Miracle-dz/UniFAR-FTUs huggingface dataset:
100-Gb/s 80-km transmission of PIM-SSB-OFDM at C-band using a single-end photodetector

Abstract. Polarization-interleave-multiplexed (PIM) with single-sideband orthogonal frequency-division multiplexing (SSB-OFDM) based on direct detection is proposed for short-reach applications transmitted up to 80 km in which the guard band can be shared for the two SSB signals with interleave electrical center frequencies. Based on two dual-drive Mach–Zehnder modulators with one single-end photodetector (PD), 100-Gb/s PIM-SSB-OFDM transmission over a 80-km standard single-mode fiber is successfully demonstrated. After 80-km transmission, the optical signal-to-noise ratio requirement is 29.1 dB with respect to the bit error rate threshold of 7% hard decision-forward error correction overhead.
Design and analysis for a multifunctional rescue robot with four-bar wheel-legged structure

Rescue robots can replace rescue workers in search and rescue missions in unknown environments and hence play an important role in disaster relief. To realize the advantages of high carrying capacity, easy control, and simple structure to adapt to a complex disaster scene, a novel wheel-legged rescue robot, integrated with rescue function modules, was designed for the present work. Three motion states were analyzed in detail. Mechanical properties were studied to provide basis for parameter optimization. The performance indices, which include mechanical properties, motion amplitudes and movement stability, were proposed, and the structural parameters were further analyzed and optimized based on these performance indices to make the overall performance of the robot achieve the best. Results show that the motion state of the wheel-legged rescue robot can perform real-time transformations and hence can be used in complex environments.
Proportional Integral Derivative Decentralized Control vs Linear Quadratic Tracking Regulator in Vehicle Overtaking within a Platoon

: This paper introduces a comparison between a decentralized Proportional Integral Derivative (PID) controller and a centralized Linear Quadratic Tracking (LQT) controller to automatise the exchange of two inner vehicles inside a platoon moving on a straight path. Lomonossoff’s model is used to represent vehicle’s longitudinal dynamics. A case study is presented to demonstrate the effectiveness of both controllers respectively on nonlinear and linearized model.
Next generation integrated drive: a novel thermal and electrical integration technique for high power density converters used in automotive drive systems

In this paper, an innovative method of electro-thermal integration of a drive system is presented. Important challenges of this integration consist of, firstly coupled thermal design of switching power modules and PM electric motor and secondly integration of high frequency switching devices into the motor housing, without compromising the performance of these transistors. To provide a solution to these challenges, an integrated liquid cooling system for both stator windings and transistor modules is designed. On the other hand, a specific module is designed to meet the specific requirements of this packaging technique.
Photochemical efficiency and growth of two provenances of Acacia senegal )gum arabic( tree seedlings under drying soil

This study was conducted to assess the impacts of water stress on diurnal photochemical efficiency of PSII and morphology of seedlings of A. senegal from two different provenances (El Fasher, P1 and Buram, P2). Seedlings were grown at the nursery of the Department of Forestry and Range Sciences, University of Al-Fashir, North Darfur, Sudan. Fifty four seedlings per provenance were selected and divided into well-watered (W) and water-stressed (D) and all data were collected for these seedlings. The results revealed that there was midday depression with evening recovery of effective photochemical efficiency of PSII (ΔF/Fm’) and maximum photochemical efficiency of PSII (Fv/Fm) in all seedlings throughout the measurement course reflecting the capability of both provenances to keep intact photosynthetic apparatus for more than nineteen days under drying soil. Substantial direct correlation between ΔF/Fm’ and electron transport for both provenances and inverse relationship between air temperature and Fv/Fm for P1 were established. Cyclic droughts affected negatively on the morphology of seedlings for both provenances as the height, stem diameter, and leaf number of water stressed seedlings was reduced substantially compared to well-watered. P1 seems to have greater morphological growth compared to P2 hence El Fasher’s provenance tends to be more appropriate for plantations in arid environments.
High-Resolution and Arbitrary-Sized Chinese Landscape Painting Creation Based on Generative Adversarial Networks

This paper outlines an automated creation system for Chinese landscape paintings based on generative adversarial networks. The system consists of three cascaded modules: generation, resizing, and super-resolution. The generation module first generates a square-shaped painting, then the resizing module predicts an appropriate aspect ratio for it and performs resizing, and finally the super-resolution module is used to increase the resolution and improve the quality. After training each module with the images we collected from the web, our system can create high-resolution landscape paintings in arbitrary sizes.
CXCR2 Is Essential for Radiation-Induced Intestinal Injury by Initiating Neutrophil Infiltration

Neutrophils, known as an important part of the immune system, are the most abundant leukocyte population in peripheral blood, but excessive recruitment will lead to tissue/organ injury. RNA sequencing showed that ionizing radiation significantly increased the expression of characteristic genes of neutrophils in intestinal tissues compared with liver and lung tissues. By clearing neutrophils with an anti-Ly6G antibody, we found that neutrophil infiltration is critical for irradiation-induced intestinal injury. CXCR2 is a G-protein-coupled receptor that mediates the migration of neutrophils by combining with its ligands. Compared with observations in liver and lung tissues, we found that CXCR2 and its ligands, including CXCL1, CXCL2, CXCL3, and CXCL5, were all significantly upregulated in irradiated intestinal tissues. Further studies showed that SB225002, an inhibitor of CXCR2, could effectively inhibit the chemotaxis of neutrophils and tissue damage mediated by the CXCL-CXCR2 signalling pathway.
Internet of Medical Things (IoMT)-Based Smart Healthcare System: Trends and Progress

Internet of Medical Thing (IoMT) is the most emerging era of the Internet of Thing (IoT), which is exponentially gaining researchers' attention with every passing day because of its wide applicability in Smart Healthcare systems (SHS). Because of the current pandemic situation, it is highly risky for an individual to visit the doctor for every small problem. Hence, using IoMT devices, we can easily monitor our day-to-day health records, and thereby initial precautions can be taken on our own. IoMT is playing a crucial role within the healthcare industry to increase the accuracy, reliability, and productivity of electronic devices. This research work provides an overview of IoMT with emphasis on various enabling techniques used in smart healthcare systems (SHS), such as radio frequency identification (RFID), artificial intelligence (AI), and blockchain. We are providing a comparative analysis of various IoMT architectures proposed by several researchers. Also, we have defined various health domains of IoMT, including the analysis of different sensors with their application environment, merits, and demerits. In addition, we have figured out key protocol design challenges, which are to be considered during the implementation of an IoMT network-based smart healthcare system. Considering these challenges, we prepared a comparative study for different data collection techniques that can be used to maintain the accuracy of collected data. In addition, this research work also provides a comprehensive study for maintaining the energy efficiency of an AI-based IoMT framework based on various parameters, such as the amount of energy consumed, packet delivery ratio, battery lifetime, quality of service, power drain, network throughput, delay, and transmission rate. Finally, we have provided different correlation equations for finding the accuracy and efficiency within the IoMT-based healthcare system using artificial intelligence. We have compared different data collection algorithms graphically based on their accuracy and error rate. Similarly, different energy efficiency algorithms are also graphically compared based on their energy consumption and packet loss percentage. We have analyzed our references used in this study, which are graphically represented based on their distribution of publication year and publication avenue.
Image transmission using OSTBC-encoded 16-QAM over MIMO time-selective fading channels

In this work we have studied the performance analysis of OSTBC-encoded 16-QAM by transmitting digital image over fading channels.The performance of 2×2 MIMO fading channels is compared with SISO fading channel with no OSTBC encoding at signal-to-noise ratio (SNR) of 20 dB. Multipath MIMO channels under-discussion are time-selective in nature and have flat channel response in frequency. Hence, we specify only Doppler shift which in our case is modelled by Jakes Doppler spectrum. The performance of 2×2 communication system over MIMO time-selective fading channels has been studied. The key performance indicative parameters of OSTBC-encoded 16-QAM over 1×1 single-input single-output (SISO), 2×1 multiple-input single-output (MISO) and 2×2 MIMO wireless communication have been recorded appropriately.
Trends in Monkeypox Research: A Sixty Year Bibliometric Analysis

Aim: The purpose of the study was to identify common descriptors and publication hotspots that may form reference themes for future monkey pox research. Method: Bibliometric analysis of monkeypox related studies between 1962 and 2022 was carried out to ascertain and describe this body of literature. Results and conclusion: A total of 1,134 documents were analysed for bibliometric indicators. The studies had 3,478 authors, an average of 5.72 co-authors per publication and a 3.73 author collaboration index. Annual scientific production peaked in 2004 (5.5%) and 2020 (5.3%). Monkeypox research accumulated 128 grants, 68 policy documents, 9 clinical trials, and 50 patents. The United States placed first in terms of the number of documents and citations, followed by Germany with 73, United Kingdom with 53, Russia and the Democratic Republic of the Congo (DRC) with 34 documents each. The DRC and Nigeria had the most documents among African countries. Text mining showed researchers have put their efforts into studies related to infectious disease ‘epidemiology’: the ‘emergence’, ‘Case diagnosis and ‘surveillance’ of ‘outbreaks’. The top keywords were ‘monkeypox’ (570 times), ‘monkeypox virus’ (411 times), ‘poxviridae infections’ (332 times), ‘small pox’ (266 times), ‘orthopox virus’ (248 times), ‘vaccinia virus’ (203 times), and ‘disease outbreaks’ (179 times). The most cited treatment related noun phrases were ‘tecovirimat’ (brand name Tembexa), ‘Cidofovir’/ ‘CMX001’ (Brincidofovir), ‘ACAM2000’ (imvanex vaccine) and ‘Vaccinia’ Immune Globulin (‘VIG’). This result will serve as a foundation for future research, guiding decision-making in monkeypox research and therapy.
Feedrate Planning for a Delta Parallel Kinematics Numerically Controlled Machine using NURBS Toolpaths

: This paper presents a concept of a computationally efﬁcient feedrate planning algorithm for parallel kinematics machine in a linear delta conﬁguration. Non-Uniform Rational B-Spline (NURBS) polynomial curve is used for toolpath deﬁnition which provides a smooth trajectory. The feedrate proﬁle is deﬁned as a jerk limited S-Curve which takes into account limitations stemming from the toolpath curvature and the machine kinematics. The article presents the outline of the method, structure of the experimental station including the real-time control system and preliminary experimental results. Further direction of the research is also described. The proposed method can provide a smooth motion trajectory obtained in real-time with small computational requirements.
ROIC development at CEA for SWIR detectors: pixel circuit architecture and trade-offs

Infrared detection is widely used in astrophysics and plays a key role in several space missions aiming for example at scanning the sky to discover new objects (coolest stars, dust-obscured galaxies, exo-planets …) or studying the evolution of the universe, where light is redshifted in the infrared range. In many cases the space telescope involves an HgCdTe infrared detector operating at low frame rate over long integration time. Due to the very low input signal, dark current and readout noise are essential figures that must be minimized to get the best detector sensitivity. This kind of application also requires very large focal plane array (FPA) often relying on a butting arrangement of large detectors. The trend is to increase the single detector format from 1Kx1K to 2Kx2K and 4Kx4K. For very large formats, material quality and detector process may affect the production yield and the global infrared FPA cost. As a result the detector format could result from a trade-off taking into account producibility.
Detecting Out-Of-Context Objects Using Graph Contextual Reasoning Network

This paper presents an approach for detecting out-of-context (OOC) objects in images. Given an image with a set of objects, our goal is to determine if an object is inconsistent with the contextual relations and detect the OOC object with a bounding box. In this work, we consider common contextual relations such as co-occurrence relations, the relative size of an object with respect to other objects, and the position of the object in the scene. We posit that contextual cues are useful to determine object labels for in-context objects and inconsistent context cues are detrimental to determining object labels for out-of-context objects. To realize this hypothesis, we propose a graph contextual reasoning network (GCRN) to detect OOC objects. GCRN consists of two separate graphs to predict object labels based on the contextual cues in the image: 1) a representation graph to learn object features based on the neighboring objects and 2) a context graph to explicitly capture contextual cues from the neighboring objects. GCRN explicitly captures the contextual cues to improve the detection of in-context objects and identify objects that violate contextual relations. In order to evaluate our approach, we create a large-scale dataset by adding OOC object instances to the COCO images. We also evaluate on recent OCD benchmark. Our results show that GCRN outperforms competitive baselines in detecting OOC objects and correctly detecting in-context objects. Code and data: https://nusci.csl. sri.com/project/trinity-ooc
Developing a Global Engineer: Study Abroad Experiences of Engineering Majors in One University System.

Author(s): Seccia, Lesley | Advisor(s): Ho, Hsiu-Zu; Conley, Sharon | Abstract: ABSTRACT Extensive literature on study abroad outcomes documents the benefits of study abroad for all undergraduate students, regardless of academic major. However, engineering majors, at 5% of all undergraduate students nationally who study abroad, are substantially less likely to study abroad than their social science peers, at 17.3% participation (IIE, 2016). Yet engineering majors have much to gain from international experiences: engineering is a global profession, and these future engineers will be expected not only to work in diverse teams but also travel and work abroad. The purpose of this study is: (a) to explore the goals, motivations and challenges or barriers that undergraduate engineering majors face in their decision-making regarding study abroad, particularly in comparison to those motivations and barriers identified in the literature; (b) to identify outcomes of study abroad for this group of students and how they believe study abroad might impact their future; and (c) to explore students’ decision-making regarding engineering study abroad from academic advisors’ perspectives. These advisors not only support undergraduates’ academic needs on campus but also help them plan for study abroad. The theory of reasoned action (Fishbein a Azjen, 1975) and transformational learning theory (Mezirow, 1991) formed the theoretical framework for this study. Combined, these theories form the basis of a conceptual model to explain the decision-making process of studying abroad and how study abroad can be a transformative learning experience for study abroad participants.This study employed a mixed methods methodology (Creswell, 2014) to address the research questions. First, a survey was sent to engineering undergraduates who had participated in study abroad at 8 different undergraduate institutions within a university system. Then, based on survey responses, in-depth interviews were conducted with 11 of the survey participants. Concurrently, 7 academic advisors were interviewed in order to shed light on the advising process for engineering majors to study abroad. Personal and institutional factors were found to be the primary considerations in deciding whether to study abroad. Personal factors included students’ desires for cultural experiences and their internal drive to overcome any obstacles they faced. Institutionally, curriculum restrictions for engineering majors and student fears about delay in graduation challenged study abroad participation. Outcomes included students’ alteration of career plans, increasing their insight into other cultures, and increasing their comfort with working abroad.
An Overview Of The Photo-Catalysis Of Titanium Dioxide Nanotubes And Their Effect On Human Life

Nanomaterials are engineered materials with extremely small particle sizes with at least one dimension ranging from one to one hundred nanometers. Nanoscale materials contain unique electrical, magnetic, catalytic, and optical properties that can be applied in various fields, including engineering, medicine, and the environment. Nanomaterials with appealing chemical and physical properties are being researched for potential energy and environmental applications. Nanomaterials have grabbed people's interest due to their ability to enhance efficiency through-beam gap control, chemical composition, structural diagram, light propagation, and charge/transport collection, among other things. Titanium dioxide (TiO2) nanoparticles are mass-produced all over the world for use in a range of applications. TiO2 nanostructured materials have aroused much interest in the energy and environmental sectors due to their future applications in photocatalysis, solar cells, and pollution remediation. Furthermore, because TiO2 nanoparticles are widely available, inexpensive, and non-toxic, they are routinely employed in various products, including cosmetics, where they are used as a UV filter in sunscreens, face creams, foundation, and lipstick. Analgesics. Because of the relevance of titanium dioxide, we will discuss it in this review by demonstrating its characteristics, photocatalysis mechanism, and uses that come into direct contact with human existence.
Improved Generative Adversarial Networks for Student Classroom Facial Expression Recognition

To assess students’ learning efficiency under different teaching modes, we used students’ facial expressions in the classroom as a study point. An enhanced generative adversarial network is presented. We designed a generator as an automatic coding-decoding combination in a cascade structure with a discriminator configuration. It can retain different expression intensity features to the maximum extent. We also added a new auxiliary classifier, which can classify different intensity features and improve the model’s recognition of detailed features of similar expressions, thus improving the comprehensive facial expression recognition accuracy. Our approach has a great advantage over the other facial expression recognition approaches on public datasets. Finally, we conduct experimental validation on the self-made student facial expression dataset in all cases. The experimental findings showed that our approach’s recognition accuracy is superior to that of other methods, demonstrating the method’s efficacy.
Learning Curricula for Humans: An Empirical Study with Puzzles from The Witness

The combination of tree search and neural networks has achieved super-human performance in challenging domains. We are interested in transferring to humans the knowledge these learning systems generate. We hypothesize the process in which neural-guided tree search algorithms learn how to solve a set of problems can be used to generate curricula for helping human learners. In this paper we show how the Bootstrap learning system can be modified to learn curricula for humans in a puzzle domain. We evaluate our system in two curriculum learning settings. First, given a small set of problem instances, our system orders the instances to ease the learning process of human learners. Second, given a large set of problem instances, our system returns a small ordered subset of the initial set that can be presented to human learners. We evaluate our curricula with a user study where participants learn how to solve a class of puzzles from the game `The Witness. ' The user-study results suggest one of the curricula our system generates compares favorably with simple baselines and is competitive with the curriculum from the original `The Witness' game in terms of user retention and effort.
Development of HADIS Algorithm for Deficit Irrigation Scheduling

Effective management of water resources and their efficient use in drought conditions are very important in the agricultural sector. Deficit irrigation is an optimal solution to produce crops under these conditions. It requires integrated, accurate and efficient management which is quite different from classic irrigation management. An irrigation manager must determine what rate of deficit irrigation is to be applied at each stage of growth; in the other words, deficit irrigation scheduling (DIS) should provide the water requirements of plants during the growing season based on water resources in a way which leads to maximum efficiency. In this study, a DIS heuristic algorithm called HADIS is developed, which is able to estimate the time, frequency and depth of irrigation events according to the crop water production function (CWPF) and FAO 56, leading to maximum yield and water productivity. HADIS is written using the C# language in Visual Studio 2010. In addition, in order to optimize CWPF, GAMS 24.1 software along with Lindo Global Solver is used and SQL Server 2008 is employed as the database. The results of implementing different water, soil and crop scenarios proved the capability of HADIS to achievE maximum crop productivity. Copyright © 2017 John Wiley & Sons, Ltd.