This study aimed to develop a high-quality dry emulsion incorporating omega-3, 6, and 9 fatty acid-rich ostrich oil for use as a dietary supplement. Extracted from abdominal adipose tissues using a low-temperature wet rendering method, the ostrich oil exhibited antioxidant properties, favorable physicochemical properties, microbial counts, heavy metal levels, and fatty acid compositions, positioning it as a suitable candidate for an oil-in-water emulsion and subsequent formulation as a dry emulsion. Lecithin was employed as the emulsifier due to its safety and health benefits. The resulting emulsion, comprising 10% w/w lecithin and 10% w/w ostrich oil, was stable, with a droplet size of 3.93 ± 0.11 μm. This liquid emulsion underwent transformation into a dry emulsion to preserve the physicochemical stability of ostrich oil, utilizing Avicel® PH-101 or Aerosil® 200 through a granulation process. Although Aerosil® 200 exhibited superior adsorption, Avicel® PH-101 granules surpassed it in releasing the ostrich oil emulsion. Consequently, Avicel® PH-101 was selected as the preferred adsorbent for formulating the ostrich oil dry emulsion. The dry emulsion, encapsulated with a disintegration time of 3.11 ± 0.14 min for ease of swallowing, maintained microbial loads and heavy metal contents within acceptable limits. Presented as granules containing butylated hydroxytoluene, the dry emulsion showcased robust temperature stability, suggesting the potential incorporation of animal fat into dry emulsions as a promising dietary supplement.

The study analyzes how graduate students in economics, administration and accounting perceive their managerial skills for employability. It focuses on the importance of developing transferable skills that meet current and future job demands. To measure the perception of skills, a structured and duly validated questionnaire (Employability Skills 2000+) was used, answered by 225 graduate students in Economics, Administrative and Accounting Sciences in Tegucigalpa, Honduras. The data obtained from the application were analyzed using the Confirmatory Factor Analysis (CFA) method with the FACTOR software. The CFA generated an adaptation of the original scale with 21 variables. The resulting scale determined three predominant factors: Personal Management Skills, Fundamental Skills and Teamwork Skills, which presented good consistency and validity, allowing us to conclude regarding employability skills in the context studied. The findings show the existence of a correlation between fundamental skills and variables such as work experience, employment status and gender, as well as a high correlation between teamwork skills and work experience and employability conditions.

This manuscript reviews three case studies from Brazil, Panama, and Portugal that illustrate Nature-based Solutions. The Tijuca Forest in Rio de Janeiro is a remarkable story of centuries of forest management that today is recognized as a UNESCO World Heritage Site. The Panama Canal Watershed produces water for Canal operations, electricity generation, and drinking water for half the country´s population. Traditional windmills and weirs near streams in the Alentejo Region, Portugal, have largely been abandoned due to the damming of the Guadiana River. Yet today, weirs are increasingly recognized for their important contribution to water provisioning in this dry region. All have a primary goal related to water provisioning, yet their ecosystem benefits are multiple. The cases offer important lessons for adaptation to climate change, cultural benefits from traditional human activities, and concerns about social equity.

Neoadjuvant therapy (NAT) for early-stage pancreatic ductal adenocarcinoma (PDA) has recently gained prominence. We investigated the clinical significance of mucin 5 AC (MUC5AC), which exists in two major glycoforms, a less-glycosylated immature isoform (IM) and a heavi-ly-glycosylated mature isoform (MM), as a biomarker in resected PDA. Immunohistochemistry was performed on 100 resected PDAs to evaluate the expression of IM and MM isoforms of MUC5AC using respective monoclonal antibodies CLH2 (NBP2-44455) and 45M1 (ab3649). MUC5AC localization (cytoplasmic, apical, and extra-cellular, EC) was determined, and H-scores were calculated. Univariate and multivariate (MVA) Cox regression models were used to estimate progression-free survival (PFS) and overall survival (OS). Of 100 resected PDA patients, 43 received NAT, and 57 were treatment-naïve with upfront surgery (UpS). In the study population (N=100), IM expression (objective response vs. no response vs. UpS = H-scores 104 vs. 152 vs. 163, p=0.01) and MM-MUC5AC detection rates (56% vs. 63% vs. 82%, p=0.02) were significantly different. In the NAT-group, MM-MUC5AC-negative patients had significantly better PFS on MVA (Hazard Ratio, 0.2, 95 % CI: 0.059-0.766, p = 0.01). Similar results were noted in a FOLFIRINOX sub-group (N=36). We established an association of MUC5AC expression with treatment response and outcomes.

Land degradation, desertification and tree mortality related to global climate change are in the spotlight of Remote Sensing research in recent decades, since extreme climatic events could affect the composition, structure and biogeography of forests. However, the complexity of tree mortality processes requires a holistic approach. Herein, we present the first global assessment and a historical perspective of tree mortality by reviewing both Remote Sensing and ground-based studies. We compiled 254 papers on tree mortality that make use of remotely sensed products, ground-based monitoring and climatic drivers, focusing on their spatial and temporal patterns, in the methods applied, while highlighting research gaps. Forested ecosystems, especially in the Mediterranean area, appear to have experienced often climatic-induced physiological stress under extreme droughts and warming, raising concern that forests may become increasingly vulnerable to tree mortality. Our core results indicated that international publications on tree mortality are on the increase with the main hotspots being North America (39%) and Europe (26%). Wetness indicators appear as the barometer in explaining tree mortality on a local scale, while vegetation indicators derived from multispectral optical sensors are promising for large scale assessment. We observed that almost all of the studies we have reviewed were based on less than 25 years of data and were of local scale. Longer timeframes and regional scale investigations that will include multiple tree species analysis could have a significant impact on future research.

Background: Blood pressure (BP) is characterized by a circadian rhythm (Circr), with lower nighttime values, called dipping. Non-dipping is associated with higher CVD risk. The Circr of urinary sodium excretion (NaCle), peaking during the day, is linked to BP patterns. Physical ac-tivity (PA) is known to improve BP control and enhance the dipping phenomenon, but its possi-ble effect on NaCle remains unclarified. Objectives: This study aimed to investigate the correla-tion between PA and the Circr of NaCle and to determine if the relationship is independent of age, sex, BP values, dipping pattern, and salt intake. Methods: A cross-sectional analysis was conducted using data from the Ticino Epidemiological Stiffness Study, involving 953 participants in Switzerland. Data collection included standardized questionnaires, blood samples, 24-hour urine collections, and ambulatory BP monitoring. Participants were categorized into sedentary, partially active, and active. The effect of PA, NaCl intake, and dipping on the day/night NaCle ratio, was assessed with multivariable linear regressions. Results: Participants median age 49 years, with 78% having normal BP values and 47% exhibiting a dipping pattern. 51% were classi-fied as sedentary and 22% as partially active. The median NaCl intake was 7.9 g/day. The youngest subjects had a higher hourly NaCle ratio compared to older subjects. Higher NaCl in-take correlated with increased BP, phenomenon more pronounced in men and younger subjects. The hourly day/night NaCle ratio positively correlates with dipping; however, PA did not show a significant correlation with the NaCle ratio. Conclusion: This study indicates that while the day/night NaCle ratio correlates with the dipping pattern, PA is unrelated to the circadian rhythm of renal sodium handling. The beneficial effects of PA on BP and cardiovascular health thus appear to be mediated through mechanisms other than NaCle. These are explorative find-ings only, but relativize the need for further investigations on the topic.

Agile procurement has emerged as a transformative strategy for organizations striving to maintain competitiveness in a rapidly evolving marketplace. This qualitative research investigates the implementation, benefits, challenges, and outcomes of agile procurement practices in supply chain management. Through semi-structured interviews and case studies across diverse industries, this study explores how agile procurement enhances organizational adaptability and responsiveness. Key findings reveal that agile procurement enables organizations to swiftly adjust strategies in response to market fluctuations and customer demands, fostering increased customer satisfaction and loyalty. The integration of advanced technologies, including AI and blockchain, facilitates real-time data analysis, optimizing procurement processes and enhancing supply chain efficiency. Organizational culture emerges as a critical factor in successful agile procurement, with leadership support and a collaborative environment driving cultural change towards agility and innovation. Despite its benefits, challenges such as resistance to change and the need for significant technology investments are identified, requiring careful change management and strategic alignment. Case studies illustrate the versatility of agile procurement across sectors, showcasing its role in enhancing operational efficiencies, innovation capabilities, and overall supply chain performance. In conclusion, agile procurement offers organizations a strategic framework to navigate complexities and uncertainties effectively, capitalizing on market opportunities while mitigating risks. Embracing agile principles fosters a resilient organizational culture capable of adapting to dynamic market conditions. Future research should focus on further refining agile procurement strategies to address emerging challenges and sustain competitive advantage in the global marketplace.

Conversational artificial intelligence (AI) has shown strong capabilities in providing low-cost and timely interventions for a wide range of people and increasing well-being. Therefore, this study examined ChatGPT’s efficacy in conducting psychological counseling and its potential for providing accessible psychological interventions, especially in school settings. This study assessed the strengths and limitations of AI to inform future research. Data were generated from ChatGPT’s responses to 80 counseling questions that college students asked during a school counseling setting. All the responses generated during these simulated counseling sessions were then analyzed using three primary metrics—warmth, empathy, and acceptance—following APA guidelines. The analysis adopted several natural language processing methodologies for emotion detection and empathy measurement to quantify ChatGPT’s high efficacy in presenting the appropriate emotions and reactions for counseling. Some responses demonstrated randomness, which is crucial for consideration regarding the use of ChatGPT or relevant technology in psychological counseling. The Discussion section also highlights future directions in the application of conversational AI to enhance students’ mental health.

The choice of dialysate buffer in hemodialysis is crucial, with acetate being widely used despite complications. Citrate has emerged as an alternative due to its favorable effects, yet concerns persist about its impact on calcium and magnesium levels. This study investigates the influence of citrate dialysate (CD) with and without additional magnesium supplementation on CKD-MBD biomarkers and assesses their ability to chelate divalent metals compared to acetate dialysates (AD). A prospective crossover study was conducted in a single center, involving patients on thrice-weekly online hemodiafiltration (HDF). Four dialysates were compared: two acetate-based and two citrate-based. Various biochemical parameters were monitored before and after each dialysis session. Seventy-two HDF sessions were performed in eighteen patients. CD showed stability in iPTH levels and reduced post-dialysis total calcium, with no significant increase in adverse events. Magnesium supplementation with CD prevented hypomagnesemia. However, no significant differences among dialysates were observed in the chelation of other divalent metals. Citrate dialysates, particularly with higher magnesium concentrations, offer promising benefits, including prevention of hypomagnesemia and stabilization of CKD-MBD parameters, suggesting citrate as a viable alternative to acetate. Further studies are warranted to elucidate long-term outcomes and optimize dialysate formulations.

It is broadly acknowledged that children with Developmental Language Disorder (DLD) show verb-related limitations. While most previous studies in Spanish have focused on tense, the mastery of lexical aspect—particularly telicity—has not been the primary focus of much research. Lexical aspect refers to whether an action has a defined endpoint (telic verbs) or not (atelic verbs). This study investigates the effect of telicity on verb recognition in Chilean children with DLD compared to their typically developing (TD) peers using the Event-Related Potential (ERP) technique. The research design is a mixed factorial design with between-group factors of 2 (DLD/TD) and within-group factors of 2 (telic/atelic verbs) and 2 (coherent/incoherent sentences). Participants included 36 school-aged children (18 DLD, 18 TD) aged 7 to 7 years and 11 months. The task required subjects to listen to sentences that either matched or did not match an action in a video, with sentences including telic or atelic verbs. The study found notable differences between groups in how they processed verbs (N400 and post-N400 components) and direct objects (N400 and P600 components). DLD children struggled to differentiate telic and atelic verbs, potentially because they employed overgeneralization strategies consistent with the Event Structural Bootstrapping model.

College students play an important role in higher education and future social life. Research has a significant impact on college students' self-efficacy. Taking college students in Chengdu, China as an example, this study adopts the fuzzy-set qualitative comparative analysis (fsQCA) method, comprehensively incorporating various influencing factors such as demographic characteristics, physical exercise behavior, and life satisfaction. From the perspective of physical exercise behavior and life satisfaction, an asymmetric causal model that affects college students' high self-efficacy is constructed. The research results support the main principles of complexity theory, confirming the heterogeneity and complexity of the antecedent conditions for high self-efficacy among college students. Nineteen causal condition combinations that can promote high self-efficacy among college students are obtained. This study conducts exploratory research on the introduction of complexity theory analysis into the study of college students' physical exercise, life satisfaction, and self-efficacy. It also provides a decision-making reference path for improving the life satisfaction, physical exercise behavior, and self-efficacy of college students.

Accurate prostate volume estimation is crucial for effective prostate disease management. Ultrasound (US) imaging, particularly transrectal ultrasound, offers a cost-effective and rapid assessment. However, US images often suffer from artifacts and poor contrast, making prostate volume estimation challenging. This review explores recent advancements in deep learning (DL) techniques for automatic prostate segmentation in US images as a primary step for prostate volume estimation. We examine various DL architectures, including traditional U-Net modifications and innovative designs incorporating residual connections, multi-directional image data, and attention mechanisms. Additionally, we discuss pre-processing methods to enhance image quality, the integration of shape information, and strategies to improve the consistency and robustness of DL models. The effectiveness of these techniques is evaluated through metrics such as Dice Similarity Coefficient, Jaccard Index, and Hausdorff Distance. The review highlights the potential of DL in improving prostate volume estimation accuracy and reducing clinical workload, while also identifying areas for future research to enhance model performance and generalizability.

This study evaluates the antimicrobial efficacy of chitosan nanoparticles (CNP), varying in size, against E. coli, S. aureus, E. faecalis, C. albicans, and clinical isolates of Mycobacterium tuberculosis (MTB), as well as the antimicrobial effects of aqueous extracts and lyophilized powders of Allium (garlic) species. CNP were synthesized through ionotropic gelation and characterized by Z potential, hydrodynamic diameter (Dynamic Light Scattering, DLS) and SEM. Aqueous garlic extracts were prepared via decoction. We assessed antimicrobial activity using disk diffusion and broth microdilution methods; besides a modified agar proportion method in blood agar was used for antimicrobial activity against MTB. CNP inhibited MTB growth at 300 μg for 116.6 nm particles and 400 μg for 364.4 nm particles. The highest antimicrobial activity was observed against E. faecalis with nanoparticles between 200 and 280 nm. Allium sativum extract produced inhibition for C. albicans at 100 μg. The results indicate that CNP possess significant antimicrobial properties against a range of pathogens, including MTB, at high concentrations. On the other hand, aqueous Allium sativum extracts exhibited antimicrobial activity, but given their instability in solution, the use of lyophilized Allium sativum powder is preferable.

Background Adjuvant therapy has improved the clinical prognosis for postoperative melanoma patients. but the long-term efficacy of acral and mucosal types has not been fully evaluated in previous trials. This study aimed to assess the 3-year recurrence-free survival (RFS) and overall survival (OS) of melanoma treated with anti-PD-1antibody (Ab) or the combination of dabrafenib and trametinib. Methods We retrospectively analyzed both the 3-year recurrence-free survival (RFS) and overall survival (OS). Results The median RFS was 18.4 months, with a range of 0.69 to 36 months. The 3-year RFS of the acral and mucosal types was 28.1% and 38.5%, respectively. Baseline tumor thickness (TT) and acral type were associated with the RFS in subgroup analysis. Moreover, we classified 104 acral and non-acral cutaneous patients into the anti-PD-1 Abs or dabrafenib plus trametinib combined therapies cohort in multiple analyses. The acral subtype and TT were detected as important prognostic factors. In the 3-year OS, only tumor ulceration was associated with the OS in both univariate and multiple analyses. Conclusion This study suggests that both acral and mucosal types in the adjuvant setting are less effective than non-acral cutaneous melanoma at the 3-year RFS.

For college students, speaking skills are a priceless commodity that can solve a wide range of social, professional, and academic problems. Proficiency in oral communication allows students to express themselves coherently and convincingly in academic and workplace contexts, which improves their involvement in group projects, presentations, and class debates. This paper determines to collect literature to prove that speaking skills can be a panacea for college students in the classroom and the workplace. Having speaking skills is, in fact, a college student's greatest asset, providing a plethora of advantages that go beyond scholastic achievement to encompass personal and professional growth. These abilities should be prioritized in colleges and institutions, with thorough curricula incorporating technological integration, practice opportunities, and public speaking courses. More investigation is required to look into creative approaches to improving speaking abilities and helping students get past obstacles. In essence, emerging strong speaking skills prepare college students with a multipurpose device that improves various aspects of their lives, making it a true panacea.

In recent studies, the circulation of a (SLG) super-Lorentz-Gaussian beam in a non-turbulent ‎troposphere has been investigated and used for laser applications. This method uses the extended ‎Huygens-Fresnel integral technique and refers to the multiplication of the Gaussian beam by the ‎Lorentz function. Formulas are derived for the normal density and approximate field of the Lo-‎Rentz-Gaussian beam in a non-turbulent troposphere. The average density power and the propagation characteristics of the SLG jet in the non-turbulent troposphere are numerically represented. ‎The characteristics of the beam boundaries at atmospheric non-turbulence for the propagation ‎distance of an SLG beam in a non-turbulent troposphere are also discussed in detail. They are ‎practical in an optical communication system used in lasers.

Creativity in virtual work environments and its influence on emotional exhaustion is a relationship with inconclusive results. Furthermore, autonomy, when it loses its original purpose of acting as a job resource, takes on an ambiguous role that needs further research. Objective: To analyze the relationship between creativity and emotional exhaustion, along with the role assumed by work autonomy in this link, in an online work context. Methodology: The sample is formed by 448 employees with university studies. The statistical analysis is done through a simple moderation process. Results: Creativity and work autonomy mitigate emotional exhaustion. Control over work surely reduces the impact of work related stressors, and this safety climate promotes adaptive and original responses that improve employees' emotional health. However, when creative demands coincide with an autonomy that extends working hours, instead of establishing limits, this supposed benefit becomes a demand that prevents employees from disconnecting until emotionally exhausting them. Conclusion: A virtual work environment is an ideal habitat for creativity and self-management to improve employees' emotional health, as long as work autonomy acts as a resource.

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.

Invasive species are one of the five main causes of biodiversity loss, along with habitat destruction, overexploitation, pollution, and climate change. Represent one of the first barriers to overcome in ecological conservation programs, since are difficult to control and eradicate. Due to the lack of records of invasive exotic species in Panama, this research is necessary to identify and register the documented groups of invasive species of the Chordates and Arthropod groups in Panama. This exhaustive search of invasive species was carried out in different bibliographic databases, electronic portals and scientific journals which addressed the topic at a global level. The results indicate that approximately 133 invasive exotic species of the Arthropoda and Chordata Phylum have been reported in Panama. Of the 133 species, 49 species belong to the Arthropoda Phylum and 84 species belong to the Chordate Phylum. The Panamanian economic activity could promote the introduction of alien species in this country. The study provides the first list of invasive exotic chordate and arthropod species reported for the Republic of Panama.

The Marquis of Benicarlo’s House is a prime example of 18th-century Baroque civil architecture in the Valencian region. Inside, it preserves ceramic panels from this period of great historical and heritage value. However, prior to its designation as a Cultural Heritage Site, the building lost some of its most architecturally significant elements, such as the flooring in one of the main rooms, which was decorated with rich iconography. Fortunately, the original tiles from this flooring have been located in the collections of the National Museum of Ceramics. This study presents the recovery and graphic restitution of the flooring based on the pieces found in the museum's collections. This work allows us to understand the original appearance of the flooring before its dismantling and may enable its in-situ restoration through digital ceramic printing techniques, thus returning one of its most unique architectural elements to the building. It also details the process of digitally restoring the flooring to its original location using advanced digitization techniques. This enables the visualization of the hall in its authentic state using virtual reality methods, thereby facilitating its appreciation and dissemination as a heritage architectural space.

The increased life expectancy of PLHIV (People Living with HIV) and the successful highly com-bined antiretroviral therapy (cART) poses new clinical challenges regarding aging and its co-morbid condition. It is commonly believed that HIV infection "accelerates" aging. Human immunodeficiency virus type 1 (HIV-1) infection is characterised by inflammation and immune activation that persists despite cART and that may contribute to the development of co-morbid conditions. Toxicity associated with cART contributes to persistent immune dysregulation. Therefore, we aimed to compare current cART regimens in the light of premature aging to evaluate residual immune activation and inflammation in virologically suppressed patients. We studied a panel of biomarkers (IFN-γ, IL-1β, IL-12p70, IL-2, IL-4, IL-5, IL-6, IL-13, IL-18, GM-CSF, TNF-α, C-reactive protein, D-dimer, soluble CD14), which could provide a non-invasive and af-fordable approach to monitor HIV-related chronic inflammation. The results of the current study do not provide hard evidence favoring a particular cART regimen, although they show less fa-vorable regimen profile containing protease inhibitor. Our data suggests incomplete reduction of inflammation and immune activation in terms of the effective cART. It is likely that the inter-est in various biomarkers related to immune activation and inflammation as predictors of clini-cal outcomes among PLHIV will increase in the future.

To control the volatility and reduce the electricity costs for indoor farming, the agrivoltaics agrotunnel introduced here uses: 1) high insulation for a building dedicated to vertical growing, 2) high-efficiency LED lighting, 3) heat pumps (HPs), and 4), solar photovoltaics (PV) provide known electric costs for 25 years. In order to size the PV array, this study develops a thermal model for agrotunnel load calculations and validates it using the Hourly Analysis Program and measured data so the effect of plants’ evapotranspiration can be included. HPs are sized, plug loads (i.e., water pump energy needed to provide for the hybrid aeroponics/hydroponics system, DC power running the LEDs hung on grow walls, and dehumidifier assisting in moisture condensation in summer) are measured/modeled. Ultimately, all models are combined to establish an annual load profile for an agrotunnel that is then used to model the necessary PV to power the system throughout the year. The results find that agrivoltaics to power an agrotunnel range from 40 to 50kW and make up an areas from 3.2 to 10.48 m²/m² of an agrotunnel footprint. Net zero agrotunnels are technically viable although future work is needed to deeply explore the economics of localized vertical food growing systems.

Vehicular ad hoc networks (VANET) are a subset of mobile ad hoc networks used to communicate between vehicles and infrastructure. During vehicular congestion communication, nodes compete to acquire channels, causing the channels to become congested. The congestion on the vehicle network results in increased delay and packet loss, resulting in reduced VANET performance. To address this problem, we developed a load-aware and priority adaptive traffic congestion control method in vehicular ad hoc networks (VANETs). The proposed scheme identifies less-congested road segments based on the network's load and reduces traffic congestion by suggesting other routes between nearby roadside units (RSUs). This research aims to improve the efficiency of the vehicular environment by utilizing the movement of vehicles with (RSUs) and sharing the traffic load between them. Simulation results demonstrate the effectiveness of the proposed protocol in reducing congestion and enhancing the overall performance of VANETs. To validate the proposed algorithm, we have implemented and tested the proposed algorithm using Network Simulator 3 (NS3) for Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication scenarios and computed the performance of the algorithm on different parameters of the network. The simulation result of the proposed load aware and priority adaptive traffic congestion control method in VANET improved the packet delivery ratio, packet lost ratio, and end-to-end delay by 96%, 4.1%, and 1102 milliseconds, when compared to TDCCA value of 92%, 5.7%, and 1154 milliseconds, respectively

The aim of this study was to synthesize and optimize polylactide-co-glycolide (PLGA) nanoparticles loaded with rifampicin (RIF), with a given size and high loading rate, using the central composite design (CCD) method. CCD was used to investigate the influence of independent factors such as PLGA:RIF ratio, type of PLGA, type and concentration of surfactants, power and duration of homogenization, and type of organic solvent and its ratio to the aqueous phase on the dependent physicochemical characteristics of the nanoparticles. The optimized nanoparticles were investigated using scanning electron microscope (SEM), Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). Comparative evaluation of the drug release kinetics was carried out using different pH and different setups: flow cuvette (USP 4 apparatus) and Franz diffusion cuvette. In addition, the mucoadhesive properties and mycobacterial activity of PLGA-RIF NPs were studied.

Aligning supply chain and marketing functions is crucial for high-tech startups aiming to successfully launch new products in competitive markets. This qualitative research explores the strategies, challenges, benefits, and best practices associated with supply chain and marketing alignment in high-tech startups. Through a detailed analysis of case studies and semi-structured interviews with industry professionals, the study identifies key insights into how startups can effectively integrate these functions to enhance operational efficiency, market responsiveness, customer satisfaction, and risk management. The findings reveal that successful alignment requires the formation of cross-functional teams, leveraging integrated technologies like CRM and ERP systems, establishing regular inter-departmental communication, and developing joint performance metrics. These strategies foster collaboration and ensure that supply chain and marketing efforts are coordinated towards shared goals. However, startups face challenges such as differing departmental objectives, resource constraints, communication barriers, and technological limitations, which hinder effective alignment. Benefits observed from effective alignment include improved operational efficiency through streamlined processes, enhanced market responsiveness to adapt quickly to changing demands, increased customer satisfaction by delivering products that meet market expectations, and better risk management through proactive identification and mitigation of supply chain and market risks. Best practices identified include fostering a culture of collaboration, investing in technology for data integration and transparency, aligning strategic objectives across functions, and continuously monitoring and adjusting alignment strategies. Integration of broader elements such as sustainability, entrepreneurship, emotional intelligence, marketing, and supplier relationship management further enriches the alignment framework. This study contributes to a deeper understanding of how high-tech startups can strategically align their supply chain and marketing functions to achieve competitive advantage and sustainable growth in dynamic market environments.

In this study, we investigated the relationship between age and microbial diversity in cattle, revealing significant changes in both protist diversity and fungal microbiota composition with age. Using fecal samples from 21 Simmental cattle, we analyzed microbial communities through 18S rRNA gene sequencing. Results indicated significant differences in alpha protist diversity among the three age groups, while fungal composition varied notably with age and was linked to hematological parameters. Despite the stability of fungal alpha diversity, compositional changes suggest the gut as a stable niche for microbial colonization influenced by diet, clinical parameters, and microbial interactions. All cattle were maintained on a consistent diet, tailored to meet specific nutritional needs of each age group. These findings emphasize the importance of understanding age-related microbial dynamics to enhance livestock management and animal health, contributing to broader ecological and biomedical research. However, the study was limited by the lack of comprehensive metabolic analyses correlating microbiota changes with specific age-related variations, indicating a need for further research in this area.

Abstract: (1) Background: to find out how COVID-19 infection during pregnancy affects the outcome of the pregnancy; (2) Methods: 166 SARS-CoV-2-positive pregnant women formed the study group. 128 SARS-CoV-2-negative pregnant women formed the control group. Anatomopathological study of the placenta was performed in all cases; (3) Results: Placental insufficiency appeared in 38 patients (22.9%) of the study group and in 17 patients (13.2%) in the control group (p=0.016). Villitis appeared in 50 patients (30.1%) of the study group and in 16 (12.6%) in the control group (p=0.000). 166 COVID-19 positive patients were further subdivided, into those with anatomopathological affection of the placenta, and those without. When gestational age between patients with placental insufficiency and those without it are compared, a difference of 4.38 days is obtained (p=0.0393). If we compare neonatal weight between patients with placental insufficiency and those without it, a difference of 406.4 grams is obtained (p=0.0000). When gestational age between patients with villitis and those with-out it are compared, a difference of 3.2 days is found (p=0.0919). When neonatal weight between patients with villitis and those without it are compared, a difference of 242.2 grams is obtained (p=0.0018). (4) Conclusions: COVID-19 infection during pregnancy may produce lower fetal weight and shorter gestational length.

The present work consisted of an exploratory study aiming to evaluate in vitro the potential of AuNPs during Radiation Therapy (RT) in human pancreatic adenocarcinoma cells. AuNPs coated with hyaluronic and oleic acids (HAOA-AuNPs) or with bombesin peptides (BBN-AuNPs) were used. AuNPs were characterized by Atomic Force Microscopy (AFM) and Dynamic Light Scattering. BxPC-3 tumour cells were irradiated with a 6 MV X-rays beam, in the absence or presence of AuNPs. AFM showed that HAOA-AuNPs and BBN-AuNPs are spherical with a mean size of 83+-20 nm and 49+-12 nm, respectively. For RT alone, a reduction in cell viability of up to 33+-12% was obtained compared to the control (p ≤ 0.0001). HAOA-AuNPs alone at 200 and 400 μM showed a reduction in cell viability of 20+-4% and 35+-4%, respectively, while for BBN-AuNPs, at 50 and 200 μM, a reduction in cell viability of 25+-3% and 37+-3% was obtained, respectively, compared to the control (p < 0.0001). At 72 h post-irradiation, a decrease in cell viability of 26+-3% and 22+-2% between RT+HAOA-AuNPs at 400 μM and RT+BBN-AuNPs at 50 μM, compared to RT alone, was obtained (p < 0.004). The combination of RT with AuNPs led to a significant decrease in cell viability compared to the control, or RT alone, thus representing an improved effect.

This qualitative research explores the influence of supply chain disruption management on brand resilience and consumer perception. Amidst increasingly complex global dynamics, effective strategies are crucial for organizations to mitigate risks, maintain operational continuity, and preserve consumer trust. The study employs semi-structured interviews with stakeholders across diverse industries, focusing on strategies employed, outcomes observed, and challenges faced in managing disruptions. Key findings underscore the significance of proactive measures such as risk assessment, contingency planning, diversification, technology integration, and collaboration in enhancing organizational resilience. These strategies not only enable businesses to navigate disruptions effectively but also contribute to sustaining competitive advantage and stakeholder confidence. Consumer perception during disruptions emerges as pivotal, shaped by brands' transparency, responsiveness, and ethical considerations in managing supply chain challenges. Transparent communication and reliable service delivery during disruptions enhance brand reputation and foster consumer loyalty. However, challenges including information gaps, resource constraints, coordination issues, and regulatory compliance complexities highlight the need for adaptive strategies and robust partnerships across the supply chain. Overall, the study provides insights into the interconnectedness of disruption management, brand resilience, and consumer perception, offering practical implications for organizations seeking to strengthen their resilience strategies and consumer relationships in dynamic market environments.

Whole body electromyostimulation (WB-EMS) is frequently presented as a safe and attractive training technology, however evidence for this description is vague. Thus, the present study aimed to provide an overview of different aspects related to safety and attractiveness of WB-EMS in non-athletic cohorts. A systematic review of the literature according to PRISMA searched five electronic databases, two study registers and google scholar without language restrictions. Briefly, WB-EMS studies that reported adverse effects, loss to follow, withdrawal or attendance rates in non-athletic cohorts were included. Finally, 58 eligible studies were eligible. All studies applied low-frequency WB-EMS predominately 1-2x 20-25 min/week. Seventeen studies provided a superimposed protocol. While no study (n=56) reported serious adverse effects, four studies observed abnormal laboratory findings, albeit without clinical relevance. Loss to follow-up (10±11%) and withdrawal rate (5±6%) of WB-EMS trials were low, but did not differ from data for the non-training (10±12% and 4±6%) or exercise control groups (12±11% and 7±8%). In parallel, we observed high attendance rates (94±7%) in the WB-EMS groups that again did not relevantly vary from findings for the exercising control groups (n=20; 91±7%). WB-EMS can indeed be considered as a safe and attractive training technology for non-athletic cohorts, be it with or without health problems.

This qualitative study explores the transformative role of digital technologies in enhancing supply chain efficiency and marketing effectiveness across diverse industries. The integration of Internet of Things (IoT), artificial intelligence (AI), blockchain, and advanced analytics has reshaped organizational practices, enabling real-time data collection, analysis, and decision-making in supply chain management (SCM) and marketing. Through semi-structured interviews with 25 professionals, including supply chain managers, marketing executives, and IT specialists, insights were gathered into the adoption, integration, and impact of digital technologies within organizational contexts. Key findings highlight IoT's contribution to enhancing supply chain visibility, predictive maintenance, and operational efficiency through continuous monitoring and data-driven insights. AI technologies support demand forecasting, inventory optimization, and personalized marketing strategies, improving customer engagement and satisfaction. Blockchain enhances supply chain transparency, traceability, and security, reducing risks associated with fraud and ensuring compliance with regulatory standards. Advanced analytics provide organizations with actionable insights into consumer behavior and market trends, guiding strategic decision-making and optimizing marketing campaigns. Despite these benefits, organizations face challenges such as technological complexity, integration issues, data privacy concerns, and organizational resistance to change. Strategic planning, leadership support, and investment in digital infrastructure are essential for overcoming these challenges and maximizing the potential of digital technologies. Future research directions include exploring sustainability initiatives in digital SCM, advancing AI-driven analytics, and understanding digital transformation in emerging markets.

A significantly reduced stress concentration effect and a stable deformation behavior are exhibited by the arc-like S-shaped auxetic structure. Analytical works beyond the bar and hinge method to capture structural effects, such as bending, shearing, etc., in the S-structure are scarce in the literature. The deformation pattern of the S-structure is dominated by bending and shearing within the linear elastic region. In this work, Timoshenko beam theory is used to derive closed-form expressions for overall elastic modulus and Poisson’s ratio. This agrees well with the results of finite element simulations. An adjusted R-square value of over 0.99 and almost 0.82 is obtained for elastic modulus and Poisson’s ratio, respectively. From parametric studies, it’s established that under quasi-static transverse load, strut thickness and the angle `α’ are the most important parameters for controlling elastic modulus, specific energy absorption, negative Poisson’s ratio (NPR) effect, and relative density of the entire auxetic structure. Also, it’s found that energy absorption and elastic modulus increase together. Interestingly, the elastic modulus of the structure under transverse load lies in the range from 3 MPa to 250 MPa, which means this structure is compliant enough and can be used in cushioning, packaging, soft robotics applications, etc.

Robotic path planning and navigation algorithms enable autonomous mobile robots to navigate complex environments. These algorithms allow robots to be deployed in search and rescue missions, where they can locate victims in hazardous areas inaccessible to humans. Additionally, autonomous driving algorithms hold the potential to revolutionize transportation by enabling self-driving cars to navigate roads safely and efficiently. This paper focuses on developing an algorithm for autonomous navigation of the mobile robot (Tortoise bot) using robot operating system (ROS), based on publish-subscribe communication facilitating seamless interaction between various nodes. Tortoise Bot is a differential wheeled robot whose movement is based on two separately driven wheels placed on either side of the robot body. The Raspberry Pi acts as the controller. A 360-degree LiDAR and RGB-D camera are used for creating a 3D map of the environment. Various state-of-the art software tools, such as Gazebo, Ubuntu, MATLAB and RPI imager are used. Initially, a simulation based on simple obstacle avoidance is done using gazebo and MATLAB. Another simulation based on trajectory tracking is implemented using MATLAB to study the kinematic model. Online navigation and path planning are executed with the help of teleoperation and Dynamic Window Approach algorithm. A novel Wander algorithm is created that avoids obstacles on its path. Object recognition is also implemented during autonomous navigation using YOLO.

The demand for a more sustainable agriculture, coupled with the need for optimized crop productivity, has driven the use of microorganisms for the biocontrol of diseases and pests, as well as for growth promotion. The use of plant growth-promoting rhizobacteria (PGPR) and plant growth-promoting fungi (PGPF) in Brazilian production systems has become increasingly common, with the number of microbial inoculant registrations in the country growing every year. PGPR and PGPF occupy various niches in the rhizosphere, playing a crucial role in soil nutrient cycling, as well as influencing various plant physiological processes. In this review, we address the main mechanisms used by these microbial agents in growth promotion and the use of strain co-inoculation as a strategy to enhance the efficacy of these products. Subsequently, we conduct an analysis of the available inoculants in Brazil, detailing the microorganisms available for the main Brazilian crops, and the prospects of this market regarding research and development of new products for the coming years based on the current challenges faced.

Flapping wing aircraft represents a new frontier in biomimetic aviation. Researchers have developed various flapping wing aircraft intending to harness their high aerodynamic efficiency to enhance flight performance. However, current flapping wing designs still have differences in morphology and structure forms compared to real bird wings. These differences may contribute to the key problem of low lift generation in flapping wing aircraft while hovering. Hence, this paper aims to find the influence of morphology and to overcome the aerodynamic efficiency problems. By using fluid-structure interaction analysis, this study investigates the influence of variation in wing area, and aspect ratio. The results show that increasing the wing area will promote the flexible deformation and passive twist of the flapping wing, resulting in a 173.7% increase in lift coefficient. However, this also leads to increased structural stress that must be taken into consideration. Additionally, as the aspect ratio increases, total deformation and tip deformation also increase; lower aspect ratios result in a more pronounced passive twist on the wing surface (84.4% higher). Moreover, this study has designed different wing structure layouts. With different rib distributions, the passive twist, stress concentration between ribs and at rib joints, maximum stress values at the root of the wing spar, and fluctuations in stress curves are influenced. Based on the result of wing parameters and structure layout, this study proposed a flapping wing structure design with efficient aerodynamic performance. The results highlight the influence of the key parameters of wing design and lay the theoretical groundwork for future research endeavors.

Computational neuroscience has undergone a significant transformation in recent years, driven by the exponential growth of neural data and advancements in data science and machine learning. While traditional theoretical models remain valuable, there is a growing emphasis on integrating data-driven approaches to develop more accurate, biologically plausible, and predictive models of neural function. This shift has led to a new equilibrium in the field, where data-driven model development, machine learning techniques, and hybrid approaches that combine data and theory are increasingly prevalent. In this article, we discuss the evolving landscape of computational neuroscience, highlighting the importance of data-driven methods and the emergence of a more integrative approach that leverages both data and theory to unlock the mysteries of the brain. We also explore the implications of this shift for future research and clinical applications, emphasizing the potential for data-driven computational neuroscience to revolutionize our understanding of neural function and pave the way for new treatments for neurological disorders.

In this work, silver nanoparticles (AgNPs) were biosynthesized from cashew nutshell liquid (CNSL) by varying the concentration of silver ions and pH of the CNSL extract. The synthesized AgNPs were further characterized to study their surface, structural, and morphological proper-ties, and tested for the degradation of methylene blue (MB) dye. The results of this study showed that depending on the conditions, particles of various sizes, ranging from 1 to 60 nm, and different degrees of stabilization and agglomeration were produced. The concentration of silver ions equal to 3 mM and the pH of the solution of ~ 4.5 (AgNP3) resulted in the most efficient biosynthesis, where particles appeared to be highly stabilized and homogeneously distributed on the surface, exhibiting a small average particle size and a narrow particle size distribution (6.7 ± 6.5 nm). Such particles further showed the highest degradation of MB, where up to 80 % degradation rates were recorded within the first 20 min. Higher concentrations of silver ions and higher pH of the extract resulted in substantial particle agglomeration and unstable synthesis, respectively, which further negatively affected the ability of particles to degrade MB. Finally, visible light showed no significant effect on the degradation of MB by AgNPs with the average degradation rates found to be about the same as under the dark conditions.

We analyzed the interaction of two acceptor materials, reduced graphene oxide (RGO) and [6,6]-phenyl-C6-butyric acid methyl ester (PCBM), and poly(3-hexylthiphene) (P3HT), as well as the dependence of its photophysical properties with the temperature in the range 90 to 300 K. The nanocomposite of the films was analyzed by optical absorption ultraviolet-visible (UV-Vis) and photoluminescence (PL) and emission ellipsometry (EE) in a function of sample temperature. The surface morphology was studied by atomic force microscopy (AFM). We noted that onset levels (Eonset) of the nanocomposite of P3HT and RGO is smaller than the others. The PL spectra showed the presence of anomalies in the emission intensities in the nanocomposite of P3HT and PCBM. It was also possible to determine the electron-phonon coupling by calculating the Huang-Hys parameters and its dependence with the sample’s temperature. Through EE it was possible to analyze the degree of polarization and the anisotropy. We observed a high degree of polarized emission of the P3HT films which varies subtly according to the temperature. For nanocomposites with RGO the polarization degree in the emission decreases and the roughness on the surface increases. As a result, the RGO improves the energy transfer between adjacent polymer chains at the cost of greater surface roughness. Then, the greater energy transfer may favor applications of this type nanocomposite in OPVC's with enhancement in energy conversion efficiency.

Collaboration across the agriculture supply chain is essential to address the high-yield demand and sustainable practices amid global overpopulation. Limited resources, such as soil, are compromised by excessive chemical agents and nutrient use. The Internet of Things (IoT) and smart farming offer solutions by optimizing agent application, data analysis, and farm monitoring. Evidence from numerous studies indicates that collaboration in the supply chain, including farmers, can improve efficiency and productivity, reduce costs, and enhance crop quality. This research focuses on implementing IoT technology to enhance decision-making for crop yield optimization and sustainable practices on a real farm. By collaborating with a farm in the southern region of Zagreb, Croatia, farmers were trained on sensor usage and yield monitoring. Small farms in that region face challenges in improving yields due to limited capacity and lack of entrepreneurial skills. The DMAIC methodology was applied to define the problem and measure relevant parameters. The analysis demonstrated consistent patterns between electrical conductivity (EC) measurements and potassium levels in soil. It suggests the potential for estimating potassium concentrations based on EC readings, or vice versa. Leveraging EC as a proxy for potassium levels could offer a cost-effective means of assessing soil fertility and nutrient dynamics. Additionally, the PCA biplot analysis highlighted that pH value behaved independently. Understanding these dynamics enhances knowledge of soil variability and informs sustainable soil management practices.

Ab initio density functional theory molecular dynamics extensive calculations were used for the first time to evaluate stability conditions for relevant phases of InN. In particular, thermal decomposition of InN with formation of N2 molecules and pressure induced wurtzite – rocksalt solid-solid phase transition were established. The results consistent with available experimental data allowed a critical evaluation of potential and limitations of the proposed simulation method. The ab initio molecular dynamics as an efficient tool for simulations of phase transformations of InN including solid-solid structural transition and thermal decomposition with formation of N2 molecules has been demonstrated. It is of high interest because InN being important component of epitaxial quantum structures has still not been obtained as a bulk single crystal making difficult a determination of its basic physical properties and designing new applications.

An increasing need for better agricultural practices that are sustainable to provide increased yields of crops for the ever increasing food demand to be met for the growing world population is a current necessity. It is estimated by the UN that in 2050 the world’s populace may be as much as 9.8 billion global, yet, farmers still face several obstacles, which includes soil degradation, extreme temperatures, and drought which as increasingly becoming more severe with climate changes. Plant health monitoring is a method that will help to increase awareness about plant enhancing by studying how to increase crop yields while decreasing the environmental impacts. The use of low-cost, controlled environments, soil quality, water levels, and pathogenic and pests attacks can be regularly monitored. Currently, several diagnostic technologies and portable point-of-use methods and technologies are employed for detection of diseases, although, the current available lab-based methods used for plant’s diagnostics test are inadequate for plant point-of-use monitoring. The promotion of use of these point of use methods will enable pathogen detection, poor plant growth, unsuitable environmental conditions and nutrient use efficiency allowing for immediate and timely corrective actions to ensure minimal damage to the plants with maximal yield. Increase in the use of sustainable agri practices are required for ensuring higher yields with minimal inputs and that are non-destructive to the land and the use of improved methodologies and technologies will be useful tools for achieving sustainable agriculture.

Elemental sulfur, commonly known for its wide range of biological activity, has a long history of being used to protect all garden and vegetable crops from a range of pests and diseases, including powdery mildew, ascochyta blight, clubroot, plant mites, oidium, anthracnose, and scab. In the present study, a quick and environmentally friendly approach has been developed for the synthesis of sulfur nanoparticles with antibacterial activity. Sulfur nanoparticles (SNPs) were prepared by modifying the surface of elemental sulfur using various polyelectrolyte-surfactant mixtures (PSM) including NaCMC-SDBS and PHMG-CTAB. The SNPs were characterized by UV–visible spectrophotometry, X-ray diffraction (XRD), and thermogravimetric analysis (TG/DSC), scanning electron microscopy (SEM), with the SNPs showing an almost spherical shape with an average size in the range of 150-200 nm. The antibacterial activity of the sulfur nanoparticles was tested using against gram-positive S. aureus and E. faecium and gram-negative E. coli and P. aeruginosa bacteria. From this, it could be seen that SNPs exhibited significant antimicrobial activity against gram-positive bacteria, i.e., S. aureus and E. faecium. The in vitro cytotoxicity of the SNPs-1 and SNPs-2 studied to normal (MeT-5A) and tumorous (MCF-7) human cell lines was assessed in the concentration range from 500 μg/ml to 0.12 mg/ml, from which it was determined as being non-cytotoxic. The received products can be considered for potential application in agriculture and medicine.

Addressing escalating energy demands and greenhouse gas emissions in the oil and gas industry has driven extensive efforts in carbon capture and utilization (CCU), focusing on power plants and industrial facilities. Utilizing CO2 as a primary feedstock for industrial fuels and petrochemical materials offers a favorable alternative to sequestration, with byproducts substituting traditional chemical feedstocks. This comprehensive review explores the current landscape of CO2 capture technologies, examining opportunities, economic viability, and efficiency challenges. It provides a detailed analysis of various CO2 utilization methods and the combined process of capture and utilization. The review highlights primary obstacles in planning, production, and widespread implementation, emphasizing the need for strategic integration of materials research, process performance, and cost-effectiveness to advance new technologies.

Singapore, being a land-scarce country, is heavily dependent on imported food, which poses a challenge in ensuring food security. In addition, the substantial amount of food waste generated in Singapore further deepens food insecurity challenges, imposing enormous pressure on the country's food and land resources. In the recent years, valorising food waste streams into higher value products has been an increasing trend in tackling food wastage due to its economical and environmental benefits. This paper provides a thorough review on food waste valorisation in Singapore and summarizes critical information from the current food landscape to the food waste management strategies adopted. The review highlights the prototypes developed from food waste streams by the local research and development capabilities and the technological processing and techniques used for versatile applications ranging from food and nutraceuticals to urban agriculture. The challenges associated with the valorisation of food waste are also addressed. Two ambitious Initiatives by the Singapore government Zero Waste Plan and the 30-by-30 food security goal to encourage food waste valorisation are explored and presented. The review serves as a reference for other countries in ensuring food security and achieving sustainable development goals.

Currently, foam mixers are predominantly categorized into two types: low-pressure and high-pressure. Low-pressure mixers primarily use agitator rotation to mix materials. However, they face challenges such as difficulty in cleaning and complex structures. High-pressure mixers, widely adopted for their structural simplicity and lack of need for cleaning devices, effectively mitigate issues associated with low-pressure mixers. Nonetheless, they encounter problems with uneven mixing when processing high-viscosity materials. Historically, the primary solution to this issue was increasing the working pressure. However, the capacity to increase pressure is finite, and higher pressure demands higher quality materials for the mixers. To address the issues high-pressure mixers face when dealing with high-viscosity materials, this study focuses on the polyimide high-pressure mixer. After reviewing previous studies, four design variables were selected: the mixer's impingement angle, inlet diameter, outlet diameter, and impingement pressure. Using a Full Factorial Design of Experiments (DOE), the significance of the impact exerted by these four variables on Mixing Unevenness was analyzed, determining the extent of their influence. Optimal Latin Hypercube Sampling generated several random sample points, followed by the establishment of both a Back Propagation (BP) Neural Network approximation model and a Kriging approximation model. A Genetic Algorithm was then applied to optimize these two approximation models, resulting in the optimal combination of design variables. The research findings indicate that the BP Neural Network exhibits higher predictive accuracy compared to the Kriging prediction model. The optimal combination of parameters, optimized through the Genetic Algorithm (GA), reduced the Mixing Unevenness by 69.1%, effectively decreasing the Mixing Unevenness of the mixer head.

The importance of rare earth elements as the basis in the development of new technologies or the improvement of the used ones, made of a necessity its recovery, besides that from raw materials, from waste materials. In this recovery, Hydrometallurgy and its derivative Solvometallurgy, play a key role due to its operational characteristics, which are emphasized with the use of ionic liquids. The manuscript reviewed the most recent advances (2023 and 2024 years) about the use of ionic liquids in the unit operations (leaching and separation technologies) aimed to the recovery of these valuable and strategic metals. Moreover, a comprehensive review about the use of these chemicals in the development of advanced materials containing some of these rare earth elements is presented.

The savings behavior of individuals has been a topic of both macroeconomic and policy importance throughout history. Theoretical and empirical research offers strong evidence that savings are the result of a number of demographic and economic factors working together to produce long-term, sustainable economic growth. This study therefore looked at how domestic savings affected South Africa's economic growth between 1970 and 2022. The ARDL framework was used to analyze data that came from the World Bank and the South African Reserve Bank. The results of the study demonstrate that corporate savings have a major effect on economic growth, especially over the long term. When corporate savings rise by 1%, the economy expands by 3.12%. On the other hand, savings by the government and the general public, especially in the long run, have no appreciable impact on economic growth. Given that domestic savings mobilization is the most suitable channel for financing capital accumulation to support economic growth and development, the study suggests reviewing current policies to encourage domestic savings mobilization.

This study aims to provide an updated overview of the systematic evaluation and management of Post-Traumatic trigeminal neuropathic pain (PTTN) resulting from dental procedures or trauma. PTTN arises following an injury to the trigeminal nerve, which is responsible for sensory and motor functions in the maxillofacial region. The etiology encompasses various dental procedures and craniofacial trauma, leading to a spectrum of symptoms, from tingling to severe pain. Diagnostic challenges stem from the absence of standardized criteria and the overlap with focal neuralgia, necessitating comprehensive evaluation. Misdiagnosis can result in prolonged suffering and unnecessary procedures. Successful management hinges on prompt diagnosis and interdisciplinary collaboration, with early intervention crucial in mitigating chronicity. While nerve recovery post-trauma is challenging, preventive measures through accurate evaluation and treatment are paramount.  Management for PTTN includes non-invasive and surgical interventions. Non-invasive intervention includes systematic and local pharmacological management. This review enhances uniformity in PTTN evaluation and treatment approaches despite standardized study limitations.

The accurate diagnosis and effective treatment of mental health disorders such as depression remain challenging owing to the complex underlying causes and varied symptomatology. Traditional information extraction methods struggle to adapt to evolving diagnostic criteria such as the Diagnostic and Statistical Manual of Mental Disorders fifth edition (DSM-5) and to contextualize rich patient data effectively. This study proposes a novel approach for enhancing information extraction from mental health data by integrating medical knowledge graphs and large language models (LLMs). Our method leverages the structured organization of knowledge graphs specifically designed for the rich domain of mental health combined with the powerful predictive capabilities and zero-shot learning abilities of LLMs. This research enhances the quality of knowledge graphs through entity linking and demonstrates superiority over traditional information extraction techniques, making a significant contribution to the field of mental health. It enables a more fine-grained analysis of the data and the development of new applications. Our approach redefines the manner in which mental health data are extracted and utilized. By integrating these insights with existing healthcare applications, the groundwork is laid for the development of real-time patient monitoring systems. The performance evaluation of this knowledge graph highlights its effectiveness and reliability, indicating significant advancements in automating medical data processing and depression management.

Background: The increase in the prevalence of obesity in South Africa is a problem and weight management play an important role in the treatment of the high prevalence. For this purpose, a quantitative study was carried out using a structured questionnaire to assess predictors of attempt and failure to lose weight. Methods: One thousand and fifty adults were enrolled in the study and 54% (n=562) were overweight and obese (BMI &gt;/25kg/m2). Descriptive statistics were analysed. Inferential statistical tests (chi-square tests, logistic regression, and Pearson’s correlation coefficients) were used to determine the relationship between variables. Results: The results revealed that age, sex, marital status, educational level, employment status, income level, area of residence, ethnic groups, and self-perceived BMI (normal weight, overweight, and obese) were predictors of attempt and failure to lose weight. There was a positive correlation between self-perceived BMI and the attempt and failure to lose weight. Conclusion: Weight management is important in the realm of public health and can be regarded as an investment in the population, as it leads people toward weight control strategies grounded in empirical evidence. Additionally, the findings can inform public health policies and interventions to improve weight management strategies at the population level.

Malignant melanoma (MM) is the most fatal form of skin cancer, accounting for 90% of all skin cancer deaths. Multiple dysregulated cellular pathways are involved in MM, including the MAPK/ERK and PI3K/PTEN/AKT pathways, which can be targeted with novel targeted inhibitors. However, these blockades can be overcome through the activation of alternative pathways, leading to treatment resistance. The high immunogenicity of MM has been exploited using checkpoint inhibitors resulting in improved survival outcomes of patients with advanced MM. However, their side effect profile and prohibitive cost remain a challenge and the survival outcomes for patients with metastatic MM remain poor. Treatment resistance has been attributed to the presence of cancer stem cells (CSCs), a small subpopulation of pluripotent, highly tumorigenic cells proposed to drive cancer progression, metastasis, and treatment resistance. CSCs reside within the MM tumor microenvironment (TME) regulated by the immune system, and the paracrine renin-angiotensin system (RAS), expressed in many cancer types, including MM. This article reviews the current treatment of advanced MM with targeted therapy and immune checkpoint blockers, highlights the emergence of mRNA vaccine. It also discusses the MM TME and its relationship with CSCs, and the local immune system and the paracrine RAS. It highlights the regulation of the MAPK/ERK and PI3K/AKT/mTOR pathways by the RAS via prorenin receptor and angiotensin II receptor 1, and how this relates to the CSCs and treatment resistance. This underscores the potential multi-modal therapeutic strategy by concurrent targeting of multiple components of the TME.

The advancement of mechanization in forestry has bolstered productivity within the sector while simultaneously precipitating impacts necessitating deeper comprehension for the attainment of heightened levels of environmental sustainability in forestry management. The aim of this study was to apply an instrument for assessing the environmental damage and impacts of forest harvesting in commercial Eucalyptus plantations, based on a combination of methodologies. The environmental impact assessment methodology for forest harvesting was applied by combining interaction network approaches and impact assessment matrices. This methodology was then applied to a commercial Eucalyptus plantation in the municipality of São Pedro, state of São Paulo, Brazil. The results show that timber transportation activities had the highest positive and negative environmental indices. The most significant negative impacts refer to the depletion of water resources and erosion, while the positive impacts are regional development and job creation. The most significant changes, both positive and negative, were observed in a greater number of environmental impacts for the physical and anthropic environment, with fewer for the biotic environment. The combination of methodologies has potential as an expedient tool for planning forestry operations, providing practical results for decision-making, making production more sustainable and applicable to different crops and production systems.

Background: This longitudinal study aimed to investigate the relationship between self-reported chewing status and increases in waist circumference (WC) after 1 year in 10,870 Japanese adults who had received health checkups. Subsequently, 8,068 participants were included in the final analysis at follow-up. Methods: Chewing status was evaluated using a self-reported questionnaire at baseline; 1,080 (13%) respondents were diagnosed as having poor chewing status. We defined an increase in WC of ≥ 5 cm after 1 year as an unhealthy increase; in total, 613 (7.5%) respondents met this criterion. Results: After adjusting for age, gender, WC, body mass index (BMI), and chewing status, an increase in WC ≥ 5 cm was found to be positively associated with gender (females: odds ratios [ORs]: 1.206; 95% confidence intervals [CIs]: 1.008–1.443), WC (ORs: 0.967; 95% CIs: 0.954–0.981), BMI (≥ 25 kg/m2; ORs: 2.194; 95% CIs: 1.715–2.808), and chewing status (poor; ORs: 1.356; 95% CIs: 1.084–1.697). Conclusions: These findings suggest that self-reported poor chewing status is associated with increases in WC after 1 year in Japanese adults.

This study investigates how students' well-being relates to sustainable development and education for sustainability at Prince Mohammad Bin Fahd University, Saudi Arabia. The authors endeavor to answer the question "How Does Students' Well-Being Relate to Sustainable Development Via Education for Sustainable Development?" and four sub-questions. Primary data were collected by semi-structured interviews exploring the viewpoints of twenty female and male students (n=26) aged between 18 and 26. The content analysis results have identified additional well-being and education for sustainability factors that influence sustainable education and, therefore, sustainable development. These antecedents include workload, transparency, grading criteria, fairness, belonging, work-life balance, mental health support, missing emotional intelligence factors, factors related to Education for Sustainable Development, such as instructors' role models, institutional commitment, leadership, and collaboration with government. In addition, the study developed a theoretical model for the relationship between antecedents for Education for Sustainable Development, Education for Sustainable Development, and Sustainable Development in the Saudi context. Finally, the study answers four research questions: What factors contribute to education for sustainable development? What are the antecedents of education for sustainable development? How do university educators contribute to sustainable education? How do the antecedents of education for sustainable development, education for sustainable development, and sustainable development relate?

In recent years, extensive research has been conducted on the IoT, one of its challenges has been the field security and penetration in these networks. security solutions it Require more planning and awareness to ensure system security and privacy protection.it has also been shown that adjusting the weights of neural networks can help improve the accuracy of detection to what extent. the challenge in the attack detection field is to increase the accuracy of attack detection by machine learning methods, in this paper, a new method is presented to adjust weights of the random neural network for attack detection. Evaluations of the proposed method show that compared to random neural network methods, nearest neighbor, and support vector machine, the accuracy of attack detection improves up to 99.49 percent, and the random neural network method has been able to improve by 99.01 percent, placing the best methods together in these experiments in the form of a multi-learning model showed that the results also had an increase in accuracy up to 99.56 percent, while the training time in the proposed model is less compared to the random neural network method.

Wireless Sensor Network (WSN) and the sensing devices are considered part of the core components of the Internet of Things (IoT). Hence, the modeling of IoT-WSNs is fundamental to having a better understanding, management, and deployment of this kind of technology. A fundamental issue in WSN is energy consumption due to the inherent limitations of this resource in the sensor devices. On the other hand, several issues arise in heterogeneous scenarios due to the coexistence of different sensor devices. Therefore, the modeling process becomes challenging and must consider the different transmission and operation cycles and modes that the transmission protocol implements to assure successful functioning in terms of transmission, synchronization, and energy savings. A duty-cycled MAC WSN protocol (PSA-MAC) has been modeled based on a pair of two-dimensional Discrete-Time Markov Chain (2D-DTMC), whose solution in terms of stationary probability distribution is used by expressions that have been derived to evaluate the energy consumption of sensor devices that could be used for WSN-based IoT applications. Analytical results of average energy consumption are obtained, where the synchronization, data, and sleep periods of a full transmission cycle are considered in a heterogeneous scenario with different node classes and priority assignments. Also, the normal and awake operation cycles are considered to assure synchronization and energy savings. Moreover, the transmission schemes of SPT (transmission of single packets) and APT (transmission of packets in aggregation) are also considered in the model. These results are validated through discrete event-based simulations, and the obtained results are accurate.

The energy transition is a challenge that affects all sectors, from transport to civil structures and industry. In the industrial sector, the greatest need is the decarbonisation of energy-intensive in-dustries, such as producers of iron and steel, aluminum, cement, petrochemicals, paper, and more. The steel industry, in particular, is a hard-to-abate high-emissivity industry that, due to chemical processes and high thermal demands (often above 500 °C), contributed to 7.4% of global CO2 emissions in 2021. This paper explores the potential applications of hydrogen in these hard-to-abate sectors, highlighting its versatility and significance in decarbonization efforts, especially as a me-dium to facilitate the transition to green electric energy uses. It provides an overview of hydrogen production methods, emphasizing the importance of sustainable and green hydrogen production. It reviews hydrogen production methods, storage, and potential in blended combustion. In the final part of the article, some considerations are introduced on the possible role of hydrogen in the steel sector (both as a supplementary fuel and as a reducing agent in innovative processes), showing that while there is potential for its inclusion as an element for decarbonization, it is necessary to carefully evaluate the energy balances of the various processes and the methods of hydrogen production, in order to avoid achieving only marginal effects.

One important goal of research on heterogeneous catalysis for Fischer Tropsch synthesis (FTS) is to understand the connection linking catalyst morphology and its activity. Development of these effective catalysts highlights the potential for understanding the effectiveness of promoted supported catalysts and revealing their complex and dynamic effects in FTS. The metal-support interaction (MSI) is influenced by the physicochemical and textural features provided by the modified support and can directly influence the sizes of active metal crystallites, reactants and/or products mass transfer, dispersion, mechanical strength, stability and consequently the adsorption-desorption characteristics of the catalyst. Herein, this article explores the general strategies for modifying silica supports (achieved through doping, coating, or promoting the support or support precursor) and how these strategies can be manipulated to further alter catalyst performance and product selectivity by enhancing the amount of active metal species and improving the intrinsic turnover frequency (TOF). Furthermore, the review emphasises a new strategy (the inverse model of the silica support modification) aiming at overcoming the challenges posed by active metal coating or coverage, as well as pore blockages by promoters that occur during conventional preparation of promoted silica supported FT catalysts.

The detection accuracy of bridge superficial defect using the deep neural network approach decreases significantly under light variation and weak texture condition. To address these issues, an enhanced intelligent detection method based on the YOLOv8 deep neural network is proposed in this study. Firstly, multi-branch coordinate attention (MBCA) is proposed to improve the accuracy of coordinate positioning by introducing a global perception module in coordinate attention mechanism. Furthermore, a deformable convolution based on MBCA is developed to improve the adaptability for complex feature shapes. Lastly, the deformable convolutional network-attention-YOLO (DAC-YOLO) detection algorithm is formed by replacing the deep C2F structure in the YOLOv8 architecture with deformable convolution. A supervised dataset consisting of 4794 bridge surface damage images is employed to verify the proposed method, and results show that it achieves improvements of 2.0% and 3.4% in mAP and R. Meanwhile, the model complexity decreases by 1.2G, increasing the detection speed by 3.5/f·s-1.

Sweden has long been hailed as a role model in climate policy. But the new right-wing government supported by a far-right populist party is undertaking a paradigm shift in Swedish climate policy and governance. This paper critically analyses this paradigm shift and its impacts on legitimacy, accountability and justice. These are democratic norms important in the analysis of a just transition to climate neutrality. Severe democratic deficits of the policy process and the policies proposed and adopted are identified, suggesting ‘nasty politics’ characterised by populist, divisive, and contentious rhetoric that entrenches polarization and us/them narratives. Climate scientists and the climate justice movement are discriminated in the policy process, the latter also being accused of terrorism and seen as a threat to democracy by the government. The deficits are partly explained by the neo-corporatist political system of Sweden and the dominance of the (neo)liberal discourse of ecological modernization in Swedish environmental policy, but primarily with the ongoing process of autocratization driven by anti-democratic far-right populist parties throughout Europe. The anti-democratic climate policy reforms in Sweden are foreboding an unwelcome development in the EU given the boost of far-right populist parties in the upcoming elections to the European Parliament in June 2024.

In this study, a new diphosphate compound, Ag0.2Na0.6FeP2O7, was synthesized using a solid-state reaction method and extensively studied using various techniques. The compound's structure was confirmed through X-ray diffraction analysis, revealing a single-phase monoclinic structure with the P21/C space group. The electrical behavior of the compound was investigated, and its conductivity followed Jonscher's universal law. The correlated barrier hopping (CBH) model explained the temperature-dependent ac conductivity and parameter "s" well. The study also explored the contribution of single-polaron and bipolaron hopping to the a.c. conductivity and discussed the ionic conductivity in relation to the structural characteristics of the sample. Overall, this investigation significantly enhances our comprehension of the distinctive electrical properties of Ag0.2Na0.6FeP2O7 and its potential practical applications.

Introduction: Emotional intelligence plays a critical role in nursing leadership, influencing organizational dynamics and patient care. However, there is limited understanding of the impact of Emotional Intelligence on leadership in Primary Health Care in the Greek context. Methods: A longitudinal experimental design assessed the effects of an educational intervention on EI and leadership among Greek Primary Health Care nurses. Questionnaires, including the Wong and Law Emotional Intelligence Scale (WLEIS) and Multifactor Leadership Questionnaire - form 5x (MLQ), were administered pre- and post-intervention. Results: The intervention group exhibited significant improvements in Emotional Intelligence and adoption of transformational leadership styles compared to the control group. Tables highlighted nuanced changes in leadership dynamics post-intervention. Conclusions: Educational interventions effectively enhance nurses' Emotional Intelligence and influence leadership styles, emphasizing the need for tailored professional development programs in nursing education.

The prognostic abilities of artificial intelligence and neuroscience in forensics and the criminal justice system stand as a reformatory paradigm for understanding any criminal conduct. While the use of artificial intelligence has been labeled transformational data analytical capabilities, neural predictive approaches also enable an intricate understanding of culpability and criminal propensities. The literature on the complex nature of neuroprediction and artificial intelligence, its ethical deliberations and its usability in curving recidivism are analyzed. This theoretical review elucidates the complex interplay, nuptial relationships and convergence of these relationships in the quest for justice. The consequences of not protecting individual rights in the criminal justice system are surveyed using grounded theory. The degree of acceptability and dependability of AI-generated evidence in legal proceedings are also reviewed. All these topics are yet to be contemplated under one roof to offer an argumentative view. The author expects to prompt readers and new commers to embrace more sociolegal and technological research before incorporating such research in the Indian Judiciary. The review focuses on the question of whether to blame such technology inclusion wholly or rather to prioritize the acquisition of bias-free pretrained datasets and processing models.

The paper presents the reconstruction of paleoenvironmental conditions in the Gdansk, Bornholm and Arcona Basins of the Baltic Sea over the last millennium. A complex study (including geochemical, XRF, grain size, AMS and micropalaeontological analyses) of five sediment cores, retrieved by short gravity corer of Niemistö type, was performed. The cores are mainly represented by undisturbed silty muds of olive-grey and grey colours. The age models for the cores were built based on Pb distribution along the sediment sequences as radiocarbon dating resulted in excessively old age. Despite generally very low foraminiferal amount and diversity the increased inflow activity was reconstructed during the Medieval Climate Anomaly. The strongly positive North Atlantic Oscillation (NAO) index during this period led to a prevalence of westerlies over the Baltic region and stronger saltwater intrusions. In the recent sediments, the reconstructed inflow frequency demonstrates a decadal variability rather than the reduction, although, the general decline compared to the Medieval Climate Anomaly is seen.

This study assesses the impact of militarization, industrialization, technological innovation, and energy consumption on CO2 emissions in NATO countries, divided into "traditional" (Group 1) and "new member" states (Group 2), using data from 1985 to 2019. It identifies heterogeneity in effects and dependencies between the groups. Employing Pedroni and Kao panel cointegration tests, a long-term equilibrium relationship among the variables is confirmed. The analysis, using panel ARDL and GMM methods, reveals distinct outcomes for each group. In Group 1, military spending and energy consumption significantly increase CO2 emissions, while industrialization and technological innovation reduce them. Conversely, in Group 2, technological innovation and energy consumption raise emissions, whereas military spending and industrialization decrease them. The findings suggest Group 1 should strategize military expenditure and energy consumption to cut emissions, whereas Group 2 should focus on eco-friendly technology and efficient energy use to achieve environmental sustainability.

: This study aimed to validate the effects of self-compassion-based forest healing therapy as an intervention for reducing stress and promoting coping resources. Therefore, we investigated the effects of self-compassion-based forest healing therapy on stress, self-compassion, and connectedness to nature. A total of 30 participants were divided into an experimental and control group. Two sessions of forest healing meditation activities were held at the Forest of Healing every two weeks between October and November 2023. As a repeated measures experiment, data were collected before the intervention, after the first intervention, and after the second intervention. Perceived stress, positive and negative affect, and salivary cortisol were measured to assess physiological and psychological stress in participants. Connectedness to nature and self-compassion were measured to evaluate stress-coping resources. The results showed that the forest healing program had significant positive effects on stress and emotional states in the experimental group after the intervention. Further, there was a significant incremental effect on connectedness to nature and self-compassion in the experimental group. Therefore, self-compassion meditation-based forest healing therapy is a feasible and efficient approach for facilitating stress management and coping resource building.

Oil and gas refineries are highly water-intensive industrial settings, with effluent containing a significant level of pollution stemming from diverse organic and inorganic compounds. Besides adhering to discharge standards for industrial effluent, incorporating treated oil refinery effluent (ORE) into the production cycle can play a pivotal role in curbing water consumption. In recent years, there has been research into different approaches to reclaiming ORE. Yet, selecting treatment methods that are technically, economically, and environmentally effective is crucial to preventing resource waste. Therefore, this study aimed to examine the last two decades of literature on methods and technologies used for ORE treatment. Based on the inclusion criteria, the final screening included 82 studies, with acceptable agreement assessed using Cohen's inter-examiner kappa equal to 0.86. The included studies were of biological treatment (n = 27), physicochemical processes (n = 12), advanced purification processes (n = 16), membrane-based technologies (n = 15), and green technologies (n = 13). This comprehensive review showed that the advanced membrane-based techniques are effective in the removal of pollutants from ORE for several reasons, such as reducing the consumption of chemicals, high efficiency, and ease of setup and maintenance. However, combined methods with a focus on membrane-based processes (e.g. UF-RO) are the most promising options for the reclamation of ORE. Since some effluent treatment methods require the use of chemicals and energy to run, future research should focus on environmentally friendly methods and the use of renewable energy.

There is evidence that the tendency to adopt a particular pattern of causal inference, known as attributional style, is likely to be associated with specific pattern of psychopathology among youth. This study aims to assess preliminary psychometric properties of the Italian Children’s Attributional Style Questionnaire-Revised (CASQ-R) and to explore the presence of any subgroups of children and early adolescents from the general population who might exhibit internally homogeneous and externally heterogeneous attributional styles, through cluster analyses, delving also potential sociodemographic and clinical differences among the identified clusters of attributional styles. A sample of 337 children was recruited and their attributional styles and depressive symptoms were analyzed. Four distinct clusters emerged using the six CASQ-R subscales in a multivariate finite mixture model. In particular, high levels of depressive symptoms were reported by children showing high scores in all the negative attributional subscales (globality, internality and stability) and medium scores in all the positive attributional subscales. Conversely, low levels of depressive symptoms were reported by children showing medium-to-high scores in the positive attributional subscales and low-to-medium scores in the negative attributional subscales. The identified clusters shed light on distinct patterns associated with depressive symptoms, offering potential insights for targeted interventions.

The fractional reduced differential transform method is a finite iterative method based on infinite fractional expansions. The result obtained is the approximation of the real value. There are few reports on the approximate error and the applicable condition. In this paper, according to the fractional expansions, we study the factors related to the approximate errors. Our research shows that the approximate errors relate not only to fractional order but also to time $t$ and increase rapidly with time $t$. This method can only be applied within a certain time range and the time range is relevant to fractional order and fractional expansions. Then, many obtained achievements may be incorrect if the applicable conditions are not satisfied. Some examples presented in this paper verify our analysis.

Marine finfish landings in Cuba have decreased during the last 30 years. However, in Cuba's most productive fishing region, certain species, including rays, herrings, and snappers, have increased landings over the past decade. Despite these anomalies, no comprehensive analysis of the interactions between multispecies landing dynamics, environmental factors, and fishing effort has been carried out. This study estimates the dynamics of multispecies finfish landings between 1981 and 2017 on the southeastern coast of Cuba. Dynamic factor analyses (DFA) were performed to identify common landing trends across multiple species and their relationship with fishing effort and environmental variables. During the period analyzed, finfish landings and fishing effort decreased by 46% and over 80%, respectively. Despite concerns about overfishing, landings per unit of effort (LPUE) increased by 2.8 times, suggesting the decline in landings was closely linked to decreasing fishing effort and Atlantic Multidecadal Oscillation cycles, with delays of 2 and 3 years. The study highlights the changing relationship between landings and fishing effort, suggesting that LPUE may not accurately reflect true stock abundance. The findings of this study will assist in integrating the dynamics of finfish species, ecosystem status, and management actions for Cuba’s most productive fishing zone.

Background: There have been reports of numerous risk factors for Alzheimer's disease. Although widely investigated, some points during the evolution of the disease have been obscure. One of them is a great frustration with therapeutic expectations. Why has there been an increase in suicidal behavior in treatments with anti-beta-amyloid drugs? Interpersonal stress is one of the factors that may be connecting Alzheimer's disease to suicide. Method: To observe possible associations between Alzheimer's disease and suicide, two validated questionnaires were selected. We recruited 20 elderly patients over 65 years old to observe the feasibility of further research using these instruments. The study was considered viable if all participants showed no difficulty in understanding the questions and completed both questionnaires in less than 30 minutes with a tendency to homogeneity. A description of the statistical data obtained was made. Results: All participants adequately understood the questions and completed the questionnaires in less than 30 minutes. In 10% of the sample, suicide attempts occurred throughout their lives. The average age of respondents was 75 years old. The QoSL Pareto diagram demonstrated a large concentration. The data demonstrated homogeneity. Conclusions: The application of the questionnaires in a sample suitable for carrying out analytical statistics was demonstrated. We have two great tools to try to understand the possible association between Alzheimer's disease and suicide.

Food safety in dairy shops has gained increasing attention. Consequently, this study aims to evaluate dairy handlers' knowledge of food safety practices, assess compliance with food safety codes regarding facility maintenance and personal hygiene, and understand retail dairy shops' capacity to implement food safety standards. This research involved surveys and interviews with 110 dairy retail workers to gauge their grasp of food safety principles, their recognition of its importance, and the obstacles they encounter in implementing proper food safety measures. Among the participants, 93% were males under 35 years old, with experience ranging from 1 to 8 years. The study revealed that while over 83% of participants were familiar with standard procedures ensuring dairy product safety, only 37% understood “HACCP” in relation to food safety. Additionally, 42% believed that freezing food at -18°C eliminates food bacteria, and 56% thought food contamination could be identified by taste, indicating misconceptions among respondents. Results showed that 90% of survey participants had a strong awareness of food safety, with 98% emphasizing the importance of regular inspection of production areas for cleanliness to ensure a safe dairy production environment. However, less than 45% had received formal training on dairy-specific food safety practices, and only 53.6% had a documented system for correctly labeling and providing production dates for dairy products. These findings have significant implications for public health and food safety policies in Jordan. Furthermore, the study provides valuable insights to enhance food safety practices among dairy retail vendors.

Viral tropism is most commonly linked to receptor use, but host cell protease use can be a notable factor in susceptibility to infection. Here we review the use of host cell proteases by human viruses, focusing on those with primarily respiratory tropism, particularly SARS-CoV-2. We first describe the various classes of proteases present in the respiratory tract, as well as elsewhere in the body, and incorporate the targeting of these proteases as therapeutic drugs for use in humans. Host cell proteases are also linked to the systemic spread of viruses and play important roles outside of the respiratory tract; therefore, we address how proteases affect viruses across the spectrum of infections that can occur in humans, intending to understand the extrapulmonary spread of SARS-CoV-2.

This paper investigates calendar anomalies, volatility patterns, and the best forecasting model for predicting volatility in the cryptocurrency market, focusing on ten prominent cryptocurrencies: Binance USD, Bitcoin, Binance Coin, Cardano, Dogecoin, Ethereum, Solana, Tether, USD Coin, and Ripple. Spanning from January 2016 to December 2023, the study utilizes sophisticated statistical models such as GARCH (p,q), EGARCH (p,q), and GJR-GARCH (p,q) to analyze precise changes in market dynamics and the impact of day-of-week fluctuations on cryptocurrency returns. Empirical evidence reveals significant findings regarding the persistence of volatility, positive and negative news effects on volatility, and day-of-week effects on cryptocurrency returns. Post-COVID-19, Sunday emerges as the least volatile day for cryptocurrencies, while Thursdays and Tuesdays exhibit greater volatility. Binance, Ethereum, Dogecoin, and Tether show anomalies where returns on Tuesday and Thursday significantly differed from those on other days of the week. Many other currencies, like the USD coin, Cardano, and Ripple, show anomalies only in the pre-COVID-19 period. The findings highlight the best forecast model for volatility for each top cryptocurrency, offering practical implications for investors, traders, regulators, and policymakers. These insights emphasize the importance of understanding and addressing calendar anomalies in the cryptocurrency market for informed decision-making, trading strategies, regulatory frameworks, and market stability.

This literature review offers a comprehensive analysis of the design and optimization of microstrip patch antennas for wireless communication systems, drawing insights from a variety of research papers. It examines diverse approaches aimed at enhancing antenna performance and functionality. Key topics explored include optimization of resonant frequency, design of antenna arrays, and bandwidth enhancement. Noteworthy optimization techniques, such as genetic algorithms and artificial neural networks, are discussed, highlighting their effectiveness in achieving superior antenna performance. Application-specific solutions tailored to areas such as military communication and RFID systems are emphasized. The review underscores the significant role played by optimization techniques in achieving desired performance metrics and identifies future research directions, including multi-objective optimization, investigation of robustness and reliability, and integration with advanced technologies. Overall, this literature review provides valuable insights into the state-of-the-art in microstrip patch antenna design and optimization, guiding future research endeavors in this dynamic and rapidly evolving field.

Surface treatment of implants facilitates osseointegration, with nanostructured surfaces exhibiting accelerated peri-implant bone regeneration. This study compared bone-to-implant contact (BIC) in implants with hydroxyapatite (HA), sand-blasted and acid-etched (SLA), and SLA with calcium (Ca)-coated (XPEED®) surfaces. Seventy-five disk-shaped grade 4 Ti specimens divided into three groups were prepared, with 16 implants per group tested in New Zealand white rabbits. Surface characterization was performed using X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), digital microscopy, and a contact angle analyzer. Cell viability, proliferation, and adhesion were assessed using MC3T3-E1 cells. Apatite formation was evaluated using modified simulated body fluid (m-SBF) incubation. After 4 weeks of healing, the outcomes reviewed were BIC, bone area (BA), removal torque tests, and histomorphometric evaluation. Microstructure analysis revealed irregular pores across all groups, with the XPEED group exhibiting a nanostructured Ca-coated surface. Surface characterization showed a crystalline CaTiO3 layer on XPEED surfaces, with evenly distributed Ca penetrating the implants. All surfaces provided excellent environments for cell growth. The XPEED and SLA groups showed significantly higher cell density and viability with superior osseointegration than HA (p &lt; 0.05); XPEED exhibited the highest absorbance values. Thus, XPEED surface treatment improved implant performance, biocompatibility, stability, and osseointegration.

Τhis study aims to assess changes in the fovea avascular zone (FAZ) in treatment naïve patients receiving aflibercept or ranibizumab injections for diabetic macular edema (DME). This is a prospective study recruiting patients with treatment-naïve DME. Best corrected visual acuity (BCVA) testing, OCT and OCT-angiography (OCTA) imaging were performed at baseline and 1 month after each injection. Injections of either aflibercept or ranibizumab were administered monthly for 6 consecutive months. FAZ in the superficial (SCP) and the deep capillary plexus (DCP) using OCTA was recorded for each visit. Fifty eyes from 50 patients with a mean age of 67.010.7 years were included in the study Twenty-five patients received aflibercept and 25 received ranibizumab. BCVA was 40.810.0 and increased to 52.17.9 ETDRS letters at the last visit (p&lt;0.001). CRT was 295.634.0 at baseline and 247.929.7 at the last study visit (p&lt;0.001). SCP FAZ was 350.679.5μm2 at baseline and 339.071.3μm2 after 6 monthly injections (p=0.132). DCP FAZ was 558.6199.0μm2 at baseline and 459.5156.1μm2 after 6 monthly injections (p&lt;0.001). There was no effect of the choice of ranibizumab or aflibercept on DCP FAZ change (p=0.277). In conclusion, treatment with 6 monthly injections of ranibizumab and aflibercept led to an increase in BCVA and a decrease in CRT and DCP FAZ area. Both drugs led to an improvement in DCP ischemia.

Verification of inclusivity of molecular detection methods gives indications on the reliability of viral infections diagnosis because of the tendency of viral pathogens to undergo sequence variation. This study was aimed to select inclusive probe based reverse transcription quantitative PCR (RT-qPCR) assays for the diagnosis of the most widespread and detrimental viruses infecting honeybees, namely the acute bee paralysis virus (ABPV), the black queen cell virus (BQCV), the chronic paralysis bee virus (CBPV), the deformed wing virus variants A (DWVA) and B (DWVB), and the sacbrood virus (SBV). Therefore, detection methods previously described were re-evaluated in silico for specificity and inclusivity. Based on this evaluation, selected methods were modified or new ones were designed and tested in duplex RT-qPCR reactions. The limits of detection (LODs), effect of multiplexing on sensitivity and viral RNA quantification potential in bees and hive debris were assessed. This study made available diagnostic assays able to detect an increased number of virus variants compared to previously described tests and two viral pathogens in a single PCR reaction.

The hotel sector generates related environmental aspects from its construction process to the operation of its activities, products and services. In this way, corporate environmental management becomes directly linked, since it provides an adequate management of its resources, thus minimizing impacts. Thus, this research aims to carry out a socioeconomic and environmental diagnosis of the hotel sector in the municipality of Mossoró-RN. The study was classified in an exploratory, descriptive and explanatory way, with a qualitative-quantitative approach that is based on bibliographic, documentary and field research, carried out in 10 lodging facilities, through the application of questionnaires, on general aspects, initial environmental assessment and environmental aspects, and the data obtained were treated in Microsoft Excel software with the objective of creating a model and demonstrating results on the sustainable level of each establishment in question. The profile of the lodging facilities analyzed is characterized by 50% having from 10 to 30 rooms, 80% having between 10 and 30 employees, 80% being micro-enterprises, with 50% in an area of 750 m² to 2250 m² and 80% operating for more than 10 years. Point out a relevant result on the impacts of companies. The projects analyzed were built without any complaint for environmental crime and without negative impacts on the local population. Actions to reduce consumption were also observed, especially for the rationalization of water and energy. To this end, it points out that the adoption of the Environmental Management System (EMS) as a differential in the management of aspects and impacts of the hotel sector.

Potato virus Y (PVY) is one of the most important constraints to potato production worldwide. There is an increasing occurrence of recombinant PVY strains PVYNTN and PVYN-Wi and a decline in the incidence of the nonrecombinant PVYO. We hypothesized that this may be due to the ability of these recombinant strains to antagonize and/or outcompete PVYO in mixed infections. To deter-mine this, we investigated interactions between PVYO and three recombinant PVY strains com-mon in North America: PVYNTN, PVYN-Wi, and PVYN:O. Overall, our study showed that these inter-actions are tissue dependent. Specifically, PVYNTN, the main causal agent of potato tuber necrotic ringspot disease (PTNRD), was found to be more adaptable than PVYO, especially in potato leaves due, at least in part, to the Ny gene that confers hypersensitive resistance (HR) to PVYO. Further-more, PVYN-Wi was found to repress PVYO in potato tubers but act synergistically in potato leaves. The PVYO-induced foliage necrosis in cultivar ‘Ranger Russet’ was observed to be more severe in plants co-infected by PVYN-Wi and PVYN:O, respectively, resulting in plant death. Strikingly, this PVYO -induced necrosis was suppressed by PVYNTN in doubly infected plants. These interactions may, at least partially, explain the decreasing incidence of PVYO in United States potato produc-tion regions, especially given that many cultivars contain the Ny gene, which likely limits PVYO enabling PVYNTN and PVYN-Wi to outcompete. We also found that replication and cell-to-cell movement of these PVY strains in tubers at 4C was similar to levels at ambient temperature.

The present paper examines the impact of herding behavior on market capitalization in the Egyptian stock market before and after the disclosure of environmental-social-governance scores (ESG Score Index). This line of thought and research contributes to the literature on the interrelationships between ESG factors and market dynamics. Consequently, the evolving landscape of how to sustain investments in emerging markets like Egypt can be enlightened. Two main hypotheses were tested in the paper. The first hypothesis is on the expected significant impact of herding behaviour on market capitalization. The second hypothesis is on the expected positive impact of ESG on the relationship between herding behaviour and market capitalization. Panel data analysis using data extracted from financial statements of 22 Egyptian EGX 30 companies, over the period 2018-2023 will be used. This is to control for the cross-section and time characteristics of the research sample. The empirical findings reveal a positive significant effect of herding behavior on market capitalization before disclosing ESG scores. Another finding is that after the implementation of mandatory ESG disclosure, the relationship between herding behavior and market capitalization is strengthened. Moreover, it is empirically evident that companies with higher ESG performance attract more investments and higher valuations. The importance of ESG in shaping investment decision-making, enhancing transparency, and market dynamics has important policy implications.

How many different writers authored the huge number of texts attributed to Galen of Pergamum (129~216 AD), medical doctor and philosopher, a giant in the history of medicine? To find out which texts were his and which ones were written by others is known as the “Galenic Question”. We propose a “solution” to it through a multidisciplinary approach based: (a) on historical research and (b) on a mathematical analysis of the Greek texts. The historical approach has considered historical independent sources and anachronisms. The mathematical approach has been based on a mathematical theory concerning deep–language variables, rarely consciously controlled by any author, therefore capable of giving indications on similarity of texts, with little or no bias. The multidisciplinary approach has convinced us that at least three authors wrote the texts attributed to Galen. The first two very likely were real historical persons: (a) a certain Galen living between the end of the I century BC and the second half of the I century AD; (b) the historical Galen of Pergamum (II–III centuries AD) and (c) several unknown authors hiding under the name Galen, but surely living after Galen of Pergamum’s death.

Advancements in computer vision are rapidly revolutionizing the way traffic agencies gather roadway geometry data, leading to significant savings in both time and money. Utilizing aerial and satellite imagery for data collection proves to be more cost-effective, more accurate, and safer compared to traditional field observations, considering factors such as equipment cost, crew safety, and data collection efficiency. Consequently, there is a pressing need to develop more efficient methodologies for promptly, safely, and economically acquiring roadway geometry data. While image processing has previously been regarded as a time-consuming and error-prone approach for capturing these data, recent developments in computing power and image recognition techniques have opened up new avenues for accurately detecting and mapping various roadway features from a wide range of imagery data sources. This research introduces a novel approach combining image processing with a YOLO-based methodology to detect turning lane pavement markings from high-resolution aerial images, specifically focusing on Florida's public roadways. Upon comparison with ground truth data from Leon County, Florida, the developed model achieved an average accuracy of 87% at a 25% confidence threshold for detected features. Implementation of the model in Leon County identified approximately 3,026 left turn, 1,210 right turn, and 200 center lane features automatically. This methodology holds paramount significance for transportation agencies in facilitating tasks such as identifying deteriorated markings, comparing turning lane positions with other roadway features like crosswalks, and analyzing intersection-related accidents. The extracted roadway geometry data can also be seamlessly integrated with crash and traffic data, providing crucial insights for policymakers and road users.

The dynamic landscape of AI adoption and its impact on employment in Malaysia demands a multifaceted approach to navigate the challenges and harness the opportunities presented. While the government's commitment to fostering AI adoption through initiatives like the National AI Framework and the Malaysia Digital Economy Blueprint is commendable, it is imperative to address concerns regarding job displacement and ensure inclusive growth. This study identifies the pressing research problem of workforce readiness for the AI-driven future, emphasizing the need to explore strategies for reskilling and upskilling affected workers. By employing critical lenses such as Marxist, feminist, and postcolonial perspectives, scholars highlight the power dynamics and societal implications inherent in AI deployment, guiding the development of policies and interventions that prioritize workers' interests and address social inequalities. Moving forward, a comprehensive approach combining policy interventions, educational reforms, and inclusive strategies is essential to maximize the benefits of AI adoption while mitigating its potential risks. Longitudinal studies, interdisciplinary research, and comparative analyses will further advance our understanding and inform evidence-based policymaking in this evolving field. Ultimately, by prioritizing workforce preparedness, social equity, and sustainable development, Malaysia can position itself as a leader in the AI-driven global economy, fostering a resilient, inclusive, and prosperous society for all.

This study evaluated the hip joints of the giant anteater (Myrmecophaga tridactyla) through imaging and macroscopic analyses and proposed a surgical approach for arthrotomy procedures in this species. The study used four samples fixed in 10% formaldehyde and six thawed carcasses. Radiographic and ultrasound examinations and anatomical dissection allowed the proposal of a surgical approach for the hip joint. The radiographic evaluation occurred with frog-legged ventrodorsal and lateral projections, and the ultrasound enabled joint soft tissue assessment. The articular elements represented similar characteristics to other domestic species. Some anatomical particularities of muscle groups were the intermuscular septum between the tensor fasciae latae and superficial gluteus muscles at the level of the greater trochanter of the femur, which provides lateral access to the femoral head and neck more conservatively. In conclusion, the anatomical particularities of radiographic positioning, the clinical applications of joint ultrasound, and the arrangement of muscle groups must be considered when evaluating and surgically accessing the hip joint of the giant anteater.

CuAl8Fe5Ni4Zn4Sn1 (OF 2238) is a new lead-free copper alloy for plain bearing applications that was first officially presented in a scientific journal in 2020. Soon after its invention, the use of the alloy for connecting rod bushings in heavy duty internal combustion engines was promoted and validated with customers. The aim of this article is to describe the material properties of the new alloy in more detail than previously and explain how the advantageous properties of CuAl8Fe5Ni4Zn4Sn1 are generated. At the beginning of the article, the general development trends in the field of copper alloys for sliding applications are presented. This is followed by a presentation of the latest research results about CuAl8Fe5Ni4Zn4Sn, before concluding with a brief summary and future outlook, emphasizing on the fact that recent trends in copper-based sliding applications show great additional potential for further material developments.

We propose a novel moving median estimator specifically designed for online detection of threshold crossings in multi-channel signals, such as extracellular neural recordings. This estimator offers two key advantages: a reduced sensitivity to outliers and the elimination of memory requirements for storing arrival times. Furthermore, its design facilitates parallel implementation on FPGAs, making it ideal for real-time processing of multi-channel recordings.

Procurement plays a central and defining role in the efficiency of supply chains. In recent years, the understanding and practice of procurement management have changed significantly due to increasing emphasis on and demand for agility and sustainability within supply chain management systems. Meanwhile, traditional supply chain systems, characterized by siloed processes, limited visibility, and inefficiencies due to manual interventions, can no longer cope with the current dynamic market conditions. Besides, the increasing requirements of sustainability, ethical sourcing, and environmental impact have intensified, making more responsible, transparent, and traceable procurement practices unnegotiable requirements for modern systems. In this paper, we examine the potential of emerging technologies and innovations such as blockchain, artificial intelligence, and the Internet of Things (IoT) in filling these gaps within the supply chain systems of enterprises in the US. The study employs a comprehensive review of relevant literature and case studies to discover and provide insights on how these technologies can improve procurement processes, optimize resource allocation and utilization, and improve sustainability. The findings of this study highlight the need for stakeholders to embrace technological advancements to effectively navigate the dynamic landscape of supply chain management.

Based on the goals of "high reliability, high frequency, rapid launch, and low cost" for space launch site, and drawing inspiration from the design principles of SpaceX's Starship launch test facility, an integrated dual-sided deflector system for convective cooling and thermal protection is presented. The interaction process between the gas jet and liquid water jet and its effect on the flow field environment are thoroughly studied using numerical calculation methods. Furthermore, Regarding the phase-change heat transfer issue in a compressible gas-liquid two-phase flow and the varying distribution of different bubble shapes and sizes at the gas-liquid interface, a modified Lee model is derived. The rationality and accuracy of the phase-change mass-transfer coefficient values can be improved by adjusting the equivalent diameter and shape factor of the bubbles. The research results demonstrate that compared to the classical Lee model, the modified Lee model can achieve a higher numerical accuracy in predicting the heat and mass transfer processes in gas-liquid two-phase flows. Through comparative analysis with traditional dual-sided deflector and conventional cooling system, the integrated dual-sided deflector system for convective cooling and thermal protection exhibits significant performance advantages in gas flow regulation, flow field environment improvement and erosion protection in the near-ground region of the launch site. Particularly, regarding the thermal environment of the dual-sided deflector, it not only achieves effective flow deflection, but also mitigates the degree of erosion caused by the gas jet on the deflector. This conclusion can provide theoretical references for the thermal protection design of commercial launch vehicle system at space launch site.

The abstract summarizes the transformative impact of artificial intelligence (AI) on employment in Malaysia, highlighting the need for comprehensive strategies to ensure inclusivity and equitable access to AI-driven opportunities and digital skills training. It addresses the research problem of potential inequalities and marginalization among vulnerable populations due to uneven distribution of AI-related employment opportunities and training. The research objectives focus on developing decentralized strategies tailored to rural communities and marginalized groups, alongside evaluating policy interventions for equitable access. The literature review provides theoretical frameworks emphasizing skill development, understanding structural shifts, fostering inclusive innovation, and promoting collaborative governance. Future research directions include implementing and evaluating strategies in real-world contexts, exploring technological solutions, conducting qualitative research on individuals' experiences, and adopting interdisciplinary approaches. Overall, a multidimensional approach combining theoretical insights, empirical evidence, and stakeholder engagement is essential for developing inclusive and sustainable solutions to harness AI's potential for the benefit of all Malaysians.

We estimated the risk of blood clots after COVID-19 vaccination accounting for the roles of vaccination in reducing the infection rate, and indirectly lowering the risk of blood clots caused by infection. A self-controlled case series method was used to examine the association between blood clots and COVID-19 vaccination. To deal with the bias due to under-reported infection among non-hospitalized subjects, a case-control study was used to compare the risk of blood clots in infected subjects to control subjects who were hospitalized due to physical injury. We found increased risks of blood clots after vaccination (incidence rate ratio is 1.13, 95% confidence interval (CI): [1.03, 1.24] after the first dose and 1.23, 95% CI: [1.13,1.34] after the second dose). Furthermore, vaccination attenuated the increased risk of blood clots associated with infection (odds ratio (OR) = 2.16, 95% CI: [1.93, 2.42] in unvaccinated versus OR=1.46, 95% CI: [1.25, 1.70] in vaccinated). A causal model was used to explain and weigh up possible risk factors for blood clots after COVID-19 vaccination. After accounting for vaccine efficacy against infection and the protection against infection-associated blood clots, receiving the COVID-19 vaccines decreases the risk of blood clots, especially during high infection rate period.

Public perception contrasts scientific findings on the depression-related effects of cannabis. However, earlier studies were performed when cannabis was predominantly illegal, its production was mostly uncontrolled, and the idea of medical cannabis was incipient only. We hypothesized that recent changes in attitudes and legislations may have favorably affected research. In addition, publication bias against cannabis may have also decreased. To investigate this hypothesis, we conducted a systematic review of research studies published over the last three years. We found 156 relevant studies. In most cross-sectional studies, depression was higher in those who consumed cannabis than in those who did not. An increase in cannabis consumption was typically followed by an increase in depression, whereas withdrawal from cannabis ameliorated depression in most cases. Albeit medical cannabis reduced depression in most studies, none of these were placebo controlled. In clinical studies published in the same period, placebo also ameliorated depression and in addition, the average effect size of placebo was larger than the average effect size of medical cannabis. We also investigated the plausibility of the antidepressant effects of cannabis by reviewing molecular and pharmacological studies. Taken together, the reviewed findings do not support the antidepressant effects of herbal cannabis.

Plant responses to different light and water availability are variable among species and their re-spective phenotypic plasticity, and the combination between these two abiotic factors can alleviate or intensify stressful effects. This study aimed to evaluate the impacts of exposure time of Cedrela fissilis Vell. seedlings to different water and light availability and the interaction of these factors. Seedlings were submitted to combinations of three shading levels – SH (0, 30 and 70%) and three water regimes based on the water holding capacity (WHC) in the substrate, constituting nine cul-tivation conditions: T1 – 0% SH + 40% WHC; T2 – 0% SH + 70% WHC; T3 – 0% SH + 100% WHC; T4 – 30% SH + 40% WHC; T5 – 30% SH + 70% WHC; T6 – 30% SH and 100% WHC; T7 – 70% SH + 40% WHC; T8 – 70% SH +70% WHC; T9 – 70% SH + 100% WHC. C. fissilis seedlings respond to water deficit, here represented by 40% WHC, regardless of exposure time, and when cultivated in full sun, the stressful effects were enhanced, acting in a synergistic manner. The condition that provided better gas exchange performance and greater total dry mass accumulation for C. fissilis seedlings was 30% shading combined with 100% WHC. C. fissilis seedlings have physiological plasticity and resilience to survive under different water and light conditions.

In this paper we present the exploration of indoor positioning technologies for UAVs, and navigation techniques for path planning and obstacle avoidance. The objective is to perform warehouse inventory tasks using a drone to search for barcodes or markers to identify the objects. For the indoor positioning techniques, we employ Visual-Inertial Odometry (VIO), Ultra-Wideband (UWB), AprilTag fiducial markers, and Simultaneous Localization and Mapping (SLAM). These algorithms encompass global positioning, local positioning, and pre-mapping positioning, comparing the merits and drawbacks of various techniques and trajectories. In UAV navigation, we combine SLAM-based RTAB-Map indoor mapping and navigation path planning of the ROS for indoor environments. This system enables precise drone positioning indoors and utilizes global and local path planners to generate flight paths that avoid dynamic, static, unknown, and known obstacles, demonstrating high practicality and feasibility. To achieve the warehouse inventory inspection, a reinforcement learning approach is proposed to recognize the markers by adjusting the UAV's viewpoint. We address several main problems in inventory management, including efficiently planning paths while ensuring a certain level of detection rate. Two reinforcement learning techniques, AC (Actor-Critic) and PPO (Proximal Policy Optimization), are implemented based on AprilTag identification. Testing is performed in both simulated and real-world environments, and the effectiveness of the proposed method is validated.Code is available at https://github.com/kellen080/Navigation and https://github.com/kellen080/Indoor\_Positioning.

The advent of social commerce (SC) has transformed the landscape of online consumer behavior, emphasizing the significance of customer-to-customer relations in shaping sustainable relation-ships with customers. This research investigated the intricate relationships between social com-merce dimensions, particularly suggestions and recommendations, forums and communities, and ratings and reviews, and their influence on customer-to-customer value co-creation (C2CVCC) and sustainable customer relationships (SCRs). A questionnaire was designed and administered to 635 respondents. We examined the psychometric properties of the measurements and subse-quently applied Partial Least Squares as a Structural Equation Modeling method (PLS-SEM) for hypothesis testing. The findings reveal that the dimensions of SC significantly impact C2CVCC, with ratings and reviews playing a pivotal role. Furthermore, C2CVCC emerges as a substantial mediator in the path between SC and SCRs. The empirical analysis showcases strong support for the proposed model, with robust path coefficients (β) and p-values confirming direct and indirect effects. These findings offer valuable insights for businesses seeking to leverage SC and customer interactions to enhance SCRs in the digital era. Understanding the dynamics of C2CVCC within the context of SC has become essential for marketers and businesses aiming to thrive in today's competitive online marketplace.

Per- and polyfluoroalkyl substances (PFAS) are arguably the most common water contaminants in the world today. While several research experiments have been done to understand and remove PFAS from the environment, there is still a lot of unknown. Little has been known about the use of Machine learning (ML) to understand PFAS. This work hence reviews some leading ML approaches and applications in PFAS studies in the distribution, transport, removal, and occurrence predictions of PFAS. Several evaluation matrices were examined and used to perform this function. There are still a lot of areas whereby ML can be used to improve our PFAS knowledge base, some of these were briefly stated in this review.

The complex dynamics of the neocortex, the outermost layer of the brain, have been a subject of intense research in neuroscience. Recent studies have suggested that magnetic fields generated by neuronal activity may play a significant role in neocortical dynamics. This paper presents a simplified mathematical model that explores the hypothesized interactions between magnetic dynamos, nondissipative systems, Hamiltonian equations, and the Lorenz force in the context of neocortical dynamics. The proposed model is based on a set of coupled Hamiltonian equations inspired by the Lorenz system, a well-known chaotic dynamical system. The generalized coordinates in the model represent the magnetic field components, while the generalized momenta are related to the electric field components or other relevant quantities. The Hamiltonian equations describe the conservative dynamics of the system, and the coupling terms in the equations are interpreted as representing the interactions between the magnetic and electric field components, analogous to the Lorenz force in electromagnetism. The model is implemented using Python, and the Hamiltonian equations are numerically solved using the odeint function from the scipy.integrate module. The resulting dynamics of the magnetic field components are visualized using matplotlib. While the model is highly simplified and does not capture the full complexity of neocortical dynamics, it serves as a starting point for investigating the potential role of magnetic dynamos and Lorenz force interactions in the brain. The paper discusses the limitations of the current model and highlights the need for further refinements, such as incorporating more realistic biological constraints, considering energy dissipation and compensation mechanisms, and validating the model against experimental data. Future work should focus on developing a more comprehensive and biologically plausible model that integrates the latest findings from neuroscience, physics, and computational modeling. By presenting this simplified Hamiltonian model, the paper aims to stimulate further research and discussion on the potential significance of magnetic dynamos and Lorenz force interactions in neocortical dynamics. The model provides a framework for exploring these hypothesized mechanisms and may guide future experimental and theoretical investigations in this emerging field of neuroscience

Abstract: Development of the fast neutron radiography with higher penetration capability in Non-Destructive Testing (NDT) techniques is rapidly. The detection efficiency and the imaging spatial resolution are the main problem of the radiography detector for many fast neutron imaging systems. In this paper, a detector composed of pixelated EJ200 scintillator array，an 16 × 16 silicon-photomultipliers (SiPM) array, and a capacitive multiplexing network readout electronics is designed. Using Monte-Carlo simulations，the main parameters of the detector was optimization. Then the detector prototype was fabricated and tested at a 14 MeV D-T neutron source. The preliminary test results showed that the prototype has spatial resolution of 1.26 mm. Using pixelated scintillator structure，the conflict between spatial resolution and detect efficiency could improved. Moreover, SiPMs offer a flexibility for the expansion of application field of the imaging system due to their excellent photon detection performance, relatively low price and joint possibility for large area.

Synthetic materials such as Carbon, Kevlar, and Glass fibers are extensively utilized in various industries due to their superior characteristics including high stiffness, great strength, low den-sity, and high wear resistance, these advantages contributed to making them widespread in ap-plications like; aerospace, automobile, civil and electronics. This research is carried out to enhance the creep compliance of epoxy composite material by considering two types of fibers as reinforcement. A composite material is produced by combining two fibers, Kevlar fiber mixed with sika epoxy resin, along with Carbon fiber also mixed with sika epoxy resin using a Hand-Layup process. Experiments and numerical modeling are examined to offer a comprehensive understanding creep behavior of epoxy composite material in different weight ratios. Burger and Prony models are used to represent stress relaxation and creep strain of Visco-elastic material. According to the results, sika epoxy resin reinforced with Kevlar and Carbon fibers exhibits enhancement in the mechanical properties compared with pure epoxy. The use of Kev-lar/Sika epoxy composite results in higher creep compliance and modulus of elasticity compared with Carbon/Sika epoxy composite.

This study explores the use of remote ultrasound vibration to enhance welding strength. It examines the effects of 20 kHz, and 40 kHz High Power Ultrasound Transducers (HPUT) in contact and contactless modes during ultrasonic assistance laser welding. Employing shear tests and microscopy for assessment, the research evaluates ultrasound's impact on welding strength and identifies the optimal transducer. Theoretical and numerical analyses investigate vibration transmission into the welding area, particularly examining the vibration distribution and cavitation initiation within the molten pool area. Results indicate that ultrasound-assisted welding increases pull test performance, including the resistance force and strain, and improves microscopic structural integrity. Numerical simulations suggest that narrow-band vibration intensifies pressure in specific welding zones. Contactless ultrasound application also shows enhanced welding quality, offering a promising alternative to current methods. This work contributes to electric car technology by suggesting improvements in welding techniques for power battery systems.