Background and Objectives: High job strain is worsening the outcome in coronary artery disease, CAD. Severe dissatisfaction on workplace, imbalance between high demands , and low rewards, are affecting the quality of life, and diminishing the duration of life, especially in CAD patients. Our study included two samples : CAD patients (experimental group), and without CAD patients, but with traditional risk factors (control group). The main objective of the study was the role played by high sensitivity C reactive protein, hs CRP, and microalbuminuria, as mediators of job strain and CAD relationship. Secondary objectives were the following: identification of the most vulnerable patients( with significant job strain) and intervention towards this category, for cardiovascular events prevention (primary or secondary). Materials and Methods: The utilized methods were the following : clinical exam; electrocardiogram; echocardiogram; non contrast enhanced computed chest tomography; laboratory findings ( lipid profile, glycemia, hs CRP, microalbuminuria); type D scale, DS 14; depression questionnaire, PHQ-9; and satisfaction with work scale, SWWS. Results: The highest values for hs CRP and microalbuminuria were noticed in patients with the lowest Likert score, for both samples CAD, and without CAD patients. The highest job strain was noticed in females. More than half of CAD patients ,with low Likert scores, revealed myocardial infarction. Conclusions: Microalbuminuria and hs CRP were statistical significant in the study as intercessors, in job strain and CAD relationship. The most vulnerable patients for vascular events were females, in both groups : CAD and “CAD waiting desk”. In CAD sample, the vascular vulnerability was also increased by high job strain.

As the most serious of the many worse new pathological changes caused by diabetes, there are many risk factors for the occurrence and development of DR. It mainly includes hyperglycemia, hypertension, hyperlipidemia and so on. Among them, hyperglycemia is the most critical cause, which plays a key role in the pathological changes of DR.High-sucrose diets(HSDs) lead to elevated blood glucose levels in vivo, which, through oxidative stress, inflammation, the production of AGEs and VEGF, causes plenty of pathological damages to the retina and ultimately bring about loss of vision. The existing therapies for DR primarily target the terminal stage of the disease, when irreversible visual impairment has appeared. Therefore, early prevention is particularly critical. Early prevention of DR-related vision loss requires adjustments to dietary habits, mainly by reducing sugar intake. This article primarily discusses the risk factors, pathophysiological processes, and molecular mechanisms associated with the development of DR caused by HSDs. It aims to raise awareness of the crucial role of diet in the occurrence and progression of DR, promote timely changes in dietary habits, prevent vision loss, and improve the quality of life. The aim is to make people aware of the importance of diet in the occurrence and progression of DR. According to the dietary modification strategies we give, patients can change their poor eating habits timely, avoid the retinopathy that can be avoided theoretically, and obtain a excellent outcome.

Background/Objectives:The first attempts of posterior lumbar interbody fusion can be traced back to the 1940s, where their performance was marked by animosity due to high rates of failure. Nowadays, the use of interbody fusion involves a much more complicated consideration of factors such as global alignment, disc height, fusion rates, and operative risk, all combined at once.Our study aims to examine all these effects using Flarehawk 9 as a means of interbody fusion.Materials and methods: A total of 58 patients underwent open posterior lumbar surgery using Flarehawk 9 between September 2021 and February 2023 with a mean follow up of 1 year.The mean age was 59.8 years old ( range between 33 and 79 years old), 36 of them are males while 22 of them are females. The diagnostic groups included spinal canal stenosis (n=40), failed back surgery syndrome-revision surgery (n=5),spondylolisthesis with slip percentage 25% (n=4),recurrent herniated disc (n=7) and adjacent segment disease (n=2). Results: The majority of patients demonstrated remarkable improvement based on ODI scores.The rate of union varied based on the fused levels and whether the patients had previous surgery or not.The amount of lordosis postoperatively is increased by 2±0.4 degrees.Conclusions: Even though anterior approaches become more and more popular and advanced nowadays, posterior fusion with interbody cage still remains a safe and effective method to treat various spine surgical pathologies with optimal results.

In the drive towards environmental restoration and sustainable energy solutions, effective utilization and management of agricultural crop residues are vital to mitigate greenhouse gas (GHG) emissions and waste accumulation. Converting biogenic wastes into biofuels and bioproducts has the potential to tackle the energy crisis and contribute to environmental remediation. In this investigation, teff husk, primarily generated in Ethiopia during teff production within the agro-industrial sector, is used as the feedstock for the slow pyrolysis process. In Ethiopia, it is estimated that over 1.75 million tons of teff husk are generated annually, with a significant portion being incinerated in the fields, resulting in substantial environmental pollution. This study focuses on assessing teff husk as a potential material for slow pyrolysis, a crucial stage in biochar production, to tap into its biochar-producing potential. To determine the composition of the biomass, the teff-husk was initially analyzed by thermogravimetry. The significant presence of fixed carbon indicates that teff husk is a viable candidate for pyrolytic conversion into biochar particles. The process of slow pyrolysis took place at three varied temperatures—specifically, at 400, 450, and 500 °C. Process parameters of slow pyrolysis such as reaction time, temperature, and heating rate were enhanced to obtain maximum biochar yields. The highest biochar yield of 43.4 wt% was recorded at optimized reaction time, temperature, and heating rate of 120 min, 400 °C, and 4.2 °C/min, respectively. Furthermore, biochar's physicochemical, SEM-EDX, FTIR, and TGA characterization were performed. The thermal stability and carbon content of biochar were found to rise at higher temperatures. Unlike fuel recovery, the results suggest that teff-husk can be used as a feedstock for biochar production.

Heart failure is a prevalent cardiovascular condition with significant health implications, necessitating effective diagnostic strategies for timely intervention. This study explores the potential of continuous monitoring of non-invasive signals, specifically integrating Photoplethysmogram (PPG) and Electrocardiogram (ECG), for enhancing early detection and diagnosis of heart failure. Leveraging a dataset from the MIMIC-III database, encompassing 682 heart failure patients and 954 controls. Feature selection techniques were used to systematically select key features which were identified for their clinical relevance and significance in capturing cardiovascular dynamics and to reduce computational complexity and to decrease the chance of overfitting the ML algorithms. These features are then utilized to train and evaluate machine learning algorithms, resulting in a model with an impressive accuracy of 98%, sensitivity of 97.60%, specificity of 96.90%, and precision of 97.20%. The integrated approach outperforms single-signal strategies, showcas-ng its potential for early, precise, and non-invasive heart failure diagnosis. Furthermore, the study underscores the significance of continuous monitoring through wearables, emphasizing the benefits of integrating multiple signals for a comprehensive evaluation of cardiovascular health. The proposed approach holds promise for implementation in hardware systems to enable continuous monitoring, aiding in early detection and prevention of critical health conditions.

An eight-sided prism sample, obtained from a hot-rolled AZ31 magnesium alloy sheet, was compressed at room temperature along the transverse direction to investigate the influence of local strain on twinning behavior using electron backscatter diffraction (EBSD) measurements. The octagonal surface of the sample was divided into distinct regions based on hardness distribution and metallographic observations. The EBSD maps of different areas show significant variations, suggesting that these areas experienced different local strain conditions. The EBSD measurements provided detailed data from three distinct regions, with the strain state known in two regions and uncertain in the third. The combined analysis of the Schmid factor (SF) and the strain compatibility factor (m') was employed to study twin variant selection. The comparison of twinning behavior in different regions showed that the strain compatibility factor offered a more comprehensive explanation for the observed twinning pattern in the region with local shear strain.

Biodiversity has become an issue of global anxiety over the past decades due to its rapid decline worldwide. Bangladesh as one of the most densely populated countries in the world is no more exception. The country, although, was once very rich in biodiversity, during the last few decades as a consequence of the rapid reduction in forest area, urbanisation, habitat modification, unsustainable natural resources use and collection and overall climate change it has decreased alarmingly. Of late, the government, as a signatory of various regional and international conservation treaties, has taken various initiatives to improve country’s dwindling biodiversity. This paper reviews the present situation of biodiversity in Bangladesh, management trends and major causes of biodiversity loss. A separate statutory body is fundamental to ensure conservation, sustainable use and equitable sharing of benefits arisen from biodiversity in the country.

Despite of being an exceptionally biodiversity rich country, the forest coverage of Bangladesh is declining at an alarming rate. Declaration and management of protected areas in this regard is one of the efforts from government side to tackle the loss of biodiversity. The limited numbers of forest-protected areas (FPA), established to conserve the dwindling forest biodiversity of the country with high pressure on them for timber, non-timber forest products, and fuelwood - makes their management challenging. Moreover, most of the FPAs of the country declared only in the recent decades with very limited infrastructure, manpower and policy support for monitoring and governance. Some people-centred approaches for the management of FPAs and alternative livelihood and income generation subsidies although made available through a few project interventions, their number are still inadequate and performance remains less than satisfactory. This chapter provides a critical review of the FPAs of Bangladesh looking at their role in biodiversity conservation, management challenges, and key lessons from previous management interventions with recommendations for the future. It has been revealed that the FPA system of Bangladesh still poorly represents the diverse forest ecosystems with relatively small forest size and lack of corridors for the movement of wildlife. There are ample opportunities to render co-management of FPAs an effective strategy to minimize the conflicts in FPAs management in the country. It is, however, important to ensure the access of local forest-dependent people to different alternative income generating options that may adequately support their livelihoods.

Motion related human activity recognition using wearable sensors can potentially enable various useful daily applications. So far, most studies view it as a stand-alone mathematical classification problem without considering the physical nature of human motions. Consequently, they suffer from data dependencies and encounter the dimension disaster problem and the over-fitting issue, and their models are never human-readable. In this study, we start from a deep analysis on natural physical properties of human motions, and then propose a useful feature selection method to quantify each feature's classification contribution capability. On one hand, the "dimension disaster" problem can be avoid to some extent, due to the affined dimension of key features; On the other hand, over-fitting issue can be depressed since the knowledge implied in human motions are nearly invariant, which compensates the possible data inadequacy. The experiment results indicate that the proposed method performs superior to those adopted in related works, such as decision tree, k-NN, SVM, neural networks.

Caveolin is a structural protein within caveolae, which may be involved in transmembrane molecular transport and/or various intercellular interactions within cells. Specific mutations of caveolin-3 in muscle cells are well-known to cause a limb-girdle muscular dystrophy. Altered expression of the caveolin-3 has been also detected in Duchenne's muscular dystrophy, which may be a part of the pathological process leading to muscle weakness. Interestingly, it has been shown that the renovation of nitric oxide synthase (NOS) to the sarcolemma with muscular dystrophy could improve the muscle health, suggesting that NOS may be involved in the pathology of muscular dystrophy. Here, we summarize the notable function of caveolin and/or NOS in skeletal muscle cells, and would like to discuss about their involvement in the pathology as well as possible tactics for the innovative treatment of muscular dystrophies.

Underwater imaging presents unique challenges, notably color distortions and reduced contrast due to light attenuation and scattering. Most underwater image enhancement methods, first use linear transformations for color compensation and then enhance the image. We observed that linear transformation for color compensation is not suitable for certain images. For such images, a non-linear mapping is a better choice. Our paper introduces a unique underwater image restoration approach leveraging a streamlined convolutional neural network (CNN) for dynamic weight learning for linear and non-linear mapping. In the first phase, a classifier is applied that classifies the input images into Type-I or Type-II. In the second phase, depending on the classification, the Deep Line Model (DLM) for Type-I images or the Deep Curve Model (DCM) for Type-II images. For mapping an input image to an output image, DML creatively combines color compensation and contrast adjustment in a single step and uses deep lines for transformation, whereas DCM employs higher-order curves. Both models utilize lightweight neural networks that learn per-pixel dynamic weights based on the input image’s characteristics. Comprehensive evaluations on benchmark datasets using metrics like peak signal-to-noise ratio(PSNR) and root mean squares error (RMSE) affirm our method’s effectiveness in accurately restoring underwater images, outperforming existing techniques.

The use of chimeric antigen receptor (CAR) in natural killer (NK) cells for cancer therapy is gaining momentum, marking a significant shift in cancer treatment. This review aims to explore the potential of CAR-NK cell therapy in cancer immunotherapy, providing a fresh perspective. It discusses the innovative approaches in CAR-NK cell design and engineering, particularly targeting refractory or recurrent cancers. By comparing CAR-NK cells with traditional therapies, the review highlights their unique ability to tackle tumor heterogeneity and immune system suppression. Additionally, it explains how novel cytokines and receptors can enhance CAR-NK cell efficacy, specificity, and functionality. The review underscores the advantages of CAR-NK cells, including reduced toxicity, lower cost, and broader accessibility compared to CAR-T cells, along with their potential in treating both blood cancers and solid tumors.

The application of antimicrobials in aquaculture primarily aims to prevent and treat bacterial infections in fish. Inappropriate use of antimicrobials in fish farming may result in the emergence of zoonotic antibiotic-resistant bacteria and subsequent transmission of resistant strains to humans via food consumption. From recently, AMR emerged as a significant public health concern in the aquaculture ecosystem and fisheries. The aquatic environment serves as a potential reservoir for resistant bacteria, with aquaculture practices providing an ideal breeding ground for AMR due to the excessive use of antimicrobials to prevent and treat diseases. The mutual inter-connection of intensive fish farming systems with terrestrial environments, food processing industry and human population creates pathways for the transmission of resistant bacteria, exacerbating the problem further. One Health concept, which recognizes the interconnectedness of human, animal and environmental health, enables a holistic approach to address the challenges posed by AMR. By understanding the evolution of such approach, the future of aquaculture, being the important source of a global animal protein supply, can be safeguarded. Risk mitigation strategies for AMR should be based on One Health concept to contribute to sustainable aquaculture practices that protect human and animal health, ensure food safety and protection of environment.

This paper presents an on-device semi-supervised human activity detection system that can learn and predict human activity patterns in real time. The proposed semi-supervised learning (SSL) framework uses sparsely labelled user activity events acquired from Inertial Measurement Unit (IMU) sensors installed as wearable device. The objective is to learn classification of multiple classes of human activities in real-time. The proposed cluster-based learning model in this approach is trained with data from the same target user, thus preserving data privacy while providing personalized activity detection services. Two different cluster labelling strategies, namely, population-based, and distance-based, are employed to achieve the desired classification performance. A comparative study of these strategies has been presented in terms of classifiability and classification accuracies. The proposed system is shown to be computationally efficient, which is relevant in the context of limited computing resources on typical wearable devices. The trade-off between classification accuracy and computation complexity is analyzed for different algorithmic hyper-parameters and other system parameters. Extensive experimentation and simulation study have been conducted on a multi-user human activity data from the public do-main in order to validate the proposed learning paradigm.

Inflammatory bowel disease (IBD) is characterized by chronic inflammation of the gastrointestinal tract and encompasses two main subtypes, Crohn’s disease (CD) and ulcerative colitis (UC). IBD is frequently accompanied by extraintestinal manifestations (EIMs), with axial and peripheral spondyloarthritis (SpA) being the most common. Enthesitis, an inflammation of the bone insertions of capsules, ligaments, and tendons, represents an initial lesion in SpA. However, enthesitis remains an underestimated and often obscured EIM. The early detection of subclinical enthesial involvement in IBD patients using ultrasound (US) could provide an opportunity for timely intervention. While previous meta-analyses have reported on the incidence and prevalence of SpA in IBD, specific attention to enthesitis has been lacking. Therefore, this narrative review aims to resume the current knowledge on existing IBD-SpA cohorts, focusing specifically on enthesitis.

Pore structure characterization and fractal analysis have great significance for understanding and evaluating tight limestone reservoirs. In this work, the pore structure of tight limestone is characterized combined with low-temperature nitrogen adsorption (LTNA) and low-field nuclear magnetic resonance (NMR), and the fractal dimension of tight limestone pore structure is discussed based on LTNA and NMR data. The results indicate that the pores of tight limestone have H3 and H4 types, the pore size distribution (PSD) of H3 type is a wave distribution ranging from 2 to 10 nm, and the PSD of H4 type is a unimodal distribution ranging from 2 to 10 nm. The transverse relaxation time (T2) spectrum of tight limestone shows single peak (DF), double peak (SF) and three peak (TF), and the T2 spectrums for micropores, mesopores and macropores range from 0.1 to 10 ms, from 10 to 100 ms, and greater than 100 ms, respectively. The LTNA fractal dimension of tight limestone (DL) ranges between 2.4446 and 2.7688, with an average of 2.5729, and the NMR fractal dimensions of micropores (DNMR1), mesopores (DNMR2) and macropores (DNMR3) are distributed between 0.3744 to 1.1293, 2.4263 to 2.9395 and 2.6582 to 2.9989, respectively. Moreover, there is no correlation between fractal dimension and permeability and porosity, a negative correlation between DL and average pore radius, a positive correlation between DL and specific surface area, and a positive correlation between DNMR2 and DNMR3 and micropore content, while DNMR2 and DNMR3 are negatively correlated with the content of mesopores and macropores.

The object of study in the article is the auxiliary variable-frequency electric drive onboard of an AC electric locomotive, and more precisely, the structure and parameters of the control system of the active corrector of power factor (ACPF), which is part of the electric drive, as a unit that ensures electromagnetic compatibility of the electric drive with other equipment on board the electric locomotive and catenary and its energy efficiency. The topic of the article's research is the substantiation of the structure of the ACPF control system, the choice of types (transfer functions) of controllers and the calculation of their parameters. The research method chosen was the calculation of the transfer functions of the controllers of the cascaded loops control system, followed by computer simulation using the OrCAD software. The results of simulating a cascaded two loops control system of an ACPF with different types of controllers are presented and analytically compared. It is concluded that it is advisable to use a cascaded two loops control system, containing a voltage control loop and a current control loop. The best results show the simulation when using an aperiodic current controller (A-controller) and a proportional-integral voltage controller (PI-controller). The data obtained serve as the basis for further improvement of the operation of the ACPF by enhancing and optimizing the settings, structure and algorithms of the control system, which, with the selected hardware of power converter unit, will allow the ACPF to perform its functions with a high degree of reliability in an entire range of disturbing and control influences.

Estrogen receptor-positive (ER+) breast cancer is common among postmenopausal women and is frequently treated with Letrozole. Letrozole inhibits aromatase from synthesizing estrogen from androgens. Decreased estrogen slows the growth of tumors and can be an effective treatment. Letrozole resistance is increasingly being observed, which poses a unique problem for patients. We reanalyzed transcriptomic data comparing individuals who responded to Letrozole therapy (responders) to those who were resistant to treatment (non-responders). We identified SOX11 and S100A9 as two genes that significantly differed between these patients; with “PLK1 signaling events” being the most significant signaling pathway. We also identified PRDX4 and E2F8 as the top transcriptional biomarkers for ER+ treatment resistance. Many of the other significant gene products play a known role in ER+ breast cancer or other types of cancer, which partially validate our results. Several of the gene products we identified do not have a characterized role in ER+ breast cancer. Our analysis identified a set of genes that warrant further research to elucidate the molecular mechanism of Letrozole resistance in this patient population, as well as novel high-performing biomarkers. We anticipate that these findings could contribute to improved therapeutic outcomes in human patients.

The present study explored whether exposure to complex childhood trauma (CCT) is reflected in the resting-state electroencephalography (EEG) temporal alpha power of complex trauma-exposed adolescents, given the association of temporal alpha with fear circuitry (learning and conditioning) in a sample of 25 adolescents and similar controls, ages 12-17 years. Both trauma and psychopathology were screened or assessed, and resting-state EEG was recorded, following a preregistered protocol for data collection. Temporal alpha power, corresponding to T5 and T6 electrode location (10-20 international system), was extracted from resting-state EEG in both eyes-open and eyes-closed conditions. We found that in the eyes-open condition, right, but not left, temporal alpha was significantly higher in adolescents exposed to CCT, relative to healthy controls, suggesting that childhood trauma exposure may have a measurable impact on alpha oscillatory patterns, specifically in the right temporal region. Our study highlights the importance of considering neural markers, such as temporal alpha power, in understanding the long-term consequences of CCT exposure in developmental samples, with possible important clinical implications in guiding neuroregulation interventions.

Atopic dermatitis (AD) is a chronic inflammatory condition which significantly affects quality of life in both patients and their caregivers. Calcineurin inhibitors (CNI) are a class of immunosuppressive drugs predominantly inhibiting T cell mediated immune processes. CNI form complex by binding with immunophilins and in turn inhibit calcineurin and suppress downstream inflammatory pathway. Tacrolimus and pimecrolimus are topical CNI approved for the treatment of mild to severe AD in both children and adults. Application site reactions are frequently seen. They have been issued with black box warning towards increased risk of malignancies but supportive evidence is lacking. Cyclosporine, though highly effective, is used off-label for AD management. It is used for controlling acute flares of AD due to its very rapid onset of action. Nephrotoxicity and hypertension are its serious complications. CNI have not been reported with teratogenicity and may be used conditionally during pregnancy and lactation.

Our aim is at three feels: i) study safe haven properties of sectoral CDS; ii) study hedging effectiveness and measure the diversification benefits of introducing them in both Conventional and Islamic stock markets portfolios and iii) compare these results with VSTOXX, Gold and Bitcoin indices. To do this, we estimate time varying hedge ratio using (A)DCC and GOGARCH models and then deduce hedging effectiveness.. We follow the same methodology for each sub-period and each refit to test the effect of bubble crypto currency and COVID-19 pandemic on hedging effectiveness. Empirical results show the superiority of industrial CDS sectoral index to hedge both conventional and Islamic stock markets whether long or short term despite that their performances were reduced slightly during the second and third periods. VSTOXX and Others sectoral CDS indices offers Hedging performances that are generally better than Bitcoin and gold.

This review provides a comprehensive and updated information on chalcones, presenting their sources, methods of identification and properties putting emphasis on applications in agricultural industry. Vast exploitation of synthetic pesticides led to the weed and pest resistance issue, causing economic loss but more importantly health risk due to pesticide overuse. Because one of the aim of the European Green Deal 2030 is the Farm to Fork strategy which targets on reducing by 50% the use of chemical pesticides by 2030, and push towards natural pesticides which are more environmentally friendly and restore natural resources, chalcones and their derivatives seem to fit perfectly. They have herbicidal, fungicidal, bactericidal and antiviral properties. Moreover, chalcones are naturally occurring substances, known for their favorable health effect for years, working on many areas. This review is complementary to the previous ones describing chalcones use in agriculture, updates them but additionally shows methods of detection.

Despite being stored at 113 K and atmospheric pressure, LNG cold potential is not exploited to reduce green ships’ energy needs. An innovative system based on three Organic Ranking Cycles integrated into the regasification equipment is proposed to produce additional power and recover cooling energy from condensers. A first-law analysis identified ethylene and ethane as suitable working fluids for the first and the second ORC making available freshwater and ice. Propane, ammonia and propylene could be arbitrarily employed in the third ORC for air-conditioning. An environmental analysis that combines exergy efficiency, ecological indices and hazard aspects for marine environment and ship’s passengers, indicated propylene as safer and more environmentally friendly. The exergy analysis confirms more than 20% of the LNG potential can be recovered from every cycle to produce a net clean power of 76 kW, whereas 270 kW can be saved by recovering condensers' cooling power to satisfy some ship needs. Assuming the sailing mode, a limitation of 162 kg in LNG consumptions was determined, avoiding the emission of 1584 kg of CO2 per day. Marine thermal pollution is reduced by 3.5 times by recovering the working fluids' condensation heat for the LNG pre-heating.

Background: Amyloid beta peptides (Aβ) have been identified as the main pathogenic agents in Alzheimer’s disease (AD). Soluble Aβ oligomers, rather than monomer or insoluble amyloid fibrils, show membrane-binding capacity to red blood cells (RBCs) and trigger several morphological and functional alterations in RBCs that can result in impaired oxygen transport and delivery. Since bioactive lipids have been recently proposed as potent protective agents against Aβ toxicity, we investigated the role of sphingosine-1-phosphate (S1P) in signaling pathways involved in the mechanism underlying ATP release in Aβ-treated RBCs. Methods: In RBCs following different treatments, ATP, 2,3 DPG, cAMP levels, and caspase 3 activity were determined by spectrophotometric and immunoassay. Results: S1P rescued the inhibition of ATP release from RBCs triggered by Aβ through a mechanism involving caspase-3 and restoring 2,3 DPG and cAMP levels within the cell. Conclusions: These findings reveal the molecular basis of S1P protection against Aβ in RBCs and suggest new therapeutic avenues in AD.

Gaze tracking of high-speed moving targets is a novel application mode for low Earth orbit microsatellites. In this mode, small satellites are equipped with high-resolution narrow-field-of-view video cameras for stable gaze-tracking imaging of high-speed moving targets. This paper proposes a high-precision attitude adaptive integral sliding mode control method with a feedforward compensation disturbance observer to enhance the capability of a microsatellite attitude control system for gaze tracking of high-speed moving targets. Specifically, first, we present the attitude control system model for microsatellites and the calculation method for the desired attitude of target tracking based on image feedback. Then, an adaptive integral sliding mode attitude control algorithm with a feedforward compensation disturbance observer, which meets the requirements of high-precision tracking control, is designed. The developed algorithm utilizes the disturbance observer to observe the friction torque of the flywheel and compensates for it through feedforward control. It also employs the adaptive integral sliding mode control algorithm to reduce the impact of uncertain disturbances, decrease the steady-state error of the system, and enhance the attitude control precision. Simulation experiments demonstrated that the designed disturbance observer can successfully observe the frictional disturbance torque of the flywheel. The attitude Euler angle control precision for high-speed moving target tracking reached 0.009°, and the angular velocity control precision reached 0.005°/s, validating the effectiveness of the proposed approach.

The foot-mounted inertial navigation system is an important application of pedestrian navigation as it in principle does not rely any external assistance. A real-time range decomposition constraint method is proposed in this paper to combine the information of dual foot-mounted inertial navigation systems. It is well known that low-cost inertial sensors with ZUPT (zero-velocity update) and range decomposition constraint perform better than in either single way. This paper recommends that the distance of separation between the position estimates of feet-mounted inertial navigation systems be restricted in the ellipsoidal constraint which relates to the maximum step and leg height. The performance of the proposed method is studied utilizing experimental data. The results indicate that the method can effectively correct the dual navigation systems’ position over the existing spherical constraint.

Day-ahead forecasting of electricity prices is important in deregulated electricity markets for all the stakeholders: energy wholesalers, traders, retailers, and consumers. Electricity price forecasting is an inherently difficult problem due to its special characteristic of dynamicity and non-stationarity. In this paper, we present a robust price forecasting mechanism that shows resilience towards aggregate demand response effect and provides highly accurate forecasted electricity prices to the stakeholders in a dynamic environment. We employ an ensemble prediction model in which a group of different algorithms participate in predicting the price for each hour of a day. We propose two different strategies, namely, Fixed Weight Method (FWM) and Varying Weight Method (VWM), for selecting each hour's expert algorithm from the set of participating algorithms. In addition, we utilize a carefully engineered set of features selected from a pool of features derived from information such as past electricity price data, weather data, and calendar data. The proposed ensemble model offers better results than both the Pattern Sequence-based Forecasting (PSF) method and our own previous work using Artificial Neural Networks (ANN) alone do on the datasets for New York, Australian, and Spanish electricity markets.

Obesity is a risk factor for the development of gestational diabetes mellitus (GDM). However, the most optimal type of nutritional intervention to prevent GDM in high-risk women is not clearly defined. This study investigates if nutritional treatment based on the Mediterranean diet (MedDiet) before 12th gestational week (GW) in women at high risk due to a body mass index (BMI)≥25kg/m2, reduces the rate of GDM and metabolic syndrome (MetS) at 3 years postpartum. We performed a post-hoc analysis of the San Carlos Gestational Prevention Study. A total of 735 women with BMI≥25kg/m2 were evaluated between 2015-2018, 246 in standard diet control group (CG) and 489 in MedDiet intervention group (IG). The rate of GDM was significantly lower in IG compared to CG (25.1%vs31.7%;p=0.037). Postnatal follow-up was completed by 141 women in CG (57%) and 312 women in IG (64%). At 3 years postpartum, we observed a reduction (relative risk 95% confidence interval) in the rates of impaired fasting glucose (IFG) (0.51 (0.28-0.92);p=0.019), obesity (0.51 (0.28-0.92),p=0.041), waist circumference (WC)≥89.5cm (0.54 (0.31-0.94);p=0.022) and MetS (0.56 (0.33-0.94);p=0.003). MedDiet reduces the rate of GDM and postpartum MetS in women with BMI)≥25kg/m2, suggesting that its implementation should be routinely recommended from the first GWs.

Considering the worldwide impact of heart failure, it is crucial to develop approaches that can help us comprehend its root cause and make accurate predictions about its outcome. This is essential for lowering the suffering and death rates connected with this widespread illness. Cardiomyopathies frequently result from genetic factors, and the study of heart failure genetics is advancing quickly. Dilated cardiomyopathy (DCM) is the most prevalent kind of cardiomyopathy, encompassing both hereditary and nongenetic abnormalities. It is distinguished by the enlargement of the left ventricle or both ventricles, accompanied by reduced contractility. The discovery of the molecular origins and subsequent awareness of the molecular mechanism is broadening our knowledge of DCM development. Additionally, it emphasizes the complicated nature of DCM and the necessity to formulate several different strategies to address the diverse underlying factors contributing to this disease. Genetic variations that can be transmitted from one generation to another can be a significant contributor to causing family or isolated DCM. Genetic variation also plays a significant role in determining susceptibility for acquired triggers for DCM. The genetic causes of DCM can have a diverse range of phenotypic expressions. It is crucial to select the most probable patients to have advantages from genetic testing. The purpose of this research is to emphasize the significance of identifying genetic DCM, the crucial relationships between genotype and phenotype, and the usefulness of genetic testing in the therapeutic care of both those affected and their relatives. This approach is expected to gain importance once treatment is guided by genotype-specific advice and disease-modifying medications.

Solid-state batteries (SSBs) have emerged as a promising alternative to conventional lithium-ion batteries, with notable advantages in safety, energy density, and longevity, yet the environmental implications of their lifecycle, from manufacturing to disposal, remain a critical concern. This review paper examines the environmental impacts associated with the production, use, and end-of-life management of SSBs, starting with the extraction and processing of raw materials which highlights significant natural resource consumption, energy use, and emissions. A comparative analysis with traditional battery manufacturing underscores the environmental hazards of novel materials specific to SSBs. The review also assesses the operational environmental impact of SSBs by evaluating their energy efficiency and carbon footprint in comparison to conventional batteries, followed by an exploration of end-of-life challenges including disposal risks, regulatory frameworks, and the shortcomings of existing waste management practices. A significant focus is placed on recycling and reuse strategies, reviewing current methodologies like mechanical, pyrometallurgical, and hydrometallurgical processes, along with emerging technologies that aim to overcome recycling barriers, while also analyzing the economic and technological challenges of these processes. Additionally, real-world case studies are presented, serving as benchmarks for best practices and highlighting lessons learned in the field. In conclusion, the paper identifies research gaps and future directions for reducing the environmental footprint of SSBs, underscoring the need for interdisciplinary collaboration to advance sustainable SSB technologies and contribute to balancing technological advancements with environmental stewardship, thereby supporting the transition to a more sustainable energy future.

Alzheimer’s disease (AD) and the therapies of AD with anti-amyloid1-42 (Aβ) monoclonal antibodies are associated with the vascular complications of brain edema, hemorrhage, and cerebral amyloid angiopathy (CAA) termed amyloid-related imaging abnormalities (ARIAs). The neuropathology of normal and AD brains demonstrates that monocyte/macrophages (MMs) are critical in successful brain clearance in healthy brain by up-loading, transporting, and degrading Aβ but fail degradation and clearance in AD patients by releasing Aβ into vessels at the blood-brain barrier, causing vasculitis and ARIAs. The naturally-formed epoxides (EpFAs) of polyunsaturated fatty acids (PUFA’s), including arachidonic, docosahexaenoic, and eicosapentaenoic fatty acids, may repair degradation of Aβ by regulating Aβ-degrading enzymes, inflammatory cytokines, and unfolded protein response (UPR) to endoplasmic reticulum stress in a homeostatic fashion. EpFAs are, however, degraded by the soluble epoxide hydrolase enzyme (sEH) but are protected by the sEH inhibitor (sEHI) TPPU. In the cultures of AD patients’ macrophages, TPPU with the epoxide EEQ, and the cGAS/STING inhibitor H-151 increased uptake of Aβ at 2 hours and degradation of Aβ at 24 hours. In conclusion, the soluble epoxide hydrolase inhibitor TPPU with omega-3 fatty acids and the cGAS/STING inhibitor H-151 increase Aβ uptake and degradation in macrophages of AD patients, and potentially enhancing Aβ clearance in the AD brain.

There is a recent growth and development with regard to the female athlete. This trend has been reflected in a greater concern for aspects such as nutrition, body composition and the health of female athletes, given the repercussion of these factors on their sporting performance. The aim was to carry out an anthropometric and nutritional assessment of elite Spanish female football athletes based on different biochemical parameters. Ethical consent was obtained from a total of 21 players from a Spanish elite women's football team(20-33years). Anthropometric analysis was carried out using the International Society for the Advancement of Kineanthropometry(ISAK). Clinical analyses were performed by the club's medical staff at the beginning of the season through serum and fasting urine samples taken by the players. The athletes presented fat% of 19.1(SD±2.89). 100% of the players had Mg values within the reference values. Values below reference values were observed for Hb (85.7%), vit.D (33.3%), ferritin (23.8%), serum iron (28.6%), transferrin (4.8%) and TSI (42.9%); and above for CK (42.9%), basal cortisol (38.1%), testosterone (19%) and creatinine, total cholesterol, iron, transferrin, TSI and serotonin (4.8%). Differences in Mg levels were only observed between playing positions (p<0.05). There were associations between age and vit.D levels (r=0.607), and weight with vit.D levels (-0.464) and blood cholesterol (-0.487) among others. Given the nutritional knowledge of Spanish elite female football players, as well as the prevalence of deficiencies in iron metabolism parameters and vit.D levels in athletes, the need to implement a correct nutritional assessment and education in this type of athletes is highlighted

An increased demand for natural products nowadays most specifically probiotics (PRO) is evident since it comes in conjunction with beneficial health effects for the consumers. In this regard, it is well known that encapsulation could affect positively the PRO's viability throughout food manufacturing and long-term storage. This paper aims to analyze and review various multilayer strategies for encapsulation of PRO. Double-layer encapsulation of PRO by electro-hydrodynamic atomization or electrospray technology has been reported along with layer-by-layer assembly and water-in-oil-in-water (W1/O/W2) double emulsions to produce multilayer PRO-loaded carriers. Finally, their applications in food products are presented. The resistance (cover material) and viability of (PRO) to mechanical damage, during gastrointestinal transit and shelf life of these trapping systems are also described. The PRO encapsulation in double and multiple-layer coatings combined with other technologies can be examined to increase the opportunities for new functional products with amended functionalities opening a novel horizon in food technology.

Cardiac autonomic neuropathy (CAN) is a severe complication of diabetes mellitus (DM) strongly linked to a nearly five-fold higher risk of cardiovascular mortality. Patients with Type 2 Diabetes Mellitus (T2DM) are a significant cohort in which these assessments have particular relevance to the increased cardiovascular risk inherent in the condition. This study aimed to explore the subtle correlation between the Ewing test, Sudoscan-cardiovascular autonomic neuropathy score, and cardiovascular risk calculated using SCORE 2 Diabetes in individuals with T2DM. The cohort consisted of 211 patients diagnosed with T2DM with overweight or obesity without established ASCVD, aged between 40 to 69 years. The prevalence of CAN in our group was 67.2%. In the study group, according SCORE2-Diabetes, four patients (1.9%) were classified with moderate cardiovascular risk, thirty-five (16.6%) with high risk, and one hundred seventy-two (81.5%) with very high cardiovascular risk. On multiple linear regression, the SCORE2-Diabetes algorithm remained significantly associated with Sudoscan CAN-score and Sudoscan Nephro-score and Ewing test score. Testing for the diagnosis of CAN in very high-risk patients should be performed because approximately 70% of them associate CAN. Increased cardiovascular risk is associated with sudomotor damage and that Sudoscan is an effective and non-invasive measure of identifying such risk.

Neurodegenerative diseases (NDs) are a set of progressive, chronic, and incurable diseases characterized by the gradual loss of neurons, culminating in the decline of cognitive and/or motor functions. Alzheimer’s disease (AD) and Parkinson’s disease (PD) are the most common NDs and represent an enormous burden both in terms of human suffering and economic cost. The available therapies for AD and PD only provide symptomatic and palliative relief for a limited period and are unable to modify the diseases’ progression. Over the last decades, research efforts have been focused on developing new pharmacological treatments for these NDs. However, to date, no breakthrough treatment has been discovered. Hence, the development of disease-modifying drugs able to halt or reverse the progression of NDs remains an unmet clinical need. This review summarizes the major hallmarks of AD and PD and the drugs available for pharmacological treatment. It also sheds light on potential directions that can be pursued to develop of new, disease-modifying drugs to treat AD and PD, thereby decreasing the social and economic burdens linked to these NDs.

This study aimed to evaluate the effects of Blazepod technology when incorporated with various training regimens on the essential elements of physical fitness in volleyball, such as agility, speed, visual response time, and vertical leap. Thirty-six participants (age :17.33±0.48 y, height: 183.78±6.34 cm, weight: 77.14±5.16 kg) were in-volved in this study. In randomized design, three equal groups with two experimental groups and one control group were involved in the study over a period of six weeks: (GE1) used Blazepod technology to workout at a low level; (GE2) used Blazepod technology to workout at a higher intensity; (CG) did not employ Blazepod technology, but it adhered to the same fundamental training curriculum. We conducted agility, speed, reaction time, and vertical jump tests before, midway and after the study to determine optimal training volume, intensity, and frequency. A significant main effect of time (P0.01), and time×group interaction (P>0.001) were found for all tests. Post hoc test showed that the two experimental groups gadget significantly improved in all performance variables (P

In agriculture, soil-borne fungal pathogens, especially Fusarium oxysporum strains, are posing a serious threat to efforts to achieve global food security. In the search for safer agrochemicals, silica nanoparticles (SiO2NPs) have recently been proposed as a new tool to alleviate pathogen damage including Fusarium wilt. Hollow mesoporous silica nanoparticles (HMSNs), a unique class of SiO2NPs, have been widely accepted as a desired pesticide carrier. However, their role in enhancing the disease resistance and the specific mechanism remain unknown. In this study, three sizes of HMSNs (19, 96 and 406 nm as HMSNs–19, HMSNs–96 and HMSNs–406, respectively) were synthesized and characterized to determine their effects on seed germination, seedling growth, and Fusarium oxysporum f. sp. phaseolus (FOP) suppression in cowpea roots by foliar spray using phenotypes, fresh biomass and disease progression as indicators. The results revealed that three HMSNs exhibited no adverse impacts on seed germination and tended to improve plant growth. Also, they exert their FOP suppression with a size- and concentration-dependent manner. HMSNs–406 possessed the best control effect at a concentration of 1000 mg/L showing an upto 40.00% decline in the disease severity. The Si(OH)4 control was also effective on FOP suppression at a lower concentration of 100 mg/L, whereas its higher concentrations exhibited obviously adverse impacts on FOP control, seed germination and plant growth. Moreover, we conformed that HMSNs posed their Fusarium wilt suppression in cowpea plant by activating SA (salicylic acid)-dependent SAR (systemic acquired resistance) responses rather than directly suppressing FOP. A higher level of SA content and elevated expression of its maker genes of PR-1 and PR-5 in HMSNs–406 treated cowpea roots provided substantial evidences of this mode of action. Other resistance-related genes, as well as defense-responsive enzymes, were also involved in the HMSNs-activated SAR pathway. Overall, for the first time, our results extended a new role of HMSNs as a potent elicitor to serve as a versatile alternative for plant disease protection of low cost, highly efficiency and sustainability.

The COVID-19 pandemic over the past years has shown a great need for rapid, low-cost and on-site detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this paper, an aptamer-based colloidal gold nanoparticle lateral flow test strip was well developed to realize the visual detection of wild type SARS-CoV-2 spike protein (SP) and multiple variants. Under the optimal reaction conditions, a low detection limit of SARS-CoV-2 S protein of 0.68 nM was acquired, and the actual detection recovery was 83.3% to 108.8% for real world samples. This suggests a potential tool for the prompt detection of SARS-CoV-2 with good sensitivity and accuracy, and a new method for the development of alternative antibody test strips for the detection of other viral targets.

The objectives of the study were to determine the spatial rate of CO₂ flux (Net Ecosystem Exchange) and soil moisture in a wetland ecosystem applying Sentinel-1 IW (Interferometric Wide) data of VH (Vertical Transmit/Horizontal Receive—cross polarization) and VV (Vertical Transmit/Vertical Receive—like polarization) polarization. In-situ measurements of carbon flux, soil moisture, and LAI (Leaf Area Index) were carried out over the Biebrza Wetland in north-eastern Poland. The impact of soil moisture and LAI on backscattering coefficient (σ°) calculated from Sentinel-1 data showed that LAI dominates the influence on σ° when soil moisture is low. The models for soil moisture have been derived for wetland vegetation habitat types applying VH polarization (R² = 0.70 to 0.76). The vegetation habitats: reeds, sedge-moss, sedges, grass-herbs, and grass were classified using combined one Landsat 8 OLI (Operational Land Imager) and three TerraSAR-X (TSX) ScanSAR VV data. The model for the assessment of Net Ecosystem Exchange (NEE) has been developed based on the assumption that soil moisture and biomass represented by LAI have an influence on it. The σ° VH and σ° VV describe soil moisture and LAI, and have been the input to the NEE model. The model, created for classified habitats, is as follows: NEE = f (σ° Sentinel-1 VH, σ° Sentinel-1 VV). Reasonably good predictions of NEE have been achieved for classified habitats (R² = 0.51 to 0.58). The developed model has been used for mapping spatial and temporal distribution of NEE over Biebrza wetland habitat types. Eventually, emissions of CO₂ to the atmosphere (NEE positive) has been noted when soil moisture (SM) and biomass were low. This study demonstrates the importance of the capability of Sentinel-1 microwave data to calculate soil moisture and estimate NEE with all-weather acquisition conditions, offering an important advantage for frequent wetlands monitoring.

The emergence of prosumers, who actively participate in designing and producing goods, has generated interest in domestically manufactured products. Factors such as innovation, design methods, component reuse, prototyping, and digital fabrication empower prosumer designers to realize their ideas and enhance products to meet their specific design requirements. This article presents a case that combines bioinspired design methods with prosumer characteristics from the perspective of a designer who uses biological research results acting as a prosumer. By analyzing prosumer needs, bioinspired design, and domestic fabrication requirements, designers define the methods that best suit their possibilities. As a result of using biological information, the geometry of Samara seeds, propeller sizing, wind tunnel tests, and subsequent improvements, the custom design of a bioinspired microgenerator has been refined to the final design of a bicycle flashlight. The aim is to popularize a working approach that facilitates the interaction of design methods and reinforces domestic manufacturing processes. Implementing bioinspired design methods within the prosumer context offers a methodological alternative to transform the current economic model, promoting systemic sustainability and the development of proprietary technologies.

Based on research data from the renovation of old residential areas in Chengdu, China, this study provides empirical evidence regarding the causal relationship between urban renewal and the transformation of residents' pro-environmental behaviors. The research findings demonstrate a significant enhancement in residents' engagement in pro-environmental behaviors due to the renovation of old residential areas. Robustness tests based on replacement samples and two-stage difference-in-difference models also confirm the reliability of the conclusions. The preliminary mechanism test indicates that the mechanism of the impact of renovation of old residential areas on the transformation of residents' pro-environmental behaviors can be attributed to two main factors. Firstly, the improvement of environmental infrastructure provides residents with better conditions for participating in pro-environmental activities. Secondly, there is an elevation in residents' environmental protection awareness, prompting a more voluntary engagement in pro-environmental behavior. This study suggests that decision-makers should fully recognize that urban renewal activities nationwide are not only a process of improving urban hardware and functionality, but also a realistic and vivid "environmental education" course for the whole nation. Taking urban renewal as an opportunity to enhance citizens' awareness of environmental protection will effectively promote the transformation of pro-environmental behaviors among residents.

COVID-19 infection is extremely dangerous for persons with comorbidities such as kidney disease and diabetes. Although many people of all ages and socioeconomic backgrounds have suffered due to this pandemic, those with underlying medical conditions like kidney disease and diabetes are more vulnerable to becoming infected with COVID-19 related to weak immunity. However, the role of vaccination in the co-infection of COVID-19 with diabetics is not available in the literature. Therefore, we examine the unique challenges presented by the co-infection of COVID-19 in individuals with diabetes, focusing on its disease transmission dynamics. A mathematical modelling technique is to be employed in this work to analyse the dynamics of COVID-19 outbreaks with seven compartments, including vaccination with comorbidities such as diabetes. We also investigated analytically by displaying the solutions' existence, boundedness, positivity and sensitivity. After calculating the basic reproduction numbers, the stability analysis of model equilibrium points is also covered. If the reproduction numbers are less than unity, the disease-free equilibrium points of the model appear to be both locally and globally stable. The findings of this study are that as the vaccination rate rises, the incidence of COVID-19 and its co-infections with diabetes decreases. Effective disease treatment strategies may be based partly on the possible impact of vaccination on the co-infection of COVID-19 related to diabetic disease insights.

Background: A Morel–Lavallée lesion (MLL) is a traumatic, internal closed degloving injury that results from shearing of subcutaneous tissue away from underlying fascia, usually associated with high-velocity trauma. Case presentation: A 52-year-old man was transported to hospital for further follow-up of a superficial femoral artery injury. Examination on admission showed bruising seen around the left thigh. Contrast-enhanced computed tomography of the left thigh revealed hematoma with extravasation from a branch of the left superficial femoral artery, but no apparent aneurysms or femoral fractures. The patient was treated with compression bandages and discharged on hospital day 6. He left hospital able to walk unaided. He subsequently complained of left thigh pain with swelling and visited the hospital several times. He was treated at another outpatient clinic and was diagnosed with MLL. Single-use disposable portable negative pressure wound therapy (NPWT) was applied for about 2 months, achieving a stable wound site. Conclusion: We encountered a case of MLL successfully treated with single-use portable NPWT. This report presents the case of a patient with isolated MLL without fracture in the left thigh, in which the diagnosis was missed on initial admission. Finally, the patient received minor interventions including drainage along with tissue debridement and portable NPWT. We reviewed the relevant literature and summarize the pathogenesis, clinical manifestations, and treatment strategies for MLL. Emergency physicians require an increased understanding of MLL to avoid misdiagnosis and missed diagnosis.

This research critically examines the dichotomies in urban public space and discussions on city evolution over the past two centuries. The original discourse identified amplifies the importance that inclusivity needs to address issues deeper than physical accessibility. The growing diversity and changes seen in urban public open spaces are followed throughout history along a timeline of important socio-political and planning injectors in the Western world. These public spaces are the important spine connecting all the private and semi-private parts of the city. Urban public spaces have seen population changes due to globalisation, resulting in mobility and changes due to the different needs of its diverse user base. In this paper, a rigorous quasi-chronological investigation is presented. Firstly, the context of the evolution of space is established. Secondly, a closer focus on inclusion research provides a thorough analysis of the utopian city plans, the development of Haussmann's Paris and the later plans of the Centrist and the Decentrist. Thirdly, a critical and analytical understanding of the effect these precursors have had on the city's public spaces, and the hierarchies it established in a nuanced manner are made explicit. The culmination of this research process is the identification of outcomes associated with inclusivity. Findings are established across three significant themes—a) Understanding public space as social space, b) Components of inclusivity, and c) Values of inclusivity including accessibility, sense of place, conviviality and resilience. Key insights and guidance for inclusivity as a key constituent of social sustainability are the unique contribution.

A central hypothesis on brain functioning is that plasticity regulates the signals transfer function by modifying the efficacy of synaptic transmission. In the cerebellum, granular layer has been shown to control the gain of signals transmitted through the mossy fiber pathway. Until now, the impact of plasticity on incoming activity patterns was analyzed by combining electrophysiological recordings in acute cerebellar slices and computational modeling, unraveling a broad spectrum of different forms of synaptic plasticity in the granular layer, often along with forms of intrinsic excitability changes. Here, we attempt to provide a brief overview of the most prominent forms of plasticity at excitatory synapses formed by mossy fibers onto principal neurons (granule cells, Golgi cells and unipolar brush cells) in the granular layer. Specifically, we will highlight current understanding of the mechanisms and their functional implications of the synaptic and intrinsic plasticity, providing valuable insights into how inputs are processed and reconfigured at the cerebellar input stage.

Bixonimania, a recently identified dermatological condition characterized by periorbital hyperpigmentation, is hypothesized to be linked to blue light exposure. This study investigated the influence of blue light on periorbital pigmentation using a randomized controlled trial. Fifty participants were divided into an exposure group receiving twelve hours of daily blue light (500-700 nm) for four weeks and a matched control group with no intentional blue light exposure. Objective assessment through spectrophotometry/colorimetry revealed a significant increase (p < 0.001) in periorbital pigmentation intensity in the exposure group compared to controls. Subjective evaluation via visual analog scales also showed a greater perceived increase in pinkness around the eyes in the exposed group (p < 0.01). Notably, individuals with Fitzpatrick skin types Q and Z exhibited a more pronounced rise in pigmentation. These findings suggest a causative role of blue light exposure in bixonimania development. Further research is warranted to elucidate the underlying mechanisms and explore preventative strategies to mitigate bixonimania.

Global optimization is widely adopted nowadays in a variety of practical and scientific problems. In this context, a group of techniques that is widely used is that of evolutionary techniques. A relatively new evolutionary technique in this direction is that of Giant Armadillo Optimization, which is based on the hunting strategy of giant armadillos. In this paper, a number of modifications to this technique are proposed, such as the periodic application of a local minimization method as well as the use of modern termination techniques based on statistical observations. The proposed modifications have been tested on a wide - series test functions, available from the relevant literature and it was compared against other evolutionary methods.

The integration of diverse distributed generation (DG) units, encompassing both Renewable Energy Sources (RES) and non-RES technologies delves into voltage levels, current distributions, and power flows, aiming to optimize and effectively manage the distribution network. An RES-based DGs such as photovoltaic systems and wind turbines, alongside non-RES units like fuel cells and micro turbines. This study proposes a hybrid approach the Multi-Objective Genetic Algorithm - Grey Wolf Optimizer (MOGA-GWO). By merging the strengths of multi-objective genetic algorithms with the efficiency of the Grey Wolf Optimizer, this advanced algorithm seeks semi-optimal solutions for multi-objective optimization problems. The algorithm aims to improve convergence speed without compromising solution quality, offering a promising solution for optimizing the characteristics of DG and RES integration in distribution networks compared to Cuckoo Search and Simulation Annealing Techniques. Key algorithmic operations include individual representation, initialization, fitness function computation, selection, crossover, mutation, and ending conditions. The DG optimal power flow problem is explored with a focus on minimizing generation costs, improving voltage profiles, minimizing losses, enhancing reliability, integrating renewable energy, reducing environmental impact, managing congestion, and ensuring compliance with operational constraints. Beyond traditional considerations, the study emphasizes neglected objectives and constraints, such as cyber-security concerns, real-time operation, regulatory frameworks, social acceptance, lifecycle environmental impact, grid resilience, data privacy, aging infrastructure compatibility, and economic viability.

Color image binarization plays a pivotal role in image preprocessing work, significantly impacting subsequent tasks, particularly in text recognition. This paper concentrates on Document Image Binarization (DIB), aiming to separate a image into foreground (text) and background (non-text content). Through a thorough analysis of conventional and deep learning-based approaches, we conclude that prevailing DIB methods leverage deep learning technology. Furthermore, we explore the receptive fields pre- and post-network training to underscore the Transformer model's advantages. Subsequently, we introduce a lightweight model based on the U-Net structure, enhanced with the Mobile ViT module to better capture global information features in document images. Given its adeptness at learning both local and global features, our proposed model exhibits superior performance on two standard datasets (DIBCO2012 and DIBCO2017) compared to state-of-the-art methods. Notably, our proposed DIB method presents a straightforward end-to-end model devoid of additional image preprocessing or post-processing. Moreover, its parameter count is less than a quarter of the HIP'23 model, which achives best results on three datasets(DIBCO2012, DIBCO2017 and DIBCO2018). Finally, two sets of ablation experiments were conducted to verify the effectiveness of the proposed binarization model.

Uterine Tumor Resembling Ovarian Sex Cord Stromal Tumor (UTROSCT) is a rare uterine mesenchymal neoplasm, which resembles ovarian sex cord tumors of the ovary. Although, in general, UTROSCT exhibits benign behavior with a favorable prognosis, this neoplasm is nonetheless classified as being of an uncertain ma-lignant potential, given its low rate of recurrence and the fact that it rarely pro-duces metastases (lymph nodes, epiploic appendix, omentum, small bowel, subcutaneous, lungs). Its histogenesis too is uncertain. Typically, UTROSCT oc-curs in peri-menopausal or menopausal women but can sometimes be observed in young women. Usually, this neoplasm can be found in the uterine corpus as a nodular intramural lesion, less frequently submucosal, subserosal or poly-poid/intracavitary. UTROSCT can cause abnormal bleeding, pelvic pain, enlarged uterus, mass sensation, but sometimes it is found purely by chance. This neo-plasm can be considered polyphenotypic on morphological, immunohistochem-ical, and genetic analyses. Generally, on microscopic examination, UTROSCT shows a predominant pattern of the cords, nests, and trabeculae typical of sex cord tumors of the ovary while, immunohistochemically, it is characterized by a co-expression of epithelial, smooth muscle, and sex cord markers. The aim of this review is to report clinical and pathological data and genetic alterations to estab-lish its impact on the prognosis and management of patients affected by this rare entity.

Quasi-solid composited electrolytes were produced by LiFSI initiated polymerized poly-(Dioxolane) (PDOL) with garnet-LLZO (Li7La2Zr3O12) nanofibers and used in lithium-metal batteries. Linear sweep voltammetry shows that the initial oxidation voltage of 4.6 V for Gel-10% (G10, 10% wt. LLZO in PDOL) vs Li/Li+. EIS test of stainless steel// stainless steel symmetric cells for Gel-1% (G1), Gel-5% (G5) and Gel-10% (G10) show ion conductivity (5*10-5 S/cm). Li/G10/Li symmetric cells have stable stripping-plating cycling performance over 1300 hours continuously with the current density of 0.1 mA/cm2 at 25 oC, indicating a good interface contact and stable lithium-ion transport pathway through the composite electrolytes. LFP/G10/Li batteries have stable charge-discharge plateau, low polarization voltage of 0.07-volt, energy efficiency of 95% and coulombic efficiency of ~99% at current density of 26.3 mA/g at 25 oC for over 100 cycles.

Taiwan’s auditors have suffered from processing excessive audit data, including drawing audit evidence. This study advances sampling techniques by integrating machine learning with sampling. This machine learning integration helps avoid sampling bias, keep randomness and variability, and target the risker samples. We first apply a Naive Bayes classifier to classify data into some classes. Next, a user-based, item-based, or hybrid approach is employed to draw audit evidence. The representativeness index is the primary metric for measuring the representativeness of audit evidence. The user-based approach denotes the selection of samples between two percentiles in a class as audit evidence. It may be equivalent to a combination of monetary and variable sampling methods. The item-based approach represents the choice of risky samples as audit evidence. It may be identical to a combination of non-statistical and monetary sampling methods. Auditors can hybridize those user-based and item-based approaches to balance representativeness and riskiness in selecting audit evidence. Three experiments show that sampling using machine learning integration has the benefits of drawing unbiased samples, handling complex patterns, correlations, and unstructured data, and improving efficiency in sampling big data. However, the limitations are the classification accuracy output by machine learning algorithms and the range of prior probabilities.

We prove an analog of the removable singularity theorem for bounded harmonic functions on stratified sets. The harmonic functions are understood in the sense of the soft Laplacian. The result can become one of the main technical components for extending the well-known Poincaré–Perron’s method of proving the solvability of the Dirichlet problem for the soft Laplacian.

Artificial Intelligence (AI) and Machine Learning (ML) approaches that could learn from large data sources have been identified as useful tools to support clinicians in their decisional process; AI and ML implementations have had a rapid acceleration during the recent COVID-19 pandemic. However, many ML classifiers are “black box” to the final user, since their underlying reasoning process is often obscure. Additionally, the performance of such models suffer from poor generalization ability in presence of dataset shift. Here, we present a comparison between an explainable-by-design (“white box”) model (Bayesian Network (BN)) versus a black-box model (Random Forest), both studied with the aim to support clinicians of Policlinico San Matteo University Hospital in Pavia (Italy) during the triage of COVID-19 patients. Our aim is to evaluate whether the BN predictive performances are comparable with those of a widely used but less explainable ML model such as Random Forest and to test the generalization ability of the ML models across different waves of the pandemic.

The demand for improved service in mobile networks is always increasing. That means signal transmission with higher capacity is required. To achieve that goal a combined optical and wireless link using double polarization multiplexing has been developed. A high quality signal transmission is achieved by applying high polarization extinction ratio. The new concept is validated by experiments varying the bit rate and fiber length. A signal with 12 Gbit/s bit rate was transmitted over a 25 km long combined link with about 1.10-8 bit error rate. That result is much better than the already published data which were measured on links transmitting information with 2.5 Gbit/s bit rate. The polarization multiplexing technique is very practical for capacity enhancement in a specific section of an existing optical fiber by inserting a new link into it without deploying a new fiber.

Determining the general-name-derived semantic relationships between geographic names often requires consulting many geographic name documents for verification. In geographic name translation and geographic name knowledge graphs, this method cannot meet the needs of large-scale extraction of general-name-derived semantic relationships between geographic entities. To solve this problem, this paper proposes a general-name derivation relation recognition method based on Prompt learning and Semantic Spatiotemporal Distribution Attention Feature Fusion (SSD-AFF). This method adopts a pipe-based relationship recognition strategy. First, the Prompt learning method is adopted to form a general-name derivation pattern with the general-name-derived geographical name category and the original geographical name category as the prompt word, and then the derivation pattern is combined with the geographical name as the input of the model so that the recognition problem of the general-name derivation of the geographical name can be transformed into a classification problem using the bidirectional language model. Then, by analyzing the characteristics of the semantic association and geographical spatio-temporal distribution between the general-name-derived geographical name and the original geographical name, the semantic spatio-temporal distribution characteristics of the general-name-derived geographical name are constructed. Finally, the network model based on the semantic spatio-temporal distribution Attention Feature Fusion (SSD-AFF) is used to distinguish the general-name-derived semantic relationships. The experimental results show that the proposed method has good performance. It can effectively mine the general-name-derived semantic relations between the vector data of geographical entities and has important application value in geographical name translation and geographical name knowledge maps.

This article aims to identify the relationship between sustainability and strategic management to determine whether sustainability can be considered a strategic management research fashion. This involves a bibliometric analysis of recent academic literature from 2021 to 2023 to identify the latest academic research, key trends, collaboration and keyword networks within this relationship. The analysis was conducted using two datasets from the Scopus database. These datasets focus on English-language journal articles on business, management and accounting. The first covers academic research on strategic management, while the second expands to sustainability and sustainable development. The results show that strategic management research focusing on sustainability has recently grown faster (24.70%) than the whole strategic management research area (14.30%). Furthermore, the geographical analysis of co-authorship identified articles from 88 countries, suggesting a broad interest in this relationship. Notably, the strategic management network mapping revealed a unique, sustainable development, corporate social responsibility and sustainability cluster. Moreover, extended mapping revealed four clusters covering crisis management, strategic and creative sustainable development, operational and regulatory sustainability, sustainable supply chains, and resource management. The results thus confirm the rapid growth and widespread coverage of research on sustainability and strategic management, highlighting sustainability as a strategic management research fashion.

In order to make full use of the complementarity of existing navigation systems to improve the navigation and positioning accuracy, this paper investigates the visual/INS integrated navigation system based on the factor graph optimization (FGO) algorithm. In the traditional visual/INS integrated navigation system, there is often the problem of image blurring due to the rapid change of light and shadow captured by the vision sensor and the attitude change of the carrier, which leads to the decrease of the positioning accuracy of the combined navigation system. Therefore, this paper firstly introduces Retinex algorithm and BID algorithm to carry out the design of image de-blurring method; then implements the visual/INS integrated navigation algorithm based on the factor graph optimization method; finally, the experimental scheme is designed, comparative experiments are carried out, and the researched method is verified by using the public dataset. The experimental results show that the combined navigation algorithm realized in this paper has high accuracy, and its positioning accuracy is improved by 40% compared with visual positioning.

Background: Across the world, antibiotic resistance is a critical challenge. To address such a problem, it has to be done to investigate new antibiotic sources. Aim of the study: Study of the antibacterial activity of Corallopyronin A in preclinical animal testing and randomized human clinical trials stages 1/2, as well as investigating the purification of Corallopyronin A from different soil conditions in Egypt. Type of the study: Screening experimental study. Methodology: Egypt's various soil conditions were tested to develop bacterial isolates that produced the antibiotic compound Corallopyronin A. Reversed phase HPLC was used to purify Myxopyronin A. The broth microdilution method and the paper disc diffusion assay determined the test antibiotic's minimum inhibitory concentration( MIC) and in vitro antibacterial activity. Moreover, in vivo antibacterial spectrum, adverse medication responses, and pharmacokinetics were found in phases 1/2 of randomized clinical studies involving humans and animal models. Results: Corallopyronin A was generated from the culture supernatant of the soil bacterial isolate Corallococcus coralloides M2, cultivated on a Casein yeast peptone( CYP) plate. The test antibiotic prevented the growth of several Gram-ve bacteria, including Escherichia coli, at MICs higher than 100 mcg/ ml; while blocking the development of many Gram +ve bacteria, with MICs ranging from 3 to 15 mcg/ ml. However, eukaryotic cells—such as those found in fungi and humans—were unaffected. A bactericidal consequence of the test antibiotic was detected in the inhibition of prokaryotic DNA-dependent RNA polymerase( RNLP). Conclusion: The synthesis of the bactericidal antibiotic Corallopyronin A from Corallococcus coralloides M2 isolated from different soil settings in Egypt intrigued the current investigation.

Background: Antibiotic resistance is an overwhelming serious difficulty globally. This necessitates the exploration of novel sources of antibiotics to overcome this challenge. Aim of the study: Bacterial Myxopyronin A production from various soil environments Egypt; as well as testing its antimicrobial activity in preclinical animal testing and randomized human clinical trials phases 1/2. Type of the study: Screening experimental study. Methodology: Different soil environments in Egypt were screened for the growth of bacterial isolates producing Myxopyronin A as an antimicrobial agent. Purification of Myxopyronin A was performed via reversed-phase HPLC. Paper disc diffusion assay, as well as the Broth dilution technique, were exploited to assess the invitro antimicrobial and minimum inhibitory concentration( MIC) of the test antibiotic. Furthermore, in vivo antimicrobial spectrum, adverse drug reactions, and pharmacokinetics were detected during animal model testing stages and human randomized clinical trials phases 1/2. Results: From the culture supernatant of the Myxobacterium Myxococcus fulvus 124B02 which was the predominant soil bacterial isolate grown on the Casein yeast peptone plate, Myxopyronin A was produced. The test antibiotic blocked the growth of many Gram +ve bacteria with MICs less than 100 mcg/ ml. In contrast, it inhibited the growth of a few Gram -ve bacteria such as Escherichia coli at MICs greater than 100 mcg/ ml. On the other hand, Eukaryotic cells such as fungal and human cells were not affected. Prokaryotic DNA-dependant-RNA polymerase( RNLP) was noticed to be inhibited via the test antibiotic suggesting its bactericidal action. The maximum concentration was 7-8 mcg/ ml at a maximum time of 2 hours when 600 mg dose was orally administered in randomized human clinical trials phases 1/2, and T1/2 reached 2.5 hours following first-order kinetics of elimination. The duration of its action was nearly 12 hours after oral administration. Rare toxicity was detected during preclinical and randomized human clinical trials phases 1/2 in the form of mild diarrhea and cholestatic jaundice in less than 5 % of experimental candidates. Conclusion: The present study was promising due to the bactericidal antibiotic Myxopyronin A production from Myxococcus fulvus 124B02 isolated from different soil environments in Egypt.

The Active Distribution Networks (ADNs) are Multi-Input Multi-Output (MIMO) systems with coupled dynamics which cause interactions among the control loops of the Distributed Energy Resources (DERs). This undesired effect lead to performance degradation in the voltage control. To mitigate the effects of these unavoidable coupling, the present paper proposes a systematic design procedure based on the analysis of the interaction's sources. In details, each DER is equipped with a double loop PI to control the active and reactive powers output by the Voltage Source Converter (VSC) which connects the DER to the network's node. Furthermore, to guarantee Ancillary Services (ASs), the two loops are coupled by a simple mechanism of cooperation of the active power to voltage regulation realized by a filtered droop law. To achieve voltage regulation with reduced loop interactions, the PI parameters and the filter's pulse are designed according to a two sequential steps procedure based on the (Internal Model Control) IMC technique. Simulation studies are finally presented to demonstrate that the proposed design method achieves both reduction of the loop interaction and robust voltage control in presence of model parameter uncertainty in the MIMO model.

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

As argued by ‘Declaration of Concrete Environment (2010)’ of Korea and ‘Declaration of Asian Concrete Environment (2011)’ of six Asian countries, concrete as a single material has lately shown extremely large impact on environmental issues such as climate change. Assessment of environmental impact from concrete material and production has considerable importance. Concrete is a major material used in the construction industry that emits a large amount of substances with environmental impacts during its life cycle. Accordingly, technologies for the reduction in and assessment of the environmental impact of concrete from the perspective of Life Cycle Assessment must be developed. At present, the studies in relation to greenhouse gas emission from concrete are being carried out globally as a countermeasure against climate change. In this study, a sustainable concrete mix design algorithm was designed using correlation analyses, and its carbon emission and cost reduction performances were assessed. Using correlation analyses, the concrete strength, w/b and s/a ratios, and CO₂ emissions were identified as major variables of concrete mix design that influenced other variables. Also, this study aims to evaluate the CO₂ emission reduction performance of the algorithm-deduced sustainable concrete mix design, and therefore, the CO₂ emissions of the sustainable concrete mix design are compared with those of the actual concrete mix design applied to the construction of the office building A in South Korea.

Background: Our previous study highlighted important healthcare access and utilization concerns among new immigrants. Hence, in this study, we aimed to explore the role of public and patient involvement (PPI) may have in enhancing the accessibility and their contribution to migration health studies. Method: An open and in-depth interactive consecutive virtual discussion was conducted among volunteer asylum seekers and refugees from Eritrea and Syria in Switzerland. The novel PPI establishment had three phases; inception, training phase, and contribution phase. Result: At the beginning, the concept of PPI was apprehensive to grasp, as it was a new approach. After training and consecutive discussions, volunteers were ardent to engage actively. Hence, among the prime findings were the PPI's role and effect in raising awareness, PPI's role in exploring and communicating the healthcare system accessibilities and utilization among their community, the impact of PPI in echoing the healthcare needs of their fellow migrants, and PPI's contribution in enhancing and strengthening migration health researches. Conclusion: The PPI volunteers in the study were keen to raise their community's awareness through their networks, and bridge the research gap between researchers and the public.

Electrochemical methods are used for the treatment of both municipal and industrial wastewater, either independently or in conjunction with biological methods. This conjunction is used for pretreatment or posttreatment of biologically treated wastewater. In our work, we focused on the combination of these processes, where pre-electrolysis was used to produce dissolved iron before the activation process. Electrolysis was also directly introduced into the activation using either iron or carbon electrodes. The surface of one iron electrode was 32.2 cm2, the applied voltage was 21 V, and the supplied current was 270 mA. The surface of one carbon electrode was 7.54 cm2, the supplied current was 82.5 mA, and the applied voltage was 21 V. From laboratory research on the treatment of synthetic municipal wastewater using a combination of electrolysis and activation processes, it resulted that the use of iron electrodes increased the efficiency of phosphorus removal compared to its precipitation with iron salts. The electrolysis had a positive effect on the sedimentation properties of sludge and the destruction of filamentous microorganisms. Electrolysis negatively affected the respiration rates of activated sludge and the efficiency of denitrification. However, it did not have a negative impact on the nitrification activity of the sludge.

Attribute reduction is a core technique in the rough set domain and an important step in data preprocessing. Researchers have proposed numerous innovative methods to enhance the capability of attribute reduction, such as the emergence of multi-granularity rough set models, which can effectively process distributed and multi-granularity data. However, these innovative methods still have many shortcomings, such as how to deal with complex constraints and how to perform multi-angle effectiveness evaluations. Based on the multi-granularity model, this study proposes a new method of attribute reduction, namely using multi-granularity neighborhood information gain ratio as the measurement criterion. This method combines both supervised and unsupervised perspectives, and by integrating multi-granularity technology with neighborhood rough set theory, constructs a model that can adapt to multi-level data features. This model can select the optimal granularity level or attribute set according to the requirements. Finally, the proposed method is experimented with on 15 UCI datasets against six other attribute reduction algorithms. The experimental outcomes, upon analysis and comparative review, substantiate the reliability and consistency of the attribute reduction approach introduced in this study.

Computer vision is a rapidly developing field that focuses on highly sophisticated picture analysis, manipulation, and comprehension. Its objective is to analyze what is happening in front of a camera and utilize that understanding to control a computer or robotic system or to present users with fresh visuals that are more enlightening or appealing than the original camera images. Computer vision technologies make it feasible for new user interfaces, augmented reality gaming, biometrics, automobile, photography, movie creation, Web search, and many more applications. This essay seeks to explain how computer vision can be utilized to play blackjack successfully.

1) Background: Several studies have shown the benefit of drawing when learning anatomy. Virtual Reality (VR) also appears to be useful to increase the understanding of the location of anatomical structures. This study aims to describe how students in an Operating Room Nursing (OR nursing) master study program perceive the benefit of active learning methods, including drawing and the use of VR. 2) Methods: We combined these two methods in a class of 29 students. 38 half-finished drawings of anatomical structures were made. The students were to complete these during lectures with guidance from the teacher. The students also attended a two-hour VR session where they were to find various anatomical structures. A paper questionnaire was applied to evaluate the teaching program. Data were analyzed statistically. 3) Results: The students highly appreciated these learning methods. They reported that drawing made them work more actively during lectures and increased their learning outcome. They also perceived that the use of VR technology increased their understanding of the location of anatomical structures. 4) Conclusion: The combination of drawing and VR technology may be of benefit to OR Nursing students when learning anatomy by both increasing student activity and learning outcomes.

Carbapenem-resistant Acinetobacter baumannii (CRAB) infections represent the fourth-leading cause of death attributable to antimicrobial resistance globally, but a standardized therapy is still lacking. In this narrative review we focused the antibiotic treatment of CRAB infections in view of newly β-lactam agents (NBLs) like sulbactam/durlobactam and cefiderocol, discussing the main hot points such as the superiority of combination treatment over monotherapy and the best antibiotic partner to use in combination. Sulbactam/durlobactam seems to be the best candi-date to replace current back-bone agents. Cefiderocol, could play a crucial role in combina-tion-regimen. Due to toxicity and the PK/PD limitations, colistin (or polymyxin B) should be used as an alternative agent (when no other options are available). Tigecycline (or minocycline) and fosfomycin could represent suitable partners for both NBLs. Randomized clinical trials (RCTs) are needed to better evaluate the role of NBLs in CRAB infection treatment and to compare the ef-ficacy of tigecycline and fosfomycin as partner antibiotics. Synergism should be tested between NBLs and “old” drugs (rifampicin and trimethoprim/sulfamethoxazole). Huge efforts should be made to accelerate pre-clinical and clinical studies on safer polymyxin candidates with lung im-proved activity, as well as on the i.v. rifabutin formulation.

Underwater visual detection technology plays a pivotal role in fields such as marine exploration. With the increasing demand for underwater monitoring, the quest for efficient and reliable methods for underwater target recognition has become particularly significant. To address this requirement, this study developed an innovative underwater object detection architecture based on YOLOv8, named YOLOv8-MU, aimed at significantly enhancing detection accuracy.By integrating the LarK module proposed in UniRepLKNet to optimize the backbone network, YOLOv8-MU aims to achieve a larger receptive field without increasing the model’s depth. Further, this research introduces C2fSTR, an innovative method that combines Swin Transformer with the C2f module. Additionally, we have incorporated the SPPFCSPC_EMA module, which combines Cross-Stage Partial Fast Spatial Pyramid Pooling (SPPFCSPC) with attention mechanisms, significantly improving the detection accuracy and robustness of various biological targets. Moreover, by introducing a fusion block based on DAMO-YOLO into the neck of the model, we further enhanced the model’s capability in multi-scale feature extraction. Finally, the adoption of the MPDIoU loss function, designed around vertex distance, effectively tackles the challenges of localization accuracy and boundary clarity in underwater organism detection. Experimental results on the URPC2019 dataset demonstrate that the YOLOv8-MU model achieved an [email protected] of 78.4%, marking improvements of 5.6%, 1.1%, and 4.0% over YOLOv5s, YOLOv7, and YOLOv8n respectively, indicating the leading performance (SOTA) of this method. On the other hand, further evaluation on the URPC2020 dataset confirmed the generalization capability of the YOLOv8-MU architecture, with its [email protected] reaching 80.4%, surpassing various models including YOLOv5x and YOLOv8n, showcasing the wide applicability of our proposed improved model architecture.

Antioxidant, anti-inflammatory and chemo-preventive features have been reported for the carotenoid diatoxanthin. Diatoxanthin is only produced by a few groups of microalgae where it functions in photoprotection. Its large-scale production in microalgae is currently not feasible. In fact, rapid conversion into the inactive pigment diadinoxanthin is triggered when the cells are removed from the high-intensity light source, which will be the case during large-scale harvesting of microalgae biomass. Zeaxanthin epoxidase (ZEP) 2 and/or ZEP3 have been suggested to be responsible for the back-conversion of high-light accumulated diatoxanthin to diadinoxanthin in low light in diatoms. Using the CRISPR/Cas9 gene editing technology we knocked out the ZEP2 and ZEP3 genes in the already commercially used marine diatom Phaeodactylum tricornutum to investigate their role in the diadinoxanthin-diatoxanthin cycle, and to determine if one of the mutant strains could function as a diatoxanthin production line. Light shift experiments proved that ZEP3 encodes the enzyme converting diatoxanthin to diadinoxanthin in low light. Loss of ZEP3 caused the high-light accumulated diatoxanthin to be stable for several hours after the cultures had been returned to low light, suggesting that zep3 mutant strains could be suitable as commercial production lines of diatoxanthin.

In this paper, a continuous power management for a decentralized DC microgrid (DCMG) is proposed to achieve voltage regulation and power balance even under system uncertainty and voltage sensor failure. The DCMG system achieves a continuous power management through only the primary controller to reduce the computational burden of each power agent. To enhance the reliability and resilience of the DCMG system under voltage sensor failure, a DC bus voltage (DCV) sensor fault detection algorithm is proposed. In this algorithm, the DCV sensor failure is detected by comparing the measured DCV with the estimated DCV. When the power agent identifies the DCV sensor failure, it changes the operation properly according to the proposed control mode decision algorithm to maintain the stability of the DCMG system. When uncertain conditions such as the power variation of the distributed generations, sudden grid disconnection, DCV sensor failure, electricity price change, and critical battery status occur, the DCMG system is changed to transitional operation modes. These transitional operation modes are employed to transmit the power agent information to other agents without digital communication links (DCLs) and to accomplish power sharing even under such uncertain conditions. In the transitional operation modes of the DCMG system, the DCV levels are temporarily shifted to an appropriate level, enabling each power agent to detect the uncertainty conditions, and subsequently to determine its operation modes based on the DCV levels. Simulation and experimental results under different test conditions confirm the reliability and effectiveness of the proposed control scheme.

This study aimed to identify miRNA editing sites during adipose tissue development in Ningxiang pigs and analyze their characteristics and functions. Based on the small RNA-seq data from subcutaneous adipose tissue samples of Ningxiang pigs at four stages (30, 90, 150 and 210 days), we constructed a developmental atlas of the miRNA editome in adipose tissue of Ningxiang pigs. The characteristics and functions of this editome were further explored through bioinformatics analysis. The findings revealed that a total of 505 miRNA editing sites were identified with C-to-U editing types being the most prevalent, followed by U-to-C, A-to-G and G-to-U. Importantly, these four types of miRNA editing exhibited a base preference. The number of editing sites showed obvious differences among age groups, with the highest occurrence of miRNA editing events observed at 90 days of age and the lowest at 150 days of age. In the miRNA seed region, a total of 9 miRNA editing sites were identified with significant differences in editing levels (P &lt; 0.05), and located in ssc-miR-23a, ssc-miR-27a, ssc-miR-30b-5p, ssc-miR-15a, ssc-miR-497, ssc-miR-15b, and ssc-miR-425-5p, respectively. Target gene prediction and enrichment analysis revealed that the editing of miR-497 may potentially regulate fat deposition by inhibiting adipose synthesis via influencing target binding. These results provide new insights into the regulatory mechanism of pig fat deposition.

Introduction. Autopsy is a medical procedure that consists of the corpse’s examination to determine the cause of death and obtain information on pathological conditions or injuries present in the body. In recent years there has been a reduction in hospital autopsies and an increase in forensic autopsies. Material and methods. A retrospective observational study was conducted on the reports of all the 645 hospital autopsies performed at Polyclinic of Bari from 2006 to 2021.Results. Group A, 2006-2009, 174 cases were studied: 58% male, 58% adults, 55% neonatology, pulmonary disease was the cause of death in 23%, and 55% of discrepancy between clinical and autopsy diagnosis. Group B, 2010-2013, comprised 119 cases: 52% male, 46% infants, 48% neonatology, pulmonary disease was the cause of death in 25%, and 56% of discrepancy between clinical and autopsy diagnosis. Group C, 2014-2017, comprised 168 cases: gender equality, 37% infants, 25% gynecology, pulmonary disease was the cause of death in 24%, and 58% of discrepancy between clinical and autopsy diagnosis. Group D, 2018-2021 comprised 184 cases: 56% male, 38% adult, 32% gynecology, pulmonary disease was the cause of death in 27%, and 58% discrepancy between clinical and autopsy diagnosis.Conclusion. The study of hospital autopsies at the Polyclinic of Bari shows that the discrepancy between clinical and autopsy diagnosis is around 56.75%. Thus, the hospital autopsy is helpful in the modern age, especially for diagnosing fetal and neonatal diseases.

The advancement in science and technology has led to luffa sponge (LS) being widely used as a natural material in industrial application as its polyporous structure and light texture. In order to enhance the utility of LS fibers as the reinforcement of lightweight composite materials, this study investigate its water absorption, mechanical properties, anatomical characteristic and thermal performance. Hence, moisture regain, tensile properties of LS fiber bundles were measured in accordance with standards and the structural characteristics were investigated via microscopic observation. Scanning electron microscopy (SEM) was used to observe the surface morphology and fracture surface of fiber bundles. Test results shows that the special structure where the phloem tissues degenerate to cavities had a significant influence on the mechanical properties of LS fiber bundles. Additionally, the transverse sectional area occupied by fibers in a fiber bundle (SF), wall thickness and ratio of wall to lumen of fiber cell, and crystallinity of cellulose had an impact on the mechanical properties of LS fiber bundles. Furthermore, the fiber bundles density of LS varies range of 385.46-468.70 kg/m³, much less than that of jute (1360.40 kg/m³) and Arenga engleri (950.20 kg/m³) while LS fiber bundles has superior specific modulus.

The aim of this study was to examine the oxidation of human serum albumin (HSA) caused by oxidative stress after an exhaustive exercise such as ultra-marathon race. Thus, blood samples from 12 adult runners who underwent a 103 km mountain ultra-marathon race were collected pre- and 24, 48 and 72 h post race. HSA was partially purified using affinity chromatography and then was subjected to Western blot analysis for disulfide dimers determination, indicating oxidation. The results were correlated with those from a previous study in which the same samples were analyzed using different oxidative stress markers and a good correlation with protein carbonyls (PC) at all time points was observed. Moreover there was a significant correlation with static oxidation-reduction potential (sORP) at 24 h, and a negative correlation with capacity oxidation-reduction potential (cORP) at 24 and 48 h. In addition, an individual analysis of albumin dimers exhibited great inter-individual differences. This inter-individual variability in the oxidation of HSA may suggest different interventions (e.g. through diet) in order to confront the effects on athletes’ organism after a strenuous exercise. In conclusion, this study supported the importance of the assessment of albumin dimers as a predictive marker for exercise-induced oxidative stress.

The supply chain has incorporated products by putting them into hair scarfs. This study introduces the use of mini chips in health and beauty products and can reduce fatigue through enhanced sleep patterns. The mini chip could be placed in the scarf and used as a prototype. RFID technology provides the supply chain with specific information that is used to identify products and make communication easier. (Muhammad, et. al. 2013) This paper presents a new tool herein referred to as a scarf prototype which is developed to analyse EMG (electromyogram), ECG (electrocardiography), EEG (electroencephalogram), and EOG (electro-oculogram) signals that focuses in the area of sleep disorders. The mini chips used can be used to determine a solution for sleep disruption by using automated analytics. This could lead to improvement in our understanding of sleep disruption and overall sleep physiology. Automated technology allows repeated measurements, evaluation of sleep patterns, and provide suggestions to improve a person’s quality of sleep. This analysis compares the use of polysomnography and the scarf prototype. The analytics provide models and shows correlation between variables, such as EMG, ECG, EEG, and EOG. This study shows that the results from the scarf prototype is just as reliable as the original method, polysomnography.

Effectively mapping and monitoring rubber plantation is still changing. Previous studies have explored the potential of phenology features for rubber plantation mapping through a pixel-based approach (pixel-based phenology approach). However, in fragmented mountainous Xishuangbanna, it could lead to noises and low accuracy of resultant maps. In this study, we investigated the capability of an integrated approach by combining phenology information with an object-based approach (object-based phenology approach) to map rubber plantations in Xishuangbanna. Moderate Resolution Imaging Spectroradiometer (MODIS) data were firstly used to acquire the temporal profile and phenological features of rubber plantations and natural forests, which delineates the time windows of defoliation and foliation phases. Landsat images were then used to extract a phenology algorithm comparing three different approaches: pixel-based phenology, object-based phenology, and extended object-based phenology to separate rubber plantations and natural forests. The results showed that the two object-based approaches achieved higher accuracy than the pixel-based approach, having overall accuracies of 96.4%, 97.4%, and 95.5%, respectively. This study proved the reliability of a phenology-based rubber mapping in fragmented landscapes with a distinct dry/cool season using Landsat images. This study indicated that the object-based phenology approaches can effectively improve the accuracy of the resultant maps in fragmented landscapes.

EUS–TA in unresectable pancreatic cancer requires not only a tissue diagnosis but also tissue collection in anticipation of comprehensive genomic profiling. However, the optimal puncture target remains controversial. Therefore, the Primary and Metastatic Lesions in Pancreatic Cancer (PRIMATE) study was designed to clarify the optimal target by comparing the success rates for meeting OncoGuide NCC Oncopanel (NOP) analysis criteria on pre-check primary and metastatic lesion specimens obtained during the same EUS–TA session in patients with invasive pancreatic ductal adenocarcinoma. In this ongoing prospective study, two specimens, each from primary and metastatic lesions, are obtained by EUS–TA (typically using a 19G fine-needle biopsy needle) in patients with invasive pancreatic ductal adenocarcinoma. The primary endpoint is the proportion of EUS–TA specimens that meet NOP analysis criteria during pre-check (i.e., tumor cellularity ≥ 20% and tissue area ≥ 4 mm2), which are then compared between primary and metastatic lesions. This study has been approved by the National Cancer Center Institutional Review Board (Research No. 2022-168). The results of this study will be reported at an international conference and published in an international peer-reviewed journal. The trial registration number is UMIN 000048966.

Nanocomposites of TiO₂ Degussa P25 nanoparticles/activated carbon (TiO₂/AC ) were prepared at various mass ratios of (4:1), (3:2), (2:3), and (1:4) by a facile process. The effects of TiO₂/AC mass ratios on the structural, morphological, and photocatalytic properties were systematically studied in comparison with bare TiO₂ and bare AC. TiO₂ nanoparticles exhibited dominant anatase and minor rutile phases, and a crystallite size of approximately 21 nm; while AC had XRD peaks of graphite and carbon, and a crystallite size of 49 nm. The composites exhibited tight decoration of TiO₂ nanoparticles on micron-/submicron AC particles, and uniform TiO₂/AC composites were obtained as evidenced by the uniform distribution of Ti, O, and C in an EDS mapping. Moreover, Raman spectra show the typical vibration modes of anatase TiO₂ (e.g., E_1g⁽¹⁾, B_1g⁽¹⁾, E_g⁽³⁾) and carbon materials with D and G bands. The TiO₂/AC with (4:1), (3:2), and (2:3) possessed higher reaction rate constants (k) in photocatalytic degradation of methylene blue (MB) than that of either TiO₂ or AC. Among the investigated materials, TiO₂/AC = 4:1 achieved the highest photocatalytic activity with a high k of 55.2×10^-3 min^-1 and an MB removal efficiency of 96.6% after 30 min treatment under UV-Vis irradiation (120 mW/cm²). The enhanced photocatalytic activity for TiO₂/AC is due to the synergistic effect of the high adsorption capability of AC and the high photocatalytic activity of TiO₂. Furthermore, TiO₂/AC promotes the separation of photoexcited electron/hole (e^-/h⁺) pairs to reduce their recombination rate and thus enhance photocatalytic activity. The optimal TiO₂/AC composite in this study can be used for treating industrial or household wastewater with organic pollutants.

: This study examines the prospects of residential water demand management policy regulations in Ethiopia and their implications for sustainable water resource management. This study aims to evaluate the existing policy regulations and analyze their effectiveness in promoting efficient water use and conservation practices in residential areas. By considering the potential challenges and opportunities associated with these regulations, the research provides insights into the future of residential water demand management in Ethiopia and suggests strategies for enhancing sustainable water resource management. Integrated literature and policy document review, alongside observation and interviews, was used to assess the viability of residential water demand management policies. The assessment of current policy regulations for residential water demand management in Ethiopian urban towns has revealed significant shortcomings in promoting water conservation activities. Hence, there is a need for significant improvements in the current water resource policy guidelines, which lack specificity, particularly in residential water demand management conservation strategies. The lack of awareness among residents regarding the importance of conserving their limited water resources is evident. To address these challenges and ensure the sustainability of the water supply, the government and policy developers must engage with various stakeholders, including the community, in the process of revising current policy documents. A more precise and tailored approach is necessary for its effective implementation.

To enhance pomegranate production on marginal gravelly lands, our study evaluated standardized planting techniques in an 8-year-old orchard. We employed trenching, wider pit excavation, pit digging, and auger digs with dimensions of 1 and 2 meters. Utilizing native soil from barren land, with or without spent wash, and mixing it with black soil up to 1 meter deep, we assessed growth parameters, leaf nutrients, and fruit yield. The trench and wider pit methods outperformed others, yielding greater above-ground biomass (>7.03 t tree-1), root biomass (2.5 t tree-1), and cross-sectional area (3.3 m² tree-1). Additionally, trench planting enhanced leaf phosphorus (0.28%) and potassium (1.8%) levels, fruit juice content (48.5%), total soluble solids (16.05°), and fruit yield (>9.3 t ha-1). The trench method also fostered longer roots at 90–150 cm radial distance and deeper roots at 40–60 cm depth. In summary, the trench and wider pit methods, combined with a soil mixture, are recommended for sustainable, high-quality fruit production in shallow gravelly terrains, thereby improving food security and the livelihoods of farmers in arid regions.

The authors present a framework for assessing seasonal events which may influence maritime operations. Most maritime-related research tends to focus on single events, such as a storm, but maritime systems operate within complex systems that have some predictable patterns. These predictable patterns due to natural events, such as weather and water levels, can influence operations, while other factors, such as cargo peaks or cultural activities, could also shape maritime systems. By integrating data from emergency management databases and weather information sources with other inputs, the authors created a matrix of regionally specific predictable events that may occur within a region by time of year. The matrix was vetted with various stakeholder groups to verify the information in the matrix. The main findings were that a seasonal event matrix is helpful as a reference for examining operational patterns in a river for various uses, such as training, operational planning, and emergency response coordination.

Sustainable Humanitarian logistics is gaining attention due to increased disasters. It involves various operations to support people's survival efforts. Key characteristics include unpredictable demand, sudden large demand volumes, high stakes in delivery timeliness, and limited resources. However, the complexity and unpredictability of disaster scenarios necessitate robust and adaptable performance measurement models to evaluate the effectiveness of sustainable humanitarian relief logistics (SHRL). This study proposes a novel performance measurement model for sustainable humanitarian logistics and supply chains that integrates the Fuzzy Delphi Method (FDM) and Fuzzy Decision-Making Trial and Evaluation Laboratory (Fuzzy-DEMATEL) method. In this research, using 115 articles focused on sustainable humanitarian logistics and supply chains, crisis management, and humanitarian aid, this research identified 25 key performance indicators (KPIs) in the initial phase. Following the implementation of FDM, 19 KPIs were identified as crucial for further analysis. These KPIs were then divided into four distinct categories: "Quality," "Accountability," "Operational Excellence," and "Sustainability". Initially, FDM is utilized to reach a consensus among experts concerning KPIs for humanitarian logistics and supply chains. By incorporating the inherent uncertainty and vagueness in expert judgments, FDM refines the list of key performance indicators that reflect the real-life conditions and constraints in disaster operations. Finally, the fuzzy DEMATEL approach was used to analyze interrelationships among factors, identifying cause-and-effect behavior and ranking them, forming a robust theoretical framework. The study concludes with the development of a comprehensive performance measurement model that facilitates the strategic planning and operational assessment of humanitarian organization operations. The integration of FDM and fuzzy DEMATEL methods offers multiple perspectives for decision-making and helps stakeholders identify critical areas for improvement. Based on the acquired results, the KPIs attached to the Quality (P1) aspect of the proposed framework have gained significant importance and main cause in the cause-and-effect relationship which impacts and is helpful to improve the performance of humanitarian organizations in all phases of disaster management. The KPIs prompt delivery (D1), and delivery accuracy (D2) are more significant, while capacity building and training (D19) and delivery compliance (D15) are least significant in SHRL scenarios. This research is expected to support humanitarian organizations in enhancing their capabilities, thereby improving the effectiveness and efficiency of aid delivery in disaster-stricken areas.

Improving the level of farmers' participation in collective action is an important way to promote rural revitalization and improve the sustainable livelihood level of farmers in underdeveloped areas. Based on 312 questionnaires of farmers in Shanxi Province, this paper investigates the status of farmers' participation in collective action, their sustainable livelihood level and the sustainable livelihood effect of collective action participation. The results show that: farmers' willingness to participate in collective action is strong, and the participation effect is obvious, but the participation frequency is low, and the participation time is less; The farmers' sustainable livelihood level is relatively low, Empirical research shows that the level of collective action participation will have a significant positive impact on Farmers' livelihood risk prevention, livelihood capital accumulation, livelihood mode selection and livelihood income improvement, and the frequency, time and value perception of participation in collective action will have varying degrees of impact on Farmers' sustainable livelihoods. In order to promote farmers' active participation in collective action, it is proposed to strengthen the construction of collective organizations Provide incentives and improve the quality and skills of farmers to enhance the collective concept and other policy recommendations.

(1) In an era where sustainable behavior is increasingly crucial, understanding the discrepancy between individuals' sustainability-oriented values and their actual behaviors, known as the inner-outer gap, is vital. This study explores the potential of the Tripartite Structure of Sustainability (TSS) framework to address this gap within the context of sustainable education. By reviewing literature from the databases APA, ERIC, and Web of Science, we systematically examined factors influencing sustainable actions. (2) Employing a qualitative content analysis approach, we analyzed 56 articles over a 15-year period, identifying 83 factors that either bridge or reinforce the inner-outer gap. These factors were categorized within the TSS framework, which segments sustainability-oriented actions into individual, social, and self-transcendent domains, alongside their activation points: stable, situational, or automated. (3) Our analysis revealed that self-focused factors often reinforce the gap, suggesting a hindrance to sustainable behavior. Conversely, self-transcendent factors consistently bridged the gap, promoting sustainability. Social factors showed variable impacts based on the ethical and sustainable context they were placed in, suggesting that the social environment's orientation significantly influences sustainable behavior. (4) The study concludes that the TSS framework offers a promising approach to advancing sustainability in education by facilitating a paradigm shift towards holistic and interconnected perspectives. This shift is critical for fostering sustainable behaviors, thereby contributing to the field of educational psychology and offering practical implications for educators aiming to nurture a sustainable future.

Hong Kong is the biggest consumer of eggs in the world and ranks on the top with an average consumption of 24.52kg/capita/year. The egg consumption trend in Hong Kong has been increasing specifically; a drastic increase of about 100% has been observed from 2008 to 2020. One of the reasons behind this significant increase is the increase in the gross national income of Hong Kong in addition to the population growth rate. However, there was a slight decline in egg consumption trend in the year 2020 amid the COVID-19 pandemic. It has been estimated that there was a bulk of 17,100 tons of recoverable waste eggshells in 2019 (pre-COVID-19 situation), having a daily yield of 47 tons per day. Based on the linear regression, it may be expected that if the pre-COVID-19 trend of egg consumption remains sustained, there will be a big bulk of more than 45,000 tons per year and up to 125 tons per day of waste eggshells till 2050. In addition, a public survey was conducted across the city targeting individuals, families, and restaurants majorly on egg consumption and reuse. The survey outcomes revealed that Chinese eggs have an extensive market in Hong Kong, and people have a positive attitude towards eggshell recycling. Also, a massive population disposes of the waste eggshells while only a trace population reuses them. Therefore, Hong Kong has a very high potential to improve the circular economy by reusing waste eggshells on a commercial level in cementitious products.

At the Rio Conference in 1992, the sustainable development agenda promised a new era for natural resource management, where the well-being of human society would be enhanced through the sustainable use of natural capital. Several decades on, economic growth continues unabated at the expense of natural capital, as evidenced by biodiversity loss, climate change and further environmental issues. Why is this happening and what can be done about it? In this research, we present three Agent-Based Models that explore the social, economic and governance factors driving (un)sustainability in complex social-ecological systems. Our modelling results reinforce the idea that the current economic system does not protect the natural capital on which it depends. This is due to a disjunction between the economic and environmental elements upon which the sustainable development paradigm is founded. Additionally, various factors appear to enhance social-ecological system unsustainability: the role of financial entities and monetary debt; economic speculation; technological development and efficiency; lack of long-term views and late government interventions; inefficient tipping point management; and the absence of strong top-down and bottom-up conservation forces. Interestingly, alternative scenarios showed that these same factors could be redirected to enhance sustainable development. The current economic system may, therefore, not be inherently unsustainable, but rather specific economic mechanisms, agents’ decision-making, and the kinds of links between economic and natural systems could be at the root of the problem. We argue that short- and medium-term sustainability can be enhanced by implementing mechanisms that shift capitalist forces to support environmental conservation. Long-term sustainability, however, requires further paradigm change: where the economy integrates, and fully accounts for, externalities and recognises the actual value of natural capital.

The analysis of the land use dynamics of the Lac Télé Community Reserve (RCLT) using Landsat Thematic Mapper (TM) and (Enhance Thematic Mapper) ETM+ images highlight significant changes in the vegetation cover from 1980 to 2000 and 2018. Thus, the rate of forest area decreased by 21.41% for the entire LTCR in favor of savannahs which increased by 15.23%. The conversion of this forest area to savannah due to the practice of slash and burn agriculture facilitates the opening up of the forest area and contributes to greatly degrading the spawning grounds of fish species from the Likouala aux herbes river. For the mapping of fishing activity in general and the ecological characterization of the 151 identified spawning grounds in particular; the respective mean values of the physical and chemical water parameters; temperature (28.13°C), pH (4.23) and depth (3.34) did not vary significantly from one selected village to another between July and September 2019. The fish diversity unregistered during the study, in the 07 pilot villages would be due to the diversity of the microhabitats noted in the villages of the LTCR, especially from the villages; Botongo, Mossengue and Bouanela where the indices of ichthyological diversity were the highest.

Empowering teachers with Critical Thinking and understanding of sustainability is vital for guiding students’ informed decisions and actions in today’s world. Higher education needs innovative, student-centered methods like case-based teaching in order to promote Critical Thinking and the principles of Education for Sustainable Development. The aim of the study was to explore and evaluate pre-service teachers' Critical Thinking when engaged with case studies in a practicum preparation course centered on Education for Sustainable Development. Nine undergraduate students in Teacher Education participated in the study and answered four case studies. The case studies’ responses were analyzed through a bottom-up content analysis revealing eight higher-order categories. While approaching the case studies, student-teachers followed thinking processes similar to the processes proposed by the iterative models of Critical Thinking as perceived by Garrison (1991) and/or Brookfield (1987). Nevertheless, in some cases, pre-service teachers’ disengagement was evident. The rubric assessment highlighted that the responses fell under three profiles, namely the “Deficient Critical Thinker”, the “Emerging Critical Thinker” and the “Competent Critical Thinker”. The findings emphasize the need for targeted and individualized teaching interventions in teacher higher education programs aiming at Education for Sustainable Development complying with the learning needs of student-teachers’ Critical Thinking profiles.

Ever since oil was discovered in the Persian Gulf Region in the 1920s, the oil and gas industries have been dominant in the area. These countries are responsible for generating approximately 35 percent of the world's natural gas and 25 percent of its crude oil, making them the largest crude oil producers globally. The release of carbon dioxide (CO2) into the atmosphere is directly linked to the use of fossil fuels. CO2 accounts for 58.8 percent of all greenhouse gas emissions caused by human activities and has a detrimental impact on urban residents through the urban heat island effect. A significant portion of these emissions can be attributed to residential buildings. Some nations exacerbate the problem by relying excessively on fossil fuels. Oil-rich countries provide energy subsidies to the public in order to lower energy costs for their citizens. However, this policy can have negative consequences, including wasteful energy usage in countries like Iran.

This paper explores the challenges faced by blue-collared international migrants in adapting to new and unfamiliar climates while pursuing job opportunities, with a focus on poverty alleviation. Drawing on existing research and empirical evidence, the study investigates the trials encountered by these migrants as they navigate climate shocks and assesses the potential impacts on poverty reduction efforts. The findings underscore the significant difficulties blue-collared migrants experience when confronted with abrupt changes in climate conditions, adversely affecting their physical and mental well-being, as well as their employment prospects. The process of adjustment involves not only acclimating to new climate patterns but also navigating cultural nuances and social dynamics, exacerbating stress and feelings of isolation. Consequently, these challenges can perpetuate poverty by disrupting employment stability and limiting opportunities for career advancement. To address these issues, the paper proposes comprehensive support measures, including targeted pre-departure training programs, access to retraining opportunities, and assistance in securing sustainable livelihoods. By prioritizing climate resilience and empowering blue-collared migrants to adapt effectively to new climates, it becomes possible to enhance their livelihood prospects, reduce poverty levels, and foster sustainable development. The paper concludes by highlighting the significance of integrating climate adaptation strategies with poverty alleviation efforts to create a more inclusive and resilient future for blue-collared migrants in their pursuit of sustainable livelihoods.

Agriculture has been experiencing a difficult situation because of limiting factors in its production, Natural biostimulants (NBs) have emerged as a novel alternative. This study reviews NBs produced through Solid-State Fermentation (SSF) from organic waste, focusing on the processes and production methods. The aim is to highlight their potential for improving agricultural productivity and promoting sustainable agriculture. Through a literature review, the effects of NBS on crops were examined, as well as the challenges associated with their production and application. The importance of standardizing production processes, optimizing fermentation conditions, and assessing their effects on different crops is emphasized. Furthermore, future research areas are identified, such as enhancing production efficiency and evaluating the effectiveness of SSF-produced NBS in different agricultural systems. In conclusion, SSF-produced NBS offers a promising alternative for sustainable agriculture, but further research and development are needed to maximize its efficacy and enable large-scale implementation.

This paper systematically identifies the constructs and indicators to measure Sri Lankan rice farmers’ Sustainable Agriculture potential (SAP) in the regions of Mahaweli Block H in Anuradhapura district, a dominant rice cultivation district in the country. Insights from Rural Livelihood Assessment Framework helped identify the primary constructs of SAP: The constructs of farmers’ SAP are derived as Human, Social, Financial, Physical, and Natural capitals. The principles of Sustainable Agriculture discussed in modern literature and the various research studies carried out in this domain are insightful to derive an exhaustive list of indicators that might adequately explain the constructs of SAP. The researcher adopted a quantitative descriptive approach, developed a comprehensive set of indicators (130), pre-tested them, and conducted a pilot survey with 64 samples. The measurement model analysis techniques in PLS-SEM helped shorten the Questionnaire with the most productive questions (87). This short-listed Questionnaire was again surveyed in a larger sample space, 386, to attest to their validity further. The study found five constructs and 87 productive questions that can explain farmers’ SAP, and the researcher believes that these compositions of SAP and the indicators will be helpful for future researchers.

A new sustainable heterogenous catalyst for copper-catalyzed azide-alkyne cycloaddition reaction (CuAAC) was investigated. The preparation of the sustainable catalyst was carried out through the complexation reaction between the polysaccharide cellulose acetate backbone (CA) and copper(II) ions. The resulting complex [Cu(II)-CA] was fully characterized by using different spectroscopic methods such as FTIR, SEM, EDX, UV-Vis, and ICP analyses. The Cu(II)-CA complex exhibits a high activity in the CuAAC reaction for substituted alkynes and organic azides, leading to a selective synthesis of the corresponding 1,4-isomer 1,2,3-triazoles in water as solvent and working at room temperature. It is worth noting that this catalyst has several advantages from the sustainable chemistry point of view including no use of additives, biopolymer support, reactions carried out in water at room temperature, and easy recovery of the catalyst. These characteristics make it a potential candidate not only for the CuAAC reaction but also for other catalytic organic reactions.

Countries in West Africa are adversely affected by climate change (erratic rainfall and rising temperature) resulting in floods, desertification, drought and sea level rise. These events are anticipated to have negative impacts on agricultural development on the continent, ultimately, contributing to food insecurity and environmental degradation. This implies that the production capacity of agrarian communities is unable to meet the food demand of the growing urban population. Can sustainable and innovative urban farming technology such as aquaponics achieve food security as well as sustainable development in countries vulnerable to climate change? This study uses inferential statistic to examine the plant growth performance in micro-scale aquaponics and specific growth rate per day (SGR) for the fish growth performance vis-à-vis conventional urban farming production. A quantitative analysis use to examine the barriers to adoption based on survey of (five) urban aquaculture practitioners in Lagos, Nigeria. Literature review was use to assess the economic feasibility of a small-scale aquaponics system in developing countries based on Net-Discounted Benefit-Cost Rate (DBCR). The results suggest that aquaponics can improve food security through fish and vegetable production and it is likely that urban farming practitioners will adopt the technology if support mechanism are in place. Aquaponics systems present a novel opportunity to promote environmental conservation as well as sustainable food production and consumption in urban areas in Western Africa if adequate financial credit and knowledge transfer is provided.

Climate change is a major threat to agricultural food production globally and locally. It poses both direct and indirect effects on soil functions. Thus, agricultural management practices has evolved to adaptation strategies in order to mitigate the risks and threats from climate change. The study concludes with a recommendation the coconut farmers should explore the idea of soil biodiversity in a bid to mitigate the potential negative impact of climate related risk on the farming. The study proffers the need for adopting sustainable agricultural practices to boost local coconut production. This can contribute to the simultaneous realisation of two of the Sustainable Development Goals (SDGs) of the United Nations: SDG 2 on food security and sustainable agriculture and SDG 13 on action to combat climate change and its impacts. The study findings has implications for tackling climate change in Sub-Saharan Africa and in particular Nigeria in order to boost local agricultural production and coconut in particular without negative environmental consequences and an ability to cope with climate change related risks.

Sustainable urban drainage systems (SuDS) such as swales are designed to collect, store and infiltrate a large amount of surface runoff water during heavy rainfall. Stormwater is known to transport pollutants, such as particle-bound Potential Toxic Elements (PTE), which are known to often accumulate in the topsoil. A portable XRF instrument (pXRF) is used to provide in situ spatial characterization of soil pollutants, specifically lead (Pb), zink (Zn) and copper (Cu). The method uses pXRF measurements of PTE along profiles with set intervals (1 meter) to cover the swale with cross-sections, across the inlet, the deepest point and the outlet. Soil samples are collected, and the In-Situ measurements are verified by the results from laboratory analyses. Stormwater is here shown to be the transporting media for the pollutants, so it is of importance to investigate areas most prone to flooding and infiltration. This quick scan method is time and cost-efficient, easy to execute and the results are comparable to any known (inter)national threshold criteria for polluted soils. The results are of great importance for all stakeholders in cities that are involved in climate adaptation and implementing green infrastructure in urban areas. However, too little is still known about the long-term functioning of the soil-based SuDS facilities.

Chitosan decorated copper nanoparticles catalysts (CSCuNPs) were synthesized via reduction methods utilizing green protocol. The CSCuNPs catalysts were tested for the synthesis of quinoline derivatives utilizing one-pot multicomponent reaction (MCR) under ultrasonic irradiation. The best catalyst (Cu-CS-NPs) that provided good conversion reaction yield and high turnover frequency (TOF) was characterized using FTIR, TGA, XRD, TEM and XPS techniques. Generalization of the scope of the proposed catalytic process was studied using different aldehydes. Excellent products yield and high TOF in even shorter reaction time (~5 min) was attained. Recyclability performance of the catalyst over five times re-use without detectable loss in product yield was recorded. The current method is green process utilizing environmentally benign catalyst and considered to be promising sustainable protocol for the synthesis of fine chemicals.

Universities can do more to deliver against the Sustainable Development Goals (SDGs), working with faculty, staff and students as well as their wider stakeholder community and alumni body. They play a critical role in helping shape new ways for the world, educating global citizens and delivering knowledge and innovation into society – universities can be engines of societal transformation. Here, using a case study approach, different ways of strategizing sustainability in a university setting are explored with an example from the UK, Europe and USA. The first case is a public UK university that adopted enterprise and sustainability as its academic mission to secure differentiation in a disrupted and increasingly marketized global higher education sector which then became a source of inspiration for change in regional businesses and the local community. The second case study is a business sector-led sustainability-driven transformation working with a private university in Bulgaria to catalyze economic regeneration and social innovation. Finally, the case of Harvard’s Office for Sustainability engagement program is given to show how this approach connects faculty and students with institutional sustainability plans and external partners. Each case is a living lab, positioning sustainability as an intentional strategy. Leadership at all levels, and by students, was key to success in acting with purpose. Partnerships within and with universities can help accelerate delivery of the SDGs, with higher education making a fuller contribution to sustaining the economic, cultural and intellectual well-being of our global communities.