Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantifying cortical bone in fragmentary archeological second metacarpals.

OBJECTIVES Skeletal variation in cortical bone thickness is an indicator of bone quality and health in archeological populations. Second metacarpal radiogrammetry, which measures cortical thickness at the shaft midpoint, is traditionally used to evaluate bone loss in bioarcheological and some clinical contexts. However fragmentary elements are regularly omitted because the midpoint cannot be determined. This methodological limitation reduces sample sizes and biases them against individuals prone to fracture, such as older individuals with low bone mass. This study introduces a new technique for measuring cortical bone in second metacarpals, the "Region of Interest" (ROI) method, which quantifies bone in archeological remains with less-than-ideal preservation while accounting for cortical heterogeneity. MATERIALS AND METHODS The ROI method was adapted from digital X-ray radiogrammetry (DXR), a clinical method used to estimate bone mineral density, and tested using second metacarpals from Middenbeemster, Netherlands, a 19th century known age and sex skeletal collection. The ROI method quantifies cortical bone area within a 1.9 cm-long, mid-diaphyseal region, standardized for body size differences using total area (CAIROI ). CAIROI values were compared to traditional radiogrammetric cortical indices (CI) to assess the method's ability to identify age-related bone loss. RESULTS CAIROI values have high intra- and interobserver replicability and are strongly and significantly correlated with CI values for both males (r[n = 39] = 0.906, p = 0.000) and females (r[n = 58] = 0.925, p = 0.000). CONCLUSION The ROI method complements traditional radiogrammetry analyses and provides a reliable way to quantify cortical bone in incomplete second metacarpals, thereby maximizing sample sizes, allowing patterns in bone acquisition and loss to be more comprehensively depicted in archeological assemblages.
The Multiple Monodisperse Outlet Differential Mobility Analyzer: Derivation of Its Transfer Function and Resolution

Conventional differential mobility analyzers (DMAs) for classification of aerosol particles have one polydisperse-particle inlet and one monodisperse-particle outlet. As a result, when they are used as particle classifiers in aerosol mobility spectrometers, it is needed to scan through different operating conditions, thereby requiring a significant amount of time (i.e., of the order of a minute) for a single mobility distribution measurement. DMAs with multiple outlets can significantly reduce this scanning time because particles of different mobilities can be classified and detected simultaneously. In addition, depending on the relative location of the first and the last outlet from the inlet, one can increase the dynamic mobility range of the selected particles in a single particle mobility distribution measurement. In this article, we derive analytical expressions for estimating the transfer function and the resolution of DMAs with multiple monodisperse outlets. Starting with the simple consideration of nondiffusing particles, we extend our analysis for diffusing particles and provide expressions of different complexity and accuracy. The theoretical framework provided in this article can be employed to optimize the design of DMAs with more than one monodisperse-particle outlet, and to analyze the measurements when such DMAs are used in aerosol mobility spectrometers. Copyright 2012 American Association for Aerosol Research
The Relationship Between Cybervictimization and Non-suicidal Self-Injury in Chinese Adolescents: A Moderated-Mediation Model

The present study investigated the mediating role of negative emotion in the relationship between cybervictimization and non-suicidal self-injury (NSSI), and the moderating role of friendship quality in the indirect relationship. This model was tested with 1,326 Chinese adolescents who suffered from cyberbullying in the last 1 year; 727 were boys and 591 were girls, and their mean age was 13.67 years (SD = 1.34, range 11–17). Participants filled out questionnaires regarding cybervictimization, negative emotion, friendship quality, and non-suicidal self-injury. After demographic variables were controlled, cybervictimization was significantly positively associated with non-suicidal self-injury. Mediation analysis revealed that negative emotion partially mediated the association between cybervictimization and non-suicidal self-injury. Moderated mediation analysis further indicated that the mediated path was weaker for adolescents with higher levels of friendship quality. These findings underscore the importance of identifying the mechanisms that moderate the mediated path between cybervictimization and non-suicidal self-injury among adolescents.
Theoretical Development: Extending the Flow Theory with Variables from the UTAUT2 Model

According to the dramatic development of innovative information technology in worldwide ranges, business climate has changed from traditional commerce to virtual commerce in recent two decades. It is important to synthetically understand customers' adoption intention of new technology for better business management and strategy involved with information technology. Thus, this study extends the Flow theory by integrating variables from the revised Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model and satisfaction to propose a theoretical development for investigating the factors determining customers' behavioral intention on adopting new information technology. In addition, the proposed theoretical development contributes the relevant researches on systematical understanding customers' adoption intention determined from technological perceptions to mental cognition. Moreover, the proposed framework and measurement method can be applied as reference for relevant researchers and stakeholders to investigate customers' behaviors for further research and future business management and strategy.
A Weak Response to Endoplasmic Reticulum Stress Is Associated With Postoperative Organ Failure in Patients Undergoing Cardiac Surgery With Cardiopulmonary Bypass

Introduction: Endoplasmic reticulum stress (ERS) is involved in inflammatory organ failure. Our objective was to describe ERS, its unfolded protein response (UPR) expression/kinetics during cardiac surgery with cardiopulmonary bypass (CPB) and its association with postoperative organ failure (OF). Methods: Prospective study conducted on patients undergoing cardiac surgery with CPB. Blood samples were taken before (Pre-CPB), 2 h (H2-CPB) and 24 h (H24-CPB) after CPB. Plasma levels of 78 kDa Glucose- Regulated Protein (GRP78, final effector of UPR) were evaluated by ELISA. The expression of genes coding for key elements of UPR (ATF6, ATF4, sXBP1, CHOP) was evaluated by quantitative PCR performed on total blood. OF was defined as invasive mechanical ventilation and/or acute kidney injury and/or hemodynamic failure requiring catecholamines. Results: We included 46 patients, GRP78 was decreased at H2-CPB [1,328 (878–1,730) ng/ml vs. 2,348 (1,655–3,730) ng/ml Pre-CPB; p < 0.001] but returned to basal levels at H24-CPB [2,068 (1,436–3,005) ng/ml]. The genes involved in UPR had increased expression at H2 and H24. GRP78 plasma levels in patients with OF at H24-CPB (n = 10) remained below Pre-CPB levels [−27.6 (−51.5; −24.2)%] compared to patients without OF (n = 36) in whom GRP78 levels returned to basal levels [0.6 (−28.1; 26.6)%; p < 0.01]. H24-CPB ATF6 and CHOP expressions were lower in patients with OF than in patients without OF [2.3 (1.3–3.1) vs. 3.0 (2.7–3.7), p < 0.05 and 1.3 (0.9–2.0) vs. 2.2 (1.7–2.9), p < 0.05, respectively]. Conclusions: Low relative levels of GRP78 and weak UPR gene expression appeared associated with postoperative OF. Further studies are needed to understand ERS implication during acute organ failure in humans.
An Analysis of Japanese EFL Learners’ Lexical Network Changes

In order to compare Japanese EFL learners’ lexical knowledge before and after undertaking extensive reading tasks, this study picked up eight words from the reading material and investigated how learners’ perceived relationship between these words changed during the task. Data were collected from 58 Japanese EFL learners who were divided into three groups, each of which was given the same reading material but with different tasks (translation task, multiple-choice question task, and no task (control)). Participants judged the degree of relationship between target words twice, before and after the assigned task. The results revealed that participants in the translation task group tended to find the relationships between the words more easily than the participants in other groups, and they were also more aware of changes in their own ability to recognize word association. In addition, the authors also analyzed the data by using AMISESCAL (Asymmetric von Mises Scaling), a statistical model that visualizes asymmetric relations among elements on a two-dimensional map. Visualization of learners’ lexical network threw some light on the restructuring process of how words were interconnected in their lexical representation.
Random Forests Based Path Loss Prediction in Mobile Communication Systems

When deploying communication systems, an accurate wireless propagation model is important to ensure the quality of service covering the region. Due to the complex radio environment, the traditional wireless propagation models need massive data for correction and calculation. To address this issue, this paper proposes a wireless propagation method to predict path loss. We use the random forest network structure to fit the complex model, accurately predicting the received signal power in the target area. To improve the training efficiency of the model, we construct the preliminary features according to the previous knowledge. A filtering feature selection method is adopted to select features as input of model. Evaluating the model on four typical terrains, the experiment results show that the proposed model outperforms the four existing models in all types of terrains.
Outage Performance of Downlink NOMA With Network-Coded Interference Cancellation

In this paper, we study a downlink non-orthogonal multiple access (NOMA) transmission system, where a novel network-coded interference cancellation (NCIC) scheme is proposed to promote the outage performance. In order to further improve the outage performance, an adaptive NCIC (A-NCIC) scheme is also studied, which dynamically switches between successive interference cancellation (SIC) and the proposed NCIC schemes according to the power allocation factors and target data rates. The expressions of the outage probability are derived to evaluate the performance of the proposed scheme. The simulation results demonstrate the remarkable performance of the proposed NCIC scheme over the conventional SIC-based NOMA on the outage probability.
Immunological Endotyping of Chronic Critical Illness After Severe Sepsis

Improved management of severe sepsis has been one of the major health care accomplishments of the last two decades. Due to enhanced recognition and improved management of severe sepsis, in-hospital mortality has been reduced by up to 40%. With that good news, a new syndrome has unfortunately replaced in-hospital multi-organ failure and death. This syndrome of chronic critical illness (CCI) includes sepsis patients who survive the early “cytokine or genomic storm,” but fail to fully recover, and progress into a persistent state of manageable organ injury requiring prolonged intensive care. These patients are commonly discharged to long-term care facilities where sepsis recidivism is high. As many as 33% of sepsis survivors develop CCI. CCI is the result, at least in part, of a maladaptive host response to chronic pattern-recognition receptor (PRR)-mediated processes. This maladaptive response results in dysregulated myelopoiesis, chronic inflammation, T-cell atrophy, T-cell exhaustion, and the expansion of suppressor cell functions. We have defined this panoply of host responses as a persistent inflammatory, immune suppressive and protein catabolic syndrome (PICS). Why is this important? We propose that PICS in survivors of critical illness is its own common, unique immunological endotype driven by the constant release of organ injury-associated, endogenous alarmins, and microbial products from secondary infections. While this syndrome can develop as a result of a diverse set of pathologies, it represents a shared outcome with a unique underlying pathobiological mechanism. Despite being a common outcome, there are no therapeutic interventions other than supportive therapies for this common disorder. Only through an improved understanding of the immunological endotype of PICS can rational therapeutic interventions be designed.
A Novel Function of TLR2 and MyD88 in the Regulation of Leukocyte Cell Migration Behavior During Wounding in Zebrafish Larvae

Toll-like receptor (TLR) signaling via myeloid differentiation factor 88 protein (MyD88) has been indicated to be involved in the response to wounding. It remains unknown whether the putative role of MyD88 in wounding responses is due to a control of leukocyte cell migration. The aim of this study was to explore in vivo whether TLR2 and MyD88 are involved in modulating neutrophil and macrophage cell migration behavior upon zebrafish larval tail wounding. Live cell imaging of tail-wounded larvae was performed in tlr2 and myd88 mutants and their corresponding wild type siblings. In order to visualize cell migration following tissue damage, we constructed double transgenic lines with fluorescent markers for macrophages and neutrophils in all mutant and sibling zebrafish lines. Three days post fertilization (dpf), tail-wounded larvae were studied using confocal laser scanning microscopy (CLSM) to quantify the number of recruited cells at the wounding area. We found that in both tlr2–/– and myd88–/– groups the recruited neutrophil and macrophage numbers are decreased compared to their wild type sibling controls. Through analyses of neutrophil and macrophage migration patterns, we demonstrated that both tlr2 and myd88 control the migration direction of distant neutrophils upon wounding. Furthermore, in both the tlr2 and the myd88 mutants, macrophages migrated more slowly toward the wound edge. Taken together, our findings show that tlr2 and myd88 are involved in responses to tail wounding by regulating the behavior and speed of leukocyte migration in vivo.
Extended series expansions for random sequential adsorption

We express the coverage (occupation fraction) θ in powers of time t for four models of two-dimensional lattice random sequential adsorption (RSA) to very high orders by improving an algorithm developed by the present authors [J. Phys. A 29, L177 (1996)]. Each of these series is, to the best of our knowledge, the longest at the present. We analyze the series and deduce accurate estimates for the jamming coverage of the models.
Detecting Unexpected Faults of High-Speed Train Bogie Based on Bayesian Deep Learning

The health management of railway vehicles is crucial to secure safety and efficiency in the long-term operation of high-speed trains. Meanwhile, complex components put forward a higher requirement for the robustness of condition monitoring systems, especially abilities to identify unexpected faults. The misidentification of infrequent faults could lead to unpredictable consequences for the vehicle's safety. This paper proposes a novel method for detecting unexpected faults of high-speed train bogie based on Bayesian deep learning. First, a Monte Carlo-Based perturbation is imposed on input samples, which can magnify the difference between unexpected faults and known ones. Then, through dropout-based Bayesian deep learning, the diagnosis result can be obtained as well as a Bayesian indicator of whether the anomalies belong to known classes. The proposed method can capture the uncertainty of model outputs and identify unexpected faults, requiring only a few samples of unexpected anomalies for calibration. Also, it is compatible with most existing neural network structures. The experiments compare the proposed method with existing methods on two real-world applications, which demonstrates the effectiveness and superiority of the proposed scheme.
Influence of the Methane–Zeolite a Interaction Potential on the Concentration Dependence of Self-Diffusivity

Studies on the diffusion of methane in a zeolite structure type LTA (as per IZA nomenclature) have indicated that different types of methane–zeolite potentials exist in the literature in which methane is treated within the united-atom model. One set of potentials, referred to as model A, has a methane oxygen diameter of 3.14 Å, while another set of potential parameters, model B, employs a larger value of 3.46 Å. Fritzsche and co-workers (1993) have shown that these two potentials lead to two distinctly different energetic barriers for the passage of methane through the eight-ring window in the cation-free form of zeolite A. Here, we compute the variation of the self-diffusivity (D) with loading (c) for these two types of potentials and show that this slight variation in the diameter changes the concentration dependence qualitatively: thus, D decreases monotonically with c for model A, while D increases and goes through a maximum before finally decreasing for model B. This effect and the surprising congruence of the diffusion coefficients for both models at high loadings is examined in detail at the molecular level. Simulations for different temperatures reveal the Arrhenius behaviour of the self-diffusion coefficient. The apparent activation energy is found to vary with the loading. We conclude that beside the cage-to-cage jumps, which are essential for the migration of the guest molecules, at high concentrations migration within the cage and guest–guest interactions with other molecules become increasingly dominant influences on the diffusion coefficient and make the guest–zeolite interaction less important for both model A and model B.
Accurate Detection of COVID-19 Using K-EfficientNet Deep Learning Image Classifier and K-COVID Chest X-Ray Images Dataset

Our present work allows efficient detection of COVID-19 from chest X-Rays at a level exceeding practicing radiologists. The algorithm uses the architecture EfficientNet extended and named K-EfficientNet. The K-EfficientNet is associated with progressive resizing, which resizes the images from $112\times 112$ to $224\times 224$ during the training process. By combining six publicly available and independent datasets, we get a large dataset named K-COVID containing 14,124 X-Rays images of patients affected by Pneumonia or COVID-19 and patient with Normal X-Ray images. The application of transfer learning on the ImageNet dataset and data augmentation allows us to achieve 97.3% accuracy and 100% sensitivity, and 100% Positive Predictive Value on COVID-19 detection.
The molecular structure and elemental composition of humic substances from Albeluvisols

The structure of humic and fulvic acids from a Siltic Albeluvisol and a Stagni-Histic Albeluvisol (Siltic) was studied. It was found that the development of hydromorphism results in the enrichment of humic substances with aliphatic fragments. The presence of unoxidised aliphatic fragments in the structure of humic substances, in combination with anaerobic conditions, favours the gley process in the Stagni-Histic Albeluvisol (Siltic). Features of the structural composition of humic substances are related to the humification rate: this process is slowed in northern regions and accelerated in southern regions, where humic substances are more humified.
The Quiet Project – UK Acoustic Community’s response to COVID19 during the easing of lockdown

Abstract The COVID-19 lockdown created a new kind of environment both in the UK and globally, never experienced before or likely to occur again. A vital and time-critical working group was formed with the aim of gathering crowd-source high quality baseline noise levels and other supporting information across the UK during the lock-down and subsequent periods. The acoustic community were mobilised through existing networks engaging private companies, public organisations and academics to gather data in accessible places. In addition, pre-existing on-going measurements from major infrastructure projects, airport, and planning applications were gathered to create the largest possible databank. A website was designed and developed to advertise the project, provide instructions and to formalise the uploading of noise data, observations and soundscape feedback. Two case studies gathered in the latter stage of full lockdown are presented in the paper to illustrate the changes in the environmental noise conditions relative to transport activity. Ultimately the databank will be used to establish the relation to other impacts such as air quality, air traffic, economic, and health and wellbeing. As publicly funded research the databank will be made publicly available to assist future research.
Comparative Investigation of Supersaturation and Automated Direct Nucleation Control of Crystal Size Distributions using ATR-UV/vis Spectroscopy and FBRM

The paper presents a thorough evaluation of different control strategies used in cooling crystallization, namely, unseeded linear cooling, seeded linear cooling, supersaturation control, and automated direct nucleation control. The sensitivity and robustness of supersaturation and automated direct nucleation control approaches are evaluated by varying different process parameters, such as seed loading and heating and cooling rates for the crystallization of paracetamol in isopropyl alcohol. The supersaturation control approach uses concentration information provided by ATR-UV/vis spectroscopy, while the direct nucleation control approach is based on focused beam reflectance measurements. Various statistics were used to assess the performance of each approach and it has been shown that the automated direct nucleation control approach, which requires no prior information about the system, outperformed the other control strategies. For the paracetamol in isopropyl alcohol system, significant variations were .
Decrease of cholesterol content in milk by sorption onto β-cyclodextrin crosslinked with tartaric acid; considerations and implications

Abstract Elevated cholesterol intake can induce the development of cardiovascular diseases in man, especially with long term animal origin foods consumption. Therefore, this work deals with the possibility of cholesterol content decrease in milk applying β-cyclodextrin crosslinked with tartaric acid (βCDcTA) as a removal agent. Evaluation of statistic data on food consumption in the Slovak Republic in 2018 aimed at total cholesterol daily intake and effects of “milky” cholesterol content decrease on total cholesterol balance. During the experiments, various amounts of βCDcTA addition to milk were studied resulting in optimal 5 % addition resulting in the cholesterol content decrease by 85.4 % in comparison to original cholesterol content. For monitoring purposes, an HPLC method analysing cholesterol content in saponified milk was employed. The food consumption data analysis showed that total per capita daily cholesterol intake was 369.8 mg, from which 86 mg was assigned to the cholesterol contained in milk and dairy products while the application of cholesterol removal procedure could decrease the total per capita daily cholesterol intake to 296.3 mg (“milky” cholesterol amount equal to 12.6 mg), which in below the recommended value of 300 mg daily intake still valid in the Slovak Republic. This approach might prove as a meaningful step to weaken health problems associated with high long term intake of cholesterol contained in foods of animal origin.