Diet-related diseases impact populations across the globe. While intertemporal preferences—a fundamental preference for the distribution of benefits across time—have been used to explain low-quality food choices, recent literature proposes another cause: inattention to future implications (or opportunity costs) of the options faced. Food choices tend to become habitual to conserve cognitive resources, rather than carefully modeling future health impacts. Both low discount rates for future benefits and attention to future health impacts predict healthier decisions. While intertemporal preferences are stable, attention may provide an opportunity to intervene in the decision process to promote healthier decisions. In this study, we test the impact of a simple message that highlights health during food choice on the healthiness of foods chosen and on health consideration and intertemporal preferences. Our results show that actively considering health outcomes and lower discount rates lead to healthier food choices. We find that messaging increases the consideration of health outcomes during food choice but does not affect intertemporal preferences, suggesting that simple prompts may be an effective way to promote decisions balancing short and long-term benefits by drawing attention to overlooked opportunity costs of choices.

This paper proposed emotion recognition methods for consecutive facial images, and implements the inference of neural network model on a field-programmable gate array (FPGA). The proposed emotion recognition methods are based on a neural network model architecture that combines convolution neural networks (CNNs), long short-term memory (LSTM), and fully connected neural networks (FCNNs), called CLDNN or ConvLSTM-FCN. This type of neural network mod-el can analyze the local feature sequences obtained through convolution of data, making it suita-ble for processing time-series data such as consecutive facial images. In this paper, sequences of facial images are sampled from videos corresponding to various emotional state of subjects. The sampled images are then pre-processed with the processes includes facial detection, greyscale conversion, resize, and data augmentation if necessary. The 2-D CNN in ConvLSTM-FCN is used for feature extraction for these pre-processed facial images. These sequences of facial im-age features are time sequences with dependent properties between the elements within them. The LSTM is then used to model these time sequences followed by fully connected neural net-works (FCNNs) for classification. The proposed consecutive facial emotion recognition method achieves an average recognition rate of 99.51% on RAVDESS dataset, 87.80% on BAUM-1s dataset and 96.82% on eNTERFACE’05 data set, using 10-fold cross-validation on the PC. Some com-parisons of recognition accuracies between the proposed method and the other existing related works are conducted in this paper. According to the comparisons, the proposed emotion recog-nition methods outperform the existing related researches. The proposed emotion recognition methods are then implemented on an FPGA chip using the neural network model inference algo-rithms in this paper, and the accuracies of the experiments conducted on the FPGA chip are iden-tical to those obtained on the PC. This verifies that the proposed neural network model imple-mented on the FPGA chip performs well.

For the first time, the effect of a significant change in the resistance of the aquatic environment of a population of protozoan microorganisms under the influence of radiofrequency electromagnetic radiation from cell phones has been experimentally studied. The results of the experiment demonstrate the biological nature of the changes occurring in the “water population of protozoa” system, which indicates that the impact of radiation directly affects the cell. This conclusion is confirmed by the same order of magnitude time of information exchange between individual individuals of the population in the calculation and in the experiment. An extremely low concentration of protozoa in the experiment was established, equal to 1000 pcs./liter, at which the indicated effect is observed.An unambiguous dependence of the biological effect in the “water – amoeba population” system on the average power of electromagnetic radiation of cell phones, both in standby mode and in talk mode, has been established. It is concluded that the presented method of changing the physical properties of the aquatic environment of a population of protozoa under the influence of electromagnetic fields can be a model experiment in identifying the mechanisms of interaction of biological systems with electromagnetic radiation, determining the response time of biological systems to external electromagnetic influence, and establishing the degree of influence of radiation in the 4G, 5G ranges.

Polycystic Ovary Syndrome (PCOS) is the most common endocrine disorder that affects women of reproductive age representing the primary cause of anovulatory infertility. The nonapeptide oxytocin (OT) plays an important role in cognitive, emotional, and reproductive functions in human beings. Oxytocin receptors are expressed in several body parts including the ovaries. Despite this, the possible role played by oxytocin in symptoms of PCOS is not clear. The present systematic review aimed at understanding, the presence of possible oxytocin level alterations in PCOS, the connection between alterations of OT levels and the symptoms of PCOS, and the effect of oxytocin administration in PCOS. After a systematic search in the principal databases, seven studies, five human and two animal, were included. Most of the studies highlighted the role played by oxytocin in fertility issues related to PCOS. Studies that analyzed oxytocin basal levels in PCOS women agreed that PCOS is associated with a reduction in the serum level of oxytocin. Two studies found that in PCOS the serum levels of oxytocin were lower than healthy controls. One human and one animal study agreed about lower levels of PCOS, confirming a possible implication of a dysfunction of OT, in the pathogenesis of PCOS.

Today's city needs more than ever methodological devices that ensure a specific urbanism, in keeping with the complexity of relationships that occur in the urban space. Networks or systems of diverse nature must be activated to achieve a certain success of the city, even more so in its fragile central fabrics. The study is focused on the historic neighborhoods of the city of Jaén (Spain), which have a high vulnerability index. The aim is to establish a strategy to revitalize their urban and social capital and improve their articulation with the rest of the urban and territorial structure. A methodological proposal for the analysis of vulnerability factors and an urban and cartographic analysis of the public space is addressed through an interweaving of a triple network: environmental, social, and urban. For this purpose, the configuration of this overlapping network of analysis and formulation of criteria is presented, which considers the urban multiplicity and promotes new dynamics for the integrated urban regeneration of the area and for the activation of public and collective urban spaces.

Vaccines decrease morbidity and mortality. Nevertheless, their benefits depend on public response. During COVID-19, vaccine hesitancy and refusal were rampant, threatening public health. A thorough understand-ing of opponents' arguments is required to address the diffusion of unreliable information on social media and prevent vaccine hesitancy from developing into vaccine refusal. Accordingly, the article examines vac-cine opponents' justifications on social media. Textual content analysis of reader comments on three health-related Israeli Facebook pages was conducted. Data collection encompassed the Israeli COVID-19 vaccination period from October 2020 to May 2022. The comments were analyzed according to the health beliefs model (HBM). We found that vaccine opponents were characterized by low perceptions of the severity of the disease combined with high perceptions of the damages of the vaccine; low perceived benefits of vac-cine compliance; vaccine hesitancy and fear along with public distrust as barriers to change; and call for ac-tion to resist the vaccine and spread related anti-establishment views on the web. As vaccination hesitancy was found to develop into public distrust in the state systems and escalate into conspiracy beliefs and an-ti-vaccination activism, its early detection may prevent future vaccine resistance.

The main inhibitory neurotransmitter in the mammalian brain is 4-aminobutyric acid (GABA). Phthalimide acts as a sodium channel antagonist, one of the finest targets for treating epilepsy is the sodium channel and JNK kinase activity is inhibited to treat epilepsy. a novel compound with multiple targets of action for the treatment of epilepsy also anti-oxidant activity has been designed. The compounds are designed in two series aldehydes and aniline. Docking of all the designed compounds has been done with the suitable protein GABA-AT, sodium channel, JNK protein, and anti-oxidant from protein bank. QSAR was done for constructing many linear regression models. In combination with the developed Docking and QSAR outcomes, ADMET has been performed for the active compounds. The result shows that 11 of the compounds have excellent binding energy in docking with all the receptors and also have good QSAR results and follow the ADMET. The structural understanding of human GABA-AT inhibition was obtained from molecular dynamics simulation studies for compound no. 11 at 5 nanoseconds. Synthesis and pharmacological activity also suggest that the designed compound no.11 be considered the best Novel Compound.

Continuous technological progress places significant demands on the materials used in increasingly modern devices. An important parameter is often the long-term thermal resistance of the material. The use of heat-resistant polymer materials worked well in technologically advanced products. An economically justified direction in searching for new materials is the area of polymer nanocomposite materials. It is necessary to appropriately select both the polymer matrix and the nanofillers best able to demonstrate the synergistic effect. A promising area of exploration for such nanocomposites is the use of organosilicon polymers, which results from the unique properties of these polymers related to their structure. This review presents the results of the analysis of the most important literature reports regarding organosilicon polymer nanocomposites with increased thermal resistance. Particular attention was paid to modification methods of silicone nanocomposites focused on the increase of their thermal resistance related to the modification of siloxane molecular structure and by making nanocomposites using inorganic additives, carbon nanomaterials. Attention was also paid to such important issues as the influence of the dispersion of additives in the polymer matrix on the thermal resistance of silicone nanocomposites and the possibility of modifying the polymer matrix and permanently introducing nanofillers thanks to the presence of various reactive groups. The thermal stability mechanism of these nanocomposites was also analysed.

As matrix representations of magic labelings of related hypergraphs, magic squares and their various variants have been applied to many domains. Among various subclasses, trimagic squares have been investigated for over a hundred years. The existence problem for trimagic squares with singly even orders and orders 16n has been solved completely. However, very little is known for the existence of trimagic squares with other even orders except for the only three examples and three families. We construct normal trimagic squares by using product constructions, row-square magic rectangles, and trimagic pairs of orthogonal diagonal Latin squares. We give a new product construction: For positive integers p, q, and r having the same parity other than 1, 2, 3, 6, if normal p × q and r × q row-square magic rectangles exist, then a normal trimagic square with order pqr exists. As its application, we construct normal trimagic squares of orders 8q^3 and 8pqr for all odd integers q not less than 7 and p,r ∈ {7, 11, 13, 17, 19, 23, 29, 31, 37}. Our construction can easily be extended to construct multimagic squares.

Silencing of the fragile X mental retardation 1 (FMR1) gene and consequently lack of synthesis of FMR protein (FMRP) are associated with fragile X syndrome, which is one of the most prevalent inherited intellectual disabilities. FMRP is a multifunctional protein involved in many cellular functions in nearly all subcellular compartments under normal conditions and under conditions of cellular stress in both neuronal and non-neuronal cell types. This is achieved through its trafficking signals, nuclear localization signal (NLS), nuclear export signal (NES), and nucleolar localization signal (NoLS), as well as its RNA and protein binding domains, and is modulated by various post-translational modifications such as phosphorylation, ubiquitination, sumoylation, and methylation. This review summarizes recent advances in understanding the interaction networks of FMRP with a special focus on FMRP stress-related functions, including stress granule formation, mitochondrion and endoplasmic reticulum plasticity, ribosome biogenesis, cell cycle control, and DNA damage response.

Over the years, the need for autonomous systems such as drones, also known as unmanned aerial vehicles (UAVs), has significantly increased in popularity across several industries, including the military. The Internet of Battlefield Things (IoBT) represents a modern technological advancement that significantly enhances the operational efficacy of defense systems. It establishes an integrated military force by connecting individuals to intelligent technology in drones, radios, equipment, antennas and ground stations. This is achieved through the utilization of cloud and edge computing, sensors, mobile devices, embedded systems, and IoT-based systems. However, IoBT security is significantly compromised by enemies that exploit the vulnerabilities and malicious intrusions that specifically target the external environment or to obtain sensitive data. In addition, a comprehensive understanding of cyberattacks and countermeasures is essential for assuring the security of IoBT. On the other hand, as cyber threats get more complicated, trust becomes increasingly important for the security of digital systems. Within this context, the zero trust architecture contends that the security of a complex network is inherently vulnerable to internal and external threats. In defense, UAV security system applications, for example, the primary purpose of the zero trust architecture is to limit the vulnerability of military UAV systems to cyberattacks, hence reducing the possibility of data breaches and illegal entry. This study conducts a systematic review aimed at identifying different aspects of cybersecurity strategies for protecting UAV systems within the IoBT domain. Furthermore, zero trust architecture is presented in the study as an effective prospective solution to the security issues that develop in defense UAV systems.

This paper presents an innovative multi-agent, data-driven reinforcement learning (RL) approach to develop and utilize the thermal equivalent network model that represents the motor's thermal dynamics. A multi-agent reinforcement learning is designed and trained to adjust the model parameters using data from several motor driving cycles. To ensure the incoming driving cycle matches the historical data before employing the pre-trained RL agents, offline statistical analysis and clustering techniques are developed and used. Numerical simulations highlighted the RL agent's ability to develop strategies that effectively address the variability of driving cycles. The proposed RL framework showed its capability to accurately reflect the motor's thermal behavior under various driving conditions.

The wealth of data obtained during the past 20 years using Laser-Induced Breakdown Spectroscopy (LIBS) indicates that the technique is very promising to detect small chemical contents of alloying elements. The potential of LIBS was looked more seriously during the past two decades or so as more data were obtained on Aluminum and steel to study the phenomena in the condition of local thermodynamic equilibrium and time-delay between a Q-switch laser and an intensified CCD camera. Since the past decade, some data on compounds were also shown to be useful in determining small concentrations of harmful elements. This manuscript is intended to show that the technique of LIBS performance is very promising in fields such as micro-machining, in alloying element analysis, surface cleaning and environmental applications even with lightweight spectrometers having a relatively low resolution, which can potentially be air-borne.

As Artificial Intelligence (AI) technology, particularly Machine Learning algorithms, becomes increasingly ubiquitous, our abilities to understand and interpret AI and machine learning algorithms are becoming increasingly desirable. Visualization has been used as a common tool to view and understand complex machine learning processes. In this paper, we will focus on developing a general framework for the visualization of machine learning models as a scalar valued multi-dimensional function to help users understand how the models behave over different viewing spaces. We first give a formal definition of the visualization problem. Interpolation-based morphing and subspace sampling techniques are applied to generate various renderings through projections and cross-sections of the model space as 3D surfaces or heatmap images. This method will be applied to two real-world datasets and applications: the diagnosis of Alzheimer's Disease (AD) using a human brain networks dataset and a real-world benchmark dataset for predicting home credit default risks. The visualizations show that different machine learning algorithms can behave quite differently under different conditions.

The study investigated the usage of open data in public organizations, focusing on the motives, preferences, and governance ideals that determine their quality. The study shed light on how open data platforms are created and improved, as well as their influence on government operations. The primary goal was to understand the motivations behind the usage of open data, evaluate gov-ernance ideals, and examine institutions' efforts to standardize data formats. Hierarchical regres-sion analysis divides variables into core reasons and different preferences, demonstrating a need for "diversification" in order to use open data effectively. Efficiency, accountability, community impact, knowledge, and high-quality service delivery are all emphasized in governance value analysis. The institution's dedication to standardizing open data formats is evidenced by legislative measures and the integration of many technologies. The findings illustrate the institution's dual strategy of em-ploying traditional techniques and new technologies for effective data management. The report suggests increasing data openness and standardization, investing in ongoing training, upgrading alerting and awareness systems, and adopting specific regulations for open data use. Monitoring and feedback techniques are critical for adjusting and refining open data services to satisfy de-velopment needs. This study adds to the scientific knowledge of open data use by highlighting important motives, preferences, and governance ideals. The offered guidelines provide practical insights for public organizations looking to improve their open data platforms by promoting openness, efficiency, and community participation.

Monitoring of clients living with HIV encompasses a specific array of activities that routinely check on various aspects of ART following its initiation depending on the availability of resources in that particular state, among other factors as per guidelines from the World Health Organisation. This is a significant practice as it promotes positive health outcomes for patients and efficient utilisation of ART regimens to reduce resistance to the medication – hence it is a measure to guard avoidable costs. It also forms a basis on which decisions are made from. It can be done clinically by assessing for signs e.g., skin rash and symptoms e.g., nausea and vomiting, checking vital organ function and measuring weights across all populations, or can be also be done by assessing specimens for their respective viral loads, white blood cell count, pregnancy status or other infections such as hepatitis B. There have not been any special indications required for one to be eligible for monitoring during ART in developing countries; all qualify for routine monitoring even though some may be more frequent than others in cases of comorbidities such as renal failure where medications can be attributed to exacerbating the condition.

Underwater Sensor Networks (UWSNs) can enable a broad range of applications such as resource monitoring, disaster prevention, and navigation-assisted. It is especially relevant for sensor nodes location in UWSNs. Global Positioning System (GPS) is not suitable for using in UWSNs because of the underwater propagation problems. Hence some localization algorithms based on the precise time synchronization between sensor nodes have been proposed which are not feasible for UWSNs. In this paper, we propose a localization algorithm called Two-Phase Time Synchronization-Free Localization Algorithm (TP-TSFLA). TP-TSFLA contains two phases, namely, range-based estimation phase and range-free evaluation phase. In the first phase, we address a time synchronization-free localization scheme base on the Particle Swarm Optimization (PSO) algorithm to decrease the localization error. In the second phase, we propose a Circle-based Range-Free Localization Algorithm (CRFLA) to locate the unlocalized sensor nodes which cannot obtain the location information through the first phase. In the second phase, sensor nodes which are localized in the first phase act as the new anchor nodes to help realize localization. Hence in this algorithm, we use a small number of mobile beacons to help achieve location without any other anchor nodes. Besides, to improve the precision of the range-free method, an extension of CRFLA by designing a coordinate adjustment scheme is updated. The simulation results show that TP-TSFLA can achieve a relative high localization ratio without time synchronization.

Subnational governments play a key role responding to climate change risks in terms of policy strategies and instruments. This article analyzes how Brazilian municipal and state governments have developed and implemented public policies to mitigate and to adapt to climate change risks. We surveyed all cities’ and states’ climate policies within the country. The methodological approach includes five main points of analysis: 1. mitigation targets and intentions; 2. adaptation actions; 3. stakeholders’ participation; 4. policy implementation; 5. participation in networks related to climate change. Our results suggest that even though subnational climate policies in Brazil are isolated initiatives within the national context, they play an important role responding to climate change risks in different scales and levels. The strongest Brazilian policies with both mitigation and adaptation actions counted on previous mobilization for the climate issue involving different stakeholders from several segments of the society. These governments have also participated in transnational cooperation networks related to climate change.

Background and Objectives: Multiple primary malignant tumors represent a small percentage of the total number of oncological cases and can involve either metachronous or synchronous development and represent challenges in diagnosis, staging, and treatment planning. Our purpose is to present a rare case of bladder adenocarcinoma in a female patient with multiple primary malignant tumors and to provide systematic review of the available literature. Materials and Methods:A 67-year-old female patient who was admitted altered general condition, and anuria. The past medical history of the patient included malignant melanoma (2014), cervical cancer (2017), colon cancer (2021), obstructive anuria (2023), liver metastasectomy (2023). Transurethral resection of bladder tumor was performed for bladder tumors. Results: Contrast CT highlighted multiple pulmonary metastases, a poly nodular liver con-glomerate, retroperitoneal lymph node, II/III grade left ureterohydronephrosis, and no digestive tract tumor masses. The pathological result of the bladder resection showed an infiltrative adenocarcinoma. Conclusions: The difference between primary bladder adenocarcinoma tumor and metastatic colorectal adenocarcinoma is the key for the future therapeutic strategy. Identification and assessment of risk factors such as viral infection, radiotherapy, chemotherapy, smoking, genetics are pivotal in understanding and managing multiple primary malignant tumors. Personalized prevention strategies, screening programs may facilitate the early detection of this tumors, synchronous or metachronous one. The use of multicancer early detection (MCED) blood tests for early diagnosis appears promising. However, additional research is needed to standardize these techniques for cancer detection.

Staphylococcus aureus is a gram-negative bacterium that causes superficial and deep infections that can be mild or potentially fatal. Recently, the bacterium has gained significant attention due to the increased incidence of multidrug-resistant (MDR) strains that make treatment with antibiotics dif-ficult. Owing to the MDR strains, alternative therapies such as antimicrobial photodynamic therapy (PDT) have emerged as good options to treat non-systemic infections. PDT combines a photosensi-tiser (PS) with light and oxygen to generate free radicals that destroy bacterial structures such as the plasma membrane, matrix, and genetic material. This systematic review aimed to identify the ef-fectiveness of PDT delivered using different types of hydrogels for treating wounds, burns, and contamination by S. aureus. This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Bibliographic research was conducted using the PubMed, Web of Science, and Scopus databases. Only full articles published in English between 2013 and 2024 from any country of origin (without restrictions) were included. The research was carried out from 15 June 2023 to 15 June 2024 and did not use any automatic biblio-graphic search tool. The articles collected were identified using keywords and selected using in-clusion and exclusion criteria in accordance with the PRISMA protocol. Seven articles were in-cluded that presented a good set of evidence associated with the use of PDT against S. aureus in in vitro and in vivo studies. To conclude, PDT can effectively complement antimicrobial therapy against S. aureus, in the healing of wounds and burns. The effectiveness of this technique depends on the PS used, hydrogel type, and lesion location. Some studies have already demonstrated the ef-fectiveness of PDT but most were in vitro and a few in vivo. Further studies are required to demonstrate the safety and efficacy of PDT delivered via hydrogels in in vivo models of bacterial infection.

Background/Objectives: Infectious Endocarditis often requires surgical intervention, with postoperative acute kidney injury (AKI) posing a significant concern. This retrospective study aimed to investigate AKI incidence, its impact on short-term mortality, and identify modifiable factors in patients with endocarditis scheduled for valve surgery. Methods: This single center study enrolled 130 consecutive endocarditis patients from 2013 to 2021 undergoing valve surgery. Creatinine levels were monitored pre- and postoperatively, and AKI was defined by Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Patient demographics, comorbidities, procedural details, and complications were recorded. Primary outcomes included AKI incidence, the relevance of creatinine levels for AKI detection, and the association of AKI with 30-, 60- and 180-day mortality. Modifiable factors contributing to AKI were explored as secondary outcomes. Results: Postoperatively, 35.4% developed AKI. The highest creatinine elevation occurred on the 2nd postoperative day. Best predictive value for AKI was a creatinine level of 1.35 mg/dl on the 2nd day (AUC: 0.901; sensitivity: 0.89, specificity: 0.79). Elevated creatinine levels on the 2nd day were robust predictors for short-term mortality at 30, 60 and 180 days postoperatively (AUC ranging from 0.708 to 0.789). CK-MB levels at 24 hours postoperatively and minimum hemoglobin during surgery were identified as independent predictors for AKI in logistic regression. Conclusions: This study highlights the crucial role of creatinine levels in predicting short-term mortality in surgical endocarditis patients. A specific threshold (1.35 mg/dl) provides a practical marker for risk stratification, offering insights for refining perioperative strategies and optimizing outcomes in this challenging patient population.

Drosophila melanogaster serves as a important research model both for genetic investigations and for the study of metal toxicity, facilitating the elucidation of physiological mechanisms comparable to those of human organisms. In our research, we evaluated the toxicity effect resulting from exposure to various concentrations of lead and copper on the prolificity rates throughout the life cycle (egg-adult) of four genotypes of Drosophila melanogaster: wild-type (control), white, brown, and white-vestigial. During our study, the prolificity rates were examined across three repetitions under the impact of exposure to concentrations of 0.50, 1.00, 2.00, and 4.00 mM of copper (CuSO₄) and lead (Pb(C₂H₃O₂₎₂). Prolificity rates throughout the life cycle exhibited variations as a direct consequence of genetic factors, the concentration of exposure, and the specific type of metal, either copper or lead. The mutant white-vestigial genotype revealed an IC₅₀ concentration for prolificity inhibition at lower doses of 2.00 mM for copper and 4.00 mM for lead, in contrast to the control genotype (wild-type), which exhibited an inhibition concentration rate >IC₅₀ of 4.00 mM only in the case of copper. Our results concluded that the (i) dose influences the prolificity rate in a directly proportional manner, (ii) comparative analyses between copper and lead revealed that copper displayed toxicity across all genotypes within the concentration range of 0.50 mM to 2.00 mM. In contrast, lead exhibited toxicity within the concentration range of 1.00 mM to 4.00 mM, highlighting a (iii) more acute toxicity characteristic in the case of copper. Thus, the results of this research reflect the importance of using Drosophila melanogaster as a genetic model in the comparative study of the interaction between genetic factors and the toxicity of metals, offering significant insights into monitoring their impact and defining the maximum permissible doses on organisms.

The agronomic characteristics of Cenchrus purpureus were assessed through a randomized block experimental design with seven accessions (Taiwan grass, King grass, Elephant grass, Merkeron, CT-115, Purpule grass and Maralfalfa) as treatments and four replications research was carried out at the Instituto Tecnológico Superior de Tantoyuca, in 2019 and 2020, under rainfed conditions. Sowing density was established at 36 tillers in 25 m2. Green and dry matter yield, daily rates of dry matter accumulation in leaves, leaf/stem ratio, height, leaf area index and cutting frequency were assessed. Rainfall amount, temperature, relative humidity and global radiation levels were recorded to assess their effect on the evaluated variables. One-way ANOVA and multivariate analysis techniques, such as multiple linear regression (MLR), Clustering, and Principal component analysis (PCA) with the Statistica V7 software, were used. The leaf area index was greatest (p < 0.05) on the dry season. Green and dry matter yield were greatest in Maralfalfa (p < 0.05). Variation in the results is attributed to weather phenomena; nonetheless, Elephant grass and Maralfalfa showed the highest yields. Quality parameters must be evaluated to identify those grasses with the best attributes.

A palladium-catalyzed aromatic dual C-H acylations followed with intramolecular cyclizations have been developed by the assistance of bidentate N-(quinolin-8-yl)benzamide. This tandem process involves the formation of three new chemical bonds, providing access to novel quinoline substituted hydroxyl isoindolones skeleton under simple reaction conditions. The deuterium-labeled competition reaction has revealed that C-H bond cleavage is the turnover limiting step.

In the era of information explosion in e-commerce, users face an overload problem. Recommender systems alleviate this by filtering target products based on user preferences. Collaborative Filtering (CF) is a popular method but struggles with high-quality recommendations due to data sparsity. Utilizing review texts to capture user preferences has improved CF recommendations. This paper proposes a deep learning-based recommendation framework leveraging bidirectional gated recurrent units (Bi-GRUs) and an attention-based Recurrent Neural Networks (RNN) structure. This framework addresses insufficient user rating data by utilizing user reviews to infer preferences. Experimental results on three datasets show that the proposed Bi-GRUCF model outperforms other state-of-the-art methods, achieving a 55.4% improvement in Mean Absolute Error (MAE) over traditional methods and a 77.8% improvement over other deep learning approaches. This demonstrates the framework's superior recommendation quality, particularly in sparse data scenarios.

Breast cancer is a global concern as a leading cause of death for women. Early and precise diagnosis can be vital in handling the disease efficiently. Breast cancer subtyping based on estrogen receptor (ER) status is crucial for determining prognosis and treatment. This study uses metabolomics data from plasma samples to detect metabolite biomarkers that could distinguish ER-positive from ER-negative breast cancers in a non-invasive manner. The dataset includes demographic information, ER status, and metabolite levels from 188 breast cancer patients and 73 healthy controls. Supervised, unsupervised, and ensemble machine learning (ML) algorithms were applied to identify key metabolites associated with ER status, including Support Vector Machines (SVM), Multidimensional Scaling (MS), Logistic Regression (LR), and Ensemble learning. The most informative feature set, containing 28 biomarkers and two demographic factors, achieved an impressive 96% accuracy and an area under the curve (AUC) of 93% using the Logistic Regression model. These results suggest that ML has great promise for identifying specific metabolites linked to ER expression, paving the development of a novel analytical tool that can minimize current lab challenges such as analytical sample handling, subjective results interpretation, biological heterogeneity of the tumor in a non-invasive and efficient manner aiding in more precise diagnosis of breast cancer.

Background/Objectives: Mesenchymal Stem Cells (MSCs) possess the remarkable ability to dif-ferentiate into various cell types, including osteoblasts. Understanding the molecular mecha-nisms governing MSC osteogenic differentiation is crucial for advancing clinical applications and our comprehension of complex disease processes. However, the key biological molecules regu-lating this process remain incompletely understood, necessitating further investigation. Methods: In this study, we employed high-throughput transcriptomic sequencing to identify and validate key biological molecules that dynamically regulate MSC osteogenic differentiation. Our approach involved comprehensive analysis of gene expression patterns across human tissues, followed by rigorous experimental validation of identified candidates. Results: Through our integrated analytical and experimental approach, we pinpointed four critical regulators of MSC osteogenic differentiation: PTBP1, H2AFZ, BCL6, and TTPAL (C20ORF121). Notably, this study represents the first instance of utilizing high-throughput transcriptomics to uncover regulatory factors involved in MSC osteogenesis, marking a significant advancement in the field. Conclusions: Our findings substantially enhance our understanding of the molecular mechanisms determining MSC differentiation fate. This research holds significant implications for clinical ap-plications involving MSCs and provides valuable insights into complex disease processes. The identification of these key regulators opens new avenues for targeted interventions and therapies in bone-related disorders and regenerative medicine. Furthermore, this study establishes a robust framework for future investigations in stem cell biology, potentially leading to innovative ap-proaches in regenerative medicine.

Background/Objectives: Skin cancer is becoming increasingly common due to increasing risk factors such as excessive UV radiation, genetic predisposition, fair skin, and a history of sunburn. Melanoma accounts for only 1% of cases but causes the majority of skin cancer deaths. Dysplastic nevi (DN) are important precursors of melanoma. The aim of this study was to investigate the influence of these risk factors on the pathogenesis, incidence, and stage of skin cancer.; Methods: The study included 591 patients aged 18 to 64 who visited the Clinic in 2022–2023 for skin examinations. Each patient completed a questionnaire regarding the risk factors for melanoma and atypical melanocytic nevi and then underwent a dermatoscopic examination of the whole body using a digital videodermatoscope. Statistical analysis of the collected data was performed.; Results: Dermatoscopic examination revealed a lesion suggestive of melanoma in 1,69% of the patients. Risk factors for developing melanoma included male gender, family history of melanoma, number of skin moles, sunburns in childhood, sun-dependent hobby, using tanning bed, using cream with low SPF, not avoiding sun exposure and co-occurrence of actinic keratosis.; Conclusions: Risk factors for melanoma and dysplastic nevi are still common among patients, but the situation has been improving over the years. Early intervention and education on sun safety can play pivotal roles in reducing the incidence of atypical moles and potentially preventing malignant transformations. Keywords: dysplastic nevum; melanoma; risk factors; dermoscopy; prevention

The development of pre-hierarchical follicle (PHF), especially small yellow follicles (SYFs), directly affects the recruitment of dominant follicles and thus affects the egg-laying performance of chickens. However, the development of PHF, especially the development of SYF, and its regulatory mechanism remain unclear. Therefore, we performed transcriptomic and metabolomic analyses of large white follicles (LWFs) and SYFs in chickens. Transcriptome sequencing revealed 258 differentially expressed genes (DEGs) between SYF and LWF, of which 172 were upregulated and 86 were downregulated. The DEGs were mapped to 17 KEGG pathways, mainly the gap junction, calcium signaling, and neuroactive ligand-receptor interaction pathways. The results of the metabolome analysis revealed 129 significant differential metabolites (DMs), including 36 upregulated DMs and 93 downregulated DMs. The DMs were mapped to 9 KEGG pathways for follicle tissue, which included mainly glutathione metabolism, alpha-linolenic acid metabolism, and tryptophan metabolism, etc. The combined transcriptional and metabolic analysis revealed significantly enriched pathways, and four metabolically related pathways, including glutathione metabolism, alpha-linolenic acid metabolism, linoleic acid metabolism, and pyrimidine metabolism, were identified. Glutathione metabolism is a critical signaling pathway that may affect ovarian follicle development to regulate the SYF reserve process in chickens. These results can act as a reference for improving the egg-laying performance of Tengchong snow chickens.

Subtilisin-like proteins are serine proteases that use two types of catalytic triads: Ser-His-Asp and Ser-Glu-Asp. Here, we investigate the two known families of subtilisin-like proteins, the subtilases (Ser-His-Asp triad) and the serine-carboxyl proteinases (Ser-Glu-Asp triad), and describe local structural arrangements (cores) that govern the catalytic residues in these proteins. We show separation of the cores into conserved structural zones, which can be repeatedly found in different structures, and compare the structural cores in subtilisin-like proteins with those in trypsin-like serine proteases and alpha/beta-hydrolases.

Water is the most important source of life. However, due to various anthropogenic activities, water is no longer pure and drinkable. Pakistan is a country that is facing an acute shortage of safe water, and safe water drinking resources in Sindh, which is the second largest province of Pakistan, are depleting day by day. Therefore, a research study was carried out to determine the Physico- Biological properties of groundwater of Larkana city of Sindh province of Pakistan, where groundwater is the only source of drinking. For this purpose, a total of 40 samples were randomly collected from various locations in Larkana city, and the Physico-Biological parameters like Color, Odor, Taste, Turbidity, Total Solids (TS), Electrical Conductivity (EC), and Fecal Coliform and E-Coli were determined in the laboratory and were compared with WHO permissible limits. The results revealed that all of the samples were colorless with no turbidity, but 20% of the samples had having odor of sewage water. Moreover, 20% of samples had having slightly bitter taste, particularly the samples collected from Ahsan Colony, Sachal Colony, and QUEST hostel. Moreover, 92% of samples had values of Total Solids and EC beyond permissible limits. Further, most of the samples were found to have no presence of E. coli, but 8% of samples were found to have faecal Coliform present.

Metabolic syndrome, obesity, and type 2 diabetes are closely related. They are characterized by chronic inflammation and oxidative stress. Obesity is the most important risk factor for metabolic syndrome and type 2 diabetes. Metabolic syndrome is characterized by insulin resistance and elevated blood glucose levels, among other conditions. These disorders contribute to the development of type 2 diabetes, which can exacerbate other metabolic disorders. Numerous studies indicate that diet and nutrients can have a major impact on preventing and treating these conditions. One such ingredient is lycopene. It exhibits antioxidant and anti-inflammatory effects and can affect metabolic processes in the body. According to the research presented, lycopene supplementation may have significant potential in the prevention and treatment of metabolic syndrome, obesity, and type 2 diabetes.

Despite nearly a century of research on water related issues, water erosion remains one of the greatest threats to soil health and soil ecosystem services around the world. Yet to date, data on water erosion needed to develop mitigation strategies is scarce, especially in the Sahelian regions. The current study therefore sets out to estimate annual soil losses caused by water erosion and to analyze trends over the period of 1981-2020 in the Mékrou watershed, located in the Middle Niger river sub-basin in West Africa. The revised universal soil loss equation, remote sensing and the Geographic Information System (GIS) were deployed in this study. Several types of data were used, including rainfall, soil conditions, topography and satellite images. The estimated average annual amount of water erosion in the Mékrou watershed is 6.49 t/ha/yr over 1981-2020. The dynamics of the ten-year average are highly variable, with a minimum of 3.45 t/ha/yr between 1981 and 1990, and a maximum of 8.50 t/ha/yr between 1991 and 2000. Even though these average soil losses in the Mékrou basin are below the tolerable threshold of 10 t/ha/yr, mitigation actions are needed for prevention. In addition, the spatial dynamics of water erosion are noticeably heterogeneous. The study reveals that 72.7% of the surface area of the Mékrou watershed is subject to slight water erosion below the threshold, compared with 27.3%, particularly in the mountainous south-western part, which is subject to intense erosion above the threshold.

A novel method has been developed based on the amplitude data of the EM waves measured by Digisondes to calculate and investigate the relative ionospheric absorption changes. The effect of 13 solar flares (> C4.8) that occurred between 06:00 and 16:30 UT from 04 to 10 September 2017 have been studied at three European Digisonde stations (Juliusruh (54.63° N, 13.37° E), Průhonice (49.98° N, 14.55° E) and San Vito (40.6° N, 17.8° E)). Present study compares the results of the amplitude method with the absorption changes measured by the Finnish Riometer Network and determined by the NOAA D-RAP model during the same events. The X-class flares caused 1.5–2.5 dB attenuation at 30–32.5 MHz based on riometer data, while the absorption changes were between 10 and 15 dB in the 2.5–4.5 MHz frequency range according to the amplitude data. The impact caused by the energetic particles after the solar flares are clearly seen in the riometer data, while it can be observed only at Juliusruh (~55°) at some certain cases among the Digisonde stations. Comparing the results of the amplitude method with the D-RAP model it seems evident that the observed values exceed the values given by the model both at 2.5 MHz and at 4 MHz almost always during the investigated period. According to the comparison between the riometer data with the D-RAP, the model underestimates the values obtained from the riometers during the X-class solar flares, while it overestimates the caused impact during the particle events.

The purpose of this study is to evaluate the amounts of apically extruded 3% sodium hypochlorite using two modes of Er:YAG laser-activated irrigation (LAI), super short pulse (SSP) and shock wave enhanced emission photoacoustic streaming (SWEEPS®), combining three types of laser tips (FT) and conventional syringe needle irrigation (SNI). Methods: Twenty extracted human maxillary central incisors prepared using Reciproc® instruments (size 40, taper 0.06). Irrigant volumetric flow (IVF) was accurately standardized using a precision syringe pump with constant irrigant delivery through the 27G needle. The tested irrigation protocols (60 s) were groups 1: 27-G SNI with 0.05 ml/s constant IVF; group 2: SSP (10 mJ, 15 Hz, pulse duration 50 μs) + Radial SWEEPS FT; group 3: SSP + photon-induced photoacoustic streaming (PIPS) FT; group 4: SSP+SWEEPS FT; group 5: AutoSWEEPS (20 mJ, 15 Hz, pulse duration 25 µs) + Radial SWEEPS FT; group 6: AutoSWEEPS+PIPS FT; group 7: AutoSWEEPS+SWEEPS FT. Each protocol was evaluated in 10 repetitions each. Apically extruded irrigant was collected, and the net weighted. Results: There were significantly lower amounts of extruded irrigant with SNI and SSP using radial SWEEPS and PIPS FTs compared to the other tested laser protocols (p<0.05). In the AutoSWEEPS groups, all three FTs had similar amounts of extruded irrigant (p>0.05). Conclusion: In straight root canals, the use of various fiber FTs in the AutoSWEEPS mode exhibited a higher potential for irrigant extrusion.

Hands-on gardening is linked with healthy eating behaviors, increased outdoor activities, and overall well-being. Although these positive associations are widely established for adults and school-agers, little evidence can be found on how such relationships may extend to early childhood, especially in the preschool years (3-5 years). One recent study conducted in North Carolina (NC) showed that participating in hands-on gardening significantly increased preschoolers’ accurate identification of fruits and vegetables (FV) and FV consumption compared to children who did not participate in hands-on gardening, but no association was found between participation in hands-on gardening and children’s liking (eating preferences) of FV. FV identification and liking during the early years may lead to lifelong healthy eating behaviors and preferences, making hands-on gardening a critical health intervention in early childhood environments, especially in childcare centers where a majority of the 13 million children in the United States between the ages of 0 and 5 spend most of their waking hours. This research aimed to investigate how hands-on gardening in childcare centers may impact preschoolers’ (3-5 years old) FV knowledge (identification) and liking in a semi-arid climate zone with a high concentration of Hispanic families by conducting experimental research with eight childcare centers and one hundred forty-nine children (n=149) in Lubbock County located in West Texas. Findings showed changes in average liking scores are generally positive in the experiment group of children who participated in hands-on gardening (compared to the control non-gardening group), implying improved liking. The findings indicate that the benefits of hands-on gardening in childcare centers for enhancing healthy eating preferences are evident even in a semi-arid climate zone, where high temperatures and limited rainfall present significant gardening challenges. This research underscores the importance of integrating hands-on gardening into childcare programs, highlighting its potential as an effective obesity prevention strategy not only within the U.S. but also in other regions with similar environmental constraints.

The aim of the study was to assess the frequency of fish consumption in Poland including sea and freshwater fish species referring to some socio-economic determinants. The frequency of consumption was assessed using Food Propensity Questionnaire data from 1489 adults (722 males, 767 females) in 2019–2020. The fish consumption frequency in Polish adults was too rare compared to the recommendations (at least twice a week). About 80% of respondents consumed fish less frequently than recommended. Sea fish were mostly consumed less than once a month (31.8%) or 1-3 times a month (30.9%). The most of subjects (44.8%) consumed freshwater fish less than once a month. It was also depended on: educational level, economic status, place of residence, declared health status, and on BMI value or BMI status. However, taking into account sex, the occurrence of these relationships was different in men and women. It seems that educational activities and dissemination of proper nutrition principles is necessary in order to increase the consumption of fish in Poland. It should be important to emphasize health benefits of fish consumption in relation to possible adverse effects of their contamination.

In this paper, a new way to obtain photoactive cements was presented. In this method amorphous TiO2 is added to cooler during the cooling of the cement clinker (Górażdże company) during cement production. Amorphous TiO2 was taken from the installation for obtaining titanium dioxide using the sulphate method. During the studies amorphous TiO2 was added to clinker at different temperature 300, 600, 700 and 800 °C. The properties of the obtained cement were tested during the bending and compressive strength and beginning and the end of bending setting time measurements. The adhesion of the obtained materials to concrete block, ceramic brick and plasterboard were also evaluated. The photocatalytic activity of the obtained materials was studied during NO and BTEX (benzene, toluene, ethylbenzene, p-,m-,o-xylenes decomposition) decomposition. Cement with 5 wt.% TiO2 added to clinker at 700 C had the highest photocatalytic activity and the best mechanical properties.

Chronic Obstructive Pulmonary Disease (COPD) is a disease characterized by local and systemic inflammation independently of the risk factor; during the exacerbations, such inflammation is accentuated and amplified. A practical inflammatory marker and one with an applicable predictive value in the follow-up has been sought. FeNO has shown an excellent performance in that respect within the context of asthma and has also been studied in tobacco-smoke COPD (COPD-TS). In Biomass-smoke COPD (COPD-BS), this, to our knowledge, has not been evaluated. Objective: To measure FeNO levels in patients with COPD-BS and to compare these with those of patients with stable COPD-TS and in healthy controls. Methods: Transversal, observational, descriptive, comparative, and analytical study. A total of 57 patients, including 23 with COPD-BS, 17 with COPD-TS, and 17 healthy control subjects. The measurement of FeNO was carried out on all of these by means of the on-line chemiluminescence technique; the values were expressed in parts per billion (ppb) for their analysis. Results: It was observed that the FeNO values were similar between COPD-BS and COPD-TS and were significantly different between the healthy and stable COPD (both groups). No correlation was found between pulmonary function and symptoms with FeNO in any of the groups. Conclusions: The level of FeNO in stable COPD is found to be increased in a similar manner in COPD-BS and COPD-TS, with a significant difference on comparing it with that of the healthy subjects.

This study aims to investigate the psychological cognitive mechanisms of rural residents amidst the renewal of suburban historical and cultural villages by examining the interplay between nostalgia, collective memory, subjective well-being and place identity in rural tourism destinations. Using Naobao Village as a case study—a suburban historical and cultural village in Hohhot, Inner Mongolia, this research employs a comprehensive approach integrating experimental methods and questionnaire surveys. The findings demonstrate that analyzing the interaction among the four emotions can elucidate the psychological cognitive mechanism of residents. Moreover, it uncovers that tourism effects significantly influence residents' perception of their living environment with positive effects on collective memory, subjective well-being and place identity. In the theoretical model for generating psychological cognition among residents in suburban historical and cultural villages, subjective well-being and collective memory play crucial mediating roles. This study provides a theoretical foundation and practical guidance for spatial reconstruction and cultural evolution of tourist landscapes in suburban rural tourist destinations.

Wheat is used for making many food products due to its diverse quality profile found among different wheat classes. Since laboratory analysis of these end-use quality traits is costly and time-consuming, genetic dissection of the traits is preferential. This study used a genome-wide association study (GWAS) of 10 end-use quality traits, including kernel protein, flour protein, flour yield, softness equivalence, solvent’s retention capacity, cookie diameter, and top-grain, in soft red winter wheat (SRWW) adapted to US southeast. The GWAS study included 266 SRWW genotypes that were evaluated in two locations over two years (2020-2022). A total of 27,466 single nucleotide markers were used and a total of 80 significant marker-trait associations were identified. There were 13 major effect quantitative trait loci (QTLs) explaining > 10% phenotypic variance out of which 12 were considered as novel. Five of the major effect QTLs were found to be stably expressed across multiple datasets, and four showed associations with multiple traits. Candidate genes were identified for eight of the major-effect QTLs including genes associated with starch biosynthesis and nutritional homeostasis in plants. These findings increase genetic comprehension of these end-use quality traits and could potentially be used for improving the quality of SRWW.

The well-known hop variety Saaz, which gives the Pilsner lager beer characteristic hop aroma may be threatened by climate change in the future. Therefore, new Saaz-related hop varieties, Saaz Late, Saaz Brilliant, Saaz Comfort, and Saaz Shine were bred recently. To evaluate whether these varieties are ac-ceptable for traditional lagers, their comparison was carried out. For this purpose, sensorial and chemical analyses of hops and related beer including namely analysis of hop resins and hop oils were performed. Sensory profiles of Saaz varieties are very similar (fine hoppy aroma, floral, herbal) except for Saaz Comfort which has a little higher aroma intensity, and Saaz Shine which has the most noticeable fruity scent with traces of citrusy of all. Also, the chemical profiles are very close, α-humulene, β-pinene, (E)-β-farnesene, β-caryophyllene, and myrcene are the most abundant. As a result of decoction mashing and kettle-hopping technology with bottom fermentation, are very similar lager beers with hoppy, floral, herbal, fruity, and spicy aromas. Typical hop oils are farnesol, linalool, methyl geranate, β-pinene, and limonene. The high concentration of farnesol in beer correlates with the concentration of (E)-β-farnesene and farnesol in hops. New Saaz varieties are well used for the production of the Pilsner type of lager without affecting the traditional sensory aroma of this widespread style. Varieties have a higher yield and concentration of bitter acids and hop oils. Moreover, Saaz Shine and Saaz Comfort have very good re-sistance to drought, which is an important property from a climate change perspective.

Zinc cobalt oxide-zinc hydroxide (ZnCo2O4-Zn(OH)2) microspheres were successfully fabricated on carbon cloth via a sample hydrothermal method. The surface morphology of these microspheres and their efficacy in degrading methyl violet were further modulated by varying the thermal annealing temperatures. The manipulation of thermal annealing temperatures was pivotal in adjusting the porosity of ZnCo2O4-Zn(OH)2 microspheres to amplify their photocatalytic performance. Various analytical techniques were utilized to evaluate the physical and chemical properties of the ZnCo2O4-Zn(OH)2 microspheres, including field-emission scanning electron microscopy, energy-dispersive spectroscopy, X-ray diffraction, field-emission transmission electron microscopy, X-ray photoelectron spectroscopy, and UV-vis spectroscopy. Compared to untreated ZnCo2O4-Zn(OH)2 microspheres, those subjected to thermal annealing exhibited increased specific surface area and light absorption capacity, rendering them highly effective photocatalysts under UVC light exposure. Subsequent studies have confirmed the superior performance of ZnCo2O4-Zn(OH)2 microspheres as a reusable photocatalyst for degrading methyl violet and tetracycline. Additionally, trapping experiments during the photodegradation process involving ZnCo2O4-Zn(OH)2 microspheres have identified hydroxyl radicals (·OH) and superoxide radicals (·O2–) as the primary reactive species.

Human development encompasses the integration of neuromotor, psychological, social-emotional, and cognitive processes across time. However, a better understanding of the interconnectedness of motor and cognitive development throughout the lifespan is needed. The integrative and dynamic nature of short-term motor skill acquisition and long-term developmental processes may foster executive functions. Unfortunately, assessments of motor competence have traditionally focused on skillfulness from a movement perspective, using restrictive task protocols that decontextualize performance and limit cognitive involvement. Additionally, traditional motor-cognitive dual-task assessments centered on cognitive involvement during specific movement protocols, have minimized impacts of task complexity and motor competence on cognitive performance. To gain a more ecologically valid understanding of the relation between motor and cognitive development, a novel assessment paradigm using an integrative approach to motor-cognitive dual-tasking is needed. The purpose of the present paper is to: 1) provide a conceptual bridge, based on multidisciplinary evidence, to effectively link the concurrent development of motor competence and executive functions via learning-related and exercise-related neurotrophic mechanisms, and 2) use this conceptual bridge to inform the development of novel motor-cognitive dual-task assessments that account for the role of task complexity, current levels of motor competence, and the continuous decision-making inherent in “real world” performance environments.

Crop production has become a priority issue in the last few years due to the exponential growth of the world population and the need to substitute chemical fertilizers. This last matter is under the spotlight to achieve a more sustainable approach in a cost-effective way. Biostimulants have gained attention as an alternative to chemical fertilizers. Although they are not considered fertilisers as inputs of nutrients, they stimulate plants’ nutrition and tolerance to stress, among other characteristics. Amino acid-based biostimulants have been found to be effective in literature. This review focuses on the effectiveness of biostimulants, their presence in the global market, and mainly in their production with fish by-products as a source, using enzymatic hydrolysis and autolysis, focusing especially on fish viscera, their possibilities in the agricultural sector and their availability in Europe for possible opportunities. Fish viscera protein hydrolysates for biostimulant production seems a feasible alternative to fishmeal production in Europe, mainly in areas located far away from fishmeal plants.

The effect of the heterogeneity in sex factor is considered in the Markovian manpower modeling model. The estimation of the transition probability matrix of the staff flow was done using the maximum likelihood method. The expected future durations of the individuals in the manpower system were obtained under the aggregated and disaggregated (male and female) staff flow as well as their variances. Test for the heterogeneity of the staff based on sex factor was performed and the result of the heterogeneity test shows that there is difference between the disaggregated staff flows. The computed entrant probabilities also indicate that the male group has higher probabilities of attaining higher grades than the female group.

Aiming at solving difficulties related to aero-engine classification and identification, the infrared spectra of aero-engine hot jets are measured by telemetry Fourier transform infrared spectrometer, and a six types aero-engine hot jet spectrum data set is generated. The spectrum data set were randomly sampled at a ratio of 8:1:1 to generate training set, validation set and prediction set. In this paper, a Peak Finding Siamese Convolutional Neural Network (PF-SCNN) is designed to match and classify spectrum data. In the first place, the matching pairs of training set and validation set are made independently with the labels of positive and negative samples creating. The spectrum feature extraction and distance similarity calculation are carried out by the Siamese convolutional neural network (SCNN). When entering the prediction phase, the prediction set and training set are integrated to predict in the trained model. The prediction set labels are ultimately determined by matching them with the training set labels having the highest similarities to ensure accurate predictions. To improve the operation efficiency of the SCNN, a peak finding method is introduced to extract the spectrum peaks. Peak positions of high frequency are counted, while the peak data are extracted. The peak data are used to take the place of the original data for training and prediction. The performance measures are defined as Accuracy, Precision, Recall, Confusion matrix and F1-score, and the prediction accuracy was up to 99%. The experimental results indicate that the proposed PF-SCNN is suitable for our spectral dataset and can complete the task of infrared spectrum classification of aero-engine hot jets.

The iron roughneck is an automated equipment utilized for the connection and removal of drilling tools. This paper presents the design of an integrated iron roughneck, providing a detailed introduction to its clamp body structure, along with an analysis of its structural characteristics and performance requirements. The study delves into the integration mode and working characteristics of the clamping mechanism and spin buckle mechanism for the integrated upper clamp body structure of the iron roughneck. Additionally, this paper conducts an in-depth theoretical study on the spin buckle mechanism. Firstly, it analyzes the actual working condition of the spin buckle roller from two perspectives: contact theory and rolling friction theory, determining the structural form of the spin buckle roller. Secondly, it investigates the relative displacement between the spin buckle mechanism and the drilling tool, proposing a design method for the floating device mounted on the spin buckle roller and establishing the kinematic equation of the spin buckle roller under the influence of the floating device. Furthermore, the kinematic equations of the spin buckle roller under the influence of the floating device are established. Finally, a dynamics simulation experiment is performed to simulate the working process of the spin buckle mechanism under actual working conditions, analyzing the dynamics and kinematics of the spin buckle mechanism and obtaining the relevant parameter curves of the spin buckle mechanism and drilling tools. Through data comparison and analysis, the correctness of the theoretical analysis results and the rationality of the performance and structure of the spin buckle mechanism are verified.

Indoor environmental comfort is fundamental to human health as people spend 90% of their time indoors. This aspect is even more crucial in hospitals, where the concept of health is closely linked to well-being, ethics, and environmental aspects. Emerging methodologies and technologies such as Digital Twin, Building Information Modeling, the Internet of Things, sensing technologies, and data analytics offer new opportunities to ensure healthier environments and more efficient building management. This paper provides an assessment of how digitalization can support decision-making processes related to maintaining high levels of indoor environmental comfort in hospital settings, particularly by analyzing how real-time data processing and the application of machine learning can promote proactive interventions in these facilities. The methodological approach was based on four phases: defining the objectives of the digital twin, identifying the input data to build and feed the digital model, defining the KPIs to evaluate the system's correct functioning, and identifying the enabling technologies to be integrated into the system to achieve the set goal. The result is a digital twin for managing the operating room and its related services, with the aim of guiding decisions based on accurate data and improving operational efficiency, levels of environmental comfort, and safety regarding the diffusion of medical gases.

In the fast-changing world of software development, the protection of software products has emerged as an imperative requirement. This paper presents a new way to increase the maturity of development teams to reach the highest level of software security. Based on these, the framework uses the Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) to systematically evaluate and enhance the people maturity of software development projects. The essence of the fuzzy logic and AHP technique interaction is to handle the uncertainty and complexity of human factors and team dynamics in the evaluation framework. Using the decision-making model allows the project managers and stakeholders to determine the appropriate areas for improvement and develop the right strategies and actions to nurture a secure and mature development culture. The paper identifies 24 human success factors (HSFs) and human security vulnerabilities (HSVs) and 38 practices for addressing these HSFs and HSVs. Furthermore, we discuss the local and global ranks of each HSF and HSV practice and categorize the identified practices into 9 categories to determine the ranks and weight of each category. Based on collected data, FAHP prioritized these practices; the category “C4: Skill Development and Stakeholder Engagement” is ranked highest at rank-1 and possesses the most significant weight of 0.12435. Similarly, the highest global weight is 0.051506, and the global ranked (rank-1) HSF and HSV practice is “P15: Hands-On Practice and Stakeholder Communication”. Research evidence and case discussions show how the described framework assists in building secure software development (SSD) practices, which can be considered evidence of the application of team maturity to improve cybersecurity in organizations. Additional research directions include improving the framework, especially using highly developed learning techniques and applying the framework to other forms of development.

We study the electron tunneling (ET) and local Andreev reflection (AR) processes in a quantum dot (QD) coupled to the left and right ferromagnetic leads with noncollinear ferromagnetisms. In particular, we consider that the QD is also side-coupled to a nanowire hosting Majorana bound states (MBSs) at its ends. Our results show that when one mode of the MBSs is coupled simultaneously to both spin-up and spin-down electrons on the QD, the height of the central peak is quite different from that if the MBS is coupled to only one spin component electrons. The ET and AR conductances which are mediated by the dot-MBS hybridization strongly depend on the angle between the left and right magnetic moments in the leads, which result in sign change of the angle-dependent tunnel magnetic resistance. This result is very different from case when the QD is coupled to regular fermonic mode, and can be used for detecting the existence of MBSs, a current challenge in condensed matter physics under extensive investigations.

A total of 27 microsatellites markers , scattered all over the genom of barley, were used for characterization,and diversity analysis in 33 barley (Hordeum vulgare L.) accessions and cultivars of Algeria.Over the 27 genetic loci studied, 110 alleles were identified with a mean of 4.1 alleles per locus and the average polymorphism information content (PIC) of 0.46,the marker Ebma0806 showed the greatest value of PIC with 0.83.Genetic diversity at 27 microsatellite loci varied from 0 to 0.84 (Mean=0.50) for 33 Algerian cultivars. The genetic distance among the cultivars ranged from 0.2 to 0.85. Cluster analysis and principal coordinate analysis (PCoA) based on the SSR data clearly differentiate the all genotypes studied.

The superfamily of Acid proteases has two catalytic aspartates for proteolysis of their peptide substrates. Here, we show a minimal structural scaffold, the Structural Catalytic Core (SCC), which packs all conserved substructure elements around the catalytic machinery, and which can be found in all enzymes of the Acid proteases superfamily. The SCC is a dimer of several structural blocks, such as the DD-link, the D-loop and the G-loop, around two catalytic aspartates in each protease subunit or within an individual chain. The dimer of two D-loop/DD-link substructures makes a DD-zone, and the dimer of two D-loop/G-loop substructures makes a psi-loop. These structural markers are useful for protein comparison, structure identification, protein family separation and protein engineering.

An undesirable sensory attribute (“floral taint”) has been recently detected in red wines in some winegrowing jurisdictions in North America (e.g. Ontario, British Columbia, Washington), caused by introduction of frost-killed leaves and petioles [materials-other-than-grapes (MOG)] during mechanical harvest and winemaking. It was hypothesized that terpenes, norisoprenoids, and higher alcohols would be the main responsible compounds. Objectives were to investigate causative volatile compounds for floral taint, and explore threshold concentrations for this problem. Commercial wines displaying varying intensities of floral taints were subjected to GC-MS and sensory analysis. Several odor-active compounds were higher in floral-tainted wines, including terpenes (geraniol, citronellol, cis- and trans-rose oxide), norisoprenoids (β-damascenone, β-ionone), five ethyl esters, and three alcohols. Thereafter, fermentations of Cabernet franc (CF) and Cabernet Sauvignon (CS) (2016, 2017) were conducted. MOG treatments were (wt/wt): 0, 0.5%, 1%, 2% and 5% petioles, and 0, 0.25%, 0.5%, 1%, and 2% leaf blades. Terpenes (linalool, geraniol, nerol, nerolidol, citronellol, citral, cis- and trans-rose oxides, eugenol, myrcene), norisoprenoids (α- and β-ionone), and others (e.g. hexanol, octanol, methyl and ethyl salicylate) increased linearly/quadratically with increasing MOG levels in both cultivars. Principal components analysis separated MOG treatments from the controls with 5% petioles and 2% leaves as extremes. Increasing MOG levels in CF wines increased floral aroma intensity, and were primarily associated with terpenes, higher alcohols, and salicylates. Increased leaf levels in CF were associated with higher vegetal and earthy attributes. Increased petioles in CS were not correlated with floral aromas, but increased leaves increased floral, vegetal and herbaceous attributes. Overall, petioles contributed more to floral taint than leaves through increased terpenes and salicylates (floral notes), while leaves contributed norisoprenoids and C6 alcohols (green notes).

Focusing on the problem of identifying and classifying aero-engine models, this paper measures the infrared spectrum data of aero-engine hot jets using a telemetry Fourier transform infrared spectrometer. Simultaneously, infrared spectral data sets with the six different types of aero-engines are created. For the purpose of classifying and identifying infrared spectral data, a CNN architecture based on the continuous wavelet transform peak seeking attention mechanism (CWT-AM-CNN) is suggested. This method calculates the peak value of middle wave band by continuous wavelet transform, and the peak data is extracted by the statistics of the wave number locations with high frequency. Attention mechanism is used for the peak data, and the attention mechanism is weighted to the feature map of the feature extraction block. The training set, vali-dation set and prediction set are divided in the ratio of 8:1:1 for the infrared spectral data sets. For three different data sets, CWT-AM-CNN proposed in this paper is compared with the classical classifier algorithm based on CO2 feature vector and the popular AE, RNN and LSTM spectral processing networks. The prediction accuracy of the proposed algorithm in the three data sets is as high as 97%, and the lightweight network structure design not only guarantees high precision, but also has a fast running speed, which can realize the rapid and high-precision classification of the infrared spectral data of the aero-engine hot jets.

Background: Bioelectrical impedance (BIA) and ultrasound (US) have become popular for estimating body fat percentage (BF%) due to their low cost and clinical convenience. However, agreement of these devices with gold standard method still require investigation. The aim was to analyze the agreement between a gold standard %BF assessment method with BIA and US devices. Methods: Twenty-three men (age 30.1 ± 7.7 years, 82.5 ± 14.9 kg, 1.77 ± 0.05 m) underwent Dual Energy X-Ray Absorptiometry (DXA), BIA (tetrapolar) and US (three-site method) %BF assessment. Pearson and concordance correlations were analyzed. T-test compared means between methods, and Bland Altman plots analyzed agreement and proportional bias. Alpha was set at < .05. Results: Pearson coefficients between BIA and US with DXA were high (BIA = 0.94; US = 0.89; both p < .001). Concordance coefficient was high for BIA (0.80) and moderate for US (0.49). BF% measured by BIA (24.5 ± 7.5) and US (19.4 ± 7.0) were on average 4.4% and 9.6% lower than DXA (29.0 + 8.5%), respectively (p < .001). Lower and upper agreement limits between DXA and BIA were -1.45 and 10.31, while between DXA and US were 2.01 and 17.14, respectively. There was a tendency of both BIA (p = .09) and US (p = .057) to present proportional bias and underestimate BF%. Conclusions: Despite the correlation, the mean difference between the methods were significant, and the agreement limits are very wide. This indicate that BIA and US, as measured in this study, have limited potential to accurately measure %BF compared to DXA, especially in individuals with higher body fat.

In this work, zinc oxide (ZnO)/ granular activated carbon (GAC) composites at different ZnO concentration (0.25M-ZnO@GAC, 0.5M-ZnO@GAC, and 0.75M-ZnO@GAC) were prepared by an in-situ hydrothermal method and demonstrated synergistic photocatalytic degradation and ad-sorption of Rhodamine B (RhB). The thermal stability, morphological structure, elemental com-position, crystallographic structure, and textural properties of developed catalysts were charac-terized by thermal gravimetric analysis (TGA/DTG), scanning electron microscopy equipped with energy dispersive-x-ray (SEM-EDS), x-ray diffraction (XRD), and Brunauer–Emmett–Teller (BET) analysis. Successful loading of ZnO onto GAC was confirmed by SEM-EDS and XRD analysis. The BET surface areas of GAC, 0.25M-ZnO@GAC, 0.5M-ZnO@GAC, and 0.75M-ZnO@GAC were 474 m2/g, 450 m2/g, 453 m2/g, and 421 m2/g, respectively. The decrease in GAC could be attributed to the successful loading of ZnO on the GAC surface. Notably, 0.5M-ZnO@GAC exhibited the best photocatalytic degradation efficiency of 82% and 97% under UV-A and UV-C light over 120 min, attributed to improved crystallinity and visible light absorption. The photocatalytic degradation parameters revealed that lowering the RhB concentration, raising the catalyst dosage and pH be-yond the point of zero charge (PZC) would favor the RhB degradation. Photocatalytic reusability was demonstrated over 5 cycles. Scavenger tests revealed that the hydroxyl radicals (•OH), su-peroxide radicals (O2−•), and photoinduced hole (h+) radicals play a major role during the RhB degradation process. Based on the TOC results, the RhB mineralization efficiency of 79.1% was achieved by 0.5M-ZnO@GAC. Additionally, GAC exhibited a strong adsorptive performance towards RhB with adsorption capacity and RhB removal of 487.1 mg/g and 99.5% achieved within 90 min equilibrium time. The adsorption characteristics were best described by pseu-do-second-order kinetics, suggesting chemical adsorption. This research offers a new strategy for the development of effective photocatalyst materials with potential for wider wastewater treat-ment applications.

This study aims to quantify greenhouse gas (GHG) emissions from China's sludge treatment industry and explore the potential of novel technologies to mitigate these emissions, promoting sustainable sludge management practices. Using a life cycle assessment approach, the total GHG emissions from sludge treatment in 2017 were estimated at 18.54 Mt CO2-eq, with significant regional variations. Incineration contributed the highest emissions (1,011.53 kg CO2-eq/t dry sludge), followed by landfill (717.51 kg CO2-eq/t) and land application (276.41 kg CO2-eq/t). The uneven distribution of emissions across cities highlights the need for targeted mitigation strategies that consider local sustainability challenges. Principal component analysis revealed that economic factors and treatment scale significantly influence emissions, emphasizing the importance of integrating sustainability goals with economic development. To reduce the carbon footprint of sludge treatment and enhance sustainability, the mitigation potential and costs of various technologies were evaluated, including thermal conversion, anaerobic digestion, hydrothermal processes, and wet oxidation. These technologies offer GHG emission reductions ranging from 0.09 to 0.46 t CO2-eq/t dry solids compared to conventional methods, while also promoting resource recovery and circular economy principles. However, further optimization is necessary to enhance their environmental and economic performance, ensuring long-term sustainability. By implementing these technologies and adopting optimization strategies, China's sludge treatment industry can significantly contribute to achieving the country's carbon neutrality goal and fostering sustainable development.

The onset of neurodegenerative diseases involves a complex interplay of pathological mecha-nisms, including protein aggregation, oxidative stress, impaired autophagy. This review focuses on the intricate connection between oxidative stress and autophagy in neurodegenerative disor-ders, highlighting autophagy as pivotal in disease pathogenesis. Reactive oxygen species (ROS) play dual roles in cellular homeostasis and autophagy regulation, with disruptions of redox sig-naling contributing to neurodegeneration. The activation of the Nrf2 pathway represents a criti-cal antioxidant mechanism, while autophagy maintains cellular homeostasis by degrading al-tered cell components. The interaction between p62/SQSTM1, Nrf2 and Keap1 forms a regulatory pathway essential for cellular stress response, whose dysregulation leads to impaired autophagy and aggregate accumulation. Targeting the Nrf2-p62/SQSTM1 pathway holds promise for thera-peutic intervention, mitigating oxidative stress and preserving cellular functions. Additionally, the review explores the potential synergy between the endocannabinoid system and Nrf2 signal-ing for neuroprotection. Further research is needed to elucidate the involved molecular mecha-nisms and develop effective therapeutic strategies against neurodegeneration.

The evidential value of an mtDNA match between biological remains and its potential donor is determined by the random match probability of the haplotype. This probability is based on the haplotype’s population frequency estimate. Consequently, implementing a population study representative of the population relevant to the forensic case is vital to correctly evaluating the evidence. The emerging number of poaching cases and the limited availability of such data emphasizes the need for improved fallow deer mtDNA population databank for forensic purposes, including targeting the entire mitochondrial control region. By sequencing the whole mitochondrial control region in 138 animals from five populations in Hungary we found four different haplotypes, including one which has not yet been described. Our results, supplemented with data already available from previous research do not support the possibility of determining the population of origin, although some patterns of geographical separation can be distinguished. Estimates of molecular diversity indicate approximately similarly low mtDNA diversity (Hd=0.565 and π = 0.002), compared with data from other countries. The calculated random match probability of 0.547 shows a high probability of coincidence and, therefore, a limited capacity for exclusion. Consequently, it may be necessary to search for polymorphic sites on other mitochondrial gene sections or to sequence the entire mitogenome of fallow deer.

Ice formation on aircraft surfaces poses significant safety risks, and current detection systems often struggle to provide accurate, real-time predictions. This paper presents the development and comprehensive evaluation of a smart ice control system using a suite of machine learning models. The system utilizes various sensors to detect temperature anomalies and signal potential ice formation. We trained and tested supervised learning models (Logistic Regression, Support Vector Machine, Random Forest), unsupervised learning models (K-means clustering), and neural networks (Multi-Layer Perceptron) to predict and identify ice formation patterns. Experimental results demonstrate that our smart system, driven by machine learning, accurately predicts ice formation in real-time, optimizes de-icing processes, and enhances safety while reducing power consumption. This solution holds the potential for improving ice detection accuracy in aviation and other critical industries requiring robust predictive maintenance.

In patients with heart failure, the evaluation of left ventricular (LV) diastolic function is vital, offering crucial insights into hemodynamic impact and prognostic accuracy. Echocardiography stands as the primary imaging modality for diastolic function assessment, and using it effectively requires a profound understanding of the underlying pathology. This review covers four main topics: first, the fundamental driving forces behind each phase of normal diastolic dynamics, along with the physiological basis of two widely used echocardiographic assessment parameters, E/e' and mitral annulus early diastolic velocity (e'); second, the intricate functional relationship between the left atrium and LV in patients with varying degrees of LV diastolic dysfunction (LVDD); third, the role of stress echocardiography in diagnosing LVDD and the significance of parameter changes in this context; and fourth, the clinical utility of evaluating diastolic function from echocardiography images across diverse cardiovascular care areas.

Background/Objectives: High-intensity anaerobic physical training frequently results in muscle damage among boxers and kickboxers, which can impede performance and recovery. Vibrational therapy (VT) and passive rest (PR) have been employed as methods to enhance muscular recovery and performance. This study evaluates the effectiveness of these two recovery methods on upper limb muscle strength and lactate levels in plasma after high-intensity exertion. Methods: Eighteen elite boxers and kickboxers, aged 19-32 years, underwent tests employing VT and PR as recovery methods in a controlled, crossover study. Muscle performance was assessed via isokinetic dynamometry, and lactate levels were measured pre-exercise, post-exercise, and post-recovery. The study adhered to the Declaration of Helsinki guidelines and was approved by the relevant bioethics committee. Results: The results showed that VT led to a faster recruitment of muscle fibers and improved muscle endurance as indicated by decreased fatigue work indices compared to PR. However, no significant differences were observed in peak torque or lactate levels between the two recovery methods. The VT group exhibited quicker recovery times in torque generation and better performance in fatigue resistance. Conclusions: VT appears to provide superior muscular recovery compared to PR following intense anaerobic effort, particularly in terms of muscle strength endurance and activation speed. These findings support the potential of VT in sports recovery protocols, although similar lactate response suggests that metabolic recovery rates are not significantly affected.

Rural landscapes are acknowledged for their potential to restore human health due to their natural characteristics. However, few studies have systematically analysed the impact of naturalness, landscape types, and combinations of landscape elements on restorativeness using both subjective and objective measurements. This study investigated the restorative effects of various rural landscapes in Guangzhou, employing electroencephalography and eye-tracking technologies to record physiological responses and using the Restorative Components Scale and the Perceived Restorativeness and Naturalness Scale to evaluate psychological responses. The results indicated the following: (1) There was a significant positive correlation between perceived naturalness and restorativeness, surpassing the impact of actual naturalness. (2) Different landscape types had a varying impact on mental health at the equal perceived naturalness. Natural forest landscapes and artificial forest landscapes exhibited the most substantial restorative effects among the natural and semi-natural landscapes examined, respectively, while settlement landscapes showed the highest restorative potential among the artificial landscapes. (3) Restorative properties varied across landscape elements, with identical elements yielding different benefits in different environments. Trees and water significantly enhanced restorativeness, whereas constructed elements such as roads and infrastructure reduced it. This study provides a scientific basis for restorative rural landscape design to enhance mental health and well-being.

With the development of deep learning, the Super-Resolution (SR) reconstruction of microscopic images has improved significantly. However, the scarcity of microscopic images for training, the underutilization of hierarchical features in original Low Resolution (LR) images, and the high-frequency noise unrelated with the image structure generated during reconstruction process are still challenges in the Single Image Super-Resolution (SISR) field. Faced with these issues, we first collected sufficient microscopic images through Motic, a company engaged in the design and production of optical and digital microscopes, to establish a dataset. Secondly, we proposed a Residual Dense Attention Generative Adversarial Network (RDAGAN). The network comprises a generator, an image discriminator, and a feature discriminator. The generator includes a Residual Dense Block (RDB) and a Convolutional Block Attention Module (CBAM), focusing on extracting the hierarchical features of the original LR image. Simultaneously, the added feature discriminator enables the network to generate high-frequency features pertinent to the image’s structure. Finally, we conducted experimental analysis and compared our model with six classic models. Compared with the best model, our model improved PSNR and SSIM by about 1.5dB and 0.2, respectively.

Buruli ulcer is a chronic ulcerative disease of skin and subcutaneous tissues caused by infection with Mycobacterium ulcerans. Although Australian possums are known to be susceptible to Buruli ulcer, many aspects of the disease in possums, including welfare impacts, remain largely unreported. Severe clinical Buruli ulcer was identified in four common ringtail possums (Pseudocheirus peregrinus) from Melbourne, Victoria. All four possums were euthanised due to welfare concerns and poor prognosis, based on the presence of deep ulcerative lesions to paws, some of which exposed carpal or tarsal bones. These lesions were considered likely to cause partial or complete loss of limb function, which would severely affect the welfare and survival of these wild arboreal animals. Histologically, there was severe ulcerative necrotising pyogranulomatous dermatitis, panniculitis, and myositis, with intralesional acid-fast bacteria. M. ulcerans was detected by real-time PCR in all swabs and biological tissues collected from all four cases. Buruli ulcer may be an important and under-recognised cause of poor possum welfare in endemic areas. In addition to severe cutaneous lesions, infection extends to underlying bones and joints, and the systemic distribution of M. ulcerans throughout all major tissues and internal organs, as observed in these four cases, may further impact the health and fitness of infected possums. Further research is needed to investigate the epidemiology, pathogenesis and impacts of Buruli ulcer in possums, and to inform the design of interventions that may protect the health and welfare of possums and other affected animal species.

Parental labour migration, either one or both parents, has been associated with various challenges among left-behind children (LBC). However, there is a limited understanding of the LBC’s own views and experiences of social and mental wellbeing and how the new daily life circumstances they encounter following their parents’ migration impact them. This study aimed to understand the influence of parental migration and its aftermath on the social and mental wellbeing of children and adolescents (referred to as LBC) in two rural districts in Indonesia. Employing a qualitative design, data were collected through individual in-depth interviews with LBC (n=24) aged 14 to 18 years, recruited using the snowball sampling technique. Data were thematically analysed, guided by a qualitative data analysis framework. The findings showed that parental migration negatively impacted the social wellbeing of LBC. This impact was reflected in negative labelling from friends and changes in familial roles which influenced their social interactions and activities with peers. Parental migration also caused challenges to the mental wellbeing of LBC. These manifested in the LBC experiencing fractured emotional bonds, leading to negative emotions, including stress, anxiety, sadness, depression, frustration, loss of motivation, and self-imposed isolation, which were associated with their parents’ migration and abrupt disruptions in parent-child communication. The transition to new life situations with caregivers after parental migration and the dynamics within the caregivers’ households were additional factors that detrimentally affected their mental well-being. Unmet basic needs and educational needs due to financial hardships faced by mothers and caregivers, further exacerbated mental health challenges for the children. The findings indicate the importance and improvement of policies and interventions in Indonesia (e.g., counselling services, non-cash food assistance, family hope program, direct cash assistance) that cover and address the diverse needs of mothers or caregivers and the LBC.

Cannabidiol (CBD) is a safe and non-psychotropic phytocannabinoid with a wide range of potential therapeutic antiinflamatory and antioxidant activity. Due to its lipophilicity, it is normally available dissolved in oily phases. The main aim of this work was to develop and characterize a new formulation of a microemulsion with a potential anti-inflammatory and antioxidant action for topical treatment of inflammatory skin disorders. The micro-emulsion system was obtained from a 20% CBD oil as hydrophobic phase, Labrasol/Plurol Oleique (1:1) as surfactant and cosurfactant (S/CoS) respectively and an aqueous vegetal extract obtained from S. ebulus L. ripe fruits, with a potential anti-oxidant and anti-inflammatory activity, as water phase. A pseudo-ternary phase diagram was elaborated, selecting an optimal proportion of 62% (S/CoS), 27% CBD oil and 11% water and, after testing its reproducibility, the aqueous phases were replaced by the vegetal hydrophilic extract. The defined systems were characterized in terms of conductivity, droplet size by laser scattering, compatibility of components by differential scanning calorimetry and rheological properties using a rotational rheometer. The designed microemulsion showed good stability and a slight pseudo-plastic behavior. The release properties of CBD from the oil phase and caffeic acid from the water phase of the microemulsion were studied by in vitro diffusion experiments using flow-through diffusion cells in comparison to a CBD oil and a microemulsion only with CBD as active substance. It was evidenced that the inclusion of the original oil in microemulsions did not provoke a significant modification of the release of CBD, incorporating the possibility of including hydrophilic active compounds in the formulation, stablishing an interesting strategy for the development of future formulations.

This study presents a critical literature review on the models of users' adoption of blockchain applications in supply chains. This review pertaining to blockchain technology adoption by supply chain stakeholders is significant as it is a pre-requisite for the technical sustainability of blockchain technology in supply chains. Through a critical literature review, the previous studies related to technology adoption models were analyzed to explore practices brought about by blockchain applications for supply chain management. This study examined the suitability of the existing models (e.g., the technology-organization-environment (TOE) framework, task technology fit (TTF), unified theory of acceptance and use of technology (UTAUT)) of technology adoption for blockchain applications in supply chains and came up with a new unified model, namely, TOE-TTF-UTAUT. This review provides implications for a more appropriate research design using mixed methods. When adopting the TOE-TTF-UTAUT model in a study, two phases of research using mixed methods can be performed. The first phase is an exploratory sequential design in which a qualitative approach to explore the TOE and supply chain task constructs is followed by a quantitative approach using a survey and quantitative analyses to investigate the factors affecting blockchain adoption in supply chains. The second phase adopts explanatory sequential design in which the quantitative findings from the first phase are reviewed for follow-up by qualitative interviews to obtain explanations.

Few-shot object detection (FSOD) aims to address the challenge of requiring a substantial amount of annotations for training in conventional object detection, which is very labor-intensive. However, existing few-shot methods achieve high precision with the sacrifice of time-consuming for exhaustive fine-tuning, or take poor performance in novel-class adaptation. We presume the major reason is that the valuable correlation feature among different categories is insufficiently exploited, hindering the generalization of knowledge from base to novel categories for object detection. In this paper, we propose Few-Shot object detection via Correlation-RPN and Transformer Encoder-Decoder (CRTED), a novel training network to learn object-relevant features of inter-class correlation and intra-class compactness while suppressing object-agnostic features in the background with limited annotated samples. And we also introduce a 4-way tuple-contrast training strategy to positively activate the training progress of our object detector. Experiments over two few-shot benchmarks (Pascal VOC, MS-COCO) demonstrate that, our proposed CRTED without further fine-tuning can achieve comparable performance with current state-of-the-art fine-tuned works. The codes and pre-trained models will be released.

The clinical features of increasing muscle weakening are shared by a diverse set of illnesses known as muscular dystrophies. In early childhood, males with Duchenne muscular dystrophy (DMD) exhibit proximal muscle weakening and calf enlargement, making it the most frequent X-linked disease of muscular dystrophy in children. Development of motor skills is typically delayed, and wheelchair confinement eventually leads to early death from heart or lung problems. In terms of function, ambulation, quality of life, and life expectancy, treatment approaches like corticosteroid therapy and intermittent positive pressure breathing have improved. This is a case report of a 6-year-old kid who had early ambulatory stage Duchenne Muscular Dystrophy and complained to the neuro-physiotherapy department about frequent falls, walking difficulties, and dyspnea when walking. Other grievances included being unable to get off the ground and having trouble ascending stairs. He had physiotherapy and dynamic neuromuscular stabilization for his complaints. The main goals of treatment were educating the family, respiratory training, preventing ankle plantar flexors, maintaining strength, balance and gait training.

Childhood obesity has become a global epidemic, with significant increases in prevalence over recent decades. While excessive calorie consumption and physical inactivity are known factors, emerging research highlights the role of Endocrine-Disrupting Chemicals (EDCs), particularly obesogens, in obesity's pathogenesis. This review explores the historical context of the environmental obesogens hypothesis, their sources, mechanism of action, impact on prenatal and postnatal development and epigenetics. Additionally, it discusses the long-term consequences of childhood obesity and proposes prevention strategies that will mitigate the negative health effects. Obesogens were found to disrupt hormonal balance and metabolic processes through various mechanisms such as altering gene expression, hormonal interference, and inflammation. Especially significant, was exposure during critical windows of development which correlates with increased risk of obesity in childhood or adolescence. Long-term effects of childhood obesity include chronic health conditions and psychosocial issues. A comprehensive approach is necessary to address childhood obesity, encompassing genetic, environmental, and lifestyle factors. Prevention strategies should focus on reducing obesogens exposure, promoting healthy lifestyles, and implementing regulatory policies. Future research should investigate obesogens-diet interactions, microbiome impacts, and combined obesogens effects. Long-term human studies are also crucial for validating findings from animal models and allow for inform decision-making to combat the obesity pandemic.

The ubiquitous presence of microplastics (MPs) in the environment poses a threat to ecosystems and increases concerns about their exposure to the human body. However, despite being consumed for health improvement, limited research has been conducted on MPs in functional foods. This study aimed to investigate the occurrence of MPs and the relation of the source of raw material or the manufacture in various omega-3 oil in the Korean market. MPs in omega-3 capsule and raw oil, sourced from both plant-based (PB) and animal-based (AB) sources, were investigated. We developed the method by direct filtration with acetone washing and analyzed MPs greater than 5 μm using microscope-Raman spectroscopy. The average number of MPs was found to be 1.2 ± 1.7 MPs/g for PB raw oil, 2.2 ± 1.7 MPs/g for AB raw oil, 3.5 ± 3.9 MPs/g for PB capsule oil, and 10.6 ± 8.9 MPs/g for AB capsule oil. Polypropylene and polyethylene terephthalate were major specious (83-95 %) found in omega-3 oil. The ratio of size range remained consistent across all groups, with a trend of higher detection rates as the size diminished. The results reveal that the main reason of MPs contamination is not the source of raw material but the manufacturing and packaging process for omega-3 oil.

Chromium (Cr) metal has garnered significant attention in alloy systems owing to its exceptional properties, such as high melting point, low density, and superior oxidation and corrosion resistance. However, its processing capabilities are hindered by the high Ductile-Brittle Transition Temperature (DBTT). Recently, powder bed fusion-laser beam for metals (PBF-LB/M) has emerged as a promising technique, offering the fabrication of net shapes and precise control over crystallographic texture. Nevertheless, research investigating the mechanism underlying crystallographic texture development in pure Cr via PBF-LB/M still needs to be conducted. This study explores the impact of scan speed on relative density and crystallographic texture. At the optimal scan speed, an increase in grain size attributed to epitaxial growth was observed, resulting in the formation of cubic texture. Consequently, a reduction in High Angle Grain Boundaries (HAGB) was achieved, suppressing defects such as cracks and enhancing relative density up to 98.1%. Furthermore, with increasing densification, Vickers hardness also exhibited a corresponding increase. These findings underscore the efficacy of PBF-LB/M for processing metals with high DBTT properties.

Organic fertilizer application in agricultural land is known to improve soil microbial processes, fertility, and yield. In particular, stable changes in soil chemical composition through multi-year fertilization of organic fertilizers are thought to cause changes in the microbial community. Here, the effects of oil cake amendments (OC) on soil bacterial diversity, community profile and enzyme activity were evaluated and compared to those amended with chemical fertilizer (NPK). The comparison of diversity indices between OC and NPK amended soils shows that application of oil cake has increased microbial diversity potentially with an increase in the number of different microbial groups. The ordination plot distinguished and clustered both treatments showing differential effects of soils chemical factors on the microbial communities of each treatment. Proteobacteria, Verrucomicrobia and Bacteriodetes were significantly abundant in OC amended soil than in the NPK received soil, indicating alterations in community structure, composition, and diversity con-current to the changes in pH, Ca and Mg contents of the soil. These shifts in bacterial community structure and composition could also be observed from the phylum to the genus level in both NPK and OC amended soils partially explained by differences in soil chemical factors. The OC soil compared to the NPK amended soil also contain significantly higher abundance of predicted genes corresponding to enzymes related to biogeochemical cycling, decomposition and plant growth promotion. Collectively, these results support the use of an unconventional organic fertilizer positively altering bacterial populations in jujube orchards. The application of oil cake-based organic fertilizer improved microbial diversity and enhanced potential ecosystem functions related to bio-geochemical cycles, mineralization and plant growth promotion.

Maize is an important staple food crop in sub-Saharan Africa (SSA). However, the average grain yield on farmers’ fields falls considerably short of the demand of the region’s population. In addition, the normal endosperm maize widely consumed in SSA is deficient in vitamin A. Drought, a consequence of climate change, is a major constraint to maize production, resulting in seasonal low grain yield in farmers’ fields. The objectives of this study were to assess the performance of newly developed extra-early maturing provitamin A hybrids under managed drought and well-watered conditions, compare the outcomes of multiple trait base-index and multi-trait genotype-ideotype distance index selection procedures, and identify drought-tolerant hybrids with stable performance across contrasting environments for commercialization in SSA. One hundred and ninety provitamin A hybrids and six checks were evaluated under managed drought and well-watered conditions at Ikenne for two seasons between 2021 and 2023. A 14*14-lattice design was used for the field evaluations under both research conditions. Drought stress was achieved by the complete withdrawal of irrigation water 25 days after planting. Results revealed significant differences among the hybrids under drought and well-watered conditions. Grain yield, ears per plant, and plant aspect under managed drought were correlated to the same traits under well-watered conditions suggesting that the expression of these traits is governed by common genetic factors. Twenty-nine hybrids were identified as top-performing drought-tolerant hybrids by the multiple trait base index and multiple-trait genotype–ideotype distance index. Of the selected outstanding 29 hybrids, 34% were derived from crosses involving the tester TZEEIOR 197, demonstrating the outstanding genetic potential of this inbred line. Further analysis of the 29 selected hybrids revealed TZEEIOR 509 × TZEEIOR 197 as the hybrid that combined the most drought-tolerant adaptive traits. However, the hybrids TZEEIOR 526 × TZEEIOR 97, TZEEIOR 384 × TZEEIOR 30, TZEEIOR 515 × TZEEIOR 249, TZEEIOR 510 × TZEEIOR 197, TZEEIOR 479 × TZEEIOR 197, and TZEEIOR 458 × TZEEIOR 197 were identified as the most stable hybrids across drought and well-watered conditions. These hybrids should be extensively tested in multi-location trials for deployment and commercialization in SSA.

According to previous studies the median raphe region (MRR) is known to contribute significantly to social behavior. Beside serotonin, there are reports of a small population of dopaminergic neu-rons in this region. Dopamine is linked to reward and locomotion, but very little has been known about its role in the MRR. To address that, we first confirmed the presence of dopaminergic cells in the MRR of mice (immunohistochemistry, RT-PCR) and humans (RT-PCR). Next, we used chemogenetic technology in mice containing Cre enzyme under the promoter of the dopamine transporter (DAT). With the help of an adeno-associated virus, artificial receptors were expressed in the dopaminergic cells of the MRR (DAT-MRR). Four weeks later, extensive behavioral charac-terization started 30 minutes after the injection of the artificial ligand (Clozapine-N-Oxide). Stimu-lation of DAT-MRR decreased social interest without influencing aggression and with an increase in social discrimination. Additionally, inhibition of the same cells increased the friendly social be-havior during social interaction test. No behavioral changes were detected in anxiety, memory and locomotion. All in all, dopaminergic cells were present both in the mice and human MRR, and manipulation of dopaminergic neurons of the MRR elicited a specific social response.

The Australian tropical montane cloud forest (TMCF) is home to approximately 18 percent of the nation’s total vascular plant species. Over the past century, human activity and industrial development have caused global climate changes, posing a severe and irreversible danger to the entire land-based ecosystem, and WTWHA is no exception. The current average annual temperature of WTWHA in FNQ is 24 °C. However, in the coming years (by 2030), the average annual temperature increase is estimated to be between 0.5 and 1.4 °C compared to the climate observed between 1986 and 2005. Looking further ahead to 2070, the anticipated temperature rise is projected to be between 1.0 and 3.2 °C, with the exact range depending on future emissions. We identified 84 plant species endemic to the WTWHA in FNQ, which are already experiencing climate change threats. Few of these plants are used in herbal medicines. This study comprehensively reviewed metabolomics studies conducted on these 84 plant species until now toward understanding their physiological and metabolomics responses to global climate change. This review also discusses: i) recent developments in plant metabolomics studies that can be applied to study and understand the interactions of wet tropical plants with climatic stress, ii) medicinal plants and isolated phytochemicals with structural diversity, and iii) reported biological activities of crude extracts and isolated compounds.

Large datasets play a crucial role in the progression of surgical robotics, facilitating advancements in the fields of surgical task recognition and automation. Moreover, public datasets enable the comparative analysis of various algorithms and methodologies, thereby assessing their effectiveness and performance. The ROSMA (Robotics Surgical Maneuvers) dataset provides 206 trials of common surgical training tasks performed with the da Vinci Research Kit (dVRK). In this work, we extend ROSMA dataset with two annotated subsets: ROSMAT24, which contains bounding box annotations for instrument detection, and ROSMAG40, which contains high and low level gesture annotations. We propose an annotation method that provides independent labels for the right-handed tool and the left-handed tool. For instrument identification, we validate our proposal with a YOLOv4 model in two experimental scenarios. We demonstrate the generalization capabilities of the network to detect instruments in unseen scenarios. For gesture segmentation, we propose two label categories: high-level annotations that describe gestures at a maneuvers level, and low-level annotations that describe gestures at a fine-grain level. To validate this proposal, we have designed a recurrent neural network based on a bidirectional long-short term memory layer. We present results for four cross-validation experimental setups, reaching up to a 77.35% mAP.

This paper focus on the modeling and time-domain analyzing method of piecewise-smooth fractional-order circuit systems. Firstly, an analytical framework is constructed based on a generalized piecewise-smooth two-port impedance network model, which takes the topological characteristics of Dickson type switched-capacitor converters (SCCs) as examples, and considers the fractional-order characteristics of class-2 X7R ceramic capacitors, which are widely used in SCCs. Secondly, the time-domain analyzing method for such a piecewise-smooth fractional-order circuit system is developed, numerical solutions are obtained, and the influence of the fractional-order capacitor on the power conversion efficiency of the system are revealed. Finally, in order to validate the analysis, both numerical simulation and experiments are provided in the work, the results of which confirm that, the proposed fractional-order analytical framework can capture the power loss mechanism of piecewise-smooth fractional-order circuit systems more effectively than the traditional integer-order based approach, thus benefiting the design of circuit systems.

Antimony (Sb) has gained significance as a critical raw material (CRM) within the European Union (EU) due to its strategic importance in various industrial sectors, particularly in the textile industry for flame retardants and as a component of Sb-based semiconductor materials. Moreover, Sb is emerging as a potential alternative for anodes used in lithium-ion batteries, a key element in the Energy transition. This study focused on exploring the feasibility of identifying and quantifying Sb mineralizations through the spectral signature of soils using reflectance spectroscopy, a non-invasive remote sensing technique, and by employing deep learning algorithms such as Convolutional Neural Networks (CNNs). Common signal preprocessing techniques were applied to the spectral data, and the soils were analyzed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Despite achieving high R-squared values, the study faces a significant challenge of generalization of the model to new data. Despite the limitations, this study provides valuable insights into potential strategies for future research in this field.

This paper proposed a three-layer distributed simulation network architecture: 1. Distributed virtual simulation network, 2. Perception and control sub-network, and 3. Collaborative communication service network. This simulation architecture runs on a distributed platform. The platform can provide a unique virtual scenario and several simulation services to verify the individual robot system's basic perception, control, and planning algorithms and the distributed collaborative algorithms of heterogeneous multi-robot systems. Furthermore, we designed a simulation experiment scenario for classical heterogeneous robot systems such as unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs). At last, We gave a rough estimation model of the bandwidth.

Immune checkpoint inhibitors (ICI’s) are in the forefront of advanced Non Small Cell Lung Cancer (NSCLC) treatment. Still, only 27- 46% of patients respond to initial therapy with ICI’s and of those, up to 65% develop resistance within four years. After disease progression (PD), treatment options are limited, with 10% Objective Response Rate (ORR) to second or third-line chemotherapy. In this context, ICI rechallenge is an appealing option for NSCLC. Most data on the efficacy of ICI rechallenge are based on retrospective real-world studies of small, heavily pretreated, and heterogeneous patient groups. Despite these limitations, these studies suggest that ICI monotherapy rechallenge in unselected NSCLC patient populations who discontinued initial ICI due to PD is generally ineffective, with a median Progression-Free Survival (PFS) of 1.6-3.1 months and a Disease Control Rate (DCR) of 21.4%-41.6%. However, there is a subpopulation that benefits from this strategy, and further characterization of this subgroup is essential. Furthermore, immunotherapy rechallenge in patients who discontinued initial immunotherapy following treatment protocol completion and progressed after an immunotherapy-free interval showed promising efficacy, with a DCR of 75-81%, according to post-hoc analyses of several clinical trials. Future research of ICI rechallenge for NSCLC should focus on better patient stratification, to reflect the underlying biology of immunotherapy resistance more accurately.

Intense climate change and rapid urbanization have increased the risk of urban flooding, seriously affecting urban economic and social stability. Enhancing the urban flood resilience (UFR) has required a new solution to cope with urban flood disasters. In this study, taking Yingtan city as an example, a system of indicators for evaluating UFR was constructed, with 17 representative indicators, comprising three subsystems: socio-economic, ecological and infrastructural. A hybrid (FAHP-EWM)-TOPSIS model was applied, to develop an index-based measurement to compare and evaluate UFR, and Gray Relational Analysis (GRA) was used to discover the main factors affecting UFR. In addition, the natural discontinuous method was innovatively used to divide the UFR grade interval into levels, and the grade change was evaluated based on the TOPSIS method. The results showed that (1) from 2010 to 2022, the UFR in Yingtan City increased by 80.69%, and the factors affecting UFR are highly correlated with urban infrastructure development. However, the ecological resilience in the subsystem showed a fluctuating downward trend, because of the influence of the surface area of lakes and rivers. (2) The grades of UFR for Yingtan City increased from Level III (2010 and 2016) to Level IV (2022), with local financial expenditures and the age structure of the population being the main factors currently limiting the development of UFR. The study provides a theoretical basis for the construction of an indicator system for assessing the UFR of Yingtan and proposes practical improvement directions for UFR.

The theory and working principle of fabric phase sorptive extraction (FPSE) is presented that eloquently explains the mystery behind this new and powerful sample preparation technique. FPSE innovatively integrates the benefits of sol-gel coating technology and the rich surface chemistry of cellulose/polyester/fiberglass fabric, resulting in a microextraction device with very high sorbent loading in the form of an ultra-thin coating. This porous sorbent coating and the permeable substrate synergistically facilitate very fast extraction equilibrium. The flexibility of the FPSE device allows for direct insertion into original, unmodified samples of different origin. Strong chemical bonding between the sol-gel sorbent and the fabric substrate permits the exposure of FPSE devices to any organic solvent for analyte back-extraction/elution and to highly acidic or basic environments (pH 1-12) if required. A sol-gel derived sorbent, highly polar sol-gel poly(ethylene glycol) coating, was generated on cellulose substrates. Five cm2 segments of these coated fabrics were used as the FPSE devices for sample preparation using direct immersion. An important class of environmental pollutants, substituted phenols, was used as model compounds to evaluate the extraction performance of FPSE. The high primary contact surface area (PCSA) of the FPSE device and porous structure of the sol-gel coatings resulted in very high sample capacities and incredible extraction sensitivities for both the compound classes in a relatively short period of time. Different extraction parameters were evaluated and optimized. The new extraction devices demonstrated part per trillion level detection limits for substitute phenols, a wide range of detection linearity, and good performance reproducibility.

In this study, a new type of temperature sensor device was developed. The circular electrode of the thermal sensitive sensor was modified with TMT and O₂ plasma to enhance the conductivity by forming a thin SnOxCy layer on the electrode surface. The Nano-Au particles were subjected to O₂ plasma pretreatment to form peroxide groups on the surface. The thermally sensitive sensor was made by mixing the above-treated Nano-Au particles with N-isopropylacrylamide (NIPAAm) to form solution and then UV-induced grafting polymerization of the NIPAAm-containing solution onto the electrode substrate. The composite hydrogels on the electrode introduce thermo-sensitive polymeric surface films for temperature sensing. Using ambient environment resistance test to measure the resistance, the LCST (lower critical solution temperature) of Nano-Au (MUA) mixed with NIPAAm hydrogel was found to be 32 °C. At ambient temperatures higher than LCST, the electrode resistance decreases linearly.

In this paper, a method is developed for presenting a novel virtual torque sensor based on precise model and position measurements avoids the need of traditional strain gauges and amplifiers. More specifically, the harmonic drive compliance model and the Gaussian process regression (GPR) technique are used together to achieve virtual torque sensor measurement. While the harmonic drive compliance model provides the analytic part, the Gaussian process regression method is used to reconstruct the unmolded part based on motor-side and link-side joint angles as well as motor current. After an automatic offline calibration, the method allows for a lean online implementation. The virtual torque sensor measurement is compared with measurements of a commercial torque sensor, and the results have attested the effectiveness of the proposed method.

This study analyses regional development in one of the poorest provinces in China, Guizhou Province, between 2000 and 2012 using a multiscale and multi-mechanism framework. In general, regional inequality has been declining since 2000. In addition, economic development in Guizhou Province presented spatial agglomeration and club convergence, which shows how the development pattern of one core area, two-wing areas and a contiguous area at the edge of the province have been developed between 2006 and 2012. Multilevel regression analysis revealed that industrialization and investment level were the primary driving forces of regional economic disparity in Guizhou Province. The influences of marketization and decentralization on regional economic disparity were relatively weak. Investment level reinforced regional economic disparity and the development of core-periphery structure in the province. However, investment level actually weakened the regional economic disparity in Guizhou Province when the variable of time was considered. In addition, both the topography and urban–rural differentiation were the two main reasons for forming a core-periphery structure in Guizhou Province.

We present a very computationally light and fast approximation algorithm and then verify it with genetic algorithm and simulated annealing. We show that our algorithm is on par with GA and SA in terms of output produced while having a tightly bounded time complexity. Our algorithm works best when there is a strong positive correlation between the reliability of a component and its cost. We present two algorithms with the same essence. One of them is system cost bounded and the other is target reliability bounded. Our proposed algorithm works on a subsystem level redundancy instead of component level redundancy.

The key towards a sustainable future is the reduction of mankind’s impact on natural systems via the development of new technologies and the improvement of source apportionment. Though days, years and seasons are arbitrarily set, their mechanisms are based on natural cycles driven by Earth’s orbital periods. This is not the case for weeks, which are a pure anthropic category and are known from literature to influence emission cycles. For the first time since it started data gathering operations, CO (carbon monoxide), CO₂ (carbon dioxide), CH₄ (methane) and eBC (equivalent black carbon) values detected by the Lamezia Terme WMO/GAW station in Calabria, Southern Italy have been evaluated via a two-pronged approach accounting for weekly variations in absolute concentrations, as well as the number of hourly averages exceeding select thresholds. The analyses were performed on seven continuous years of measurements, from 2016 to 2022. Moreso, the two results have been combined into a new parameter: the hereby defined WDWO (Weighed Distribution of Weekly Outbreaks) normalizes weekly trends of CO, CO₂, CH₄ and eBC on an absolute scale as percentages, with the scope of providing regulators and researchers alike with a new tool meant to better evaluate anthropogenic pollution and mitigate its effects.

Aedes albopictus is considered one of the major invasive species in the world and can transmit viruses such as dengue, Zika, or chikungunya. The Sterile Insect Technique (SIT) can be used to suppress the native populations of Ae. albopictus. To support the development of the release strategy during the SIT application, Mark-Release-Recapture (MRR) studies are crucial. Mean-while, weather conditions can affect the MRR trial’s results and it is critical to understand the influence of climatic factors on the results. In October 2022 in Faro, Southern Portugal, 84,000 ir-radiated sterile males were released for three consecutive weeks and mosquitoes were recapture by Human Landing Collections (HLC) one, two, four and six days after. Generalised linear models with a negative binomial family and log function were used to estimate the factors asso-ciated with the number of recaptured mosquitoes, prevalence ratios, and the 95% confidence in-tervals (CI). A total of 84,000 sterile male mosquitoes were released, with 528 recaptured (0.8%) by HLC. The prevalence of recaptured mosquitoes was 23% lower when the wind intensity was moderate. Sterile-marked males had an average median distance travelled of 88.7 m. Median probability of daily survival and the average life expectancy were 61.6% and 2.1, respectively. Wild male population estimates was 443.33 males/ ha. Despite no statistically significant asso-ciation was found with humidity, temperature and precipitation, it is crucial to consider weather conditions during MRR trials analyses to obtain the best determinants estimation and a more ef-ficient application of SIT in an integrated vector management program.

Introduction: Despite its high prevalence and impact on health, metabolic dysfunction-associated steatotic liver disease (MASLD) is inadequately addressed in European primary care (PC), with a large proportion of cases going undiagnosed or diagnosed too late. A multi-country European re-search consortium led a project to design and evaluate a patient-centered, integrated model for MASLD screening, diagnosis and linkage to specialty care for European PC settings. Aim: Based on the lessons from this project, the latest research evidence and existing guidelines for the management of MASLD, we sought to develop a set of practice recommendations for screening, referral and management of MASLD in PC. Methods: The Rand/UCLA modified Delphi panel method, with two rounds, was used to reach consensus on practice recommendations. The international panel consisted of experts from six countries, representing family medicine, gastroenterology, hepatology, cardiology and public health. Initially, fifteen statements were drafted based on a synthesis of evidence from the literature and earlier findings from our consortium. Prior to the consensus meeting, the statements were rated by the experts in a first round. Then, in a hybrid meeting, the experts discussed findings of round one, adjusted the statements and reassessed the updated recommendations in a second round. Results: In round one, there was already a high level of consensus on 10 out of 15 statements. After round 2, there were fourteen statements with a high agreement (>90%). One statement was not endorsed. The approved recommendations addressed the following practice areas: risk screening and diagnosis, management of MASLD – Lifestyle interventions, pharmacological treatment of MASLD/MASH, pharmacological treatment for co-morbidity, integrated care, surgical management and other referrals to specialists. Conclusion: The final set of 14 recommendations focuses on increasing comprehensive care for MASLD in PC. The recommendations provide practical evidence-based guidance tailored to PC practitioners. We expect that these recommendations will contribute to the ongoing discussion on systematic approaches to tackle MASLD and support European PC providers by integrating the latest evidence into practice.

Clinical microbiology studies and systematic reviews have largely concluded that SARS-CoV-2 RNA is rarely present in the urine of COVID-19 patients. Thus, wastewater surveillance has largely focused on human stool and defecation as the relevant matrix and behavior. But, the over-performance of wastewater testing during near-source surveillance, especially in settings where on-site defecation is presumed to be de minimis such as aircraft and non-residential schools, suggests the possibility of SARS-CoV-2 RNA input from a non-fecal source. To revisit the possibility of urine as an explanation, data was compiled from 45 studies reporting on SARS-CoV-2 RNA in the urine of 1,924 COVID-19 patients. In general, the reporting quality was low with most studies (86.7%) failing to report even basic details such as the volume of urine collected. Only 11 reported quantitative data and of these only a single study reported its experiments to the standards established for publication of quantitative PCR data. Taking the data at its face value, the pooled prevalence of urinary SARS-CoV-2 RNA shedding was 11.3% (95%CI: 8.4 - 14.3), which roughly agrees with previous analyses. However, the percentage of variability in the estimate attributable to heterogeneity between studies (I² = 93.66%) warrants careful consideration. Notably, for the 8 studies reporting sufficient workflow information, the observed urinary RNA shedding prevalence was normally distributed (r² = 1.00) as a function of the volume of urine being assayed in a single PCR reaction (i.e., the equivalent sample volume, ESV). The study achieving the highest ESV (83.3 µL of urine) detected SARS-CoV-2 RNA in urine sediments of 95.5% of COVID-19 patients. Conversely, during two studies achieving ESVs of only 2 µL and 11.7 µL of urine, SARS-CoV-2 RNA was not detected in the urine of 72 and 132 patients, respectively. For wastewater surveillance of COVID-19, these observations suggest the rarity of SARS-CoV-2 RNA in urine may be a methodological artifact. Further, the data on which rarity is presumed are of low quality. Beyond COVID-19, the findings demonstrate that clinical studies, by virtue of their design to answer clinically relevant questions, could produce datasets subject to large biases that make them less useful when assessing the feasibility of wastewater surveillance of infectious agents. Wastewater surveillance practitioners must carefully consider the appropriateness and limitations of clinical data considering the important differences between the methods and aims of the two disciplines. Given the great potential of wastewater testing, clinical and environmental microbiologist should collaborate to produce robust quantitative datasets for reliable feasibility assessments for both community and near-source public health surveillance.

Sleep deprivation is an increasing problem in the modern age. While molecular theories on the mechanism of sleep are still developing, sleep’s importance for cognitive function and physical health has been well reported. In the past 2 decades, major advances in the genetics of sleep have been made. Among families of natural short sleepers averaging around 4-6 hours nightly, mutations on 4 genes (DEC2, ADRB1, NPSR1, and GRM1) have been associated with significantly shorter sleep without observed cognitive or health detriments. Studies in mice have further established causality of these mutations as well as finding increased resistance to neurodegeneration. Yet, despite these promising results, there is a current lack of studies investigating potential chronic risks of sleep deprivation, particularly physical and physiological effects that may not be apparent. For circadian repressor element DEC2, circadian dysregulation risks should be evaluated further. For adrenergic receptor ADRB1, cardiovascular and heart failure risks would be of interest. For NPSR1, asthma and other immune responses, as well as mood disorders are relevant. For the currently least studied G-protein receptor GRM1, its altered regulation of the extracellular signal-regulated kinase (ERK) pathway could result in developmental and proliferation effects. While these familial natural short sleep genes hold potential for our understanding of sleep and therapeutic development, it is critical not to overdraw conclusions. By investigating the possible downstream effects, one can be aware of the potential risks of natural short-sleep genetics, better understand the mechanisms of sleep, and advance research in reducing the harms of sleep deprivation.

We propose a new approach to extending the notion of commutator and Lie algebra to algebras with ternary multiplication laws. Our approach is based on ternary associativity of the first and second kind. We propose a ternary commutator, which is a linear combination of six (all permutations of three elements) triple products. The coefficients of this linear combination are the cube roots of unity. We find an identity for the ternary commutator that holds due to ternary associativity of the first or second kind. The form of the found identity is determined by the permutations of the general affine group GA(1,5)⊂S5. We consider the found identity as an analogue of the Jacobi identity in the ternary case. We introduce the concept of a ternary Lie algebra at the cubic root of unity and give examples of such an algebra constructed using ternary multiplications of rectangular and three-dimensional matrices. We point out the connection between the structure constants of a ternary Lie algebra with three generators and an irreducible representation of the rotation group.

We investigate solutions of the classical Mathieu-Hill (MH) equation which characterizes the dynamics of trapped ions, based on the Floquet theory and starting from a well known analytical model. The analytical model we introduce demonstrates that the equations of motion are equivalent to those of the harmonic oscillator (HO). Two independent approaches are used, based on two classes of complex solutions of the MH equation. The paper addresses both the damped HO and parametric oscillator (PO) for an ion confined in an electrodynamic (Paul) trap. Stability and instability regions for the periodic orbits associated to the MH equation which describes a HO (PO) confined in an electrodynamic trap are also discussed, depending on the values of the Floquet exponent, for very small values of the $q$ parameter. The main objective of the paper is to identify stable and bounded solutions for the dynamics of a HO levitated in an electrodynamic trap. This paper represents a follow-up of a recently published article in Photonics, 11 (6) 551.

Particulate Organic Carbon (POC) plays a crucial role in the marine carbon cycle, influencing carbon flux and many important ocean biogeochemical processes in the Bay of Bengal. The purpose of this study was to examine the seasonal and annual variability of POC in the Bay of Bengal (BoB) region and its correlation with Sea Surface Temperature (SST) and Chlorophyll-a (Chlor_a). This study uses level-3 POC, Chlor_a, and SST data from the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua satellite. The surface POC concentration in the Bay of Bengal declined at a rate of -1.30 mgm^-3y^-1 over a ten-year period (2003-12) and ranged from 86.48 mgm^-3 to 110.93 mgm^-3 with an average of (93.74±7.50 mgm^-3). Seasonally, the mean POC was highest (97.40 mgm^-3) during the post-monsoon (October-November) and lowest (79.36 mgm^-3) in the pre-monsoon (March-May). Seasons were observed to have statistically significant differences in POC concentration in the study area (F_(3,2155) = 6.298; p <0.05). A strong positive correlation between POC and Chlorophyll was observed whereas a week positive correlation between POC and SST was observed. POC was observed to be very prominent in post-monsoon (97.40 mgm^-3) and in northeast-monsoon (97.14 mgm^-3) and moderate to low in southwest (81.12 mgm^-3) and pre-monsoon (79.36 mgm^-3). The Bay of Bengal’s annual mean POC:Chlor_a ratio ranged from 97.56 mgm^-3 to 332.89 mgm^-3, indicating a significant impact of biological processes on POC composition. To see how POC fluctuation affects biogeochemical processes in the Bay of Bengal, deeper investigation is required.

Background: Among the cognitive markers of Alzheimer’s disease (AD), semantic and phonemic verbal fluency tasks seem to be an early indicator of deterioration. The aims of this study are 1) to evaluate both types of Verbal Fluency in the early stages of AD in order to know which of them deteriorates earlier and, 2) to investigate if Verbal Fluency Tasks can help to differentiate between patients with Mild Cognitive Impairment (MCI) who will progress to AD two years later (progresses) and those who do not (non-progresses). Method: A Verbal Fluency Task was administered to 25 patients with MCI and their respective control subjects. All patients underwent a neuropsychological evaluation twice in order to follow up their global cognitive status. The second time, 8 of them converted to AD. Results: On the one hand, Phonemic Verbal Fluency deteriorates earlier than Semantic Verbal Fluency in MCI patients; on the second hand, although we found statistically significant differences between patients with MCI and AD in both type of fluency tasks, they were not found when comparing the performance of progresses and non-progresses. Conclusion: These results point to a greater impairment in Phonemic Verbal Fluency in MCI patients and its potential predictive capacity to predict conversion to AD.

This study uses simulation and experimental methodologies to explore the efficacy of bi-sectional horizontal kinetic shading systems (KSS) featuring horizontal fins in enhancing daylight comfort across various climates. Given the increasing energy demands and shifting climatic patterns, optimizing daylight levels while minimizing solar heat gain is vital. The paper introduces a bespoke horizontal bi-sectional KSS, simulated in three distinct climates—Wroclaw, Tehran, and Bangkok—using Climate Based Daylight Modelling methods with Ladybug and Honeybee tools in Rhino software. The study employs standard daylight metrics such as Useful Daylight Illuminance (UDI) and Daylight Glare Probability (DGP), along with custom metrics designed to capture the specific dynamics of the bi-sectional KSS. Initial simulations indicated that the KSS significantly improved daylight distribution and uniformity, reducing glare and over-illumination risks by av. 42.34%. Including KSS switching schedules, which are seldom detailed in similar research, enhances the reproducibility and understanding of findings. Subsequently, a physical reduced-scale mock-up of the bi-sectional KSS was tested under real-weather conditions in Wroclaw (lat. 51° N) during June-July 2024. The mock-up utilized two chambers: one equipped with the prototype of bi-sectional KSS and the second without any protection. The operation of fins was guided by two stepper motors controlled by a Python script running on a Raspberry Pi 3 minicomputer. The control chamber served to benchmark the bi-sectional KSS's efficiency by providing results that would be expected if no shading system were installed. The experimental outcomes supported the simulations, demonstrating the KSS's robustness in reducing high illuminance levels to the target comfort level, thus enhancing indoor visual comfort. The values below 3,000 lux were maintained for 68% of the time. However, it must be explicitly stated that during the June-July 2024 heat waves, the illuminance levels inside the test room momentarily exceeded the comfort threshold of 3,000 lux, reaching up to 4,674 lux. Through quantitative and qualitative analyses, the paper advocates for the broader application and further development of KSS as a climate-responsive shading system in diverse architectural contexts.

The Great Reset has been presented by the World Economic Forum (WEF) in response to the COVID-19 pandemic in 2022 as a model through which a “stakeholder economy” would achieve “resilient, equitable and sustainable” economic, social and environmental goals. A more equitable distribution of resources, better working conditions, and ecological transitions are included in a social, economic and environmental reform agenda. This article raises the question of whether the Great Reset project should be interpreted as a “realistic utopia” and what is its reform potential. In an attempt to answer the question of whether the Great Reset as a realist utopia is consistent with the current state of science and philosophy, the article re-examines the idea of utopia in the light of recent philosophical and scientific approaches, such as critical realism in philosophy, so-cial systems theory in sociology and complexity theory in science. A comparative conceptual analysis is carried out and discussed introducing the idea of a realist utopia in Rawls' theory of justice as fairness. In the final discussion, some doubts are raised about the logical coherence, rigor of scientific theorizing, policy prescriptions, and predictive potential of the Great Reset emerging paradigm. It is concluded that utopian projects of radical reform can become realistic when they offer explanations of the deep structural changes that underlie social and economic evolution, drawing from these explanations the policy implications and prescription that can support struc-tural changes, rather than from assumed long-term effects of exogenous shocks or “black swan” events such as the COVID-19 pandemic.