Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermophysical properties and atomic structure of liquid Zr–Nb alloys investigated by electrostatic levitation and molecular dynamics simulation

The investigation of the thermophysical properties of liquid Zr–Nb alloys holds great significance for theoretical research and technical application in liquid physics. However, the high temperatures involved make their experimental measurement challenging. In this study, the densities of liquid Zr-x wt. % Nb (x= 1.0, 2.5, 6.0) alloys were examined by electrostatic levitation and molecular dynamics calculation. Remarkably, the alloys achieved maximum undercooling of 335 K, 311 K and 326 K, respectively. Correspondingly, the densities are 6.20, 6.22 and 6.26 g·cm−3 at the liquidus temperatures (T L), respectively. The corresponding temperature coefficients are 2.61 × 10−4, 2.75 × 10−4 and 2.84 × 10−4 g·cm−3·K−1, respectively. Notably, the experimental density results align well with the simulated results. Moreover, the molar volume (V m), thermal expansion coefficient (α) and diffusion coefficient (D) were derived based on the experimental data and simulations. The thermal expansion coefficients reduce linearly with decreasing temperature. The analysis of the pair distribution function, coordination number (CN) and the radial distribution function reveals the temperature-dependent evolution of the atomic structure. The CN total and CN Zr–Zr initially increase and then decrease with decreasing temperature, while the change trends for CN Zr–Nb and CN Nb–Nb varied among the three alloys. The radial distribution function of three liquid alloys reveals that the atomic number density increases as the temperature drops. Additionally, the total diffusion coefficients decrease with the reduction of temperature and the rise of Nb content from 1.0 wt. % Nb to 6.0 wt. % Nb.
Migration and differentiation of muscle stem cells are coupled by RhoA signalling during regeneration

Skeletal muscle is highly regenerative and is mediated by a population of migratory adult muscle stem cells (muSCs). Effective muscle regeneration requires a spatio-temporally regulated response of the muSC population to generate sufficient muscle progenitor cells that then differentiate at the appropriate time. The relationship between muSC migration and cell fate is poorly understood and it is not clear how forces experienced by migrating cells affect cell behaviour. We have used zebrafish to understand the relationship between muSC cell adhesion, behaviour and fate in vivo. Imaging of pax7-expressing muSCs as they respond to focal injuries in trunk muscle reveals that they migrate by protrusive-based means. By carefully characterizing their behaviour in response to injury we find that they employ an adhesion-dependent mode of migration that is regulated by the RhoA kinase ROCK. Impaired ROCK activity results in reduced expression of cell cycle genes and increased differentiation in regenerating muscle. This correlates with changes to focal adhesion dynamics and migration, revealing that ROCK inhibition alters the interaction of muSCs to their local environment. We propose that muSC migration and differentiation are coupled processes that respond to changes in force from the environment mediated by RhoA signalling.
Interventions to reduce social isolation and loneliness among older people: an integrative review

This is the peer reviewed version of the following article: Gardiner, C. , Geldenhuys, G. and Gott, M. (2016), Interventions to reduce social isolation and loneliness among older people: an integrative review. Health & Social Care in the Community. , which has been published in final form at http://dx.doi. org/10.1111/hsc.12367. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving (http://olabout.wiley.com/WileyCDA/Section/id-828039.html)
The rice NUCLEAR FACTOR-YA5 and MICRORNA169a module promotes nitrogen utilization during nitrogen deficiency

Abstract Nitrogen (N) is essential for plant growth and development. Therefore, understanding its utilization is essential for improving crop productivity. However, much remains to be learned about plant N sensing and signaling. Here, rice (Oryza sativa) NUCLEAR FACTOR-YA5 (OsNF-YA5) expression was tightly regulated by N status and induced under N-deficient conditions. Overexpression (OE) of OsNF-YA5 in rice resulted in increased chlorophyll levels and delayed senescence compared to control plants under normal N conditions. Agronomic traits were significantly improved in OE plants and impaired in knockout mutants under N-deficient conditions. Using a dexamethasone-inducible system, we identified the putative targets of OsNF-YA5 that include amino acid, nitrate/peptide transporters, and NITRATE TRANSPORTER 1.1A (OsNRT1.1A), which functions as a key transporter in rice. OsNF-YA5 directly enhanced OsNRT1.1A expression and N uptake rate under N-deficient conditions. Besides, overexpression of OsNF-YA5 also enhanced the expression of GLUTAMINE SYNTHETASE 1/2 (GS1/2) and GLUTAMINE OXOGLUTARATE AMINOTRANSFERASE 1/2 (GOGAT1/2), increasing free amino acid contents under N-deficient conditions. Osa-miR169a expression showed an opposite pattern with OsNF-YA5 depending on N status. Further analysis revealed that osa-miR169a negatively regulates OsNF-YA5 expression and N utilization, demonstrating that an OsNF-YA5/osa-miR169a module tightly regulates rice N utilization for adaptation to N status.
A procedure to harmonize the hydrodynamic force during microbial cultivation in shaking flasks

ABSTRACT Shake flask cultivation is a routine technique in microbiology and biotechnology laboratories where cell growth can be affected by the hydrodynamic conditions, which depend on the agitation velocity, shaking diameter, and shake flask size. Liquid agitation is implemented inherently to increase aeration, substrate transfer to the cells, and prevent sedimentation, disregarding the role of hydrodynamics in microbial growth and metabolism. Here, we present a simple approach to help standardize the hydrodynamic forces in orbital shakers to increase the experimental accuracy and reproducibility and give students a better knowledge of the significance of the agitation process in microbial growth.
Learning Model Predictive Control with Error Dynamics Regression for Autonomous Racing

This work presents a novel Learning Model Predictive Control (LMPC) strategy for autonomous racing at the handling limit that can iteratively explore and learn unknown dynamics in high-speed operational domains. We start from existing LMPC formulations and modify the system dynamics learning method. In particular, our approach uses a nominal, global, nonlinear, physics-based model with a local, linear, data-driven learning of the error dynamics. We conducted experiments in simulation and on 1/10th scale hardware, and deployed the proposed LMPC on a full-scale autonomous race car used in the Indy Autonomous Challenge (IAC) with closed loop experiments at the Putnam Park Road Course in Indiana, USA. The results show that the proposed control policy exhibits improved robustness to parameter tuning and data scarcity. Incremental and safety-aware exploration toward the limit of handling and iterative learning of the vehicle dynamics in high-speed domains is observed both in simulations and experiments.
Enhancing Elasticity Models: A Novel Corrective Source Term Approach for Accurate Predictions

With the recent wave of digitalization, specifically in the context of safety-critical applications, there has been a growing need for computationally efficient, accurate, generalizable, and trustworthy models. Physics-based models have traditionally been used extensively for simulating and understanding complex phenomena. However, these models though trustworthy and generalizable to a wide array of problems, are not ideal for real-time. To address this issue, the physics-based models are simplified. Unfortunately, these simplifications, like reducing the dimension of the problem (3D to 2D) or linearizing the highly non-linear characteristics of the problem, can degrade model accuracy. Data-driven models, on the other hand, can exhibit better computational efficiency and accuracy. However, they fail to generalize and operate as blackbox, limiting their acceptability in safety-critical applications. In the current article, we demonstrate how we can use a data-driven approach to correct for the two kinds of simplifications in a physics-based model. To demonstrate the methodology's effectiveness, we apply the method to model several elasticity problems. The results show that the hybrid approach, which we call the corrective source term approach, can make erroneous physics-based models more accurate and certain. The hybrid model also exhibits superior performance in terms of accuracy, model uncertainty, and generalizability when compared to its end-to-end data-driven modeling counterpart.
Intracellular K+ limits T cell exhaustion and preserves antitumor function

The cancer-killing activity of T cells is often compromised within tumors, allowing disease progression. We previously found that intratumoral elevations in extracellular K+ related to ongoing cell death constrained CD8+ T cell Akt-mTOR signaling and effector function (1,2). To alleviate K+ mediated T cell suppression, we pursued genetic means to lower intracellular K+. Transcriptomic analysis of CD8+ T cells demonstrated the Na+/K+ ATPase to be robustly and dynamically expressed. CRISPR-Cas9 mediated deletion of the catalytic alpha subunit of the Na+/K+ ATPase lowered intracellular K+ but produced tonic hyperactivity in multiple signal transduction cascades along with the acquisition of co-inhibitory receptors and terminal differentiation in mouse and human CD8+ T cells. Mechanistically, Na+/K+ ATPase disruption led to ROS accumulation due to depletion of intracellular K+ in T cells. Antioxidant treatment or high K+ media prevented Atp1a1 deficient T cells from exhausted T (TEx) cell formation. Consistent with transcriptional and proteomic data suggesting a TEx cell phenotype, T cells lacking Atp1a1 had compromised persistence and antitumor activity in a syngeneic model of orthotopic murine melanoma. Translational application of these findings will include efforts to lower intracellular K+ while limiting ROS accumulation within tumor specific T cells. Synopsis High extracellular K+ (↑[K+]e) is found within tumors and suppresses T cell effector function. Collier et al. find that deletion of the Na+/K+ ATPase in T cells lowers intracellular K+ and promotes ROS accumulation, tonic signal transduction and T cell exhaustion owing to ROS accumulation. Engineering T cell ion transport is an important consideration for cancer immunotherapy.
INDoRI: Indian Dataset of Recipes and Ingredients and its Ingredient Network

Exploring and comprehending the culinary heritage of a nation holds a captivating allure. It offers insights into the structure and qualities of its cuisine. The endeavor becomes more accessible with the availability of a well-organized dataset. In this paper, we present the introduction of INDoRI (Indian Dataset of Recipes and Ingredients), a compilation drawn from seven distinct online platforms, representing 18 regions within the Indian subcontinent. This comprehensive geographical span ensures a portrayal of the rich variety within culinary practices. Furthermore, we introduce a unique collection of stop words, referred to as ISW (Ingredient Stop Words), manually tuned for the culinary domain. We assess the validity of ISW in the context of global cuisines beyond Indian culinary tradition. Subsequently, an ingredient network (InN) is constructed, highlighting interconnections among ingredients sourced from different recipes. We delve into both the defining attributes of INDoRI and the communal dimensions of InN. Additionally, we outline the potential applications that can be developed leveraging this dataset. Addressing one of the applications, we demonstrated a research problem on InN with a simple weighted community detection algorithm. Furthermore, we provide a comparative analysis of the results obtained with this algorithm against those generated by two baselines.
ATM inhibition augments type I interferon response and antitumor T-cell immunity when combined with radiation therapy in murine tumor models

Background Radiation therapy (RT) elicits DNA double-strand breaks, resulting in tumor cytotoxicity and a type I interferon (IFN) response via stimulator of interferon genes (STING) activation. We investigated whether combining RT with an ataxia-telangiectasia mutated inhibitor promoted these effects and amplified tumor immunity. Methods Mice-bearing syngeneic flank tumors (MOC2 head and neck squamous cell carcinoma or B78 melanoma) were treated with tumor-directed RT and oral administration of AZD0156. Specific immune cell depletion, type 1 interferon receptor 1 knock-out mice (IFNAR1-KO), and STING-deficient tumor cells were used to investigate tumor-immune crosstalk following RT and AZD0156 treatment. Results Combining RT and AZD0156 reduced tumor growth compared with RT or AZD0156 alone in mice bearing MOC2 or B78 tumors. Low-dose AZD0156 (1–100 nM) alone did not affect tumor cell proliferation but suppressed tumor cell clonogenicity in combination with RT. Low-dose AZD0156 with RT synergistically increased IFN-β, major histocompatibility complex (MHC)-I, and programmed death-ligand 1 (PD-L1) expression in tumor cells. In contrast to wild-type mice, IFNAR1-KO mice showed reduced CD8+T cell tumor infiltration and poor survival following RT+AZD0156 treatment. CD8+T cell depletion reduced antitumor response during RT+AZD0156 treatment. STING-deficient MOC2 (MOC2-STING+/–) or B78 (B78-STING–/–) tumors eliminated the effects of RT+AZD0156 on the expression of IFN-β, MHC-I, and PD-L1, and reduced CD8+T cell infiltration and migration. Additional anti-PD-L1 therapy promoted antitumor response by elevation of tumor-MHC-I and lymphocyte activation. Conclusions Combined radiation and AZD0156 increase STING-dependent antitumor response. Tumor-derived cell-autonomous IFN-β amplification drives both MHC-I and PD-L1 induction at the tumor cell surface, which is required by anti-PD-L1 therapy to promote antitumor immune response following RT and AZD0156 combination therapy.
Implementation and evaluation of the AAPM TG 111 for radiation dosimetry in a state-of-the-art C-arm cone beam CT system

The aim of this study was to assess the dosimetric characteristics of a state-of-the-art C-arm cone beam computed tomography (CBCT) system using the methodology proposed by the American Association of Physicists in Medicine (AAPM) Task Group (TG) 111. The dose measurement methodology described in AAPM TG 111 for wide cone beam acquisitions without table translation was employed to estimate equilibrium beam length ( αeq‾ ) and equilibrium dose ( feq‾ ) in various interventional task-specific protocols with different tube arc projection geometries. Dose profiles were derived from point dose measurements in the centre and peripheral locations of the ICRU/AAPM and standard polymethyl methacrylate (PMMA) body phantom. Dose measurements were performed in phantom and free-in-air using a solid-state point detector. Monte Carlo (MC) based simulation dosimetry was performed to quantify the inhomogeneous dose patterns imparted in the phantoms. Estimated αeq‾ and feq‾ on the ICRU/AAPM phantom was up to 49.4 cm and 6.17 mGy/100 mAs, respectively. Corresponding values determined on the PMMA phantom were 139 cm and 8.8 mGy/100 mAs, respectively. Free-in-air dose measurement ranged from 1.43 mGy/100 mAs to 5.93 mGy/100 mAs. Per cent difference in αeq‾ and feq‾ between MC simulation and solid-state point detector measurement methods in the ICRU/AAPM phantom were within 16% and 18%, respectively. Manufacturers can use the presented methodology to characterize the dosimetric properties of C-arm CBCT systems. Clinical medical physicists may follow this methodology to verify corresponding data provided by the manufacturer and check for C-arm CBCT system performance dosimetric consistency.
Substance Use Disorder Treatment Programs during a Health Crisis: Response to the COVID-19 Pandemic and Future Implications

Abstract Background: The COVID-19 pandemic rapidly changed how substance use disorder (SUD) treatment services are delivered. In this qualitative study, we examined what changes SUD treatment programs in Arkansas implemented in response to the pandemic, what factors influenced their ability to implement these changes, and their reflections, outlook, and future recommendations. Methods: Between May and August 2020, we conducted semi-structured phone interviews with 29 leaders at 21 SUD programs throughout Arkansas. Interview questions focused on what changes programs implemented in response to the pandemic, barriers and facilitators to implementation, and future outlook. Interviews were thematically analyzed. Results: Programs implemented similar infection control practices, including COVID-19 screening at entry, masks, hand hygiene, and social distancing. Residential programs discontinued outside visitations and capped admissions, and outpatient programs implemented telehealth services. Clients generally responded well to the changes, however many experienced difficulties (e.g., anxiety, lack of access to telehealth). While programs welcomed additional financial support (e.g., CARES act) and looser regulatory restrictions (e.g., telehealth use), many struggled economically due to lower demand and insufficient reimbursement. Programs varied in leadership and staff responses to the pandemic, and in their capacity to implement the changes (e.g., facilities, staffing). Finally, interviewees acknowledged they were unprepared for the pandemic and were uncertain about the future. Conclusions: The insights from the COVID-19 pandemic and SUD programs’ responses helps researchers, policymakers and practitioners understand what has happened during the pandemic, how to prepare for future crises, and how to build more resilient SUD and public health systems.
Endoscopic vacuum therapy for anastomotic leakage after upper gastrointestinal surgery

Background Recently, endoscopic vacuum therapy (EVT) was introduced as treatment for anastomotic leakage after upper gastrointestinal (GI) surgery. The aim of this study was to describe the initial experience with EVT for anastomotic leakage after upper GI surgery in a tertiary referral center. Methods Patients treated with EVT for anastomotic leakage after upper GI surgery were included retrospectively (January 2018–June 2021) and prospectively (June 2021–October 2021). The primary end point was the EVT success rate. Secondary end points included mortality and adverse events. Results 38 patients were included (31 men; mean age 66 years): 27 had undergone an esophagectomy with gastric conduit reconstruction and 11 a total gastrectomy with esophagojejunal anastomosis. EVT was successful in 28 patients (74 %, 95 %CI 57 %–87 %). In 10 patients, EVT failed: deceased owing to radiation pneumonitis (n = 1), EVT-associated complications (n = 2), and defect closure not achieved (n = 7). Mean duration of successful EVT was 33 days, with a median of six EVT-related endoscopies. Median hospital stay was 45 days. Conclusion This initial experience with EVT for anastomotic leakage after upper GI surgery demonstrated a success rate of 74 %. EVT is a promising therapy that could prevent further major surgery. More experience with the technique and its indications will likely improve success rates in the future.
Pkd2, mutations linking to autosomal dominant polycystic kidney disease, localizes to the endoplasmic reticulum and regulates calcium signaling in fission yeast

Autosomal dominant polycystic kidney disease (ADPKD) is a renal disorder caused by mutations in the PKD2 gene, which encodes polycystin‐2/Pkd2, a transient receptor potential channel. The precise role of Pkd2 in cyst formation remains unclear. The fission yeast Schizosaccharomyces pombe has a putative transient receptor potential channel, Pkd2, which shares similarities with human Pkd2. In this study, truncation analyses of fission yeast Pkd2 were conducted to investigate its localization and function. The results revealed that Pkd2 localizes not only to the plasma membrane but also to the endoplasmic reticulum (ER) in fission yeast. Furthermore, Pkd2 regulates calcium signaling in fission yeast, with the transmembrane domains of Pkd2 being sufficient for these processes. Specifically, the C‐terminal region of Pkd2 plays a crucial role in the regulation of calcium signaling. Interestingly, human Pkd2 also localized to the ER and had some impact on calcium signaling in fission yeast. However, human Pkd2 failed to suppress the loss of fission yeast Pkd2. These findings indicate that hPkd2 may not completely substitute for cellular physiology of fission yeast Pkd2. This study provides insights into the localization and functional characteristics of Pkd2 in fission yeast, contributing to our understanding of the pathogenesis of ADPKD.
Differential Survival In Carrion Crows Through Eavesdropping on Human Speech: An Agent-Based Model

Wild carrion crows eavesdrop on human speech and respond more strongly to it than to the calls of pigeons or parakeets. However, it remains unclear whether this behaviour provides any benefit to them, and if so, under which environmental conditions such a benefit could be expected. I used an agent-based model to examine the effect of eavesdropping on the survival of a carrion crow under different environmental conditions. The crow could gain points from foraging, but also had to avoid encounters with a human in order to not lose points. In addition to eavesdropping, it could visually scan the patch for human presence and, once detected, could keep track of the human’s location. I found that eavesdropping led to higher final scores and higher rates of survival than visual scanning alone if the human density on the patch was elevated, or if there were visual obstacles reducing the accuracy of visual scans. Such environmental conditions are particularly common for urban crows foraging in areas such as public parks. The model provides a proof of concept for future empirical research into the potentially differential survival of urban crows eavesdropping on speech.
Spanish hate-speech detection in football

: In the last few years, Natural Language Processing (NLP) tools have been successfully applied to a number of different tasks, including author profiling, negation detection or hate speech detection, to name but a few. For the identification of hate speech from text, pre-trained language models can be leveraged to build high-performing classifiers using a transfer learning approach. In this work, we train and evaluate state-of-the-art pre-trained classifiers based on Transformers. The explored models are fine-tuned using a hate speech corpus in Spanish that has been compiled as part of this research. The corpus contains a total of 7,483 football-related tweets that have been manually annotated under four categories: aggressive, racist, misogynist, and safe. A multi-label approach is used, allowing the same tweet to be labeled with more than one class. The best results, with a macro F1-score of 88.713%, have been obtained by a combination of the models using Knowledge Integration.