Miracle-dz/UniFAR-FTUs huggingface dataset:
Using observational epidemiology to evaluate COVID-19 vaccines: integrating traditional methods with new data sources and tools

Although clinical trials are necessary for vaccine approval, observational epidemiology will be required to evaluate the long-term effectiveness, safety, and population impacts of newly approved COVID-19 vaccines under real-world field conditions. In this commentary, I argue that a hybrid approach that combines new data sources and tools, including COVID-19 vaccine registries, with traditional epidemiological methods will be needed to evaluate COVID-19 vaccines using observational epidemiology. Wherever possible, primary data collection, active surveillance, and linkage with existing population-based cohorts should be leveraged to supplement secondary data sources and passive surveillance systems. Evidence-informed public health decision making around provincial COVID-19 immunization programs will need to account for potential biases, incomplete or conflicting information, and heterogeneity across subpopulations.
Contraction $\mathcal{L}_1$-Adaptive Control using Gaussian Processes

We present $\mathcal{CL}_1$-$\mathcal{GP}$, a control framework that enables safe simultaneous learning and control for systems subject to uncertainties. The two main constituents are contraction theory-based $\mathcal{L}_1$ ($\mathcal{CL}_1$) control and Bayesian learning in the form of Gaussian process (GP) regression. The $\mathcal{CL}_1$ controller ensures that control objectives are met while providing safety certificates. Furthermore, $\mathcal{CL}_1$-$\mathcal{GP}$ incorporates any available data into a GP model of uncertainties, which improves performance and enables the motion planner to achieve optimality safely. This way, the safe operation of the system is always guaranteed, even during the learning transients. We provide a few illustrative examples for the safe learning and control of planar quadrotor systems in a variety of environments.
Structure analysis of CaTi1−x Sn x O3 (x = 0.0–1.0) solid solutions

CaTi1−x Sn x O3 (x = 0.0–1.0) solid solutions were prepared by solid-state reaction at 1450 °C. Rietveld refinement of their powder X-ray diffraction patterns revealed that all the solid solutions crystallized in orthorhombic cells with the perovskite-type structure, the space group Pbnm. The refined unit-cell parameters linearly increased with nominal tin contents x.
Towards a Molecular-level Understanding of Organic Aerosol Composition

Towards a Molecular-level Understanding of Organic Aerosol Composition Laxminarasimha Reddy Yatavelli Chair of the Supervisory Committee: Associate Professor Joel Thornton Department of Atmospheric Sciences Aerosol organic matter significantly contributes to the total aerosol burden in the atmosphere, but significant uncertainties related to sources and removal processes persist due, in part, to a poor understanding of the species which make up gas and aerosol-phase organic matter. Fast, in-situ, and speciated measurements are needed to elucidate chemical and physical mechanisms controlling the sources and sinks of aerosol organics. This dissertation describes the development of a novel technique to provide high time resolution, in-situ speciated measurements of gas and aerosol-phase organic matter. The method is termed micro orifice volatilization impactor chemical ionization mass spectrometer (MOVI-CIMS) and couples two well proven techniques, inertial impaction and chemical ionization. Gas-phase compounds are analyzed while particles are collected on a post. This collection step is followed by thermal desorption in an inert atmosphere to detect condensed-phase compounds. Differentiation between gas and condensed-phase compounds can likely occur on hourly or shorter timescales. The unique aspects of this approach are the use of an impactor with 100 nozzles that allows particle collection at a pressure within 15% of ambient and the ability to use a wide suite of negative and positive reagent ions. A sample flow rate of 10 L min −1 results in a cutpoint diameter (d50, diameter of 50% collection efficiency) of 0.13 μm. I demonstrate the capabilities of this technique by applying it to the determination of monoand dicarboxylic acid vapor pressures and studies of the heterogeneous oxidation of oleic acid aerosol particles using a Quadrupole mass spectrometer (QMS) To eliminate the inherent limitation that QMSs have, I modified the MOVI-CIMS technique by coupling it to a high-resolution time-of-flight mass spectrometer (MOVICI-HTOFMS). The TOF analyzer allows collection of a large range (>500 Th) of molecular ions in fraction of a second. In addition, the high mass resolving power and mass accuracy provided by the HTOF analyzer aids in accurate mass determination of the detected compounds thus making it possible to estimate their elemental composition. Preliminary calibrations show that the technique is very sensitive with detection limit in the nanogram range, especially for dicarboxylic acids.
A ug 2 02 0 Design-Based Uncertainty for Quasi-Experiments ∗

Social scientists are often interested in estimating causal effects in settings where all units in the population are observed (e.g. all 50 US states). Design-based approaches, which view the treatment as the random object of interest, may be more appealing than standard sampling-based approaches in such contexts. This paper develops a design-based theory of uncertainty suitable for quasi-experimental settings, in which the researcher estimates the treatment effect as if treatment was randomly assigned, but in reality treatment probabilities may depend in unknown ways on the potential outcomes. We first study the properties of the simple difference-in-means (SDIM) estimator. The SDIM is unbiased for a finite-population design-based analog to the average treatment effect on the treated (ATT) if treatment probabilities are uncorrelated with the potential outcomes in a finite population sense. We further derive expressions for the variance of the SDIM estimator and a central limit theorem under sequences of finite populations with growing sample size. We then show how our results can be applied to analyze the distribution and estimand of difference-in-differences (DiD) and two-stage least squares (2SLS) from a design-based perspective when treatment is not completely randomly assigned. We thank Isaiah Andrews, Iavor Bojinov, Peng Ding, Pedro Sant’Anna, Yotam Shem-Tov, and Neil Shephard for helpful comments and suggestions. Rambachan gratefully acknowledges support from the NSF Graduate Research Fellowship under Grant DGE1745303. Harvard University, Department of Economics. Email: asheshr@g.harvard. edu Microsoft Research. Email: Jonathan.Roth@microsoft.com
Preservative Moisture-Repellent Treatments for Wooden Packing Boxes

THE WOODS COMMONLY USED for shipping crates and boxes have nb appreciable natural resistance to fungi and insects. Consequently, containers exposed to the elements are usually attacked by biological deteriorating agents. These agents include decay fungi that destroy wood, and staining and molding fungi that cause little loss in strength but can obscure stencil markings. For fungus decay it is necessary, of course, for the wood to be wet (above
Evaluation of the curative effects of Bailing capsules for treating chronic obstructive pulmonary disease

Abstract Background: The goal of the present study is to evaluate the efficacy and safety of Bailing capsules, which is a traditional Chinese drug that can improve lung functionality when used to treat chronic obstructive pulmonary disease (COPD) patients. Methods: A comprehensive search will be performed on the following primary electronic databases: PubMed, EMBASE, Cochrane Library, Chinese National Knowledge Infrastructure, and WanFang database. A search of secondary sources includes reference lists of included studies. Two pairs of review authors will screen and scrutinize selected articles. This study will analyze continuous data as mean differences and dichotomous data as odds ratios, both with 95% confidence intervals. A sensitivity analysis will also be conducted to evaluate the stableness of the outcomes. RevMan 5.3 software was adopted to accomplish all the statistical analysis. Results: The results obtained in this research shall be published in a peer-reviewed journal. Conclusion: Based on the interpretations of the results, useful conclusions will be presented. These conclusions will offer additional insights with useful evidence to assess whether it is viable to use Bailing capsules as an effective and safety treatment option for COPD. Ethics and dissemination: The present work does not involve any humans or animals; therefore, ethical approval is not needed. Systematic review registration: March 26, 2021.osf.io/kvgbu. (https://osf.io/kvgbu/)
International Journal of Instruction

This study utilized the quantitative meta-analysis technique to integrate chemistry education research findings conducted in the Philippines covering the period 2005 – 2016. It aimed to describe and examine the effects of teaching methodologies on academic performance in the secondary chemistry teaching-learning process. A search procedure and broad literature review were conducted to identify the potential and qualified chemistry studies from both published and unpublished graduate theses, dissertations and journal articles. Meta-analysis was effectively and systematically carried out through study acquisition, study coding, determination of inter-rater reliability, establishing inclusion criteria, computation of effect size including mean and interpreting the analyses. A total of 51 studies met the criteria and have qualified in the meta-analysis. Results presented that a statistically significant positive effect (Cohen’s d = 1.208) was observed in the use of teaching interventions on academic performance. The findings affirmed the effectiveness of the use of varied teaching strategies in chemistry education toward student achievement in contrast to the traditional teaching method. The metaanalytic review revealed that during the last decade, the incorporation of other avenues of learning via innovative teaching methods promotes academic gain. As far as quality of instruction is concerned, the findings give a holistic understanding of the current educational practices in chemistry instruction that would serve as basis for future educational reforms.
Potential energy functions for atomic solids. IV: Reproducing the properties of more than one solid phase

Potentials have been derived for carbon and tin by optimizing to the energies, bond lengths and phonon frequencies of the diamond structures and the energies and bond lengths of the other experimentally known solid phase, graphitic carbon and β-tin, respectively. In both cases the other cubic solids (SC, BCC and FCC) and 2-dimensional networks (triangles and squares) are shown to have higher energies. Potentials have also been produced for silicon and germanium which reproduce the diamond structure data, and the lattice energies and distances predicted by electronic structure calculations for the SC, BCC and FCC solids
Defeating Architectures for Low-Latency Services: The Case of L4S

—For a couple years, new services with low-latency requirements appear to be a major challenge for the future Internet. Many optimizations, all targeting the latency reduction have been proposed, and among them, re-architecting the network packet processing has been particularly considered. In this effort, the L4S proposal aims at allowing both classic and low-latency trafﬁc to cohabit within a single node architecture. However, although this architecture sounds promising for latency improvement, it also lacks an in-depth study of security issues. More speciﬁcally, it is possible for an attacker to manipulate end-to-end protocols to defeat the low-latency feature of L4S nodes. In this paper, we analyze the set of weaknesses in L4S that could be exploited by an attacker to perform a set of malicious actions whose purpose is to defeat the low-latency.
What is Different about Eating Disorders for Those with Autistic Spectrum Condition?

Introduction: Eating Disorders (EDs) are increasingly recognised as a common comorbid condition in autistic spectrum condition (ASC). The diagnosis of ASC may be delayed in those who present with EDs, especially in females who account for 90% of such presentations. They often mask autistic symptoms by copying their neurotypical peers. This can have adverse consequences, as standard therapeutic approaches to the management of EDs are often ineffective at achieving complete recovery in those with ASC, even among those whose body weight is restored. Methods: We reviewed the recent literature to explore the common factors defining ED’s in ASC and illustrated this with examples from those with lived experience to define potential for therapeutic strategies. Results: Anorexia Nervosa (AN) is the commonest subtype of ED in ASC and is contributed to by a high prevalence of associated gastrointestinal disorders. Anxiety over sensory issues with taste and smell are often a significant factor. Biosocial factors such as cognitive rigidity, obsession, compulsion and rigidity are also important. The role of specific issues such as alexithymia, hyperactivity, rejection sensitive dysphoria, personality disorder and gender dysphoria has been previously understated. EDs are likely to be less to do with body image and more to be a consequence of rigid or ritualistic behaviour patterns driven by ASC. Conclusions: Treatment approaches must account for the unique challenges faced by this group. Art and drama therapy may be of help. Cognitive Remediation Therapy, dietitian-led interventions and clinician/carer/patient education have been proposed but have not yet been trialled extensively. We recommend that involvement of those with lived experience of these conditions is an essential part of treatment planning
Data-Driven Stochastic Distribution Network Reconfiguration

Distribution network reconfiguration (DNR) is indispensable for the operation of active distribution networks. To address the uncertainties of renewables and variables loads, a data-driven stochastic DNR model is proposed for day-ahead DNR of three-phase unbalanced distribution networks. The switching cost and expected costs resulted from power losses and load balance are minimized. Based on the analysis of historical data, the probability distribution of DG output and load demand is derived using a data-driven method. To improve computation efficiency, a mixed-integer linear programming problem is formulated using linearization techniques. Numerical tests are carried out in an IEEE unbalanced benchmark. The comparison with the conventional deterministic method verifies the effectiveness of the proposed method.
M ar 2 00 9 Multi-Field Inflation on the Landscape

We examine a wide class of multi-field inflationary models based on fields that decay or stabilize during inflation in a staggered fashion. The fields driving assisted inflation are on flat, short stretches, before they encounter a sharp drop; whenever a field encounters such a drop due to its slow roll evolution, its energy is transferred to other degrees of freedom, i.e. radiation. The rate at which fields decay is determined dynamically and it is not a free parameter in this class of models. To compute observables, we generalize the analytic framework of staggered inflation, allowing for more general initial conditions and varying potentials. By searching for generic situations arising on the landscape, we arrive at a setup involving linear or hilltop potentials and evenly spread out initial field values. This scenario is not more fine tuned than large-field models, despite the fact that many more degrees of freedom are involved. Further, the η-problem can be alleviated. The additional decrease of the potential energy caused by the decay of fields provides leading order contribution to observables, such as the scalar and tensor spectral index or the tensor to scalar ratio, for which we derive general expressions. We compare the predictions with WMAP5 constraints and find that hilltop potentials are borderline ruled out at the 2σ-level, while linear potentials are in excellent agreement with observations. We further comment on additional sources of gravitational waves and non-Gaussianities that could serve as a smoking gun for staggered inflation. email:diana.battefeld(AT)helsinki.fi Electronic address: tbattefe(AT)princeton.edu
Efficient calculation of local dose distribution for 1 response modelling in proton and ion beams

12 We present an algorithm for fast and accurate computation of the local dose distribution in MeV beams of protons, carbon ions or other heavy-charged particles. It uses compound Poisson-process modelling of track interaction and succesive convolutions for fast computation. It can handle mixed particle fields over a wide range of fluences. Since the local dose distribution is the essential part of several approaches to model detector efficiency or cellular response it has potential use in ion-beam dosimetry and radiotherapy.
EXTRACELLULAR GLUTAMINASE-FREE L-ASPARAGINASE FROM TRICHODERMA VIRIDE F2: PURIFICATION, BIOCHEMICAL CHARACTERIZATION AND EVALUATION OF ITS POTENTIAL IN MITIGATING ACRYLAMIDE FORMATION IN STARCHY FRIED FOOD

L-asparaginase is an antitumor agent that suppresses cancer cell growth by eliminating L-asparagine from malignant cells. However, the intrinsic glutaminase activity is responsible for significant life-threatening adverse effects. Therefore, glutaminase-free L-asparaginase is far required to improve the therapeutic efficacy of L-asparaginase treatment. L-asparaginase was also used to combat the development of acrylamide in foods rich in carbohydrates cooked at high temperatures. Therefore, this study explores the purification and characterization of glutaminase-free L-asparaginase from Trichoderma viride F2 using agro-industrial residues as substrate. The enzyme was purified 36-folds with 688.1 U/mg specific activity and a final yield of 38.9% through ethanol precipitation, gel filtration on Sephadex G-100 followed by Sephadex G-200. The purified L-asparaginase is monomeric with a molecular mass of 57 kDa and exhibited optimum activity at pH 7.5 and 37 °C, which is relatively close to the human body's internal environment. The purified L-asparaginase showed high affinity and catalytic efficiency towards its natural substrate L-asparagine with Km and Vmax of 1.2 mM and 71.3 U/mL, respectively, and did not exhibit any intrinsic glutaminase activity. Among the salts tested, the univalent cations Na+ and K+ enhanced the activity by 145.7% and 163.5%, respectively, while the presence of Ag+ and Fe+3 displayed a considerable loss in activity. The enzyme showed a good anti-oxidant activity with IC50 of 66. 1μg/mL and was able to convert L-asparagine exist in potatoes to L-aspartic acid and ammonia, suggesting its use as anti-carcinogenic agent and as potential food industry candidate to mitigate acrylamide content in starchy fried food.
Mixed ligand complexes of Ru(II) complexes with 5,6-dimethyl -3-pyridin-2- yl-[1,2,4]triazine: Synthesis, Characterization and Quantum Chemical Study using Semi-empirical PM 3 and Ab initio Methods

The condensation product between 2,6-diacetylpyridinedihydrazone and pyridine-2aldehyde were prepared and this was reacted with cis-Ru(phen)2Cl2.2H2O and cisRu(bipy)2Cl2.2H2O to form two mixed – ligand complexes. The complexes were characterized using elemental analyses, infrared and electronic spectra, mass spectra, 1 H NMR, and the molar conductances determined. The elemental analyses data is satisfactory with the formation of the prepared complexes which conformed to the electrocyclisation of the introduced ligand. The mass spectra data is consistent with the molecular structural patterns of the complexes. The conductivity measurement revealed that the complexes were 1:2 electrolytes. Quantum chemical methods are used to calculate the binding and stabilization energies of the two complexes which suggested that binding and stabilization energies of [Ru(phen)2L] 2+ are thermodynamically more favourable compared to [Ru(bipy)2L] 2+ . © 2013 Elixir All rights reserved ARTICLE INF O Articl e h istory: Received: 7 June 2013; Received in revised form: 24 July 2013; Accepted: 6 August 2013;
Semantic Based Security for health data over Sensor Network

: An acquiescent juxtaposition of wireless technologies, micro-electromechanical systems (MEMS), micro-services and the internet paved an ecosystem named Internet of Things (IoT), which ascertains link between physical objects that are reachable through the internet. The embedded technology in those objects succors them to interact with internal states or the external milieu, which in turn influences on decisions. This new connectivity, bridges the gap between physical objects and digital world to improve the quality and productivity of life, has become common and going beyond laptops and smartphones, in applications like cars, smart homes, smart cities, healthcare, retails, energy management agriculture, wearables etc. IoT connects smart objects together (through internet and intelligent sensors) using internet protocol, and make them to be read, controlled, and managed at any time at anywhere. Since this communication is in the public environment, these devices are vulnerable to attacks, and hence the security and privacy are vitiated. Detection of abnormality in propositional information must be followed by recovery action to ensure the correct semantics of the frame network. This paper focuses on building a semantic based security platform to analyze the data received from sensors using Hidden Markov Model (HMM), semantic sensor network ontology, and temporal ontology to detect the malicious attack data. The HMM is used for reasoning purpose and the label for visible states are created. The Stream Annotation Ontology is used to represent the quality of the data over the Semantic Sensor Network Ontology.
Interroger des Lacs de Données en utilisant Spark & Presto

Squerall est un outil permettant l’interrogation de sources de données hétérogènes à large échelle en utilisant à bon escient des moteurs de traitement dédiés aux larges volumes de données issus de la littérature: Spark et Presto. Les requêtes à destination des lacs de données sont évaluées à la volée, i.e., directement sur les sources originelles sans procéder à de quelconques transformations préalables des données. Nous démontrons la capacité qu’a Squerall à interagir avec cinq sources différentes parmi lesquelles Cassandra et MongoDB. En particulier, nous mettons en évidence que notre outil peut joindre ensemble plusieurs sources en même temps, tout en montrant qu’étendre la couverture à d’autres sources potentielles reste simple. Des interfaces graphiques sont aussi mises à disposition pour (1) construire les requêtes SPARQL et (2) mettre en place les fichiers de configuration nécessaires.