Miracle-dz/UniFAR-FTUs huggingface dataset:
The building science of office surfaces: Implications for microbial community succession

The Surface Project studied the microbial succession on office surfaces in nine offices in three North American cities. Building science parameters including relative humidity (RH), temperature, equilibrium relative humidity (ERH), illumination, and occupancy were measured to investigate their impact on microbial communities. Parameters were measured every five minutes over the course of a year. ERH, RH, temperature, occupancy, and illumination varied between offices, and cities which suggests that building characteristics and climate are important factors. RH, ERH, and temperature showed clear seasonal variation. The drywall ERH varied from ERH of ceiling tile and carpet and from the RH of air. Illumination was different in occupied and unoccupied offices. Occupancy did not cause that much difference in RH. Methodology analysis revealed no difference between different frequency measurements, although it is suggested that short-term intervals to be considered since long-term intervals may not show the large variation of building science parameters.
Intelligent image processing based on VPX architecture

Multiple bands cameras with high pixel resolution and fast frame rate bring challenges for real-time signal process which is important in monitoring and alerting application. Especially, the deep neural network algorithm which has been applied in practical EO system, requires high parallel computation ability. Thus, the traditional signal processing method in imaging sensor cannot satisfy the novel demands for balancing the capability and consumption. The system based on VPX architecture and all optical signal transmission can provide a promising improvement in computation capability, transmission bandwidth and data transfer capability. In this paper, a novel signal processing system for intelligent computing based on VPX architecture is indicated. Based on the system structure and components indication, the main configuration design is also explained. Especially the thermal deisgn of the full system is explained in details, because the thermal effect and related methods are important in high speed conputation system. The main intelligent signal processing circuit is based on FPGA SOC processor. After introducing the hardware design and scheme, an optimized SSD algorithm is introduced for multi-scales target detection, and the method to applying these algorithms on FPGA chip for real-time compuation is explained. Finally, this method is verified in both visible and IR images, especially for the small target in IR images. The whole design is verified that it can provide a promising solution for high performance and distributed EO imaging system.
Structural and Functional Analyses of Type I IFNa Shed Light Into Its Interaction With Multiple Receptors in Fish

Teleost type I interferons (IFNs) are categorized into group I and II subgroups that bind to distinct receptors to activate antiviral responses. However, the interaction between ifn ligands and receptors has not fully been understood. In this study, the crystal structure of grass carp [Ctenopharyngodon idella (Ci)] IFNa has been solved at 1. 58Å and consists of six helices. The CiIFNa displays a typical structure of type I IFNs with a straight helix F and lacks a helix element in the AB loop. Superposition modeling identified several key residues involved in the interaction with receptors. It was found that CiIFNa bound to cytokine receptor family B (CRFB) 1, CRFB2, and CRFB5, and the three receptors could form heterodimeric receptor complexes. Furthermore, mutation of Leu27, Glu103, Lys117, and His165 markedly decreased the phosphorylation of signal transducer and activator of transcription (STAT) 1a induced by CiIFNa in the Epithelioma papulosum cyprini (EPC) cells, and Glu103 was shown to be required for the CiIFNa-activated antiviral activity. Interestingly, wild-type and mutant CiIFNa proteins did not alter the phosphorylation levels of STAT1b. Our results demonstrate that fish type I IFNs, although structurally conserved, interact with the receptors in a manner that may differ from mammalian homologs.
The effects of aromatherapy on patients undergoing coronary angiography: A systematic review of clinical trials

As a diagnostic and therapeutic technique for coronary artery disease, angiography is usually associated with some disorders and complications such as fear, pain, discomfort, limited mobility, and anxiety. The present study is a systematic review determining the effects of aromatherapy with different plants in patients undergoing angiography. This review was conducted according to the 06-PRISMA guideline and registered in the CAMARADES-NC3Rs Preclinical Systematic Review and Meta-Analysis Facility (SyRF) database. The English databases were Google Scholar, PubMed, Scopus, Web of Science, EBSCO, and ScienceDirect to search articles regarding the effects of aromatherapy with different plants in patients experiencing angiography without a date limitation. The searched keywords in this study were "aromatherapy", "angiography", "coronary artery disease", "anxiety", "stress", and "cardiovascular diseases". Out of 1835 papers, 20 papers up to 2021, met the inclusion criteria for discussion in this systematic review with the data extracted. Most studies were intended to evaluate the effect of aromatherapy on patients’ anxiety with coronary artery bypass graft surgery (11 papers, 55.0%). The most widely used essential oil belonged to the lavender essential oil (13 papers, 65.0%). The results of the current review confirmed that aromatherapy management with lavender, damask rose, orange, and peppermint is able to significantly decrease anxiety, pain, nausea and vomiting, sleep quality, hemodynamic indices, blood pressure, etc. in patients with coronary angiography. However, more investigation is required to confirm the precise mechanisms and side effects of the alternative treatment.
Electrospun poly(3-caprolactone)/gelatin nanofibrous scaffolds for nerve tissue engineering

Nerve tissue engineering is one of the most promising methods to restore nerve systems in human health care. Scaffold design has pivotal role in nerve tissue engineering. Polymer blending is one of the most effective methods for providing new, desirable biocomposites for tissue-engineering applications. Random and aligned PCL/gelatin biocomposite scaffolds were fabricated by varying the ratios of PCL and gelatin concentrations. Chemical and mechanical properties of PCL/gelatin nanofibrous scaffolds were measured by FTIR, porometry, contact angle and tensile measurements, while the in vitro biodegradability of the different nanofibrous scaffolds were evaluated too. PCL/gelatin 70:30 nanofiber was found to exhibit the most balanced properties to meet all the required specifications for nerve tissue and was used for in vitro culture of nerve stem cells (C17.2 cells). MTS assay and SEM results showed that the biocomposite of PCL/gelatin 70:30 nanofibrous scaffolds enhanced the nerve differentiation and proliferation compared to PCL nanofibrous scaffolds and acted as a positive cue to support neurite outgrowth. It was found that the direction of nerve cell elongation and neurite outgrowth on aligned nanofibrous scaffolds is parallel to the direction of fibers. PCL/gelatin 70:30 nanofibrous scaffolds proved to be a promising biomaterial suitable for nerve regeneration. 2008 Elsevier Ltd. All rights reserved.
T Intelligent Frequency Control Strategy of Wind Turbine Generation System with DFIG by Using PI and Fuzzy Logic Controllers

In today world’s market; main disadvantage of Doubly fed induction generator is that under its operation mode, rotor speed decoupled from frequency of power grid resulted as not responding situation about changes of system frequency. With largescale integration of DFIG; frequency stability of power system decreases and most significantly it creates disturbance in frequency regulation so its foremost priority to study control strategies for purpose of overall system frequency adjustment. The aim of this paper is to study and analysis of DFIG along with its frequency control strategy based on existing methods (PI traditional controller) as well as proposed new method based on Fuzzy control logic. Initially, establishes the mathematical model, build power decoupling control strategy, analyze response under varying system load. It is noticed that due to external performance of zero inertia, it changes characteristics of frequency response as well as reduces the equivalent inertia of power system. In order to cope this critical issue; theoretical and simulation-based analysis has performed. Furthermore, paper focuses on selection of control coefficients (Kp, Kd) in DFIG comprehensive inertial control strategy, analyzes the influence of inertial control coefficients and finally optimizes the control coefficient to meet the frequency regulation. ISSN (e) 2520-7393 ISSN (p) 2521-5027 Received on 28 Feb, 2020 Revised on 14 Mar, 2020 www.estirj. com 15 JAMSHED ALI et.al: INTELLIGENT FREQUENCY CONTROL STRATEGY OF WIND TURBINE GENERATION Copyright ©2020 ESTIRJ-VOL.4, NO.1 (15-21) different situations, PID coefficients are optimized based on a multi objective function using particle swarm optimization (PSO) algorithm. An optimization strategy of power deviation control (pitch angle control) is proposed in [12] in order to improve the DFIG based wind farm contribution to power system frequency regulation demand. The output power of wind turbines can be adjusted more rapidly, but it is limited by the amount of rotor kinetic energy that can be released, in order to make full use of the limited rotor kinetic energy to support system frequency, a variable parameters frequency control loop and the gain of the control loop is adjusted along with the change of wind speed and the size of power imbalance are proposed in [13]. On the other hand, authors in [14] are proposed method using the kinetic energy stored in the “hidden inertia” of the turbine blades to let variable-speed wind turbines emulate inertia and support primary frequency control. Finally, the basic idea is to introduce a closed-loop frequency control into the active power control scheme. The active power output setting is modified according to the variation speed of frequency and its deviation compared to the nominal value, thus emulating inertia and offering primary frequency regulation respectively.
Social Policy Report Vol. 24, Number 2

R ecent prevalence rates for autism spectrum disorders (ASDs) are now estimated at about 1 in 110 children in the U.S. Increases in public awareness and research funding in response to the growing numbers of children and adults with this disorder have led to numerous important scientific advances over the last several years. Nevertheless, because ASD remains a diagnosis that is defined completely on the basis of behavior, diagnostic assessment is both complex and expensive. Appropriate interventions and services are also multi-faceted and costly, and because of the pervasive nature of the disorder, are often required in some form across the lifespan. In the absence of standard societal mechanisms to pay for appropriate assessment and treatment, families must personally shoulder many of the costs associated with securing appropriate services for their children. This Social Policy Report summarizes selected recent studies on diagnosis, prevalence, and intervention, and discusses strategies for designing social policies to help improve the outcomes and independence of children and
Racism, Islamophobia and Western Media: An Analysis How Western Media Portrays Muslims and Islam in the West

This article is a meta-analysis that investigates how Muslims and Islam are portrayed by the Western media. It purposes that the Western media often represents the Muslims as murderous, frame out as terrorists and also present the incorrect information about the Muslims and Islam. The paper presents the pragmatic evidences about the treatment of Western media with Muslims and Islam that follows the particular pattern of framing based on deviance. In this article the secondary data has been used to dig out the clear concept of Islamophobia. However, as scholarly inquiry into this topic remains relatively embryonic, this article seeks to contribute new thinking and ideas about, how to better comprehend, conceptualize and subsequently understand the Islamophobia. This article suggests the modernized tactics to reduce the discriminatory structures and the disruption of mechanisms that propagate racism. In this affection, particularly in the background of independent and human rights based framework, it is responsibility of the media to check information which conveys regarding racial identities is truthful, ethical and transparent.
CS 224W P ROJECT R EPORT : P REDICTING MICROBE CO - OCCURRENCE WITH METABOLITE NETWORK EMBEDDINGS

The human microbiome is replete with microorganisms that compete, collaborate, and cooexist. The interactions of these microbes can support human health or foster diseases [1]. Knowledge of microbe interactions can be applied to design effective probiotics or identify species that will out-compete pathogens [2]. Thus it is important to determine which microbes tend to live together, or co-occur, and which compete. Traditional methods of determining co-occurrence require collecting large numbers of invasive samples from human body sites, sequencing the resulting information, and estimating co-occurrence from relative abundances of organisms, which can be both expensive and time-intensive [1]. These costs could be substantially reduced if microbial co-occurrence could be accurately predicted from existing data.
Towards new frontiers in mobile manipulation: Team CTU-UPenn-NYU at MBZIRC 2020

In this paper we present an autonomous robotic system for picking, transporting, and precisely placing magnetically graspable objects. Such a system would be especially beneficial for construction tasks where human presence is not possible, e.g. due to chemical or radioactive pollution. The system comprises of two primary components – a wheeled, mobile platform and a manipulator arm. Both are interconnected through an onboard computer and utilize various onboard sensors for estimating the state of the robot and its surroundings. By using efficient processing algorithms, data from the onboard sensors can be used in a feedback loop during all critical operational sections, resulting in a robust system capable of operating on uneven terrain and in environments without access to satellite navigation. System functionality has been proven in Challenge II of the MBZIRC 2020 competition. The Challenge required a ground robot to build an L-shaped structure of colored bricks laid in a predefined pattern. Such a mission incorporates several demanding subchallenges, spanning multiple branches of computer science, cybernetics, and robotics. Moreover, all the subchallenges had to be performed flawlessly in rapid succession, in order to complete the Challenge successfully. The extreme difficulty of the task was highlighted in the MBZIRC 2020 finals, where our system was among the only two competitors (out of 32) that managed to complete the task in autonomous mode.
International Journal of Instruction

Student achievement in learning mathematics is considerably low in Indonesia. This study aims to discuss factors affecting learning achievements in mathematics in Indonesia, including direct and indirect influences, such as students' perception of teacher competence, learning anxiety, problem-solving ability, learning motivation, and mathematical connection ability. Quantitative approach and correlational method were used with a sample comprising 171 class XI students of Senior High School in Purworejo Regency, Central Java. The stratified cluster random sampling technique was used to determine the sample composition based on the National Examination scores for the 2018/2019 academic year. The results showed that four variables, except anxiety, significantly influence learning achievement. Furthermore, mathematical connection ability had the greatest direct impact on learning success at 0.38. Other indirect factors, such as influence through learning motivation and problem-solving ability, were at 0.140 and 0.133, respectively. These results are in line with previous studies which stated that mathematical connection ability is an important aspect in achieving student learning achievement. The ability to connect various materials studied with topics inside and outside mathematics has helped students understand the material to improve learning achievement. Furthermore, teachers can use these results as references in learning management by paying attention to various aspects, especially mathematical connection ability.
UAV Relay Assisted Cooperative Jamming for Covert Communications Over Rician Fading

Covert communication can hide the legitimate transmission from unauthorized eavesdropping. Benefiting from the deployment flexibility, unmanned aerial vehicles (UAVs) can be utilized to enhance communication confidentiality. In this correspondence, we consider a covert communication network with the aid of a full-duplex UAV relay, which is employed to help the transmission and confuse the warden. The warden adopts a radiometer to detect the covert transmission. We first find the optimal detection threshold and calculate the minimum detection error probability. Furthermore, a closed-form expression of outage probability via UAV relaying is derived over Rician fading. Then, a power optimization problem is formulated to maximize the effective convert throughput with covertness constraint. Numerical results illustrate that the cooperative jamming can disrupt the warden, and the optimal power tradeoff can guarantee the covert transmission effectively.
Islamic Social Reporting in Shariah Banks in Indonesia

From the Islamic perspective, the growth of Corporate Social Responsibility became an additional dimension for financial reporting. Islamic Social Reporting (ISR) is becoming a common practice among Shariah Banks in Indonesia. This study attempted to measure the determinants of ISR as practiced by shariah-approved Indonesian banks listed on the Indonesia Stock Exchange, as stated in their annual reports. The three variables used to test the determinants of ISR were company size, profitability, and leverage. Content analysis was used to evaluate ISR and analyze the annual reports of 11 shariah banks during the period 2014– 2016. Multiple regression analysis with panel data showed that company size, profitability, and leverage significantly affected the level of ISR. The findings contribute a new dimension to the knowledge of corporate reporting from the religiousity perspective.
Lessons Learned from two iterations of LLAMA, an Electrically Powered, Dynamic Quadruped Robot

This paper presents the design, control, and initial performance from two iterations of human-scale (∼75 kg) quadrupedal robots built under the U.S. Army Research Laboratory (ARL) Robotics Collaborative Technology Alliance (RCTA) LLAMA (Legged Locomotion and Movement Adaptation) project. These all-electric, quadruped robots are designed with custom quasi-directdrive actuators powering 3-DOF, serial-parallel legs. To our knowledge, this is the first all-electric quadruped robot of this mass scale. The centralized energy management system uses a capacitor bank to supply burst loads and buffer regenerated energy. A hierarchical control scheme enables rapid motions (up to 1.8 m/s) over a variety of terrains. The onboard sensing suite enables deliberate, autonomous operation across rubble fields. In addition, we report on practical observations, lessons learned from field testing of two generations of the platform, and current drawbacks, such as low absolute payload (9 kg) and battery life (35 minutes). These lessons include strategies to address secondary effects at larger scales and parameters with the most impact to improve future designs.
An Approach to Reduce the Sample Consumption for LIBS based Identification of Explosive Materials

An experimental design based on spectral construction, which has potential to minimise the sample consumption, the number of laser shots and time required to collect the data from laser induced breakdown spectroscopy for identification of the explosive materials is reported in the study. This approach is an ideal solution in the field of hazardous material detection, where the availability of the sample can be a serious limiting factor. The experimental data recorded on a set of five high energy materials has been considered to test the performance of the proposed methodology. Multiple spectra are constructed by assuming a normal distribution at each wavelength of the spectrum, where random numbers are generated using the mean and standard deviations obtained from arbitrarily chosen five experimental spectra from each class. The newly generated spectra are called as synthetic spectra. The correct classification obtained from – K - nearest neighbour combined with principal component analysis and partial least square – discriminant analysis demonstrated very promising results. The correct classification rates differed by only 4 per cent - 7 per cent as compared to conventional approach where experimental spectra alone are considered for the analysis. Further, when RDX is excluded, the obtained results are almost identical with conventional approach.
Evaluation and comparison of 3D lidar based SLAM algorithms

—This article has two main objectives: ﬁrst, evaluating the performance of recent 3D lidar based SLAM (Simultaneous Localization And Mapping) algorithms; second, contributing actively to the advancement of knowledge in that ﬁeld. To that end, it brieﬂy explains the underlying theory and draws up an inventory list of 3D SLAM algorithms available on the ROS platform. Based on this list, it selects the two most promising algorithms compatible with 3D lidar sensors and compares their performance in indoor and outdoor environments. To simplify this evaluation, the metrics assessing SLAM quality that were deﬁned in the literature are summed up and most of them are proven to be correlated. Hence, only some of the metrics need to be analyzed before ranking the two algorithms. The best one is then further investigated: improvements that can be brought to this method are looked for. The different improvements are combined in a brand new algorithm that proves to be a signiﬁcant step forward compared to previous methods regarding SLAM quality, determinism, and computing heaviness. This new package is ﬁnally made available to the community.