This study introduces the Data-Driven Personalized Learning Model (DDPLM), a sophisticated framework designed to enhance foreign language acquisition through the integration of big data analytics. Implemented within the educational platforms Edmodo and Duolingo, DDPLM utilizes real-time data processing to tailor learning paths and content dynamically to individual learner needs. Our findings indicate significant improvements in language learning efficiency, engagement, and retention. The model's adaptability across different digital environments showcases its potential scalability and effectiveness in various educational contexts. Additionally, the research addresses the critical role of personalized feedback and adaptive challenges in maintaining learner motivation and promoting deeper linguistic comprehension. The outcomes suggest that DDPLM significantly transforms traditional language education, making it more personalized, efficient, and aligned with individual learning preferences.

Vitamin D is crucial for athletes' health and performance. Although the exact vitamin D requirements for athletes have not been established, maintaining 25(OH)D levels of at least 40 ng/ml is considered beneficial. This study aimed to determine whether an individual loading dose formula for vitamin D supplementation is suitable to meet a target value of 40 ng/ml and is more effective than standardized supplementation. In a 10-week supplementation study during the winter months in Germany, 90 athletes with insufficient vitamin D levels (25(OH)D<30ng/ml) were randomly assigned to receive either a universal dose of 2000 IU/day of vitamin D or a loading dose of 4000 IU/day, followed by a maintenance dose of 1000 IU/day. Total 25(OH)D concentration was measured from dried blood spots at three time points: at baseline, at the computed date of 40ng/ml, and after the 10-week period. Additionally, a vitamin D-specific questionnaire was issued. On the day when 25(OH)D blood concentrations of 40 ng/ml were calculated to prevail, the individualized group had a significantly higher 25(OH)D level than the standardized group (41.1+-10.9 ng/ml vs. 32.5+-6.4 ng/ml, p<0.001). This study demonstrated that the examined formula is suitable for athletes to achieve a 25(OH)D concentration of 40 ng/ml. This indicates that a personalized approach is more effective than a one-size-fits-all approach in restoring adequate vitamin D levels in athletes.

In recent years, there has been an increasing demand for personalized experiences in various domains, including the cultural and educational sectors. Museums, as custodians of art, history, and scientific knowledge, are seeking innovative ways to engage their visitors and provide tailored content that enhances their understanding and appreciation of the exhibits. This article presents ExhibitXplorer, a distributed architecture service that leverages geofencing, artificial intelligence, and microservices to enable personalized content delivery in museums. By combining implicit and explicit segmentation of museum visitors and utilizing the GPT API for content generation, ExhibitXplorer offers a dynamic experience to different visitor segments, including researchers, students, casual visitors, and children. The system utilizes push notifications triggered by visitor location changes, allowing seamless delivery of personalized information both indoors and outdoors. Tests were conducted to evaluate the user experience of visitors to an outdoor ethnographic museum. The results showed that 55% of the test participants were satisfied and 45% very satisfied with the way personalized content was delivered.

Malaria remains a primary public health challenge in Africa, and there is growing interest in leveraging artificial intelligence (AI) to raise malaria interventions. This research examines the possible influence, challenges, and recommendations for implementing AI-based personalized malaria interventions in Africa. AI offers several opportunities in malaria management, including early detection and prediction of outbreaks, improved diagnosis, personalized interventions, optimal treatment recommendations, surveillance and response, resource optimization, and research innovation. However, the implementation of AI in malaria interventions faces various challenges. These include data availability and quality, infrastructure and resource constraints, contextual relevance and generalizability, ethical and privacy considerations, integration into healthcare workflows, and the need to build trust and acceptance among stakeholders. To address these challenges, it is recommended to strengthen data infrastructure, build local capacity in AI technologies, contextualize AI models to local settings, address ethical considerations, establish monitoring and evaluation frameworks, promote collaboration and knowledge sharing, and secure sustainable funding and long-term commitment. By considering these recommendations, stakeholders can work towards implementing AI-based personalized malaria interventions in Africa that can contribute to improving malaria control outcomes, reducing the weight of the disease, and advancing public health in the region.

The most aggressive primary malignant brain tumor in adults is glioblastoma (GBM), which has poor overall survival (OS). There is a high relapse rate among patients with GBM despite maxi-mally safe surgery, radiation therapy, temozolomide (TMZ), and aggressive treatment. Hence, there is an urgent and unmet clinical need for new approaches to managing GBM. The current study identified modules (MYC, EGFR, PIK3CA, SUZ12, and SPRK2) involved in GBM disease through the NeDRex plugin. Furthermore, hub genes were identified in a comprehensive interaction network containing 7,560 proteins related to GBM disease and 3,860 proteins associated with signaling pathways involved in GBM. By integrating the results of the aforementioned analyses and performing centrality analysis again, eleven key genes involved in GBM disease were identi-fied. ProteomicsDB or Gliovis databases were used for determining the gene expression in normal or tumor brain tissue. The NetworkAnalyst and the mGWAS-Explorer tools identified miRNAs, SNPs, and metabolites associated with these 11 genes. Moreover, a literature review of recent studies revealed other lists of metabolites related to GBM disease. The enrichment analysis of iden-tified genes, miRNAs, and metabolites associated with GBM disease was done using ExpressAna-lyst, miEAA, and MetaboAnalyst tools. Further investigation of metabolite roles in GBM was done through the pathway, joint pathway, and network analyses. The results of this study identified 11 genes (UBC, HDAC1, CTNNB1, TRIM28, CSNK2A1, RBBP4, TP53, APP, DAB1, PINK1, and RELN), five miRNAs (hsa-mir-221-3p, hsa-mir-30a-5p, hsa-mir-15a-5p, hsa-mir-130a-3p, hsa-let-7b-5p), six metabolites (HDL, N6-acetyl-L-lysine, cholesterol, formate, N, N-dimethylglycine/xylose and X2. piperidinone) and 15 distinct signaling pathways that play an indispensable role in the GBM disease development. To establish early diagnostic methods and plan personalized GBM treatment strategies, the identified top genes-miRNAs and metabolite signatures can be targeted.

Cognitive rehabilitation is useful for many after traumatic brain injury (TBI), but we lack critical knowledge about which patients benefit the most from different approaches. Advanced neuroimaging techniques have provided important insight into brain pathology and systems plasticity after TBI and have potential to inform new practices in cognitive rehabilitation. In this study, we aimed to identify candidate structural brain measures with relevance for rehabilitation of cognitive control (executive) function after TBI. Twenty-eight patients (9 female, mean age 40.5 (SD = 13.04) years) with moderate/severe TBI (>21 months since injury) that participated in a randomized controlled cognitive rehabilitation trial (NCT02692352) were included in the analyses. Regional brain volume was extracted from T1-weighted MRI scans before treatment using tensor-based morphometry. Both positive and negative associations between treatment outcome (everyday cognitive control function) and regional brain volume were observed. The most robust structural brain measures with relevance for improvement in function were observed in midline fronto-parietal regions, including the anterior and posterior cingulate cortices. The study pro-vides proof of concept and valuable insight for planning future studies focusing on neuroimaging in cognitive rehabilitation after TBI.

Chronic and non-healing wounds demand personalized and more effective therapies for treating complications and improve patient adherence. This work aims to develop a suitable chitosan-based scaffold to provide 24 hours controlled release of DKT, by taking advantage of chitosan’s thermo-responsive behavior as well as local hyperthermia in wounds. Three formulation prototypes were developed using chitosan (F1), 2:1 chitosan: PVA (F2), and 1:1 chitosan:gelatin (F3). Compatibility tests were done by DSC, TG, and IR spectroscopy. SEM was employed to examine the morphology of the surface and inner layers from the scaffolds. In vitro release studies were performed at 32 °C and 38 °C to evaluate the release profiles, which were later adjusted to different kinetic models for the best formulation. F3 showed the most controlled release of DKT at 32 °C for 24 hours (77.75 ± 2.72 %), and reduced the burst release in the initial 6 hours (40.18 ± 1.00 %), while at 38 °C the release reached 88.52 ± 2.07 % at 12 hours. The release profile for this formulation fits with Hixson-Crowell and Korsmeyer-Peppas kinetic models at both temperatures. Therefore, the developed chitosan/gelatin thermo-responsive scaffold provides a suitable system for wound healing with a controlled release of DKT for 24 hour-use, which can overcome adherence issues and wound complications.

Worldwide, over 2.2 million people are suffered from multiple sclerosis (MS), a multifactorial demyelinating disease of the central nervous system. MS is characterized by a wide range of motor, autonomic, and psychobehavioral symptoms including depression, anxiety, and dementia. The blood, cerebrospinal fluid, and postmortem brain samples of MS patients evidenced the disturbance of reduction-oxidation (redox) homeostasis such as the alterations of oxidative and antioxidative enzyme activities and the presence of degradation products. This review article discussed the components of redox homeostasis including reactive chemical species, oxidative enzymes, antioxidative enzymes, and degradation products. The reactive chemical species covered frequently discussed reactive oxygen/nitrogen species, infrequently featured reactive chemicals such as sulfur, carbonyl, halogen, selenium, and nucleophilic species that potentially act as reductive as well as pro-oxidative stressors. The antioxidative enzyme systems covered the nuclear factor erythroid-2-related factor 2 (NRF2)-Kelch-like ECH-associated protein 1 (KEAP1) signaling pathway. The NRF2 and other transcriptional factors potentially become a biomarker sensitive to the initial phase of oxidative stress. Altered components of the redox homeostasis in MS were discussed in search of a diagnostic, prognostic, predictive, and/or therapeutic biomarker. Finally, monitoring a battery of reactive chemical species, oxidative enzymes, antioxidative enzymes and degradation products helps evaluate the redox status of MS patients to expedite building personalized treatment plans for the sake of better quality of life.

In the context of food packaging design, customization enhances the value of a product by meeting the needs of the consumer. Personalization is also linked to adaptation. This makes it possible to improve the properties of the packaging from various points of view: functional, aesthetic, economic and ecological. Currently the functional and formal properties of packaging are not investigated among themselves, however the study of both properties are the basis for creating a new concept of personalized and sustainable product. In accordance with this approach, the conceptual design procedure of packaging with personalized and adapted geometries based on the digitization of fresh food is proposed in this work. This study is based on the application of advanced technologies for the design and development of food packaging, in this case apples, in order to improve the quality of the packaging. The results obtained show that it is possible to use advanced technologies in the early stages of product design in order to obtain competitive products adapted to new emerging needs.

Coordinated sets of extremely numerous digital data, on a given social or economic event, are treated by Artificial Intelligence tools to obtain reasonably accurate, valuable predictions. The same approach, applied to biomedical issues, as how to choose the right drug to completely cure a given cancer patient, does not reach satisfactory results. It is the “organized biological complexity”, which requires a different systems approach, to integrate, in an Augmented Intelligence strategy, statistical computations of digital data, network construction of “omics” findings, well-designed mathematical models and new experiments in an iterative pathway to reconstruct the “logic” beneath the “organized complexity”, as shown here for Systems Metabolomics of cancer. On this basis new diagnostic approaches, able to identify precision drug treatments, as well as new discovery strategy for more effective anti-cancer drugs are described.

The rare abscopal effect during radiotherapy is thought to be caused by the release of immune-stimulated damage-associated molecular patterns, such as high mobility group box-1 protein (HMGB1), from cancer cells. Although external irradiation of cancer cells increases HMGB1 release, it is not clear if HMGB1 is released from cells after administering 131I-labeled m-iodobenzylguanidine (131I-MIBG) as an internal targeted radiotherapeutic agent. This study aimed to determine if HMGB1 is released from human-derived cancer and normal cells after administering 131I-MIBG. Methods: Extracellular lactate dehydrogenase (LDH) and HMGB1 released from H441 (human-derived lung adenocarcinoma cell line) and HaCaT (human keratinocyte cell line) 1 day after 2- and 10-Gy X-ray irradiation were measured. Accumulations of 131I-MIBG in SH-SY5Y (human-derived neuroblastoma cell line) and HaCaT were measured 60 min after administering 131I-MIBG (0.37, 1.85, 3.7 MBq/well). Extracellular LDH and HMGB1 released from SH-SY5Y and HaCaT 1 day after administering 131I-MIBG were also measured. Results: The extracellular LDH and HMGB1 released from H441 after 10-Gy X-ray irradiation were significantly increased. However, the extracellular LDH and HMGB1 released from HaCaT after 2-Gy and 10-Gy X-ray irradiation were not increased. After administering 1.85 MBq and 3.7 MBq 131I-MIBG, the extracellular LDH and HMGB1 released from SH-SY5Y were both significantly increased, but only the extracellular LDH released from HaCaT was significantly increased. Conclusions: HMGB1 was released from neuroblastomas but not from normal cells after 131I-MIBG administration, suggesting that a combination of 131I-MIBG and immunotherapy may be feasible.

Breast cancer is the most commonly diagnosed cancer in women in both developed and developing countries. Due to the increasing alarms in the detection of cases every year, it is considered a priority to evaluate new molecules as potential antitumoral agents. Among these molecules, cationic peptides have emerged as promising therapeutic agents with a membrane-based mechanism of action very hard to counteract by the cancer cells. This biophysical study seeks to offer preliminary insights into how NA-CATH:ATRA-1-ATRA-1, a synthetic cationic peptide derived of the peptide NA-CATH, isolated from the species Natra aja or Chinese cobra, is a potential antitumoral compound at the membrane level on breast cancer cell lines. The interaction of the NA-CATH-ATRA-1-ATRA-1 with two lipid systems representative of tumoral and non-tumoral membranes was followed by differential scanning calorimetry and Fourier-transform infrared spectroscopy. The results showed a strong interaction of NA-CATH-ATRA-1-ATRA-1 with the lipids present in the eukaryotic membranes, especially phosphatidylserine, suggesting a mechanism based on the electrostatic interaction of the peptide with the anionic lipids of the tumoral cancer membranes. The biophysical studies are essential to understand the mechanism of action of a potential pharmaceutics.

Data privacy is a critical concern in health informatics, where the management of sensitive patient information requires robust and secure database systems. This study aims to explore the data privacy challenges faced in health informatics and conduct a comparative analysis of popular Database Management Systems (DBMS), including MySQL, MongoDB, PostgreSQL, and Oracle, with a focus on their effectiveness in safeguarding patient data. Through a review of existing literature, case studies, and interviews with database administrators, the research identifies common privacy threats such as data breaches and unauthorized access. It examines the security features of each DBMS, such as encryption methods, access controls, and user authentication mechanisms. The findings reveal variations in the privacy protection capabilities of different DBMS, highlighting the trade-offs between security, performance, and usability. The study provides recommendations for healthcare organizations in selecting a DBMS that balances privacy with operational needs and offers insights for policymakers to improve regulatory frameworks in health data security. This research contributes to the ongoing discourse on enhancing data privacy in health informatics and suggests directions for future studies to integrate emerging technologies for more secure health data management.

Diabetic kidney disease (DKD) is regarded as a silent assassin due to its delayed signs. It is a progressive illness that can appear in various ways, from mild to severe. The severity of DKD must be determined in order to make educated treatment decisions and understand the hazards that the patient may encounter. DKD is one of the primary causes for death and morbidity among noncommunicable illnesses, affecting 10% to 15% of the global population. Timely prediction of DKD is expected to improve patients' health and reduce mortality. This study aims to predict DKD using machine learning models like Decision Trees, Random Forest, Logistic Regression, Bagging Tree Model and Support Vector Machine, to help in timely detection and cure of this deadly disease. Clinical data required for model training were taken from Kaggle's public repository and additional samples of 50 individuals were collected from local hospital, Coimbatore, Tamil Nadu. Meta-heuristic algorithms based on Swarm Intelligence, such as Particle Swarm Optimization, Ant Colony Optimization, and Firefly Optimization, were employed to optimize the selected models. The main aim of this study is to compare the predictions of different models and identify models that best agree with the given scenario.

The main objective of the present study is to demonstrate the possibility of actively influencing the position of the bow shock wave and the main parameters of supersonic flow over a blunt body by organizing a gas discharge near the front surface, in the region between the body and the bow shock wave. The research is carried out using both experimental and numerical methods. The working gas was xenon. It is shown that the steady bow shock wave stand-off distance along with the current and power of the discharge, is associated with the change in the adiabatic index of the plasma created by the discharge, which, in turn, is determined by the plasma parameters, such as the degrees of nonequilibrium and the degree of ionization. It is shown that the adiabatic index with the power supplied to the impact zone in the range of 30-120 kW can both increase and de-crease in the range of 1.25-1.288. The study of the discharge created plasma zone was conducted and the correspondence between the discharge current and power, and the average parameters in the plasma zone created by the discharge is presented. A good agreement between the numerical and experimental data was shown. The results may be useful in developing control systems for high-speed civil aircrafts.

Human immunodeficiency virus (HIV) and malaria, caused by infection with Plasmodium spp., are endemic in similar geographical locations. As a result, there is high potential for HIV/Plasmodium co-infection, which increases the pathology of both diseases. However, the immunological mechanisms underlying the exacerbated disease pathology observed in co-infected individuals are poorly understood. Here, we used the rhesus macaque (RM) model to characterize the immunopathogenic impact of Plasmodium fragile co-infection during antiretroviral therapy (ART)-treated simian immunodeficiency virus (SIV)-infection. We observed that P. fragile co-infection resulted in parasitemia and anemia, as well as persistently detectable viral loads (VL) and decreased absolute CD4+ T-cell counts despite daily ART treatment. Notably, P. fragile co-infection was associated with increased levels of inflammatory cytokines linked with neutrophil function, including monocyte chemoattractant protein 1 (MCP-1). P. fragile co-infection was associated with increased levels of neutrophil elastase, a plasma marker of neutrophil extracellular trap (NET) formation, but significant decreases in markers of neutrophil degranulation, potentially indicating a shift in neutrophil functionality during co-infection. Finally, we characterized levels of plasma markers of gastrointestinal (GI) barrier permeability and microbial translocation and observed significant correlations between indicators of GI dysfunction, clinical markers of SIV and Plasmodium infection, and neutrophil frequency and function. Taken together, these data indicate that neutrophil-driven inflammation and GI dysfunction may underlie heightened SIV/P. fragile co-infection pathogenesis.

Opuntia ficus-indica has always interacted with many phytophagous insects at its center of origin; two of them are Dactylopius coccus and D. opuntiae. D. coccus, or true cochineal, is produced to extract carminic acid, and D. opuntiae or wild cochineal is a key invasive pest of O. ficus-indica in more than 20 countries around the world. Despite the economic and environmental relevance of this cactus and, D. opuntiae and D. coccus, there are few studies that have explored volatile organic compounds (VOCs) derived from the plant-insect interaction. The aim of this work was to determine VOCs of D. coccus and D. opuntiae feeding on cultivars suitable for their development and to identify different VOCs in cladodes infested by each Dactylopius species. Volatiles were identified through their essential oils, which were obtained by hydrodistillation. A total of 66 VOCs from both Dactylopius species were identified, and 125 from the Esmeralda and Rojo Pelón cultivars infested by D. coccus and D. opuntiae, respectively, were determined. Differential VOCs production due to infestation by each Dactylopius species was also found. Some changes in methyl salicylate, terpenes such as linalool or the alcohol p-vinylguaiacol were related to Dactylopius feeding on cladodes of their respective cultivars. Changes in these VOCs and their probable role in plant defense mechanisms should receive more attention because this knowledge could improve D. coccus rearing, or to its inclusion in breeding programs for D. opuntiae control in regions where it is a key pest of O. ficus-indica.

In the recent past, the number of invasive species around the world has increased significantly due to increased globalization and climate change. Understanding biological invasions under climate change is crucial for sustainable conservation of biodiversity. The insect pest Pseudococcus viburni (Signoret) can cause damages to plants, resulting in leaf yellowing, leaf defoliation, and reduced plant growth. A serious attack by this insect post can even lead to the entire plant withering and dying, bringing huge economic and ecological losses. Despite these damages, the potential distribution range and management strategies for this insect pest are poorly understood. Based on historical distribution data and environmental factors, the present study predicted the potentially suitable areas for P. viburni spread under different climate change scenarios using MaxEnt (maximum entropy). The results showed that precipitation of the coldest quarter (Bio19), precipitation seasonality (Bio15), and mean temperature of the wettest quarter (Bio8) were the most important environmental factors determining the distribution of P. viburni. Under the current climate conditions, its potential suitable areas are southern China, the whole of Japan, North America (especially the eastern part of the United States), the southwestern part of South America, the Mediterranean coast and most of Europe, the central part of Africa i.e., the south of the Sahara Desert and most of the southern coast of Australia. The total area of habitats suitable for this insect pest is predicted to be increased in the future. In order to prevent P. viburni transmission and spread, there is a need to strengthen the monitoring and quarantine measures against this pest at the Southern ports.

Lignin, and its by-products in the effluent of most agrochemical-based industries like pulp and paper, increase environmental pollution. There is, therefore, an increasing demand to degrade lignin and its derivatives using bacteria-produced ligninolytic enzymes. This study focused on optimizing growth and lignin peroxidase production of ligninolytic potential bacterial strains (E. coli accession no: LR0250096.1 and P. aeruginosa accession no: CP031449.2) for the first time. A submerged fermentation process was used to simultaneously optimize growth and crude lignin peroxidase production using kraft lignin as the substrate. The E. coli and P. aeruginosa were separately cultured under different pH, temperature, lignin (substrate) concentration and incubation periods. It was observed that the enzyme production was growth dependent. The optimum conditions for E. coli were pH 7.5, temperature 30 °C and lignin concentration 1 g/L. For P. aeruginosa the best conditions were pH 6.5, temperature 40 °C and lignin concentration 1 g/L. The enzyme production peaked after 7 days of incubation for both organisms were 21.53 ± 3.11 mg/ml and 18.13 ± 2.1 mg/ml respectively. It is apparent that both E. coli (LR0250096.1) and P. aeruginosa (CP031449.2) are mesophiles bacteria. E. coli function best in alkaline pH while P. aeruginosa prefers a slightly acidic environment. Hence, they are promising candidates in the reduction of lignocellulosic wastes.

The development of good conductivity p-type β-Ga2O3 is critical to realize its devices and applications. The nitrogen-doped p-type β-Ga2O3 films with enhanced conductivity characteristics were prepared through the thermal oxidation of GaN in the N2O atmosphere. Further measurements were performed on the oxidized films at 1000, 1050, and 1100 °C to have insight into the underlying mechanism of the thermally activated transformation process. The room temperature photoluminescence (PL) spectra demonstrated a moderate ultraviolet emission peak at 246 nm, confirming the generation of gallium oxide with a band gap of ~5.0 eV. The normalized X-ray diffraction (XRD), the high-resolution transmission electron microscopy (HRTEM), and the selected area electron diffraction (SAED) patterns were used to confirm the characteristic of polycrystalline and anisotropic growth. Then, the effects of the oxidation temperature on the amount of incorporated nitrogen were analyzed using secondary ion mass spectrometry (SIMS). Moreover, the ionization energy of the acceptor of films oxidized at 1000, 1050, and 1100 °C was calculated and analyzed using the temperature-dependent Hall test results. The results showed that nitrogen doping was the main contributor to p-type electrical properties. The activation energy of the polycrystalline β-Ga2O3 prepared through thermal oxidation of GaN in the N2O atmosphere was estimated to be 147.175 kJ·mol-1 using the Arrhenius plot, which was considerably lower than that of both dry and wet oxidations of GaN in O2 ambient, thus confirming the efficiency of thermal oxidation of GaN in N2O.

The Mediterranean region offers good weather conditions for outdoor pig production (OPP), which is considered more environmentally friendly than intensive indoor production. However, the continuous input of food and pigs' excreta increases the soil organic matter (SOM) and phosphorus (P), increasing the risk of waterbodies eutrophication. This work aimed at evaluating in OPP areas soil P dynamics and the role of SOM on P sorption and P release. The experiment was done for two years, at an area of 2.8 ha with an animal charge of 9 adults ha-1. Georeferenced soil samples were taken at 0.20 m depth, and a soil P sorption experiment was carried out. At the end of the experiment, for the background value, the levels of SOM increased between 85–376%, and Olsen P values ranged between -82–884%. SOM levels above 2% caused a decrease in the binding energy of P sorption according to the linear model b=-15.541SOM+115.20 (p <0.01) as well as a decrease of the soil P sorption capacity Qmax=-41.272SOM+298.37 (p <0.01). To avoid the accumulation of SOM and P preventing hotspots for waterbodies eutrophication, an adequate animal charge together with soil cultivation for pig grazing can be a cost-effective practice.

Antisense technologies consist of the utilization of oligonucleotides or oligonucleotide analogs to interfere with undesirable biological processes, commonly through inhibition of expression of selected genes. This field holds a lot of promise for the treatment of a very diverse group of diseases including viral and bacterial infections, genetic disorders, and cancer. To date, drugs approved for utilization in clinics or in clinical trials target diseases other than bacterial infections. Although several groups and companies are working on different strategies, the application of antisense technologies to prokaryotes still lags with respect to those that target other human diseases. In those cases where the focus is on bacterial pathogens, a subset of the research is dedicated to produce antisense compounds that silence or reduce expression of antibiotic resistance genes. Therefore, these compounds will be adjuvants administered with the antibiotic to which they reduce resistance levels. A varied group of oligonucleotide analogs like phosphorothioate or phosphorodiamidate morpholino residues, as well as peptide nucleic acids, locked nucleic acids and bridge nucleic acids, the latter two in gapmer configuration, have been utilized to reduce resistance levels. The major mechanisms of inhibition include eliciting cleavage of the target mRNA by the host’s RNase H or RNase P, and steric hindrance. The different approaches targeted resistance to β-lactams including carbapenems, aminoglycosides, chloramphenicol, macrolides, and fluoroquinolones.

Adsorption is an effective strategy for the removal of pollutants from the wastewater. Herein, a 2-hydroxyterephthalic acid (HTC) modified hypercrosslinked polymer (HTC-HCP) is successfully synthesized via Friedel-Crafts reactions, and used as an adsorbent for the different types of pollutants including organic contaminants and heavy metal ions from wastewater. Excellent adsorption capacities are observed for amines (aniline, p-methylaniline (p-MA), p-chloroaniline (p-CA), and p-aminobenzoic acid (p-ABA)), phenols (phenol, p-chlorophenol (4-CP) Bisphenol A (BPA), 1-Naphthol (1-NP)), dyes (rhodamine B (RhB) and methyl orange (MO)), and metal ions (Pb2+, Hg2+, and Cd2+). The resulting polymers exhibited excellent adsorption performance towards these pollutants. Especially, the removal rate of aniline is above 95% in the concentration of 2.5 mg/L in 40 min at 25 °C. The interaction mechanism has been investigated, and confirmed by FTIR and the theoretical calculation results. It is due to surface complexation and chemisorption between adsorbent and adsorbate. The polymer exhibits good performance such as high adsorption capacity, high separation efficiency, biodegradable properties, and easy regeneration, suggesting that its potential technological applications for the removal of organic compounds and heavy metal ions from actual industrial effluent.

In these times electricity is big trouble of problem facing by the world. Therefore, there is necessitating for the property basis of energy that is employed for as bio-electricity. Many of the scientists and researchers are trying to find out the sustainable energy generates with the help of plant microbial fuel cell. Plant microbial fuel cell (P-MFCs) could be feasibility technology approach of bio-electricity generation which is mutualism interaction of the plants along with their rhizospheric bacteria. In the present study, Plant-microbial fuel cell was observed in grass e-table evaluated in term of bioelectricity generation from Cynodon dactylon (Dooba Ghas). This e-table was connected with electrode and different condition (physical and chemical) to detect the change in bioelectric potential. It was found that maximum voltage generated among all the conditions was 4.24 ±2V at 15 days by using Cynodon dactylon through P-MFCs. The potential difference generated through P-MFCs was measured using a multimeter. The generation of bioelectricity was observed under different conditions like exposure to light and shade condition measured for voltage was found to be significantly different parameters. The maximum recorded under light and shade conditions were 3.82 ±2 V and 4.25 ±2 V respectively at 15 days of incubation.

Alterations in root morphology and physiology are important strategies in plants to adapt to low-phosphorus (P) environments. Maize genotypes differed in nitrogen (N) efficiency may also respond differently to low P stress. This study aimed to investigate the responses of root morphological and physiological traits of these two maize cultivars to P deficit and how these traits were linked with the acquisition of soil P. Two maize cultivars, XY335 (N efficient) and ZD958 (N inefficient), were cultivated for 40 days in a calcareous loamy soil amended with (high P) or without (low P) P. Functional root traits were used to evaluate the morphological and physiological responses to low P supply. Two separate short-term experiments determined the correlation between P uptake rate and P supply intensity (hydroponic) or root hair length under two P treatments (rhizobox). Low P status significantly simulated biomass allocation to roots, specific root length and exudations of carboxylates, while decreased root diameter and rhizosphere pH in both maize cultivars. Two cultivars had different total root length and root surface area under low P stress: increased in ZD958 and decreased in XY335. Both genotypes developed longer root hair under P deficit. ZD958 (greater biomass and shoot P content) has a greater capability at accessing soil P than XY335. Rhizosphere exudation of citric acid was significantly higher in ZD958 than in XY335, while there was not significant genotypic difference in rhizosphere pH and exudation of malic acid and acid phosphatase activity. ZD958 had higher P uptake rate than XY335 when solution P was between 12.5 and 250 µM. This study identified ZD958 as a P-efficient genotype, which better adapted to low P stress by altering root physiological traits (exudation of citric acid and P uptake rate), rather than root morphological traits (total root length, root surface area, root hair length). Our results highlight the importance of analyzing root morphological and physiological traits to enhance our understanding of the physiological mechanisms of P acquisition.

Parametric quantile regression is illustrated for the one parameter new unit Rayleigh distribution called Median Based Unit Rayleigh distribution (MBUR) distribution. The estimation process using re-parameterized maximum likelihood function is highlighted with real dataset example. The inference and goodness of fit is also explored.

Background/Objectives: Post traumatic growth (PTG) has the potential to draw positive consequences from trauma. Hence, the interest of finding ways to promote PTG. Research has identified an attentional bias towards positive resilience-related words (e.g., “persistence”, “purpose”) in university students who report high PTG after experiencing adversities. Although people can respond to these experiences by showing low PTG, this bias seems to help with their struggle by making purposeful contents more accessible. Therefore, boosting attentional bias towards positive resilience-related words could help people with low PTG. Methods: In this study, the participants were thirty-six university students who had experienced bullying before entering university. Using a Stroop emotional task, they identified the color of resilience and neutral words, either positive or negative, before and after being submitted to transcranial direct current stimulation. Stimulation was targeted at the right temporal area involved in intentionality processing. Results: In the anodal condition, the results support a stimulation effect on the resilience attentional bias that could benefit participants with low PTG. A significant moderation of approach motivation for this effect was also found. Specifically, only when participants had medium or high approach motivation, did stimulation boost the attentional bias in students with low PTG. Conclusions: These results support that tDCS stimulation in this brain area is effective in enhancing resilience attentional bias in low PTG students. However, for this effect to occur it is necessary to have approach motivation, which is motivation related to goals.

This paper presents a comprehensive review of the transformative impact of 3D printing technology on smart cities. As cities face rapid urbanization, resource shortages, and environmental degradation, innovative solutions such as additive manufacturing (AM) offer potential pathways for sustainable urban development. By synthesizing 66 publications from 2015 to 2024, the study examines how 3D printing improves urban infrastructure, enhances sustainability, and fosters community engagement in city planning. Key benefits of 3D printing include reducing construction time and material waste, lowering costs, and enabling the creation of scalable, affordable housing solutions. The paper also addresses emerging areas such as the integration of 3D printing with digital twins (DT), machine learning (ML), and AI to optimize urban infrastructure and predictive maintenance. It highlights the use of smart materials and soft robotics for structural health monitoring (SHM), and repairs. Despite the promising advancements, challenges remain in terms of cost, scalability, and the need for interdisciplinary collaboration among engineers, urban planners, and policymakers. The findings suggest a roadmap for future research and practical applications of 3D printing in smart cities, contributing to the ongoing discourse on sustainable and technologically advanced urban development.

This article explores the use of vegetation indices (VIs) in remote sensing for estimating standing wood volume and volume increments in forest ecosystems. The study investigates the correlations between various VIs and wood volume across different forest stand age classes, focusing on the effectiveness of commonly used indices such as Squared Ratio Simple Red Edge (SQSR) and Red-Edge Ratio Vegetation Index (RERVI), as well as other typical indicators including Enhanced Vegetation Index (EVI), Red-Edge EVI (RE-EVI), and Green Normalized Difference Vegetation Index (GNDVI). Additionally, the analysis considers a pair of indicators based on blue and near-infrared channels, resembling the Blue-normalized Difference Vegetation Index (BNDVI). The research reveals that quadratic and power-law models of SQSR and RERVI demonstrate higher correlations (>0.40) with wood volume, especially in younger forest stands (>0.80). Furthermore, the study highlights the potential of NDII and NDWI indices for estimating volume increments in certain classes of forest stands (0.70). However, correlations vary across different forest stand classes, suggesting the need for further investigation into the reliability of VIs for monitoring wood volume and volume increments in forest ecosystems. Overall, this research contributes to the understanding of the applicability of VIs in remote sensing for forest management and ecosystem monitoring.

Background/Objectives: Periodic fever, aphthous stomatitis, pharyngitis and cervical adenitis syndrome, often referred to as PFAPA syndrome, may enigmatically recur for an undetermined time in the affected children: a potential reason to explain its recurring pattern for an unpredictable period and its self-limitation is currently unknown. We explored the relationship of PFAPA symptom evolution during a variable follow-up with PFAPA disease pictures and breastfeeding for less than 6 months during infancy. Methods: In the Outpatients Clinic of Pediatric Rheumatology of our Institution we have retrospectively screened 150 Italian children with history of PFAPA syndrome during the period 2014-2024, all without any recognized chronic diseases: 88 males, 62 females, mean age at onset of 2.5±1.7 years, age range of 0.3-9.4 years, and mean age at diagnosis of 4.5±2.0 years. Results and Conclusions: After dividing patients into two groups based on either the disappearance or persistence of PFAPA symptoms during a variable median follow-up we found that positive family history of recurring fevers, cervical lymphadenopathy, arthralgia, myalgia, and breastfeeding for less than 6 months were associated with the persistence of the disease over time. Inherited autoinflammatory disorders were excluded on a genetic basis in 16.3% of the cohort. Performing a multivariate analysis adjusted for sex and age we found that only breastfeeding for more than 6 months and a higher level of education in PFAPA patients’ mothers were independently associated with the resolution of the recurring PFAPA symptoms.

This article provides a comprehensive overview of lung cancer from a genetic perspective, emphasizing the molecular pathways involved in its pathogenesis. This review presents the genetic syndromes and key genomic variations, including alterations and instabilities, that contribute to tumor development and progression. Furthermore, advancements in genomic testing, such as liquid biopsy, are explored, highlighting their utility in early diagnosis, prognostic evaluation, and personalized treatment strategies. The role of biomarkers in informing therapeutic decisions and optimizing patient outcomes is also examined, offering insights into their potential to refine clinical interventions. This review aims to enrich the understanding of the genetic landscape of lung cancer, providing insights that may lead to improved diagnostic and therapeutic approaches.

This paper explores the critical role of biomathematics in cancer research, focusing on how mathematical models enhance our understanding of tumor growth and optimize treatment strategies. It begins with an overview of cancer biology, highlighting the complexities of tumor dynamics and the molecular mechanisms driving growth. The paper then delves into various mathematical modeling approaches, including deterministic, stochastic, and agent-based models, illustrating their applications in predicting tumor behavior and treatment responses. Case studies demonstrate the real-world impact of these models on optimizing chemotherapy, radiation therapy, and immunotherapy. Challenges such as data availability, model complexity, and clinical translation are discussed, alongside future directions in the field, including advances in computational power and personalized medicine. Ultimately, this research emphasizes the transformative potential of biomathematics in improving cancer treatment outcomes and underscores the importance of interdisciplinary collaboration in advancing the field.

Cutaneous squamous cell carcinoma (cSCC) is the second most common form of skin cancer, with an increasing global incidence. While most cases are successfully treated with surgical excision, a subset can metastasize, leading to significant morbidity and mortality. Current staging systems based on clinical and histopathological features have shown limitations in accurately predicting metastatic risk. This review examines the role of gene expression profiling (GEP), particularly the 40-gene expression profile (40-GEP) test, in improving risk stratification and management of cSCC. We assess the prognostic value of the 40-GEP test, its integration with current staging systems, and its impact on clinical decision-making. Recent studies suggest that incorporating GEP results with traditional staging methods can enhance the identification of high-risk patients, potentially leading to more personalized treatment strategies. The review also explores the challenges of implementing GEP in routine clinical practice, including cost-effectiveness considerations and the need for standardization. Finally, we discuss the implications for future cSCC management and highlight areas for further research. As molecular profiling techniques continue to evolve, GEP represents a promising approach to optimizing care for cSCC patients, aligning with the growing emphasis on personalized medicine in oncology.

Background Homologous recombination deficiency (HRD) evolved into a major diagnostic marker in high grade ovarian cancer (HGOC) predicting the response to poly (Adenosine diphosphate-ribose) polymerase inhibitors (PARPi) and also platinum-based therapy. In addition to HRD, the type of peritoneal tumor spread influences treatment response and patient survival; miliary type tumor spread has poorer predicted outcome than non-miliary type tumor spread. Methods Known methods for HRD assessment were adapted for our technical requirements and the Predictive-value Integrated Genomic Instability Score (PIGIS) for HRD assessment evolved as an outcome. PIGIS was validated in HGOC samples from 122 patients. We used PIGIS to analyze whether the type of tumor spread correlated with HRD status and whether this had an impact on survival. Results We demonstrated that PIGIS can discriminate HRD positive from HRD negative samples. Tumors with miliary tumor spread are HRD negative and have a very bad prognosis with a progression free survival (PFS) of 15.6 months and an overall survival (OS) of 3.9 years. However, HRD negative non-miliary spreading tumors in our cohort had a much better prognosis (PFS 35.4 months, OS 8.9 years), similar to HRD positive tumors (PFS 34.7 months, OS 8.9 years). Conclusions Our results indicate that in a predominantly PARPi naïve cohort the type of tumor spread might be a better predictor of response to platinum sensitivity than HRD. It remains to be determined, whether this also applies for sensitivity to PARPi.

Background: Post-Covid condition can reduce activity and quality of life, resulting in a significant socioeconomic and health burden. Understanding its impact on patients' health is important for the development of personalized rehabilitation interventions. An independent association between obesity and post-covid condition was found because of complications and comorbidities. Methods: Sixteen patients with obesity and post-COVID symptoms (i.e., dyspnea, pain, poor sleep quality, muscle fatigue) admitted to the Istituto Auxologico Italiano, Piancavallo (VB), Italy, were recruited for a four-week rehabilitation program including conventional exercise therapy, nutritional intervention, psychological support and whole-body cryostimulation (WBC). Results: All participants attended all sessions of the program. Anthropometric data showed statistically significant changes in weight, waist circumference and body mass index. Biochemical analyses showed significant reductions in lipid and inflammatory profiles. There was a significant improvement in physical performance, reduction in pain and improvement in psychological well-being. Conclusion: A multidisciplinary rehabilitation protocol including WBC designed for patients with obesity and post-covid condition is safe and feasible. The overall improvements demonstrate that multidisciplinary rehabilitation was effective on post COVID patients and suggest that the use of WBC is safe and could play a role as a booster in rehabilitation programs.

Robin sequence is a congenital anomaly characterized by a triad of features that include micrognathia, glossoptosis, and airway obstruction. This comprehensive historical review maps the evolution of approaches and appliances for its treatment from the past until current modern possibilities of interdisciplinary combination of modern engineering, medicine, materials, and computer science combined approach with emphasis to design appliances inspired by nature - individual human anatomy. Current biomimetic designs are clinically applied resulting in appliances that are more efficient, comfortable, sustainable, and safer than legacy traditional designs. Review maps the treatment modalities that have been used for patients with Robin sequence over the years. Early management of Robin sequence focused primarily on airway maintenance and feeding support, while current management strategies involve both nonsurgical and surgical interventions and biomimetic biocompatible personalized appliances. The goal of this paper was to provide a review of the evolution of management strategies for patients with Robin sequence that led to the current interdisciplinary biomimetic approaches impacting the future of Robin Sequence treatment with biomimetics at the forefront.

Enophthalmos is a severe complication of primary reconstruction following orbital floor frac-tures, oncological resections or maxillo-facial syndromes. The goal of secondary reconstruction is to re-store symmetrical globe positions to recover function and aesthetics. In this article we pre-sent a method of computer-assisted orbital floor reconstruction using a mirroring technique and a customized titanium or high-density polyethylene mesh, printed using computer aided manufac-turing techniques. This reconstructive protocol involves 4 steps: mirroring of the healthy orbit at the affected site, vir-tual design of a patient specific orbital floor mesh, computer-assisted manufacturing (CAD) of the implant, and surgical insertion of the device. Using a computed tomography data set, the un-injured side of the craniofacial skeleton was reflected onto the contralateral injured side, and a reconstructive orbital floor prosthesis was virtually designed on the mirrored orbital bone sur-face. The solid-to-layer (.STL) files of the prosthesis were then manufactured using Direct Metal Laser Sintering (DMLS) or Computer Numerical Control (CNC) methods, leading to the produc-tion of 10 titanium meshes and 2 high density polyethylene (HDPE) implants. Clinical outcomes were assessed using 3dMD photogrammetry and computed tomography measures in 14 treated patients. The technique described here appears to be a viable method to correct complex orbital floor de-fects needing delayed reconstruction. This article represents the prosecution of a previous study, which is part of a wider experimental protocol for orbital floor reconstruction using comput-er-assisted design-computer-assisted manufacturing (CAD-CAM) technology

Breast cancer (BC) is the most common malignancy and the second cause of cancer specific death in women from high-income countries. More than 70% of all breast cancer are hormone receptor-positive BC, and elevated estrogen circulating in blood has been proved to be a strong risk for BC development. This is due to its contribution to enhance proliferation of cancerous cells, angiogenesis and metastasis stimulation and therapy resistance. The estrogen (E) metabolism–gut microbiome axis is functional with underlying individual variations in E levels. It is reasonable that the estrobolome (bacterial genes whose products are capable of metabolizing E) could contribute to the risk of hormone-driven malignancies including BC and may serve as a potential biomarker and target. Gut microbial β -glucuronidase (GUS) enzymes have been suggested to be involved in the estrobolome. Furthermore, bacterial GUS enzymes within the gastrointestinal tract have been postulated to contribute to hormone breast cancer. In this review, we discuss the recent knowledge about the role of GUS enzyme in the pathogenesis of breast cancer. We focus on the role of GUS in (i)-the microbioma and estrogen metabolism, (ii) diet, estrobolome, and the BC development, (iii) other activities of the bacterial β-glucuronidase, and (iv) the new molecular target for BC therapeutic application.

Blood glucose (BG) monitoring is an important issue for critically ill patients. Previous studies reported that poor sugar control was associated with increased mortality in admitted patients. However, repeated blood glucose monitoring can be resource-consuming and cause a healthcare burden in clinical practice. In this study, we aimed to develop a personalized machine-learning model to predict dysglycemia based on electrocardiogram (ECG) findings. The study included patients with more than 20 ECG records during single hospital admission in the Medical Information Mart for Intensive Care III database, focusing on the lead II recordings, along with the corresponding blood sugar data. We processed the data and used ECG features from each heartbeat as inputs to develop a one-class support vector machine (SVM) algorithm to predict dysglycemia. The model prediction for dysglycemia using a single heartbeat had an AUC level of 0.92 ± 0.09, with a sensitivity of 0.92 ± 0.10 and specificity of 0.84 ± 0.04. Based on 10 s majority voting, the model prediction for dysglycemia improved to an AUC of 0.97 ± 0.06. In this study, we found that a personalized machine-learning algorithm could accurately detect dysglycemia using a single-lead ECG.

Aim of this research paper is to introduce a novel method of hybrid orthodontic tooth-borne distalizer treatment of class II malocclusion by using 3D printed biocompatible personalized distalizer. Explains 3D designing, printing and clinical application of individualized biocompatible medical device dedicated for orthodontic teeth distalization. Compares such distalizer manufactured from two different biocompatible photopolymers (white and transparent). Evaluates their clinical performance and also patients’ aesthetical perception. Clinical part includes comparison of treatment debonding on the set of 12 complete orthodontic treatments with uni-lateral class II malocclusion managed with hybrid approach (CAT-Invisalign with 3D printed distalizer). Paper offers an evaluation of the personalized distalizer functioning in regard to current publications and comparison to conventional prefabricated alternatives like Carriere® Distalizer™ appliance. Results showed no significance of material differences on clinical performance of such individualized distalizers. Research showed preference of patients towards transparent biocompatible photopolymer instead of white A2 shade.

Plants and plant-derived food products have been used for medicinal purposes since the ancient. Medicinal Plant-based functional foods or plant-based dietary compounds are a re-emerged interest for their therapeutic benefits and nutritive supports which has implicated in healthcare systems across the world. Neurological disorders are one of the greatest threats to public health and according to the World Health Organization, about 100 million people are affected globally by several neurological and mental ailments. In a traditional medication system, medicinal plants have been applied as both neuro-therapeutic purposes and micro-macro nutrients provider for the wellbeing of psychological states e.g. anti-depressant, anti-anxiety, anti-convulsions, anti-dementia, anti-psychotic, etc. Herein, it is a topic of great interest to present a conceptual aspect by reviewing relevant scientific literature about the plant-based functional foods or bioactive phytochemicals for the prevention and treatment of mental and neurological disorders. From the literature assessment, we have found that nutritional neuroscience is becoming an advanced research discipline and there has been a growing pile of evidence concerning the therapeutic use of plant-based functional foods and/or plant-derived food compounds for the management of neurologic health, evolving with promising impact over the time.

This study presents an advanced integration of Multi-modal Raman Light Sheet Microscopy with zero-shot learning-based computational methods to significantly enhance the resolution and analysis of complex three-dimensional biological structures, such as 3D cell cultures and spheroids. The Multi-modal Raman Light Sheet Microscopy system incorporates Rayleigh scattering, Raman scattering, and fluorescence detection, enabling comprehensive, marker-free imaging of cellular architecture. These diverse modalities offer detailed spatial and molecular insights into cellular organization and interactions, critical for applications in biomedical research, drug discovery, and histological studies. To improve image quality without altering or introducing new biological information, we apply Zero-Shot Deconvolution Networks (ZS-DeconvNet), a deep learning-based method that enhances resolution in an unsupervised manner. ZS-DeconvNet significantly refines image clarity and sharpness across multiple microscopy modalities without requiring large, labeled datasets, or introducing artifacts. By combining the strengths of multi-modal light sheet microscopy and ZS-DeconvNet, we achieve improved visualization of subcellular structures, offering clearer and more detailed representations of existing data. This approach holds significant potential for advancing high-resolution imaging in biomedical research and other related fields.

Aim: To evaluate the impact of applying alternative diagnostic criteria for gestational diabetes mellitus (GDM) during the COVID-19 pandemic on GDM prevalence, obstetrical and perinatal outcomes, and costs, as compared to the standard diagnostic method. Methods: A cohort of pregnant individuals undergoing GMD screening with the alternative GDM method, which uses plasma glucose (fasting or non-fasting) and HbA1c, was compared with a cohort of pregnant individuals undergoing the standard GDM screening method. Both cohorts were obtained from 6 hospitals across Catalonia, Spain, from April 2020 to April 2022. The primary outcome was large for gestational age rate at birth. Secondary outcomes were composite adverse outcomes including pregnancy complications, delivery complications, and neonatal complications. Cost differences between screening methods were also evaluated. A similar analysis was performed in the subgroup diagnosed with GDM. Results: Data were collected from 1,543 pregnant individuals in the standard screening group and 2,197 in the alternative screening group. The standard screening group had a higher GDM diagnostic rate than the alternative screening group (10.8% vs 6.9%, respectively; p<0.0001). The primary outcome (large for gestational age rate) was similar between groups: 200/1543 (13.0%) vs 303/2197 (13.8%). The adjusted OR for this outcome was 1.74 (95% CI: 0.74-4.10). An adjusted analysis showed no differences between groups in composite adverse outcomes for pregnancy complications (OR: 1.11; 95% CI: 0.91-1.36), delivery complications (OR: 0.95; 95% CI: 0.75-1.19), and neonatal complications (OR: 1.28; 95% CI: 0.94-1.75). Among individuals diagnosed with GDM, the large for gestational age rate was similar between groups: 13/166 (7.8 %) vs 15/151 (9.9 %). The OR adjusted for this outcome was 1.24 (95% CI: 0.51-3.09). An adjusted analysis showed no differences in composite adverse outcomes for pregnancy complications (OR: 1.57; 95% CI: 0.84-2.98), delivery complications (OR: 1.21; 95% CI: 0.63-2.35), and neonatal complications (OR: 1.35; 95% CI: 0.61-3.04). The mean cost (which included expenses for consumables, equipment and personnel) of the alternative screening method was 46.0 euros (22.3 SD), as compared to 85.6 euros (67.5 SD) for the standard screening method. Conclusions: In this Spanish population during the COVID-19 pandemic, GDM prevalence was lower in the alternative screening group than in the standard screening group. After adjusting for GDM risk factors, outcomes related to obstetrics, delivery, and neonatal complications were comparable between both groups. Finally, the alternative screening method was cheaper than the standard screening method.

Antecedents. EFs (EFs) are the basis for establishing a goal and working towards that goal by coordinating thoughts and actions. EFs are fundamental to several aspects of daily life, specifically for academic performance. Aim. To analyze and compare the development of EFs in the transition period between the first and second cycles of Early Childhood Education. Methodology. Non-experimental methodology, ex post facto design, descriptive, cross-sectional evolution study. Participants. Preschoolers of different educational levels (first and second cycle of Infant Education). In this study the participants have been evaluated by different informants: 54.42% by parents and 45.58% by teachers. In relation to gender, 52.65% were male and 47.35% were female. In relation to age, 37.54% had a range of 2-3 years and 62.46% had a range of 4-5 years. Measurement. Instrument development of EFs were evaluated using BRIEF-P by key informants. Results. Preschoolers in the first cycle show significantly higher scores than preschoolers in the second cycle in BRIEP-P. Conclusions. The development of EF is key in these first key moments, having a special impact on later development and academic performance. It is necessary to work on EFs from the first cycle of Early Childhood Education, considering the evolutionary development of EFs.

Growth hormone therapy (GHT) can improve growth velocity and final height but can also accelerated the process of bone growth, which is related to structural bone modelling, both in formation and resorption. The study evaluated the capacity of bone turnover markers to predict early growth response to one year GHT in short stature children born as small for gestational age (SGA). 25 prepubertal SGA children were included. We have estimated P1NP (N-terminal procollagen type 1), CTX (C-terminal telopeptide of collagen type I), P3NP (N-terminal procollagen type III), NT-pro-CNP (amino-terminal C-type natriuretic peptide) and Ca-P metabolism using standard ECLIA, IRA and ELISA methods. A statistically significant increase in bone resorption markers (Ctx ) was found both at 6 and 12 months. P1NP bone markers increased at 6 months and after 12 months of therapy. The P3NP marker of collagen synthesis also increased after 12 months of therapy. We obtained significant increases in phosphorus levels at 6 and 12 months and similarly ALP. We have found a significant correlation between height (cm) and Ctx after 6 -12 months as well as P1NP / height (SD) after 12 months. Calcium levels significantly correlated with height (SD) after 12 months. We find a strong reaction of bone resorption and bone formation markers during growth hormone therapy that may determine their selection as prediction of GH treatment outcome in SGA children. However, the issue requires further research.

Polysulfides are endogenously produced in mammals and generally associated with protective functions. Our aim was to investigate the effect of dimethyl trisulfide (DMTS) in a mouse model of acute stress. DMTS activates transient receptor potential ankyrin 1 (TRPA1) channels and leads to neuropeptide release, potentially that of substance P (SP). We hypothesize that DMTS might inhibit the degrading enzymes of endocannabinoids, so this system was also investigated as another possible pathway for mediating the effects of DMTS. Trpa1 gene wild type (WT) and knock out (KO) mice were used to confirm the role of the TRPA1 ion channel in mediating the effects of DMTS. C57BL/6J, NK1 gene KO, and Tac1 gene KO mice were used to evaluate the effect of DMTS on the release and expression of SP. Some C57BL/6J animals were treated with AM251, an inhibitor of the cannabinoid CB1 receptor, to elucidate the role of the endocannabinoid system in these processes. Open field test (OFT) and forced swim test (FST) were performed in each mouse strain. Tail suspension test (TST) was performed in TRPA1 WT and KO animals. C-FOS immunohistochemistry was carried out on TRPA1 WT animals. DMTS treatment increased the number of highly active periods and decreased immobility time in the FST in WT animals, but had no effect on Trpa1 KO mice. DMTS administration induced neuronal activation in stress-related brain areas such as the locus coeruleus, dorsal raphe nucleus, lateral septum, paraventricular nucleus of the thalamus, and paraventricular nucleus of the hypothalamus. DMTS may have a potential role in the regulation of stress-related processes, and the TRPA1 ion channel may also be involved in mediating the effects of DMTS. DMTS can be an ideal candidate for further study as a potential remedy in stress-related disorders.

p-Toluenesulfonic acid is commercially available, non-toxic, cheap organic compound with robust stability. p-Toluenesulfonic acid is solid, non-corrosive and a strong organic acid that can be handled easily. Due to this p-toluenesulfonic acid could be the better replacement of other conventional acids like nitric acid, sulfuric acid, perchloric acid and AlCl3 in organic transformations. Moreover, p-toluenesulfonic acid could be used synergistically with other mode of catalysis like transition metal catalysis and photocatalysis. In recent years, the use of this solid organic acid in organic and polymer synthesis has grown tremendously. In this review, we present an overview of p-toluenesulfonic acid promoted various organic reactions with particular emphasis to the more recently reported methods. In some cases, we also detailed the understanding of the reactions by providing the reaction mechanism. Despite these advances, there are still many opportunities for the development of new reactions using PTSA. Industry and academia have become more conscious to adopt sustainable chemical processes using safer reagents and solvents and the use of PTSA in this context is highly significant. This review will inspire researchers for further reaction development employing p-toluenesulfonic acid.

Sechium compositum (Cucurbitaceae) is a wild species that is distributed in the Soconusco region, Chiapas, Mexico, and the border with Guatemala. This species has an intangible biochemical value resulting from the pharmacological relevance of its secondary metabolites. However, as a consequence of the lack of knowledge about its importance, it is being displaced from its habitat at an accelerated rate, incurring the risk of genetic loss. Therefore, an in vitro culture protocol with two experimental phases was evaluated to propagate, conserve, and regenerate this species. The first phases considered the multiplication of seedlings, adding seven concentrations (0.1, 0.2, 0.4, 0.6, 0.8, 1.0, 1.2 mg mL-1) of 6-benzylaminopurine (BA) and thidiazuron (TDZ) and evaluating the number of buds, shoots, and seedling height. The best multiplication response was recorded with 0.1, 0.2, 0.4, and 1.0 mg L-1 of BA and 0.1 mg L-1 of TDZ, as well as the MS base culture medium. With 0.1 mg L-1 of BA, 52-mm height, 1.36 shoots, and 9.22 buds were obtained, surpassing the MS control (MS culture medium alone); likewise, twice more roots (80%) and a 14% reduction in the bud structure were packed in 50 repetitions. The second phase consisted of inducing callus formation from stem and leaf explants through the addition of 0.5, 1.0, and 2.0 mg L-1 of TDZ and 2,4-Dichlorophenoxyacetic acid (2,4-D) to the medium. The results demonstrated that the induction of callogenesis in S. compositum has a better start from the stem in a medium with 2.0 mg L-1 of 2,4-D, whose value was 4.89 —equivalent to 97.8% callus formation around the explant. The addition of 500 mg L-1 of polyvinylpyrrolidone (PVP) is also suggested to reduce oxidation. This protocol represents a significant advance in the conservation, multiplication, and callogenesis of S. compositum and contributes to its rescue and revaluation in the face of the danger of extinction.

In this study, we investigate the existence of positive solutions within a system of Riemann-Liouville fractional differential equations that incorporate the (r1,r2,r3)-Laplacian operator while being subject to three-point boundary conditions. These equations incorporate various fractional derivatives and are influenced by parameters represented as (ψ1,ψ2,ψ3). Our approach involves employing techniques such as cone expansion and compression of the functional type, in conjunction with the Leggett-Williams fixed point theorem, to establish the existence of positive solutions. To emphasize the practical significance of our findings in the realm of fractional differential equations, we provide two illustrative examples.

In recent years, numerous approaches have been developed to comprehend the molecular altera-tions underlying thyroid cancer (TC) oncogenesis and explore novel therapeutic strategies for TC. It is now well established that the neurokinin-1 receptor (NK-1R) is overexpressed in cancer cells and that NK-1R is essential for viability of cancer cells. The binding of substance P (SP) to NK-1R in neoplastic cells plays a pivotal role in cancer progression by promoting neoplastic cell growth, protecting tumour cells from apoptosis, triggering invasion and metastasis through enhanced migration of cancer cells, and stimulating endothelial cell proliferation for tumour angiogenesis. Remarkably, all types of human TC (papillary, follicular, medullary, anaplastic), as well as met-astatic lesions, exhibit overexpression of SP and NK-1R compared to the normal thyroid gland. TC cells synthesize and release SP, which exerts its multiple functions through autocrine, para-crine, intracrine, and neuroendocrine processes, including the regulation of tumour burden. Con-sequently, the secretion of SP from TC results in increased SP levels in plasma, which are signifi-cantly higher in TC patients compared to controls. Additionally, NK-1R antagonists have demonstrated a dose-dependent antitumour action. They impair cancer cell proliferation on one side and induce apoptosis of tumour cells on the other side. Furthermore, it has been demonstrat-ed that NK-1R antagonists inhibit neoplastic cell migration, thereby impairing both invasiveness and metastatic abilities, as well as angiogenesis. Given the consistent overexpression of NK-1R in all types of TC, targeting this receptor represents a promising therapeutic approach for TC. Therefore, NK-1R antagonists, such as the drug aprepitant, may represent novel drugs for TC treatment.

The aim of this systematic review is to describe and to identify prospect of β-Tricalcium Phosphate (β-TCP) as Alveolar Bone Grafting (ABG) in Cleft Lip/Palate (CL/P) or alveolar bone cleft defect. A systematic review protocol based on Preferred Reporting Items for Systematic Reviews and Meta Analyses 2020 (PRISMA 2020) was drafted. The literature search was conducted with MEDLINE/PubMed, Web of Science/ ISI-Web of Knowledge, Scopus and Cochrane Library with English language and no publication year limits. The keywords yielded a total of 5824 publications. There are 3196 suitable articles to evaluate after removing duplicates and languages. Afterward, 1315 studies left after doing title and abstract reading. In addition, 85 full-articles were assessed for eligibility. The read the complete texts of those papers and eventually chose 20 that matched the inclusion requirements. Thirteen of the twenty studies included in this systematic review had a low risk of bias, one had a high risk of bias, and six had moderate bias which not report the randomization. β-TCP as ABG is biocompatible, visible and practical, offers a less invasive procedure, and does not interfere with orthodontic treatment. β-TCP as synthetic ABG can be the alternative to autologous bone grafts with several terms and conditions. Improvement of β-TCP efficacy for ABG in CL/P or alveolar bone cleft defects can be done by a tissue engineering approach combining β-TCP with growth factor, mesenchymal stem cells, or other graft materials and modification of β-TCP physical properties.

Respiratory syncytial virus (RSV) RNA synthesis takes place in cytoplasmic viral factories also called inclusion bodies (IBs), which are membrane-less organelles concentrating the viral RNA polymerase complex. IBs assembly is driven by liquid-liquid phase separation promoted by interactions between the viral nucleoprotein N and the phosphoprotein P. We recently demonstrated that cyclopamine (CPM) inhibits RSV multiplication by disorganizing and hardening IBs. Although a single mutation in the viral transcription factor M2-1 induced resistance to CPM, the mechanism of action of CPM still remains to be characterized. Here, using FRAP experiments on reconstituted pseudo-IBs both in cellula and in vitro, we first demonstrated that CPM activity depends on the presence of M2-1 together with N and P. We show that CPM impairs the competition between P and RNA binding to M2-1. As mutations on both P and M2-1 induced resistance against CPM activity, we suggest that CPM may affect the dynamics of the M2-1−P interaction, thereby affecting the relative mobility of proteins contained in RSV IBs. Overall, our results reveal that stabilizing viral protein-protein interactions is an attractive new antiviral approach. They pave the way for the rational chemical optimization of new specific anti-RSV molecules.

The paper considers coherent states for the representation of Weyl commutation relations over a field of $p$-adic numbers. A geometric object, a lattice in vector space over a field of p-adic numbers, corresponds to the family of coherent states. It is proved that the bases of coherent states corresponding to different lattices are mutually unbiased, and the operators defining the quantization of symplectic dynamics are Hadamard operators.

A paradigm shift away from null hypothesis significance testing seems in progress. Based on simulations, we illustrate some of the underlying motivations. First, P-values vary strongly from study to study, hence dichotomous inference using significance thresholds is usually unjustified. Second, statistically significant results have overestimated effect sizes, a bias declining with increasing statistical power. Third, statistically non-significant results have underestimated effect sizes, and this bias gets stronger with higher statistical power. Fourth, the tested statistical hypotheses usually lack biological justification and are often uninformative. Despite these problems, a screen of 48 papers from the 2020 volume of the Journal of Evolutionary Biology exemplifies that significance testing is still used almost universally in evolutionary biology. All screened studies tested default null hypotheses of zero effect with the default significance threshold of p = 0.05, none presented a pre-specified alternative hypothesis, pre-study power calculation, and the probability of ‘false negatives’(beta error). The results sections of the papers presented 49 significance tests on average (median 23, range 0–390). Of 41 studies that contained verbal descriptions of a ‘statistically non-significant’ result, 26 (63%) falsely claimed the absence of an effect. We conclude that studies in ecology and evolutionary biology are mostly exploratory and descriptive. We should thus shift from claiming to ‘test’ specific hypotheses statistically to describing and discussing many hypotheses (possible true effect sizes) that are most compatible with our data, given our statistical model. We already have the means for doing so, because we routinely present compatibility (‘confidence’) intervals covering these hypotheses.

A vivid debate is ongoing in the scientific community about statistical malpractice and the related publication bias. No general consensus exists on the consequences and this is reflected in heterogeneous rules defined by scientific journals on the use and reporting of statistical inference. This paper aims at discussing how the debate is perceived by the agricultural economics community and implications for our roles as researchers, contributors to the scientific publication process, and teachers. We start by summarizing the current state of the p-value debate and the replication crisis, and commonly applied statistical practices in our community. This is followed by motivation, design, results and discussion of a survey on statistical knowledge and practice among the researchers in the agricultural economics community in Austria, Germany and Switzerland. We conclude that beyond short-term measures like changing rules of reporting in publications, a cultural change regarding empirical scientific practices is needed that stretches across all our roles in the scientific process. Acceptance of scientific work should largely be based on the theoretical and methodological rigor and where the perceived relevance arises from the questions asked, the methodology employed, and the data used but not from the results generated. Revised and clear journal guidelines, the creation of resources for teaching and research, and public recognition of good practice are suggested measures to move forward.

We utilized laser irradiation as a potential technique in tuning the electrical performance of NiOx/SiO2 thin film transistors (TFTs). By optimizing the laser fluence and the number of laser pulses, the TFT performance is evaluated in terms of mobility, threshold voltage, on/off current ratio and subthreshold swing, all of which were derived from the transfer and output characteristics. The 500 laser pulses irradiated NiOx/SiO2 TFT exhibited an enhanced mobility of 3 cm2/V-s from a value of 1.25 cm2/V-s for as-deposited NiOx/SiO2 TFT. The laser-irradiated NiOx material likely has a significant concentration of defect gap states, which could also be involved in light absorption processes. Second, and more importantly, the excess energy that the photogenerated charge carriers possess (due to the significant difference between the photon energy and the bandgap of NiOx), combined with the very high light intensity, would result in complex thermal and photo thermal changes thus resulting in an enhanced electrical performance of p-type NiOx/SiO2 TFT structure.

Increasing evidence suggests that prenatal exposure to opioids can adversely influence brain development, yet, limited data exists on the effects of opioid-exposure on preschool language development. Our study aimed to characterize the nature and prevalence of language problems in children prenatally exposed to opioids, and the factors that support or hinder language acquisition. A sample of 100 children born to pregnant women in methadone maintenance treatment and 110 randomly identified non-exposed children were studied from birth to age 4.5 years. At 4.5 years, 89 opioid-exposed and 103 non-exposed children completed the preschool version of the Clinical Evaluation of Language Fundamentals (CELF-P) as part of a comprehensive neurodevelopmental assessment. Children prenatally exposed to opioid had poorer receptive and expressive language outcomes at age 4.5 years compared to non-exposed children. After adjustment for child sex, maternal education, other pregnancy substance use, maternal pregnancy nutrition and prenatal depression, opioid exposure remained a significant independent predictor of children’s total CELF-P language score. Examination of a range of potential intervening factors showed that a composite measure of the quality of parenting and home environment at 18 months and early childhood education participation at 4.5 years were important positive mediators.

A renewable cyclic monoterpene obtained from citrus peel, limonene is widely used as a fra-grance, nutraceutical ingredient, antibacterial, biopesticide, and green extraction solvent. Indus-trial demand largely exceeds supply. After reviewing recent advances in the recovery of limonene from citrus peel and residues with a particular attention to benign-by-design extractive processes, we focus on the latest results in its dehydrogenation to p-cymene via heterogeneous catalysis.

Distinguishable annual growth rings produce in Pinus roxburghii are an asset to find out the age of individual tree. This paper aimed to determine the age of P. roxburghii through coring samples and test the relationship with forest production. The biomass estimated, girths measured at two different sections and heights measured which allowed to determine the rate of tapering of the stand. The regression analysis was performed to test the relationship between various variables. The mean age of the P. roxburghii stand was found to be 23.97 (~24 years). The result showed the significant (p<0.05) positive correlation coefficient has been seen between age with girth at breast height, biomass, volume and carbon stock. However, no significant (p>0.05) correlation (r = 0.08) was found between age and height of the stand. In contrast, a correlation between diameter at breast height (DBH) was significant (p<0.05) and positive with volume, biomass, but no significant (p>0.05) correlation (r = 0.14) found between DBH and height of the stand. However, height has a significant (p<0.05) positive correlation with biomass. The mean biomass was 375 kg and mean annual increment (MAI) was 15 kg per tree. Rate of tapering of the studied stand predicted to be 3 cm diameter decreased with trunk height running at 100 cm from base to upward of P. roxburghii stand and vice versa. Result suggests that height-age relation is very weak whereas age, DBH, biomass and carbon has a significant correlation signifies that time-based forests' production and potential production estimation can be obtained in a relatively accurate way by utilizing the age of stand. The time-based forest production analysis is pioneer work in Nepal. The study affirms the tree ring count in P. roxburghii would be a credible and accurate method to determine the age of standing trees.

In this work, magnetic CuFe₂O₄/Ag nanoparticles activated by porous covalent organic frameworks (COF) was fabricated to evaluate the heterogenous reduction of 4-nitrophenol (4-NP). The core-shell CuFe₂O₄/Ag@COF was successfully prepared by polydopamine reduction of silver ions on CuFe₂O₄ nanoparticles, followed by COF layer condensation. With integrating the intrinsic characteristics of the magnetic CuFe₂O₄/Ag core and COF layer, the obtained nanocomposite exhibited features of high specific surface area (464.21 m² g^-1), ordered mesoporous structure, strong environment stability, as well as fast magnetic response. Accordingly, the CuFe₂O₄/Ag@COF catalyst showed good affinity towards 4-NP via π-π stacking interactions and possessed enhanced catalytic activity compared with CuFe₂O₄/Ag and CuFe₂O₄@COF. The pseudo-first-order rate constant of CuFe₂O₄/Ag@COF (0.77 min^-1) is 3 and 5 times higher than CuFe₂O₄/Ag and CuFe₂O₄@COF, respectively. The characteristics of bi-catalytic CuFe₂O₄/Ag and the porous COF shell of CuFe₂O₄/Ag@COF made a contribution to improve the activity of 4-NP reduction. The present work demonstrated a facile strategy to fabricate COF activated nano-catalysts with enhanced performance in the fields of nitrophenolic wastewater treatment.

In this paper, we have used magnetron sputtering to grow the high-quality GeSn layer on Ge (100) with Sn compositin up to 7%. The crystallinity of the GeSn layer is pretty good, and the strain relaxation degree of the GeSn layer is evaluated to be approximately 50%. The root mean square (RMS) value is 0.8 nm, and the averaged TDDs in the GeSn layer is 8.7×109 cm-2, which is obtained from the rocking curve of GeSn layer along (004) plane. PL measurement result shows the significant optical emission from the deposited high-quality GeSn layer, which also means that magnetron sputtering is an optional way to achieve the higher Sn composition GeSn luminescent material. To verify whether our deposited GeSn can used for optoelectronic devices, we fabricate the simple vertical p-i-n diode, and the room temperature current-voltage (I-V) characteristic was obtained. This result paves the way for future sputtered-GeSn optimization, which is critical for the optoelectronic application.

In this work, nylon 6/ P(N-phenylmaleimide-alt-styrene) blends were prepared by melt blending, and the mechanical, heat-resistant, crystallographic and dynamical mechanical properties of nylon 6/ P(N-phenylmaleimide-alt-styrene) blends with different contents were investigated and analyzed. The results showed that the mechanical properties decreased with increasing PNS, while the heat deflection temperature (HDT), relative crystallinity (Xn), and storage modulus (G’) increased with increasing PNS. The results of differential Scanning Calorimetry (DSC) proved the PNS played the positive role of nucleating PA6. And the results of dynamic mechanical analysis (DMA) proved the PNS could improve the rigidity of PA6/PNS blends. From the SEM, these PNS domains were between 0.2 and 4 μm in diameter. The experimental results indicated that the addition of PNS improved the rigidity of PA6/PNS blends, and then improved the heat-resistant property.

Incidental P losses from non-point sources may contribute to eutrophication and to decreased soil fertility. These incidents have been related to heavy rainfall on freshly fertilized agricultural soils and little is known about such incidents on more natural soils or in forests. The aim of this work is to determine if incidents of high P leaching also occur in spruce forests, and if such incidents are of significance in P cycling. We found a peak in the mineral soil solution showing that single events of high P leaching occur. The orthophosphate concentration in the Bf-horizon of the 80-year old spruce forest peaked in the autumn of the second year of a continuous monitoring. The concentration increased by more than 85 times compared to the highest concentration obtained earlier during the sampling. The amount leached during this 6 months peak is 10 times higher than the average annual leaching. This P leaching might be due to a combination of high P deposition/through-fall and a high anion exchange with dissolved-organic-carbon and Cl-. We suggest that single events of high sub-surface P leaching may contribute to the overall P leaching, and might increase with the global warming as more DOC is expected to be released to the soil solution.

The objective of the this study was to reduce the benzo[a]pyrene-induced hepatotoxicity method in herbal medicine products and to give proof that neferine, daidzein, genistein possess antihepa-totoxic effects. B[a]P which classified as a group 1 carcinogen and metabolized to B[a]P-7,8-dihydrodiol-9,10-epoxide (BPDE) causes mutagenic DNA addition products. The reduc-tion of BPDE-DNA adduct formation by B[a]P-7,8-dihydrodiol-9,10-epoxide (BPDE) was derived by benzo[a]pyrene (B[a]P). In HepG2 cells, B[a]P exhibited toxicity and substance treatment of the cells with B[a]P with neferine in lotus and daidzein, genistein in soybean reduced the BPDE-DNA ad-ducts level. The level of B[a]P-metabolites in the substance treatment of the cells was presented that BPDE levels were reduced by neferine in lotus and daidzein, genisten in soybean. These results suggest that neferine in lotus and daidzein, genistein in soybean prevent B[a]P-induced hepato-toxicity for BPDE-DNA adduct formation.

J/ψ, a charmonium bound state made of a charm and an anti-charm quark, has been discovered in the 1970s and confirmed the quark model. Because the mass of charms quarks is significantly above the Quantum Chromodynamics (QCD) scale ΛQCD, charmonia are considered as excellent probes to test perturbative Quantum Chromodynamics (pQCD) calculations. Over the past decades, they have been studied extensively at different high energy colliders. However, their production mechanisms, which involves multiple scales, are still not very well understood. Recently, in high multiplicity p+p collisions at RHIC and at the LHC, a significant enhancement of J/ψ production yield has been observed, which suggests a strong contribution from the Multi-Parton Interaction (MPI). This is different from the traditional pQCD picture where charm quark pairs are produced from a single hard scattering between partons in p+p collisions. In this work, we will report the J/ψ normalized production yield as a function of normalized charged particle multiplicity over a board range of rapidity and event multiplicity in the J/ψ→μ+μ− channel with PHENIX Run 15 p+p data at \sqrt{s}=200 GeV. The results are compared with PYTHIA 8 simulations with the MPI option on and off. Finally, the outlooks of J/ψ in p+Au and Au+p collisions along with Color Glass Condensate (CGC) predictions and of multiplicity dependent ψ(2S)/J/ψ ratio in p+p data will be briefly discussed.

Liver disease can significantly impact life expectancy, making early diagnosis and therapeutic intervention critical challenges in medical care. Imaging diagnostics play a crucial role in diagnosing and managing liver diseases. Recently, the application of artificial intelligence (AI) in medical imaging analysis has become indispensable for healthcare. AI, trained on vast datasets of medical images, has sometimes demonstrated diagnostic accuracy that surpasses human experts. AI-assisted imaging diagnostics are expected to contribute significantly to the standardization of diagnostic quality. Furthermore, AI has the potential to identify image features imperceptible to humans, thereby playing an essential role in clinical decision-making. This capability enables physicians to formulate more accurate diagnoses and develop effective treatment strategies, ultimately improving patient outcomes. Additionally, AI is anticipated to become a powerful tool in personalized medicine. By integrating individual patient imaging data with clinical information, AI can propose optimal treatment plans, making it an essential component in providing the most appropriate care for each patient. Current reports highlight the advantages of AI in managing liver diseases. As AI technology continues to evolve, it is expected to further advance personalized diagnostics and treatments, contributing to overall improvements in healthcare quality.

Type 2 Diabetes (T2D) is a major public health concern. We have previously shown that the biochemical functions of the gut microbiome contribute to the postprandial glucose response and built a machine learned (ML) model that can personalize dietary choices using a stool metatranscriptomic test. We integrated this data-driven personalized nutrition process into the Viome Precision Nutrition Program (VPNP), which includes sample collection kits (capillary blood and stool), an AI/ML nutritional recommendation engine, and an app for digital delivery of dietary recommendations. To test the efficacy of VPNP, we conducted a decentralized, blinded, randomized, placebo-controlled trial in a prediabetic and diabetic adult population in the USA, with HbA1c as the primary endpoint. For this pilot trial, we recruited 27 participants and randomized them into two arms. The placebo arm included sample collection, digital delivery of the USDA dietary recommendations, and physical delivery of supplements filled with inert material. The VPNP (interventional) arm included digital delivery of data-driven and personalized dietary recommendations, and physical delivery of precision supplements. The nutritional intervention lasted ~90 days. The ANCOVA analysis method was employed to control for potential confounders measured at baseline. VPNP intervention (n=12) reduced HbA1c more than the placebo (n=15) in a clinically significant manner (HbA1c difference of 0.42%, p = 0.028). We demonstrate that a precision nutrition program based on stool and blood metatranscriptomic data and AI/ML analyses can significantly reduce HbA1c relative to USDA recommended nutrition in a prediabetic and diabetic population. These results suggest that integrating data-driven precision nutrition into the healthcare system could reduce the burden of T2D.

This paper presents a novel framework for Collaborative Learning Networks (CLNs) in classrooms, aiming to optimize resource utilization and enhance educational services. The study addresses the inefficiencies of traditional education models, particularly the underutilization of computational resources and limited access to specialized software. The proposed framework employs a mix of task-based and random allocation strategies to distribute computational tasks within the CLN, considering each device’s capabilities and task requirements. The findings show significant improvement in resource utilization, facilitated by device-to-device collaboration and task sharing, thus enriching students’ learning experiences. This work contributes to optimizing resource utilization in education, advancing the field of CLNs.

In an era where dietary habits significantly impact health, technological interventions can offer personalized and accessible food choices. This paper introduces Chef Dalle, a recipe recommen-dation system that leverages multimodal human-computer interaction (HCI) techniques to pro-vide personalized cooking guidance. The application integrates voice-to-text conversion via Whisper, ingredient image recognition through GPT-Vision, and employs TF-IDF vectorization alongside cosine similarity for personalized recipe recommendations. These methods enable users to interact with the system using voice, text, or images, accommodating various dietary re-strictions and preferences. Furthermore, the utilization of DALL-E 3 for generating recipe images enhances user engagement. User feedback mechanisms allow for the refinement of future rec-ommendations, demonstrating the system's adaptability. Chef Dalle showcases potential appli-cations ranging from home kitchens to grocery stores and restaurant menu customization, ad-dresses accessibility, promoting healthier eating habits. This paper underscores the significance of multimodal HCI in enhancing culinary experiences, setting a precedent for future developments in the field.

This study addresses the challenge of treating skin cancer effectively, especially in visible areas like the face, where traditional methods may be undesirable. Current options, including surgery and radiation therapy, have limitations such as complexity, expense, and imprecise dose delivery. The proposed solution involves additively manufacturing personalized patches using diagnostic imaging data, offering a targeted and controlled dose of beta-emitting isotopes like Y-90. The patches, tailored to the tumor's shape and depth, aim to minimize damage to healthy tissues and structures. Through 3D printing technology we demonstrated the feasibility of creating individualized applicators filled with radioisotopes, that have the potential to deliver therapeutic doses while ensuring patient comfort and affordability. This innovative approach, based on radiation delivery simulations, offers a promising future alternative to conventional radiation therapy methods. Clinical trials are required to validate its efficacy and safety, but the potential for reduced radiation exposure and enhanced treatment precision positions this personalized and targeted therapy as a valuable advancement in skin cancer treatment.

This study introduces the Dynamic Feedback-Driven Learning Optimization Framework (DFDLOF), an innovative machine learning-based approach to personalize educational pathways. DFDLOF leverages advanced algorithms for in-depth analysis of learner data, enabling the dynamic customization of educational content and methodologies. Its application in diverse online platforms, including Khan Academy and Coursera, underscores its adaptability and scalability. DFDLOF enhances learner engagement and outcomes by providing tailored learning experiences and real-time feedback. Key insights reveal its strengths in personalized education, particularly in dynamically adapting learning paths and the importance of real-time feedback. Challenges identified include integration complexities and data privacy concerns. Future research directions emphasize the need for longitudinal impact studies and broader demographic applications. This study contributes significantly to the evolving domain of adaptive learning technologies, demonstrating the transformative potential of machine learning in personalizing education.

Patient-derived tumor organoids (PDTOs) are a novel preclinical model of non-small cell lung cancer (NSCLC) for studying tumor biology and precision medicine, which recapitulates tumor morphology and gene expression profile. However, some issues such as low establishment rates, long-term production, and the loss of the immune microenvironment have hindered their widespread practical use. In this study, we investigated the efficacy of a recently introduced free-floating organoid production method to address these issues. The free-floating approach provided PDTO establishment success rate of over 90 % resulting in organoid formation within a short period of one week. These organoids retained the elements of the parental tumor morphology and contained stroma and immune cell populations, as confirmed by flow cytometry analysis. Importantly, we found that the cytokine and growth factor expression profiles of the free-floating organoids correlated with those of the original tumors in 58 % of cases, indicating the preservation of tumor-associated signaling pathways. Obtained organoids exhibited different responses to anticancer chemotherapeutics that might be a result of variable expression of drug resistance-associated genes. Considering the high establishment rate and short time of free-floating organoid production, this technique provides a valuable tool for a more accurate evaluation of therapeutic strategies and cancer biology studies.

Despite evidence-based therapies, patients presenting with atherosclerosis involving more than one vascular bed, such as those with peripheral artery disease (PAD) and concomitant coronary artery disease (CAD), constitute a particular vulnerable group characterized by enhanced residual long-term risk for major adverse cardiac events (MACE), as well as major adverse limb events (MALE). The latter are progressively emerging as a hard outcome to be targeted, being correlated with increased mortality. Antithrombotic therapy is the mainstay of secondary prevention in both patients with PAD or CAD however, the optimal intensity of such therapy is still topic of debate, particularly in the post-acute and long-term setting. Recent well powered randomized clinical trials (RCTs) have provided data in favor of a more intense antithrombotic therapy, such as prolonged dual antiplatelet therapy (DAPT) with aspirin and a P2Y12 inhibitor or a therapy with aspirin combined with an anticoagulant drug. Both approaches increase bleeding and patients selection is a key issue. The aim of this review is therefore to discuss and summarize the most updated available evidences for different strategies of anti-thrombotic therapies in patients with chronic PAD and CAD, particularly focusing on studies enrolling patients with both type of atherosclerotic disease and comparing a higher versus a lower intensity antithrombotic strategy. The final objective is to identify the optimal tailored approach in this setting, to achieve the greatest cardiovascular benefit and improving precision medicine.

The use of artificial intelligence (AI) applications in education has the potential to revolutionize the learning experience for international students, who face unique challenges when studying in a foreign country. This paper explores various examples of AI applications in education and their potential impact on international students. AI applications such as personalized learning experiences, adaptive testing, predictive analytics, and chatbots for learning and research are examined for their potential to improve learning efficiency and provide customized education support. It also explores the significant risks and limitations associated with AI technologies, such as privacy, cultural differences, language proficiency, and ethical implications. To maximize the potential benefits of AI applications in higher education, it is crucial to implement appropriate safeguards and regulations. This paper provides a starting point for research on the potential impact of artificial intelligence on international students’ educational experiences and how AI may be integrated into educational administration and learning processes.

Nutraceuticals have taken the spotlight during the past two decades as evidenced by the exponential publications on them. Long a part of routine in Traditional Medicine Systems, the rise of their mainstream use globally raises both safety concerns and need for better understanding of efficacious dosing. We attempt to answer these questions in this preliminary scoping review by an analysis of current literature on nutraceutical use as a personalized or prescription medicine. Using Covidence, Rayyan, and manual searches of PubMed, 598 unique publications were selected. 32 are systematic reviews, of which we overview the scope. We also overview 30 papers that address adverse drug reactions. To obtain an unbiased landscape of the 598 papers, we analyzed keywords using multiple methods. Expectedly, the most frequent keywords were probiotics and vitamins. Unexpectedly and remarkably, among the highest keyword yield was ‘COVID’. Further exploring this aspect, we review 15 pertinent papers, that not only provide robust evidence for nutraceutical benefits as part of SARS-CoV-2 treatment, but also amplify the notion that nutraceuticals are protective. Overall, the strident note is that further robust targeted research is needed in order to reap the full benefits of nutraceuticals in a safe and efficacious manner.

In this paper, the P versus NP problem is studied based on a six-dimensional space-time perspective. The gap between the P-class and NP-class arises from the relationship between time and the solution, as well as the answer that is independent of time. The complexity of solving a problem depends on the time dependence of the answer. Solving problems whose answers do not depend on the passage of time is very difficult and impossible. Like the description of the gravitational factor in Newtonian physics, NP class problems require different mathematical tools. Based on the generalization of physical facts in mathematics, based on six-dimensional space-time, a method to solve problem P versus NP problem has been stated. The results of this study offer a fresh insight into information processing that occurs independent of the passage of time.

In this work, a GaN-on-Si quasi-vertical Schottky diode was demonstrated on a locally grown n-GaN drift layer. The diode achieves a high current density of 2.5 kA/cm², a specific on-resistance RON,sp of 1.9 mΩ.cm² despite the crowding effect in quasi-vertical device and on/off current ratio (Ion/Ioff) of 1010. Temperature-dependent current-voltage characteristics have been measured in the range of 300-433 K to investigate the mechanisms of leakage conduction in the device. At near zero bias, thermionic emission (TE) was found to dominate. At voltage range from -1 to -10 V, electrons gain enough energy to excite into trap states, leading to the dominance of Frenkel-Poole emission (FPE). For a higher voltage range (-10V to -40V), the increased electric field promotes electron hopping along the threading dislocations in the “bulk” GaN layers, and thus, Variable Range Hopping becomes the main mechanism for the whole temperature range. This work provides an in-depth insight into the leakage conduction mechanisms on vertical GaN-on-Si Schottky barrier Diodes (SBDs) grown by localized epitaxy.

The correct selection of the value of p is a complex and iterative procedure that requires experience in the interpretation of the obtained interpolated maps. Inverse Distance Weighting is a method applied to the porosities of the K and L hydrocarbon reservoirs, discovered in the Neogene (Lower Pontian) subsurface sandstones in the northern Croatia (Pannonian Basin System). They represent small and large data samples. Also a standard statistical analysis of the data was made, followed by the qualitative-quantitative analysis of the maps, based on the selection of different values of the power distance exponent (p-value) for the K and L reservoirs maps. According to the qualitative analysis, for a small data set, p-value could be set on 1 or 2 giving the most optimal result, while for a large data set, a p value of 3 and 4 could be applied. By quantitative analysis, for the case of small data p=2 is recommended, resulting in a root mean square error value of 0.03458, a mean absolute error of 0.02013 and a median absolute deviation of 0.00546. Oppositely, a p-value of 3 and 4 is selected as appropriate for a large data set, with root mean square errors of 0.02435 and 0.02437, mean square errors of 0.01582 and 0.01509 and median absolute deviations 0.00896 and 0.00444. Eventually for a small data set, it is recommended to use a p-value of 2, and for a large data set, a p-value of 3 or 4.

Mesoporous silica nanoparticles (MSNs) can be used as carrier materials for the controlled release of pesticides while reducing their negative environmental impact. In this study, we screened an active ingredient, p-cymene (PC), with an excellent inhibitory effect on rice bacterial blight. Subsequently, the PC was successfully loaded onto MSNs via physisorption(PC@MSNs). PC@MSNs, characterized by a regular spherical shape, smooth surface, and an MSN average size of 262.9 nm, achieved an 8.6 % drug loading capacity. The release kinetics of the PC from the PC@MSNs demonstrated a sustained release (288 h) pattern influenced by drug diffusion. The efficacy of the PC@MSNs against Xanthomonas oryzae pv. Oryzae paralleled those of PC. Acute toxicity assays re-vealed that the PC@MSNs were less toxic to aquatic life (LC50=257.867 mg/L) and that the formu-lation showed no adverse effects on rice seedling growth. In summary, these results suggest that PC@MSNs can broaden PC's application scope in managing rice diseases.

Given a set of distinct non-negative integers X^n and a target certificate S in parametrized form: ∃X^k⊆X^n,∑_(x_i∈X^k)▒x_i =S (k=|X^k |,n=|X^n |). We present a polynomial solution of the subset sum problem with time complexity T≤O(kn)≤O(n^2) and space complexity S≤O(((n-1)n)/2)≤O(n^2 ), so that P = NP.

Electrocardigraphy remains as a first-line evaluation method for cardiac function, recording the electrical activity of the heart from the body surface. Since atrial activation is seen on the ECG as P-wave, several factors are known to impact the appearance of the P-wave, such as direction of electric impulse, conduction abnormalities and anatomical characteristics of the atria. The aim of this retrospective study was to find statistically significant associations between anatomy of pulmonary veins (PVs) osberved in cardiac computed tomography (CT) and P-wave appearance during sinus rhythm on resting ECG. For each patient, a resting 12-lead ECG was recorded, the field of analysis was P wave – its’ duration, morphology and axis. The evaluation of the CT scan recordings was performed by creating 3D models of the left atrium and analyzing anatomy of the PVs and left atrial appendage (LAA). Noteworthy correlations were found: anatomy of the left PVs showed an association with LAA volume, LAA morphology and P-wave notching in lead II. The right PVs demonstrated relation with P wave axis and amplitude. Although these correlations cannot be classified as strong, they may play a role in significant scientific discoveries in future research projects.

The scope of this study was twofold: first, to introduce a new method in examining measurement invariance, especially with large-scale studies where a large number of group comparisons are involved: the alignment approach, where only configural invariance is necessary to achieve measurement invariance. Second, to evaluate the psychometric robustness of this approach using real-life data. Particularly, we applied this approach to examine whether the factor structure of a cognitive ability test (PGAT) exhibits measurement invariance across the 26 universities of the Kingdom of Saudi Arabia. The sample consisted of 9,849 graduate students from 26 universities around the Kingdom. The results indicated a robust configural model suggesting that the P-GAT subscales were invariant across the 26 universities. Finally, the aligned factor mean values were estimated, and factor mean comparisons of every group’s mean with all other group means were conducted for both cognitive domains (Verbal and Quantitative). In both domains, King Saud University had the highest mean score among all universities. Moreover, its mean factor score was significantly higher than any other university besides Dammam University. On the other hand, several universities allocated at the northern and Southern borders of the country exhibited the lowest factor mean scores.

Panax ginseng C. A. Meyer (P. ginseng), has been widely used in traditional Chinese medicine (TCM). It contains a number of chemical components and possesses a variety of pharmacological activities. Alzheimer's disease (AD) is neurodegenerative disease that creates a huge burden on the lives and health of individuals. In recent years, studies have indicated that the chemical components of P. ginseng, especially ginsenosides, play a pronounced positive role in the prevention and treatment of neurological diseases. This review aimed to summarize currently studies on chemical components and the mechanisms action in AD intervention treatment of P. ginseng, especially ginsenosides. In this review, the components of P. ginseng and their respective active effects were first introduced. Then the key molecular mechanisms and signaling pathways of P. ginseng were introduced, and its different active ingredients in the prevention and treatment of Alzheimer's disease-related pathogenesis were also summarized from the pathogenesis of AD Aβ generation and aggregation, hyperphosphorylation of tau protein，oxidant stress，neuroinflammation，mitochondrial damage，disorder of neurotransmitter and gut microbiota. Signaling pathway networks related to the action of ginseng active ingredients was constructed, which could serve as a therapeutic target for Alzheimer's disease. In addition to a detailed report on P. ginseng in improving Alzheimer's disease-related pathogenesis, the application of the current technology, spatial metabonomics in AD therapeutics and diagnostics were later discussed. Spatial metabonomics could be applied to investigate the multi-target intervention of P. ginseng on Alzheimer's disease. Research perspectives for the study of P. ginseng in the treatment of Alzheimer's disease were provided for further studies.

The research is a deep study of the CBOE Volatility Index (VIX), which represent the market sentiments of the S & P 500 Index (SPX) over a period of 33 years. It evaluates how the two indexes perform in the stock market crash and how reliable VIX is in predicting market sentiments. The research distributes the market rally in two forms, and one is a trust rally, when investors are happy to see the market in a stable form, and investors' sentiments are positive towards the stock market. Second is a fear rally, where investors' sentiments are negative, and their outlook is bearish for various reasons. It observes the pattern of rallies, like the longest trust or fear rally, in which year and its duration. The research analyzes data to reach a meaningful conclusion and various inferences that can be drawn from the study of historical data.

When 2−1/Q<p≤2, we establish the C^{0,1} and C^{1,α}-regularities of weak solutions to quasi-linear p-Laplacian type non-homogeneous equations in the Heisenberg group.

Paenibacilli are efficient producers of potent agents against bacterial and fungal pathogens, which are of great interest both for therapeutic applications in medicine as well as in agrobiotechnol-ogy. Lipopeptides produced by such organisms play a major role in their inactivation potential. In this work we investigated two lipopeptide complexes, the fusaricidins and the polymyxins, produced by Paenibacillus polymyxa strains DSM 32871 and M1 by MALDI-TOF mass spectrometry. The fusaricidins show potent antifungal activities and are distinguished by an unusual variabil-ity. For strain DSM 32871 we identified numerous yet unknown variants mass spectrometrically. DSM 32871 produces polymyxins of type E (colistins), while M1 forms polymyxins P. For both strains novel, but not yet completely characterized polymyxin species were detected, which pos-sibly are glycosylated. These compounds may be of interest therapeutically, because polymyxins attain increasing attention as last-resort antibiotics against multiresistant pathogenic Gram-negative bacteria. In addition, the volatilomes of DSM 32781 and M1 were investigated with a GC-MS approach using different cultivation media. Production of volatile organic com-pounds (VOCs) was strain and medium dependent. In particular, strain M1 manifested as an effi-cient VOC-producer that exhibited formation of 25 volatiles in total. A characteristic feature of Paenibacilli is the formation of volatile pyrazine derivatives.

The trace element selenium (Se) is taken up from the diet and becomes metabolized mainly by hepatocytes. Selenoprotein P (SELENOP) constitutes the liver-derived Se transporter. Biosynthesis of extracellular glutathione peroxidase (GPx3) in kidney depends on SELENOP-mediated Se supply. We hypothesized that Se status may serve as a useful prognostic marker for outcome in patients undergoing liver transplantation. Serum samples from patients were routinely collected before and after transplantation. Concentration of serum SELENOP and total Se as well as GPx3 activity were determined by standardized tests and related to survival, aetiology and pre-operative Child-Pugh and Model for End-Stage Liver Disease Scores. A total of 314 serum samples from 78 transplanted patients were available for analysis. The Se and SELENOP concentrations were on average below the reference ranges of healthy subjects. Patients with ethanol toxicity-dependent aetiology showed particularly low SELENOP and Se concentrations and GPx3 activity. Longitudinal analysis indicated declining Se concentrations in non-survivors. We conclude that severe liver disease necessitating organ replacement is characterized by a pronounced Se deficit before, during and after transplantation. A recovering Se status after surgery is associated with positive prognosis, and an adjuvant Se supplementation may thus support convalescence.

In developed countries, especially the big-sized ones like Australia and the USA, a car is almost an inevitable necessity to carry out daily activities. Due to this, used cars have become a great alternative to brand new cars because of their cost effectiveness. In this work, estimation of prices of used cars based on numerous factors is studied statistically. Data is based on prices of used cars sold across Australia. Statistical methods like correlation and permutation tests using linear regression model, exact tests and non-parametric bootstrapping is implemented to study the relationship of price with mileage and year of manufacture of the car using p-values and null hypothesis. Predictions are also made on the price by calculating a 95% confidence interval (CI) of median prices in small portions of the dataset. The study presents potential ideas for understanding correlation between variables and parameters in business studies.

Epigallocatechin-3-gallate (EGCG) is the most abundant polyphenol in green tea. In this study, the effects of dietary EGCG on oxidative stress and the metabolism and toxicity of acetaminophen in liver were investigated. Rats were fed the diets with (0.54 %) or without EGCG supplementation for four weeks and were then intraperitoneally injected with acetaminophen (1g/kg). Results showed EGCG lowered hepatic oxidative stress and cytochrome P450 (CYP) 1A2, 2E1, and 3A, and UDP-glucurosyltransferase activities prior to acetaminophen injection. After acetaminophen challenge, the elevations in plasma alanine aminotransferase activity and histological changes in liver were ameliorated by EGCG treatment. EGCG reduced acetaminophen-induced apoptosis by increasing the Bax/Bcl2 ratio in liver. EGCG mildly increased autophagy by increasing the LC3B II/I ratio. Lower hepatic acetaminophen-glutathione and acetaminophen-protein adducts contents were observed after EGCG treatment. EGCG increased glutathione peroxidase and NAD(P)H quinone 1 oxidoreductase activities and reduced organic anion-transporting polypeptides 1a1 expression in liver after acetaminophen treatment. Our results indicate that EGCG may lower oxidative stress and reduce the metabolism and toxicity of acetaminophen. The reductions in CYP-mediated acetaminophen bioactivation and uptake transporter, as well as enhanced antioxidant enzyme activity, may limit the accumulation of toxic products in liver and thus lower hepatotoxicity

Copulas are useful tools for modeling the dependence structure between two or more variables. Copulas are becoming a quite flexible tool in modeling dependence among the components of a multivariate vector, in particular to predict losses in insurance and finance. In this article, we study the dependence structure of some well-known real life insurance data (with two components mainly) and subsequently identify the best bivariate copula to model such a scenario via VineCopula package in R. Associated structural properties of these bivariate copulas are also discussed.

In this paper, we introduced many new notions and new contraction named as S-weakly contraction after that we obtained the p-common best proximity point theorems for different types of contractions in the setting of complete metric spaces by using weak P_p-property and proved the uniqueness of these points. Also we presented some examples to prove the validity of our results.

Metal oxide p-n heterojunction nanofibers (NFs) are among the most promising approaches to enhancing the efficiency of gas sensors. In this paper, we report the preparation of a series of p-NiO-loaded n-ZnO NFs, namely (1 − x) ZnO-xNiO (x = 0.03, 0.05, and 0.1 wt%), for hydrogen gas sensing experiments. Samples were prepared through the electrospinning technique followed by a calcination process. The sensing experiments showed that the sample with 0.05 wt% NiO loading resulted in the highest sensing performance at an optimal sensing temperature of 200 °C. The sensing mechanism is discussed in detail and contributions of the p-n heterojunctions, metallization of ZnO and catalytic effect of NiO on the sensing enhancements of an optimized gas sensor are analyzed. This study demonstrates the possibility of fabricating high-performance H₂ sensors through the optimization of p-type metal oxide loading on the surfaces of n-type metal oxides.

Kummerowia striata is a traditional medicine used for the therapy of inflammation-related diseases. Herein, we investigated the anti-melanogenic and antioxidant activities of an ethanolic extract of K. striata (EKS) using a number of in vitro and cell culture model systems. The anti-melanogenic effect was assessed in B16F10 melanoma cells based on melanin synthesis and in vitro tyrosinase inhibitory activity and the anti-oxidant activity assays were performed using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2ʹ-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS); EKS exhibited strong anti-oxidant activities in both the assays. The expression of tyrosinase, tyrosinase-related protein 1, tyrosinase-related protein 2, and microphthalmia-associated transcription factor was decreased in a dose-dependent manner at mRNA and protein levels upon treatment with EKS. Notably, EKS did not affect the cell viability at all the EKS concentrations used in this study, indicating that EKS-mediated inhibition of melanin synthesis is not accompanied with cytotoxicity. Collectively, our findings demonstrate, for the first time, that EKS possesses anti-melanogenic and anti-oxidant activities, and suggest that further evaluation and development of EKS as a functional supplement or cosmetic might be useful for skin whitening and for reduction wrinkles.

Graph coloring is a manifestation of graph partitioning, wherein, a graph is partitioned based on the adjacency of its elements. Partitioning serves potentially as a compartmentalization for any structural problem. Vertex coloring is the heart of the problem which is to find the chromatic number of a graph. The fact that there is no general efficient solution to this problem that may work unequivocally for all graphs opens up the realistic scope for combinatorial optimization algorithms to be invoked. The algorithmic complexity of graph coloring is non-deterministic in polynomial time (NP) and hard. To the best of our knowledge, there is no algorithm as yet that procures an exact solution of the chromatic number comprehensively for any and all graphs within the polynomial (P) time domain. However, several heuristics as well as some approximation algorithms have been attempted to obtain an approximate solution for the same. Here, we present a novel heuristic, namely, the 'trailing path', which returns an approximate solution of the chromatic number within polynomial time, and, with a better accuracy than most existing algorithms. The ‘trailing path’ algorithm is effectively a subtle combination of the search patterns of two existing heuristics (DSATUR and Largest First), and, operates along a trailing path of consecutively connected nodes (and thereby effectively maps to the problem of finding spanning tree(s) of the graph) during the entire course of coloring, where essentially lies both the novelty and the apt of the current approach. The study also suggests that the judicious implementation of randomness is one of the keys towards rendering an improved accuracy in such combinatorial optimization algorithms. Apart from the algorithmic attributes, essential properties of graph partitioning in random and different structured networks have also been surveyed, followed by a comparative study. The study reveals the remarkable stability and absorptive property of chromatic number across a wide array of graphs. Finally, a case study is presented to demonstrate the potential use of graph coloring in protein design – yet another hard problem in structural and evolutionary biology.

This paper includes some new investigations and results for post quantum calculus, denoted by (p,q)-calculus. A chain rule for (p,q)-derivative is developed. Also, a new (p,q)-analogue of the exponential function is introduced and some its properties including the addition property for (p,q)-exponential functions are investigated. Several useful results involving (p,q)-binomial coefficients and (p,q)-antiderivative are discovered. At the final part of this paper, (p,q)-analogue of some elementary functions including trigonometric functions and hyperbolic functions are considered and some properties and relations among them are analyzed extensively.

In this paper we establish several Hermite-Hadamard type integral inequalities for hyperbolic p-convex functions. Applications for special means are provided as well.

In this paper, we introduce a new generalization of the Hermite polynomials via (p, q)-exponential generating function and investigate several properties and relations for mentioned polynomials including derivative property, explicit formula, recurrence relation, integral representation. We also de…ne a (p, q)-analogue of the Bernstein polynomials and acquire their some formulas. We then provide some (p, q)-hyperbolic representations of the (p, q)-Bernstein polynomials. In addition, we obtain a correlation between (p, q)-Hermite polynomials and (p, q)-Bernstein polynomials.

In this study, a graphene-doped porous silicon (G-doped/p-Si) substrate for low ppm H₂ gas detection by an inexpensive synthesis route was proposed as a potential noble graphene-based gas sensor material and to understand the sensing mechanism. The G-doped/p-Si gas sensor was synthesized by a simple capillary force-assisted solution dropping method on p-Si substrates, whose porosity was generated through an electrochemical etching process. G-doped/p-Si was fabricated with various graphene concentrations and exploited as a H₂ sensor operated at room temperature. The sensing mechanism of the sensor with/without graphene decoration on p-Si was proposed to elucidate the synergetic gas sensing effect generated from the interface between the graphene and p-type silicon.

The current generation of nuclear reactors are evolutionary in design, mostly based on the technology originally designed to power submarines, and dominated by Light Water Reactors. The aims of the GenIV consortium are driven by sustainability, safety and reliability, economics, and proliferation resistance. The aims are extended here to encompass the ultimate and universal vision for strategic development of energy production, the ‘perpetuum mobile’ – at least as close as possible. We propose to rethink nuclear reactor design with the mission to develop a system which uses no fresh resources and produces no fresh waste during operation as well as generates power safe and reliably in economic way. The results of the innovative simulations presented here demonstrate that, from a theoretical perspective, it is feasible to fulfil the mission through the reuse of spent nuclear fuel from currently operating reactors as the fuel for a new reactor. The produced waste is less burdensome than current spent nuclear fuel which is used as feed to the system. However, safety, reliability and operational economics will need to be demonstrated to create the basis for the long term success of nuclear reactors as a major carbon free, sustainable, and applied highly reliable energy source.

Customized wrist splints, particularly for upper extremity orthoses like wrist support braces, are commonly used across numerous clinical scenarios. However, the traditional process for producing personalized wrist splints is largely manual and highly dependent on the expertise of orthopedic specialists. This experience-based approach often leads to suboptimal outcomes, necessitating further refinement of the designs. Recent advancements in Additive Manufacturing (AM) have brought significant innovation to various industries, including orthopedics. This study aims to present a comprehensive methodology that integrates advanced design tools ,like 3D Scanning, with digital manufacturing techniques to produce tailored wrist splints. The produced hand brace aims to offer enhanced mechanical performance and comfort by precisely fitting an individual’s anatomy while minimizing material usage and weight. To achieve optimal design efficiency, the study explores the application of a Topology Optimization (TO) approach for design, while the manufacturing process utilizes Fused Deposition Modeling (FDM), an evolving technology within the Additive Manufacturing (AM) sector.