Miracle-dz/UniFAR-FTUs huggingface dataset:
A Wideband High-efficiency Doherty Power Amplifier for LTE

This article describes a broadband Doherty power amplifier designed with a class AB and class C PA that is suitable for LTE Band-7 and Wi-Fi applications. The output matching network is theoretically analyzed, with emphasis on the effect of the auxiliary amplifier’s non-ideal infinite output impedance on parasitic devices. A novel Doherty-like power amplifier (DPA) is constructed with 25 W, 2.2-2.8 GHz GaN HEMT transistors. The quarter-wave transformer that was previously used in the DPA topology was replaced by the corresponding Klopfenstein tapper network. Real-world prototype implementations have shown that this modification increases the achieved DPA bandwidth (BW) compared to conventional topologies while maintaining efficiency values. (Fractional bandwidth equals 24%) The DPA assumes an OBO value of 6 dB, which is typical for basic designs and explanations because the voltage level involved is 1:4 and the peak power amplifier is activated at half of the input voltage’s dynamic range. However, in order to increase the OBO value, the signal must first be compatible with the PAPR value. This can be accomplished by adjusting the power divider in an asymmetrical manner. The OPBO range was extended using the asymmetric DPA technique.
A Static Machine Learning Based Evaluation Method for Usability and Security Analysis in E-Commerce Website

Measurement of e-commerce usability based on static quantities variable is state-of-the-art because of the adoption of sequential tracing of the next phase in the categorical data. The global COVID-19 outbreak has completely disrupted society and drastically altered daily life. The concept refers to an electronic commerce network that appears with thorough, understandable conviction, demand, and rapid confirmation as a replacement for the economical market’s “brick-and-mortar” model, which replaces how we do everything, including business strategy, and provides a better understanding with the interpretation of e-commerce features. This study was supervised to analyze usability assessments using statistical methods and security assessments using online e-commerce security scanner tools to investigate e-business standards that consider the caliber of e-services in e-commerce websites across Asian nations. The method was developed to optimize complex systems based on multiple criteria. The initial (supplied) weights are used to determine the compromise ranking list and compromise solution. This paper examines the usability of e-commerce in rural areas using a new data set from the Jharkhand region. On the e-commerce websites of Jharkhand, India, usability is commonly considered in conjunction with learnability, memorability, effectiveness, engagement, efficiency, and completeness. Using a user-oriented questionnaire testing method, this survey attempts to close the gaps mentioned above. Then, across each column, divide each value by the column-wise sum that is created using their corresponding value, whichever produces a new matrix B. Finally, determine the row-wise sum of matrix B representing the ( $3\times1$ ) matrix. Using model trees and bagging, this study addresses classification-related issues. This regression technique is useful for problems involving classification. The model is trained using secondary data from the MBTI 16 personality factors affecting personality category.
Multi-Input Bidirectional DC-DC Converter for Energy Management in Hybrid Electrical Vehicles Applications

Battery storage systems are widely used in several applications; in particular, they are fundamental in electrical or hybrid electrical vehicles. The different storages are interfaced to the inverter with a DC-DC converter in order to match the different voltage levels. The battery systems are subjected to aging phenomenon and if one battery is deteriorated, all the series is involved. To avoid this problem, a double-input DC-DC converter is proposed in this paper. The two storages can be controlled independently and, therefore, the system reliability is improved. Moreover, the deteriorated battery is not bypassed, therefore it can provide energy to the system at a limited rate and so the system performance is maximized. In addition, batteries based on different technologies can be mixed by the proposed converter obtaining the best from each technology.
The feasibility of Hall effect imaging in humans

Hall effect imaging is a new technique for mapping the electrical properties of a sample non-invasively. Its principle has been demonstrated with two and three-dimensional imaging of phantoms and biological samples. This paper addresses the potential of this technique for diagnostic imaging of the human body, based on experimental data and theoretical models of this technique developed over the past few years. The analysis is applicable to complex biological samples in general. The arguments are given at the basic physics level, so that the conclusion is independent of current technology status. These arguments are corroborated with imaging experiments of an aorta sample. The conclusion is that Hall effect imaging is not suited for quantifying the electrical constants in complex biological systems. Although this technique is able to produce detailed images that qualitatively reflect the electrical heterogeneity of a tissue sample, quantitative measurements of electrical constants are not practical for complex biological systems.
A simplified Approach for Accurate Arrythmia Detection using Automated Machine Learning

This paper introduces a straightforward and computationally inexpensive approach to classifying heartbeat anomalies based on ECG signals. Cardiac arrests are often associated with irregular heart rhythm, making arrythmia a major factor to cardiac events when not sufficiently monitored. In this context, the current paper presents a comprehensive analysis and arrythmia prediction for 44 patients. For each patient in the study, heartrate signals manually labeled by physicians were available. The preprocessed time-series were used to train machine learning models available in various automated frameworks, allowing for accurate binary classification. The highest scores after benchmarking were obtained by LightGBM. Our proposed method provides similar results in terms of classification performance with state-of-the-art algorithms for arrythmia detection. The current work thus introduces a simplified pipeline, improvement in prediction time and classification accuracy.
PGSLM: Edge-enabled probabilistic graph structure learning model for traffic forecasting in Internet of vehicles

With the rapid development of the 5G communications, the edge intelligence enables Internet of Vehicles (IoV) to provide traffic forecasting to alleviate traffic congestion and improve quality of experience of users simultaneously. To enhance the forecasting performance, a novel edge-enabled probabilistic graph structure learning model (PGSLM) is proposed, which learns the graph structure and parameters by the edge sensing information and discrete probability distribution on the edges of the traffic road network. To obtain the spatio-temporal dependencies of traffic data, the learned dynamic graphs are combined with a predefined static graph to generate the graph convolution part of the recurrent graph convolution module. During the training process, a new graph training loss is introduced, which is composed of the K nearest neighbor (KNN) graph constructed by the traffic feature tensors and the graph structure. Detailed experimental results show that, compared with existing models, the proposed PGSLM improves the traffic prediction performance in terms of average absolute error and root mean square error in IoV.
BP-SCIM: A Reconfigurable 8T SRAM Macro for Bit-Parallel Searching and Computing In-Memory

This work presents BP-SCIM: a reconfigurable 8T static random access memory (SRAM) macro for bit-parallel searching and computing in-memory (CIM). The decoupled read/write ports of the employed 8T SRAM bit-cell eliminate read disturbance during search and CIM operations. BP-SCIM can support both in-memory Boolean logic and arithmetic operations. Novel CIM-friendly algorithms and peripheral circuits are proposed to reduce the latency of complex arithmetic operations such as multiplication and division. In addition, BP-SCIM can be configured as either a binary content-addressable memory (CAM) or a ternary CAM for fast searching. A $256\times64$ BP-SCIM test chip was implemented in 65-nm CMOS technology. The 8-bit addition and 8-bit multiplication operations can achieve the maximum energy efficiency of 3.11 TOPS/W and 0.17 TOPS/W, respectively at 0.7 V supply. For the binary CAM search operation, BP-SCIM can achieve the minimum energy consumption of 0.91 fJ/bit/search at 87 MHz and 0.8 V supply.
Design of a Miller Amplifier using gm/ID based on A First-order Building Block Approximation

In this paper the gm/ID methodology for designing analog CMOS circuits is used. As a case of study the single-ended Miller OTA design is widely discussed and analized. In order to show the advantage of gm/ID it is demonstrated that the first order building block approximation allows to understand not only how to correctly do the sizing of each transistor, but also the physical meaning of each small-signal design model. This design flow is carried out by using design rules of a 130 nm CMOS technology, where Cadence is used for performing simulations at transistor level, obtaining results that confirm the usefullnes of the design models and the basics’ veracity.
Task offloading and resource allocation for edge-enabled mobile learning

Mobile learning has evolved into a new format of education based on communication and computer technology that is favored by an increasing number of learning users thanks to the development of wireless communication networks, mobile edge computing, artificial intelligence, and mobile devices. However, due to the constrained data processing capacity of mobile devices, efficient and effective interactive mobile learning is a challenge. Therefore, for mobile learning, we propose a "Cloud, Edge and End" fusion system architecture. Through task offloading and resource allocation for edge-enabled mobile learning to reduce the time and energy consumption of user equipment. Then, we present the proposed solutions that uses the minimum cost maximum flow (MCMF) algorithm to deal with the offloading problem and the deep Q network (DQN) algorithm to deal with the resource allocation problem respectively. Finally, the performance evaluation shows that the proposed offloading and resource allocation scheme can improve system performance, save energy, and satisfy the needs of learning users.
On the Performance Analysis of the Microprocessor Based DC Voltage Calibrator

A microcontroller-based architecture of a DC voltage calibrator is presented in the paper and its performance is analyzed. The voltage calibrator is used as a basic measurement, test and adjustment technique for setting and checking measurement instrumentation. The voltage provided is used to achieve optimal performance of the device or process under test. The proposed calibrator is built around the PIC 18F452 microcontroller, using its PWM output signal generator facility. Both 8 bits and 10 bits resolution have been used and studied along this work. The advantages of using a microcontroller are: the possibility to display useful information (number, duty cycle, and voltage), communication with a computer and easy operation with buttons. The experiments revealed also the importance of the used components (for example, by changing the output operational amplifier with a quality one, it was possible to reduce the output residual voltage from 39 mV to 0.9 mV). Aspects regarding errors and their correction are analyzed. The designed calibrator can be used for the calibration of measuring instruments, in other measurement applications and for educational purposes.
VLF system for SID monitoring

This paper presents a proposal for a SID (sudden ionosphere disturbances) monitoring system based on the VLF method. The research focuses on the assembly of a solar flare monitoring system by monitoring a VLF Bafa Turkey transmitter with a working frequency of 26.7kHz. The study also shows the effect of the VLF radio wavess over the ionosphere. Results are presented of solar flares recorded on the territory of Sofia Bulgaria in September 2022, when multiple M-class and C-class flares were observed. The results are compared with data recorded by DIAS (Dublin Institute for Advanced Studies) as well as against data from SpaceWeatherLive and https://solarmonitor.org. There is a similarity in the results obtained from different systems, and from different geographical areas, which proves the functionality of the proposed system and the method used.
Conflict about Climate Change at the American Meteorological Society: Meteorologists’ Views on a Scientific and Organizational Controversy

AbstractThis article analyzes open-ended survey responses to understand how members of the American Meteorological Society (AMS) perceive conflict within the AMS over global warming. Of all survey respondents, 53% agreed that there was conflict within the AMS; of these individuals who perceived conflict, 62% saw it as having at least some productive aspects, and 53% saw at least some unproductive aspects. Among members who saw a productive side to the conflict, most agreed as to why it was productive: debate and diverse perspectives enhance science. However, among members who saw an unproductive side, there was considerable disagreement as to why. Members who are convinced of largely human-caused climate change expressed that debate over global warming sends an unclear message to the public. Conversely, members who are unconvinced of human-caused climate change often felt that their peers were closed-minded and suppressing unpopular views. These two groups converged, however, on one point: politics was se.
Description of Method-level Mutation Operators for Java

This document provides a brief description of method-level mutation operators for Java used by muJava. When designing method-level mutation operators for Java, we followed the selective approach [1]. The selective results found that the traditional operatorso of modifying operands and statements give little effectiveness to mutation testing. Therefore, we only consider mutation operators that modify expression by replacing, deleting, and inserting primitive operators. muJava provides six kinds of primitive operators; (1) arithmetic operator, (2) relational operator, (3) conditional operator, (4) shift operator, (5) logical operator, and (6) assignment. For some of them, muJava provides short-cut operators. This section presents designs of mutation operators for those six kinds of primitive operators. We try to design mutation operators that replace, insert, and delete the primitive operators. We defined total 12 method-level operators in Table 1. The detailed description for the operators are described in the following subsections, according to each primitive operator.
Locally Quasi-Convex Compatible Topologies on a

Instituto de Matematica Interdisciplinar y Departamento de Geometria y Topologia,Universidad Complutense de Madrid, Madrid 28040, Spain; E-Mail: peinador@mat.ucm. es* Author to whom correspondence should be addressed; E-Mail: lydia.aussenhofer@uni-passau.de;Tel. : +49-851-509-3059.Academic Editor: Sidney A. MorrisReceived: 4 May 2015 / Accepted: 8 October 2015 / Published: 13 October 2015Abstract: For a locally quasi-convex topological abelian group (G;˝), we study the posetC(G;˝) of all locally quasi-convex topologies on Gthat are compatible with ˝(i.e., havethe same dual as (G;˝)) ordered by inclusion. Obviously, this poset has always a bottomelement, namely the weak topology ˙(G;Gb). Whether it has also a top element is an openquestion. We study both quantitative aspects of this poset (its size) and its qualitative aspects,e.g., its chains and anti-chains. Since we are mostly interested in estimates “from below”,our strategy consists of ﬁnding appropriate subgroups Hof Gthat are easier to handle andshow that C(H) and C(G=H) are large and embed, as a poset, in C(G;˝). Important specialresults are: (i) if Kis a compact subgroup of a locally quasi-convex group G, then C(G)and C(G=K) are quasi-isomorphic (3.15); (ii) if Dis a discrete abelian group of inﬁniterank, then C(D) is quasi-isomorphic to the poset F
One Natural Gas Production Prediction Grey Model Based on Exponential Smoothing

In order to improve forecasting ability of grey model in prediction of natural gas production,one improved grey model is put forward in this paper,which is based on exponential smoothing method and improved calculating method of background value.Exponential smoothing method is used firstly not only makes full use of the available information but also diminishes the randomness of data.Then the calculating method of background value of grey model is improved to transform the calculated production data to be a regular exponential variety sequential.Experiments show the improved grey model has more reliable forecasting ability.
Geometric properties of deep-water breaking waves

The time-space evolution of a steep water wave reaching the breaking stage is observed by means of a visualization technique. In particular, the asymmetry of the wave profile in the near-breaking region is displayed. Measurements at breaking onset on a sample of breaking waves show a relation between the rate of asymmetry growth and the breaker type. The shape evolution of a plunging crest after breaking has started, and the related splash-up phenomenon and its part in the air-entrainment process are also observed.
Context shapes: a novel approach for partial complementary shape matching in proteins

Interactions between proteins are governed by the kinetics and stability of the docked conformation, or "pose". The stability of a pose is governed by the surface electrostatics and by the surface shape. Shapes that are more nearly complimentary will fill space better when docked. The stability of a pose can be approximated by the amount of surface area excluded from solvent, which is approximately the total area over which the two surfaces are complimentary. For this work we assume proteins are static shapes, i.e. rigid-bodies. To enable interaction-based systems biology studies, we develop a new shape matching approach which successfully docks proteins in a rigid-body sense. When two rigid shapes are positioned as close as possible without passing through each other, there are at least three points of actual contact, called Physical Contact Points (PCP). If two proteins can be docked, the partial surfaces from the two proteins around any one of the three PCPs should be in high degree of complementarity. We define the notion of Context Shape (CS) as the local shape of the protein around a PCP. Superimposing two context shapes implies aligning two surface points. Since surface points are aligned at PCPs, the task of finding PCPs reduces to the problem of evaluating the complementarity of context shapes, which is a rotational alignment problem obviating the need for translational search. We propose to speed up the pose (mapping) computation considerably by pre-computing a matching table of all possible mappings. This approach is very efficient because table checking is much faster than rotation operations. Other filters based on solid vectors and solid angles are employed to further reduce the search space. Our preliminary results indicate that our method finds the crystallographically determined binding interaction within 2.5 A in a majority of the test cases. Comparisons with PatchDock and ZDOCK(PSC) show that our method based on CS gives better predications in both bound-vs-bound and unbound-vs-bound scenarios on a benchmark v2.4 with 84 cases.
COL1A1–PDGFB Fusion Gene Detection Through Bulk RNA-Seq and Transcriptomic Features of Dermatofibrosarcoma Protuberans

Supplemental Digital Content is Available in the Text. BACKGROUND Dermatofibrosarcoma protuberans (DFSP) is a cutaneous sarcoma with obscure origin and multidirectional differentiation. Application of RNA-Seq in the detection of COL1A1–PDGFB is still at early stages. OBJECTIVE We aim to test the efficacy of fusion gene detection using bulk RNA-Seq in DFSPs, explore altered molecular pathways and biological processes for evidences of tumor origin and cell identity shift. MATERIALS AND METHODS Dermatofibrosarcoma protuberans and normal dermis samples were acquired for RNA-Seq. Fusion gene detection was performed using STAR-Fusion. RNA-Seq 2G yielded differentially expressed genes. Altered pathways, key gene ontology terms, and similar cell/tissue types were identified with gene set enrichment analysis. xCell was used for cell types enrichment analysis. RESULTS 28/30 CD34(+) cases were positive for COL1A1–PDGFB. 406 upregulated and 543 downregulated genes were determined. Among the top 10 upregulated genes, 6 had neural distribution, function, or disease correlation. The upregulated genes were related to synapse, trans-synaptic signaling, neural development, and extracellular matrix. Similarities between DFSP and nervous system components were highlighted, with fibroblast cellular abundancy increased during xCell analysis. CONCLUSION Bulk RNA-Seq provided with high detection rate of COL1A1-PDGFB. Dermatofibrosarcoma protuberans showed fibroblastic activity and neural features, which validated DFSP's fibroblast origin and tendency of neural differentiation.
Introduction of the Personal Domain in Water Sanitation and Hygiene (WASH), a New Approach to Identify Missing Health Impacts

The water sanitation and hygiene (WASH) sector has provided beneficiaries in low and middle-income countries with latrines and clean water for decades. However, we still need good evidence documenting the expected health impact. This paper investigates why we lack this evidence and ways to move forward. Using mTEC agar, we monitored E. coli contamination on selected “hotspot” surfaces within the kitchen environments of 32 low-income households in Dhaka, Bangladesh, every six weeks for two years. Despite being washed, the highest average contamination was found on food plates, at 253 cfu/10 cm2, followed by cutting knives, with 240 cfu/10 cm2. The drinking vessel surfaces and the latrine doorknobs had the lowest contaminations, with E. coli means of 167 and 73 cfu/10 cm2, respectively. These findings imply a need to measure an individual’s pathogen exposure as close to the mouth as possible to estimate the true pathogen exposure. The paper proposes introducing the new “personal domain”—the point of consumption—as the physical sphere in which WASH interventions should be assessed. With this approach, we can observe and quantify the different pathogen exposure routes and, with this, further improve WASH interventions.
Thermal and Power Challenges in High Performance Computing Systems

This paper provides an overview of the thermal and power challenges in emerging high performance computing platforms. The advent of new sophisticated applications in highly diverse areas such as health, education, finance, entertainment, etc. is driving the platform and device requirements for future systems. The key ingredients of future platforms are vertically integrated (3D) die-stacked devices which provide the required performance characteristics with the associated form factor advantages. Two of the major challenges to the design of through silicon via (TSV) based 3D stacked technologies are (i) effective thermal management and (ii) efficient power delivery mechanisms. Some of the key challenges that are articulated in this paper include hot-spot superposition and intensification in a 3D stack, design/optimization of thermal through silicon vias (TTSVs), non-uniform power loading of multi-die stacks, efficient on-chip power delivery, minimization of electrical hotspots etc.