Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploration of Standardized Greening Applied in Improving Air Environment in subway Cars

The main contradiction in our society has been transformed into a contradiction between the people’s growing need for a better life and the lack of development imbalance. Nowadays, with the development of high quality and encouraging green travel, People's pursuit of travel comfort and high quality of travel environment is getting higher and higher. This paper analyses the problems existing in the current high-speed development of subway transport industry and its air improvement mode, puts forward a new greening product scheme designed with standardization concept, and preliminarily analyses its application value. It has certain value to enhance the passenger experience, reduce the damage to the staff around the subway, promote high-quality life, and alleviate traffic congestion.
The acceptance of school counselor in the use of ICT during school from home in the Covid-19 era

The Covid-19 pandemic marks an era of using online as a medium of learning communication, including counseling services. School Counselor are required to use ICT as a form of adaptation to learning with students. The research design using a quantitative Structural equation modeling aimed to test correlation of two or more variables. The participants are 214 School Counselor who are members of the Indonesian Guidance and Counseling Association (ABKIN) and the Guidance and Counseling Teacher Council (MGBK). This study measures the participation of School Counselor who fill out online questionnaires with respect to their perceptions of maximizing the use of ICT in providing counseling services. Measurement of the successful use of ICT in Guidance and counseling (BK) services during a pandemic will be measured through the attributes of Computer Anxiety (CA), Computer Self-Efficacy (CSA), Collegial Collaboration (CC), Lack Facility (LF), Perceive Usefulness (PU)
Non-Steady State of a Hydromagnetic xw-Dynamo and Its Application to the Geomagnetic Reversals

The non-steady state of a simplified hydromagnetic xw-dynamo is investigated. The hydromagnetic a-effect is derived by taking into consideration Coriolis, Lorentz and viscous forces, based on a simple, nearly homogeneous and isotropic turbulence. The nonuniform rotation is also taken to be non-stationary and subjected to the above forces. Numerical calculations of the initial value problem of the aw-dynamo equations have revealed that the dipole field undergoes relatively gradual variations and occasional polarity changes similar to the geomagnetic reversals. The reversal of the dipole field is caused essentially by the disruption of the non-uniform rotation. The time required for a complete decay of the dipole field is estimated to be about 3,000 years which is consistent with paleomagnetic observations. By taking into account the electrical conductivity of the bottom part of the mantle, electromagnetic coupling of the mantle to the core has also been studied. It is found that the field reversal is accompanied by the acceleration of the rotational speed of the mantle, and a change in l.o. d. of 95 msec.
Distributed evolution for swarm robotics

Traditional approaches to designing multi-agent systems are offline, in simulation, and assume the presence of a global observer. Artificial Physics (AP) or physicomimetics can be used to self-organize swarms of mobile robots into formations that move towards a goal. Using an offline approach, we extend the AP framework to moving formations through obstacle fields. We provide important metrics of performance that allow us to (a) compare the utility of different generalized force laws in the artificial physics framework, (b) examine trade-offs between different metrics, and (c) provide a detailed method of comparison for future researchers in this area. In the online, real world, a global observer may be absent, performance feedback may be delayed or perturbed by noise, agents may only interact with their local neighbors, and only a subset of agents may experience any form of performance feedback. Under these constraints, designing multi-agent systems is difficult. We present a novel approach called "Distributed Agent Evolution with Dynamic Adaptation to Local Unexpected Scenarios'' or DAEDALUS to address these issues, by mimicking more closely the actual dynamics of populations of agents moving and interacting in a (task) environment. This thesis merges DAEDALUS and AP by using obstacle avoidance as a case study to illustrate the feasibility of DAEDALUS when the environment changes. We present empirical and practical results that address (a) offline vs. online learning, (b) obstructed perception, (c) homogeneous vs. heterogeneous agent cooperation, and (d) implementation of obstacle avoidance with real robots.
New analgesics in cancer pain

Purpose of review Cancer pain continues to be a significant problem despite the range of analgesic and adjuvant medications available. The purpose of this review is to explore the most recent developments in the management of cancer pain. Recent findings Tapentadol, launched in the United Kingdom in May 2011, represents the last new analgesic entity with a novel mode of action to enter clinical practice for moderate-to-severe pain. Recent evidence describes the benefit of duloxetine for cancer-related neuropathic pain, and parecoxib by continuous subcutaneous infusion for refractory cancer pain. There is interest in the role of cannabinoids in cancer pain management but much of the evidence to date is in chronic noncancer pain. Conflicting evidence complicates the role that biased opioid agonism may offer in terms of alternative analgesics in the future. Summary There is development of new drugs with clinical utility on the horizon but a need for high-quality, randomized controlled trials specifically assessing efficacy and tolerability in cancer pain.
Is Methadone Safe for Patients With Opioid Use Disorder and Coronavirus Disease 2019 Infection?

Abstract The coronavirus disease 2019 (COVID-19) pandemic has led to not only increase in substance misuse, substance use disorder, and risk of overdose but also lack of access to treatment services. Due to lack of knowledge of the course and impact of COVID-19 and outcomes of it’s interactions with existing treatments, the Substance Misuse Service Team initiated a safety improvement project to review the safety of opioid substitution treatment, particularly the safety of methadone. This preliminary retrospective cross-sectional audit of safety improvement intiative underscores the importance of providing treatment services to those with opioid use disorders and that methadone is safe among this population with a high burden of comorbidity, most of which leads to negative outcomes from COVID-19. The outcomes show that patients who have COVID-19 should continue with opioid substitution treatment with methadone. Although treatment with methadone is safe, symptomatic patients should be monitored. In addition, patients who take methadone at home should be educated on the risk of overdose due to, and adverse outcomes from, COVID-19 infection. Patients should monitor themselves using pulse oximeter for any signs of hypoxia.
Influence of various parameters of INM RAS climate model on the results of extreme precipitation simulation

The results of simulation of extreme weather indices of modern climate by two versions of the INM RAS climate model (INMCM4, INMCM5) are considered. It is shown that the INMCM5 model simulates most of the temperature and average precipitation related indices better, but the simulation results of extreme precipitation related indices are worse. Various precipitation related physical factors in the model are analyzed. A parameterization of vertical mixing of the horizontal velocity components due to large-scale condensation, as well as air resistance acting on falling precipitation, is implemented in the INMCM5. The corresponding model parameters are adjusted. The effect of the adjustments on the simulation results of extreme indices is presented.
EFFECT OF CURRENT DENSITY ON MORPHOLOGY AND SURFACE ENHANCED RAMAN SCATTERING PROPERTIES OF SILVER NANOPARTICLES ARRAYS FABRICATED BY ELECTROCHEMICAL DEPOSITION

Surface-enhanced Raman scattering (SERS) is an analytical technique that allows the detection of trace amounts of organic and biological molecules. In this technique, the SERS substrate, where the Raman scattering signal of the analyte molecules is to be enhanced, plays a particularly important role. One of the most commonly used SERS substrates is the SERS substrate made of silver nanoparticles (AgNPs) immobilized on a solid substrate. Typically AgNPs arrays are fabricated by electroless deposition, in this report we present the fabrication of AgNPs arrays on a silicon surface by electrochemical deposition method. Results showed that this method allows the creation of an array of silver nanoparticles which are relatively uniform in size, morphology, as well as the distance between the particles. Moreover, the size and the density of the AgNPs can be controlled by changing the electrochemical current density. To test the performance of the SERS substrate, AgNPs arrays were used as SERS substrates for detecting traces of crystal violet (CV). The results showed that the intensity of the SERS signal depends strongly on the size of the AgNPs, and the distance between them. With optimal AgNPs arrays, we have recorded a SERS spectrum of CV at concentrations below 0.1 ppb.
Are (cid:98) -Blockers Effective in Elderly Patients Who Undergo Coronary Revascularization After Acute Myocardial Infarction?

Background: Although randomized clinical trials have demonstrated that (cid:98) -blocker therapy is effective in reducing mortality after acute myocardial infarction (AMI), many of these studies excluded patients who undergo coronary revascularization. However, the clinical practice guidelines established by the American College of Cardiology and the American Heart Association recom-mend that (cid:98) -blocker therapy be considered for patients who underwent successful revascularization after AMI. Methods: Using data from the Cooperative Cardiovascular Project, we compared the initiation of (cid:98) -blocker therapy at discharge in patients aged 65 years or older who underwent coronary artery bypass surgery (CABG) or percutaneous transluminal coronary angioplasty (PTCA) during their hospitalization for AMI with that of patients who did not undergo revascularization. We then examined whether (cid:98) -blocker therapy was associated with lower 1-year mortality between revascularized and nonrevascularized groups. Results: After excluding patients with contraindications to (cid:98) -blockertherapy,84 457patientsremainedinthestudy sample. Of these, 8482 patients underwent CABG, and 13 997 patients underwent PTCA. After adjusting for de-mographic and clinical factors, we found that these patients were less likely to initiate (cid:98) -blocker therapy after CABG(oddsratio[OR],0.44;95%confidenceinterval[CI], 0.41-0.47) or PTCA (OR, 0.89; 95% CI, 0.85-0.93) relative to the nonrevascularized group. After adjusting for potential confounders, (cid:98) -blockers were Conclusions: Therapy after AMI with (cid:98) -blockers to be as effective in Our findings suggest that routine use of (cid:98) -blockers should be considered for revascularization
On-site Radioscopic Qualitative Assessment of Historic Timber Structures: Identification and Mapping of Biological Deterioration of Wood

ABSTRACT The recent development of portable, battery-charged x-ray tubes and digital detectors has made digital radioscopic examination of wooden buildings a realistic option. Lack of experience with the often very complex radiographs of building structures makes the interpretation of such radiographs difficult. A set of radiographs of wood in different, identified conditions was established for use when interpreting radiographs of wood in unknown condition. This article presents radiographs of a trestle-framed building. The recordings were done in areas where the condition of the wooden elements was known in advance, either on the basis of dendrochronological drill samples or because the building element had been replaced recently and the wood was sound. The radiographs were compared with NIKU´s collected guideline radiographs and discussed with respect to the information they provide about the wood’s condition. Finally, we discuss radioscopy as a supplement to traditional methods of building surveying. The authors took all of the photos and radiographs (©NIKU). The radiographs are shown as “shadow” images—materials of higher density are seen lighter than materials of less density, as long as they are of same thickness.
Swept-source optical coherence tomography: choroidal analysis in healthy eyes

Purpose. To evaluate choroidal thickness (CT) in healthy individuals using swept-source optical coherence tomography (SS-OCT). Methods. Ophthalmological examination, axial length using Aladdin optical biometer and choroidal thickness using SS-OCT in 40 healthy eyes were assessed. Results. Females had a thicker choroid than males in all subfields, N3000 region. A negative correlation between CT and age was detected in all subfields and between axial length and SF, T1500 and N1500 subfields (p < 0.05). Conlusions . A negative statistically significant correlation between CT and age and between axial length and SF, T1500 and N1500 subfields were observed.
Design, fabrication and characterization of a hybrid III-V on silicon transmitter for high-speed communications

For several years, the volume of digital data exchanged across the world has increased relentlessly. To manage this large amount of information, high data transmission rates over long distances are essential. Since copper-based interconnections cannot follow this tendency, high-speed optical transmission systems are required in the data centers. In this context, silicon photonics is seen as a way to obtain fully integrated photonic circuits at an expected low cost. While this technology has experienced significant growth in the last decade, the high-speed transmitters demonstrated up to now are mostly based on external laser sources. Thus, the aim of this PhD thesis was to design and produce a high-speed silicon photonic transmitter with an integrated laser source.This transmitter is composed of a high-speed silicon Mach-Zehnder, co-integrated on the same wafer with a hybrid III-V on silicon distributed Bragg reflector laser, which emission wavelength can be electrically tuned in the 1. 3μm wavelength region. The design of the various elements constituting both the laser (III-V to silicon adiabatic couplers, Bragg reflectors) and the modulator (p-n junctions, travelling-wave electrodes) is thoroughly detailed, as well as their fabrication. During the characterization of the transmitters, high-speed data transmission rates up to 25Gb/s, for distances up to 10km are successfully demonstrated, with the possibility to tune the operating wavelength up to 8.5nm. Additionally, in order to further improve the integration of the laser source with the silicon photonic circuit, a solution based on the low-temperature (below 400°C) deposition of an amorphous silicon layer during the fabrication process is also evaluated. Tests on a distributed feed-back laser structure have shown performances at the state-of-the-art level (with output powers above 30mW), thus establishing the viability of this approach.
Grounds for Grounding: A Circuit to System Handbook

the 2008 National Electrical Code and the NEC 2008 Handbook respectively. A home's In addition, all of the home's branch circuits and feeders system. They each have different functions, but they work together to make the building's extends the ground connection — and the Code defines “ground” as the earth. Abstract: This article outlines power, ground PCB, and system layout hints Just like a high-rise building in earthquake-prone areas, great circuit design 5. American Technical Ceramics, Circuit Designer's Notebook, (Capacitor handbook).
Distributed Ledger Technology Based Integrated Healthcare Solution for Bangladesh

Healthcare data is highly sensitive and must be safeguarded. Personal and sensitive data, such as names and addresses, is stored in Encrypted Electronic Health Records (EHRs). This paper proposes a Blockchain-based distributed application platform for Bangladesh’s public and private healthcare service providers. The proposed application framework enables users to create secure digital agreements for commerce or collaboration by leveraging data immutability and smart contracts. As a result, all stakeholders can collaborate securely over the same Blockchain network, taking advantage of their data’s openness and read/write nature. The proposed application is made up of various application interfaces for various stakeholders. The proposed solution employs Hyperledger Fabric and Blockchain to ensure data integrity, privacy, permissions, and service availability. In the application portal, each user has a profile. The creation of a unique identity for each user, as well as the establishment of digital information centers across the country, has greatly aided the process. This application collects health data from each user in a systematic manner, which is useful for research institutes and healthcare-related organizations. For this application, a national data warehouse in Bangladesh is feasible, and various healthcare-related analyses can be performed using the collected data, assisting the strategy and planning department in making informed decisions regarding the healthcare sector in Bangladesh. Because Bangladesh has both public and private healthcare providers, a simple digital strategy is essential for all organizations to accomplish their services. This study proposes a solution to achieve this goal.
VoGE: A Differentiable Volume Renderer using Gaussian Ellipsoids for Analysis-by-Synthesis

The Gaussian reconstruction kernels have been proposed by Westover (1990) and studied by the computer graphics community back in the 90s, which gives an alternative representation of object 3D geometry from meshes and point clouds. On the other hand, current state-of-the-art (SoTA) differentiable renderers, Liu et al. (2019), use rasterization to collect triangles or points on each image pixel and blend them based on the viewing distance. In this paper, we propose VoGE, which utilizes the volumetric Gaussian reconstruction kernels as geometric primitives. The VoGE rendering pipeline uses ray tracing to capture the nearest primitives and blends them as mixtures based on their volume density distributions along the rays. To efficiently render via VoGE, we propose an approximate closeform solution for the volume density aggregation and a coarse-to-fine rendering strategy. Finally, we provide a CUDA implementation of VoGE, which enables real-time level rendering with a competitive rendering speed in comparison to PyTorch3D. Quantitative and qualitative experiment results show VoGE outperforms SoTA counterparts when applied to various vision tasks, e.g., object pose estimation, shape/texture fitting, and occlusion reasoning. The VoGE library and demos are available at: https://github.com/Angtian/VoGE.
DNA Pattern Matching Acceleration with Analog Resistive CAM

—DNA pattern matching is essential for many widely used bioinformatics applications. Disease diagnosis is one of these applications, since analyzing changes in DNA sequences can increase our understanding of possible genetic diseases. The remarkable growth in the size of DNA datasets has resulted in challenges in discovering DNA patterns efﬁciently in terms of run time and power consumption. In this paper, we propose an efﬁcient hardware and software codesign that determines the chance of the occurrence of repeat-expansion diseases using DNA pattern matching. The proposed design parallelizes the DNA pattern matching task using associative memory realized with analog content-addressable memory and implements an algorithm that returns the maximum number of consecutive occurrences of a speciﬁc pattern within a DNA sequence. We fully implement all the required hardware circuits with PTM 45-nm technology, and we evaluate the proposed architecture on a practical human DNA dataset. The results show that our design is energy-efﬁcient and signiﬁcantly accelerates the DNA pattern matching task compared to previous approaches described in the literature.
Short Communication: Cone-Constrained Monotone Mean-Variance Portfolio Selection under Diffusion Models

We consider monotone mean-variance (MMV) portfolio selection problems with a conic convex constraint under diffusion models, and their counterpart problems under mean-variance (MV) preferences. We obtain the precommitted optimal strategies to both problems in closed form and find that they coincide, without and with the presence of the conic constraint. This result generalizes the equivalence between MMV and MV preferences from non-constrained cases to a specific constrained case. A comparison analysis reveals that the orthogonality property under the conic convex set is a key to ensuring the equivalence result.
Variational Transfer Learning using Cross-Domain Latent Modulation

To successfully apply trained neural network models to new domains, powerful transfer learning solutions are essential. We propose to introduce a novel cross-domain latent modulation mechanism to a variational autoencoder framework so as to achieve effective transfer learning. Our key idea is to procure deep representations from one data domain and use it to influence the reparameterization of the latent variable of another domain. Specifically, deep representations of the source and target domains are first extracted by a unified inference model and aligned by employing gradient reversal. The learned deep representations are then cross-modulated to the latent encoding of the alternative domain, where consistency constraints are also applied. In the empirical validation that includes a number of transfer learning benchmark tasks for unsupervised domain adaptation and image-to-image translation, our model demonstrates competitive performance, which is also supported by evidence obtained from visualization.
AI-based automated Meibomian gland segmentation, classification and reflection correction in infrared Meibography

Purpose: Develop a deep learning-based automated method to segment meibomian glands (MG) and eyelids, quantitatively analyze the MG area and MG ratio, estimate the meiboscore, and remove specular reflections from infrared images. Methods: A total of 1600 meibography images were captured in a clinical setting. 1000 images were precisely annotated with multiple revisions by investigators and graded 6 times by meibomian gland dysfunction (MGD) experts. Two deep learning (DL) models were trained separately to segment areas of the MG and eyelid. Those segmentation were used to estimate MG ratio and meiboscores using a classification-based DL model. A generative adversarial network was implemented to remove specular reflections from original images. Results: The mean ratio of MG calculated by investigator annotation and DL segmentation was consistent 26.23% vs 25.12% in the upper eyelids and 32.34% vs. 32.29% in the lower eyelids, respectively. Our DL model achieved 73.01% accuracy for meiboscore classification on validation set and 59.17% accuracy when tested on images from independent center, compared to 53.44% validation accuracy by MGD experts. The DL-based approach successfully removes reflection from the original MG images without affecting meiboscore grading. Conclusions: DL with infrared meibography provides a fully automated, fast quantitative evaluation of MG morphology (MG Segmentation, MG area, MG ratio, and meiboscore) which are sufficiently accurate for diagnosing dry eye disease. Also, the DL removes specular reflection from images to be used by ophthalmologists for distraction-free assessment.