Our study provides guidelines on how to build long-term customer relationship in the non-contract mechanism context. More specifically, the findings show that special, social, and core benefits influence calculative commitment, and operational and special benefits influence affective commitment. This study also supports that calculative and affective commitment play a crucial role in understanding multi-channel agencies’ loyalty. In sum, this study revealed that calculative and affective commitment can be considered as partial or full mediators in the relationship between RBs (relational benefits) and loyalty. This study not only contributed to the existing SET (social exchange theory) and RBs paradigm but also provided practical implications for food distribution management.

Background: We investigated ion channels at the skin, including peripheral nerve endings, which serve as output machines and molecular integrators of many pruritic inputs mainly received by multiple G protein-coupled receptors (GPCRs). Methods: Based on the level of chronic kidney disease–associated pruritus (CKD-aP), subjects were divided into two groups: non-CKD-aP (no or slight pruritus; n=12) and CKD-aP (mild, moderate, or severe pruritus; n=11). Skin samples were obtained from the forearm or elbow during operations on arteriovenous fistulas. We measured ion channels expressed at the skin, including peripheral nerve endings by RT-PCR: Nav1.8, Kv1.4, Cav2.2, Cav3.2, BKCa, Anoctamin1, TRPV1, TRPA1, and ASIC. Results: Expression of Cav3.2, BKCa, and anoctamin1 was significantly elevated in patients with CKD-aP. On the other hand, expression of TRPV1 was significantly reduced in these patients. We observed no significant difference in the levels of Cav2.2 or ASIC between subjects with and without CKD-aP. TRPA1, Nav1.8，and Kv1.4 were not expressed. Conclusions: It was concluded that this greater difference in expression of ion channels at the skin tissue including specific for cutaneous peripheral nerve endings in CKD patients with CKD-aP may increase generator potential related to itching.

Hypertension is a common and growing medical problem that leads to enormous cardiovascular and kidney disease worldwide. While many drugs exist to treat hypertension, there is large individual variation in how a given individual responds to different agents, which contributes to dismal rates of hypertension control. While demographic factors predict which drugs may work better in certain individuals, a great degree of this variation has a genetic basis. In recent years, genome wide association studies have begun to identify specific gene variants that predict drug response to particular agents. This review identifies the major genetic variants influencing antihypertensive response that have emerged from this growing body of work. For novel genetic variants without a previously known biologic basis in blood pressure, it is crucial to validate initial findings in subsequent studies. This information may eventually lead to a more personalized approach to hypertension management that will improve blood pressure control and patient outcomes. The integration of this large amount of data and its real world application will be highly challenging, but strategies to accomplish this are discussed.

As an important part of coastal wetlands, tidal flats provide unique ecosystem services and functions. China's tidal flats are significantly threatened by industrialization, urbanization, aquaculture expansion and coastline reconstruction, and there is an urgent need for sustainable strategies to balance the protection and utilization of tidal flats. Remote sensing technology can realize large-scale spatiotemporal research of tidal flats, comprehensively improve the ecological environment of coastal zones, and help achieve the overall planning goals of major projects for the protection and restoration of important ecosystems in China. In this study, based on GEE (Google Earth Engine) platform, Sentinel-2 (MSI), Landsat 8 (OLI) and Landsat 9 (OLI-2) remote sensing images were used to construct multi-source intensive time series remote sensing image collection, combined with MSIC-OA algorithm. The tidal flat data of China in 2018 and 2023 are extracted and analyzed. The results show as follows: 1) The overall classification accuracy of the tidal flat in 2023 is 95.19%, and the Kappa coefficient is 0.89; In 2018, they were 92.77% and 0.83 respectively. 2) The total tidal flat area in 2018 and 2023 is 8300.34km2 and 8151.54km2, respectively, a decrease of 148.80km2; 3) In 2023, estuarine and bay tidal flats will account for 54.88% of the total area, and most of the tidal flats will be distributed near river inlets and bays; 4) In 2023, the total length of the coastline adjacent to the tidal flat is 10196.17km, of which the artificial shoreline accounts for 67.06%, and the development degree of the tidal flat is 2.04, indicating that most of the tidal flat has been developed and utilized. The research results provide valuable reference for the scientific planning and rational utilization of tidal flat resources in China.

The mechanical properties of the materials stored inside agricultural silos influence the loads generated inside them. The different silo calculation methodologies allow predicting these loads under static and dynamic conditions if the mechanical properties of the stored materials are known. It has been known for many years that these properties are highly dependent on the moisture content of the material. However, to date there are not many studies focused on its determination. The goal of this research is the determination of the angle of internal friction, apparent cohesion, dilatancy angle and apparent specific weight of maize subjected to different moisture contents. Direct shear and oedometer assay devices were used for this purpose. In addition, the maize samples used were moistened using a climatic chamber. Moisture contents applied to maize sample ranged from 9.3% to 17.4%. The results obtained for the angle of internal friction and apparent cohesion, as well as those obtained for the apparent specific weight, were similar to those reported in the literature. However, the values obtained for the dilatancy angle of maize as a function of moisture content could not be compared because nothing has been published so far. The values obtained for this parameter overlap with those published for this material under ambient conditions. In addition, no direct relationship between the values obtained for this parameter and the moisture content of the sample could be found. Finally, the apparent specific weight increased with increasing moisture content of the samples, which differed from that published in the literature. The values provided here can be used for the optimization of storage and handling structures for granular agricultural materials using numerical methods.

Unmanned aerial vehicles (UAVs), commonly known as drones, present a cost-effective solution for the swift collection of data from vast and remote areas that are otherwise difficult to access. The Mediterranean Basin, known for being a hot spot for plant biodiversity, hosts several habitats and taxa of significant naturalistic value. However, many of these areas are often inaccessible to botanists, making exploration and research challenging. The aim of this paper is to involve the utilization of drone surveys and open-source software for botanical research. Our primary goal is to show the effectiveness of these tools in the field and demonstrate their practical application in Natura 2000 sites. The protected area chosen for this research is Rocca di Novara, situated in northeastern Sicily. Thanks to our drone investigations, we were able to capture images of the mountain’s side that is inaccessible to humans. This allowed us to observe the habitat of some species in detail. One of the most fascinating discoveries was the reappearance of Saxifraga callosa subsp. australis, which had not been confirmed in this area for over 140 years. Using drones for botanical research can boost field research, making monitoring easier and more cost-effective over time, especially in Natura 2000 sites.

Asymptotic theories for fractional cointegrations have been extensively studied in the context of time series data, with numerous empirical studies and tests developed. However, most of the previously developed testing procedures for fractional cointegration were primarily designed for time series data. This paper proposes a generalized residual-based test for fractionally cointegrated panels with fixed effects. The test development is based on bivariate panel series with the regressor assumed to be fixed across cross-sectional units. The proposed test procedure accommodates any integration order between [0,1], and it is asymptotically normal under the null hypothesis. Monte Carlo experiments demonstrate that the test exhibits better size and power compared to a similar residual-based test across varying sample sizes.

Inflammation is a cause of number of disorders. Many anti-inflammatory drugs are available to cure and prevent inflammation and its related disorders. Some of the drugs are from plant and animal origin. Among animals snake venom is also utilized as treatment option of certain disorders. In the current study the venom of N. oxiana from Northern areas of Pakistan is assayed to determine its anti-inflammatory activity. The Naja oxiana is also called central Asian cobra is endemic to Central Asia. Naja oxiana belong to family Elapidae and it is highly venomous snake. The venom has many enzymatic proteins as well as nonenzymatic proteins that is neurotoxins. The venom is lethal having very high mortality rate and the death may occur due to respiratory failure in 45 minutes to 24 hrs depending upon the nature and amount of venom. As the venom is highly toxic so initially after venom milking its protein estimation was done and toxicity profile and LD50 was determined to find out its therapeutic dose at which anti-inflammatory activity was observed. The toxicity and anti-inflammatory activity was determined on mice model. Inflammation was induced by carrageenan induced peritonitis method. The inflammatory markers ROS, TNF-α and IL-β were determined by ELIZA in peritoneal fluid. The LD50 of crude venom, fraction 1 and fraction 2 was found as 34 µg/kg, 7.4 µg/kg and 416 µg/kg respectively. Anti-inflammatory activity crude venom, fraction 1 and fraction 2 was found at dose 19 µg/kg, 1.8 µg/kg and 267 µg/kg respectively. The levels of inflammatory markers reduced after therapeutic dose administration of venom and its fractions that indicates that it can be utilized as anti-inflammatory agent and so can be effective in various disorders.

The Xihan River basin is located in the southern part of Gansu Province, where flood disasters occur frequently in summer and autumn, which easily pose significant risks to human life. In order to improve the accuracy of flood disaster predictions and early warnings, a flood model suitable for this region was constructed based on the HEC-HMS (Hydrologic Engineering Center's-hydrologic modeling system) model and used to determine the critical areal rainfall for flood disasters. Calibration of this model was performed using data of four flood events from May to October between 2020 and 2021, reserving data of two additional flood events for model validation. Using the calibrated HEC-HMS model, the critical areal rainfall was determined for the Pingluo and Tanjiaba hydrological stations in the basin through the model testing method. The results indicate that: (1) The stable infiltration rate of the XiHanShui River Basin was between 0.06 and 0.10 mm/h, with runoff concentration times primarily varying from 22.5 to 24.1 hours, a direct runoff storage coefficient was 0.2 hours, and a base flow index decay constant seted at 0.03 hours. (2) During the calibration and validation periods, the average peak flow relative error was 7.56%, the average runoff volume relative error was 14.76%, the average peak occurrence time difference was -0.5 hours, and the Nash efficiency coefficient was 0.769. (3) The warning areal rainfall for the Pingluo and Tanjiaba hydrological stations were 108.1mm and 128.5mm, and the guaranteed areal rainfall were 230.8mm and 184.6mm. The HEC-HMS model demonstrated high applicability and accuracy in simulating flood events in the XiHanShui River Basin, providing technical support for hydrological research and operational applications in the region.

The combined use of lasmiditan and triptan is unexplored in medical literature. This study aimed to investigate whether the intake of lasmiditan following triptan improves migraine pain. Following triptan intake, if headache relief was less than 50% at 1 hour, patients took 50 mg lasmiditan within 2 hours of migraine onset. Patients recorded headache intensity and adverse events(AEs) caused by lasmiditan at 1, 2, and 4 hours after intake of additional 50 mg of lasmiditan. A significant reduction in pain scale was observed post 50 mg lasmiditan intake (p < 0.001, t-test). Pain relief was reported for 32 migraine attacks (80%) at 1 hour after additional lasmiditan intake. Although AEs were observed in 63% of the patients who took an additional lasmiditan, most were mild and resolved 1 hour after lasmiditan intake. Our study revealed the significant headache reliefs provided by an additional lasmiditan for patients who did not achieve satisfactory results following initial triptan intake for treating migraine. The AEs associated with this treatment strategy were mild and lasted for a short term. This study suggested that the combination of triptan and lasmiditan is promising for the treatment of migraine and should be studied in a randomized placebo-controlled trial.

Incisional hernias have a particular dynamic related both to the repair method and to the absence or presence of a prosthetic material. The incidence of incisional hernias is estimated at 9.8% after 21 months and increases to 18.7% after ten years. This study presents a surgical method for the repair of recurrent incisional hernias, through open surgery and the use of existing mesh. The selection criteria regarding the use of this method are: the prosthesis is well integrated, without granulomas, suppurations, defect appearing on the same prosthetic abdominal area. The analyzed factors were the location of the incisional hernias, the duration of the operation, the duration of hospitalization, identified complications, the size of the parietal defect. The retrospective study carried out focused on recurrences of incisional hernias from a group of 631 patients operated on for incisional hernias in a general surgery department of Dr. Constantin Andreoiu County Emergency Hospital, Ploiești, Romania, during January 2018 - December 2022. Of the total of 18.22% relapses, 13.6% were relapsed eventrations after prosthetic procedures. Following the application of the selection criteria, several 8 patients with recurrent eventrations were operated by the open method using the existing mesh. In the case of recurrences after prosthetic procedures of incisional hernias, the recurrence can be solved by open surgery using the existing well-integrated prosthesis, without tension, absence of suppuration in the wound, and the peritoneal cavity. For the presented case, the return to daily activities occurred after 22 hours of hospitalization.

Strategic intelligence covers the examination of what impacts and influences the business and the related SWOT analysis, (strengths, weaknesses, opportunities, and threats mapping). Through this research, leaders will be able to properly allocate and re-route resources, identify areas of improvement, and ensure that strategic initiatives are aligned with the organization's mission. Strategic intelligence is, therefore, effective through the use of critical thought and data-driven decisions and seeing the outcomes of different positioned alternatives. It must also form and support a culture of cooperation and open communication within the organizations, stimulating employees' inputs and learning curves. The article's subject is the necessity for strategic intelligence, a crucial competence for leaders, managers, and companies striving to remain competitive, to be utilized and best leveraged in today's volatile and dynamic business contexts. It helps the leadership turn proactive, foresee trends, and make correct, agile decisions that enforce companies' long-term growth and success. This study follows a research design that includes a thorough literature review and bibliometric research, executed via VoSViewer, illustrating the concept of strategic intelligence from a leadership point of view as a driver of competitive advantage. Further, the article points out that the limitations are acknowledged because the literature on the matter is limited, as strategic intelligence is relatively new to the business sector; moreover, more research is required to fully understand and use the potential of strategic intelligence in business growth. By overcoming these limitations and continuing to study this concept, businesses can gain a competitive edge and make informed decisions that fuel their success in an ever-evolving market. As a result, this study contributes to developing strategic intelligence in leadership and business and paves the road for further research and applications of strategic intelligence theories in organizational contexts.

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.

A U.S. government health agency conducted epidemiological studies to evaluate whether exposures to drinking water contaminated with volatile organic compounds at U.S. Marine Corps Base Camp Lejeune, North Carolina, were associated with increased health risks to children and adults. These health studies required knowledge of contaminant concentrations in drinking water—at monthly intervals—delivered to family housing, barracks, and other facilities within the study area. Because concentration data were limited or unavailable during much of the period of contamination (1950s–1985), the historical reconstruction process was used to quantify estimates of monthly mean contaminant-specific concentrations. This paper integrates many efforts, reports, and papers into a synthesis of the overall approach to, and results from, a drinking-water historical reconstruction study. Results show that at the Tarawa Terrace water treatment plant (WTP) reconstructed (simulated) tetrachloroethylene (PCE) concentrations reached a maximum monthly average value of 183 micrograms per liter (ug/L) compared to a one-time maximum measured value of 215 ug/L and exceeded the U.S. Environmental Protection Agency’s current maximum contaminant level (MCL) of 5 ug/L during the period November 1957–February 1987. At the Hadnot Point WTP, reconstructed trichloroethylene (TCE) concentrations reached a maximum monthly average value of 783 ug/L compared to a one-time maximum measured value of 1,400 ug/L during the period August 1953–December 1984. The Hadnot Point WTP also provided contaminated drinking water to the Holcomb Boulevard housing area continuously prior to June 1972, when the Holcomb Boulevard WTP came on line (maximum reconstructed TCE concentration of 32 ug/L) and intermittently during the period June 1972–February 1985 (maximum reconstructed TCE concentration of 66 ug/L). Applying the historical reconstruction process to quantify contaminant-specific monthly drinking-water concentrations is advantageous for epidemiological studies when compared to using the classical exposed versus unexposed approach.

Oxytetracycline (OTC) serves as a widely employed antibiotic in veterinary treatment and prevention of infections, potentially leaving residues in animal-derived food products, such as milk, that are consumed by humans. Given the detrimental effects of prolonged human exposure, it becomes imperative to develop precise and sensitive methods for monitoring the presence of OTC in food. This work reports on the fabrication of a label-free electrochemical aptasensor for the determination of OTC as a proof-of-concept.

With opioid overdose rates on the rise, we aim to develop a county-level risk stratification, specifically focusing on access to Medications for Opioid Use Disorder (MOUD) and high overdose rates. We examined over 15 million records from the South Carolina Prescription Tracking System (SCRIPTS) across 46 counties. Additionally, we incorporated data from opioid treatment programs, healthcare professionals prescribing naltrexone, clinicians with buprenorphine waivers, and county-level overdose fatality statistics. To assess the risk of opioid misuse, we classified counties into high-risk and low-risk categories based on prescription rates, overdose fatalities, and treatment service availability. Utilizing statistical methods, we compared prescription patterns and outcomes between these groups. Our study shows that between 2017 and 2021, opioid prescriptions decreased from 64,223 to 41,214 per 100,000 residents, while fentanyl-related overdose deaths increased by 312%. High-risk counties have significantly higher rates of fentanyl prescriptions and rely more on out-of-state doctors. They also exhibit higher instances of doctor shopping and had fewer medical doctors per capita, with limited access to MOUD. To effectively combat the opioid crisis, we advocate for improved local healthcare infrastructure, broader treatment access, stricter management of out-of-state prescriptions, and vigilant tracking of prescription patterns. Tailored local strategies are essential for mitigating the opioid epidemic in these communities.

We report a case in which a 74-year-old man suffering from esophageal achalasia complicated with epiphrenic esophageal diverticulum was successfully treated with a simultaneous laparoscopic surgery. The gentleman was referred with symptoms suggestive of a passage disorder in lower esophagus from 5 years. Esophagogastroduodenoscopy demonstrated an epiphrenic diverticulum at the left wall of the lower esophagus, and esophagography led to the suspicion of a combined esophageal achalasia. A simultaneous laparoscopic surgery, with an abdominal approach was performed in which, following the opening of the esophageal hiatus, the diverticular wall was separated from the mediastinal organs and diverticulectomy was performed with linear staplers. After Heller’s myotomy, Dor’s fundoplication was subsequently performed in which both incisional line of muscle layer and the suturing line of diverticulectomy were wrapped by the fornix of stomach to make up for the wall strength and avoid the suture leakage. It was theoretically considered logical and effective to reinforce this vulnerable site with Dor’s fundoplication. He had an uneventful recovery and a rapid relief from symptoms following surgery.

Packaged water consumption has grown rapidly in urban areas of many low and middle income countries, but particularly in Ghana. However, the sources of water used by this growing packaged water industry and its implications for water resource management and transport-related environmental impacts have not been described. This study aimed to assess the spatial distribution of regulated packaged water production in Ghana, both in relation to demand and for natural mineral water, to hydrogeological characteristics. 764 addresses for premises licenced to produce packaged water from 2009-2015 were mapped and compared to regional sachet water consumption and beverage import/export data examined. We find evidence to suggest packaged water is transported shorter distances in Ghana than in developed countries. For natural mineral waters, producers should be able to address the most widespread water quality hazards (including high salinity, iron and nitrates) in aquifers used for production through reverse osmosis treatment. The study suggests there is scope to integrate beverage product and groundwater regulatory databases to support groundwater management.

In the paper, the authors find closed forms for derangement numbers in terms of the Hessenberg determinants, discover a recurrence relation of derangement numbers, present a formula for any higher order derivative of the exponential generating function of derangement numbers, and compute some related Hessenberg and tridiagonal determinants.

Background: Health insurance (HI) run by government is providing health care service to large population. Due to poor accountability, participation and sustainability, cooperative health insurance is becoming more popular and effective in low and middle income and some high-income countries too. In Nepal, there are public and cooperative HI is in practice. The aim of this study is to compare the effectiveness of public (government) and cooperative HI in relation to benefit packages, population coverage, inclusiveness, health care utilization, and promptness for treatment in these two health insurance models in Nepal. Method: This is an institution based concurrent mixed study consists of qualitative and quantitative variables from public and cooperative groups. We included all public HI operated by government hospitals and cooperatives groups those purchased hospital service in contract. Two separate study tools were applied to access the effectiveness of insurance models. The key questions were asked for the representatives of government and private health insurance. The numeric information consisted of in quantitative data and subjective response was included in qualitative approach. Descriptive statistics and Mean Whitney U test was applied in numeric data and qualitative information were analyzed by inductive approach Results: The study revealed that new enrolment was not increased, health care utilization rate was increased and the benefit package was almost same in both groups. The overall inclusiveness was higher for the government HI, but enrolment from the religious minority, proportion of negotiated amount during treatment were significantly higher (p<0.05). During illness, the response time to reach hospital was significantly faster in cooperative health insurance than government health insurance. Qualitative findings showed that level of participation, accountability, transparency and recording system was better in cooperative health insurance than public. Conclusion: Cooperative HI could be more sustainable and accountable to the community for all; low, middle and high-income countries.

This study aimed to evaluate the safety and tolerability of STP1, a combination of ibudilast and bumetanide, tailored for the treatment of a specific subgroup of patients with Autism Spectrum Disorder (ASD), namely ASD Phenotype 1 (ASD-Phen1). We conducted a randomized, double-blind, placebo-controlled, parallel-group phase 1b study with two 14-day treatment phases (registered at clinicaltrials.gov as NCT04644003). Nine ASD-Phen1 patients were administered STP1, while three received a placebo. We assessed safety and tolerability, along with electrophysiological markers, such as EEG, Auditory Habituation, and Auditory Chirp Synchronization, to better understand STP1's mechanism of action. Additionally, we used several clinical scales to measure treatment outcomes. The results showed that STP1 was safe and well-tolerated, with electrophysiological markers indicating a significant and dose-related reduction of gamma power in the whole brain and in brain areas associated with executive function and memory. Treatment with STP1 also increased alpha 2 power in frontal and occipital regions and improved habituation and neural synchronization to auditory chirps. Although numerical improvements were observed in several clinical scales, they did not reach statistical significance. Overall, this study suggests that STP1 is safe and well-tolerated in ASD-Phen1 patients and shows indirect target engagement in ASD brain regions of interest.

Leaf springs are critical components for the railway vehicle safety in which they are installed. Although these components are produced in high-strength alloyed steel and designed to operate under cyclic loading conditions in the high-cyclic fatigue region, their failure is still possible to occur and hence lead to economic and human catastrophes. The aim of this document is precisely to characterise the mechanical crack growth behaviour of the 51CrV4 spring steel representative of leaf springs under cyclic conditions, that is, crack propagation in mode I. The common fatigue crack growth prediction models (Paris and Walker) considering the effect of stress ratio and parameters such as propagation threshold, critical stress intensity factor and crack closure ratio are also determined using statistical methods, which resulted in good approximations with respect to the experimental results. Lastly, the fracture surfaces under the different test conditions were analysed using SEM, with no significant differences to declare. As a result of this research work, it is expected that the developed properties and fatigue crack growth prediction models can assist design and maintenance engineers in understanding fatigue behaviour in the initiation and propagation phase of cracks in leaf springs for railway freight wagons.

Weather conditions appear to be undergoing significant deviations from the long-term average, marked by pronounced extremes of heat, prolonged droughts, and heightened rainfall occurring with greater frequency worldwide. Consequently, new patterns of extreme weather are emerging, like the unusual and unorganized tropical cyclone called "Yaku", that influenced the extreme amount of rain that between March 6th to 10th, 2023 hits more than 1000 districts in the northwestern of Peru. One of the district more affected was Íllimo, in the Lambayeque province, due to the river that pass through the city, so called “La Leche”, after the continuous and intensive rain overflow devastating his surrounding areas and causing victims and damage. This emergency provided and excellent opportunity to apply, on the aforementioned areas, the “change detection” technique, that allows identifying areas of change between data obtained before and after of emergency events. In this research, optical data (Sentinel-2, Landsat, MODIS Terra and Aqua, and PeruSAT-1) and synthetic aperture radar (SAR) data (Sentinel-1 and COSMO SkyMed) were analyzed. A benchmark could also be carried out between open-source and commercial spatial analysis tools. The results indicated that in an extreme rain event the optical data are obscured by clouds and do not allow their use, while SAR data overcome clouds, and can be used for this research. The benchmark indicated that using the Jaccard index score, the Sentinel-1A set showed a 33% of correlation, while COSMO SkyMed demonstrated a 38% of match between the maps. The results obtained could be used to sensitize the population and develop a better management of future emergency events (floods) in different areas of Peru.

Virus taxonomy uses a Linnaean-like subsumption hierarchy to classify viruses into taxonomic units at species and higher rank levels. Virus species are considered monophyletic groups of mobile genetic elements (MGEs) often delimited by phylogenetic analysis of aligned genomic or metagenomic sequences. Taxonomic units are assumed independent organizational, functional and evolutionary units that follow a ‘natural’ historical rationale. Here, I use phylogenomic and other arguments to show that viruses are not self-standing genetically-driven biological systems. Instead, they are crucial components of holobionts, units of biological organization that dynamically integrate the genetics, epigenetic, physiological and functional properties of their co-evolving members. Remarkably, phylogenomic analyses show viruses share protein domain and loop structures with cells throughout history via massive processes of reticulate evolution, helping spread evolutionary innovations across a wider taxonomic spectrum. Thus, viruses are not merely MGEs or microbes. Instead, their genomes and proteomes conduct cellularly integrated processes akin to those cataloged by the GO Consortium. This prompts the generation of compositional hierarchies that replace the ‘is-a-kind-of’ by a ‘is-a-part-of’ logic to better describe the mereology of integrated cellular and viral makeup. My analysis demands a new paradigm that integrates virus taxonomy into a modern evolutionarily centered taxonomy of organisms.

Accurate measurement of systemic financial risk is critical to maintaining the stability of financial markets. Taking China as the subject of investigation, the Chinese Financial Stress Index (CFSI) indicator system was con-structed by integrating six dimensions and employing Gray Relation Analysis (GRA) for dimensionality reduction of the indicators. The CFSI was derived using the Attribute Hierarchy Model (AHM) method with the Criteria Importance Through the Intercriteria Correlation (CRITIC) method, and an Improved Gravitational Search Algorithm (IGSA) optimized Radial Basis Function Neural Network (RBFNN) was proposed for out-of-sample prediction of CFSI trends from 2024 to 2026. By analyzing the trend of financial pressure indicators, the relationship between financial pressure and economic activity can be effectively identified. The research findings indicate that: (1) The CFSI is capable of accurately reflecting the current financial stress situation in China; (2) The IGSA-RBFNN demonstrates good robustness and generalization capabilities, predicting that the CFSI index will reach a peak value of 0.543 by the end of 2024, and there exists a regular pattern of stress rebound towards the end of each year. The novel methodology benefits policymakers and regulatory authorities to formulate preventive measures and risk management by identifying potential risks and vulnerabilities in advance.

The aim of this study was to evaluate the use of a flexible synthetic polymer bone graft to provide implant stability in the absence of implant stability during implant placement in a dense cortical bone model. Sockets were prepared on polyurethane blocks according to the standard implant socket drilling protocol in the control group, both oversizing and deepening in group 2, and oversizing only in group 3. In groups 2 and 3, flexible synthetic polymer bone grafts were placed in the sockets prior to implant placement. The implants were placed at bone level in all groups. The highest torque value obtained was recorded as the insertion torque. 75 implant sites in 3 groups were included in the study. The torque values of the implants in the control group were significantly higher than those of the implants with the oversized and deepened sockets and the oversized-only sockets (p&lt;0.05; p&lt;0.01).The torque values of the implants with the oversized and deepened sockets were significantly higher than those of the implants with the oversized-only sockets (p&lt;0.01). In this study, flexible synthetic polymer bone graft was shown to be effective in achieving implant stability in the management of implants with loss of primary stability.

The informational synthesis of neural structures, processes, parameters and characteristics that allow a unified description and modeling as neural machines of natural and artificial neural systems is presented. The general informational parameters as the global quantitative measure of the neural systems computing potential as absolute and relative neural power were proposed. Neural information organizing and processing follows the way in which nature manages neural information by developing functions, functionalities and circuits related to different internal or peripheral components and also to the whole system through a non-deterministic memorization, fragmentation and aggregation of afferent and efferent information, deep neural information processing representing multiple alternations of fragmentation and aggregation stages. The relevant neural characteristics were integrated into a neural machine type model that incorporates unitary also peripheral or interface components as the central ones. The proposed approach allows overcoming the technical constraints in artificial computational implementations of neural information processes and also provides a more relevant description of natural ones.

We discuss a central concept of nanothermdynamics; the subdivision potential. We explain how it can be measured or calculated for some typical ensembles, as this has been disputed in the literature. We proceed to discuss its meaning for particular systems, and predict scaling laws for three ensembles. The laws depend on the small system geometry in a predictable way for an ideal gas model with surface adsorption. We provide new equations which relate the subdivision potential to experimental investigations, and give expressions for grand canonical ensembles of spheres, cylinders, slit pores and fluids confined in porous media. The subdivision potential is not compatible with the popular Hadwiger theorem in geometry, and can therefore not be described by a Minkowski set of variables. It is equivalent to Gibbs descriptions when shape- and size variables are defined.

The study of underwater vehicle wake detection is of significant importance within the field of target detection, localisation and tracking of underwater vehicles. Given that propellers are the propellers of modern ships and underwater vehicles, the propeller wake field represents the principal target source for wake detection in underwater vehicles. The objective of this paper is to propose a method for measuring the wake of an underwater propeller based on a position-sensitive detector. A theoretical model of the relationship between the laser spot displacement and the change of refractive index of the wake field is established on the basis of the principle of laser beam deflection. A prototype experimental setup for underwater propeller wake measurement was constructed based on the aforementioned optical measurement method. Furthermore, the simulation of the propeller wake flow field with strong density stratification and linear density stratification was conducted based on the experimental setup. In the experiment, a three-bladed propeller with a diameter of 39mm was selected, the water tank size was 980mm×380mm×380mm, and the laser acted at a distance of 550 mm from the propeller. The experimental results indicate that the wake dissipation time of the propeller in a strong density-stratified water environment is approximately 800s. Following the stabilization of the wake field density, the laser spot position is observed to be stable at 0.341 mm, with a corresponding refractive index change of 2.99×10-6 RIU. The wake dissipation time of the propeller in a linear density-stratified water environment is approximately 750 s. Once the wake field density has reached a stable state, the laser spot position is found to be 0.441mm, corresponding to a refractive index change of 3.87×10-6 RIU. These experimental results are found to be in general agreement with the simulation results of the propeller wake field. A comparison of the experimental device-based wake measurements with the CTD-based wake measurements reveals a consistent trend.

Microscopic vision plays an important role in automated micro-assembly. However, some uncertain factors in the assembly process, such as occlusion and stains can lead to the mistakes of feature extraction. Herein, to solve the problem, the deep learning techniques are introduced into the feature recognition tasks, focusing on the attention mechanism and visualizing CNNs for DL-based microscopic vision. The main contributions are summarized as follows: The CBAM attention mechanism is combined with the YOLOv5 algorithm to improve the accuracy and robustness of feature extraction. The micropart feature occlusion experiment results show that at 70% occlusion degree, YOLOV5-CBAM can reach 97.9% [email protected], which is 4.6% higher than the original one. Visualization analysis of DL-based model is conducted using Grad-CAM to make the decision result more transparent and avoid potential visual detection risks during assembly. The heatmap matching degree between GT area and high-light area is increased by 27.81% on average, which further verify the effectiveness of attention mechanism in micropart feature localization. Additionally, micropart surface stain and droplet quality classification models based on ResNet50 are trained to replace the manual sorting. The visual results are consistent with human eye discernment and judgement, confirming the reliability of parts and droplets sorting.

Background: The resurgence of syphilis, primarily in MSM populations, has necessitated novel prophylactic strategies, such as the use of doxycycline post-exposure prophylaxis (doxy-PEP). However, the potential for increased doxycycline use to select for tetracycline resistance represents significant challenges in managing this sexually transmitted infection. This study aims to identify chromosomal mutations associated with tetracycline resistance in Spirochaetales to inform treatment strategies and surveillance measures.Methods: Whole genome sequences (WGS) from the Spirochaetales order, including 4,355 genomes, were analyzed for the presence of mutations in 16S rRNA and non-synonymous mutations in the rpsC and rpsJ genes. The study utilized WGS from GenBank® and sequence data from the PubMLST Treponema pallidum isolate collection. Genetic resistance to tetracycline was detected using a combination of BLASTN searches and gene-gene analysis. Results: A transition mutation TGA to TGG at positions 965-967 in the 16S rRNA gene was detected in 5.6% of Treponema spp. and 3.97% of Spirochaeta spp. genomes. The rpsJ gene exhibited a V57G amino acid substitution across a significant subset of Treponema spp. Notably, the V57K mutation was common in Spirochaeta spp. The rpsC gene had the H178Q mutation and was found to be present in the Spirochaetales bacterium.Conclusion: The identification of mutations associated with tetracycline resistance in Spirochaetales provides a foundation for the development of rapid molecular diagnostics and guides the clinical selection of antibiotics for syphilis treatment. This study underscores the complexity of antibiotic resistance mechanisms and the critical importance of surveillance in the era of antibiotic prophylaxis for STI management.

A key step in the study of tree pathology is the identification of appropriate method for inoculating pathogens of diseases in branch and trunk. Pathogens of diseases in branch and trunk are commonly inoculated through punching, burning, and toothpick inoculation. However, there is a lack of comparative analysis of the inoculation outcomes of these three methods. In this work, Six‐year‐old P. alba var. pyramidalis were inoculated with V. sordida, using punching, burning, and toothpick techniques, respectively, to investigate the differences in the effectiveness of these inoculation methods. Results reveal that the incidence rate was 93.55% in the toothpick inoculation group, significantly higher than 80.65% in the burning inoculation group (p = 0.007), while punching inoculation exhibited significant pathological responses in the early stages, with spontaneous healing in the later stage. Addi-tionally, toothpick inoculation was more efficient in inducing Valsa canker when inoculating the pathogen at the bottom of the tree, with lower intra‐ and inter‐row spacing (stand density) providing better outcomes than higher intra‐ and inter‐row spacing. The results of this study demonstrate that toothpick inoculation is an optimal option for studying the artificial inoculation of V. sordida in six‐year‐old P. alba var. pyramidalis, providing technical support for research on poplar diseases and offering a theoretical basis for the inoculation of other diseases in branch and trunk.

Recently the number of studies investigating triterpenoid saponins has drastically increased due to their diverse and potentially attractive biological activities. Currently the literature contains chemical structures of few hundreds of triterpenoid saponins of plant and animal origin. Triterpenoid saponins consist of a triterpene aglycone with one or more sugar moieties attached to it. However, due to similar physico-chemical properties, isolation and identification of a large diversity of triterpenoid saponins remain challenging. This study demonstrates a methodology to screen saponins using hyphenated analytical platforms, GC-MS, LC-MS/MS, and LC-SPE-NMR/MS, in the example of two different phenotypes of the model plant Barbarea vulgaris (winter cress), glabrous (G) and pubescent (P) type that are known to differ by their insect resistance. The proposed methodology allows for detailed comparison of saponin profiles from intact plant extracts as well as saponin aglycone profiles from hydrolysed samples. Continuously measured 1D proton NMR data during LC separation along with mass spectrometry data revealed significant differences, including contents of saponins, types of aglycones and numbers of sugar moieties attached to the aglycone. A total of 49 peaks were tentatively identified as saponins from both plants; they are derived from eight types of aglycones and with 2–5 sugar moieties. Identification of two previously known insect-deterrent saponins, hederagenin cellobioside and oleanolic acid cellobioside, demonstrated the applicability of the methodology for relatively rapid screening of bioactive compounds.

Succinic semialdehyde dehydrogenase (SSADH) is a mitochondrial enzyme involved in the catabolism of the neurotransmitter γ-amino butyric acid. Pathogenic variants in the gene encoding this enzyme cause SSADH deficiency, a developmental disease manifesting as hypotonia, autism and epilepsy. SSADH deficiency patients usually have family-specific gene variants. Here, we describe a family exhibiting four different SSADH variants, Val90Ala, Cys93Phe, and His180Tyr/Asn255Asp (a double variant). We provide a structural and functional characterization of these variants and show that Cys93Phe and Asn255Asp are pathogenic variants that affect the stability of the SSADH protein. Due to impairment of the cofactor NAD+ binding, these variants show a highly reduced enzyme activity. However, Val90Ala and His180Tyr exhibit normal activity and expression. The His180Tyr/Asn255Asp variant exhibits a highly reduced activity as a recombinant species, is inactive and shows a very low expression in eukaryotic cells. A treatment with substances that support protein folding by either increasing chaperone protein expression or by chemical means was not capable of increasing the expression of the pathogenic variants of the SSADH deficiency patient. However, stabilization of the folding of pathogenic SSADH variants by other substances may provide a treatment option for this disease.

In today's world, news events are emerging incessantly. Classifying the same event reported by different countries is of significant importance for public opinion control and intelligence gathering. Due to the diverse types of news, relying solely on translators would be costly and inefficient, while depending solely on translation systems would incur considerable performance overheads in invoking translation interfaces and storing translated texts. To address this issue, we mainly focus on the clustering problem of cross-lingual news. To be specific, we use a combination of sentence vector representations of news headlines in a mixed semantic space and the topic probability distributions of news content to represent a news article. In the training of cross-lingual models, we employ knowledge distillation techniques to fit two semantic spaces into a mixed semantic space. We abandon traditional static clustering methods like K-Means and AGNES in favor of the incremental clustering algorithm Single-Pass, which we further modify to better suit cross-lingual news clustering scenarios. Our main contributions are as follows: (1) We adopt the English standard BERT as the teacher model and XLM-Roberta as the student model, training a cross-lingual model through knowledge distillation that can represent sentence-level bilingual texts in both Chinese and English. (2) We use the LDA topic model to represent news as a combination of cross-lingual vectors for headlines and topic probability distributions for content, introducing concepts such as topic similarity to address the cross-lingual issue in news content representation. (3) We adapt the Single-Pass clustering algorithm for the news context to make it more applicable. Our optimizations of Single-Pass include adjusting the distance algorithm between samples and clusters, adding cluster merging operations, and incorporating a news time parameter.

This study investigates the applications of reconfigurable intelligent surfaces (RIS) in heterogeneous downlink networks (HetNet). Due to the network densification, the small cell base station (SBS) interferes with the macrocell users (MUE). In this paper, we utilize RIS to mitigate cross-tier interference in an HetNet via directional beamforming by adjusting the phase shift of the RIS. We consider an RIS-assisted HetNet consisting of multiple SBS nodes and MUEs that utilize both direct paths and reflected paths. Therefore, the aim of this study is to maximize the sum rate of all MUEs by jointly optimizing the transmit beamforming of the macrocell base station (MBS) and the phase shift of the RIS. An efficient RIS reflecting coefficients-based optimization (RCO) is proposed based on a successive convex approximation approach. Simulation results are provided to show the effectiveness of the proposed scheme in terms of its sum rate in comparison with the scheme HetNet without RIS and the scheme HetNet with RIS but with random phase shifts.

Objective: The aim of this study was to provide a new machine learning method to determine temporal events and inner-cycle parameters (e.g., cycle, poles and skis contact and swing time) in cross-country roller ski skating on the field, using a single deported inertial measurement unit (IMU). Methods: The developed method is based on long short-term memory neural networks to detect poles and skis initial and final contact with the ground during the cyclic movements. Eleven athletes skied four laps of 2.5 km at low and high intensity using skis with two different rolling coefficients. They were equipped with IMUs attached to the upper back, lower back and to the sternum. Data from force insoles and force poles were used as reference system. Results: The IMU placed on the upper back provided the best results, as the LSTM network was able to determine the temporal events with an accuracy ranging from 49 to 55 ms and the corresponding inner-cycles parameters were calculated with a precision of 63 to 68 ms. The method detected 95% of the events for the poles and 87% of the events for the skis. Conclusion: The proposed LSTM method provides a promising tool for assessing temporal events and inner-cycle phases in roller ski skating showing the potential of using a deported IMU to estimate different spatio-temporal parameters of human locomotion.

Mass crises are disruptive to people's mental health. The study aimed to explore mental distress during COVID-19 quarantine in a sample of university workers in Brazil. The survey included sets of questions about demographics, health, and support, an open question about major concerns, and the Clinical Outcome Routine Evaluation (CORE-OM), a measure of mental distress. 407 professionals participated in the study: mean age of 40 years (SD = 11.2), mostly female (67.8%), married (64.8%) and fulfilling social distancing to avoid COVID-19 infection (99%). Using the Consensual Qualitative Research for simple qualitative data (CQR-M) the main areas of concern were grouped into six domains, as follows: Work, Health, Isolation, Personal life and routine, Social environment, and Future. Many responses were multiple. They form categories indicating specific concerns within these domains. Quantitative data were analyzed by identifying the simple effects of potential predictors of mental distress. The results indicated medium effects of help with household chores, psychiatric treatment, age and physical exercise. Having someone available to listen was the only variable with a large effect in reducing mental suffering. The hybrid approach showed that the psychological experience during the pandemic is quite multifaceted and complex pointing new clues for public mental health.

Zika virus (ZIKV) is a flavivirus that originated in Africa but emerged in Latin America in 2015. In this region, other flaviviruses such as Dengue (DENV), West Nile, and Yellow Fever Virus (YFV) also circulate, allowing for possible antigenic cross-reactivity to impact viral infections and immune responses. Studies have found antibody mediated enhancement between DENV and ZIKV, but the impact of YFV antibodies on ZIKV infection has not been fully explored. ZIKV infections cause congenital syndromes, such as microcephaly, necessitating further research into ZIKV vertical transmission through the placental barrier. Recent advancements in biomedical engineering have generated co-culture methods that allow for in vitro recapitulation of the maternal: fetal interface. This study utilized a transwell assay, which is a co-culture model utilizing human placental syncytiotrophoblasts, fetal umbilical cells, and a differentiating embryoid body to replicate the maternal: fetal axis. To determine if cross reactive YFV vaccine antibodies impact the pathogenesis of ZIKV across the maternal fetal axis, maternal syncytiotrophoblasts were inoculated with ZIKV or ZIKV incubated with YFV vaccine anti-sera, and viral load was measured 72 hours post inoculation. The data show that the impact of YFV on ZIKV replication is cell line dependent. In differentiating embryoids, the presence of YFV antibodies enhanced ZIKV infection. Since viral pathogenesis, and the impact of antigenic cross-reactive antibodies, is cell line specific at the maternal-fetal axis, this suggests there may be discreet mechanisms that impact congenital ZIKV infections.

With the rapid development of Internet and the widely usage of smart devices, massive multimedia data are generated, collected, stored and shared on the Internet. This trend makes cross-modal retrieval problem become a hot issue in this years. Many existing works pay attentions on correlation learning to generate a common subspace for cross-modal correlation measurement, and others uses adversarial learning technique to abate the heterogeneity of multi-modal data. However, very few works combine correlation learning and adversarial learning to bridge the inter-modal semantic gap and diminish cross-modal heterogeneity. This paper propose a novel cross-modal retrieval method, named ALSCOR, which is an end-to-end framework to integrate cross-modal representation learning, correlation learning and adversarial. CCA model, accompanied by two representation model, VisNet and TxtNet is proposed to capture non-linear correlation. Beside, intra-modal classifier and modality classifier are used to learn intra-modal discrimination and minimize the inter-modal heterogeneity. Comprehensive experiments are conducted on three benchmark datasets. The results demonstrate that the proposed ALSCOR has better performance than the state-of-the-arts.

An appearance model plays a crucial rule in multi-target tracking. In traditional approaches, the two steps of appearance modeling i.e visual representation and statistically similarity measure are modeled separately. Visual representation is achieved either through hand-crafted features or deep features and statically similarity is measure through a cross entropy loss function. A loss function based on cross-entropy (KL-divergence, mutual information) find closely related probability distribution for the targets. However, if the targets have similar visual representation, it ends up mixing the targets. To tackle this problem, we come up with a synergetic appearance model named Single Shot Appearance Model based on Siamese neural network. The network is trained with a contrastive loss function for finding the similarity between different targets in a single shot. The input to the network is two target patches and based on their similarity, a contrastive score is output by the network. The proposed model is evaluated on accumulative dissimilarity metric on three datasets. Quantitatively, promising results are achieved against three baseline methods.

Abstract Optimal targeting of nanoparticles (NP) to dendritic cells (DCs) receptors to deliver cancer-specific antigens is key to an efficient induction of anti-tumor immune responses. Poly (lactic-co-glycolic acid) (PLGA) nanoparticles containing tètanus toxoid and gp100 melanoma-associated antigen, toll-like receptor adjuvants were targeted to the DC-SIGN receptor in DCs by specific humanized antibodies or by ICAM3-Fc fusion proteins mimicking natural ligand. Despite higher binding and uptake efficacy of anti-DC-SIGN antibody-targeted NP vaccines than ICAM3-Fc ligand, no difference were observed in DC activation markers CD80, CD83, CD86 and CCR7 induced. DCs loaded with NP coated with ICAM3-Fc appeared more potent in activating T cells via cross-presentation than antibody-coated NP vaccines. This fact could be very crucial in the design of new cancer vaccines.

Multi-task Gaussian processes (MTGPs) are a powerful approach for modeling structured dependencies among multiple tasks. Researchers on MTGPs have contributed to enhance this approach in various ways. Current MTGP methods, however, cannot model nonlinear task correlations in a general way. In this paper we address this problem. We focus on spectral mixture (SM) based kernels and propose an enhancement of this type of kernels, called multi-task generalized convolution spectral mixture (MT-GCSM) kernel. The MT-GCSM kernel can model nonlinear task correlations and mixtures dependency, including time and phase delay, not only between different tasks but also within a task at the spectral mixture level. Each task in MT-GCSM has its own generalized convolution spectral mixture kernel (GCSM) with a different number of convolution structures and all spectral mixtures from different tasks are dependent. Furthermore, the proposed kernel uses inner and outer full cross convolution between base spectral mixtures, so that the base spectral mixtures in the tasks are not necessarily aligned. Extensive experiments on synthetic and real-life datasets illustrate the difference between MT-GCSM and other kernels as well as the practical effectiveness of MT-GCSM.

Previous studies implied the different behavioral intention formation of a specific object for individuals in different age groups, but few research to Chinese consumers’ sustainable fast fashion behaviour were found considering the enormous amount of consumption and waste of fast fashion products in China. Meanwhile, as a fast developing country, it might be insufficient to conduct research ignoring the consequences of different education level and growing environment among different generations. Thus, to generate in-depth and heuristic Chinese consumers information, this study developed proposed theoretical framework (TORA) based on research by Fishbein and Ajzen (1975), while the validity among Chinese consumers was tested as well. Following the TORA model, this study aims to investigate if consumers’ age will moderate the relationship between attitude and intention, and the relationship between subjective norms to behavioral intention. Through structural equation modelling in AMOS, it was found that the model has a well fit to large sample of Chinese consumers, while the moderation effect of age was not significant in the whole sample. Further hierarchical regression analysis conducted in SPSS and Process was able to locate the moderation effect of if divide the consumers into groups by age. Which is, age is significantly and positively moderating the path subjective norms to intention in younger generation (18-25), but significantly positive moderating attitude to intention in consumers aged 26-39. Implications in marketing and to policy makers are discussed at the end of this research.

With around one billion of the world's population affected, the era of Metabolic-associated fatty liver disease (MAFLD) pandemic has entered the global stage. MAFLD is a chronic progressive liver disease with accompanying metabolic disorders such as type 2 diabetes mellitus and obesity which can progress asymptomatically to liver cirrhosis and subsequently to hepatocellular carcinoma (HCC), and for which, to date there is almost no approved pharmacologic options. Because MAFLD has a very complex etiology and it affects also extrahepatic organs, a multidisciplinary approach is required when it comes to finding an effective and safe active substance for MAFLD treatment. The optimal drug for MAFLD should diminish steatosis, fibrosis and inflammation in the liver, and the winner for MAFLD drug authorisation seems to be the one that significantly improves liver histology. Saroglitazar (Lipaglyn®) was approved for Metabolic dysfunction associated steatohepatitis (MASH) in India in 2020; however, the drug is still being investigated in other countries. Despite that a pharmaceutical industry is still lagging behind to develop an ap-proved pharmacologic therapy for MAFLD, research has been recently intensified and many molecules which are underway in the final stages of clinical trials are expected to be approved in the coming few years. Already this year, the first drug (Rezdiffra™) in the United States was ap-proved via accelerated procedure for treatment of MAFLD, i.e. of MASH in adults. This review underscores the most recent information related to the development of drugs for MAFLD treatment, focusing on the molecules that have come furthest towards approval.

The editorial explores the realm of emerging translational research in neurology and psychiatry, providing insights into various subjects, including neurodegenerative disorders and innovative therapeutic methods. The main objective is to study neurological and psychiatric disorders, such as Alzheimer's disease, with a particular emphasis on techniques for neural regeneration and repair. The editorial highlights the importance of taking a comprehensive approach to studying and treating complex neurological and psychiatric conditions. This involves thoroughly reviewing research papers on the causes, development, biomarkers, and treatment options for these conditions. The editorial emphasizes the necessity of using multidisciplinary and integrative methods to gain a deeper understanding and improve the treatment of these conditions. The development of an animal model for recurrent primary dysmenorrhea showcases the innovative techniques employed in the investigation of gynecological disorders, illustrating the capacity of translational research to connect fundamental scientific knowledge with practical medical applications. The cooperative endeavors of researchers and clinicians emphasized in this editorial lay the foundation for revolutionary advancements that hold the potential to enhance outcomes for individuals afflicted with neurological and psychiatric disorders globally.

The part transportation efficiency is a main factor of aircraft sortie generation rate. Part transportation is used to transport spare part from base to carrier. Transportation strategy depends on both demand on carrier and inventory in transportation base. The transportation time and stochastic demand will induce fluctuations of cost and inventory. Thus, a Takagi-Sugeno fuzzy system of dynamic part transportation is established considering transportation time and stochastic demand. And a novel Takagi-Sugeno fuzzy robust control is designed for dynamic part transportation, which will keep transportation cost and part inventory stable. First of all, a fuzzy model with stochastic demand and transportation time is proposed. Then, a novel robust control with cross rule groups is conducted according to production and transportation strategy, which will reduce fluctuations induced by strategies switch. Moreover, robust stability is guaranteed and part can be supplied in time under a low cost. Finally, simulation illustrates usefulness and quickness of the novel Takagi-Sugeno fuzzy robust control. Besides, the proposed method will be useful in other transportation electrification systems with delay time and uncertainty.

This study aimed to compare the levels of physical activity and quality of life reported by Chileans with and without osteoarthritis (OA). Educational level and monthly income data were collected from eighty-two participants (62 women and 20 men), of whom 41 had OA. Concerning the medical information of the persons suffering from OA, diseases, and date of diagnosis were indicated. The International Physical Activity Questionnaire-Short Form (IPAQ-SF) and its Elderly version (IPAQ-E) estimated physical activity levels. The Short Form 36 Questionnaire (SF-36) assessed health-related quality of life. The findings indicate that non-OA subjects scored higher on all dimensions of the SF-36, including physical function, physical role, bodily pain, general health, vitality, social function, emotional role, and mental health. Individuals with OA reported better physical function and role, general health, vitality, social function, and mental health when they walked more. However, no associations were found between any physical activity levels and the degree of pain in people with OA. Our findings underscore the critical role of investigating physical activity in OA patients to enhance their quality of life, particularly in light of the increased sedentary behavior observed post-pandemic.

In Southeast Asia, the incidence of Leukemia, a malignant blood cancer originating from hema-topoietic progenitor cells, is on the rise, marked by a concerning 54% mortality rate. This study focuses on enhancing early-stage prediction to improve patient recovery prospects significantly. Leveraging Machine Learning and Data Science, we employ protein sequential data from frequently mutated genes such as BCL2, HSP90, PARP, and RB to predict Chronic Myeloid Leukemia (CML). Our approach relies on robust feature extraction techniques, namely Di-peptide Composition (DPC), Amino Acid Composition (AAC), and Pseudo amino acid composition (Pse-AAC), with prior attention to addressing outliers and validating feature selection through the Pearson Corre-lation Coefficient. Data augmentation ensures a well-rounded dataset for analysis. Employing a range of Machine Learning models, including Support Vector Machine (SVM), XGBoost, Random Forest (RF), K Nearest Neighbor (KNN), Decision Tree (DT), and Logistic Regression (LR), we achieve accuracy rates spanning from 66% to 94%. These classifiers undergo comprehensive as-sessment using performance metrics such as accuracy, sensitivity, specificity, F1-score, and the confusion matrix. Our proposed solution, encompassing a user-friendly web application dashboard, presents an invaluable tool for early CML diagnosis with profound implications for practitioners, offering a deploy-able asset within healthcare institutions and hospitals.

Mango (Mangifera indica L.) is an allotetraploid (2n = 4X= 40) drupe fruit and has high nutritional value belongs to genus Mangifera and family Anacardiaceae. Mango cultivars are used with worldwide acceptance to pharmacological, ethnomedical, and phytochemical industries. Assessment of the genetic distinctiveness of a cultivar through morphological descriptors is an important tool for both the registration and the protection. New mango genotypes have been improved using valuable diverse germplasm resources to ensure food security. DNA fingerprinting based simple sequence repeats (SSR)-markers have been the most broadly used, effective and accurate in evaluation of genetic characterization of a cultivar. Molecular breeding is an effective source of genetic gain after improvement of fruit trees using marker assisted genomic selection. Total genomic DNA (gDNA) was generated using CTAB method from each cultivar. The most effective 50 hyper-variable SSR markers were selected. Highly specific DNA fingerprints were identified in the candidate line ‘Azeem Chaunsa’ compared with three standard cultivars using SSR-PCR. An agglomerative hierarchical clustering method was used to construct dendrogram based on the UPGMA clustering method. Cultivar identification diagram (CID) was constructed to evaluate association among standard cultivars and Azeem Chaunsa. Our results showed that SSR markers could efficiently assess genetic diversity in mango. The genetic similarity coefficients were recorded between the cultivars of mango ranged from 0.49 to 0.67. CID results concluded that cultivar ‘Azeem Chaunsa’ varied significantly from the check cultivar, Sindhri (46.2%), S.B Chaunsa (45%) and Sufaid Chaunsa (46.7%). The results obtained in this study will orient cultivar identification strategies for a successful future.

Porous α-Al2O3 ceramics is a highly demanded material for multitude applications such as filters, substrates, biomedicine materials, etc. Despite the availability of the raw materials, a challenge of their technology is in a high energy budget caused by the sintering above 1500 °C. For a cold sintering processing (CSP) of ceramics, the lowering of α-Al2O3 sintering temperature is one of the most urgent challenges at the background of its rapid development. The current paper for the first time demonstrates the solution of the mentioned problem by the CSP of α-alumina ceramics in a presence of pure water as a transient liquid. The manufactured materials were examined by XRD analysis; the evolution of their microstructures during the CSP was revealed by SEM, and the porosity evaluated by the Archimedes method. The ceramics with an open porosity up to 36 % was produced at 380-450 °C, 220 MPa in 30 min. An increase in the pressure was found to impede α-Al2O3 formation from γ-AlOOH. The development of the microstructure was discussed within the frameworks of the dissolution-precipitation model and the homogenous nucleation. The results of the SEM study pointed to the coalescence of γ-AlOOH grains during the CSP.

This study investigates the mean annual water temperature trends at the confluence of the Sava and Danube Rivers, along with air temperature trends at the Belgrade meteorological station, spanning from 1956 to 2020. Results reveal a consistent increase in temperature across all three measuring stations, with the Danube experiencing a rise of 0.34°C/10 years, the Sava at 0.44°C/10 years, and Belgrade's air temperature increasing by 0.39°C/10 years. Employing the RAPS method, sharp rises in water temperature were pinpointed in 1989 for the Sava and 1990 for the Danube, while Belgrade's air temperature surge began in 1998. The highest intensity of air temperature increase within the recent period (1998-2020) was observed at the Belgrade observatory, reaching 0.76°C/10 years. Notably, the Sava exhibited a faster increase in water temperature over the last thirty years compared to the Danube. August marked the peak average water temperature for both rivers, while July recorded the highest average air temperature in Belgrade. Despite differing flow rates, both rivers exhibit similar hydrological regimes, with maximum flows occurring in April and minimum flows in August for the Sava, and October for the Danube. Seasonal temperature increases were most pronounced in summer, notably in August, with the smallest rises occurring during cold periods. Additionally, an inverse proportional relationship between mean annual water temperatures and discharges was observed at both river stations.

Freezing of Gait (FoG) is a disabling motor complication in Parkinson’s disease (PD), affecting approximately 50% of advanced PD patients. It is characterized by sudden and transient inability to initiate or maintain walking, leading to falls and reduced quality of life. This study investigates the relationship between white matter integrity and step initiation impairments in FoG. Forty-three PD patients (26 with FoG) underwent diffusion-weighted imaging to assess white matter DTI metrics and kinematic analysis during step initiation tasks. Multiple regression analyses were conducted to explore the connection between white matter tract integrity and step initiation behavior. The multiple regression analysis shows that (1) Right Inferior Longitudinal Fasciculus RD explained 31% of APA duration’s variance; (2) Corpus Callosum Forceps Major explained 25% of the step length's variance. There was a positive correlation between the Right Inferior Longitudinal Fasciculus RD and APA duration and a negative correlation between Corpus Callosum Forceps Major RD and step length. The findings suggest that compromised white matter integrity in RILF and CC contributes to impaired motor control during step initiation in FoG. These regions are critical for inhibitory control and interhemispheric coordination, crucial for APA execution and step length regulation.

The field of epigenetics, which explores how heritable traits or stable alterations of cell functions occur without changes to the DNA sequence and how environmental factors affect gene expression, is rapidly advancing. Epigenetics plays a critical role in memory formation, learning, and cognitive functioning, effectively bridging genetics with environmental influence. Maternal behavior in rats, for instance, can modify the stress response of their offspring through epigenetic mechanisms such as histone acetylation and DNA methylation. Understanding neurodegenerative diseases like Parkinson's disease (PD) depends on comprehending the mechanisms of epigenetic regulation. Epigenetic modifications, which alter proteins and DNA structure without changing the DNA sequence, can activate or suppress gene expression, assisting organisms in adapting to environmental changes. These modifications may influence genes involved in inflammation, synaptic plasticity, and neuroprotection, potentially contributing to cognitive deficits in PD patients. MicroRNAs (miRNAs), histone modifications, and DNA methylation are the epigenetic mechanisms that significantly influence cell differentiation and maintain normal cellular activity. Understanding the intricate molecular processes of epigenetics could lead to more targeted and effective therapies. Despite numerous findings on how epigenetics affects cognitive alterations in PD patients, only some studies coordinate and integrate these results. Here, we summarize recent findings on how epigenetic changes impact gene expression linked to cognitive impairments in PD.

Background: Glioma surgery was remarkably renewed in the past 2 decades, with improved safety and limited but yet improved life expectations. Fluorescence-guided resection of high-grade gliomas (HGG) plays a central role in this sense, by allowing higher degrees of extent of resection (EOR). The introduction of the exoscopic guided surgery may be considered an implementation for fluorescence techniques over the traditional microscopes. We present the application and the advantages of the exoscopic guided surgery compared to the microscopic surgery in tumor resection guided by 5-ALA fluorescence in patients with HGG. Methods: ten consecutive patients underwent a surgery for HGG resection. The surgery was performed via an exoscopic-guided procedure (Olympus Orbeye) and after oral administration of Gliolan 5 hours before the procedure. During surgery, the procedure was shifted to microscope (Kinevo 900, Zeiss) view. The intensity of the fluorescence under the two different was subjectively measured in different picture samples during the surgery in a 1 to 5 (from minimum to maximum) scale. The brightness of the surgical field and the detailing of the anatomy were also analyzed comparatively. Results: among the ten patients the histopathological diagnosis was an high grade glioma in all cases. In 9 cases was possible to achieve the gross total resection. There was no perioperative mortality. The median fluorescence intensity, on a scale of 1–5, was 4.5 in the exoscope group and 3.5 in the microscope group (p<0.01). Conclusions: The exoscopic guided surgery adds advantages to the traditional fluorescence- guided surgery with 5-aminolevulinic acid. Beyond the important advantage of low cost and the possibility to perform collaborative surgeries, it adds a plain and continuous visualization of the tumor and the surgical field in the fluorescence guided glioma surgery compared to the microscopic guided one.

The assessment of soil contamination in the vicinity of integrated siderurgical plants is of outmost importance for agroecosystems and human health, and sensitive techniques should be employed for accurate assessment of chemical elements (metals, potential toxic elements, rare earths, radioelements) in soil and further evaluation of potential ecological and safety risk. In this paper a total of 45 major, minor and trace elements (Al, As, Au, Ba, Br, Ca, Cd, Ce, Co, Cr, Cs, Cu, Dy, Eu, Fe, Hf, Hg, I, K, La, Mg, Mn, Mo, Na, Nd, Ni, Pb, Rb, Sb, Sc, Sm, Sn, Sr, Ta, Tb, Th, Ti, Tm, U, V, W, Y, Yb, Zn and Zr) were quantified in soils located around a large siderurgical works (Galati, SE Romania) using instrumental neutron activation analysis (INAA) in combination with X-ray fluorescence (XRF) and inductively coupled plasma mass spectrometry (ICP-MS). The statistical analysis results and vertical distribution patterns for three depths (0-5 cm, 5-20 cm, 20-30 cm) indicate inputs of toxic elements in the sites close to the ironmaking and steelmaking facilities and industrial wastes dumping site. For selected elements, a comparison with historical, legislated and world reported concentration values in soil was performed and depth migration, contamination and toxic risk indices were assessed. The distribution of major, rock forming elements was closer to the Upper Continental Crust (UCC), and to the Dobrogea loess, finding confirmed by the ternary diagram of the incompatible trace elements Sc, La and Th, as well as by the La to Th rate. At the same time, the La/Th vs. Sc and Th/Sc vs. Zr/Sc bi-plots suggested a felsic origin and a weak recycling of soils mineral components.

Patients with metastatic epidural spinal cord compression (MESCC) and favorable survival prognoses may benefit from radiation doses exceeding 10 x 3.0 Gy. In a multi-center phase 2 trial, patients receiving 15 x 2.633 Gy (41.6 Gy10) or 18 x 2.333 Gy (43.2 Gy10) were evaluated for local progression-free survival (LPFS), motor/sensory functions, ambulatory status, pain, distress, toxicity, and overall survival (OS). They were compared (propensity score adjusted Cox regression) to a historical control group (N=266) receiving 10 x 3.0 Gy (32.5 Gy10). In the phase 2-cohort, 50 (of 62 planned) patients were evaluable for LPFS. Twelve-month rates of LPFS and OS were 96.8% and 69.9%, respectively. Motor and sensory functions improved in 56% and 57.1% of patients, and 94.0% were ambulatory following radiotherapy. Pain and distress decreased in 84.4% and 78.0% of patients. Ten and two patients experienced grade 2 and 3 toxicities, respectively. Phase 2 patients showed significantly better LPFS than the control group (p = 0.039) and a trend for improved motor function (p = 0.057). Ambulatory and OS rates were not significantly different. Radiotherapy with 15 x 2.633 Gy or 18 x 2.333 Gy was well tolerated and appeared superior to 10 x 3.0 Gy.

In this paper, the deformation behavior of S32750 duplex stainless steel during low cycle fatigue was studied by controlling number of cycles. The microstructure of the specimens under different cycles was characterized by optical microscope (OM), scanning electron microscope (SEM), electron backscatter diffraction (EBSD) and transmission electron microscope (TEM). Microhardness of two phases was measured by a digital microhardness instrument. The results showed that the microhardness of ferrite increases significantly after the first 4000 cycles, while the austenite shows a higher strain hardening rate after fatigue fracture, and the microhardness of ferrite and austenite increases by 23 HV and 87 HV, respectively. Two-phase kernel average misorientation (KAM) diagram showed that the continuous accumulation of plastic deformation easily leads to the initiation of cracks inside the austenite and at the phase boundaries. The evolution of dislocation morphology in two phases was obviously different. With the increase of cycle number, the dislocation in ferrite gradually transforms from dislocation bundles and dislocation array to sub-grain structure, while the dislocation in austenite gradually develops from dipole array to ordered Taylor lattice network structure.

Spent coffee grounds (SCG) have great potential as a useful, value-added biological material. In this context, activated carbon (AC) was prepared from SCG by an activation process using H3PO4 at 600°C in air and used as an adsorbent for the azo dye AO7, a model molecule for dye colorants found in textile industry effluents. X-ray diffraction, SEM and BET revealed that the AC was predominantly amorphous, consisting of a powder of 20-100 µm particles with mesopores averaging 5.5 nm in pore size. Adsorption kinetics followed a pseudo-second-order law, while the Langmuir model best fitted experimental isotherm data (maximum capacity of 119.5 mg AO7 per AC g). Thermodynamic parameters revealed that adsorption was endothermic and spontaneous. All the characterizations indicated that adsorption occurred by physisorption via mainly - interactions. The best experimental removal efficiency optimized by means of a Box-Behnken design and response surface methodology was 98% for an initial AO7 concentration of 20 mg.L-1 at pH 7.5 with a dose of 0.285 g.L-1 of AC and a contact time of 40 min. These results clearly show that activated carbon prepared from SCG can be a useful material for efficiently removing organic matter from aqueous solutions.

Alcoholic liver disease (ALD) is a major cause of chronic liver disease. This term covers a broad spectrum of liver lesions, from simple steatosis to alcoholic hepatitis and cirrhosis. The patho-genesis of ALD is multifactorial and not fully elucidated due to complex mechanisms related to direct ethanol toxicity with subsequent hepatic and systemic inflammation. The accumulation of pro-inflammatory cytokines and the reduction of anti-inflammatory cytokines promote the development and progression of ALD. To date, there are no targeted therapies to counteract disease progression and prevent acute liver failure. Corticosteroids reduce mortality by acting on the hepatic-systemic inflammation. On the other hand, several studies analyzed the effect of the inhibition of pro-inflammatory cytokines and the stimulation of anti-inflammatory cytokines as potential therapeutic targets in ALD. This narrative review aims to clarify the role of the cy-tokines in the pathogenesis and treatment of ALD.

Piezoelectric c-axis oriented zinc oxide (ZnO) thin films, from 1.8 up to 6.6 µm thick, have been grown by radio frequency magnetron sputtering technique onto fused silica substrates. A delay line consisting in two interdigital transducers (IDTs) with wavelength λ = 80 µm was photolith-ographically implemented onto the surface of the ZnO layers. Due to the IDTs split finger con-figuration and metallization ratio (0.5), the propagation of both the fundamental, third and nineth harmonic Rayleigh waves is excited; also, three leaky surface acoustic waves (SAWs) were detected travelling at velocity close to that of the longitudinal bulk wave in SiO2. The acoustic waves propagation in ZnO/fused silica was simulated by using 2D finite-element method (FEM) tech-nique to identify the nature of the experimentally detected waves. It turned out that, in addition to the fundamental and harmonic Rayleigh waves, also high-frequency leaky surface waves are ex-cited by the harmonic wavelengths; such modes are identified as leaky-Sezawa (LS) waves under cut-off. The velocity of all the modes was found in good agreement with the theoretically calcu-lated values. The existence of a low-loss region for the Sezawa wave below the cut off was theo-retically predicted and experimentally assessed.

Soil management in orchards can have several economic and environmental implications. In this study, three different soil management systems were compared in a dry-farmed olive grove: conventional tillage (Tillage), glyphosate-based herbicide (Herbicide) and Sheep Walking. The experiment lasted eleven years (2011-2022) and was carried out after a previous trial conducted on the same plot with the same treatments and duration (2001-2011). However, in the earlier trial, the Herbicide and Sheep Walking treatments switched positions in the plot, while the tillage treatment remained in its original place. The average total accumulated olive yields between 2011 and 2022 were 225.1, 230.9, and 245.0 kg tree–1 for the Sheep Walking, Tillage, and Herbicide treatments, respectively. However, no significant differences were observed between the treatments. The levels of total organic carbon in the soil, measured in samples collected in the last year of the study, were 41.3, 33.7, and 37.3 g kg–1, respectively for the same treatments. These findings indicated that the Tillage treatment exhibited lower soil organic matter content and reduced bioavailability of some nutrients, which raises concerns about its sustainability. On the contrary, employing Sheep Walking with an appropriate stocking rate, effectively controlling vegetation in the spring, ensured favourable soil properties and olive yields comparable to the other treatments. Moreover, the Sheep Walking approach provides supplementary advantages to the farmer, including revenue from the sale of animal products and the opportunity to transition to organic farming systems, which better align with the preferences of contemporary societies.

Since December 2019, the COVID-19 virus has rapidly spread worldwide, prompting the World Health Organization (WHO) to declare it a pandemic and advocate for the widespread use of face masks to mitigate transmission. In this review, we delve into the potential impact of prolonged face mask use on temporomandibular joint (TMJ) health, an area that has garnered limited attention amidst COVID-19 research. Research has revealed that improper mask fit, and constant readjustment can lead to TMJ abnormalities. Similarly, there is a demonstrated correlation between continuous mask usage and increased incidence of headaches, temporomandibular pain, and diminished quality of life. Many studies have highlighted discomfort in the preauricular area, headaches, TMJ noises, headache, jaw pain, and muscle fatigue, as well as dermatological disorders that have been attributed to prolonged mask wear and its impact on TMJ. Our study catalyzes future research endeavors, urging a deeper exploration of the implications of long-term mask wear, not only in the context of the COVID-19 pandemic but also among occupational groups regularly exposed to extended mask use. By unraveling the complexities of TMJ health in the face of evolving preventive measures, we aim to enhance our understanding and safeguard the well-being of mask-wearers worldwide.

The black-chinned tilapia Sarotherodon melanotheron is the most abundant fish species in the Nakwa (a closed lagoon) and Brenu (an open lagoon) in the Central region of Ghana. Aspects of the life history characteristics and the ecology of the fish populations in both lagoons were studied to assess the bio-ecological status of this important resource. The estimated von Bertalanffy growth parameters were L∞ = 12.04 cm; K =2.76 year-1 for the Nakwa Lagoon samples and L∞ = 13.44 cm; K = 3.27 years-1 for Brenu Lagoon samples. Daily otolith incremental rate ranged from 0.01-0.03mm per day and 0.01-0.02mm per day for Nakwa and Brenu lagoons respectively. Stomach content analysis of the fish samples revealed that the species are planktivorous and the range of food varied between the lagoons. Green algae was the most prevalent food item in the stomachs of the fish samples from Nakwa with frequency of 69% while diatoms (80.5%) were most prevalent phytoplanktonic food item in for the fish in Brenu lagoon. The results of this study of Sarotherodon melanotheron from the two lagoons and can be used to improve on management policies, maximize yield and to sustain the fishery resources.

Artificial intelligence (AI) techniques have grown rapidly in recent years in the context of computing with smart mobile phones that typically allows the devices to function in an intelligent manner. Popular AI techniques include machine learning and deep learning methods, natural language processing, as well as knowledge representation and expert systems, can be used to make the target mobile applications intelligent and more effective. In this paper, we present a comprehensive view on mobile data science and intelligent apps in terms of concepts and AI-based modeling that can be used to design and develop intelligent mobile applications for the betterment of human life in their diverse day-to-day situation. This study also includes the concepts and insights of various AI-powered intelligent apps in several application domains, ranging from personalized recommendation to healthcare services, including COVID-19 pandemic management in recent days. Finally, we highlight several research issues and future directions relevant to our analysis in the area of mobile data science and intelligent apps. Overall, this paper aims to serve as a reference point and guidelines for the mobile application developers as well as the researchers in this domain, particularly from the technical point of view.

Breast cancer (BC) is a prevalent malignancy with various subtypes, each presenting unique diagnostic and therapeutic challenges. Triple-negative breast cancer (TNBC), which comprises 12-17% of breast cancers, is particularly aggressive due to its lack of estrogen receptor (ER), progesterone receptor (PR), and HER2 expression. This case report details the management of a 64-year-old woman with TNBC. Initially presenting with a left breast nodule, she underwent a biopsy that confirmed triple-negative infiltrating ductal carcinoma. Despite negative BRCA genetic testing, her significant family history of cancer and a newly detected right breast lesion led to a bilateral mastectomy. Post-surgery imaging revealed multiple hypodense nodules and a spiculated pulmonary nodule, prompting further investigation. An endoscopic lung biopsy identified a primary pulmonary carcinoma with histological features similar to the breast cancer, indicating the lung as the primary source. This case underscores the complexity of TNBC, the importance of comprehensive diagnostic evaluations, and the need for considering extramammary origins in metastatic cases. The findings emphasize the role of multidisciplinary teams in managing such rare and challenging cases and highlight the necessity for thorough and repeated evaluations in atypical BC presentations.

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.

3D printing is a non-traditional additive manufacturing process. It is different from the traditional subtractive manufacturing process. It offers exceptional rapid prototyping capabilities and results that traditional subtractive manufacturing methods cannot attain, especially in applications involving curved or intricately shaped components. Despite its advantages, metal 3D printing will face porosity, warpage, and surface roughness issues. These issues will affect the future practical application of the parts indirectly, for example, the structural strength and the parts assembly ca-pability. Therefore, this study compares the qualities of the warpage, weight, and surface rough-ness after milling and grinding processes under the same materials (316L stainless steel) between general rolled steel and 3D additive steel. Experimental results show that 3D printing parts are approximately 13% to 14% lighter than the general rolled steel. The surface roughness performance of 3D printing steel is better than general rolled steel under the same material after milling or grinding processing. The hardness of the 3D printing steel is better than that of the gen-eral rolled steel. The research verifies that 3D additive manufacturing can use surface processing to optimize surface performance and achieve the functions of lightness and hardness.

Hybrid electric vehicles (HEVs) are perceived as a first step towards the future of sustainable transport. Of course, battery electric vehicles (EVs) are currently ideal for what is wanted to stand for transport in the future. The lack of infrastructure for these vehicles makes many potential users choose hybrid vehicles in these conditions. This paper analyzes the influence of the engine and electric motor of hybrid vehicles on their performances. Three engines with slightly different power and close characteristics were considered for configured models. Also, two electric motors with very different power but having a very close maximum continuous torque have been used in models. One is an induction motor, and the other is a permanent magnet synchronous motor. ADVISOR software has been used for vehicles configuration and simulation. Series and parallel hybrid vehicles have been considered. The main dynamic performances and the fuel consumption in two driving cycles were compared for the configured models. Three conventional models with the same engines used in HEVs have also been simulated for reference. The results highlight that in the case of HEVs, the choice of combination engine/electric motor is crucial in obtaining the best report between dynamic performances and low fuel consumption, and implicitly a low negative impact on the environment.

Neuron degeneration is the most common old age complications worldwide. Alzheimer's disease (AD) is one of the most common neurodegenerative condition with limited drug options and significant adverse effects. Hence, there is a growing interest in exploring natural products for their potential pharmacological activities against AD. This study investigates the efficacy of Verbesina encelioides flower extract (VFE) in alleviating neurobehavioral damage induced by Scopolamine in rat mimicking AD model. GC-MS analysis showed that V. encelioides flower extract is rich in carotenoids like spirilloxanthin. Various behavioural models were used to assess the rats' learning and memory capabilities. Additionally, biochemical tests were conducted on the AD rat models to evaluate oxidative stress in the brain, including superoxide dismutase (SOD), nitric oxide (NO), reduced glutathione (GSH), and anti-acetylcholinesterase (AChE) enzyme assays. Findings from this study suggest that the VFE significantly improved the rats' cognitive aptitude and alleviated them from oxidative stress by reducing free radical generation. Based on the results obtained from GC-MS analysis, in silico interaction analysis of gingkolide A and spirilloxanthin with acetylcholinesterase was carried out. In summary, this study suggests that V. enceloides flower extract improves learning abilities and mitigates cognitive deficits caused by scopolamine. Thus V. enceloides could be potentially seen as natural therapeutic intervention against neurodegenerative disorders likes Alzheimer’s disease and dementia.

In Mexico viticulture represents the second source of employment in the agricultural area after the fruit and vegetable sector. In developed countries, remote sensing is widely used for vineyard monitoring, however, this tool is barely used in developing countries of Iberoamerica. In this re-search, our overall objective is to characterize two vineyards in the state of Queretaro (Mexico) using Sentinel-2 and meteorological data, specifically spectral and thermal indices. Results showed that spectral indices obtained from Sentinel-2 bands have characterized adequately the phenolog-ical evolution of the different varieties of the vineyards. The Modified Soil-Adjusted Vegetation Index (MSAVI) was adequately used to discriminate the first stages of vineyards, while the Nor-malized Difference Vegetation Index (NDVI) was useful to monitor vineyards during the rest stages of vineyards. Thermal indices have shown that the best grape varieties were those that can adapt to both cooler and warmer temperatures, have a reasonable ripening period, and can produce wines with balanced acidity and flavors. In conclusion, the combination of meteorological (including thermal indices) and remote sensing data (NDVI and MSAVI) provide information for choosing the suitable grape variety for this region.

Coal gasification with carbon dioxide is a process for generating clean gaseous fuels and relieving greenhouse effect. Zhundong coal has high alkali and alkali earth metals (AAEMs) content, medium volatile and low ash in nature. Isothermal CO₂ gasification of char derived from Zhundong coal (R-char) and char from acid washing R-char (AR-char) are performed in thermo-gravimetric analyzer (TGA). The effect of AAEMs is investigated on the gasification behavior in the range of temperatures 1073 K to 1273 K. The carbon conversion increases rapidly with increasing reaction temperature and CO₂ concentration. R-char has high gasification rate and carbon conversion compared with AR-char. The accuracy of the free-model approach for calculating activation energy at different conversions is validated by compared with different kinetic models (volume reaction model, distributed activation energy model). Moreover, R-char gasification with CO₂ shows a compensation effect as the Arrhenius parameters (EA and k0) increase or decrease simultaneously.

The numerical simulation of entropy generation at mixed natural free and forced convection flow in a square lid-driven cavity filled with an eletrically conducting binary fluids saturated porous media in the presence of a magnetic field is performed in this investigation. Both the top and bottom horizontal walls of the cavity are kept at constant and different temperatures while the left and right vertical walls are adiabatic and insulated. The magnetic field is applied in normal direction to the cavity. The Darcy model, including Brinkman term relative to viscous effects and Forchheimer term due to inertial forces, is used for the momentum equations, and the SIMPLER algorithm, based on the control volume finite-element method approach is used to solve the pressure –velocity coupling. The flow pattern and the heat transfer characteristics inside the cavity are presented in the form of isotherms, streamlines and isentropic lines and average Nusselt number trend. The entropy generation rate is determined for various values of Darcy number (10^-3 ≤ Da ≤ 1) and for a range of Hartmann number (0 ≤ Ha ≤ 10²). This study is limited to Pr = 7 which corresponds to water. It is observed that entropy generation is very affected by the variations of dimensionless control parameters considered.

Observe the synergistic effect and dose-effect relationship of Trimethoprim (TMP) on bactericidal activity with Flos Lonicerae in vitro. Microamount chessboard dilution method was conducted to determine the minimal inhibitory concentration (MIC) of Trimethoprim, Flos Lonicerae, as well as the combination of Trimethoprim and Flos Lonicerae separately against Staphylococcus aureus, Escherichia coli in vitro and Salmonella. The pour plate count method was used to determine the combined bactericidal activity of Flos Lonicerae combined with Different concentrations TMP. The results showed that the MIC values of the combination of Flos Lonicerae with TMP was much less than the MIC values of the independent use of Flos Lonicerae or TMP, The FIC values of the combination of Flos Lonicerae with TMP were between 0.5 and 1, there was additive effect between them. The bactericidal rates were fitted with least square method, the 95% confidence intervals of the optimal blending quantity about the combination of Flos Lonicerae with TMP on the test organisms were 231μg·mL^-1-249μg·mL^-1, 237μg·mL^-1-259μg·mL^-1, and 235 -259μg·mL^-1

To investigate the impact of electrode structure on Electrical Stimulation Therapy (EST) for chronic wound healing, this study designed three variants of flexible microelectrodes (FMs) with Ag-Cu coverings (ACCs), each exhibiting distinct geometrical configurations: hexagonal, cross-shaped, and serpentine. These were integrated with PPY@PDA/PANI (3/6) hydrogel dressings. Comprehensive animal studies, coupled with detailed electrical and mechanical modeling and simulations, were conducted to assess their performance. Results indicated that the serpentine-shaped FM outperformed its counterparts in terms of flexibility and safety, exhibiting minimal thermal effects and a reduced risk of burns. Notably, FMs with metal coverings under 3% demonstrated promising potential for optoelectronic self-powering capabilities. Additionally, simulation data highlighted the significant influence of hydrogel non-uniformity on the distribution of electrical properties across the skin surface, providing critical insights for optimizing EST protocols when employing hydrogel dressings.

Background: Long COVID, characterized by a persistent symptom spectrum following SARS-CoV-2 infection, poses significant health, social, and economic challenges. This review aims to consolidate knowledge on its epidemiology, clinical features, and underlying mechanisms to guide global responses; Methods: We conducted a systematic literature review, analyzing peer-reviewed articles and reports to gather comprehensive data on long COVID’s epidemiology, symptomatology, and management approaches; Results: Our analysis revealed a wide array of long COVID symptoms and risk factors, with notable demographic variability. The current understanding of its pathophysiology suggests a multifactorial origin yet remains partially understood. Emerging diagnostic criteria and potential therapeutic strategies were identified, highlighting advancements in long COVID management.; Conclusion: This review highlights the multifaceted nature of long COVID, revealing a broad spectrum of symptoms, diverse risk factors, and the complex interplay of physiological mechanisms underpinning the condition. Long COVID symptoms and disorders will continue to weigh on healthcare systems in years to come. Ad-dressing long COVID requires a holistic management strategy that integrates clinical care, social support, and policy initiatives. The findings underscore the need for increased international cooperation in research and health planning to address the complex challenges of long COVID. There is a call for continued refinement of diagnostic and treatment modalities, emphasizing a multidisciplinary approach to manage the ongoing and evolving impacts of the condition.

(1) Background: With the rising incidence of life expectancy, obesity, and tumours, understanding the incretory influence of adipose tissue in tumorigenesis becomes increasingly important. As the adipokines leptin and adiponectin are released by fat tissue, we aimed to analyse the expression of their respective receptors in tumours for which an association with obesity is epidemiologically hypothesized; (2) Methods: The expression of leptinR and adipoR1 were analysed in cohorts of renal cell cancer (n = 391), cervical cancer (n = 155), vulvar cancer (n = 107), and endometrial cancer (n = 90) by immunohistochemistry and correlated with clinicopathological parameters including survival times; (3) Results: Expression of leptinR was high in renal cell cancer (62.2% of cases), vulvar carcinoma (50%) and endometrial cancer (80.5% of tissue-samples). High expression was associated with favourable clinicopathological markers and longer overall survival times in renal cell cancer and vulvar cancer. AdipoR1 was only weakly expressed in all four tumor entities and did not show significant associations with clinicopathological parameters or prognosis; (4) Conclusion: High leptinR is a promising biomarker for favourable tumour outcome in renal cell carcinoma and vulvar carcinoma.

Tryptophan, an essential amino acid in mammals obtained from the diet, is influenced by maternal diet, which impacts early life and development of offspring. This is studied under the Developmental Origins of Diseases and Health (DOHaD) concept, so factors from conception to early childhood affect health and disease susceptibility. Tryptophan is metabolized mainly through two pathways: serotonin (5-HT) and kynurenine. The kynurenine pathway, active in the brain, gut, liver, and placenta, breaks down over 95% of tryptophan and plays roles in inflammation, neurotransmission, immune responses, and immune modulation during pregnancy. The serotonin pathway uses up to 5% of Tryptophan, mainly in the gut, adipose tissues, pancreatic cells, and central nervous system, and regulates responses to environmental changes, including sleep, cognition, and feeding behavior. Key enzymes in these pathways include Trp-2,3-dioxygenase (TDO), indoleamine-2,3-dioxygenase (IDO) type1 (IDO1), and type 2 (IDO2) (kynurenine pathway), and tryptophan hydroxylase type 1 (TPH1) and type 2 (TPH2), serotonin pathway. The fetus-placental unit manages tryptophan metabolism. Serotonin and kynurenine are crucial for placental health and fetal development. Serotonin adjusts placental blood volume and aids neurodevelopment. Kynurenine metabolites protect the fetus from maternal immunity and offer initial neuroprotection. At birth, infants switch from placental nutrients to breast milk, rich in tryptophan and protective bioactive molecules. Tryptophan, solely from breast milk, is crucial for infants. Its levels are high in newborns (first three weeks, 2-4 times higher than in adults), gradually declining to adult levels by the fourth week. The highlights the importance of tryptophan for the serotonin and kynurenine pathways in fetuses, newborns and babies applied to the DOHaD concept.

In this pilot study, 84 subjects with a history of poor oral hygiene were enrolled in an interventional, randomized, prospective, open-label controlled trial. The aim was to provide preliminary clinical data on the products, the recruitment monthly rate, and patient satisfaction to estimate resources for the main study, as well as descriptive data on oral microbiota rebalancing. The population was divided into five groups: 20 participants received delicate mint toothpaste, 12 mint toothpaste, 20 mint mouthwash, and 20 delicate mint toothpaste and mint mouthwash using a specifically custom-designed toothbrush. The 12 subjects in the control group continued to use their oral care products without changing their normal routine. The study duration was 28 days.All subjects tolerated the products well, and there were no adverse events. Recruitment capability and procedures allowed a realistic estimation for the future main trial. The products did not cause any changes in tooth color. The participants who completed the treatment consisting of delicate mint toothpaste, mint mouthwash, and the specifically custom-designed toothbrush showed the gingival sensitivity best results (p≤0.000). The products induced a statistically significant decrease in plaque in all treated groups (p≤0.000) and an improvement of gingival sensitivity (delicate mint toothpaste, p≤0.005; mint toothpaste, p≤0.015; and mint mouthwash, p≤0.015). All the products were effective in stabilizing the oral microbiota.The tested products showed an optimal safety profile. They also stabilized the biodiversity of the oral microbiota, making it less susceptible to microbial fluctuations than the control group.

The effects of the climate crisis are affecting ecosystems at different scales and magnitudes. This paper focuses on a massive Mediterranean mussel die-off observed along the middle Italian Adriatic coast in the summer of 2022. We considered the possible environmental causes of this phenomenon and carried out a climatic analysis of the last decade. We performed field surveys in different locations along a 16 Km coastal stretch (from Martinsicuro (TE) on the South, to Grottammare (AP) on the North). The study area includes two marine Sites of Community Importance under the European Natura 2000 network. The mussels die-off has interested practically all the natural mussel-beds colonizing the study area. Mussels are sessile filter-feeding organisms inhabiting the intertidal zone, therefore, are highly exposed to variations in environmental conditions such as temperature and nutrient load. We discuss the possible causes of this die-off, proposing that high temperature and the scarce availability of food acted simultaneously as stress factors, generating local unsustainable living conditions for this species.

Based upon Maxwell's equations, it has long been established that oscillating electromagnetic (EM) fields incident upon a metal surface decay exponentially inside the conductor, leading to a virtual EM vacuum at sufficient depths. Magnetic resonance imaging (MRI) utilizes radiofrequency (r.f.) EM fields to produce images. Here we present the first visualization of a virtual EM vacuum inside a bulk metal strip by MRI, amongst several novel findings. We uncover unexpected MRI intensity patterns arising from two orthogonal pairs of faces of a metal strip, and derive formulae for their intensity ratios, revealing differing effective elemental volumes (voxels) underneath these faces. Further, we furnish chemical shift imaging (CSI) results that discriminate different faces (surfaces) of a metal block according to their distinct nuclear magnetic resonance (NMR) chemical shifts, which holds much promise for monitoring surface chemical reactions noninvasively. Bulk metals are ubiquitous, and MRI is a premier noninvasive diagnostic tool. Combining the two, the emerging field of bulk metal MRI can be expected to grow in importance. The fundamental nature of results presented here may impact bulk metal MRI and CSI across many fields.

With the urgent need of precise positioning faced by internet of things (IoT) applications, the universality and cost of indoor positioning devices become key factors. Since the 5G network has been widely deployed, new opportunity is brought by tightly fusing the traditional low-cost sensors, i.e., the magnetometer. In this study, using 5G channel state information (CSI) and geomagnetic data, a multi-input convolutional neural network (CNN) localization system was proposed. First, to generate a data tensor that is easy for CNN processing, the raw data was reconstructed individually. Then, to comprehensively incorporate the features of 5G CSI and geomagnetic strength data, the ReLU function was chosen as the activation function of the convolutional layer. After that, a multi-input CNN was trained using the incorporated geomagnetic strength and CSI amplitude in the off-line side, and the trained CNN was recorded as a location fingerprint, which can be used for the user position prediction. Finally, in the online side and using a multi-input CNN, the 2-D coordinates are estimated and tested indoors in a typical conference room scenario. The results showed that longer sampling time of fingerprint data result in better uniqueness of the reference point, while the data collection time of locating points does not need to be long. Taking the positioning efficiency and accuracy into consideration, a sampling time of 3s at the reference point and 0.2s at the locating point are recommended. The positioning accuracy using the proposed method was 1.41 m, with an improvement of 22.9% compared with the 5G positioning, and an improvement of 18.0% compared with the 5G and geomagnetic fusing positioning using single CNN.

This study introduces a method for quantitatively assessing the complexity and predictability of fish behavior in closed systems through the application of information entropy, offering a novel lens to understand how fish adapt to environmental changes. Utilizing simulations rooted in a random walk model for fish movement, we delve into entropy fluctuations under varying environmental conditions, including responses to feeding and external stimuli. Our findings underscore the utility of information entropy in capturing the intricacies of fish behavior, particularly highlighting the synchrony in collective actions and adaptations to environmental shifts. This research not only broadens our comprehension of fish behavior but also paves the way for its application in fields like aquaculture and resource management. Through our analysis, we discovered that smaller grid sizes in simulations capture detailed local fluctuations, while larger grids elucidate general trends, pinpointing a 2.5m grid as optimal for our study. Moreover, changes in swimming speeds and behavioral adaptations during feeding were quantitatively analyzed, with results illustrating significant behavior modifications. Additionally, employing a Gaussian Mixture Model helped to clarify the nuanced changes in fish behavior in response to altered light conditions, demonstrating the layered complexity of fish responses to environmental stimuli. This investigation confirms the efficacy of information entropy as a robust metric for evaluating fish shoal behavior, offering a fresh methodology for ecological and environmental studies, with promising implications for sustainable management practices.

COVID-19 has brought unprecedented challenges and exacerbated existing work-related struggles resulting in heightened occupational stress and impacted work performance among health caregivers. This study utilised the transactional model of stress and coping to explore the coping strategies adopted by radiology health caregivers during the pandemic with the aim to provide baseline data for enhancing preparedness and development of interventions to support staff during future health crises. A qualitative, interpretative phenomenological analysis (IPA) methodology coupled with constructivist and interpretivist philosophical views were utilised in a multi-method context to conduct semi-structured interviews and focus group discussions among 24 radiology health caregivers in the eThekwini district of KwaZulu-Natal, South Africa. Data were transcribed verbatim and manually analysed using the IPA framework. The radiology health caregivers highlighted resilience, adaptability and identified emotion-focused and problem-focused coping as their mostly preferred strategies of dealing with COVID-19 related mental distress. These included accepting professional responsibilities and duties, social coping, spiritual therapy, adaptive behavioural coping, escape-avoidance and solution-oriented approaches. The findings can guide radiology departments in developing bespoke mental health interventions to support radiology health caregivers during any future health crises.

The management of erectile dysfunction (ED) shows several grey zones, especially in terms of patient satisfaction and adherence to the treatment. The main and first-line treatment for ED is drug therapy, mainly phosphodiesterase-5 inhibitors (PDE-5is) but the adherence to the therapy is not optimal due to the low patient satisfaction reported in several cases. To address this issue, different administration routes and PDE-5is pharmacological formulations have been introduced in the pharmacological market. The pharmaceutical market has recently seen the introduction of a novel sildenafil oral suspension. This device offers access to all therapeutic regimens in one device, releasing 0.5 mL of suspension containing 12.5 mg of sildenafil with each pulse. This formulation enables tailored dosing based on clinical requirements and the demands of ED patients. Here, we aim to give a brief narrative review of the management of this new oral suspension in order to provide the readers with some suggestions to use in everyday clinical practice, on the basis of the recent evidence, by using an easy and rapid-to-consult questions and answers form. Also included are the conclusions of a board meeting of experienced andrologists regarding the most recent developments in this area.

Savannas and adjacent vegetation types like gallery forests are highly valuable ecosystems contributing to several ecosystem services including carbon budgeting. Financial mechanisms such as REDD+ have provided an opportunity for developing countries to alleviate poverty through conservation of its forestry resources. For availing this opportunity carbon stock assessments are essential. Therefore, a research study at two protected areas i.e. Nazinga Game Ranch and Bontioli Nature Reserve, in Burkina Faso was conducted with the objective of assessing carbon Mg C ha-1 in aboveground biomass (AGB)dry of trees in different formations of the south-sudanian savanna in Burkina Faso, West Africa. Similarly analysis of various vegetation parameters was also conducted to understand the overall vegetation structure of these two protected areas. For estimating AGBdry, existing allometric equation for dry tropical woody vegetation types was used. The Importance Value Index (IVI) and Family Importance Value (FIV) were estimated through standard procedures. Various linear and non-linear regression analyses were conducted to test the relationships between carbon and other parameters such as DBH, height and basal area (BA). The results showed that both sites collectively contain mean carbon of 3.41 ± 4.98 Mg C ha-1. Amongst different vegetation types, gallery forests recorded the highest mean carbon of 9.38 ± 6.90 Mg C ha-1. The highest IVI of 115.56 at Nazinga Game Ranch was recorded for Anogeissus leiocarpa. Similarly, highest IVI of 98.59 was recorded for Mitragyna inermis at Bontioli Nature Reserve. The highest FIV was recorded for Combretaceae for both of the sites. To our knowledge, this was the first study conducted to assess the carbon stocks at the two protected areas in southern Burkina Faso. The study therefore was an attempt for addressing the knowledge gap particularly on carbon stocks of protected savannas. It could serve as a baseline for carbon stocks for future initiatives such as payment for environmental services and REDD+ at these areas.

Pathogenicity of many bacteria including Bacillus cereus and Staphylococcus aureus depends on pore-forming toxins (PFTs), which cause lysis of host cells by forming pores in membranes of eukaryotic cells. Bioinformatic analysis revealed in over 600 PFTs a region homologous to the Lys171-Gly250 sequence in hemolysin II (HlyII) from B. cereus, which we designated as “homologous peptide”. Three β-barrel PFTs were used for a detailed comparative analysis. Two of them –HlyII and cytotoxin K2 (CytK2), – are synthesized in Bacillus cereus sensu lato; the third – S. aureus α-toxin (Hla) – is the most investigated representative of the family. Protein modeling showed certain amino acids of homologous peptide to be located on the surface of the monomeric forms of these β-barrel PFTs. We obtained monoclonal antibodies against both a cloned homologous peptide and a 14-membered synthetic peptide DSFNTFYGNQLFMK as part of homologous peptide. The HlyII, CytK2 and Hla regions recognized by the obtained antibodies, as well as an antibody capable of suppressing the hemolytic activity of CytK2, were identified in the course of the work. Antibodies capable of recognizing PFTs of various origins can be useful tools for both identification and suppression of the cytolytic activity of PFTs.

The increase in population and the challenges caused by it are always among the concerns of decision-makers and policymakers in large countries. One of the most serious concerns is in the field of energy consumption. Optimizing energy use is one of the most effective ways to manage limited resources and energy. Energy consumption in residential houses constitutes a significant percentage of the total energy consumption worldwide; therefore, current research focusing on mathematical models aims to provide a predictive multi-objective linear mathematical model for residential house consumption. For this purpose, the consumption of water, electricity, and gas for 80 residential houses, including 10 household appliances and equipment on a weekly basis, has been considered. The results showed that the mixed-integer multi-objective predictor model is able to optimize household consumption plans compared to the actual state of household energy consumption. Since the goals of household satisfaction and energy consumption costs in the model conflict with each other, the influence coefficient was calculated to demonstrate the simultaneous achievement of these goals. The optimal value achievable with the default model for the model's purposes is 69%.

Wind energy is a kind of renewable energy with great potential for development. This study mainly investigated the application of shock waves generated by high-pressure gases (wind energy) for generating energy. In this study, we designed a new supersonic shock wave generator that can be reused without disassembling and assembling bolts and developed a supersonic shock wave monitoring system. This system monitored the velocity of the generated shock waves, which was Mach 3-5, and the output pressure was more than 100 times higher than the input pressure of the shock wave generator tank.Then, we developed a power generation system driven by supersonic shock waves based on the characteristics of the new shock wave generator, which can generate high-pressure and high-speed blast waves and can be reused. The shock wave generator can repeatedly generate high-pressure waves to drive the Tesla turbine and then the magnetic energy generator for power generation. We established a complete control process for power generation driven by shock waves by controlling the valve stem. The system can detect the tank pressure, output pressure, gas flow, rotation speed, voltage, and current during the control process for the performance analysis of power generation.

Leishmaniasis is the third most common vector-borne disease and a very important protozoan infection. Cutaneous leishmaniasis is one of the most common types of leishmaniasis infectious diseases with up to 2 million occurrences of new cases each year worldwide. A dynamic transmission multivariate time series model was applied to the data to account for overdispersion and evaluate the effects of three environmental layers as well as seasonality in the data. Furthermore, ecological niche modeling was used to investigate the geographical suitable conditions for cutaneous leishmaniasis using temperature, precipitation and altitude as environmental layers, together with the leishmaniasis presence data. A retrospective analysis of the cutaneous leishmaniasis spatial data in Afghanistan between 2003 and 2009 indicates a steady increase from 2003 to 2007, a small decrease in 2008, then another increase in 2009. An upward trend and regularly repeating patterns of highs and lows was observed related to the months of the year which suggests seasonality effect in the data. Two peaks were observed in the disease occurrence-- January to March and September to December -- which coincide with the cold period. Ecological niche modelling indicates that precipitation has the greatest contribution to the potential distribution of leishmaniasis.

Primary Ciliary Dyskinesia (PCD) is a rare genetic disorder characterized by alterations in motile cilia func-tion. The diagnosis of PCD is challenging due to the lack of standardized methods in clinical practice. High-speed video microscopy analysis (HSVA) directly evaluates ciliary beat frequency (CBF) in PCD. Recently, open-source ciliary analysis software applications have shown promise in measuring CBF accurately. How-ever, there is limited knowledge about the performance of different software applications, creating a gap in understanding their comparative effectiveness in measuring CBF in PCD. We compared two open-source software applications, CiliarMove and Cilialyzer, against the manual count method. We used videos rec-orded at high-speed of nasal ciliary brush samples from PCD patients and healthy controls. All three meth-ods showed lower median CBF values in PCD patients than healthy controls. CiliarMove and Cilialyzer identified lower CBF in PCD patients, similar to the manual count. Cilialyzer, CiliarMove and manual count demonstrated statistical significance (p-value < 0.0001) in the difference of median CBF values be-tween PCD and healthy controls. These findings support the utility of open-source software-based analysis tools. Further studies are needed to validate these findings with other genetic variants and identify the op-timal software for accurate CBF measurement in PCD.

(Background) Canine mammary tumors (CMT) have emerged as an important model for understanding pathophysiological aspects of human disease. Liquid biopsy (LB), which relies on blood-borne biomarkers and offers minimal invasiveness, holds promise for reflecting the disease status of patients. Small extracellular vesicles (SEVs) and their protein cargo have recently gained attention as potential tools for disease screening and monitoring. (Objectives) This study aimed to isolate SEVs from canine patients and analyze their proteomic profile to assess their diagnostic and prognostic potential. (Methods) Plasma samples were collected from female dogs grouped into CMT (malignant and benign), healthy controls, relapse, and remission groups. SEVs were isolated and characterized using ultracentrifugation (UC), nanoparticle tracking analysis (NTA) and transmission electron microscopy (TEM). Proteomic analysis of circulating SEVs was conducted using Liquid Chromatography–Mass Spectrometry (LC–MS). (Results) While no significant differences were observed in the concentration and size of exosomes among the studied groups, proteomic profiling revealed important variations. Mass spectrometry identified exclusive proteins that could serve as potential biomarkers for mammary cancer. These included Inter-alpha-trypsin inhibitor heavy chain (ITIH2 and ITI4), phosphopyruvate hydratase or alpha enolase (ENO1), eukaryotic translation elongation factor 2 (eEF2), actin (ACTB), transthyretin (TTR), beta-2-glycoprotein 1 (APOH) and gelsolin (GSN) found in female dogs with malignant tumors. Additionally, Vitamin D-binding protein (VDBP), also known as group-specific component (GC), was identified as a protein present during remission. (Conclusion) The results underscore the potential of proteins found in SEVs as valuable biomarkers in CMT. Despite the lack of differences in vesicle concentration and size between the groups, the analysis of protein content revealed promising markers with potential applications in CMT diagnosis and monitoring. These findings suggest a novel approach in the development of more precise and effective diagnostic tools for this challenging clinical condition.

Blood vessels are essential for maintaining tumor growth, progression, and metastasis, yet the tumor vasculature is under a constant state of remodeling. Since the tumor vasculature is an attractive therapeutic target, there is a need to predict the dynamic changes in intratumoral fluid pressure and velocity which occur across the tumor microenvironment (TME). The goal of this study is to get insight into perfusion anisotropy within lung tumors. To achieve this goal, we used the perfusion marker Hoechst 33342 and vascular endothelial marker CD31 to stain tumor sections from C57BL/6 mice harboring Lewis Lung Carcinoma tumors on their flank. Vasculature, capillary diameter, and permeability distribution were extracted at different time points along the tumor growth curve. A computational model was generated applying a unique modeling approach based on the smeared physical fields (Kojic Transport Model, KTM). KTM predicts spatial and temporal changes in intratumoral pressure and fluid velocity within the growing tumor. Anisotropic perfusion occurs within two domains - capillary and extracellular space. Anisotropy in tumor structure causes nonuniform distribution of pressure and fluid velocity. These results provide insights regarding local vascular distribution for optimal drug dosing and delivery to better predict distribution and duration of retention within the TME.

The development of new diabetes drugs continues to be explored. Loureirin B, a flavonoid, extracted from Dracaena cochinchinensis, has been confirmed to increase insulin secretion and decrease blood glucose levels. For understanding the mechanism, a series of experiments had been employed based on computational methods and cell experiments. The insulin secretion significantly increased with the incubation of 0.01μM loureirin B for 4 hours. The viability of Ins-1 cells showed no significant difference with the treatment of loureirin B. Through computational methods, we hypothesized that loureirin B could interacts with K_ATP channels to promote insulin secretion. In cell experiments, it could be found that the current of K_ATP channel of Ins-1 cells was inhibited by the effect of loureirin B. After then, the voltage-dependent calcium channels were activated, the increase of Cx43 protein expression might mediate the Ca²⁺ to the intracellular. In summary, it could be concluded that loureirin B promoted insulin secretion mainly through inhibiting K_ATP current, the influx of Ca²⁺ to the Intracellular and the expression of Cx43.

Survival models have become popular for credit risk estimation. Most current credit risk survival models use an underlying linear model. This is beneficial in terms of interpretability but is restrictive for real-life applications since it cannot discover hidden nonlinearities and interactions within the data. This study uses discrete time survival models with embedded neural networks as estimators of time to default. This provides flexibility to express nonlinearities and interactions between variables, and hence allows for models with better overall model fit. Additionally, the neural networks are used to estimate Age-Period-Cohort (APC) models so that default risk can be decomposed into time components for loan age (maturity), origination (vintage) and environment (e.g., economic, operational and social effects). These can be built as general models, or as local APC models for specific customer segments. The local APC models reveal special conditions for different customer groups. The corresponding APC identification problem is solved by a combination of regularization and fitting the decomposed environment time risk component to macroeconomic data, since the environmental risk is expected to have a strong relationship with macroeconomic conditions. Our approach is shown to be effective when tested on a large publicly available US mortgage data set. This novel framework can be adapted by practitioners in the financial industry to improve modelling, estimation and assessment of credit risk.

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.

Background and Objectives: ARNE score was developed for the prediction of difficult airway for both general and ENT surgery with a universal cut-off value. We tested the accuracy of this score in the case of laryngeal surgery and provided an insight of its combination with flexible laryngoscopy. Materials and Methods: This prospective pilot clinical study included 100 patients who were being scheduled for microscopic laryngeal surgery. We have calculated ARNE score for every patient and flexible laryngoscopy was provided preoperative. Difficult intubation was assessed according to intubation difficulty score (IDS). Results: A total of 33% patients had difficult intubation according to IDS. ARNE score showed to be accurate for prediction of difficult intubation in laryngology with P&lt;0.0001 and AUC 0.784. Flexible laryngoscopy showed to be an independent parameter with P&lt;0.0001 and AUC 0.766. We have defined a new cut-off value of 15.50 for laryngology, according to AUC curve. After the patients were divided in two groups, according to the new cut-off value and provided cut-off value, AUC improved to 0.707 from 0.619 respectively. Flexible laryngoscopy improved the prediction model of ARNE score to AUC 0.882 and of new cut-off value to AUC 0.833. Conclusions: It is recommended to use flexible laryngoscopy together with ARNE score in difficult airway prediction in patients with laryngeal pathology. Also, universally recommended cut-off value of 11 can not be effectively used in laryngology and a new cut-off value of 15.50 is recommended.

Interest grows in designing silicon-on-insulator slot waveguides to trap optical fields in subwavelength-scale slots and developing their optofluidic devices. However, it is worth noting that the inherent limitations of the waveguide structures may result in high optical losses and short optical paths, which challenge the device performance in optofluidics. Incorporating the planar silicon-based slot waveguide concept into a silica-based hollow-core fiber can provide a perfect solution to realize an efficient optofluidic waveguide. Here we propose a subwavelength-scale liquid-core hybrid fiber (LCHF), where the core is filled with carbon disulfide and surrounded by a silicon ring in a silica background. The waveguide properties and the Stimulated Raman Scattering (SRS) effect in the LCHF are investigated. The fraction of power inside the core of 56.3% allows an improved sensitivity in optical sensing; while the modal Raman gain of 23.60 m-1·W-1 is 2 times larger than that generated around a nano fiber with the interaction between the evanescent optical field and the surrounding Raman media benzene-methanol, which enables a significant low-threshold SRS effect. Besides, this in-fiber structure features compactness, robustness, flexibility, ease of implementation in both trace sample consumption and reasonable liquid filling duration, as well as compatibility with optical fiber systems. The detailed analyses of the properties and utilizations of the LCHF suggest a promising in-fiber optofluidic platform, which provides a novel insight into optofluidic devices, optical sensing, nonlinear optics, etc.

In this study, we primarily assess the relationship between social safeguards and the living standards of local communities in different ecological zones of Ghana. This research aims to assist policymakers and stakeholders to make informed and appropriate decisions when developing social safeguards for emission reductions projects. Principal component analysis was employed to develop a living condition index, after which we generated a second construct based on the number of factors affecting living conditions. The results showed that access to sharecropping, literacy, extension services, financial institutions, a mobile phone network, and markets have significant positive relationships with the living conditions of local communities in Ghana. In addition, 78% of the social safeguards described in Ghana’s REDD+ Strategy, Forest and Wildlife Policy, Benefits Sharing Mechanism, and Forest Plantation Development Strategy are aligned with the determinants of local communities’ living conditions. The findings suggest a need to enforce benefit-sharing mechanism, better forest governance, and tenancy reforms in order to prevent the overexploitation of landowners and avoid elite capture. Furthermore, farmers must be linked to financial institutions in order to obtain credits. Additionally, we must seek to provide local communities with better access to markets and mobile phone networks in a way that allows them to carry out their livelihood activities effectively and efficiently. These measures help to reduce the risk of REDD+ actions and ensure sustainability.

Monitoring the integrity of aeronautical structures is fundamental for safety. Structural Health Monitoring Systems (SHMS) perform real-time monitoring functions, but their performances must be carefully assessed. In this work the damage detection performances of a strain-based SHMS, were evaluated on a composite helicopter rotor blade root. The SHMS monitored the bonding between the central core and the surrounding antitorsional layer. A damage detection algorithm was trained through Finite Element analyses performed on the component. The effects of the loads variability and of damages were decoupled by including a load recognition step in the algorithm. Load recognition was accomplished in different ways: version#1 adopted an Artificial Neural Network (ANN) trained on blades in pristine condition; version#2 was trained also on damaged blades; version#3 adopted a calibration matrix method. Anomaly detection, damage assessment, and localization were performed by using an ANN. Results showed a higher load identification and anomaly detection accuracy for version#1 and version#2 compared to version#3. Gaussian noise reduced anomaly detection and damage assessment performances, and reduced damage localization accuracy for bigger damages. The damage detection performance were obtained for a fibre optic based-SHMS, including the trade-off between probability of detection and false alarm rate for different damage sizes.