Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) continues to be a global threat due to its ability to evolve and generate new subvariants, leading to new waves of infection. Additionally, other coronaviruses like Middle East respiratory syndrome coronavirus (MERS-CoV, formerly known as hCoV-EMC) which first emerged in 2012, persists and continues to present a threat of severe illness to humans. The continued identification of novel coronaviruses, coupled with the potential for genetic recombination between different strains, raises the possibility of new coronavirus clades of global concern emerging. As a result, there is a pressing need for pan-CoV therapeutic drugs and vaccines. After extensive optimization of an HCV protease inhibitor screening hit, a novel 3CLPro inhibitor (MK-7845) was discovered and subsequently profiled. MK-7845 exhibited nanomolar in vitro potency with broad spectrum activity against a panel of clinical SARS-CoV-2 subvariants and MERS-CoV. Furthermore, when administered orally, MK-7845 demonstrated a notable reduction of viral burdens by >6 log orders in the lungs of transgenic mice infected with SARS-CoV-2 (K18-hACE2 mice) and MERS-CoV (K18-hDDP4 mice).

Diabetes is a major health concern that the next-generation of on-demand insulin releasing implants may overcome for personalized therapy. Therein, 3D-printed phenylboronic acid-containing subcutaneous implants with on-demand glucose-triggered drug release abilities are produced using high resolution stereolithography technology. To that end, the methacrylation of phenylboronic acid is targeted following a two-step reaction. The resulting photocurable phenylboronic acid derivative is accordingly incorporated within bioinert polyhydroxyethyl methacrylate-based hydrogels at varying loadings. The end result are sub-centimeter scaled 3D-printed bionert implants that can be remotely activated with 1,2-diols and 1,3-diols such as glucose for on-demand drug administration such as insulin. As a proof of concept, varying glucose concentration from hypoglycemia to hyperglycemia levels readily allow the release of pinacol, i.e. a model molecule with similar release properties than insulin, at respectively low and high rates. In addition, the results demonstrated that adjusting the geometry and size of the 3D-printed part is a simple and suitable method for tailoring the release behavior and dosage.

This study examines the dynamic relationship between Green Human Resource Management (Green HRM), Environmental Performance (EP), Green Employee Behavior (GEB), and Environmental Knowledge and Awareness (EKAW) within the Egyptian hospitality sector context. Using Pearson correlation coefficients and regression analyses on a sample of 400 staff members from hotels and tourist villages in Egypt, the study examines Green HRM practices’ influence on EP, mediated by GEB and moderated by EKAW. The findings reveal significant positive correlations between Green HRM practices and these mediators, indicating that comprehensive environmental strategies and incentive management are pivotal in promoting eco-friendly practices among employees. The study further confirms GEB and EKAW’s substantial mediating role in enhancing EP. The results also suggest that while EKAW and GEB independently contribute to EP, their interaction and the role of environmental awareness as a potential moderator warrant further examination. This research contributes to the literature on sustainable business practices by underscoring human resource strategies’ integral role in achieving environmental sustainability goals, highlighting the importance of incentivizing green practices, and cultivating an organizational culture that prioritizes EKAW. These insights are particularly valuable for organizations seeking to enhance their ecological footprint through effective Green HRM practices.

Different from national systems of innovation, a knowledge-based economy is grounded in the volatility of discursive knowledge enabling us to specify expectations. Expectations can be improved by testing against observations. Furthermore, expectations can differently be codified; for example, in terms of market perspectives and technological opportunities. The Triple Helix of university-industry-government relations provides first a (neo-)institutional model. However, three functions are recombined at the systems level in each instantiation: wealth generation (by industry), novelty production (academia), and legislation and regulation (government). The Triple-Helix synergy indicator enables us to use the institutional arrangements as instantiations of the knowledge-dynamics and thus to assess the generation of options and reduction of uncertainty in information-theoretical terms. The Fourth Industrial Revolution entails the transition to the reflexive entertaining of expectations in terms of models as increasingly the sources of innovations.

Citrus species essential oils (EOs) are significant sources of bioactive compounds and demonstrate diverse therapeutic effects. However, limited documentation exists regarding the phytochemicals associated with their biological activities. This study aims to assess the antioxidant activity, plant inhibitory properties, and brine shrimp cytotoxic effects of EOs derived from three Citrus species: C. sinensis, C. limon, and C. hystrix. Utilizing chemometric analysis and gas chromatography-mass spectrometry (GC-MS) fingerprints, the volatile components contributing to antioxidant activity were elucidated. The peels of the Citrus samples were hydro-distillated to obtain EOs, and subsequently subjected to antioxidant, plant inhibitory, and brine shrimp cytotoxic assays. The results indicated that C. limon EO exhibited the highest antioxidant activity, while C. hystrix and C. sinensis EOs demonstrated pronounced inhibitory effects against Aetrmia salina and Lactuca sativa, respectively. GC-MS analysis facilitated the identification of key compounds in each EO. Principal component analysis (PCA) and hierarchy cluster analysis (HCA) effectively categorized Citrus EOs based on their antioxidant properties, highlighting the proximity of C. limon and C. sinensis. Among the identified compounds, D-limonene, α-Terpineol, Caryophyllene, (+)-3-Carene, β-Pinene, (-)-Spathulenol, trans-p-Mentha-1(7),8-dien-2-ol, and trans-Verbenol were the most discriminating compounds affected the antioxidant activity of C.limon and C. sinensis EOs.

This work presents a novel compact CMOS potentiostat designed circuit for electrochemical cell. The proposed topology functions as a circuit interface, controlling the polarization of voltage signals at the sensor electrodes and facilitating current measurement during the oxidation-reduction process of a analyzed solution. The potentiostat, designed for CMOS technology, comprises a two-stage amplifier, two current mirror blocks coupled to this amplifier, and a CMOS push-pull output stage. It employs the electrochemical method of cyclic voltammetry, operating within voltage range of ±0.8 V and scan rates of 10mV/s, 25mV/s, 100mV/s and 250 mV/s. The circuit is capable of reading currents ranging from 10 µA to 500 µA. Experimental results were obtained using a potassium ferrocyanide (K3(FeCN)6) redox solution with concentrations of 10, 15 and 20 mmol/L, and their corresponding voltammograms were evaluated. The experimental results from a discrete circuit demonstrate that the proposed potentiostat topology produces outcomes consistent with those of classical topologies presented in the literature and industrial equipment.

The interaction forces and mechanical properties of the interaction between melittin (Mel) and lipopolysaccharide (LPS) are considered a crucial driving force for Mel in killing Gram−negative bacteria (GNB). However, how their interaction forces are performed at the single−molecule level and the dissociation kinetic characteristics of the Mel/LPS complex remain poorly understood. In this study, the single−molecule level interaction forces between Mel and LPSs from E. coil K−12, O55:B5, O111:B4, and O128:B12 were explored using atomic force microscopy (AFM) based single−molecule force spectroscopy (SMFS). Further, the AFM−based dynamic force spectroscopy (DFS) and advanced analytical model were employed to investigate the kinetic characteristics of the Mel/LPSs complex dissociation. The results indicated that Mel could interact with both rough (R)−form LPS (E. coli K−12) and smooth (S)−form LPSs (E. coli O55:B5, O111:B4, O128:B12), and the S−form LPSs showed a more robust interaction with Mel than R−form LPS, and a slight difference existed in the interaction forces between Mel and diverse S−form LPSs. The Mel interacts with S−form LPSs showed greater specific and non−specific interaction forces than R−form LPS (p < 0.05), as determined by AFM−based SMFS. However, there was no significant difference in the specific and non−specific interaction forces among the three S−form LPSs (p > 0.05), indicating the variability of O−antigen could not affect the interaction between Mel and LPSs. The DFS result showed that the Mel/S−form LPSs complexes had a lower dissociation rate constant (koff), a shorter energy barrier width (xβ), a longer bond lifetime (τoff), and a higher height of the energy barrier (∆G), demonstrating that Mel could interact with S−form LPSs to form more stable complexes. In conclusion, this study promotes our knowledge of the interaction micromechanics and kinetics characteristics between Mel and LPS at the single−molecule level. Moreover, it can help us design and evaluate new anti−GNB drugs.

Autonomous navigation in dynamic environments poses a significant challenge in the field of ro-botics with the primary goals of ensuring both smooth and safe movement. This study introduces control strategy based on an Adaptive Neuro-Fuzzy Inference System (ANFIS) to enhance au-tonomous robot navigation in dynamic environments, emphasizing on collision-free path plan-ning. This strategy employs, a path planning technique to develop a trajectory that allows the ro-bot to navigate smoothly while avoiding collisions with both static and dynamic obstacles. The developed control system incorporates four ANFIS controllers: two are tasked with guiding the robot toward its end point, and the other two are activated for obstacle avoidance. The experi-mental setup conducted in CoppeliaSim involves a mobile robot equipped with ultrasonic sensors navigating in an environment with static and dynamic obstacles. Simulation experiments are conducted to demonstrate the model's capability in ensuring collision-free navigation, employing a path planning algorithm to ascertain the shortest route to the target destination. The simulation results highlight the superiority of the ANFIS-based approach over conventional methods, partic-ularly in terms of computational efficiency and navigational smoothness.

The Qiushuwan Cu-Mo deposit, located in the East Qinling molybdenum belt, which is a major mining site recognized for its enormous reserves of medium-sized molybdenum. In order to enhance our comprehension and ascertain supplementary mineral resources, it is critical to conduct an in-depth investigation of both the deep and peripheral regions. The primary goal of this study is to investigate the Qiushuwan Copper Molybdenum Mine, which is located in Zhenping County, Henan Province. The spread spectrum-induced polarization (SSIP) method is utilized as a means of conducting mining exploratory analysis. Significant findings have been obtained through the collection of SSIP data, geological analysis, and electrical parameter study of rock and ore samples along profile-80. By conducting a meticulous examination of the SSIP data at suitable frequencies, two prominent conductive ore bodies, specifically C2 and C4, have been successfully discovered. C2 exhibits a correlation with granite porphyry and molybdenum veins, while C4 is linked to a skarn deposit that contains a concentration of copper ore. The spatial differences in conductivity within the research area have been precisely characterized using resistivity models obtained from the SSIP data. The precision and dependability of our conclusions have been confirmed through the integration of borehole data and the matching of geological sections with inversion models. The recovered core samples show a diverse range of minerals, containing both valuable ores and minerals that have undergone alteration. Pyrite constantly appears with molybdenite in the majority of samples. The aforementioned results provide a strong foundation for future exploration initiatives and sustainable resource exploitation, enabling informed decision-making in the effective use and administration of natural resources. This study adds to the existing body of knowledge on the Qiushuwan Cu-Mo deposit and improves exploration methods in the region by utilizing the SSIP approach. The findings are a useful asset for geologists, mining experts, and stakeholders, offering essential knowledge for future exploration and sustainable utilization of resources.

The research presented in the article is devoted to the study of the influence of phase compounds on the friability of the Fe-Si-Mn-Al complex alloy. The urgency of the problem lies in the development of technology for producing a non-scatterable alloy from manganese-containing ores and high-ash coals. The main goal of the work is to determine the range of alloy compositions and the resulting phases that affect the dispersibility of the alloy, which is critically important for its industrial implementation. Research methods include thermodynamic diagram analysis (TDA) using data on the standard enthalpy of formation of intermetallic compounds, as well as experimental tests in an ore-thermal electric furnace with a capacity of 200 kV*A. The results show that Fe-Si-Mn-Al complex alloys form a variety of silicide and aluminide phases, including intermetallic compounds and ternary systems, which is critical for understanding and controlling their physicochemical properties. When smelting a complex alloy, the content of leboite (Fe3Si7) in the Fe-Si-Mn-Al system plays a significant role. The development of smelting technology will be aimed at avoiding the FeSi2-Fe3Si7-F2(FeAl3Si2)-Mn11Si19 tetrahedron area. This approach to controlling the composition of a complex alloy is critical to ensuring its consistent friability properties in industrial applications. Thus, this work represents an important step in understanding the physical properties and stability of Fe-Si-Mn-Al complex alloys, which have potential for widespread use in metallurgical and other industrial applications.

Oral cancer (OC) presents a significant global health burden with rising incidence rates. Despite advancements in diagnosis and treatments, the survival rate for OC patients, particularly those with advanced or recurrent disease, remains low at approximately 20%. This poor prognosis is often due to a small population of cancer stem cells (CSCs) that are capable of self-renewal and immune evasion, thus playing pivotal roles in proliferation, tumor initiation, progression, metastasis, and therapy resistance. Exosomes, nano-sized extracellular vesicles (EVs), have emerged as crucial mediators of cell-to-cell communication within the tumor microenvironment (TME). These vesicles carry diverse molecules such as DNA, RNA, proteins, lipids, and metabolites, influencing various cellular processes. Emerging evidence suggests that CSC-derived EVs are significant in promoting tumor progression and metastasis and maintaining the balance between CSCs and non-CSCs, which is vital for intracellular communication within the TME of oral cancer. Recent reports indicate that oral cancer stem cell-derived EVs (OCSC-EVs) influence stemness, immune evasion, metastasis, angiogenesis, tumor reoccurrence, and drug resistance. Understanding OCSC-EVs could significantly improve oral cancer diagnosis, prognosis, and therapy. In this mini-review, we explore OCSC-derived exosomes in oral cancer, examining their potential as diagnostic and prognostic biomarkers that reflect CSC characteristics, and delve into their therapeutic implications, emphasizing their roles in tumor progression and therapy resistance. However, despite their promising potential, several challenges remain, including the need to standardize isolation and characterization methods and to elucidate exosome-mediated mechanisms. Thus, a comprehensive understanding of OCSC-EVs could pave the way for innovative therapeutic strategies that have the potential to improve clinical outcomes for OC patients.

Producing translucent eggs has been found to reduce the quality and safety of the eggs produced., as well as the demand from consumers. However, the intestinal function and the molecular mechanism for the production of translucent eggs remain uncertain. A total of 120 eggs were allocated into two groups, one for the translucent egg group (group T) and one for the normal group (group C), according to the degree of eggshell translucence. Translucent eggs showed thicker eggshell and lower egg yolk color. We also detected the plasma biochemical index, intestinal morphology and structure, enzyme activity, and antioxidant capacity of the hens’ producing translucent eggs and normal eggs. The results showed that the ratio of duodenal villus length to crypt depth, succinate dehydrogenase (SDH) activity, chymotrypsin, total ATPase (T-ATPase), alkaline phosphatase (AKP) and glutathione peroxidase (GSH-Px) activities were decreased in the hens produced translucent eggs (P < 0.05), but malondialdehyde (MDA) content was increased (P < 0.05); jejunal lipase activity, Na+K+-ATPase activity, total antioxidant capacity (T-AOC), GSH-Px activities were decreased (P < 0.05) in group T; ileal amylase and Ca2+Mg2+-ATPase activities were also decreased (P < 0.05) in group T. In addition, we identified a total of 471 differentially expressed genes (DEGs) in duodenal tissue, with 327 up-regulated genes and 144 down-regulated genes (|log2FC| ≥ 1 and P < 0.05). Enrichment analysis showed that the up-regulated genes, such as GSTT1, GSTO2, GSTA3, were mostly enriched in metabolism of xenobiotics by cytochrome P450, drug metabolism-cytochrome P450 and oxidative phosphorylation pathways. The results of our study indicate that plasma lipid metabolism disorder, decreased intestinal antioxidant capacity, and altered intestinal metabolism capabilities may influence the formation of translucent eggs.

Digital transformation provides new drivers for economic performance growth in enterprises, but can it further improve ESG performance and support sustainable development? Based on the perspective of resources and capabilities, this paper uses the relevant data of 1588 listed companies in strategic emerging industries from 2011 to 2021 to study the differential impact of digital transformation on enterprise ESG performance, and further tests the mediating role of absorptive capacity and the moderating role of regional digital level. The research results indicate that: firstly, digital transformation of enterprises can positively promote the improvement of ESG performance; Secondly, there are significant differences in the impact of digital transformation on the ESG performance of enterprises in terms of property rights and industry characteristics. The ESG performance of state-owned enterprises and high-end equipment manufacturing enterprises is more sensitive to digital transformation; Thirdly, absorptive capacity plays a mediating role between digital transformation and corporate ESG performance; Fourthly, the positive regulation of regional digital level promotes the ESG performance of enterprises through digital transformation. The research conclusion is based on a digital perspective, providing relevant insights for improving the ESG performance of strategic emerging industry enterprises and expanding their ESG development paths.

Visual object tracking is an important technology in camera based sensor networks, which has a wide range of practicability in auto drive system. A transformer is a deep learning model that adopts the mechanism of self-attention, and it differentially weights the significance of each part of the input data. It has been widely applied in the field of visual tracking. Unfortunately, the security of the transformer model is unclear. It makes such transformer-based applications be exposed to security threats. In this work, the security of the transformer model is investigated with the important component of autonomous driving, visual tracking. Such deep-learning-based visual tracking is vulnerable to adversarial attacks, so adversarial attacks are implemented as the security threats to conduct the investigation. First, adversarial examples are generated on top of video sequences to degrade tracking performance, and the frame-by-frame temporal motion is taken into consideration when generating perturbations over the predicted tracking results. Then, the influence of perturbations on performance is sequentially investigated and analyzed. Finally, numerous experiments on OTB100, VOT2018, and GOT-10k data sets demonstrate that the executed adversarial examples are effective on the performance drops of the transformer-based visual tracking.

Structural deformations are one of the most significant factor that affects machine tool (MT) positioning accuracy. These induced errors are complex to be represented by a model, nevertheless they need to be evaluated and predicted in order to increase the machining performance. This paper presents a novel approach to calibrate a machine tool in real-time, analyzing the thermo-mechanical errors through Fibre Bragg Grating (FBG) sensors embedded in the MT frame. The proposed configuration consists of an adaptronic structure of passive materials, Carbon Fibre Reinforced Polymers (CFRP), equipped by FBG sensors that are able to measure in real-time the deformed conditions of the frame. By using a proper thermo-mechanical kinematic model, the displacement of the end effector may be predicted and corrected when it is subjected to external undesired factors. By starting from a set of FE simulations to develop a model able to describe the MT structure stresses, a prototype has been fabricated and tested. The scope was to compare the numerical model with the experimental tests using FBG sensors. The experimental campaign has been performed varying the structure temperature over time and measuring the tool tip point (TTP) positions. The obtained results showed a substantial matching between the real and the predicted position of TTP confirming the effectiveness of the proposed calibration system.

Federated learning is an effective approach for preserving data privacy and security, enabling machine learning to occur in a distributed environment and promoting its development. However, an urgent problem that needs to be addressed is how to encourage active client participation in federated learning. The Shapley Value, a classical concept in cooperative game theory, has been utilized for data valuation in machine learning services. Nevertheless, existing numerical evaluation schemes based on the Shapley Value are impractical as they necessitate additional model training, leading to increased communication overhead. Moreover, participants’ data may exhibit Non-IID characteristics, posing a significant challenge to evaluating participant contributions. Non-IID data weakens the marginal effects of participants, which in turn affects model accuracy and leads to underestimated contribution measurements. Current works often overlook the impact of heterogeneity on model aggregation. This paper presents a fair federated learning contribution measurement scheme that addresses the need for additional model computations. By introducing a noval aggregation weight, it enhances the accuracy of contribution measurement. Experiments on the MNIST dataset show that the proposed method can accurately compute the contributions of participants. Compared to existing baseline algorithms, the model accuracy is significantly improved, with a similar time cost.

Aim: This study aimed to understand the role of workforce agility as a coping strategy to curtail the COVID-19 pandemic. Method: The study reviewed and integrated two lines of literature to develop a theoretical framework to help business organizations to respond, adapt, and recover from the COVID-19 pandemic crisis. Results: The results showed that there are several commonalities between the workforce agility literature and the crisis management literature, mostly manifested in the speed of responding to uncertain and unpredictable, adverse events in the business environment. A thorough review of key themes in both kinds of literature led to developing a theoretical framework that links crisis drivers, crisis enablers, crisis capabilities, and response strategy. Workforce agility can be used as a coping strategy to deal with the COVID-19 pandemic crisis. Both kinds of literature evolve to respond to any crisis; the crisis management literature focuses on Meso-level (organizational level) or collective actions to mitigate the crisis, while the workforce agility literature focuses on the Micro-level (individual level). However, the successful response to any crisis requires the synergy of both actions. Future Studies: The results of this research are of prime importance for both researchers and practitioners. Researchers can use the theoretical framework as a baseline for building empirical research design. The current study also sets the context for future researchers who are interested in workforce agility to test the validity of agile work behaviors in real adverse context. It also opens a new stream of debate by deconstructing understudied links between workforce agility, resilience, and crisis management. Mangerial implication: For practitioners to ensure a successful response to any impending crisis, they must develop their employees’ agile behaviors. Practitioners can also redesign their recruitment strategy to select the right individuals with the right agile attributes, abilities, and behaviors to easily alter their behaviors according to the progressing crisis phases. Finally, practitioners can design continual learning interventions to include required agile skills and competencies to prepare their employees for future crises.

A model for enabling the production of lower carbon cement paste is proposed in this research. The model is based on predicting the strength of cement pastes with partial replacement of wheat straw ash (WSA) and silica fume (SF), two major wastes of agricultural and industrial production. The model is set up based on response surface methodology and Box-Behnken design, and included a suite of mechanical tests with distinct replacements following a micro an meso characterization. The model shows capability for predicting strength of any cement paste, including partial substitution of WSA and/or SF at any combination level with excellent accuracy, which is verified with three validation mixtures demonstrating maximum errors of less than 6% at the three ages. The analysis of the response surface evidences that any cement replacement in the range of 0-20% WSA and above 5% SF allows the reduction of the carbon footprint by maximizing the incorporation of both wastes. The proposed model can be used by setting the required strength of cement paste and calculating the maximum possible replacement, which should contribute to making the construction industry more sustainable by utilizing local waste.

The impact of climate change is undeniable: considering the significant carbon footprint of surgical activity, there is an urgent need to pursue sustainability in the operating room as well. At the Breast Surgery Clinic of the IRCCS Ospedale Policlinico San Martino in Genoa, a prospective study was conducted from September 2023 to May 2024 to evaluate the effectiveness of a series of measures aimed at reducing the environmental impact in the operating room. 34 women affected by invasive breast cancer T1-2, cN0 underwent quadrantectomy and sentinel lymph node biopsy (SNLB): 17 according to a standard, high environmental impact approach; 17 according to a green approach based on the "5 R rule" (reduce, reuse, recycle, rethink, research). The implementation of measures such as the use of indocyanine green (ICG) for SNLB, the use of local anesthesia and intravenous sedation, the minimization of waste production, the use of reusable gowns, drapes and surgical instruments and the separate collection of non-infectious plastic waste resulted not only in a reduced environmental impact, but also in benefits for patients, who were spared a hospital admission the day before surgery, the administration of a radiotracer, and, in 58.8% of cases, an overnight stay. Considering the alarming data regarding the threat to our health, it is both possible and necessary to adopt virtuous behaviors in the operating room that reverse the current trend of emitting greenhouse gases.

A convenient and efficient strategy for the preparation of 2-sulfonylindoles has been achieved through iodophor/H2O2-mediated 2-sulfonylation of indoles with readily available sulfonyl hydrazides in aqueous phase. Iodophor is commercially available and serves as the green catalyst and aqueous phase. A series of 2-sulfonylated products from indoles and N-methylpyrrole were synthesized in moderate yields in only 10 min. Control experiments were also conducted to reveal the mechanism. This method is environment friendly, easy to operate and suitable for a wide range of substrates.

This paper studies the influence mechanism of industrial agglomeration and foreign direct investment (FDI) on green total factor productivity (GTFP). We use the SBM Directional Distance Function to measure the GTFP of Chongqing's manufacturing industry from 1999 to 2015. The results show that the level of GTFP in Chongqing's manufacturing industry is relatively low, which is contrary to the current green development mode. By clarifying the conduction path of industrial agglomeration and FDI on GTFP, we use the panel Tobit model to study the effect of industrial agglomeration and FDI on GTFP. The main findings are: the higher the level of industrial agglomeration, the more beneficial it is to increase GTFP. FDI has an inhibitory effect on GTFP. The spillover effect of FDI on GTFP is not significant. At the same time, FDI counteracts the role of industrial agglomeration in promoting GTFP. The findings in a present study indicate that, according to Chongqing's experience, the "pollution haven" is established. Therefore, relying solely on foreign technology to promote the development of the manufacturing industry has many drawbacks clearly. Only by improving the ability of independent innovation is the reliable way to enhance GTFP effectively.

With the popularity of solar energy in the electricity market, demand arises for data such as precise locations of solar panels for efficient energy planning, management, and distribution. However, this data is not easily accessible and in some cases, information such as precise locations does not exist. Furthermore, existing data sets for training semantic segmentation models of PV installations are limited, and their annotation is time-consuming and labor-intensive. Therefore, for additional remote sensing (RS) data creation, the pix2pix generative adversarial network (GAN) is utilized, enriching the original resampled training data of varying GSDs without compromising its integrity. Experiments done with the DeepLabV3 model, ResNet-50 backbone, and pix2pix GAN architecture were conducted to find the optimal configuration for an accurate RS imagery segmentation model. The result is a fine-tuned solar panel semantic segmentation model, trained using transfer learning and utilizing an optimal amount – 60% of generated RS imagery for additional training data, increasing model accuracy. The findings demonstrate the benefits of using GAN-generated images as additional training data, increasing the size of small data sets, and improving the capabilities of the segmentation model for solar panel detection in RS images.

The rapid growth of the sharing economy has propelled shared mobility to the forefront of attention. The continuous advancement of autonomous driving technology also brings new opportunities and challenges to the shared mobility market. This study comprehensively analyzes the market potential concerning autonomous vehicles (AVs) to provide shared mobility services, utilizing SWOT analysis, PESTLE analysis, and Porter’s Five Forces. The findings reveal that AVs can provide improved shared mobility services by increasing transportation safety, reducing emissions, reducing costs, enhancing traffic efficiency, and increasing customer satisfaction and the profitability of shared mobility services. However, challenges such as technological and policy uncertainties, safety concerns, high initial costs, inadequate public communication infrastructure, and the absence of standardized regulations can hinder the widespread adoption of AVs. The benefits are also restricted with a low market penetration rate of AVs. To promote AVs in the shared mobility market, this study also provides implications for AV stakeholders tailored to the evolving shared mobility market dynamics.

This research aimed to study and compare prevalence of work-related musculoskeletal (MSK) problem and perceived discomfort among port crane operators consisting of quay and rubber tyred gantry (RTG) cranes working in the Laem Chabang Deep-sea Port, Thailand. Direct interviews for a cross-sectional analysis was selected for this unique job with a small amount of sample size. A standardized modified version of the Nordic Musculoskeletal Questionnaire (NMQ) was lunched for 26 male participants, consisting of 11 quay and 15 RTG, where a priori power analysis using G*Power suggested the minimum as 24 for the hypothesis test. Socio-demographic characteristics showed no significant difference among them. The NMQ revealed lower back as the highest prevalent body part (76.9%) followed by neck, shoulders and upper back at the same percentage (23.1%) for all port crane group, with up to 96.2% reporting MSK problem over the past 12 months. And Borg scale rating, assessing the perceived discomfort, revealed lower back with the highest score (2.38) followed by upper back (0.65), shoulders (0.54) and neck (0.5). Remarkably, the comparation between the quey and RTG crane operators on the MSK prevalence (χ2 test) and perceived discomfort levels (Kruskal-Wallis test), regarding different 9 body parts, revealed a significant difference between the two on upper back with quay crane having more problem than the RTG at p < 0.05. while the rest of them were mainly in the same direction. MSK contributors such as: working awkward posture, mental stress, height, trolley distance and vibration are considerably the main causes of this. However, the larger in scale of exposure to those for the quey crane compared to the RTG might have led to the distinguishing MSK problem found in this study which require thoroughly deliberation for the particular solutions.

As customer demand for green products increases in the digital economic era, this study analyses the green innovation of the e-tailer and supplier in drop shipping models. Moreover, drop shipping e-tailers and suppliers with a drop shipping option need to make choices regarding whether to provide green or normal products to the market. When a supplier with a drop shipping option produces green products, more fees may be invested on the production of green products than on normal products. The drop shipping e-tailers and suppliers with a drop shipping option can also choose to sell normal products at a low cost, as before. This study designs four models of drop shipping e-teilers and suppliers with a drop shipping option under different choices, analyzes their operational process in drop shipping models, and investigates five theorems. The optimal pricings decisions and green degree of drop shipping e-tailers and suppliers with a drop shipping option were evaluated in this study. The impacts of the green innovation factor, green elasticity coefficient, manufacturing and distribution costs on the drop shipping e-tailers and suppliers with a drop shipping option, and the effect of other environmental parameters on the green degree of green products are also analyzed through computer simulation. The findings of the simulation analysis provide valuable guidance for e-tailers and suppliers with green innovation in drop shipping models and offer important academic and practical implications for e-commerce and the digital economy.

Background: Staphylococcus aureus (S. aureus) occasionally threatens the life of the host as a persistent pathogen even though it is normal flora of humans and animals. We characterized drug resistance in S. aureus isolated from animal carcasses and milk samples from the abattoirs and dairy farms in the Eastern Cape Province. Methods: A 1000 meat swab samples and 200 raw milk samples were collected from selected abattoirs and dairy farms in the Eastern Cape Province, South Africa. S. aureus was isolated and positively identified using biochemical tests and confirmed by molecular methods. Antibiotic susceptibility test against 14 different antibiotics was performed against all isolates. Antibiotic resistance genes were also detected. Results: Of the 1200 samples collected, 134 (11.2%) samples were positive for S. aureus. Resistance ranged from 71.6% for penicillin G to 39.2% for tetracycline. Resistance gene (blaZ) was detected in 13 (14.9%), while msrA was found in 31 (52.5%) of S. aureus isolates. Conclusions: The present result shows the potential dissemination of multidrug-resistant S. aureus strains in the dairy farms and abattoirs in the Eastern Cape. Therefore, this implies that the organism may rapidly spread through food and pose serious public health risk

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

Abstract: Lipodystrophies (LDs) are rare, complex disorders of the adipose tissue characterized by selective fat loss, altered adipokines profile and metabolic impairment. Sirtuins (SIRTs) are class III NAD+-dependent histone-deacetylases linked to fat metabolism. SIRT1 plays a critical role in metabolic health by deacetylating target proteins in tissues including liver, muscle and adipose tissue. Circulating SIRT1 levels have been found to be reduced in obesity while increased in anorexia nervosa and in patients experiencing weight loss. We evaluated circulating SIRT1 levels in relation to fat amount in 32 lipodystrophic patients affected by congenital or acquired LDs compared to non-LD subjects (24 with anorexia nervosa, 22 normal weight and 24 with obe-sity). SIRT1 serum levels were higher in LDs as compared with normal weight subjects (mean ± SEM: 4.17 ± 0.48 vs. 2.59 ± 0.20 ng/mL) or subjects with obesity (1.7 ± 0.39 ng/mL), whereas they were close to those measured in anorexia nervosa (3.44 ± 0.46 ng/mL). Our findings show that within the LD group there was no relationship between SIRT1 levels and the amount of body fat. The mechanisms responsible for secretion and regulation of SIRT1 in LD deserve further investi-gation.

Brown rice is a familiar whole grain in Japan. We examined national trends in brown rice consumption among Japanese adults aged ≥ 20 years old, using individual-level data from the National Health and Nutrition Surveys conducted between 2012 and 2019. We employed multivariable logistic regression to identify factors associated with brown rice consumption. The 95th percentile of daily brown rice intake remained at 0.0 grams throughout the study period. The percentage of brown rice consumers increased from 1.8% (95% confidence interval: 1.6–2.1) in 2012 to 2.3% (95% confidence interval: 1.8–3.0) in 2019. Compared with individuals who consumed only white rice, brown rice consumers had significantly higher mean intake levels of macronutrients, legumes, vegetables, fruits, and nuts. Brown rice consumption was positively associated with certain sociodemographic characteristics (being female, older age, residing in a major city, living without very young children, and having higher education levels) and health behaviors (lower body mass index, engaging in regular exercise, and being a former or never smoker). Despite its potential nutritional benefits in balanced diets, only a small fraction of adults in Japan consume brown rice, indicating a need for further promotion, particularly among individuals with characteristics associated with brown rice consumption.

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

'Cv 'Doña María' table grape is a high-quality table grape variety included in the Protected Designation of Origin (PDO) of the European Union "The bagged grape of the Vinalopó." The PDO stipulates that grape clusters must be protected with paper bags from inclement weather and insects, which helps enhance the final grape quality. However, 'Doña María' is a variety prone to high shattering in the late stages of ripening on the vine and during postharvest. Inorganic calcium treatments are one of the most commonly used tools to reduce this disorder, but the translocation of this mineral from veraison onward has been questioned. In this study, five applications were performed, from veraison to harvest, using sorbitol-chelated calcium (0.7 % + 1.0 %), Ca(NO3)2 (Ca) at 0.7% and sorbitol at 1%. It was observed that bagged grapes (not wetted with the solutions) only increased the concentration of total and bound calcium when treated with Sorbitol-Ca. This resulted in reduced berry drop during cultivation and postharvest and improved fruit firmness. Additionally, it reduced grape metabolism indicators such as respiration rate, weight loss, malic acid degradation, prevented abscisic acid (ABA) and malondialdehyde (MDA) accumulation, and favored the accumulation of secondary metabolites such as total polyphenols, increased antioxidant activity, and sugar content. The application of sorbitol-chelated calcium is an effective and safe tool that enhances fruit quality and prevents losses due to shattering during postharvest.

With increasing air and sea temperatures, the thermodynamic environments over the oceans become more favourable for the development of intense tropical cyclones (TCs) with rapid intensification (RI). In fact, the number of TCs undergoing RI is rising (Zhao, et al., 2018; Bhatia, et al., 2019; Song, et al., 2020; Hong & Wu, 2021; Liu, et al., 2022). RI over coastal sea areas before landfalling is particularly impactful and threatening to coastal lives and properties. There have been studies showing that offshore areas within 400 km of the coastline have experienced a significant increase in RI events with the count tripling from 1980 to 2020 (Li et al., 2023). The south China coastal region consists of highly densely populated cities especially the Pearl River Delta (PRD) region. Intense TCs maintaining its strength or RI of TCs close to the coastal region presents substantial forecasting challenges. This study investigates the effect of sea surface and subsurface temperature and salinity on the intensification of five TCs, namely Super Typhoons Hato in 2017 and Mangkhut in 2018, Typhoon Talim, Super Typhoon Saola and Severe Typhoon Koinu in 2023, which significantly affected the south China coastal region and triggered high TC warning signals in Hong Kong. The analysis utilized the Hong Kong Observatory (HKO) TC track and intensity data, along with the sea temperature and salinity profiles generated using the China Ocean ReAnalysis version 2 (CORA2) of the National Marine Data and Information Service (NMDIS) of China. While high sea surface temperature (SST) of 30°C or above, low surface sea surface salinity (SSS) of 34 psu or below, and strong salinity stratification of at least 0.8 psu per 100 m depth may offer useful hints for predicting RI, they are part of a broader set of contributing factors. This study represents the initial documentation of sub-surface salinity's impact on intense TCs over the South China Sea (SCS) in recent years and will encourage further research to refine forecasting RI of TCs before making landfall near PRD taking into account the effect of freshwater from the Pearl River.

Cloud computing refers to applications delivered as services over the Internet. Cloud systems employ policies that are inherently dynamic in nature and that depend on temporal conditions defined in terms of external events, such as the measurement of bandwidth, use of hosts, intrusion detection or specific time events. In this paper, we investigate an optimized resource management scheme named v-Mapper. The basic premise of v-Mapper is to exploit application-awareness concepts using software-defined networking (SDN) features. This paper makes three key contributions to the field: (1) We propose a virtual machine (VM) placement scheme that can effectively mitigate the VM placement issues for data-intensive applications; (2) We propose a validation scheme that will ensure that a service is entertained only if there are sufficient resources available for its execution and (3) We present a scheduling policy that aims to eliminate network load constraints. An evaluation was carried out with various benchmarks and demonstrated that v-Mapper shows improved performance over other state-of-the-art approaches in terms of average task completion time, service delay time and bandwidth utilization. Given the growing importance of supporting large-scale data processing and analysis in datacentres, the v-Mapper system has the potential to make a positive impact in improving datacentre performance in the future.

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

The ever deepening population aging has brought opportunities and challenges to the continued expansion of tourism consumption in China. In this article, the impact of population aging on household tourism consumption was studied from both theoretical and empirical aspects. First, the micro mechanisms of the impact of population aging on household tourism consumption were analyzed, which include economic condition mechanism, intergenerational care mechanism, health status mechanism and Internet use mechanism. Subsequently, the impact of population aging on household tourism consumption and its impact mechanisms were tested, and the heterogeneity analysis was conducted, by using the data of China Family Panel Studies (CFPS) from 2014, 2016 and 2018. The main conclusions of the article are as follows: (1) Population aging has a significant negative impact on household tourism consumption, and a series of robustness test results such as endogenous treatment support this finding. (2) The results of the impact mechanism test show that population aging has a negative mediating effect on household tourism consumption by reducing household economic conditions. The moderating effect of intergenerational care on the effect of population aging on household tourism consumption is insignificant. Health status of the elderly and Internet use have a significant positive moderating effect on the impact of population aging on household tourism consumption. (3) The results of the heterogeneity analysis show that the negative impact of population aging on household tourism consumption in urban areas is greater than that in rural areas, and the negative impact of population aging on household tourism consumption of families with the old-old elderly is greater than that of falimies with the young-old elderly. The conclusions of this article provide important references for activating tourism consumption in China in the context of population aging.

Stroke constitutes a significant public health concern due to its impact on mortality and morbidity. This study investigates the utility of machine learning algorithms in predicting stroke and identifying key risk factors using data from the Suita study, comprising 7,389 participants and 53 variables. Initially, unsupervised K-prototype clustering categorized participants into risk clusters, while five supervised models including Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosted Machine (Light-GBM) were employed to predict stroke outcomes. Stroke incidence disparities among identified risk clusters using the unsupervised K-prototype clustering method are substantial, according to the findings. Supervised learning, particularly RF was a preferable option because of the higher levels of performance metrics. The Shapley Additive Explanations (SHAP) method identified age, systolic blood pressure, hypertension, estimated glomerular filtration rate, metabolic syndrome, and blood glucose level as key predictors of stroke, aligning with findings from the unsupervised clustering approach in high-risk groups. Additionally, previously unidentified risk factors such as elbow joint thickness, fructosamine, hemoglobin, and calcium level demonstrate potential for stroke prediction. In conclusion, machine learning facilitated accurate stroke risk predictions and highlighted potential biomarkers, offering a data-driven framework for risk assessment and biomarker discovery.

It has been shown that Human papillomavirus (HPV) infection is associated with several forms of cancer. Additionally, although there are more than 100 types of HPV, more than ten types of it, including types 16 and 18, are considered high-risk. The two proteins that make up the viral capsid of HPV 16 are L1, the major capsid protein, and L2, the minor capsid protein. FDA (The Food and Drug Administration) approved HPV vaccines mostly target L1 and L2 capsid proteins, which facilitate intracellular entry during infection. In this study, it was set out to analyze the creation of phylogenetic relations of L1 nucleic acid sequences of viral isolates. This study also analyzed sequences of three key elements within the amino acid sequences of HPV 16 L1: loops critical for structural stability, nuclear localization signal sequences, and residues implicated in viral attachment. As highlighted by the literature, these elements represent pivotal aspects of viral function. Furthermore, the report highlighted the particular inter-sequence variability within the HPV 16 L1 protein sequences. Overall analysis revealed clustering of sequences primarily due to geographical and characterized by more phylogenetic relatedness within location-specific clusters.

Chemical pollution poses a significant threat to human health, with detrimental effects on various physiological systems, including the respiratory, cardiovascular, mental, and perinatal domains. While the impact of pollution on these systems has been extensively studied, the intricate relationship between chemical pollution and immunity remains a critical area of investigation. The focus of this study is to elucidate the relationship between chemical pollution and human immunity. To accomplish this task, this study presents a comprehensive review that encompasses in vitro, ex vivo, and in vivo studies, shedding light on the ways in which chemical pollution can modulate human immunity. Our aim is to unveil the complex mechanisms by which environmental contaminants compromise the delicate balance of the body's defence systems going beyond the well-established associations with defence system delving into the less-explored link between chemical exposure and various immune disorders, adding urgency to our understanding of the underlying mechanisms and their implications for public health.

Accurate power curve modelling is essential to continuously evaluate the performance of a wind turbine (WT). In this work, we characterize the wind power curves using SCADA data acquired at a frequency of 5 minutes in a wind farm (WF) consisting of 5 WTs. Regarding the non-parametric methods, we select artificial neural networks (ANNs) to make curve estimations. Given that, we have the curves provided by the manufacturer of the WTs given by some very precisely measured pair of wind speed and power points. We can evaluate the difference between the manufacturer characterization and the ones estimated with the data provided by the SCADA system. Before the estimation, we propose a method of filtering the anomalies based on the characteristics provided by the manufacturer. We use three-quarters of the available data for curve estimation and one-quarter for the test. One WT suffered a break in the test part, so we can check how the test estimates reflect this problem in its wind-power curve compared to the estimations obtained in the WTs that worked adequately.

Under the new pattern of "Double-Cycle" economy, how to restructure the domestic economic structure to cope with the continuous softening of the global economic structure is an urgent issue. This paper empirically examines the impact of digitalization level on the division of labor in National Value Chain (NVC) within cities using panel data from 263 cities between 2001 and 2016, employing a spatial Durbin model.The study demonstrates that the digitization level can enhance division of labor in NVC in neighboring regions through spatial spillovers. An increase in digitization not only positively deepens the construction of NVC but also contributes to the development of NVC in adjacent areas.The digitization level can deepen the division of labor in NVC through the impact of cost reduction, consumption upgrading, and market integration. This effect exhibits regional variations, with consumption upgrading playing a crucial role in expanding the division of labor in NVC in the eastern region through improving digitization levels, while cost reduction is a key factor in the central region. The research results of this paper provide some empirical evidence for further progress and transition of China's NVC developing mode from the perspective of digital level.

The digital economy (DE) has become a major force driving the optimization and upgrading of industrial structures (ISOU), and research on the driving mechanism has yet to be verified. To this end, the driving influence of DE on the ISOU is targeted, and the role played by economic resilience (ER) and innovation is explored. Based on the panel data of 31 provinces in China from 2011 to 2020, the driving influence of the DE on the ISOU is analyzed using a two-way fixed-effects model. The empirical study finds that the DE presents a positive driving effect on both industrial structure advancement and rationalization, and the driving effect is still significant after the addition of control variables and the robust-type test with one period of lag; the DE presents regional differences in ISOU, with the driving effect of the DE on industrial structure advancement in the eastern region having a more significant performance than that of the central and western regions, and the driving influence on the rationalization of industrial structure in the eastern and western regions exceeds that in the central region; the impact of DE on the ISOU has a mediating role through innovation, ER has a moderating role in the process, and innovation as a partial mediator also has a threshold effect, and finally countermeasure suggestions are put forward.

This study explores fault-tolerant consensus in leader-following heterogeneous multi-agent systems, focusing on actuator failures in uncrewed aerial vehicles (UAVs) and uncrewed ground vehicles (UGVs). An optimization-based fault-tolerant consensus algorithm is proposed. The algorithm utilizes the Euler-Lagrange formula to ensure system consistency under actuator failures, with the Lyapunov stability theory proving the asymptotic stability of the consistency error. The algorithm is applied to heterogeneous multi-agent systems of UAVs and UGVs to derive optimal fault-tolerant consensus control laws for each vehicle type. Simulation experiments give evidence for the feasibility of the proposed control strategy.

Background/Objectives: Asthma is a chronic inflammatory disorder of the airways affecting over 10% of the global population. It is characterized by airway inflammation, mucus hypersecretion, and bronchial hyperresponsiveness, driven predominantly by type 2 helper T cells (Th2) and type 2 innate lymphoid cells (ILC2s) in a subset of patients. However, a significant portion of asthmatic individuals present with "type 2-low" asthma, often refractory to standard inhaled corticosteroid (ICS) therapy. Therefore, developing innovative therapeutic strategies has become essential. Recent studies have highlighted cannabidiol (CBD) as a promising anti-inflammatory agent capable of modulating immune responses. This study investigates the therapeutic potential of a high-CBD extract (CBD-X) in asthma; Methods: We evaluated the effects of CBD-X on cells involved in asthma pathogenesis using primary human Th2 cells, neutrophils and asthma mouse model; Results: Our findings indicate that CBD-X extract inhibits Th2 differentiation and reduces the secretion of IL-5 and IL-13, which are crucial cytokines in asthma. Additionally, CBD-X significantly reduces pro-inflammatory cytokines IL-8 and IL-6 in neutrophils and impairs their migration, a critical step in airway inflammation. In a murine asthma model, CBD-X administration led to marked downregulation of IgE and pro-asthmatic cytokines, along with reduced leukocyte, eosinophil, and neutrophil infiltration in lung tissues; Conclusions: These results suggest that CBD-X extract could offer a novel, complementary approach to managing both type 2-high and type 2-low asthma by targeting key inflammatory pathways and modulating immune cell behavior.

Intrinsically Disordered Proteins (IDPs) play crucial roles in signal transduction, cell differentiation, and transcriptional regulation. Many disrupted genes associated with mental disorders are identified as IDPs, and emerging evidence suggests the functional role of IDPs in neuropsychiatric disorders. However, few studies comprehensively explore the functional association between protein disorder properties and different mental diseases. To address this gap, we collected disrupted gene sets for seven mental diseases (MDD, SCZ, BP, ID, AD, ADHD, ASD) and a control gene set from normal brains using DisGeNET and GeneCards databases. The state-of-the-art predictor IUPred2A was then utilized to calculate the disorder properties , followed by a thorough comparison between the disordered proteins in mental diseases and healthy controls. Functional enrichment analysis and protein-protein interaction networks were conducted to investigate the IDPs’ functional roles in psychiatric diseases. Additionally, we demonstrated the role of IDPs in protein binding formations through a case study of alpha-synuclein using protein docking. Our findings reveal that differentially expressed proteins in mental disorders, especially in ASD and ADHD, exhibit more IDPs than those in healthy controls. IDPs in psychiatric disorders are significantly enriched in neurodevelopmental pathways and play an important role in in gene expression regulation. Our results indicate distinct functional patterns of disorder proteins among mental diseases and healthy controls. When comparing the IDPs between ASD and ADHD, we observed that IDPs in ADHD are more likely linked to the synaptic signaling and regulation, while IDPs in ASD are more tendentiously related to diverse and complex biological processes. Our work offers valuable insights into the important functions of IDPs in psychiatric disorders, enhancing our understanding of the molecular mechanisms involved in psychiatric disorders.

Aspalathin (ASP) can protect H9c2 cardiomyocytes against high glucose (HG)-induced shifts in myocardial substrate preference, oxidative stress and apoptosis. While the protective mechanism of aspalathin remains unknown, nuclear factor (erythroid-derived 2)-like 2 (Nrf2) has emerged as a key factor for intracellular responses against oxidative stress. Therefore, we hypothesized that aspalathin protects the myocardium against hyperglycemia-induced oxidative damage by up-regulating Nrf2 expression in H9c2 cardiomyocytes and diabetic (db/db) mice. Using an oxidative stress RT2 Profiler PCR array, ASP at a dose of 1 µM was demonstrated to protect H9c2 cardiomyocytes against HG-induced oxidative stress, but silencing of Nrf2 abolished this protective response of ASP and exacerbated cardiomyocyte apoptosis. Db/db mice and their non-diabetic (db/+) littermate controls were subsequently treated daily for 6 weeks with either a low (13 mg/kg) or high (130 mg/kg) ASP dose. Compared to nondiabetic mice the db/db mice presented increased cardiac remodeling and enlarged left ventricular wall that occurred concomitant to enhanced oxidative stress. Daily treatment of mice with ASP at a dose of 130 mg/kg for 6 weeks was more effective at reversing complications than both a low dose ASP or metformin, eliciting enhanced expression of Nrf2 and its downstream antioxidant genes. These results indicate that ASP maintains cellular homeostasis and protects the myocardium against hyperglycemia-induced stress through activation of Nrf2 and its downstream target genes.

Highly realistic media created through Artificial Intelligence and Deep Learning, commonly known as deepfakes, presents a serious risk to political stability and the integrity of information. We are entering an era where images and videos, which were once considered reliable evidence, are now being altered to spread false information and incite unrest. This threat is especially heightened in developing nations, where misinformation and manipulation of public sentiment could lead to the collapse of the fragile democracies. This study delves deep into the increased vulnerability of these regions to deepfakes due to slower technological advancement and widespread lack of awareness. This study provides a detailed analysis and sets the stage for future investigations, proposing a combined approach to counteract the consequences of deepfakes. This includes combining technical methods for detection of deepfakes with public awareness campaigns and legal frameworks. Reducing the harmful effects of deepfakes requires cooperation among a diverse group of experts.

Intermediate temperature solid oxide fuel cell (SOFC) operation provides numerous advantages such as high combined heat and power (CHP) efficiency, potentially long-term materials stability, and the use of low-cost materials. However, due to the sluggish kinetics of the oxygen reduction reaction at intermediate temperature, the cathode of SOFC requires an efficient and stable catalyst. Significant progress in the development of cathode materials has been made over recent years. In this article, multiple strategies for improving the performance of cathode materials have been extensively reviewed such as A and B site doping of perovskites, infiltration of catalytic active materials, the use of core-shell composites, etc. Emphasis has been given to intrinsic properties such as thermal expansion compatibility, chemical and thermal stability, and oxygen transport number. Furthermore, to avoid any insulating phase formation at the cathode/electrolyte interface, strategies for interfacial layer modifications have also been extensively reviewed and summarized. Based on major technical challenges, future research directions have been proposed for efficient and stable intermediate temperature solid oxide fuel cell (SOFC) operation.

This study analyzes the effect of economic growth and income distribution on health inequality using data from the Organization for Economic Cooperation and Development (OECD). A panel analysis was conducted by combining 21 years of data (from 2000 to 2020) from 38 OECD countries. Life expectancy and avoidable mortality were set as the dependent variables; gross domestic product and poverty gap were set as the independent variables; body mass index, consumption, smoking rate, healthcare personnel, number of beds in health service facilities, national medical expenses, and unemployment were set as control variables. First, economic growth and poverty gap significantly affect life expectancy and avoidable mortality. It has been confirmed that to resolve health inequality, growth during growth and distribution must be prioritized. Second, it has been confirmed that as the poverty gap increases, life expectancy increases and the avoidable mortality rate decreases. A mechanism different from the existence of a medical security system targeting the lowest class or an increase in the welfare of society worked. In conclusion, as a policy proposal to alleviate health inequality, this study suggests that policy intervention is necessary to block or alleviate the negative impact of income inequality in health care policies.

Motivated by a common Mathematical Finance topic, this paper surveys several results concerning windings of 2-dimensional processes, including planar Brownian motion, complex-valued Ornstein-Uhlenbeck processes and planar stable processes. In particular, we present Spitzer's asymptotic Theorem for each case. We also relate this study to the pricing of Asian options.

Digital transformation and green innovation are critical to firms’ competitive advantage and, thus, firms desire to make digital transformation enhance green innovation. However, the relationship between the digital transformation on green innovation is unclear. Drawing on digital empowerment, we delineate types of digital transformation and their impacts on green innovation in manufacturing firms. Our empirical results indicate that production digitalization and service digitalization have a significant promoting effect on both of green technological innovation and green management innovation. However, the effect of production digitalization on green management innovation is stronger than that of service digitalization. Moreover, environmental regulation enhances the positive effect of service digitalization on green technological innovation and green management innovation. While it enhances the effect of production digitalization on green management innovation. Peer firms’ green innovation strengthens the effect of service digitalization on both of green technological innovation and green management innovation.

The growing expansion of the economy and population has resulted in an increased inclination towards the utilization of groundwater resources. Conducting a geophysical survey is a widely employed method for subsurface mapping and the detection of groundwater. A geophysical study was conducted in Nanshan township, Huarong County, located in the Hunan province of the South-Central region of China. The investigation involved the utilization of a 2D Electrical Resistivity Imaging technique employing forward and inverse pole-dipole electrode array. A total of six survey lines were established, each with an electrode distance from the nearest measuring point to exceeding 800 m. The maximum current electrode separation was utilized in this setup. The spacing between the electrical resistivity sounding points was established at regular intervals. The findings from the exploration indicate the existence of multiple faults within the surveyed region. The study additionally identified two regions of structural failure, which occurred due to the convergence of faults oriented in different directions. This convergence led to the fracturing of rocks, an increase in water content, and a decrease in resistivity. The findings from the exploration were utilized in the formulation of five verification target boreholes. The results of this study offer significant insights that can inform future investigations into groundwater exploration endeavors within the region.

In this paper, we present an experimental procedure to enhance the dimensional accuracy of fabrication via Stereolithography (SLA) of features at the micro-scale. Using a custom benchmark part, deviations in feature dimensions (micro-pores diameters and depths) were detected and measured by confocal microscopy. Samples characterization and experimental observations allowed the identification of inaccuracy sources, mainly due to the laser beam scanning strategy and to the incomplete removal of uncured liquid resin in post-processing (i.e., IPA washing). As a technology baseline, the measured dimensional errors on pores diameters were up to -46%. A compensation method of the nominal laser spot diameter (85m) was defined and implemented resulting in relevant improvements in dimensional accuracy of 9.8% and 11.3% on full-open pores diameter and depth, respectively. Further investigation was performed on a customized test part to adjust the calibration procedure. The measurements revealed that the estimate of the laser beam spot size is 968m. Measurements on micro-pores having different sizes revealed that a constant compensation parameter (i.e., C=85, 96, 120m) is not fully effective at the micro-scale, where average errors still remain at -24%, -18.8%, and -16% for compensations equals to 85, 96 and 120m, respectively. A further experimental campaign allowed the identification of an effective nonlinear compensation law where the compensation parameter depends on the micro-feature size C= f (D). Results show a sharp improvement in dimensional accuracy on micro-pore fabrication, with errors consistently below +8.2%. The proposed compensation method can be extended for the fabrication of any micro-features without restrictions on the specific technology implementation. Concerning the inaccuracy introduced by the laser path, experimentation with a customized part allowed the optimization of the part orientation to reduce the errors and their differences along the X and Y machine axes.

Smartwatches are one of the most relevant fitness trends of the past two decades, and they collect increasing amounts of health and movement data. The accuracy of these data may be questionable and requires further investigation. Therefore, the aim of the present study is to validate smartwatches for use in triathlon training. Ten different smartwatches were tested for accuracy in measuring heart rate, distance (via global navigation satellite systems, GNSS), swim stroke rates and the number of swim laps in a 50 m Olympic-size pool. The optical heart rate measurement function of each smartwatch was compared to that of a chest strap. Thirty participants (15 females, 15 males) ran five 3-minute intervals on a motorised treadmill to evaluate the accuracy of the heart rate measurements. Moreover, for each smartwatch, running und cycling distance tracking was tested over six runs of 4,000 m on a 400 m tartan stadium track, six hilly outdoor runs over 3.4 km, and four repetitions of a 36.8 km road bike course, respectively. Three swimming protocols ranging from 200 m to 400 m were performed in triplicate in a 50 m Olympic-size pool, evaluating tracked distance and detected number of strokes. The mean absolute percentage errors (MAPEs) for the average heart rate measurements varied between 3.1% and 8.3%, with the coefficient of determination ranging from 0.22 to 0.79. MAPE results ranged from 0.8% to 12.1% for the 4,000 m run on the 400 m track, from 0.2% to 7.5% for the 3.4 km outdoor run, and from 0.0% to 4.2% for the 36.8 km bike ride. For the swimming tests, in contrast, the deviations from the true distance varied greatly, starting at a 0.0% MAPE for the 400 m freestyle and reaching 91.7% for the 200 m medley with style changes every 25 m. In summary, for some of the smartwatches, the measurement results deviated substantially from the true values. Measurements taken while road cycling over longer distances with only a few curves were in relative terms more accurate than for outdoor runs and even more accurate than for the 400 m track. In the swimming exercises, the accuracy of the measured distances was severely deteriorated by the medley changes among the majority of the smartwatches. Altogether, the results of this study should help in assessing the accuracy and thus suitability of smartwatches for general triathlon training.

This work presents a Fault-Tolerant Model Predictive Control (FTMPC) algorithm applied to a simulation model for sewer networks. The control system will aim to prevent contaminated water from escaping the network, especially during periods of heavy rainfall, that can cause combined sewer overflows (CSO), while maintaining the flow of water towards the wastewater treatment plant (WWTP) as close as possible to its nominal value. The main purpose of the work is to preserve the operation of the predictive controller as much as possible, in accordance with its operational objectives, when there may be anomalies affecting the elements of the control system, mainly sensors and actuators. Comparing the results obtained considering various types of faults, with situations of normal controlled operation and with the behavior of the sewer network when no control is applied, will allow some conclusions to be drawn at the end.

The paper presents a new type of hydraulic clutch operating with magnetorheological (MR) fluids and the results achieved from both theoretical analysis and experimental measurement. The hy-draulic clutch system of its own design with MR working fluid and a rotating magnetic field lo-cated is designed. The principle of this clutch is to use a rotating magnetic field created by an al-ternating current electromagnet to set the MR fluid in motion. In the tests of the hydraulic clutch with a rotating magnetic field, MR fluid produced on their own, consisting of solid iron particles of various diameters mixed with a silicone oil, are used as working fluids. The rheological properties of MR fluids are assessed on the basis of tests carried out with a Brookfield DV2T rheometer equipped with a magnetic device for generating the magnetic field of its own design. The char-acteristics of the hydraulic clutch with MR working fluid and the rotating magnetic field are tested on a specially built test stand. As a result of the research, it has been found that the torque transmitted by the clutch is the greater, the higher the rotational speed of the magnetic field and the lower the rotational speed of the beaker in which the working fluid is placed, and that the greatest torque occurs for the working fluid with the highest iron content. Based on the analysis of the structure and characteristics of the clutch in which the magnetic field is used, it has been shown that the design of the developed clutch is similar to that of an induction clutch, and its characteristics correspond to the characteristics of the eddy current clutch. Therefore, the proposed new clutch working with MR fluid and the rotating magnetic field can be applied to stationary power transmission system similarly to an eddy current clutch.

This paper details the comprehensive activities conducted in a laboratory setting to assess the Structural Health Monitoring (SHM) of prefabricated building envelopes. Aimed at enhancing the structural evaluation of buildings, the focus of this research lies in employing nondestructive sensors for SHM with the objective to advance in the understanding and assessment of facade conditions. The paper outlines the methodologies employed, starting with a modal analysis to define the structural vibration's modal frequency. Subsequently, tests were defined and executed to validate building envelope compliance in case of stress typical of high-rise building. Throughout these tests, continuous monitoring of the façade was conducted using both conventional (accelerometers, extensimeter washers) and non-conventional sensors (Fiber Optic Sensing) The gathered data underwent thorough processing and analysis to provide an overall perspective on the structure's behavior during the stress test. The investigation aimed to identify whether specific physical phenomena correlate with distinct signals and to evaluate if continuous façade monitoring over the building's lifespan aids in preventing potential structural damage. Moreover, two modal analyses were conducted to compare final data and frequencies with earlier data, enabling the detection of any structural alterations. The results from compliance testing and structural analysis yielded noteworthy insights contributing to the evolving field of structural health monitoring, offering valuable findings that advance our ability to proactively manage and maintain the integrity of building structures.

In the face of escalating climate concerns and the push for sustainable development, the global shift towards renewable and decentralized energy systems presents new challenges and opportunities. This study investigates integrating decentralized energy production, particularly photovoltaic (PV) systems, into national energy planning, aiming to optimize energy strategies that balance local production and consumption with national objectives. By analyzing the Swiss energy model, the research employs the EnergyScope and REHO models to assess the strategic implications of decentralized versus centralized energy systems. Results show that a decentralized approach can significantly reduce PV installation needs to 35 GW, about 23% of potential capacity, and decrease annual system costs by 10% to CHF 1230 per capita. This strategy emphasizes local consumption, minimizes grid reinforcement demands, and leverages economic advantages while addressing overproduction challenges through effective energy storage and grid management. Conclusions underline the strategic value of combining centralized and decentralized methods for resilient and sustainable energy planning. The study contributes to the discourse on energy policy and infrastructure planning, advocating for a hybrid model that accommodates both local conditions and broader energy objectives, urging further research into climate impacts and technology integration for a comprehensive energy future.

Climate change has become a major agenda item in international relations and in national energy policy-making circles around the world. This article studies the surprising evolution of the energy policy, and more particularly the energy transition, currently happening in the Arabian Gulf region, which features some of the world’s largest exporters of oil and gas. Qatar, Saudi Arabia and other neighboring energy exporters, plan to export blue and green hydrogen across Asia as well as towards Europe in the years and decades to come. Although poorly known and understood abroad, this recent strategy doesn’t threaten the current exports of oil and gas (still needed for a few decades) but prepares the evolution of their national energy industries towards the future decarbonized energy demand of their main customers in East and South Asia, and beyond. The world’s largest exporters of Liquefied Natural Gas, Qatar, has established industrial policies and projects to upscale CCUS, which can enable blue hydrogen production, as well as natural carbon sinks domestically via afforestation projects.

The achievement of size uniformity and monodispersity in perovskite quantum dots (QDs) requires the implementation of precise temperature control and the establishment of optimal reaction conditions. Nevertheless, the accurate control of a range of reaction variables represents a considerable challenge. This study addresses the aforementioned challenge by employing manganese (Mn) doping to achieve size uniformity in CsPbBr₃ perovskite QDs without the necessity for precise control of the reaction conditions. By optimizing the Mn:Pb ratio, it is possible to successfully dope CsPbBr₃ QDs with appropriate concentrations of Mn²⁺ and achieve a uniform size distribution. The spectroscopic measurements on single QDs indicate that the appropriate Mn²⁺ concentrations can result in a narrower spectral linewidth, a longer photoluminescence (PL) lifetime, and a reduced biexciton Auger recombination rate, thus positively affecting the PL properties. This study not only simplifies the size control of perovskite QDs, but also demonstrates the potential of Mn-doped CsPbBr₃ QDs for narrow linewidth light-emitting diode applications.

Models of subsurface structures are important for successful deposit exploration but are challenged by the need to integrate data from different geophysical methods. In the present study, we evaluated a method of joint inversion in which audio-magnetotelluric (AMT) and dual frequency induced polarization (DFIP) data sets are inverted simultaneously to produce a consistent 2D resistivity model to show a clear image of subsurface structures. To achieve the objectives, we conducted AMT and DFIP surveys first on the same survey line within the Dongjun lead-zinc deposit in inner Mongolia by developing 31 AMT survey sites with an interstation separation of 40 m on a 1440 m survey track and operated in fifty-three frequencies in the range 1–10,400 Hz to record the resistivity distribution of subsurface to depths exceeding 800 m. The same survey setup up was applied to the DFIP method by utilizing the SQ-3C model with a pole-dipole array configuration and conducted measurements at frequencies of 4 Hz and 4/13 Hz. We first separately inverted AMT and DFIP measurements. The two-dimensional (2D) model obtained from AMT data revealed distinct low resistivity anomalies in the middle of the 2D inversion model. In contrast, the DFIP inversion model showed a high resistive body in the same region. In response to the discrepancies observed in the separate 2D inversion models, we implemented a joint inversion for both the AMT and DFIP datasets. The joint inversion resistivity model shows surficial conducting bodies and a high conductive body along the profile with relatively high Percent Frequency Effect (PEF) indicating high chargeability. The final joint inversion resistivity model clearly images the large silica alteration zone and the Pb-Zn mineralization. This study demonstrates the feasibility of a joint inversion methodology and highlights the value of integrating geophysical methods through joint inversion for enhanced characterization and exploration of lead-zinc ores.

In times of water scarcity, water conservation measures from authorities are primarily directed to the residential sector—homeowners and renters who engage in individual activities to reduce water consumption. Business owners, manufacturers, and institutional workers—the ICI sector, generally, do not receive targeted information and education on water savings measures, and when they do, the information, typically, refers to indoor technologies, and behavior choice. In answer to this shortfall, this research illustrates how the ICI sector might engage in outdoor water conservation and, thus, realize water savings using the well-established Pittenger’s Simplified Landscape Irrigation Design Estimation (SLIDE) formula that estimates outdoor water conservation/savings for the lesser studied industrial, commercial, and institutional (ICI) sector. We applied the SLIDE formula five diverse climate areas in Texas to demonstrate the potential water savings in each, as well as identifying the type of water technology measures that yielded the greatest water savings for outdoor ICI landscapes. Overall, the greatest water savings for outdoor ICI landscapes was realized through smartscape design with soil moisture sensors-SMS technology, second best. Our findings will provide ICI facility owners/managers with knowledge and examples of a simplified system for quantitative decision making when considering choices among technologies and/or practices toward outdoor water conservation for their own facilities.

Tuberculosis cause of death worldwide and the leading cause from a single infectious agent, ranking above Human immunodeficiency virus (HIV) and Acquired Immune Deficiency Syndrome (AIDS). The aim of this study is to ascertain the trend of tuberculosis prevalence and the effect of HIV prevalence onl Tuberculosis case in some West African countries from 2000 to 2016 using count panel data regression models. The data used annual HIV and Tuberculosis cases spanning from 2000 to 2016 extracted from online publication of World health Organization (WHO). Panel Poisson regression model and Negative binomial regression model for fixed and random effects were used to analyzed the count data, the result revealed a positive trend in TB cases while increased in HIV cases leads to increase in TB cases in West African countries. Among the competing models used in this study, Panel Negative Binomial Regression Model with fixed effect emerged the best model with log likelihood value of -1336.554. This study recommended that Government and NGOs need more strategies to fight against HIV menace in West Africa as this will in turn reduced TB cases in West Africa.

The current green development in the context of public policy and industrial economy is difficult to fully match the new infrastructure process driven by massive data. Its connotation and exten-sion and the level of rule of law need to be deepened to ensure that data production, processing, circulation, elimination and other activities can get high-quality and sustainable development in the collaborative construction of hard facilities and soft environment in the new era. Based on the practical needs of data industry green development in key areas, we can resolve the legal risk of data industry green development from three aspects: improving the legal level of green public policy, clarifying the green legal benchmark of data industry development, and improving the green legal system of digital society. Then, it considers the design of environmental protection system based on hardware facilities and the structural and readable clean data system innova-tion of soft data industry development framework mode, so as to clarify the legalization scheme of data industry green development under the new infrastructure. Overall, achieving the green development of the data industry requires not only active attempts by China but also joint efforts by China and other countries.

Boeing and Airbus developed a special testing procedure to investigate the compressive response of laminates that have been impacted (following standards ASTM D 7137 and DIN 65561). This study focuses on both experimental and numerical analysis of Kevlar plates subjected to compression after impact. To ensure high quality and appropriate mechanical properties, the composite plates were manufactured using autoclaving. The DIN 65561 protocol was followed for all three test systems. Initially, ultrasonic C-scanning was performed on all plates before testing to confirm they were free of any significant defects arising from the manufacturing process. Subsequently, low-energy impact testing was conducted at levels ranging from 0 to 8 Joules. Three specimens were tested at each energy level. After the impact, all specimens underwent ultrasonic C-scanning again to assess the internal delamination damage caused by the impactor. Finally, both pristine and impacted specimens were subjected to compressive testing using the special jig specified in DIN 65561. The compressive impact strength results obtained from these tests were plotted against the delamination area measured by C-scanning. This data was then compared to results obtained from specimens with artificial damage. Semi-empirical equations were used to fit both sets of curves. The same procedure (impact testing, C-scanning, and data analysis) was repeated to investigate the relationship between impact energy and total delamination area. Lastly, finite element modeling was employed to predict the buckling stresses that develop under compression in the impacted systems studied. These modelling approaches have demonstrated good accuracy in reproducing experimental results for CAI tests.

Microparticles derived from biomaterials are becoming increasingly popular for various applications, particularly in drug delivery systems. In this study, the water-in-oil (W/O) emulsification-diffusion method was used to create cellulose (C), silk fibroin (SF), and C/SF composite microparticles. We then observed the morphology of all obtained microparticles using scanning electron microscopy (SEM), evaluated their functional groups using attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR), and conducted thermogravimetric analysis using a thermogravimetric analyzer (TGA). SEM micrographs indicated that the native SF microparticles have the highest spherical shape with smooth surfaces. With blue dextran, the C microparticle was smaller compared to the native microparticle, while the drug-loaded SF microparticles were bigger than the native microparticle. The morphological surfaces of the C/SF composite microparticles were varied in shape and surface depending on the C/SF ratio used. The spherical shape of the C/SF composite microparticle was increased as SF content increased. Furthermore, the size of drug-loaded C/SF composite microparticles was gradually increased by the SF content. The significant functional groups in the C and SF structures were identified based on the ATR-FTIR data, and a suggestion was made regarding the interaction between the functional groups of each polymer. When compared to both native polymers, the C/SF composite microparticles exhibit improved thermal stability. The C/SF composite microparticle at a 1:3 ratio had the lowest drug release content, whereas the hydrophilicity of the C microparticle affected the highest drug release content. As a result, one crucial factor affecting the medication released from the microparticle is its thermal stability. According to the obtained results, C, SF, and C/SF composite microparticles show promise as delivery systems for drugs with controlled release.

We are currently facing a potential ‘polycrisis’, a critical inflection point that requires a whole-of-society response aimed at building collective foresight and preparedness for short-, medium-, and long-term risks. The role of higher education institutions and social stakeholders is decisive to make an impact. This paper depicts the alignment of academia, governance, and industry with the aim to challenge, inspire, and encourage universities to go beyond commodified courses and mere employability, enhance student growth and bind macro-scale measures that lead to a sustainable future. A modest teaching innovation project has served as a transforming lever, with the private sector joining in, to create a platform that reaches more than 50 000 undergraduate students and teaching staff. The resulting structure, rooted in the University’s strategic plan, has served to channel local and regional initiatives, establish effective partnerships with broad social members, raise awareness and promote actions to advance in the pursuit of Sustainable Development Goals. Chronology, materials and methodology, together with a description of the different courses, programmes and actions are provided. The paper concludes with some recommendations for future research, policy and cooperation among stakeholders. Research methodology posted on clinicaltrials.gov under ID NCT04392869, NCT05598944, and NCT05775978.

We are currently facing a potential ‘polycrisis’, a critical inflection point that requires a whole-of-society response aimed at building collective foresight and preparedness for short-, medium-, and long-term risks. The role of higher education institutions and social stakeholders is decisive to make an impact. This paper depicts the alignment of academia, governance, and industry with the aim to challenge, inspire, and encourage universities to go beyond commodified courses and mere employability, enhance student growth and bind macro-scale measures that lead to a sustainable future. A modest teaching innovation project has served as a transforming lever, with the private sector joining in, to create a platform that reaches more than 50 000 undergraduate students and teaching staff. The resulting structure, rooted in the University’s strategic plan, has served to channel local and regional initiatives, establish effective partnerships with broad social members, raise awareness and promote actions to advance in the pursuit of Sustainable Development Goals. Chronology, materials and methodology, together with a description of the different courses, programmes and actions are provided. The paper concludes with some recommendations for future research, policy and cooperation among stakeholders. Research methodology posted on clinicaltrials.gov under ID NCT04392869, NCT05598944, and NCT05775978.

Recently, environmental degradation has become an international issue due to the extensive economic activities around the globe. This aspect demands the policymakers' and new researchers’ emphasis. Hence, the present article examines the impact of corporate social responsibilities (CSR) to community and environment on the environmental performance (ENP) of the manufacturing industry in China. The article also investigates the mediating role of green innovation and environmental strategy among CSR to community, CSR to environment and ENP of manufacturing industry in China. The article gets the primary data from the selected employees of the manufacturing industry using questionnaires. The article also tests the data's validity and reliability, and association among variables using smart-PLS. The outcomes indicated that CSR to environment has a positive association with ENP. The outcomes also revealed that green innovation and environmental strategy significantly mediate among CSR to community, CSR to environment and ENP. The article guides the policymakers in making policies related to improve ENP using CSR to environment and green innovation.

The structure and physicochemical properties of polyvinyl alcohol (PVA) and PVA/glycerol films have been investigated by Fourier-transform infrared spectroscopy (FT-IR), X-ray Diffraction (XRD), thermogravimetry/differential thermal analysis (TG/DTA), and advanced scanning probe microscopy (SPM). In the pure PVA films, SPM allowed us to observe ribbon-shaped domains with a different frictional and elastic contrast, which apparently originated from a correlated growth or assembly of PVA crystalline nuclei located within individual PVA clusters. The incorporation of 1.0 wt.% glycerol led to modification in shape of those domains from ribbon-like in pure PVA to rounded in PVA/glycerol 1.0 wt.% films; changes in the relative intensities of the XRD peaks and a decrease of the amorphous halo in the XRD pattern were also detected, while the DTA peak corresponding to the melting point remained at almost the same temperature. For higher glycerol content, FT-IR revealed additional glycerol-characteristic peaks presumably related to the formation of glycerol aggregates, and XRD, FT-IR, and DTA all indicated a reduction in crystallinity. For more than 2.0 wt.% glycerol, the plasticization of the films complicated the acquisition of SPM images without tip-induced surface modification. Our study contributes to the understanding of crystallinity in PVA and how it is altered by a plasticizer such as glycerol.

Direct Energy Deposition (DED) is a versatile and efficient method in metal additive manufacturing. However, humping, caused by abnormal dynamics in the melt pool (MP), poses a significant threat to the geometric integrity of manufactured products. Current state-of-the-art (SOTA) methods primarily detect humping by analyzing late-stage spatial abnormalities, such as MP detachment. This approach is fundamentally reactive, leading to a tendency to miss early humping spatiotemporal dynamics, like cyclic elongation of the MP. This study introduces a novel, proactive indicator named VIMPS (Variability of Instantaneous MP Solidification-Front Speed), a physics-based tool designed to quantify early abnormal fluctuations in MP solidification speed. The experiments demonstrate VIMPS correlation with humping-induced geometric inaccuracies. By capturing early spatiotemporal dynamics of the MP, VIMPS reduces detection latency by 30 seconds compared to existing SOTAs that focus solely on spatial abnormalities. This significant improvement transforms detection from reactive to proactive, providing the time needed for corrective actions to enhance the overall productivity and quality of the DED process.

With more companies entering the realm of electric vertical take-off and landing (eVTOL), and governments enacting policies to support the development of low-altitude economies, the commercial potential of eVTOL is being recognized by the public. However, true commercialization is still a long way off. This article analyzes the technologies, product features, potential markets, and government policies related to eVTOL, and constructs a four-stage, four-layer Policy-Technology Roadmap (P-TRM) model to guide the R&D process of eVTOL. Then transform it into a system structural model, and the Decision-making Trial and Evaluation Laboratory (DEMATEL) method is used to identify several key nodes in the R&D process. Utilizing the Technology Adoption Life Cycle (TALC) theory for interpretation and analysis, the article concludes by proposing strategies in product, technology, and policy support for how eVTOL can successfully cross the chasm. This preliminary analysis of the development path, key nodes, and necessary measures for crossing the chasm provides insights for the R&D and commercialization of eVTOL.

Aspalathin, a C-glucosyl dihydrochalcone, has previously been shown to protect cardiomyocytes against hyperglycemia-induced shifts in substrate preference and subsequent apoptosis. However, the precise gene regulatory network remains to be elucidated. To unravel the mechanism and provide insight into this supposition, the direct effect of aspalathin in an isolated cell-based system, without the influence of any variables, was tested using an H9c2 cardiomyocytes model. Cardiomyocytes were exposed to high glucose (33 mM) for 48 hours before post-treatment with or without aspalathin. Thereafter, RNA was extracted and RT2 PCR Profiler Arrays were used to profile the expression of 336 genes. Results showed that, 57 genes were differentially regulated in the high glucose or high glucose and aspalathin treated groups. STRING analysis revealed lipid metabolism and molecular transport as the biological processes altered after high glucose treatment, followed by inflammation and apoptosis. Aspalathin was able to modulate key regulators associated with lipid metabolism (Adipoq, Apob, Cd36, Cpt1, Pparγ, Srebf1/2, Scd1 and Vldlr), insulin resistance (Igf1, Akt1, Pde3 and Map2k1), inflammation (Il3, Il6, Jak2, Lepr, Socs3, and Tnf13) and apoptosis (Bcl2 and Chuk). Collectively, our results propose that aspalathin could reverse metabolic abnormalities by activating Adipoq while modulating the expression of Pparγ and Srebf1/2, decreasing inflammation via Il6/Jak2 pathway, which together with an observed increased expression of Bcl2 prevents myocardium apoptosis.

The purpose of this paper is to examine the role and impact of public governance on European supranational public policies that seek to foster scientific and economic growth within innovation ecosystems (IEs) through the PITCCH initiative. The PITCCH is a European innovation development initiative funded by Horizon 2020 under the 'Innovation in SMEs' measure.The research methodology for this study is based on a 10-month real-time ethnographic field study of the PITCCH project, which allowed for the observation of the project governance and the capture of the perspectives of innovation-driven small and medium enterprises (i-SMEs) in their engagement with IE stakeholders.The findings of this research demonstrate the role of public governance in providing result-oriented practical support to the IE through the lens of i-SMEs, and they contribute to the existing literature on regional economic growth supported by supranational public policies. These findings have both academic and practical applications. They enrich the current literature on this topic and provide insights for policymakers and governing representatives seeking to implement effective public policies.

Northern Nigeria has had historically low antenatal care (ANC) utilization rates with poor health outcomes. Group antenatal care (gANC) improves ANC behavior and pregnancy outcomes. The gANC has been adopted in Kaduna and Kano states, Nigeria. This paper presents baseline findings from the evaluation of the implementation of the gANC program to support scaling in real-world setting. Baseline data were collected from a cohort of 1,269 and 1,200 pregnant women enrolled in gANC at health facilities in Kaduna and Kano states respectively from March to April 2024. Analyses of socio-demographic and pregnancy behavior data were done. Participants were mostly between ages 19-31 years, married or living with a partner, with over 50% having their own businesses. Over 62% and 34% had completed secondary or higher-level education with 60% and 80% living in urban areas in Kaduna and Kano States, respectively. In Kano State, >60% of the women had their last delivery at home with 41.6% not assisted by a skilled birth attendant. In Kaduna, >63% delivered in the hospital and >50% had skilled attendance during labor. Almost half had not used contraceptives previously. Subsequent longitudinal data will examine the impact of gANC utilization on perinatal outcomes.

Vertical-axis wind turbines (VAWTs) are receiving more and more attention as they involve simple design, cope better with turbulence and are insensitive to wind direction which has a huge impact on the cost since the yaw mechanism is not needed. However, VAWTs still suffer from low conversion efficiency. As a results tremendous efforts are exerted to improve its efficiency which mainly focus on two methods regardless of whether the study is a CFD simulation or a field test or lab test experiment. An active approach which involves the modification of the rotor itself such as the blade design, angle, trailing and leading edges, inner blades, chord thickness, contra-rotating rotor, etc. While the second approach involves passive techniques where the flow is directed to optimally face the downwind rotor by mounting a guiding vane such as a diffuser or other shapes at the upwind position of the rotor. Among all techniques undertaken, the CRWT rotor technique seems to be the most effective with an output even comparable to that of Horizontal Axis Wind Turbines (HAWT), while the Savonius rotor received more attention compared to other designs of VAWTs. Apart from technological issues, it was also suggested that geographical issues such as proper site siting of the wind turbine rotor at a particular location where a uniform flow could be guaranteed is of paramount importance to ensure an effective conversion capacity of wind turbines.

Involving local people in natural area management is very important to address the complexity of environmental management issues for sustainable use of local resources. Participatory methods require the contribution of local stakeholders in decision making. Mapping the environmental views of local communities allows for detecting aspects that could facilitate management efforts. This research – in the frame of the Skyros LIFE project and the PAMNATURA project - measures local acceptability of the conservation actions proposed by the LIFE project in Skyros Island (Greece) in relation with recording local people’s environmental orientation using the 15-item revised New Ecological Paradigm (NEP) scale. The research was carried out by means of questionnaires. The LIFE project proposed actions were grouped into three categories according to their theme, i.e. promoting (a) Nature protection, (b) Agro-pastoralism and (c) Ecotourism. The sample seems to largely agree with the LIFE project proposals, while the results showed high scores for most of the NEP scale items, implying pro-environmental beliefs, though there appears disagreement or neutrality regarding a few items. Local acceptability of the proposed actions was found to correlate to local people’s environmental concern measured through the NEP scale. Drawing on the results, implementation of actions related directly or indirectly to economic activities, preservation of traditional activities, as well as environmental education, interactive informing and consultation could enhance local participation. Skyros island seems to offer an appropriate social background for applying participatory and adaptive management and implementing conservation programs.

Electrical contacts are important circuit components with diverse industrial applications, and their failure can lead to multiple unwanted effects. Hence, the behavior of electrical contacts is a widely studied topic in scientific literature based on various approaches, tools, and techniques. The present study proposes a numerical modeling and simulation approach based on the Holm contact theory to study the dependence between the electric potential and the temperature within an electrical contact. Structured in 5 sections, the research was conducted using COMSOL Multiphysics software and its solid-state mechanics, electric current, and heat transfer modules in order to highlight contact behavior from mechanical, electrical and thermal points of view: the von Mises stress, contact force, the electric field amplitude, the variation of the electrical potential along the current path, the temperature gradient, and dependence of temperature along the contact elements edges were obtained by simulation and graphically represented. The results are in line with the expectations and with past research that was studied in the literature review.

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

The aim of this study is to provide a detailed strategy for Safe-by-Design (SbD) 3D printed lab-on-a-chip (LOC) device manufacturing, using Fused Filament Fabrication (FFF) technology. At first, the applicability of FFF in lab-on-a-chip device development is briefly discussed. Subsequently, a methodology to categorize, identify and implement SbD measures for FFF is suggested. Furthermore, the most crucial health risks involved in FFF processes are examined, placing the focus on the examination of ultrafine particle (UFP) and Volatile Organic Compound (VOC) emission hazards. Thus, a SbD scheme for lab-on-a-chip manufacturing is provided, while also taking into account process optimization for obtaining satisfactory printed LOC quality. This work can serve as a guideline for the effective application of FFF technology for lab-on-a-chip manufacturing through the safest applicable way, towards a continuous effort to support sustainable development of lab-on-a-chip devices through cost-effective means.

This panel study investigates the relationship between green logistics indices, economic, environmental, and social factors in the perspective of Asian emerging economies. This study adopted FMOLS and DOLS methods to test research hypothesis, catering the problem of endogenity and serial correlation. The results suggest that logistics operations, particularly LPI2 (efficiency of customs clearance processes), LPI4 (quality of logistics services) and LPI5 (trade and transport-related infrastructure), are positively and significantly correlated with per capita income, manufacturing value added and trade openness. While, greater logistics operations are negatively associated with social and environmental problems including, climate change, global warming, carbon emissions, and poisoning atmosphere. In addition, human health is badly affected by heavy smog, acid rainfall, and water pollution. The findings further extend and reveal that political instability, natural disaster and terrorism are also a primary cause of poor economic growth and environmental sustainability with poor trade and logistics infrastructure. Further, the application of renewable energy resources and green practices can mitigate negative effects on social and environmental sustainability without compromising the performance of economic growth. There is very limited empirical work presented in literature using renewable energy and green ideology to solve macro-level social and environmental problems, while this study will assist the policymakers and researchers to understand the importance of green concept in improving countries’ social, economic and environmental performance.

Phytochemicals have a long and successful history in drug discovery. With recent advancements in analytical techniques and methodologies, discovering bioactive leads from natural compounds has become easier. Computational techniques like molecular docking, QSAR modelling and machine learning, and network pharmacology are among the most promising new tools that allow researchers to make predictions concerning natural products' potential targets, thereby guiding experimental validation efforts. Additionally, approaches like LC-MS or LC-NMR speed up compound identification by streamlining analytical processes. Integrating structural and computational biology aids in lead identification, thus providing invaluable information to understand how phytochemicals interact with potential targets in the body. Emerging computational approach is machine learning involving QSAR modelling and deep neural networks that interrelate phytochemical properties with diverse physiological activities such as antimicrobial or anticancer effects.

Taiwan's bed and breakfast (B&B) development has been more than 25 years ago, from the first generation of retirement to the B&B industry, serving tourists from all over the world accom-modation, providing breakfast and accommodation mode to the present, after the change of employees from the second generation, more and more attention is paid to the cultivation and cultivation of business ability. With the advent of the era of AI technology networking, the ca-pabilities required for B&B operation are more focused on all aspects of service, and the good marketing ability of B&B can promote a green chimney-free tourism economy, which is also a favorite industry of various governments and the public. This study explores the basic vocational competency indicators required for running a B&B, with (1)EQ emotion management skills, (2)Financial management ability, (3)(SK) technical skills, and (4)Marketing and promotion management capabilities. Through the study method, the K-S Z test was determined by the con-sensus conclusion of expert reliability and validity p value

The paper provides and comments on the results of studies of the effect of sandstone-based abrasives and quartz sand alone on the wear of martensitic surfaces of wear-resistant steels. The wear process was examined on a ring-on-ring test rig seeking to determine the mass decrement parameter which characterised wear. The tests were conducted for three sandstone varieties: Carboniferous, Permian, and Cretaceous, and they made it possible to determine that the most intense process of deterioration of wear-resistant steels took place in the presence of quartz sand grain, while less intense wear was observed in the case of sandstone-based abrasives. The mass decrement values established in the presence of the sandstones in question did not differ significantly between individual sandstone varieties. Based on a surface damage analysis, the basic damage mechanism was found to be micro-scratching, however, with regard to the sandstones examined, it was also determined that individual grains could be pressed into surface irregularities, as well as that films of soft hematite cement developed in the Permian sandstone and that inclusions of carbonaceous matter were formed in the Carboniferous sandstone. With reference to the wear process observations, a wear model was described for the surface of the steels examined in the presence of sandstone-based abrasives.

The paper presents the findings of research on companies in the early stage of development based on the concept of ensuring their sustainability. The starting point is attributes shaping a sustainable model of start-ups. A solution has been proposed and examined that identifies the factors dynamising a business model, which give the company the ability to make fast changes in the configuration of the business model, and that applies stabilizing factors based on the concept of the Triple Bottom Line. The research problem is a response to the phenomena of the bankruptcy of many start-ups that cannot find a way to survive in the long term. The business models of companies in the early stage of development should be designed taking into account the possibility of their dynamic and iterative changes when the earlier assumptions do not work when implemented in practice. A cognitive gap has been observed as the relevant literature does not propose a systemic solution to the problem of instability of the startups viewed from the perspective of the business model concept. The research problem, therefore, is to identify potential new methods to ensure the sustainability of young companies trying to combine aspects dynamising changes in business models, taking into account economic, environmental and social aspects. The findings of research on companies in the early stage of development show that when the methods of increasing the flexibility of the business model are applied and attention is drawn to environmental and social activities and a strong emphasis is put on financial performance, reflecting the expectations of shareholders, the concept of ensuring the sustainability of young companies from the point of view of sustainable business model attributes emerges.

The per capita availability of freshwater resources on a global scale is gradually decreasing due to population growth, rapid urbanization, industrialization, and modern lifestyles. In this situation, wastewater management becomes a major concern. Conventional treatment processes used to treat wastewater discharges are not adequate for the advanced removal of pollutants, especially refractory organic pollutants, which are mainly organic compounds that are not easily biodegradable in the environment. The use of photocatalytic membrane reactors (PMRs) for tertiary wastewater treatment has attracted much interest in recent periods, and various configurations have been investigated. The performance of a PMR using an iron doped titanium photo catalyst and Polysulfone-based polymeric membrane for municipal wastewater treatment was evaluated under natural and simulated solar light. Obtained results proved that solar driven PMRs can remove organic loading (COD) with high efficiencies and may represent a suitable alternative for the tertiary treatment step of municipal wastewater.

Mannosylerythritol lipids (MELs), one of the most promising biosurfactants (BS), are glycolipids produced by yeasts or fungi, with great environmental performance and a high compatibility with the human body. MELs besides working as typical surfactants, can form diverse structures when in the critical aggregation concentration (CAC), reducing the surface tension of water and other solutions, and being stable over a wide range of conditions. Among others, MELs present anti-microbial, antitumor, antioxidant and anti-inflammatory activity, skin and hair repair capacity, which opens possibilities for their use in applications from cosmetics and pharmaceutics to bio-remediation and agriculture. However, their market share is still low when compared to other glycolipids, due to their less developed production process and higher production cost. This re-view gathers information on the potential applications of MELs mentioned on the literature since 1993. Furthermore, it is also explored the current strategies being developed to enhance the market presence of MELs, in parallel with the ones developed for rhamnolipids and sophorolipids.

Autonomous vehicle technology, employing image sensors for road marking recognition, is largely dependent on the Lane Departure Warning System (LDWS) to prevent vehicular deviations from driving lanes. The effectiveness of image-based lane recognition, however, is susceptible to environmental influences like weather conditions and the surrounding road environment. This study investigates the impact of road marking retro-reflectivity on LDWS under varied environmental conditions. Conducted at the Yeoncheon SOC Demonstration Research Center, the experiments encompassed a spectrum of weather scenarios, incorporating rainfall and shifts between day and night lighting. Controlled wear was applied to white, yellow, and blue road markings, followed by measuring their retro-reflectivity at different stages of degradation. The LDWS's performance was evaluated by assessing the recognition rates of these markings under these diverse environmental settings. The study reveals that enhanced retro-reflectivity significantly boosts LDWS detection, especially in challenging weather conditions. Furthermore, the research led to the development of a simulation framework to analyze the cost-effectiveness of road marking maintenance, aligning it with the safety needs of autonomous vehicles. This framework suggests the necessity for updated road marking guidelines that cater to the advanced needs of driver assistance systems and autonomous vehicle technology.

The dynamic behaviour of a machine tool (MT) directly influences the machining performances. The adoption of lightweight structures may reduce the effects of undesired vibrations and increasing the workpiece quality. This paper aims to present and compare a set of hybrid materials that may be excellent candidate to fabricate the MT moving parts. The selected materials have high dynamic characteristics and capacity to damp mechanical vibrations. In this way, starting by the kinematic model of a milling machine that highlights the main critical factors, this study paper evaluates a number of prototypes made of Al Foam sandwiches (AFS), Al Corrugated sandwiches (ACS) and materials reinforced by carbon fibres (CFRP). A set of prototypes has been fabricated, represented the Z-axis ram of a commercial milling machine. The static and dynamical properties have been evaluated by using both FE simulations and experimental tests. The obtained results show that the proposed structures may be a valid alternative to the conventional materials of MT moving parts, increasing machining performances. In particular, the AFS prototype highlighted a damping coefficient that is 20 times greater than a conventional ram (e.g. steel). The CFRP structure is able to satisfy the machining requirements with a reduced weight of 48.5%, while the ACS prototype showed a good trade-off between stiffness and damping.

This paper proposes an innovative mechatronic piezo-actuated module to control vibrations in modern machine tools. Vibrations represent one of the main issues that compromise seriously the quality of the workpiece. The active vibration control (AVC) device is composed by a host part integrated with sensors and actuators synchronized by a regulator, able to make a self-assessment and adjust to the environmental alteration. This study presents the mechatronic model based on the kinematic and dynamic analysis of the AVC device. To ensure a real time performance, a H2-LQG controller has been developed and validated by simulations involving machine tool, PZT actuator and controller models. The Hardware-in-the-loop (HIL) architecture is adopted to control and attenuate the vibrations. A set of experimental tests has been performed to validate the AVC module on a commercial machine tool. The feasibility of the real time vibration damping is demonstrated and the simulation accuracy is evaluated.

Ming-style round-backed armchairs as a classic Chinese chair design are renowned for the blend of ergonomics, practicality, and elegance. Although the Chinese armchair furniture industry has made strides in sustainability, there is still a need for further improvements in material selection, manufacturing processes, and supply chain management to fully support the development of sustainable furniture. Laminated bamboo lumber as new sustainable materials are becoming a popular option for furniture designers in the era of "sustainable design". This research aims to investigate the feasibility and application of laminated bamboo lumber in the design of Chinese armchair furniture and proposes innovative ideas for optimizing the armchair's design. First, an empirical study was conducted to comprehensively understand the classification of Ming-style round-backed armchairs’ structure to develop a 3D model. Secondly, an experimental research method was then employed to explore the parameters of laminated bamboo lumber for future studies. Additionally, a validation experiment was conducted to compare real-world scenarios with simulations using finite element analysis in Ansys. Finally, finite element analysis was used to test the feasibility and application of laminated bamboo lumber in furniture design, focusing on the material’s mechanical properties. Results indicated that laminated bamboo lumber has excellent mechanical properties as furniture design materials, subsequently, using the optimized results, the use of 0.6319 kg of steel was successfully reduced by 23.68% to ensure the armchair’s stability. This provides a reference for the future compter-assist and standardized innovative design of Chinese armchair. By incorporating compter-assist design and lightweight optimization, it is possible to save materials and make more efficient use of resources, thereby contributing to sustainable development goals in the field of furniture design.

This study empirically examines the spatial spillover effect of various environmental regulations on green technology innovation using panel data from 284 county-level cities in China between 2007 and 2019. A geographical-economic spatial weight matrix is constructed, and the spatial Durbin model is employed to identify the specific characteristics of this spillover effect. The findings indicate that the spatial spillover effect of green technology innovation primarily occurs through geographical transmission. However, there is no significant spatial autocorrelation when using the economic distance weight matrix. Various types of environmental regulations influence the spatial spillover effect of green technology innovation in distinct ways. Specifically, Market-motivated environmental regulation exhibits a U-shaped relationship with the spatial spillover effect, while Command-controlled environmental regulation demonstrates an inverted U-shaped relationship, suggesting a complementary effect. Additional research shows that the upgrading of industrial structure acts as a mediator between command environmental regulation and the spatial spillover effect of green technology innovation. Government departments should comprehensively coordinate Market-motivated environmental regulation and Command-controlled environmental regulation, accurately assess the intensity of Command-controlled measures, and prevent the migration of green technology innovation elements caused by excessive regulatory measures within enterprises.

In recent experimental studies, we reported the aggravating effects of Asian sand dust (ASD) on male reproductive function in mice. However, the effects of fetal ASD exposure on male reproductive function have not been investigated. The present study investigated the effects of fetal ASD exposure on reproductive function in male offspring. Using pregnant CD-1 mice, ASD was administered intratracheally on days 7 and 14 of gestation, and the reproductive function of male offspring was determined at 5, 10, and 15 weeks after birth. The secondary sex ratio was significantly lower in the fetal ASD-exposed mice than in the controls. Histologic examination showed partial vacuolation of seminiferous tubules in immature mice. Moreover, daily sperm production (DSP) was significantly less in the fetal ASD-exposed mice than in the controls. DSP in the fetal ASD-exposed mice was approximately 10% less than the controls at both 5 and 10 weeks. However, both the histologic changes and the DSP decrease were reversed as the mice matured. These findings suggest that ASD exposure affects both the fetal development and the reproductive function of male offspring. In the future, it will be necessary to clarify the onset mechanisms of ASD-induced male fetus death and male reproductive disorders.

A well-prepared public health workforce is essential for reducing disease burdens and improving population health, requiring an education that addresses global and complex challenges. This paper examines the integration of the relational employability framework in public health education to cultivate critical global citizenship among students and graduates. Our research, conducted at Edith Cowan University in Perth, Western Australia, involved two case studies using qualitative interviews. Case Study 1, drawn from Cook’s doctoral research, explored student experiences with the relational employability framework within an undergraduate capstone unit. Case Study 2, a school-funded project, gathered graduate perspectives to inform ongoing curriculum development. The findings indicate that the relational employability framework enhances global competencies among students and graduates, through research skills development and critical reflective practice. Students reported improved awareness of their learning needs, self-confidence, and an increased ability to engage with diverse perspectives and societal challenges. Graduates highlighted the framework’s role in understanding ethical standards, conducting rigorous research and applying evidence-based practices in professional settings. Additionally, the framework supported the development of a reflective mindset, enabling graduates to make informed, value-based career decisions and advance their professional growth. The study suggests that adopting a relational employability approach can effectively prepare globally competent and reflective public health professionals. We advocate for the broader implementation of this framework in health education and higher education, offering practical recommendations for curriculum transformation. Such an approach will equip future professionals to contribute meaningfully to public health debates and embody the principles of global citizenship in their practice.

This study investigated the efficiency of scale-propellers, typically used on small drones. A scale-propeller is accepted as having a diameter of 7 to 21 inches. The Ukraine War has demonstrated the utility of relatively small, low-cost first-person view (FPV) drones, which are attritable. This investigation outlines the development of a MATLAB optimisation code, based on minimum induced loss propeller theory, which calculates the optimal chord and twist distribution for a chosen propeller operating in known flight conditions. The MATLAB code includes a minimum Reynolds number functionality, which provides the option to alter the chord distribution to ensure the entire propeller is operating above a set threshold value of Reynolds (>100,000), as this has been found to be a transition point between low and high section lift-to-drag ratios. Additional functions allow plotting of torque and thrust distributions along the blade. The results have been validated on experimental data taken from an APC ‘Thin Electric’ 10” x 7” propeller, where it was found that both the chord and twist distributions were accurately modelled. The MATLAB code resulted in a 16% increase in the maximum propulsive efficiency. Further work will investigate a direct interface to SolidWorks to aid rapid propeller manufacturing capability.

For the purpose of improve the sustainability of products sold in the EU, Digital Product Passports is a mandatory solution. These passports would systematically gather information about products, such as detailing the materials involved to aid recycling and remanufacturing efforts, or recording the emissions produced throughout the manufacturing process. The overall goal is the establishment of a circular economy in the EU. Current research on Digital Product Passports is focused on collating content for sector-specific applications. However, achieving sustainability goals through Digital Product Passports will require new methods and technical solutions for digital collaboration between supply chain participants, especially in the manufacturing sector. Collaborative work on Digital Product Passports requires trust and traceability in data and access management to ensure privacy over the data contained. One way to enable this securely and confidentially is through the use of blockchain technology, in which stored data cannot be concealed, which is key to the traceability of digital product data documentation. This paper therefore presents a concept for the implementation of generically applicable cross-industry blockchain-based digital product passports. To this end, generic supply chain processes have been abstracted and condensed into the architecture of smart contracts. Great attention is paid to the establishment of traceability as well as privacy through the selection of the blockchain technology Secret Network in combination with Gaia-X functionalities. An illustrative use case for digital product passports in manufacturing is used to demonstrate the applicability of the presented concept. In this use case information about the digital nameplate and carbon footprint is exchanged securely and confidentially in a multi-tenant supply chain network based on the Industry 4.0 infomation model of the Asset Administration Shell.

This essay studies Afro-Asian sociocultural interactions in cultural production by or about Asian Latin Americans, with an emphasis on Cuba and Brazil. Among the recurrent characters are the black slave, the china mulata, or the black ally who expresses sympathy or even marries the Asian character. This reflects a common history of bondage shared by black slaves, Chinese coolies, and Japanese indentured workers, as well as a common history of marronage. These conflicts and alliances between Asians and blacks contest the official discourse of mestizaje (Spanish-indigenous dichotomies in Mexico and Andean countries, for example, or black and white binaries in Brazil and the Caribbean), which, under the guise of incorporating the Other, favored whiteness, all the while attempting to silence, ignore, or ultimately erase their worldviews and cultures.

The Double Diaphragm Forming (DDF) process uses vacuum pressure and heat to pre-shape composite reinforcements between flexible diaphragms. Accurate modelling of heat transfer within DDF requires knowledge of the thermophysical properties of the constituent materials. This study investigates the specific heat and thermal conductivity of silicone diaphragms, carbon fibers (chopped and powdered), thermoplastic veils, and their combinations. Experiments measured the specific heat of each material using differential scanning calorimetry and the thermal conductivity of silicone and carbon fabric preforms using the transient plane source method and modified transient plane source method respectively. The influence of reheating cycles on specific heat of carbon fiber-veil samples and the effect of compaction on thermal conductivity of silicone and carbon fabrics were explored. While silicone exhibited linear specific heat behavior, the thermoplastic veil showed non-linearity due to phase change. The combined carbon fiber-veil samples demonstrated slight non-linear specific heat variations depending on reheating cycles. Thermal conductivity of the fabric preforms decreased with the addition of thermoplastic veil and under vacuum-compaction conditions. The established temperature-dependent property relationships provide valuable data for optimizing DDF preforming parameters and enhancing energy efficiency in composite manufacturing.

A partial mitochondrial DNA Cytochrome Oxidase subunit I (mtCOI) gene haplotype variant of the coconut rhinoceros beetle (CRB) Oryctes rhinoceros classed as ‘CRB-G (clade I)’ has been the focus of much research since 2007 with reports of invasions into new Pacific Island locations (e.g., Guam, Hawaii, Solomons Islands). For numerous invasive species, inference of invasion biology via whole genome is superior to assessments via the partial mtCOI gene. Here, we explore CRB draft mitochondrial genomes (mitogenomes) from historical and recent collections, with assessment focused on individuals associated within the CRB-G (clade I) classification. We found that all Guam CRB individuals possessed the same mitogenome across all 13 protein coding genes and differed from individuals collected elsewhere, including ‘non-Guam’ individuals designated as CRB-G (clade I) by partial mtCOI assessment. Two alternative ATP6 and COIII partial gene primer sets were developed to enable distinction between CRB (clade I) that invaded Guam and CRB-G (Clade I) individuals collected elsewhere. Phylogenetic analyses based on concatenated ATP6-COIII genes showed that only Guam CRB-G (clade I) individuals clustered together, and therefore Guam was not the source of the CRB that invaded the other locations in the Pacific assessed in this study. The use of the mtCOI and/or mtCOIII genes for initial molecular diagnosis of CRB remained crucial, and assessment of more native CRB populations will further advance our ability to identify the provenance of CRB invasions being reported within the Pacific and elsewhere

This study addresses the implementation of the International Financial Reporting Standard 9 (IFRS 9) in the European Union as of January 1, 2018, replacing the International Accounting Standard 39 (IAS 39) to introduce a new model for recognizing Loan Loss Provisions (LLP) based on Expected Credit Loss (ECL). This model responds to criticisms of the former Incurred Credit Loss (ICL) system for its inability to reflect credit losses in a timely manner, potentially exacerbating the effects of financial crises (Bushman & Williams, 2015; Gebhardt & Novotny-Farkas, 2011). The study focuses on the effects of adopting the ECL model on the level of Loan Loss Allowances (LLA) in loans, own equity, and the Common Equity Tier 1 (CET1) ratio across 13 Portuguese commercial banks. A mean comparison test is used to evaluate scenarios before and after the application of the ECL model, highlighting the importance of regulator actions and the adequacy of loss recognition policies, including the effects of Regulation (EU) 2017/2395 of December 12. The results obtained demonstrate significant negative impacts on the net values of loans, own equity, and the CET1 ratio upon adopting the IFRS 9 ECL model, due to the widespread increase in LLAs.

The enterprise software sector is experiencing a significant transformation driven by rapid technological progress and evolving business needs. An effective release management process is crucial for the solution providers and customers, as they incorporate the principles of Industry 4.0 and 5.0. With the growing dependence on software solutions and services, ensuring their quality, reliability, and security is highly necessary. The release management process incorporates strategic planning, regression testing, accurate deployment, and continuous monitoring of software updates. However, the rapid advancements in artificial intelligence (AI) and machine learning (ML) create a unique challenge to the release management process. The existing research needs to address the necessary adaptations for Industry 5.0, mainly in product-based software organizations, to the release management process without a change management system. After working with several software solution stakeholders, based on the responses from SaaS project stakeholders, we have presented a revised software release readiness workflow by incorporating a change management module. The preliminary result based on data over a limited period of time indicates that the revised workflow has the potential to improve the management of slippage, particularly by more effectively addressing NFR-related issues, thereby resulting in more predictable and reliable release cycles.