Miracle-dz/UniFAR-FTUs huggingface dataset:
Mono or Dual Antiplatelet Therapy for Treating Patients with Peripheral Artery Disease after Lower Extremity Revascularization: A Systematic Review and Meta-Analysis

The efficacy of dual antiplatelet therapy (DAPT) for patients with peripheral artery disease (PAD) after lower-limb intervention remains controversial. Currently, the prescription of DAPT after an intervention is not fully recommended in guidelines due to limited evidence. This study compares and analyzes the prognosis for symptomatic PAD patients receiving DAPT versus monotherapy after lower-limb revascularization. Up to November 2021, PubMed/MEDLINE, Embase, and Cochrane databases were searched to identify studies reporting the efficacy, duration, and bleeding complications when either DAPT or monotherapy were used to treat PAD patients after revascularization. Three randomized controlled trials and seven nonrandomized controlled trials were included in our study. In total, 74,651 patients made up these ten studies. DAPT in PAD patients after intervention was associated with lower rates of all-cause mortality (HR = 0.86; 95% CI, 0.79–0.94; p < 0.01), major adverse limb events (HR = 0.60; 95% CI, 0.47–0.78; p < 0.01), and major amputation (HR = 0.78; 95% CI, 0.64–0.96) when follow-up was for more than 1-year. DAPT was not associated with major bleeding events when compared with monotherapy (OR = 1.22; 95% CI, 0.69–2.18; p = 0.50) but was associated with a higher rate of minor bleeding as a complication (OR = 2.54; 95% CI, 1.59–4.08; p < 0.01). More prospective randomized studies are needed to provide further solid evidence regarding the important issue of prescribing DAPT.
Frequent 4EBP1 Amplification Induces Synthetic Dependence on FGFR Signaling in Cancer

Simple Summary Our work establishes that amplification of 4EBP1, as a part of Chr. 8p11, creates a synthetic dependency on FGFR1 signaling in cancer. 4EBP1 is phosphorylated by FGFR1 and PI3K signaling, and accordingly cancer with 4EBP1-FGFR1 amplification is more sensitive to FGFR1 and PI3K inhibition due to inhibition of 4EBP1 phosphorylation. Moreover, we characterize the translational targets of 4EBP1 and identify that 4EBP1 specifically regulates the translation of genes involved in insulin signaling, glucose metabolism, and the inositol pathway that plays a role in cancer progression. Abstract The eIF4E translation initiation factor has oncogenic properties and concordantly, the inhibitory eIF4E-binding protein (4EBP1) is considered a tumor suppressor. The exact molecular effects of 4EBP1 activation in cancer are still unknown. Surprisingly, 4EBP1 is a target of genomic copy number gains (Chr. 8p11) in breast and lung cancer. We noticed that 4EBP1 gains are genetically linked to gains in neighboring genes, including WHSC1L1 and FGFR1. Our results show that FGFR1 gains act to attenuate the function of 4EBP1 via PI3K-mediated phosphorylation at Thr37/46, Ser65, and Thr70 sites. This implies that not 4EBP1 but instead FGFR1 is the genetic target of Chr. 8p11 gains in breast and lung cancer. Accordingly, these tumors show increased sensitivity to FGFR1 and PI3K inhibition, and this is a therapeutic vulnerability through restoring the tumor-suppressive function of 4EBP1. Ribosome profiling reveals genes involved in insulin signaling, glucose metabolism, and the inositol pathway to be the relevant translational targets of 4EBP1. These mRNAs are among the top 200 translation targets and are highly enriched for structure and sequence motifs in their 5′UTR, which depends on the 4EBP1-EIF4E activity. In summary, we identified the translational targets of 4EBP1-EIF4E that facilitate the tumor suppressor function of 4EBP1 in cancer.
Learning Efficient Dynamic Controller for HVAC System

People employ a variety of devices to achieve comfort in various aspects of their lives; for example, numerous types of air conditioners are used to maintain a pleasant indoor temperature. The wide applications of heating, ventilation, and air conditioning (HVAC) systems have significantly improved the comfort level of the indoor environment for commercial buildings. However, air conditioners have their own set of issues, the most significant of which is the increased energy usage. Besides the fact that HVAC is a recent move toward the indoor temperature adjustment, the energy cost that arose from the HVAC system is still high, which takes up over 40% of the total energy. How to develop an energy-eﬀicient HVAC system has become one of the challenging topics that need further investigation. This paper addresses this problem with the aid of deep learning (DL) algorithms. Furthermore, this study proposes an energy-eﬀicient controller and improvement schemes for HVAC systems based on deep reinforcement learning algorithms. To reduce the implementation cost of the proposed design, this study utilizes neural network pruning techniques to develop a low-complexity HVAC controller. The experimental results show that the algorithm proposed in this study not only retains a high energy-saving rate but also reduces the implementation cost of the HVAC control algorithm.
Telehealth and Burn Care: From Faxes to Augmented Reality

Despite advances in telemedicine, practices remain diverse, ranging from telephonic to still images and video-based conferencing. We review the various modes of telemedicine in burn care and summarize relevant studies, including their contributions and limitations. We also review the role of a more recent technology, augmented reality, and its role in the triage and management of burn patients. Telemedicine in burn care remains diverse, with varied outcomes in accuracy and efficiency. Newer technologies such as augmented reality have not been extensively studied or implemented but show promise in immersive, real-time triage.
Spotlight on Tepotinib and Capmatinib for Non-Small Cell Lung Cancer with MET Exon 14 Skipping Mutation

Abstract Mesenchymal-epithelial transition (MET) receptor tyrosine kinase is overexpressed, amplified, or mutated in 1–20% of NSCLC. MET dysregulation is associated with a poor prognosis. Recently, development of targeted therapies against MET exon 14 mutations has demonstrated efficacy and tolerability in early trials. Here we focus on tepotinib and capmatinib in regards to molecular characteristics, early preclinical and clinical data, and the emerging role in future studies and clinical practice.
Spin Polarization of Mn Could Enhance Grain Boundary Sliding in Mg

Segregation of rare earth alloying elements are known to segregate to grain boundaries in Mg and suppress grain boundary sliding via strong chemical bonds. Segregation of Mn, however, has recently been found to enhance grain boundary sliding in Mg, thereby boosting its ductility. Taking the Mg (2¯114) twin boundary as an example, we performed a first-principles comparative study on the segregation and chemical bonding of Y, Zn, and Mn at this boundary. We found that both Y-4d and Mn-3d states hybridized with the Mg-3sp states, while Zn–Mg bonding was characterized by charge transfer only. Strong spin-polarization of Mn pushed the up-spin 3d states down, leading to less anisotropic Mn–Mg bonds with more delocalized charge distribution at the twin boundary, and thus promotes grain boundary plasticity, e.g., grain boundary sliding.
Radiation Pattern, Surface Current Distribution, and Q-Factor Improvement Technique Using DMS CSPA: Part-II

In order to improve the efficiency, reliability, and accuracy during fabrication of antenna in 5G regime of frequencies, a Double-Material Substrate (DMS) Cylindrical Surrounding micro-strip fed Patch Antenna (CSPA) has been designed for use in 2.4/5.8 GHz WLAN, 2.5/5.15 GHz WiMAX wireless standards, 5.9 GHz Intelligent Transportation Society (ITS) band (5.85-5.925 GHz) and middle band of 5G technology (2.3 GHz ~ 2.4 GHz and 2.5 GHz ~ 2.69 GHz). The proposed antenna addresses the negative effect of dimension inaccuracy caused by the high permittivity substrate material used in CSPA. The antenna was designed, simulated, and thoroughly analyzed on the basis of the radiation pattern, surface current distribution, and Q factor. Findings reveal that the DMS CSPA showed a worthy radiation pattern and Q-factor of 3.62 and 2.31 at 2.68 GHz and 5.55 GHz bands, respectively. The radiation plots of simulation results present the angular width values between 450 ~ 1040, showing a wider coverage area with minimal sidelobe level between -4.4 dB ~ 11.9 dB for the E-planes and H-planes at both resonance frequencies.
Impacts of Learning Orientation on the Modeling of Programming Using Feature Selection and XGBOOST: A Gender-Focused Analysis

In programming, modeling is a generalized explanatory system that organizes key characteristics of a specific matter or object of interest using computer science concepts. Modeling is integral for both automation design in programming education and communication in the collaborative process. This study investigates the effect of learning orientation on the modeling stage based on gender. The study includes 756 male and 688 female elementary-school students. We analyzed the results of XGBOOST by extracting the influential characteristics from feature selection along with the basic statistics. As a result of the study, it was confirmed that learners, regardless of gender, had the largest gap in modeling and that this was the stage at which differences occurred in programming education. For male students, the process of collecting data for modeling or devising a solution was found to be an important learning method. This shows that it is necessary to create an environment to focus on activities that derive solutions from the collected data along with strengthening information retrieval education. Although female students showed a similar tendency to male students, the process of cooperating with friends as a differentiating factor was found to be an important learning method. It seems necessary to apply teaching and learning methods that can strengthen team projects that can collaborate with friends. The findings could serve as a reference for teaching and learning design and operation for effective programming education.
Knowledge Infrastructure, Process, and the Effectiveness of Manufacturing SMEs in Selangor, Malaysia

Introduction- In today’s competitive business environment, companies are always looking for ways to improve employees’ speed and efficiency. However, the nature of knowledge work is more complex, and therefore more difficult to evaluate. Knowledge workers think and behave differently, and have different needs (Hollar et al. 2002). Organizations whose success or failure is determined by the decisions they make are handicapped by systems that are centered on processes or functions. They face many challenges in today’s business climate. As a result, these organizations struggle to improve business productivity while managing costs and find it hard to make changes in their systems quickly, despite a pressing need to do so. To succeed, these organizations need to move their thinking from processes and functions to decisions; (Andreeva and Kianto, 2012)
Successive approximation type resistance to digital converter

Successive approximation type direct resistance to digital converter (SAR RDC) topology is presented here. The conventional SAR type ADC is augmented with an additional opamp inverting summer and a standard resistance such that the digital output of the SAR directly indicates the value of an unknown resistance connected between the output of the digital to analog converter of the SAR RDC and the inverting input of the added inverting summer. Analysis of the proposed technique presented here helps select proper components at the design stage itself to obtain minimal errors in the measurement of the unknown resistor. The major advantage of the proposed scheme is that it retains the basic architecture of an SAR ADC and hence can be implemented with all available SAR ADC architectures, including the ability to install ‘auto-ranging’. An added advantage is that the value of the unknown resistor is determined in terms of a standard resistor and hence good accuracy is easily obtained. Simulation studies and results obtained from a prototype SAR RDC built and tested, establish the efficacy of the proffered technique. The results indicate a worst-case error of < ±0.2% and no missing codes.
Development of a Model for Genomic Prediction of Multiple Traits in Common Bean Germplasm, Based on Population Structure

Due to insufficient identification and in-depth investigation of existing common bean germplasm resources, it is difficult for breeders to utilize these valuable genetic resources. This situation limits the breeding and industrial development of the common bean (Phaseolus vulgaris L.) in China. Genomic prediction (GP) is a breeding method that uses whole-genome molecular markers to calculate the genomic estimated breeding value (GEBV) of candidate materials and select breeding materials. This study aimed to use genomic prediction to evaluate 15 traits in a collection of 628 common bean lines (including 484 landraces and 144 breeding lines) to determine a common bean GP model. The GP model constructed by landraces showed a moderate to high predictive ability (ranging from 0.59–0.88). Using all landraces as a training set, the predictive ability of the GP model for most traits was higher than that using the landraces from each of two subgene pools, respectively. Randomly selecting breeding lines as additional training sets together with landrace training sets to predict the remaining breeding lines resulted in a higher predictive ability based on principal components analysis. This study constructed a widely applicable GP model of the common bean based on the population structure, and encouraged the development of GP models to quickly aggregate excellent traits and accelerate utilization of germplasm resources.
The EBEX Balloon-borne Experiment—Gondola, Attitude Control, and Control Software

The E and B Experiment (EBEX) was a long-duration balloon-borne instrument designed to measure the polarization of the cosmic microwave background (CMB) radiation. EBEX was the first balloon-borne instrument to implement a kilopixel array of transition edge sensor (TES) bolometric detectors and the first CMB experiment to use the digital version of the frequency domain multiplexing system for readout of the TES array. The scan strategy relied on 40 s peak-to-peak constant-velocity azimuthal scans. We discuss the unique demands on the design and operation of the payload that resulted from these new technologies and the scan strategy. We describe the solutions implemented, including the development of a power system designed to provide a total of at least 2.3 kW, a cooling system to dissipate 590 W consumed by the detectors’ readout system, software to manage and handle the data of the kilopixel array, and specialized attitude reconstruction software. We present flight performance data showing faultless management of the TES array, adequate powering and cooling of the readout electronics, and constraint of attitude reconstruction errors such that the spurious B-modes they induced were less than 10% of the CMB B-mode power spectrum with r = 0.05.
Mobile Internet Technology Adoption for Sustainable Agriculture: Evidence from Wheat Farmers

Mobile internet technology (MIT) is considered a significant advancement in information and communication technology (ICT), due to its crucial impact on the financial system and social life. In addition, it is an essential technology to overcome the digital divide between urban and rural areas. In terms of agricultural advancement, MIT can play a key role in data collection and the implementation of smart agricultural technologies. The main objectives of this study were to (i) investigate MIT adoption and use in sustainable agriculture development among selected wheat farmers of Pakistan and (ii) examine the crucial factors influencing MIT adoption. This study selected 628 wheat farmers from four districts of Khyber Pakhtunkhwa Province (KPK), Pakistan, for sampling. This study used a bivariate probit method for sampling wheat farmers. The analysis of wheat farmer’s data showed farmer’s age, farm size, farm location, and knowledge about Internet technology (IT) are strongly correlated with MIT adoption in sustainable agriculture development. Results showed on average, 65% of wheat farmers have mobile devices supporting these Internet technologies, and 55% use MIT in agricultural environments. Since the extant research on MIT adoption for agriculture production in Pakistan is sparse, this study helps advance MIT adoption-based studies. These outcomes may draw the attention of decision-makers dealing with IT infrastructure and agricultural equipment who can support farmers adopting MIT.
Comparative Study of Two Proposed Methods for Image Enhancement of Abnormal MRI Brain Images in Spatial and Frequency Domain

: Image enhancement is the part of image pre-processing that is used to improve image quality and adjust image information content for further processing and includes techniques such as removing noise or reducing noise levels to a certain extent, adjusting contrast, sharpening the image, etc. In this research, 5 original grayscale images which are abnormal magnetic resonance imaging (MRI) brain images have been processed by using enhancement techniques in two different domains, spatial and frequency. This research described method of enhancement abnormal MRI brain images by using combining spatial domain techniques in MATLAB and method of enhancement abnormal MRI brain images by using combined 2-D stationary wavelet transform for denoising in Wavelet Analyzer technique within MATLAB and filtering in frequency domain technique in MATLAB. Image data used in this research were obtained from Radiopaedia, an educational radiology resource. The best technique to applied on abnormal MRI brain images has been detected by comparing the results of peak signal to noise ratio (PSNR), signal to noise ratio (SNR) and mean square error (MSE). Based on results obtained for PSNR, SNR and MSE measurements, it has been concluded and confirmed that better results for image enhancement of abnormal MRI brain images gives us combining spatial enhancement techniques.
Unpacking the Stories Behind the Crafting of Modules among English College Instructors: A Phenomenology

Quality education has been the constant aim and commitment of the tertiary institutions (TEIs) in the Philippines. This commitment has been put to test during the emergence of the Covid-19 pandemic which started in January 2019. During this time, English instructors were suddenly compelled to devise selflearning modules to support their learners’ transition to blended learning. Hence, the purpose of the study was to uncover the lived experiences of college instructors who were assigned to become module writers for English courses. The study is qualitative research adopting the phenomenological approach. Using purposive sampling, the participating 14 college instructors were identified and divided equally for in-depth interview and focus group discussion. Data were analyzed through the use of coding and thematic analysis. Results revealed the experiences of the participants: (1) lack of reference materials, (2) alignment of activities to objectives, (3) pressures on the limited time, (4) doubts on the quality of the module, (5) mixed emotions, and (6) lack of knowledge. In response to the challenges they have encountered, they deem the following coping strategies as essential: (7) collaborated with colleagues, (8) motivated by students’ learning, (9) asked for God’s providence, (10) conducted peer review, and (11) utilized different references. Upon reflecting on their entire experience, they arrived at the following insights: (12) provision of trainings and seminars, (13) reduction of unnecessary activities in the modules, (14) provision of resource materials, (15) importance of preparation, and (16) provision of adequate time in writing the module. The results, imply that certain improvements should be made within the institution to improve the writing experiences of the assigned English instructors as well as enhance the overall quality of the produced modules. This study is therefore deemed significant as this highly contributes to the body of knowledge related to materials development.
A Concept Analysis of Illness Intrusiveness in Chronic Disease: Application of the Hybrid Model Method

This study clarifies the concept of illness intrusiveness in patients with a chronic disease using the hybrid model method. To clarify the dimension, attributes, and definition of illness intrusiveness in chronic disease, three phases of analysis were conducted. In the theoretical phase, a working definition was devised through a systematic review. In the fieldwork phase, individual in-depth interviews were conducted with nine participants with chronic diseases. In the final analytic phase, the results were integrated through comparison and review. There are four domains and eleven attributes of illness intrusiveness in chronic disease. The domains include physical, psychological, social/contextual, and spiritual. The physical domain consists of four attributes: pain, fatigue, physical malfunction, and change of body image. The psychological domain consists of three attributes: psychological weakness, uncertainty, and stigma. The social/contextual domain is made up of three attributes: withdrawal of role play, limit of daily life, and burden of changing health habits. Finally, the spiritual domain had one attribute: unstable spiritual state. Thus, based on the study findings, it is necessary to develop a suitable illness intrusiveness in chronic disease assessment scale to assess chronic disease patients.
Pedestrian safety system with crash prediction

Every year nearly 1.5 million people are dying in traffic collisions around the world, due to the unexpected behavior of pedestrians while crossing the road. To address this problem an augmentation function for predicting the crash risk of the active pedestrian is proposed. The augmentation function has several functions like pre-crash scenario, vehicle trajectory, and pedestrian trajectory. In a Pre-Crash scenario, pedestrian movement such as entering the road boundary or not is detected. The input comes from the sensor which is located at the head of the car. After the pre-crash scenario vehicle trajectory is used to control the speed of the vehicle. Then the Markov IRW model-based pedestrian trajectory finding is used to predict the state of each pedestrian. The states are categorized into three types: Running, Walking and Standing. In this model, the pedestrian types whether the pedestrian is a child or young or old aged people is predicted. And the crash risk is evaluated based on the Monte Carlo algorithm that calculates the minimum detection range for active pedestrians. If the crash risk is exceeded the threshold limit then an augmentation function is activating the evasive action.
Wide-range grounded non-linear transconductor and its application as a frequency doubler

ABSTRACT A non-linear transconductor with quadratic-type non-linearity is designed and experimentally verified in this article. The inherent non-linearity of a single N-type Metal Oxide Semiconductor (NMOS) transistor is used to obtain this transconductor with extra biasing circuitry that enables the reconfiguration of the drain-to-source voltage () and the gate-to-source voltage () such that both are weighted replicas of the applied input voltage (). The cancellation of the threshold voltage () eliminates the linear term and renders the design () independent. Experimental results using off-shelf components validate the derived theory.