CAMx-LPiG (Comprehensive Air Quality Model with Extensions – Linear Plume in Grid) is an online hybrid model, based on the Chemistry and Transport Model (CTM) CAMx, that includes a sub-grid scale module to simulate the dispersion of linear road traffic emissions, called LPiG. LPiG is a plume in grid module specifically developed by extending the capabilities of the Lagrangian puff sub-grid model available in CAMx. The online integration of the local scale model within the Eulerian CTM allows for a multiscale simulation of air quality from the regional scale to the urban scale, preserving a coherent description of the chemical state of the atmosphere at all spatial scales and avoiding any double counting of the emissions simulated by the sub-grid module. In this work the model is presented and evaluated against measured NO2 concentrations for the city of Milan for the month of January 2017. The model is able to introduce road traffic induced gradient in NO2 concentration at sub-grid resolution. Moreover, CAMx-LPiG is shown to reduce the bias compared to CAMx stand-alone simulations.

Polarimetry is used to determine the Stokes parameters of a laser beam. Once all four S0,1,2,3 parameters are determined, the state of polarisation is established. Upon reflection of a laser beam with the defined S polarisation state, the directly measured S parameters can be used to determine the optical properties of the surface, which modified the S-state upon reflection. Here, we demonstrate polarimetry for the determination of surface anisotropies related to birefringence and dichroism from different materials, which have a common feature of linear patterns of different alignments and scales. It is shown that polarimetry in the back-reflected light is complementary to ellipsometry and four-polarisation camera imaging.

A comparative analysis between Bidirectional Evolutionary Structural Optimization (BESO) and Smoothing-ESO (SESO), simultaneously considering Reliability-Based Topology Optimization (RBTO) and the structure's self-weight in the case of three-dimensional elasticity, is presented in this study. Due to the important role of the existence of uncertainties in making the structural design more realistic, geometry, volumetric fraction, modulus of elasticity, compliance, and loading are considered random variables with normal probability distribution. When adopting the First Order Reliability Method (FORM), the failure probability is calculated based on the reliability index. Furthermore, considering the influence of self-weight in problems involving large structures in civil engineering, especially in the case of bridges, makes the optimal configuration more reliable for design. A series of examples are covered to validate the methods presented, showing their efficiency and robustness.

The development of fetal organs can be impacted by systemic changes in the mother's circulation, and the placenta is essential for pregnancy homeostasis and feeding. In clinical obstetrics, oxytocin (OXT) is used to induce labor. To further explore the placental homeostasis of OXT, we compared OXT levels in neonatal cord blood among newborns whose mothers either received OXT prenatally or underwent natural labor. Our previous study revealed that the oxytocin receptor (OXTR), a vital component of the neural retina that forms the blood-retina barrier, is expressed in the retinal pigment epithelium (RPE). We hypothesized that. the formation of the neural retina and vessels within it may be impacted by perinatal OXT injection, which suggests that it may be used as a therapeutic intervention for developing eye illnesses such as retinopathy of prematurity (ROP). We first studied the amounts of OXT in neonatal cord blood. To investigate this subcellular activity, we administered OXT to mature RPE cells. With the aid of network analysis, our results suggest that perinatal administration of OXT may affect the growth of the neural retina and its corresponding retinal vessels, making it a potential therapeutic intervention for developmental eye diseases such as retinopathy of prematurity (ROP).

Atlas Posterior Arch Deficiency (APAD) is a rare anatomical variation of the atlas vertebra that can be detected using cone-beam computed tomography (CBCT). This study aims to evaluate the prevalence, classification, and clinical implications of APAD in an Italian cohort.

Keywords: Security robot; kalman filtering; millimeter wave; inertial navigation system.

The pervasive use of plastic for milk packaging has raised significant health concerns, despite its advantages in terms of cost-effectiveness, convenience, and durability. The potential correlation between cancer and plastic packaging is one of these concerns. This mini-review examines the health implications of plastic materials used in milk packaging, with a particular emphasis on their carcinogenic hazards. This work endeavors to summarize the current state of knowledge regarding the influence of plastic components on human health and underscore the importance of ongoing research in this field by utilizing insights from a comprehensive review article. Harmful chemicals have been observed to leach into milk from plastics used in milk packaging, including high-density polyethylene (HDPE), low-density polyethylene (LDPE), and polyethylene terephthalate (PET), particularly under conditions of protracted storage and heat. Bisphenol A (BPA), phthalates, and styrene are among the most prevalent leachates. These chemicals have been associated with a variety of health issues, such as an elevated risk of cancer, and are recognized for their endocrine-disrupting properties. BPA and phthalates, in particular, have the potential to disrupt hormone function, which may result in breast cancer, prostate cancer, and other hormone-related malignancies.This review emphasizes the significance of comprehending the precise components of plastics utilized in milk packaging and their potential health consequences. It advocates for more rigorous research to completely elucidate the long-term health impacts of these materials by emphasizing the current state of knowledge and regulatory initiatives. Additionally, it underscores the necessity of innovative packaging technologies to guarantee consumer protection and mitigate the risk of exposure to carcinogenic substances.

The nonlinear dynamics exhibited by aircraft flying at high angle of attack (AOA) pose great challenges to the design of flight control. The control design based on nonlinear dynamic inversion (NDI) is to reversely find the required control input based on the current nonlinear dynamics of the aircraft and the control objectives to be achieved. Since it is derived from the nonlinear dynamics of the aircraft, a single NDI controller can cover the entire flight envelope without the need for controller switching or gain scheduling. This paper employs the layered structure of the flight control loop to implement the NDI controller through the combination of aerodynamic control and thrust vectoring control (TVC). The resulting NDI controller is applied to an experimental F-16 installed with TVC to verify its high AOA maneuverability in the post-stall region. The verification simulation shows that the experimental F-16 under the NDI control can effectively track the high AOA command and successfully demonstrate the Herbst maneuver by performing the heading reversal with 70° AOA.

The surface thermodynamic properties of polymers and copolymers modified by supramolecular structures are very used in several industrial processes, such as selective adsorption, paints, coatings, colloids, and adhesion applications. Background: Inverse gas chromatography at infinite dilution was proved to be the best technique to determine the surface properties of solid surfaces by studying the adsorption of some model polar and non-polar organic molecules adsorbed on solid surfaces by varying the temperature. Methods: The retention volume of adsorbed solvents is a precious parameter to obtain the London dispersive and polar free energies and the London dispersive surface energy of styrene–divinylbenzene copolymer modified by supramolecular structure of melamine using the Hamieh thermal model and our new methodology consisting in the separation of the two polar and dispersive free energy of interaction. This led to the determination of the polar acid and base surface energy, and the Lewis’s acid-base constants of the various solid materials. Results: all surface energetic properties of styrene–divinylbenzene copolymer modified by melamine at different percentages were determined as a function of temperature, following our new methodology. Conclusions: It was observed that the styrene–divinylbenzene copolymer exhibited the highest London dispersive surface energy which decreased when the melamine percentage increased. All materials presented higher Lewis’s basicity and this Lewis’s basicity increased with the percentage of melamine.

The tumor necrosis factor receptor associated factor 1 (TRAF1) plays a key role in promoting lymphocyte survival, proliferation, and cytokine production. Recent evidence showed that TRAF1 plays opposing roles in monocytes and macrophages where it controls NF-B activation and limits pro-inflammatory cytokine production as well as inflammasome-dependent IL-1 secretion. Importantly, TRAF1 polymorphisms have been strongly linked to an increased risk of rheumatoid arthritis (RA). However, whether and how TRAF1 contributes to RA pathogenesis is not fully understood. Moreover, investigating the role of TRAF1 in driving RA pathogenesis is complicated by its multifaceted and opposing roles in various immune cells. In this study, we show that intraarticular injection of TRAF1 deficient macrophages into knee joints of wildtype (WT) mice subjected to the collagen antibody induced arthritis (CAIA) model of RA significantly exacerbated joint inflammation, immune cell infiltration and tissue damage compared to mice injected with WT macrophages. This study may lay the groundwork for novel therapies for RA that target TRAF1 in macrophages.

In the present work, a predictive modelling and optimization with the adaptive network based fuzzy inference system(ANFIS) modelling of mechanical properties of laser-coated NB/SiC/Ni welds was studied based on Taguchi design by laser cladding. An ANFIS model based on a Sugeno type fuzzy inference system was developed for predicting the hardness properties of SiC/BN/Ni welds by laser cladding with experimental data required for network training and prediction. Based on analysis of variance, three important factors were taken as inputs for the fuzzy logic inferences, while the hardness properties was taken as the output of the ANFIS. The microstructure of welds were analysed using scanning electron microscopy with an energy dispersive X-Ray spectrometer. Highly developed leaf-like dendrites and eutectic crystals were found in some areas of the melting zone for the BN/SiC/Ni weld, which was significantly hardened. The ANFIS model based on Taguchi's design provides a better pattern of response because the predicted and experimental values were highly similar. As a result, a satisfactory result was achieved between the predicted and experimental values of hardness in laser-coated NB/SiC/Ni welds, whereby the success and validity of the method was verified.

Being forced to live in an area following a catastrophic landslide may adversely impact people's mental well-being. Unprivileged communities such as Adivasis, Dalits, plantation workers, and people with low incomes in Kerala's hilly districts are forced to live in landslide-affected areas despite their fear. This paper examines the fears and concerns of landslide survivors from the marginalized sections of society from a broader framework of the political economy of mental health. This approach aligns with the assertion made by the World Health Organisation that individual factors do not solely determine mental health but are intricately linked to broader social, political, and economic circumstances. Data were collected through in-depth interviews with fatal landslide survivors and key informants [ ]. The study employed thematic data analysis from in-depth interviews of various fatal landslide survivors since 2018. The three major themes unveiled in the analysis are: 1. post-disaster fears, 2. The factors that triggered fear and concern and 3. Socio-economic marginality and mental health. The study asserts that individuals who are poor and unprivileged are highly susceptible to mental health issues associated with landslides.

Neurology is a quickly evolving specialty that requires clinicians to make precise and prompt diagnoses and clinical decisions based on the latest evidence-based medicine practices. In all Neurology subspecialties, Stroke and Epilepsy in particular, clinical decisions affecting patient outcomes depend on neurologists accurately assessing patient disability. Artificial intelligence (AI) can predict the expected neurological impairment from an AIS (Acute Ischemic Stroke), the possibility of ICH (IntraCranial Hemorrhage) expansion, and the clinical outcomes of comatose patients. This review article informs readers of artificial intelligence principles and methods. The article introduces the basic terminology of artificial intelligence before reviewing current and developing AI applications in neurology practice. AI holds promise as a tool to ease a neurologist’s daily workflow and supply unique diagnostic insights by analyzing data simultaneously from several sources, including neurological history and examination, blood and CSF laboratory testing, CNS electrophysiologic evaluations, and CNS imaging studies. AI-based methods are poised to complement the other tools neurologists use to make prompt and precise decisions that lead to favorable patient outcomes.

Hyperlipidemia is an identified risk factor for metabolic syndrome, obesity and cardiovascular complications characterized by elevated levels of lipids in blood. The present study aimed to inhibit HMG-CoA reductase with 15-oxoursolic acid through in-vivo and in-silico assessments. HFD-induced hyperlipidemia in rats was developed with a marked increase in total cholesterol (58.34 ± 0.21 mg/dl), triglycerides (45.45 ± 0.39 mg/dl), LDL-c (66.12 ± 0.10 mg/dl), VLDL-c (19.34 ± 0.16 mg/dl), and a decrease in HDL-c (10.34 ± 0.18 mg/dl). The oral administration of 15-oxoursolic acid at a concentration of 30 mg/Kg b.w significantly reduced the serum concentration of total cholesterol (42.65 ± 0.54 mg/dl), triglycerides (32.33 ± 0.16 mg/dl), LDL-c (50.34 ± 0.15 mg/dl) and VLDL-c (13.15 ± 0.45 mg/dl) respectively and an increased in the serum HDL-c (18.56 ± 0.34 mg/dl). 15-oxo ursolic acid also caused a decrease in the coronary risk index and atherogenic risk index. In-silico studies of 15-oxoursolic acid with HMG-CoA reductase showed significant interaction capability with binding energy (-9.26805 Kcal/mol). It is concluded that 15-oxoursolic acid could significantly reduce the total cholesterol, triglycerides and LDL levels in HFD-induced hyperlipidemia rats which might lead to new medication with significant hypolipidemic potential.

Machine learning has gained significant recognition within healthcare organizations as a potent technology for medical image analytics. Among various medical image modalities, Contrast-Enhanced CT (CECT) is widely utilized to acquire additional diagnostic information that can help to better visualize and evaluate certain structures or abnormalities in the human body. Accordingly, there is an increasing demand for machine learning systems for disease analytics using CECT. However, developing such systems presents two significant challenges: high technical complexity and high development effort. This paper presents a software platform that can effectively remedy these challenges. This platform embodies a unified software process for CECT-specific disease diagnosis including oncological diseases, cardiovascular diseases, and gastrointestinal diseases. It integrates multiple types of machine learning models into the disease diagnosis process, where the models can diagnose lesions, malignancies, tumors, medical features of tumors, temporal transitions with a contrast agent, and disease progress. The platform has been implemented in Python using Scikit-learn and TensorFlow libraries. To validate its applicability and reusability, a Hepatocellular Carcinoma (HCC) diagnosis system has been implemented.

Opioids have served as a cornerstone in pain management for decades. However, the emergence of increasingly potent synthetic analogs brings forth a range of side effects, including respiratory depression, tolerance, dependence, constipation, and, more importantly, the development of severe and debilitating opioid use disorder (OUD). Search for therapeutics to mitigate OUD has been challenging and this has called for novel approaches that include design of small molecules targeting neuronal circuits involved in addiction (opioid, dopamine, serotonin, norepinephrine, and glutamate receptors, etc.) and development of biologics that target circulating opioids/opiates. In this review, we retrieved and discussed over two dozen of relevant patents filed in the past twelve (12) years that focus on novel approaches to produce therapeutics for OUD. The current review excluded patents on biologics and concentrated on small molecules, which will be discussed separately in a subsequent sequel. The chemical entities disclosed were highlighted and specific examples were provided where necessary. Although the number of patents in the realm of drug discovery for OUD is currently limited, we foresee a continued expansion in the quest for therapeutics for OUD in the years to come.

The advent of Sixth Generation (6G) wireless technologies introduces challenges and opportunities for Mobile Ad Hoc Networks (MANETs) and Vehicular Ad Hoc Networks (VANETs), necessitating a reevaluation of traditional routing protocols. This paper introduces the Multi-Metric Scoring Dynamic Source Routing (MMS-DSR), a novel enhancement of the Dynamic Source Routing (DSR) protocol, designed to meet the demands of 6G-enabled MANETs and the dynamic environments of VANETs. MMS-DSR integrates advanced technologies and methodologies to enhance routing performance in dynamic scenarios. Key among these is the use of a CNN-LSTM based beamforming algorithm, which optimizes beamforming vectors dynamically, exploiting spatial-temporal variations characteristic of 6G channels. This enables MMS-DSR to adapt beam directions in real-time based on evolving network conditions, improving link reliability and throughput. Furthermore, MMS-DSR incorporates a multi-metric scoring mechanism that evaluates routes based on multiple QoS parameters, including latency, bandwidth, and reliability, enhanced by the capabilities of Massive MIMO and the IEEE 802.11ax standard. This ensures route selection is context-aware and adaptive to changing dynamics, making it effective in urban settings where vehicular and mobile nodes coexist. Additionally, the protocol uses machine learning techniques to predict future route performance, enabling proactive adjustments in routing decisions. The integration of dynamic beamforming and machine learning allows MMS-DSR to effectively handle the high mobility and variability of 6G networks, offering a robust solution for future wireless communications, particularly in smart cities.

The emerging and promising paradigm of the Internet of Vehicles (IoV) employ vehicle-to-everything communication for facilitating vehicles to not only communicate with one another but also with the supporting roadside infrastructure, vulnerable pedestrians, and the backbone network in a bid to primarily address a number of safety-critical vehicular applications. Nevertheless, owing to the inherent characteristics of IoV networks, in particular, of being (a) highly dynamic in nature and which results in a continual change in the network topology and (b) non-deterministic owing to the intricate nature of its entities and their interrelationships, they are susceptible to a number of malicious attacks. Such sort of attacks, if and when materializes, jeopardizes the entire IoV network, thereby putting the human lives at risk. Whilst the cryptographic-based mechanisms are capable of mitigating the external attacks, the internal attacks are extremely hard to tackle. Trust, therefore, is an indispensable tool since it facilitates in the timely identification and eradication of malicious entities responsible for launching internal attacks in an IoV network. To date, there is no dataset pertinent to trust management in the context of IoV networks and the same has proven to be a bottleneck for conducting an in-depth research in this domain. The manuscript-at-hand, accordingly, presents a first of its kind trust-based IoV dataset encompassing 96,707 interactions amongst 79 vehicles at different time instances. The dataset involves 9 salient trust parameters, i.e., packet delivery ratio, similarity, external similarity, internal similarity, familiarity, external familiarity, internal familiarity, reward / punishment, and context, which play a considerable role for ascertaining the trust of a vehicle within an IoV network.

The research investigates the factors affecting the financial performance of Micro, Small, and Medium Enterprises (MSMEs) in Indonesia and their impact on the country’s economic growth. The research methods of the studies involve data collection through surveys or interviews, followed by statistical analysis. The study found that entrepreneurial qualities such as motivation, entrepreneurial orientation, and risk behavior positively influence the financial performance of MSMEs. MSMEs that manage working capital optimally tend to increase profitability and growth, despite operational difficulties like worker shortages. MSMEs engaged in foreign trade usually achieve higher profitability. Bank loans can enhance profitability and sales, but the collateral requirement may hinder growth. The owner’s involvement doesn’t affect growth but can enhance profitability. Factors like the Human Capital Index, interest rates, the Indonesian Rupiah exchange rate, and inflation do not significantly impact MSME investment. However, business units, labor, investment, and exports of MSMEs significantly influence Indonesia’s economic growth. MSMEs play a crucial role in job creation, rural development, economic diversification, and GDP contribution in Indonesia. Despite challenges, they have the potential for sustainable growth. The research also explores strategies for overcoming challenges faced by MSMEs and investigates the role of universities in supporting the MSME sector. The University of Indonesia (UI) supports the MSME sector through strategic initiatives, including education, training, mentoring, and internship programs. The research provides valuable insights into the operation of MSMEs in Indonesia and their contribution to the economy, highlighting areas for further exploration and potential strategies for supporting the growth and sustainability of these enterprises.

A special vibration damper is proposed for material property identification through a scratching process on a vibrating object. This paper presents the design and working principle of a scratching damper based on a scratch test device. A non-contact electromagnetic shaker is used to generate the shaking force for the vibration of the tested object. The required pressure on the scratched material during the scratching process is generated by a compression spring and adjusted by changing the amount of compression of the spring. The proposed damper is designed and tested on extruded aluminum samples for the determination of its Young’s modulus and hardness and validated by using the standard test instruments. Observations of physical dimensions of the scratching tracks are determined by microscope and were utilized to compute the scratching energy factor. Load curves are obtained at different pressure of the scratching process. The hysteresis loop energy during the scratching process of the tested object is measured and used for the determination of material properties of the object. Furthermore, energy conservation law, scratch energy release rate and loop energy release rate are used to determine the Young’s modulus and hardness of the sample. The measurement accuracy of the modulus and hardness of the tested sample is evaluated. The proposed method of material testing has several advantages over the traditional methods such as low cost and high repeatability, and may be used as an alternative to the standard modulus and hardness testers.

: In the realm of data management, data preservation stands as a critical undertaking aimed at preserving and upholding the integrity of data. Regardless of whether it concerns personal or enterprise data, the detrimental effects of malicious alterations implemented by attackers cannot be overlooked. Particularly in conventional industrial control environments, the prevalent practice involves the transmission of data from sensors to databases for storage purposes. However, it is essential to recognize that this process exposes the data to various vulnerabilities. Thus, to ensure the long-term security and reliability of the data, it becomes imperative to implement robust data preservation strategies within these industrial control systems. However, the reliance of these databases on physical hard disks introduces inherent vulnerabilities, including the potential for data loss due to disk damage or targeted malicious attacks. Consequently, it becomes imperative to prioritize the implementation of robust data preservation measures. These measures are crucial in mitigating the risk of disruptions and protecting critical data from compromise. By establishing effective data backup systems, employing advanced security protocols, and implementing proactive monitoring mechanisms, organizations can bolster their data preservation capabilities and safeguard against potential threats to data integrity and availability. As a result, many enterprises opt to store their data with third-party providers to ensure data integrity. However, this approach carries inherent risks. If the third-party service experiences an attack or if the data is tampered with, it becomes challenging to verify the integrity of the data. To address these concerns and ensure data preservation within the context of the Internet of Things (IoT), a growing number of individuals are integrating IoT with Distributed Ledger Technology (DLT). By leveraging DLT, the integrity of data can be ensured, reducing reliance on centralized third-party storage and enhancing security in the IoT ecosystem. In this article, IOTA is the DLT, which employs Directed Acyclic Graph (DAG) to store transaction information. Compared to Ethereum or other blockchain technologies, IOTA offers notable advantages in terms of transaction verification speed, making it highly suitable for real-time IoT environments. However, the conventional transmission path from sensors to IOTA nodes entails a complex route, involving multiple hardware devices before reaching the intended destination. This complexity poses challenges in ensuring data integrity during transmission and introduces vulnerabilities such as man-in-the-middle attacks or SQL injection attacks. To address these issues, we propose a method to streamline the transmission path between sensors and IOTA, specifically tailored for industrial fields with numerous IoT devices. Our approach involves preprocessing the data stored on the server using our method before uploading, ensuring data confidentiality, and leveraging IOTA to guarantee data integrity. To achieve the shortest path between IoT and DLT nodes, it becomes necessary to establish IOTA nodes on lower-level devices, such as Raspberry Pi or IoT controllers. By simplifying the transmission path, we can reduce the potential for tampering and enhance overall data security. Implementing our proposed method enables the assurance of data confidentiality and integrity during both transmission and storage on the server, strengthening the trustworthiness of the IoT, and IOTA integration.

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

An analysis of the stiffness theory reveals that coal mass compression bumps occur only when both the failure criterion and the stiffness criterion are simultaneously satisfied. Then a new structural factor called uneven stiffness coal seam structure (USCS) is proposed, which consists of an uneven stiffness coal seam along with continuous roof and floor. The USCS serves the dual functions of pressure concentration and stiffness reduction. The former facilitates stress concentration from the low stiffness zone (LSZ) to the high stiffness zone (HSZ), thus raising the risk (rF) of failure. The latter reduces the stiffness of the surrounding rock of the HSZ, allowing the system to meet the stiffness criterion even with a hard roof, thereby reconciling the contradiction between the stiffness theory and engineering experience and raising the risk (rI) of instability. The HSZ of the USCS, including thinning zones, bifurcating areas, magmatic intrusion areas, and remnant pillar affected areas, is more susceptible to coal bump incidents than a conventional coal seam. Mechanical analysis and simple numerical simulations validate the pressure concentration and stiffness reduction functions of the USCS. The results demonstrate the following: 1) The normal stress of the HSZ positively correlates with ER, HR, KH, and SL, but negatively correlates with KL and SH; The stiffness of surrounding rock of the HSZ negatively correlates with HR, KH, SL, and SH, but positively correlates with ER and KL. 2) Failures within the HSZ of the USCS enables the roof strata to release bending deformation energy without undergoing fracturing. 3) The alignment between the HSZ of an existing USCS and the HSZ of an artificial USCS advancing with the working face intensifies stress concentration and reduces stiffness, thereby significantly increases the risk (rCB) of coal bump. By applying the stiffness theory and relevant USCS findings, new explanations can be provided for engineering phenomena such as the time-delayed coal bumps, the inefficient pressure relief in ultra thick coal seams, and the “microseism deficiency” observed prior to certain coal bumps.

The investigation of the correlation between Foreign Direct Investments (FDIs) and wage dynamics, particularly in the context of gender-related aspects, is of paramount importance in understanding the broader implications of economic globalization. This study aims to provide a comprehensive analysis of the intricate relationship between FDIs and wage trends, with a specific focus on the Dutch context. Using data from the United Nations Conference on Trade and Development (UNCTAD) and the World Bank, the research applies statistical techniques, including regression analysis, to explore the relationship between FDIs and wage trends over time, with a focus on gender differences. The analysis reveals that while FDIs contribute to overall wage growth, their impact varies significantly between male and female employees in the Netherlands. This highlights the need for policies addressing these gender-based disparities, providing a unique gender-focused perspective on the influence of FDIs on wage trends and expanding the existing literature on economic globalization and wage dynamics.

In this study, we developed a lightweight shoe sensor system equipped with four high-capacity, compact triaxial force sensors and an inertial measurement unit. Remarkably, this system enabled measurements of localized three-directional ground reaction forces (GRFs) at each sensor position (heel, first and fifth metatarsal heads, and toe) and estimations of stride length and toe clearance during walking. Compared to conventional optical motion analysis systems, the developed sensor system provided relatively accurate results for stride length and minimum toe clearance. To test the performance of the system, 15 older and eight young adults were instructed to walk along a straight-line while wearing the system. The results revealed that compared to the young adults, older adults exhibited lower localized GRF contributions from the heel and greater localized GRF contribution from the toe and fifth metatarsal locations. Furthermore, the older adults exhibited greater variability in their stride length and smaller toe clearance with greater variability compared to the young adults. These results underscore the effectiveness of the proposed gait analysis system in distinguishing the gait characteristics of young and older adults, potentially replacing traditional motion capture systems and force plates in gait analysis.

High-precision, ultra-thin angular detectable imaging upon a single pixel holds significant promise for light field detection and reconstruction, thereby catalyzing advancements in machine vision and interaction technology. Traditional light-direction angle sensors relying on optical components like gratings and lenses face inherent constraints from diffraction limits in achieving device miniaturization. Recently, angle sensors via coupled double nanowires have demonstrated prowess in attaining high-precision angle perception of incident light at sub-wavelength device scales, which may herald a novel design paradigm for ultra-compact angle sensors. However, the current approach to measure the three-dimensional (3D) incident light direction is unstable. In this paper, we propose a flexible segmented concentric nanorings structure capable of discerning the 3D light-direction based on its sensitivity character to both elevation (θ) and azimuth (ϕ) angles at a micrometer device scale. Through deep learning (DL) analysis and prediction, our simulations reveal that for angle scanning with a step size of 1o, the device can still achieve a detection range of 0∼360o for azimuth and 45o∼90o for elevation, with an average accuracy of 0.19o, and DL can further solve some data aliasing problems to expand the sensing range. Our design broadens the angle sensing dimension based on mutual resonance coupling among nanorings segments, and through waveguide implementation or sensor array arrangements, the detection range can be flexibly adjusted to accommodate diverse application scenarios.

Synthetic Aperture Radar has been extensively used in numerous fields and can gather a wealth of information about the area of interest. This large-scene data-intensive technology puts a high value on automatic target recognition (ATR) which can free the utilizers and boost the efficiency. Recent advances in artificial intelligence have made it possible to create a deep learning-based SAR ATR that can automatically identify target features from massive input data. In the last 6 years, intensive research has been conducted in this area, however, most papers in the current SAR ATR field used recurrent neural network (RNN) and convolutional neural network (CNN)-varied models to deepen the regime’s understanding of the SAR images. To equip SAR ATR with updated deep learning technology, this paper tries to apply a lightweight vision transformer (LViT)-based model to classify SAR images. The entire structure was verified by an open- accessed SAR data set and recognition results show that the final classification outcomes are robust and more accurate in comparison with referred traditional network structures without even using any convolutional layers.

To guide the design and optimization of King Grass (KG) harvesting machinery, this paper studied the cutting characteristics of KG stalks under different physical properties and mechanical parameters. A cutting device that can achieve different parameter adjustments was designed, and indoor cutting experiments were conducted. The results of the single factor experiment show that with the increase of moisture content and stalk height, the ultimate shear stress (USS) and unit-area cutting energy consumption (UCEC) gradually decrease. The optimal range of blade clearance for cutting KG stalks is 2.0-4.0 mm. The optimal value range for oblique cutting angle is 10 ° -40 °. The reasonable range of skew cutting angle is 10 °-20 °. The optimal range for sliding cutting angle is 20 ° - 40 °. The response surface methodology was used to conduct parameter optimization experiments. The regression models were established for various factors and the USS, as well as the UCEC. The optimal combination of cutting parameters has been determined. Under this parameter setting, the USS is 0.4 MPa and UCEC is 3.5 mJ/mm2. The average relative errors between the predicted and experimental values of USS and UCEC were 6.34% and 4.71%, respectively. This indicates that the model can correct reflect the mathematical relationship between various factors and USS and UCEC. This study provides theoretical support for the design of KG harvesting machinery.

Increasingly, information technology facilitates the storage and management of data useful for risk analysis and event prediction. Studies on data extraction related to occupational health and safety are increasingly available; however, due to its variability, the construction sector warrants special attention. This review is conducted under the research programmes of the National Institute for Occupational Accident Insurance (Inail). Objectives: The research question focuses on identifying which data mining (DM) methods, among supervised, unsupervised, and others, are most appropriate to be applied to certain investigation objectives, types, and sources of data, as defined by the authors. Methods: Scopus and ProQuest were the main sources from which we extracted studies in the field of construction, published between 2014 and 2023. The eligibility criteria applied in the selection of studies, were based on the Preferred Reporting Items for Systematic Review and meta-analysis (PRISMA). For exploratory purposes, we applied hierarchical clustering, while for in-depth analysis, we use principal component analysis (PCA) and meta-analysis. Results: The search strategy based on the PRISMA eligibility criteria, provided us with 61 out of 2,234 potential articles, 202 observation, 91 methodologies, 4 survey purposes, 3 data sources, 7 data types, and 3 resource type. Cluster analysis and PCA organized the information included in the paper dataset into two dimensions and labels: "supervised methods, institutional dataset, and predictive and classificatory purposes" (correlation 0.97÷8.18E-01; p-value 7.67E-55÷1.28E-22) and the second, Dim2 "not-supervised methods; project, simulation, literature, text data; monitoring, decision-making processes; machinery and environment" (corr. 0.84÷0.47; p-value 5.79E-25÷3.59E-06). We answered the research question regarding which method, among supervised, unsupervised, or other, is most suitable for application to data in the construction industry. Conclusions: The meta-analysis provided an overall estimate of the better effectiveness of supervised methods (Odds Ratio = 0.71, Confidence Interval 0.53÷0.96) compared to not-supervised methods.

Since the outbreak of COVID-19, mask-wearing has become a widespread phenomenon. Even after the pandemic, people continue to maintain the habit of wearing masks in their daily lives. While existing research has explored how mask-wearing can influence wearers’ behavior in everyday life, its effects in the workplace have received less attention. Drawing on self-perception theory, this study examined the positive effect of mask-wearing in the workplace on wearers’ voice behavior via psychological safety. An online experiment (N = 291) using a within-subject manipulation of wearing masks supported our hypotheses. This study uncovered the psychological and behavioral consequences of mask-wearing beyond its benefits in people’s health conditions and everyday life.

Access to urban green and blue spaces (UGBS) has been associated with positive effects on health and wellbeing; however, the past decades have seen a decline in quality and user satisfaction with UGBS. This reflects the mounting challenges that many UK cities face in providing appropriate public facilities alongside issues such as health inequalities, an ageing population, climate change, and loss of biodiversity. At present, little is known about the preferences of different population subgroups and, specifically, the UGBS they visit and the spaces they avoid. Using a public participatory geographic information system (PPGIS), the overall aim of the research presented here was to investigate the preferences of different population subgroups in urban areas, and the UGBS they visit, using Edinburgh, Scotland as a case study. We created a baseline visitor demographic profile for UGBS use, and highlighted how visitors perceive, physically access, use, and engage with UGBS. The results revealed considerable variation in UGBS preference: one person’s favourite UGBS may be one that someone else dislikes and avoids. It is clear that adapting UGBS to suit local communities should not be a ‘one-size-fits-all’ approach. The conflicting views and preferences of different groups of respondents point to the importance of developing policies and park management plans that can accommodate a variety of uses and experiential qualities within individual parks. PPGIS offers an ideal tool for achieving this

C. auris is a newly emerging yeast, raising public health concerns due to its outbreak potential, lack of protocols for decontamination and isolation of patients or contacts, increased resistance to common antifungals and associated high mortality. This research aimed to describe the challenges related to identifying the outbreak, limiting further contamination, and treating affected individuals. We retrospectively analysed all cases of C. auris detected between October 2022 and August 2023, but our investigation focused on a three-month-long outbreak in the department of cardio-vascular surgery and the related intensive care unit. Along with isolated cases in different wards, we identified 13 patients who became infected or colonized in the same area and time, even though the epidemiological link could be traced only in 10 patients, according to the epidemiological investigation. In conclusion, our study emphasizes the substantial challenge encountered in clinical practice when attempting to diagnose and limit the spread of an outbreak. Therefore, it is crucial to promptly apply contact precaution measures and appropriate environmental cleaning, from the first case detected positive.

Background/Objectives: Nail technicians frequently have musculoskeletal pain, which impairs their job performance. A high-risk profession linked to back discomfort that causes morbidity is nail technician. QEC is a tool used for observing and assessing risks in a work environment. The goal of this research is to assess the ergonomic risks, pain, and their relationship with posture among manicurists. Methods: The 35 nail technicians filled the assessment form which consists of occupational information, pain, European Community Respiratory Health Survey, Nordic Musculoskeletal Questionnaire and QEC worker part. Physicians assessed nail technicians’ workspace and QEC outcomes. Results: It was stated that they worked an average of 61.92±11.09 hours per week, served an average of 11±5 customers per day, and their condition lasted 53.96±36.51 months. There is a strong significant correlation between discomforts, time spent in occupation (p=0,000) and working hours. Manicure, pedicure, unwanted hair removal, correction of eyebrow were considered for ergonomic risk evaluation. Each occupation accompanied repeated bad postures. Most of them were scored in very high risk categorization for back static positions (more than 29 point). Conclusions: This study may be useful for nail technicians seeking ergonomic improvements in the areas of engineering, administration, behavior, or personal.

Treatment of HIV-associated lymphoma (HIV-Ly) with autologous stem cell transplantation (ASCT) has shown a surprisingly low relapse rate in several series. The aim of this study was to compare the clinical outcomes of HIV-Ly and lymphomas of the general population receiving ASCT. We compared two series of consecutive HIV-positive and HIV-negative patients, based on a 1:1 propensity score analysis, matching for age, sex, histology, disease status and prior therapies. We identified 44 patients in both groups. All HIV-positive patients received combination antiretroviral therapy (cART). With a median follow-up of 51 months, PFS was significantly higher in HIV-positive patients (4-years PFS 81% and 51%, in HIV-positive and HIV-negative patients, respectively, p=0.027). Four-year OS was 81% for HIV-positive and 67% in HIV-negative patients (p=0.15). The relapse rate was significantly higher in HIV-negative patients (36% vs 23%) (p=0.04). Our results clearly show that ASCT is an effective curative option for HIV-Ly, with better PFS and lower relapse rate compared to uninfected patients. A favourable effect of ASCT on HIV infection and immune system recovery, potential off-target effects of cART or other yet unknown factors may account for this observation.

Background: It has shown that meal timing, poor sleep quality and chronotype could play a relevant role in the development of type 2 diabetes mellitus (T2DM). However, the relationship with macronutrients by eating occasions has not been explored deeply. Objective: Our aim was to estimate the association between chrono-nutrition, sleep quality, chronotype and the prevalence of T2DM. Methods: This cross-sectional study included a subset of 3465 middle-aged adults (2068 women) from the European Prospective Investigation into Cancer and Nutrition (EPIC) Spain cohort study. In the 2017-18 follow-up, we assessed chronotype, sleep quality, diet, and sociodemographic data by validated questionnaires. Further, we used blood samples to determinate serum levels of glucose. We defined a case of T2DM when serum glucose concentration was ≥126 mg/dl or when participants self-reported diabetes. Results: Higher prevalence of T2DM was associated with poor sleep quality (ORpoorvsgood=2.90, 95%CI=1.30, 6.28). Carbohydrate intake at breakfast was inversely associated with the prevalence of T2DM (OR=0.75, 95%CI=0.66, 0.85). Finally, lipid intake at breakfast were associated with a 13% higher the prevalence of T2DM (OR=1.13, 95%CI=1.01, 1.26) for each 1 standard deviation (1-SD) increase. We observed no associations between macronutrient intake at lunch or dinner and T2DM. Conclusions: The study concludes that a breakfast with higher content in carbohydrate at breakfast is correlated with a reduced prevalence of T2DM. While higher lipids intake at breakfast was associated with higher prevalence of T2DM. Furthermore, poor sleep quality is as a potential factor associated with an elevated prevalence of T2DM. Our results emphasize the need for prospective studies to validate and strengthen these observed associations.

Chronic obstructive pulmonary disease (COPD) is a condition that significantly impacts both patients and healthcare systems. The management of COPD involves various pharmacological intervention strategies, and addressing the issue of low adherence to these strategies has become a subject of significant interest. In response to this concern, there has been a shift towards utilizing telemedicine and mobile applications. The primary objective of this scoping review is to delineate the usage of mobile applications to enhance pharmacological therapeutic adherence in adult patients with COPD. The study involved a search of databases such as Medline, Google Scholar, Cochrane, and ClinicalTrial.gov, focusing on literature published in English and Spanish over the last decade. The selected studies assessed interventions involving mobile applications (mobile apps) designed to improve pharmacological adherence. Four digital aids were identified, available on online platforms, mobile apps, or both: m-PAC, myCOPD, Wellinks mHealth, and Propeller Health. Pro-peller Health, in particular, is an app that directly measures pharmacological adherence through electronic medication monitors attached to participants' inhalers. Opening the app was associated with higher odds of using control medications compared to participants who did not open the app. The findings suggest that these digital interventions serve as valuable tools to enhance patient adherence to treatment. Future research should focus on evaluating the effectiveness of different digital devices, such as digital inhalers and mobile applications, that directly measure pharmacological adherence.

Inhalation allergies caused by cats and dogs can lead to a range of discomforting symptoms, such as rhinitis and asthma, in humans. Given the increasing popularity and care provided to these companion animals, the allergens they produce pose a growing threat to the health of susceptible patients. Allergens from cats and dogs have emerged as significant risk factors for triggering asthma and allergic rhinitis worldwide; however, there remains a lack of systematic measures aimed at assisting individuals in recognizing and preventing allergies caused by these animals. This review provides comprhensive insights into the classification of cat and dog allerges, alongwith their pathogenic mechanisms. The study also discusses implementation strategies for prevention and control measures, including physical methods, gene editing technology, immunological approaches, as well as potential strategies for enhancing allergen immunotherapy combined with immunoinformatics. Finally, it presents future prospects for the prevention and treatment of human allergies caused by cats and dogs. This review will improve knowledge regarding allergies to cats and dogs, while identifying potential targets for the development of next-generation treatments.

Background and Objective: Intimate relationships hold significant importance during emerging adulthood. This study aimed to investigate the critical determinants of perceived well-being in friendship relationships during emerging adulthood.Method: Using a quantitative approach, a sample of 726 undergraduate students from the Ferdowsi University of Mashhad were selected through convenience sampling. They completed the Interpersonal Behaviors Questionnaire (IBQ), the Compassionate and self-image goals scale (CSIGS), the Basic Need Satisfaction in Relationships Scale (BNS-RS), the Interpersonal Needs Questionnaire (INQ-10), Friendship Self-Regulation Questionnaire (SRQ-F), Interpersonal Behaviors Questionnaire-Self (IBQ-self), State Level Subjective Vitality Scale (SVS-SL), the Perceived Relationship Quality Component (PRQC), and the Basic Empathy Scale (BES). Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM).Results: The results indicated that the critical determinants in predicting perceived well-being in friendship relationships were, in order, goals in friendship relationships, friendship self-regulation, perceived support of basic psychological needs by friends, satisfied basic psychological needs, frustrated psychological needs, and supporting the basic psychological needs of friends.Conclusion: The findings demonstrate that self-determination theory (SDT) provides a coherent framework for explaining perceived well-being in friendships.

The thermodynamic phase behavior of charged polymers is a crucial property underlying their role in biology and various industrial applications. A complete understanding of the phase behaviors of such polymer solutions remains challenging due to the multi-component nature of the system and the delicate interplay among various factors, including the translational entropy of each component, excluded volume interactions, chain connectivity, electrostatic interactions, and other specific interactions. In this work, the phase behavior of partially charged, ion-containing polymers in polar solvents is studied by further developing a liquid-state (LS) theory with local short-range interactions. This work is based on the LS theory developed for fully-charged polyelectrolyte solutions. Specific interactions between charged groups of the polymer and counterions, between neutral segments of the polymer, and between charged segments of the polymer are incorporated into the LS theory by an extra Helmholtz free energy from the perturbed-chain statistical associating fluid theory (PC-SAFT). The influence of the sequence structure of the partially charged polymer is modeled by the number of connections between bonded segments. The effects of chain length, charge fraction, counterion valency, and specific short-range interactions are explored. A computational App for salt-free polymer solutions is developed and presented, which allows easy computation of the binodal curve and critical point by specifying values for the relevant model parameters.

Due to bacterial contamination, natural medicinal preservatives may be an alternative to enhance the quality of milk. Besides, thorough biocompatibility testing is deemed essential before integrating natural extracts into food products. To address this matter, our research focused on evaluating the antimicrobial potential of Plectranthus amboinicus, Flueggea leucopyrus, Cymbopogon citratus, and Bacopa monnieri against prevalent foodborne pathogens, including Staphylococcus aureus, Escherichia coli, Salmonella spp, and Pseudomonas aeruginosa and investigating the efficacy of plant extracts as natural preservatives along with biocompatibility and toxicity assessments. The methanolic extracts of plant materials were used for measuring antimicrobial activity using the agar well diffusion method, Minimum Inhibitory Concentration (MIC) and Minimum bactericidal concentration (MBC) assays. The preservative activity was tested by isolating pathogenic organisms in a sterilized milk medium and toxicity and biocompatibility was assessed using zebrafish embryo and brine shrimp lethality assays. At a concentration of 400 mg/ml, all plant extracts demonstrated notable activity against bacterial strains. B. monnieri at 400 mg/ml exhibited particularly significant effects on S. aureus (30.3 mm ± 0.6), surpassing the positive control, gentamicin (28.3 mm ± 0.6), while also displaying pronounced activity against E. coli. F. leucopyrus, at the same concentration, showed antimicrobial activity comparable to the positive control against both S. aureus (28.0 mm ± 1.0) and E. coli (27.0 mm ± 1.0). However, as there’s weak-mild toxicity in these herbs, prior to consumption, careful consideration of their toxicity and biocompatibility is imperative for ensuring their safe use.

The optimal timing for actively discontinuing immune checkpoint inhibitor therapy in long-term responders with recurrent/metastatic head and neck squamous cell carcinoma (R/M HNSCC) remains unresolved. We conducted a retrospective study of 246 patients with R/M HNSCC treated with nivolumab to determine the optimal timing to actively discontinue nivolumab therapy. We examined the point at which progression-free survival (PFS) plateaued in all cases. We compared the prognosis of 19 (7.7%) ongoing cases and 227 (92.3%) discontinued cases and analyzed treatment duration and treatment-free interval (TFI). The 6-year overall survival was 11.8% (median, 12.1), and the 6-year PFS was 15.3% (median, 3.0). The PFS curve remained stable for 3 years. The median duration of nivolumab treatment was 2.9 months (range, 0.03–81.9): Ongoing group, 41.8 (5.6–81.9); Decision group, 36.8 (4.0–70.1); Toxicity group, 30.6 (2.8–64.8); and progressive disease group, 2.0 (0.03–42.9). TFI in the Decision group was 15.1 months (0.6–61.6) and 30.6 months (2.8–64.8) in the Toxicity group. Limited number of long-term responders in R/M HNSCC cases treated with nivolumab exists. Given that PFS plateaued at 3 years, we propose that the optimal duration of treatment for this subset of patients is 3 years.

Legionella bacteria can proliferate in poorly maintained water systems, posing risks to users. All Legionella species are potentially pathogenic but Legionella pneumophila (L. pneumophila) is usually the primary focus of testing. However, Legionella anisa (L. anisa) also colonises water distribution systems, is frequently found with L. pneumophila and could be a good indicator for increased risk of nosocomial infection. Anonymized data from three commercial Legionella testing laboratories afforded analysis of 565,750 water samples. Data covered July 2019 to August 2021, including the COVID-19 pandemic. Results confirmed L. anisa commonly colonises water distribution systems, being the most frequently identified non-L. pneumophila species. Proportions of L. anisa and L. pneumophila generally remained similar but increases in L. pneumophila during COVID-19 lockdown suggests static water supplies might favour its growth. Disinfection of hospital water systems was effective but re-colonization did occur, appearing to favour L. pneumophila, although L. anisa colony numbers also increased as a proportion of the total. While L. pneumophila remains the main species of concern as a risk to human health, L. anisa’s role should not be under-estimated, either as a potential infection risk or as an indicator of the need to intervene to control Legionella colonization of water supplies.

Prostate cancer, according to the World Health Organization (WHO), ranks as the fourth most prevalent type in the population, even though it is highly frequent when detected early and promptly treated, resulting in a low mortality rate. However, in some cases, despite adherence to proper clinical protocols, there is a progression to castration-resistant prostate cancer (CRPC). In these cases, as outlined in clinical guidelines such as those developed by the National Comprehensive Cancer Network (NCCN), one approach involves the utilization of the pharmaceutical agent abiraterone to implement androgen deprivation therapy (ADT), aimed at suppressing the production of hormones directly implicated in disease progression. Another noteworthy aspect is the limited literature on clinical protocols and their efficacy concerning the Amazonian indigenous population, which often exhibits unique genomic profiles, with descriptions of variants not yet documented in the literature. Building upon these considerations, this study aims to survey the variants identified in genes associated with the abiraterone signaling pathway, their frequencies in the Amazonian indigenous population, and the correlation of these frequencies with those observed in other global populations. The objective is to contribute to the refinement of clinical practices in the treatment of prostate cancer within this population.

In recent decades, the development of surgical systems that minimize patient impact has been a major focus for surgeons and researchers, leading to the advent of robotic systems for minimally invasive surgery. These technologies offer significant patient benefits, including enhanced outcome quality and accuracy, reduced invasiveness, lower blood loss, decreased postoperative pain, diminished infection risk, and shorter hospitalization and recovery times. Surgeons benefit from the elimination of human tremor, ergonomic advantages, improved vision systems, better access to challenging anatomical areas, and magnified 3DHD visualization of the operating field. Since 2000, Intuitive Surgical has developed multiple generations of master-slave multi-arm robots, securing over 7,000 patents, which created significant barriers for competitors. This monopoly resulted in the widespread adoption of their technology, now used in over 11 million surgeries globally. With the expiration of key patents, new robotic platforms featuring innovative designs, such as modular systems, are emerging. This review examines advancements in robotic surgery within the fields of general, urological, and gynaecological surgery. The objective is to analyse the current robotic surgical platforms, their technological progress, and their impact on surgical practices. By examining these platforms, this review provides insights into their development, potential benefits, and future directions in robotic-assisted surgery.

The development of innovative materials, based on the modern technologies and processes, is the key factor to improve the energetic sustainability and reduce the environmental impact of the electrical equipment. In particular, modeling of magnetic hysteresis is crucial for the design and construction of electrical and electronic devices. In recent years, additive manufacturing techniques are playing a decisive role in the project and production of magnetic elements and circuits for applications in various engineering fields. To this aim, the use of Deep learning paradigm, integrated with the most common models of the magnetic hysteresis process, has become increasingly present in recent years. Particularly in the paper, different Neural networks used in scientific literature, integrated with various hysteretic mathematical models, including the well-known Preisach model, are compared. It is shown that this hybrid approach not only improves the modelling of hysteresis by significantly reducing computational time and efforts, but also offers new perspectives for analysis and prediction of the behavior of magnetic materials, with significant implications for the production of advanced devices.

Mitral valve disease is a common heart disease in dogs. The aim of this study was to describe the cases of dogs who underwent mitral valve repair using a v-clamp device and to provide their long-term follow-up data on cardiac function after mitral valve repair. Four dogs with mitral valve regurgitation who experienced coughing and dyspnea underwent surgical mitral valve repair between December 2023 and June 2024. The patients were evaluated by transthoracic and transesophageal echocardiography. Echocardiography revealed mitral valve leaflet regurgitation. Mitral valve repair was performed under general anesthesia using a v-clamp device introduced through an introducer wire guide. Echocardiography was conducted at baseline and the 6-month follow-up. Blood analysis results after surgical repair were normal. Follow-up echocardiography revealed no complications related to the procedure, with all dogs demonstrating improved respiratory signs and quality of life after repair. No adverse reactions were reported after surgery. A v-clamp device was used to repair mitral valve regurgitation in four dogs. Mitral valve repair using a v-clamp device is another treatment option for mitral valve disease in dogs.

This study evaluated the epidemiological and genetic susceptibility profile caused by coronavirus 2 (SARS-CoV-2) in children ≤3 years of age with acute gastroenteritis (AGE) or acute respiratory infection (ARI), living in the northwestern region of the Amazon (NWAR). Fecal and saliva sam-ples collected from 202 children (n=404) were subjected to detection of SARS-CoV-2 by RT-qPCR. Polymorphisms in the angiotensin-converting enzyme (ACE rs4646994) and ACE2 G8780A; rs2285666) genes were detected by SYBR GREEN real-time PCR and PCR/Alul digestion, respec-tively. Secretory and Lewis status of histo-blood group antigen (HBGA) was performed using phenotyping/ELISA. Frequencies for the AGE group: SARS-CoV-2; 8.9%; ARI group: SARS-CoV-2; 2.9%. The ACE I/I homozygous polymorphism gene was majority. Males with the ACE2 G8780A SNP were more susceptible to ARI symptoms than AGE (OR = 3.85; 95% CI-1.42-10.38; P 0.007). Most children were secretory FUT2 phenotype (92.6%). Surveillance of diarrhea and respiratory infections in children, along with understanding their causes, are crucial for identifying preven-tion and control strategies and for prioritizing and developing new vaccines. Clinical manifesta-tions of COVID-19 in children ≤3 years of age include AGE.

Membrane gas absorption technology and solar-assisted regeneration system are two promising approaches to reduce high energy consumption associated with carbon dioxide capture from coal fired power plants. In the present study, a solar-assisted hollow fiber membrane contactor (SOL-HFMC) power plant is proposed to capture and desorb CO₂ in hollow fiber membrane contactors with the assistance of solar thermal collectors. Techno-economic assessment and sensitivity analysis of the proposed system is carried out in three studied locations with different weather conditions for a 580 MWe pulverized coal power plant. Research results show that, the output capacity and net efficiency of the SOL-HFMC power plant are significantly higher than those of the reference power plant regardless whether TES system is applied or not. In addition, CEI of the SOL-HFMC power plant with TES system is 4.36 kg CO₂/MWh, 4.45 kg CO₂/MWh and 4.66 kg CO₂/MWh lower than that of the reference power plant. The prices of membrane, vacuum tube collector and phase change material should be reduced to achieve lower LCOE and COR values. Specifically for SOL-HFMC power plant with TES system, the corresponding vacuum tube collector price shall be lower than 25.70 $/m² for Jinan, 95.20 $/m² for Xining, and 128.70 $/m² for Lhasa, respectively. To be more competitive than solar-assisted ammonia-based post-combustion CO₂ capture power plant, the membrane price in Jinan, Xining and Lhasa shall be reduced to 0.012 $/m, 0.015 $/m and 0.016 $/m for the sake of LCOE, and 0.03 $/m, 0.033 $/m and 0.034 $/m for the sake of COR, respectively. The findings can provide guidance for decision-making and risk management strategies.

Optical communication systems pose significant challenges, including the effects of nonlinear noises. The nonlinearities, including Kerr-induced phase noise, become more problematic in m-QAM as the orden of the format increases becoming a highly densed set of data-symbols and therefore, requiring advanced signal processing for successful separation of symbols at the demodulation stage. Machine learning techniques have recently been applied to improve signal integrity in such scenarios. This paper explores the application of a spectral clustering algorithm adapted to deal with data streaming to mitigate nonlinear noise in long-haul optical channels dominated by nonlinear phase noise, offering a promising solution to a pressing issue. We demonstrate that the spectral clustering algorithm outperforms the k-means algorithm in the face of nonlinear phase noise in -90, -100, and -110 dBc/Hz scenarios at 1 MHz in a simulated 10 GHz symbol rate channel.

Background: Stroke is one of the leading causes of death and disability worldwide. The diagnosis of stroke remains largely clinical, yet widely used stroke scoring systems and brain imaging do not satisfactorily allow distinction of ischaemic stroke (IS) patients from stroke mimics (SM). Blood biomarkers are promising tools that could facilitate clinical triage. Methods: This study recruited 66 patients with IS and 24 SM. The levels of Glial fibrillary acidic protein (GFAP), Neuron-specific enolase (NSE), Neurofilament light chain (NfL) and blood-brain barrier (BBB) proteins [Occludin (OCLN), Zonula occludens 1 (ZO-1), Claudin-5] in blood serum were measured by enzyme-linked immunosorbent assay technique. Biomarker levels in IS patients and SM was compared using the Mann–Whitney U test. Multivariable logistic regression analysis was used to evaluate the diagnostic performance of biomarkers in combination with the National Institutes of Stroke Scale (NIHSS) score. Results: Significant differences in circulating GFAP, NfL, OCLN, ZO-1, and Claudin-5 but not NSE in IS patients compared to SM. The combination of circulating ZO-1, Claudin-5, and OCLN with NIHSS score gives the highest diagnostic accuracy, sensitivity, and specificity. Conclusion: A prediction model with Circulating BBB proteins in combination with NIHSS score differentiates between IS patients and SM.

Optical Wireless Communication (OWC) technology has gained significant attention in recent years due to its potential to provide high data rate wireless connections through the large license-free bandwidth available. A key challenge in OWC systems, similar to high-frequency Radio Frequency (RF) systems, is the presence of dead zones caused by obstacles like buildings, trees, and moving individuals, which can degrade signal quality or disrupt data transmission. Traditionally, relays have been used to mitigate these issues. Intelligent Reflecting Surfaces (IRS) have recently emerged as a promising solution, enhancing system performance and flexibility by providing reconfigurable communication channels. This paper presents an overview of the application of IRS in OWC systems. Specifically, we categorize IRS into two main types: mirror array-based IRS and metasurfaces-based IRS. Furthermore, we delve into modeling approaches of mirror array-based IRS in OWC and analyze recent advances in IRS control, which are classified into system power or gain optimization oriented, system link reliability optimization oriented, system data rate optimization oriented, and system security optimization oriented approaches. Finally, we discuss the key challenges and potential future directions for integrating IRS with OWC systems, providing insights for further research in this promising field.

Paediatric supraventricular tachycardia (SVT) is a common arrhythmia of great clinical significance. If not treated promptly, it can cause heart failure and cardiogenic shock. Depending on the patient’s condition SVT treatment involves vagal manoeuvres, pharmacological or direct current cardioversion. The goal of acute SVT management is to immediately convert SVT to normal sinus rhythm (NSR) and prevent its recurrence. Adenosine is recommended as first-line treatment for stable SVT by the European Resuscitation Council (ERC) and American Heart Association (AHA) guidelines when vagal manoeuvres have proven ineffective. ERC and AHA guidelines recommend the intravenous route of administration. Intraosseous (IO) administration technique is also possible, but still relatively unknown. The aim of this paper is to describe a 3.5-year old child with SVT which was converted to NSR following IO administration of adenosine. Successful conversion was achieved in the second attempt with the adenosine dose. In the described case, there was no recurrence of SVT.

Music cultural heritage, as an important component of cultural heritage, possesses significant cultural value and inheritance significance. With the development of society and the passage of time, these precious traditional music cultural heritages inevitably face the dilemma of gradual depletion or even disappearance. In the digital age, effectively protecting and inheriting these music cultural heritages has become an urgent problem to be addressed. Therefore, this paper proposes an application method based on digital twin technology, exploring how to protect and inherit music cultural heritages through digital twin technology. By leveraging digital twin technology, a virtual museum dedicated to showcasing the richness and historical connotations of music cultures is created, preserving and simulating the soundscapes of historical music eras. Through the integration of audio archives, 3D modeling, and interactive displays, users can immerse themselves in the experience of historical music in the digital space. This paper evaluates the feasibility and cultural preservation value of this digital music history museum through the creation of music digital twin technology instances and user survey feedback, and discusses the prospects of digital twins in the field of music cultural heritage.

This study aimed to conduct a cross-cultural adaptation of the development of the cat-owner/dog-owner relationship scales. The method encompassed several stages: conceptual, item, semantic, operational, measurement, and functional equivalence. Processes included translations, synthesis of translations, back-translations, consensus on the English versions, external evaluation by the original authors, expert committee evaluation, and pre-tests. The study involved surveying 342 pet owners throughout Brazil using a 20-item questionnaire. Data analyses utilized confirmatory factor analysis, covariance-based modeling, and multigroup analysis. The techniques confirmed that the scale preserved its psychometric properties and showed no variance between dog and cat owners, indicating that the measured constructs are universal and unaffected by specific cultural nuances. Hence, the cross-cultural adaptation and validation of the scale facilitate applying and testing concepts and measures in diverse contexts, enriching our understanding of the dynamics between owners and their pets (dogs and cats) in different living situations. In addition, this research holds particular significance in Brazil, given the country’s vast cultural diversity.

Biocultural heritage-based products, including regional specialty foods, are increasingly part of sustainable rural development strategies. While export-oriented biocultural products are often the most visible, we examine the role of campesino gastronomic heritage in the Central Valley of Tarija, Bolivia, as a case study of a local market-centered biocultural resource-based development strategy reflected in an alternative agri-food network. We develop a biocultural sustainability framework to examine this network from ecological, economic and sociocultural perspectives. Data are drawn from interviews (n=77), surveys (n=89) and participant observation, with primary and secondary producers of traditional and new products, as well as restaurant owners, market vendors and local consumers. We find that campesino biocultural heritage and the alternative agri-food network surrounding it represent an influential territorial project that underpins many household economies, particularly for women. We conclude that the relatively small investments by local governments to promote campesino gastronomic heritage are having positive ripple effects on small-scale producer livelihoods and on biocultural sustainability. We suggest that further support to increase market access and reduce other barriers to participation in alternative food networks will likely increase the options and benefits available to small-scale producers mobilising campesino gastronomic heritage within the local economy.

The intestinal microbiota, comprised of bacteria, archaea, and phages, inhabits the gastrointestinal tract of the organism. Male reproductive sterility is currently a prominent topic in medical research. Increasing research suggests that gut microbiota dysbiosis can result in various reproductive health problems. This article specifically investigates the impact of gut microbiota dysbiosis on male reproductive infertility development. Gut microbiota imbalances can disrupt the immune system and immune cell metabolism, affecting testicular growth and sperm production. This dysfunction can compromise the levels of hormones produced and secreted by the endocrine glands, affecting male reproductive health. Furthermore, imbalance of the gut microbiota can disrupt the gut-brain-reproductive axis, resulting in male reproductive infertility. This article will explore how the imbalance of the gut microbiota impacts male reproductive infertility through immune regulation, endocrine regulation, and interactions of the gut-brain-reproductive axis, concluding with recommendations for prevention and treatment.

For a left module RM over non-commutative ring R, the notion for the class of nilpotent elements (nilR(M)) was first introduced and studied by SSevviiri and Groenewald . Moreover, Armendariz and semicommutative modules are generalizations of reduced modules and nilR(M)=0 in the case of reduced modules. Thus, the nilpotent class plays a vital role in these modules. Motivated by this, we present the concept of nil-Armendariz modules as a generalization of reduced modules and a refinement of Armendariz modules, focusing on the class of nilpotent elements. Further, we demonstrate that the quotient module M/N is nil-Armendariz if and only if N is within the nilpotent class of RM. Additionally, we establish that the matrix module Mn(M) is nil-Armendariz over Mn(R) and explore conditions under which nilpotent classes form submodules. Finally, we prove that nil-Armendariz modules remain closed under localization.

Accurate fire severity mapping is essential for understanding the impacts of wildfires on vegetation dynamics in arid savannas. The frequent wildfires in these biomes often cause topkill, where vegetation experiences above-ground combustion, but the below-ground root structures survive, allowing for subsequent regrowth post-burn. Investigating post-fire regrowth is crucial for maintaining ecological balance, elucidating fire regimes, and enhancing the knowledge base of land managers regarding vegetation response. This study examined the relationship between bush fire severity and post-burn coppicing/regeneration events of woody vegetation in the Kalahari Desert of Botswana. Utilizing UAV-derived RGB imagery combined with a Random Forest (RF) classification algorithm, we aimed to enhance the precision of burn severity mapping at a fine spatial resolution. Our research focused on a 1 km2 plot within the Modisa Wildlife Reserve, extensively burnt by the Kgalagadi Transfrontier Fire of 2021. The UAV imagery, captured at various intervals post-burn, provided detailed orthomosaics and canopy height models, facilitating precise land cover classification and burn severity assessment. The RF model achieved an overall accuracy of 79.5% and effectively identified key burn severity indicators, including green vegetation, charred grass, and ash deposits. Our analysis revealed a >50% probability of woody vegetation regrowth in high severity burn areas six months post-burn, highlighting the resilience of these ecosystems. This study demonstrates the efficacy of low-cost UAV photogrammetry for fine scale burn severity assessment and provides valuable insights into post-fire vegetation recovery, thereby aiding land management and conservation efforts in savannas.

(1) Background: This report aims to illustrate the development, progression, diagnosis and treatment of chronically present articular surface lesions; (2) Methods: In this report, two patients are described from the point of initial presentation of symptoms to surgical consultation based on radiologic findings. These patients underwent corrective surgery in the form of mosaicplasty to repair the lesion present at the articular surface and the underlying subchondral bone. (3) Discussion: Diagnosing juvenile OCD remains challenging due to variable clinical presentation and minute radiologic discoveries. X-rays are useful, however, the gold standard remains to be arthroscopy which can be both diagnostic and therapeutic. Future prospects include the use of novel sonographic methods and the use of artificial intelligence within the given modalities. (4) Conclusions: The detailed imaging provided by MRI, combined with the insights from X-rays and potentially other modalities, allows for a nuanced understanding of the disease. This comprehensive approach ensures that treatment decisions are well-informed, optimizing outcomes for young patients with this condition.

In recent years, the research community has been interested in members of the Acinetobacter genus mainly because of their role as causative agents of nosocomial infections. However, this rich-in-species genus has been proven to play a significant role in different biotechnological processes, such as bioremediation and fermented foods production. To partially fill the lack of information on Acinetobacter’s dualistic nature, in this review, based on literature data, we attempt to summarize the available information on the different roles the members of the genus play by considering their genetic constitution and metabolic properties. We found pieces of evidence of genetic divergence between the pathogenic and non-pathogenic species and strains, which can be explained by their high adaptability to the different ecological niches. In turn, this adaptability could result from intrinsic genetic variability due to mechanisms of horizontal genetic transfer, as well as high mutability determined by the expression of error-prone DNA polymerases. Yet, further studies are needed, especially whole-genome sequencing of non-pathogenic isolates, which for the moment are relatively scarce.

Due to their remarkable intrinsic physical properties, carbon nanotubes (CNTs) can enhance mechanical properties and confer electrical and thermal conductivity to polymers currently investigated for use in advanced applications based on thermal management. An epoxy resin filled with varying concentrations of CNTs (up to 3 wt.%) was produced and experimentally characterized. The electrical percolation curve identified two critical filler concentrations: 0.5 wt%, near the electrical percolation threshold, suitable for exploring mechanical and piezoresistive properties, and 3 wt% for investigating thermo-electric properties due to the Joule effect with applied voltages ranging from 70V to 200V. Numerical models were developed using multiphysics simulation software. Once validated with experimental data, these models were used to investigate additional physical properties of the composites. Furthermore, a statistical approach based on the design of experiments (DoE) was employed to examine the influence of certain thermal parameters on the final performance of the materials. The purpose of this research is to promote the use of contemporary statistical and computational techniques alongside experimental methods to enhance understanding of materials science. New materials can be identified through these integrated approaches, or existing ones can be more thoroughly examined.

Recent advancements in communication technology have catalyzed the widespread adoption of realistic content, with augmented reality (AR) emerging as a pivotal tool for seamlessly inte-grating virtual elements into real-world environments. In construction, architecture, and urban design, the integration of mixed reality (MR) technology enables rapid interior spatial mapping, providing clients with immersive experiences to envision their desires. The rapid advancement of MR devices, or devices that integrate MR capabilities, offers users numerous opportunities for enhanced entertainment experiences. However, to support designers at a high level of expertise, it is crucial to ensure the accuracy and reliability of the data provided by these devices. This study explores the potential of utilizing spatial mapping within various methodologies for surveying architectural interiors. The objective is to identify optimized spatial mapping procedures and determine the most effective applications for their use. Experiments were conducted to evaluate the interior survey performance, using HoloLens 2, iPhone 13 Pro for spatial mapping, and photogrammetry. The findings indicate that HoloLens 2 is most well-suited for the tasks exam-ined in the scope of experiments. Nonetheless, based on the acquired parameters, the author also proposes approaches to apply the other technologies in specific real-world scenarios.

Although mask-wearing is now widespread, knowledge of how to quantify or improve its performance remains surprisingly limited and largely based on empirical evidence. The objective of this study was to visualize the expiratory airflows from facemasks and evaluate aerosol transmission between two persons. Different visualization methods were explored, including the Schlieren optical system, laser/LED-particle imaging system, thermal camera, and vapor-SarGel system. The leakage flows and escaped aerosols were quantified using a hotwire anemometer and a particle counter, respectively. The results show that mask-wearing reduces the exhaled flow velocity from 2~4 m/s (with no facemask) to around 0.1 m/s, thus decreasing droplet transmission speeds. Cloth, surgical, and KN95 masks showed varying leakage flows at the nose top, sides, and chin. The leakage rate also differed between inhalation and exhalation. The neck gaiter has low filtration efficiency and high leakage fractions, providing low protection efficiency. There was considerable deposition in the mouth-nose area, as well as the neck, chin, and jaw, which heightened the risk of self-inoculation through spontaneous face-touching. A face shield plus surgical mask greatly reduced droplets on the head, neck, and face, indicating that double face coverings can be highly effective when a single mask is insufficient. The vapor-SarGel system provided a practical approach to study interpersonal transmission under varying close contact scenarios or with different face coverings.

The oral microbiome is a diverse and complex ecosystem essential for maintaining oral and systemic health. Our study is the first to define the oral microbial community in Egyptian young adults and investigate the effects of natural antimicrobials on the oral microbiome. SuperMint (SM) is a proprietary blend of peppermint, Japanese mint, bergamot mint, and spearmint essential oils encapsulated in a tiny soft beadlet. This work aimed to evaluate the effects of SM beadlets on the oral microbiome. This study recruited twenty healthy participants. A baseline investigation of the oral microbiome of the selected participants was performed by collecting saliva and swab samples before treatment. Treatment included chewing four SM beadlets twice a day for 7 days, and then post-administration saliva and swab samples were collected at the end of treatment. The oral microbiome samples were analyzed by high-throughput amplicon sequencing of 16S rRNA gene fragments, and the community composition was determined. The results showed that the abundance of some microbial genera and families decreased after using SM, including Prevotella, Streptococcus, Neisseria, and Haemophilus. However, some genera showed inconsistent patterns. We also found that the subject's gender and SM usage were significantly associated with diverse microbial composition. The results suggest that SM treatment decreased the abundance of several bacteria associated with halitosis and periodontal diseases, such as Actinomyces and Streptococcus. Furthermore, Corynebacterium species increased while Streptococcus decreased after SM usage. More research is needed to fully understand the antimicrobial effects of mint oils and their potential applications in maintaining good oral health.

Chronic rhinosinusitis (CRS) is a complex inflammatory condition affecting the nasal and paranasal sinus mucosa. Gastroesophageal reflux disease (GERD) has been implicated as a potential exacerbating factor in CRS, but the specific endoscopic features of nasopharyngeal pathology in this context remain poorly understood. Background and Objectives: CRS is a multifactorial disease with various underlying etiologies, including inflammation, anatomical factors, and environmental triggers. While GERD has been suggested as a potential contributor to CRS, the specific endoscopic features indicative of nasopharyngeal pathology in CRS patients with GERD symptoms have not been clearly elucidated. Our aim is to identify specific endoscopic features of nasopharyngeal pathology in patients with CRS associated with GERD symptoms, and to propose a method for assessing the influence of GERD on the mucosal layer of the nose and nasopharynx. Materials and Methods: We conducted a cross-sectional observational study involving 521 adult patients presenting with symptoms suggestive of CRS. From this cohort, 95 patients with the highest scores on the Reflux Symptom Index (RSI) and Reflux Symptom Score-12 (RSS-12) questionnaires were selected as the main group. Endoscopic examinations were performed to assess the nasal and nasopharyngeal mucosa. Results: Our study revealed significant alterations in the nasopharyngeal mucosa of patients with CRS associated with GERD symptoms. Increased vascularity of the nasopharyngeal mucosa was observed in 91 patients (95.7%), while hypertrophy was noted in 83 patients (87.4%). Mucus was present in the nasopharynx of 77 patients (81.1%), exhibiting varying characteristics of color and consistency. Asymmetric hypertrophy of the oropharyngeal mucosa was noted in 62 patients (65.3%). Conclusions: We propose a method for assessing the influence of GERD on the mucosal layer of the nose and nasopharynx, which may aid in diagnostic and management decisions. Further research is warranted to explore the potential impact of GERD symptoms on the course and severity of CRS exacerbations.

Recently, the Portuguese parliament approved the decriminalisation of euthanasia for incurable illnesses. As the experiences of other countries show us, it will be a matter of time before mental disorders are addressed. Studying the phenomenon, particularly in vulnerable groups, in advance is essential for proper law drafting. Therefore, instruments which allow an objective assessment and comparison between groups must be available. This study aims to explore the validation of Faria's Attitude about Euthanasia scale in Portuguese older adult patients with mixed anxiety-depressive disorder. A sample of 114 older adult patients with mixed anxiety-depressive disorder collected by convenience in the Psychiatry Department of Senhora da Oliveira Hospital in Portugal was included. The pre-final version of the scale was tested in a small group with good results. The validity of the internal structure was analysed using exploratory factorial analysis. The internal consistency study verified reliability. For construct validity, we assessed the correlation with other validated scales measuring attitudes toward euthanasia, cognitive performance, personality and empathy. Attitude about euthanasia scale showed good internal consistency. One factor was retained in the principal component analysis. Significant correlations verified construct validity. The results support the scale's usefulness and validity. This study makes available a unique instrument to assess the overall tendency of the attitudes towards euthanasia in European-Portuguese, which can be used, for example, to compare Portuguese with Brazilian older adult psychiatric patients suffering from the same disorder. Furthermore, the adapted scale paves the way for other cross-cultural translations, adaptations, validations, and comparative analyses.

There are several well-described molecular mechanisms that influence cell growth and are relat-ed to the development of cancer. Chemokines constitute a fundamental element which are not only involved in local growth but also affect angiogenesis, tumor spread and metastatic disease. Among them, the C-X-C motif chemokine ligand 12 (CXCL12) and its specific receptor the chemo-kine C-X-C motif receptor 4 (CXCR4) have been widely studied. The overexpression in cell mem-branes of CXCR4 has been shown to be associated with the development of different kinds of his-tological malignancies, such as adenocarcinomas, epidermoid carcinomas, mesenchymal tumors or neuroendocrine neoplasms (NENs). The molecular synapsis between CXCL12 and CXCR4 leads to the interaction of G proteins and activation of different intracellular signaling pathways in both gastroenteropancreatic (GEP) and bronchopulmonary (BP) NENs conferring greater ca-pacity for locoregional aggressiveness, epithelial-mesenchymal transition (EMT) and the ap-pearance of metastases. Therefore, it has been hypothesized how to design tools that target this receptor. The aim of this review is to focus on current knowledge of the relationship between CXCR4 and NENs, with a special emphasis on diagnostic and therapeutic molecular targets.

Newborn screening (NBS) is hailed as a public health success, but little is known about long-term outcomes following a positive newborn screen. There has been difficulty gathering long-term follow-up (LTFU) data consistently, reliably, and with minimal effort. Six programs developed and tested a core set of minimal LTFU data elements. After an iterative data collection process and the development of a data collection tool, the group agreed on minimal LTFU data elements. The denominator captured all infants with an NBS diagnosis, accounting for children who moved or died prior to the follow-up year. They also agreed on three LTFU outcomes: if the child was still alive, had contact with a specialist, and received appropriate care specific to their diagnosis within the year. The six programs representing NBS public health programs, clinical providers, and research programs provided data across multiple NBS disorders. In 2022, 83.8% (563/672) of the children identified by the LTFU programs were alive and living in the jurisdiction; of those, 92.0% (518/563) saw a specialist, and 87.7% (494/563) received appropriate care. The core LTFU data elements can be applied as a foundation to address the impact of early diagnosis by NBS within and across jurisdictions.

Acute myeloid leukemia (AML) is a malignant disease of the blood and bone marrow that is characterized by uncontrolled clonal proliferation of abnormal myeloid progenitor cells. Nucleophosmin 1 (NPM1) gene mutations are the most common genetic abnormality in AML, detectable in blast cells from about one third of adults with AML. AML NPM1mut is recognized as a separate entity in the World Health Organization (WHO) classification of AML. Clinical and survival data suggest that patients with this form of AML often have a more favorable prognosis, which may be due to the immunogenicity created by the mutations in the NPM1 protein. Consequently, AML with NPM1mut can be considered an immunogenic subtype of AML. However, the underlying mechanisms of this immunogenicity and associated favorable survival outcomes need to be further investigated. Immune checkpoint molecules, such as the programmed cell death-1 (PD-1) protein and its ligand, PD-L1, play important roles in leukemogenesis through their maintenance of an immunosuppressive tumor microenvironment. Preclinical trials have shown that the use of PD-1/PD-L1 (PDx) checkpoint inhibitors in solid tumors and lymphoma work best in novel therapy combinations. Patients with NPM1mut AML may be better suited to immunogenic strategies that are based on the inhibition of the immune checkpoint pathway of PDx than patients without this mutation, suggesting the genetic landscape of patients may also inform best practice for the use of PDx inhibitors.

Endometrial cancer (EC) poses a significant global health challenge, with increasing prevalence in 26 of 43 countries and over 13,000 deaths projected in the United States by 2024. This rise correlates with aging populations, the obesity epidemic, and changing reproductive patterns, including delayed childbearing. Despite the early diagnosis in 67% of cases, approximately 30% of cases present with regional or distant spread, leading to nearly 20% mortality rates. Unlike many cancers, EC mortality rates are escalating, outpacing therapeutic advancements until recently. One of the reasons for this was the lack of effective therapeutic options for advanced disease until recently. The introduction of immunotherapy has marked a turning point in EC treatment, particularly benefiting patients with defects in mismatch repair proteins (dMMRs). However, dMMR status alone does not ensure a favorable response, underscoring the need for precise patient selection. This review explores the pivotal role of mismatch repair proteins in EC, emphasizing their heterogeneity, the challenges in their assessment, and their potential as predictive biomarkers.

Fission-track modelling rests on etching, counting and measuring the lattice damage trails from uranium fission. The tools for interpreting fission-track data are advanced but the results are never better than the data. Confined-track samples must be an adequate size for statistical analysis, representative of the track population, consistent with the model assumptions and with the calibration data. Geometrical and measurement biases are understood and can be dealt with up to a point. The interrelated issues of etching protocol and track selection are however more difficult to untangle. Our investigation favours a two-step protocol. The duration of the first step is inversely proportional to the apatite etch rate, so that different apatites etch to the same Dpar. A long immersion reveals many more confined tracks, terminated by basal and prism faces. This allows consistent length measurements and permits to orient each track relative to the c-axis. Long immersion times combined with deep ion irradiation reveal confined tracks deep inside the grains. Provided it is long enough, the precise immersion time is not important if the effective etch times of the selected tracks are calculated from their measured widths. Then, whether the sample is mono- or multi-compositional, we can, post hoc, select tracks with the desired properties. The second part of the protocol has to do with the fact that fossil tracks in geological samples appear to be under-etched compared to induced tracks etched under the same conditions. This should be assumed if the semi-axes (l_C, l_A) of a fitted ellipse plot above the induced-track line. In that case an additional etch can increase the track lengths to a point where they are consistent with the model based on lab-annealing of induced tracks, a condition for valid thermal histories. Here too, it is possible to select a subset with effective etch times consistent with the model if the widths of confined tracks are measured along with their lengths and orientations.

Energy consumption is a critical issue in the energy sector, and recent events such as the global energy crisis, costs, the need to reduce greenhouse emissions, and extreme weather conditions have increased the demand for energy efficiency. Accurately predicting energy consumption is one of the key steps to addressing inefficiency in energy consumption, and its optimization. In this regard, accurate predictions of energy consumption would not only help to minimize wastage, but also to save cost. In this article, we propose intelligent models using an ensemble of Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) neural networks for predicting energy consumption in smart buildings. The proposed model outperforms other state-of-the-art deep learning models for predicting minute energy consumption, with a mean square error of 0.109. The proposed model also accurately captures latent trends in the data that other models struggle to capture. The results highlight the potential of using hybrid deep learning models for improved energy efficiency management in smart buildings.

Microbial composition across substrates in mangroves, particularly in the Middle East, remains unclear. This study characterized bacterial communities in sediment, water, Terebralia palustris snail guts, and plastic associated with Avicennia marina mangrove forests in two coastal lagoons in the Sea of Oman using 16S rDNA gene MiSeq sequencing. The genus Vibrio dominated all substrates except water, which featured unique genera Sunxiuqinia and Pseudomonas. There were significant differences in bacterial communities on different substrata, in particular plastic. Snail guts harbored the highest number of unique Operational Taxonomic Units (OTUs) in both lagoons. Plastic in the polluted Sawadi lagoon with low salinity harbored distinct genera like Vibrio, Aestuariibacter, Zunongwangia, and Jeotgalibacillus absent in Qurum lagoon with higher salinity and low pollution. Sawadi lagoon exhibited higher species diversity in sediment and plastic substrates, Qurum lagoon demonstrated lower overall species diversity. The PCA indicates that environmental factors like salinity, pH, and nutrient levels significantly influence bacterial community composition across substrates. Variations in organic matter and potential anthropogenic influences, particularly from plastics, further shape bacterial communities. This study highlights the complex microbial communities in mangrove ecosystems, emphasizing the importance of considering multiple substrates in mangrove microbial ecology studies.

Abstract — Game development using technology was started in 1950 around the first video game created Tennis for Two by Higginbotham as a fun diversion, to show the power of technology. The advanced development of Artificial intelligence (AI), has turned out to be the heart of game development technology and AI has revolutionized gaming and brought so many features to life.in reality, it isn't easy to give a definition and meaning to it even though games are becoming a part of human survival. It is difficult to define the real meaning of a game but it is part of human survival as it usually refers to the cleverness of the way the human being involvement in the characters of the game. As a part of game development, many technologies were used to create a game for the players with creativity, complex design, variety of levels, and aspects for the player to use choices effectively and efficiently to interact with the character in the game and enhance the experience to the next levels. This paper initially gives the importance of game development and need for the technology usage to enhance the current state of games. Then analyzes the history and present state of Artificial intelligence in game development. Finally, it explains the highlights of potential changes in game development and the impact and influence of artificial intelligence and machine learning models in the future development of games.

Forest resources are renewable,rational exploitation and utilization of forest resources are not only conducive to sustainable development of population, but also can obtain higher economic benefits. Based on actual timber harvesting problems,a combined harvesting model of timber and non-timber with nonlinear harvesting term was established.Firstly, using the qualitative theory of ordinary differential equations, the dynamic behavior of the model is studied, and the existence and stability of the equilibrium point of the model are proved .Secondly, the optimal control solution is obtained by using the optimal control theory.Finally, the optimal harvesting strategy of timber and non-timber products is given based on the numerical simulation results, which provides a certain theoretical basis for the sustainable development of forestry ecological economy.

Background: The commonly known assumption that combinations of several herbs in one formulation can have better efficacy due to additive or synergistic effects has not been systematically studied despite some evidence supporting the synergy concept. Study aim: The study aimed to reveal the molecular interactions in situ of host cells in response to the intervention of BHP and justify the benefits of implementing BHP in clinical practice. Results: This overview provides the results of recent clinical and network pharmacology studies of botanical herbal preparations (BHP) of Rhodiola with other plants, including Ashwagandha, Green Tea, Eleutherococcus, Schisandra, Eleutherococcus, Leuzea, Caffeine, Cordyceps, Gingko, Black Cohosh, saffron, and L-carnosine. Conclusions: The most important finding from network pharmacology studies of BHP was the evidence supporting the synergistic interaction of BHP ingredients, revealing unexpected new pharmacological activities unique and specific to the new BHP. Some studies show the superior efficacy of BHP compared with mono-drugs. At the same time, some a priori-designed combinations can fail, presumably due to antagonistic interactions and crosstalk between molecular targets within molecular networks involved in the cellular and overall response of organisms on the intervention. Network pharmacology studies help predict the results of studies to discover new indications and unpredicted adverse events.

Abstract. Graphene family (GF)-Calcium phosphate (CaP) composites, holds great potential as components of bone regeneration materials. GF nanomaterials can be modified physically as well as chemically, which are to be biomimetic, mechanically to be hard due to their capability to support exceptional mechanical, thermal and electronic properties. These biocompatible GF composites coated on the calcium phosphate can enhance and tolerate stem cell growth and differentiation, proliferation into various lineages or interact with bioorganisms. The development in CF-CaP materials and their physicochemical/biointeractions and strategies towards osteoblasts is a great concern to promote faster healing and reconstructions of large bone imperfections or defects. In this review, we explain the influence of the CF-CaP and summarize recent developments on designing CF-CaP architectures as multifunctional bone regeneration platforms. We have also explored the typical biological applications concerning these CF-CaP based bioactive nanocomposites. Furthermore, the future viewpoints and evolving challenges will also be emphasized. Due to the shortage of full-length reviews in this emerging research field, this review would be caught great attention and encourage various new chances across a wider range of disciplines.

In recent decade water pollution by micropollutants is an increasing environmental concern. Since 2019, due to COVID-19 pandemic, increased stormwater pollution by chlorine based disinfectants has been determined. Research aimed to treat of chlorine contaminated stormwater after outdoors spaces disinfection are very limited. Runoff from disinfected areas and residual chlorine present in stormwater are transported to surface water bodies. Residual chlorine reacts with dissolved organic compounds in water and results the formation of environmentally toxic disinfection by-products. Studies present event low residual chlorine concentrations may pose a risk to aquatic flora and fauna. In this study the efficiency of different filter materials, including peat, wood chips, sawdust (column tests) and ceramzites Leca, Pollytag, Polski, Ceski (batch tests), in retaining residual chlorine were tested in laboratory scale batch and flow through experiment. The best efficiency to retain chlorine presented sawdust (96 %) and ceramzite Leca (76 %). The plants abilities to reduce pollution by chlorine was analyzed in raised garden bed. Research results will contribute to future studies aimed to retain various micropollutants in stormwater using remediation technologies.

Childhood emotional abuse (CEA) has been linked to a range of unfavorable outcomes, including the development of unhealthy personality traits and maladaptive coping mechanisms and behaviors. In this study, our objective was to investigate whether neuroticism and perfectionism act as mediators in the relationship between CEA and workaholism, while also evaluating the gender invariance of the hypothesized model. A cohort of 1176 young workers, with a balanced gender representation (50% female), aged 18-25, participated in the study by completing self-report questionnaires. The results revealed significant connections between all direct and indirect links, indicating a complex interplay between childhood emotional abuse, neuroticism, perfectionism, and workaholism. Importantly, the mediation model exhibited no significant differences between genders, suggesting that the identified relationships are consistent across both male and female participants. This research underscores the critical importance of early identification of childhood emotional abuse and advocates for the implementation of trauma-informed care to address the negative consequences of emotional abuse, ultimately aiming to prevent the development of workaholism. Furthermore, the findings emphasize the necessity for tailored prevention strategies, focusing on mitigating neuroticism and perfectionism as potential pathways for effective therapeutic interventions.

Land use and cover change (LUCC) is an important method to investigate the causes of global environment change. We utilized the emergy ecological footprint (EEF) model to construct a land-use change model to be used as a systematic measuring tool for monitoring sustainable development trends. In particular, we estimated the eco-security of the Cing-jing region as a case study so that responsible agencies can use it to maintain a balance between ecological preservation and tourism development. The results indicated the following: First, the ecological environment of the Cing-jing region satisfied the safety standard in 2008–2014; however, the related indices increased considerably. Second, the grey model predicted a decrease in 2015–2024 ecological carrying capacities of Cing-jing and a large increase in capita EFs, resulting in a larger ecological deficit and higher EFI. The eco-security from 2015–2024 was higher compared to 7 years ago and is predicted to reach the Grade 2 intermediate level in 2022; thus the Cing-jing region is gradually becoming ecologically unsustainable. Strengths of our study included the use of EEF theory in a quantitative analysis of slope lands for the effective evaluation of ecological security. Finally, we expanded our research to include ecological security issues.

A complete understanding of groundwater dynamics and its interaction with surface water underthe impact of agricultural activities is vital for local agriculture, ecology, and residents of dry regions, which is not commonly recognized in arid areas. This research outlines the geochemical characteristics, recharge sources, and potential factors impacting groundwater quality in a new land reclamation located in the small basin of Abu Mina, which is part of the Western Nile Delta region.1 Thirty‑one groundwater samples and two surface water samples were collected in 2021 to represent the Pleistocene aquifer and were subjected to multivariate statistical, hydrochemical, and stable isotope analyses. Data analysis demonstrates that Na+ > Ca2+ > Mg2+ > K+ and SO4 2– > Cl– > HCO3 – > NO3 – are the predominant cations and anions, respectively. Groundwater salinity ranged from 465.60 to 6455.18 mg/l, with slightly alkaline. Most of the water samples fall into one of three types of facies: Ca–Cl, Na–Cl, and Mixed Ca–Mg–Cl, in decreasing order. The meteoric genesis index (r2) indicates that deep meteoric water percolation dominates the Pleistocene aquifer. The aquiline diagrams, correlation matrix, and different ionic ratios indicate that evaporation, reverse ion exchange reactions, and the dissolution of carbonate and silicate minerals are the main processes governing groundwater chemistry. Factor analysis (FA) indicated that three factors explain groundwater hydrochemistry, accounting for 71.98% of the total variance. According to the rotating components matrix (F1–F3), the chemistry of the Quaternary aquifer is principally affected by evaporation, ion exchange reactions, and anthropogenic influences. Additionally, salinity increases due to the return flow of irrigation activities and mixing between old and recent water. The stable isotopes (δ18O and δ2H) indicate that the Quaternary aquifer receives groundwater recharge through the return flow of excess irrigation and canal seepage. Under desert reclamation conditions, groundwater salinization processes should be given special consideration. All groundwater samples are appropriate for agricultural irrigation based on the Sodium Adsorption Ratio (SAR), Permeability Index (PI), Percent Sodium (%Na), and Residual Sodium Carbonate (RSC).

Accurate forecasting and efficient management of commodities are crucial for stakeholders in the industry, given the volatile nature of these markets. This study addresses these needs by leveraging advanced forecasting techniques and machine learning models to predict prices and enhance supply chain efficiency. TThe focus is on utilizing ARIMA, SARIMAX, and LSTM models to analyze historical trading data for commodities such as cocoa, coffee, and sugar sourced from Kaggle’s comprehensive dataset. The research applies ARIMA and SARIMAX models to forecast price trends, overcoming initial challenges related to data index frequency and seasonality. LSTM models are employed for more nuanced demand forecasting, particularly for random-length lumber, demonstrating the model's capability to predict future market trends accurately. The study highlights significant improvements in prediction accuracy and supply chain management through meticulous feature engineering and model optimization, offering valuable insights for strategic decision-making in the supply chain sector.

By using the method of high-temperature solid-phase reaction, the new piezoceramic SrBi2Nb2-2xWxSnxO9 was obtained, in which partial substitution of niobium (Nb) atoms with Sn4+ and W6+ atoms in the compound SrBi2Nb2O9 took place in the octahedra of the perovskite layer (B-position). X-ray diffraction studies have shown that these compounds are single-phase SrBi2Nb2-2xWxSnxO9 (x = 0.1, 0.2) and two-phase SrBi2Nb2-2xWxSnxO9 (x = 0.3, 0.4), but they all had the structure of Aurivillius – Smolensky phases (ASPs) with similar parameters of orthorhombic elementary cells, corresponding to the spatial group A21am. The dependences on temperature of the relative permittivity ε/ε0 and the tangent of the loss angle tan d at different frequencies were measured.

Traumatic brain injury (TBI) is an important global clinical issue, requiring not only prevention but also effective treatment. Following TBI, diverse parallel and intertwined pathological mechanisms affecting biochemical, neurochemical, and inflammatory pathways can have severe impact on the patient’s quality of life. The current review summarizes evidence for utility of amantadine in TBI in connection to its mechanism of action. Amantadine combining multiple mechanisms of action may offer both neuroprotective and neuroactivating effects in TBI patients. Indeed, use of amantadine in TBI has been encouraged by several clinical practice guidelines/recommendations. Amantadine is also available as infusion which may be of particular benefit in unconscious patients with TBI, due to immediate delivery to the central nervous system and the possibility of precise dosing. In other situations, orally administered amantadine may be used. There are several questions that remain to be addressed: Can amantadine be effective in disorders of consciousness requiring long-term treatment and in combination with drugs approved for treatment of TBI? Do the observed beneficial effects of amantadine extend to disorders of consciousness due to factors other than TBI? Well controlled clinical studies are warranted to ultimately confirm its utility in the TBI and provide answers these questions.

The research that we are referring to examines the morphological, structural, and optical characteristics of kesterite (Cu1-xAgx)2ZnSnS4 (CAZTS) thin films, which are produced using a process known as thermal evaporation (TE). The study's main goal was to determine how different Ag contents affect the characteristics of CAZTS systems. X-ray diffraction (XRD) and Raman Spectroscopy: were used to confirm the crystal structure of the CAZTS thin films. Using a mathematical model of spectroscopic ellipsometry, the refractive index (n) represented the part of the complex refractive index, the extinction coefficient (k) portrayed the imaginary one, and also the energy band gap of the fabricated films were all calculated. The energy band gap of the thin films was also calculated. This is a crucial parameter for solar cell applications, as it determines the wavelength of light that the material can absorb. The energy band gap was found to decrease from 1.74 eV to 1.55 eV with increasing Ag content. The ITO/n-CdS/p-CAZTS/Mo heterojunction was well constructed, and the primary photovoltaic characteristics of the n-CdS/p-CAZTS junctions were examined for use in solar cells. Different Ag contents of the CAZTS layers were used to determine the dark and illumination (current-voltage) characteristics of the heterojunctions. The study's findings collectively point to CAZTS thin layers as potential absorber materials for solar cell applications.

The study examines projected changes in dry- and wet-spell probabilities in West Africa using a Markov chain approach. Four simulations of regional climate models from the CORDEX-Africa program were used to analyze projected changes in intraseasonal variability. The results show an increase in the probability of having a dry day, a dry day preceding a wet day and a dry day preceding a dry day, and a decrease in the probability of wet days in the Sahel region under anthropogenic forcing scenarios RCP4.5 and RCP8.5. The decrease in wet days is stronger in the far future and under the RCP8.5 scenario (up to -30%). The study also finds that the probability of consecutive dry days (lasting at least 7 days and 10 days) is expected to increase in the Western Sahel, the Central Sahel, and the Sudanian Area under both scenarios, with stronger increases in the RCP8.5 scenario. In contrast, the decrease is expected over the Guinea Coast, with the changes more important under the RCP4.5. These changes in dry- and wet-spell probabilities are important for water management decisions and risk reduction in the energy and agricultural sectors. The study also highlights the need for decision-makers to implement mitigation and adaptation policies to minimize the adverse effects of climate change.

Digital twin technology is revolutionizing traditional manufacturing paradigms. In modern manufacturing systems, digital twin technology is fraught with challenges due to the scarcity of labeled data. Specifically, existing supervised machine learning algorithms, with their reliance on voluminous training data, find their applicability constrained in real-world production settings. This paper introduces an unsupervised 3D reconstruction approach tailored for industrial applications, aimed at bridging the data void in creating digital twin models. Our proposed model, by ingesting high-resolution 2D images, autonomously reconstructs precise 3D digital twin models without the need for manual annotations or prior knowledge. Through comparisons with multiple baseline models, we demonstrate the superiority of our method in terms of accuracy, speed, and generalization capabilities. This research not only offers an efficient approach to industrial 3D reconstruction but also paves the way for the widespread adoption of digital twin technology in manufacturing.

This paper focuses on environmental policies for mitigating the impacts of climate change on the Taj Mahal, an iconic structure built on the banks of the Yamuna River from 1632 to 1653 with a blend of Persian and Indian architectural styles. The Taj Mahal is threatened by damage caused by climate change, including air pollution resulting in acid rain and floods that lead to erosion and discoloration of the main marble material of the Taj Mahal. This study employs a Systematic Literature Review (SLR) of peer-reviewed journal articles with a primary focus on environmental policy, the impacts of climate change, and the preventive measures undertaken by the Indian government. Based on the analysis of 270 papers, it is concluded that out of the total, 30 papers specifically address objectives relevant to this research. The study period spans from 2014 to 2024. The research findings reveal that air pollution has a significantly adverse impact on the Taj Mahal. Furthermore, nine policies are generally identified from the journal literature review aimed at preserving and protecting the Taj Mahal from the negative effects caused by air pollution.

Abstract: Lung cancer, characterized by its heterogeneity, presents a significant challenge in ther-apeutic management, primarily due to the development of resistance to conventional drugs. This resistance is often compounded by the tumour’s ability to reprogram its metabolic pathways, a survival strategy that enables cancer cells to thrive in adverse conditions. This review article ex-plores the complex link between drug resistance and metabolic reprogramming in lung cancer, offering a detailed analysis of the molecular mechanisms and treatment strategies. It emphasizes the interplay between drug resistance and changes in metabolic pathways, crucial for developing effective lung cancer therapies. The review examines the impact of current treatments on metabolic pathways and the significance of considering metabolic factors to combat drug resistance. It highlights the different challenges and metabolic alterations in non-small cell lung cancer and small cell lung cancer, underlining the need for subtype-specific treatments. Key signalling pathways, including PI3K/AKT/mTOR, MAPK, and AMPK, have been discussed for their roles in promoting drug resistance and metabolic changes, alongside the complex regulatory networks involved. The article evaluates emerging treatments targeting metabolism, such as metabolic inhibitors, dietary management, and combination therapies, assessing their potential and challenges. It concludes with insights into the role of precision medicine and metabolic biomarkers in crafting personalized lung cancer treatments, advocating for metabolic targeting as a promising approach to enhance treatment efficacy and overcome drug resistance. The review underscores ongoing advancements and hurdles in integrating metabolic considerations into lung cancer therapy strategies.

Educational institutions must identify students who are academically struggling to provide them with necessary support to improve their performance. In this context, recommendation systems powered by deep learning techniques are vital for detecting and categorizing such students. These systems help students plan their future by uncovering patterns in their historical academic data. This study introduces a new deep learning model designed to classify academically underperforming students in educational settings. The model incorporates a Gated Recurrent Neural Network (GRU) and includes specific neural network features like a dense layer, max-pooling layer, and the ADAM optimization algorithm. The model's training and evaluation were conducted using a dataset comprising 15,165 student assessment records from various academic institutions. The performance of the developed GRU model was benchmarked against other educational recommendation systems, including Recurrent Neural Network models, AdaBoost, and the Artificial Immune Recognition System v2. The proposed GRU model demonstrated remarkable accuracy, achieving an overall rate of 99.70%.

Anthropogenic development can strongly influence natural river processes, leading to environmental changes that negatively affect important habitats and biodiversity, and consequently reduce economically important natural resources. This study investigated the effects of salinity intrusion on the habitat of the clam Corbicula japonica in the Seomjin River estuarine zone. We employed the Environmental Fluid Dynamics Code (EFDC) model, which incorporates topographic data and hydrological changes, to simulate salinity concentrations. Two salinity measurement facilities were installed in Seomjin River estuarine and operated to optimize the EFDC model. The results show that reduced flow rates due to intake have a negligible impact on the increased salinity. Maintaining optimal salinity (15–20 psu) during neap tides at the Seomjin River Bridge requires constant high flow rates, which poses significant challenges. Saltwater stratification is identified as the primary cause of pronounced salinity stratification, particularly during neap tides. Addressing this issue through river discharge and intake facility operation is challenging. Structural measures, including riverbed restoration and underwater barriers, are recommended to improve resistance to seawater intrusion. Future research should aim to develop scenarios to reduce salinity concentrations, quantify the reduction efficiency, and propose region-specific measures.

Once considered relatively benign, superficial vein thrombosis (SVT) of the lower limbs is often linked to deep vein thrombosis (DVT) or pulmonary embolism (PE). Treatment goals include alleviating local symptoms and preventing SVT from recurring or extending into DVT or PE. Fondaparinux 2.5 mg once daily for 45 days is the treatment of choice for most patients with SVT. Potential alternatives include intermediate-dose low-molecular-weight heparin or the direct oral factor Xa inhibitor rivaroxaban. Despite these treatment options, significant gaps remain, including the role of systemic or topical anti-inflammatory agents alone or combined with anticoagulants, and the optimal duration of anticoagulation for patients at varying risk levels. Additionally, the efficacy and safety of factor Xa inhibitors other than rivaroxaban, management of upper extremity SVT, and optimal treatment for SVT near the sapheno-femoral or sapheno-popliteal junctions are not well understood. This narrative review aims to summarize current evidence on anticoagulant treatment for SVT, highlight key unmet needs in current approaches, and discuss how ongoing studies may address these gaps.

Dairy products are an important source of protein and other nutrients in the Mediterranean diet. In these countries the most common source of milk for producing dairies are cow, goat, sheep and buffalo. Andalusia is traditionally the largest producer of goat milk in Spain. Kefir is a fermented product made from bacteria and yeasts which has health benefits beyond its nutritional properties. There is a lack of knowledge about the molecular mechanisms and metabolites that bring about these benefits. In this work, the combination of analytical techniques (GC-FID, UHPLC-MS-QToF, GC-QqQ-MS, and GC-ToF-MS) resulted in the detection of 105 metabolites in kefir produced with goat milk from two different thermal treatments (raw and pasteurized) fermented at four times (12, 24, 36, and 48 h, using 0 h as control). Of these, 27 metabolites differed between kefir produced with raw and pasteurized milk. These changes could be possibly caused by the effect of pasteurization on the microbial population in the starting milk. Some interesting molecules were identified, as shikimic acid, dehydroabietic acid, GABA and tyramine that could be related to antibacterial properties, enhance of immune system and arterial pressure. Moreover, a viability assay of the NIRS technique was performed to evaluate its use on monitoring the fermentation and classification of samples, which had resulted in a 90 % of correct classified samples according to their fermentation time. This study represents the most comprehensive metabolomic analysis of goat milk kefir so far, revealing the intricate changes in metabolites during fermentation and the impact of milk treatment.

A new type of artificial block is proposed by modifying the traditional block. Based on the physical model experiment, the wave reflection and run-up characteristics of the new ecological blocks under regular waves were examined, and the influence of the height of the "planting trough" border on the hydrodynamic properties was analyzed. The results indicate that the wave reflection and run-up would decrease with a decrease in the breakwater slope. As wave height increases, wave run-up increases, and the reflection coefficient falls. Wave reflection and run-up increase with an increasing wave period. The relative depth of the water has a smaller impact on the wave reflection than the wave run-up. The reflection coefficient of the new ecological blocks is consistently lower than that of the conventional and continues to decrease as the border of the "planting trough" is raised. The raised borders prevent water loss in the trough, resulting in no significant improvement in the wave run-up performance of the new blocks. The reflection coefficient and the relative run-up R/H gradually increase with the average wave breaking parameter ξ increase. The crude permeability coefficients for the new blocks, New Heights 1 and New Heights 2, are 0.53, 0.53, and 0.54, respectively.

Laser range-gated underwater imaging technology, by removing most of the back scattering noise, can effectively increase the image contrast and extend the detection range. The optical signal captured by a range-gated imaging system primarily comprises reflected light from the object and backscattered light from the surrounding water. Consequently, surfaces with low reflectivity or highly turbid water environments substantially constrain the applicability of the range-gated imaging system. To enhance the detection capability of underwater laser range-gated imaging, this paper proposes the incorporation of underwater polarized light imaging technology as an enhancement method. Based on polarization differences, backscattered light and reflected light from an object can be distinguished. Experimental results indicate that, compared to images obtained using a conventional range-gated laser imaging system, those captured with a polarization-enhanced system exhibit an increase of up to 47%. The proposed approach, which integrates polarization imaging with range-gated laser imaging, has the potential to broaden the applicability of underwater laser imaging scenarios.

Recent advancements in the study of the protein complex photosystem II have clarified the sequence of events leading to the formation of oxygen during the S3->S4->S0 tran-sition, wherein the inorganic Mn4Ca(µ-O)6(OHx)4 cluster finishes photo-catalyzing the water splitting reaction (Greife et al, Nature 2023, 617, 623-628; Bhowmick et al, Nature 2023, 617, 629-636) . During this final step a tyrosine radical (TyrZ), stable for a couple of milliseconds, oxidizes a cluster bound oxygen while the hydrogen bonding patterns of nearby waters shift a proton away. A treatment of this redox reaction within the context of accepted transition state theories predicts rate constants that are significantly higher than experimentally recovered values (10^12s^-1 versus 10^3s^-1). In an effort to understand this disparity, temperature dependent experiments have revealed large entropic con-tributions to the rates with only a moderate energy of activation. We suggest that the entropic source may be related to the observed proton rearrangements, and further possible near isoenergetic variations in the nearby extended h-bonding network de-laying the realization of an ‘ideal’ transition state. In the following we explore this re-lation in the context of Eyring’s transition state theory and Marcus’ electron transfer theory, and evaluate their compatibility with the experimental evidence.

Over the last two decades, a considerable amount of equipment has been acquired (spreaders, seeders, sprayers, among others) to respond to the challenges of Precision Agriculture (PA) concept. Most of this equipment has been purchased at a high cost. However, many of them, despite still being functional and equipped with sensors, actuators, and electronic processing units capable of adjusting to variations in speed, have become obsolete in terms of communication, and incompatible with new monitoring and control systems based on the “Isobus” protocol. This work aims to present a solution for updating the control system (“Ferticontrol”) of a “Vicon RS-EDW” spreader with variable rate application (VRA), making it compatible with the “InCommand” system from “Ag Leader”. The solution includes low-cost “Arduino” and “Raspberry Pi” microcontrollers and open-source software. The development shows that it is possible to implement a solution that is accessible to farmers in general. It also provides a niche business opportunity for young researchers to set up small technology-based enterprises associated with universities and research centers. These partnerships guarantee permanent innovation and represent a decisive step towards modern, technological, competitive, and sustainable agriculture.

Summary: Hypertension is a public health problem with serious social, economic, and health consequences. The World Health Organisation (WHO) estimates that 1 in 3 adults worldwide suffers from hypertension. In Cameroon, the prevalence of hypertension is estimated at 35%, with nearly 17,000 deaths recorded each year. This study aimed to determine the factors associated with the occurrence and complications of hypertension at the Sangmélima Referral Hospital (HRS). A total of 528 patients treated in the cardiology department of the HRS were identified between January and December 2023. The data were analyzed using SPSS 28 software. Binary logistic regression determined the odds ratios and 95% confidence intervals associated with each variable. Differences were statistically significant for a p-value < 0.05. At the HRS, the annual incidence of hypertension was 16.13%. Hypertension was present in 78.8% of patients. The factors associated with the occurrence and complications of hypertension were age (OR=1.028; p=0.003 ), level of education (OR=15.49; p=0.023), marital status (OR=3.859; p=0.04), hypercholesterolemia (OR=2.856; p=0.01), monthly income (OR=0.882; p=0.026), number of dependents (OR=1.231; p=0.025), food security (OR=16.666; p<0.001), tobacco consumption (OR=8.592; p=0.041), fruit and vegetable consumption (OR=0.027; p=0.031), salt/sugar consumption (OR=8.129; p<0.001), place of residence (OR=4.794; p=0.005), access to essential technologies (OR=8.851; p=0.002), and use of traditional care (OR=3.137; np=0.032). HTA at the HRS is associated with several factors. In order to limit the impact of hypertension, it is crucial to emphasize improving socioeconomic and health conditions.

The emergence of drug resistance inducing mutations in Hepatitis C virus (HCV) coupled with genotypic heterogeneity has made targeting NS3/4A serine protease difficult. In this work, we investigated the mutagenic variations in the binding pocket of Genotype 3 (G3) HCV NS3/4A and evaluated ligands for efficacious inhibition. We report mutations at 14 positions within the ligand-binding residues of HCV NS3/4A including H57R and S139P within the catalytic triad. We then modeled each mutational variant for pharmacophore-based virtual screening (PBVS) followed by covalent docking towards identifying a potential covalent inhibitor, i.e. cpd-217. The binding stability of cpd-217 was then supported by molecular dynamic simulation followed by MM/GBSA binding free energy calculation. The free energy decomposition analysis indicated that the resistant mutants alter the HCV NS3/4A-ligand interaction, resulting in an unbalanced energy distribution within the binding site leading to drug resistance. cpd-217 was identified to interact with all NS3/4A G3 variants with significant covalent docking scores. In conclusion, cpd-217 emerges as a potential inhibitor of HCV NS3/4A G3 variants that warrants further in vitro and in vivo studies. The study will pave the way for drug design and development of HCV G3 NS3/4A.

The Myval is a balloon-expandable transcatheter heart valve (THV) devel-oped by Meril Life Sciences Pvt. Ltd. that has innovative operator-friendly de-sign which aids to improve deliverability and features precise deployment. Vari-ous clinical studies demonstrate its effectiveness and safety, making it a promis-ing choice in valvular interventions. Myval has been successfully utilized as a transcatheter aortic valve implanta-tion (TAVI) device in cases with conduction disturbances, bicuspid aortic valve anatomy, non-calcified aortic regurgitation, dysfunctional stenosed right ventric-ular outflow tract (RVOT) conduits, pulmonary valve replacement, mitral valve replacement, Vave-in-valve and Valve-in-ring implantation procedures. Myval’s diverse sizes are also of key importance in complex cases of large and complex annuli anatomy. Further long-term studies are needed to consolidate these results. Its introduction signifies a significant advancement in cardiology, aiming to enhance patient outcomes and quality of life. In the present review, we provide an update on new-generation Myval THVs and review the available clinical data published till date with an emphasis on diverse use in specific clinical scenarios.