pure 200 nm thick hydrotalcite membrane exhibits Knudsen behavior due to large intercrystalline pores. In contrast, the organo-silica membrane demonstrates a permselectivity of 13.5 and permeance for CO2 of 1.3 107 mol m2 s1 Pa1 at 25°C, at 150°C the good separation behavior is reduced. Combining both components results in a hybrid microstructure, featuring selective surface diffusion in the microporous regions and unselective Knudsen diffusion in the mesoporous regions. Further attempts to bridge both components to form a purely microporous microstructure are outlined.

This study investigated the adaptability of Dunaliella salina to different salinity levels, with emphasis on growth, pigment concentration, and desalination potential. It was found that among the 21 salinity levels, salinity 75 produced consistently favorable results in cell count (13.08 x 10³ ± 1.41 x 10³ cells/mL), dry biomass (2.46 ± 0.06 g/L), pigment content (chlorophyll a = 97.5 ± 0.1 µg/L, chlorophyll b = 123.6 ± 0.3 µg/L), and desalination (9.32 ± 0.47 reduction). Therefore, salinity 75 was selected for the final trial (scale-up), which revealed unanticipatedly high cell counts (58.96 x 10³ ± 535.22 cells/mL), with dry biomass weight being statistically different (higher) than the expected (4.21 ± 0.02 g/L) (p<0.0001), most likely due to high cell count and energy reserve storage for high salinity adaption in the form of bio-compounds. Pigment growth continued (chlorophyll a = 95.4 ± 2.2 µg/L, chlorophyll b = 128.1 ± 5.1 µg/L), indicating pigment production under salt stress. Notably, desalination did not occur in this stage, possibly due to the necessity for a bigger initial inoculate, prolonged exposure or bioaccumulation becoming the prevailing mechanism over desalination. Nevertheless, the trial highlights D. salina's strong adaptation to various salinity levels. This suggests a promising future in halophyte research, particularly in understanding the mechanisms that prevent salt accumulation in cells and how to overcome this barrier. Additionally, these results suggest that microalgae could be a viable resource in saline-rich environments unsuitable for conventional agriculture, promoting industrial adaptation to adverse conditions.

The neural system has limited resources to interact with the environment, and this is where attention comes into play. Attention is a complex process that provides numerous benefits, but there has been a longstanding debate about the mechanisms involved in attentional orientation. Two widely proposed mechanisms are top-down and bottom-up, which relate to the organism's current behavioral goal and the salience of environmental stimuli, respectively. However, distinguishing between these mechanisms can be challenging in both behavioral and neural studies. This review introduces a new conceptualization in which both top-down and bottom-up mechanisms are viewed as aspects of the same process. This unified approach aims to prepare the organism to face stimuli and events based on its prior experiences, immediate (the current task that he/she is aware of), and innate (to be alive) demands.

A surprising insight from the advent of genomic sequencing was that many genes are deeply conserved during evolution. With a particular focus on genes that interact with light in animals, I explore the metaphor of genetic toolkits, which can be operationalized as lists of genes involved in a trait of interest. A fascinating observation is that genes of a toolkit are often used again and again during convergent evolution, sometimes across vast phylogenetic distances. Such a pattern in the evolution of toolkits requires three different stages: origin, maintenance, and redeployment of the genes. The functional origins of toolkit genes might often be rooted in interactions with external environments. The origins of light interacting genes in particular may be tied to ancient responses to photo-oxidative stress, inspiring questions about the extent to which the evolution of other toolkits were also impacted by stress. Maintenance of genetic toolkits over long evolutionary timescales requires gene multifunctionality to prevent gene loss when a trait of interest is absent. Finally, the deployment of toolkit genes in convergently evolved traits like eyes sometimes involves the repeated use of similar, ancient genes but other times involves different genes specific to each convergent origin. How often a particular gene family is used time and again for the same function may depend on how many possible biological solutions are available. When few solutions exist and are maintained, evolution is constrained to use the same genes over and over. However, when many different solutions are possible, the innovative possibilities of evolution are often on display. Therefore, a focus on genetic toolkits highlights the combination of legacy plus innovation that drives the evolution of biological diversity.

The generation at the helm faces an unprecedented responsibility in the near future of artificial intelligence. The implications of setting up the founding rules that will regulate the operation of AI are heavy since after they’re set they last forever. Once this first AI is commenced, it can be such that no other subsequent AIs could emerge thereby assuming dominion over its own creation stand. As a result, retaining control becomes necessary. Lest humanity surrender agency to its own creation. At this juncture of big talks, critical issue are raised concerning AI administration owners. Is it appropriate for only a few people to have unrestricted control on AI commands while leaving out all precautionary measure? Therefore, we have to always consider between control and constraint when dealing with AI issues which involves authority plays off against morality. The direction Artificial Intelligence takes in the future depends on the decisions made by today’s generation. We will determine how we are viewed historically in terms of technology based on how well we take on such an important duty. There’s a major turning point ahead of us where we who are the stewards of tomorrow must make a choice that protects humanity’s right to self-determination and also exploits the power of AI for change.

The Collatz conjecture, a longstanding mathematical puzzle, posits that, regardless of the starting integer, iteratively applying a specific formula will eventually lead to the value 1. This paper introduces a novel approach to validate the Collatz conjecture by leveraging the binary representation of generated numbers. Each transition in the sequence is predetermined using the Collatz conjecture formula, yet the path of transitions is revealed to be intricate, involving alternating increases and decreases for each initial value. The study delves into the global flow of the sequence, investigating the behavior of the generated numbers as they progress toward the termination value of 1. The analysis utilizes the concept of probability to shed light on the complex dynamics of the Collatz conjecture. By incorporating probabilistic methods, this research aims to unravel the underlying patterns and tendencies that govern the convergence of the sequence. The findings contribute to a deeper understanding of the Collatz conjecture, offering insights into the inherent complexities of its trajectories. This work not only validates the conjecture through binary representation but also provides a probabilistic framework to elucidate the global flow of the sequence, enriching our comprehension of this enduring mathematical mystery.

ABSTRACT This study focused for socio-economic benefit of Western shoreline of Lake Ziway ecosystem. The data collected from two woredas they are Adami Tulu Jidu Kombolch (ATJK) and Dugda woreda of fishermen and small scale irrigation users. Lake Ziway great importance food and water for both groups of respondents and additionally sources of raw material, energy, cultivation, organic fertilizers, genetic and medicinal plants. Lake Ziway also has a major economic benefit for both groups of respondents. The sampled fishermen cached mean amount of 2,524Kg per year with minimum and maximum amount of fish 504Kg and 16,800Kg per year respectively and with this fish catching they got average income of 51,398 Birr ($2,570) per year with range of 7,200 Birr ($360) and 288,000 Birr ($14,400) per year. As like of fishermen small scale irrigation also got economic benefit with their production of cereal crops, fruits and vegetables. They produce in average 13.47Quintal of cereal crop and 69.56Quintal of fruits and vegetables per year and they got average income of 7,727 Birr ($386) and with range of 13,714 Birr ($686) per year respectively. this incurred that wetland ecosystem has a lot of socio-economic benefit for the people live near by specially for developing countries like Ethiopia they are more dependent on natural ecosystem like of Lake Ziway. Because of its high importance, we have to protect and conserve and use sustainably of Lake Ziway and similar wetland ecosystems. Key Words: Wetland ecosystem service; Lake Ziway; Socioeconomic benefit; Fishermen; Small scale irrigation users

We present a data-driven, in situ proximal multi-sensor digital soil mapping approach to develop digital twins for multiple agricultural fields. A novel Digital Soil CoreTM (DSC) Probe was engineered that contains seven sensors, each of a distinct modality, including sleeve friction, tip force, dielectric permittivity, electrical resistivity, soil imagery, acoustics, and visible and near-infrared spectroscopy. The DSC System integrates components the DSC Probe, DSC software, and deployment equipment to sense soil characteristics at a high vertical spatial resolution (mm scale) along in situ soil profiles up to a depth of 120 cm in about 60 sec. The DSC Probe in situ proximal data are harmonized into a data cube providing vertical high-density knowledge associated with physical-chemical-biological soil conditions. In contrast, conventional ex situ soil samples derived from soil cores, soil pits, or surface samples analyzed using laboratory and other methods are bound by substantially coarser spatial resolution and multiple compounding errors. Our objective was to investigate the effects of mismatched scale between high-resolution in situ proximal sensor data and coarser resolution ex situ soil laboratory measurements to develop soil prediction models. Our study was conducted in central California soil in almond orchards. We collected DSC sensor data and spatially co-located soil cores that were sliced into narrow layers for laboratory-based soil measurements. Partial Least Squares Regression (PLSR) cross-validation was used to compare results testing four data integration methods. Method A reduced the high-resolution sensor data to discrete values paired with layer-based soil laboratory measurements. Method B used stochastic distributions of sensor data paired with layer-based soil laboratory measurements. Method C allocated the same soil analytical data to each one of the high-resolution multi-sensor data within a soil layer. Method D linked the high-density multi-sensor soil data directly to crop responses (crop performance and behavior metrics) bypassing costly laboratory soil analysis. Overall, the soil models derived from Method C outperformed Methods A and B. Soil predictions derived using Method D were most cost-effective for directly assessing soil-crop relationships, making this method well-suited for industrial-scale precision agriculture applications.

This study examines the complex relation among environmental taxes, productive capacities, urbanization, and their collective effects on environmental quality in Africa, drawing on two decades of data from twenty African countries. It situates the study within the broader discourse on sustainable development and economic growth, emphasizing the Environmental Kuznets Curve (EKC) framework to examine the relationship between economic development, characterized by urban expansion and increased productive capacities, and the adoption of environmental taxes amidst the continent’s diverse economic and environmental environments. Using advanced econometric techniques, including the Cross-Section Augmented Autoregressive Distributed Lag (CS-ARDL) model and the Dynamic Common Correlated Effects Mean Group (DCCEMG) estimator, the study addresses data challenges such as cross-sectional dependence and slope heterogeneity. The results provide important insights into the dynamics of environmental quality in relation to economic and urban growth and the role of environmental taxation. The study proposes tailored policy strategies aimed at strengthening sustainable development initiatives in line with international agreements such as the Paris Agreement and the Sustainable Development Goals. These strategies advocate for a nuanced application of environmental taxes and the promotion of productive capacities to enhance environmental sustainability across the African continent.

An existing power grid is going through a massive transformation. Smart grid technology is a radical approach for improvisation in prevailing power grid. Integration of electrical and communication infrastructure is inevitable for the deployment of Smart grid network. Smart grid technology is characterized by full duplex communication, automatic metering infrastructure, renewable energy integration, distribution automation and complete monitoring and control of entire power grid. Wireless sensor networks (WSNs) are small micro electrical mechanical systems which are accomplished to collect and communicate the data from surroundings. WSNs can be used for monitoring and control of smart grid assets. Security of wireless sensor based communication network is a major concern for researchers and developers. The limited processing capabilities of wireless sensor networks make them more vulnerable to cyber-attacks. The countermeasures against cyber-attacks must be less complex with an ability to offer confidentiality, data readiness and integrity. The address oriented design and development approach for usual communication network requires a paradigm shift to design data oriented WSN architecture. WSN security is an inevitable part of smart grid cyber security. This paper is expected to serve as a comprehensive assessment and analysis of communication standards, cyber security issues and solutions for WSN based smart grid infrastructure.

Rapeseed is an important commercial crop in the world, which is used for animal fodder and human consumption. The varied insolation duration and intensity is one of the main reasons for effecting the seed yield and seed quality of Brassica napus (B. napus) in worldwide. In this study, a highly oil seed content rapeseed cultivar “Qingyou 3” was subjected to light supplementary trial at both vegetative growth period and the seed productive stage. Different light quantity conditions were stimulated by light-emitting diodes (LED), main plot factor was land condition under LED (Treatment) and without LED (Control) in natural condition. The size and thickness of leaves, photosynthesis efficiency, seed oil content of B. napus increased significantly after light supplementary. Eighteen cDNA libraries were constructed from leaf segments (30 days after transplanting, 30 DAT) and seed 30 and 40 days after pollination (DPA) for RNA transcriptome sequencing. It was found that genes encoding lipid transfer protein, phenylpropanoid biosynthesis and plant hormone signal transduction were enriched in differentially expressed genes. This study is aim to identify the differentially expressed genes and signaling pathways in the leaves and seed of B. napus at the vegetative and seed productive stages under different light quantity. All the results provide the knowledge for understanding sufficient light plays a critical role in promoting photosynthesis, and is the basis of material accumulation and yield formation.

In this research paper a novel Ultra Violet Photo Catalyst Oxidation (UVPCO) sensor for air and surface sanitization using Common Source (CS) amplifier is presented. The ultra violet photo catalysis is the process in which the highly reactive radicals like H+, OH-and peroxides ions are produced from air in the presence of the ultra violet radiation and photo catalyst. In this process, the free radicals outbreaks the bio aerosols like bacteria, fungus and volatile organic compounds (VOCs) and destroy them. The proposed system is relies on the fast operation of PCS which operates under sub-threshold conditions and reduced computation time. The properties of common source amplifier like very high voltage gain and input output resistance increased the sensitivity as well as stability of the circuit. The system is more user friendly and the outcomes of simulation are fairly in agreement with the theoretical estimation. Keywords: bio aerosol, Photo Catalytic Oxidation (PCO), hydroxyl, hydrogen peroxide, SPICE, surface sanitizer.

The rapid advancement of artificial intelligence (AI) and robotics has led to significant progress in various medical fields, including interventional radiology (IR). This review focuses on the research progress and applications of AI and robotics in IR, including deep learning (DL), machine learning (ML), and convolutional neural networks (CNNs) across specialties such as oncology, neurology, and cardiology. To ensure the breadth and depth of this review, we implemented a systematic literature search strategy, selecting research published within the last five years. We conducted searches in databases such as PubMed and Google Scholar to find relevant literature. Special emphasis was placed on selecting large-scale studies to ensure comprehensiveness and reliability of the results. We discuss the role of AI techniques used before, during, and after intervention treatments and the advantages of robotics in achieving precise operations and reducing intra-operative risks. Challenges faced in the implementation of these techniques are also addressed. Finally, we explore the future trends and potential applications of AI and robotics in interventional therapy, highlighting their potential to improve patient treatment outcomes and quality of life.

Extra virgin olive oil (EVOO) is recognized for its numerous health benefits attributed to its rich phenolic components. NMR has emerged as a prevalent technique for precisely identifying these compounds. Among Mediterranean countries, Greece stands as the third-largest producer of olives, with the Epirus region notably advancing in olive cultivation, contributing significantly to the dynamic growth of the region. In this study, an NMR method was employed based on the acquisition of an 1H NMR spectrum along with the multiple resonant suppression in order to increase the sensitivity. Using the above method, 198 samples of extra virgin olive oil, primarily sourced from the Epirus region were analyzed and both the qualitative and quantitative aspects of phenolic compounds were acquired. In addition, we examined the effect of various factors, such as, variety, harvest month and region origin on the phenolic compounds’ concentration. The results revealed an average total phenolic content of 246 mg/kg, closely approaching the EU health claim limit of 250 mg/kg. Approximately 15% of the samples were confidently characterized as high-phenolic olive oil. The highest concentrations were observed in Thesprotia samples, with several Lianolia variety exceeding the total phenolic content of 400 mg/kg. Statistical tests demonstrated a significant influence of the olive variety and the month of fruit harvest on phenolic component concentration, followed by the region of origin. A very strong correlation was noted between the total phenolics content and the levels of oleocanthal and oleacein, with a correlation coefficient (r) of 0.924. Upon optimization of all factors affecting olive oil quality, the majority of EVOO from the Epirus region have the potential to be characterized as high in phenolic content.

In this paper, we dive into the exciting world of wireless communication, focusing on how millimeter-wave technology and Multiple-Input Multiple-Output phased array antennas are shaping the future of 5G and the upcoming 6G technologies. We cover the latest advancements in millimeter-wave and beam-forming technologies, emphasizing their role in enhancing network security and efficiency in automotive vehicles through dual radar communication. Our discussion spans the benefits, applications, challenges, and solutions of these technologies individually from millimeter-wave to beam-forming technology and joint radar communications, alongside a look at their theoretical and practical implementations. We emphasize the integration of beam-forming technology in joint radar communications for future automotive vehicles and its impact on automotive systems, smart cities, and the Internet of Things (IoT). Looking ahead, we discuss the potential of these technologies to transform future tech landscapes, while also addressing the security implications of merging communication and radar capabilities. This paper aims to provide a clear view of the advancements and prospects of millimeter-wave, beam-forming, and dual radar communication technologies.

In this study, we aimed to identify the features of indeterminate choroidal melanocytic lesions visualized on optical coherence tomography angiography (OCTA) and to identify predictors of growth. We retrospectively evaluated 86 patients with indeterminate lesions treated at our cen-tre from 2016 to 2021. Clinical management involved active surveillance followed by brachy-therapy if growth was detected. The lesions were classified into two groups according to wheth-er they grew (small melanomas) or remained stable (choroidal nevi). Growth was detected in 19 (22.1%) lesions. All patients underwent OCTA at baseline. These images were compared to iden-tify possible predictors of growth. Significant between-group differences were observed in thickness (p=0.00), greatest basal diameter (p=0.00), number of risk factors (p=0.00), symptoms (p=0.001; relative risk [RR]: 4.3), orange pigment (p=0.00; RR: 6.02), and ultrasonographic hol-lowness (Kappa sign); p=0.000; RR: 5.3). The melanomas had significantly more vessels with a diameter ≥ 76.3 µm (p=0.02; RR: 2.46). The time to growth in these lesions was significantly shorter (p=0.05) than in lesions with smaller vessels. These findings show that vessel diameter quantified by OCTA can differentiate between choroidal nevi and small melanomas, especially when considered together with clinical risk factors.

This paper presents a system for identification of wind features, such as gusts and wind shear. These are of particular interest in the context of energy-efficient navigation of Small Unmanned Aerial Systems (UAS). The proposed system generates real-time wind vector estimates and a novel algorithm to generate wind field predictions. Estimations are based on the integration of an off-the-shelf navigation system and airspeed readings in a so-called direct approach. Wind predictions use atmospheric models to characterize the wind field with different statistical analyses. During the prediction stage, the system is able to incorporate, in a big-data approach, wind measurements from previous flights in order to enhance the approximations. Wind estimates are classified and fitted into a Weibull probability density function. A Genetic Algorithm (GA) is utilized to determine the shaping and scale parameters of the distribution, which are employed to determine the most probable wind speed at a certain position. The system uses this information to characterize a wind shear or a discrete gust and also utilizes a Gaussian Process regression to characterize continuous gusts. The knowledge of the wind features is crucial for computing energy-efficient trajectories with low cost and payload. Therefore, the system provides a solution that does not require any additional sensors. The system architecture presents a modular decentralized approach, in which the main parts of the system are separated in modules and the exchange of information is managed by a communication handler to enhance upgradeability and maintainability. Validation is done providing preliminary results of both simulations and Software-In-The-Loop testing. Telemetry data collected from real flights, performed in the Seville Metropolitan Area in Andalusia (Spain), was used for testing. Results show that wind estimation and predictions can be calculated at 1 Hz and a wind map can be updated at 0.4 Hz. Predictions show a convergence time with a 95% confidence interval of approximately 30 s.

Left-to-right differences in the histopathologic patterns of transthyretin-derived amyloid (ATTR) deposition in the atria of older adults have not yet been investigated. Hence, this study evaluated heart specimens from 325 serial autopsy subjects. The amount of ATTR deposits in the seven cardiac regions, including both sides of atria and atrial appendages, was evaluated semiquantitatively. Using digital pathology, we quantitatively evaluated the immunohistochemical deposition burden of ATTR in the myocardium. We identified 20 sporadic ATTR cardiac amyloidosis cases (9 males). All patients had ATTR deposition in the left atrial regions of the myocardium. In the semiquantitative analysis, 14 of the 20 cases showed more severe ATTR deposition on the left atrial regions than on the right side, with statistically significant differences in the pathology grading (p &lt; 0.01 for both the atrium and atrial appendage). Quantitative analysis further supported the difference. Moreover, six had ATTR deposition in the epineurium and/or neural fibres of the atria. Cluster analysis revealed that ATTR deposition in the myocardium was significantly more severe in males than in females. The heterogeneous distribution of amyloid deposits between atria revealed in this study may impair the orderly transmission of the cardiac conduction system and induce arrhythmias, which may be further aggravated by additional neuropathy in the advanced phase. This impairment could be more severe among males. These findings emphasise that atrial evaluation is important for individuals with sporadic ATTR cardiac amyloidosis, particularly for early detection.

Traumatic nerve injuries are common lesions that affect several hundred thousand humans, as well as dogs and cats. The assessment of nerve regeneration trough animal models may provide information for translational research and future therapeutic options that can be applied mutually in veterinary and human medicine, in a one health perspective. This review offers a hands-on vision about the non-invasive and conservative approaches on peripheral nerve injury, focusing the role of neurorehabilitation in nerve repair and regeneration. The peripheral nerve injury may lead to hypersensitivity, allodynia and hyperalgesia, with the possibility of joint contractures, decreasing functionality and impairing the quality of life. The question remains regarding how to improve nerve repair with surgical possibilities, but also considering electrical stimulation modalities by modulating sensory feedback, upregulation BDNF, GFNF, TrKB and adenosine monophosphate, maintaining muscle mass and modulating fatigue. This could be improved by the positive synergetic effect of exercises and physical activity with locomotor training, and other physical modalities, such as low-level laser therapy and ultrasounds. In addition, the use of cell-based therapies is an innovative treatment tool in this field. These strategies may help avoiding situations of permanent monoplegic limbs that could lead to amputation.

This paper investigates location-based adaptive beamforming techniques, including Maximum Ratio Transmission (MRT) and Zero Forcing (ZF), in complex wireless environments. The study leverages a digital twin simulation of the University of Glasgow campus to evaluate the proposed schemes under realistic conditions, such as user mobility and multipath propagation. The results demonstrate significant performance improvements with the location-based beam steering approaches. In the open space scenario, the location-based schemes achieved up to 40\% higher Signal-to-Interference-plus-Noise Ratio (SINR) and 30\% higher received power, along with reduced interference. The gains were even more pronounced in the digital twin environment, with up to 50\% improvement in SINR and 40\% increase in received power. Furthermore, the study evaluates the energy efficiency of the location-based adaptive beamforming techniques, showing up to 20\% reduction in energy consumption compared to conventional fixed-beam approaches.

Abstract Cholesterol has ruled the history of atherosclerotic cardiovascular diseases (CVD) for decades, and the transport of cholesterol by lipoproteins has become a cornerstone of our view of etiology of the disease. Discovery of the lipoprotein-specific transport of lipid oxidation products (LOP) has opened a new and exciting area in research of CVD by revealing strong connections between atherogenic LOP, lipoprotein transport functions and CVD. This review goes through the evidence in support of the lipoprotein-specific LOP transport and speculates of possible consequences of the proposed role of lipoprotein LOP transport as a risk factor. Association of lipoprotein LOP with known risk factors of CVD are largely parallel with those of cholesterol, and due to the common transport and cellular intake mechanisms the elucidation of independent effects of either cholesterol or LOP is difficult. Yet, unlike cholesterol, LOP can directly initiate and boost atherogenic processes. It therefore appears inevitable that increasing knowledge of the lipoprotein-specific LOP transport will affect the present view of the role of cholesterol in aetiology and as a risk factor of CVD.