Miracle-dz/UniFAR-FTUs huggingface dataset:
New physics with cold molecules : precise microwave spectroscopy of CH and the development of a microwave trap

Cold polar molecules provide unique opportunities to test fundamental physics and chemistry. Their permanent electric dipole moments and rich internal structure arising from their vibrational and rotational motion, makes them sensitive probes for new physics. These features also make them ideal for studying ultracold chemistry, for simulating the behaviour of stronglyinteracting many-body quantum systems, and for quantum information science. This thesis describes a number of advances in cold molecule physics. The optimum method for producing an intense, pulsed, supersonic beam of cold CH molecules is investigated, resulting in a beam with 3.5 × 109 ground state CH molecules per steradian per shot. The beam has a translational temperature of 400 mK and a velocity that is tuneable between 400 and 1800 m s−1. The lowest-lying Λ-doublet transitions of ground state CH, at 3.3 GHz and 0.7 GHz, are exceptionally sensitive to variations in the fine-structure constant α and the electron-to-proton mass ratio μ. Many modern theories predict that these constants may depend on time, position, or local matter density. Using a novel spectroscopic method, the frequencies of these microwave transitions are measured with accuracy down to 3 Hz. By comparing to radio-astronomical observations, the hypothesis that fundamental constants may differ between the high and low density environments of the Earth and the interstellar medium of the Milky Way is tested. These measurements find no variation and set upper limits of |∆α/α| < 2.1×10−7 and |∆μ/μ| < 4.3×10−7. The frequency of the lowest millimetre-wave transition of CH, near 533 GHz, is also measured with an accuracy of 0.6 kHz. The development of a novel type of trap for ground-state polar molecules is presented. Trapping polar molecules is a necessary condition to cool them to ultracold temperatures of 1 μK and below. The trap uses a high intensity microwave field in a Fabry-Pérot resonator. Experimental and theoretical investigations are presented that explore the modes of the cavity, how to obtain the highest possible quality factor, and how to optimally couple the microwave power into the cavity. Finally, a cold supersonic beam of BH molecules is developed. This molecule appears to be particularly well-suited to direct laser cooling due to its favourable rotational structure and Franck-Condon factors. The laser cooling concept is described, and a first spectroscopic investigation of the relevant molecular structure is presented.
A New Hybrid ARAR and Neural Network Model for Multi-Step Ahead Wind Speed Forecasting in Three Regions of Pakistan

Wind is one of the most essential sources of clean, environmental friendly, socially constructive, economically beneficial, and renewable energy. To intuit the potential of this energy in a region the accurate wind speed modeling and forecasting are crucially important, even for planning, conversion of wind energy to electricity, energy trading, and reducing instability. However, accurate prediction is difficult due to intermittency and intrinsic complexity in wind speed data. This study aims to suggest a more appropriate model for accurate wind speed forecasting in the Jhimpir, Gharo, and Talhar, regions of Sindh, Pakistan. Therefore, the present study combined the Autoregressive-Autoregressive (ARAR) and Artificial Neural Network (ANN) models to propose a new hybrid ARAR-ANN model for better prediction by precisely capturing different patterns of the wind speed time-series data sets. The proposed hybrid model is efficient in modeling, reducing statistical errors, and forecasting the wind speed effectively. The performance of the proposed hybrid ARAR-ANN model is compared using three error-statistics and Nash-Sutcliffe efficiency-coefficient. The empirical results of the four performance indices fully demonstrated the superiority of the hybrid ARAR-ANN model than persistence model, ARAR, ANN and SVM. Indeed, the proposed model is an effective and feasible approach for wind speed forecasting.
Susceptibility to Severe Acute Respiratory Syndrome Coronavirus 2 Infection Among Children and Adults: A Seroprevalence Study of Family Households in the Barcelona Metropolitan Region, Spain

Abstract Background Susceptibility of children and adults to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and persistence of antibody response to the virus after infection resolution remain poorly understood, despite their significant public health implications. Methods A prospective cross-sectional seroprevalence study with volunteer families that included at least 1 first-reported adult case positive by SARS-CoV-2 by polymerase chain reaction (PCR) and at least 1 child aged <15 years living in the same household under strict home confinement was conducted in the metropolitan Barcelona Health Region, Spain, during the pandemic period 28 April 2020–3 June 2020. All household members were tested at home using a rapid SARS-CoV-2 antibody assay with finger prick–obtained capillary blood. Results A total of 381 family households including 381 first-reported PCR-positive adult cases and 1084 contacts (672 children, 412 adults) were enrolled. SARS-CoV-2 seroprevalence rates were 17.6% (118 of 672) in children and 18.7% (77 of 335) in adult contacts (P = .64). Among first-reported cases, seropositivity rates varied from 84.0% in adults previously hospitalized and tested within 6 weeks since the first positive PCR result to 31.5% in those not hospitalized and tested after that lag time (P < .001). Nearly all (99.9%) positive children were asymptomatic or had mild symptoms. Conclusions Children appear to have similar probability as adults to become infected by SARS-CoV-2 in quarantined family households but remain largely asymptomatic. Adult antibody protection against SARS-CoV-2 seems to be weak beyond 6 weeks post-infection confirmation, especially in cases that have experienced mild disease.
Correlates of the Mental Fitness of Female High School Freshmen: Focus on Multidimensional Empathy and Brain Function

We examined the association between multidimensional empathy, brain function, and mental fitness and identified correlates of mental fitness. In total, 146 female high school freshmen from a South Korean school participated in this cross-sectional study. Data were collected from March to April 2019, using a self-report questionnaire and quantitative electro-encephalographic data (QEEG). Instruments included the Interpersonal Reactivity Index and the Mental Fitness Scale, to access multidimensional empathy and mental fitness. Prefrontal cortex brain function was assessed with the brain quotient measure from the QEEG during free time after school. Data were analyzed using descriptive statistics, Pearson’s correlation coefficient, and multiple regression analysis. Mental fitness had statistically significant relationships with multidimensional empathy (r = 0.36, p < 0.001) and brain quotient (r = 0.23, p = 0.005). Demographic factors affecting mental fitness included satisfaction with school life (β = 0.23, p = 0.001) and economic status (β = 0.17, p = 0.024). Factors from the subscales of multidimensional empathy included perspective taking (β = 0.26, p = 0.001), fantasy (β = 0.22, p = 0.004), and personal distress (β = −0.19, p = 0.010); and the brain function factor was brain quotient (β = 0.14, p = 0.038). The explanatory power of the model was 49.4% (F = 14.44, p < 0.001). There is a need for a concrete and objective understanding of mental fitness in adolescents to develop intervention programs for freshmen with various maladaptation problems.
Using LSTM Network to Predict Circulating Water Pump Bearing Condition on Coal Fired Power Plant

Condition Based Maintenance is one method to predict bearing condition. However, this method requires high accuracy of Remaining Useful Life estimation. Estimating Remaining Useful Life can be very difficult especially when the amount of data sensor is too large. A machine learning approach could be useful in order to understand all the hidden correlations between the sensor measurements, allowing an accurate RUL prediction. Conventional machine learning such as Auto Regressive Moving Average and RNN conventional failed to predict the accurate prediction because produce high mean absolute percentage error. Long-Short Term Memory network is a best machine learning method that needed to predict the condition of the equipment because it has the ability to store memories for a long time simultaneously and can understand complex correlations between data thus providing information that is very useful in determining Remaining Useful Life. This study uses the Long-Short Term Memory method to predict circulating water pump bearing condition from vibration signal. The modelling results show accurate signal predictions. It can be seen from the estimated value of the resulting Long-Short Term Memory model equal to the actual signal value. The accuracy of the results of the Long-Short Term Memory modeling is also supported from the results of research conducted by previous authors, where modeling using the Long-Short Term Memory method produces the smallest mean absolute percentage error of the two other conventional algorithm methods (Auto Regressive Moving Average and plain Recurrent Neural Network) which is 3.8%. The accuracy of the Long-Short Term Memory model shows the reliability of the architecture so that the plant gets a warning before damage occurs.
Diagnostic Value of Initial Chest CT Findings for the Need of ICU Treatment/Intubation in Patients with COVID-19

Computed tomography (CT) plays an important role in the diagnosis of COVID-19. The aim of this study was to evaluate a simple, semi-quantitative method that can be used for identifying patients in need of subsequent intensive care unit (ICU) treatment and intubation. We retrospectively analyzed the initial CT scans of 28 patients who tested positive for SARS-CoV-2 at our Level-I center. The extent of lung involvement on CT was classified both subjectively and with a simple semi-quantitative method measuring the affected area at three lung levels. Competing risks Cox regression was used to identify factors associated with the time to ICU admission and intubation. Their potential diagnostic ability was assessed with receiver operating characteristic (ROC)/area under the ROC curves (AUC) analysis. A 10% increase in the affected lung parenchyma area increased the instantaneous risk of intubation (hazard ratio (HR) = 2.00) and the instantaneous risk of ICU admission (HR 1.73). The semi-quantitative measurement outperformed the subjective assessment diagnostic ability (AUC = 85.6% for ICU treatment, 71.9% for intubation). This simple measurement of the involved lung area in initial CT scans of COVID-19 patients may allow early identification of patients in need of ICU treatment/intubation and thus help make optimal use of limited ICU/ventilation resources in hospitals.
Feature Extraction for Heroin-Use Classification Using Imbalanced Random Forest Methods

Abstract Background and aims: The National Survey on Drug Use and Health (NSDUH) contains a large number of responses and many features. This study aims to identify features from within NSDUH that are important in classifying heroin use. Proper implementation of random forest (RF) techniques copes with the highly imbalanced nature of heroin usage among respondents to identify features that are prominent in classification models involving nonlinear combinations of predictive variables. To date, methods for the proper application of RF to imbalanced medical datasets have not been defined. Methods: Three different RF classification techniques are applied to the 2016 NSDUH. The techniques are compared using scoring criteria, including area under the precision recall curve (AUPRC), to identify the best model. Variable importance scores (VIS) are checked for stability across the three models and the VIS from the best model are used to highlight features and categories of features that most influence the classification of heroin users. Findings: The best performing method was RF with random oversampling (AUPRC = 0.5437). The category of features regarding other drug use was most important (average z-scored VIS = 1.66) followed by age-of-first-use features (0.32). The most important individual feature was cocaine usage (z-scored VIS = 11.05), followed by crack usage (6.51). The most important individual feature other than specific drug use flags was the use of marijuana under the age of 18 (3.11). This study demonstrates a method for the use of RF in feature extraction from imbalanced medical datasets with many predictors.
Steroid Hormone Receptor and Infiltrating Immune Cell Status Reveals Therapeutic Vulnerabilities of ESR1-Mutant Breast Cancer

Targetable alterations in MBC, including AR, CHI3L1, and ISG, arise following estrogen-deprivation, and ER-mutant metastases may respond to immunotherapies due to elevated PD-L1+ macrophages. Mutations in ESR1 that confer constitutive estrogen receptor alpha (ER) activity in the absence of ligand are acquired by ≥40% of metastatic breast cancers (MBC) resistant to adjuvant aromatase inhibitor (AI) therapy. To identify targetable vulnerabilities in MBC, we examined steroid hormone receptors and tumor-infiltrating immune cells in metastatic lesions with or without ER mutations. ER and progesterone receptor (PR) were significantly lower in metastases with wild-type (WT) ER compared with those with mutant ER, suggesting that metastases that evade AI therapy by mechanism(s) other than acquiring ER mutations lose dependency on ER and PR. Metastases with mutant ER had significantly higher T regulatory and Th cells, total macrophages, and programmed death ligand-1 (PD-L1)-positive immune-suppressive macrophages than those with WT ER. Breast cancer cells with CRISPR-Cas9–edited ER (D538G, Y537S, or WT) and patient-derived xenografts harboring mutant or WT ER revealed genes and proteins elevated in mutant ER cells, including androgen receptor (AR), chitinase-3-like protein 1 (CHI3L1), and IFN-stimulated genes (ISG). Targeting these proteins blunted the selective advantage of ER-mutant tumor cells to survive estrogen deprivation, anchorage independence, and invasion. Thus, patients with mutant ER MBC might respond to standard-of-care fulvestrant or other selective ER degraders when combined with AR or CHI3L1 inhibition, perhaps with the addition of immunotherapy. Significance: Targetable alterations in MBC, including AR, CHI3L1, and ISG, arise following estrogen-deprivation, and ER-mutant metastases may respond to immunotherapies due to elevated PD-L1+ macrophages. See related article by Arnesen et al., p. 539
Total nitrogen removal in two-step biofiltration

A one-year study was carried out on two semi-industrial submerged up-flow biofilters - a pre-denitrification (pre-DN) step followed by a nitrifying (N) step, designed to treat the primary settled municipal wastewater of a full scale plant for both carbon and nitrogen removal. Performances of the pre-DN step have been investigated showing high removal denitrifying capacities – 1 to 1.2 kg NO3−–N removed per m3 of reactor per day–, obtained with high TSS and carbon loading rates, at a water velocity up to 21.5 m3/ m2.h. The complete treatment plant – primary settlement + pre-DN/N loop – has demonstrated a nitrogen removal efficiency ranging from 70% without any additional carbon, up to 85% with methanol. COD and TSS removal rates were 91% and 97% respectively. The above results show that two submerged biofilters in series form a treatment line suitable for nitrogen removal. This technical choice leads to very compact full scale plants such as Ahlen WWTP (Germany, 85 000 PE).
The Aggregate Model of Business Valuation by Three Methods

An express model that combines three main methods of assessing a company’s value is considered. An analytical formula for the value is derived under the assumption that some specific parameters applicable for mature companies are constant. The problem of value optimization for some combinations of parameters is solved. Calculations were made for one of the largest Russian companies.
Short-Term Lesion Change Detection for Melanoma Screening With Novel Siamese Neural Network

Short-term monitoring of lesion changes has been a widely accepted clinical guideline for melanoma screening. When there is a significant change of a melanocytic lesion at three months, the lesion will be excised to exclude melanoma. However, the decision on change or no-change heavily depends on the experience and bias of individual clinicians, which is subjective. For the first time, a novel deep learning based method is developed in this paper for automatically detecting short-term lesion changes in melanoma screening. The lesion change detection is formulated as a task measuring the similarity between two dermoscopy images taken for a lesion in a short time-frame, and a novel Siamese structure based deep network is proposed to produce the decision: changed (i.e. not similar) or unchanged (i.e. similar enough). Under the Siamese framework, a novel structure, namely Tensorial Regression Process, is proposed to extract the global features of lesion images, in addition to deep convolutional features. In order to mimic the decision-making process of clinicians who often focus more on regions with specific patterns when comparing a pair of lesion images, a segmentation loss (SegLoss) is further devised and incorporated into the proposed network as a regularization term. To evaluate the proposed method, an in-house dataset with 1,000 pairs of lesion images taken in a short time-frame at a clinical melanoma centre was established. Experimental results on this first-of-a-kind large dataset indicate that the proposed model is promising in detecting the short-term lesion change for objective melanoma screening.
Impact of the Use of a Larger Forearm Artery on the Efficacy and Safety of Transradial and Transulnar Access: A Randomized Trial with Preprocedural Ultrasonography

(1) Background: We aimed to assess the impact of the selection of a larger radial or ulnar artery on the efficacy of access and vascular complications, based on preprocedural ultrasonographic examination. (2) Methods: This prospective, randomized trial included patients undergoing coronary angiography (CAG) or percutaneous coronary intervention (PCI). Patients were randomized into either a larger ulnar artery (UA) or radial artery (RA) group or smaller UA/RA group. The primary endpoint was successful CAG/PCI without crossover to another artery. The secondary endpoints were incidences of radial or ulnar artery occlusion (RAO/UAO) at the 24 h and 30 day follow-up. (3) Results: Between 2017 and 2018, 200 patients (107 men, mean age 68 ± 8 years) were enrolled. The success of CAG/PCI via the access site was 98% and 83% (p < 0.001) in the larger UA/RA group and smaller UA/RA group, respectively. The independent factor for CAG/PCI success was the larger artery (OR 9.8, 95%CI 2.11–45.5; p < 0.005). The larger UA/RA was superior, with RAO/UAO at 24 h: OR 0.07, 95%CI 0.09–0.61; p < 0.016; and RAO/UAO at 30 days: OR 0.25, 95%CI 0.05–0.12; p < 0.001. (4) Conclusions: Larger artery access was shown to be more efficient and safer than recessive forearm artery access.
Co-Administration of Fendiline Hydrochloride Enhances Chemotherapeutic Efficacy of Cisplatin in Neuroblastoma Treatment

Despite significant improvement of neuroblastoma (NB) patients’ survival due to recent treatment advancements in recent years, NB is still associated with high mortality rate. In search of novel strategies to increase NB’s susceptibility to pharmacological treatments, we investigated the in vitro and in vivo effects of fendiline hydrochloride as an enhancer of cisplatin antitumor activity. To assess the modulation of fendiline treatment on cisplatin responses, we used in vitro (evaluating NB cell proliferation by XCELLigence technology and colony formation, and gene expression by RT-PCR) and in vivo (NB cell grafts in NOD-SCID mice) models of NB. NB cell treatment with fendiline induced the expression of the ncRNA NDM29, leading to cell differentiation and to the reduction of the expression of MDRs/ABC transporters linked to multidrug resistance. These events were correlated to higher NB cell susceptibility to cisplatin and, consequently, increased its cytotoxic potency. In vivo, this drug interaction causes an enhanced ability of cisplatin to induce apoptosis in NB masses, resulting in tumor growth reduction and prolonged animal survival rate. Thus, the administration of fendiline might be a possible novel therapeutic approach to increase cisplatin efficacy in aggressive and poorly responsive NB cases.
Influence of dapivirine vaginal ring use on cervicovaginal immunity and functional microbiome in adolescent girls

Objective: The antiretroviral-based dapivirine vaginal ring reduced HIV risk among women in phase III clinical trials. However, limited data exists on the impact of dapivirine on the vaginal microenvironment in adolescents. Design: A comprehensive metaproteomics approach was used to assess host proteome and microbiome changes in cervicovaginal mucus with dapivirine ring use in adolescents enrolled in the MTN-023/IPM 030 (MTN-023) trial. Methods: Participants were randomized 3 : 1 to use dapivirine or placebo vaginal rings monthly for 6 months. Cervicovaginal samples from a subset of 35 participants (8 placebo, 27 dapivirine) were analyzed. Results: Mass spectrometry analysis identified 405 human and 2467 bacterial proteins belonging to 15 unique genera. The host proteome belonged to many functional pathways primarily related to inflammation. When stratified by study treatment arm, 18 (4.4%) and 28 (6.9%) human proteins were differentially abundant (adjusted P < 0.05) between baseline and follow-up in the placebo and dapivirine arms, respectively. The vaginal microbiome was predominantly composed of Lactobacillus, Gardnerella, and Prevotella. Although bacterial taxa did not differ by arm or change significantly, Lactobacillus crispatus increased (P < 0.001) and Lactobacillus iners decreased (P < 0.001) during the 6-month follow-up. There were no significant differences in bacterial functions by arm or time in the trial. Protected vaginal sex significantly associated with decreased neutrophil inflammatory biomarkers and may be associated with changes in bacterial taxa and metabolism. Conclusion: Condom use may associate with differences to inflammation and bacterial function but dapivirine ring use does not, thereby supporting the mucosal safety profile of this vaginal ring for adolescents.
Caregiver behaviors and childhood maladaptive grief: Initial validation of the Grief Facilitation Inventory

Abstract The Grief Facilitation Inventory (GFI) is a newly-developed measure of caregiver behaviors theorized to facilitate or hinder children’s adaptive grief reactions. We examine its factor structure, reliability, and validity. An exploratory factor analysis identified four factors: Ongoing Connection, Existential Continuity/Support, Caregiver Grief Expression, and Grief Inhibition/Avoidance. Both child- and caregiver-report versions had adequate-to-good internal consistency. The child-report GFI showed evidence of criterion-referenced validity via significant correlations with measures of child maladaptive grief and other psychological symptoms. Results provide preliminary evidence of the reliability, validity, and clinical utility of the GFI as a measure of caregiver grief-facilitation behaviors.