Miracle-dz/UniFAR-FTUs huggingface dataset:
Experimental investigations of crater formation as a result of high-velocity impacts on sand bed

The formation of craters is an important issue in the investigations of the surface of the earth and other planets. The aim of the study was to check whether the different textures of sand beds affect the size and dynamics of the formation of craters and ejection curtain after high-velocity impacts. The experiments were conducted using an aluminium impactor at two impact speeds (~700 and ~1300 m∙s-1) and a sand bed composed of either a broad range of sizes (<2.0 mm) or any of the three fractions obtained from it (<0.5, 0.5–1, 1–2 mm). The diameters, depths, wall slope, and rim heights of the resulting craters were measured. The ejecta curtain was characterized by the inclination angle of walls, base diameter, and expansion velocity. The mass of the transferred material and the depth of the impactor penetration were also determined. Additionally, the results were used to calculate dimensionless parameters commonly considered in crater studies (πV, π2 and α). The texture of the sand most clearly influenced the diameters of the craters, its effect could also be seen in the case of the distance covered by the ejected material. This information appears to be relevant for future research, providing some rationale to help assess in which aspects of the phenomenon the texture may be important.
An Attitude Determination Method for Comprehensive Inspection Vehicle Based on Track Profile Registration

An Attitude Determination Method Based on Track Profile Registration 2017 45 4 Abstract The attitude of the comprehensive inspection vehicle is one of the important factors that affect the accuracy of the inspection of metro line infrastructure, meanwhile the metro environment restricts the employment of common attitude determination methods. A new method of attitude determination is presented in this paper, which takes the track as reference and employs non-contact measurement to acquire the track profile simulta-neously. By registration of measurement track profile and the standard track profile, the relative position between the vehicle and the track reference can be calculated; and the instantaneous attitude of the vehicle can be determined by the matrix inverse calculation. The performance of the method is verified by an experiment using the road-rail comprehensive inspection vehicle.
Comparison of instability indices from COSMO-I7 and ECMWF-IFS analyses over Piemonte Region and new modifications of K Index.: Analysis of convective heavy rain events on Piemonte Region

This paper presents a statistical analysis of heavy rain events recorded by the high resolution network of ARPA Piemonte (Piedmont Region Environmental Protection Agency) rain gauges between 2007 and 2014. In order to define convective heavy rain events over the region, a rainfall threshold of 10 mm in 20 min was chosen. Events were sampled at intervals of 6 h for the warning areas of the Piedmont Region, Italy, and their distribution was studied in relation to the values of instability indices obtained from the European Centre for Medium Range Weather Forecasts Integrated Forecasting System and the COnsortium for Small-scale MOdeling (COSMO)-I7 operational analyses. The performances of the indices of the two meteorological models were investigated for the different warning areas in a pseudo-operational weather forecasting context, obtaining useful information in the phase of issuing thunderstorm early warnings. The second part of the work had the goal of improving the performance of these indices, modifying the one that showed better verification results in terms of receiver operating characteristic (ROC) area increase and the K Index (KI). This was done by introducing dependences on the thickness of geopotential height and wind direction at different levels. KI modifications that displayed better results were called reduced K Index (KR), obtained by dividing KI by the thickness of geopotential height between 500 and 850 hPa, and KW, obtained by adjusting the KR value with additive constants depending on the wind direction at different levels. KW in particular led to a net improvement of the performance of the original KI over the region.
APPLYING AN AI PLANNER TO SCHEDULE GROUND SATELLITES OPERATIONS

Planning and scheduling are closely related areas that AI community has been long concerned with. The first one deals with finding plans to achieve some goals from an initial state. The second one refers to the allocation of available resources to known activities over time in order to produce schedules that respect temporal relations and resource capacity constrains. They can also optimize a set of objectives, such as minimize tardiness, minimize work in process, maximize resource allocation or minimize cycle time. Planning refers to what should be done and scheduling to how it should be done. Due to these differences, planning and scheduling have been traditionally solved separately using rather different methods. Depending on the problem complexity some domains allow a strict separation between planning and scheduling. But, in other cases, there is an indirect temporal and resource dependency with other states and goals that can not be taken into account if we separate both tasks. In this paper we present a way of integrating them that consists on allowing the planner to reason about resources, although not as explicitly as in the case of other systems. We wanted to explore how to use a standard planner, PRODIGY, to also schedule in a real domain. In this approach, the designer has to be able of determining the elements that can and can not be tackled and the way to express them in the planner language for an efficient internal treatment. In PRODIGY there is not a language that allows an explicit representation of resource or temporal information as in [Chien et al 2000]. However, thanks to three representation facts, the user can use numeric variables and constrains. They are: its capability to represent infinite types (numeric variables); the possibility to define functions that obtain variables values in preconditions of operators; and the use of control rules to prune the search. We have used this approach to plan and schedule nominal operations to perform in three satellites along the year for a Spanish satellites company, HISPASAT. Satellite Operations
Novel “late potential map” algorithm: Abnormal potentials and scar channels detection for ventricular tachycardia ablation

Automated systems for substrate mapping in the context of ventricular tachycardia (VT) ablation may annotate far‐field rather than near‐field signals, rendering the resulting maps hard to interpret. Additionally, quantitative assessment of local conduction velocity (LCV) remains an unmet need in clinical practice. We evaluate whether a new late potential map (LPM) algorithm can provide an automatic and reliable annotation and localized bipolar voltage measurement of ventricular electrograms (EGMs) and if LCV analysis allows recognizing intrascar conduction corridors acting as VT isthmuses.
Genome-wide screening identifies Polycomb repressive complex 1.3 as an essential regulator of human naïve pluripotent cell reprogramming

Uncovering the mechanisms that establish naïve pluripotency in humans is crucial for the future applications of pluripotent stem cells including the production of human blastoids. However, the regulatory pathways that control the establishment of naïve pluripotency by reprogramming are largely unknown. Here, we use genome-wide screening to identify essential regulators as well as major impediments of human primed to naïve pluripotent stem cell reprogramming. We discover that factors essential for cell state change do not typically undergo changes at the level of gene expression but rather are repurposed with new functions. Mechanistically, we establish that the variant Polycomb complex PRC1.3 and PRDM14 jointly repress developmental and gene regulatory factors to ensure naïve cell reprogramming. In addition, small-molecule inhibitors of reprogramming impediments improve naïve cell reprogramming beyond current methods. Collectively, this work defines the principles controlling the establishment of human naïve pluripotency and also provides new insights into mechanisms that destabilize and reconfigure cell identity during cell state transitions.
Structural determinants of dual incretin receptor agonism by tirzepatide

Significance Tirzepatide is a dual agonist of the glucose-dependent insulinotropic polypeptide receptor (GIPR) and the glucagon-like peptide-1 receptor (GLP-1R), which are incretin receptors that regulate carbohydrate metabolism. This investigational agent has proven superior to selective GLP-1R agonists in clinical trials in subjects with type 2 diabetes mellitus. Intriguingly, although tirzepatide closely resembles native GIP in how it activates the GIPR, it differs markedly from GLP-1 in its activation of the GLP-1R, resulting in less agonist-induced receptor desensitization. We report how cryogenic electron microscopy and molecular dynamics simulations inform the structural basis for the unique pharmacology of tirzepatide. These studies reveal the extent to which fatty acid modification, combined with amino acid sequence, determines the mode of action of a multireceptor agonist.
Nuclear HMGB1 protects from nonalcoholic fatty liver disease through negative regulation of liver X receptor

Dysregulations of lipid metabolism in the liver may trigger steatosis progression, leading to potentially severe clinical consequences such as nonalcoholic fatty liver diseases (NAFLDs). Molecular mechanisms underlying liver lipogenesis are very complex and fine-tuned by chromatin dynamics and multiple key transcription factors. Here, we demonstrate that the nuclear factor HMGB1 acts as a strong repressor of liver lipogenesis. Mice with liver-specific Hmgb1 deficiency display exacerbated liver steatosis, while Hmgb1-overexpressing mice exhibited a protection from fatty liver progression when subjected to nutritional stress. Global transcriptome and functional analysis revealed that the deletion of Hmgb1 gene enhances LXRα and PPARγ activity. HMGB1 repression is not mediated through nucleosome landscape reorganization but rather via a preferential DNA occupation in a region carrying genes regulated by LXRα and PPARγ. Together, these findings suggest that hepatocellular HMGB1 protects from liver steatosis development. HMGB1 may constitute a new attractive option to therapeutically target the LXRα-PPARγ axis during NAFLD.
Patients' self-perceived strengths increase during treatment and predict outcome in outpatient cognitive behavioral therapy.

OBJECTIVE Modern conceptualizations suggest the independence of positive and negative mental health constructs. Research of positive constructs in psychotherapy is scarce. This study analyzed the development of patients' strengths during psychotherapy and whether pre-therapy strengths incrementally predict treatment outcome. METHODS Two hundred and two patients (56.44% female, mean age = 42.49) treated by 54 therapists underwent cognitive behavioral therapy. Patients' strengths in different contexts as well as psychopathology, interpersonal problems, and self-esteem were assessed at the beginning and end of therapy. RESULTS Strengths increased in the contexts of everyday life (EvdayS; d = 0.44, p < 0.001) and current problems (ProbS; d = 0.70, p < 0.001). Strengths in the context of previous crises that were managed successfully (CrisesS) did not change. However, baseline scores of CrisesS were a significant incremental predictor of all outcomes. CONCLUSION A differentiated assessment of positive constructs is useful for outcome prediction and the implementation of strength-based interventions.
Local anesthetic levobupivacaine inhibits stemness of osteosarcoma cells by epigenetically repressing MAFB though reducing KAT5 expression

Osteosarcoma is the most prevalent bone cancer and accounts for over half of sarcomas. In this study, we identified that the treatment of levobupivacaine suppressed proliferation of osteosarcoma cells in vitro. The tumor xenograft analysis showed that levobupivacaine significantly repressed the osteosarcoma cell growth in the nude mice. The treatment of levobupivacaine improved the apoptosis rate and attenuated invasion and migration abilities of osteosarcoma cells. The sphere formation capabilities of osteosarcoma cells were repressed by levobupivacaine. The protein levels of Sox-2, Oct3/4, and Nanog were inhibited by the treatment of levobupivacaine in osteosarcoma cells. Regarding mechanism, we identified that levobupivacaine inhibited MAFB and KAT5 expression in osteosarcoma cells. We observed that lysine acetyltransferase 5 could enriched in the promoter region of MAF BZIP transcription factor B, while levobupivacaine treatment could repressed the enrichment. The suppression of KAT5 by siRNA repressed the enrichment of histone H3 acetylation at lysine 27 and RNA polymerase II on promoter of MAFB. The expression of MAFB was decreased by KAT5 knockdown in osteosarcoma cells. The expression of MAFB was repressed by levobupivacaine, while the overexpression of KAT5 could reverse the repression of MAFB. KAT5 contributes to the cell proliferation and stemness of osteosarcoma cells. The overexpression of KAT5 or MAFB could reverse levobupivacaine-attenuated cell proliferation and stemness of osteosarcoma cells. Therefore, we concluded that local anesthetic levobupivacaine inhibited stemness of osteosarcoma cells by epigenetically repressing MAFB though reducing KAT5 expression. Levobupivacaine may act as a potential therapeutic candidate for osteosarcoma by targeting cancer stem cells.
Strong interlayer interactions in bilayer and trilayer moiré superlattices

Moiré superlattices constructed from transition metal dichalcogenides have demonstrated a series of emergent phenomena, including moiré excitons, flat bands, and correlated insulating states. All of these phenomena depend crucially on the presence of strong moiré potentials, yet the properties of these moiré potentials, and the mechanisms by which they can be generated, remain largely open questions. Here, we use angle-resolved photoemission spectroscopy with submicron spatial resolution to investigate an aligned WS2/WSe2 moiré superlattice and graphene/WS2/WSe2 trilayer heterostructure. Our experiments reveal that the hybridization between moiré bands in WS2/WSe2 exhibits an unusually large momentum dependence, with the splitting between moiré bands at the Γ point more than an order of magnitude larger than that at K point. In addition, we discover that the same WS2/WSe2 superlattice can imprint an unexpectedly large moiré potential on a third, separate layer of graphene (g/WS2/WSe2), suggesting new avenues for engineering two-dimensional moiré superlattices.
Non-Contact Heartbeat Detection Based on Ballistocardiogram Using UNet and Bidirectional Long Short-Term Memory

Benefiting from non-invasive sensing tech- nologies, heartbeat detection from ballistocardiogram (BCG) signals is of great significance for home-care applications, such as risk prediction of cardiovascular disease (CVD) and sleep staging, etc. In this paper, we propose an effective deep learning model for automatic heartbeat detection from BCG signals based on UNet and bidirectional long short-term memory (Bi-LSTM). The developed deep learning model provides an effective solution to the existing challenges in BCG-aided heartbeat detection, especially for BCG in low signal-to-noise ratio, in which the waveforms in BCG signals are irregular due to measured postures, rhythm and artifact motion. For validations, performance of the proposed detection is evaluated by BCG recordings from 43 subjects with different measured postures and heart rate ranges. The accuracy of the detected heartbeat intervals measured in different postures and signal qualities, in comparison with the R-R interval of ECG, is promising in terms of mean absolute error and mean relative error, respectively, which is superior to the state-of-the-art methods. Numerical results demonstrate that the proposed UNet-BiLSTM model performs robust to noise and perturbations (e.g. respiratory effort and artifact motion) in BCG signals, and provides a reliable solution to long term heart rate monitoring.
Impact of Centrality Measures on the Common Neighbors in Link Prediction for Multiplex Networks

Complex networks are representations of real-world systems that can be better modeled as multiplex networks, where the same nodes develop multi-type connections. One of the important concerns about these networks is link prediction, which has many applications in social networks and recommender systems. In this article, similarity-based methods such as common neighbors (CNs) are the mainstream. However, in the CN method, the contribution of each CN in the likelihood of new connections is equally taken into account. In this work, we propose a new link prediction method namely Weighted Common Neighbors (WCN), which is based on CNs and various types of Centrality measures (including degree, k-core, closeness, betweenness, Eigenvector, and PageRank) to predict the formation of new links in multiplex networks. So, in this model, each CN has a different impact on the node connection likelihood. Moreover, we investigate the impact of interlayer information on improving the performance of link prediction in the target layer. Using Area under the ROC Curve and precision as evaluation metrics, we perform a comprehensive experimental evaluation of our proposed method on seven real multiplex networks. The results validate the improved performance of our proposed method compared with existing methods, and we show that the performance of proposed methods is significantly improved while using interlayer information in multiplex networks.
Palliative care for older people with dementia—we need a paradigm shift in our approach

Abstract Older people with dementia have multiple palliative care needs, with pain, agitation, dyspnoea, aspiration and pressure ulcers being common and persistent in advanced dementia. Anticipating the person’s possible symptoms requires knowledge of the whole person, including the type of dementia, which is problematic when the dementia type is often not documented. A palliative care approach to dementia should look at symptoms across the four pillars of palliative care, but in reality, we tend to over-focus on physical and psychological symptoms, while spiritual and emotional needs can be overlooked, especially around the time of diagnosis, where such needs may be significant. Advance care planning (ACP) is a central tenet of good dementia palliative care, as the person may lose their ability to communicate and make complex decisions over time. Despite this, care planning is often approached too late, and with the person’s family rather than with the person; much of the literature on ACP in dementia is based on proxy decision-making for people in residential care. Thus, we need a paradigm shift in how we approach dementia, beginning with timely diagnosis that includes the dementia type, and with services able to assess and meet emotional and spiritual needs especially around the time of diagnosis, and with timely ACP as an integral part of our overall approach.
Multilevel Factors for Adiposity Change in a Population-Based Prospective Study of Black Breast Cancer Survivors

PURPOSE Unfavorable weight change after breast cancer diagnosis increases the risk of mortality, but individual and neighborhood risk factors affecting postdiagnosis weight and body fat changes are unclear among Black women, who have higher rates of obesity and mortality than any other racial/ethnic group. METHODS Adiposity changes during the period approximately 10 months-24 months after diagnosis were evaluated among 785 women diagnosed between 2012 and 2018 and enrolled in the Women's Circle of Health Follow-Up Study, a population-based prospective cohort of Black breast cancer survivors in New Jersey. Multilevel factors for weight and fat mass change (with gain or loss defined as a relative difference of 3% or more, and considering whether changes were intentional or unintentional) were estimated using multivariable polytomous logistic regressions and multilevel models. RESULTS Adiposity gain was prevalent: 28% and 47% gained weight and body fat, respectively, despite a high baseline prevalence of overweight or obesity (86%). Risk factors for fat mass gain included receiving chemotherapy (relative risk ratio: 1.59, 95% CI, 1.08 to 2.33) and residing in neighborhoods with a greater density of fast-food restaurants (relative risk ratio comparing highest with lowest tertile: 2.18, 95% CI, 1.38 to 3.46); findings were similar for weight gain. Only 9% of women had intentional weight loss, and multilevel risk factors differed vastly from unintentional loss. CONCLUSION Both individual and neighborhood factors were associated with adiposity change among Black breast cancer survivors. Residential environment characteristics may offer clinically meaningful information to identify cancer survivors at higher risk for unfavorable weight change and to address barriers to postdiagnosis weight management. Neighborhood & individual factors are collectively associated with adiposity change in Black #BreastCancer survivors
Clinical assessment or scoring model for acute lung injury: A crossing path?

Acute type A aortic dissection (ATAAD) is a clinical emergency and is associated with significant mortality and morbidity which necessitates immediate surgical intervention. 1 Although surgical techniques have improved over time, resulting in lower mortality rates, 2 the high incidence of postoperative complications remains the primary factor influencing the patient's long ‐ term outlook. One of these complications is acute lung injury (ALI), a major cause of postoperative mortality with an incidence of 15% – 30%. 3 Wang et al. should be commended for developing a scoring model for severe ALI following ATAAD and highlighting the predictive risk factors. 4 The results of this study extend the findings of the previous models that predict ALI following ATAAD and are comparable to what is reported elsewhere in the literature. 5 – 7 However, Wang et al. are the first to incorporate the preoperative echocardiographic variables in the predictive model and demonstrated that left atrial diameter ≥ 35.5mm and left ventricular posterior wall thickness ≥ 10.5mm were independent risk factors for severe ALI after ATAAD. This warrants future research regarding potential underlying mechanisms,