As an International Union for Conservation of Nature (IUCN) voluntary reviewer of the natural World Heritage sites nominations focusing on criteria (vii) superlative natural phenomena and (viii) geological history I had the opportunity of evaluating 13 nominations from 12 countries from 2009 - 2022 from the Central Highlands of Sri Lanka to the Vatnajokull National Park Iceland. An early appreciation of the natural history and landscapes were developed as a geologist studying, working and visiting various areas in the USA and Canada. Further experience, as an academic in Sri Lanka and Australia, where I also had the opportunity of various assignments and meetings that afforded field trips and study tours to many World Heritage sites in Asia, Africa, South America and Europe. In this paper, I highlight the following sites that were subject to IUCN World Heritage evaluations and their potential for geo-education: Central Highlands Sri Lanka, China Danxia, Ningaloo Australia, Trang An Vietnam, Lut Desert Iran, Barberton South Africa, Trondek Klondike Canada, Vatnajokull Iceland, Classic Karst Slovenia, Sof Omar Ethiopia, Ha Long Bay – Cat Ba Archipelago, Vietnam and Evaporitic Karst Caves of Northern Apennines, Italy. From these experiences it is apparent that this relevant topic, the conservation of nature, should be an important part of the geoscience’s study curriculum along with other social and environmental subjects.

5-Pentadecylresorcinol (C15) is a natural alkylresorcinol that has been shown to protect against complications caused by imbalanced nutrition. Although the exact mechanisms of beneficial activity of C15 are not known, we assume that the protective effects of C15 on metabolic health are mediated by their modulatory influence on the composition of the intestinal microbiota and functional activity. Cobamides and vitamin B12 are believed to be crucial modulators of mammalian gut ecosystems. We proposed that C15 may influence the representation of enzymes and pathways for vitamin B12 synthesis in the gut microbiome, providing compositional and functional changes in the microbial community. High-throughput metagenome sequencing of the contents of the small and large intestines of C57Bl6 mice fed a regular or high-fat diet with or without C15 supplementation was performed followed by reconstruction of the metabolic activity of the microbiota to clarify the role of C15 in vitamin B12 synthesis by the gut microbiota. It has been established that C15 significantly increases the representation of the cobalamin salvage pathway and enzymes in the microbiome of the large intestine of mice fed a high-fat diet. The genera Clostridium, AF12, and [Ruminococcus] had shown the highest number of correlations with enzymes for B12 synthesis and were negatively associated with the representation of probiotic bacteria. Therefore, the beneficial effect of C15 on the gut microbiota community can be achieved by modulating B12 synthesis that, in turn, serves as one of the key regulators of gut microbiota ecology.

Education is generally considered to be a great equalizer as well as a tool the young generation can use in becoming the nation’s future leaders. It is imperative that today’s young people are well equipped with good quality education to better lead a country into the future. As a consequence, it is also important that we find out the factors that affect the learning success of the youth, since knowing these factors, either positive or negative will help the government in designing programs that can help propagate the positives and rectify the negatives. This study utilized data from the elementary and high school students of a private educational institution in the Philippines. Multiple linear regression using lin-lin model was used to analyze the data. Results indicated both the over-all significance of the model and the absence of violations regarding the basic assumptions of CLRM. Three variables English proficiency, Math proficiency, and time spent in playing video games turned out to be significant. This study adds to the existing body of knowledge by showing that time spent in commuting between house and school can also at times to be used to study resulting and impacting Cumulative Grade Point Average positively.

Large language models have recently made significant progress in natural language processing, and there is observation that these models exhibit reasoning abilities when they are sufficiently large. This has sparked considerable research interest since reasoning is a hallmark of human intelligence that is widely considered missed in artificial intelligence systems. Due to large size of these models, evaluation of LLMs’ reasoning ability is largely empirical. Creating datasets to evaluate the reasoning ability of LLMs is therefore an important area of LLM research. A key open question is whether LLMs reason or simply recite memorized texts they have encountered during their training phase. This work conducts simple experiments using Cheryl’s Birthday Puzzle and Cheryl’s Age Puzzle and their variants created in this work to investigate whether LLMs recite or reason and discovers that LLMs tend to recite memorized answers for well-known questions, which appear more frequently on the internet, even though such answers may not be sensible for the modified versions of the questions. When presented with less well-known questions, it is observed that LLMs answer with correct reasoning more frequently. A possible inference is that LLMs tend to reason on less well-known questions but recite memorized answers on popular questions. As a result, to accurately evaluate the reasoning ability of LLMs, it is essential to create new datasets to ensure that LLMs are elicited to truly use their reasoning ability to generate responses to the presented questions. In view of the finding, this work proposes a new dataset comprising of unseen questions requiring semantic and deductive logical reasoning skills to elicit reasoning ability from LLMs. The proposed evaluation framework is based on the intuition that some questions or puzzles can only be answered through the mastery of reasoning needed for situational awareness, and the dataset consists of 84 logical reasoning questions on room assignment subject to constraints. The proposed evaluation framework has several desirable properties, including resilience to training data contamination, ease of response verification, extensibility, usefulness and automated test case generation. This work then applies the proposed dataset to evaluate the reasoning ability of state-of-the-art LLMs, including GPT-3, GPT-4, Llama-3.1, Gemini-1.5 and Claude-3.5, and compare their performance with the performance of human intelligence on the dataset.

Steel surface protection with hard coatings is essential in the metalworking industry, yet developing high-performance hard coatings still remains a challenge. Quaternary nitride coatings, particularly TiAlSiN, have been extensively studied, but commercial TiAlSiN coatings vary widely, and there is a lack of consistent data. This study presents findings on the development and evaluation of TiAlSiN and TiAlSiN/TiN thin films, with an 800 nm thick TiAlSiN top coating and a 100 nm thick TiN mid-coating. The films were deposited on C120 tool steel discs via reactive DC magnetron sputtering. Ti and TiAlSi 75–20–5 (at.%) disc-shaped targets (50.8 mm diameter × 6.3 mm thickness), fabricated by our team through spark plasma sintering, were used for the sputtering process. Coatings were grown on smooth steel substrates heated to 300 °C, resulting in a uniform micro-structure with nanoparticles of globular (TiN) or pyramidal shape (TiAlSiN), as evidenced by SEM analysis. Nanoindentation tests showed superior mechanical properties for all coatings compared to the steel substrate. Micro-scratch tests indicated better scratch resistance for TiAlSiN/TiN bilayer (BL) coatings than for TiAlSiN single-layer (SL) coatings. Electrochemical impedance spectroscopy tests in a 3.5 wt.% NaCl solution revealed that the BL coatings demonstrated superior corrosion resistance compared to the SL coatings, even after thermal aging at 800 °C for 1 hour. The superior properties of the synthesized TiAlSiN/TiN films recommend them as protective coatings for tool steel surfaces.

The SOC (State of Charge) in Lithium-ion battery packs refers to determining a battery's current energy level or capacity at a given time. SOC is important for many battery-operated systems since it shows how much energy is available. In the earlier stage SOC is calculated by different techniques such as Coulomb counting, open-circuit voltage, Kalman filters, Data-Driven Approaches, and Real-Times Updates so these all methods are used to calculate the SOC Estimation in battery packs. In recent years, these old methods have had some errors and accuracy malfunctions in SOC estimation in battery packs. The SOC estimation errors occur on Two-Wheeler, Three-Wheeler, and four-wheeler of Electric Vehicles (EV). To Overcome this problem in current years the AI&ML Algorithms Methods are applied everywhere related to Accuracy, Solutions & All. To increase the accuracy of SOC Estimations we are going to use Machine Learning Algorithms to improve the SOC in Machine Learning there are various methods such as supervised, unsupervised, and reinforcement. Of these three methods, one of the best methods is to select the Algorithms is apply to the Battery packs to get accurate SOC Estimations. In Machine Learning, we select the Supervised Learning Algorithms. Currently, the project will focus on the use of a Supervised Machine Learning Algorithm which includes an Extra Trees Regressor, Bagging Regressor, K-Neighbors Regressor, Decision Tree Regressor, and Random Forest Regressor for SOC Estimation. In this, we will develop algorithms applied to Lithium-ion Battery Packs to accurately the SOC estimates. In conclusion, the algorithms we will develop by using Machine Learning are compared with the algorithms and analytical Models.

Serotonin (5-hydroxytryptamine: 5-HT), a neurotransmitter that regulates mood in the brain and signaling in the gut, has receptors throughout the body that serve various functions. Selective serotonin reuptake inhibitors (SSRIs) are used to treat depression, but their efficacy is uncertain. Depression is often associated with early gastrointestinal symptoms. Gut disorders such as functional dyspepsia (FD), irritable bowel syndrome (IBS) and inflammatory bowel disease (IBD), including ulcerative colitis (UC) and Crohn's disease (CD), are linked to elevated serotonin levels. In this review, we would like to discuss the approach of using serotonin as a biomarker for gut-brain and body-wide organ communication may lead to the development of preventive and innovative treatments for gut-brain disorders, offering improved visibility and therapeutic monitoring. It could also be used to gauge stress intensity for self-care and mental health improvement.

Electrowetting display (EWD) device is a new type of electrowetting-on-dielectric (EWOD) equipment which can achieve a paper-like display effect under the control of electric field. In this microfluidic system, the stability of grayscale could be affected by various factors, such as the physicochemical properties of materials, device structure, and electric field distribution. To improve the grayscale stability of active matrix electrowetting displays (AM-EWDs), the impact of different polarities of driving voltage on oil backflow was investigated in this study. Based on the driving principles of AM-EWD, an optimized inter-frame bipolar reset driving waveform was designed to overcome oil backflow. The proposed driving waveform maintained the stability of the oil state by periodically and rapidly releasing trapped charges in the dielectric layer through a reverse driving voltage. Additionally, the effect of feed through voltage on the pixel driving voltage was eliminated by compensating for the driving voltage on common electrode. Finally, the performance of the designed driving waveform was evaluated with a 6-inch AM-EWD driving platform. Compared to the conventional unipolar reset driving waveform, the backflow speed decreased by 2.70 a.u./s. The standard deviation of the display luminance was also reduced by 11.24 a.u. Experimental results indicated that both the oil backflow speed and the fluctuation range of luminance were effectively suppressed by the proposed driving waveform.

The technological revolution has contributed significantly to environmental and social issues worldwide. In higher education institutions, there is a theoretical gap in systematic reviews on the integration of digital transformation into sustainability. This systematic review of the literature aims to address this gap by exploring how digital transformation improves sustainability in higher education institutions, identifying emerging trends and best practices for effective strategies. Using the PRISMA guidelines, the study conducted a comprehensive search in the Scopus database, producing 1,686 publications from 2019 to 2024. The findings reveal a widespread awareness of digital technology integration but highlight a lack of consensus on sustainable integration strategies. Furthermore, the results demonstrate that educational achievements can be enhanced through tools and methodologies that align with the Sustainable Development Goals of the United Nations. The analysis identifies three primary domains: sustainability capabilities enabled by digital transformation, innovative sustainable approaches, and the conceptualisation of sustainability in higher education. The incorporation of digital tools, such as AI chatbots, institutions foster innovation and achieves sustainability objectives, thus transforming teaching and learning approaches. This review contributes significantly to understanding the role of digital transformation in promoting a sustainable and digitally enabled future in higher education.

The present study deals with the transplantation of mature Argan trees (Argania spinosa L. Skeels) and focuses on optimizing survival rates depending on the seasons, the type of shoot pruning applied to the trees and preconditioning treatments consisting of root pruningand watering for a few months before transplanting. So far, the transplantation of this species at the adult stage has not received enough attention in spite of its ecological and socio-economic importance for the regions where it thrives. The results obtained show that transplanting in summer, autumn and winter resulted in survival rates exceeding 50%. The Argan trees transplanted in spring hardly achieved 10% survival. However, the total cutback of the crown induced survival improvement that reached a rate greater than 70% for summer, autumn and winter, and 50% for spring. Watering alone or combined with root pruning for 6 months helped improve the recovery rate but only when carried out in autumn with transplantation in spring. On the other hand, when these pre-treatments were applied in the spring to transplant the trees in summer, the recovery rate was not improved.

This study checked whether vitamin D (Vit-D) supplementation improves the efficacy of resistance training (RT) in terms of increasing muscle strength and lean body mass (LBM) and influencing cardiorespiratory fitness (VO2max) in Vit-D insufficient middle-aged healthy men. Participants (n = 28) were quasi‐randomly assigned to one of the two groups, which, in a double‐blind manner, supplemented their diet daily with either Vit‐D (8000 IU; VD) or placebo (PLC) during participation in a 12‐week supervised RT program. During the intervention, serum Vit‐D concentrations increased 2.6‐fold (p < 0.001) in the VD group, while no changes occurred in the PLC group. Muscle strength gains (p < 0.001) as measured in seven exercises performed on RT equipment and increases (p < 0.001) in LBM were similar in the two groups. Total fat mass, percent total fat, and percent android fat decreased (p < 0.05) to a similar extent in both groups, but there was no change in VO2max in either group. In conclusion, in healthy Vit‐D insufficient middle-aged men engaged in resistance training, Vit‐D supplementation increases serum 25(OH)D levels but does not enhance gains in muscle strength and LBM or decreases in fat mass and fat percentage and does not affect cardiorespiratory fitness.

Planar catechin (PCat), a natural antioxidant with a fixed 3D catechin structure on a plane, exhibits radical-scavenging activity approximately five times stronger than the conventional catechin. We synthesized a compound, PCat–TrOH, by binding Trolox (TrOH), an α-tocopherol analog, to PCat to enhance its antioxidant effect against oxidative stress, such as lipid peroxidation. TrOH shows radical-scavenging activity about 6.5 times greater than PCat, and PCat–TrOH exhibited a similar level of radical-scavenging activity to TrOH. Additionally, PCat–TrOH demonstrated twice the radical-scavenging activity against reactive oxygen species compared to PCat or TrOH. This compound is also expected to exhibit an excellent antioxidant effect against lipid peroxidation caused by radical chain reactions, through interactions with vitamin C, similar to that in the case of α-tocopherol.

Forty percent of patients with acute coronary occlusion myocardial infarction (OMI) do not present with STEMI criteria, which delays their treatment and increases morbidity and mor-tality. The need to identify these patients promptly is crucial, and this sets the stage for the pro-posed reclassification. Many of these patients can be identified by other ECG and clinical fea-tures. Background/Objectives: We sought to evaluate STEMI/NSTEMI cases that result in OMI and the consequences of delayed revascularization immediately among NSTEMI patients who have ACO (NSTEMI-OMI). Methods: The study is a retrospective analysis conducted on 334 pa-tients who underwent coronary angiography for acute coronary syndrome at UHC ‘‘Mother Te-resa,’’ Tirana, Albania, during January-May 2023. OMI was defined as an acute culprit lesion with TIMI 0-2 flow, or TIMI 3 flow with highly elevated troponin (cTnI>10.0 ng/mL, hs-cTnI>5000 ng/L). Ejection fraction (EF), total ischemia time, hospital day stay and complications were com-pared between groups. Results: There were 334 patients included of whom NSTEMI-OMI were 98 patients (29.3%) of patients with ACS. 96 patients (40%) of OMI patients did not fulfill the STEMI criteria. Only 11 patients (11%) of STEMI(-)OMI had PCI performed within the first 12 hours vs 76 patients (77%) of STEMI(+)OMI, p<0.001. There was no difference in the percent of patients requiring PCI between the STEMI(+)OMI 98 patients (93%) and STEMI(-)OMI 87 patients (89%) (p<0.001). The overall in-hospital mortality was 19 patients (5.7 %), with subgroup mortality of 14 patients (4.2%) STEMI(+)OMI, two patients (0.6%) STEMI(+) NOMI, three patients (0.9%) STEMI(-)OMI, 0% STEMI(-)NOMI, (p=0.013). Patients with mechanical complications were: 67 patients (46.8%) STEMI(+)OMI and 45 patients (46.4%) STEMI(-)OMI. 26 patients (18.5%) STEMI(+)OMI and 13 patients (13.1%) STEMI(-)OMI developed electrical complications. Conclusions STEMI(-)OMI patients had significant delays in catheterization, yet had angiographic findings, rate of PCI, and complications similar to STEMI(+)OMI. These data add further support to refocusing the paradigm of acute MI to improve recognition and rapid reperfusion of all OMIs, rather than only those with STEMI criteria.

Recently concluded, large-scale cancer genomics studies involving multiregion sequencing of primary tumors and paired metastases appear to indicate that many or most cancer patients have one or more “clonal" mutations in their tumors. Clonal mutations are those that are present in all of a patient’s cancer cells. Clonally mutated proteins can potentially be targeted by inhibitors or E3 ligase small molecule glues, but developing new small molecule drugs for each patient is not feasible currently. Achilles Therapeutics is currently the only company specifically targeting clonal mutations. However, they are doing so with tumor-derived T cells. To address the potential limitations of immunotherapy, I have devised another approach for exploiting clonal mutations, which I call “Oncolytic Vector Efficient Replication Contingent on Omnipresent Mutation Engagement” (OVERCOME). The ideal version of OVERCOME would likely employ a bioengineered facultative intracellular bacterium. The bacterium would initially be attenuated, but (transiently) reverse its attenuation upon clonal mutation detection.

A degree in physiology in Nigeria offers a enormous opportunities that many undergraduates may be unaware of.This article explores different career paths available to physiology undergraduate and graduates in Nigeria. It outlines various fields within clinical and healthcare settings, research and academia, biotechnology and pharmaceuticals, and even alternative careers. It also details specific specializations within clinical physiology, including cardiovascular, respiratory, neurophysiology, sleep, gastrointestinal, and renal physiology.The article emphasizes the importance of gaining practical experience through internships, volunteer work, and networking to equip physiology them with essential skills for job market.

Field surveys were conducted in October 2022 and March 2023 (60 fields each year) to determine the prevalence, incidence and severity of cassava mosaic disease (CMD) and cassava brown streak disease (CBSD), whitefly numbers and incidence of cassava green mite (CGM) in six counties of western Kenya. A total of 29 varieties were recorded out of which 13 (45%) were improved. The improved varieties were present in 62% of the 120 fields sampled with the most predominant MM96/4271 found in 36% of the fields. There was more CMD infection in 2022 with a prevalence of 68%, incidence of 26.4% and severity score of 2.7, while in 2023 these parameters were 60%, 10.1% and 3.0 respectively. CMD incidence attributed to planting infected cuttings was 20.1% in 2022 but dropped to 4.3% in 2023 while for whitefly-borne infection incidence remained 4.4% for both years. CMD incidence was significantly lower (5.9%) for improved varieties than it was for local varieties (35.9%) in contrast to CBSD incidence which did not differ significantly between improved (2.3%) and local varieties (9.7%). However, the improved variety MM96/4271 was among the varieties most affected by CBSD, with an incidence of 6.3%. Overall, CBSD in 2022 had a prevalence of 20%, incidence of 6.4% and severity of 2.7, while in 2023 these parameters were 12%, 4.1% and 2.7 re-spectively. Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV) were both detected. Most infections were single CBSV infections (82.9%), followed by single UCBSV (34.3%) and coinfection with both viruses (16.7%). Whiteflies were more abundant in 2023, in which 28% of the fields had super-abundant populations of >100/plant, compared to 5% in 2022. Molecular characterization based on mtCOI sequencing identified the whiteflies as Bemisia tabaci. KASP SNP genotyping designated 92.8% of the specimens as SSA-ECA for 2022 while it was 94.4% for 2023, compared to 72% for an earlier sample collection in western Kenya in 2017. CGM prev-alence was 95% with a severity of 2.7 in both years, but incidence was lower in 2022 (65.4%) compared to 2023 (79.9%). This study demonstrates that the majority of farmers are cultivating improved varieties, although cassava viruses, whiteflies and cassava green mites are still a threat. There is a need to develop and deploy integrated management strategies against these pests which will include components of resistant varieties, clean seed and control of whiteflies and CGM.

We define the function $Col: \mathbb{N} \to \mathbb{N}$ as the Collatz function, given by $3n + 1$ if $n$ is odd and $\displaystyle\frac{n}{2}$ if $n$ is even \cite{Lagarias1990}. The conjecture postulates that for any positive integer, at some point, its iteration will reach 1, or equivalently, every orbit will fall into the periodic cycle $\{4, 2, 1\}$. Two conditions would invalidate the conjecture: the existence of a divergent orbit or the presence of another cycle. In 2019 Terence Tao \cite{tao} proved that almost all orbits converge to the trivial cycle of $\{1,4,2\}$, in this work we will prove the non-existence of divergent orbits. The central idea is to decompose the dynamic system $Col$ into a binary dynamic system, generated by different compositions of two functions. This differs from a typical dynamic system, which is generated by the iteration of a single function. We consider the system generated by the functions $\theta, \psi: \mathbb{R} \to \mathbb{R}$, defined as $\displaystyle\theta(x) = \frac{x}{2}$ and $\displaystyle\psi(x) = \frac{3x + 1}{2}$, denoted as $\langle \theta, \psi \rangle$. We examine sequences of functions in $\langle \theta, \psi \rangle$ of the form $S_k(x) = s_k \circ S_{k-1}(x)$ with $s_k \in \{\theta, \psi\}$. We define a function that assigns to each element of these sequences an integer, called the minimum value positive integer or simply the minimum value. This corresponds to the smallest positive integer $n$ such that $S_k(n)$ is an integer. As we will prove later, the minimum value is monotonically increasing, meaning that increasing the terms of the sequence will never result in a value lower than the previous one. Based on this behavior, we distinguish two types of sequences: stable ones, where the minimum value is constant from a certain point, and unstable ones, where the minimum value is divergent. The main result for unstable sequences is that when the slope of the sequence is divergent, the sequence is unstable. From this result, we can prove that there are no divergent orbits for the function $Col$.

Many young people are reluctant to seek support for mental health concerns and a preference for self-reliance has been identified as a key barrier. Yet, the conceptualisation and measurement of self-reliance is not well understood. This study examines the meaning of self-reliance as it affects young people’s help-seeking, with an emphasis on the role of trust (both in self and in others). 30 Australian young people aged 18-25 years were interviewed. Reflexive thematic analysis, using both inductive and deductive approaches, was used to construct themes about the relationships between trust, self-reliance, and help-seeking for young people. Participants identified that both self-reliance and help-seeking exist on a continuum from insufficient self-reliance to extreme self-reliance and excessive help-seeking to unwillingness to seek help. Trust was a key component of self-reliance, and a balance between trust in self and trust in others is necessary for self-reliance to be adaptive and appropriate help-seeking to occur. To maintain this balance, young people felt that a level of self-awareness was necessary. A high level of trust in self is considered to increase self-reliance, whereas a high level of trust in others increases help-seeking behaviours. Understanding the role of trust in self-reliance informs developmentally appropriate ways to address self-reliance as a barrier to mental health help-seeking for young people.

In recent decades, both in Italy and internationally, the phenomenon of abandoned industrial buildings has grown considerably, causing inevitable social, urban and economic impacts. At the same time, the cultural debate has increased awareness of the problem and the strategic role that abandoned industrial sites can play in responding to new needs. This contribution analyzes the dismantling process of the Akragas Montedison factory in Porto Empedocle, Sicily, examining the evolution of disused industrial areas from the 20th century to the present day and the possibilities of reconversion for appropriate reuse.

Leishmania spp. commonly infects phagocytic cells of the immune system, particularly macrophages, employing various immune evasion strategies that enable their survival by altering the intracellular environment. In mammals, these parasites establish persistent infections by modulating gene expression in macrophages thus interfering with immune signaling and response pathways ultimately creating a favorable environment for the parasite survival and reproduction. In this study, our objective was to use data mining and subsequent filtering techniques to identify the genes that play a crucial role in the infection process of Leishmania spp. We aimed to pinpoint genes that have the potential to influence the progression of Leishmania infection. To achieve this, we exploited prior, curated knowledge from major databases and constructed 16 datasets of human molecular information consisting of coding genes and corresponding proteins. We obtained over 400 proteins, identifying approximately 200 genes. The proteins coded by these genes were subsequently used to build a network of protein-protein interactions, which enabled the identification of key players. Approximately 10% of these genes were then selected for biological validation. THP-1 cells, a line of human macrophages, were infected with L. major in vitro for the validation process. We observed that L. major has the capacity to impact crucial genes involved in the immune response, resulting in macrophage inactivation and creating a conducive environment for the survival of Leishmania parasites

Recent developments in flexible printed heaters (FPH) for wearable thermal applications, driven by the advancement of printed electronics, show great promise in revolutionizing patient care through the development of wearable flexible heaters for medical applications. Wearable heaters with high thermal stability, heat uniformity, safety, flexibility, comfort, biocompatibility, and power efficiency are desirable for stand-alone medical thermotherapy applications. This paper reviews recent advancements in the design of FPHs for wearable thermal applications. Materials for FPHs, fabrication methods, designs, temperature control mechanisms, medical applications, and performance analysis of specific FPHs are all thoroughly discussed. Materials for FPHs, such as conductive and substrate materials, have received special attention, along with the heater design parameters. Finally, the challenges and future directions for developing FPHs for wearable medical applications are addressed.

This article develops duality principles and numerical results for a large class of non-convex variational models. The main results are based on fundamental tools of convex analysis, duality theory and calculus of variations. More specifically the approach is established for a class of non-convex functionals similar as those found in some models in phase transition. Finally, in some sections we present concerning numerical examples and the respective softwares.

Secondary envelopment of the human cytomegalovirus (HCMV) is a critical but not well-understood process that takes place at the cytoplasmic viral assembly complex (cVAC) where nucleocapsids acquire their envelope by budding into cellular membranes containing viral glycoproteins. Previous studies presented controversial results regarding the composition of the viral envelope, suggesting trans-Golgi and endosomal origins, as well as intersections with the exosomal and endocytic pathways. Here, we investigated the role of endocytic membranes for the secondary envelopment of HCMV by using wheat germ agglutinin (WGA) pulse labelling to label glycoproteins at the plasma membrane and to follow their trafficking during HCMV infection by light microscopy and transmission electron microscopy (TEM). WGA labelled different membrane compartments within the cVAC, including early endosomes, multivesicular bodies, trans-Golgi, and recycling endosomes. Furthermore, TEM analysis showed that almost 90% of capsids undergoing secondary envelopment and 50% of enveloped capsids were WGA-positive within 90 minutes. Our data reveal extensive remodeling of the endocytic compartment in the late stage of HCMV infection, where the endocytic compartment provides an optimized environment for virion morphogenesis and serves as the primary membrane source for secondary envelopment. Furthermore, we show that secondary envelopment is a rapid process in which endocytosed membranes are transported from the plasma membrane to the cVAC within minutes to be utilized by capsids for envelopment.

Esophageal cancer (EC) is one of the most common malignant tumors worldwide, and its two major types, esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC) present a severe global public health problem with an increasing incidence and mortality. Established risk factors include smoking, alcohol consumption, and dietary habits, but recent research highlights the substantial role of oral microbiota in EC pathogenesis. This review explores the intricate relationship between microbiome and esophageal carcinogenesis, focusing on eight significant mechanisms: chronic inflammation, microbial dysbiosis, production of carcinogenic metabolites, direct interaction with epithelial cells, epigenetic modifications, interaction with gastroesophageal reflux disease (GERD), metabolic changes, and angiogenesis. Certain harmful bacteria, such as Porphyromonas gingivalis and Fusobacterium nucleatum, are specifically implicated in sustaining irritation and tumor progression through pathways including NF-κB and NLRP3 inflammasome. Additionally, the review explores how microbial byproducts, including short-chain fatty acids (SCFAs) and reactive oxygen species (ROS), contribute to DNA harm and disease advancement. Furthermore, the impact of reflux on microbiota composition and its role in esophageal carcinogenesis is evaluated. By combining epidemiological data with mechanistic understanding, this review underscores the potential to target microbiota-immune system interplay for novel therapeutic and diagnostic strategies to prevent and treat esophageal cancer.

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 study highlights the importance of quantifying groundwater resources for the Monahans and Kermit dune fields in the northern Chihuahua Desert, West Texas USA as potential contributors to the regional Pecos Valley Aquifer (PVA). Sedimentary architecture models of these dune fields show perched aquifers with water tables 1-10m below the surface and southwestward groundwater flow sub-parallel to a Pleistocene/Pliocene aquitard. Sinkhole-like features into the top of the aquitard are infilled with the thickest occurrences of aeolian sand. Groundwater recharge occurs from the enhanced capture of precipitation on mostly bare active dunes where infiltration rates >250mm/hr. The deuterium and oxygen isotopic ratios for groundwater from the Kermit and Monahans dune fields show pronounced evaporative isotopic depletion and less isotopic variability than corresponding rainfall, particularly for deuterium values. Groundwater from a shallow central well in the Kermit dune field yielded contemporary 14C activity (Fm =1.02), indicating contributions from recent precipitation. In contrast, more evolved 14C values at the western margin (FM=0.84) and at 30m below the surface (FM=0.76), similar to proximal Fm values from the PVA (0.89-0.82), may indicate dissolution of older (&gt; 100 ka) DIC from buried playa-lake sediments and carbonate-soils with groundwater flux to the southwest, and less direct atmospheric influence. The perched aquifers of the Monahans and Kermit dune fields contain water volumes > 0.1 km3 and may contribute up to 9% of the total annual recharge to the PVA.

Artificial Intelligence (AI) and Machine Learning (ML) are rapidly advancing. These technologies have significantly impacted the consumer goods market, including the smart footwear industry. AI and ML are extensively utilized in the design and production of smart and agile footwear. There are various methods for manufacturing smart footwear, which can be categorized based on their applications. These include medical and healthcare smart footwear, assistive footwear for individuals with impairments, footwear designed for navigation in unfamiliar areas, foot-wear for studying foot movements and gait analysis, safety footwear, anti-skid footwear, foot-wear for the elderly, army shoes, and energy-harvesting footwear, among others. These smart shoes enable real-time patient monitoring and provide appropriate suggestions for their care. Additionally, smart footwear can be classified based on the tools and techniques used in their production, as well as the sensors and Internet of Things (IoT) devices integrated into them. This paper reviews the various tools and techniques used in the creation of smart footwear for dif-ferent applications.

Co-management is increasingly recognized as an effective approach of forest governance while recognizing local people's forest dependency and traditional rights. Moreover, co-management is expected to positively impact forest cover and ecosystem health. Bangladesh, facing a rapid decline in forest cover, has one of the lowest per capita forest areas worldwide. For quite a while, co-management practices have been used to improve forest cover and the livelihoods of forest-dependent people in Bangladesh. Several studies have assessed the efficacy of co-management in different protected areas in Bangladesh from livelihood, social, and cultural aspects. However, the overall changes in forest cover due to co-management from the very beginning of co-management initiatives in the country have been overlooked. We used remotely sensed Landsat images to assess the changes in forest cover and overall land use in five forest protected areas where co-management was piloted. Three major vegetation indices (NDVI, EVI, and MSAVI) were examined to ensure the study's robustness. This study aims to assess the scope and weaknesses of the current policy that incorporates co-management in the country's first five protected areas (SNP, LNP, RKWS, TWS, and CWS), which were brought under co-management in 2003, and compare the efficacy of the co-management relative to non-comanaged protected areas (RRF). The land cover analysis based on NDVI, MSAVI, and EVI values indicated dominant dense forest coverage (41–71%) across five protected areas. During the co-management period (2004–2015), there was a significant decrease in the dense forest proportion, with slopes ranging from -3.7 to -0.96. Similarly, the RRF showed a decreasing pattern, with the slope of the decreasing trendline ranging from -0.48 to -0.62 across the three indices. Agriculture and forest-agriculture mosaics showed a significant increase, with varying slopes among protected areas in both co-managed and non-comanaged sites. Pixel-to-pixel changes revealed dynamic shifts in vegetation indices, and Global Forest Watch data highlighted forest cover losses, notably in CWS (158.77 ha) and SNP (0.49 ha).

The color match between natural teeth and restorative materials is critical in dentistry for achieving aesthetic outcomes. Various factors such as light source, brightness, opacity, and visual perception influence teeth color. The intrinsic color of dental structures is determined by light absorption and scattering within the tooth material. Recent advancements in CAD/CAM systems have improved treatment approaches in prosthodontics, particularly with the introduction of new temporary materials. However, data on the color stability and masking ability of these CAD/CAM materials is limited. Telio® CAD-Temp and VITA CAD-Temp® blocks were cut into slices and polished. Composite resin specimens were prepared using a custom-designed metal resin former and light-cured. A healthy bovine incisor was used to create another type of base. Samples were paired randomly and assigned to experimental groups based on base type and thickness (n=30). Samples were stored in a controlled environment for 24 hours before color evaluation using an EasyShade® V spectrophotometer. Color difference (ΔE) was calculated using L*, a*, and b* values. Statistical analyses included Shapiro-Wilk test, Levene’s test, and three-way ANOVA, with post-hoc comparisons using the Bonferroni method (α=0.05). ΔE was classified according to perceptibility (PT=1.2) and acceptability (AT=2.7) values.

Background and Objectives: The new molecular classification of endometrial cancer continuously changes the management of the disease in every day clinical practice. Lately, FIGO released a new staging system for endometrial cancer, which incorporates molecular sub-stages and subdivides further early-stage disease. The aim of this study is to investigate the differences between the two FIGO staging systems and evaluate the prognostic precision of the new one. Materials and Methods: We retrospectively analyzed the records of patients with endometrial cancer that were fully treated in the 1st Department of Obstetrics-Gynecology, 2012-2023. Patient characteristics, oncological outcome and follow-up information were collected. The primary outcomes were the stage shifts and the survival data. Results: 67 (15.5%) patients had a stage shift and the majority of them concerned early-stage disease and specifically up-shift from 2009 stages IA and IB to 2023 stage IIC. Concerning, survival a better median and 5-year PFS was present in Stage II disease and when compering the prognostic precision of the two FIGO staging systems no significant difference was present. Conclusions: The new 2023 FIGO staging system better distinguishes early-stage endometrial cancer into its prognostic groups and seems to be as precise as the old 2009 FIGO staging system.

As with all new fields of discovery, work on the biological role of G-quadruplexes (GQ) has produced a number of results that at first glance are quite baffling, sometimes because they do not fit well together, but mostly because they are different from commonly held expectations. Like other classes of flipons, those that form G-quadruplexes have a repeat sequence motif that enables the fold. The canonical DNA motif (G3N1-7)3G3, where N is any nucleotide and G is guanine, a feature that is under active selection in avian and mammalian genomes. The involvement of G-flipons in genome maintenance traces back to the invertebrate C. elegans and to ancient DNA repair pathways. A role for GQ in transcription is supported by the observation that yeast Rap1 protein binds both B-DNA, in a sequence-specific manner, and GQ, in a structure-specific manner, through the same helix. Other sequence-specific transcription factors (TF) also engage both conformations. RNAs can also modulate GQ formation in a sequence-specific manner and engage the same cellular machinery as localized by TF, linking the ancient RNA world with the modern protein world. The coevolution of both sequence-specific RNA and proteins is supported by studies of early embryonic development, where the transient formation of G-quadruplexes potentially coordinates the epigenetic specification of cell fate.

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

With the increasing use of automatic transmissions in passenger vehicles, there is a growing need for improved gear shifting control strategies that aim to enhance performance and fuel efficiency. This paper introduces a knowledge-based fuzzy control system designed specifically for automatic transmissions in light vehicles. The proposed system utilizes a fuzzy inference system as the controller, enabling the emulation of the driver’s perceptions during the gear shifting process. Consequently, the input signal consists of variables that are either sensitive to or observable by the driver, while the output represents the selected gear. The paper evaluates three distinct control strategies, each based on different inputs. These inputs include the longitudinal velocity of the vehicle, the angular velocity of the engine, or a combination of both, along with the time-derivative of the throttle valve opening. Through the evaluation, it is observed that the combination of inputs yields significantly improved performance. Therefore, the methodology presented in this paper demonstrates that the combined input approach is more effective for gear shifting control.

The production and consumption of plastic bottled water have several negative environmental impacts worldwide. The EU countries have adopted strategies and programs to reduce single-use plastics, including PET bottles. A key aspect of designing effective policies is understanding consumer behaviour. To identify barriers and motivations for drinking tap and bottled water, we conducted a nationally representative questionnaire survey among 3,411 respondents in the Czech Republic in 2022. The results reveal that people aged 18-34 appear to be moderate consumers of bottled water and very frequent consumers of tap water. Bottled water consumption tends to be less frequent among people with higher education, while tap water consumption is less frequent among people with lower incomes. The most important factors that explain the frequency of drinking bottled and tap water are taste perception, health concerns and habit. Health concerns about tap water and the unpleasant taste of tap water influence higher consumption of bottled water and vice versa. People with a strong habit of drinking tap water are less likely to consume bottled water. The constructs from the Theory of Planned Behaviour were statistically significant. The results can guide decision-makers in promoting tap water to consumers. To encourage tap water drinking, we suggest measures to increase the availability of tap water in public places in conjunction with campaigns targeting taste and health perception and the habit of drinking tap water.

Ciliated microeukaryotes are insufficiently integratively investigated despite their ubiquity and ecological significance. The morphology and ontogenesis of a new Stichotrichida species, Pseudosincirra binaria sp. nov., and the known Perisincirra paucicirrata Foissner et al., 2002, are here studied using live observations and protargol staining methods. The new species is characterized by having one buccal, one parabuccal and three frontal cirri, one frontoventral row extending to the posterior half of the cell, three left and two right marginal rows, three dorsal kineties with the left kinety conspicuously bipartite, along with one caudal cirrus at the rear end of each kinety. During morphogenesis, there exist five frontal-ventral cirral anlagen with anlagen IV and V forming frontoventral row in the proter, and four anlagen with anlage IV generating frontoventral row in the opisthe. The anlagen for marginal rows and dorsal kineties develop intrakinetally. The new population of Perisincirra paucicirrata corresponds well with other isolates regarding morphology and cell development. Phylogenetic analyses based on the small subunit ribosomal gene sequence data revealed that both Perisincirra and Pseudosincirra are deeply clustered in the clade consisting of species from the genera Deviata and Heterodeviata, supporting the placement of both genera into the family Deviatidae Foissner, 2016.

We evaluated the immunogenicity persistence of different immunization regimens of freeze-dried human rabies vaccine (Vero cells) in the 10–60 years age group of the Chinese population. Based on phase III clinical trials of Vero cells, participants who completed the full course of immunization were continuously enrolled in four-dose trial, five-dose, and five-dose control groups. Venous blood samples were collected 12 months after completion of the full immunization for rabies virus-neutralizing antibody (RVNA) testing, and the antibody-positive rate and geometric mean concentration (GMC) were calculated. Analysis of variance was used to compare three groups. The four-dose trial, five-dose trial, and five-dose control groups included 200, 186, and 214 participants, respectively. Twelve months after full immunization, the overall RVNA-positive rates were 97.00%, 93.55%, and 94.86% in the four-dose trial, five-dose control, and five-dose trial groups, respectively. The post-immunization RVNA GMCs values were 2.50, 2.05, and 2.04 IU/mL, respectively, with no statistically significant differences between them. Twelve months after full immunization, the overall RVNA-positive rate remained high, demonstrating satisfactory immunogenicity persistence for both immunization regimens.

When a circular body is immersed in a fluid, its interaction with the surrounding water leads to the formation of waves and ripples. This fascinating phenomenon is primarily driven by the fluid encountering a crucial point on the body, known as the complex centre of pressure (iCoP). This point acts as a threshold that instigates disturbances in the fluid, illustrating why the body affects the fluid dynamics even before it is fully submerged. The concept of the iCoP introduces a new dimension to our understanding of fluid dynamics defined by the equation as . The iCoP is symmetric and dependent solely on the diameter of the body, which enables it to pinpoint where fluid disturbances originate in the water. The immersion depth and oscillatory behaviour of the circular body are described by . Here, signifies that the body should be half-immersed, with its centre positioned halfway below the waterline, while the term indicates that the body’s oscillatory movement, with an amplitude of , causes the body to move up and down from this equilibrium position which makes the body not to be totally half immersed as indicated by . Consequently, the immersion depth varies and reflecting both partial immersion and dynamic oscillation. The real part of the iCoP reveals critical locations for fluid displacement, which leads to wave formation, while the imaginary part uncovers the phase shifts that describe the body’s dynamic interaction with fluid motion.

A review discusses recent research findings spanning the last two decades concerning ultrasonic technologies applicable to the oil, gas, and coal sectors. Various experiments conducted in laboratories have demonstrated the efficacy, cost-effectiveness, and environmental friendliness of ultrasound in recovering and processing oil, bitumen, coal, and oil shale. Ultrasound enhances formation permeability, coal gas permeability, and oil viscosity, particularly when delivered in short, powerful pulses at medium frequencies. Combining ultrasound with traditional recovery methods has shown promising results, boosting recovery efficiency by up to 100%. At the same time, ultrasonic treatment reduces the use of traditional reagents, thereby reducing environmental pollution. Moreover, ultrasound treatment shows potential in tasks such as separating oil-water emulsions, desulfurization, dewaxing oil, coal enrichment, and extracting valuable metals from metal-bearing shales through hydrometallurgical leaching. However, widespread industrial implementation of ultrasonic technology necessitates further field and mathematical research.

TETRA (Terrestrial Trunked Radio, formerly known as Trans-European Trunked Radio) is used worldwide for Radio Frequency (RF) communications by emergency services, militaries, transportation and for commercial use. TETRA systems have been in use since the 1990’s in critical infrastructure worldwide and are still being deployed in the US for use in new projects. One example is the deployment of TETRA in new Offshore Wind Farm installations which are new to the US and still mimic European standards and installations. Even though the TETRA standard has been around since the nineties, it is still relevant and important to secure. Many of these systems remain in service or are still being deployed without a solution to a recently discovered Air Interface Encryption (AIE) vulnerability. Voice and data transmitted by TETRA radio systems is Air Interface Encrypted to protect its confidentiality and integrity and prevent eavesdropping and man-in-the-middle type attacks. This paper presents a recently discovered vulnerability in one of TETRA’s Air Interface Encryption Algorithms, examines existing solutions, and explores the use of Friendly Jamming (FJ) techniques to solve this problem.

Products made from petroleum-derived plastic materials are linked to many environmental problems such as greenhouse gas emissions and plastic pollution. It is desirable to manufacture products from environmentally friendly materials instead of petroleum-based plastic materials. Products made from biomass-fungi composite materials are biodegradable and can be utilized for packaging, construction, and furniture. In biomass-fungi composite materials, biomass particles (derived from agricultural wastes) serve as the substrate and the fungal hyphae network binds the biomass particles together. There are many reported studies on 3D printing of biomass-fungi composite materials. However, there are no reported studies on biodegradation of 3D printed samples from biomass-fungi composite materials. In this study, two types of biomass materials were used to prepare printable mixture hemp hurd and beechwood sawdust. The fungi strain used was Trametes versicolor. Extrusion based 3D printing was used to print samples. 3D printed samples were left for five days to allow fungi to grow. The samples were then dried in an oven for 4 hours at 120ºC to kill all the fungi in the samples. The samples were buried in the soil using a mesh bag and kept in an environmental chamber at 25℃ with a relative humidity of 48%. The weight of these samples was measured every week over the period of three months. Both types of samples (prepared from beechwood sawdust and hemp hurd, respectively) showed weight change after three months. Furthermore, the samples made from hemp hurd had more weight change than the samples made from beechwood sawdust. The SEM (scanning electron microscope) micrographs and FTIR (Fourier transform infrared) spectroscopy showed evidence of biodegradation of these samples.

Correlated binary data in a 2x2 table has been analyzed from both the frequentist and Bayesian perspectives, but a fully Bayesian hierarchical model has not been proposed. This is a commonly used model for correlated proportions when considering, for example, a diagnostic test performance where negative subjects are tested a second time. We consider a new hierarchical Bayesian model for the parameters resulting from a 2x2 table with a structural zero. We investigate the performance of the hierarchical model via simulation. We then illustrate the usefulness of the model by showing how a set of historical studies can be used to build a predictive distribution for a new study that can be used as a prior distribution for both the rate ratio and marginal probability of a positive test. We then show how the prior based on historical 2x2 tables can be used to power a future study that accounts for pre-experimental uncertainty. High quality prior information can lead to better decision making by improving precision in estimation and by providing realistic numbers to power studies.

Since ancient times, music has been instrumental in giving life to the stories we build our identities and cultures around. Music perpetuates myth by storytelling, retelling and updating old stories, and creating new ones. Many musicals, such as The Phantom of the Opera, Les Miserables, Wicked, and Hamilton, have been based on novels or epic poems. I will examine adaptations on a smaller scale, of rock songs based on novels, poems, and/or myths, and look at how, in our time, music creates myth by creating its own heroes and heroines through capital and the star system. In traditional literary and cultural analysis, a distinction was drawn between the natural and the supernatural when discussing literary mythology (Frye, 1957); in the twentieth century, an equivalent distinction was made in works of art that, in Baudrillard’s terminology, make use of the realms of the real and the “hyperreal” (1981). In today’s mythmaking, the supernatural has been largely replaced by the technological, and recent developments blur the line between science fiction and fantasy; tech has become megalotech. Examples can be seen in a number of recent and current songs, as well as films and television shows about music, musicians, and the music business.

The Akosombo Nile tilapia is the only approved local strain for aquaculture production in Ghana. In this study, an exotic red tilapia sample suspected to be cultured in a fish farm within the Lower Volta River Basin of the Lake Volta was collected for species identification. A molecular screening using DNA barcoding sequencing was performed on the samples targeting the cytochrome C oxidase subunit 1 mitochondrial gene (COX1). We confirmed the identity of the red tilapia fish to be a non-native Oreochromis sp. recently introduced into the country. The data obtained clearly demonstrates a breach of biosecurity that potentially threatens Ghana’s native tilapia genetic resources and aquaculture development.

Background. While selective use of antibiotics for infected pancreatic necrosis (IPN) in acute pan-creatitis (AP) is recommended, studies indicate a high rate of inadequate treatment. Methods. A search of PubMed, Scopus, and Cochrane databases was conducted, focusing on primary research and meta-analyses. Data were categorized based on core concepts, and a narra-tive synthesis was performed. Results. The searches yielded 1016 publications. After assessing 203 full texts and additional sources, 80 studies were included. The answers obtained were: (1) Preventive treatment does not decrease the incidence of IPN or mortality. Given the risks of bacteria resistance and fungal infec-tions, antibiotics should be reserved for highly suspected or confirmed IPN; (2) The diagnosis of IPN not always require microbiological samples, as clinical suspicion or CT signs can suffice. Early di-agnosis and treatment may be improved by using biomarkers such as procalcitonin and novel mi-crobiological methods; (3) When indicated, early initiation of antibiotics of IPN is a key determinant in reducing mortality; (4) Antibiotics with good penetration into pancreatic tissue covering Gram-negative and Gram-positive bacteria should be used. Routine antifungal therapy is not recommended; (5) The step-up approach, including antibiotics, is the standard for IPN manage-ment; (6) Antibiotic duration should be kept to a minimum and should be based on the quality of source control and patient condition. Conclusions. Early antibiotic therapy is essential for the treatment of IPN, but prophylactic anti-biotics are not recommended in AP. High-quality RCTs are required to better understand the role of antibiotics and antifungals in AP management.

Peanut is one of the important legumes grown in Kenya, ranking second after beans. Its production is most common in Western and Nyanza regions of the country with higher volumes being produced in Nyanza Region compared to the Western Region. The value chain for peanuts in Kenya consist of many actors including input dealers, producers, aggregators, traders, processors, exporters and consumers. The general objective of this study was to map the value chain for peanuts, indicating the opportunities that value chain actors can benefit from and strategies that can be used to upgrade the chain. The specific objectives were to characterize the key actors along the peanut value chain; determine the costs and value added along the groundnut value chain; and determine the constraints and opportunities in the value chain and suggest ways to upgrade the chain. A cross-sectional survey was conducted among the key actors in the value chain in 2 purposively selected sub-counties in Kenya where peanuts are predominantly produced marketed and/or consumed. The sub-counties are Karachuonyo and Nyakach. The data collected included socio-economic characteristics of the value chain actors, sales volumes and prices, trends in demand and supply, constraints and opportunities in peanuts and trade policy related issues. Secondary information mainly on value chain aspects was drawn from past research reports and internet. The data were analyzed using descriptive statistics and parameters such as means and percentages were determined and used to interpret the results. These enabled the drawing of peanut value chain map illustrating interrelations among chain actors, and activities they conduct. Results show that more females (68%) compared to 32% male participate in peanut production. Results further show that the female farmers were order compared to the male farmers. Few farmers were aware of improved technologies, for example only about 26% were aware of existence of improved peanuts varieties, and only 1.5% used the improved seed. No peanut farmer was using inorganic fertilizers, citing high price, nature of the soil and lack of knowledge as the major hindrance. At wholesale level, the chain was dominated by male traders partly attributed to the very versatile nature of the business that requires intensive travels, and also being capital intensive afforded by few females. On the other hand, retail traders were dominated by females. Retailers do deal in small quantities and therefore use less capital compared to other categories of traders. The majority of the processors were males also attributed the capital-intensive nature of the processing business. Most of the businesses were located in urban areas because of easier access to the raw materials and markets for the processed groundnuts. On multi-stakeholder platforms with various parties in the chain, an analysis of strengths, weaknesses, opportunities, and threats (SWOT) was undertaken. Cost variables were used to calculate gross margin profit and benefit-cost ratios. Overall, the sector was mostly a fresh food market, with a focus on peanut producers, processors, and direct sales to wholesalers, retailers, and end users. The SWOT analysis indicated numerous prospects, such as advantageous production ecologies, processing alternatives, and insatiable local and international markets. To operate synergistically with a collective profit motivation, institutional players must network with primary actors. Priority production restrictions, such as seed availability, chemical fertilizer costs, field pests and diseases, and declining soil fertility, should be addressed.

Perioperative acute pain management in pediatric patients is essential to reduce complications. Adenoidectomy-Tonsillectomy are surgical procedures requiring pain control, and risk minimization for postoperative bleeding, nausea, and vomiting. Despite their known secondary effects, the use of opioid analgesics remains preponderant in pediatric perioperative management. We present an updated review on perioperative pain management in children and describe the development and implementation of a multimodal analgesia protocol aimed to improve patients’ pain management while consistently reducing opioids use. Information from relevant articles was summarized, then compared to our clinical needs. Learnings were used to create and implement a multimodal analgesia protocol to be used in patients 3-9 years-old undergoing adenoidectomy/tonsillectomy. Analgesic strategies have emerged to reduce or avoid the use of opioids. Among these strategies, combining different non-opioid analgesics (Ibuprofen, Paracetamol, Metamizole) has been shown to be an effective and safe pharmacological strategy when implemented as part of postoperative multimodal analgesia protocols. Significant evidence associating the use of NSAIDs with a bigger risk of postoperative bleeding does not exist. Multimodal and preventive analgesia has shown to provide significantly more effective analgesia than some opioid regimens. Ibuprofen offers highly effective analgesia for postoperative pain, particularly when combined with acetaminophen.

Pain diagnosis remains a challenging task due to its subjective nature, the variability in pain expression among individuals, and the difficult assessment of the underlying biopsychosocial factors. In this complex scenario, artificial intelligence (AI) can offer the potential to enhance diagnostic accuracy, predict treatment outcomes, and personalize pain management strategies. This review aims at dissecting the current literature on computer-aided diagnosis methods. It also discusses how AI-driven diagnostic methods can be integrated into multimodal models that combine various data sources, such as facial expression analysis, neuroimaging, and physiological signals, with advanced AI techniques. Despite the significant advancements in AI technology, its widespread adoption in clinical settings faces crucial challenges. Ethical considerations related to patient privacy, biases, and lack of reliability and generalizability are the main issues. Furthermore, there is a need for high-quality real-word validation as well as the development of standardized protocols and policy rules to guide the implementation of these technologies in diverse clinical settings.

Petit vert (scientific name: Brassica oleracea var. gemmifera DC. × Brassica oleracea var. acephala DC.) is a new variety of vegetable created by crossbreeding kale and brussels sprouts (Brassica oleracea species). The present study aimed to identify biologically active compounds in extracts of the outer leaves of Petit vert by purification and to examine their biological activities. Dried and powdered outer leaves of Petit vert were extracted, fractionated, and purified to isolate active compounds. Nuclear magnetic resonance and mass spectrometries were performed to elucidate the structures of five compounds (1‒5). The compounds isolated from Petit vert leaves were glycosides that contained kaempferol, quercetin (flavonol), or sinapinic acid (phenylpropanoid).　Glucose uptake in cultured C2C12 murine myoblasts in the absence of insulin was significantly increased by these compounds, kaempferol, sinapic acid, and ferulic acid, while that in the presence of insulin was also significantly increased by compounds 3 and 4, kaempferol, and sinapic acid. The present study reports for the first time the isolation of five compounds containing sinapic acid from the outer leaves of Petit vert and their stimulation of glucose uptake in cultured C2C12 murine myoblasts. The results obtained herein suggest the potential of these compounds to effectively attenuate hyperglycemia and maintain muscle strength by promoting glucose metabolism in muscle cells.

Is it possible that educating women could be the key to reducing birth rates and protecting the environment? Women's education in 3rd countries is far more than just access to basic education. It is a pathway to economic growth, social stability and self-awareness. This essay reflects on the ethical challenges and benefits of educating women in areas such as interpersonal relationships, changing the traditional role of women and sustainability. In exploring this key issue, it is possible to discover that education can transform society and bring about real change, provided humanity accepts its responsibility for the state and sustainability of a quality environment for future generations.

We use Fourier analysis to access risk in financial products. With it we analyze price changes of e.g. stocks. Via Fourier analysis we scrutinize quantitatively whether the frequency of change is higher than a change in (conserved) company value would allow. If it is the case, it would be a clear indicator of speculation and with it risk. The entire methods or better its application is fairly new. However, there were severe flaws in previous attempts; making the results (not the method) doubtful. We corrected all these mistakes by e.g. using Fourier transformation instead of discrete Fourier analysis. Our analysis is reliable in the entire frequency band, even for frequency of 1/1d or higher if the prices are noted accordingly. For the stocks scrutinized we found that the price of stocks changes disproportionally within one week which clearly indicates speculation. It would be an interesting extension to apply the method to crypto currencies as these currencies have no conserved value which makes normal considerations of volatility difficult.

Science seeks to explicate truths about our reality. But what is truth? How do we know things? Given our ignorance, and our fallibility, why should scientists be trusted? A theory of knowledge that addresses these human questions is sketched, in conversation with recent advances in thermodynamics which underline the seminal importance of unity by demonstrating (i) a definite physical meaning of the idea of “unitary entity”, (ii) the commensurability of the local and the non-local (resolving the Loschmidt Paradox), and (iii) the applicability of this entropic physics to entities at all scales, whether small (“quantum mechanical”) or large (subject to “general relativity”). Similarly, integrity is indispensable to the scientific enterprise, whether at the level of the mathematico-physical, the practising scientist, the scientific community, or the public. As a human activity aimed at touching reality, it is fundamental that the scientific enterprise necessarily also has an irreducibly poetic component. Although in principle it cannot be completely specified, this enterprise is a cluster of procedures designed to increase our understanding of the natural world. Our apprehension of knowledge is irreducibly personal, depending both on our own individual integrity as well as on the integrity of the scientific community. Believing that “reality” exists and can be grasped (however incompletely), scientists look for coherence and value unified accounts. Strictly speaking, although reality can be known truly (if only in part) the idea of “objective” knowledge is an oxymoron, even if such an idea is often a useful approximation. Knowledge is necessarily personal.

Until now, crystalline NiCo2S4 and its composites have demonstrated improve performances in supercapacitor applications, compared to their oxide analogous, due to their relatively higher electrical conductivity, and multifaceted redox reaction. However, amorphous phase materials have recently shown promise in electrochemical energy storage systems. In this work, urea-assisted amorphous NiCo2S4 on nickel foam (referred to as aNCS) with high nitrogen atom% content, was obtained via hydrothermal method. In comparison to the crystalline NiCo2S4 (referred to as cNCS), aNCS exhibited superior electrochemical performance with specific capacitance of ~3506 F g-1 which is higher than cNCS specific capacitance of ~2185 F g-1 at 2 A g-1. Additionally, aNCS in two-electrode asymmetry supercapacitor exhibited specific capacitance and energy density of ~196 F g-1 and 56 Wh kg-1, respectively.

The study examines the effects of transitioning to hydrogen production in the National Capital Region (NCR) and Palawan Province, Philippines, focusing on technology, environment, and stakeholder impact. The research, conducted through a July 2022 survey, aimed to assess public awareness, knowledge, risk perception, and acceptance of hydrogen and its environmentally friendly variant, green hydrogen, infrastructure. Disparities were found between urban NCR and rural Palawan, with lower awareness in Palawan. Safety concerns were highlighted, with NCR respondents generally considering hydrogen production safe, while Palawan respondents had mixed feelings, particularly regarding nuclear-based hydrogen generation. The report emphasizes the potential ecological advantages of hydrogen technology but highlights potential issues concerning water usage and land impacts. It suggests targeted public awareness campaigns, robust safety assurance programs, regional pilot projects, and integrated environmental plans to facilitate the seamless integration of hydrogen technology into the Philippines' energy portfolio. This collective effort aims to help the country meet climate action obligations, foster sustainable development, and enhance energy resilience.

Deep Eutectic Solvents (DESs) show promising abilities for the delamination of multilayer packaging films that are used in food packaging and in pharmaceutical blister packs. Due to the complexity of their structure, the recycling of these materials is a challenging task, leading to the easiest or cheapest option, landfilling. Towards the development of ‘green’ solvents for the efficient waste management and recycling, the conducted research focuses on the preparation of a range of hydrophobic and hydrophilic DES based on carboxylic acids. Also, their chemical and physical characterization, such as DSC, rheometer and density measurements, was followed for the determination of their properties. The laminate packaging waste products that were tested were Al/PE, PE/Al/PET, Al/PE/paper and PVC/PE/Al. Different batches of solvent systems were tested based on various naturally derived aliphatic and aromatic organic compounds as well as amino acids. The separated films were collected and studied further for the examination of the delamination extend. Results showed full or partial delamination of some materials as well as challenges of solvent systems. Variables such as temperature, agitation rate, mixing time and solvents ratios were monitored and collected during the design of experimental process. The results showed that the used DESs can offer an efficient, low-energy, affordable and green option for the delamination tested packaging materials.

The aim of this study was to identify differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) in the endometrium of individuals with and without EMS during the proliferative (P) and secretory (S) phases of the menstrual cycle. Tissues were obtained from 18 control (CT; P-phase [pCT], n=8; S-phase [sCT], n=13) and 23 EMS patients (P-phase [pEMS], n=13; S-phase [sEMS], n=12). DElncRNAs and DEmRNAs were analyzed using total RNA-sequencing. In P-phase, expression of NONHSAG019742.2 and NONHSAT120701.2 was significantly higher in EMS than control patients, that of while NONHSAG048398.2 and NONHSAG016560.2 was lower in EMS patients. In S-phase, expression of NONHSAT000959.2, NONHSAT203423.1, and NONHSAG053769.2 was significantly increased in EMS patients, while that of NONHSAG012105.2 and NONHSAG020839.2 was lower. In addition, the expression of HSD11B2, THBS1, GPX3, and SHISA6 was similar to that of neighboring lncRNAs in both P- and S-phases. In contrast, ELP3 and NR4A1, respectively, were up- or downregulated in pEMS tissues. In sEMS, expression of LAMB3 and HIF1A was increased, while expression of PAM was reduced. Our findings on lncRNAs and mRNAs encourage not only to explore the potential clinical applications of lncRNAs and mRNAs as prognostic or diagnostic biomarkers for EMS but also to gain valuable insights into its pathogenesis.

In today's technologically advanced landscape, sensors feed critical data for accurate decision-making and actions. Ensuring the integrity and reliability of sensor data is paramount to system performance and security. This paper introduces an innovative approach utilizing discrete wavelet transforms (DWT) embedded within microcontrollers to scrutinize sensor data meticulously. Our methodology aims to detect and isolate malfunctions, misuse, or any anomalies before they permeate the system, potentially causing widespread disruption. By leveraging the power of wavelet-based analysis, we embed computational intelligence directly into the microcontrollers, enabling them to monitor and validate their outputs in real-time. This proactive anomaly detection framework is designed to distinguish between normal and aberrant sensor behaviors, thereby safeguarding the system from erroneous data propagation. Our approach significantly enhances the reliability of embedded systems, providing a robust defense against false data injection attacks and contributing to overall cybersecurity.

The advancement of computational drug discovery and design necessitates continuous innovation to enhance the accuracy and scope of predictive models for early-stage drug research and development. This article introduces a novel workflow for in silico generation of structural and intermolecular binding affinity data with reasonable accuracy, combining two computational tools: Modeller and Prodigy. By leveraging synthetic structural and biophysical data, this approach addresses the limitations of existing experimental datasets, generating extensive, high-quantity binding affinity data with reasonable accuracy for biomolecular binding pairs, which broadens the horizon of computational biomolecule design and discovery by enabling extensive exploration of the sequence space of biomolecular binding pairs, and narrows the gap between experimental binding affinity data and its unexplored territories. Overall, this article presents a methodological advance to enhance the accuracy and scope of computational biomolecule discovery and design, paves the way for the development of preclinical candidates with improved efficacy and specificity, and holds transformative potential for further advancements in artificial intelligence-enabled biomolecule discovery and design in the future.

Advancements in biological and medical science are intricately linked to the biological central dogma. In recent years, gene editing techniques, especially CRISPR/Cas systems, have emerged as powerful tools for modifying genetic information, supplementing the central dogma and holding significant promise for disease diagnosis and treatment. Extensive research has been conducted on the continuously evolving CRISPR/Cas systems, particularly in relation to challenging diseases, such as cancer and HIV infection. Consequently, the integration of CRISPR/Cas-based techniques with contemporary medical approaches and therapies is anticipated to greatly enhance healthcare outcomes for human. This review begins with a brief overview of the discovery of the CRISPR/Cas system. Subsequently, using CRISPR/Cas9 as an example, a clear description of the classical molecular mechanism underlying the CRISPR/Cas system was given. Additionally, the development of the CRISPR/Cas system and its applications in gene therapy and high-sensitivity disease diagnosis were discussed. Furthermore, we address the prospects for clinical applications of CRISPR/Cas-based gene therapy, highlighting the ethical consideration associated with altering genetic information. This brief review aims to enhance understanding of the CRISPR/Cas macromolecular system and provide insight into the potential of genetic macromolecular drugs for therapeutic purposes.

A prime gap is the difference between consecutive prime numbers. The $n^{\text{th}}$ prime gap, denoted $g_{n}$, is calculated by subtracting the $n^{\text{th}}$ prime from the $(n+1)^{\text{th}}$ prime: $g_{n}=p_{n+1}-p_{n}$. Oppermann's conjecture is a prominent unsolved problem in pure mathematics concerning prime gaps. Despite verification for numerous primes, a general proof remains elusive. If true, the conjecture implies that prime gaps grow at a rate bounded by $g_{n}<{\sqrt {p_{n}}}$. We examine the ratio of Chebyshev functions for consecutive primes, $\frac{\theta(p_{n+1})}{\theta(p_{n})}$, and compare it to the square root of their ratio, $\sqrt {\frac{p_{n+1}}{p_{n}}}$. Assuming this inequality holds for primes larger than $10^{8}$, we demonstrate the truth of Oppermann's conjecture. For sufficiently large $n$, this inequality guarantees that $g_{n}<{\sqrt {p_{n}}}$ for all primes beyond a certain point. Our proof also validates Andrica's, Legendre's, and Brocard's conjectures for primes exceeding a specific threshold.

The world is currently facing an energy crisis. To solve the problem, many countries have been exploring renewable energy sources. However, the existing renewable energy sources are highly dependent on weather changes, necessitating the utilization of significantly expensive and large storage batteries.As a solution, we propose a system for generating renewable energy. The proposed system comprises a current source and a voltage source connected in series. With appropriate adjustments, the current source supplies current without voltage and the voltage source provides voltage without current. Considering that electric power is a product of current and voltage, electric power is generated from the interaction between the current source and voltage source. In our previous study, the same result was obtained; however, the output voltage was low, which resulted in a low amount of generated energy. In this study, by introducing some ingenuities, we successfully increased the output voltage. Consequently, we succeeded in powering a light-emitting diode and charging a super-condenser to the standard voltage. Using this system, we generated a relatively large amount of energy in the right place and at the right time, validating our systems’ robustness to changes in weather. The large-scale adoption of our system could contribute to solving the global energy crisis.

Background: Attendance to neonatal follow-up programs (NFU) presents as a significant factor associated with long-term outcome of high-risk infants. Few studies have focused on attrition or loss to follow up particularly during COVID-19 pandemic. Methods: In this retrospective observational study, data from 1137 high-risk neonates who participated in a hospital NFU program were collected (573 before and 564 after the onset of COVID-19 pandemic). The study sample was grouped to: G1 (N=831) who maintained participation in the program, G2 (N=196) who discontinued, and G3 (N=110) who never visited the outpatient clinics. Data was obtained from the hospital's Systems Applications and Products Software, and a structured questionnaire, answered by parents of newborns either discontinuing (G2) or not attending (G3) the NFU program, through a telephone contact.Results: The most frequently reported reason for discontinuance before the onset of the pandemic was the parents' perception that it was not necessary to maintain participation in the program (44.12%). During the COVID-19 pandemic, provider-related barriers to maintaining hospital access, inability to provide high-quality services (37.14%), and feelings of fear and insecurity (18.5%), emerged as factors for non-attendance. Citizenship and morbidity (RDS, sepsis, NEC, jaundice) acted as incentives to join the NFU program during both study periods. Multiple regression analysis showed that multiple gestation infants had higher odds for maintaining participation during the COVID-19 period (OR, 4.04; CI, 1.09-14.9). Conclusion: Understanding the potential impact of COVID-19 and the transformative changes in NFU clinics is crucial to apply compliance strategies. Removing barriers to maintain family participation can lead to increased attendance rates.

This research delves into the evolution of architectural styles throughout the 20th century, examining the transition from traditional to modern architecture. The study aims to identify the key factors influencing this transformation and analyze the impact of modernist principles on architectural design and practice. Employing a historical and analytical methodology, the research investigates the works of influential architects and the role of technological advancements. Key findings reveal that a confluence of cultural, technological, and socioeconomic forces drove the shift towards modernism, which focused on functionality, form, and innovation. The research concludes that the modernist movement fundamentally reshaped the built environment, leaving a lasting legacy on contemporary architectural discourse. It is recommended that future studies explore the long-term implications of modernism on urban planning and sustainability, as well as the potential for a synthesis between traditional and contemporary architectural approaches.

Geochemical mapping of river sands in the Manufahi area of Timor-Leste revealed potential areas for future mineral exploration. River sand samples from the study area were collected and geochemically analyzed to identify anomalous concentration distributions of several valuable elements and locate potential target areas and geological formations that may host mineral deposits. The 26 major and minor elements were identified using wavelength-dispersive X-ray fluorescence. The river sands exhibited varying elemental concentrations, with Cr, Cu, Zn, and Ba showing deviations from the normal distribution patterns. Identification of geochemical anomalies is an important task in mineral exploration geochemistry. The mean + 2 standard deviations (mean+2STD), median + 2 median absolute deviations (median+2MAD), and Tukeyâs inner fence (TIF) methods were used to determine the geochemical thresholds. This study shows that TIF and principal component analysis (PCA) methods are highly effective in calculating appropriate threshold values and identifying relevant elemental associations. These approaches have proven useful for delineating target areas for mineral deposits, resulting in reliable outcomes. Four predicted target areas with high potential for deposits and mineralization anomalies of Cr, Cu, Ni, and Ba were delineated in the study area.

Emotional agility and social intelligence at small to medium-sized enterprises (SMEs) can be an invigorating experience, filled with opportunities for growth, innovation, and collaboration. This research aims to investigate the Omani entrepreneurs’ emotions and intelligence at workplace through self-experiences in SMEs. A sample of 222 Omani entrepreneurs participated in online survey that was designed to attain the objectives of this research. Data was collected using google drive and analyzed using multiple regression path analysis. The results revealed that emotional agility and social intelligence have positive and significant impact on employee thriving at work in Omani SMEs. Further, openness to experience mediates the relationships between entrepreneurs’ emotions and intelligence and sustainable workplace. These results confirm the effective role of openness to experience among Omani entrepreneurs where they should adopt new strategies and techniques to improve their skills and support their SMEs. This research highlighted the role of interpersonal skills including agility and intelligence of entrepreneurs in Arab context.

Rapid microscopic analysis of tissue is an essential diagnostic tool in oncological surgery. The gold standard for intraoperative histological tissue evaluation are frozen sections. However, frozen sections are prone to a variety of artefacts and require skilled staff and specialized lab equipment. A potential method for rapid intraoperative tissue evaluation that does not require fixation, freezing nor sectioning of the tissue, is ex vivo fluorescence confocal microscopy (FCM). The visualization of the structurally important extracellular matrix (ECM) in conventional ex vivo FCM lags behind the standards of conventional histology. The objective of this study was to find a stain that will improve the depiction of the ECM to resemble FFPE H&amp;E sections as closely as possible.

Emerging evidence suggests that low socioeconomic status (SES) home environments may play a role by promoting excess energy intake through a lack of access to non-food reinforcers. Because of the deleterious effects of SES related disparities on child health and development, feasible and culturally acceptable interventions are urgently needed. Community-based music enrichment programs may be an ideal intervention strategy. In collaboration with a local non-profit organization and music studio, we conducted a pilot randomized controlled trial to assess the effects of a music enrichment program versus playdate control in a group of 9-24-month-old healthy infants (N = 16). Overall, we found some intervention effects on relative reinforcing value of food (RRVfood) and the home environmental enrichment measures (i.e., increased music use at home and home language environment). Our intervention demonstrated large effects on an increased use of music at home. We did not find significant group differences on the RRVfood and home language environment, but some of the effect sizes were medium-to-large. Results also suggest that our intervention is feasible and acceptable. Parent feedback indicated the intervention was well-liked and steps we took to help reduce barriers worked. Music enrichment programs maybe a high-impact, low-cost strategy to address socioeconomic disparities.

The present study investigates the impact of electrode surface roughness on the electrofreezing of water. This research focuses on how the electrode roughness induced by a laser treatment affects the nucleation and growth of ice crystals under controlled electric fields. To achieve this, a series of experiments were conducted using deionized water samples placed between electrodes with varying surface roughness. The electrodes, fabricated with the Al6061 T6 alloy were structured via the Laser Shock Processing (LSP) method. For this purpose, the pulsed densities during the LSP process were varied from 900 to 2500 pulses/cm2. The increase of the pulse density was correlated to the surface structuring and to the microstructural features and average roughness of the LSP-treated Al6061 alloy. A wavy-like microstructure was induced upon the LSP treatment with average roughnesses between ~ 3.5 and 6 µm at the selected pulse densities. The results indicate that electrode roughness significantly influences the electrofreezing process. Rougher electrodes were found to lower the nucleation temperature compared to smoother ones, suggesting enhanced ice nucleation activity. The findings are attributed to the increased electric field concentration at the asperities of the rough surfaces, which may facilitate the alignment of water molecules and the formation of critical ice nuclei.

Explainable AI (XAI) has the potential to transform healthcare by making AI-driven medical decisions more transparent, trustworthy, and ethically compliant. Despite its promise, the healthcare sector faces several challenges, including balancing interpretability and accuracy, integrating XAI into clinical workflows, and ensuring adherence to rigorous regulatory standards. This paper provides a comprehensive review of XAI in healthcare, covering techniques, challenges, opportunities, and advancements, thereby enhancing the understanding and practical application of XAI in healthcare. The study also explores responsible AI in healthcare, discussing new perspectives and emerging trends and providing valuable insights for researchers and practitioners. The insights and recommendations presented aim to guide future research and policy-making, promoting the development of transparent, trustworthy, and effective AI-driven solutions.

This study presents an innovative method for producing thermosensitive bio-ink from chitosan hydrogels saturated with carbon dioxide and agarose. It focuses on a detailed characterization of their physicochemical properties and potential applications in biomedicine and tissue engineering. The ORO test approved rapid regeneration of the three-dimensional structure of chitosan-agarose composites in the unidirectional bench press simulation test. The diffusion of dyes through chitosan-agarose hydrogel membranes strongly depended on the share of both polymers in the composite and the molecular weight of the dyes. Glucose, as a nutrient marker, also diffused through all membranes regardless of composition. Biocompatibility assessment using MTT tests on 46BR.1N fibroblasts and HaCaT keratinocytes confirmed the safety of the bioink. The regenerative potential of the bioink was confirmed by efficient cell migration, especially HaCaT. Long-term viability studies showed that chitosan-agarose scaffolds, unlike the agarose ones, support cell proliferation and survival, especially 14 days after bioink extrusion. Experiments in a skin wound model in mice confirmed the biocompatibility of tested dressing and the beneficial action of chitosan on healing. Studies on vessel formation in chicken embryos highlight the potential of the chitosan-agarose composition for enhancing proangiogenic effects. This composition meets all entry criteria and possesses excellent biological properties.

The understanding of the ‘I-Thou’ relationship is the recognition that there is a relation between one and another in the world of human being. Each individual is an entity that carries a great deal of dignity and the good appropriation of this dignity fosters a great interpersonal relationship. For there to be any peace-relation among beings, a way to human enquiry and understanding of common good and advancement, there is a need for unbiasness. In Robert Kane’s view, it is through a positive I-Thou peace-relation which is achievable through ‘openness’ that human beings sustain the moral sphere, and avoid breaking it. It will help them to arrive at truth and a way forward to any debatable issue among human beings. Openness is a form of respect for another even in the face of divided or different opinions. Hence, in any deliberation of any sort, one has to take the part of Openness by limiting narrowness of vision and choose to respect every other point of view and way of life. This will help to foster the ideal I-Thou or inter-human beings’ peace-relation in the face of obstacles and conflicts. However, he seems to take for granted the uniqueness or difference in human thinking patterns and so he creates back the problem which he sets out to resolve by not giving a stand on what truth is and how human beings can get to it when openness fails. Adopting expository and analytic methods, the research argues that Kane’s idea of Openness appears to be a solution to sustain harmony among human beings.

Nickel electrodeposition is a widely utilized method for creating thin films on various substrates with various desirable attributes. Recently, there has been a growing interest in developing nickel composite coatings that incorporate additional elements or particles into the nickel matrix to enhance their properties. These composite coatings offer superior wear resistance, corrosion resistance, hardness, and other functional benefits compared to pure nickel coatings. Some of the recent advancements in electrodeposited nickel composite coatings include improved wear resistance, enhanced mechanical properties and better corrosion resistance. Researchers have discovered that adding Al, Si, Zr, C, W, and Ti particles to nickel coatings can significantly enhance wear resistance. The uniform distribution of these particles within the nickel matrix acts as a barrier to wear and tear. Studies have also shown that nickel composite coatings with Al, Si, Zr, C, W, and Ti particles exhibit superior mechanical properties, including increased hardness. These particles refine the grain size of the nickel matrix and hinder defect movement, leading to greater mechanical strength. Moreover, nickel composite coatings offer improved protection against corrosion compared to pure nickel coatings. This review provides a detail discussion of nickel composite coatings with regard to their comparative advantaged compared to pure nickel coatings on different substrates.

As the number of Small and Medium Enterprises (SMEs) rises in the world, the amount of sensitive data used also increases, making them targets for cyberattacks. SMEs face a host of issues such as lack of resources, and poor cybersecurity talent, resulting in multiple vulnerabilities that increase overall risk. Cybersecurity risk assessment frameworks have been developed by multiple organizations such as the National Institute of Science and Technology (NIST) and the International Organization for Standardization (ISO), but they are complicated to understand, and challenging to implement. This research aimed to create an effective cybersecurity risk assessment framework specifically for SMEs while considering their limitations. This was achieved by first identifying common threats and vulnerabilities and categorizing them according to their importance, and risk. Secondly, popular frameworks like the NIST CSF and ISO 27001/2 were analyzed for their proficiencies and deficiencies while identifying relevant areas for SMEs. Finally, novel techniques catered to SMEs were explored and incorporated to create an effective framework for SMEs. This framework was also developed in the form of a tool, providing an interactive and dynamic environment. The tool was effective and the framework is a promising start but requires more quantitative analysis.

Pesticides are chemical compounds or mixtures of hazardous substances that are used by humans to increase and protect crops from pests and control disease-carrying insects. Because of its wide use, it may be poisonous to helpful and non-targeting plants and animals. Spraying or spreading pesticides over whole fields of crops can cause runoff to transfer the chemicals into aquatic ecosystems, and wind can carry the chemicals to nearby grazing regions, farms, and populated areas, where they can endanger other animals. This review summarises recent studies on pesticide combination toxicity to aquatic biota and approaches used to anticipate toxic effects. When toxicants harm economically significant organisms that humans consume, the negative effects become more severe and can cause stress conditions, vital organ damage, biochemical damage, or even the death of living things in both terrestrial and aquatic environments. Pesticides are highly toxic to aquatic organisms such as snails, fish, etc. Neurological dysfunction in freshwater organisms is also caused by pesticides. By producing excessive ROS, pesticides can cause severe biochemical and histological changes in freshwater organisms. So, it is therefore easy to understand the attention of the public on these substances. Because aquatic organisms play a major part in the food chain. However, through the biomagnification process, the quantity of pesticides increases in the higher organisms through the food chain. Which results play a terrific role in the higher organism’s body. So, It's essential to comprehend the way that insecticides work on aquatic organisms. In this review article, we are focusing on the way that pesticides work, which will help in the system of biomonitoring.

This study was conducted to analyse viability of primary chicken embryo fibroblasts by pre-plating and efficiency of adipogenic trans-differentiation for cultured meat production. Morphology and proliferative capabilities of chicken embryo fibroblasts (CEF) were compared with those of chicken satellite cells (CSC) isolated from chicken embryos. Isolated CEF exhibited significantly lower expression of Pax7 (paired-box protein 7) and MHC (Myosin Heavy Chain) than CSC (p &lt; 0.05). Over 90% of isolated CEF expressed CD29 and Vimentin. Analysis of proliferative capabilities of CEF revealed no significant differences in EdU-positive cell (%), cumulative cell number, doubling time, and growth rate from passage 1 to passage 9 (p &gt; 0.05). Up to the passage 9, CEF underwent adipogenic trans-differentiation. As passages increased, lipid accumulation and adipocyte size decreased significantly (p &lt; 0.05). This indicates that CEF can be isolated by 2 hours of pre-plating and survive stably up to the 9th generation. Moreover, efficient production of fat can be achieved by inducing adipogenic trans-differentiation of lower-generation CEF.

In this work, we studied light-output properties, efficiency function as well as PSD capability of p-Terphenyl scintillator. The selected solid cylindrical scintillation detector has a size of (45 x 45) mm with PSD properties. Recently presented studies of light-output functions have been meas-ured only for low neutron energies. Our motivation has been to determine more accurate the light output function for p-Terphenyl scintillator over a wider neutron energy range. The measurements have been carried out with mono-energetic neutron beams in the wide energy range from 2.5 to 19 MeV. The neutron-gamma spectrometric system, which we developed has been used for the measurement. The input analogue signal from the detector is digitized with fast 12-bits analogue to digital converter with sampling frequency of 1 GHz. Measured data from the detector are processed into gamma and neutron spectra. The light output function for protons has been determined by finding the position of the protons for given neutron energies. The more accurate light output function for p-Therphenyl scintillator has been calculated. The pulse-shape discrimination capability as well as efficiency of p-Terphenyl scintillator in comparison with NE-213 equivalent detector is lower.

While the beneficial effects of using magnetic and electromagnetic treatment (ET) of brackish and saline waters on soil salinity reduction in the root zone were widely reported more studies are needed to answer questions about the soil salt leaching efficiency and the effect of the duration of the exposure to ET. For this aim, pot experiments were conducted using an Aqua-4DR physical water treatment device. The first experiment included two trials. The first considered 5 concentrations: C0:1.0; C1:4.5; C2:9; C3:13.5; and C4:18 dSm-1. The results revealed that the volume and the salt concentrations of the drained waters were significantly higher under irrigation with ET saline waters than those provided by untreated waters. The drained fraction of water varied from 20 to 26% under irrigation with untreated water and increased from 33 to 56% under irrigation with electromagnetized water indicating an improvement of salt leaching. The second trial was carried out with different irrigation doses. The result showed that the higher the dose, the more obvious and significant ET effect. The different treatment durations of water exposure revealed that the volume and salinity of drained water significantly increase as the ET duration increases. An increase in ET duration induces also an increase in soil water content of around 2.5%. Based on the experimental findings, we may conclude that the ET of saline water can reduce the adverse effect of salinity on the top soil, but these leached salts are carried away in depth and there is no concentration limit of water to the effect of the ET.

K-band radar waves have high penetration and low attenuation coefficients. However, the wavelength of this radar wave is relatively short; thus, designing and preparing both broadband and wide-angle radar wave absorbers in this band presents considerable challenges. In this study, a resin-based K-band radar wave absorber with a biomimetic lotus leaf structure was designed and formed by UV curing. Here, microscale lotus leaf papillae and antireflection structures were prepared using a DLP 3D printer, and the contact angle between the material and water droplets was increased from 56° to 130°. In addition, the influence of the geometric parameters of the lotus leaf antireflection structure on the electromagnetic absorption performance and mechanical strength was investigated. After simulation optimization, the maximum electromagnetic loss of the lotus leaf structure 3D printed sample was −32.3 dB, and the electromagnetic loss was below −10 dB in the 20.8–26.5 GHz frequency range. When the radar incidence angle was 60°, the maximum electromagnetic loss was still less than −10 dB. The designed lotus leaf structure has a higher mechanical energy absorption per unit volume (337.22 KJ/m3) and per unit mass (0.55 KJ/Kg) than commonly used honeycomb lightweight structures during the elastic deformation stage, and we expect that the designed structure can be used as an effective lightweight material for K-band radar stealth.

Based on molecular phylogenetic analyses, but also considering morphological characters, four new families are separated from the family Glomeraceae within the Glomerales and the class Glomeromycetes. The revised family Glomeraceae comprises only four genera: the type genus Glomus, Complexispora, Sclerocarpum and Simiglomus. Septoglomeraceae fam. nov. comprises, besides Septoglomus, also Funneliformis, Funneliglomus, Blaszkowskia and Viscospora. Sclerocystaceae fam. nov. is represented by the type genus Sclerocystis, but also by Halonatospora, Oehlia, Parvocarpum, Rhizoglomus and Silvaspora. Kamienskiaceae fam. nov. encompasses Kamienskia, Microkamienskia and Epigeocarpum. Finally, Dominikiaceae fam. nov. includes the genera Dominikia, Macrodominikia gen. nov. Microdominikia, Nanoglomus and Orientoglomus. The genera Oehlia and Halonatospora form two other clades well separated from Silvaspora, Sclerocystis and Rhizoglomus and might represent two further families within the Glomerales. Such deeper-going separation is to our opinion fully supported by molecular phylogeny, but in view of the low numbers of taxa, this separation is not yet needed at this stage of research progress.

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

The coal mining process generates wastes such as overburden and tailings, the disposal of which is a significant environmental challenge. The circular economy model of eliminat-ing waste and regenerating the economy and ecosystems can minimise the impact of coal mining wastes. Another resource-intensive industry is the construction industry, which is responsible for significant resource consumption, waste generation, and emissions. Reus-ing and recycling coal mining wastes as secondary or value-added building materials in the construction industry per circular economy principles will help minimise the impact and have environmental and economic benefits. Several studies have demonstrated the use and reuse of coal mining wastes in the construction industry. This article conducts a systematic literature review to understand the state-of-the-art utilisation of coal mining waste in the construction industry. After a series of refinements using the PRISMA approach, 54 articles were included in the review. The articles were further divided based on using coal mining wastes in the construction industry as end products/application areas. The review results show that coal mining waste has been successfully used to make bricks and aggregates (fine and coarse), replace cement, and develop geopolymers, concrete, roads, and embankments. The studies suggest the utilisation of coal mining waste primarily in non-structural components, with very few studies suggesting using coal mining waste in structural applications. The systematic literature review helped in understanding the knowledge development related to the possible application of coal mine wastes in the construction industry, identifying the gap in the field, and suggesting future research directions.

This paper deals with the formulation of a Cobot kinematic model by developing both the direct and inverse kinematics and choosing the noa transformation matrix for defining the end-effector position and orientation with respect to the base frame. These algorithms have been validated via software in Matlab environment and by means of suitable experimental tests, which have been carried out by using a UR5e Cobot. Moreover, a specific industrial application regarding the robotized assembling of a multi-cylinder IC engine, has been designed in terms of layout and corresponding automatic cycle that is intended as a sequence of the robot elementary actions. In particular, the proposed robotized cell is composed by the UR5e Cobot along with its controller and a suitable electropneumatic circuit that includes a PLC with its user interface, which are both governed by means of a specific electronic board and a switch control box. The IC engine in scale of 1:5 and specific parts of the end-effector, which takes the role of vacuum gripper and torque limiting screwdriver, have been designed and manufactured by using a 3D printer.

There are many features of homeostasis worth investigating such as how it works (information pathways, set point processing), where its command and control processors are located in the cell, the language used and how homeostasis interacts with all aspects of an organism's functional maintenance and development. All are necessary and valid inquiries, but this paper examines the implications of ignoring it as a factor of disease causation. Alternatively when properly understood the homeostasis profile becomes a rational explanation for any individual’s range of health; where some areas are very resistant to disease (resilient) and other areas of homeostasis are dysfunctional leading to minor, moderate or very susceptible tendencies to disease (lack of resilience in homeostasis). An understanding of this phenomenon, its interactions with gene expression (epigenetics) is necessary in order to evaluate the solutions for acute and chronic diseases. By this method diseases can be defined more precisely as specific susceptibilities in homeostasis, leading to a method to restore specific homeostasis functions.

The Mixture of Experts (MoE) architecture has evolved as a powerful and versatile approach for improving the performance and efficiency of deep learning models. This survey aims to provide the fundamental principles of MoE in details, a paradigm that harnesses the collective power of multiple specialized "expert" models working in concert to tackle complex tasks.Our exploration is a thorough analysis of the core components that constitute the MoE framework. We begin by dissecting the routing mechanism, a crucial element responsible for dynamically assigning input data to the most appropriate expert models. This routing process is pivotal in ensuring that each expert's specialized knowledge is optimally utilized. The survey places significant emphasis on expert specialization, a key feature that sets MoE apart from traditional architectures. We examine various strategies for developing and training specialized experts, exploring how this specialization enables MoE models to effectively handle diverse and multifaceted problems.Load balancing, another critical aspect of MoE systems, receives thorough attention. We discuss techniques for efficiently distributing computational resources among experts, ensuring optimal model performance while managing hardware constraints. This section provides insights into the delicate balance between model capacity and computational efficiency. Furthermore, we provide an in-depth discussion of the expert models themselves, examining their architectural designs, training methodologies, and how they interact within the larger MoE framework. This includes an analysis of different types of experts, from simple neural networks to more complex, task-specific architectures. The survey also navigates through diverse research avenues within the MoE landscape, highlighting recent advancements and innovative applications across various domains of machine learning. We pay particular attention to the burgeoning use of MoE in two rapidly evolving fields: computer vision and large language model (LLM) scaling. By providing this comprehensive overview, our survey aims to offer researchers and practitioners a deep understanding of MoE's capabilities, current applications, and potential future directions in the ever-evolving landscape of deep learning.The Mixture of Experts (MoE) architecture has evolved as a powerful and versatile approach for improving the performance and efficiency of deep learning models. This survey aims to provide the fundamental principles of MoE in details, a paradigm that harnesses the collective power of multiple specialized "expert" models working in concert to tackle complex tasks.Our exploration is a thorough analysis of the core components that constitute the MoE framework. We begin by dissecting the routing mechanism, a crucial element responsible for dynamically assigning input data to the most appropriate expert models. This routing process is pivotal in ensuring that each expert's specialized knowledge is optimally utilized. The survey places significant emphasis on expert specialization, a key feature that sets MoE apart from traditional architectures. We examine various strategies for developing and training specialized experts, exploring how this specialization enables MoE models to effectively handle diverse and multifaceted problems.Load balancing, another critical aspect of MoE systems, receives thorough attention. We discuss techniques for efficiently distributing computational resources among experts, ensuring optimal model performance while managing hardware constraints. This section provides insights into the delicate balance between model capacity and computational efficiency. Furthermore, we provide an in-depth discussion of the expert models themselves, examining their architectural designs, training methodologies, and how they interact within the larger MoE framework. This includes an analysis of different types of experts, from simple neural networks to more complex, task-specific architectures. The survey also navigates through diverse research avenues within the MoE landscape, highlighting recent advancements and innovative applications across various domains of machine learning. We pay particular attention to the burgeoning use of MoE in two rapidly evolving fields: computer vision and large language model (LLM) scaling. By providing this comprehensive overview, our survey aims to offer researchers and practitioners a deep understanding of MoE's capabilities, current applications, and potential future directions in the ever-evolving landscape of deep learning.

Biomaterials have been the subject of extensive research, with their applications in medicine and pharmacy expanding rapidly. Collagen and its derivatives stand out as valuable biomaterials due to their high biocompatibility, biodegradability, and lack of toxicity and immunogenicity. This review comprehensively examines collagen from various sources, its extraction and processing methods, and its structural and functional properties. Preserving the native state of collagen is crucial for maintaining its beneficial characteristics. The challenges associated with chemically modifying collagen to tailor its properties for specific clinical needs are also addressed. The review discusses various collagen-based biomaterials, including solutions, hydrogels, powders, sponges, scaffolds, and thin films. These materials have broad applications in regenerative medicine, tissue engineering, drug delivery, and wound healing. Additionally, the review highlights current research trends related to collagen and its derivatives. These trends may significantly influence future developments, such as using collagen-based bioinks for 3D bioprinting or exploring new collagen nanoparticle preparation methods and drug delivery systems.

Apartment buildings, which make up 83% of all structures in Jordan, play a crucial role in the country's construction sector. This study examines the main barriers that are preventing the implementation of low-carbon emission techniques in these buildings. It uses the Fuzzy Delphi Method to collect ideas from 14 housing investors. The results suggest that a major obstacle is the insufficient knowledge among end-users regarding environmental concerns, along with financial limitations, resulting in a lack of enthusiasm for low-carbon construction initiatives. Moreover, insufficient cooperation between consultants and contractors leads to subpar constructability, which is worsened by the prevailing conventional procurement method that prioritizes cost and schedule above environmental consequences. To further investigate, it is advisable to examine the utilization of contemporary procurement methods, such as Design-Build and Construction Management, in the housing industry of Jordan. These alternative methods have the potential to solve the current difficulties by promoting more effective and environmentally friendly building practices. This will help increase the use of low-carbon emission solutions and improve the overall sustainability of Jordan's construction sector.

This article discusses advances in molecular technologies for detecting foodborne pathogens, specifically Listeria monocytogenes and Salmonella. Although traditional detection methods are reliable, they are time- and labor-intensive. On the other hand, molecular methods include polymerase chain reaction (PCR), quantitative real-time PCR (qPCR), and next-generation sequencing (NGS), which enable rapid, specific, and sensitive detection of pathogens. The introduction of such procedures has significantly improved food safety testing and monitoring. Although challenges such as accessibility and cost remain, future developments in molecular diagnostics will lead to greater implementation in improving pathogen management throughout the food supply chain.

Decidualization of the uterine endometrium is a critical process for embryo implantation in mammals, primarily occurring on gestational day 8 in pregnant mice. However, the interplay between the maternal gut microbiome, metabolism, and the uterus at this specific time point remains poorly understood. This study employed a multi-omics approach to investigate the metabolic, gut microbiome, and transcriptomic changes associated with early pregnancy (gestational day 8 (E8)) in mice. Serum metabolomics revealed a distinct metabolic profile in E8 compared to controls, with differential metabolites primarily enriched in amino acid metabolism pathways. Gut microbial composition showed that E8 mice exhibited higher alpha-diversity and a significant shift of beta-diversity. Specifically, the E8 group displayed a decrease in pathogenic Proteobacteria and an increase in beneficial Bacteroidetes and S24-7 taxa. Transcriptomics identified myriads of distinct gene between E8 and control mice. The differentially expressed genes were enriched in pathways involved in Alanine, Aspartate and Glutamate metabolism, PI3K-Akt signaling, and PPAR signaling pathway. Integrative analysis of the multi-omics data uncovered potential mechanistic relationships among the differential metabolites, gut microbiota, and uterine gene expression changes. Notably, the gene Asns showed strong correlations with specific gut S24-7 and metabolite L-Aspartatic acid, suggesting its potential role in mediating the crosstalk between the maternal environment and embryo development during early pregnancy. These findings provide valuable insights into the complex interplay between the maternal metabolome, gut microbiome, and uterine transcriptome in the context of early pregnancy, which may contribute to our understanding of the underlying mechanisms of embryo implantation and development.

This article addresses the complex challenge of simultaneously enhancing contrast and detail in an image, where improving one property often compromises the other. This trade-off is tackled using a multi-objective optimization approach. Specifically, the proposal's model integrates the sigmoid transformation function and unsharp masking highboost filtering with the NSGA-II algorithm. Additionally, a posterior preference articulation is introduced to select three key solutions from the Pareto front: the maximum contrast solution, the maximum detail solution, and the knee point solution. The proposed technique is evaluated on a range of image types, including medical and natural scenes. The final solutions demonstrated significant superiority in terms of contrast and detail compared to the original images. The three selected solutions, although all are optimal, captured distinct characteristics within the images, offering different solutions according to field preferences. This highlights the method's effectiveness across different types and enhancement requirements and emphasizes the importance of the proposed preferences in different contexts.

Integrated nutrient management (INM) is an approach that optimizes the benefits derived from various nutrient sources and beneficial soil microorganisms in an integrated manner to increase crop productivity while maintaining soil fertility. An open-field experiment was conducted at Cabuyao, Laguna, Philippines to investigate the effects of combining chemical fertilizers, vermicompost, arbuscular mycorrhizal fungi (AMF), and nitrogen-fixing bacteria (Azospirillum spp.) on the growth, nutrient uptake and yield of tomato. The experiment was arranged in a randomized complete block design replicated four times. The treatments were recommended rate of chemical fertilizer (RRC), combined 50% RRC and 4 t ha-1 vermicompost (INM 1), AMF inoculation with combined nutrient sources (INM 2), and dual inoculation with AMF and Azospirillum in synergy with combined nutrient sources (INM 3). Results revealed that the growth parameters were not significantly affected by the treatments, but the highest data were observed in the treatments under INM. AMF inoculation significantly increased phosphorus, potassium, calcium, and magnesium uptake of tomato while INM 3 recorded the highest nitrogen uptake. Treatments with vermicompost application recorded significantly higher uptake of copper. INM 1, INM 2, and INM 3 gave a significantly higher fruit yield than the RRC with an increase of 7.98%, 13.40%, and 13.65%, respectively. The percentage of mycorrhizal root colonization and number of rhizosphere spores were higher in mycorrhizal plants. Fruit yield and AMF root colonization are positively correlated with uptake of various nutrients. The results imply that these INM strategies can improve growth of tomato, increase fruit yield, reduce the amount of chemical fertilizers applied, and potentially lead to economic, soil health and environmental benefits.

Novel ZNF proteins such as ZNF671 that are located on chromosome 19q13 are known to be hypermethylated at a high frequency in HNSCC as well as in other epithelial solid tumors. Their function is largely unknown. Here, we show that ZNF671 is epigenetically silenced in HNSCC primary tumors compared to matched adjacent normal tissue. Moreover, low expression of ZNF671 is significantly associated with decreased survival in HNSCC patients. Over-expression of ZNF671 in UM-SCC-1 oral cancer cells resulted in a significant reduction in tumor cell mobility and invasion compared to the empty-vector control cells. Transcriptomic analysis showed that ZNF671 re-expression resulted in a significant decrease in the expression of a major oncogenic long non-coding RNA LINC00665. Together, these results suggest that epigenetic silencing of ZNF671 may activate multiple oncogenic signaling pathways via the resulting up-regulation of LINC00665.

Background: The implementation of tyrosine kinase inhibitors (TKIs) in the treatment of chronic myeloid leukemia (CML) has brought a significant improvement in the prognosis for CML patients and a decrease in the number of patients requiring allogeneic hematopoietic stem cell transplantation (allo-HCT). Nevertheless, the impact of TKIs on allo-HCT outcomes have not been thoroughly explored. Objectives: The main endpoint of our research was to assess the impact of prior TKI treatment on acute graft-versus-host disease (aGvHD) and chronic graft-versus-host disease (cGvHD). Methods: In our retrospective analysis we included 240 patients treated between 1993 and 2013, and divided them into 3 groups according to the therapy administered prior to matched related or matched unrelated donor allo-HCT (imatinib group n=41, dasatinib/nilotinib group n=28, TKI naïve group n=171). Results: Both the cumulative incidence of aGvHD (p=0.044) and cGvHD (p&lt;0.001) in individuals receiving second generation TKIs (2G-TKIs) prior to allo-HCT compared to patients receiving no TKIs or imatinib (IMA) (40.7% vs 61.4% vs 70.7%, p=0.044; 25.0% vs 76.4% vs 51.2%, p&lt;0.001, respectively). In case of the 2G-TKI cohort, the number of low-grade aGvHD and cGvHD was significantly lower compared to the IMA and TKI-naïve groups (p=0.018, p=0.004; p&lt;0.001 versus TKI-naïve, respectively). In terms of 3-year overall survival (OS) there were no important variations between TKI-naïve, IMA and 2G-TKI (55% vs 49.9% vs 69.6%, p=0.740). Conclusions: The results of our study suggest that TKI treatment prior to allo-HCT may have protective impact on immune-mediated outcomes.

Recent advancements in nanotechnology have led to the development of multifunctional iron oxide nanoparticles, presenting new opportunities in cancer therapy. This study aimed to synthesize and evaluate citric acid-coated/ folic acid conjugated nanoparticles loaded with doxorubi-cin and investigate their efficacy in experimental tumor models. For synthesis, controlled co-precipitation method was employed to produce highly dispersive, multifunctional nanofluids with a narrow size distribution of iron oxide nanoparticles. Nanoparticles were characterized using Dynamic Light Scattering (DLS) and Electrophoretic Light Scattering (ELS) for size distribution and zeta potential, X-ray Diffraction (XRD) and Transmission Electron Microscopy (TEM) for structure and morphology, Vibrating Sample Magnetometry (VSM) for magnetic properties, and UV-Visible (UV-Vis) and Fourier-Transform Infra-red (FTIR) spectroscopy for modification confirmation. In vitro experiments employed RM1 (prostate cancer) and MEC1 (Chronic lymphocytic leukemia) cell lines to assess cytotoxicity and drug delivery efficiency. Fluorescence microscopy confirmed the intracellular delivery of doxorubicin by these nanoparticles, highlighting their potential for targeted therapy. As a result, nanoparticles conjugated with folic acid showed reduced efficacy over time. This study underscores the critical role of nanoparticle modifications in optimizing therapeutic outcomes. Future research should focus on further refining nanoparticle formulations and long-term effects in vivo, for development of effective and safe agents for targeted cancer treatment.

Inhalation allergies caused by cats and dogs can lead to a range of discomforting symptoms, such as rhinitis and asthma, in humans. Given the increasing popularity and care provided to these companion animals, the allergens they produce pose a growing threat to the health of susceptible patients. Allergens from cats and dogs have emerged as significant risk factors for triggering asthma and allergic rhinitis worldwide; however, there remains a lack of systematic measures aimed at assisting individuals in recognizing and preventing allergies caused by these animals. This review provides comprhensive insights into the classification of cat and dog allerges, alongwith their pathogenic mechanisms. The study also discusses implementation strategies for prevention and control measures, including physical methods, gene editing technology, immunological approaches, as well as potential strategies for enhancing allergen immunotherapy combined with immunoinformatics. Finally, it presents future prospects for the prevention and treatment of human allergies caused by cats and dogs. This review will improve knowledge regarding allergies to cats and dogs, while identifying potential targets for the development of next-generation treatments.

In the dynamic arena of healthcare research, where the complexities of data often rival the intricacies of biological systems, the ability to model and analyze such multifaceted datasets is crucial. This comprehensive review delves into the evolution and application of Soft Sets and their extensions, including HyperSoft Sets, SuperHyperSoft Sets, IndetermSoft Sets, IndetermHyperSoft Sets, and TreeSoft Sets, in healthcare claims data analysis. These extensions address intricate challenges in data analysis, offering versatile frameworks for managing uncertainty and indeterminacy inherent in healthcare claims data. By exploring their definitions and applications, this review elucidates how these mathematical tools have evolved and their significance in advancing healthcare research and enhancing data analysis methodologies. Real-world examples underscore the implications of these tools, emphasizing their pivotal role in facilitating informed decision-making and knowledge discovery in healthcare. The review systematically examines various case studies and research findings to illustrate the practical utility of Soft Set extensions. Detailed analyses of real-world scenarios highlight advancements in processing complex healthcare data. The conclusions drawn from this analysis indicate that the adoption of Soft Sets and their extensions can significantly improve the accuracy and efficiency of healthcare data analysis, ultimately contributing to better healthcare outcomes and more informed policy-making. Future research directions are also discussed, suggesting further potential applications and developments in this field.

Satellite clock bias (SCB) prediction is a crucial technology for satellite navigation systems, holding significant importance for Global Navigation Satellite System. This paper proposes a deep learning model for SCB prediction based on the fusion of the Beluga Whale Optimization (BWO), Convolutional Neural Network (CNN), Bidirectional Gated Recurrent Unit (BiGRU), and an attention mechanism. The CNN is utilized to extract the spatiotemporal characteristic information from the clock bias sequence, while the BiGRU fully extracts relevant features through forward and backward propagation. The introduction of an attention mechanism aims to preserve essential features within the clock bias sequence to enhance feature extraction by both CNN and BiGRU networks. Additionally, the BWO is employed to optimize parameter selection in order to improve model accuracy. Experimental verification demonstrates that for the BeiDou Navigation Satellite System's (BDS) hydrogen-maser atomic clocks, the predicted clock bias for 6 hours, 3 days, and 15 days are 0.078 ns, 0.475 ns, and 2.130 ns respectively - representing improvements of 31%, 45%, and 66% over CNN-BiGRU-Attention; 6%, 51%, and 56% over CNN-BiGRU; and 32%, 35%, and 73% over BiGRU, respectively.

Objectives: The goal of this pilot study was to validate and introduce a new AI tool (algorithm), providing and comparing (1) the periodontal/peri-implant diagnosis between professional (specialist) and automated tool, (2) risk assessment and prognostication with the algorithm, and (3) establish cut-off limits for clinically significant disease with a new score system (GF-PeDRA score). Methods: All patients were evaluated by two evaluators, and in case of any divergence, the case was revisited and discussed until clarification and definition. The validation sample constituted 221 patients. The AI tool (GF-PeDRA©) had eighteen parameters to be assessed, involving systemic and local predictors, achieving an octadecagon (an eighteen-sided polygon). The parameters were: (1) The highest probing depth (PD); (2) Number of interproximal sites with bone loss; (3) The highest clinical attachment loss (CAL); (4) Maximum radiographic bone loss (RBL); (5) Bleeding on probing (% BoP); (6) Bone loss pattern; (7) Tooth loss including periodontally hopeless teeth planned for extraction; (8) Evidence of progression over five years; (9) Need for complex rehabilitation; (10) Patient’s age; (11) CAL and biofilm accumulation; (12) Smoking; (13) Diabetes; (14) Extension and distribution of the disease; (15) Peri-implant disease; (16) Other systemic conditions (other than diabetes); (17) Furcation involvement; and (18) Necrotizing lesion. A new score system (GF-PeDRA© score) based on the percentual of the octadecagon area is obtained; if the area was ≥0% to ≤9%, the prognosis is good; ≥10% and ≤ 24%, it is fair; ≥25% and ≤37%, poor; ≥38% and ≤49%, it is questionable; and between ≥50% to ≤100%, the prognosis is hopeless. Results: 221 patients were enrolled, with a mean age of 46.73. 5301 teeth were examined. 187 non-smokers (84.62%) and 34 smokers (15.38%) were included. 193 (87.33%) patients did not have diabetes, whereas 28 (12.67%) had. Comparing the diagnosis between both evaluators, k=0.83; all disagreed cases were re-discussed, and a final decision/diagnosis was reached. After this, the diagnosis found was contrasted with the diagnosis achieved by GF-PeDRA© and a perfect agreement was observed, 100% (k=1.0). 28 patients were diagnosed as periodontally healthy, 55 with plaque-induced gingivitis, and 138 with periodontitis. Only one case of molar/incisor pattern was observed. No peri-implant disease or necrotizing condition was found. The mean CAL found was 3.19 mm; 25 patients (11.31%) had a furcation involvement. The mean percentual of BoP found was 28.67% (median = 19%; maximum: 100%; minimum: 100%); and the mean PD was 5.31 mm. The mean of the new GF-PeDRA© score (ranging from 0% to 100%) was 28.64%, with a median of 32.2% (minimum: 0.6% and maximum: 64.1%). Then, analyzing the GF-PeDRA© score of 221 patients enrolled, 48 (21.73%) were sorted as a Good prognosis for periodontal treatment, 43 (19.45%) had a Fair prognosis, 43 (19.45%) had a Poor prognosis, 68 (30.77%) had a Questionable prognosis, and 19 (8.60%) had a Hopeless prognosis. Conclusion: The new AI tool (GF-PeDRA©) was validated and proved to be extremely helpful in diagnosing and providing risk assessment and prognosis.

This paper explores a novel approach to establishing the topological equivalence of manifolds embedded in ℝ

Nasal polyposis is defined by a Th2-driven chronic inflammation of the nose and sinus with polyps visible in the nasal fossae. It is a prevalent disease with a significant impact on the HRQL. Allergy, allergic rhinitis, asthma, and aspirin intolerance are frequently associated. The management is individual. The first line of treatment is a long-term treatment with intranasal corticosteroids. Oral corticosteroids should be used with caution. When the medical treatment fails the patient is eligible for sinus surgery. In case of symptomatic recurrence after both medical treatment and ethmoidectomy, biologics are nowadays a very promising treatment effective on all the respiratory tract. Dupilumab seems in the literature the molecule of choice. However, besides the international guidelines published by EPOS and Euforea, the molecule prescribed depends also on the availability of it in each country and the criteria edited by the health authorities to get reimbursement. Long treatment is mandatory. Traditional medical treatment is necessary as a complement to biologics.

Background/Objectives: Dengue is an arbovirus caused by a virus. It is an endemic infectious and occurs in warmer climates. It is not uncommon for the disease to be asymptomatic. However, the severe form can also be triggered and require intensive care. In this sense, patients present a wide variety of symptoms, which can trigger comorbidities such as arthritis, hematologic diseases, liver diseases, kidney diseases, autoimmune diseases, and, mainly, diabetes and hypertension. Among the symptoms, the presence of fever, myalgia, headache, nausea, vomiting, leukopenia, petechiae, retroorbital pain, arthralgia, rashes, skin eruptions, cardiovascular symptoms, respiratory symptoms and, depending on the severity, the presence of hemorrhages may occur. Methods: 235 patients' anonymized records from a secondary hospital were analyzed. Ethics approval was obtained and no patients’ consent was needed. Statistical analysis used frequency distributions and Chi-square tests, with SPSS software. Results: Similar to other studies, our results show that dengue can lead to complications. Furthermore, there was no significant difference in the distribution of the proportion of symptoms between patients with positive and negative serology. However, there was a significant association between age group and symptoms of fever and myalgia, with the occurrence of fever decreasing with increasing age and myalgia being more frequent in adults and less frequent in those &lt;10 years old. Conclusions: Dengue can lead to complications, with fever becoming less common and muscle pain increasing as people age. Climate change could spread dengue to new areas. To address this, we need better vaccines and more effective mosquito control.

Background: The Advanced Lung Cancer Inflammation Index (ALI) is a novel, comprehensive index that integrates inflammation and nutritional status, incorporating parameters such as albumin, body mass index (BMI), and the neutrophil-to-lymphocyte ratio (NLR). Unlike traditional inflammation biomarkers, this study aims to evaluate the prognosis of IPF patients by considering both inflammation and nutritional status. Method: A total of 102 patients with IPF were included in the study. Clinical data were obtained from the patients' medical records. NLR and ALI score were calculated based on data collected at the initiation of antifibrotic treatment using the following formula: Neut/Lym and albumin × BMI / NLR. Results: IPF subject subgroups in terms of ALI based on gender–age–physiology (GAP) stages (1,2,3), FVC (median split,