Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of the Parameters Affecting the Stiffness of Short Sisal Fiber Biocomposites Manufactured by Compression-Molding

The use of natural fiber-based composites is on the rise in many industries. Thanks to their eco-sustainability, these innovative materials make it possible to adapt the production of components, systems and machines to the increasingly stringent regulations on environmental protection, while at the same time reducing production costs, weight and operating costs. Optimizing the mechanical properties of biocomposites is an important goal of applied research. In this work, using a new numerical approach, the effects of the volume fraction, average length, distribution of orientation and curvature of fibers on the Young’s modulus of a biocomposite reinforced with short natural fibers were studied. Although the proposed approach could be applied to any biocomposite, sisal fibers and an eco-sustainable thermosetting matrix (green epoxy) were considered in both simulations and the associated experimental assessment. The results of the simulations showed the following effects of the aforementioned parameters on Young’s modulus: a linear growth with the volume fraction, nonlinear growth as the length of the fibers increased, a reduction as the average curvature increased and an increase in stiffness in the x-y plane as the distribution of fiber orientation in the z direction decreased.
Copper Surface Treatment Method with Antibacterial Performance Using “Super-Spread Wetting” Properties

In this work, a copper coating is developed on a carbon steel substrate by exploiting the superwetting properties of liquid copper. We characterize the surface morphology, chemical composition, roughness, wettability, ability to release a copper ion from surfaces, and antibacterial efficacy (against Escherichia coli and Staphylococcus aureus). The coating shows a dense microstructure and good adhesion, with thicknesses of approximately 20–40 µm. X-ray diffraction (XRD) analysis reveals that the coated surface structure is composed of Cu, Cu2O, and CuO. The surface roughness and contact angle measurements suggest that the copper coating is rougher and more hydrophobic than the substrate. Inductively coupled plasma atomic emission spectroscopy (ICP-AES) measurements reveal a dissolution of copper ions in chloride-containing environments. The antibacterial test shows that the copper coating achieves a 99.99% reduction of E. coli and S. aureus. This study suggests that the characteristics of the copper-coated surface, including the chemical composition, high surface roughness, good wettability, and ability for copper ion release, may result in surfaces with antibacterial properties.
Development of Force Sensor System Based on Tri-Axial Fiber Bragg Grating with Flexure Structure

Fiber Bragg grating (FBG) sensors have an advantage over optical sensors in that they are lightweight, easy to terminate, and have a high flexibility and a low cost. Additionally, FBG is highly sensitive to strain and temperature, which is why it has been used in FBG force sensor systems for cardiac catheterization. When manually inserting the catheter, the physician should sense the force at the catheter tip under the limitation of power (<0.5 N). The FBG force sensor can be optimal for a catheter as it can be small, low-cost, easy to manufacture, free of electromagnetic interference, and is materially biocompatible with humans. In this study, FBG fibers mounted on two different flexure structures were designed and simulated using ANSYS simulation software to verify their sensitivity and durability for use in a catheter tip. The selected flexure was combined with three FBGs and an interrogator to obtain the wavelength signals. To obtain a calibration curve, the FBG sensor obtained data on the change in wavelength with force at a high resolution of 0.01 N within the 0.1–0.5 N range. The calibration curve was used in the force sensor system by the LabVIEW program to measure the unknown force values in real time.
Early antitumor activity of oral Langerhans cells is compromised by a carcinogen

Significance Oral cancer is often diagnosed at late stages, resulting in a poor prognosis of this disease. Understanding early carcinogenic events taking place during the development of oral cancer is, therefore, an important unmet clinical need. This study identifies an early anticancer protective role of oral Langerhans cells (LCs), the principal mononuclear phagocyte involved in immunosurveillance of the oral epithelium. Continuous exposure to the carcinogen 4NQO hampers the local differentiation of LCs, while other mononuclear phagocytes and T cells with immunosuppressive characteristics populate the epithelium, leading to the development of oral cancer. These findings reveal an initial step by which immunosurveillance is compromised by a carcinogen, which could facilitate novel diagnostic approaches to better detection of oral cancer. Early diagnosis of oral squamous cell carcinoma (OSCC) remains an unmet clinical need. Therefore, elucidating the initial events of OSCC preceding tumor development could benefit OSCC prognosis. Here, we define the Langerhans cells (LCs) of the tongue and demonstrate that LCs protect the epithelium from carcinogen-induced OSCC by rapidly priming αβT cells capable of eliminating γH2AX+ epithelial cells, whereas γδT and natural killer cells are dispensable. The carcinogen, however, dysregulates the epithelial resident mononuclear phagocytes, reducing LC frequencies, while dendritic cells (DCs), macrophages, and plasmacytoid DCs (pDCs) populate the epithelium. Single-cell RNA-sequencing analysis indicates that these newly differentiated cells display an immunosuppressive phenotype accompanied by an expansion of T regulatory (Treg) cells. Accumulation of the Treg cells was regulated, in part, by pDCs and precedes the formation of visible tumors. This suggests LCs play an early protective role during OSCC, yet the capacity of the carcinogen to dysregulate the differentiation of mononuclear phagocytes facilitates oral carcinogenesis.
Assessing diagnosis disclosure and concealment in multiple sclerosis: Building a framework for moving forward

Especially early in the disease course, people with multiple sclerosis (PwMS) may be able to choose whether to reveal their diagnosis to their employer, colleagues, and friends. Concealment might prevent discrimination but can also be stressful, resulting in the fear of being discovered, the need for continual self-monitoring to avoid disclosing too much, and a sense of detachment from one’s true self. A few studies have addressed this topic in multiple sclerosis (MS), in part because the field lacks a formal, validated measurement tool assessing diagnosis and disclosure and concealment behavior in PwMS.
A Talk-Listen-Ack Beaconing Strategy for Neighbor Discovery Protocols in Wireless Sensor Networks

Neighbor discovery is a fundamental function for sensor networking. Sensor nodes discover each other by sending and receiving beacons. Although many time-slotted neighbor discovery protocols (NDPs) have been proposed, the theoretical discovery latency is measured by the number of time slots rather than the unit of time. Generally, the actual discovery latency of a NDP is proportional to its theoretical discovery latency and slot length, and inversely proportional to the discovery probability. Therefore, it is desired to increase discovery probability while reducing slot length. This task, however, is challenging because the slot length and the discovery probability are two conflicting factors, and they mainly depend on the beaconing strategy used. In this paper, we propose a new beaconing strategy, called talk-listen-ack beaconing (TLA). We analyze the discovery probability of TLA by using a fine-grained slot model. Further, we also analyze the discovery probability of TLA that uses random backoff mechanism to avoid persistent collisions. Simulation and experimental results show that, compared with the 2-Beacon approach that has been widely used in time-slotted NDPs, TLA can achieve a high discovery probability even in a short time slot. TLA is a generic beaconing strategy that can be applied to different slotted NDPs to reduce their discovery latency.
Modelling of gradual construction of road bridge and its creep

Fast construction of new highways in the Czech Republic makes demand on efficient technologies of highway bridges construction. The construction of bridges is one of the most expensive and the most complicated parts of the whole highway construction. Therefore, a lot of interest is devoted to the concrete bridges construction. Detailed analysis of the gradual bridge construction is not performed in practice because it is very time consuming and necessitates the use of specialised software. This contribution deals with an analysis of gradual construction of a highway prestressed concrete bridge. Two technologies are studied and modelled. In the first case, the first span and approximately one fourth of the second span of the bridge is cast on prepared falsework. After curing the falsework is removed and the remaining part of the second span and one fourth of the third span is cast and so on. In the second case, the first span is cast on prepared falsework. After time for certain concrete hardening, falsework is moved and the second span is cast and so. The whole bridge, as in the final stage of construction, is discretized by a finite element mesh. A virtual falsework occurring along the whole bridge is also discretized by a finite element mesh. The gradual construction is modelled with the help of time functions which are used for switching the nodes and finite elements on or off. The time functions of finite elements describing existing spans of the bridge and the actual position of the falsework are unity while the time functions of remaining elements are zero. It is assumed that the falsework supports newly cast span for some time and then the new span is connected with the preceding span and the falsework can be removed. Applied loads play an important role in the analysis. First of all, dead load of the falsework and the bridge is taken into account. Beside the dead load, longitudinal and transverse prestress is assumed as a load case. The loads are also managed by time functions which switch them on or off. The loads are applied during the early stages of the hardening of concrete and therefore creep effects have to be considered. The analyses are based on the modified B3 creep models for concrete developed
Computational perspective on recent advances in quantum electronics: from electron quantum optics to nanoelectronic devices and systems

Quantum electronics has significantly evolved over the last decades. Where initially the clear focus was on light–matter interactions, nowadays approaches based on the electron’s wave nature have solidified themselves as additional focus areas. This development is largely driven by continuous advances in electron quantum optics, electron based quantum information processing, electronic materials, and nanoelectronic devices and systems. The pace of research in all of these areas is astonishing and is accompanied by substantial theoretical and experimental advancements. What is particularly exciting is the fact that the computational methods, together with broadly available large-scale computing resources, have matured to such a degree so as to be essential enabling technologies themselves. These methods allow to predict, analyze, and design not only individual physical processes but also entire devices and systems, which would otherwise be very challenging or sometimes even out of reach with conventional experimental capabilities. This review is thus a testament to the increasingly towering importance of computational methods for advancing the expanding field of quantum electronics. To that end, computational aspects of a representative selection of recent research in quantum electronics are highlighted where a major focus is on the electron’s wave nature. By categorizing the research into concrete technological applications, researchers and engineers will be able to use this review as a source for inspiration regarding problem-specific computational methods.
Maternal pre‐pregnancy body mass index, gestational weight gain, and pubertal timing in daughters: A systematic review and meta‐analysis of cohort studies

The timing of daughter's puberty onset is constantly earlier. It is still unclear about the maternal pre‐pregnancy body mass index (BMI) and gestational weight gain (GWG) as important prenatal factors that may affect offspring's onset of puberty. Thus, we evaluated the association among maternal pre‐pregnancy BMI, GWG, and daughters' early pubertal development based on the existing literature. Literature review was conducted in different databases, including Web of Science, Pubmed, Wiley, ScienceDirect, Web of Science, and Chinese National Knowledge Infrastructure databases up to June 2021. We selected random effects model or fixed effects model for meta‐analysis according to the I2 statistics value to obtain the summary measurement. A total of 12 cohort studies were included. Compared to maternal pre‐pregnancy normal weight, maternal pre‐pregnancy overall overweight/obesity (RR = 1.24; 95% CI 1.17 to 1.32), obesity (RR = 1.35; 95% CI 1.23 to 1.48), and overweight (RR = 1.17; 95% CI 1.09 to 1.26) were significantly associated with the increased risk of earlier timing of pubertal onset in daughters. Daughters born of mothers with pre‐pregnancy overall overweight/obesity, obesity, and overweight had earlier pubertal onset compared to those born of mothers with normal weight ([mean difference = −3.03, 95% CI: −3.97 to −2.10], [mean difference = −3.50, 95% CI: −5.38 to −1.62], and [mean difference = −2.89, 95% CI: −4.07 to −1.71], respectively). The effects were also significant in the assessed three milestones (menarche, breast development, and pubic hair development). Maternal excessive GWG increased the risk of early pubertal timing in daughters (RR = 1.19; 95% CI 1.09 to 1.30).
Sensor Data Fusion for a Mobile Robot Using Neural Networks

Mobile robots must be capable to obtain an accurate map of their surroundings to move within it. To detect different materials that might be undetectable to one sensor but not others it is necessary to construct at least a two-sensor fusion scheme. With this, it is possible to generate a 2D occupancy map in which glass obstacles are identified. An artificial neural network is used to fuse data from a tri-sensor (RealSense Stereo camera, 2D 360° LiDAR, and Ultrasonic Sensors) setup capable of detecting glass and other materials typically found in indoor environments that may or may not be visible to traditional 2D LiDAR sensors, hence the expression improved LiDAR. A preprocessing scheme is implemented to filter all the outliers, project a 3D pointcloud to a 2D plane and adjust distance data. With a Neural Network as a data fusion algorithm, we integrate all the information into a single, more accurate distance-to-obstacle reading to finally generate a 2D Occupancy Grid Map (OGM) that considers all sensors information. The Robotis Turtlebot3 Waffle Pi robot is used as the experimental platform to conduct experiments given the different fusion strategies. Test results show that with such a fusion algorithm, it is possible to detect glass and other obstacles with an estimated root-mean-square error (RMSE) of 3 cm with multiple fusion strategies.
Integration of text messaging intervention into hypertension management among older adults: A systematic review and meta-analysis.

BACKGROUND An aging population and required hypertension control are global concerns that burden the healthcare system. Text messaging interventions have been developed to support hypertension management, but their effects on the older population are unknown. OBJECTIVES This review aimed to identify the effects of a text messaging intervention on hypertension management among older adults. METHODS Four English and two Chinese databases with randomized controlled trials published between January 2010 and December 2020 were searched. The mean age of the participants was 60 years or above. Participants were also diagnosed with hypertension. The Cochrane risk-of-bias tool was used for the critical appraisal. Data in each study were extracted, and a meta-analysis was presented in terms of mean difference (MD) and standardized mean difference (SMD). RESULTS A total of 1670 records were screened, of which six were included in the final review. The intervention of the included studies lasted up to 6 months, and one-way text messaging was commonly used. Meta-analysis showed that a text messaging intervention significantly reduced systolic blood pressure (MD = -6.11, p < .01) but not diastolic blood pressure. Regarding medication adherence, a moderate effect was noted with the use of text messaging among older adults with hypertension (SMD = 0.65, p = .01). LINKING EVIDENCE TO ACTION A text messaging intervention can improve hypertension management among older adults. The standardized content of one-way text messaging is suggested to be delivered weekly.
Intention to Stay in Specialist Trauma Nurses: Relationship With Role Conflict, Stress, and Organizational Support

BACKGROUND: Specialist trauma nurses contribute to shortening hospital stay, lowering intensive care unit readmission rates, and improving treatment outcomes through early detection and management of health problems in trauma patients. However, Korean specialist trauma nurses have a higher turnover rate than other nurses due to negative factors like unclear job descriptions and inconsistent job activities. OBJECTIVE: This study aimed to examine the levels of and relationships among role conflict, occupational stress, perceived organizational support, and intent to stay in Korean specialist trauma nurses. METHODS: We enrolled 53 specialist trauma nurses from eight regional trauma centers in Korea. Data on role conflict, occupational stress, perceived organizational support, and intent to stay were collected using a structured questionnaire. Mann–Whitney U test, Kruskal–Wallis test, and Bonferroni post hoc tests were conducted to examine differences in intent to stay. Spearman's correlation coefficients were used to examine correlations between the key variables. RESULTS: High intent to stay was associated with periodic job training, job satisfaction, and perceived high workload. Role conflict was positively correlated with occupational stress, whereas both were negatively correlated with perceived organizational support. Intent to stay was negatively correlated with occupational stress and positively correlated with perceived organizational support. CONCLUSIONS: Effective improvement measures that lower occupational stress and increase perceived organizational support will help maintain the positions of specialist trauma nurses. These results highlight the need to specify the scope of practice and implement practical measures like career development programs that enhance professional nursing competencies to retain specialist trauma nurses.
Influence of FOXP3 gene polymorphisms on the risk of preeclampsia: a meta‐analysis and a bioinformatic approach

ABSTRACT Background and aim Preeclampsia (PE), a multifactorial disorder, is the main cause of maternal mortality and morbidity. Genetic polymorphisms in key proteins involved in the immune system may change the risk of PE risk. In this study, we examined the association of two rs2232365 and rs3761548 common polymorphisms of the FOXP3 immune response gene with PE susceptibility by a meta-analysis which was followed by an in-silico analysis. Materials and methods Through a systematic search in databases including PubMed, MEDLINE, Google Scholar, and Science Direct, we find eligible studies for meta-analysis. Some bioinformatics tools were used to detect the impact of rs2232365 and rs3761548 polymorphisms on the FOXP3 gene function. Results Our data revealed that there is a significant association between rs3761548 polymorphism and decreased risk of PE. In addition, we observed a significant association between rs2232365 and increased risk of mild preeclampsia. Also, our bioinformatic analysis showed that both rs2232365 and rs3761548 polymorphisms could affect FOXP3 gene function. Conclusion Based on our findings, the rs3761548 genetic variation could be a protective factor against PE risk. While the rs2232365 polymorphism may be a genetic risk factor for mild preeclampsia. Therefore, as a preliminary study, these genetic variations could be considered molecular biomarkers for PE disorder.
Towards Hybrid Energy-Efficient Power Management in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are prone to highly constrained resources, as a result ensuring the proper functioning of the network is a requirement. Therefore, an effective WSN management system has to be integrated for the network efficiency. Our objective is to model, design, and propose a homogeneous WSN hybrid architecture. This work features a dedicated power utilization optimization strategy specifically for WSNs application. It is entitled Hybrid Energy-Efficient Power manager Scheduling (HEEPS). The pillars of this strategy are based on the one hand on time-out Dynamic Power Management (DPM) Intertask and on the other hand on Dynamic Voltage and Frequency Scaling (DVFS). All tasks are scheduled under Global Earliest Deadline First (GEDF) with new scheduling tests to overcome the Dhall effect. To minimize the energy consumption, the HEEPS predicts, defines and models the behavior adapted to each sensor node, as well as the associated energy management mechanism. HEEPS’s performance evaluation and analysis are performed using the STORM simulator. A comparison to the results obtained with the various state of the art approaches is presented. Results show that the power manager proposed effectively schedules tasks to use dynamically the available energy estimated gain up to 50%.
Predictive value of arterial blood lactic acid concentration on the risk of all-cause death within 28 days of admission in patients with severe acute pancreatitis

ABSTRACT Objective To evaluate the ability of arterial blood lactic acid concentration to predict death within 28 days of admission of patients with severe acute pancreatitis (SAP) in the intensive care unit (ICU). Methods Clinical data of 523 SAP patients in the MIMIC-IV database were retrospectively analyzed. Patients were divided into those who survived (n = 461) and those who died (n = 62) within 28 days of admission. The association between lactic acid concentration and all-cause death in SAP patients was determined by Cox regression analysis, Kaplan-Meier survival analysis and subgroup analysis. The ability of lactic acid concentration to predict the risk of all-cause death in SAP patients was determined by time-dependent receiver operating curve (ROC) analysis. Results Arterial blood lactic acid concentration was significantly higher in the 62 patients who died within 28 days than in the 461 patients who survived (P < 0.05). Adjusted multivariate Cox regression analysis showed that lactic acid concentration was a significant independent predictor on all-cause mortality within 28 days of admission for SAP (hazard ratio = 1.22, 95% confidence interval 1.09–1.36, P < 0.001), as did time-dependent ROC analysis (area under the ROC curve = 0.741). Kaplan-Meier analysis showed that the rate of all-cause mortality within 28 days of admission was significantly higher in patients with high than low lactic acid concentration (P < 0.0001). Subgroup analysis showed that there was no significant interaction between lactic acid concentration and other factors with all-cause death within 28 days of admission (all P > 0.05). Conclusion Arterial blood lactic acid concentration is an important independent predictor of all-cause mortality within 28 days of admission of SAP patients in the ICU.