Miracle-dz/UniFAR-FTUs huggingface dataset:
Scheduling of Electric Vehicle’s Power in V2G and G2V Modes Using an Improved Charge–Discharge Opportunity-Based Approach

With rise in the popularity of electric vehicles (EVs), challenges related to its charging infrastructure are also soaring. In the upcoming smart grid scenario with significant renewable energy sources and distributed generation, EVs have been identified as a key element for grid stability and its optimal operation, primarily due to energy storage capacity. With a large number of EVs in parking, it has huge potential with optimal scheduling. However, EV owners should have the motivation to participate in vehicle-to-grid (V2G). This article proposes a scheduling mechanism using a novel forward–backward energy allocation, based on an improved charge–discharge opportunity approach. The proposed method (PM) addresses the scheduling of power flow in EVs to operate in V2G and grid-to-vehicle (G2V) modes considering EV owners’ preferences, optimal cost, and low battery degradation. The implementation of the PM is facile and flexible with the vehicle’s time of arrival and departure. A 40- and 60 kWh battery capacity EVs with multiple real-life scenarios have been considered in this study to demonstrate the effectiveness of the PM. The performance and features of the PM have been compared with the existing methods to distinguish its benefits.
Minorations des fonctions aléatoires gaussiennes

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LoRa-based smart greenhouse control system

With the continuous development of the intelligent society, smart greenhouses are also developing rapidly in the direction of intelligence and precision, realizing intelligent monitoring of the growth environment of each crop in the greenhouse, and making up for the high labor cost, high labor intensity and high labor intensity of traditional greenhouse planting. Disadvantages such as low production efficiency. The LoRa-based smart greenhouse control system adopts wireless communication technology, uses a variety of sensor modules to realize real-time monitoring of the growth environment, and combines the terminal display of various webpages and small programs to realize remote monitoring and intelligent monitoring of various environmental factors in the greenhouse. Management, early warning reminders and other functions, so as to achieve the purpose of increasing crop yield, improving product quality, and improving production efficiency, thereby greatly improving the economic benefits of smart agriculture.
Male-Biased Parasitism of Brandt’s Voles (Lasiopodomys brandtii) in Inner Mongolia, China

Simple Summary Previous studies had reported sex-biased parasitism (SBP) in small rodents. In this study, we investigate the prevalence of six intestinal parasites in Brandt’s voles (Lasiopodomys brandtii) that were captured in May, June, July, and August 2022 around the Xilingol Grassland in Inner Mongolia, China. Syphacia obvelata, Aspiculuris tetraptera, and the Trichostrongylidae family were the dominant intestinal parasites for the Brandt’s voles captured in the study areas. Season and human activities such as grazing had no significant effect on the infection rates of parasites, but the parasite reproduction level was higher when the ambient temperature was around 18 °C. We found that the sexual size dimorphism (SSD) was ubiquitous in Brandt’s voles, and males had bigger body sizes than females. Simple linear regression analysis showed a significant positive correlation between bodyweight and parasite infection rates, so the sex-biased parasitism in Brandt’s voles could be explained by the body size hypothesis, as a larger body could provide more ecological niches for parasitic infection. Abstract The abundance and prevalence of parasitic infection often vary in different host sexes, and this phenomenon has been named sex-biased parasitism. Brandt’s voles are the dominant rodent species in typical steppe habitat and are widely distributed in Inner Mongolia, China, but the prevalence of parasites in Brandt’s voles are poorly reported. In this study, we investigated the prevalence of six intestinal parasites in Brandt’s voles in May, June, July, and August 2022 around the Xilingol Grassland in Inner Mongolia, China. The results showed that Syphacia obvelata, Aspiculuris tetraptera, and Trichostrongylidae family were the dominant intestinal parasites in Brandt’s voles that we captured in this study, and the infection rates of the three parasites were significantly higher in males than females, which showed obvious male-biased parasitism. Season and human activities such as grazing had no significant effect on the infection rates for different parasites, while the parasite reproduction level was higher when the ambient temperature was around 18 °C. Sexual size dimorphism was ubiquitous in Brandt’s voles, and it was mainly manifested by the differences in body weight and length between males and females. Simple linear regression analysis showed a significant positive correlation between bodyweight and parasite infection rates, so the sex-biased parasitism in Brandt’s voles could be explained by the body size hypothesis, as a larger body could provide more ecological niches for parasitic infection.
Staphylococcus lugdunensis infective endocarditis with perforation of the sinus of Valsalva: a case report

Abstract Background Staphylococcus lugdunensis endocarditis is a rare but fulminant disease. Case summary A 74-year-old female with a history of asymptomatic severe aortic valve stenosis and permanent atrial fibrillation presented with acute onset of fever (39.0°C). Electrocardiogram showed diffuse ST-segment elevation. She was hospitalized for further analysis. All blood cultures were positive for Staphylococcus lugdunensis and antibiotic treatment was started. Transthoracic echocardiography (TTE) showed known aortic valve stenosis without clear signs of endocarditis. The following day, a transoesophageal echocardiogram (TEE) showed a new moderate aortic valve regurgitation, new pericardial effusion (PE), and a thickened sinus of Valsalva (SOV) consistent with endocarditis with paravalvular involvement. Positron emission tomography-computed tomography was consistent with aortic valve endocarditis with paravalvular expansion. The patient was transferred to a tertiary referral centre for surgical treatment. On admission, patient was in shock and a second TTE revealed a new systolic and diastolic flow through the SOV to the right ventricle indicating SOV perforation. Additionally, there was flow in the PE suggestive of perforation of one of the cardiac chambers or large vessels. Emergent surgery showed extended infection with SOV perforation and a large perforation of the right ventricle. Ultimately, patient died during the operation because of extensive infection and refractory shock. Conclusion Staphylococcus lugdunensis endocarditis is a severe disease with poor response to conventional anti-microbial treatment, destructive complications requiring surgery, and has a high mortality risk.
Framework for Guiding the Development of High-Quality Conversational Agents in Healthcare

Evaluating conversational agents (CAs) that are supposed to be applied in healthcare settings and ensuring their quality is essential to avoid patient harm and ensure efficacy of the CA-delivered intervention. However, a guideline for a standardized quality assessment of health CAs is still missing. The objective of this work is to describe a framework that provides guidance for development and evaluation of health CAs. In previous work, consensus on categories for evaluating health CAs has been found. In this work, we identify concrete metrics, heuristics, and checklists for these evaluation categories to form a framework. We focus on a specific type of health CA, namely rule-based systems that are based on written input and output, have a simple personality without any kind of embodiment. First, we identified relevant metrics, heuristics, and checklists to be linked to the evaluation categories through a literature search. Second, five experts judged the metrics regarding their relevance to be considered within evaluation and development of health CAs. The final framework considers nine aspects from a general perspective, five aspects from a response understanding perspective, one aspect from a response generation perspective, and three aspects from an aesthetics perspective. Existing tools and heuristics specifically designed for evaluating CAs were linked to these evaluation aspects (e.g., Bot usability scale, design heuristics for CAs); tools related to mHealth evaluation were adapted when necessary (e.g., aspects from the ISO technical specification for mHealth Apps). The resulting framework comprises aspects to be considered not only as part of a system evaluation, but already during the development. In particular, aspects related to accessibility or security have to be addressed in the design phase (e.g., which input and output options are provided to ensure accessibility? ) and have to be verified after the implementation phase. As a next step, transfer of the framework to other types of health CAs has to be studied. The framework has to be validated by applying it during health CA design and development.
Performance of a blood-based RNA signature for gemcitabine-based treatment in metastatic pancreatic adenocarcinoma

Background Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer, and chemotherapy is a key treatment for advanced PDAC. Gemcitabine chemotherapy is still an important component of treatment; however, there is no routine biomarker to predict its efficacy. Predictive tests may help clinicians to decide on the best first-line chemotherapy. Methods This study is a confirmatory study of a blood-based RNA signature, called the GemciTest. This test measures the expression levels of nine genes using real-time polymerase chain reaction (PCR) processes. Clinical validation was carried out, through a discovery and a validation phases, on 336 patients (mean 68.7 years; range, 37–88 years) for whom blood was collected from two prospective cohorts and two tumor biobanks. These cohorts included previously untreated advanced PDAC patients who received either a gemcitabine- or fluoropyrimidine-based regimen. Results Gemcitabine-based treated patients with a positive GemciTest (22.9%) had a significantly longer progression-free survival (PFS) {5.3 vs. 2.8 months; hazard ratio (HR) =0.53 [95% confidence interval (CI): 0.31–0.92]; P=0.023} and overall survival (OS) [10.4 vs. 4.8 months; HR =0.49 (95% CI: 0.29–0.85); P=0.0091]. On the contrary, fluoropyrimidine-based treated patients showed no significant difference in PFS and OS using this blood signature. Conclusions The GemciTest demonstrated that a blood-based RNA signature has the potential to aid in personalized therapy for PDAC, leading to better survival rates for patients receiving a gemcitabine-based first-line treatment.
Anomalous Wave Propagation in Magnetic Hyperbolic Metasurfaces

Topological transitions in reciprocal space, widely existing in hyperbolic metasurfaces, have attracted significant attention due to their unprecedented capabilities to redirect surface plasmon polaritons, for example, anomalous wave propagation, negative refraction, non-diffraction transmission, etc. However, previous studies have mostly focused on electric hyperbolic metasurfaces, while magnetic configurations that enable magnetic light-matter interaction and the manipulation of magnetic surface waves have seldom been studied. Here, we theoretically and numerically study a terahertz magnetic topological transition metasurface consisting of the double-split ring resonator arrays, demonstrating that breaking the symmetry of the metal pattern is an efficient method to introduce Fano resonance and novel independent self-collimation frequency. Furthermore, we try to combine two different magnetic hyperbolic metasurfaces to manipulate the magnetic surface waves at the topological transition interface at will. The proposed integrated metasurface provides new degree of freedom for the control of magnetic plasmons and presents a great potential in the applications of plasmonic devices.
Non-thermal effects and mechanisms of interaction between electromagnetic fields and living matter

The fundamental Physical mechanisms of the resonant action of an extremely weak (40 nanoT) alternating magnetic field at the cyclotron frequency combined with a weak (40 mcT) static magnetic field, on living systems are analyzed in the present article. The experimental effects of such sort of magnetic fields were described in different articles: the very narrow resonant peaks in electrical conductivity of the aqueous solutions in the in vitro experiments and the Biomedical in vivo effects on living animals of magnetic fields with frequencies tuned to some amino acids. The existing experimental in vitro data had a good repeatability in different laboratories and countries. Unfortunately, for free ions such sort of effects are absolutely impossible because the dimensions of an ion rotation radius should be measured by meters at room temperature and at very low static magnetic fields used in all the above experiments. Even for bound ions these effects should be also absolutely impossible from the positions of Classic Physics because of rather high viscosity of biological liquid media. Only modern Quantum ElectroDynamics of condensed media opens the new ways for solving these problems. The proposed article is devoted to detailed analysis of Quantum mechanisms of these effects.
Introducing Transfer Learning Framework on Device Modeling by Machine Learning

In this study, we propose a novel transistor modeling method using machine learning techniques, with a focus on extrapolation performance. Our method leverages knowledge from a base model that is related to the target model, instead of relying solely on device-specific information. The results show that our approach outperforms other transistor modeling methods based on machine learning, particularly in modeling similar but different transistors that belong to the same device family. Our method was able to reduce the root mean squared error (RMSE) by up to 80.0% compared to other methods.
Automatically Reconfigurable Optical Network for HPC System Based on Deep Reinforcement Learning

High-density optical interconnects enable high-bandwidth, low-latency and energy-efficient communication. Also, in order to enhance the adaptability of High Performance Computing (HPC) networks for traffic variation, optical networking reconfiguration capability is a promising alternative to traditional fixed interconnection architecture. We propose a reconfigurable optical network for HPC systems that can automatically switch between different topologies controlled by a Deep Reinforcement Learning (DRL) agent. By varying the topology of our network, we evaluate it using an Advantage Actor-Critic (A2C) and a Deep Deterministic Policy Gradient (DDPG) algorithm-based scheme. Results show that our prototype achieves up to 1.7x performance improvement.
SPSA-Based Switch Updating Algorithm for Constrained Stochastic Optimization

Simultaneous perturbation stochastic approximation (SPSA) is widely used in stochastic optimization due to its high efficiency, asymptotic stability, and reduced number of required loss function measurements. However, the standard SPSA algorithm needs to be modified to deal with constrained problems. In recent years, sequential quadratic programming (SQP)-based projection ideas and penalty ideas have been analyzed. Both ideas have convergence results and a potentially wide range of applications, but with some limitations in practical consideration, such as computation time, complexity, and feasibility guarantee. We propose an SPSA-based switch updating algorithm, which updates based on the loss function or the inequality constraints, depending on current feasibility in each iteration. We show convergence results for the algorithm, and analyze its properties relative to other methods. We also numerically compare the switch updating algorithm with the penalty function approach for a constrained example.
Changes in the structure of cellulose aerogels with depolymerization

To compare the cellulose aerogels from hydrolyzed and unhydrolyzed cotton linter, we prepared cellulose wet gels from cellulose solution dissolved in hydrated calcium thiocyanate at 110 °C and dried them by using the freeze-drying method. The initial root-mean-square (RMS) radius and the weight average molar mass of cotton linter decreased from 71 nm and 405 kg·mol −1, respectively, to 13 nm and 35 kg·mol −1 upon acid hydrolysis. The density of cellulose aerogels increased from 39 to 87 kg/m3 as the cellulose starting material was depolymerized. The microstructure of the cellulose aerogel was viewed with a scanning electron microscope (SEM), and the microstructure and the micro-sized pores were found to be destroyed by cellulose degradation. The degree of polymerization (DP) of the cellulose was found to affect the aerogel’s density and network structure.
Prospect Theoretic Contract Design in a Stackelberg Game via Bayesian Inference

Dynamic contract design with a cognitively biased principal is studied in this work using a Stackelberg game framework. Prospect theory is used to model the decision making of the cognitively biased principal. The goal of the principal is to design a sequence of contracts when faced with adverse selection-lack of knowledge of agent's private information- and moral hazard- noisy observation of agent's effort. The principal observes the noisy output of the agent's effort and using the prior probabilities of the agent's private information, performs a Bayesian inference of the agent's type taking into account Prospect theoretic probability weighting. The prospect theoretic decision making of principal is studied for a static game (one shot) and a dynamic game (finite number of rounds). It is demonstrated that the agent will benefit from principal's irrationality by extracting higher rent than the game with a rational principal. Theoretical results are derived for the binary type games, and the investigation is expanded to an $M$ -ary hypothesis testing framework through numerical simulation results. The results demonstrate that in estimating the agent's type, a cognitively biased principal becomes more conservative to ensure agent's participation in the game than a rational principal thus allowing increased rent for the agent.
An Integrated Optimal Resource Management Scheduling for Dual Target in Remote MIMO Systems

Distributed MIMO radar offers a novel concept for the evolution of networked radar as a new radar system with increasing efficiency. In this research, we offer a resource planning technique for multi target imaging in dispersed netted radar predicated on the greatest organizing advantages, with the goal of addressing the constrained resource provisioning issue inherent in netted radar. The technique takes into account the angle and dwell duration in detail to finish the multi radar and multi target matching under the assumption of target knowledge. Then, it employs the compressed sensing concept to figure out how many pulses will be needed to image each object sparsely with the matching radar. In this study, we use a weighted average of the planning positive outcome, the hit value rate, as well as the pulse resource utilization rate to quantify the planning advantage of a radar system. Maximum scheduling benefits are used to build the resource scheduling mechanism, which is then solved to use a heuristic method. The simulated findings demonstrate that the scheduling advantages of the radar system are enhanced when compared to those obtained using the conventional methodology.
Collaborative Domain Adaptation Network for Partial Discharge Source Localization in Gas-Insulated Switchgear

Abnormal discharge in gas-insulated switchgear (GIS) is the key cause of insulation failure, and it is also an external manifestation of insulation defects. Sensitive discharge source localization is an important goal of GIS partial discharge (PD) monitoring. However, most existing GIS PD source localization methods rely on time-delay estimation, which not only requires a high-precision synchronous sampling device but also suffers from serious interference. To this end, a collaborative domain adaptation network (CDAN) is proposed for GIS PD source localization. First, a synchronous squeezing wavelet transform (SWT) is introduced to filter out the noise, eliminating the influence of noise on GIS PD source localization. Then, 1-D attention convolutional neural network (1DACNN) is constructed to ensure that discriminative temporal fine-grained information is extracted. Next, a CDAN is proposed to transfer the localization knowledge learned from the simulation to actual GIS and achieve high-precision localization through domain matching and alignment. The results demonstrate that the error of the CDAN proposed is only 19.87 cm, which is considerably better than that from other methods. This work provides a reference solution for the GIS PD source localization.
The role of LIN28B in tumor progression and metastasis in solid tumor entities

LIN28B is an RNA-binding protein that targets a broad range of microRNAs and modulates their maturation and activity. Under normal conditions, LIN28B is exclusively expressed in embryogenic stem cells, blocking differentiation and promoting proliferation. In addition, it can play a role in epithelial-to-mesenchymal transition by repressing the biogenesis of let-7 microRNAs. In malignancies, LIN28B is frequently overexpressed, which is associated with increased tumor aggressiveness and metastatic properties. In this review, we discuss the molecular mechanisms of LIN28B in promoting tumor progression and metastasis in solid tumor entities and its potential use as a clinical therapeutic target and biomarker.
Transport-Free Placement of Mixers for Realizing Bioprotocol on Programmable Microfluidic Devices

A Programmable Microfluidic Device (PMD) is one of the promising biochip platforms. On a PMD having a two-dimensional array of cells, fluids are mixed by a module called a mixer. We can configure various kinds of mixers, such as a $2\times 2$ mixer and a $2\times 3$ mixer consisting of $2\times 2$ and $2\times 3$ arrays of cells, respectively. Unlike other biochip platforms, it is difficult to precisely move a fluid from one cell to another in a PMD without any contamination. Thus, recently a “No Transport Mixing (NTM)’ method has been proposed, which binds and schedules the mixers without fluid transportation. However, NTM works with only $2\times 2$ mixers on a PMD biochip. In this paper, we propose an efficient method to bind and schedule the mixing operations using $2\times 3$ mixers as well as $2\times 2$ mixers. The proposed method is based on the transformation of a mixing tree into another one based on the “Placement Priority’ values as estimated. Simulation results confirm that this transformation indeed is useful to decrease the number of washing operations (‘flushing’) required during the implementation of a bioprotocol on a PMD biochip, which, in turn, reduces the consumption of expensive biochemical fluids in the bioprotocol.