Miracle-dz/UniFAR-FTUs huggingface dataset:
Generalized Space Time Block Coded Spatial Modulation for Open-Loop Massive MIMO Downlink Communication Systems

In this paper, we propose a generalized space-time block coded spatial modulation (GSTBC-SM) scheme for open-loop massive multiple-input and multiple-output (MIMO) downlink communication systems. Specifically, we firstly partition the information bits into multiple groups with each group modulated by the spatial modulation (SM), where the SM symbols are invoked for orthogonal STBC (OSTBC) and quasi-orthogonal STBC (Q-OSTBC) structures. Then, message passing (MP) and block minimum mean square equalization (B-MMSE) detectors are designed for our GSTBC-SM systems, to achieve near-optimal performance with significantly reduced complexity in massive MIMO configurations. Finally, we derive the theoretical average bit error probability (ABEP) of the proposed scheme. The main contribution is that the propose scheme achieves high transmission rate and diversity gain even with small number of radio frequency (RF) chains at the transmitter. Simulation results verify the theoretical derivations and show that the proposed GSTBC-SM scheme provides near 20 dB gain over the conventional GSTBC scheme under massive MIMO configurations.
Crack Detection Method for Tunnel Lining Surfaces using Ternary Classifier

The inspection of cracks on the surface of tunnel linings is a common method of evaluate the condition of the tunnel. In particular, determining the thickness and shape of a crack is important because it indicates the external forces applied to the tunnel and the current condition of the concrete structure. Recently, several automatic crack detection methods have been proposed to identify cracks using captured tunnel lining images. These methods apply an image-segmentation mechanism with well-annotated datasets. However, generating the ground truths requires many resources, and the small proportion of cracks in the images cause a class-imbalance problem. A weakly annotated dataset is generated to reduce resource consumption and avoid the class-imbalance problem. However, the use of the dataset results in a large number of false positives and requires post-processing for accurate crack detection. To overcome these issues, we propose a crack detection method using a ternary classifier. The proposed method significantly reduces the false positive rate, and the performance (as measured by the F1 score) is improved by 0.33 compared to previous methods. These results demonstrate the effectiveness of the proposed method.
Application of Flipped Lassroom Teaching Method Based on VR Technology in Physical Education and Health Care Teaching

This research is mainly based on the research on learning space design at home and abroad, researching and discussing the definition, characteristics, significance and theoretical basis design principles of the learning space of SPOC flipped classroom, and then the real space of SPOC flipped classroom implemented by universities Design improvements with virtual space, through continuous classroom observation, interviews and other research, after two rounds of design, the university SPOC flips the classroom real space and virtual space model. In the virtual space, teachers use the platform to teach sports and health care, communicate with students, and formulate corresponding methods for common problems such as video knowledge points on the Internet to further promote the effective implementation of education. At the same time, adopting multiple evaluation modes such as the combination of process evaluation and result evaluation, increasing the reward mechanism of the learning process, can improve the fairness of evaluation and also enhance students’ learning enthusiasm. And through questionnaire surveys, interviews to optimize the improvement effect of SPOC flipped classroom real space and virtual space. After the combination of VR and flipped classroom, student satisfaction rose from 4.19 to 4.6486. The research results show that the flipped classroom teaching method based on VR technology realizes the fair distribution of teaching resources and the differential distribution of personalized teaching resources. The comprehensive ability of students has been significantly improved, and the diversification of teaching evaluation models has been realized.
Shelf Life Study and Antagonistic Activity of Trichoderma viride in Different Oil Formulations

Trichoderma is a genus of asexually reproducing fungi that are often the most frequently isolated soil fungi; nearly all temperate and tropical soils contain 101-103 culturable propagules per gram. These fungi also colonize woody and herbaceous plant materials, in which the sexual Teleomorph (genus Hypocrea) has most often been found. They show a high level of genetic diversity, and can be used to produce a wide range of products of commercial and ecological interest. They are prolific producers of extracellular proteins, and are best known for their ability to produce enzymes that degrade cellulose and chitin—although they also produce other useful enzymes (Harman and Kubicek., 1998). Trichoderma is considered as most efficient biocontrol agents and have attracted considerable scientific attention as they are considered as promising alternative to International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 7 Number 11 (2018) Journal homepage: http://www.ijcmas. com
Ambipolar Trap for Dust Particles in a V-Shaped Homogeneous Positive Column of Glow Discharge at Low and Medium Pressures

The spatial distribution of dust particles in a low-pressure homogeneous positive column of a dc glow discharge in a right-angle curved (V-shaped) glass tube in different spatial orientations was observed and analyzed. It is found that in all cases, the ambipolar field prevents charged dust particles from falling on the wall of the glass tube. As a result, the design of the curved glass tube makes it possible to create in practice a simple and effective ambipolar trap and to implement the collection and control of dust particles in plasma.
Demand for light fuels in Brazil: an approach using spatial panel data models

Abstract The need for changes in the current energy matrix is a reality due to the possibility of a shortage of fossil fuels and the environmental damage caused by emissions related to fossil fuel use. The correct prescription of public policies for energy markets depends on the knowledge of demand elasticities. Hence, the aim of this work was to estimate the main determinants of light fuel demands in Brazil. Dynamic and non-dynamic estimators were used, and the results indicated that both demands respond more to changes in gasoline prices than changes in ethanol prices. Therefore, public policies that aim to change consumption patterns should focus on gasoline prices.
Iodine-125 seed implantation treatment of lung metastases < 2.5 cm using 5-ml syringe as a guide

Purpose Small lung metastases change their location with respiration, making difficult to localize, therefore, increasing the number of punctures. Accurate puncture can reduce trauma to lung tissue and accelerate patient’s recovery. The aim of the study was to present our experience with the technique of using local anesthesia 5-ml syringe as a guide for computerized tomography-guided iodine-125 seed implantation (CT-ISI). Material and methods This was a retrospective study, including patients with small metastatic tumors in the lung, treated with CT-ISI between December 2013 and March 2018 at the Affiliated Hospital of the University. The patients were divided according to whether a 5-ml syringe was used as a guide during CT-ISI or not. The final follow-up was on March 31st, 2018. Implantation success and complications were examined. Results Nineteen patients were included. A total of 840 seeds were used, with 44.2 ±33.6 (range, 10-160) seeds per patient. The mean D90 for CT-ISI was 134.5 ±7.5 Gy. Treatment intervention for eleven patients was performed using a 5-ml syringe as a guide during CT-ISI. There were no differences in total dose and number of implanted seeds between the two groups, but the number of punctures per lesion was lower in the syringe group than in the no-syringe group (1.9 ±0.5 vs. 2.9 ±0.6, p < 0.001), suggesting a higher puncture accuracy. The total number of SMTIL was 50 (median, 2; range, 1-10), and the median size was 1.9 cm (range, 0.8-2.4 cm). All SMTIL were well-controlled at 6-months follow-up (response rate [RR] = 100%). One patient in the no-syringe group experienced grade 2 chest tightness, chest pain, intraoperative needle tract bleeding, and post-operative blood in sputum. Conclusions Puncture with a 5-ml syringe as a guide during CT-ISI seems to be a more accurate option for patients with small (< 2.5 cm) lung metastasis.
Indoor Intelligent Fingerprint-Based Localization: Principles, Approaches and Challenges

With the rapid development of Internet of Things (IoT) technology, location-based services have been widely applied in the construction of smart cities. Satellite-based location services have been utilized in outdoor environments, but they are not suitable for indoor technology due to the absence of global positioning system (GPS) signal. Therefore, many indoor localization technologies and systems have emerged by utilizing many other signals. In particular, fingerprinting localization has recently garnered attention because its promising performance. In this work, we aim to study recent indoor localization technologies and systems based on various fingerprints, which use machine learning and intelligent algorithms. We also present the architecture of intelligent localization. The development of indoor localization technology should have the ability of self-adaptation and self-learning in the future. And the architecture shows how to make localization become more “smart” by advanced techniques. The state-of-the-art localization systems’ working principles are summarized and compared in terms of their localization accuracy, latency, energy consumption, complexity, and robustness. We also discuss the challenges of existing indoor localization technologies, potential solutions to these challenges, and possible improvement measures.
Multidrug Resistance Like Protein 1 Activity in Malpighian Tubules Regulates Lipid Homeostasis in Drosophila

Simple Summary Multidrug resistance proteins (MRPs) are important for ion transport, toxin/xenobiotic secretion, and signal transduction. Although studies have been undertaken to understand their physiological function, it is not fully known how MRPs may regulate metabolism. We knocked down the expression of Drosophila multidrug-resistance like protein 1 (MRP) in several tissues central to metabolic regulation. Reducing MRP in Malpighian tubules, the functional equivalent to the human kidney, was sufficient to disrupt metabolic homeostasis, owing to abnormal lipid accumulation, as well as changes in feeding behavior. It also increased oxidative stress resistance in adult flies, possibly due to reduced levels of reactive oxygen species. Abstract Multidrug resistance proteins (MRPs), members of the ATP-binding cassette transporter (ABC transporter) family, are pivotal for transporting endo- and xenobiotics, which confer resistance to anticancer agents and contribute to the clearance of oxidative products. However, their function in many biological processes is still unclear. We investigated the role of an evolutionarily conserved MRP in metabolic homeostasis by knocking down the expression of Drosophila multidrug-resistance like protein 1 (MRP) in several tissues involved in regulating metabolism, including the gut, fat body, and Malpighian tubules. Interestingly, only suppression of MRP in the Malpighian tubules, the functional equivalent to the human kidney, was sufficient to cause abnormal lipid accumulation and disrupt feeding behavior. Furthermore, reduced Malpighian tubule MRP expression resulted in increased Hr96 (homolog of human pregnane X receptor) expression. Hr96 is known to play a role in detoxification and lipid metabolism processes. Reduced expression of MRP in the Malpighian tubules also conveyed resistance to oxidative stress, as well as reduced normal levels of reactive oxygen species in adult flies. This study reveals that an evolutionarily conserved MRP is required in Drosophila Malpighian tubules for proper metabolic homeostasis.
Historical Methodology and Critical Thinking as Synergised Concepts

The post-truth era is plagued by numerous pseudoscientific theories and narratives that took root in various disciplines. History and historical knowledge belong to the enterprises abused today. The output of historical inquiry in a narrative form is often considered as a correct description of the real past from which we may draw normative conclusions about society. However, the endemic plurality of historical narratives and theories presents an opportunity for intentional misinterpretation. This paper aims to sketch a solution to this threatening situation with the help of contemporary philosophy of historiography. It is argued that it is necessary to move from historical narratives to the process of historical inquiry itself. The historiography developed over its existence many useful tools on how to guard itself against various logical fallacies, cognitive biases, and pseudoscientific methodology. The situation of a historian encountering contradictory sources about the same subject is strikingly similar to the situation of an inquisitive person confronted by pseudoscientific articles and fake news. The paper highlights a strong synergy between fully developed methods of scientific historiography and critical thinking that is considered as a possible cure to our current predicament. We should teach history as critical thinking, not as stories.
Learning in the Air: Secure Federated Learning for UAV-Assisted Crowdsensing

Unmanned aerial vehicles (UAVs) combined with artificial intelligence (AI) have opened a revolutionized way for mobile crowdsensing (MCS). Conventional AI models, built on aggregation of UAVs’ sensing data (typically contain private and sensitive user information), may arise severe privacy and data misuse concerns. Federated learning, as a promising distributed AI paradigm, has opened up possibilities for UAVs to collaboratively train a shared global model without revealing their local sensing data. However, there still exist potential security and privacy threats for UAV-assisted crowdsensing with federated learning due to vulnerability of central curator, unreliable contribution recording, and low-quality shared local models. In this paper, we propose SFAC, a secure federated learning framework for UAV-assisted MCS. Specifically, we first introduce a blockchain-based collaborative learning architecture for UAVs to securely exchange local model updates and verify contributions without the central curator. Then, by applying local differential privacy, we design a privacy-preserving algorithm to protect UAVs’ privacy of updated local models with desirable learning accuracy. Furthermore, a two-tier reinforcement learning-based incentive mechanism is exploited to promote UAVs’ high-quality model sharing when explicit knowledge of network parameters are not available in practice. Extensive simulations are conducted, and the results demonstrate that the proposed SFAC can effectively improve utilities for UAVs, promote high-quality model sharing, and ensure privacy protection in federated learning, compared with existing schemes.
DFIG Active Damping Control Strategy Based on Remodeling of Multiple Energy Branches

Concerning subsynchronous oscillation caused by the integration of doubly-fed induction generator (DFIG) to power grid via series compensation line, an active damping control strategy based on remodeling of multiple energy branches in DFIG is proposed. First, according to the flow path of oscillation components, energy branches in DFIG are divided. Second, potential energy and dissipation energy are defined characterizing accumulation and consumption of energy during oscillation. Then, by analyzing the contribution of energy branches to potential energy and dissipation energy, key energy branches affecting the stability of system are screened. On this basis, the relations among stator voltage, potential energy, and dissipation energy are established, and frequency-dependent energy compensation functions in key branches are derived. By assessing their impact on low voltage ride through (LVRT) performance of DFIG, the compensation branch compatible with DFIG fundamental frequency characteristics are screened. Then, take sub/supersynchronous frequency stability coefficient ratio as the objective function, and the requirement on stability in sub/supersynchronous frequency band as the constraints. The compensation branch parameter optimization scheme is established. Finally, a test system is built in RT-LAB for verification. Simulation results demonstrate that, the proposed strategy can realize active damping control in multiple oscillation cases, and guarantee the stability of system in full frequency band. Besides, the strategy does not affect LVRT performance of DFIG and is well compatible with DFIG fundamental frequency characteristics.
Hardware-Efficient Emulation of Leaky Integrate-and-Fire Model Using Template-Scaling-Based Exponential Function Approximation

We present a method to emulate a leaky integrate-and-fire (LIF) model in a field-programmable gate array (FPGA) in a hardware-efficient manner. The simplified spike-response model (SRM<sub>0</sub>) is chosen as an LIF model. For the hardware-efficient implementation of SRM<sub>0</sub>, we adopt the template-scaling-based exponential function approximation (TS-EFA). This method allows high precision and low latency exponential function approximations with the efficient use of hardware resources. We subsequently propose an algorithm for SRM<sub>0</sub>, which leverages the advantage of TS-EFA. An implementation of 512 neurons conforming to SRM<sub>0</sub> in an FPGA highlights (i) high precision of SRM<sub>0</sub> emulation (mean squared error of membrane potential approximation: <inline-formula> <tex-math notation="LaTeX">$4\times 10^{-12} - 1\times 10^{-10}$ </tex-math></inline-formula>), (ii) low latency (eight clock cycles), and (iii) high efficiency in hardware usage (only 125b memory per neuron).
Neuroblast-specific chromatin landscapes allow integration of spatial and temporal cues to generate neuronal diversity in Drosophila

During early neurogenesis in flies and mice, spatial and temporal cues interact to specify neuronal diversity, yet in no organism is it known how spatial and temporal cues are integrated. We used Targeted DamID (TaDa) to identify the genomic binding sites of the temporal transcription factor Hunchback in two adjacent Drosophila neuroblasts (NB5-6 and NB7-4). Hunchback targets were different in each neuroblast. Profiling chromatin accessibility showed that each neuroblast had a distinct chromatin landscape: Hunchback-bound loci in NB5-6 were in open chromatin, but the same loci in NB7-4 were in closed chromatin. Moreover, binding of the spatial factor Gsb/Pax3, essential for NB5-6 specification, was correlated with open chromatin and Hunchback-enriched loci in NB5-6, but not NB7-4. We propose early-acting spatial factors establish a unique chromatin landscape in each neuroblast, thereby restricting temporal factor binding to different loci in each neuroblast, resulting in different neurons in each neuroblast lineage. Impact statement Integration of spatial and temporal identity during Drosophila neurogenesis is due to spatial factors generating neuroblast-specific chromatin thereby biasing subsequent temporal transcription factor binding and producing neuroblast-specific neurons.
Mitigatory Effects of Quercetin on Bisphenol A-Induced Oxidative Stress in Testis of Swiss Albino Mice

Background: Bisphenol A is a well-known xenoestrogen, mainly used in plastics and food can liners manufacture. Hence, it becomes an integral part of the food chain. Experimental studies shows negative health effects. Quercetin is one of the most effective antioxidants of the flavonoids, generally present in food stuff. The present study was an attempt to assess the mitigatory effects of quer on BPA–induced reduction in fertility of mice. Materials and methods: Inbred male Swiss strain albino mice were orally administered with various doses of BPA for 45 days. In another experiment quer along with high dose of BPA was administered to study the mitigatory consequence. Result: Administration of BPA caused significant (P<0.05) and dose-dependent increase in oxidative stress compared to control groups. Administration of quer along with high dose of BPA caused amelioration in enzymatic and non-enzymatic antioxidant. Histopathological alteration was also seen in BPA treated groups, which were ameliorated on administration of quer. Conclusion: Quer is potent enough to mitigate the toxic effect of BPA. Biochemical alteration was mitigated by quer and dose dependent increase in fertility was observed.
BEHST: genomic set enrichment analysis enhanced through integration of chromatin long-range interactions

Transforming data from genome-scale assays into knowledge of affected molecular functions and pathways is a key challenge in biomedical research. Using vocabularies of functional terms and databases annotating genes with these terms, pathway enrichment methods can identify terms enriched in a gene list. With data that can refer to intergenic regions, however, one must first connect the regions to the terms, which are usually annotated only to genes. To make these connections, existing pathway enrichment approaches apply unwarranted assumptions such as annotating non-coding regions with the terms from adjacent genes. We developed a computational method that instead links genomic regions to annotations using data on long-range chromatin interactions. Our method, Biological Enrichment of Hidden Sequence Targets (BEHST), finds Gene Ontology (GO) terms enriched in genomic regions more precisely and accurately than existing methods. We demonstrate BEHST’s ability to retrieve more pertinent and less ambiguous GO terms associated with results of in vivo mouse enhancer screens or enhancer RNA assays for multiple tissue types. BEHST will accelerate the discovery of affected pathways mediated through long-range interactions that explain non-coding hits in genome-wide association study (GWAS) or genome editing screens. BEHST is free software with a command-line interface for Linux or macOS and a web interface (http://behst.hoffmanlab.org/).
Vibrating FRET-Based Nanomechanical Sensor Preparation and Characterization for Environmental Monitoring Applications

In this study, the recently introduced graphene nanomechanical sensor design based on the vibrating Förster resonance energy transfer (VFRET) was experimentally demonstrated for the first time. VFRET was realized by the dynamic FRET between quantum dots on vibrating graphene layers. Graphene nanomechanical membranes were fabricated and experimentally analyzed with quantum dots donor and acceptor material loads. The loaded membranes were paired in the VFRET based sensor device structure. The FRET and the VFRET tests were applied to the prepared devices, experimental challenges and the device development solutions were utilized. Novel technology and the future applications of the VFRET based sensor examples were discussed with the advanced capabilities of sensing nano- and micro-scale particles around the device for the real-time point-of-care (PoC), and the environmental monitoring applications include imaging, monitoring and tracking of intra- or inter- cellular mechanical processes as the nanophotonic applications by exploiting the VFRET based nanoscale sensor design.