Miracle-dz/UniFAR-FTUs huggingface dataset:
First-principles study of thermodynamic stability and mechanical properties of fifteen high-entropy quaternary metal disilicides

By combining first-principles density-functional calculations and thermodynamics, we investigated the thermodynamic stability and mechanical properties of 15 quaternary high-entropy metal disilicides composed of silicon and four of the six refractory transition metals Ti, Zr, Hf, V, Nb, and Ta. We constructed a three-dimensional diagram specified by two thermodynamic parameters (the mixing enthalpy and the ratio of the entropy term in the Gibbs free energy to enthalpy) and a structural parameter (the lattice size difference). The obtained diagram allows us to predict that, except for TiZrHfVSi8, the formation of all other fourteen single-phase metal disilicides is thermodynamically favorable. Our calculations show that, for the formation of each of the 14 metal disilicides, the driving force suppresses the resistance at temperatures well below the melting point, suggesting that it is feasible to synthesize these high-entropy materials. One of these (TiHfNbTaSi8) has already been experimentally realized. Furthermore, the values of the mechanical parameters and melting points of the predicted fourteen quaternary high-entropy metal disilicides are all greater than the corresponding average values of the four single-metal disilicides.
Diversity and host specificity of Borrelia burgdorferi’s outer surface protein C (ospC) alleles in synanthropic mammals, with a notable ospC allele U absence from mixed infections

ABSTRACT Interactions among pathogen genotypes that vary in host specificity may affect overall transmission dynamics in multi-host systems. Borrelia burgdorferi, a bacterium that causes Lyme disease, is typically transmitted among wildlife by Ixodes ticks. Despite the existence of many alleles of B. burgdorferi’s sensu stricto outer surface protein C (ospC) gene, most human infections are caused by a small number of ospC alleles [“human infectious alleles” (HIAs)], suggesting variation in host specificity associated with ospC. To characterize the wildlife host association of B. burgdorferi’s ospC alleles, we used metagenomics to sequence ospC alleles from 68 infected individuals belonging to eight mammalian species trapped at three sites in suburban New Brunswick, New Jersey (USA). We found that multiple allele (“mixed”) infections were common. HIAs were most common in mice (Peromyscus spp.) and only one HIA was detected at a site where mice were rarely captured. ospC allele U was exclusively found in chipmunks (Tamias striatus), and although a significant number of different alleles were observed in chipmunks, including HIAs, allele U never co-occurred with other alleles in mixed infections. Our results suggest that allele U may be excluding other alleles, thereby reducing the capacity of chipmunks to act as reservoirs for HIAs.
Developing subsurface energy exploitation strategies by considering seismic risk

The injection or extraction of fluids in the subsurface for energy purposes (e.g. geothermal exploitation, CO2 storage or geological energy storage) requires both the operation efficiency and the associated environmental risks to be assessed and controlled. Even though scientific and technological progress allows more accurate 3D modelling of the subsurface, we still do not have a thorough understanding of coupled underground hydromechanical processes. Indeed, the injection or production of fluids interacting with existing geological features can still result in unintended and unexpected ‘harmful’ consequences. This review aims to propose a unified strategy ranging from an understanding of the hydromechanical factors at the origin of the induced seismicity to seismic risk evaluation expressed in terms of ground-motion effects. The challenge is to utilize mechanical modelling to anticipate the evolution of seismicity; how the population perceives this is also an important factor to be taken into account in this risk evaluation. While mechanical modelling may include some degree of uncertainty, probabilistic analysis is capable of providing a quantitative estimation of the risk incurred and feedback to the exploitation strategy.
Algorithms for Modeling Mass Movements and their Adoption in Social Networks

Online social networks have become a staging ground for many modern movements, with the Arab Spring being the most prominent example. In an effort to understand and predict those movements, social media can be regarded as a valuable social sensor for disclosing underlying behaviors and patterns. To fully understand mass movement information propagation patterns in social networks, several problems need to be considered and addressed. Specifically, modeling mass movements that incorporate multiple spaces, a dynamic network structure, and misinformation propagation, can be exceptionally useful in understanding information propagation in social media. This dissertation explores four research problems underlying efforts to identify and track the adoption of mass movements in social media. First, how do mass movements become mobilized on Twitter, especially in a specific geographic area? Second, can we detect protest activity in social networks by observing group anomalies in graph? Third, how can we distinguish real movements from rumors or misinformation campaigns? and fourth, how can we infer the indicators of a specific type of protest, say climate related protest? A fundamental objective of this research has been to conduct a comprehensive study of how mass movement adoption functions in social networks. For example, it may cross multiple spaces, evolve with dynamic network structures, or consist of swift outbreaks or long term slowly evolving transmissions. In many cases, it may also be mixed with misinformation campaigns, either deliberate or in the form of rumors. Each of those issues requires the development of new mathematical models and algorithmic approaches such as those explored here. This work aims to facilitate advances in information propagation, group anomaly detection and misinformation distinction and, ultimately, help improve our understanding of mass movements and their adoption in social networks. Algorithms for Modeling Mass Movements and their Adoption in Social Networks
Antiretroviral therapy and HIV‐associated cardiovascular disease: a prospective cardiac biomarker and CMR tissue characterization study

Abstract Aims Biochemical markers are fundamental in cardiac evaluation, and various novel assays have recently been discovered. We prospectively evaluated the hearts of newly diagnosed people living with human immunodeficiency virus (PLWH) using cardiac biomarkers, compared them with human immunodeficiency virus (HIV)‐uninfected controls, and correlated our prospective findings with cardiovascular magnetic resonance imaging (CMR). Methods and results Newly diagnosed, antiretroviral therapy (ART)‐naïve PLWH were recruited along with HIV‐uninfected, age‐matched, and sex‐matched controls. All participants underwent measurement of high‐sensitivity cardiac troponin T (hs‐cTnT), N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP), soluble ST2 (sST2), and galectin‐3, as well as a CMR study with multiparametric mapping. The HIV group started ART and was re‐evaluated 9 months later. The cardiac biomarkers and their correlation with CMR parameters were evaluated in and between groups. Compared with controls (n = 22), hs‐cTnT (4.0 vs. 5.1 ng/L; P = 0.004), NT‐proBNP (23.2 vs. 40.8 ng/L; P = 0.02), and galectin‐3 (6.8 vs. 9.0 ng/mL; P = 0.002) were all significantly higher in the ART‐naïve group (n = 73). After 9 months of ART, hs‐cTnT (5.1 vs. 4.3 ng/L; P = 0.02) and NT‐proBNP (40.8 vs. 28.5 ng/L; P = 0.03) both decreased significantly and a trend of decrease was seen in sST2 (16.5 vs. 14.8 ng/L; P = 0.08). Galectin‐3 did not demonstrate decrease over time (9.0 vs. 8.8 ng/mL; P = 0.6). The cardiac biomarkers that showed the best correlation with CMR measurements native T1, T2, and extracellular volume were NT‐proBNP (r s ≥ 0.4, P < 0.001) and galectin‐3 (r s ≥ 0.3, P < 0.01). Conclusions Our cardiac biomarker data support the presence of subclinical myocardial injury, remodelling, and fibrosis at HIV diagnosis, and ART had a positive influence on these blood markers. It remains unclear if the underlying pathological processes were fully addressed by ART. The ability of cardiac biomarkers to detect and track tissue abnormalities diagnosed with CMR showed promise. With additional research, this could lead to improvements in screening and monitoring myocardial abnormalities, even in CMR‐limited settings.
Social media analysis, Twitter and the London Olympics (a research note)

During the course of this paper we examine publically available social media data that relates to the London 2012 Olympic Games that has been harvested and analysed using the Cardiff Online Social Media ObServatory (COSMOS). Social media has matured sufficiently in terms of user uptake and incorporation into traditional media platforms and outlets that the recent London Olympics has been described as the first social media games. For example, the BBC used the Twitter stream to incorporate and mobilise audience participation into its Olympic coverage. With this in mind, this paper will explore the analysis of social media data in relation to sporting events and social media use. In doing so we identify the ways in which COSMOS can be used to identify hashtag popularity over a specific time period to identify real world events, in this case ‘Super Saturday’. The paper reports on indicative evidence that links real-world sporting events to spikes in real time populations’ reaction through self-reported social media updates. In turn, the paper provides an analysis of frequency and sentiment of tweets containing the most popular UK hashtag connected to the London 2012 Olympics over a specified time period. This has consequences for conceptualising the relationship between social actors, events and social media and methodological strategies for understanding the dynamic (locomotive) reactions of populations.
Implementing Systemwide Physician Change Management in an Integrated Health Care Setting: Improving Physician Participation in an Advanced Care at Home Model

Abstract Introduction Advanced Care at Home is a clinical model that delivers hospital-level care in a patient’s home. This model of care has been studied for decades, but there have been difficulties scaling the model to a higher census because of poor physician participation. Kaiser Permanente at Home, an Advanced Care at Home model created by Kaiser Permanente Northwest, was able to quickly increase its patient census by using several different change management interventions. The aim of this study was to describe the specific physician change management interventions used and to determine their relative impacts on physician participation with Kaiser Permanente at Home. Methods This study used a retrospective qualitative approach. Hospitalist and emergency department (ED) physicians completed an online survey in December 2021. This was followed by focused, one-on-one interviews that were held in February 2022. Content analysis was performed using a general inductive approach to identify core themes. Results Of 78 ED and 79 hospitalist physicians recruited, 35% submitted responses. Of these respondents, 16 (29%) were ED physicians, and 39 (61%) were hospitalist physicians. Of these respondents, 90% rated Kaiser Permanente at Home favorably over the course of a year. More than 90% of respondents rated a combination of multiple approaches as impactful, but respondents overwhelmingly noted that physician-to-physician engagement was the most important (51%). Conclusion In the development of the Kaiser Permanente at Home, physicians highlighted that a multifactorial change management approach centered on peer-to-peer engagement had the most substantial effect on their participation, a process that could extend up to a year.
Determinants of under‐five pneumonia in randomly selected health facilities at Aleta Wondo Woreda, Sidama Region Ethiopia: Case–control study

Abstract Introduction Under‐five mortality reduction due to pneumonia is not Signiant, particularly in developing countries. Pneumonia contributed to 27.5% to 31.3% of health facility visits by children 2 to 59 months in Aleta Wondo Woreda. Previous studies have shown inconclusive evidence on determinants of pneumonia in children. Methods An institution‐based unmatched case–control study was conducted to assess determinants of pneumonia among under‐five children at Aleta Wondo Woreda, Sidama Region. Result One‐hundred forty‐five cases and 290 controls of children aged 2 to 59 months participated in the study. The mean ± (SD) age of the children was 18.81 months (2.1 ± 11.43) and 28.26 months (2.1 ± 16.007) for cases and controls, respectively. Only 56% (n = 145) of cases open house windows daily, whereas most 68.6% (n = 290) of controls house windows open daily. Ninety five (62.8%) of cases and 68.6% of controls were exclusively breastfed for 6 months. Household income ≥1500 Ethiopian birr (AOR = 0.45, 95% CI, 0.017–0.120, p < 0.000), child location outside of cooking house during cooking (AOR = 0.101, 95% CI, 0.43–0.238, p < 0.000), no formal education of the mother (AOR = 2.398, 95% CI, 1.082–5.316, p < 0.031), and presence of history of upper respiratory tract infections (URTIs) in last 2 weeks (AOR = 2.183, 95% CI, 1.684–5.273, P < 0.049) were determinants of pneumonia. Conclusion Determinants of pneumonia in under‐five children were multifactorial (socioeconomic, nutritional, and environmental). Addressing these factors by involving all relevant stakeholders is important to reduce pneumonia‐related morbidity and mortality among under‐five children in the study area.
The causal relationship between bacterial pneumonia and diabetes: a two-sample mendelian randomization study

ABSTRACT The escalating worldwide occurrence of diabetes mellitus, recognized as a chronic metabolic ailment contributing to an amplified global disease burden, has stimulated researchers to explore its etiology. Consequently, the study employed a two-sample Mendelian randomization (MR) methodology to examine the causal connection between bacterial pneumonia and diabetes, drawing upon the existing observational study that identified a potential association between bacterial pneumonia and diabetes. Furthermore, MR investigations suggest a reciprocal causal relationship between bacterial pneumonia and gestational diabetes mellitus(GDM), and a plausible causal link between bacterial pneumonia and T1DM. Background Previous observational studies have established the high prevalence of bacterial pneumonia in diabetic patients, which in turn leads to increased mortality. However, the presence of a causal connection between bacterial pneumonia and diabetes remains unobserved. Methods We chose genome-wide significant (Ρ < 1 × 10−5 and Ρ < 1 × 10−6) and independent (r2 < 0.001) single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs) to proceed a bidirectional two-sample MR study. The extracted SNPs explored the relationship between bacterial pneumonia and diabetes by Inverse variance weighted (IVW), MR-Egger, and weighted median methods. In addition, we conducted the Heterogeneity test, the Pleiotropy test, MR-presso and the Leave-one-out (LOO) sensitivity test to validate the reliability of results. Results In an MR study with bacterial pneumonia as an exposure factor, four different types of diabetes as outcome. It was observed that bacterial pneumonia increases the incidence of GDM (OR = 1.150 (1.027–1.274, P = 0.011) and T1DM (OR = 1.277 (1.024–1.531), P = 0.016). In the reverse MR analysis, it was observed that GDM (OR = 1.112 (1.023–1.201, P = 0.009) is associated with an elevated risk of bacterial pneumonia. However, no significant association was observed bacterial pneumonia with T1DM and other types of diabetes (P > 0.05). Conclusion This study utilizing MR methodology yields robust evidence supporting a bidirectional causal association between bacterial pneumonia and GDM. Furthermore, our findings suggest a plausible causal link between bacterial pneumonia and T1DM.
Simultaneous Single-Cell Measurements Demonstrate a Positive Correlation between RNA Copy Number for Mitochondrial Division and Fusion Genes and Mitochondrial Fragmentation

Summary Mitochondria are some of the most highly dynamic organelles in eukaryotic cells. The spatial distribution and morphology of mitochondria undergo constant changes via division and fusion to adapt to cellular conditions and to maintain various biological processes. However, how mitochondrial division and fusion are coordinated within a cell is currently unclear. Here, we performed microscopic observation using single-molecule ﬂuorescence in situ hybridization (smFISH) combined with immunostaining to simultaneously measure RNA molecules transcribed from mitochondrial division or fusion genes and the number of mitochondria in an individual cell. The RNA copy number in a single cell varied widely; with up to a 6–10 fold difference among cells. Notably, the expression levels of both types of genes seemed to be positively correlated with the number of fragmented mitochondria. Moreover, multiplexed smFISH imaging conﬁrmed that the expression levels of eight species of mitochondrial division and fusion genes were signiﬁcantly correlated in individual cells. These ﬁnd-ings suggest that the increased expression of mitochondrial division/fusion genes is likely to trigger the homog-enization of mitochondrial component molecules such as DNA, RNA, proteins, and lipids among mitochondria through structural remodeling via frequent division and fusion.
Decadal-to-interdecadal variability of precipitation in North China and associated atmospheric and oceanic anomaly patterns

This study investigates the decadal-to-interdecadal variability of precipitation in North China and associated atmospheric and oceanic anomaly patterns, with using records of precipitation at 26 stations over North China and global analysis data of ocean and atmosphere for the period 1951-1998 The variability of precipitation in North China over the past 50 years is characterized by the interdecadal oscillation with two regime shifts occurring in 1965 and 1980, especially resulting in a severe drought in the 1980s. The lag and simultaneous correlations between precipitation in North China and selected variables for the global ocean and atmosphere are computed on the decadal-to-interdecadal time scales (8 years and longer). Such correlations suggest a framework for the relationship of the precipitation anomaly in North China with the thermal anomalies in surrounding oceans and the regional atmospheric circulation anomalies. Under the framework, the Pacific inter-Decadal Oscillation (PDO) plays an important role in occurrence of the decadal-to-interdecadal drought or flood in North China. During the drought period, the sea surface temperature anomaly is positive in the tropical eastern Pacific but negative in the extratropical North Pacific, indicating a warm PDO phase, and vice versa. Accompanying the warm PDO phase, the sea level pressure anomaly is negative over eastern Siberia and north of Japan but positive over most of Southern China, which generates an anomalous northwesterly over North China and reduces gain of the water vapor from oceans.
Morphology of the stagnant slab from the northern Okhotsk arc to the northeastern Japan arc and its geodynamic implications

The slab morphology as revealed by the seismic tomography is supposed to have much information on the physical properties of mantle transition zone, viscosity structure, geologic history and e.t. c. Incorporating the results of seismic tomography and the geologic history around the northeastern Japan arc with 2D numerical geodynamic models, Honda (2016) concluded that the stagnant slab there is the accumulated slab from the time when the ridge plate boundary between the Izanagi and Pacific plate subducted there around 60 Ma. The similar subduction history can be expected also around the northern Okhotsk arc. However, the slab morphology of each region is quite different, that is, the significant slab stagnation around the northeastern Japan arc versus the slab penetration around the northern Okhotsk arc. Honda (2016) also noticed that the slab stagnation around the northeastern Japan zone requires steeper Clapeyron slope than that estimated by the experiments. In this presentation, I seek the consistent answer to these problems based on the dynamics of hot subslab mantle under the Pacific plate (Morishige et al., 2010; Ismail-Zadeh et al. 2013), because it gives the additional force to support the negative buoyancy of the slab in addition to the endothermic phase change at 660 km and it shows the along-arc variations. An example of results is shown in the figure. Upper figures are derived from the seismic tomography following the procedure described in Honda (2016). The lower figures are derived from the numerical models described in Honda (2016). References Honda, S. , Tectonophysics, 671,127-138, 2016. Ismail-Zadeh et al., Scientific Reports 3:1137, doi:10.1038/srep01137, 2013. Morishige et al., Phys. Earth Planet. Int. 183, 353-365, 2010.
Considerations for enhanced mesenchymal stromal/stem cell myogenic commitment in vitro

Abstract The generation of tissue from stem cells is an alluring concept as it holds a number of potential applications in clinical therapeutics and regenerative medicine. Mesenchymal stromal/stem cells (MSCs) can be isolated from a number of different somatic sources, and have the capacity to differentiate into adipogenic, osteogenic, chondrogenic, and myogenic lineages. Although the first three have been extensively investigated, there remains a paucity of literature on the latter. This review looks at the various strategies available in vitro to enhance harvested MSC commitment and differentiation into the myogenic pathway. These include chemical inducers, myogenic‐enhancing cell culture substrates, and mechanical and dynamic culturing conditions. Drawing on information from embryonic and postnatal myogenesis from somites, satellite, and myogenic progenitor cells, the mechanisms behind the chemical and mechanical induction strategies can be studied, and the sequential gene and signaling cascades can be used to monitor the progression of myogenic differentiation in the laboratory. Increased understanding of the stimuli and signaling mechanisms in the initial stages of MSC myogenic commitment will provide tools with which we can enhance their differentiation efficacy and advance the process to clinical translation.
An Exploratory Comparison of Stock Prices Prediction using Multiple Machine Learning Approaches based on Hong Kong Share Market

Stock price prediction has always been challenging due to its volatility and unpredictability. This paper performs a preliminary exploratory comparison that utilizes Long Short-Term Memory (LSTM) and Support Vector Machine (SVM) algorithms to forecast the stock market in Hong Kong. It considers a public dataset publicly available and uses feature engineering to extract relevant features. Then, LSTM and SVM algorithms are applied to predict stock prices. Our results show that the proposed machine learning techniques can predict stock prices in Hong Kong's share market with the error metrics presented, and, for this purpose, LSTM achieved better results than SVM, with MSE = 0.0026, RMSE = 0.0508, MAE = 0.0406, and MAPE = 1.325.