Miracle-dz/UniFAR-FTUs huggingface dataset:
A verifiable hidden policy CP‐ABE with decryption testing scheme and its application in VANET

As a new kind of cryptographic primitive, attribute‐based encryption (ABE) is widely used in various complex scenarios because it has the characteristic of access control while encrypting messages. However, the existing ciphertext policy ABE (CP‐ABE) encryption schemes have some inherent defects, such as the lack of privacy‐preserving and inefficient decryption. These weak points make them difficult to play a role in scenarios with high real‐time and high data confidentiality requirements, for example, vehicle ad hoc network (VANET). Therefore, we proposed a verifiable hidden policy CP‐ABE with decryption testing scheme (or VHPDT, for short). It has the following features: hidden policy to privacy‐preserving and outsourced decryption testing can verify the correctness of the decrypted result. Furthermore, we apply it into VANET.
Components Sharing Based Integrated HVDC Circuit Breaker for Meshed HVDC Grids

DC fault isolation is one of the main challenges of the HVDC grid. DC fault current can be interrupted within several milliseconds by employing hybrid HVDC circuit breaker. However, this scheme is not cost-effective, especially in meshed HVDC grid. In this paper, a novel integrated HVDC circuit breaker by sharing components is proposed to overcome these drawbacks. Suppose that a converter in a meshed HVDC grid is connected to m DC lines. The integrated HVDC circuit breaker consists of m + 1 ultra-fast disconnectors (UFDs), m + 1 load commutation switches (LCSs), m + 1 mechanical disconnectors (DSs), and only one main breaker (MB) and surge arrester (SA). The behavior of the proposed integrated HVDC circuit breaker is similar to that of the conventional hybrid HVDC circuit breaker. These two kinds of breakers have the same operating time, which means the integrated HVDC circuit breaker is fast enough to clear DC faults. Besides, the IGBT modules in the MB and LCSs of the proposed integrated HVDC circuit breaker are connected in one direction, and the m DC lines share a single MB. Therefore, this scheme is more cost-effective compared to the conventional hybrid HVDC circuit breaker. Moreover, the adjacent lines can still be used to transmit power after DC bus faults. Simulation results on a three-terminal HVDC grid are presented to verify the effectiveness and feasibility of the proposed scheme.
Comparison of throat swabs and sputum specimens for viral nucleic acid detection in 52 cases of novel coronavirus (SARS-Cov-2)-infected pneumonia (COVID-19)

Abstract Objectives In December 2019, a novel coronavirus (SARS-CoV-2)-infected pneumonia (COVID-19) occurred in Wuhan, China. Laboratory-based diagnostic tests utilized real-time reverse transcriptase polymerase chain reaction (RT-PCR) on throat samples. This study evaluated the diagnostic value to analyzing throat and sputum samples in order to improve accuracy and detection efficiency. Methods Paired specimens of throat swabs and sputum were obtained from 54 cases, and RNA was extracted and tested for 2019-nCoV (equated with SARS-CoV-2) by the RT-PCR assay. Results The positive rates of 2019-nCoV from sputum specimens and throat swabs were 76.9% and 44.2%, respectively. Sputum specimens showed a significantly higher positive rate than throat swabs in detecting viral nucleic acid using the RT-PCR assay (p = 0.001). Conclusions The detection rates of 2019-nCoV from sputum specimens were significantly higher than those from throat swabs. We suggest that sputum would benefit for the detection of 2019-nCoV in patients who produce sputum. The results can facilitate the selection of specimens and increase the accuracy of diagnosis.
Characterization of the complete chloroplast genome of Viburnum schensianum (Adoxaceae)

Abstract The whole chloroplast (cp) genome sequence of Viburnum schensianum has been characterized from Illumina pair-end sequencing. The complete cp genome was 158,408 bp in length, containing a large single copy region (LSC) of 86,998 bp and a small single copy region (SSC) of 18,386 bp, which were separated by a pair of inverted repeat (IR) regions of 26,512 bp. The genome contained 130 genes, including 84 protein-coding genes, 37 tRNA genes, eight ribosomal RNA genes (four rRNA species), and a pseudogene. Most genes occur as a single copy, whereas 16 gene species are duplicated. Phylogenetic analysis revealed that V. schensianum is closely related to the species of V. utile.
A Semantic Enhanced Topic Model Based on Bi-directional LSTM Networks

Topic modeling techniques are widely used for text modeling and analysis. However, they suffer from the sparseness problem and the complex inference process, which can be alleviated by deep learning techniques such as bi-directional long short-term memory (LSTM) networks. To explore the combination of topic modeling and bi-directional LSTM, we propose a new probabilistic topic model, named GPU-LDA-LSTM. Differently from existing approaches, we first design a document semantic coding framework based on bi-directional LSTM (DSC-LSTM) to learn the representation of documents. Then, we utilize the document-topic and word-word dual-generalized Polya urn (GPU) mechanism to enhance semantics. Furthermore, a LSTM network is also used to improve the contextual consistency in the parameter inference process. Experimental results on two real-world datasets show that our model significantly outperforms state-of-the-art models on several evaluation metrics, suggesting that it can extract more meaningful topics.
Contour-constrained Specular Highlight Detection from Real-world Images

Specular highlight detection is a fundamental research topic in computer graphics and computer vision. In this paper, we present a new full-scale deep supervision model to detect specular highlights from single real-world images. The core of our approach is a novel self-attention module to improve the detection accuracy of the network. We also introduce a refinement strategy with a new loss function for highlight detection task by generating contour maps from the highlight detection masks. Experiments on a public dataset demonstrate that our approach outperforms state-of-the-art methods for highlight detection.
Direct Synthesis and Design of Dispersive Waveguide Bandpass Filters

In this article, a direct synthesis and dimensional design method for narrowband waveguide bandpass filters with a general dispersive coupling element is proposed. Comparing with the dispersion-less filter synthesis approaches, the general dispersive coupling matrix (DCM) that incorporates unique dispersive characteristics of a physical realization is introduced to provide an accurate description of the filter to be designed. Moreover, the DCM can describe not only strong dispersive coupling elements for realizing transmission zeros (TZs), but also dispersive resonators. A DCM consists of a frequency-invariant part and a dispersive part. For a given dispersive part, by iteratively remedying the characteristic polynomials, the frequency-invariant part for an equal-ripple response can be directly obtained. Consequently, according to the synthesized frequency-invariant coupling matrix, the filter dimensions can be designed only by electromagnetic (EM) simulation of each individual coupling element at the center frequency. Two design examples are presented, including a four-pole filter with two TZs and an eight-pole filter with four TZs. The examples are validated either by hardware prototyping or by EM simulation, demonstrating the effectiveness, accuracy, and generality of the proposed synthesis and design framework.
Parallel Algorithms for Masked Sparse Matrix-Matrix Products

Computing the product of two sparse matrices (SpGEMM) is a fundamental operation in various combinatorial and graph algorithms as well as various bioinformatics and data analytics applications for computing inner-product similarities. For an important class of algorithms, only a subset of the output entries are needed, and the resulting operation is known as Masked SpGEMM since a subset of the output entries is considered to be “masked out”. Existing algorithms for Masked SpGEMM usually do not consider mask as part of multiplication and either first compute a regular SpGEMM followed by masking, or perform a sparse inner product only for output elements that are not masked out. In this work, we investigate various novel algorithms and data structures for this rather challenging and important computation, and provide guidelines on how to design a fast Masked-SpGEMM for shared-memory architectures. Our evaluations show that factors such as matrix and mask density, mask structure and cache behavior play a vital role in attaining high performance for Masked SpGEMM. We evaluate our algorithms on a large number of real-world and synthetic matrices using several real-world benchmarks and show that our algorithms in most cases significantly outperform the state of the art for Masked SpGEMM implementations.
Decentralized fault detection in building services by means of tensor decomposed qualitative models

Fault detection and diagnosis (FDD) methods are most of the time deployed in buildings as supervisory solutions on a management level or as cloud computing solution. The deployment of Internet of Things devices will enable to embed FDD methods as edge-computing solutions directly on subsystems like heat pumps or air handling units. This paper shows how qualitative models can be used for fault detection in building services and how tensor decomposition methods can enable their integration on decentralized subsystems as edge-computing solution.
Responses of Two Soybean Cultivars on Growth and Development in Two Different Light Intensities

Soybean is an important economic plant that prefers full sunlight and performs poor under shaded conditions that affect the reproductive phase of some soybean cultivars. The study aimed to find the interaction of soybean cultivars by comparing morphological, anatomical and physiological characters of two soybean cultivars on acidic soils under shaded and non-shaded conditions under West Java rainforest conditions to select against shade tolerance. The experiment was arranged in a split-plot design with two factors and used three replications. The main factor was the intensity of light (without and with 55% shading). The subfactor was soybean cultivars (Godek and Ceneng). The results showed positive effects of 55% shading on yield and yield components compared to those plants grown without shading. The 55% shaded plants had good growth with a large number of branches, leaf area index, leaf length, leaf width, and highest water content while non-shaded plants failed to grow properly with lower flowering, ratio of chlorophyll a/b, the number of root nodules and the sugar contents. The shaded plants also had the highest number of pods and pod weights after 8 weeks after sowing (WAS). It is concluded that high acidic Ultisol soil type can be managed to produce economic yields of soybean at pH of 4.8 which is below the recommended soil acidity under low shading conditions.
Preliminary phytochemical and anti-diabetic activity of Cassia sophera Linn

The medicinal plant Cassia sophera was analysed for screening of phytochemical and anti-diabetic activity. The objective of the present study was to investigate anti-diabetic activity of Cassia sophera bark, using Streptozocin induced diabetic rats as model. The biochemical study was carried out and the results shown that ethanolic extract of dose 400 mg/Kg has more effective against Streptozocin induced diabetic rats. We conclude from the present study that the ethanolic extract of bark of Cassia sophera may be beneficial in the management of diabetes.
A review of applications of visual inspection technology based on image processing in the railway industry

In order to ensure the safety of railway transportation, it is necessary to regularly check for faults and defects in the railway system. Visual inspection technology is conducive to improving the low efficiency, poor economy and inaccurate detection results of traditional detection methods. This paper introduces the research and contribution of various scholars in the field of visual inspection, summarizes the application and development of visual inspection technology in the railway industry, and finally forecasts the future research direction of visual inspection technology.
Mild Stage 1 post-operative acute kidney injury: association with chronic kidney disease and long-term survival

Abstract Background Mild cases of acute kidney injury (AKI) are identified by a small rise in serum creatinine (SCr) according to the KDIGO AKI definition. The aim of this study was to examine the long-term outcomes of individuals with mild AKI. Methods. This was a retrospective cohort study of all adult patients who underwent abdominal, cardiothoracic, vascular or orthopaedic surgery at Landspitali–The National University Hospital of Iceland in 1998–2015. Incident chronic kidney disease (CKD), progression of pre-existing CKD and long-term survival were compared between patients with mild Stage 1 AKI (defined as a rise in SCr of ≥26.5 μmol/L within 48 h post-operatively without reaching 1.5× baseline SCr within 7 days), and a propensity score-matched control group without AKI stratified by the presence of CKD. Results Pre- and post-operative SCr values were available for 47 333 (42%) surgeries. Of those, 1161 (2.4%) had mild Stage 1 AKI and 2355 (5%) more severe forms of AKI. Mild Stage 1 AKI was associated with both incident CKD and progression of pre-existing CKD (P < 0.001). After exclusion of post-operative deaths within 30 days, mild Stage 1 AKI was not associated with worse 1-year survival in patients with preserved kidney function (94% versus 94%, P = 0.660), and same was true for patients with pre-operative CKD (83% versus 82%, P = 0.870) compared with their matched individuals. Conclusions. Mild Stage 1 AKI is associated with development and progression of CKD, but not with inferior 1-year survival. These findings support the inclusion of a small absolute increase in SCr in the definition of AKI.
DENGUE FEVER: A TRIGGERING FACTOR FOR IMMUNE THROMBOCYTOPENIC PURPURA IN ADULT FEMALE- A RARE CASE REPORT

Immune thrombocytopenic purpura (ITP) can be both primary and secondary. The secondary form of this disease may occur in association with systemic lupus erythematosus, antiphospholipid antibody syndrome, immunodeficient states, lymphoproliferative disorders, viral infections and using drugs such as quinidine, sulfa and heparin.
Non-linear behavior of flexoelectricity

Coupling between polarization and the strain gradient, namely, flexoelectricity, is a universal phenomenon that widely exists in all solid dielectrics and polymers. At a low level of the applied strain gradient, this electromechanical coupling is strictly a linear effect. In this Letter, a strong nonlinearity between the polarization and the strain gradient was experimentally found in polyvinylidene fluoride when the strain gradient was higher than a material-dependent threshold value. Such nonlinear behavior was in good accordance with an ion chain theory and could be fitted by a nonlinear equation. The observed flexoelectric nonlinearity in this work will help in the understanding of the discrepancy between the previous findings about the bulk materials and their nanoscale counterparts.
Interplay between topography, fog and vegetation in the central South Arabian mountains revealed using a novel Landsat fog detection technique

In the central South Arabian mountains of Yemen and Oman, monsoon fog interception by the endemic cloud forest is essential for ecosystem functions and services. Yet, we know little about the local factors affecting fog distributions and their cumulative effects on vegetation. To examine these relationships, we developed a novel method of high‐resolution fog detection using Landsat data, and validated the results using occurrence records of eight moisture‐sensitive plant species. Regression tree analysis was then used to examine the topographic factors influencing fog distributions and the topoclimatic factors influencing satellite‐derived vegetation greenness. We find that the interplay between the complex mountain topography and the incoming fog results in heterogeneous fog densities. Specifically, fog accumulates against steep windward slopes and landforms, resulting in hotspots of fog interception, while lower fog densities occur in leeward locations. We also find that fog distributions correlate with patterns of vegetation greenness, and overall, that greenness increases with fog density. The layer of fog density describes patterns of vegetation greenness more accurately than topographic variables alone, and thus, we propose that regional vegetation patterns more closely follow a fog gradient, than an altitudinal gradient as previously supposed. The layer of fog density will enable an improved understanding of how species and communities, many of which are endemic, range‐restricted and in decline, respond to local variability in topoclimatic conditions.
Thermomechanical modelling for the linear friction welding process of Ni-based superalloy and verification

This paper presents a fully coupled thermomechanical model for the linear friction welding process of Inconel-718 nickel-based superalloy by using the finite element method. Friction heat, plastic work, and contact formulation were taken into account for two deformable plastic bodies oscillating relative to each other under large compressive force. The modelling results of the thermal history at the weldline interface and thermal field at a distance away from the rubbing surfaces were compared to instrumented data sourced from related publications for model verification. Optimal linear friction welding process parameters were identified via comparison of weld temperature to the liquidus temperature of Inconel-718 alloy. Comparison of interface temperature showed a consistent range of values above the solidus melting temperature (1250 ℃) and below the liquidus melting temperature (1360 ℃) of Inconel-718 alloy. For the first time, a visible linear friction welding process window is identified using a thermomechanical computational modelling method. Through computational modelling, the influence of welding process parameters on the heat transfer and deformation of weld was systematically investigated.
Energy-Efficient Multiuser Partial Computation Offloading With Collaboration of Terminals, Radio Access Network, and Edge Server

Mobile-Edge Computing (MEC) could relieve computing pressure and save energy of resource-constrained Smart Mobile Devices (SMDs) via computation offloading. Nevertheless, offloading strategy design for multiuser MEC systems is challenging. Specifically, offloading operations (i.e., terminal execution strategy, access rate, and cloud execution strategy) are not only inner-coupled for each SMD due to parallel local and cloud execution, but also inter-coupled among SMDs due to competition for radio and computation resources. Worse still, the inner- and inter-coupling interplay each other. However, existing works generally weaken this inner-inter-coupling, resulting in an inability to adapt to network differences, terminal capacity differences, and application requirements differences. Hence, only suboptimal performance could be achieved. As motivated, we jointly optimizes terminal execution strategy, radio resource allocation, and MEC computation resource allocation to minimize weighted sum of terminal energy consumption. Additionally, via dynamically matching individual offloading behavior and group’s competitive resources allocation, our proposed algorithm could not only reflect mechanism of interaction between inner- and inter-coupling relationship, but also well adopt to diversities of network conditions, terminal capacity, and application requirements to further harvest MEC gain. Finally, simulation results demonstrate that our algorithm significantly outperforms existing schemes, more specifically up to 73.8% less energy consumption.
Incapacitated Patients' Wellbeing: Surrogate Decision Making

Patients' wellbeing often depends on making the right decision with regards to their healthcare treatment and other decisions relating to their health care or finances in terms of their end of life. If they are unable to make decisions for themselves, other people have to make those decisions on their behalf. This important task is described in literature as surrogate decision making. We survey and illustrate several important issues that are associated with surrogate decision making and provide an overview of the factors that have been found to affect its accuracy. Selection of a surrogate decision maker has been found to be affected by the beneficiary’s nationality, risk attitudes, and personality and by specific qualities of the surrogate. Decision accuracy (as indexed by matching between choices for self or relative) has been found to be affected by factors such as nationality, surrogate qualities, surrogate person choice, risk attitudes and personality.
New Minimally Invasive Approaches to Early Cancer Detection

Early cancer detection is known to improve clinical outcome. For screening purposes, it is possible to make a diagnosis of malignancy by cytological analysis, circumventing the need for an invasive procedure and tissue biopsy. Minimally invasive methods of harvesting cellular specimens from an anatomical site include direct sampling of surface cells by taking a smear or brushings. This simple approach forms the basis of population screening for cervical cancer, in which cervical smears are processed for cytological assessment with the Papanicolau (Pap) stain to determine both nuclear morphology and the extent of keratinocyte differentiation.1 At present, this represents an effective screening method for the detection of pre-malignant or early invasive lesions of the uterine cervix, for which prompt treatment intervention reduces disease mortality.
Determination of VVER-1000 Thermal Power Based on Background Signals of Self-Powered Neutron Detectors

The value of the reactor thermal power (RTP) is used in the VVER-1000 control systems in most algorithms for generation of control, blocking and protection signals. Besides, the technical and economic indicators of the power unit are determined by this parameter. Plans to increase VVER‑1000 RTP to 101.5%, and later to 104-107% of the nominal require additional justification of the accuracy of the RTP determination. Therefore, the task of increasing the accuracy of RTP determination is important. The paper describes the ways to improve the accuracy of weighted mean thermal power (WMTP) determination by selecting the optimal weight coefficient (that subsequently is used for WMTP determination) of each of the methods of RTP determination, namely: by thermotechnical parameters of the primary and secondary sides by neutron flux in the in-core monitoring system (ICMS) and in the neutron flux control equipment (NFCE). Another possibility of increasing the accuracy of WMTP determination, namely by increasing the number of methods of RTP determination, is also considered in the paper. The analysis of changes in the background signals of self-powered neutron detectors (SPNDs) during the VVER-1000 fuel campaigns shows the fundamental possibility of using the total background signal as a separate and independent method for RTP determination. The paper presents the results of the calculation of RTP determination error taking into account the coefficients of the components of the total RTP determination error: systematic, dynamic and random errors, which must be determined during the commissioning phase. The results of reduction of the error of WMTP determination in case of application of the additional method of RTP determination based on background signals of the SPNDs are presented. Theoretically, possible minimum values of the WMTP determination error are given depending on the values of the error of the RTP determination by separate methods.