Miracle-dz/UniFAR-FTUs huggingface dataset:
Path Planning Algorithm Based on Teachinglearning-Based-Optimization for an Autonomous Vehicle

Resume This study provides a teaching-learning-based optimization (TLBO) path planning method for an autonomous vehicle in a cluttered environment, which takes into account path smoothness and the possibility of collision with nearby obstacles. The path planning problem is tackled as a multiobjective optimization in order to plan an efficient path that allows the vehicle to travel autonomously in crowded settings. The TLBO algorithm is used to find the ideal path, with the goals of finding the shortest path to the target site and maximizing path smoothness, while avoiding obstacles and taking into account the vehicle's dynamic and algebraic properties. Article info Received 1 October 2021 Accepted 18 January 2022 Online 22 February 2022
Study of digital/analog performance parameters of misaligned gate recessed double gate junctionless field-effect-transistor for circuit level application

In this work, the effect of gate misalignment towards the source and drain ends for 20 nm recessed double gate junctionless field-effect-transistor (R_DGJLFET) have been studied on various digital and analog performance parameters from device to circuit level while setting the simulation set-up using 2D Silvaco ATLAS technology computer aided design (TCAD). With recessed silicon channel, the quantum confinement effects have been considered for channel thickness <7 nm. In comparison to conventional double gate junctionless FET (C_DGJLFET), the device exhibits lesser OFF-current, improved ON-to-OFF current ratio, better subthreshold slope (SS), and lower drain-induced-barrier-lowering (DIBL). Analogically, it has been found that the misaligned gate towards drain affects the digital and analog parameters more severely in comparison to gate misalignment towards the source end. However, the misaligned R_DGJLFET towards the drain end shows robustness in terms of SS and DIBL with smaller variations of ∼10.84% and ∼61.79%, respectively. Moreover, due to very low parasitic capacitances, the device shows lesser variations in different alternating current (AC) performance parameters namely, transconductance generation factor (TGF), unity gain frequency, and gain-bandwidth product in comparison to C_DGJLFET. With gate misalignment towards source the unity gain frequency, and gain-bandwidth improve by ∼9.67% and ∼19.9%, respectively whereas the TGF remains almost unaffected. Furthermore, to ensure the device capability in circuit application a complementary metal-oxide-semiconductor (CMOS) inverter and common-source (CS) amplifier based on R_DGJLFET have been designed. In contrast to C_DGJLFET based counterpart, the R_DGJLFET expresses its suitability for low-power digital applications with better noise margins and smaller short-circuit current in the CMOS inverter. In analog domain, the R_DGJLFET based CS amplifier shows an improved amplification factor of 4.75 in comparison to C_DGJLFET. This paper provides deep insight into the severity of gate misalignment towards source/drain for R_DGJLFET in both digital and analog domains from device to circuit level.
Pond Assay for the Sensory Systems of Caenorhabditis elegans: A Novel Anesthesia-Free Method Enabling Detection of Responses to Extremely Low Chemical Concentrations

Simple Summary We propose a pond assay for the sensory systems (PASS) of Caenorhabditis elegans as a novel method of behavioral analysis. In PASS, the test solution is injected into a recess(es) formed on agar and the response of C. elegans to its odor and/or taste is examined. Once C. elegans individuals fall into recesses (ponds) filled with liquid, they cannot return to the solid medium. In this way, the animals are trapped with certainty without the use of anesthesia. The anesthesia used to keep animals in the attractant area in conventional chemotaxis assays is no longer required, allowing pure evaluation of the response to specific substances. Furthermore, the test itself can be greatly streamlined because the preparation can be completed simply by providing a recess(es) and filling the liquid. The present paper reports the detailed method and effectiveness of the novel PASS through a series of chemotaxis assays. By using the PASS method, we found that the olfactory system of C. elegans accurately senses odors even at extremely low concentrations lower than the previously known detection threshold. This method can be applied to biosensor technology that uses C. elegans to detect chemical substances present at extremely low concentrations in environmental samples and biological samples with high sensitivity. Abstract Chemotaxis in the nematode Caenorhabditis elegans has basically been examined using conventional assay methods. Although these can be problematic, for example, in their use of anesthesia, the method has never been improved. We propose a pond assay for the sensory systems (PASS) of C. elegans as a novel population-based method of behavioral analysis. The test solution is injected into a recess(es) formed on agar and the response of C. elegans to its odor and/or taste is examined. Once C. elegans individuals fall into recesses (ponds) filled with liquid, they cannot return to a solid medium. In this way, the animals are trapped with certainty without the use of anesthesia. The anesthesia used to keep animals in the attractant area in conventional chemotaxis assays is no longer required, allowing pure evaluation of the attractant or repellent response to specific substances. Furthermore, the assay itself can be greatly streamlined because the preparation can be completed simply by providing a recess(es) and filling the liquid. The present paper reports the detailed method and effectiveness of the novel PASS.
A Coordinate Rotational Transformation Based Virtual Power V/f Droop Control Method for Low Voltage Microgrid

Power coupling is a common problem in a microgrid because of the differences in impedance ratios between low voltage microgrid lines and traditional high voltage transmission lines.A virtual power V/f droop control method based on coordinate rotational transformation is proposed to handle this problem.The method achieves the decoupled real and reactive power control through orthogonal transformation matrix.By improving the voltage-frequency droop control,a new drooping restriction control algorithm is also introduced.Furthermore,a low pass filter is designed specifically to reduce the harmonic effect and improve the control accuracy.Taking the load disturbance of microgrid in the islanded mode and its transformation from islanded mode to interconnected mode into consideration,the good adaptability of low-voltage microgrid controller is proved by simulation results.Experimental results indicate that the proposed method can achieve the load power sharing effectively in the low-voltage microgrid,with relatively stable frequency and amplitude,good dynamic effect,and enhanced accuracy and stability of system power sharing.
Monitoring and Inference of Behavioral Resistance in Beneficial Insects to Insecticides in Two Pest Control Systems: IPM and Organic

Pyrethrins are the most widely used insecticide class in olive groves with organic management. Although there are data sets about insect pests of stored products and human parasites developing resistance to pyrethrins, there is no information on the long-term effect on olive agroecosystems. A field method based on the experimental induction of sublethal effects by means of insecticide application, and the monitoring of the response of insects through post-treatment sampling, has recently been developed. This method has allowed for the detection of populations behaviorally resistant to organophosphates in integrated pest management (IPM) and conventional crops. With the application of a similar methodology, this study aimed to verify the possible reaction of natural enemies in organic crops, using pyrethrins as an inducing insecticide. The study was carried out in 2019 in two olive groves in southern Spain (Jaén, Andalusia), one of them being IPM and the other being an organic production system. The results did not allow for verification of the behavioral resistance in populations of natural enemies of both IPM and organic management against pyrethrins, while against dimethoate, behavioral resistance was verified in IPM management. The possible causes involved in obtaining these results are discussed.
Tests for a whole-spacecraft vibration isolation platform using a magnetorheological damper

In order to reduce all kinds of vibration and impact load exerted on a satellite and coming from its carrier rocket,here,a new semi-active whole-spacecraft vibration isolation(WSVI) platform was presented.In the WSVI platform,the magneto-rheological(MR) damping technique was adopted and utilized.The proposed WSVIP and the satellite model were designed and manufactured,and then the WSVI system was assembled.The tests of WSVI were conducted.Furthermore,the isolation performances of the WSVI system,a conventional MR damper vibration isolation platform and a conical adapter were evaluated and compared.The results showed that the passive isolation effect of the WSVI system is significantly better than that of the conical adapter;high-frequency decoupled MR dampers in the WSVI system can help the vibration isolation platform to reduce high frequency transmission rate and improve high frequency vibration isolation performance.
The Effect of Tree Enrichment in an Oil Palm Plantation on the Biodiversity of the Understorey Vegetation

I Abstract Tropical regions worldwide and in particular the island state of Indonesia have been affected by high deforestation rates and a severe land-use change to agricultural landscapes such as oil palm monocultures. This is generally linked to a loss in biodiversity and ecosystem functioning. Reduced-impact agroforestry appears to have considerable potential to mitigate these losses. To explore the processes, constraints and trade-offs for ecological restoration in already existing oil palm plantations, the Collaborative Research Centre (CRC) 990 established a Biodiversity Enrichment Experiment in Sumatra (Indonesia). A key element among the various ecosystem variables and biotic characteristics investigated in the experiment is the understorey vegetation, an ecologically important but inadequately studied group. The aim of this Master’s thesis is the deeper knowledge about the effects of enrichment plantings in oil palm plantations on the diversity, the composition, and the structure of the understorey vegetation. The understorey vegetation was expected to alter according to the gradients of the experimental key variables: size and tree diversity level of the enriched islands. The conducted understorey vegetation survey consists of vascular plant species inventories in all 56 plots of the experiment and additional data collection concerning species-area relations. The results of the study show that the species pool has already increased compared to the baseline survey five years ago. However, species diversity, composition, and vegetation structure were not clearly dependent on the gradients of the plot size and tree diversity level but more strongly influenced by other factors, such as canopy cover. The comparison of the enriched plots with the managed as-usual plots showed a considerable shift in the species community. In addition, a significantly increased proportion of tree and seedling species and cover was found in the plots with experimental treatment. In the context of ecological restoration, these findings can be interpreted as an already positive development. However, due to the early stage of succession, assessments of the success of enrichment plantings in oil palm plantations are limited. This study contributes to a deeper understanding of biodiversity restoration in palm oil plantations and the role of the understorey in this context.
Relationships Among Gut Microbiota, Ischemic Stroke and Its Risk Factors: Based on Research Evidence

Abstract Stroke is a highly lethal disease and disabling illness while ischemic stroke accounts for the majority of stroke. It has been found that inflammation plays a key role in the initiation and progression of stroke, and atherosclerotic plaque rupture is considered to be the leading cause of ischemic stroke. Furthermore, chronic inflammatory diseases, such as obesity, type 2 diabetes mellitus (T2DM) and hypertension, are also considered as the high-risk factors for stroke. Recently, the topic on how gut microbiota affects human health has aroused great concern. The initiation and progression of ischemic stroke has been found to have close relation with gut microbiota dysbiosis. Hence, this manuscript briefly summarizes the roles of gut microbiota in ischemic stroke and its related risk factors, and the practicability of preventing and alleviating ischemic stroke by reconstructing gut microbiota.
The Influence of Analgesic Modalities on Postoperative Cancer Recurrence

The potential for cancer cells to grow and to metastasize depends on complex interactions between inflammatory signals and pathways, immune cells, and elements of the stromal tissue in which they invade. Related to the nature of many cancers, the probability of recurrence can potentially be quite high for some patients. Immunology, lifestyle modifications, timing of disease, genetics, age, gender, and race are only a handful of ways the likelihood of cancer recurrence can be influenced. The quantity, or density, of certain immunological cells or factors, plays a role in the propagation of cancer cells. Opioids are often used in cancer patients for acute postoperative and chronic pain management. While they can produce significant pain relief, the type of analgesic utilized is important, as it may influence cancer propagation. In this regard, certain opioids have been found to increase T regulatory cells while suppressing NK cell function. Morphine may promote tumor neovascularization and expansion. Fentanyl administration significantly diminishes NK-cells and CD8+ cytotoxic T-cells. In a recent meta-analysis, propofol-based anesthesia improved both cancer-free survival and overall survival. COX inhibitors have also shown promise in persevering cancer immune function, as in literature involving ketorolac and celecoxib. In summary, inhaled anesthesia and opioids may contribute to a pro-tumor metastasis environment also known as cancer propagation; whereas propofol and COX inhibitors may provide a better alternative to reduce cancer recurrence and propagation.
I-SEA: Importance Sampling and Expected Alignment-Based Deep Distance Metric Learning for Time Series Analysis and Embedding

Learning effective embeddings for potentially irregularly sampled time-series, evolving at different time scales, is fundamental for machine learning tasks such as classification and clustering. Task-dependent embeddings rely on similarities between data samples to learn effective geometries. However, many popular time-series similarity measures are not valid distance metrics, and as a result they do not reliably capture the intricate relationships between the multi-variate time-series data samples for learning effective embeddings. One of the primary ways to formulate an accurate distance metric is by forming distance estimates via Monte-Carlo-based expectation evaluations. However, the high-dimensionality of the underlying distribution, and the inability to sample from it, pose significant challenges. To this end, we develop an Importance Sampling based distance metric -- I-SEA -- which enjoys the properties of a metric while consistently achieving superior performance for machine learning tasks such as classification and representation learning. I-SEA leverages Importance Sampling and Non-parametric Density Estimation to adaptively estimate distances, enabling implicit estimation from the underlying high-dimensional distribution, resulting in improved accuracy and reduced variance. We theoretically establish the properties of I-SEA and demonstrate its capabilities via experimental evaluations on real-world healthcare datasets.
Gastrointestinal Microbiome and Neurologic Injury

Communication between the enteric nervous system (ENS) of the gastrointestinal (GI) tract and the central nervous system (CNS) is vital for maintaining systemic homeostasis. Intrinsic and extrinsic neurological inputs of the gut regulate blood flow, peristalsis, hormone release, and immunological function. The health of the gut microbiome plays a vital role in regulating the overall function and well-being of the individual. Microbes release short-chain fatty acids (SCFAs) that regulate G-protein-coupled receptors to mediate hormone release, neurotransmitter release (i.e., serotonin, dopamine, noradrenaline, γ-aminobutyric acid (GABA), acetylcholine, and histamine), and regulate inflammation and mood. Further gaseous factors (i.e., nitric oxide) are important in regulating inflammation and have a response in injury. Neurologic injuries such as ischemic stroke, spinal cord injury, traumatic brain injury, and hemorrhagic cerebrovascular lesions can all lead to gut dysbiosis. Additionally, unfavorable alterations in the composition of the microbiota may be associated with increased risk for these neurologic injuries due to increased proinflammatory molecules and clotting factors. Interventions such as probiotics, fecal microbiota transplantation, and oral SCFAs have been shown to stabilize and improve the composition of the microbiome. However, the effect this has on neurologic injury prevention and recovery has not been studied extensively. The purpose of this review is to elaborate on the complex relationship between the nervous system and the microbiome and to report how neurologic injury modulates the status of the microbiome. Finally, we will propose various interventions that may be beneficial in the recovery from neurologic injury.
Probabilistic Deep Learning with Generalised Variational Inference

We study probabilistic Deep Learning methods through the lens of Approximate Bayesian Inference. In particular, we examine Bayesian Neural Networks (BNNs), which usually suﬀer from multiple ill-posed assumptions such as prior and likelihood misspeciﬁcation. In this direction, we investigate a recently proposed approximate inference framework called Generalised Variational Inference (GVI) in comparison to state-of-the-art methods including standard Variational Inference, Monte-Carlo Dropout, Stochastic gradient Langevin dynamics and Deep Ensembles. Also, we expand the original research around GVI by exploring a broader set of model architectures and mathematical settings on both real and synthetic data. Our experiments demonstrate that approximate posterior distributions derived from such a method oﬀer attractive properties with respect to uncertainty quantiﬁcation, prior speciﬁcation robustness and predictive performance, especially in the case of BNNs. The code for all the experiments can be found in the following public Github repository: https://github.com/gfelekis/GVI-posteriors-in-Probabilistic-Deep-Learning
Parental Divorce and Maldivian Young Adult Student’s Romantic Relationship Quality: Indirect Pathways through Attitude towards Divorce

This study aimed to identify the mediating roles of attitude towards divorce on the relationship between parental divorce and romantic relationship quality of young adult student’s. A total of 463 Maldivian undergraduate students participated as respondents. They were in a romantic relationship, ages 18 to 25. Data was collected using a self-administered questionnaire. Relationship quality were measured using relationship quality component inventory and attitudes towards divorce were measured using attitudes towards divorce scale. Data was analyzed using the PLS-SEM technique. Results revealed that parental divorce was associate with low romantic relationship quality through favorable attitude towards divorce. This will be helpful for professionals as it can be used to identify specific preventive measures to reduce the negative impact of parental divorce. The future study suggest incorporating a larger sample with participants that are more representative of the general population in terms of gender and working population.
Making Instant Spiced Coffee Drink to Prevent Covid-19

Spicy drinks are derived from types of spices such as turmeric, ginger, kunci, kencur, temulawak, galangal, and so on have been widely known by the Indonesian people as herbs and fresh drinks. However, there are still many who do not like this type of drink because of the distinctive and sharp aroma and taste of the spices. To make variations of spiced drinks so that they can be more accepted by the public, practical, and have a higher selling value, innovations can be made by adding ingredients that can improve the taste, namely coffee and creamer so that the processed product is called "Instant Spiced Coffee". The purpose of this research is to find out: 1) the level of preference of the panelists towards the finished instant spiced coffee which includes texture, color, aroma, and taste; 2) nutritional content of instant spiced coffee per 100 grams, and 3) the selling price of instant spiced coffee per sachet. The type of research is experimental, data collection using observation, and preference testing techniques. The analysis technique for organoleptic test results is quantitative descriptive to determine nutritional content based on laboratory tests which include Energy, Carbohydrates, Fat, Calcium, Protein, Vitamin A, Vitamin C, and Antioxidants, as well as to calculate the selling price using the standard cost method. The results showed: 1) the panelists' preference for color was 93.335 likes, 93.33% likes aroma, 93.33% likes taste, 86.67% viscosity, and 93.33% solubility; 2) the nutritional content per 100 grams is Energy: 208.50 kcal, Carbohydrates 44.80%, Fat 2.15%, Calcium 89.50 mg, Protein 1.38%, Vitamin A 42.50 grams, Vitamin C 38, 10 grams, and Antioxidants 198.20 mek, and 3). the selling price of instant spiced coffee is Rp. 2.500,(per sachet). Keywords— Instant Drinks, Spices, Coffee, Creamer, Covid-19
GIT Partial Discharge UHF On-line Monitoring System

According to the structure and operating characteristic of gas insulated transformer (GIT),an outer ultra high frequency (UHF) microstrip patch antenna (MPA) sensor was designed suitable for detecting the partial discharge on site. Some effective methods for expanding bandwidth are utilized in the design process,such as choosing the material,adding impedance matching and multi-tuning loop. The effective working bandwidth of the antenna is 340～440 MHz,and the relative bandwidth is 25.6%,at the same time ,the maximal gain reaches 5.38 dBi. MPA sensors were installed on the GIT insulators,which were located in the cable section of incoming line,fan duct,cooling pipe of 110 kV and 10 kV side. Then online monitoring system for GIT was structured and detecting system software based on #C was developed. Through the operation of GIT substation in Xinmin street of Chongqing City,the results show that the online monitoring system developed can detect UHF GIT PD signal for a long time,which have provided lots of reliable data for condition-based maintenance.