Miracle-dz/UniFAR-FTUs huggingface dataset:
High-Efficiency WPT Systems for Potable Electronics Based on DC-Bias-Voltage- Controlled Variable Capacitor

The power density of wireless power transfer (WPT) systems employed in portable electronics can be enhanced by increasing the operating frequency, but at the expense of lower efficiency due to increased switching and parasitic losses. This article proposes a method, based on the dc-bias-voltage-controlled variable capacitor (VC) and variable frequency (VF) regulation, to improve the overall efficiency of the WPT system for portable electronics. The method uses VC on the primary side to detune the resonant tank and dynamically regulate the output power, while VF is employed to improve the system efficiency using a look-up table based on a power loss model. A dc bias voltage control module with self-supply ability is employed to control the equivalent capacitance of the VC. A control strategy is proposed to regulate both VC and VF. Experimental results of a 150 W prototype are presented to demonstrate that constant output voltage can be maintained despite a wide load range, with an overall efficiency range of 82.1% (@25W) and 92.2% (@150W).
Qualitative Exploration of Enabler, Purpose, and Benefits of Digitalisation in the Informal Sector: Understanding the Role of Bricolage Among Women Entrepreneurs

Women entrepreneurship literature is blooming and largely indicate the challenges faced by women entrepreneurs in setting up and scaling businesses. Much of the research on women’s entrepreneurship revolves around entrepreneurial activities in the formal sector. Women entrepreneurship in the informal sector is still less explored. In this study, we explore the enablers and benefits of digitalisation among women entrepreneurs in the informal sector in the Indian context. We employ a qualitative study to unravel the experiences of women entrepreneurs (n = 30). Data were collected through interviews, and analysis was carried out through Voyant tools and Atlas.ti. Findings revealed that respondents attempted to bricolage with existing resources to run and manage their businesses. Family support, social influence, and willingness to learn emerged as key enablers of digitalisation. Digitalisation benefitted women entrepreneurs in several ways including ease of transaction, getting feedback, selling and promoting their offerings, and business collaborations. Based on the findings, a model of enabler, purpose, and benefits of digitalisation is proposed. Findings are discussed in the light of existing literature and future research agenda is presented.
Revised refractive index and absorption of In_1-xGa_xAs_yP_1-y lattice-matched to InP in transparent and absorption IR-region

For the revision of the refractive indices and absorption of the In1-xGaxAsyP1-y material system lattice matched to InP ellipsometric measurements were carried out. For the first time general parameters for the Tanguy model were determined from these measurements of these material compositions. With the help of these determined Tanguy parameters, the refractive indices and the absorption coefficients were reviewed in transparent and absorption region which includes the near and mid-infrared region. Furthermore, an estimation of the group velocity and the chromatic dispersion is presented for these material compositions.
Surveying Flux Density in Galaxies with Apparent Large Black Holes at Millimeter/Submillimeter Wavelengths

We present millimeter and submillimeter continuum observations for 36 sources with potentially large black hole shadows at 230 and 345 GHz using the Submillimeter Array. The sources are selected based on the criterion of the large diameter of the black hole shadows. Our motivation is to explore the nature of the accretion flow of the potential candidates of low-luminosity active galactic nuclei (LLAGNs) through photometry at millimeter/submillimeter wavelengths. The detected result serves as the pathfinder of future high-angular resolution observations such as the Event Horizon Telescope. As a result, we successfully detected 17 and eight sources at 230 and 345 GHz, respectively. We reveal that three of the detected sources (IC 310, NGC 1277, and NGC 5846) show significant excess at millimeter/submillimeter wavelengths in comparison with the extrapolation both from low-frequency radio and infrared, which are considered to be attributed to the extended jet and dust component, respectively. One possible explanation is that these excesses are associated with the hot accretion flow onto the supermassive black holes of the LLAGNs. By adopting the advection-dominated accretion flow model's semi-analytic model, we obtained the upper bound of the mass accretion rate. Those are less than 10−2 ṀEDD , where ṀEDD is the Eddington mass accretion rate computed via the Eddington luminosity. This is in good agreement with the expected range of the LLAGNs. The ∼200 mJy flux densities and negative spectral index of IC 1459 within millimeter and submillimeter wavelengths make it a promising candidate for future submillimeter high-angular resolution experiments for imaging the black hole shadow.
H-Mode Pedestal and L-H Transition Studies on Alcator C-Mod

Abstract H-mode research on Alcator C-Mod is described, with a focus on the edge transport barrier (ETB). ETB pedestals are characterized using several diagnostics, leading to a thorough description of profile structure in H-mode. L-H transition criteria are discussed, along with the fast evolution of the pedestal following the L-H transition. H-mode regimes are described in terms of their edge transport characteristics and the local edge parameters favoring each. Empirical scalings of the pedestal with operational parameters are found, helping to illuminate physics governing the pedestal structure, and the relationship between edge transport and global confinement is discussed. Dimensionless comparisons between discharges on different tokamaks are discussed. Finally, ongoing work and directions for the future are described.
Variation in North American bumble bee nest success and colony sizes under captive rearing conditions

Abstract Of the 265 known bumble bee (Bombus) species, knowledge of colony lifecycle is derived from relatively few species. As interest in Bombus commercialization and conservation grows, it is becoming increasingly important to understand colony growth dynamics across a variety of species since variation exists in nest success, colony growth, and reproductive output. In this study, we reported successful nest initiation and establishment rates of colonies and generated a timeline of colony development for 15 western North American Bombus species, which were captively reared from wild-caught gynes from 2009 to 2019. Additionally, we assessed variation in colony size among 5 western North American Bombus species from 2015 to 2018. Nest initiation and establishment rates varied greatly among species, ranging from 5–76.1% and 0–54.6%, respectively. Bombus griseocollis had the highest rates of nest success across the 11-yr period, followed by B. occidentalis, B. vosnesenskii, and B. huntii. Furthermore, days to nest initiation and days to nest establishment varied among species, ranging from 8.4 to 27.7 days and 32.7 to 47 days. Colony size also differed significantly among species with B. huntii and B. vosnesenskii producing more worker/drone cells than B. griseocollis, B. occidentalis, and B. vancouverensis. Additionally, gyne production differed significantly among species with B. huntii colonies producing more gynes than B. vosnesenskii. Results from this study increase knowledge of systematic nesting biology for numerous western North American Bombus species under captive rearing conditions, which can further improve rearing techniques available to conservationists and researchers.
Inhibition of YAP1 activity ameliorates acute lung injury through promotion of M2 macrophage polarization

Abstract The balance of M1/M2 macrophage polarization plays an important role in regulating inflammation during acute lung injury (ALI). Yes‐associated protein (YAP1) is a key protein in the Hippo–YAP1 signaling pathway and is involved in macrophage polarization. We aimed to determine the role of YAP1 in pulmonary inflammation following ALI and regulation of M1/M2 polarization. Pulmonary inflammation and injury with upregulation of YAP1 were observed in lipopolysaccharide (LPS)‐induced ALI. The YAP1 inhibitor, verteporfin, attenuated pulmonary inflammation and improved lung function in ALI mice. Moreover, verteporfin promoted M2 polarization and inhibited M1 polarization in the lung tissues of ALI mice and LPS‐treated bone marrow‐derived macrophages (BMMs). Additionally, siRNA knockdown confirmed that silencing Yap1 decreased chemokine ligand 2 (CCL2) expression and promoted M2 polarization, whereas silencing large tumor suppressor 1 (Lats1) increased CCL2 expression and induced M1 polarization in LPS‐treated BMMs. To investigate the role of inflammatory macrophages in ALI mice, we performed single‐cell RNA sequencing of macrophages isolated from the lungs. Thus, verteporfin could activate the immune‐inflammatory response, promote the potential of M2 macrophages, and alleviate LPS‐induced ALI. Our results reveal a novel mechanism where YAP1‐mediated M2 polarization alleviates ALI. Therefore, inhibition of YAP1 may be a target for the treatment of ALI.
Face Mask Use and Associated Factors Among Students: Mixed Methods Study

Background COVID-19 has gravely affected the world, including students, due to the high level of contracting infections. Objective This study assessed the magnitude of mask use and associated factors among students. Methods A cross-sectional study using mixed methods was conducted among students at Gambella Teachers’ Education and Health Science College, Gambella Region, Southwest Ethiopia, from March 5 to March 30, 2021. The stratified random sampling technique was used. Proportional allocation of samples was used to randomly select case teams, and a simple random sampling technique was used to recruit the students. The data were collected by trained and experienced enumerators. Data were entered into EpiData (version 3.1; EpiData Association) and exported to SPSS (version 22; IBM Corp) for analysis. Logistic regression was executed. The adjusted odds ratio (AOR) with the 95% CI was used to determine the association and strength with the outcome variable. The qualitative data were transcribed, translated, coded, and analyzed using thematic analysis. Then, the themes were used to triangulate the quantitative study. Results The study included a total of 379 participants and yielded a response rate of 95.5% (379/397). The majority of study participants were older than 25 years, with the mean age being 26.34 (SD 5.8) years. This study found that the magnitude of mask use among students was 87% (330/379). The odds of mask use were higher among students who were female (AOR 3.32, 95% CI 1.191-9.248), younger (AOR 2.55, 95% CI 1.155-5.627), agreed that not all persons with COVID-19 develop severe disease (AOR 3.38, 95% CI 1.36-8.41), agreed that there is currently no effective cure (AOR 6.28, 95% CI 1.36-28.99), performed proper washing with soap and water (AOR 0.027, 95% CI 0.004-0.182), had started to stay home (AOR 0.168, 95% CI 0.054-0.52), agreed that COVID-19 is fatal (AOR 0.236, 95% CI 0.084-0.666), agreed that a flu vaccine is sufficient for COVID-19 prevention (AOR 3.874, 95% CI 1.540-9.749), and disinfected equipment and working areas at least once a day (AOR 0.222, 95% CI 0.086-0.575). Conclusions This study found that the magnitude of mask use among students was relatively moderate in Ethiopia. Sex, age, agreeing that not all persons with COVID-19 develop severe disease, agreeing that there is currently no effective cure, performing proper washing with soap and water, starting to stay home, agreeing that COVID-19 is fatal, and agreeing that the flu vaccine is sufficient to prevent COVID-19 were independently associated with mask use among students. Therefore, colleges should aggressively encourage students to wear masks and monitor the implementation of COVID-19 prevention regulations along with the accessibility of masks.
Second-Order Gâteaux Differentiable Bump Functions and Approximations in Banach Spaces

Abstract In this paper we study approximations of convex functions by twice Gâteaux differentiate convex functions. We prove that convex functions (respectively norms) can be approximated by twice Gâteaux differentiate convex functions (respectively norms) in separable Banach spaces which have the Radon-Nikody m property and admit twice Gâteaux differentiable bump functions. New characterizations of spaces isomorphic to Hilbert spaces are shown. Locally uniformly rotund norms that are limits of Ck -smooth norms are constructed in separable spaces which admit Ck -smooth norms.
Feasibility Study and Design of Registration System for Upper Gastrointestinal Bleeding Patients in Isfahan Province

Background: Disease registration is an organized system for collecting, storing, retrieving, analyzing a particular disease or exposure to known substances in a specific population. The aim of this study was to assess the feasibility and design of the registration system for upper gastrointestinal bleeding patients based on patients referring to Al-Zahra and Khorshid hospitals, Isfahan, Iran. Materials and Methods: This study is a research action study in which the members of the registration system team are hospital triage physicians, internal residents in the Emergency department of hospital, subspecialty assistants and gastroenterologists, statisticians (epidemiologists and methodologists), and two trained persons were specified to collect medical information and documents. The data collection tool is a researcher-made checklist. Based on the available tools, the most important criteria related to gastrointestinal bleeding were selected. In the next step, the criteria selected in the council, including team members, were reviewed and a preliminary draft was prepared to record the information of patients. Results: The results indicated the final version of the checklist in three parts including demographic variables (age, sex, education, et al.), main variables (as the minimum data required by a person to register in the checklist (patient's clinical signs)), extended main variables (its information is designed to be used to diagnose, treat, and follow-up the patient in later stages). Conclusion: It seems to be predictable by establishing a system for recording gastrointestinal bleeding diseases, disease prevalence, monitoring services and treatment of patients, survival analysis and evaluation of clinical care outcomes, finding patients at higher risk for emergency treatment, reviewing drug interventions, and interventional activities.
The central limit theorem for the Poisson shot-noise process

The Poisson shot-noise process discussed here takes the form f:oo H(t, s)N(ds), where N(· is the counting measure of a Poisson process and the H(·, s) are independent stochastic processes. Necessary and sufficient conditions are obtained for convergence in distribution, as t ∼ OC, to any infinitely divisible distribution. The main interest is in the explosive transient one-sided shot-noise, Y(t) = f:1 H(t, s)N(ds) where Var Y(t)∼ oc, Here conditions for asymptotic normality are discussed in detail. Important examples include the Poisson cluster point process and the integrated stationary shotnoise.
Policy Gradient in Robust MDPs with Global Convergence Guarantee

Robust Markov decision processes (RMDPs) provide a promising framework for computing reliable policies in the face of model errors. Many successful reinforcement learning algorithms build on variations of policy-gradient methods, but adapting these methods to RMDPs has been challenging. As a result, the applicability of RMDPs to large, practical domains remains limited. This paper proposes a new Double-Loop Robust Policy Gradient (DRPG), the first generic policy gradient method for RMDPs. In contrast with prior robust policy gradient algorithms, DRPG monotonically reduces approximation errors to guarantee convergence to a globally optimal policy in tabular RMDPs. We introduce a novel parametric transition kernel and solve the inner loop robust policy via a gradient-based method. Finally, our numerical results demonstrate the utility of our new algorithm and confirm its global convergence properties.
The HADES RV programme with HARPS-N at TNG

Context. Small rocky planets seem to be very abundant around low-mass M-type stars. Their actual planetary population is however not yet precisely understood. Currently, several surveys aim to expand the statistics with intensive detection campaigns, both photometric and spectroscopic. Aims. The HADES program aims to improve the current statistics through the in-depth analysis of accurate radial-velocity (RV) monitoring in a narrow range of spectral sub-types, with the precision needed to detect small planets with a few Earth masses. Methods. We analyse 106 spectroscopic HARPS-N observations of the active M0-type star GJ 685 taken over the past five years. We combine these data with photometric measurements from different observatories to accurately model the stellar rotation and disentangle its signals from genuine Doppler planetary signals in the RV data. We run an MCMC analysis on the RV and activity index time series to model the planetary and stellar signals present in the data, applying Gaussian Process regression technique to deal with the stellar activity signals. Results. We identify three periodic signals in the RV time series, with periods of 9, 24, and 18 d. Combining the analyses of the photometry of the star with the activity indexes derived from the HARPS-N spectra, we identify the 18 d and 9 d signals as activity-related, corresponding to the stellar rotation period and its first harmonic, respectively. The 24 d signal shows no relation to any activity proxy, and therefore we identify it as a genuine planetary signal. We find the best-fit model describing the Doppler signal of the newly found planet, GJ 685 b, corresponding to an orbital period Pb = 24.160−0.047+0.061 d and a minimum mass MP sin i = 9.0−1.8+1.7 M⊕. We also study a sample of 70 RV-detected M-dwarf planets, and present new statistical evidence of a difference in mass distribution between the populations of single- and multi-planet systems, which can shed new light on the formation mechanisms of low-mass planets around late-type stars.
Retrosynthesis Prediction with Local Template Retrieval

Retrosynthesis, which predicts the reactants of a given target molecule, is an essential task for drug discovery. In recent years, the machine learing based retrosynthesis methods have achieved promising results. In this work, we introduce RetroKNN, a local reaction template retrieval method to further boost the performance of template-based systems with non-parametric retrieval. We first build an atom-template store and a bond-template store that contains the local templates in the training data, then retrieve from these templates with a k-nearest-neighbor (KNN) search during inference. The retrieved templates are combined with neural network predictions as the final output. Furthermore, we propose a lightweight adapter to adjust the weights when combing neural network and KNN predictions conditioned on the hidden representation and the retrieved templates. We conduct comprehensive experiments on two widely used benchmarks, the USPTO-50K and USPTO-MIT. Especially for the top-1 accuracy, we improved 7.1% on the USPTO-50K dataset and 12.0% on the USPTO-MIT dataset.These results demonstrate the effectiveness of our method.
Distributed accelerated proximal conjugate gradient methods for multi-agent constrained optimization problems

The purpose of this paper is to introduce two new classes of accelerated distributed proximal conjugate gradient algorithms for multi-agent constrained optimization problems; given as minimization of a function decomposed as a sum of M number of smooth and M number of nonsmooth functions over the common fixed points of M number of nonlinear mappings. Exploiting the special properties of the cost component function of the objective function and the nonlinear mapping of the constraint problem of each agent, a new inertial accelerated incremental and parallel computing distributed algorithms will be presented based on the combinations of computations of proximal, conjugate gradient and Halpern methods. Some numerical experiments and comparisons are given to illustrate our results.
PILLAR: How to make semi-private learning more effective

In Semi-Supervised Semi-Private (SP) learning, the learner has access to both public unlabelled and private labelled data. We propose a computationally efficient algorithm that, under mild assumptions on the data, provably achieves significantly lower private labelled sample complexity and can be efficiently run on real-world datasets. For this purpose, we leverage the features extracted by networks pre-trained on public (labelled or unlabelled) data, whose distribution can significantly differ from the one on which SP learning is performed. To validate its empirical effectiveness, we propose a wide variety of experiments under tight privacy constraints (\(\epsilon=0.1\)) and with a focus on low-data regimes. In all of these settings, our algorithm exhibits significantly improved performance over available baselines that use similar amounts of public data.
International Spillovers of ECB Interest Rates: Monetary Policy&Information Effects

This paper shows that disregarding the information effects around the European Central Bank monetary policy decision announcements biases its international spillovers. Using data from 23 economies, both Emerging and Advanced, I show that following an identification strategy that disentangles pure monetary policy shocks from information effects lead to international spillovers on industrial production, exchange rates and equity indexes which are between 2 to 3 times larger in magnitude than those arising from following the standard high frequency identification strategy. This bias is driven by pure monetary policy and information effects having intuitively opposite international spillovers. Results are present for a battery of robustness checks: for a sub-sample of ``close'' and ``further away'' countries, for both Emerging and Advanced economies, using local projection techniques and for alternative methods that control for ``information effects''. I argue that this biases may have led a previous literature to disregard or find little international spillovers of ECB rates.
BAA-NGP: Bundle-Adjusting Accelerated Neural Graphics Primitives

Implicit neural representation has emerged as a powerful method for reconstructing 3D scenes from 2D images. Given a set of camera poses and associated images, the models can be trained to synthesize novel, unseen views. In order to expand the use cases for implicit neural representations, we need to incorporate camera pose estimation capabilities as part of the representation learning, as this is necessary for reconstructing scenes from real-world video sequences where cameras are generally not being tracked. Existing approaches like COLMAP and, most recently, bundle-adjusting neural radiance field methods often suffer from lengthy processing times. These delays ranging from hours to days, arise from laborious feature matching, hardware limitations, dense point sampling, and long training times required by a multi-layer perceptron structure with a large number of parameters. To address these challenges, we propose a framework called bundle-adjusting accelerated neural graphics primitives (BAA-NGP). Our approach leverages accelerated sampling and hash encoding to expedite both pose refinement/estimation and 3D scene reconstruction. Experimental results demonstrate that our method achieves a more than 10 to 20 $\times$ speed improvement in novel view synthesis compared to other bundle-adjusting neural radiance field methods without sacrificing the quality of pose estimation. The github repository can be found here https://github.com/IntelLabs/baa-ngp.