Miracle-dz/UniFAR-FTUs huggingface dataset:
Genomic surveillance identifies SARS-CoV-2 transmission patterns in local university populations, Wisconsin, USA, 2020–2022

Novel variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continue to emerge as the current coronavirus disease 2019 (COVID-19) pandemic extends into its third year. Understanding SARS-CoV-2 circulation in university populations is vital for effective interventions in a higher education setting that will inform pubic health policy during pandemics. In this study, we performed whole-genome sequencing of 537 of 1,717 SARS-CoV-2 positive nasopharyngeal/nasal swab samples collected for nearly 20 months from the two university populations in Wisconsin, United States. We observed that the viral sequences were distributed into 57 lineages/sub-lineages belonging to 15 clades of which the majority were from 21K (Omicron, 36.13%) and 21J (Delta, 30.91%). Nearly 40% (213) of the sequences were Omicron of which BA.1 and its eight descendent lineages account for 91%, while the remaining belong to BA.2 and its six descendent lineages. The independent analysis of these two universities sequences revealed significant differences in circulating the SARS-CoV-2 variants. The genome-based analysis of closely-related strains along with phylogenetic clusters had identified that potential virus transmission occurred within as well as between universities, and between the university and local community. Although this study improves our understanding of distinct transmission patterns of circulating variants in local universities, expanding the genomic surveillance capacity will aid local jurisdictions in identifying emerging SARS-CoV-2 variants like BA.4 and BA.5, and improve data-driven public health mitigation and policy efforts.
Wireless Condition Monitoring of Machinery and Equipment in Maritime Industry

Seagoing vessels are highly complex systems. Major requirements of marine vessels are continuous running time and high production output. As such, these systems require high availability and reliability, and are dependent on preventive maintenance procedures. Development of diverse range of sensors, combined with overall reduction in price, enabled implementation of condition based maintenance in such systems. Large increases in fuel cost, environmental restrictions and further crew reduction are current trend in maritime industry. Considering marine sector emphasis on the reduction of fuel consumption, environmental restrictions, and reduction of crew size, implementation of condition based maintenance is favourable, especially with regard to lost man-hours. However, high initial cost of installation on moving vessels, necessary crew training and additional sensor maintenance inhibits implementation of condition based maintenance. Replacing wired monitoring system with wireless ship-board sensor network would mitigate the above mentioned problems. However, current research of wireless sensor networks is based on terrestrial installation. This paper analyses the application of wireless sensor network technology on board seagoing vessels. Practical engineering solutions, including sensor types, configurations and wireless network topologies have been identified and reviewed.
Dual-Agent Progressive Join

It is crucial to provide real-time performance in many query work-loads, such as interactive and exploratory data analysis. In these settings, users need to view a subset of query results or a progressive presentation of the entire results quickly. Nevertheless, it is challenging to deliver such results over large dataset for common relational binary operators, such as join. Join algorithms usually spend a long time on scanning and attempting to join parts of relations that may not generate any result. Current solutions to this problem usually require lengthy and repeating preprocessings, which are costly in general settings and may not be possible to do in some cases, such as interactive workloads or evolving datasets. Also, they may support restricted types of joins. In this paper, we outline a novel approach for achieving efficient progressive join processing in which the scan operator of the join learns online and during query execution the portions of its underlying relation that might satisfy the join condition and use them in the join. We further improve this method by an algorithm in which both scan operators collaboratively learn an efficient join execution strategy. We also show that this approach generalizes traditional and non-learning methods of join. Our empirical studies using standard benchmarks indicate that this approach outperforms similar methods considerably.
Transforming Marginalized Communities through Virtual Healthcare during a Pandemic

The COVID-19 pandemic has encouraged governments and public health administrators to rapidly adopt digital solutions and advanced public health information systems. Sub-Saharan African countries have also made transitions to the digital platforms in response to the unprecedented challenges related to the delivery of health services. However, acceptance and use of such digital solutions was found to differ between countries. Based on these gaps, we build a conceptual representation that is based on the Technology Readiness Index. This conceptual mapping highlights the technological optimism, associated with innovation, while showing the perceived usefulness and usage of Telehealth. In this research, we elaborate a set of proposals to increase the body of knowledge regarding the implementation of technologies for health and to provide decision makers with key evidence for the implementation of policies for the development of community digital solutions.
Design, Construction, and Characterization of a Magic Angle Field Spinning RF Magnet

Magic angle field spinning (MAFS) is a Nuclear Magnetic Resonance (NMR) spectroscopy technique used in NMR Compact Devices to enhance the spectral resolution. In this technique, the sample is placed inside a magnet which generates a magnetic flux density oriented at 54.74° with respect to the sample main axis and spun at high frequencies. We present here, the design and construction of a novel magnet that generates a magnetic field according to the MAFS technique. The prototype generates two radio frequency and one dc magnetic fields by the combined action of three electromagnets. This combination results in a magnetic flux density of ~10 mT, with field deviations ≤1% inside a cylindrical volume of $30\times 30$ mm, an orientation easily controlled by field amplitudes and precessing at frequencies up to 12 kHz. The magnet has been characterized by using a novel Flux+Gauss meter (FGM) built and calibrated in-house. The FGM is able to measure ac and dc magnetic fields along seven different longitudinal axes, one of them corresponds to the longitudinal axis of the prototype. The other six axes are placed at six angular orientations on a 30-mm-diameter circumference. The characterization of the magnet includes field profiles of the RF and dc fields along the FGM axes and deviations of the field in the $30\times 30$ mm cylinder. The homogeneity is evaluated as the relative differences between the field measured at the centered axis and the field measured along the six extra axes for both RF and dc fields.
A Hierarchical Multiagent-Based Protection Structure for Meshed Microgrids

This paper proposes a new protection structure to locate any type of faults in a meshed micro grid based on only measuring the current and voltage of the Distributed Generator (DG) that communicates with its neighboring DGs. In the first step, following a wavelet transform, a set of features are selected and fed to a Multiclass Support Vector Machine (MSVM) to detect occurrence and type of fault. Then, faulted zone-the area between two DGs that fault occurs between them- is determined thanks to two facts. First, one of the DG in two sides of the faulted zone endures the lowest voltage. Second, regarding fundamental frequency of 50 Hz, if this DG injects a harmonic of 300 Hz, the DG with the lowest voltage at 300 Hz is the next closest DG. Finally, based on the optimum features and these two DGs, a SVM is used to locate the faulted line. Simulation results show the effectiveness of the proposed method in a meshed micro grid.
Efficiency of Moroccan Seaports: Application of DEA Using Window Analysis

The efficiency of 8 seaports in the Kingdom of Morocco region was evaluated. Two associated studies were conducted based on data collected for 4 years (2014-2017), Standard Data Envelopment Analysis (DEA) method was used in the first analysis through CCR and BCC models, and thus a scale of efficiency analysis was used in a second analysis. By using both methods, enhanced insight into the efficiency situation is collected, proving subsequently that a majority of the container ports and terminals in the Kingdom of Morocco are found to be technically inefficient. The research concludes through returns to scale method how port resources should be utilized in the aim to impulse inefficient ports perform better.
Machine Learning with Word Embeddings applied to Biomedical Concept Disambiguation

Artificial Intelligence (AI) has grown in the last years and it has many applications. Natural Language Processing is one of the AI tasks, which has the objective to endow the machines the capability of understanding human language. This is an important process due to the amount of information stored in textual form. There is a growing need for automatic extraction of knowledge, and NLP comes in this direction helping in tasks such as information extraction and information retrieval. Word sense disambiguation is an important NLP subtask, which is responsible for assigning the proper concept to an ambiguous word or term. In this paper, we present results obtained from applying supervised machine learning algorithms with local features, and word embeddings as global features extracted from Wikipedia and PubMed knowledge sources. These results indicate that word embedding features are informative and may improve the biomedical word disambiguation accuracy.
Inequalities in Job Loss and Income Loss in Sub-Saharan Africa During the COVID-19 Crisis

This paper uses high-frequency phone survey data from Ethiopia, Malawi, Nigeria, and Uganda to analyze the impacts of the COVID-19 crisis on work (including wage employment, self-employment, and farm work) and income, as well as heterogeneity by gender, family composition, education, age, pre-COVID19 industry of work, and between the rural and urban sectors. The paper links phone survey data collected throughout the pandemic to pre-COVID-19 face-to-face survey data to track the employment of respondents who were working before the pandemic and analyze individual-level indicators of job loss and re-employment. Finally, it analyzes both immediate impacts, during the first few months of the pandemic, as well as longer run impacts through February/March 2021. The findings show that in the early phase of the pandemic, women, young, and urban workers were significantly more likely to lose their jobs. A year after the onset of the pandemic, these inequalities disappeared and education became the main predictor of joblessness. The analysis finds significant rural/urban, age, and education gradients in household-level income loss. Households with income from nonfarm enterprises were the most likely to report income loss, in the short run as well as the longer run.
Position estimation of robotic platform using optical flow

This paper deals with a base research of an alternative type of navigation for our project ARES (Autonomous Research Exploration System). This system is focused on exploration of unknown areas. The navigation of this platform is based on fusion of several navigation methods. The first method is based on the visual odometry using SURF (Speeded Up Robust Feature). The second navigation method is based on Hector Slam and Lidar sensor. The third method is based on optical flow. The implementation of third method based on the Lucas-Kanade method is descripted in this paper.Keywords: Robot navigation, Visual Odometry, Lucas-Kanade, Optical Flow
Nonlinear analysis of the locomotive traction system with rub-impact and nonlinear stiffness

Considering rub-impact forces, eccentricity of rotor, and nonlinear stiffness of armature shaft, a dynamic differential equation is built to investigate the bifurcation and chaos behavior of the locomotive traction system. The nonlinear analysis methods are inclusive of bifurcation diagrams, phase plane portraits, Poincaré maps, displacement–time curves, and spectrograms. The simulation results reveal the complex dynamic comprising period-3 to quasi-periodic bifurcation and intermittent bifurcation. Some research results are references for dynamic design and rub-impact fault diagnosis of the locomotive traction system.
Quarter-Turn Transformer Design and Optimization for High Power Density 1-MHz LLC Resonant Converter

In this paper, quarter-turn planar transformer structure is proposed and implemented in an LLC resonant converter for server power supply applications. Main power losses of high-frequency resonant converters are secondary-side winding loss and transformer core loss. Conventional transformer winding structures limit the minimum number of turns on the primary and secondary sides, such that the core size and secondary-side conduction loss cannot be reduced by increasing the frequency. To achieve high efficiency and high power density, a fractional-turn transformer structure can reduce core volume and conduction loss in the windings. The optimized transformer design also enables the turn ratio of the fractional-turn to achieve normal coupling of primary and secondary sides without generating flux imbalance. The effects of different fractional-turn windings on efficiency are examined, and Maxwell simulation results are used to verify the structure and operation of the planar transformer. The printed circuit board layout is analyzed using Q3D Extractor to reduce the uneven current generated by parasitic components on the secondary-side windings. Wide-bandgap switches are utilized to implement a resonant converter with 1-MHz operating frequency, 380-V input voltage, 12-V output voltage, 1-kW output power, 37.6-W/cm3 power density, and 97% maximum efficiency.
A Zero Voltage Switching Topology for Non-Inverting Buck–Boost Converter

This brief summarizes soft-switching methods for the non-inverting buck-boost converter (NIBBC). Then a new zero voltage switching (ZVS) NIBBC is proposed. This new NIBBC employs a triple coupled inductor, two resonant inductors, and two auxiliary diodes. All transistors of this new NIBBC will work under ZVS conditions. Furthermore the current across the main inductor will be continuous during all the period, and therefore its ripples will be small. Benefit from low current ripples of the main inductor, ripples and harmonics of the output current are also reduced. To verify this new NIBBC, an experimental platform was built, and waveforms (voltage and current) and efficiency are measured. Measuring results show that ZVS conditions of all transistors are obtained. And the efficiency of the new NIBBC is higher than traditional continuous conduction mode and triangular current mode NIBBCs.
New Divider Design for Stochastic Computing

Stochastic computing (SC) is an unconventional computing paradigm which enables low power and massive parallelism in various applications. The numerical values in SC are represented as random bit-streams and interpreted as probabilities. The SC design provides the low-cost arithmetic units, while suffering from long latency and accuracy degradation. The division operation is the most challenging in SC. Chen et al. have recently developed a stochastic divider, called correlated divider (CORDIV), by exploiting the conditional probability. It has been proved that the CORDIV has a lower hardware cost than the previous designs and provides good accuracy performance. This brief presents a new stochastic divider, which includes one saturating subtractor and one JK flip flop. The subtractor is designed by taking advantage of correlation among inputs. Simulation results reveal that the proposed divider has the same accuracy performance as CORDIV. However, the new divider has competitive advantages over CORDIV. With applications to the piecewise linear function implementation, the proposed design is superior to the finite state machine (FSM)-based method in terms of accuracy and hardware cost.
Theory of Magnetism:Application to Surface Physics

The book is intended for graduate students and researchers who wish to learn the main properties of magnetic materials in the bulk state and at the nanometric scale such as thin films and multilayers. The book provides fundamental theories and methods of simulation to study and to understand these properties in an explicit manner. Exercises and problems are given for each chapter to help the reader apply the methods to discover new related phenomena and applications which are complementary to the lecture. Detailed solutions are provided for self-learning. In the first part of the book, fundamental methods in magnetism are presented: systems of independent electrons and atoms, systems of interacting spins, spin-wave theory, spin transport, phase transition,. The second part is devoted to surface effects and thin films.
Plasma in the Magnetosheath

Measurements of th y; magnetosheath plasma made by the MIT Plasma Experiment during the outbound passage of Pioneer 6 in the dusk meridian (December 16, 1965) are presented and compared with theoretical predictions for the same region. While the comparison indicates that the plasma flow around the earth agrees in many ways with a gas dynamic model, observed discrepancies in the density ratio across the know shock and the non-Maxwellian velocity distribution in the magr:etosheath warrant further. ex-planation. Magnetosphere and magnetosheath low energy electron measurements indicate a region of anisotrepic flux in the magnetosphere near the magnetopause.
Angiogenic and osteogenic regeneration in rats via calcium phosphate scaffold and endothelial cell coculture with hBMSCs, hUCMSCs, hiPSC-MSCs and hESC-MSCs.

Angiogenesis is a limiting factor in regenerating large bone defects. The objective of this study was to investigate angiogenic and osteogenic effects of coculture on calcium phosphate cement (CPC) scaffold using human umbilical vein endothelial cells (hUVECs) and mesenchymal stem cells (MSCs) from different origins for the first time. hUVECs were cocultured with four types of cells: human umbilical cord MSCs (hUCMSCs), human bone marrow MSCs (hBMSCs), and MSCs from induced pluripotent stem cells (hiPSC-MSCs) and embryonic stem cells (hESC-MSCs). Constructs were implanted in 8-mm cranial defects of rats for 12 weeks. CPC without cells served as control 1. CPC with hBMSCs served as control 2. Microcapillary-like structures were successfully formed on CPC in vitro in all four cocultured groups. Microcapillary lengths increased with time (p 0.1). Therefore, hUCMSCs, hiPSC-MSCs and hESC-MSCs could serve as alternative cell sources to hBMSCs which require an invasive procedure to harvest. In conclusion, this study showed for the first time that cocultures of hUVECs with hUCMSCs, hiPSC-MSCs, hESC-MSCs and hBMSCs delivered via CPC scaffold achieved excellent osteogenic and angiogenic capabilities in vivo. The novel coculture constructs are promising for bone reconstruction with improved angiogenesis for craniofacial/orthopedic applications.
Biomass feedstock supply chain design – a taxonomic review and a decomposition-based methodology

In this paper, we present a taxonomic review of the literature devoted to the use of operations research approaches for the design and operation of biomass feedstock supply chains (BFSCs). A total of 185 publications that have appeared from 1989 to 2017 are classified based on (1) the embedded optimisation subproblems; (2) the modelling methodologies used for their formulations; and (3) the methods employed for their solution. Our objective of using this classification scheme is to highlight the presence of some useful substructures in a BFSC problem that can, then, be exploited in developing its solution procedure. We illustrate this idea on some generic BFSC problems and present a Dantzig–Wolfe decomposition-based methodology for developing customised approaches to effectively tackle these difficult and large-sized BFSC problems. Finally, we suggest several promising future research directions.
CHURCH-ROSSER THEOREM.

This paper is a continuation of An abstract form of the Church-Rosser theorem. I (this JOURNAL, vol. 35 (1969), pp. 545-560). In Part I, the Church-Rosser property was deduced from abstract premises (A1)-(A8). The original draft of Part II con tained some applications of this result, and a fairly simple abstract result by which the Church-Rosser property could be extended from A/3-reduction to A/Sij-reduction (Curry's notation [3, Chapter 3]). But since this draft was written, these results have been obtained independently and improved by other workers, and a simple and natural new proof for A/S-reduction has been discovered by W. W. Tait and P. Martin-Ldf (see §11 later, and [17, §2.4.3]). So the main purpose of the present Part II is merely to justify the claim in Part I that the abstract theorem does cover the case of A/S-reduction (and various modifica tions). I shall also include a summary of the main kinds of Church-Rosser proofs. The paragraph and theorem numbers in Part II will continue from those of Part I.
Towards connected autonomous driving: review of use-cases

ABSTRACT Connected autonomous vehicles are considered as mitigators of issues such as traffic congestion, road safety, inefficient fuel consumption and pollutant emissions that current road transportation system suffers from. Connected autonomous vehicles utilise communication systems to enhance the performance of autonomous vehicles and consequently improve transportation by enabling cooperative functionalities, namely, cooperative sensing and cooperative manoeuvring. The former refers to the ability to share and fuse information gathered from vehicle sensors and road infrastructures to create a better understanding of the surrounding environment while the latter enables groups of vehicles to drive in a co-ordinated way which ultimately results in a safer and more efficient driving environment. However, there is a gap in understanding how and to what extent connectivity can contribute to improving the efficiency, safety and performance of autonomous vehicles. Therefore, the aim of this paper is to investigate the potential benefits that can be achieved from connected autonomous vehicles through analysing five use-cases: (i) vehicle platooning, (ii) lane changing, (iii) intersection management, (iv) energy management and (v) road friction estimation. The current paper highlights that although connectivity can enhance the performance of autonomous vehicles and contribute to the improvement of current transportation system performance, the level of achievable benefits depends on factors such as the penetration rate of connected vehicles, traffic scenarios and the way of augmenting off-board information into vehicle control systems.