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Abstract Background Uricase is a bio-drug used to reduce urate accumulation in gout disease. Thus, there is a continuous demand for screening soil samples derived from a variety of different sources in order to isolate a strain that possesses a high potential for producing uricase. Methods Streptomyces sp. strain NEAE-5 demonstrated a significant capacity for uricase production was identified based on the physiological, morphological and biochemical characteristics, as well as 16S rDNA sequencing analysis. Using a Plackett–Burman statistical design, the impact of eighteen process factors on uricase production by Streptomyces griseorubens strain NEAE-5 was investigated. Using central composite design, the most important variables that had a favourable positive impact on uricase production by Streptomyces griseorubens strain NEAE-5 were further optimized. Results It is clear that the morphological and chemotaxonomic features of Streptomyces sp. strain NEAE-5 are typical for the Streptomyces genus. Phylogenetic analysis indicated that Streptomyces sp. strain NEAE-5 belongs to the genus Streptomyces and closely related to Streptomyces griseorubens which it has a 95–96% identity in 16S rDNA gene sequencing. Accordingly, the strain is proposed to be identified as Streptomyces griseorubens strain NEAE-5. The three factors that had the significant positive impacts on uricase production were uric acid, hypoxanthine, and yeast extract. As a result, the best conditions for achieving the highest experimental uricase production by Streptomyces griseorubens strain NEAE-5 after central composite design were (g/L): uric acid 6.96, glycerol 5, hypoxanthine 5.51, MgSO4.7H2O 0.1, KNO3 2, CaCl2 0.5, K2HPO4 0.5, NaCl 0.5, yeast extract 1.08. In addition, the period of incubation is seven days, pH 7.5 and 37 °C with an inoculum size of 2 mL (105 cfu/mL) /100 mL medium. Conclusions After optimization, the obtained uricase activity was 120.35 U/mL, indicating that the Streptomyces griseorubens strain NEAE-5 is a potent uricase producer and that the statistical approach used for optimization was appropriate.

Abstract Accurate bacterial identification is essential for determining the causative agent of an infection, thus facilitating appropriate treatment and management strategies in both human and animal health contexts. Some species in the Vibrio genus are recognized pathogens, associated with a variety of infections. However, identification of these bacteria is oftentimes controversial. Therefore, we aimed to evaluate different identification approaches in terms of their reliability in distinguishing Vibrio species. To achieve this, we selected a set of 40 Vibrio isolates previously recovered from water and floating plastic samples in a large bay environment and identified them employing MALDI-TOF mass spectrometry, and rrs and pyrH gene sequencing. A subset of isolates was also submitted to whole genome sequencing. Overall, MALDI-TOF was found to be a fast-screening methodology for identification, notably at genus-level. However, for better species discrimination, pyrH gene sequencing stood out as a more reliable tool in contrast to rrs gene sequencing and MALDI-TOF, as corroborated by whole genome sequencing analysis.

The Mangshan pit viper, Protobothrops mangshanensis, is a rare, highly endangered snake native to the mountainous regions of Hunan Province in China. Snakes possess abdominal scent glands, which have been chemically studied in several species. These glands can contain various lipids and peptides, but very often also complex mixtures of carboxylic acids. We report here the occurrence of novel methyl-branched unsaturated acids found in the secretions of six captive individuals living in a zoo. The structures of these compounds, 4.6-dimethylalk-5-enoates in a homologous series from C11–C16, were characterized by GC–MS and GC–IR analysis and various microderivatization reactions including hydrogenation and esterification leading to methyl and pyridylmethyl esters. In addition, dimethyloxazoline formation helped to localize the double bond. The synthesis of methyl 4,6-dimethyldodec-5-enoate allowed the correct assignment of structures and showed the (E)-configuration of the double bond for the major naturally occurring diastereomers. These acids occur in small amounts compared to the major glandular components, cholesterol, and 1-O-hexadecylglycerol, as well as other common long-chain alcohols and amides. Although a general defensive function has been proposed for snake abdominal scent glands, the specific chemistry and moderate amounts of acids reported here may suggest a function in chemical signaling for the Mangshan pit viper. In addition, proline-containing diketopiperazines were identified for the first time in snake scent glands, although an artificial formation from amino acids likely present in the secretion cannot be excluded.

Abstract Purpose To develop and validate a radiomic model for differentiating pulmonary invasive adenocarcinomas from benign lesions based on follow-up longitudinal CT images. Methods This is a retrospective study including 336 patients (161 with invasive adenocarcinomas and 175 with benign lesions) who underwent baseline (T0) and follow-up (T1) CT scans from January 2016 to June 2022. The patients were randomized in a 7:3 ratio into training and test sets. Radiomic features were extracted from lesion volumes of interest on longitudinal CT images at T0 and T1. Differences in radiomic features between T1 and T0 were defined as delta-radiomic features. Logistic regression was used to build models based on clinicoradiological (CR), T0, T1, and delta radiomic features and compute signatures. Finally, a nomogram based on the CR, T0, T1 and delta signatures was constructed. Model performance was evaluated for calibration, discrimination, and clinical utility. Results The T1 radiomic model was superior to the other independent models. In the training set, it had an area under the curve (AUC) of 0.858), superior to the CR model (AUC 0.694), the T0 radiomic model (AUC 0.825), and the delta radiomic model (AUC 0.734). In the test set, it had an AUC of 0.817, again outperforming the CR model (AUC 0.578), the T0 radiomic model (AUC 0.789), and the delta radiomic model (AUC 0.647). The nomogram incorporating the CR, T0, T1 and delta signatures showed the best predictive performance in both the training (AUC: 0.906) and test sets (AUC: 0.856), and it exhibited excellent fit with calibration curves. Decision curve analysis provided additional validation of the clinical utility of the nomogram. Conclusion A nomogram utilizing radiomic features extracted from longitudinal CT images can enhance the discriminative capability between pulmonary invasive adenocarcinomas and benign lesions.

Abstract Considering the challenges of low multi‐object detection accuracy and difficulty in identifying small targets caused by challenging environmental conditions including irregular lighting patterns and ambient noise levels in the mining environment with autonomous electric locomotives. A new network model based on SOD−YOLOv5s−4L has been proposed to detect multi‐objects for autonomous electric locomotives in underground coal mines. Improvements have been applied in YOLOv5s to construct the SOD−YOLOv5s−4L model, by introducing the SIoU loss function to address the mismatch between real and predicted bounding box directions, facilitating the model to learn target position information more efficiently. This research introduces a decoupled head to enhance feature fusion and improve the positioning precision of the network model, enabling rapid capture of multi‐scale target features. Furthermore, the detection capability of the model has been increased by introducing the small target detection layer which is developed by increasing the number of detection layers from three to four. The experimental results on multiple object detection dataset show that the proposed model achieves significant improvement in mean average precision (mAP) of almost 98% for various types of targets and an average precision (AP) of nearly 99% for small targets on the other hand it achieves 5.19% (mAP) and 9.79% (AP) compared to the YOLOv5s model. Furthermore, comparative analysis with other models like YOLOv7 and YOLOv8 shows that the proposed model has superior performance in terms of object detection.

One of the plantation products that is a mainstay export commodity and is considered quite strategic in supporting the Indonesian economy is tea. However, in recent years tea production has fluctuated, to keep Indonesia as the world's main tea producer, production problems and intensive efforts that support productivity need to be managed optimally. Tea quality is strongly influenced by environmental factors such as the presence of weeds. Assessment of the types of weeds in tea plants can be done by identification based on morphology. The purpose of this study was to identify weeds in tea plants (Camellia sinensis L.) in the Liki plantation unit at PT. Mitra Kerinci. This activity was carried out in July - August 2022 at PT. Mitra Kerinci, Sungai Lambai, Nagari Lubuk Gadang Selatan, Sangir District, South Solok Regency, West Sumatra Province. Observations were made using descriptive methods. It was concluded that there were 8 families and 14 species of broad-leaf weeds; 1 family and 2 species of Cyperaceae weeds; 1 family and 3 species of Poaceae weeds; and 3 families and 4 species of Filicinae weeds in this tea plantation.

Currently, switched reluctance motors are considered the most promising type of electromechanical energy converter without permanent magnets, especially for operations at sub-nominal speeds. To control of a switched reluctance motor to minimize torque ripple requires the regulation of phase currents based on the rotor angular position, utilizing the flux linkage as a function of both current and rotor angle. The flux linkage characteristic is essential in control systems that indirectly determine the rotor position. The paper presents an experimental methodology for deriving the flux linkage characteristic of a switched reluctance motor. The calculation of flux linkage for each rotor position angle of the electric machine is provided. The proposed methodology involves mechanically locking the rotor and periodically applying voltage to one of the motor phases using a power converter to gather data on phase current and voltage. Using the proposed experimental methodology, the relationships between flux linkage, phase current, and rotor angle were obtained. The results demonstrate that this methodology can be effectively utilized to accurately determine the flux linkage characteristic of a switched reluctance motor. The experimental methodology proposed in this paper can be employed to generate the flux linkage characteristic of a switched reluctance motor. This approach is particularly advantageous for designing model predictive control systems.

In the realm of image-based breast cancer detection and severity assessment, this study delves into the revolutionary potential of sophisticated artificial intelligence (AI) techniques. By investigating image processing, machine learning (ML), and deep learning (DL), the research illuminates their combined impact on transforming breast cancer diagnosis. This integration offers insights into early identification and precise characterization of cancers. With a foundation in 125 research articles, this article presents a comprehensive overview of the current state of image-based breast cancer detection. Synthesizing the transformative role of AI, including image processing, ML, and DL, the review explores how these technologies collectively reshape the landscape of breast cancer diagnosis and severity assessment. An essential aspect highlighted is the synergy between advanced image processing methods and ML algorithms. This combination facilitates the automated examination of medical images, which is crucial for detecting minute anomalies indicative of breast cancer. The utilization of complex neural networks for feature extraction and pattern recognition in DL models further enhances diagnostic precision. Beyond diagnostic improvements, the abstract underscores the substantial influence of AI-driven methods on breast cancer treatment. The integration of AI not only increases diagnostic precision but also opens avenues for individualized treatment planning, marking a paradigm shift toward personalized medicine in breast cancer care. However, challenges persist, with issues related to data quality and interpretability requiring continued research efforts. Looking forward, the abstract envisions future directions for breast cancer identification and diagnosis, emphasizing the adoption of explainable AI techniques and global collaboration for data sharing. These initiatives promise to propel the field into a new era characterized by enhanced efficiency and precision in breast cancer care.

Abstract Background Plastids originated from an ancient endosymbiotic event and evolved into the photosynthetic organelles in plant cells. They absorb light energy and carbon dioxide, converting them into chemical energy and oxygen, which are crucial for plant development and adaptation. However, little is known about the plastid genome to light adaptation. Petrocosmea, a member of the Gesneriaceae family, comprises approximately 70 species with diverse light environment, serve as an ideal subject for studying plastomes adapt to light. Results In this study, we selected ten representative species of Petrocosmea from diverse light environments, assembled their plastid genomes, and conducted a comparative genomic analysis. We found that the plastid genome of Petrocosmea is highly conserved in both structure and gene content. The phylogenetic relationships reconstructed based on the plastid genes were divided into five clades, which is consistent with the results of previous studies. The vast majority of plastid protein-coding genes were under purifying selection, with only the rps8 and rps16 genes identified under positive selection in different light environments. Notably, significant differences of evolutionary rate were observed in NADH dehydrogenase, ATPase ribosome, and RNA polymerase between Clade A and the other clades. Additionally, we identified ycf1 and several intergenic regions (trnH-psbA, trnK-rps16, rpoB-trnC, petA-psbJ, ccsA-trnL, rps16-trnQ, and trnS-trnG) as candidate barcodes for this emerging ornamental horticulture. Conclusion We newly assembled ten plastid genomes of Petrocosmea and identified several hypervariable regions, providing genetic resources and candidate markers for this promising emerging ornamental horticulture. Furthermore, our study suggested that rps8 and rps16 were under positive selection and that the evolutionary patterns of NADH dehydrogenase, ATPase ribosome, and RNA polymerase were related to the diversity light environment in Petrocosmea. This revealed an evolutionary scenario for light adaptation of the plastid genome in plants.

Abstract Culicoides, among the tiniest and most abundant hematophagous insects globally, serve as vectors for a variety of pathogens such as viruses, bacteria, parasites, protozoa, and nematodes. This study aimed to identify Culicoides species and assess their spatial distribution and seasonal occurrence in selected districts of the Central, South, and West Gondar zones, Northwest Ethiopia. A cross-sectional study was conducted between January to July 2023. A total of 44 UV light- onderstepoort traps were deployed in the study districts near specific areas. The traps were operational from dusk (6:00 PM) until dawn (6:00 AM) and were suspended at a height of 1.5 to 2 m above the ground. Poisson regression was used to assess associations, the Shannon diversity index to measure diversity, and QGIS 3.22.6 to create maps. In this study, 8,857 Culicoides were captured across the 44 trapping sites. Of the total flies captured flies, 8,838 were identified as belonging to 12 distinct species, while the classification of the remaining 19 flies remained unclear. Notably, C. kingi (54.01%) was the most prevalent species, followed by C. imicola (44.55%). The abundance of Culicoides observed from January to late April (3505) was significantly lower compared to the wet season (5355), with a marked increase in the capture of C. kingi (2499) from May to late July. A statistically significant association (p

The purpose of the work is to study the definition and content of the terms “digital personality”, “digital image of a person”, “digital profile”, “digital citizenship”, their interrelation, as well as legal problems related to these categories. The relevance of the topic is confirmed by the active discussion of regulatory legal acts in the areas of building a system of digital profiles, digital citizenship in different countries of the world. The method of research is the analysis of Russian and foreign literature and practice, identification of their fundamental provisions, study of interrelations with more “classical” legal categories, including classical human rights and personal data. The conclusion is drawn about the fundamental position of the category of “digital personality” for the study of the phenomenon of the modern digital person. It is primarily related to human rights in the modern digital world. Such a category directly affects other concepts under study, including information (data) about individuals, as well as the overall policy in the sphere of citizens' participation in state governance. In order to study the phenomenon of the digital person, it is necessary, first of all, to study the category of the digital person from the point of view of their rights in the digital world, i.e., from the point of view of human rights.

INTRODUCTION. The quality evaluation of live anthrax vaccines will benefit from the implementation of alternative testing methods that are capable of specific identification of the Bacillus anthracis spore antigen using the appropriate diagnostic products that are authorised in the Russian Federation for the detection of B. anthracis spores.AIM. This study aimed to investigate the applicability of immunofluorescence analysis to the identification of live anthrax vaccines and compare this method with immunochromatography.MATERIALS AND METHODS. The study used commercial batches of a live anthrax vaccine and Russian diagnostic products, including diagnostic dry adsorbed fluorescent anti-anthrax spore immunoglobulins and an immunochromatographic assay (ICA) reagent kit for rapid detection and identification of B. anthracis spores (ICA system for B. anthracis). For smears and ICA system reactions, the authors prepared working solutions of bacterial suspensions at spore concentrations typical of the B. anthracis STI-1 vaccine strain. The spore concentrations were achieved using the pharmacopoeial reference standard (RS) for the opacity of bacterial suspensions of 10 international units (IU). Identification reactions involved the registration of immune complex formation.RESULTS. Immunofluorescence tests of the live anthrax vaccine demonstrated bright greenish-yellow envelope fluorescence with an intensity score of 3+ to 4+ for smears stained with diagnostic immunoglobulins at 1:32 and 1:64 dilutions. Immunochromatographic tests of the live anthrax vaccine detected the spore antigen at vaccine concentrations of 109 and 108 spores/mL, with the test strips showing two distinct dark-pink lines indicative of immunoprecipitation. According to the results obtained using the selected methods, the tested microbial culture was confirmed as B. anthracis.CONCLUSIONS. Immunochromatography and immunofluorescence tests with appropriate diagnostic preparations are convenient and reliable tools for the species-specific detection of B. anthracis STI-1 spores in the live anthrax vaccine. The results obtained in the anthrax vaccine identification tests provide a basis for recommending the above methods as supplementary alternatives to Ziehl–Neelsen bacteriological staining, which is currently prescribed by the State Pharmacopoeia of the Russian Federation.

The Screening, Identification, Assessment and Support (SIAS) policy was developed to enable South African schools to respond systemically to diverse needs within an inclusive education (IE) system. This study explored teachers’ role as case managers with the implementation of the SIAS policy in inclusive education in three schools in the Pinetown District of KwaZulu-Natal. One departmental head and one principal from each of the selected schools were interviewed while two focus group discussions per school consisting of six teachers were conducted. The researcher used a reflective journal during the research process to ensure that the study was conducted rigorously as this improves the quality of the study. This qualitative study was grounded by Bronfenbrenner’s Bio-Ecological Systems Theory. The findings revealed that teachers lack adequate knowledge of the SIAS policy, leading to insecurity in its implementation. Overcrowded classes also pose a challenge, hindering teachers’ ability to provide individual support. The research aimed to contribute to a greater understanding of teachers’ challenges in understanding SIAS policy and the effective implementation of inclusive education. This study discusses the inadequate knowledge, understanding, and skills of teachers in implementing the SIAS policy effectively. To remedy this, regular workshops should be provided to teachers, which should explain the SIAS process or protocol, provide information on the responsibilities of all stakeholders, and inform teachers about their roles and responsibilities as case managers. Additionally, collaboration between the DBST, SBST, parents, and teachers is essential for the successful implementation of the policy, as it aims to provide teachers with the necessary support and resources.

Abstract The humanitarian discourse has recently shifted towards bolstering the intervention capacities of affected countries and communities through “localization.” However, the implementation of this approach has encountered challenges and disappointments, partly due to conventional short-term interventions driven by external organizations rather than beneficiaries. Empowering women in developing nations is vital for gender equality and women’s rights, given the barriers they face such as unequal access to resources and underrepresentation in governance. Malawi”s context, marked by poverty, limited access to education and healthcare, and cultural norms posing barriers to gender equity, complicates efforts to address inequalities against women. This article explores how localization, particularly through local NGOs, can advance women’s rights in Malawi by challenging gender norms. While recognizing its potential, caution is advised to avoid reinforcing past exclusions. This research investigates how aid localization, leveraging identification, affects gender equality and women’s rights in disaster management and humanitarian efforts. Through field research in Malawi, including 33 interviews with NGO members and beneficiaries, it underscores the role of localization in promoting gender equality and women’s rights, advocating for a more equitable and locally responsive approach to humanitarian action.

Background According to the UN Committee Against Torture, all state parties to the Torture Convention have a responsibility to meet the rehabilitation needs of torture victims who have sought asylum within their borders. General practitioners (GPs) can play a crucial role in identifying torture victims and securing rehabilitation when needed. There is a pressing knowledge gap on the knowledge and practices of GPs vis-à-vis potentially tortured patients, and an urgent need for research that investigates GPs’ practices of identification, referral, and rehabilitation – in Norway and beyond. This article presents an exploratory qualitative pilot study that investigates the experiences of GPs in Oslo vis-à-vis this patient group.Methods Semi-structured interviews with five experienced GPs in the greater Oslo area. Interview data was analyzed through thematic analysis and discussed within a theoretical framework seeing GPs as street-level bureaucrats.Results Issues that emerged in the pilot involve a consistent professional confidence and a particular concern for victims of sexual violence and sexualized torture. The pilot also found a troubling commonsensical reasoning about identification in the asylum process. The GPs asked for the re-establishment of specialist rehabilitation centers for refugees and torture victims to consult in case of need. Alas, the study also confirmed that GPs are a difficult profession to recruit for research.Conclusions This study indicates that GPs are important actors in terms of identifying torture victims after resettlement, but that there are shortcomings in their training and knowledge, in the overall organization of the healthcare system, and in specialized healthcare, that limit prospects for rehabilitation.

Background Carotid atherosclerosis (CAS) is often considered an early warning signal for cardiovascular diseases (CVD). The diagnostic technique of carotid artery Doppler ultrasonography has not been included in public health service programs, and the Framingham Risk Score (FRS) lacks accuracy in assessing CAS risk, hindering the identification of CAS by primary healthcare personnel. Currently, there is a lack of research on machine learning methods to identify CAS in the medium-high risk population assessed by FRS. Objective To construct a CAS risk prediction model for the medium-high risk population assessed by FRS using machine learning methods, compare its discriminative efficacy, select the optimal model, and assist primary healthcare personnel in identifying CAS more conveniently and accurately. Methods Using convenience sampling method, a total of 674 local residents from two townships in Liuzhou City, Guangxi Zhuang Autonomous Region, who met the inclusion criteria from 2019 to 2021 and 2023, were selected as the study subjects. Relevant information was collected, and biochemical indicators were measured in fasting blood and urine samples. FRS was used to assess the risk of CVD occurrence, and carotid ultrasound was used to diagnose CAS. Among the 517 subjects from 2019 to 2021, a random 8∶2 split was used to create a training set and a validation set. The training set was used to build Logistic regression, Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), and Gradient Boosting Decision Tree (GBDT) models, while the validation set was used for internal validation. The 157 subjects from 2023 served as the test set for external validation. Feature variables were selected using Lasso regression analysis, and discriminative efficacy was evaluated using sensitivity, specificity, accuracy, F1 score, and area under curve (AUC) value. External validation assessed the generalization ability of the optimal model using AUC value, and the Shapley Additive exPlanation (SHAP) method explored the important variables influencing the optimal model's identification of CAS. Results Lasso regression analysis identified 15 feature variables: age, BMI, systolic blood pressure (SBP), smoking, drinking, hypertension, total cholesterol, high density lipoprotein cholesterol, C-reactive protein (CRP), fasting plasma glucose, apolipoprotein B (ApoB), lipoprotein a (LPA), aspartate aminotransferase (AST), AST/ alanine aminotransferase, urinary microalbumin creatinine ratio. The constructed Logistic regression, RF, SVM, XGBoost, and GBDT models exhibited high AUC values, with the GBDT model showing the best discriminative performance. Its sensitivity, specificity, accuracy, F1 score, and AUC value were 0.755 1, 0.836 4, 0.798 1, 0.778 9, and 0.834 9, respectively, and the external validation AUC value was 0.794 0. The SHAP method revealed that age, SBP, CRP, LPA, and ApoB were the top five factors influencing the GBDT model's identification of CAS. Conclusion Logistic regression, RF, SVM, XGBoost, and GBDT models for identifying CAS based on machine learning all demonstrated high discriminative performance, with the GBDT model exhibiting the best comprehensive discriminative efficacy and strong generalization ability.

Introduction. The evaluation of microbial biodiversity is an important step in the process of its conservation, and the identification of bacterial strains of biotechnological interest allows their application as support for the development of sustainable agriculture technologies. Material and methods. From the lakes of the "La Izvor" park, 213 types of bacteria, 148 of them pathogenic, were isolated. From the non-pathogenic ones, those of biotechnological interest were determined the enzymatic properties, and antimicrobial activity and were identified by molecular biological methods after that preserved by the lyophilization method with the determination of viability before and after lyophilization. Results. The microbial biodiversity of the "La Izvor" lakes was studied, 213 types of bacterial colonies were isolated in pure culture, which of 148 proved to be enteropathogenic belonging to the genera Escherichia, Salmonella, Shigella, Enterobacter and Klebsiella and other strains from the Enterobacteriaceae family. The purpose of the research consisted of the isolation and identification of non-pathogenic bacteria of biotechnological interest with different properties that could serve to elaborate and improve the development of sustainable agriculture technologies. Nineteen strains with enzymatic properties and high antifungal activity against phytopathogenic fungi were selected for molecular identification, passported, submitted to the NCNM and preserved by the lyophilization method for determination of valuable properties for a long time. Conclusions. In the lakes of "La Izvor" park, there is a very large variety of microorganisms, especially bacteria, some of which are enteropathogenic bacteria that can cause diseases in the population. Selected non-pathogenic strains stored in the NCNM can be applied against phytopathogens that cause dangerous diseases and damage in agriculture's major crops. As a result of lyophilization, we found that all strains showed osmotic and thermal shock tolerance and had a viability of over 75%.

Abstract Areca (Areca catechu L.) nut is a tropical plantation fruit cultivated mainly in South and Southeast Asia. As a chewing hobby, it has become the most common psychoactive substance in the world, besides tobacco, alcohol, and caffeine. Areca catechu contains abundant nutrients and active components such as alkaloids, polyphenols, polysaccharides, proteins, and vitamins, which have been reported to have anti‐inflammatory, antioxidant, antibacterial, anti‐depressant, anti‐hypertensive, anti‐fatigue, and other biological properties. However, at present, the resource utilization rate of the whole‐plant areca nut is low, which not only causes resource waste but also damages the environment. Establishing effective, safe, and environmentally friendly techniques and methods is necessary for the comprehensive utilization of A. catechu resources. In this review, we summarized the traditional and advanced methods for the extraction and identification of main bioactive substances in A. catechu and compared the advantages and disadvantages of these methods. Furthermore, the possible trends and perspectives for future use of A. catechu are also discussed. Our objective is to extend the application of this bioactive ingredient to improve the added value, provide valuable information for developing new A. catechu products and derivatives, and improve the comprehensive utilization of areca nut resources.

Identification and examination of export-import goods, in particular lemons, plays a significant role in facilitating the detection of customs violations and crimes, as well as in ensuring preventive measures to eliminate them. The article analyses the peculiarities of examination of citrus fruits, in particular lemons, with a view to their classification under classifier of goods Commodity Nomenclature of Foreign Economic Activity. The methodological approaches to the classification of citrus fruits within the framework of commodity expertise are considered. The main diagnostic tasks to be solved by a forensic expert in the course of lemon examination are identified: determination of product quality, chemical analysis, phytopathological analysis, toxicological analysis, organoleptic analysis, microbiological analysis, identification of origin, assessment of storage and transportation conditions. Modern analytical methods allow to conduct a comprehensive study of lemons at various levels – molecular, chemical and morphological – to obtain objective data on their quality, safety and other important characteristics. This data can be useful in legal proceedings to determine the origin, compliance with quality standards and dispute resolution. The article summarises information on the typical defects of lemons, namely: mechanical damage, diseases and lesions, growth and development defects, skin defects, parasites and pests, physiological defects, chemical defects (these defects are of natural origin). Defects inherent in low-quality products with signs of deterioration include mechanical damage, rot and mould, discolouration, wrinkling, shape defects, pests, disease damage, additional chemical treatment, loss of aroma and taste, improper storage and transportation, black spots, and skin tears. The mechanism for conducting a forensic examination of lemons is described in detail.

INTRODUCTION. The range of liquid multivitamins for toddlers approved in the Russian Federation comprises two imported syrups. Pharmacy compounding of vitamin syrups will meet the demand for optimally formulated multivitamins in the pharmaceutical market. Therefore, a necessary step for their release into medical practice is to develop and validate analytical procedures for assessing the quality of such medicinal products.AIM. This study aimed to select and adapt analytical procedures for assessing the quality of a compounded multivitamin product for children.MATERIALS AND METHODS. The study focused on a compounded sorbitol syrup containing vitamins C, PP, B1, B2, and B6. The quantities of vitamin components in the syrup corresponded to the recommended daily intake for children aged 1–3 years. For identification, the authors used qualitative reactions and spectrophotometry. Indicator-free direct iodometry was selected for the quantitative determination of ascorbic acid. Alkalimetry with bromothymol blue was used to quantitate nicotinic acid in the presence of ascorbic acid, pyridoxine hydrochloride, and thiamine hydrochloride. The sum of thiamine hydrochloride and pyridoxine hydrochloride was determined by direct argentometry (Fajans method) with bromophenol blue in an acetic acid medium. Riboflavin quantification involved visible spectrophotometry at 445 nm and spectrofluorometry. The sorbitol content was measured by refractometry, and the calculations accounted for the content of other syrup components. The validation was conducted in line with the applicable pharmacopoeial requirements (State Pharmacopoeia of the Russian Federation).RESULTS. The authors selected analytical procedures for the quality evaluation of the multivitamin syrup containing five water-soluble vitamins (С, РР, В1, В2, В6) and sorbitol. These analytical procedures were adapted to the simultaneous presence of riboflavin, ascorbic acid, nicotinic acid, thiamine hydrochloride, and pyridoxine hydrochloride. The authors developed analytical procedures for the determination of riboflavin by spectrofluorometry and spectrophotometry and for the selective determination of thiamine hydrochloride by photometry after a precipitation reaction with Reinecke’s salt. The analytical procedure for the determination of riboflavin by spectrofluorometry was validated for specificity, accuracy, linearity, precision (repeatability and intermediate precision), and range.CONCLUSIONS. The study confirmed the applicability of the analytical procedures that were selected and adapted for all components of the multivitamin syrup. The authors identified the conditions for the selective determination of thiamine hydrochloride by spectrophotometry after a precipitation reaction with Reinecke’s salt. The analytical procedure for the quantitative determination of riboflavin by spectrofluorometry was validated and considered suitable for use in analytical laboratories for the quantitative determination of riboflavin in multivitamin mixtures and for syrup stability testing.

The article presents an analysis of issues regarding the current state and prospects of using machine learning elements in industrial applications of vision systems. The analysis is preceded by a short introduction to the subject of machine vision as well as a presentation of the results of research on industrial 3D vision systems, leading to conclusions that affect the prospects for further development of vision systems with elements of machine learning.

Gram-negative bacilli Klebsiella pneumoniae are among the most important pathogens responsible for healthcare-associated infections (HAIs). These bacteria often have high pathogenic and epidemic potential, contributing to infection outbreaks worldwide. K. pneumoniae is part of the natural microbiota of humans. At the same time, as an opportunistic microorganism, when the host organism is weakened, it can cause serious infections such as pneumonia, urinary tract infections, septic infections and intra-organ abscesses. Widespread distribution in nature and exceptional adaptability provide K. pneumoniae with the opportunity to master new niches in the hospital environment, which poses a threat to hospitalized patients. Also, the bacteria are increasingly causing life-threatening infections in the non-hospital environment. The pathogenicity of K. pneumoniae is determined by the presence of many virulence factors such as capsular polysaccharide (CPS, K antigen), lipopolysaccharid (LPS, O antigen), fimbrial and non-fimbrial adhesins, siderophores (aero-bactin, enterobactin, salmochelin and yersiniabactin), heat-stabile and heat-labile enterotoxins, cytotoxins and biofilm-forming ability. Currently, hypervirulent strains of K. pneumoniae (hvKp) equipped with new virulence traits constitute a significant danger. The paper presents these bacteria concerning the global threat arising from the dynamic spread of hvKp strains in hospitals in Poland and worldwide.

This research aimed to study the life cycle and duration of each biological stage of the blow fly Calliphora vicina. Adult specimens were collected from various locations in the Erbil provinces and reared on decaying chicken meat. Each female fly produced between 440 to 620 eggs during her lifetime, laying them in clusters of up to 180 eggs at a time. The larvae feed for three to four days under warm, optimal conditions, with the puparium forming two to three days later. The entire life cycle of this insect is completed in approximately 15 days. Morphologically, the adult fly is robust, dark black-blue in color, about 5-12 mm in length, while the immature stages (1st, 2nd, and 3rd larval instars) are vermiform, creamy-white, and feature a distinct cephaloskeleton and varying body lengths, while the Larva 1: Vermiform, pale yellow, length 1.7-3.4 mm.the slits of posterior spiracles were conducted to gather slightly appeared as one part,. Larva 11 Vermiform, Milky white –pale yellow, length 4.7-7.8 mm.and sometimes absent dorsally, the slits of the posterior spiracles were clearly found and separated in to two lines; . Larva III: The mature larva milky white, reaches a length 14-19 mm. Female: resembles the male but differs by the eyes are an holoptic separated from one another by board frons. The slits of the posterior spiracles were distinctly observed and divided into three lines. Another part of the study focused on identifying the insect using molecular methods, specifically PCR. Species-specific primers were prepared and the COI sequence of samples (550 bp) was aligned using the BLAST program from GenBank (http://blast.ncbi.nlm.nih.gov/) with the submitted accession number PP733158 to compare our amplified sequences with other stored sequences. The BLAST results indicated that the highest identity query sequence was recorded in the NCBI gene bank for insect identification.

Abstract A data‐driven Buck converter model identification method is proposed to deal with missing (incomplete) outputs, which is robust to the data length and percentage of missing data. A nuclear norm based convex optimization problem instead of linear interpolation, to guarantee the recovered missing data satisfying the potential model structured low‐rank character, is constructed to estimate missing outputs. The alternating direction method of multiplier strategy is used to solve the nuclear norm based convex optimization problem. In this way, the high‐quality missing data can be estimated, even for short data length and high percentage of missing data. Based on the recovered data, the subspace identification method provides accurate estimates of the structure and parameter of the Buck converter synchronously. By applying the proposed method to a Buck converter, experimental results demonstrate its effectiveness.

In September 2023, a leaf spot disease occurred on chrysanthemum (Chrysanthemum morifolium) in Imsil-gun Agricultural Technology Center, Korea. A fungal species was isolated from the diseased plant and identified as an ascomycete Epicoccum sorghinum based on morphological characteristics and phylogenetic analyses using the sequences of the ITS, TUB2, and ACT genes. A pathogenicity test revealed that the isolate was the causal agent of leaf spot disease on chrysanthemum. This is the first report of leaf spot disease caused by E. sorghinum on chrysanthemum in Korea.

With the development of science and technology, forensics has become a more attractive scientific subject to study, and the field of nanoforensic research has seen a lot of interest in nanomaterials. Fingerprints are crucial pieces of evidence at each crime scene, and future fingerprint investigations could greatly benefit from nano-based procedures. In terms of tangible evidence for proving a person’s identity, fingerprints have historically been and now are considered to be the most valuable sort. The prints left behind at a crime scene are typically latent (invisible) fingerprints; therefore, the distinctive ridge details of fingerprints can be obtained by coating various object surfaces with various nanoparticles, with gold being the most popular choice. These nanoparticles include silver, zinc oxide, silicon dioxide, aluminum oxide, gold, carbon, and silica. Latent fingerprints can be made better and more stable using nanoparticles. This review study concentrates on the employment of various nanomaterials in the creation and identification of latent fingerprints as a consequence.

Abstract Crystal violet dye poses significant health risks to humans, including carcinogenic and mutagenic effects, as well as environmental hazards due to its persistence and toxicity in aquatic ecosystems. This study focuses on the efficient removal of crystal violet dye from aqueous media using novel Co3O4/Co3(BO3)2 nanostructures synthesized via the Pechini sol–gel approach. The nanostructures, which were abbreviated to EN600 and EN800, were fabricated at calcination temperatures of 600 and 800 °C, respectively. X-ray diffraction (XRD) analysis revealed that the synthesized samples have a cubic Co3O4 phase and an orthorhombic Co3(BO3)2 phase, with mean crystal sizes of 43.82 nm and 52.93 nm for EN600 and EN800 samples, respectively. The Brunauer–Emmett–Teller (BET) surface areas of EN600 and EN800 samples were 65.80 and 43.76 m2/g, respectively, indicating a significant surface area available for adsorption. Optimal removal of crystal violet dye was achieved at a temperature of 298 K, a contact time of 70 min, and a pH of 10. The maximum adsorption capacities were found to be 284.09 mg/g for EN600 and 256.41 mg/g for EN800, which are notably higher compared to many conventional adsorbents. The adsorption process followed the pseudo-second-order kinetic model and fitted well with the Langmuir isotherm. The adsorption was exothermic, spontaneous, and physical in nature. Moreover, the adsorbents exhibited excellent reusability, retaining high efficiency after multiple regeneration cycles using 6 mol/L hydrochloric acid. These findings highlight the potential of these Co3O4/Co3(BO3)2 nanostructures as effective and sustainable materials for water purification applications.

Citizen science has been widely adopted in monitoring air quality by indexes of lichen diversity. Since the identification of lichens is challenging, volunteers are often involved in adopting simplified sampling protocols, which require identification at a higher level than the species, or the use of morpho-types, or colors. In Italy, a simple citizen science protocol for monitoring air quality with lichens by involving schools has been successfully tested, and will be replicated at the national level.

Objective: To determine the prevalence of cheiloscopic patterns in Pakistani population. Study Design: Cross-sectional study. Place and Duration of Study: The study was conducted at Post Graduate Medical Institute (PGMI), Lahore, Capital diagnostic Centre CDC Islamabad, HITEC Taxilla for a duration of 12 months from 1 September 2021 to 31 August 2022. Materials and Methods: The lip prints of 320 males and females were taken by applying lip shades and then cellophane tapes (2 inches). They were transferred to an A4 sheet (white A4 ROCO Premium 80g copy papers) and then observed with magnifying hand lenses Deluxe magnifier (70mm diameter). The data was analyzed by IBM SPSS statistics 27.0. Chi square test was applied and a p value of ≤ 0.05 was considered statistically significant. Results: The results showed differences in all individuals in both lip prints. The predominant lip pattern was type III, observed in 159 (99.4%) male participants while it was observed in all the female participants. Type I' observed in 37 (23.1%) female participants and IV are greater in females 160(100%) than males. Type II (was) greater in males 152 (95.0%) than females. Conclusion: Lip prints are useful tool that can be used as biometric markers in dentistry and forensic odontology.

For years, the Bacillus genus has encompassed a heterogeneous group of individuals whose main common trait was their ability to sporulate in the presence of oxygen. This criterion has been revised, resulting in the reclassification of several species into new genera and to a redefinition of the characteristics of the members of this taxon. Currently, the species of the genus are grouped into the Subtilis clade and the Cereus clade. The former, called Bacillus sensu stricto, initially composed of B. subtilis, B. licheniformis, B. pumilus, and B. amyloliquefaciens, has subsequently incorporated new species related to these. The Cereus clade, Bacillus cereus sensu lato, consists of pathogenic species (B. anthracis, B. cereus, and B. thuringiensis) as well as others of significance in agriculture and industry. Furthermore, identifying these individuals remains complex, requiring alternatives to 16S rRNA sequencing. The ability to form spores resistant to stressful conditions provides a significant advantage over other genera, with observable differences in sporulation rates and spore structure among different species. Additionally, Bacillus spp. are known for their capacity to produce antimicrobial substances, lytic enzymes, and volatile organic compounds, each with diverse applications. Some species are even used as probiotics. This review delves into aspects related to the taxonomy and identification of microorganisms belonging to the genus Bacillus, which often present challenges. The aim is to provide a comprehensive overview of the topic. In addition, it highlights the characteristics and applications of the genus, emphasizing its importance in biotechnology and microbiology.

Various microorganisms can grow in egg-based food products, and yeast is among the microorganisms that thrive in egg products. Yeasts naturally produce large enzymes by breaking down organic materials during growth. Yeast has a great biotechnological potential owing to its extracellular enzymatic activity. Therefore, it is important to study yeast species, especially those from food sources and the environment. Protease production and activity are affected by various factors such as temperature, time, and pH. In this study, 47 yeast isolates were identified and purified from traditionally processed Indonesian duck eggs via repeated sub-culturing and quadrant streaking. Screening of the yeast isolates on skim milk agar medium showed that 23 isolates exerted proteolytic activity, whereas the remaining 25 did not. Yeast isolates with proteolytic capabilities belonged to the Saccharomyces, Pichia, and Candida genera. The highest protease activities were observed in isolates TA-17 and TPi-08, with activity values of 0.618 and 0.098 U/mL, respectively.

Background. The relevance of the study is determined by two core factors. (1) In conditions of uncertainty and reduction of the usual bases of social solidarity, the analysis of the patterns of generational identity sets a new perspective for understanding the dynamic unity of the processes of constructing social and personal identities. (2) Identifying the phenomenology of identity of different generations seems necessary for the needs of practical psychological assistance to various social subjects. Objective. The research is focused on revealing and describing the features of identification with the generational group in people belonging to different generations. Methods. Author's questionnaire (Appendix 1) consisting of: (1) questions about historical events that influenced the formation of a generational group; (2) questions about the cultural life scenario of a generation and an assessment of the probability of a particular typical event; (3) unfinished sentences on the psychological portrait of one's generation. Study Participants. 215 respondents (Generations of Stagnation, Reform, Millennials, and Zoomers) took part in the research. Results. The identity portrait of the stagnation generation includes: an emphasis on large-scale events; the prevalence of collectivist and family values; self-attribution of such qualities as patriotism, openness to the world, conscientiousness, responsiveness. The identity of the reform generation is based on the events of the 1990s, interpreting them through the prism of the policy of openness to the outside world, as well as technological events; it is “transitional” in terms of typical life scenarios and personality traits. The identity portrait of millennials includes: mainly the events of the 2010s and economic events, the prevalence of the values of freedom, creativity, progress; self-attribution of experiencing life's difficulties. The identity of the zoomer generation is significantly different: they do not have political events in their identity portrait; recent events (pandemic, digitalization) act as an identification support; marriage and childbirth are unlikely in life scenarios; self-attributions include flexibility, individualism, political correctness, and peacefulness. Conclusion. The socio-psychological analysis of the identity of generations is implemented at three interconnected levels through identification: with historical events, with events of the life scenario and with a typical psychological portrait of a representative of the generation.

This study describes a new species, Nanopsocus ajabu n. sp., discovered on Unguja Island, Zanzibar. The species exhibits unique morphological characteristics and complex colour patterns. Material was collected and examined following standard protocols, with specimen deposited at the National Museum of Natural History, Sofia, Bulgaria. An identification key for all known Nanopsocus species is provided.

Objective: To investigate the differences in metabolites of Chinese nectarine, peento, yellow peach, Yangshan honey peach and Xinyi honey peach by using non-target metabolomics. Methods: 250 Fresh peaches of comparable maturity were used as test materials, and the fresh peach pulp was determined by high performance liquid chromatography-quadrupole tandem time-of-flight mass spectrometry (UPLC-QTOF-MS), and the metabolites of different varieties of fresh peaches were investigated by principal component analysis and metabolite variability analysis. Results: A total of 74 metabolites were detected, mainly phenolic acids, flavanols, flavonols, anthocyanins, amino acids, glycosides, iridoid glycosides, B vitamins, etc. PCA analysis revealed that compared with the other 4 fresh peaches, Yangshan honey peach had higher contents of 7-hydroxycoumarin, pinocembrin, chlorogenic acid, neochlorogenic acid, epicatechin, procyanidin A2, cryptochlorogenic acid, plantagoside, procyanidin B2, and lower levels of vitamin B2, kaempferol, rutin. Based on OPLS-DA analysis, 4 fresh peaches were screened for differential metabolites with Yangshan honey peach respectively. Nectarine had 18 species of procyanidin B3 and other metabolites, peento had 12 species of procyanidin B2 and other metabolites, yellow peach had 18 species of procyanidin A2 and other metabolites, and Xinyi honey peach had 15 species of procyanidin C1 and other metabolites, which could be used as a potential biomarker to differentiate between Yangshan honey peach and the other 4 fresh peaches. In this study, the differential metabolites of the 5 fresh peaches were mainly plant polyphenolic compounds, and chlorogenic acid and procyanidin metabolites were high in Yangshan honey peach, which were the key differential metabolites. Conclusion: The non-target metabolomics technology can effectively distinguish the five fresh peaches, which is feasible for the identification of fresh peaches, and can be used to assist the qualitative identification of fresh peaches and deep-processed fresh peaches as an important basis for the identification of true and false Yangshan honey peaches, and it is of great significance to protect the development of Yangshan honey peach speciality industry.

The study was conducted in the laboratory of the Department of Parasitology and Veterinary-Sanitary Examination of the Poltava State Agrarian University. In total, 154 slaughtered rabbits of the Grey Giant breed aged 34 months, reared at private farms of the Poltava region (Ukraine) were examined. The aim of the research was to establish differential morphological and metrical features of meta-cestodes isolated from domestic rabbits. Only one species, Cysticercus pisiformis was recorded; inva-sion rate was 17.53%. White-grey bubbles were found on the serous membranes of the abdominal and, less often, thoracic cavities. The ultrastructural characteristics of the main parts of the scolex, such as suckers, rostellum and hooks are given. The morphometric characteristics of metacestodes collected from male and female rabbits were slightly different. The study of chitinoid hooks had the greatest diagnostic value. A statistically significant variation was noted for large and small hooks. Thus, the average size of large and small hooks was likely to be smaller by 1.33 and 3.37%, respectively in samples obtained from female rabbits. The metacestodes isolated from female rabbits were larger than those obtained from male rabbits regarding length of the handle of the large (114.28 μm vs. 105.26 μm) and small hooks (43.06 μm vs. 39.3 μm, respectively).

This study was conducted to address the lack of information regarding celery crop damage in South Kalimantan due to Root Knot Nematode (RKN). This study is critical for determining the extent of celery plant damage caused by RKN (Meloidogyne spp.) in numerous districts/cities in South Kalimantan and identifying the Meloidogyne species discovered. The purposive sampling of celery crop infected with RKN was conducted in one city and three districts in South Kalimantan. Sampling was conducted at Sukamaju Ujung village, Landasan Ulin Utara, Banjarbaru City; Mandiangin village, Banjar Regency; Hamak Village, Telaga Langsat District, Hulu Sungai Selatan Regency and Jamil, Banyu Jaranih and Mahang Baru Villages, Labuan Amas Selatan District, Hulu Sungai Tengah Regency. The result showed that RKN were discovered in the Sukamaju Ujung and Mahang Baru villages. Sukamaju Ujung was the most heavily attacked by RKN, with high damage levels ranging from 85-90%, a high galling index of 8-9, and the greatest population of 1282 nematodes/5 grams of roots. In Mahang Baru village, RKN was found to have a damage level of only 15% but a high galling index of 8 (eight) and population of 1049 nematodes/5 grams of roots. Based on the perineal pattern of adult females, three species of Meloidogyne were found in Mahang Baru village, namely M. javanica, M. incognita, and M. arenaria. These three species had previously been found in Sukamaju Ujung village.

A new method for the synthesis of adaptive state observation for a class of nonlinear non-stationary systems is proposed. This task is important and fundamental in control theory and is related to both the control problem and the task of monitoring the efficiency of the system operation. The solution to the problem is based on the generalized observer parameter estimation method to obtain the regression equation necessary for estimating the state and parameters of the system. Further, the dynamic regressor expansion and blending method dynamic regressor extension and mixing method is applied to identify the unknown system parameters. The paper proposes a method for estimating the state vector for a nonlinear non-stationary system in which the unknown parameters depend on the state vector under external disturbances. The results obtained are rigorously proved using mathematical theory. Simulation in Matlab/Simulink is performed to demonstrate the effectiveness of the developed algorithm. The mathematical model of the considered objects is a nonlinear system of equations with variable parameters. Compared to previous methods, the method proposed in this paper is more general, especially in a system where the unknown parameters depend on the state vector with nonlinear functions. However, the problem is currently solved only for discrete systems. In the future, it may be possible to extend it to continuous systems.

Within the framework of the linear theory of elasticity, using the model of an isotropic body, the problem of steady-state vibrations of an inhomogeneous hollow cylinder is formulated. The vibrations of the cylinder are caused by a load applied to the side surface, and the conditions of sliding embedding are implemented at the ends. The variable material properties are described by the Lamé parameters and density, which change along the radial and longitudinal coordinates. The direct problem solution of the cylinder vibrations is constructed using the finite element method implemented in the FlexPDE package, its main advantages are noted. To study the influence of variable properties on the values of resonant frequencies and components of the displacement field, the laws of these properties are considered in the general form used in modern works for modeling functionally graded materials. On the basis of the performed numerical calculations, the degree of influence of the amplitude values of each of the Lamé parameters and density on the first resonant frequency and the displacement field are studied. Graphs are also presented that demonstrate the influence of the type of the law of density change on the values of the displacement field components. A new inverse coefficient problem is formulated to determine the density distribution function in the cylinder wall from the displacement field data measured at a finite set of points inside the considered area for a fixed frequency. The main difficulties in the implementation of the reconstruction procedure in practice are noted. To increase the accuracy of calculating the first and second derivatives of the two-dimensional functions calculated in the finite element package, which are used in solving the inverse problem, an approach based on the locally weighted regression algorithm is proposed. The results of computational experiments on solving the inverse problem are presented, which demonstrate the possibility of using the proposed method to restore various types of two-dimensional laws of density. Practical recommendations are given for the implementation of the most accurate reconstruction procedure.

Abstract This paper proposed the additional fractional gradient descent identification algorithm based on the multi-innovation principle for autoregressive exogenous models. This algorithm incorporates an additional fractional order gradient to the integer order gradient. The two gradients are synchronously used to identify model parameters, thereby accelerating the convergence of the algorithm. Furthermore, to address the limitation of conventional gradient descent algorithms, which only use the information of the current moment to estimate the parameters of the next moment, resulting in low information utilisation, the multi-innovation principle is applied. Specifically, the integer-order gradient and additional fractional-order gradient are expanded into multi-innovation forms, and the parameters of the next moment are simultaneously estimated using multi-innovation matrices, thereby further enhancing the parameter estimation speed and identification accuracy. The convergence of the algorithm is demonstrated, and its effectiveness is verified through simulations and experiments involving the identification of a 3-DOF gyroscope system.

To solve the current problems of fermented glutinous rice wine produced with traditional Jiuqu as a fermentation starter such as unstable quality, weak aroma and high alcohol content, this study selected non-Saccharomyces yeast strains with ester-producing and aroma-enhancing characteristics from traditional Jiuqu by analyzing the structure of its fungal community, and explored the effects of co-fermentation with each selected strain and Rhizopus arrhizus on the volatile flavor components of fermented glutinous rice wine. The results showed that Ascomycota and Mucoromycota were the dominant fungal phyla in Jiuqu and Rhizopus and Saccharomycopsis were the major fungal genera. Four non-Saccharomyces yeast strains, JLY1–JLY4, were obtained, and JLY1 and JLY2 were identified by sequencing as Saccharomycopsis fibuligera, while JLY3 and JLY4 as Torulaspora delbrueckii and Wickerhamomyces anomalus, respectively. Co-fermentation with JLY2 and Rhizopus arrhizus increased the number of volatile components from 46 to 62 compared with the control group, increasing the numbers of esters and alcohols and significantly increasing the relative contents of major flavor compounds such as isoamyl alcohol, phenylethanol, and phenylethyl acetate. Partial least squares-discriminant analysis (PLS-DA) was performed on 40 volatile flavor components shared by fermented glutinous rice wines, and 20 differential flavor substances were selected using the cut-off of variable importance for the projection (VIP) value ≥ 1, including 5 alcohols, 10 esters, 3 acids, 1 aldehyde or ketone, and 1 alkane. Differential substance analysis and sensory evaluation indicated that JLY1 and JLY2 were better than the other strains in terms of ester production and aroma enhancement, and synergistic fermentation significantly enhanced the contents of volatile flavor substances in fermented glutinous rice wine and consequently improved its quality.

The possibility of new viruses emerging in various regions worldwide has increased due to a combination of factors, including climate change and the expansion of international trading. Plant viruses spread through various transmission routes, encompassing well-known avenues such as pollen, seeds, and insects. However, research on potential transmission routes beyond these known mechanisms has remained limited. To address this gap, this study employed metatranscriptomic analysis to ascertain the presence of plant viruses in imported frozen fruits, specifically cherries and blueberries. This analysis aimed to identify pathways through which plant viruses may be introduced into countries. Virome analysis revealed the presence of six species of plant viruses in frozen cherries and blueberries: cherry virus A (CVA), prunus necrotic ringspot virus (PNRSV), prune dwarf virus (PDV), prunus virus F (PrVF), blueberry shock virus (BlShV), and blueberry latent virus (BlLV). Identifying these potential transmission routes is crucial for effectively managing and preventing the spread of plant viruses and crop protection. This study highlights the importance of robust quality control measures and monitoring systems for frozen fruits, emphasizing the need for proactive measures to mitigate the risk associated with the potential spread of plant viruses.

In the last decade there has been established an increase in the prevalence of Puccinia helianthi in sunflower crops in Russia. In the Rostov region, on the territory of the Don Experimental Station (the Azov region), severe damage by the sunflower rust pathogen was established in 2020. In this regard, there was a need to study the race of the fungus on sunflower crops in the Rostov region. The purpose of the study was to identify rust pathogen isolates collected from sunflower crops in accordance with the accepted international triplet nomenclature in different areas of the Rostov region in the period 2021–2023. As testers, there was used a set of differentiating lines of sunflower resistance to the pathogen, containing SM 90, SM 29, P-386, HA-R1, HA-R2, HA-R3, HA-R4, HA-R5 and the line ‘ED 47’, susceptible to all biotypes of the fungus. The total sample consisted of 237 parasite urediniospore isolates collected from infected leaves of sunflower plants. There were differentiated 34 biotypes of P. helianthi. The most virulent pathotype 777 was identified among isolates from the Tatsinsky, Morozovsky and Konstantinovsky districts of the region in 2023. The race with code number 700 was identified in almost all represented areas of the region and accounted for 52.7% of the studied sample of sunflower rust pathogen isolates. In the current work the racial composition of the pathogen in the Rostov region was studied for the first time. The study results have indicated the need to continue monitoring new biotypes of P. helianthi, as well as expand and accelerate work on the development of sunflower hybrids resistant to the predominant race with code 700 in the sample.

Animal welfare is a daily concern for livestock farmers. It is known that the activity of cows characterizes their general physiological state and deviations from the normal parameters could be an indicator of different kinds of diseases and conditions. This pilot study investigated the application of machine learning for identifying the behavioral activity of cows using a collar-mounted gyroscope sensor and compared the results with the classical accelerometer approach. The sensor data were classified into three categories, describing the behavior of the animals: “standing and eating”, “standing and ruminating”, and “laying and ruminating”. Four classification algorithms were considered—random forest ensemble (RFE), decision trees (DT), support vector machines (SVM), and naïve Bayes (NB). The training relied on manually classified data with a total duration of 6 h, which were grouped into 1s, 3s, and 5s piles. The obtained results showed that the RFE and DT algorithms performed the best. When using the accelerometer data, the obtained overall accuracy reached 88%; and when using the gyroscope data, the obtained overall accuracy reached 99%. To the best of our knowledge, no other authors have previously reported such results with a gyroscope sensor, which is the main novelty of this study.

[Objective] This study aimed to screen the excellent lactic acid bacteria strains to construct a special pickle fermentation strain for radish. [Methods] Lactic acid bacteria were isolated from the pickle brines of Laotan sauerkraut collected from different regions by dilution coating method. The species were determined by physiological identification, morphological identification （colony observation, Gram staining）, 16S rDNA gene sequencing and phylogenetic tree construction, and their growth characteristics, tolerance and flavor substances were detected. [Results] Isolation, screening, and physiological identification yielded 120 colonies of round, convex bacteria, which appeared rod-shaped or spherical under the microscope and were all Gram-positive strains. Further 15 strains with high acid production capacity were obtained by acid production capacity test. By molecular sequencing, 1 strain was identified as Bacillus, 13 strains as Lactobacillus plantarum and 1 strain as Pediococcus pentosus. Among them, L. plantarum was the dominant lactic acid fermentation strain screened in Sichuan, Chongqing, Liaoning, Guizhou, Hunan and Nanping of Hubei province, and Bacillus and P. pentosus were screened in Tuanbao area of northern Hubei Province. The growth characteristics of different types of fermentation strains were analyzed, and the growth rate of strains LA-8 and LA-11 was faster than other strains; Strain LA-8 had the highest acid production capacity, and was resistant to 10% salt and 15% sucrose. All four strains had the ability to degrade nitrite. Strains LA-4 and LA-6 were able to produce 15% sucrose, and their growth rate and acid-producing capacity were slightly lower than that of L. plantarum. The initial experiment of radish fermentation showed that LA-8 and LA-11 had stronger fermentation ability and faster acid production. The electronic nose detection technology was used to detect the fermentation flavor of radish, and it was found that the volatile substances produced by four strains of different types of lactic acid bacteria were different. [Conclusion] Three different types of dominant fermentation strains were screened from the mother water of radish laotan pickle in different regions, which could be further used as the source of strains for the production of radish pickle industry.

Halimeda is a genus of calcified alga that inhabits tropical aquatic environments. The presences of Halimeda is essential for waters around mining sites, such as the waters of Maba District, wich is the center of mining in East Halmahera. As a calcareous organism, Halimeda functions as a buffer to neutralize the pH of waters. Although the presence of Halimeda in waters is not rare, studies on Halimeda taxonomy in Indonesia are very limited. Identification of Halimeda species can be done by looking at morphological and anatomical structures as an alternative based on the key to determining Halimeda species in the Indo-Pacific by Hillis & Collinvaux (1980), in addition to looking at DNA sequences. This study was aimed at identifying Halimeda species distributed in the waters of Maba District, East Halmahera based on morphological and anatomical characteristic. Besides, it also aims to determine the distribution and similarity of species between sampling locations. Sampling was carried out using purposive sampling method. Halimeda sample collection was prepared before identification. Eight species of Halimeda were found from four sampling sites, namely Halimeda cylindracea, H. distorta, H. macroloba, H. opuntia, H. simulans, H. discoidea, H. melanesica, and H. tuna. In additional to these eight species, seven unidentified Halimeda species were also found based on morphological and anatomical characteristc. Most similarity percentage of Halimeda species was found between Tanjung Buli-Monoropo at 75% and the lowest between Gee Island-Pakal Island (0%). The distribution of Halimeda species in waters in influenced by many factors, including substrate type, nutrients, light intensity, salinity, pH, temperature, depth, wave and current action.

To achieve rapid and accurate identification of valuable wood products, an analytical method was developed by combining electric soldering iron cauterization with soft ionization by chemical reaction in transfer-mass spectrometry (SICRIT-MS). SICRIT is a flow-through dielectric barrier discharge ionization technique pioneered by Zenobi et al. in 2016. The electric soldering iron cauterization-SICRIT-MS method requires no sample pretreatment, easy operation and a single analysis in less than 5 s, meeting the demands of rapid analysis. Operating parameters for the soldering iron and SICRIT ion source were optimized to achieve maximum total ion current intensity under soldering iron temperature of 450 ℃, ion source AC voltage amplitude of 2 000 V, and sample transfer line temperature of 150 ℃. With the optimized parameters, the SICRIT-MS method was applied to analyze valuable wood samples, including 29 certified standard wood samples and 6 online-purchased real samples, resulting in a dataset of 210 sets of mass spectral fingerprint data. Based on the mass spectral fingerprint data acquired under positive ion mode, a predictive model was trained using the random forest algorithm. The random forest model underwent optimization for the number of decision trees, max feature algorithm, and feature selection criteria, was evaluated through out-of-bag and 10-fold cross-validation. The results showed the error rates of out-of-bag and 10-fold cross-validation are 4.76% and 4.74%, respectively. The established random forest model can accurately distinguish wood samples from the genera Dalbergia, Guibourtia, and Pterocarpus with a classification accuracy of larger than 95%. The importance of features in distinguishing the three wood genera was investigated through binary classification modeling, revealing features 269.1, 270.1, 255.1, 159.0, 182.1, 102.1 and 83.1 as crucial in classification. These features may correspond to characteristic compounds in different wood species or differences in the content of the same compound across species. The predictive model was successfully applied to rapid identification of genera in valuable wood products sold online. Three purchased Guibourtia samples are confirmed as authentic, while the other three are not identified as the claimed genera. This method provides a scientific basis and experimental reference for authenticity identification and quality evaluation.

During the survey of open tomato fields in Vojvodina (Serbia), characteristic anthracnose disease symptoms, including black, circular, sunken, and watery lesions, were observed in about 20% of fruits in September 2018. Subsequent pathogen isolations formed white aerial mycelia and numerous spherical, black conidiomata on the Potato Dextrose Agar. Ten representative isolates produced hyaline, smooth-walled, cylindrical, and aseptate conidia. The presence of initially brownish necrotic lesions on the tomato, which later expanded into large rotted areas, ultimately leading to complete fruit rot, confirmed the pathogenicity of the tested isolates. Molecular identification was performed using Bayesian analysis of concatenated ITS, TUB2, CHS-1, and ACT loci. Based on the combination of the morphological and molecular features, the fungus Colletotrichum nigrum was identified as the causal pathogen. As this is the first report on this fungal pathogen on tomatoes in Serbia, it highlights the importance of early and accurate detection for effective disease prevention, thus reducing crop damage and market losses.

Abstract Background Delirium is a common disorder affecting patients’ psychiatric illness, characterized by a high rate of underdiagnosis, misdiagnosis, and high risks. However, previous studies frequently excluded patients with psychiatric illness, leading to limited knowledge about risk factors and optimal assessment tools for delirium in psychiatric settings. Objectives The scoping review was carried out to (1) identify the risk factors associated with delirium in patients with psychiatric illness; (2) synthesize the performance of assessment tools for detecting delirium in patients with psychiatric illness in psychiatric settings. Design Scoping review. Data sources PubMed, Web of Science, and Embase were searched to identify primary studies on delirium in psychiatric settings from inception to Dec 2023 inclusive. Two independent reviewers screened eligible studies against inclusion criteria. A narrative synthesis of the included studies was conducted. Results A final set of 36 articles meeting the inclusion criteria, two main themes were extracted: risk factors associated with delirium in patients with psychiatric illness and assessment tools for detecting delirium in psychiatric settings. The risk factors associated with delirium primarily included advanced age, physical comorbid, types of psychiatric illness, antipsychotics, anticholinergic drug, Electroconvulsive therapy, and the combination of lithium and Electroconvulsive therapy. Delirium Rating Scale-Revised-98, Memorial Delirium Assessment Scale, and Delirium Diagnostic Tool-Provisional might be valuable for delirium assessment in patients with psychiatric illness in psychiatric settings. Conclusions Delirium diagnosis in psychiatric settings is complex due to the overlapping clinical manifestations between psychiatric illness and delirium, as well as their potential co-occurrence. It is imperative to understand the risk factors and assessment methods related to delirium in this population to address diagnostic delays, establish effective prevention and screening strategies. Future research should focus on designing, implementing, and evaluating interventions that target modifiable risk factors, to prevent and manage delirium in patients with psychiatric illness.

At present, the issue of obtaining a complex of biologically active substances with antioxidant activity from psychrophilic Psychrophilic microalgae and cyanobacteria are a prospective source of biologically active antioxidant substances. New antioxidant complexes could expand the scope of their industrial application. The research objective was to identify psychrophilic microalgae and cyanobacteria from the Baltic Sea in order to study their antioxidant properties. The research featured psychrophilic microalgae and cyanobacteria obtained from the Curonian Lagoon and the Baltic Bay in the Baltic Sea, Kaliningrad Region, Russia, in March – May 2022. The authors used the Pasteur method and the flow cytometry method to isolate pure cultures of psychrophilic microalgae and cyanobacteria. The method of spectrophotometry made it possible to study the antioxidant activity by analyzing radical scavenging, reducing ability, and chelating. The psychrophilic microalga Skeletonema pseudocostatum demonstrated the highest antioxidant activity in all three methods: 17.62 μmol/g trolox equivalents according to the ABTS method, 58.16 μmol/g trolox equivalents according to the DPPH method, and 3.91 μmol/g trolox equivalents according to the FRAP method. The psychrophilic microalga Thalassiosira pseudonana exhibited the following values of antioxidant activity: 12.08, 12.42, and 3.13 μmol/g trolox equivalents, respectively. The antioxidant activity of the psychrophilic microalgae Fragilariopsis kerguelensis was 13.53, 11.84, and 1.09 μmol/g trolox equivalents, respectively. The antioxidant activity of the psychrophilic cyanobacterium Aphanizomenon gracile was 15.73, 19.89, and 2.47 μmol/g trolox equivalents, respectively. The antioxidant activity of the psychrophilic cyanobacterium Anabaena cylindrica was 12.62, 13.16, and 2.16 μmol/g trolox equivalents, respectively. The samples of psychrophilic microalgae and cyanobacteria obtained from natural environment in the Russian Baltic Sea demonstrated good antioxidant properties, which makes them a potential raw material for new pharmaceutical substances.

Abstract Aims Vitiligo is a chronic dermatological condition characterized by the progressive loss of melanocytes, for which traditional therapy has shown limited efficacy. This study aimed to establish a vitiligo model with easy operability, high repeatability, and stable depigmentation to provide a foundation for studying the pathogenesis and developing novel therapies for vitiligo. Methods (1) Establishing vitiligo model: Firstly, deliver B16F10 cells to the back skin of C57BL/6 J via intradermal injection (day 0), and the CD4 depletion antibody was injected intraperitoneally on day 4 and 10. Secondly, the melanoma was surgically removed on day 12. Thirdly, CD8 antibody was administered intraperitoneally every fourth day till day 30. (2) Identification of vitiligo model: H&E staining, immunohistochemistry, and immunofluorescence were used to detect the melanocytes. The melanin was detected by transmission electron microscopy (TEM), Lillie ferrous sulfate staining and L-DOPA staining. Results (1) The back skin and hair began to appear white on day 30. Melanin loss reached peak on day 60; (2) Hematoxylin and eosin (H&E) staining, immunohistochemistry and immunofluorescence results showed melanocytes were reduced. L-DOPA staining, Lillie ferrous sulfate staining and TEM results showed that melanin decreased in the epidermis. Conclusion We successfully establishment a vitiligo mouse model which can be more capable to simulate the pathogenesis of human vitiligo and provide an important basis for the study of pathogenesis and therapy of vitiligo.