Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of a Grid-Connected Solar System for Borehole Pumps

This paper present grid-connected Solar System to energize 3-phase borehole motors, the solar system will be the primary source of energy and the local electricity network will be used as back-up during the day night unfavorable weather conditions (cloudy or rainy days). The design solar energy system will supply the borehole motors with energy harnessed from the sun. The borehole motors that are to be supplied only operate during the day, hence this solution aims to take advantage of this by harnessing energy from the sun to run the motors. The process of converting DC electrical energy into AC electrical energy to be used by the load; will be managed by SMA inverters that will ensure that supply to the motors is as good as the one supplied by the utility grid.
A Review of GPS Trajectories Classification Based on Transportation Mode

GPS trajectories generated by moving objects provide researchers with an excellent resource for revealing patterns of human activities. Relevant research based on GPS trajectories includes the fields of location-based services, transportation science, and urban studies among others. Research relating to how to obtain GPS data (e.g., GPS data acquisition, GPS data processing) is receiving significant attention because of the availability of GPS data collecting platforms. One such problem is the GPS data classification based on transportation mode. The challenge of classifying trajectories by transportation mode has approached detecting different modes of movement through the application of several strategies. From a GPS data acquisition point of view, this paper macroscopically classifies the transportation mode of GPS data into single-mode and mixed-mode. That means GPS trajectories collected based on one type of transportation mode are regarded as single-mode data; otherwise it is considered as mixed-mode data. The one big difference of classification strategy between single-mode and mixed-mode GPS data is whether we need to recognize the transition points or activity episodes first. Based on this, we systematically review existing classification methods for single-mode and mixed-mode GPS data and introduce the contributions of these methods as well as discuss their unresolved issues to provide directions for future studies in this field. Based on this review and the transportation application at hand, researchers can select the most appropriate method and endeavor to improve them.
Room temperature long-range coherent exciton polariton condensate flow in lead halide perovskites

Long-range coherent polariton condensate flow is observed in all-inorganic perovskite microcavities. Novel technological applications significantly favor alternatives to electrons toward constructing low power–consuming, high-speed all-optical integrated optoelectronic devices. Polariton condensates, exhibiting high-speed coherent propagation and spin-based behavior, attract considerable interest for implementing the basic elements of integrated optoelectronic devices: switching, transport, and logic. However, the implementation of this coherent polariton condensate flow is typically limited to cryogenic temperatures, constrained by small exciton binding energy in most semiconductor microcavities. Here, we demonstrate the capability of long-range nonresonantly excited polariton condensate flow at room temperature in a one-dimensional all-inorganic cesium lead bromide (CsPbBr3) perovskite microwire microcavity. The polariton condensate exhibits high-speed propagation over macroscopic distances of 60 μm while still preserving the long-range off-diagonal order. Our findings pave the way for using coherent polariton condensate flow for all-optical integrated logic circuits and polaritonic devices operating at room temperature.
Few-shot learning with attention-based sequence-to-sequence models

End-to-end approaches have recently become popular as a means of simplifying the training and deployment of speech recognition systems. However, they often require large amounts of data to perform well on large vocabulary tasks. With the aim of making end-to-end approaches usable by a broader range of researchers, we explore the potential to use end-to-end methods in small vocabulary contexts where smaller datasets may be used. A significant drawback of small-vocabulary systems is the difficulty of expanding the vocabulary beyond the original training samples -- therefore we also study strategies to extend the vocabulary with only few examples per new class (few-shot learning). Our results show that an attention-based encoder-decoder can be competitive against a strong baseline on a small vocabulary keyword classification task, reaching 97.5% of accuracy on Tensorflow's Speech Commands dataset. It also shows promising results on the few-shot learning problem where a simple strategy achieved 68.8\% of accuracy on new keywords with only 10 examples for each new class. This score goes up to 88.4\% with a larger set of 100 examples.
Synergistic antitumor effect of the combination of a dual cancer-specific oncolytic adenovirus and cisplatin on lung cancer cells

The effect of the combination of a recombinant adenovirus (ATV) expressing a specific apoptin protein and cisplatin on human lung cancer cells (A549 cells) was determined. The inhibitory effects of ATV and cisplatin, ATV alone, or cisplatin alone on the migration and invasion of A549 cells were evaluated in vitro using cell proliferation, wound healing, Transwell migration and Matrigel invasion assays. The tumor inhibition effect on A549 cells in vivo was assessed by observing the tumor growth and survival rate of nude mice with subcutaneous tumor xenografts grown from implanted A549 cells after treatment with ATV, cisplatin, or ATV combined with cisplatin. The proliferation (P<0.01), migration (P<0.01), and invasion (P<0.01) on A549 cells was suppressed significantly by ATV, cisplatin, and ATV and cisplatin, in a dose- and time-dependent manner. The inhibition of tumor growth in transplanted nude mice in the ATV combined with cisplatin group was significantly higher than that displayed in the other groups, and the survival rate of the combined treatment group was significantly higher than that of the group treated with cisplatin alone. The results indicated that the combined application of ATV and cisplatin could reduce toxicity and showed a synergistic effect in reducing tumor growth and increasing survival. Thus, there is a potential research value in treating tumors using the combination of ATV and cisplatin, which provides a foundation for future preclinical studies on this antitumor treatment.
Different weight shift trainings can improve the balance performance of patients with a chronic stroke

Background: Improving balance ability, increasing walking ability, and reducing the occurrence of falls are important objectives in the rehabilitation of stroke patients. Do the posture balance training and the intervention of lateral wedge insoles to improve of balance function and increase walking ability in patients with a chronic stroke? Methods: A randomized, controlled trial with concealed allocation, intention-to-treat analysis, and blinded assessors. Participants who had a chronic stroke (onset >6 months) were recruited from the rehabilitation and neurology departments of a hospital in central Taiwan. Subjects were divided into 3 groups: a visual biofeedback balance training group, a lateral wedge group, and a control group; apart from their usual rehabilitation program, and both experimental groups received a 6-week training session program. The primary outcome was the balance computerized adaptive test (balance CAT), and secondary outcome was timed up and go (TUG) test. All subjects were evaluated at the baseline, posttraining (6-week), 1st follow-up (10-week), and 2nd follow-up (18-week). Results: A total of 56 subjects were participated in this study, including 38 males and 18 females. The mean age of the subjects was 59.1 years old, and the mean time was 43.7 months after the onset of the stroke. This study found the interaction in groups and measurement time points reached statistical significance of the balance CAT and TUG test (F = 5.740, P < .001; F = 2.926, P = .011; respectively). In addition, the performance of both the visual biofeedback training and lateral wedge group was superior to that of the control group. Conclusion: Six-week visual biofeedback training and intervention of 5° lateral wedge insoles can improve the balance ability of patients with a chronic stroke. Trial registry: http://www.chictr. org.cn, ChiCTR-IPR-15007092.
Berberine Combined with Triple Therapy versus Triple Therapy for Helicobacter pylori Eradication: A Meta-Analysis of Randomized Controlled Trials

Objective To assess the effects and safety of berberine combined with triple therapy on Helicobacter pylori (H. pylori) eradication in adults. Methods PubMed, MEDLINE, EMBASE, Cochrane Library, and Chinese databases including China National Knowledge Infrastructure (CNKI), Wanfang data, Chinese Technology Journal Full-text Database (VIP), and China biomedical literature database (CBM) were searched to obtain the eligible studies published up to October 10, 2017. The primary outcome was eradication rate of H. pylori. The secondary outcome was incidence of adverse effects. Data analysis was conducted by RevMan5.2 and Stata V.9. 0 software. Trial sequential analysis (TSA) was performed to assess the risk of random error and the validity of conclusion with TSA program version 0.9 beta. Results The meta-analysis results indicated berberine combined with triple therapy could improve the eradication rates of H. pylori (urea breath test subgroup: RR=1.18, 95%CI=(1.12,1.24), P < 0.00001, biopsy subgroup: RR=1.23, 95%CI=(1.13,1.34), P < 0.00001) and reduce the total occurrence of adverse effects (OR=0.59, 95%CI(0.46, 0.75), P < 0.0001) when compared with only using triple therapy. Besides, the incidence of nausea (OR=0.59, 95%CI(0.41, 0.86), P < 0.05) and diarrhea (OR=0.41, 95%CI(0.24, 0.71) was remarkably lower in experimental group while that of abdominal distention (OR=0.64, 95%CI(0.40,1.04), P > 0.05) and vomiting (OR=0.65, 95%CI(0.37, 1.15), P > 0.05) had no significant change. TSA of H. pylori eradication rates and adverse effects incidence illustrated that the cumulative value of Z-curve went across the conventional boundary value, trial sequential monitoring boundary for benefit, and required information size, suggesting the results were stable. Conclusion Evidence from meta-analysis suggested that berberine combined with triple therapy can be an option for increasing H. pylori eradication rates and reducing overall therapy-related adverse effects incidence, particularly nausea and diarrhea, whereas more randomized controlled trials designed according to CONSORT statement are demanded to support the efficacy in further studies.
Novel Factor XIII variant identified through whole-genome sequencing in a child with intracranial hemorrhage

Pediatric stroke can be either hemorrhagic or ischemic, with ∼5% of hemorrhagic strokes being caused by genetic coagulopathies. We report an 8 mo old presenting with a hemorrhagic stroke caused by severe Factor XIII deficiency (OMIM # 613225) in whom rapid whole-genome sequencing identified a novel variant in the F13A1 gene c. 1352_1353delAT (p.His451ArgfsTer29).
A wood-warbler produced through both interspecific and intergeneric hybridization

Hybridization between divergent taxa can provide insight into the breakdown of characters used in mate choice, as well as reproductive compatibility across deep evolutionary timescales. Hybridization can also occur more frequently in declining populations, as there is a smaller pool of conspecific mates from which to choose. Here, we report an unusual combination of factors that has resulted in a rare, three-species hybridization event among two genera of warblers, one of which is experiencing significant population declines. We use bioacoustic, morphometric and genetic data, to demonstrate that an early generation female hybrid between a golden-winged warbler (Vermivora chrysoptera) and a blue-winged warbler (V. cyanoptera) went on to mate and successfully reproduce with a chestnut-sided warbler (Setophaga pensylvanica). We studied the product of this event—a putative chrysoptera × cyanoptera × pensylvanica hybrid—and show that this male offspring sang songs like S. pensylvanica, but had morphometric traits similar to Vermivora warblers. The hybrid's maternal parent had V. chrysoptera mitochondrial DNA and, with six plumage-associated loci, we predicted the maternal parent's phenotype to show that it was likely an early generation Vermivora hybrid. That this hybridization event occurred within a population of Vermivora warblers in significant decline suggests that females may be making the best of a bad situation, and that wood-warblers in general have remained genetically compatible long after they evolved major phenotypic differences.
Multidimensional Balance-Based Cluster Boundary Detection for High-Dimensional Data

The balance of neighborhood space around a central point is an important concept in cluster analysis. It can be used to effectively detect cluster boundary objects. The existing neighborhood analysis methods focus on the distribution of data, i.e., analyzing the characteristic of the neighborhood space from a single perspective, and could not obtain rich data characteristics. In this paper, we analyze the high-dimensional neighborhood space from multiple perspectives. By simulating each dimension of a data point’s <inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> nearest neighbors space (<inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula>NNs) as a lever, we apply the lever principle to compute the balance fulcrum of each dimension after proving its inevitability and uniqueness. Then, we model the distance between the projected coordinate of the data point and the balance fulcrum on each dimension and construct the <inline-formula> <tex-math notation="LaTeX">$DHBlan$ </tex-math></inline-formula> coefficient to measure the balance of the neighborhood space. Based on this theoretical model, we propose a simple yet effective cluster boundary detection algorithm called Lever. Experiments on both low- and high-dimensional data sets validate the effectiveness and efficiency of our proposed algorithm.
Bootstrapped Rectifier–Antenna Co-Integration for Increased Sensitivity in Wirelessly- Powered Sensors

This paper addresses the challenge of increasing the sensitivity of wireless powering approaches to achieve targeted output voltage for wirelessly-powered sensors with the compact area. The design exploits a bootstrapping approach where the rectifier first stage and the antenna are reused to increase the rectifier output voltage following an initial charging phase. Area-constrained rectifier–antenna co-optimization results in a compact high-<inline-formula> <tex-math notation="LaTeX">$Q~2.4$ </tex-math></inline-formula>-GHz antenna with 1.2-cm<sup>2</sup> area which is then used in two topologies [cross-coupled (CC) and cross-coupled pMOS (CP)] based on the proposed bootstrapping concept. Both topologies increase the rectifier output voltage with no additional off-chip inductors or capacitors. The CC/CP topologies and the associated logic are integrated into a 65-nm CMOS with the IC occupying 1.1 mm<sup>2</sup> of the area. The CC topology achieves input sensitivity of −34.5 dBm for 1.6-V output voltage with <inline-formula> <tex-math notation="LaTeX">$R_{\mathrm{ LOAD}}$ </tex-math></inline-formula> of 1.8 <inline-formula> <tex-math notation="LaTeX">$\text{M}\Omega $ </tex-math></inline-formula>, while the CP topology achieves −26.5-dBm input sensitivity with the 2.5-V output voltage and <inline-formula> <tex-math notation="LaTeX">$R_{\mathrm{ LOAD}}$ </tex-math></inline-formula> of 250 <inline-formula> <tex-math notation="LaTeX">$\text{k}\Omega $ </tex-math></inline-formula>. These results confirm more than <inline-formula> <tex-math notation="LaTeX">$2\times $ </tex-math></inline-formula> longer distance for wirelessly powering sensors compared to state of the art, with only 1.2 cm<sup>2</sup> of the rectifier–antenna area.
Identification of Six Potentially Long Noncoding RNAs as Biomarkers Involved Competitive Endogenous RNA in Clear Cell Renal Cell Carcinoma

Background. Clear cell renal cell carcinoma (ccRCC), the most common subtype of renal cell carcinoma (RCC), usually is representative of metastatic heterogeneous neoplasm that links with poor prognosis, but the pathogenesis of ccRCC remains unclear. Currently, numerous evidences prove that long noncoding RNAs (lncRNAs) are considered as competing endogenous RNA (ceRNA) to participate in cellular processes of tumors. Therefore, to investigate the underlying mechanisms of ccRCC, the expression profiles of lncRNAs, miRNAs, and mRNAs were downloaded from the Cancer Genome Atlas (TCGA) database. A total of 1526 differentially expressed lncRNAs (DElncRNAs), 54 DEmiRNAs, and 2352 DEmRNAs were identified. To determine the connection of them, all DElncRNAs were input to the miRcode database. The results indicated that 85 DElncRNAs could connect with 9 DEmiRNAs in relation to our study. Then, databases of TargetScan and miRDB were used to search for targeted genes with reference to DEmiRNAs. The results showed that 203 out of 2352 targeted genes were identified in our TCGA set. Subsequently, ceRNA network was constructed according to Cytoscape and the targeted genes were functionally analyzed to elucidate the mechanisms of DEmRNAs. The results of survival analysis and regression analysis indicated that 6 DElncRNAs named COL18A1-AS1, WT1-AS, LINC00443, TCL6, AL356356.1, and SLC25A5-AS1 were significantly correlative with the clinical traits of ccRCC patients and could be served as predictors for ccRCC. Finally, these findings were validated by quantitative RT-PCR (qRT-PCR). Based on these discoveries, we believe that this identified ceRNA network will provide a novel perspective to elucidate ccRCC pathogenesis.
Delay Guaranteed Network Association for Mobile Machines in Heterogeneous Cloud Radio Access Network

In the heterogeneous cloud radio access network (H-CRAN), which consists of multiple access points (APs) providing smaller coverage and a high power node (HPN) providing ubiquitous coverage, the mobile machines can connect to multiple APs and HPN by coordinated multi-point transmission (CoMP) concurrently to achieve ultra-reliable and low-latency communication. However, the current network association (or priorly known as handovers), which only focuses on switching between two base stations, may not be an efficient scheme in H-CRAN. In this paper, we innovate a proactive network association mechanism by taking CoMP into consideration under the H-CRAN architecture. We consider two scenarios under the H-CRAN architecture: with and without the assistance of HPN in the network. By regarding APs/HPN in H-CRAN as resources that allocated to mobile machines, a novel proactive network association concept is proposed, and then generalized from one-to-one to multiple-to-multiple case. With the assistance of Lyapunov optimization theory, effective bandwidth, and capacity theory, we can prove that this proactive network association scheme can guarantee that the queueing delay performance and the delay violation probability can be both smaller than a corresponding upper bound. That is, both low-latency and ultra-reliable communication can be guaranteed. We also conduct experiments by using real trace from taxis movement data to verify the analytical results. Our results suggest the guidelines to design the proactive network association scheme in H-CRAN.
ANFIS Damping Controller Design for SSSC to Improve Dynamic Stability of a Grid Connected Wind Power Systems

Adaptive Neural Fuzzy Inference System (ANFIS) is an adaptation and robustness method as it is the combination between the advantages of Artificial Neural Network (ANN) and Fuzzy Logic (FL). Besides, it is also a non-linear controller that can face the different operating points of the system. This paper shows the simulation results of using a Static Synchronous Series Compensator (SSSC) to achieve damping improvement of a grid connected Wind Power (WP) to a multi-machine system was presented. A time-domain scheme based on a nonlinear system model is subject to a three-phase short-circuit fault at the connected bus is utilized to test the effectiveness of the proposed controller. It can be concluded from the simulation results that the proposed SSSC combined to the designed ANFIS damping controller can improve the stability of the studied system under many fault conditions.
The Hard-CoRe Coreference Corpus: Removing Gender and Number Cues for Difficult Pronominal Anaphora Resolution

We introduce a new benchmark task for coreference resolution, Hard-CoRe, that targets common-sense reasoning and world knowledge. Previous coreference resolution tasks have been overly vulnerable to systems that simply exploit the number and gender of the antecedents, or have been handcrafted and do not reflect the diversity of sentences in naturally occurring text. With these limitations in mind, we present a resolution task that is both challenging and realistic. We demonstrate that various coreference systems, whether rule-based, feature-rich, graphical, or neural-based, perform at random or slightly above-random on the task, whereas human performance is very strong with high inter-annotator agreement. To explain this performance gap, we show empirically that state-of-the art models often fail to capture context and rely only on the antecedents to make a decision.
A Framework for Semantic based Image Retrieval from Cyberspace by mapping low level features with high level semantics.

Today, the development is going fast towards data analysis in every field of research. It makes image retrieval system a hot topic regarding the design and implementation of CBIR. The previous research has been focused on image-size based approaches that methods are not intelligent or convenient for accurate retrieval of image from the cyberspace. In order to retrieve an accurate and desired image from a large-scale image database of cyberspace in less time-consumption, we propose an algorithm based on the low level feature and high level semantics of image in this paper. We present a framework, that extract low level features of the image. Its goal is to explicitly extract the basic information content of the image as far as possible. Local statistics of the image function is captured for extracting the LLF. For extracting the features of the image, a framework has been proposed and advance algorithm has been used to achieve the desired goal.