Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel PEV Charging Approaches for Extending Transformer Life

The study investigates how variable rate charging can affect PEV charging and identifies how this capability can be integrated into residential neighborhoods. The results show that creating PEV chargers that can deliver variable rates will enhance uncontrolled and controlled PEV charging. The integration is summarized into 4 phases. In phase 1, uncontrolled PEV chargers should be enabled to provide any rate to vehicles within 0 to 11.5 kW, which can reduce overloading by up to 28.34%. Phase 2 introduces smart chargers that use forecasted data to determine the optimal time intervals for PEVs to charge using a fixed rate of 4.8 kW, capable of reducing overloading by 42.69%. In Phase 3, a controlled smart charging strategy that can deliver any rate to a vehicle using SRVF’s approach is proposed, which will reduce overloading by up to 42.87%. Lastly, phase 4 recommends a smart charging control that can deliver any rate to a vehicle using RIVF’s approach, reducing overloading by up to 43.37%.
Embolization for Type Ia Endoleak after EVAR for Abdominal Aortic Aneurysms: A Systematic Review of the Literature

(1) Successful endovascular repair for abdominal aortic aneurysms is based on the complete exclusion of the aneurysm sac from the systemic circulation. Type Ia endoleak (ELIA) is defined as the persistent perfusion of the aneurysm sac due to incomplete proximal sealing between aorta and endograft, with a consequent risk of rupture and death. Endoleak embolization has been sporadically reported as a viable treatment for ELIA. (2) A systematic literature search in PubMed of all publications in English about ELIA embolization was performed until February 2022. Research methods and reporting were performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Data regarding patient numbers, technical success (endoleak absence at control angiography), reinterventions, clinical and imaging follow-up, and outcomes were collected and examined by two independent authors. (3) Twenty-one papers (12 original articles, 9 case reports) reported on 126 patients (age range 58–96 years) undergoing ELIA embolization 0–139 months after the index procedure. Indication for embolization was most often founded on unfavorable anatomy and patient comorbidities. Embolic agents used include liquid embolic agents, coils, plugs and combinations thereof. Technical success in this highly selected cohort ranged from 67–100%; the postprocedural complication rate within 30 days was 0–24%. ELIA recurrence was reported as 0–42.8%, with a secondary ELIA-embolization-intervention success rate of 50–100%. At a follow-up at 0–68 months, freedom from sac enlargement amounted to 76–100%, freedom from ELIA to 66.7–100%. (4) Specific literature about ELIA embolization is scant. ELIA embolization is a valuable bailout strategy for no-option patients; the immediate technical success rate is high and midterm and long-term outcomes are acceptable.
Global Estimates of Biogenic Methane Production in Marine Sediments Using Machine Learning and Deterministic Modeling

We have developed a model of geospatially estimating carbon accumulation and methanogenesis in seabed sediments that uses more accurate and sophisticated inputs to models than used in previous estimates. Using this hybrid stochastic and deterministic model, we estimate the maximum carbon available for methanogenesis in the global seabed, and subsequent microbial methane generated as a function of location and depth (including the gas hydrate stability zone). Global integration over present and previously microbially reactive sediments column yields total carbon and methane to be ∼0.8–2.2 × 106 and 1.1–3.0 × 106 Pg C and CH4, respectively. Our improvements to accuracy include using geospatially machine learned estimates of seafloor inputs to which the methanogenesis modeling is most sensitive (e.g., total organic carbon, heat flux, porosity). Our improvements to model sophistication include geospatially dependent modeling (on a 5 × 5 arc‐minute grid), a new model of sediment compaction (allowing for non‐linear geothermal gradients), and variable age versus depth at each grid cell. A carbon reservoir of the magnitude we estimate here is consistent with the recent IPCC suggestion that long‐term carbon sinks could explain imbalances in reduction of atmospheric CO2 over the last 50 million years. Our technique provides a foundation of using globally updateable machine learning parameters as the input to geologic and geochemical models, allowing for new observations to update global budgets of carbon available for methane, and subsequent total estimates of seabed methane.
An Elecrostatic Pest Exclusion Strategy for Greenhouse Tomato Cultivation

Electrostatic devices generating an electric field (EF) are promising tools for greenhouse tomato cultivation. In these devices, an EF is generated in the space surrounding an insulated conductor (IC) that is charged by a voltage generator. Thus, a physical force is exerted on any insect that enters the EF, as a negatively charged IC (NC-IC) pushes a negative charge (free electrons) out of the insect body. The insect is polarized positively to be attracted to the NC-IC, and a grounded metal net (G-MN) repels the insect. This dual function of the apparatus (insect capture and repulsion) is the core of the electrostatic pest-exclusion strategy. In this study, we applied various innovative EF-based devices to evaluate their efficacy in greenhouse tomato cultivation. Our objective was to determine the optimal apparatus for simple, inexpensive construction by greenhouse workers. The results of this study will contribute to the development of sustainable pest-management protocols in greenhouse horticulture.
Growth of Anagnostidinema amphibium LBABL-2 (Oscillatoriales, Cyanobacteria) in Different Abiotic stress conditions

The Bolonha reservoir (Belém, Pará) is eutrophicated and dominated by aquatic macrophytes that are often removed and deposited on the banks of the environment, suffering decomposition. Some microorganisms that live associated with macrophytes return to the environment through leaching, among them cyanobacteria. The objective of the study was to evaluate the growth of the species Anagnostidinema amphibium LBABL-2, in microcosm, by three experiments under different environmental conditions and nutritional stress simulating its growth during the cleaning process of the Bolonha reservoir. Growth was determined by optical density and chlorophyll-a. The species formed a slime mat composed of tangles of green, not capitate, not constricted, not attenuated, slightly curved trichomes 600 μm long, composed of cells that measured, on average, 4.1 μm -2.2 μm in length and width, respectively, and showed cyanophycin granules in the cell wall between two cells. The absence of nutrients was the main stressor of Anagnostidinema amphibium LBABL-2, which showed higher growth in the roots of macrophytes immersed in the reservoir, but low growth in the absence of nutrients. The study will support actions for the management of aquatic macrophytes in the reservoir with emphasis on stressors and growth promoters of cyanobacteria associated with their roots.
Evolutionary Analysis and Functional Identification of Ancient Brassinosteroid Receptors in Ceratopteris richardii

Phytohormones play an important role in the adaptive evolution of terrestrial plants. Brassinosteroids (BRs) are essential hormones that regulate multiple aspects of plant growth and development in angiosperms, but the presence of BR signaling in non-seed plants such as ferns remains unknown. Here, we found that BR promotes the growth of Ceratopteris richardii, while the synthetic inhibitor PCZ inhibits the growth. Using full-length transcriptome sequencing, we identified four BRI1-like receptors. By constructing chimeric receptors, we found that the kinase domains of these four receptors could trigger BR downstream signaling. Further, the extracellular domains of two receptors were functionally interchangeable with that of BRI1. In addition, we identified a co-receptor, CtSERK1, that could phosphorylate with CtBRL2s in vitro. Together, these proved the presence of a receptor complex in Ceratopteris richardii that might perceive BR and activate downstream hormone signaling. Our results shed light on the biological and molecular mechanisms of BR signaling in ferns and the role of BR hormone signaling in the adaptive evolution of terrestrial plants.
Centralized and Distributed Optimization for Vehicle-to-Grid Applications in Frequency Regulation

This paper proposes centralized and distributed optimization models for V2G applications to provide frequency regulation in power systems and the electricity market. Battery degradation and dynamic EV usages such as EV driving period, driving distance, and multiple charging/discharging locations are modeled. The centralized V2G problem is formulated into the linear programming (LP) model by introducing two sets of slack variables. However, the centralized model encounters limitations such as privacy concerns, high complexity, and central failure issues. To overcome these limitations, the distributed optimal V2G model is developed by decomposing the centralized model into subproblems using the augmented Lagrangian relaxation (ALR) method. The alternating direction method of multipliers (ADMM) is used to solve the distributed V2G model iteratively. The proposed models are evaluated using real data from the Independent Electricity System Operator (IESO) Ontario, Canada. Simulation results show that the proposed models can aggregate EVs for frequency regulation; meanwhile, the EV owners can obtain monetary rewards. The simulation also shows that including battery degradation and dynamic EV usage increases the model accuracy. By using the proposed approaches, the high cost and the low efficiency power generation units for frequency regulation can be compensated or partially replaced by EVs, which will reduce the generation cost and greenhouse gas emissions.
H2RUN: An efficient vendor lock‐in solution for multi‐cloud environment using horse herd Runge Kutta based data placement optimization

Vendor lock‐in is a scenario where the cost of switching to another vendor is mainly high and for this reason, the consumer is mainly struck with a single cloud vendor. The vendor lock‐in mainly implies the situation of an organization where it is locked into a service or product of a single Cloud Service Providers (CSP) to prevent the disruption of the business operation or due to an insufficient workforce. Due to its high availability, portability, and other benefits, various researchers frequently adopt the multi‐cloud strategy to prevent vendor lock‐in. However, the multi‐cloud architecture also comes with major drawbacks such as cost, multiple CSP management, and the tradeoff between cost and availability. The organizations are mainly considerate about achieving the tradeoff between the cost and availability. To overcome this problem, we have proposed an H2RUN (Horse Herd Runge Kutta) optimization algorithm to achieve a tradeoff between the cost and availability using erasure coding. The proposed H2RUN optimization algorithm selects the optimal CSP and erasure coding parameters that enhance the availability of the CSP with minimal cost. The efficiency of the proposed methodology can be evaluated using the experiments conducted on different real‐time CSPs using various metrics. Based on the results achieved, the H2RUN optimizer minimizes the cost up to 48% and availability up to 58%.
Mutation-inspired symbolic execution for software testing

Software testing is a complex and costly stage during the software development lifecycle. Nowadays, there is a wide variety of solutions to reduce testing costs and improve test quality. Focussing on test case generation, Dynamic Symbolic Execution (DSE) is used to generate tests with good structural coverage. Regarding test suite evaluation, Mutation Testing (MT) assesses the detection capability of the test cases by introducing minor localised changes that resemble real faults. DSE is however known to produce tests that do not have good mutation detection capabilities: in this paper, the authors set out to solve this by combining DSE and MT into a new family of approaches that the authors call Mutation-Inspired Symbolic Execution (MISE). First, this known result on a set of open source programs is confirmed: DSE by itself is not good at killing mutants, detecting only 59.9% out of all mutants. The authors show that a direct combination of DSE and MT (naive MISE) can produce better results, detecting up to 16% more mutants depending on the programme, though at a high computational cost. To reduce these costs, the authors set out a roadmap for more efficient versions of MISE, gaining its advantages while avoiding a large part of its additional costs.
Improve Quality of Life Client with Visual Impairment

Introduction: Blindness is considered one of the most serious diseases. Blindness causes mental and emotional problems in a person and is one of the most complex health problems in the world. Rehabilitation of blind clients focuses on independent performance of daily activities. The Kawa model in occupational therapy is a model that promotes better interaction between the client and the therapist and makes it possible to guide the client taking into account cultural factors. The model is used in different areas of occupational therapy and brings positive results. The purpose of this research is to learn about the Kawa model and apply it to blind clients. Methods: a qualitative research, a singular diachronic single case study was conducted. One case, which lasted 4 months, included a client who has been blind since birth. The occupational therapy process was conducted using Kawa’s step-by-step models. A tactile picture and a tactile magnetic board were made to represent the models, which are an innovative occupational therapy medium. Results: The Kawa model is interesting due to a different way of handling and at the same time very easy for the client to understand. The tactile aids made also contributed to this. The use of the Kawa model is also interesting from the point of view of how the client applies the theoretical knowledge in practice. The client expressed satisfaction with the ease of use of the model itself. Conclusion: The used modified media magnetic board and tactile picture represent an important contribution to the treatment. The occupational therapist in the rehabilitation of blind clients contributes with her knowledge to the independence and quality of life of these clients. It would be useful to conduct further studies on a larger sample and to include more other occupational therapy assessments in the occupational therapy process.
Model of Series-Parallel Photovoltaic Arrays Using Double-Diode Model and Parallel Computing

Several applications require to estimate the power production of photovoltaic (PV) systems under partial shading conditions. For example, dynamic reconfiguration of the array connections is needed to maximize the power production under partial shading conditions, which requires estimating the power generated by the PV array in several possible configurations. Therefore, a fast and accurate modeling technique is needed to perform those calculations in practical times and with low estimation errors. To address those kinds of problems, this paper proposes a modeling approach based on the double-diode model to provide high accuracy at low voltage and low irradiance conditions, which are important for partial-shading analysis. Moreover, the proposed modeling technique is designed to be implemented in parallel processing devices; thus, the calculation time is much shorter in comparison with classical serial solutions. The proposed model is tested in terms of accuracy and speed, obtaining satisfactory results. Finally, the applicability of the parallel model in reconfiguration applications is demonstrated using an application example.
Revealing population flow patterns in the Sichuan-Chongqing region, China, during the COVID-19 epidemic in 2020

ABSTRACT COVID-19 has had a serious impact on the lives and health of people and severely affected the population flow in 2020. Baidu migration data offer great opportunities to study spatiotemporal interactions among cities. Revealing population flow patterns has important scientific significance for the precise prevention and control of the COVID-19 epidemic. The aim of this article is to reveal the spatiotemporal patterns of population flow and associated influential factors in 22 cities in the Sichuan-Chongqing region (SCR), which is regarded as the fourth pole of China’s economy. Four typical time periods are selected to study the spatiotemporal patterns of population flow. The regional population flow intensities in all cities and between different cities in the SCR are illustrated. Stepwise regression is used to analyse the factors affecting regional population flow intensity in four selected periods. The results show that (1) the COVID-19 epidemic greatly affected population flow in the SCR, (2) more travel occurred between cities on holidays than on weekdays in the SCR when the epidemic was not serious, and (3) the regional population flow intensity was strongly correlated with the population education level and transportation facilities when the epidemic was not serious.
Effectiveness of 8 weeks of vestibular exercise on stress and cognitive parameters in patients with type 2 diabetes

Studies related to vestibular exercises in the management of diabetes were sparse. Hence, the present study was undertaken to observe the effectiveness of 8 weeks of vestibular exercise on stress and cognitive parameters in patients with type 2 diabetes. A total of 30 participants were recruited for the study. After recruiting, the participants were randomly assigned to the control and intervention groups with a 1:1 distribution. The vestibular exercises comprise three sets of exercises of 45 minutes duration each session. Four sessions per week were administered to the participants. The exercises were standardized by earlier researchers. The same was adopted in the present study. There was a significant decrease in the depression, anxiety, and stress scores in the participants. Spatial memory was significantly increased followed by the intervention. There was a significant increase in the verbal memory also followed by intervention.The present study results show that practicing vestibular exercises along with the prescribed treatment helps to improve cognition and to reduce stress levels. The study recommends long-term studies with a higher sample size for a better understanding of the vestibular exercises and also recommends adopting these exercises in the treatment protocol.
Weakly Supervised Boot Strapping Algorithm to Extract Comparative Questions

Compared to anything else, especially during an online purchase plan is a typical part of human decision-making process. Since performance is not ideal without comparing, not just to buy a product. To get rid of this difficulty, in this paper proposed automatically comparative questions that users posted online presence comparable offers an ideal way for the mine. It gives an opportunity to improve the search experience by automatically providing comparisons for the user. A weakly supervised bootstrapping algorithm is used here for comparative question identification and comparable entity extraction by collecting a large online question archive. It also provides users to add new attributes his interest in book-entry form, so that the next query retrieves the new attribute information provided. This technique could overcome the current system of online shopping.
Design, fabrication and characterization of III-nitrides-based photodiodes : application to high-speed devices

III-Nitrides semi-conductor materials with flexible bandgap has revealed a major interest for the future development of optoelectronic devices. The aim of this work is to study, design and develop a PIN photodiode based on InxGa1-xN and GaN materials deposited by MOCVD and MBE. Different configurations are considered for the InGaN absorbent layer: a single layer (SL) and multiple quantum wells (MQW). In order to observe the shift in the absorption wavelength, the composition of the InGaN layer ranges from10 to 50%. Structural, microstructural and optical analysis are performed using XRD, TEM, PL, AFM and SEM. We have verified that the material quality promptly degrades when increasing the indium content which impacts on the device performances. The design of the PIN structure is governed by the limitation of the active surface (from 25 to 104 μm²) in order to limit the global capacitance. Different prototypes are fabricated in clean room before characterization. Static and dynamic characterizations have been realized to qualify the photodiode response. We have investigated the influence of the indium content on the electrical performance. For the large-scale photodiodes, photocurrent value has reached a maximum of 3.2 mA with laser power of 75 mW demonstrating cut-off frequency of 940 MHz. μ-photodiode has revealed 395 μA of maximal photocurrent with cut-off frequency of 1.45 GHz.
Shear Wave Elastography Implementation on a Portable Research Ultrasound System: Initial Results

Ultrasound shear wave elastography (SWE) has emerged as a promising technique that enables the quantitative estimation of soft tissue stiffness. However, its practical implementation is complicated and presents a number of engineering challenges, including high-energy burst transmission, high-frame rate data acquisition and high computational requirements to process huge datasets. Therefore, to date, SWE has only been available for high-end commercial systems or bulk and expensive research platforms. In this work, we present a low-cost, portable and fully configurable 256-channel research system that is able to implement various SWE techniques. We evaluated its transmit capabilities using various push beam patterns and developed algorithms for the reconstruction of tissue stiffness maps. Three different push beam generation methods were evaluated in both homogeneous and heterogeneous experiments using an industry-standard elastography phantom. The results showed that it is possible to implement the SWE modality using a portable and cost-optimized system without significant image quality losses.
Harmonic Analysis and Attenuation Strategy for a Two-Stage Matrix Converter Fed by Dual-Inverter Based on Pulse Barycenter Method

Since the DC-link of the dual-inverter two-stage matrix converter (TSMC) has no energy storage element, its grid-side current waveform is closely related to the load-side condition. The conventional modulation strategy of the dual-inverter TSMC is only the stack of the double inverters, without considering the cooperation between both modulation strategies. Thus, the fluctuations in the grid-side currents synthesized by both load-side currents will be obvious. To solve this problem, this paper analyzes the effect of the current pulse position on the grid-side current waveform quality, and relevant relationship between the pulse position and current harmonics is obtained according to Fourier transform. On this basis, the harmonic attenuation strategy for the dual-inverter TSMC is proposed. In the proposed strategy, the grid-side current harmonic is reduced based on the optimal duty-cycle combination, obtained from the harmonic optimization problem. The simulation and experimental results are provided to verify that the theoretical analysis of grid-side current harmonic content is consistent with the actual condition, and the proposed modulation strategy can effectively reduce the grid-side current harmonic.