Miracle-dz/UniFAR-FTUs huggingface dataset:
Upgradation plans of SST-1 Cryogenics system at IPR

Steady State Superconducting Tokamak (SST-1) is India’s First Superconducting Tokamak and has Toroidal Field (TF) and Poloidal Field (PF) superconducting coils along with the cold mass support structure weighing about 38 ton of cold mass. A 1.3 kW Helium refrigeration and liquefaction (HRL) at 4.5 K along with its distribution network facilitates the cooling down of the cold mass and cryo-stable operation of SST-1TF magnets. SST-1 experimental campaigns have revealed that the existing HRL is just sufficient for the heat loads acting on it. Further, the SST-1 PF magnets require a higher pressure head and mass flow rate than the nominal values on account of the longer paths of some of the PF magnets. In order to make SST-1 being fully superconducting device, we are introducing superconducting central solenoid (CS). Detailed estimates have been made and it has been found that an additional ∼ 900 W at 4.5 K of cryo power is required towards (i) cooling all the PF magnets (ii) the cooling down and the operation of a new Nb3Sn based CS of SST-1. This paper will elaborate on (i) the experimental heat loads acting on the cryo system (ii) the ‘thermal runaway amongst the PF magnets observed in the SST-1 campaign’ (iii) the robust need of a higher operation pressure up to 2.1 bar (a) (iv) the need of the flow optimizations as per the hydraulic paths (v) the engineering solutions at each of these described (i)-(v) above.
Methods of weather variables introduction into short-term electric load forecasting models - a review

Short-term load forecasting (STLF) is a problem of noticeable significance for operation of power systems. Wide range of methodologies for STLF is given in the literature – univariate models as well as multivariate ones (mostly extended with weather variables). This paper is an attempt to categorize various approaches of introducing exogenous variables into models. Different classifications of this aspect are created and described in an effort to demonstrate the problem from various perspectives. Finally, the advantages and disadvantages of reviewed solutions are discussed. Streszczenie. Krótkoterminowe prognozowanie obciążeń jest istotnym elementem działania systemów elektroenergetycznych. W literaturze opisane zostało szerokie spektrum metod – modele zarówno jednojak i wielowymiarowe (najczęściej używające zmiennych pogodowych). W pracy podjęto próbę przeglądu metod prognozowania pod kątem sposobu w jaki korzystają one ze zmiennych egzogenicznych. Przedstawiono klasyfikacje dla tych metod opisujące problem z różnych perspektyw. (Przegląd metod uwzględniania zmiennych pogodowych w modelach prognozowania krótkoterminowego).
Methodological evaluation of individual cognitive prediction based on the brain white matter structural connectome

An emerging trend is to use regression‐based machine learning approaches to predict cognitive functions at the individual level from neuroimaging data. However, individual prediction models are inherently influenced by the vast options for network construction and model selection in machine learning pipelines. In particular, the brain white matter (WM) structural connectome lacks a systematic evaluation of the effects of different options in the pipeline on predictive performance. Here, we focused on the methodological evaluation of brain structural connectome‐based predictions. For network construction, we considered two parcellation schemes for defining nodes and seven strategies for defining edges. For the regression algorithms, we used eight regression models. Four cognitive domains and brain age were targeted as predictive tasks based on two independent datasets (Beijing Aging Brain Rejuvenation Initiative [BABRI]: 633 healthy older adults; Human Connectome Projects in Aging [HCP‐A]: 560 healthy older adults). Based on the results, the WM structural connectome provided a satisfying predictive ability for individual age and cognitive functions, especially for executive function and attention. Second, different parcellation schemes induce a significant difference in predictive performance. Third, prediction results from different data sets showed that dMRI with distinct acquisition parameters may plausibly result in a preference for proper fiber reconstruction algorithms and different weighting options. Finally, deep learning and Elastic‐Net models are more accurate and robust in connectome‐based predictions. Together, significant effects of different options in WM network construction and regression algorithms on the predictive performances are identified in this study, which may provide important references and guidelines to select suitable options for future studies in this field.
Functional adaptation of glial cells at neuromuscular junctions in response to injury

Synaptic elements from neuromuscular junctions (NMJs) undergo massive morphological and functional changes upon nerve injury. While morphological changes of NMJ‐associated glia in response to injury has been investigated, their functional properties remain elusive. Perisynaptic Schwann cells (PSCs), glial cells at the NMJ, are essential for NMJ maintenance and repair, and are involved in synaptic efficacy and plasticity. Importantly, these functions are regulated by PSCs ability to detect synaptic transmission through, notably, muscarinic (mAChRs) and purinergic receptors' activation. Using Ca2+ imaging and electrophysiological recordings of synaptic transmission at the mouse NMJ, we investigated PSC receptors activation following denervation and during reinnervation in adults and at denervated NMJs in an ALS mouse model (SOD1G37R). We observed reduced PSCs mAChR‐mediated Ca2+ responses at denervated and reinnervating NMJs. Importantly, PSC phenotypes during denervation and reinnervation were distinct than the one observed during NMJ maturation. At denervated NMJs, exogenous activation of mAChRs greatly diminished galectin‐3 expression, a glial marker of phagocytosis. PSCs Ca2+ responses at reinnervating NMJs did not correlate with the number of innervating axons or process extensions. Interestingly, we observed an extended period of reduced PSC mAChRs activation after the injury (up to 60 days), suggesting a glial memory of injury. PSCs associated with denervated NMJs in an ALS model (SOD1G37R mice) did not show any muscarinic adaptation, a phenotype incompatible with NMJ repair. Understanding functional mechanisms that underlie this glial response to injury may contribute to favor complete NMJ and motor recovery.
Coral‐bleaching responses to climate change across biological scales

The global impacts of climate change are evident in every marine ecosystem. On coral reefs, mass coral bleaching and mortality have emerged as ubiquitous responses to ocean warming, yet one of the greatest challenges of this epiphenomenon is linking information across scientific disciplines and spatial and temporal scales. Here we review some of the seminal and recent coral‐bleaching discoveries from an ecological, physiological, and molecular perspective. We also evaluate which data and processes can improve predictive models and provide a conceptual framework that integrates measurements across biological scales. Taking an integrative approach across biological and spatial scales, using for example hierarchical models to estimate major coral‐reef processes, will not only rapidly advance coral‐reef science but will also provide necessary information to guide decision‐making and conservation efforts. To conserve reefs, we encourage implementing mesoscale sanctuaries (thousands of km2) that transcend national boundaries. Such networks of protected reefs will provide reef connectivity, through larval dispersal that transverse thermal environments, and genotypic repositories that may become essential units of selection for environmentally diverse locations. Together, multinational networks may be the best chance corals have to persist through climate change, while humanity struggles to reduce emissions of greenhouse gases to net zero.
Modeling of the PHEMA-gelatin scaffold enriched with graphene oxide utilizing finite element method for bone tissue engineering

Abstract The development of computer-aided facilities has contributed to the optimization of tissue engineering techniques due to the reduction in necessary practical assessments and the removal of animal or human-related ethical issues. Herein, a bone scaffold based on poly (2-hydroxyethyl methacrylate) (PHEMA), gelatin and graphene oxide (GO), was simulated by SOLIDWORKS and ABAQUS under a normal compression force using finite element method (FEM). Concerning the mechanotransduction impact, GO could support the stability of the structure and reduce the possibility of the failure resulting in the integrity and durability of the scaffold efficiency which would be beneficial for osteogenic differentiation.
Nanoparticles Targeting Delivery Antagomir-483 -5p to Bone Marrow Mesenchymal Stem Cells Treat Osteoporosis by Increasing Bone Formation.

BACKGROUND Promoting bone marrow mesenchymal stem cell (BMSC) osteoblastic diﬀerentiation is a promising therapeutic strategy for osteoporosis (OP). The present study demonstrates that miR-483-5p inhibits the osteogenic differentiation of BMSCs. Therefore, selectively delivering the nanoparticles carrying antagomir-483-5p (miR-483-5p inhibitor) to BMSCs is expected to become an effective treatment drug for OP. METHODS Real-time PCR assays were used to analyze miR-483-5p, ALP and Bglap levels in BMSCs of ovariectomized and aged osteoporotic mice. To selectively and efficiently delivering antagomir-483-5p to BMSCs in vivo, immunoglobulin G and poloxamer-188 were used to encapsulate the functional small molecules, and BMSC-targeting aptamer was employed to confirm the direction of the nanoparticles. Luciferase assays were used to determine the target genes of miR-483-5p. Western blot assays and immunohistochemistry staining were used to detect the targets in vitro and vivo. RESULTS miR-483-5p levels were increased in BMSCs of ovariectomized and aged osteoporotic mice. Inhibition of miR-483-5p levels in BMSCs by antagomir-483-5p in vitro promoted the expression of bone formation markers, such as ALP and Bglap. The FAM-BMSC-aptamer-nanoparticles carrying antagomir-483-5p were taken up by BMSCs, resulting in stimulation of BMSC osteoblastic diﬀerentiation in vitro and osteoporosis prevention in vivo. Furthermore, our research demonstrated that mitogen-activated protein kinase 1 (MAPK1) and SMAD family member 5 (Smad5) were direct targets of miR-483-5p in regulating BMSC osteoblastic diﬀerentiation and osteoporosis pathological processes. CONCLUSIONS The important therapeutic role of FAM-BMSC-aptamer-nanoparticles carrying antagomir-483-5p in osteoporosis was established in our study. These nanoparticles are novel candidate for the clinical prevention and treatment of osteoporosis. The optimized targeted drug delivery platform for small molecules will provide new ideas for the treatment of clinical diseases.
Computational modeling of threat learning reveals links with anxiety and neuroanatomy in humans

Influential theories implicate variations in the mechanisms supporting threat learning in the severity of anxiety symptoms. We use computational models of associative learning in conjunction with structural imaging to explicate links among the mechanisms underlying threat learning, their neuroanatomical substrates, and anxiety severity in humans. We recorded skin-conductance data during a threat-learning task from individuals with and without anxiety disorders (N=251; 8-50 years; 116 females). Reinforcement-learning model variants quantified processes hypothesized to relate to anxiety: threat conditioning, threat generalization, safety learning, and threat extinction. We identified the best-fitting models for these processes and tested associations among latent learning parameters, whole-brain anatomy, and anxiety severity. Results indicate that greater anxiety severity related specifically to slower safety learning and slower extinction of response to safe stimuli. Nucleus accumbens gray-matter volume moderated learning-anxiety associations. Using a modeling approach, we identify computational mechanisms linking threat learning and anxiety severity and their neuroanatomical substrates.
Mind the gap! A survey comparing current strength training methods used in men’s versus women’s first team and academy soccer

ABSTRACT Purpose Much less is known about strength and conditioning (S&C) practice in women’s versus men’s soccer. The aim of this study was to compare S&C practice between coaches working in men’s or women’s soccer, at first team or academy level, worldwide. Methods A total of 170 participants, who were involved with S&C support at their soccer club (in Europe, USA and South America, within men’s or women’s first team or academy settings) completed a comprehensive online survey, designed to evaluate (i) their academic qualifications and S&C coaching experience; and their preferred methods for (ii) physical testing; (iii) strength and power development; (iv) plyometric training; (v) speed development; and (vi) periodization. Results Women’s academies had fewer weekly in-season S&C sessions than men’s academies (1.6±0.6 vs. 2.3±0.9, p=0.005). Relatively, fewer women’s academy S&C coaches (6%) used Olympic weightlifting movements than men’s academy S&C coaches (32%, p=0.030). Relatively, more women’s academy coaches (47%) used the Nordic hamstring exercise (NHE) compared to men’s academy coaches (15%, p=0.006), but relatively more women’s vs. men’s first team coaches (61% vs. 38%, p=0.028) and women’s vs. men’s academy (61% vs. 38% coaches, p=0.049) utilised rating of perceived exertion-based load prescriptions. Conclusion Notable differences in S&C practice exist between coaches of men’s and women’s soccer squads, particularly at academy level. Fewer weekly S&C sessions in women academy players may have implications for physical development, while the greater use of subjective load prescriptions in both academy and first team women’s squads may lead to sub-optimal performance gains.
Chidamide stacked in magnetic polypyrrole nano-composites counter thermotolerance and metastasis for visualized cancer photothermal therapy

Abstract Photothermal therapy (PTT) has become one of the most promising therapies in cancer treatment as its noninvasiveness, high selectivity, and favorable compliance in clinic. However, tumor thermotolerance and distal metastasis reduce its efficacy, becoming the bottleneck of applying PTT in clinic. In this study, a chidamide-loaded magnetic polypyrrole nanocomposite (CMPP) has been fabricated as a visualized cancer photothermal agent (PTA) to counter tumor thermotolerance and metastasis. The efficacy of CMPP was characterized by in vitro and in vivo assays. As a result, this kind of magnetic polypyrrole nanocomposites were black spherical nanoparticles, possessing a favorable photothermal effect and the suitable particle size of 176.97 ± 1.45 nm with a chidamide loading rate of 12.92 ± 0.45%. Besides, comparing with PTT, CMPP exhibited significantly higher cytotoxicity and cellular apoptosis rate in two tumor cell lines (B16-F10 and HepG2). In vivo study, the mice showed obvious near-infrared (NIR) and magnetic resonance imaging (MRI) dual-modal imaging at tumor sites and sentinel lymph nodes (SLNs); on the other hand, magnetic targeting guided CMPP achieved a cure level on melanoma-bearing mice through preventing metastasis and thermotolerance. Overall, with high loading efficiency of chidamide and strong magnetic targeting to tumor sites and SLNs, CMPP could significantly raise efficiency of PTT by targeting tumor thermotolerance and metastasis, and this strategy may be exploited therapeutically to upgrade PTT with MPP as one of appropriate carriers for histone deacetylase inhibitors (HDACis).
It Is Not What Happens to You But How You React to It That Matters

Abstract We examined the moderating role of posttraumatic stress disorder (PTSD) in the association between trauma and impulsive behaviors. Adult women (N = 97) with a history of childhood sexual abuse (CSA; n = 26), rape in adulthood (n = 21), both CSA and adult rape (n = 25), or no history of sexual trauma (n = 25) completed self-report questionnaires. PTSD symptoms were positively associated with self-harm and with stealing and accident proneness, but not with sexual impulsivity. Trauma group had no independent associations with impulsive behaviors. PTSD reexperiencing symptoms interacted with trauma group such that reexperiencing symptoms were positively associated with self-harm for the two trauma groups that included CSA but not for the control and adult rape–only groups. Overall, results indicate that PTSD symptoms—more so than the occurrence of trauma itself—associate with impulsive behavior. Results highlight the importance of assessing posttraumatic symptomatology, and not just trauma occurrence, when aiming to prevent or treat impulsive behaviors.
Knowledge of evidence-based practices for PTSD among mental health court judges

Mental health courts offer access to community-based care for defendants with psychiatric disorders, including posttraumatic stress disorder (PTSD). However, limited information is available on how judges make treatment decisions about evidence-based practices. In this qualitative study, we interviewed mental health court judges to evaluate: (1) perspectives toward the role of PTSD in criminal behavior; (2) knowledge about evidence-based practice for PTSD; (3) treatment decisions for defendants with PTSD; and (4) treatment decisions for defendants at risk for suicide, a common comorbidity with PTSD. We hypothesized that mental health court judges would report low familiarity with evidence-based practices for PTSD despite wide recognition of the impact of trauma on criminal behavior. Methods: Mental health court judges (N = 11, 60% women, 60% between 50–59 years) were recruited from 7 states in the US and completed a demographics questionnaire and semi-structured qualitative interview that was transcribed and double-coded. Results: Judges in mental health court unanimously agreed that PTSD is highly prevalent among their defendants, but that they had not having received formal education about evidence-based practices for PTSD. They reported relying on their team members to provide recommendations for treatment planning and viewed their role as the enforcer of the treatment teams’ suggestions. Finally, judges also reported that suicide prevention is an important consideration and that there is a need for universal suicide risk assessments. Conclusions: These findings have implications for continuing education among judges in mental health court, and we recommend mandated training to increase awareness of evidence-based practices for PTSD and suicide prevention.
Curcumin relieved the rheumatoid arthritis progression via modulating the linc00052/miR-126-5p/PIAS2 axis

ABSTRACT Curcumin, with its antioxidant, anti-inflammatory, and antitumor properties, is widely used in the treatment of bone disorders, including rheumatoid arthritis (RA). We investigated the effects of curcumin on fibroblast-like synoviocytes in RA and its underlying mechanism. mRNA and microRNA (miRNA) expression levels were determined using reverse transcription-quantitative polymerase chain reaction. Cellular functions were detected using cell counting kit-8, 5-ethynyl-2’-deoxyuridine, Transwell, and flow cytometric assays. Enzyme-linked immunosorbent assay was performed to measure the cytokine release. Western blotting was used to determine the protein expression levels. An in vivo assay was performed to verify the role of linc00052 in RA. Curcumin promoted apoptosis and inhibited the growth, migration, and invasion of RA fibroblast-like synovial (RAFLS) cells. Curcumin treatment suppressed the inflammatory response of RAFLS cells. Moreover, curcumin increased linc00052 levels, and linc00052 knockdown reversed the effects of curcumin. Additionally, linc00052 functioned as a competing endogenous RNA to upregulate the expression of the protein inhibitor of activated STAT 2 (PIAS2) by sponging miR-126-5p. Curcumin inhibited the Janus kinase 2 (JAK2)/signal transducer and activator of transcription 3 (STAT3) signaling pathway. In vivo assays showed that curcumin decreased the arthritis score and improved inflammatory infiltration and synovial cell proliferation. These results reveal that curcumin protects against RA by regulating the inc00052/miR-126-5p/PIAS2 axis through JAK2/STAT3 signaling pathway. Graphical abstract
Empirical Research on Network Size and Technological Progress

The aim of this paper is to examine the correlation between network size and technological progress in China. This study mainly focuses on three aspects. First, we use a data envelopment analysis (DEA) model to calculate the efficiency of technological progress. The result shows that Beijing, Heilongjiang, Shanghai, Jiangsu and Zhejiang, Fujian, Shandong, Hubei, Hunan and Guangdong are at the low level. Tianjin, Hebei, Shanxi, Henan, Guangxi, Hainan, Chongqing, Sichuan, Guizhou, Yunnan and Xinjiang are at the medium level. Shanxi, Liaoning, Jilin, Anhui, Jiangxi, Xizang, Shaanxi, Gansu, Qinghai and Ningxia are at the high level. Second, we use an ordinary least square (OLS) model, an econometric model, to estimate the relationship between the efficiency of technological progress and network size. The result shows that the efficiency of technological progress and network size are significantly related. Finally, we use Structural Holes, a complex network approach, to analyze the correlation of network size in various regions. Keyword: Efficiency of technological progress, Network Size, DEA model, OLS model, Structural Holes
Multimodal Pipeline for Collection of Misinformation Data from Telegram

The paper presents the outcomes of AI-COVID19, our project aimed at better understanding of misinformation flow about COVID-19 across social media platforms. The specific focus of the study reported in this paper is on collecting data from Telegram groups which are active in promotion of COVID-related misinformation. Our corpus collected so far contains around 28 million words, from almost one million messages. Given that a substantial portion of misinformation flow in social media is spread via multimodal means, such as images and video, we have also developed a mechanism for utilising such channels via producing automatic transcripts for videos and automatic classification for images into such categories as memes, screenshots of posts and other kinds of images. The accuracy of the image classification pipeline is around 87%.
Mapping suburban bicycle lanes using street scene images and deep learning

On-road bicycle lanes improve safety for cyclists, and encourage participation in cycling for active transport and recreation. With many local authorities responsible for portions of the infrastructure, official maps and datasets of bicycle lanes may be out-of-date and incomplete. Even “crowdsourced” databases may have significant gaps, especially outside popular metropolitan areas. This thesis presents a method to create a map of bicycle lanes in a survey area by taking sample street scene images from each road, and then applying a deep learning model that has been trained to recognise bicycle lane symbols. The list of coordinates where bicycle lane markings are detected is then correlated to geospatial data about the road network to record bicycle lane routes. The method was applied to successfully build a map for a survey area in the outer suburbs of Melbourne. It was able to identify bicycle lanes not previously recorded in the official state government dataset, OpenStreetMap, or the “biking” layer of Google Maps.