The present study focuses on establishing the quality assurance of laboratories for recent infections (RTRI) in Thailand. We developed a cold-chain independent method, using fully characterized plasma obtained from the Thai Red Cross Society, and prepared as dried tube specimens (DTS). Twenty microliters of HIV-seronegative, recent, and long-term infected samples were aliquoted into individual tubes and dried at room temperature, 20–30 degrees Celsius, in a biosafety cabinet overnight to ensure optimal preservation. The DTS external quality control and external quality assessment were tested for homogeneity and stability following the ISO/Guide 35 guidelines. The DTS panels were distributed to 48 sites (FY 2022) and 27 sites (FY 2023) across 14 and 9 provinces, respectively, in Thailand. The results from participating laboratories were collected and evaluated for performance. The results were scored, and acceptable performance criteria were defined as the proportion of panels correctly tested, which was set at 100%. The satisfactory performance ranged from 96% to 100% and was not significantly different among the 13 health regions. The developed and implemented DTS panels can be used to monitor the quality of RTRI testing in Thailand. Full article

The advent of Version Control Systems (VCS) in computer science education has significantly improved the learning experience. The Learning Analytics community has started to analyze the interactions between students and VCSs to evaluate the behavioral and cognitive aspects of the learning process. Within the aforesaid scope, a promising research direction is the use of Artificial Intelligence (AI) to predict students’ exam outcomes early based on VCS usage data. Previous AI-based solutions have two main drawbacks: (i) They rely on static models, which disregard temporal changes in the student–VCS interactions. (ii) AI reasoning is not transparent to end-users. This paper proposes a time-dependent approach to early predict student performance from VCS data. It applies and compares different classification models trained at various course stages. To gain insights into exam performance predictions it combines classification with explainable AI techniques. It visualizes the explanations of the time-varying performance predictors. The results of a real case study show that the effect of VCS-based features on the exam success rate is relevant much earlier than the end of the course, whereas the timely submission of the first lab assignment is a reliable predictor of the exam grade. Full article

In this study, thermal elasto-plastic finite element analysis was conducted to derive the optimal welding sequence to minimize overlay welding deformation on the water wall panels of an SRF (solid refuse fuel) boiler. The water wall panels of an SRF boiler are exposed to high temperatures and corrosive environments, making overlay welding essential. However, because the length of the water wall panels and tubes exceeds 7 m, significant deformation occurs after overlay welding. Additionally, due to the large size of the water wall panels, full-size thermal elasto-plastic analysis requires huge computational costs. Therefore, in this study, the effects of welding sequence on overlay welding deformation were first investigated for a reduced model to derive the optimal welding sequence. Subsequently, an analysis model for the full-size pipe panels was established to compare and analyze the conventional welding sequence with the optimal welding sequence, thereby verifying the validity of the study. According to the welding sequence derived from the reduced model, welding deformation in the full-size model was significantly reduced compared to the conventional sequence. This reduction in deformation was discussed by analyzing the deformation behavior of the structure at each stage of the overlay welding process. Full article

It is common to see cases in which, when performing tasks in close vision in front of a digital screen, the posture or position of the head is not adequate, especially in young people; it is essential to have a correct posture of the head to avoid visual, muscular, or joint problems. Most of the current systems to control head inclination require an external part attached to the subject’s head. The aim of this study is the validation of a procedure that, through a detection algorithm and eye tracking, can control the correct position of the head in real time when subjects are in front of a digital device. The system only needs a digital device with a CCD receiver and downloadable software through which we can detect the inclination of the head, indicating if a bad posture is adopted due to a visual problem or simply inadequate visual–postural habits, alerting us to the postural anomaly to correct it.The system was evaluated in subjects with disparate interpupillary distances, at different working distances in front of the digital device, and at each distance, different tilt angles were evaluated. The system evaluated favorably in different lighting environments, correctly detecting the subjects’ pupils. The results showed that for most of the variables, particularly good absolute and relative reliability values were found when measuring head tilt with lower accuracy than most of the existing systems. The evaluated results have been positive, making it a considerably inexpensive and easily affordable system for all users. It is the first application capable of measuring the head tilt of the subject at their working or reading distance in real time by tracking their eyes. Full article

The study aimed to explore patients’ experiences and perceptions throughout the various stages of endoscopic procedures and examine the association between patient-centered communication and the patient’s experience. A total of 191 patients responded to pre- and post-procedure surveys that inquired about fear and pain, patients’ satisfaction regarding the information provided to them, perceptions and experience. Pain was associated with post-procedure fear (r = 0.63, p < 0.01) and negatively associated with reported patient experience at the end of the visit (r = −0.17, p < 0.01). Significant positive associations were found between patient experience and satisfaction from the information provided before (r = 0.47, p < 0.01) and the information provided after the procedure (r = 0.51, p < 0.001). A predictive model found that perceptions toward the physicians, satisfaction from information provided before discharge, and feelings of trust are predictors of the patient experience (F = 44.9, R² = 0.61, p < 0.001). Patients’ satisfaction with information provided before and after the procedure can positively affect the patients’ experience, leading to a decrease in fear and anxiety and increasing compliance with medical recommendations. Strategies for PCC with endoscopic patients should be developed and designed in a participatory manner, taking into account the various aspects associated with the patient experience. Full article

Renal vein thrombosis (RVT) is a relatively uncommon condition that is most frequently observed in individuals with nephrotic syndrome. While rare, pyelonephritis (PN) may serve as a predisposing factor for secondary RVT. In such cases, one should consider the possibility of RVT when patients fail to respond to appropriate antibiotic treatment. Typically, these patients require additional anticoagulation therapy for a duration of 3 to 6 months, with a generally favorable prognosis. In this report, we present the case of a 74-year-old female who developed RVT due to Klebsiella pneumoniae PN. Additionally, we reviewed 11 cases of PN complicated by RVT, which were documented in the PubMed database over a span of 40 years, emphasizing key elements in diagnostic and therapeutic approaches. Lastly, we elaborated upon the role of thrombo-inflammation, especially in the context of sepsis. Full article

Multimodal motion capability is an emerging topic in the robotics field, and this paper presents a hybrid robot system maneuvering in both terrestrial and aerial environments. Firstly, a micro quadruped–quadrotor robot with onboard sensing and computing is developed. This robot incorporates both the high mobility of unmanned aerial vehicles and the long endurance of mobile robots on the ground. A coordinated motion control scheme is then exploited for adaptive terrestrial–aerial motion transition. In this scheme, a bio-inspired terrestrial locomotion controller is proposed to generate various quadruped locomotions, and a model-based aerial locomotion controller is proposed to generate various quadrotor configurations. Then, an unified motion controller for the two subsystems which dynamically adjusts crawling and flying motion in a complicated environment is presented. Consequently, several practical trials are conducted to demonstrate the adaptability and the robustness of the proposed system. Full article

Accurate snow depth estimation is of significant importance, particularly for preventing avalanche disasters and predicting flood seasons. The predominant approaches for such snow depth estimation, based on deep learning methods, typically rely on passive microwave remote sensing data. However, due to the low resolution of passive microwave remote sensing data, it often results in low-accuracy outcomes, posing considerable limitations in application. To further improve the accuracy of snow depth estimation, in this paper, we used active microwave remote sensing data. We fused multi-spectral optical satellite images, synthetic aperture radar (SAR) images and land cover distribution images to generate a snow remote sensing dataset (SRSD). It is a first-of-its-kind dataset that includes active microwave remote sensing images in high-latitude regions of Asia. Using these novel data, we proposed a multi-scale feature perception and aggregation neural network (MFPANet) that focuses on improving feature extraction from multi-source images. Our systematic analysis reveals that the proposed approach is not only robust but also achieves high accuracy in snow depth estimation compared to existing state-of-the-art methods, with RMSE of 0.360 and with MAE of 0.128. Finally, we selected several representative areas in our study region and applied our method to map snow depth distribution, demonstrating its broad application prospects. Full article

This study evaluated the potential of using combined relaxation (CRelax) spectra within time-domain nuclear magnetic resonance (TD-NMR) measurements to predict meat quality. Broiler fillets affected by different severities of the wooden breast (WB) conditions were used as case-study samples because of the broader ranges of meat-quality variations. Partial least squares regression (PLSR) models were established to predict water-holding capacity (WHC) and meat texture, demonstrating superior CRelax capabilities for predicting meat quality. Additionally, a partial least squares discriminant analysis (PLS-DA) model was developed to predict WB severity based on CRelax spectra. The models exhibited high accuracy in distinguishing normal fillets from those affected by the WB condition and demonstrated competitive performance in classifying WB severity. This research contributes innovative insights into advanced spectroscopic techniques for comprehensive meat-quality evaluation, with implications for enhancing precision in meat applications. Full article

The performance properties of various types of parts are predominantly determined by the subsurface layer forming methods of these parts. In this regard, cutting processes, which are the final stage in the manufacturing process of these parts and, of course, their subsurface layers, play a critical role in the formation of the performance properties of these parts. Such cutting processes undoubtedly include the drilling process, the effect of which on the mechanical characteristics of the drill holes subsurface layers is evaluated in this study. This effect was evaluated by analyzing the coincidence of the energy characteristics of the short hole drilling process with the mechanical characteristics of the drilled holes’ subsurface layers. The energy characteristics of the short-hole drilling process were the total drilling power and the cutting work in the tertiary cutting zone, which is predominantly responsible for the generation of mechanical characteristics in the subsurface layers. As mechanical characteristics of the drill holes’ subsurface layers were used, the microhardness of machined surfaces and total indenter penetration work determined by the instrumented nanoindentation method, as well as maximal indenter penetration depth, were determined by the sclerometry method. Through an analysis of the coincidence between the energy characteristics of the drilling process and the mechanical characteristics of the subsurface layers, patterns of the effect of drilling process modes, drill feed, and cutting speed, which essentially determine these energy characteristics, on the studied mechanical characteristics have been established. At the same time, the increase in the energy characteristics of the short-hole drilling process leads to a decrease in the total indenter penetration work and the maximum indenter penetration depth simultaneously with an increase in the microhardness of the drilled holes’ subsurface layers. Full article

Traditional aero-engine bearings rotate simultaneously with their inner and outer rings, which makes the temperature rise prediction model computationally large with low accuracy, and it cannot be accurately verified due to the means of testing. This paper presents a method for predicting the temperature rise characteristics of aero-engine bearings under composite load conditions. Firstly, the local method is used to calculate the heat generation from heat sources such as bearing spin, lubricant drag, and the differential sliding of steel ball and collar, respectively, then finite element modelling and steady-state thermal analysis are carried out for aero-engine bearings under the simultaneous action of axial and radial external loads, a double-rotor test setup is designed and the predictive model is validated, and finally, the influences of rotational speed and load on the temperature rise characteristics of the bearings are investigated. The study shows that the aero-engine bearing prediction model proposed in this paper has high accuracy; with the increase in the rotational speed of the inner ring of the bearing, the temperatures of both the inner and outer rings of the bearing increase significantly; the temperatures of the inner and outer rings of the bearing increase with the increase in the axial load, and the effect of the radial load on the temperature of the bearing is not obvious. Full article

This paper presents an observer-based dynamic output-feedback controller design procedure using linear matrix inequality (LMI) optimization for second-order systems with uncertainty and persistent perturbation in the states. Using linear-quadratic criteria, cost functions are minimized in a two-stage procedure to compute optimal state-feedback gains, and observer gains are coupled into a dynamic output-feedback optimal controller. The LMI set used in the two stages is matrix inversion free, a key issue for polytope formulation when uncertainty is present. The approach is tested in a mobile inverted pendulum robotic platform, and the effectiveness is verified in this underactuated and undesensed case. Full article

Breathing temporarily pauses during swallowing, and the occurrence of inspiration before and after these pauses may increase the likelihood of aspiration, a serious health problem in older adults. Therefore, the automatic detection of these pauses without constraints is important. We propose methods for measuring respiratory movements during swallowing using millimeter wave radar to detect these pauses. The experiment involved 20 healthy adult participants. The results showed a correlation of 0.71 with the measurement data obtained from a band-type sensor used as a reference, demonstrating the potential to measure chest movements associated with respiration using a non-contact method. Additionally, temporary respiratory pauses caused by swallowing were confirmed by the measured data. Furthermore, using machine learning, the presence of respiring alone was detected with an accuracy of 88.5%, which is higher than that reported in previous studies. Respiring and temporary respiratory pauses caused by swallowing were also detected, with a macro-averaged F1 score of 66.4%. Although there is room for improvement in temporary pause detection, this study demonstrates the potential for measuring respiratory movements during swallowing using millimeter wave radar and a machine learning method. Full article

This paper aims to improve the deicing performance and energy utilization of bridge pylon crossbeams with built-in carbon fiber electric heating (BPB–CFEH). Therefore, a three-dimensional thermal transfer model of BPB–CFEH with one arrangement is established. Two ice-melting regions and two ice-melting stages were set up according to the characteristics of the icing of the crossbeam. The effects of wind speed and ambient temperature on the paving power required to reach the complete melting of the icicles within 8 h were analyzed. The effects of the laying spacing and rated voltage of the carbon fiber heating cable on the melting ice sheet and the thermal exchange of the two regions of the icicle after heating for 8 h were compared. Additionally, its effect on energy utilization of the process from the ice sheet melting stage to the ice column melting stage was analyzed. Ice-melting experiments verified the applicability and reasonableness of the simulated ice-melting calculation formula. The results show that under ambient temperature of −10 °C and wind speed of 4.5–13.5 m/s, the proposed paving power is 817.5–2248.12 W/m². Increasing the rated voltage and shortening the spacing increases the thermal exchange capacity of the two melting regions. The shortening of the spacing improves the energy utilization rate of the melting stage of the ice sheet to the melting stage of the icicle processes. The difference between the melting time obtained from the formula proposed by numerical simulation and the melting time obtained from indoor tests is about 10 min. This study provides a design basis for the electrothermal ice melting of bridge pylon crossbeams. Full article

Accurate localization of apples is the key factor that determines a successful harvesting cycle in the automation of apple harvesting for unmanned operations. In this regard, accurate depth sensing or positional information of apples is required for harvesting apples based on robotic systems, which is challenging in outdoor environments because of uneven light variations when using 3D cameras for the localization of apples. Therefore, this research attempted to overcome the effect of light variations for the 3D cameras during outdoor apple harvesting operations. Thus, integrated single-point laser sensors for the localization of apples using a state-of-the-art model, the EfficientDet object detection algorithm with an [email protected] of 0.775 were used in this study. In the experiments, a RealSense D455f RGB-D camera was integrated with a single-point laser ranging sensor utilized to obtain precise apple localization coordinates for implementation in a harvesting robot. The single-point laser range sensor was attached to two servo motors capable of moving the center position of the detected apples based on the detection ID generated by the DeepSORT (online real-time tracking) algorithm. The experiments were conducted under indoor and outdoor conditions in a spindle-type apple orchard artificial architecture by mounting the combined sensor system behind a four-wheel tractor. The localization coordinates were compared between the RGB-D camera depth values and the combined sensor system under different light conditions. The results show that the root-mean-square error (RMSE) values of the RGB-D camera depth and integrated sensor mechanism varied from 3.91 to 8.36 cm and from 1.62 to 2.13 cm under 476~600 lx to 1023~1100 × 100 lx light conditions, respectively. The integrated sensor system can be used for an apple harvesting robotic manipulator with a positional accuracy of ±2 cm, except for some apples that were occluded due to leaves and branches. Further research will be carried out using changes in the position of the integrated system for recognition of the affected apples for harvesting operations. Full article

A new technique for finishing the surfaces of friction pairs has been proposed, which, in combination with the original test method, has shown a significant influence of the initial roughness configuration (surface texture) on friction and wear. Two types of finishing processing of the shaft friction surfaces were compared, and it was found that the friction and wear coefficients differ by more than 2–5 and 2–4 times, respectively. Based on a new methodology for analyzing standard roughness parameters, the tribological efficiency criteria (in the sense of reducing friction and wear) are proposed for the initial state of the friction surface of a radial plane sliding bearing shaft relative to the friction direction, which is consistent with its frictional characteristics. Comparison of the laboratory test results with the surface tribological efficiency criteria showed that these criteria are very promising for controlling existing technologies and optimizing new technologies for friction surface finishing in various friction systems. Full article

Biochar, an organic, porous, and carbon-rich material originating from biomass via pyrolysis, showcases compelling attributes and intrinsic performances. Its appeal as a reinforcement material for biocomposites, as well as its auspicious electrical properties, has gained more attention, and makes biochar a versatile candidate for applications ranging from energy storage to catalytic devices. This scientific review undertakes a comprehensive exploration of biochar, spanning production methodologies, physicochemical intricacies, and critical process parameters. The focus of this paper extends to optimization strategies for biochar properties tailored to specific applications, with a dedicated inquiry into diverse production methods and activation strategies. This review’s second phase delves into a meticulous analysis of key properties within biochar-based composites, emphasizing limitations and unique performance characteristics crucial for diverse applications. By synthesizing a substantial body of research, this review aims to catalyze future investigations by pinpointing areas that demand attention in upcoming experiments, ultimately emphasizing the profound potential of biochar-based materials across technical and scientific domains. Full article

The quantification of human DNA extracts from forensic samples plays a key role in the forensic genetics process, ensuring maximum efficiency and avoiding repeated analyses, over-amplified samples, or unnecessary examinations. In our laboratory, we use the Quantifiler^® Trio system to quantify DNA extracts from a wide range of samples extracted from traces (bloodstains, saliva, semen, tissues, etc.), including swabs from touched objects, which are very numerous in the forensic context. This method has been extensively used continuously for nine years, following an initial validation process, and is part of the ISO/IEC 17025 accredited method. In routine practice, based on the quantitative values determined from the extracts of each trace, we use a standard method or a low-copy-number method that involves repeating the amplification with the generation of a consensus genetic profile. Nowadays, when the quantification results are less than 0.003 ng/μL in the minimum extraction volume (40 μL), we do not proceed with the DNA extract analysis. By verifying the limits of the method, we make a conscious cost-benefit choice, in particular by using the least amount of DNA needed to obtain sufficiently robust genetic profiles appropriate for submission to the Italian DNA Forensic Database. In this work, we present a critical re-evaluation of this phase of the method, which is based on the use of standard curves obtained from the average values of the control DNA analysed in duplicate. Considering the various contributions to uncertainty that are difficult to measure, such as manual pipetting or analytical phases carried out by different operators, we have decided to thoroughly investigate the contribution of variability in the preparation of calibration curves to the final results. Thus, 757 samples from 20 independent experiments were re-evaluated using two different standards for the construction of curves, determining the quantitative differences between the two methods. The experiments also determined the parameters of the slope, Y-intercept, R², and the values of the synthetic control probe to verify how these parameters can provide information on the final outcome of each analysis. The outcome of this revalidation demonstrated that it is preferable to use quantification ranges rather than exact quantitative limits before deciding how to analyse the extracts via PCR or forgoing the determination of profiles. Additionally, we present some preliminary data related to the analysis of samples that would not have been analysed based on the initial validation, from which genetic profiles were obtained after applying a concentration method to the extracts. Our goal is to improve the accredited analytical method, with a careful risk assessment as indicated by accreditation standards, ensuring that no source of evidence is lost in the reconstruction of a criminal event. Full article

Background: Carotid stenosis (CS) is an atherosclerotic disease of the carotid artery that can lead to devastating cardiovascular outcomes such as stroke, disability, and death. The currently available treatment for CS is medical management through risk reduction, including control of hypertension, diabetes, and/or hypercholesterolemia. Surgical interventions are currently suggested for patients with symptomatic disease with stenosis >50%, where patients have suffered from a carotid-related event such as a cerebrovascular accident, or asymptomatic disease with stenosis >60% if the long-term risk of death is <3%. There is a lack of current plasma protein biomarkers available to predict patients at risk of such adverse events. Methods: In this study, we investigated several growth factors and biomarkers of inflammation as potential biomarkers for adverse CS events such as stroke, need for surgical intervention, myocardial infarction, and cardiovascular-related death. In this pilot study, we use a support vector machine (SVM), random forest models, and the following four significantly elevated biomarkers: C-X-C Motif Chemokine Ligand 6 (CXCL6); Interleukin-2 (IL-2); Galectin-9; and angiopoietin-like protein (ANGPTL4). Results: Our SVM model best predicted carotid cerebrovascular events with an area under the curve (AUC) of >0.8 and an accuracy of 0.88, demonstrating strong prognostic capability. Conclusions: Our SVM model may be used for risk stratification of patients with CS to determine those who may benefit from surgical intervention. Full article

The utilization of lithium–sulfur battery is hindered by various challenges, including the “shuttle effect”, limited sulfur utilization, and the sluggish conversion kinetics of lithium polysulfides (LiPSs). In the present work, a theoretical design for the viability of graphitic carbon nitride (g-C₃N₄) and phosphorus-doping graphitic carbon nitride substrates (P-g-C₃N₄) as promising host materials in a Li-S battery was conducted utilizing first-principles calculations. The PDOS shows that when the P atom is introduced, the 2p of the N atom is affected by the 2p orbital of the P atom, which increases the energy band of phosphorus-doping substrates. The energy bands of P_C and P_i are 0.12 eV and 0.20 eV, respectively. When the lithium polysulfides are adsorbed on four substrates, the overall adsorption energy of P_C is 48–77% higher than that of graphitic carbon nitride, in which the charge transfer of long-chain lithium polysulfides increase by more than 1.5-fold. It is found that there are powerful Li-N bonds between lithium polysulfides and P-g-C₃N₄ substrates. Compared with the graphitic carbon nitride monolayer, the anchoring effect of the LiPSs@P-g-C₃N₄ substrate is enhanced, which is beneficial for inhibiting the shuttle of high-order lithium polysulfides. Furthermore, the catalytic performance of the P-g-C₃N₄ substrate is assessed in terms of the S₈ reduction pathway and the decomposition of Li₂S; the decomposition energy barrier of the P-g-C₃N₄ substrate decrease by 10% to 18%. The calculated results show that P-g-C₃N₄ can promote the reduction of S₈ molecules and Li-S bond cleavage within Li₂S, thus improving the utilization of sulfur-active substances and the ability of rapid reaction kinetics. Therefore, the P-g-C₃N₄ substrates are a promising high-performance lithium-sulfur battery anchoring material. Full article

Accurate identification of spatial domains is essential in the analysis of spatial transcriptomics data in order to elucidate tissue microenvironments and biological functions. However, existing methods only perform domain segmentation based on local or global spatial relationships between spots, resulting in an underutilization of spatial information. To this end, we propose SECE, a deep learning-based method that captures both local and global relationships among spots and aggregates their information using expression similarity and spatial similarity. We benchmarked SECE against eight state-of-the-art methods on six real spatial transcriptomics datasets spanning four different platforms. SECE consistently outperformed other methods in spatial domain identification accuracy. Moreover, SECE produced spatial embeddings that exhibited clearer patterns in low-dimensional visualizations and facilitated a more accurate trajectory inference. Full article