A conventional electrical grid mostly depends on the electrical power generated from fossil fuels. However, the pollutants from fossil fuels are the key factors for adverse climate change. Most of the developed countries of the world have already recognized the fact that the energy mix requires to be diversified by incorporating renewable energy. This is especially relevant for many of the member countries of the Organization of Islamic Cooperation (OIC), consisting of 57 countries, whose abundance of fossil fuel reserve indicates that much of their electric power is still generated from fossil fuels. In order to integrate renewable energy sources into the hybrid energy mix, an existing conventional grid needs to undergo drastic changes. Alongside this, the population boom in the OIC member countries has caused higher demand for a steady supply of electricity that the conventional grids have long been struggling to cope with. With a view to solving this multifaceted problem, incorporation of the smart power management schemes is indispensable using a smart electrical grid, where information and communications technology is integrated into its major building blocks. This allows advanced applications of a grid, such as the formation of micro-grids, demand-side management, energy storage, high-tech power electronic converters, etc. As the smart grids are being adopted by many developed countries, it is high time for the OIC member countries to pay due attention to this development, if they have not already done so. This paper explains, with special focus on the OIC member countries, the various smart power management technologies, their operations and applications, and the benefits and challenges. Then it goes on to carry out the Strength-Weakness-Opportunity-Threat with Analytical-Heuristic-Procedure (SWOT-AHP) analysis to evaluate its feasibility of incorporation and the underlying strategies appropriate for its implementation. Furthermore, a Hybrid Multi-Criteria-Decision-Making (MCDM) analysis is performed to evaluate the sequence of the emphasis that should be given on each of the technologies from those available for the smart power management initiative. Finally, the study reinforces the stance by drawing parallels from the UN Sustainable Development Goals (SDG) and highlights the importance of the smart grid in line with the global vision of SDG. This paper aims at assisting the decision-makers in implementing smart power management schemes in the OIC member countries, in particular, and other countries of the world, in general.

Magnesium (Mg) is a vital element, which involves in various key cellular processes in plants. Mg transporter (MGT) genes play an important role in magnesium distribution and ionic balance maintenance. Here, MGT family members were identified and characterized in three species of the plant family Malvaceae, including Theobroma cacao, Corchorus capsularis, and Gossypium hirsutum to improve our understanding of their structure, regulatory systems, functions, and possible interactions. We identified 18, 41, and 16 putative non-redundant MGT genes from the genome of T. cacao, G. hirsutum, and C. capsularis, respectively, which were clustered into five groups within maximum likelihood tree. Several segmental/tandem duplication events were determined between MGTs genes. It seems that MGTs were slowly evolving and have been evolved under a purifying selection. Analysis of gene promoter regions showed that MGTs have a high potential to respond to biotic/abiotic stresses as well as hormones. The expression patterns of MGT genes revealed their possible T. cacaorole in response to P. megakarya fungi in T. cacao, whereas MGT genes showed differential expression in various tissues and respond to several abiotic stresses, including cold, salt, drought, and heat stress in G. hirsutum. Besides, the co-expressions network of MGTs indicated that genes involved in auxin responsive, lipid metabolism, cell wall organization, and photoprotection can interact with MGTs.

Metabolic pathways provide key information to achieve a better understanding of life and all its processes; this is useful information for the improvement of medicine, agronomy, pharmacy, and other similar areas. The main analysis tool used to study these pathways is based on the idea of pathway comparison, using graph data structures. Metabolic pathway comparison has been defined as a computationally complex task \cite{ay2011submap,abaka2013campways}. In previous work from 2017, two different approaches that simplify the problem of comparing pathways represented as graphs were introduced. The first algorithm consists of the transformation of a two-dimensional graph structure, representing a metabolic pathway, to a one-dimensional structure and thus aligning the corresponding data using a reduced 1 dimension string. The second algorithm consists of performing a paired analysis between reactions in pathways and thus eliminating all similarities, finally, showing these differences to the user. The suggestion is to use the information provided by these algorithms as a previous analysis to a deeper, more expensive, comparison tool use. Here we provide an extension of this work with more data and deeper analysis. These methods have shown to be an effective way to treat the problem of metabolic pathway comparison as listed in the discussion and results section. Our results show evidence of a quick, simple and effective way to resolve the described problem.

In recent years, weeds is responsible for most of the agricultural yield losses. To deal with this threat, farmers resort to spraying pesticides throughout the field. Such method not only requires huge quantities of herbicides but impact environment and humans health. One way to reduce the cost and environmental impact is to allocate the right doses of herbicide at the right place and at the right time (Precision Agriculture). Nowadays, Unmanned Aerial Vehicle (UAV) is becoming an interesting acquisition system for weeds localization and management due to its ability to obtain the images of the entire agricultural field with a very high spatial resolution and at low cost. Despite the important advances in UAV acquisition systems, automatic weeds detection remains a challenging problem because of its strong similarity with the crops. Recently Deep Learning approach has shown impressive results in different complex classification problem. However, this approach needs a certain amount of training data but, creating large agricultural datasets with pixel-level annotations by expert is an extremely time consuming task. In this paper, we propose a novel fully automatic learning method using Convolutional Neuronal Networks (CNNs) with unsupervised training dataset collection for weeds detection from UAV images. The proposed method consists in three main phases. First we automatically detect the crop lines and using them to identify the interline weeds. In the second phase, interline weeds are used to constitute the training dataset. Finally, we performed CNNs on this dataset to build a model able to detect the crop and weeds in the images. The results obtained are comparable to the traditional supervised training data labeling. The accuracy gaps are 1.5% in the spinach field and 6% in the bean field.

Class attendance in institutions of higher learning plays a major role in the success of students and as such putting in measures to curb absenteeism of students would go a long way to help improve their grades. This research sought to design a ‘Bring Your Own Device’ System which will be very suitable for the post-COVID era as well as the fast-growing university community. The research results in a mobile-based attendance infrastructure used by students to prove their presence for class sessions. Flutter, a Software Development Kit (SDK) was used to program the mobile platform and Firebase was used for both the authentication and database. This system also comes in as an improvement on most existing systems as it functions on both Android and iOS. After the testing phase, the models achieved high accuracy and the proposed design has proven to have great potential. This solution stands beyond a research model as a ready-to-use platform.

Background: Helicobacter pylori (H. pylori) is a prevalent bacterial pathogen implicated in various gastroduodenal diseases, including chronic gastritis, peptic ulcer disease, and gastric cancer. The COVID-19 pandemic has significantly influenced antibiotic prescription practices, potentially exacerbating antibiotic resistance in H. pylori. Objective: This study aims to investigate antibiotic prescription during COVID-19 pandemic in Croatia and its possible impact on H. pylori antibiotic resistance, with a focus on Croatia. Methods: A comprehensive literature search was conducted to identify relevant studies from March 2020 to June 2024. The search strategy included terms related to COVID-19, antibiotic prescription, and Croatia. Studies were selected based on predefined eligibility criteria, focusing on observational research addressing antibiotic use during the pandemic. Results: The COVID-19 pandemic leads to significant fluctuations in community antibiotic consumption within the European Union/European Economic Area. In Croatia, antibiotic use in 2022 surpassed 2019 levels, driven by increased consumption of macrolides and other antibiotics. This surge, influenced by early pandemic treatment claims and penicillin shortages, contributed to rising antibiotic resistance in H. pylori. Resistance rates to clarithromycin and levofloxacin were notably high, driven by mutations in the 23S rRNA, gyrA, and gyrB genes. Discussion: The increased antibiotic use during the COVID-19 pandemic has highly likely complicated H. pylori eradication efforts, highlighting the necessity of judicious antibiotic use and robust antimicrobial stewardship. The pandemic underscored the need for new therapeutic strategies, optimized eradication regimens, and advanced diagnostic methods to manage bacterial infections effectively. Conclusions: The COVID-19 pandemic has significantly impacted antibiotic use and resistance patterns, posing new challenges for H. pylori eradication. Addressing these challenges requires a multifaceted approach, including the development of new drugs and advanced diagnostics, coupled with sustained efforts in antimicrobial stewardship to combat emerging resistance threats.

Life is a field of senses and the experience of feeling, thinking, acting, and building relationships with everything around us. These senses and experiences are also consumed in travel destinations to pursue the traveler's escapism and happiness. However, while the field of tourism studies has recognized the importance of experience and focused on the relationship between various travel experiences and happiness, research on the variables that mediate and strengthen these relationships is lacking. Therefore, this study aims to apply the five strategic experiential models proposed by Schmitt [1]— sense, feel, think, act, and relate — to investigate the mediating effect of escapism on travelers' well-being. Data were collected from travelers visiting three major heritage sites in Gyeongju (Bulguksa Temple, Seokguram Grotto, and Bunhwangsa Temple), and 509 responses were used for analysis. The analysis was conducted using statistical package programs SPSS and AMOS employing frequency analysis, reliability analysis, confirmatory factor analysis, and structural equation modeling. The results indicated significant positive effects between variables such as cultural heritage travel experience, escapism, and well-being. In the analysis of the mediating effect of escapism, escapism showed a significant mediating effect on the relationship between travel experience and well-being. This study confirmed that, during cultural heritage travels, individuals’ well-being can be enhanced through a holistic experience encompassing sensory, emotional, cognitive, behavioral, and relational aspects rather than an isolated experience centered on escapism. This finding provides important implications for the design and planning of travel programs and products.

This paper highlights the importance of one-shot learning from prototype SKU images for efficient product recognition in retail and inventory management. Traditional methods require large supervised datasets to train deep neural networks, which can be costly and impractical. One-shot learning techniques mitigate this issue by enabling classification from a single prototype image per product class, thus reducing data annotation efforts. We introduce the variational prototyping-encoder (VPE), a novel deep neural network for one-shot classification. Utilizing a support set of prototype SKU images, VPE learns to classify query images by capturing image similarity and prototypical concepts. Unlike metric learning-based approaches, VPE pre-learns image translation from real-world object images to prototype images as a meta-task, facilitating efficient one-shot classification with minimal supervision. Our research demonstrates that VPE can significantly reduce the need for large datasets while accurately classifying query images into their respective categories, providing a practical solution for product classification tasks.

Transformation formula under the action of a general linear fractional transformation for generalized Dedekind eta-function has been a subject of intensive study, Rademacher, Dieter, Meyer et al. However, the (Hecke) modular relation structure has not been recognized until the work of Goldstein-de la Torre, and streamlining the classical proofs in the modular relation will reveal the meaning hidden in those works. Our main aim is to elucidate the works of these researchers in the context of modular relations.

The current study was formulated with the aim of assessing the impact of the Extent of Drug addiction on the Family environment and interventions for drug-addicted youth in rural areas of Dir Lower Khyber Pakhtunkhwa, Pakistan. The study comprised a dependent variable (Extent of Drug addiction) and an independent variable (Family Environment). A sample size of 266 was randomly selected for primary data collection through structured interviews. The collected information was evaluated through descriptive analysis (frequency and percentage distribution) and inferential analysis, specifically utilizing the Chi-square Statistical Test. The study concluded that drug addiction among youth has an adverse impact on the family environment, leading to instability and violent behavior. Further, families of drug-addicted youth experience a high level of dissatisfaction in relationships, often culminating in divorce. Similarly, the families of drug-addicted are characterized by low cohesion, role conflict, and tolerance. Thus, the government should formulate polices and strategies for the prevention of drug addiction, with speedy implementation across all institutional dynamics, including family. Moreover, It is also crucial to rehabilitate the lifeblood of a nation (youth) in terms of socio-economic, emotional and psychological growth. These recommendations were put forward in the light of the current study.

Continuous cropping of Platycodon produces problems that significantly impact its yield and quality making it a pressing issue that requires immediate attention. In this study, the sandwich method is employed to evaluate the allelopathic activity of different plant parts (leaves, stems, and roots) of Platycodon. The inhibitory effects of the various Platycodon plant parts were quantified based on their effects on lettuce seedlings growth by Sandwich method, with the following average inhibition percentages at 1 mg/ml (agar) of : leaves (79.4%, 61.8%), stems (58.0%, 45.7%), and roots (53.4%, 49.3%) for lettuce radicals and hypocotyls, respectively. At a concentration of 5 mg/ml, the inhibitory effects were as follow: leaves (91.9%, 72.2%), stems (79.5%, 60.3%), and roots (71.4%, 65.2%). Also, by employing the Plant Box method, it was determined that Platycodon root exudation. The growth inhibition rates of lettuce seedling roots and hypocotyls were 45.5% and 18.9%, respectively. The effect of activated carbon on the adsorption of allelopathic substances was investigated, and the results of the sandwich method with a concentration of 1 mg/ml showed the following growth inhibitory effects on lettuce seedlings and hypocotyls: roots (27.8%, 25.7%), leaves (13.3%, 25.7%), and stem (9.07%, 13.6%). The Plant Box method revealed average rates of inhibition of -16.7% and -4.70% on the growth of lettuce seedlings and hypocotyls, respectively. The results of this study demonstrated that activated carbon has a mitigating effect on the allelopathic inhibition associated with the different plant parts and root exudation of Platycodon, thus may provide a potential solution for overcoming obstacles associated with continuous cropping of Platycodon.

In order to explore the effect of fertilization patterns on the growth of rapeseed seedlings under waterlogging stress, three fertilization patterns (conventional fertilization, supplemental organic fertilization, and supplemental microbial fertilization) were set up using the variety Xiangyou 708 as the material, and waterlogging treatment was carried out during the seedling stage of rapeseed. The effects of fertilization patterns on the growth of rapeseed seedlings and rhizosphere microorganisms under waterlogging stress were investigated. The results showed that all three fertilization patterns exhibited that waterlogging stress inhibited the growth of rapeseed seedlings, inhibited root activity, and changed the structure of rhizosphere bacterial colonies. However, supplemental organic fertilization and microbial fertilization could better promote the growth of rapeseed seedlings, reduce the impact of waterlogging stress on the growth of rapeseed seedlings, and accelerate the recovery of rapeseed seedlings after waterlogging stress. In addition, supplemental microbial fertilization could also change the structure of rhizosphere bacterial colonies. Under normal water supply, supplemental organic fertilization enriched P_Bacteroidota, P_Actinobacteriota, P_Chloroflexi, and G_Flavisolibacter in the rhizosphere soil of rapeseed, while supplemental microbial fertilization enriched P_Bacteroidota and G_Flavisolibacter in the rhizosphere soil of rapeseed. After 7 days of waterlogging treatment, supplemental organic fertilization enriched P_Verrucomicrobiota in the rhizosphere soil of rapeseed, while supplemental microbial fertilization enriched P_Actinobacteriota, G_SC-I-84, and G_Ellin6067 in the rhizosphere soil of rapeseed. The enrichment of these bacteria may be related to the growth promotion and waterlogging tolerance of rapeseed. This study provides evidence that microbial fertilizer and organic fertilizer can promote the growth of rapeseed and enhance its waterlogging tolerance, as well as evidence that some rhizosphere microorganisms have a potential role in promoting the growth and waterlogging tolerance of rapeseed.

Sterol regulatory element-binding proteins (SREBPs) are transcription factors that regulate genes involved in the biogenesis of cholesterol, fatty acids, and triglycerides. SREBPs are involved in the pathogenesis of non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), fibrosis, and hepatocellular carcinoma (HCC). We review the mechanisms by which SREBPs regulate lipogenesis, the alterations in these processes associated with liver diseases, and therapeutic strategies to target these pathways.

Plants of the golden Camellia group are not only high-quality camellia germplasm , but also a plant group with rich medicinal and nutritional value, which are used as food, cosmetics and traditional medicine in China. There are approximately 50 species in this group around the world, and more than 30 species of golden camelliaplants have been published in China. The leaves and flowers of these species have similar shapes, so they are often confused as species. Our study used simplified genome sequencing technology to construct a phylogenetic tree of plants in the Chinese golden Camellia group and describe the evolutionary relationships . At the same time, the secondary metabolic indexes of total phenols, total flavonoids, total anthocyanins and ellagic acid in the leaves were determined., and principal component clustering analysis was performed . The results showed that the chemical classification and genetic phylogenetic trees showed some of the same trends, indicating that Camellia chinensis can be used as Biomarkers for chemical type. The research results provide phylogenetic information for the genotype and performance diversity of golden camelliaregionally distributed in China. At the same time, molecular biology phylogenetic methods are used to understand or explain the characteristics of secondary metabolites of golden Camellia , and provide theoretical basis for the search and development of potential bioactive substances.

Conical emission is a typical nonlinear phenomenon that occurs when the femtosecond laser pulses interact with transparent media. In this work, the conical emission induced by two kinds of typical vortex beams (i.e., Laguerre-Gaussian (LG) and Bessel-Gaussian (BG) beams) in water is experimentally studied. By recording the light spots of different wavelengths on the screen, the characteristics of the conical emission induced by femtosecond vortex beams are studied. It is found that the spots of the supercontinuum induced by the two kinds of vortex beams differ greatly from each other: The spots of the supercontinuum induced by the BG beam are a set of concentric rings like a rainbow with a white center, while the whit light spot in the case of the LG beam are a circular white disk, which is different from the commonly observed white light spots. By measuring the maximum divergence angle, it is observed that the divergence angle increases with the decrease of the wavelength, while the TC merely affects the divergence angle, which is explained from the formation mechanism of conical emission in terms of self-phase modulation. We hope this work can be helpful to the understanding of interaction between the intense laser pulses and matters.

Candidatus Accumulibacter belongs to phosphate-accumulating organisms (PAO) which exhibit cyclic metabolism and are capable of intracellular polyphosphate accumulation and their hydrolysis under feast-famine anaerobic-aerobic cycling. In consortia of activated sludge microorganisms, these bacteria are responsible for enhanced biological phosphorus removal (EBPR). The spectrum of the substrates used by Ca. Accumulibacter remains insufficiently studied. It was investigated by measuring the oxygen uptake rates (OUR) of Ca. Accumulibacter-enriched culture supplemented with 17 different organic substrates. The highest oxygen uptake rates values were observed in the presence of tryptone, volatile fatty acids (acetate, propionate, and butyrate), succinate, pyruvate, and amino acids (aspartate and glutamate). Phosphate dynamics in the medium under shifts from anaerobic to aerobic cultivation in batch experiments was studied for these compounds (except for tryptone). All tested substrates were shown to cause phosphate cycling (release in the anaerobic phase and uptake in the aerobic one), with OURs for the substrates correlating with the amount of phosphates consumed during the aerobic phase. It was concluded that OUR may be used as an indicator of the monosubstrates used by Ca. Accumulibacter in the anaerobic/aerobic cycle. The possible pathways for substrate transport and metabolism by Ca. Accumulibacter are discussed using the stoichiometric data and the results of metagenomic analysis.

Background: this study aimed to describe the distribution of the genotype and allele frequencies of GJB2 variants in the Chinese population of the Dongfeng Tongji cohort and to analyze the features of the hearing phenotype. Methods: we used data from 9910 participants in the Dongfeng Tongji cohort in 2013 and selected nine GJB2 variants. Pure-tone audiometry was employed to measure hearing. Differences in genotype and allele frequencies were analyzed by chi-squared test or Fisher's exact test. Results: of the 9910 participants, 5742 had hearing loss. The genotype frequency of the GJB2 variant p.V37I was statistically significantly distributed between the normal and impaired hearing groups, but not for the variant c.235delC. A higher frequency of the p.V37I homozygous genotype was found in the hearing loss group (0.5%) than in the normal hearing group (0.1%). Patients with p.V37I and c.235delC homozygous mutations exhibited varying degrees of hearing loss, mainly presenting sloping and flat audiogram shapes. Conclusions: a significant difference was found in the genotype frequency of the GJB2 variant p.V37I between the case and control groups, but not for the variant c.235delC. Different degrees of hearing loss and various audiogram shapes were observed in patients with p.V37I and c.235delC homozygous mutations.

(1) Background: This study aimed to evaluate the implications of IL-31 in the pathogenesis of chronic spontaneous urticaria (CSU) and to assess the differences that occur between its serum values compared to controls. Additionally, the serum IL-31 levels were measured alongside other clinical and paraclinical parameters identified in the patients to understand its immunological importance in this skin disease and to determine if it could potentially serve as a therapeutic target in CSU in the future. (2) Methods: The serum levels of IL-31 were estimated in 50 patients diagnosed with CSU according to the international guidelines. Additionally, 38 controls who had not experienced any episodes of urticaria during their lifetime were included. (3) Results: Our data have shown higher serum levels of IL-31 in CSU patients compared to controls. A correlation between the serum level of IL-31 and other inflammatory markers, such as ERS, CRP, or serum eosinophils and total IgE was not identified. On the other hand, statistically significant differences were found in IL-31 serum values in UCS patients depending on the severity of the disease, its impact on the patients' quality of life, the severity of itching, and the response to H1 antihistamines. (4) Conclusions: In the present study, IL-31 did not change directly with non-specific inflammation, nor with eosinophilic inflammation or atopy. However, its expression was modified in CSU depending on major characteristics of the disease: severity, pruritus, and response to H1 antihistamines. The focus on the pathogenesis of CSU is of indisputable significance since any additional information in understanding the mechanisms of this disease can open doors to new therapeutic targets. This is particularly important considering that the available therapies are deficient, incomplete, and the remaining symptoms are uncontrolled in many cases.

Tamanu oil has traditionally been used to treat various skin problems. The oil has wound-healing and skin-regenerating capabilities, and encourages the growth of new skin cells, all of which are helpful for fading scars and hyperpigmentation, as well as promoting an all-around glow. The strong nutty odor and high viscosity are the major disadvantages associated with their application. The aim of this study was to create bigels using tamanu oil for its anti-scarring properties. Bigels were prepared with Tamanu oil ranging from 5 to 20% along with micronized xanthan gum and evaluated for their pH, viscosity, and spreadability. In silico studies were performed to analyze the binding affinity of the protein with the drug, and the anti-scarring activity was established using a full-thickness excision wound model. In silico studies have reported that the components Calanolide A, Inophyllum C, and 4-Norlanosta-17(20),24-diene-11,16-diol-21-oic acid, and 3-oxo-16,21-lactone had docking scores of -9.8, -11.3, and -11.1, respectively with the cytokine TGF- β1 receptor. An acute dermal irritation study in rabbits showed no irritation, erythema, eschar, or edema. In vivo excisional wound healing studies performed on wistar rats and subsequent histopathological studies showed that bigels had better healing properties when compared to the commercial formulation (Murivenna oil). This study substantiates the wound healing and scar reduction potential of Tamanu oil bigels.

Bacteria’s ability to withstand the detrimental effects of antimicrobials may take the form of resistance or tolerance with the minimum inhibitory concentration (MIC), the mutant prevention concentration (MPC), and the mutant selection window as salient concepts. Isolates exposed for 30 days to different concentrations of selected antibiotics, biocides, and heavy metals, singly and in combination, were additionally exposed to very high (15 × MIC) concentrations of ampicillin., and their tolerance was calculated the time to kill 99.9% of the isolate population (MDK99.9). These values were increased by 30 to 50% in test isolates compared to the untreated control. BAC 10-exposed isolates had the highest tolerance increase, and the tolerance appeared to originate from two sources, i.e., stochastic persistence and genetic-induced persistence, involving multiple genes using diverse mechanisms. The mutant selection window of the isolates to ampicillin, amoxicillin, and oxytetracycline also slightly increased compared to the control, indicating the amplification of persister cells during the 30-day exposure. These findings indicate that bacterial exposure to sub-inhibitory concentrations of environmental chemical stressors may not always result in the development of antimicrobial resistance but could initiate this process by selecting for persisters that could evolve into resistant isolates.

In post-COVID-19 syndrome, clinical presentation of the nerve fiber dysfunction plays an important role. The possibility of autoantigen cross-mimicry of coronavirus infection and the peripheral nervous system need to be investigated. The bioinformatic analysis was applied to search for possible common protein sequences located in the immunological epitopes. Among the autoantigens of the human nervous system, fibroblast growth factor receptor protein 3, myelin protein P0, myelin protein P2, sodium channel protein type 9, alpha protein subunit, plexin-D1 protein and ubiquitin-carboxyl-terminal hydrolase protein of the L1 isoenzyme were selected. The “Alignmentaj” program was created. The UniProt database, Protein Data Bank and AlphaFold databases were used. The analysis of protein sequence similarities of spike glycoproteins in human coronaviruses revealed common pentapeptides of the MERS-CoV-2 virus with the fibroblast growth factor receptor 3 and myelin protein P2. Among seasonal coronaviruses, common peptide sequences were identified in HCoV-HKU-1 virus with sodium channel protein type 9 subunit alpha and Plexin-D1, HCoV-OС43 with Plexin-D1, as well as HCoV-NL63 with Plexin-D1 and Ubiquitin carboxyl-terminal hydrolase isozyme L1. The data obtained make it possible to identify new potential targets for the development of autoimmune reactions that occur against the background of the activity of highly pathogenic and seasonal coronaviruses.

Ceruminous gland tumours are rare injuries of the external auditory canal (EAC). This tumor, even if considered a slow-growing carcinoma, has high rate of perineural invasion and metastasis. For this reason, it must be promptly diagnosed, then it must be treated with aggressive surgery combined with postoperative radiation. The present case report is about a case of an adenoid cystic carcinoma arising the external auditory canal of 46 years old female patient, who complained hypoacusis and pain. The profile of medical liability is substantiated on the delayed diagnosis when the lately observed tumor progression by the invasion of both surrounding bone and vascular structures.

Poor hygiene in the food services industry is a critical public health concern in the Maldives, with an average of 35 public complaints per month regarding the poor hygienic conditions of the restaurants in Male’, the capital of Maldives. Thus, this study aimed to identify the level of knowledge, attitude, and the gap of self-reported with the observed practice (KAP) of food handlers as well as the potential association between KAP. 290 food handlers from restaurants were surveyed, demonstrating moderate knowledge (55.5%), moderate attitude (3.62±0.51) and good practice (4.18±0.54). However, it is critical the result shows the food handlers in Male’ have poor practice on the time and temperature control where especially on thawing and storage resulting from a lack of training in the temperature danger zone. The work experience impacting the level of knowledge, education impacts the level of attitude and age, and education and work experience impacting practice. Male’ restaurants mostly employed the foreigners mostly from Bangladesh and the food handlers were identified to have low level of education. Association analysis identified significant relationships between knowledge, attitude, and practice, while the principle component analysis shows categories that are related to each of KAP. This study is fundamental for policymakers to review and improve law enforcement to address the current food safety situation in the Maldives.

The synthesis and structural characterization of a new triangular Cu3-3OH pyrazolato complex of formula, [Cu3(μ3-OH)(pz)3(Hpz)3][BF4]2 (1-Cu3), Hpz = pyrazole, is presented. The triangular unit forms a quasi-isosceles triangle with Cu-Cu distances of 3.3739(9), 3.3571(9), and 3.370(1) Å. This complex is isostructural to the hexanuclear complex [Cu3(μ3-OH)(pz)3(Hpz)3](ClO4)2]2 (QOPJIP). A comparative structural analysis with other reported triangular Cu3-3OH pyrazolato complexes has been done, showing that, depending on the pyrazolato derivative, auxiliary ligand or counter-anion can affect the nuclearity and/or the dimensionality of the system. The magnetic properties of 1-Cu3 are analyzed by experimental data and DFT calculation. A detailed analysis is done on the magnetic properties comparing experimental and theoretical data of other molecular triangular Cu3-3OH complexes, showing that the displacement of the μ3-OH- from the Cu3 plane, together with the type of organic ligands, influences the nature of the magnetic exchange interaction between the spin-carrier centers, since it affects the overlap of the magnetic orbitals involved in the exchange pathways. Finally, a detailed comparison of the magnetic properties of 1-Cu3 and QOPJIP was done, which allowed us to understand the differences in their magnetic properties.

Starch being renewable and biodegradable is a viable resource for developing sustainable and environmentally friendly materials. This work explores the potential of starch/Ca2+ gels based on waxy corn starch (WCS), normal corn starch (NCS), and two high-amylose corn starches, G50 (55% amylose content) and G70 (68% amylose content) as flame-retardant adhesives. Being stored at 57% relative humidity for up to 30 days, the G50/Ca2+ and G70/Ca2+ gels are stable without water absorption or retrogradation. The starch gels with increasing amylose content displayed increased cohesion, as reflected by significantly higher tensile strength and fracture energy. All the four starch-based gels show good adhesive properties on corrugated paper. For wooden boards, because of the slow diffusion of the gels, the adhesive abilities are weak initially but improve with storage extension. After storage, the adhesive abilities of the starch-based gels are almost the same except for G70/Ca2+, which is peeled off from the wood surface by itself. Moreover, all the starch/Ca2+ gels exhibit excellent flame retardancy with limiting oxygen index (LOI) values all around 60. This work demonstrates a facile method to prepare starch-based flame-retardant adhesives simply by gelating starch with a CaCl2 solution, which can be used in paper or wood products.

Introduction: Diclofenac is the most prescribed non-steroidal anti-inflammatory drug worldwide and used to reliev pain and inflammation for inflammatory arthritis. Diclofenac do not slows disease progression and cartialge damage of Rheuamtoid Arthritis individuals. Moreover, it associated with seriuos adverse effects even using regular dose regimens. Drug delivery systems can overcome this issues reducing adverse effects and optmizing efficacy. Objectives: to evaluate the activity of a lipid-core nanocapsule loaded of Diclofenac (DIC-LNC) in an experimental model of adjuvant-induced arthritis and its anti-arthritic properties at the joint components. Methods: The diclofenac nanoformulation was obtained by self-assembling methodology. The stereology analysis aproach was applied for morphological quantification of the volume, density and cellular profile count of the metatarsophalangeal joints of rats induced to adjuvant arthritis. Proinflamatory cytokines and biochemical profile was also obtained. Results: DIC-LNC is able to reduce arthitis compared to control group (p<0.0001) and DIC group (p=0.009). The TNF and IL1 cytokine as well as C-reative protein and Xanthine-oxidade were efficiently reduced by DIC-LNC. Additionally, DIC-LNC reduces synovites and condrocytes lossing compared to DIC (p<0.05)and control group (p<0.05). The synovial space volume was higher for DIC-LNC compared to DIC (p<0.05) and Control (p<0.05). These data are suggesting that DIC-LNC is showing anti-arthritic actvity preserving deep joint components. Conclusion: DIC-LNC is a promissing nanoformulation for clinical use, since is able to reduce joint inflamation and synovits, avoiding damage of cartilage and synovial space at advjuvant athrits. Further studies and developments are necessary to achieve future clinical use.

Drug delivery systems consist of cyclodextrins (CyDs) have kept constant attention for good compatibility, negligible toxicity, and improved pharmacokinetics of drugs. The unique hollow structure has endowed a lot of functions, such as inclusion of guest molecules, functional modification of active hydroxyl groups, and noncovalent interactions. Besides, the polyhydroxy structure has further extended the functions of CyDs by inter/intramolecular interactions and chemical modification. Furthermore, the versatile functions of the complex contribute to physicochemical characteristics alteration of the drugs, therapeutic talent, stimulus-responsive switch, self-assemble capability, and fiber formation. This review attempts to list the recent progress of CyDs and discuss their roles in the drug delivery system. Future perspectives of the construction of CyD-based drug delivery systems are also discussed at the end of this review, which may be the possible directions for the construction of more rational and cost-effective delivery vehicles.

Color plays an important part in human activities, affects circadian cycle and decision making process. Therefore, it is important to investigate human judgment under different color of illumination, especially, because color perception is subjective. In this study, we developed required instrumentation to control the red (R), green (G), Blue (B) and Amber (A) colored light emitting diode (LED) lamp for carrying out Magneto Encephalography (MEG) brain scan. We developed a software to generate all the colors in the visual spectrum, predefined white light combinations and saturation of an illuminated objects by using RGBA color pallet. The lamp is required to control from outside of the MEG electromagnetically shielded room with the LED lamp located inside the MEG room. Hence, USB is used for the communication mode. The feasibility of using LED lamp with MEG brain scanner has been validated for bio-medical and psychological MEG experiments.

Premature ventricular contraction (PVC) is one of the common ventricular arrhythmias, which may cause stroke or sudden cardiac death. Automatic long-term electrocardiogram (ECG) analysis algorithms could provide diagnosis suggestion even early warning for physicians, however, they are mutually-exclusive in terms of robustness, generalization and low complexity. In this study, a novel PVC recognition algorithm that combines deep learning-based heartbeat template clusterer and expert system-based heartbeat classifier is proposed. Long short-term memory-based auto-encoder (LSTM-AE) network was used to extract features from ECG heartbeats for K-means clustering. Thus, the templates were constructed and determined based on clustering results. Finally, the PVC heartbeats were recognized based on a combination of multiple rules, including template matching and rhythm characteristics. Three quantitative parameters, sensitivity (Se), positive predictive value (P+) and accuracy (ACC), were used to evaluate the performances of the proposed method on the MIT-BIH Arrhythmia database and the St. Petersburg Institute of Cardiological Technics database. Se on the two test databases was 87.51% and 87.92%, respectively; P+ was 92.47% and 93.18%, respectively; and ACC was 98.63% and 97.89%, respectively. The PVC scores on the 3rd China Physiological Signal Challenge 2020 training set and hidden test set were 36,256 and 46,706, respectively, which could rank first in the open-source codes. The results showed that the combination strategy of expert system and deep learning can provide new insights for robust and generalized PVC identification from long-term single-lead ECG recordings.

Time series data are significant and are derived from temporal data, which involve real numbers representing values collected regularly over time. Time series have a great impact on many types of data. However, time series have anomalies. We introduce hybrid algorithm named novel matrix profile (NMP) to solve the all-pairs similarity search problem for time series data. The proposed NMP inherits the features from two state-of-the art algorithms: similarity time-series automatic multivariate prediction (STAMP), and short text online microblogging protocol (STOMP). The proposed algorithm caches the output in an easy-to-access fashion for single- and multidimensional data. The proposed NMP algorithm can be used on large data sets and generates approximate solutions of high quality in a reasonable time. The proposed NMP can also handle several data mining tasks. It is implemented on a Python platform. To determine its effectiveness, it is compared with the state-of-the-art matrix profile algorithms i.e., STAMP and STOMP. The results confirm that the proposed NMP provides higher accuracy than the compared algorithms.

The current research work illustrates an economic and rapid approach towards biogenic synthesis of silver nanoparticles using aqueous Punica granatum leaves extract (PGL-AgNPs). The optimization of major parameters involved in the biosynthesis process was done using Box-Behnken Design (BBD). The effects of different independent variables (parameters) namely concentration of AgNO3, temperature and ratio of extract to AgNO3on response viz. particle size and polydispersity index were analyzed. As a result of experiment designing, 17 reactions were generated which were further validated experimentally. The statistical and mathematical approaches were employed on these reactions in order to interpret the relationship between the factors and responses. The biosynthesized nanoparticles were initially characterized by UV-vis spectrophotometry followed by physicochemical analysis for determination of particle size, polydispersity index and zeta potential via dynamic light scattering (DLS), SEM and EDX studies. Moreover, the determination of functional group present in the leaves extract and PGL-AgNPs was done by FTIR. Antibacterial and antibiofilm efficacies of PGL-AgNPs against Gram-positive and Gram-negative bacteria were further determined. The physicochemical studies suggested that PGL-AgNPs were round in shape and of ~ 37.5 nm in size with uniform distribution. Our studies suggested that PGL-AgNPs exhibit potent antibacterial, and antibiofilm properties.

The tryptophan (TRP)-kynurenine (KYN) metabolic pathway is a main player of TRP metabolism through which more than 95% of TRP is catabolized. The pathway is activated by acute and chronic immune responses leading to a wide range of illnesses including cancer, immune diseases, neurodegenerative diseases, and psychiatric disorders. The TRP-KYN pathway synthesizes multifarious metabolites including oxidants, antioxidants, neurotoxins, neuroprotectants, and immunomodulators. The immunomodulators are known to facilitate the immune system towards a tolerogenic state, resulting in chronic low-grade inflammation (LGI) that is commonly present in obesity, poor nutrition, exposer to chemicals or allergens, prodromal stage of various illnesses, and chronic diseases. KYN, kynurenic acid, xanthurenic acid, and cinnabarinic acid are aryl hydrocarbon receptor ligands that serve as immunomodulators. Furthermore, TRP-KYN pathway enzymes are known to be activated by the stress hormone cortisol and inflammatory cytokines, and genotypic variants were observed to contribute to inflammation and thus various diseases. The tryptophan 2,3-dioxygenase, the indoleamine 2, 3-oxygenases, and the kynurenine-3-monooxygenase are main enzymes in the pathway. This review article discusses the TRP-KYN pathway with special emphasis on its interaction with the immune system and the tolerogenic shift towards chronic LGI and overviews the major symptoms, pro- and anti-inflammatory cytokines, and toxic and protective KYNs to explore the linkage between chronic LGI, KYNs, and major psychiatric, including depressive disorder, bipolar disorder, substance use disorder, post-traumatic stress disorder, schizophrenia, and autism spectrum disorder.

Melanoma is considered the most serious and aggressive type of skin cancer, and metastasis appears to be the most important factor in prognosticating this type of cancer. With the emergence of new therapeutic strategies for metastatic melanoma that have shown improvement in patient survival, we developed a transfer learning-based biomarker discovery model that could help in the diagnosis and prognosis of this disease. After applying it to the ensemble machine learning model, results reveal that the genes we found show consistency with other methodologies previously applied to the same TCGA (The Cancer Genome Atlas) data set, and our methods found novel biomarker genes as well. Our ensemble model achieved Area Under the Receiver Operating Characteristic (AUC) of 0.9861, an accuracy of 91.05, and an F1 score of 90.60 using an independent validation data set. This study was able to identify potential genes for diagnostic classification (C7 and GRIK5) and diagnostic and prognostic biomarkers (S100A7, S100A7, KRT14, KRT17, KRT6B, KRTDAP, SERPINB4, TSHR, PVRL4, WFDC5, IL20RB). We also assessed the potential sources of bias for our model and confirmed some of them by the model's performance.

The adoption of Pump as Turbines (PATs) both in small scale hydroelectric plants and water supply systems has brought different advantages, the most recognized being cost-effectiveness as compared to other hydroturbines. However, due to their lack of flow control ability, their intolerance to off-design operations constitutes one tough shortfall. Moreover, this technology’s newness leads to PAT flow dynamics still being ununderstood even to date. Therefore, this study intends to numerically investigate the mixed flow PAT’s pump mode flow dynamics for five operating conditions expanding from optimum (1QBEP) to deep part-load (0.41 QBEP) conditions. Moreover the effect of runner blade angle on the same has been investigated where three angles namely -2°, 0°, and 2° have been considered. PAT flow stability was found to deteriorate as the flow decreased, where associated pressure pulsation level worsened at different flow zones. In addition, the blade angle increase led correspondingly increasing flow unsteadiness and pressure pulsation levels, where the pulsation frequencies from rotor-stator interactions were dominant for most of flow zones. This study’s findings are of a crucial importance to both scientific and engineering communities as they contribute to thorough understanding of PAT flow dynamics.

The emergence of three-dimensional human organoids has opened the door for development of patient-derived cancer organoid (PDO) models, which closely recapitulate parental tumor tissue. Mainstays of preclinical cancer modeling include in vitro cell lines and patient-derived xenografts, but these models lack the cellular heterogeneity seen in human tumors. Moreover, xenograft establishment is resource- and time-intensive, rendering these models difficult to use to inform clinical trials and decisions. PDOs, however, can be created efficiently and retain tumor-specific properties such as cellular heterogeneity, cell-cell and cell-stromal interactions, tumor microenvironment, and therapeutic responsiveness. PDO models and drug screening protocols have been described for several solid tumors and, more recently, for gliomas. Since PDOs can be developed in clinically relevant timeframes and share many characteristics of parent tumors, they may enhance the ability to provide precision oncologic care for patients. This review explores the current literature on cancer organoids, highlighting the history of PDO development, organoid models of glioma, and potential clinical applications of PDOs.

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

The epithelial-mesenchymal (E/M) hybrid state has emerged as an important mediator of elements of cancer progression, facilitated by epithelial mesenchymal plasticity (EMP). We review here evidence for the presence, prognostic significance, and therapeutic potential of the E/M hybrid state in carcinoma. We further assess modelling predictions and validation studies to demonstrate stabilised E/M hybrid states along the spectrum of EMP, as well as computational approaches for characterising and quantifying EMP phenotypes, with particular attention to the emerging realm of single-cell approaches through RNA sequencing and protein-based techniques.

Corundum-rich (up to 55 vol.%) felsic dykes formed by albite, ±K-feldspar, ±hercynite and ±biotite-siderophyllite cut the lower crustal rocks exposed in the Ivrea-Verbano Zone (NW Italy). Zircon is an abundant accessory mineral and its investigation through LA-ICP-(MC)MS has allowed to directly constrain the timing of emplacement, as well as petrology and geochemistry of parental melts. Zircons are characterised by very large concentration in REE, Th, U, Nb and Ta, and negative Eu anomaly. U–Pb analysis points to Norian emplacement ages (223±7 Ma and 224±6 Ma), whereas large positive εHf(t) values (+13 on average) indicate a derivation from depleted to mildly enriched mantle source. The mantle signature and the corundum oversaturation were preserved thanks to limited crustal contamination of the host, HT refractory granulites and mafic intrusives. According to the geochemical data and to the evidence of the development of violent explosions into the conduits, it is proposed that dykes segregated from peraluminous melts produced by exsolution processes affecting volatile-rich differentiates during alkaline magmatism. This work provides robust evidence about the transition of the geochemical affinity of Southern Alps magmatism from orogenic-like to anorogenic during Norian, linked to a regional uprising of the asthenosphere and change of tectonic regime.

Wind power as a renewable source of energy, has numerous economic, environmental and social benefits. In order to enhance and control the renewable wind power, it is vital to utilize models that predict wind speed with high accuracy. Due to neglecting of requirement and significance of data preprocessing and disregarding the inadequacy of using a single predicting model, many traditional models have poor performance in wind speed prediction. In the current study, for predicting wind speed at target stations in the north of Iran, the combination of a multi-layer perceptron model (MLP) with the Whale Optimization Algorithm (WOA) used to build new method (MLP-WOA) with a limited set of data (2004-2014). Then, the MLP-WOA model was utilized at each of the ten target stations, with the nine stations for training and tenth station for testing (namely: Astara, Bandar-E-Anzali, Rasht, Manjil, Jirandeh, Talesh, Kiyashahr, Lahijan, Masuleh and Deylaman) to increase the accuracy of the subsequent hybrid model. Capability of the hybrid model in wind speed forecasting at each target station was compared with the MLP model without the WOA optimizer. To determine definite results, numerous statistical performances were utilized. For all ten target stations, the MLP-WOA model had precise outcomes than the standalone MLP model. The hybrid model had acceptable performances with lower amounts of the RMSE, SI and RE parameters and higher values of NSE, WI and KGE parameters. It was concluded that WOA optimization algorithm can improve prediction accuracy of MLP model and may be recommended for accurate wind speed prediction.

A fast calculation method for the full parallax high-resolution hologram is proposed based on the elemental light field image (EI) rendering. A 3D object located near the holographic plane is firstly rendered as multiple EIs with a pinhole array. Each EI is interpolated and multiplied by a divergent sphere wave and interfered with a reference wave to form a hogel. Parallel acceleration is used to calculate the high-resolution hologram because calculation of each hogel is independent. A high-resolution hologram with the resolution of 20,0000×20,0000 pixels is calculated only within 8 minutes. Full parallax high-resolution 3D displays are realized by optical reconstructions.

As a part of our ongoing effort in the search for promising antileishmanial agents based on the thiochroman scaffold, we prepared a series of substituted 2H-thiochromenes. Thirty-three compounds were evaluated against intracellular amastigotes forms of L. (V) panamensis. Twelve compounds were active with EC₅₀ values lower than 40 μM, and among those three compounds displayed the highest antileishmanial activity with EC₅₀ values below 10 uM. Cytotoxicity was determined against human U-937 macrophages; thus, compounds having electrophilic alkenes (α,β-unsaturated carbonyl, or nitriles) displayed the highest antileishmanial activity but also moderate to high cytotoxicities. Based on SAR analysis, compounds 8d and 10, which differ only in the hydroxy group at C4, were selected as the most promising compounds in this library because good antiparasitic activity and Selectivity Index.

(1) Background: Previous systematic review suggested a beneficial effect of progressive muscle relaxation (PMR) for cancer patients receiving chemotherapy. However, poor quality of eligible studies impaired the reliability and validity of findings. Moreover, additional potential studies with good quality published in Chinese language have been published recently. The aim of the present systematic review was to investigate the value of PMR training in preventing and alleviating nausea and vomiting caused by chemotherapy among cancer patients. (2) Methods: We assigned two independent investigators to search all potential studies in PubMed, Cochrane Controlled Register of Trial (CENTRAL), Cumulative Index to Nursing and Allied Health Literature (CINAHL), China Biomedical Literature database (CBM), China National Knowledge Infrastructure (CNKI), and Wanfang data. We used data extraction sheet extracted all essential information, and used the Cochrane risk of bias assessment tool to appraise the quality of eligible studies. Finally, we qualitatively summarized the results of all included studies. (3) Results: Six studies enrolling 288 patients were considered to meet our selection criteria finally. Of these 6 studies, three were labeled as moderate quality, and the remaining studies were low quality. All included studies consistently suggested that PMR has a positive impact on nausea and vomiting caused by chemotherapy among cancer patients especially alleviating the incidence, frequency and degree of delayed nausea and vomiting. (4) Conclusions: Independent studies indicated that PMR was a beneficial approach to prevent and alleviate nausea and vomiting caused by chemotherapy among cancer patients. However, further studies considering other types of primary tumors should be designed in order to increase the generality of PMR because studies included in the present systematic review mainly enrolled lung cancer and breast cancer.

Techniques of stripping voltammetry (SV) determination of silver and gold in pyrites and carbonaceous matter were developed. The problem of quantitative transfer of the sample into the solution was solved. For this purpose, the ore matrix of carbonaceous shales was decomposed by mineral acids in autoclaves at high pressures. The element to be determined from the sample matrix was separated by extraction. Ag(I) ions from the solutions were extracted in the form of dithizonate complex in CCl₄. Au(III) ions were extracted by diethyl ether. The extracts were decomposed thermally. The dry residue was dissolved in the background electrolyte, and the element was determined by the SV method. The graphite electrode (GE) impregnated with polyethylene was used as a working electrode in SV–determination of silver. SV–determination of gold was carried out using GE modified by bismuth. The limits of detection (LOD) of Ag(I) and Au(III) contents were equal to 0.016 mg L^-1 and 0.0086 mg L^-1, respectively. The results of SV-determination of gold and silver in standard samples, pyrites and carbonaceous shales were presented. The silver content in the pyrite was 13.6 g t^-1, in carbon shale—0.34 g t^-1. The concentration of gold in the pyrite ore zone "Kirovsko–Kryklinskaya" was 1.15 g t^-1; in carbonaceous shales—2.66 g t^-1. The obtained data were consistent with the data of atomic emission spectroscopy (AES) and inductively coupled plasma mass spectrometry (ICP—MS). The error of determination of elements by stripping voltammetry was calculated when determining the silver content of 10...6 g t^-1 in pyrite and carbonaceous material, which was less than 12%, and when determining the gold content of 1...3 g t^{- 1} in pyrite and carbonaceous matter, which was less than 23%.

Three polyimides and six inorganic fillers in a form of nanometer-sized particles were studied as thick film solution cast mixed matrix membranes (MMMs) for transport of CO₂, CH₄ and H₂O. Gas transport properties and electron microscopy images indicate good polymer-filler compatibility for all membranes. The only filler type which demonstrated good distribution throughout the membrane thickness at 10 wt. % loading was BaCe_0.2Zr_0.7Y_0.1O₃ (BCZY). The influence of this filler on MMM gas transport properties was studied in detail for 6FDA-6FpDA in a filler content range from 1 to 20 wt.% and for Matrimid^® and P84^® at 10 wt. % loading. The most promising result was obtained for Matrimid^® - 10wt% BCZY MMM, which showed improvement in CO₂ and H₂O permeabilities accompanied by increased CO₂/CH₄ selectivity and high water selective membrane at elevated temperatures without H₂O/permanent gas selectivity loss.

Examining the soil microbiome structure has a great significance in exploring the mechanism behind plant growth changes due to maize (Zea mays L.) and soybean (Glycine max Merr.) crop rotation. This study explored the effects of soil microbial community structure after soybean and maize crop rotation by designing nine treatments combining three crop rotations (continuous cropping maize or soybean; and maize after soybean) with three fertility treatments (organic compound fertilizer, chemical fertilizer, or without fertilizer). Soil was sampled to 30 cm depth the second year at approximately the middle of the growing season, and was analyzed for physical, chemical, and phospholipid fatty acid (PLFA) profiles. Bacteria was found to be the predominant component of soil microorganisms, which mainly contain the PLFAs i15:0, 16:1 ω 7c, 16:0, 10Me16:0, and 18:1 ω 7c. The concentration of soil gram-negative bacteria from the soybean and maize rotation was less than in soybean continuous cropping when organic fertilizer was applied to both. Crop rotation reduced the percentage of fungi in the soil, among which the effect of organic compound fertilizer application was significantly reduced 24%. The combined crop rotation with organic fertilizer can reduce maximum the percentage of fungi/bacteria. In addition, the content of soil aggregate and organic matter had great influence on gram-positive bacteria and actinomyces, and soil pH had a greater impact on other fungi.

We report the results of an analysis of the functional capabilities of the KTP crystal and its isomorphs for nonlinear-optical frequency conversion of all types of interaction in the transparency range of the crystal. The possibility of implementing angle-, wavelength- (frequency-) and temperature-noncritical phase matching is shown.

In 2015, the Self-Action Leadership Theory—a qualitative, nomological expansion of self-leadership theory rooted in atmospheric and astronomical metaphor aimed at expanding the personal freedom of individuals, organizations, and nations by bolstering the existential growth of individuals through a series of Maslow-esque stages of holistic, personal development. This article introduces an accompanying, practitioner-based Model of Self-Action Leadership (SAL) aimed at the implicit enhancement of a holistic range of administrative processes through explicit training, mentoring, and coaching in the model’s general and universally-applicable principles and practices. The SAL model produces an original construct of personal leadership practice that builds upon the extant self-leadership academic canon, which dates back to 1983 (Manz, 1983). It also provides an analogue to four of the five core processes of Project Management by positioning a self-action leader (an individual) as the ongoing “project” at hand. The SAL Model is rooted in action research and was developed through a variety of self-oriented, action research projects in conjunction with a comprehensive, qualitative, analytical autoethnographic study of a scholar’s life experiences.

This research investigates entrepreneurial attitudes among 415 students in the academic sports domain. Utilizing a 15-item questionnaire, participants were categorized into four groups based on their sports background: individual and team sports with competitive history, amateur athletes, and non-practitioners. The questionnaire exhibited good internal consistency (Cronbach's alpha coefficient = 0.755). Statistical analysis using the Chi-Square Test of Homogeneity across criteria such as gender, competitive sports involvement, type of competitive sports, and engagement in amateur sports revealed significant differences in nine out of 60 comparisons. Furthermore, this study employs an explanatory approach to elucidate the distinctions among athletes, amateur, and non-athlete students in academic sports programs regarding assumption of responsibilities, proactive initiative, determination to establish their own businesses, perception of the comfort zone, and the perception of post-sports career adaptation. Additionally, a gender comparison is conducted concerning the perception of business risk, comfort and security in a stable workplace, and the applicability of sports-oriented approaches in business. These results provide valuable insights into how sports backgrounds shape entrepreneurial perspectives, thereby contributing to the development of customized entrepreneurial programs. Moreover, the study seeks to offer a nuanced comprehension of the diverse factors influencing the entrepreneurial attitudes and perceptions of students in sports academic programs.

Crisis management is essential for businesses to effectively respond to, recover from, and mitigate the effects of unexpected disruptions. This study investigates factors influencing organizational resilience in Himachal Pradesh's pharmaceutical sector (India), focusing on crisis management techniques. The primary goal is to identify key components that support resilience in this industry. Data were collected using structured online and offline questionnaires, yielding 483 valid responses from a sample size of 500 across six pharmaceutical companies. Factor analysis with SPSS software identified three crucial components: "Innovations and Employee Engagement," "Organizational Resources," and "Organizational Culture and Values." Innovations and Employee Engagement" highlight the importance of fostering a creative environment where employees feel empowered to take initiative during crises. "Organizational Resources" underscore the critical role of adequate infrastructure, financial resources, and technological advancements in building resilience. "Organizational Culture and Values" emphasize the importance of shared standards, values, and beliefs in promoting cohesion and unity during adversity. By prioritizing these elements, pharmaceutical companies in Himachal Pradesh can enhance their crisis response capabilities and foster a resilient organizational culture. Implementing these insights through targeted strategies can ensure long-term viability and improve preparedness for future crises.

AYOLO differentiates itself with a new fusion architecture proposal that leverages the strengths of unsupervised learning and integrates the Vision Transformer approach, taking the YOLO series models as a reference. This innovation enables the model to effectively use rich, unlabeled data, providing a new example in pre-training methodology for YOLO architectures. On the benchmark COCO val2017 dataset, AYOLO demonstrates its superiority by achieving an impressive 38.7 % AP while maintaining an outstanding rendering speed of 239 FPS (Frame Per Second) on the Tesla K80 GPU. This performance outperforms the previous state-of-the-art YOLO v6-3.0 by a significant margin of +2.2 % AP while maintaining comparable FPS. AYOLO is presented as a demonstration of the potential of integrating complex information fusion techniques with supervised pretraining in improving the precision and speed of object detection models.

Covalent drugs can offer significant advantages over noncovalent drugs, in terms of pharmacodynamics (i.e. target-binding properties). However, the development of covalent drugs is sometimes hampered by pharmacokinetic limitations (e.g. low bioavailability, rapid metabolism, and toxicity due to off-target binding). Polymeric nanoparticles offer a potential solution to these limitations. Delivering covalent drugs via polymeric nanoparticles provides myriad benefits in terms of drug solubility; permeability; lifetime; selectivity; controlled release; and the opportunity for synergistic administration alongside other drugs. In this short review, we examine each of these benefits in turn, illustrated through multiple case-studies.

Health resorts aim to create health sanctuaries, fostering an environment conducive to treatment, healing, and well-being. Material selection choices for health resort designers should comply with specific minimal requirements and criteria to provide a suitable atmosphere for health and wellness. Based on this assumption and some selection criteria, the study intended to analyse purposefully selected health resorts as the foundation for identifying acceptable materials to construct health resorts. This study had three main goals: to define the evaluated health resorts’ physical characteristics, determine their external works specifications, and investigate the material usage utilised in the interior of three primary functional spaces. We employed a case study approach as the qualitative research method.Top of Form Data was analysed using narrative and content analysis. According to the findings, natural materials, particularly those produced locally, are best suited for the outside and interior of health resort buildings. Wood is the most commonly used material, appearing in all instances studied. The findings are consistent with current worldwide trends toward environmentally friendly facilities. Adopting natural materials such as wood, stone, and soil for health resort planning would be practical, considering the health advantages of such environmentally friendly materials.

Pharmaceutical companies use crisis management as a vital technique to lessen the effects of catastrophes. In this study, the author highlighted the significance of supply chain management for crisis management in the pharmaceutical industry. The study concludes by discussing the role that supply chain management plays in crisis management and offering pharmaceutical businesses advice on how to run their supply chains in an emergency. We conclude after conducting a thorough analysis of the literature review and regress research. These are actions that pharmaceutical organizations can take to strengthen their supply chain management skills and enhance their crisis readiness: Identifying possible supply chain risks through routine risk evaluations; Creating backup strategies in case the supply chain is disrupted; Establishing procedures to guarantee a smooth and efficient supply of medications in an emergency; and Collaborating with vendors and other stakeholders to increase the resilience of the supply chain. The pharmaceutical industry is critical to healthcare, providing safe and effective medicines to patients. Supply chain management is essential for maintaining the flow of medicines during crises. Proactive risk assessment, backup plans, teamwork, and efficient communication are all critical for crisis management in the pharmaceutical industry, particularly in supply chain management. In India, inadequate transportation infrastructure leads to a significant expense for pharmaceutical businesses. To mitigate negative effects, such as reduced healthcare access and insurance coverage, the study suggests implementing multi-echelon, closed-loop green supply chain models. These strategies aim to minimize total costs and ensure efficient resource management. To improve the resilience of pharmaceutical and consumable medical equipment during crises, policymakers should integrate modern technologies and consider business complexity, economic development, intense competition, and changing customer needs. The relationship between manufacturers, distributors, prescribers, and insurance organizations as purchasers should also be considered.

Silicon (Si) is the major material of semiconductor element. For semiconductor element producing, Si need to refined into high-purity silicon crystals, which has the approximate characteristics of intrinsic semiconductor, then doping 13th group or 15th group trace element. Producing the high-purity silicon crystals with well-lattice structure need a lot of energy and highly cost. Besides, the high-purity silicon is very hard and fragile which limits the scope of application. For this reason, this study added low-grade non-complete lattice silicon in the elastic polymer, and then doped with high concentrations of fine carbon powder. This material can be conductive by physisorption;therefore, it can be used to making semiconductors. Using this material to produce electronic components can significantly reduce the cost of purification and crystallization, saving energy at the same time. Moreover, because this elastic polymer materials containing silicon, which has soft, warm, and durable physical properties. With those properties, the design of the device could be more flex, full scalability and close to the skin.

Urban ultra-low altitude airspace (ULAA) presents unique challenges for unmanned aerial vehicle (UAV) path planning due to high building density and regulatory constraints. This study analyzes and improves classical path planning algorithms for UAVs in ULAA. Experiments were conducted using A*, RRT, RRT*, and artificial potential field (APF) methods in a simulated environment based on building data from Chengdu City, China. Results show that traditional algorithms struggle in dense obstacle environments, particularly APF due to local minima issues. Enhancements were proposed: a density-aware heuristic for A*, random perturbation for APF, and a hybrid optimization strategy for RRT*. These modifications improved computation time, path length, and obstacle avoidance. The study provides insights into the limitations of classical algorithms and suggests enhancements for more effective UAV path planning in urban environments.

Breakthroughs in surgical and medical techniques have significantly improved outcomes for children with congenital heart disease (CHD), but research continues to address the ongoing challenge of organ dysfunction after surgery. Our study explored circular RNAs (circRNAs) within plasma-derived extracellular vesicles (EVs) in children undergoing CHD surgery. Post-surgery EV circRNAs showed dramatic expression changes between organ dysfunction (OD) and control groups. Tissue injury-related pathways were consistent across pre- and post-surgery in OD. The top two significant predicted tissue sources of these circRNAs originated from the respiratory system, aligning with the major organ dysfunction type (respiratory failure). Five of these circRNAs, namely circ-CELSR1, circ-PLXNA1, circ-OBSL1, circ-DAB2IP, circ-KANK1, significantly correlated between PELOD (Pediatric Logistic Organ Dysfunction), supporting the potential of circRNAs as prognostic markers. These findings pave the way for EV circRNAs as promising tools for managing post-surgical organ dysfunction and potentially guiding therapeutic strategies in children with CHD.

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

Dams fragment stream habitat and fishways around dams typically serve few species that are strong swimmers or jumpers. We test a prototype wetted ramp designed to allow upstream passage of small-bodied fishes while blocking upstream movement of invasive sea lamprey in the Laurentian Great Lakes. We tested short, smooth ramps with 5-10 mm water depth in various combinations of ramp angle, water flow and swim channel width with the aim to selectively block adult migrating sea lamprey while passing sub-adult white suckers (Catostomus commersonii) and creek chubs (Semotilus atromaculatus). Sea lamprey easily passed a 0.75 ramp at 5 angle, but very few individuals passed a similar ramp at 10 angle and none passed a longer ramp at the 5 angle. Limiting the amplitude of tailbeats in a narrow channel did not hamper lamprey or the other species. Greater water flow, and thereby greater immersion depth on the ramp fostered passage for all species. Smaller-bodied individual of creek chubs and white suckers performed best on the ramp. We show that wetted ramps could be incorporated into fishways at low-head dams to aid passage of smaller-bodied fishes while also blocking the spawning migration of adult sea lamprey.

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

To support the integration of renewable energy sources and preserve grid stability, this study examines several approaches for controlling the temperature of Battery Energy Storage Systems (BESS) in modern energy settings. Specifically, the usage of BESS in Virtual Power Plants (VPPs) is the focus of this study. The effectiveness, safety features, dependability, affordability, and suitability for VPP applications of these systems are examined. Among the various hybrid cooling alternatives, two particularly promising combinations emerge. Firstly, the integration of heat pipes and phase change materials leverages their ability to conduct heat efficiently away from heat sources with minimal temperature differences, making them excellent for rapid heat transfer. Secondly, an approach employing heat pipes and liquid passive cooling a combination that capitalizes on the efficient heat transfer capabilities of heat pipes and the consistent cooling offered by liquid passive systems. The study underscores the importance of improving BESS performance and sustainability within VPPs by providing useful recommendations for choosing the best thermal management system depending on climate conditions and geographic location.

As a widely used plastic, the aging and degradation of polyethylene (PE) are inevitable problems, whether the goal is to prolong the life of PE products or address the issue of white pollution. Molecular simulation is a vital scientific tool in elucidating the mechanisms and processes of chemical reactions. To obtain the distribution and evolution process of PE's thermal oxidation products, this work employs the self-consistent charge density functional tight binding (SCC-DFTB) method to perform molecular simulations of the thermal oxidation of PE with different crystallinity and branched structures. We discovered that crystallinity does not affect the thermal oxidation mechanism of PE, but higher crystallinity makes PE more susceptible to cross-linking and carbon chain growth, reducing the degree of PE carbon chain breakage. The branched structure of PE results in differences in pore size between the carbon chains, with larger pores leading to a concentrated distribution of O2 and free radicals subsequently formed. The breakdown of PE is slowed down when free radicals are localized in low-density regions of the carbon chain. The specifics and mechanism of PE's thermal oxidation are clearly revealed in this paper, which is essential for understanding the process in-depth and for the development of anti-aging PE products.

This bibliometric study explores the cryptocurrency accounting (CA) literature and the connections between authors, institutions, and countries where cryptocurrency activity involves transactions that must be legally recognized in accounting, assure accuracy and reliability for auditing, and adhere to tax compliance. The design involves data selection from Web of Science Core Collection (WoS) and Scopus, published between 2007 - 2023. The technique helps identify influential publications, collaboration networks, thematic clusters, and trends in research on CA using tools VOSviewer, Biblioshiny, and MS Excel. The originality of the study lies in its dual role as a support for accounting professionals and academics to develop innovative solutions for the challenges posed by crypto technology across core accounting areas: financial and managerial accounting, taxation, and auditing. The findings offer insights into the themes mentioned, and even if the collaboration between the authors is not very developed, the innovation and public recognition of the subject could raise researchers' interest. The limitation of the dataset is that it does not cover all relevant publications in a different period from the one in which the data was retrieved, 9-11 May 2024. This review might need periodic updates because the CA landscape is constantly changing.

In this paper, we studied the problem of early detection of natural phenomena associated with the formation of severe floods and the possibility of constant monitoring of their occurrence. The test object for the study was severe floods on the Crimean Peninsula, which occurred due to heavy rainfall in the summer of 2021. Based on the selected satellite and other data related to this period, an analysis carried out and key atmospheric objects identified, according to the proposed algorithm for their identification and grouping. Based on the results of the work, a positive conclusion made on the issue of their use to identify the likelihood of natural disasters that could lead to floods. In addition, the authors proposed to develop a portal for collecting and processing a large amount of satellite data related to flood prevention and monitoring the development of such processes, and stressed the need to create it.

Neuronal timing is critical for many brain functions such as perception and learning. At the level of the chemical synapse, the synaptic delay is determined by the presynaptic release probability (Pr) and the waveform of the presynaptic action potential (AP). Depolarization-induced analogue-digital facilitation (d-ADF) is a form of context-dependent synaptic facilitation that is induced by constant depolarization of the presynaptic neuron and is mediated by voltage inactivation of presynaptic Kv1 channels. Whether synaptic delay is modulated during d-ADF remains unclear. We show here that despite Pr is elevated during d-ADF at L5-L5 synapses, the synaptic delay is surprisingly unchanged, suggesting that both Pr- and AP-dependent changes in synaptic delay compensate for each other. We conclude that in contrast with other short- or long-term modulation of presynaptic release, timing is not affected during d-ADF because of the opposite interaction of Pr- and AP-dependent modulations of synaptic delay.

Animals are distinguished by their complex developmental programs, in which transcription factors play essential roles in coordinating the regulation of the genome. Thus, it has been hypothesized that animal origins involved the evolution of increasingly complex transcriptional regulatory mechanisms that permit greater spatiotemporal control over gene expression. Here, we revisit this hypothesis in light of new genomic and functional data from diverse phylogenetically-relevant taxa, including early branching animals (sponges, ctenophores) and close relatives of animals (choanoflagellates, filastereans, ichthyosporeans). We argue that many of the mechanisms posited to explain animal transcriptional complexity, such as large increases in transcription factor numbers, new transcription factor families, and distal enhancers, did not factor significantly into animal origins. Instead, we propose that the re-purposing of pre-existing transcriptional regulatory modules through cis-regulatory evolution and gene duplication events, combined with new protein-protein interactions among TFs, may have been fundamental to the transcriptional regulatory architecture of the first animals.

Bacteriophages are viruses obligately infecting bacteria. They constitute the most numerous categories of biological forms populating our biosphere and are highly diverse and capable of infecting almost all bacteria. Phages make use of their host cell molecular machinery to express their own genes as they lack the ability to independently reproduce themselves. The inimitable characteristics of bacteriophages have enabled them to become propitious tools in biotechnology and genetic engineering. Phages show no tropism for mammalian cells but however, can be easily modified to present targeting ligands on their surface as coat protein fusions without any negative impacts on phage structure. These displayed ligands thereupon guide the recognition, interaction, and internalization of the phage into cells wherein efficiency of transfection is directly influenced by the copy number of the ligands used for targeting. Engineered phages are more efficacious for transgene delivery and gene expression in cancer cells when compared to other non-viral gene transfer strategies and are therefore being employed in developing cancer vaccines. The high level of stability as well as resistance of bacteriophages to various environmental conditions have enabled the development of virus-like particles (VLPs) capable of successful deliverance of several therapeutic drug cargos into tumors by selective targeting. Phage display technology has been used in therapy of Alzheimer’s disease and drug delivery into the brain. Exogenous peptides fused into the coat protein of phages enables the display of these peptides on the phage surface to generate combinatorial phage that facilitates their rapid separation using their ability to bind to a specific molecular target. Phage therapy has been shown to be safe in clinical settings when compared to antibiotics as it shows no adverse anaphylaxis nor adverse effects such as the emergence of multi-drug resistant bacteria. This review provides intriguing details of the use of natural and engineered phages in the therapy of diseases such as cancer, bacterial infections, bovine mastitis and dementia in addition to the use of CRISPR-Cas9 technology in generating genetically engineered phages. Further, the use of phage display technology in generating monoclonal antibodies against various human diseases is elucidated.

Angiotensin-converting enzyme (ACE) inhibitors are used primarily in the treatment of hypertension, heart failure, and in the acute phase of myocardial infarction. Lisinopril [N2-[(1S)-1-car-boxy-3-phenylpropyl]-L-lysyl-L-proline], enalapril [(S)-1-[N-[1-(ethoxycarbonyl)-3-phenylpropyl]-L-alanyl]-L-proline] and ramipril [2-aza-bicyclo-[3.3.0]-octane-3-carboxylic acid] are all five-membered heterocycles and three of the most prevalent ACE inhibitors in clinical use worldwide. ACEi-induced angioedema (ACEi-AE) is clinically characterized by self-limited edema of the dermis and subcutaneous lipid tissue, localized on face skin, oral mucosa and tongue in most cases. However, severe episodes of intestinal AE misdiagnosed as acute appendicitis and laryngeal AE requiring incubation have been reported. The pathophysiology of ACEi induced-AE is attributed to the accumulation of bradykinin, which is a potent vasodilator with proinflammatory activity that is normally degraded by angiotensin-converting enzyme (ACE) and aminopeptidase P; however, a small proportion of treated patients is affected. Given that patients do not respond to anti-H1 antihistamines and steroids, the early clinical recognition and the ACEi discontinuation are the treatment of choice for the long term management of ACEi-AE.

As the cost of conventional energy continues to rise, and concerns over the environment grow, there is a growing interest in sustainable energy. It is believed that conventional energy will only last for around 50 years, making it essential to find a renewable energy source that is safe and feasible to replace fossil fuels. Solar energy is a superior alternative to conventional energy, as it is renewable and produces green energy that can be used directly. The maritime industry has found itself at the forefront of an evolving environmental consciousness, driven by the imperative to mitigate the carbon footprint left in the wake of ships. In this journey towards sustainability, solar energy has emerged as a beacon of hope, harnessing the boundless energy of the sun to wean vessels off their dependence on fossil fuels. Technological advancements have made solar power more accessible, and we can now see the use of solar panels on large ships and small crafts to reduce fuel usage and emissions. Solar panels are also increasingly used to power homes and businesses, and many countries are implementing policies to encourage their use. Solar energy is a key solution in reducing our dependence on non-renewable energy sources and combating climate change. However, the adoption of solar energy is but a stepping stone towards maritime sustainability, as the integration of CO2 capture, utilization, and storage (CCUS) technologies promises to amplify the industry's environmental impact to unprecedented heights.

FLH 13-11 is an F1 interspecific hybrid muscadine grape genotype that was developed to produce new anthocyanins for pigment color stability. This hybrid resulted from a cross between ‘Marsh’ (Vitis munsoniana) and ‘Magoon’ (V. rotundifolia). This report characterizes the anthocyanins produced in fully ripe berries, and reveals a significant difference in total anthocyanin contents from two continuous cropping seasons. High-performance liquid chromatography with a diode array detector (HPLC-DAD) and HPLC-quadrupole time-of-flight tandem mass spectrometry (HPLC-qTOF-MS/MS) were used to profile anthocyanins in berries. The resulting data showed that fourteen anthocyanins were detected, six from 2011 and nine from 2012, with only one produced in both seasons. However, the anthocyanidin profiles of berries were the same. Five anthocyanins were annotated as diglucosides of anthocyanidins based on MS/MS features, including delphinidin 3,5-diglucoside produced in both seasons, cyanidin 3,5-diglucoside mainly formed in 2011, petunidin 3,5-diglucoside, malvidin 3,5-diglucoside, and peonidin 3,5-glucoside only detected in 2012. Also, three anthocyanidin-diglucoside like anthocyanins and three monoglucosides including peonidin 3- glucoside, delphinidin 3- glucoside like, and pelargonidin 3- glucoside like anthocyanins, were detected in 2011 and 2012, respectively. These results indicate that FLH 13-11 can produce both anthocyanidin-diglucosides and -monoglucosides, and their biosynthesis is closely dependent on cropping years.

Towards smart batteries for electric vehicles (EVs) smart algorithms to control battery packs, mainly reconfigurable batteries, have to be developed. This work proposes a reinforcement learning (RL) algorithm to balance the State of Charge (SoC) of reconfigurable batteries based on the topologies half-bridge and battery modular multilevel management (BM3). As RL algorithm, Amortized Q-learning (AQL) is implemented, which allows enourmous numbers of possible configurations of the reconfigurable battery to be controlled, as well as the combination of classical controlling approach and machine learning methods. This enables safety mechanisms in control. As a neural network of the AQL a Feedforward Neuronal Network (FNN) is implemented consisting of three hidden layers. The experimental evaluation using a 12-cell hybrid cascaded multilevel converter illustrates the applicability of the method to balance the SoC and maintain the balanced state during discharge. The evaluation shows a 20.3% slower balancing compared to the classical. Nevertheless, AQL shows great potential to be applied for multiobjective optimizations as an applicable RL algorithm for control in power electronics.

Machine learning models are increasingly being used in critical domains, but their complexity, lack of transparency, and poor interpretability remain problematic. Decision trees (DTs) and rule-based approaches are well-known examples of interpretable models, and numerous studies have investigated techniques for approximating tree ensembles using DTs or rule sets; however, tree ensemble approximators do not consider interpretability. These methods are known to generate three main types of rule sets: DT-based, unordered-based, and decision list-based. However, no known metric has been devised to distinguish and compare these rule sets. Therefore, the present study proposes an interpretability metric to allow comparisons of interpretability between different rule sets, such as decision list- and DT-based rule sets, and investigates the interpretability of the rules generated by the tree ensemble approximators. To provide new insights into the reasons why decision list-based and inspired classifiers do not work well for categorical datasets consisting of mainly nominal attributes, we compare objective metrics and rule sets generated by the tree ensemble approximators and the \textit{Recursive-Rule eXtraction algorithm (Re-RX) with J48graft}. The results indicated that \textit{Re-RX with J48graft} can handle categorical and numerical attributes separately, has simple rules, and achieves high interpretability, even when the number of rules is large.

As artificial intelligence takes an increasingly prominent role in healthcare, a growing body of research is being dedicated to its application in the investigation of communication sciences and disorders (CSD). This study conducts a bibliometric analysis of AI-based research in the field of CSD published up to December 2023. Utilizing the Web of Science and Scopus databases, we identified 15,035 publications, with 4,375 meeting our inclusion criteria. From 1985 onwards, there has been a consistent annual increase in publications, averaging at 16.51%, notably surging from 2012 to 2023. The primary communication disorders studied include autism, dysarthria, dementia, Parkinson’s, and aphasia. Noteworthy AI techniques employed in CSD research encompass machine learning, automatic speech recognition, support vector machine, and deep learning. Our analysis provides a comprehensive overview, serving as a valuable resource for researchers, developers, and professionals seeking to comprehend the evolving landscape of AI in CSD research. Moving forward, collaborative efforts need to prioritize addressing ethical concerns, ensuring data privacy, enhancing methodological enhancements, and considering ecological validity in the application of AI in studies related to communication disorders.

The seed industry plays a crucial role in the global food production, but it faces a persistent challenge in ensuring the health and quality of seeds, particularly those of tomato and pepper, which represent key seed commodities on the global market. Seeds can serve as potential pathways for the introduction and dissemination of seed-borne bacteria, which may have devastating effects on crop yield, farmers’ remunerability, and food security. Therefore, fungicides and other anti-microbial compounds are extensively used to disinfect the seeds, thus increasing the input of chemicals in the agri-enviroment. In this review, we address aspects that connect disease epide-miology with seed infection and health, including seed contamination, endophytic colonization, and seed-borne infections. We focused on the main bacterial diseases affecting tomato and pepper by discussing their official seed testing methods as requirements supporting a smooth seed trade. Moreover, we present a survey on the past and recent innovations for seed treatments, focusing on sustainable disinfection methods. Therefore, this review will be a short, but indispensable guide for seed technologists and pathologists involved in the production of high-quality seeds, providing indications and suggestions to contrast seed-borne pathogens dissemination, avoid international controversies and complaints by phytosanitary authorities, extension services and farmers.

Traditional gene set enrichment analysis falters when applied to large genomic domains, where neighboring genes often share functions. This spatial dependency creates misleading enrichments, mistaking mere physical proximity for genuine biological connections. Here we present Spatial Adjusted Gene Ontology (SAGO), a novel cyclic permutation-based approach, to tackle this challenge. SAGO separates enrichments due to spatial proximity from genuine biological links by incorporating the genes' spatial arrangement into the analysis. We applied SAGO to various datasets in which the identified genomic intervals are large, including replication timing domains, H3K9me3 and H3K27me3 large domains, HiC compartments and lamina associated domains (LADs). Intriguingly, applying SAGO to prostate cancer samples with large copy number alteration (CNAs) domains eliminated most of the enriched GO terms, thus helping to accurately identify biologically relevant gene sets linked to oncogenic processes, free from spatial bias.

When it comes to financial transactions and counterfeit detection systems, banknote classification is crucial. In this paper, we propose an approach for the classification of Kazakhstan banknote images integrating Learning Vector Quantization (LVQ) with Statistical Texture Feature Extraction using the Gray Level Co-occurrence matrix (GLCM). Our methodology demonstrates effectiveness in accurately classifying banknote images, as evidenced by experimental results. The comprehensive testing scenarios show promising outcomes, with the combination of GLCM and Color Histogram under the LVQ algorithm achieving a high accuracy of 94.87 percent at distance 1 and 90°. These findings indicate the robustness and practical viability of the proposed method for authenticating banknotes.

We propose a method that enables precise determination of the number of atoms in a Dick-noise-free optical lattice clock, by effectively addressing quantum projection noise. Our approach relies on conducting stability measurements at three distinct parameter sets, allowing us to differentiate between quantum projection noise, photon shot noise, and technical noise. Importantly, our method enables accurate extraction of the atom number, even in the presence of photon shot noise and technical noise. To validate the effectiveness of our approach, we employ numerical simulations and optimize the modulation parameters to achieve the smallest uncertainty possible. The numerical simulations show the validity of our method and demonstrate a measurement uncertainty in the atom number that is below 4% across a wide range of atom numbers, provided that the standard deviation of atom number fluctuation is kept below 0.23 times the average atom number.

The goal of this study was to determine the relative susceptibility of four common equine wound pathogens to ten different types of antimicrobial agents based on minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC). Additionally, to describe the comparison of bactericidal activity of medical grade Manuka honey, local honey, and commercial, food-grade honey to other commonly used wound dressings. The objective is to provide veterinary practitioners with comparative data on the use of a variety of antimicrobial dressings for inhibiting growth of common wound bacteria. MIC and MBC for Manuka, store, and local honeys were comparable to those of sterile gauze, sugar, and hypertonic saline. Across bacterial species, local honey proved to have more bactericidal activity when compared to Manuka and commercial, food-grade honey. The MIC and MBC for PHMB gauze and foam was consistently at a higher dilution compared to the other antimicrobials. The majority of antimicrobials exhibited stronger inhibitory and bactericidal activity against a Streptococcus zooepidemicus isolate obtained from a wound compared to other bacteria that were ATCC lab acclimated. Additional research for in-vivo applications needs to be done to see whether differences exist in effective wound management.

Integrating sustainable processes and innovative waste utilization not only addresses environ-mental challenges but also aligns with evaluating energy sustainability and creating the circular waste management. This study presents a comparative analysis of liquid fuel production from waste tires and water hyacinth using two thermochemical methods: co-pyrolysis (direct method) and co-gasification integrated with the Fischer-Tropsch (FT) process (indirect method). The As-pen Plus simulation software version 9 is employed to develop models, determining optimal operating conditions for maximum liquid fuel, and assessing economic viability. Co-pyrolysis simulations reveal an increase in oil products and a decrease in gas products with higher blending weight ratios of waste tires/water hyacinth (W/B) and lower pyrolyser temperatures. Operating at 400°C with a blending weight ratio of 75:25 provided the maximum liquid fuel rate of 6649.22 gal/day. For co-gasification, optimal conditions (W/B = 50:50, T = 800°C, steam to feed ratio (S/F) = 1) result in the highest syngas yield of 115.92 kmol/h. Fischer-Tropsch simulations demonstrate an increase in gasoline and a decrease in diesel with rising reactor temperatures. At 230°C, the maximum liquid fuel rate reaches 8817.15 gal/day. The economic and production yield analysis indicates that the indirect method better than the direct method, providing higher liquid fuel yields and investment worthiness.

Prostate cancer (PC) is a common malignancy of elderly men, characterized by great heterogeneity in its clinical course, ranging from an indolent to a highly aggressive disease. The aggressive variant prostate cancer (AVPC) clinically shows an atypical pattern of disease progression, similar to that of small cell PC (SCPC), and also shares the chemo-responsiveness of SCPC. The term AVPC does not describe a specific histologic subtype of PC but rather the group of tumors that, irrespective of morphology, show an aggressive clinical course, dictated by androgen receptor (AR) indifference. AR indifference represents an adaptive response to androgen deprivation therapy (ADT), driven by epithelial plasticity, an inherent ability of tumor cells to adapt to their environment by changing their phenotypic characteristics in a bi-directional way. The molecular profile of AVPC entails combined alterations in tumor suppressor genes retinoblastoma protein 1 (RB1), tumor protein 53 (TP53) and phosphatase and tensin homolog (PTEN). The understanding of the biologic heterogeneity of castration-resistant PC (CRPC) and the need to identify the subset of patients that would potentially benefit from specific therapies necessitate the development of prognostic and predictive biomarkers. This review aims to discuss the possible pathophysiologic mechanisms of AVPC development and the potential use of emerging tissue-based biomarkers in clinical practice.

The necessity for effective intrusion detection systems (IDS) in big data environments has grown critical due to the rising prevalence of big data systems and the rising amount of security threats. Applying conventional intrusion detection methods to the enormous and intricate data produced by big data ecosystems presents difficulties. Deep learning, has proven to be exceptionally adept at deciphering complex, large-scale data. This study proposes a Deep Learning-based Intrusion Detection System (IDS) created specifically for the Big Data environment. Traditional intrusion detection systems struggle to efficiently identify and prevent cyber threats due to the ever-increasing volume and complexity of data in current networks. We suggest an IDS that makes use of Deep Learning (CNN, LSTM, GAN, etc.), to address this problem. These cutting-edge neural network topologies give the system the ability to process and analyze massive amounts of data for precise intrusion detection. Data collection, data preprocessing, feature engineering, DL model training, intrusion detection, warning generation, and reaction are some of the crucial parts of the suggested IDS. The data collection module mines the Big Data environment for network traffic, system logs, and security event information. To make sure the data is suitable for analysis, it is preprocessed. To improve the detection abilities of the DL models, important features are extracted from the data using feature engineering approaches.

Abstract: In this comprehensive review, we delve into the significance of the mul-timodal imaging in diagnosing and managing of complications of congenital optic nerve anomalies.. While the Fundus examination is the gold standard tool in diagnosisc of these pathologies, SD OCT and OCTA could shed a light in the pathogenesis, and treatment. Moreover , this review seeks to offer a comprehensive insight into a multimodal approach of these rare congenital pathologies. In conclusion, congenital anomalies of the optic nerve represent a major challenge for ophthalmologists Further research could be clarify the pathophysiology of these diseases and define a correct and specific treatment approach. Keywords: keyword 1; ODC, ODP, MGS, OCT; OCTA, Multimodal imaging.

Digital twin, an innovative technology propelled by data and models, plays a seminal role in the digital transformation and intelligent upgrade of ships. This study introduces a digital twin methodology for real-time monitoring of ship structure deformation fields, based on finite discrete strain data, and a visualization tool framework is developed using virtual reality technology. First, the inverse Finite Element Method (iFEM) is employed to derive the deformation field of the ship structure in real time via sensor strain data. Secondly, the deformation field data obtained based on the iFEM algorithm is converted into general visualization data conducive to interpretation within VR applications. Lastly, a digital twin software tool is built to enable synchronous response and interaction between the virtual scene and the physical scene, directly superposing particular virtual objects (data acquired by sensors, CAD virtual models, and deformation field cloud images) onto the physical scene in real-time. The digital twin tool embodies a virtual reality visualization system framework integrating physical data measurement, reconstruction, analysis, expression, storage, rendering and interaction of deformation field data. Through practical application, the flexibility, effectiveness and compatibility of the developed prototype tool are verified. According to the results, the system can enhance the efficiency of scientific communication, model validation, and interdisciplinary sharing during the analysis and evaluation of mechanical properties of ship structures.

Cellular therapies have started an important new therapeutic direction for Autistic Spectrum Disease (ASD), and the ample diversity of ASD pathophysiology and the different types of cell therapies need an equally ample effort for studying the applicable ASD causes and the specific benefits of cell therapies via clinical studies.CORDUS Clinical Study is a crossover study in which autologous cord blood was administered intravenously to 56 patients between January 2019 and July 2023, and has compared its efficacy versus an individualized combination of supplements; both treatments were administered in a different sequence to all participants. Treatment efficacy was evaluated pre- and post- treatments by an independent psychotherapist with ATEC, Q-CHAT and a 16-item comparative table score, after interviews with the children’s parents and therapists.Cord blood was beneficial in the group of 3–7-year-old children (n=28; 3 out of 4 children – 78.57% - improved scores), but was much less effective in kids older than 8 years or with body weight of more than 35 kg (n=28; 1 out of 10 children improved scores). Individualized supplements were more efficacious than cord blood in 5 cases out of 28, while in 23 kids cord blood brought more improvement than supplements; 6 kids registered minor or no improvement. Statistically significant improvements were seen after cord blood infusion on areas such as verbalization and social interaction, but not on irritability or aggressive behavior; also ample individual differences were noted. No serious adverse reactions were noted during and after cord blood or supplement administration.

The rise of the Internet has enabled people to express their opinions on various subjects through social media, blogs, and website comments. As a result, there has been a significant increase in research on sentiment analysis. However, most of the research efforts have focused on analyzing sentiment in English-language data, neglecting the wealth of information available in other languages. In this paper, we provide a comprehensive review of the current state-of-the-art in multilingual sentiment analysis. The survey investigates techniques for data preprocessing, representation learning, and feature extraction in multilingual sentiment analysis. It explores cross-lingual transfer learning, domain adaptation, and data augmentation methods that enhance the performance of sentiment analysis models, particularly in low-resource languages and domains. It provides insights into the state-of-the-art approaches, challenges, and opportunities in this evolving field and encourages further advancements in multilingual sentiment analysis research.

Online learning is gaining massive popularity with time. The e-learning platforms operate differently from traditional educational institutions and hence need different strategy for course recommendations. This survey aims to cover the major emerging research areas in e-learning recommender systems. Our study covers different areas of research including graph-based methodologies, ITS, query optimization, content-based, and collaborative filtering, big data, and association rules mining. This survey aimed to explore all major emerging directions of recommender systems in education. This study analyzed existing literature in all of the areas mentioned before and performed objective-based analysis. A brief performance analysis was also done for the researches where the values were comparable. Limitations of existing researches were also identified and studied to shed some light on future directions.

The use of friction-based Beam-to-Column Connections (BCC)s for earthquake-resistant Moment Resistant Frames (MRFs), aiming at eliminating damage to beam end sections due to the development of plastic hinges, has taken hold since the early eighties. Different technical solutions were proposed for steel structures, some were also designed for timber structures, while few more recent studies concern friction joints employed in reinforced concrete structures. Research aimed at characterizing the behavior of joints has focused on the evaluation of the tribological properties of the friction materials, coefficient of friction, shape and stability of the hysteresis cycles, influence of the temperature, speed of load application, effects of the application method, stability of preload, the influence of seismic excitation characteristics on the structural response, statistical characterization of amplitude and frequency of the slip excursion during seismic excitation. Studies aimed at identifying the design parameters capable of optimizing performance have focused attention mainly on the slip threshold, device stiffness, and deformation capacity. This review compiles the main and most recent solutions developed for MRFs. Furthermore, the pros and cons for each solution are highlighted, focusing on the dissipative capacity, shape and stability of hysteresis loops. In addition, the common issues affecting all friction connections, namely characteristics of friction shims and the role of bolt preload, are discussed. Based on the above considerations, a guideline can be outlined, which can help to choose the appropriate solutions for beam-to-column connections for MRFs.

The Internet of Things (also known as IoT), a revolution, has enhanced the relevance of mobile employees' job efficiency in mobile crowd sensing (MCS). Incentives based on reputation for mobile workers (MW) play an important role in increasing service utilization, motivating mobile employees, and developing confidence in the service. The cell phone is the most exploited entity in mobile crowd-sensing MCS and cloud computing. In the underlying investigation, we observed that they had not evaluated the complexity level of a task, resulting in a strong reputation for executing multiple basic tasks. A person who completes a tough task may have a lower reputation score. Complexity levels of tasks (CLT) were developed for reputation evaluation on a crowd-sensing network, which would be utilized to evaluate the MW reputation. We offered simple and complex levels of challenges to assess reputation scores. Tasks receive incentives based on their reputation. By measuring reputation on (CLT) complexity level of task, this research will help the system to Maintain the reputation of the mobile worker so that entities of the system get the maximum benefit out of it, by hiring well-reputed mobile workers and MW receive an incentive on it. Furthermore, we conduct a comparative analysis between our scheme and various machine learning algorithms to identify the algorithm that best performs in evaluating task complexity. Considering both the simple and complex reputation scores, the comparison suggests that after analyzing the data, it is clear that the CLT (proposed) scheme and the Linear regression scheme not only outperformed the Neural Network scheme in terms of Complex Reputation Scores but also in terms of Simple Reputation Scores. We also apply statistical tests, such as p-tests and t-tests, to determine the significance of the results obtained from different algorithms. Considering MW 308, MW 345, and MW 1045's efforts and abilities, the MCS system may offer incentives and awards to further motivate and consider their continuing contributions. This reputation-based incentivization technique not only encourages strong competition among mobile workers, but also makes sure the delivery of high-quality services inside the MCS system.

The poor solvent crystallization of carbapenem CS-023 has been performed at 25 °C. The following results have been obtained: 1) A solvate crystal Form A (5/2 Ethanol·1/2 H2O) is recovered from 80 v/v% ethanol solution, 2) Form A transforms to Form H (4H2O) by the solid-phase transition through the solvate-free polymorph, Form A-2, and Form A also transformed to Form C (1Ethanol·3H2O) by the solvent-mediated transformation. In the present study, we found that Form C also transforms to Form H by the solid-phase transition through the solvate-free polymorph, Form C-2. The three polymorphs, Form A, H, and C, were composed of the helical-chain structures, respectively. However, there was an incomprehensible affair in the solid phase transition among the three polymorphs. Namely, Form A comprised a left-handed helix.On the other hand, Form C and Form H’s helix chains were in a left- and right-handed helix complex. The solid-phase transition of Form A into Form H suggested the switch of helicity in the solid. We attempted to explain the helicity change in the solid phase transition. As a result, it was suggested that the over-absorption of water of Form A-2 at high humidity plays a vital role in the helicity change.

Non-alcoholic beer (NAB) or low alcoholic beer (LAB) are taking over the market with a growing sale. Sus-tainable recycling and valorization of exhausted brewer’s spent grains (BSG) coming from craft beer is a relevant issue in brewing process. In this work, recycled BSG and BSG+GJ (supplemented with 10% grape juice) were used as wort-substrate to inoculate already selected non-conventional yeasts to produce NABLAB craft beer. Results showed that wort composed by only recycled BSG produced appreciate NAB beers (ethanol from 0.12% to 0.54 % v/v) while the addition of 10% of grape juice made LAB beers (ethanol from 0.82 to 1.66 % v/v). As expected, volatile compounds production was highest with the addition of grape juice. Lachancea thermotolerans confirmed the lactic acid production and, as Saccharomyces cerevisiae, is characterized by (in both worts) ethyl butyrate and isoamyl acetate, while Torulaspora delbrueckii produced relevant amounts of exanol, phenylethyl acetate and β-phenyl ethanol (wort added with grape juice). Wickeramhomyces anomalus and Pichia kluyvery showed consistent volatile production but only in wort with grape juice addition where a fermentation activity was exhibited. The overall results indicated that reused BSGs, non-conventional yeasts and grape juice is a suitable strategy for specialty NABLAB beer.

This paper introduces an innovative approach to lipreading, leveraging a web application designed to generate subtitles for videos where the speaker's mouth is visible and a comprehensive literature review that precedes the discussion, encompassing a thorough examination of various lipreading methods employed over the past decade. Our method employs a powerful deep learning model, featuring a 3D-convolution network and bidirectional LSTM, enabling accurate sentence-level predictions based solely on visual lip movements. With an impressive accuracy of 97%, our model is trained using pre-segmented lips regions, transformed into animated GIFs for effective pre-training. This work stands as a significant contribution to the evolving landscape of lipreading research, offering a practical and accurate solution for real-world applications.

China is facing the development requirements of the dual carbon goal and the construction needs of resilient cities. Currently, high-strength composite structural systems are a feasible solution, but their research and application in the construction field are insufficient, especially for the combination forms of concrete above C100 and steel above Q550. In response to this issue, this paper proposes a new high-performance structural system, namely the composite frame - high-strength steel plate wall core tube resilient structure system, which includes high-strength steel plate (Q550) - ultra-high strength concrete (C100) shear walls, replaceable energy dissipation coupling beams, and composite frames. Taking a 200 meter building as an example, this paper designs and establishes calculation models for a conventional reinforced concrete frame-core tube structure and a high-performance structure based on PKPM software, and establishes elastoplastic analysis models for both based on SAUSAGE software, and then conducts dynamic elastoplastic time history analysis and seismic resilience assessment of structures under design basis earthquakes (DBEs), maximum considered earthquake (MCEs) and extremely rare earthquakes (EREs). Research has shown that compared to conventional structures, new high-performance structures can effectively reduce the size of shear walls, reduce the self-weight of the structure, and enhance the space for building use; The story drift ratio has higher redundancy than specification limits, lower plastic damage and overall stiffness degradation of the structure, and better seismic performance; The seismic resilience has significantly improved, especially in the case of casualties, which can better ensure the safety of people's lives and property.

This paper proposes a simulation technique for investigating the battery thermal management system based direct refrigerant cooling (BTMS-DRC). It employs finite element method for a combined-conduction-convection heat transfer to predict the module temperature and to prove the temperature uniformity. The refrigerant side cooling is based on the two-phase flow evaporation which is represented by the convection heat transfer (flow evaporation) under a certain refrigerant saturation temperature. The battery heat generation is modeled as the constant heat flux. The main module is modeled as the conduction heat transfer. The real BTMS-DRC is constructed for experimentation with the test bench which is based on the dual-evaporators vapour compression refrigeration system. The simulated result is validated with the experimental results to ensure the correction of the modelling. The simulation also investigates the impact of the heat generation, convection heat transfer coefficient, refrigerant saturation temperature, and thermal conductivity on the module temperature and temperature uniformity. It is found that the simulated results agree well with the experimental results. The errors are around 2.9 - 7.2% throughout the specified working conditions. Overall, the proposed technique can be used as a design tool for further developing the BTMS-DRC.

The research on the impact of excavation of underpass tunnels has already had certain results, but there is a lack of research cases of double-line highway tunnels with oblique angles underpass the existing railway tunnels, especially the method of determining the area of the impact of the dynamic and static loads of the new tunnels and existing trains to be enriched by considering them at the same time. In this paper, based on the tunnel project of the new double-line Shiqian Highway Tunnel with oblique angles underpass the Hurong Railway in Wanshoushan. By constructing a three-dimensional finite element model and simulating the application of static tunnel excavation load, dynamic blasting load and dynamic train operation load of the existing tunnel, the overall displacement of the existing tunnel and the settlement value of the bottom plate of the track surface by the static tunnel excavation load were analyzed. Then, the stresses, vibration speeds and displacements of the tunnel due to the dynamic blasting loads and the dynamic train operation loads were obtained. The results show that: the area of influence of the static loads of the new tunnel excavation on the existing tunnel is divided into three types of perturbations presenting strong, weak and slight; the area affected by the blasting dynamic load of new tunnel excavation is a circular domain with the datum point in the tunnel section as the center; the area affected by the dynamic load of train operation in the existing tunnel is an ellipse with the center of the track surface of the existing tunnel as the datum; there is an anomalous shape in the area affected by the blasting dynamic load of new tunnel excavation and the area affected by the dynamic load of train operation in the existing tunnel.

The article describes the use of microwave irradiation in the synthesis of bis(cyclo carbonate) compounds (BCC) in bulk (without solvent) from carbon dioxide capture using an epoxidized compound - a commercial epoxy resin, and compares this process to the conventional method. CO2 cycloaddition to epoxides is an ecological and efficient method for the formation of bis(cyclic carbonates). Moreover, the introduction of gas into the reaction mixture was carried out at atmospheric pressure with a controlled flow rate, which is advantageous from an economic point of view. Progressive structural changes and the presence of characteristic chemical groups were monitored using attenuated total reflectance infrared spectroscopy with Fourier transform. The obtained crude products were purified to obtain three fractions, which were subjected to detailed structural analysis using FT-IR and 13CNMR. The formation of the main product with two cyclic carbonates was confirmed. The presence of monomers, dimers and trimers in individual fractions as well as their thermal stability were determined, and the molecular masses in individual fractions were determined using gel permeation chromatography (GPC).

Seaweed polysaccharides can substitute synthetic compounds present in commercial stimulants and fertilizers, used in agriculture to improve crops yield and vigor. In this study, three different poly-saccharides (alginate, agar and carrageenan) were extracted from one brown seaweed, Saccorhiza polyschides, and two red seaweeds, Gracilaria gracilis and Chondrus crispus, respectively, and applied on potted turnip greens (Brassica napus L.), with intention to analyze their impact on plant growth, development and metabolism. Turnip plants treated with polysaccharides, specially, carrageenan of Chondrus crispus showed the best results in improving the crop’s productivity, such as plant length and weight, number of leaves, nutrient and pigment content, and soil fertility, compared with turnip plants from the negative control or treated with a commercial leaf fertilizer. λ-carrageenan extracted from the tetrasporophyte generation of Chondrus crispus had the highest bioactivity and positive effect in turnip plants among all treatments. λ-carrageenan has shown that can improve plant growth, increase plant’s biomass, and root system, enhance photosynthetic activity, increase the uptake of soil nutrients, and protect plants against abiotic and biotic stresses, stimulating the production of secondary metabolites and manage its defense pathways. Seaweed extracted polysaccharides have the potential to be used in sustainable agriculture.

The unsafe behavior of frontline workers at construction sites is the most important cause of construction accidents. This study proposed a comprehensive model of frontline workers' unsafe behaviors based on a systems perspective and used structural equation modeling (SEM) to explore the influence mechanisms between Objective Conditions (e.g., work environment, work climate, task complexity), Safety Management (e.g., safety education and training, safety reward and punishment regulations, safety inspection, safety technology disclosure, safety warning signs), Group Influence (propagation of unsafe behaviors among workers), Personal Perception (subjective judgment of operators on their safety knowledge and skills), and Unsafe Behaviors. Data from 460 frontline workers were collected through questionnaires and the correlation hypotheses were tested using SPSS 26.0 and Amos 26.0 software. The following conclusions were obtained: (1) Objective Conditions directly positively influence Safety Management, Group Influence, and Personal Perception, but indirectly negatively influence Unsafe Behavior; (2) Safety Management not only directly positively affects Personal Perception but also directly negatively affects Unsafe Behavior. However, the direct effect of Safety Management on Group Influence is not significant; (3) Group Influence has a direct positive effect on Unsafe Behavior, but the direct effect on Personal Perception is not significant; (4) The direct effect of Personal Perception on Unsafe Behavior is insignificant. These findings can be used as preliminary data to guide decision-makers or managers in construction companies to develop reasonable management plans to curb unsafe behaviors of frontline workers.

When it is in the template RNA, the naturally occurring m¹A epitranscriptomic RNA modification was recently reported to be able to stop the RNA polymerization reaction catalyzed by the RNA dependent RNA polymerase (RdRp) of SARS-CoV-2. In this report, we report that m¹A via its triphosphate form (m¹ATP) can be incorporated into RNA by the same RdRp. These two findings point a new direction for antiviral drug development based on m¹A for combatting COVID-19. More broadly, it is possible that the large pool of epigenetic RNA as well as DNA modifications could serve as a treasury for drug discovery aimed at combating various infectious and other diseases.

The objective of this study was to create yogurts enriched with freeze-dried probiotic culture and freeze-dried fermented black chokeberry juice, in conjunction with a commercial starter culture. This approach was adopted to boost functionality and optimize the nutritional content of the yogurt. The study specifically investigated the impact of supplements, which included (i) freeze-dried probiotic culture Lactobacillus plantarum ATCC 14917 and (ii) freeze-dried fermented chokeberry juice Lactobacillus plantarum ATCC 14917, as adjuncts in different formulations of yogurt. These formulations were then compared with commercially produced yogurt. All the products exhibited favorable physicochemical properties, and the probiotic strain consistently maintained levels exceeding 7 log cfu/g throughout the entire storage period. The highest lactic acid production was observed in yogurts produced with the proposed adjuncts (1.44 g/100 g yogurt at the 28th days of storage). Levels of syneresis were observed in lower values in yogurt produced with freeze-dried fermented chokeberry juice. Yogurts prepared with the supplement derived from fermented juice displayed elevated total phenolic content and antioxidant capacity (25.74 µg GAE/g and 69.05 µmol TE/100g respectively). Moreover, sensory tests indicated an exceptional aroma and fruit flavor. The results demonstrate that the inclusion of dried probiotic-fermented chokeberry juice as an adjunct in yogurt production enhances both the antioxidant capacity and the growth of beneficial bacteria. Furthermore, the dried form of this product makes it a significant candidate for industrialization potential due to its stability and ease of application.

The purpose of these studies was to investigate effect of selenate (Se6), selenized yeast (SeYe) and carnosic acid (CA) supplementation to the diet containing fish oil (F-O) and rapeseed oil (R-O) on contents of fatty acids (FA), malondialdehyde (MDA), tocopherols (Ts) and total cholesterol (TCh) in lambs’ spleens. 24 male lambs (4 groups per 6 animals) have been fed: the control diet - the basal diet (BD) enriched in F-O and R-O; the CA diet - BD enriched in F-O, R-O and CA; the SeYeCA diet - BD enriched in F-O, R-O, CA and SeYe; the Se6CA diet - BD enriched in F-O, R-O, CA and Se6. Dietary modifications affected profiles of FA in spleens. The SeYeCA and Se6CA diets increased the docosapentaenoic acid preference in Δ4-desaturase, hence the higher content of docosahexaenoic acid was found in spleens of SeYe- or Se6-treated lambs than in spleens of animals receiving the CA and control diets. Experimental diets reduced the level of atherogenic FA in the spleen in comparison with the control diet. The experimental diets supplemented with SeYe or Se6 increased levels of TCh and Ts in spleens in comparison with the CA and control CA diets. The present studies documented that Se6, SeYe and CA influenced the metabolism of FA, Ts and cholesterol in spleens.

One of the most common subgroups of cutaneous T-cell lymphomas is the that of primary cutaneous CD30 positive lymphoproliferative disorders. The group includes lymphomatoid papulosis (LyP) and primary cutaneous anaplastic large cell lymphoma (pcALCL), as well as some borderline cases. Recently, significant progress has been made in understanding the genetics and treatment of these disorders. This review article summarizes the clinical evidence supporting the current treatment options in these diseases. Recent years have seen the introduction of novel agents into clinical practice; most of these target CD30, such as anti-CD30 monoclonal antibodies and conjugated antibodies (brentuximab vedotin), bispecific antibodies and cellular therapies, particularly anti-CD30 CAR-T cells. This paper briefly reviews the biology of CD30 that makes it a good therapeutic target, and describes the anti-CD30 therapies that have emerged to date.