Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic characterization of intramuscular myxomas

Introduction: Intramuscular myxomas are benign tumors that are challenging to diagnose, especially on core needle biopsies. Acquired chromosomal aberrations and pathogenic variants in codon 201 or codon 227 in GNAS complex locus gene (GNAS) have been reported in these tumors. Here we present our genetic findings in a series of 22 intramuscular myxomas. Materials and methods: The tumors were investigated for the presence of acquired chromosomal aberrations using G-banding and karyotyping. Pathogenic variants in codon 201 or codon 227 of GNAS were assessed using direct cycle Sanger sequencing and Ion AmpliSeq Cancer Hotspot Panel v2 methodologies. Results: Eleven tumors carried chromosomal abnormalities. Six tumors had numerical, four had structural, and one had both numerical and structural chromosomal aberrations. Gains of chromosomes 7 and 8 were the most common abnormalities being found in five and four tumors respectively. Pathogenic variants in GNAS were detected in 19 myxomas (86%) with both methodologies. The detected pathogenic variants were p.R201H in nine cases (seven with abnormal and two with normal karyotypes), p.R201C in five cases, all with normal karyotypes, p.R201S in three cases (two with abnormal and one with normal karyotype), p.R201G in one case with a normal karyotype, and p.Q227E in one case with a normal karyotype. Conclusion: Firstly, our data indicate a possible association between chromosomal abnormalities and GNAS pathogenic variants in intramuscular myxomas. Secondly, the presence of the rare pathogenic variants R201S, p.R201G and p.Q227E in 26% (5 out of 19) of myxomas with GNAS pathogenic variants shows that methodologies designed to detect only the common “hotspot” of p.R201C and p.R201H will give false negative results. Finally, a comparison between Ion AmpliSeq Cancer Hotspot Panel v2 and direct cycle Sanger sequencing showed that direct cycle Sanger sequencing provides a quick, reliable, and relatively cheap method to detect GNAS pathogenic variants, matching even the most cutting-edge sequencing methods.
Carnitine Deficiency in Intensive Care Unit Patients Undergoing Continuous Renal Replacement Therapy: A Single-center Retrospective Study

Introduction: Carnitine deficiency is common in patients undergoing intermittent hemodialysis and may also occur during continuous renal replacement therapy (CRRT). We evaluated intensive care unit (ICU) patients undergoing CRRT for carnitine deficiency and its associated risk factors. Methods: This was a single-center, retrospective, observational study performed between June 2019 and March 2020. The primary outcome was the incidence of carnitine deficiency in ICU patients undergoing CRRT. Results: Eighty-eight patients underwent 103 blood carnitine concentration measurements. The median age was 68 years (interquartile range: 55-80), Acute Physiology and Chronic Health Evaluation II score was 28 (24-33), Sequential Organ Failure score was 8.5 (5-11), Nutrition Risk in Critically Ill score was 6 (5-7), and blood carnitine concentration was 66.1 μmol/L (51.8-83.3). In total, 34 of 88 patients (38.6%) were found to have carnitine deficiency; however, there was no significant difference in the proportions of patients with carnitine deficiency characterized by disease. CRRT was performed in 44 (50%) patients, and the median blood total carnitine concentration measured after 24 h of CRRT without changing the settings was 65.5 μmol/L (48.6-83.3). The purification volume of CRRT and blood carnitine concentration were negatively correlated (R = −0.63; P = 0.02). Conclusions: Carnitine deficiency is seen in patients receiving CRRT and may increase in incidence as the purification volume increases, requiring regular monitoring.
The effects of Ca++ on the strength of polycrystalline ice

ABSTRACT Recent studies have suggested a physical link between Ca++ ions and an increase in the ductility or ‘softening’ of polycrystalline ice. In order to investigate the potential effects of Ca++ on deformation, we created sets of both undoped and CaSO4-doped specimens of polycrystalline ice for testing in uniaxial tension or compression. Deformation tests in tension were carried out under a constant load at an initial stress of 0.75 MPa and a temperature of −6°C. Compression tests were carried out at −10 and −20°C at constant strain rates of 1×10−4 s−1, 1 × 10−5 s−1 and 1 × 10−6 s−1 and taken to 5% strain. Our results show that CaSO4 increases the strength of polycrystalline ice at higher strain rates and lower temperatures, an effect that decreases with decreasing strain rate and higher temperatures. A microstructural analysis of the post-test compression specimens reveals mean grain diameters much larger in the CaSO4-doped specimens tested at the lowest applied strain rate of 1 × 10−6 s−1. Precipitates were found to have formed along grain boundaries in some doped specimens and evidence of intergranular fracture was observed in all specimens tested at 1 × 10−4 and 1 × 10−5 s−1. In tension-tested specimens, there was no difference in the mean grain diameter between doped and undoped specimens at 25% strain.
Study of Addition Metal (Ti, Zn) Dopan on the Structure of NASICON as Solid Electrolyte Batteries

This study aims to analysized the effect of addition doped metal (Ti and Zn) on NASICON structure to morphology, materials structure, and electrochemical performance especially ionic conductivity properties. NASICON is a sodium super ionic conductor that it could be as solid electrolyte batteries. One of the problems that exist in the secondary battery is the low working temperature of the electrolyte, which makes it easy to explode when exposed to free air. The common electrolyte in liquid phase, so NASICON as replacement alternative. The synthesis method used is the solid-state reaction method by mixing sodium carbonate, silicon dioxide, zirconium oxide, ammonium dihydrogen phosphate, doped metal (titanium oxide and zinc oxide) and some anhydrous ethanol into a planetary ball mill, dried then calcined. Then the material is pressed to produce pellets and the sintered. The doping used varies from 0 to 5 mol% of titanium and zinc. XRD results showed that all variations in titanium doped had found rhombohedral and monoclinic. whereas in zinc doping also have those phase. The highest ionic conductivity is 7.8x10-3 S/m on 2% mol Zinc Addition
A New Prediction Algorithm Based on Local Neighbor Closeness and Influence of Node

Link prediction in complex networks has been one of the important issue within the realm of data mining and science analysis. Therefore, it wins an increasing attention and many link prediction based on similarity-based algorithm have proposed so far. The traditional similarity-based algorithms only make use of common neighbors having many shared feature to predict the future structure in complex network, but it ignored the influence of predicting nodes. The greater the influence of node the higher the likelihood that the node will be selected as future links between two ends. In this paper, an efficient method is proposed by combining influence of predicting nodes and clustering coefficient of common neighbors to improve the accuracy and applicability of link prediction for complex networks. The influence of nodes can be expressed by node centrality, which is a local centrality to identify influential nodes by combining the degree of the target node and clustering coefficients of second-order neighbors. A comparison between the proposed method and other similarity-based algorithms has been performed, and results have been reported for nine real-world datasets. The results further validate that had a higher prediction accuracy compared with other link prediction approaches.
Development of Ankle-Foot Orthosis Using Servo Motor with On-Off Control System for Drop-Foot

This research addresses the imperative need for a lightweight, compact, and efficient design of an Active Ankle-Foot Orthosis (AFO), with the potential for everyday use and enhancement of gait cycles in individuals with drop-foot. The proposed AFO employs a servo motor to generate ankle moments based on gait phase detection, ensuring low power consumption and a structurally lightweight configuration. The study encompasses a kinematic analysis of the gait mechanism utilizing a graphical method, facilitating the determination of the requisite force for the motor actuator. Additionally, a finite element approach is employed to assess the strength of linkages. The connecting mechanism utilizes Poly (methyl methacrylate) or PMMA board due to its lightweight nature and ease of fabrication. Based on the simulation result, the minimum safety factor of link bars was 1.8. While, based on the kinematic analysis, the minimum required torque that should be provided by the servo motor is 3.838 Nm. The servo motor serves as the active element within the AFO, and an on-off control system, driven by a rotary encoder detecting gait phases, governs the AFO's movement. Ankle joint angle readings obtained through AFO implementation exhibit values within the range of normal individuals. The entire control system operates with remarkably low power consumption, registering at 0.06 W over one running cycle. Based on these analyses, a prototype has been developed for further evaluation in patient trials, underscoring the potential efficacy and practicality of the proposed active AFO design.
Development of Liquid Organic Hydrogen Carriers for Hydrogen Storage and Transport

The storage and transfer of energy require a safe technology to mitigate the global environmental issues resulting from the massive application of fossil fuels. Fuel cells have used hydrogen as a clean and efficient energy source. Nevertheless, the storage and transport of hydrogen have presented longstanding problems. Recently, liquid organic hydrogen carriers (LOHCs) have emerged as a solution to these issues. The hydrogen storage technique in LOHCs is more attractive than those of conventional energy storage systems like liquefaction, compression at high pressure, and methods of adsorption and absorption. The release and acceptance of hydrogen should be reversible by LOHC molecules following favourable reaction kinetics. LOHCs comprise liquid and semi-liquid organic compounds that are hydrogenated to store hydrogen. These hydrogenated molecules are stored and transported and finally dehydrogenated to release the required hydrogen for supplying energy. Hydrogenation and dehydrogenation are conducted catalytically for multiple cycles. This review elaborates on the characteristics of different LOHC molecules, based on their efficacy as energy generators. Additionally, different catalysts used for both hydrogenation and dehydrogenation are discussed.
Probabilistic Adaptive Slow Feature Analysis for State Estimation and Classification

Slow feature analysis (SFA), as a method for learning slowly varying features in classification and signal analysis, has attracted increasing attention in recent years. It is guaranteed to find the optimal solution within a family of transformations and can learn to extract a large number of such “slow” features that are additionally orthogonal. While being effective, SFA suffers from three major shortcomings. First, it is not adaptive, in that the notion of “slowness” is fixed to be the average of the squared derivative of a signal. Second, its formulation assumes deterministic features/observations, which renders it ineffective for applications involving stochastic features/measurement uncertainties. Third, SFA is not necessarily suited for nonlinear processes. In this work, all these issues are addressed by proposing adaptive SFA and its probabilistic version, termed the ASFA and probabilistic ASFA (PASFA), respectively. The ASFA essentially introduces an optimally tunable filter that accommodates task-dependent slowness. We provide guidelines and a procedure for tuning the ASFA filter for a given application. We prove that linear SFA is a special case of ASFA for a specific choice of filter and demonstrate that it outperforms the standard SFA. PASFA extends ASFA to accommodate measurement and process noises, wherein the features are modeled as filtered Gaussian white noise (GWN) sequences, and the measurement noise is assumed to be GWN. Furthermore, it accommodates nonlinear generative models. A variational expectation-maximization (EM) algorithm is used for estimating the filter parameters and the statistical properties of noise sequences. Frequency-domain interpretations of ASFA are also provided to enhance interpretability. Case studies involving applications to signal analysis and classification are presented to demonstrate the effectiveness and superiority of the proposed methods.
Summarizing Financial Reports with Positional Language Model

Financial reports are essential for the decision-making processes of various stakeholders, containing vast amounts of both quantitative and qualitative data. As the business world becomes increasingly intricate, stakeholders require a swift means to understand a company’s financial status. Text summarization is a useful tool in this regard, aiming to present long texts concisely without losing their essence. Given the complexity and the structured nature of financial documents, summarizing them poses a significant challenge. This paper suggests a method employing Positional Language Models (PLMs), a subset of non-neural language models that assess the sequence of tokens in input data, for financial report summarization. Our proposed method is unsupervised, eliminating the need for training and ensuring computational efficiency for lengthy documents.
Using a Mixed-Method Approach to Explore the Factors Influencing the Family Resilience of Stroke Survivors in China

Background Stroke is a critical public health issue in China that necessitates a closer examination of family resilience (defined here as the collective capacity of individuals, families and communities to effectively navigate challenges, recover from adverse events and foster positive adaptation). Amid rising stroke incidence, this study addresses the dearth of research on family resilience among stroke survivors in China, aiming to assess its level, identify influencing factors and establish coping strategies for family caregivers. Methods This mixed-methods research employed a sequential explanatory design. Questionnaires were distributed to 258 stroke survivors and their family members at outpatient follow-up visits. In the first stage (ie the quantitative research stage), the research tools for data collection included a general demographic sociological data questionnaire, the Family Resilience Assessment Scale (FRAS), the Self-Efficacy for Managing Chronic Disease 6-Item Scale, the Caregiver Burden Scale, the Family Functioning Scale and the Social Support Rating Scale. Quantitative data were analysed using IBM SPSS 26.0 software, utilising descriptive statistics for summarising sociodemographic characteristics and conducting analyses, such as independent-sample t-tests, one-way analysis of variance and Spearman correlation analysis. The second stage (ie the qualitative research stage) involved complementing and validating the data, developing a quantitative–qualitative interview framework and selecting participants for interviews. Colaizzi’s seven-step analysis was applied to analyse interview data. In the third stage, the quantitative and qualitative research results were integrated, and a comprehensive analysis was performed to obtain an accurate conclusion. Results A total of 242 families responded to the questionnaire (response rate: 93.8%). In total, the mean age of stroke survivors was 61.86 ± 8.76 years old, and 69.8% were male. The quantitative results showed that the FRAS mean score was (185.33 ± 24.78), which was above the medium level. The multiple linear regression analysis confirmed that family function was the strongest influencing factor on family resilience (β = 0.948, p < 0.01). The qualitative analysis revealed four themes of family adaptation experience: loss of independence and certainty, facing threats and challenges, seeking family advantage resources and adopting coping strategies. Conclusion This hybrid study sheds light on the adaptation process of the families of stroke survivors, revealing family function as the primary influencer of resilience. Recognising that eliminating risk factors is challenging, our suggestion is for clinical practitioners to emphasise family strengths and implement resilience-oriented interventions. Focusing on enhancing coping abilities and fostering adaptation within families can aid in the rehabilitation process, promoting the well-being and growth of both the family unit and individual members, while alleviating caregiver burden.
Analysis of the error in an iterative algorithm for asymptotic regulation of linear distributed parameter control systems

Applications of regulator theory are ubiquitous in control theory, encompassing almost all areas of systems and control engineering. Examples include active noise suppression [Banks et al., Decision and Control, Active Noise Control: Piezoceramic Actuators in Fluid/structure Interaction Models, IEEE, Los Alamitos, CA (1991) 2328–2333], design and control of energy efficient buildings [Borggaard et al., Control, Estimation and Optimization of Energy Efficient Buildings. Riverfront, St. Louis, MO (2009) 837–841. ] and control of heat exchangers [Aulisa et al., IFAC-PapersOnLine 49 (2016) 104–109. ]. Numerous other examples can be found in [Aulisa and Gilliam, A Practical Guide to Geometric Regulation for Distributed Parameter Systems. Chapman and Hall/CRC, Boca Raton (2015). ]. In the geometric approach to asymptotic regulation the main object of interest is a pair of operator equations called the regulator equations, whose solution provides a control solving the tracking/disturbance rejection regulation problem. In this paper we present an iterative algorithm, called the β-iteration method, which is based on the geometric methodology, and delivers accurate control laws for approximate asymptotic regulation. This iterative scheme has been successfully applied to a wide range of linear and nonlinear multi-physics examples and in practice only one or two iterations are usually required to deliver sufficiently accurate results. One drawback to these research efforts is that no proof was given of the convergence of the method. This work contains a detailed analysis of the error in the iterative scheme for a large class of linear distributed parameter systems. In particular we show that the iterative errors converge at a geometric rate. We demonstrate our estimates on three control problems in multi-physics applications.
The Fear of Covid-19 and Perceived Employability Effect on Emotional Exhaustion and Work Engagement: The Mediating Role of Job Insecurity

Frontline workers are one of the jobs affected due to Covid-19. Covid-19 events can have negative and positive consequences for frontline workers. This study aims to see how fear of covid affects employee emotional exhaustion during a pandemic. Based on the conservation of resources theory, fear of covid-19 can cause frontline workers to experience emotional exhaustion. In addition, during a pandemic, employees can feel high job insecurity, resulting in low work engagement in the company where employees work. The method used in this research is quantitative. Data analysis was performed on 259 company employees who worked as frontline workers using the Structural Equation Modeling technique. The results of the analysis show that fear of covid-19 has a positive effect on job insecurity, and job insecurity has a significant positive effect on emotional exhaustion. In addition, perceived employability has a positive and significant effect on job insecurity and a significant positive effect on work engagement. It is essential for companies to pay attention so that employees do not have high job insecurity and high emotional exhaustion and can create employee work engagement by conducting various kinds of training and health education to increase engagement and reduce employee fear of Covid.
Preparation of genetically or chemically engineered exosomes and their therapeutic effects in bone regeneration and anti-inflammation

The treatment of bone or cartilage damage and inflammation-related diseases has been a long-standing research hotspot. Traditional treatments such as surgery and cell therapy have only displayed limited efficacy because they can’t avoid potential deterioration and ensure cell activity. Recently, exosomes have become a favorable tool for various tissue reconstruction due to their abundant content of proteins, lipids, DNA, RNA and other substances, which can promote bone regeneration through osteogenesis, angiogenesis and inflammation modulation. Besides, exosomes are also promising delivery systems because of stability in the bloodstream, immune stealth capacity, intrinsic cell-targeting property and outstanding intracellular communication. Despite having great potential in therapeutic delivery, exosomes still show some limitations in clinical studies, such as inefficient targeting ability, low yield and unsatisfactory therapeutic effects. In order to overcome the shortcomings, increasing studies have prepared genetically or chemically engineered exosomes to improve their properties. This review focuses on different methods of preparing genetically or chemically engineered exosomes and the therapeutic effects of engineering exosomes in bone regeneration and anti-inflammation, thereby providing some references for future applications of engineering exosomes.
Coastal terraces and Holocene sea-level changes along the Patagonian Atlantic coast

The results of morphological, pedostratigraphical, and geochronological studies of marine terraces along the Patagonian Atlantic coast are reported in this work. There is evidence for the preservation of up to three Last Interglacial, and at least three Penultimate Interglacial beach ridge systems as well as several levels of Holocene beach ridges. Towards the interior, these beach ridges are frequently bordered by elevated beach deposits from the Middle and Early Pleistocene / Late Pliocene (Schellmann, 1998a, b). The various Holocene shorelines are due to different stages of relative sea-level lowering since the Middle Holocene transgression maximum. The relative sea-level seemed to decline continuously during the Middle and Late Holocene. However, this decline may have been interrupted by a significant high tide water level rise in the early Late Holocene (around 2,700 14 C BP; not calibrated). The equivalent sea-level changes cannot be accurately quantified through raised beach ridge systems since their altitudes mainly depend on wave extension and therefore on storm frequency and strength. The elevation of fluvial terraces at the mouths of dry valleys with periodic runoff ('Canadones') is a better indicator for sea-level reconstruction. Dry valleys are adjusted to the present high tide water level, while terrace surfaces are adjusted to a high tide water level (hTw) at the time of their formation. Beach deposits are intertwined with fluvial sediments near the coast. These marine insertions often contain articulated shells, which allow for a numeric dating of modern and fossil hTw. Fluvio-littoral terraces were dated near Camarones and suggest a 5 ± 1 m increase of the hTw during the Holocene transgression maximum (about 6,600 14 C years ago). Sea-level declined to about 3 ± 1 m above the present hTw about 5,800 14 C years ago.