Miracle-dz/UniFAR-FTUs huggingface dataset:
Testing Frequency Matters | An Evaluation of the Diagnostic Performance of a SARS-CoV-2 Rapid Antigen Test in United States Correctional Facilities

Abstract Background: The CDC recommends serial rapid antigen assay collection within congregate facilities for screening and outbreak testing. Though modeling and observational studies from community and long-term care facilities have shown serial collection provides adequate sensitivity and specificity, the diagnostic accuracy of this testing strategy within correctional facilities remains unknown. Methods: Using Connecticut Department of Corrections (DOC) data from November 21st 2020 to June 15th 2021, we estimated the accuracy of a rapid assay, BinaxNOW, under three collection strategies, a single test in isolation and two and three serial tests separated by 1-4 day intervals. Diagnostic accuracy metrics were estimated in relation to RT-PCRs collected within one day before the first or after the last included rapid antigen tests in a series. Results: Of the 17,669 residents who contributed at least one RT-PCR or rapid antigen during the study period, 3,979 contributed [≥]1 paired rapid antigen test series. In relation to RT-PCR, the three-rapid antigen test strategy had a sensitivity of 89.6% (95% confidence intervals: 86.1-92.6%) and specificity of 97.2% (CI: 95.1-98.3%). The sensitivities for two and one-rapid antigen test strategy were 75.2% and 52.8%, respectively, and the specificities were 98.5% and 99.4%, respectively. The sensitivity was higher among symptomatic residents and when the RT-PCR was collected before the rapid antigen tests. Conclusions: We found the serial collection of an antigen test resulted in high diagnostic accuracy. These findings support serial testing within correctional facilities for outbreak investigation, screening, and when rapid detection is required (such as intakes or transfers).
Inactivation of Cytochrome P450 3A4 but not P450 3A5 by OSI-930, a Thiophene-containing Anticancer Drug

An investigational anti-cancer agent that contains a thiophene moiety, 3-[(quinolin-4-ylmethyl)- amino]- N-[4-trifluoromethox)phenyl]thiophene-2-carboxamide (OSI-930), was tested to investigate its ability to modulate the activities of several cytochrome P450 enzymes. Results showed that OSI-930 inactivated purified, recombinant cytochrome P450 3A4 in the reconstituted system in a mechanism-based manner. The inactivation was dependent on cytochrome b 5 and required NADPH. Catalase did not protect against the inactivation. No inactivation was observed in studies with human 2B6, 2D6, or 3A5 either in the presence or in the absence of b 5 . The inactivation of 3A4 by OSI-930 was time-and concentration-dependent. The inactivation of the 7-benzyloxy-4-(trifluoromethyl) coumarin (BFC) catalytic activity of 3A4 was characterized by a K I of 24 μ M and a k inact of 0.04 min -1 . This K I is significantly greater than the clinical OSI-930 C max of 1.7 μ M at MTD indicating clinical drug interactions of OSI-930 via this pathway are not likely. Spectral analysis of the inactivated protein indicated that the decrease in the reduced CO spectrum at 450 nm was comparable to the amount of inactivation, thereby suggesting that the inactivation was primarily due to modification of the heme. HPLC analysis with detection at 400 nm showed a loss of heme comparable to the activity loss, but a modified heme was not detected. This result suggests either that the heme must have been modified enough so as not to be observed in a HPLC chromatograph or, possibly, that it was destroyed. The partition ratio for the inactivation of P450 3A4 was approximately 23, suggesting that this P450 3A4-mediated pathway occurs with about 4% frequency during the metabolism of OSI-930. Modeling studies on the binding of OSI-930 into the active site of the P450
Inverse simulation techniques applied to the external validation of nonlinear models

The external validation of a continuous system model is a process which involves comparison of the behaviour of a mathematical model with that of areal system which it is intended to represent. Although most methods of external validation involve comparisons of chosen output variables of the system and the model, an alternative is to compare the inputs needed to achieve a specified output time history. The paper provides an outline of established techniques for the development of inverse models and describes the application of one approach to the external validation of a nonlinear dynamic model of a laboratory-scale system involving two inter-connected tanks of water. It is shown that inverse simulation can provide a potentially useful tool for external validation of nonlinear dynamic models, especially when used in conjunction with other validation techniques.
Physiological stress and higher reproductive success in bumblebees are both associated with intensive agriculture

Free-living organisms face multiple stressors in their habitats, and habitat quality often affects development and life history traits. Increasing pressures of agricultural intensification have been shown to influence diversity and abundance of insect pollinators, and it may affect their elemental composition as well. We compared reproductive success, body concentration of carbon (C) and nitrogen (N), and C/N ratio, each considered as indicators of stress, in the buff-tailed bumblebee (Bombus terrestris). Bumblebee hives were placed in oilseed rape fields and semi-natural old apple orchards. Flowering season in oilseed rape fields was longer than that in apple orchards. Reproductive output was significantly higher in oilseed rape fields than in apple orchards, while the C/N ratio of queens and workers, an indicator of physiological stress, was lower in apple orchards, where bumblebees had significantly higher body N concentration. We concluded that a more productive habitat, oilseed rape fields, offers bumblebees more opportunities to increase their fitness than a more natural habitat, old apple orchards, which was achieved at the expense of physiological stress, evidenced as a significantly higher C/N ratio observed in bumblebees inhabiting oilseed rape fields.
Emergency Scheduling of Multiple Imaging Satellites with Dynamic Merging

Scheduling plays a significant role in improving observation effectiveness of imaging satellites. Although extensive satellite scheduling algorithms have been proposed, none of them focuses on emergency scheduling in dynamic environment. In this paper, a novel dynamic emergency scheduling model of multiple imaging satellites is established. To improve user’s satisfaction ratio and resource utilization, we propose a novel task dynamic merging strategy, developing an alternative task set establishment (ATSE) algorithm used for dynamic merging. Besides, a novel dynamic emergency scheduling algorithm called DMDES is presented, which considers the dynamic merging. To demonstrate the superiority of our DM-DES, we conduct extensive experiments by simulations to compare DM-DES with an existing algorithm––RBHA as well as a baseline algorithm––DES. The experimental results indicate that DM-DES improves the scheduling quality of others and is suitable for emergency scheduling.
Review of Regenerative design theories for school buildings in the tropics of India

2014, том 14, № 4 5 Introduction The definition of school as per oxford dictionary is “An institution for educating people”. In the ancient times in India, the schools (called as Gurukuls) were the centres of learning in natural setting; where the overall development of the child in terms of physical, mental and spiritual took place living with the nature. As the climate in India is predominately tropical, the gurukuls used to be open schools where all pupils (shishyas) lived together as equals irrespective of their social standing, learn from the teacher (guru) and car-ry out daily chores. These traditional schools were located in a natural environment away from the hustle and bustle of the town. The materials used in these traditional schools were locally available materials. These schools were the best example of environmen-tally responsive architecture where the shishyas learnt the principles of sustainability right from their early childhood. A contemporary example of gurukul is, Visva Bharti campus, Shantiniketan, West Bengal, India set up by the Nobel Laureate Guru Ravindra Nath Tagore, Fig. 1 (a). It is India’s most renowned places of higher learning in a natural context. The contemporary Indian school buildings are mostly concrete structures, Fig. 1 (b) and devoid of environmental integration, standing as disintegrated elements on the site. Hence, with technological ad-vancement, schools instead of the centre of learning the lessons of living a natural life are the centre of
PENGARUH ROTASI AUDIT, WORKLOAD, DAN SPESIALISASI TERHADAP KUALITAS AUDIT PADA PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BURSA EFEK INDONESIA PADA TAHUN 2009-2013

This purpose research is for to understand the effect of structure corporate governance to performance companies listing on the Indonesia Stock Exchange in 2012-2014. The sample used in this study were manufacturing sector companies for the year 2012-2014. The method used in data collection is the secondary method of data collection, financial report its being obtained from website IDX. The method of analysis of this study used multiple regression . The result from research is indicate that structure corporate governance is significant effect on performance of manufacturing companies. Tujuan penelitian ini adalah untuk memahami efek dari struktur tata kelola perusahaan pada perusahaan yang listing di Bursa Efek Indonesia pada 2012-2014. Sampel yang digunakan dalam penelitian ini adalah perusahaan manufaktur sektor untuk tahun 2012-2014. Metode yang digunakan dalam pengumpulan data adalah metode pengumpulan data sekunder berupa laporan keuangan yang diperoleh dari website Bursa Efek Indonesia. Metode analisis penelitian ini menggunakan regresi berganda. Hasil dari penelitian adalah menunjukkan struktur yang tata kelola perusahaan yang berpengaruh signifikan terhadap kinerja perusahaan manufaktur.
Triple targeting of HER receptors overcomes heregulin-mediated resistance to EGFR blockade in colorectal cancer.

Current treatment options for patients with advanced colorectal cancers (CRC) include anti-EGFR/HER1 therapy with the blocking antibody cetuximab. Although a subset of patients with KRAS wild-type disease initially respond to the treatment, resistance develops in almost all cases. Relapse has been associated with the production of the ligand heregulin (HRG) and/or compensatory signaling involving the receptor tyrosine kinases HER2 and HER3. Here we provide evidence that triple HER receptor blockade based on a newly developed bispecific EGFRxHER3-targeting antibody (scDb-Fc) together with the HER2 blocking antibody trastuzumab effectively inhibited HRG-induced HER receptor phosphorylation, downstream signaling, proliferation and stem cell expansion of DiFi and LIM1215 CRC cells. Comparative analyses revealed that the biological activity of scDb-Fc plus trastuzumab was sometimes even superior to that of the combination of the parental antibodies, with PI3K/Akt pathway inhibition correlating with improved therapeutic response and apoptosis induction as seen by single cell analysis. Importantly, growth suppression by triple HER targeting was recapitulated in primary KRAS wild-type patient-derived organoid (PDO) cultures exposed to HRG. Collectively, our results provide strong support for a pan-HER receptor blocking approach to combat anti-EGFR therapy resistance of KRAS wild-type CRC tumors mediated by the upregulation of HRG and/or HER2/HER3 signaling.
Dynamical Control of Interlayer Excitons and Trions in WSe$_2$/Mo$_{0.5}$W$_{0.5}$Se$_2$ Heterobilayer via Tunable Near-Field Cavity

WSe2/Mo0.5W0. 5Se2 Heterobilayer via Tunable Near-Field Cavity Yeonjeong Koo, Hyeongwoo Lee, Tatiana Ivanova, Ali Kefayati, Vasili Perebeinos, Ekaterina Khestanova, Vasily Kravtsov, and Kyoung-Duck Park Department of Physics, Pohang University of Science and Technology (POSTECH), Pohang 37673, Korea School of Physics and Engineering, ITMO University, Saint Petersburg 197101, Russia Department of Electrical Engineering, University at Buffalo, The State University of New York, Buffalo, New York 14260, United States Email: vasily.kravtsov@metalab.ifmo. ru, parklab@postech.ac. kr
Usability Measurement Model (UMM): A New Model for Measuring Websites Usability

Usability is commonly recognized as one of the most important quality factors of information systems. Different usability models for traditional information systems have been proposed. The current movement towards web-based information systems (WBIS) necessitates the need for special usability models for these systems. Accordingly questions such as how to measure the usability of WBIS and what to be considered during the development of websites to attain a high usability are raised. As a result, modeling usability of WBIS becomes an active researches filed and a new usability models for WBIS have been proposed. The goal of this paper is to develop a conceptual robust model that measure usability of WBIS. To achieve this goal we use an analytical methodology to analyze existing usability models to investigate their interrelationships, strength, and weaknesses. As a result, our developed model, the Usability Measurement Model (UMM), is built on the advantages and strength of usability models; ISO-9126-1 software quality standard, McCall model, website QEM model and 2QCV3Q model. We define the high-level usability factors in the new usability model as; accessibility, understandability, learnability, operability, attractiveness, and navigability, which are all defined in previous models, but not in one model. The new model defines a set of new sub factors; findability, clear labeling links, languages support, guidelines, help documents, descriptive comments, page load time, clear fonts, consistency, relevant graphics, good alignment of page elements, menu bar, link to home, use of frames, and search engine. To test the applicability and output of the UMM, we use the model in measuring usability of websites of three Sudanese universities. The attained results show that UMM is a promising, highly efficient usability model.
ClarET: Pre-training a Correlation-Aware Context-To-Event Transformer for Event-Centric Generation and Classification

Generating new events given context with correlated ones plays a crucial role in many event-centric reasoning tasks. Existing works either limit their scope to specific scenarios or overlook event-level correlations. In this paper, we propose to pre-train a general Correlation-aware context-to-Event Transformer (ClarET) for event-centric reasoning. To achieve this, we propose three novel event-centric objectives, i.e., whole event recovering, contrastive event-correlation encoding and prompt-based event locating, which highlight event-level correlations with effective training. The proposed ClarET is applicable to a wide range of event-centric reasoning scenarios, considering its versatility of (i) event-correlation types (e.g., causal, temporal, contrast), (ii) application formulations (i.e., generation and classification), and (iii) reasoning types (e.g., abductive, counterfactual and ending reasoning). Empirical fine-tuning results, as well as zero- and few-shot learning, on 9 benchmarks (5 generation and 4 classification tasks covering 4 reasoning types with diverse event correlations), verify its effectiveness and generalization ability.
A general alternating-direction implicit Newton method for solving complex continuous-time algebraic Riccati matrix equation

In this paper, applying the Newton method, we transform the complex continuous-time algebraic Riccati matrix equation into a Lyapunov equation. Then, we introduce an efficient general alternating-direction implicit (GADI) method to solve the Lyapunov equation. The inexact Newton-GADI method is presented to save computational amount effectively. Moreover, we analyze the convergence of the Newton-GADI method. The convergence rate of the Newton-GADI and Newton-ADI methods is compared by analyzing their spectral radii. Furthermore, we give a way to select the quasi-optimal parameter. Corresponding numerical tests are shown to illustrate the effectiveness of the proposed algorithms.
Non-Markovian quantum state diffusion for spin environments

We introduce an exact open system method to describe the dynamics of quantum systems that are strongly coupled to specific types of environments comprising of spins, such as central spin systems. Our theory is similar to the established non-Markovian quantum state diffusion theory, but for a spin bath instead of a Gaussian bath. The method allows us to represent the time-evolved reduced state of the system as an ensemble average of stochastically evolving pure states. We present a comprehensive theory for arbitrary linear spin environments at both zero and finite temperatures. Furthermore, we introduce a hierarchical expansion method that enables the numerical computation of the time evolution of the stochastic pure states, facilitating a numerical solution of the open system problem in relevant strong coupling regimes.
Efficient Analog CAM Design

Content Addressable Memories (CAMs) are considered a key-enabler for in-memory computing (IMC). IMC shows order of magnitude improvement in energy efficiency and throughput compared to traditional computing techniques. Recently, analog CAMs (aCAMs) were proposed as a means to improve storage density and energy efficiency. In this work, we propose two new aCAM cells to improve data encoding and robustness as compared to existing aCAM cells. We propose a methodology to choose the margin and interval width for data encoding. In addition, we perform a comprehensive comparison against prior work in terms of the number of intervals, noise sensitivity, dynamic range, energy, latency, area, and probability of failure.
Adversarial Patterns: Building Robust Android Malware Classifiers

Deep learning-based classifiers have substantially improved recognition of malware samples. However, these classifiers can be vulnerable to adversarial input perturbations. Any vulnerability in malware classifiers poses significant threats to the platforms they defend. Therefore, to create stronger defense models against malware, we must understand the patterns in input perturbations caused by an adversary. This survey paper presents a comprehensive study on adversarial machine learning for android malware classifiers. We first present an extensive background in building a machine learning classifier for android malware, covering both image-based and text-based feature extraction approaches. Then, we examine the pattern and advancements in the state-of-the-art research in evasion attacks and defenses. Finally, we present guidelines for designing robust malware classifiers and enlist research directions for the future.
Truncation Error Analysis for an Accurate Nonlocal Manifold Poisson Model with Dirichlet Boundary

In this work, we introduced a class of nonlocal models to accurately approximate the Poisson model on manifolds that are embedded in high dimensional Euclid spaces with Dirichlet boundary. In comparison to the existing nonlocal Poisson models, instead of utilizing volumetric boundary constraint to reduce the truncation error to its local counterpart, we rely on the Poisson equation itself along the boundary to explicitly express the second order normal derivative by some geometry-based terms, so that to create a new model with $\mathcal{O}(\delta)$ truncation error along the $2\delta-$boundary layer and $\mathcal{O}(\delta^2)$ at interior, with $\delta$ be the nonlocal interaction horizon. Our concentration is on the construction and the truncation error analysis of such nonlocal model. The control on the truncation error is currently optimal among all nonlocal models, and is sufficient to attain second order localization rate that will be derived in our subsequent work.
Cloud-Edge Training Architecture for Sim-to-Real Deep Reinforcement Learning

Deep reinforcement learning (DRL) is a promising approach to solve complex control tasks by learning policies through interactions with the environment. However, the training of DRL policies requires large amounts of training experiences, making it impractical to learn the policy directly on physical systems. Sim-to-real approaches leverage simulations to pretrain DRL policies and then deploy them in the real world. Unfortunately, the direct real-world deployment of pretrained policies usually suffers from performance deterioration due to the different dynamics, known as the reality gap. Recent sim-to-real methods, such as domain randomization and domain adaptation, focus on improving the robustness of the pretrained agents. Nevertheless, the simulation-trained policies often need to be tuned with real-world data to reach optimal performance, which is challenging due to the high cost of real-world samples. This work proposes a distributed cloud-edge architecture to train DRL agents in the real world in real-time. In the architecture, the inference and training are assigned to the edge and cloud, separating the real-time control loop from the computationally expensive training loop. To overcome the reality gap, our architecture exploits sim-to-real transfer strategies to continue the training of simulation-pretrained agents on a physical system. We demonstrate its applicability on a physical inverted-pendulum control system, analyzing critical parameters. The real-world experiments show that our architecture can adapt the pretrained DRL agents to unseen dynamics consistently and efficiently.11A video showing a real-world training process under the proposed method can be found from https://youtu.be/hMY9-c0SST0.
From spin foams to area metric dynamics to gravitons

Although spin foams arose as quantizations of the length metric degrees of freedom, the quantum configuration space is rather based on areas as more fundamental variables. This is also highlighted by the semi-classical limit of four-dimensional spin foam models, which is described by the Area Regge action. Despite its central importance to spin foams the dynamics encoded by the Area Regge action is only poorly understood, in particular in the continuum limit. We perform here a systematic investigation of the dynamics defined by the Area Regge action on a regular centrally subdivided hypercubical lattice. This choice of lattice avoids many problems of the non-subdivided hypercubical lattice, for which the Area Regge action is singular. The regularity of the lattice allows to extract the continuum limit and its corrections, order by order in the lattice constant. We show that, contrary to widespread expectations which arose from the so-called flatness problem of spin foams, the continuum limit of the Area Regge action does describe to leading order the same graviton dynamics as general relativity. The next-to-leading order correction to the effective action for the length metric is of second order in the lattice constant, and is given by a quadratic term in the Weyl curvature tensor. This correction can be understood to originate from an underlying dynamics of area metrics. This suggests that the continuum limit of spin foam dynamics does lead to massless gravitons, and that the leading order quantum corrections can be understood to emerge from a generalization of the configuration space from length to area metrics.