Miracle-dz/UniFAR-FTUs huggingface dataset:
Roda, Weston C.; Liu, Suli; Power, Christopher; Li, Michael Y. Modeling the effects of latency reversing drugs during HIV-1 and SIV brain infection with implications for the “shock and kill”

Combination antiretroviral therapy (cART) has greatly increased life expectancy for human immunodeficiency virus-1 (HIV-1)-infected patients. Even given the remarkable success of cART, the virus persists in many different cells and tissues. The presence of viral reservoirs represents a major obstacle to HIV-1 eradication. These viral reservoirs contain latently infected long-lived cells. The “shock and kill” therapeutic strategy aims to reactivate latently infected cells by latency reversing agents (LRAs) and kill these reactivated cells by strategies involving the host immune system. The brain is a natural anatomical reservoir for HIV-1 infection. Brain macrophages, including microglia and perivascular macrophages, display productive HIV-1 infection. A mathematical model was used to analyze the dynamics of latently and productively infected brain macrophages during viral infection and this mathematical model enabled prediction of the effects of LRAs applied to the “shock and kill” strategy in the brain. The model was calibrated using reported data from simian immunodeficiency virus (SIV) studies. Our model produces the overarching observation that effective cART can suppress productively infected brain macrophages but leaves a residual latent viral reservoir in brain macrophages. In addition, our model demonstrates that there exists a parameter regime wherein the “shock and kill” strategy can be safe and effective for SIV infection in the brain. The results indicate that the “shock and kill” strategy can restrict brain viral RNA burden associated with severe neuroinflammation and can lead to the eradication of the latent reservoir of brain macrophages.
Analysis of the Productive Capacity of an Aquaponic System with Macrobrachium Amazonicum (Heller, 1862) and Lettuce Culture (Lactuta Sativa Var. Crispa)

Aquaculture is one of the activities that depend on integrally of availability of water to be developed, both in quantity and quality. The present work aimed to realize one study in the productive capacity of the aquaponic system using farm shrimp (M. amazonicum Heller) with the development olive tree of Lactuta sativa specie. The method used was the experimental one, performing analyzes on physicochemical water parameters: Dissolved Oxygen (DO), pH, Electrical Conductivity (EC), Temperature, Turbidity (Tb), Ammonia, Nitrate, and Total Phosphor). The data analyzed indicated that there was one increment of biomass satisfactory (0,25 g to 0,878 g). Concerning water quality, it was noticed that dissolved oxygen and total phosphor were the only parameters that were outside the normative standards (4,59 mg/L and 2,91 mg/L, respectively), therefore, below of standard indicated for the National Environmental Council 357/05 (>5 mg/L and ≤ 0,03 mg/L, respectively). About parameters for farming shrimp, DO (4,59 mg/L), pH (5.84), ammonia (3,07 mg/L) and total phosphorus (2,91 mg/L) were prone to abnormality, therefore, non-standard (>5 mg/L;7,4 to 8,4; ≤1,6 mg/L; <0,5 mg/L, respectively). Regarding the development of L. sativa var. crispa, six individuals were analyzed, of which 1 presented better development than the others. Thus, aquaponic can provide good water quality from both a zootechnical, environmental, and hydroponic point of view.
GLOBAL EXPONENTIAL STABILITY CRITERIA FOR SWITCHED NEUTRAL SYSTEMS WITH INTERVAL TIME-VARYING DELAY

The delay-dependent and delay-independent conditions are proposed to guarantee the global exponential stability for uncertain switched neutral system with interval time-varying state delay. New additional nonnegative inequalities are introduced to improve the conservativeness of system. Razumikhinlike approach is used to prove the exponential stability for system. Structured and unstructured uncertainties are investigated in this paper. The solving schemes based on Linear Matrix Inequality (LMI) approach along with the selective examples are presented to demonstrate the improvements achieved.
Rigorous full-wave space-domain solution for dispersive microstrip lines

The eigenmode problem for the open microstrip line is analyzed in the space domain starting from the calculation of a dyadic Green's function in the spectral domain. The transverse and the longitudinal current are discretized using the method of moments. A point-matching technique is used to impose the boundary condition, i.e., zero tangential electric field, on the strip. The edge conditions at the end points of the strip are explicitly incorporated and special care is taken to accurately retain the static behavior of the field on and near the strip. Special attention is given to the variation of the current distribution as a function of frequency. >
DESIGN AND OPTIMIZATION OF EMBEDDED CONTROL SYSTEMS

: Today , numerous embedded or the cyber-physical system, e.g, in comprise several control applications, automotive domain, sharing same platform. It well known that the such resources sharing leads into the complex temporal behavior that degrade quality of more importantly, control, may even risk stability in worst case, but not properly taken into the account. In this paper, we consider the embedded control or the cyber-physical system, where the several control application share same processing units. Focus is on control-scheduling, the co-design problem, where controller and the scheduling parameter are both optimized. The basic difference between the control application and the traditional embedded application motivate need for the original methodologies for design and optimization of the embedded control system. This work is one other step towards correct design and the optimization of the embedded control system. online and Offline methodologies for the embedded control system are enclosed in this paper. The significance of considering both expected manage stability and performance is discuss and control preparation co-design methodology proposed to the optimize direct performance as guarantee stability. Orthogonal to this band the width efficient stabilize control server is planned, which supports the isolation, compositionality and resource-efficiency in the design. Lastly, we extend scope of future approach to the non-periodic control scheme and the address challenges in the sharing platform by means of self-triggered controller. In addition to the offline methodologie, a narrative online scheduling policy to the stabilize control application is planned.
A Combinatorial Approach to Flag Codes

In network coding, a flag code is a collection of flags, that is, sequences of nested subspaces of a vector space over a finite field. Due to its definition as the sum of the corresponding subspace distances, the flag distance parameter encloses a hidden combinatorial structure. To bring it to light, in this paper, we interpret flag distances by means of distance paths drawn in a convenient distance support. The shape of such a support allows us to create an ad hoc associated Ferrers diagram frame where we develop a combinatorial approach to flag codes by relating the possible realizations of their minimum distance to different partitions of appropriate integers. This novel viewpoint permits to establish noteworthy connections between the flag code parameters and the ones of its projected codes in terms of well known concepts coming from the classical partitions theory.
Supplementary Material for Learning to Track with Object Permanence

In this supplementary material, we provide additional visualizations, experimental results and implementation details that were not included in the main paper due to space limitations. We begin by describing the contents of the supplementary video, which includes qualitative examples of our algorithm’s output in Section 1. In Section 2 we provide details about the datasets used in our work, and further elaborate on the PD dataset in Section 3. A real world nuScenes [5] dataset for 3D tracking could potentially be used to train our method directly, and we demonstrate preliminary results on it in Section 4. We conclude by reporting all the metrics on KITTI [6] and MOT17 [9] benchmarks in Section 5 and listing the remaining implementation details in Section 6.
Characterizing the IETF through its consensus mechanisms

We propose analysis into the consensus mechanism of IETF [7] that promotes internet drafts into RFCs. Using the data publicly available from IETF, such as mailing lists, internet draft action history, minutes of meeting, affiliation records, etc, we identify various mechanisms with which to characterize its dynamics. Through the use of novel text mining, time series clustering, graph mining and psycholinguistic approaches to understand the consensus mechanism within IETF deeply, we propose to derive actionable insights to facilitate greater diversity, inclusion and fairness in its operations.
YOLO를 이용한

In the case of blur processing, it is common to use a tool such as Photoshop to perform processing manually. However, it can be considered very efficient if the blur is processed at one time in the object detection process. Based on this point, we can use the object detection model to blur the objects during the process. The object detection is performed by using the YOLO [3] model. If such blur processing is used, it may be additionally applied to streaming data of video or image
Performance and economic evaluation of the first grid-connected installation in Colombia, over 4 years of continuous operation

In January 2004, the Photovoltaic System Laboratory of the Universidad Nacional de Colombia installed the first grid-connected system in the country. A sophisticated monitoring system was implemented for measuring and analysing the performance and power quality of the building-integrated photovoltaic (BIPV) system. The meteorological and solar radiation data at the site of installation were also analysed for correlation with system performance. On the basis of 4-year monitoring results, the performance of the BIPV system was analysed from a component perspective (photovoltaic array and power conditioning unit) and global perspective (system efficiency, electrical energy, power quality, etc.). Energy analysis and economic evaluation revealed that, to get a trade-off between energy and economic viability, the BIPV system installations must be heavily subsidized.
PARAMETER IDENTIFICATION USING THE NELDER?€“MEAD SIMPLEX ALGORITHM FOR LOW SIGNAL-TO-NOISE RATIO SYSTEMS IN A FREQUENCY DOMAIN

Parameter identification algorithms are very fundamental techniques in system engineering practices. For example, estimating the parameters of the AutoRegresive model with an eXternal input or AutoRegresive Moving-Average model with an eXternal input by using the least squares (LS) method has become a standard approach. However, the estimated parameters may generate extremely erroneous results when the signal is disturbed by large noise, which cannot be effectively filtered. If a frequency response method that scatters the power of a broadband noise over different frequencies is adopted, the effect of noise on the estimated parameters would be relatively reduced. Moreover, estimating whether the plant is a highorder system or is perturbed by a large noise is difficult. The estimated accuracy decreases even after applying the generalized LS method or other modified approaches. To overcome this problem, this study proposed a new technique combining a simplex algorithm and frequency response method for improving the accuracy of the parameter estimation of a dynamic system with a large noise (i.e., an extremely low signal-to-noise ratio) of the system. The algorithm is simple and easy to implement. Moreover, the precision of parameter identification can be increased even when estimated systems suffer from large measurement noises.
A Review on Effects of Bisphenol a on Reproductive, Endocrine Systems and its Influencing Mechanism

Corresponding Author: Qinglu Wang College of Sports and Health, Shandong Sport University, China Email: Wql_zcq@126.com Abstract: Background and purpose: Bisphenol A (BPA) is a pervasive environmental toxicant with known adverse effects on human immune system and nervous system et al. Although, BPA is widely known to affect endocrine function in animals, the linkage between human exposure to BPA and human reproductive function is still not clearly clarified. Results: Systematic review of all articles about BPA and human reproductive function identified in SCOPUS and PubMed. Literature was summarized in narrative form and results are presented per category. Some observational surveys investigating the relationship between BPA exposure and human reproductive and/or endocrine function are inconsistent. Conclusion: Our review integrates the studies of BPA on reproductive and/or endocrine system in recent years, mainly explains the effects of BPA on these systems and provides the basis for subsequent studies on BPA.
ARISTOTLE UNIVERSITY OF THESSALONIKI DEPARTMENT OF PHYSICS Direct dark matter search by measuring the differential rate for ionization electrons produced in neutralino-nucleus collisions

Dark matter and its detection is one of the greatest unsolved problems in Physics. The biggest part of the Universe’s gravitating matter, about 95%, is nonluminous and its properties are mostly unknown. Numerous methods of detection and various experiments have been employed in order to explain its nature and determine its consisting particles. The present thesis studies the direct detection of dark matter by measuring the differential rate for the ionization electrons produced when a neutralino and a nucleus collide. The first chapter presents the many evidences for dark matter existence, its multiple candidates and all its known properties. The various dark matter detection experiments and its distribution in cosmic structures are discussed in the second chapter. Some of the most important experiments and their results are also included. The last chapter consists of the theoretical background and the method used to conduct the experimental part of this thesis. Finally, the results and the code used for the analysis are presented in the appendix.
Bioinformatic Analysis of Differentially Expressed Genes in Porcine Intestinal Epithelial Cells Infected with Transmissible Gastroenteritis Virus

Transmissible Gastroenteritis Virus (TGEV) infection is one of the leading causes of diarrhea in piglets. Intestinal immune system plays an important role in maintaining the intestinal mucosa’s integrity and resisting infection by pathogens. However, the relationship between the immune response induced by TGEV infection and disease progression is unclear. Using the microarray data set GSE41756 from the Gene Expression Omnibus database, we analyzed porcine small intestinal epithelial cells at 6 and 12 h of TGEV infection. Differentially expressed genes (DEGs) were detected using the ‘limma’ R package. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway enrichment, and the proteinprotein interaction network analyses were performed with the detected DEGs. We found 56 DEGs (47 up-regulated and 9 down-regulated) after the intersection. Pathway enrichment analysis revealed that the DEGs were mainly associated with immune response, extracellular space, cytokine activity, and positive regulation of nuclear factor-κB import into the nucleus. This revealed the strong relationships among DEGs in the tumor necrosis factor signaling pathway, inflammatory bowel disease, and influenza A. Interleukin 6 (IL6), IL8, IL18, tumor necrosis factor, and tolllike receptor hub genes may play important roles during TGEV infection.
Turnstile-Juncti on-Based Omnidirectional Antennas for Space Applications

com Abstract Omnidirectional biconical antennas are widely used in satellites as a constituent part of the telemetry, command, and ranging (TC&R) RF subsystems. They provide a toroidal radiation pattern, and are mainly used in combination with other low-gain antennas to provide an omnidirectional pattern (1) during transfer orbit, and for on-station communications of the satellite with ground. The design of the feeding network of this type of antenna is critical, since the receiving antenna is situated right on top of the transmitting antenna. Previously used feeding configurations resorted to cables and intermediate connectors to reduce mass and envelope. In this paper, a novel feeding configuration -entirely waveguide based -is presented as a tradeoff between mass and robustness. It is based on the use of a turnstile junction to avoid weak links and to provide a robust and reliable design, a must in space applications. Considerations related to the design of the radiating elements and manufacturing will also be discussed, as well as a comparison between the simulated and measured performance of the final prototype of the omnidirectional antenna.
Deep Learning for Arabic Image Captioning: A Comparative Study of Main Factors and Preprocessing Recommendations

Captioning of images has been a major concern for the last decade, with most of the efforts aimed at English captioning. Due to the lack of work done for Arabic, relying on translation as an alternative to creating Arabic captions will lead to accumulating errors during translation and caption prediction. When working with Arabic datasets, preprocessing is crucial, and handling Arabic morphological features such as Nunation requires additional steps. We tested 32 different variables combinations that affect caption generation, including preprocessing, deep learning techniques (LSTM and GRU), dropout, and features extraction (Inception V3, VGG16). Moreover, our results on the only publicly avail-able Arabic Dataset outperform the best result with BLEU-1=36.5, BLEU2=21.4, BLEU-3=12 and BLEU4=6.6. As a result of this study, we demonstrated that using Arabic preprocessing and VGG16 image features extraction enhanced Arabic caption quality, but we saw no measurable difference when using Dropout or LSTM instead of GRU. Keywords—Deep learning; NLP; Arabic image captioning; Arabic text preprocessing; LSTM; VGG16; INCEPTION V3
Comparative Studies between Finite and Infinite Time Interval Controllers for Flexible Joint Robots

Motivated by the work by Spong (1) on the control of flexible joint robots, an adaptive control law guaranteeing that statements from the Tychnov theorem hold on an infinite time interval is presented first. Computer simulation comparisons are then carried out between the proposed infinite time interval controller and the conventional finite time interval controller.
Towards Explaining Exchange Traded Funds’ Impact on Market Volatility Using an Agent-based Model

Exchange traded funds (ETF), which are baskets of securities that trade on the stock market, have become a popular investment tool, but potentially increase the price co-movement of their underlying securities. We study index-based ETFs, because underlying securities trade on the same market as their corresponding ETF, which creates ample opportunities for traders to arbitrage between price deviations in the ETF and the market index. Considering the increase in market volatility in 2018 and 2019 in the US stock market, we examine if an ETF spreads mini flash crashes, or small volatility events, from one of its underlying symbols to another. We address this question in a simulated environment with an ETF and two symbols which compose the ETF’s portfolio. We explore two market environments, one with an ETF and arbitrage agents, and one without an ETF and arbitrage agents. We find that the presence of an ETF and arbitrage agents increases underlying symbols’ overall volatility, and when one symbol experiences a mini flash crash, the other symbol does experience a momentary price change in the opposite direction. This supports the idea that ETFs potentially increase market-wide volatility by spreading volatility events through their portfolios. To further this work, we hope to utilize learning to implement smarter arbitrage agents and smarter background agents who might avoid adverse selection by not trading during mini flash crashes.
Trend of Life Expectancy in Sudan

The main objective of this paper is to construct a time series model to monitor and forecast the life expectancy at birth in Sudan. To achieve this objective, a series of life expectancy at birth ranged from 1990 to 2013was obtained from the Sudan Central Bureau of statistics and United Nation Annual Reports, time series analysis technique mainly box and Jenkins were used to find the required model . Analysis done by e-views package. The paper conclude that The most proper time series model to forecast the life expectancy at birth in Sudan is the ARIMA model, The highest forecasted Life Expectancy at Birth in the Sudan for the coming ten years will be attained in year 2023 as 66.4835 years and finally The life expectancy at Birth in Sudan is increasing at a decreasing rate.
Deep sea hammer corer

The objective of this multi-national project is to develop a novel deep sea coring system capable of acquiring long, undisturbed sediment cores, from seabed formations which cannot be satisfactorily cored by present methods. To enable this system to function, the development mounts hydraulic, electronic control and data monitoring systems on the corer. The corer is controlled indirectly from a surface computer, with power and communications being transmitted through a combined power and lift umbilical. Real time geotechnical information from a bore hole can be obtained by replacing the core barrel with a cone penetrometer and fluid sampler. The system is designed to operate from oceanographic research vessels, but may be transferred to any suitably equipped survey vessel. The development builds upon technology developed by the individual partners in the project.
Using an electronic frailty index to predict adverse outcomes in geriatric COVID-19 patients: data from the Stockholm GeroCovid study

Background: The Clinical Frailty Scale (CFS) is a strong predictor for worse outcomes in geriatric COVID-19 patients, but it is less clear whether an electronic frailty index (eFI) constructed from routinely collected electronic health records (EHRs) provides similar predictive value. This study aimed to investigate the predictive ability of an eFI in comparison to other frailty and comorbidity measures, using mortality, readmission, and the length of stay as outcomes in geriatric COVID-19 patients. Methods: We conducted a retrospective cohort study using EHRs from nine geriatric clinics in Stockholm, Sweden, comprising 3,405 COVID-19 patients (mean age 81.9 years) between 1/3/2020 and 31/10/2021. Frailty was assessed using a 48-item eFI developed for Swedish geriatric patients, the CFS, and Hospital Frailty Risk Score (HFRS). Comorbidity was measured using the Charlson Comorbidity Index (CCI). We analyzed in-hospital mortality and 30-day readmission using logistic regression and area under receiver operating characteristic curve (AUC). 30-day and 6-month mortality were modelled by Cox regression, and the length of stay by linear regression. Results: Controlling for age and sex, a 10% increase in the eFI was associated with higher risks of in-hospital mortality (odds ratio [OR]=2.84; 95% confidence interval=2.31-3.51), 30-day mortality (hazard ratio [HR]=2.30; 1.99-2.65), 6-month mortality (HR=2.33; 2.07-2.62), 30-day readmission (OR=1.34; 1.06-1.68), and longer length of stay ({beta}=2.28; 1.90-2.66). The CFS, HFRS and CCI similarly predicted these outcomes, but the eFI had the best predictive accuracy for in-hospital mortality (AUC=0.775). Conclusions: An eFI based on routinely collected EHRs can be applied in identifying high-risk geriatric COVID-19 patients.