Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatial Patterns of Species Diversity of Alien Invasive Plants in China and Their Relationship with Native Plants

The knowledge of spatial patterns of alien invasive species diversity and their relationship with native species is of important significance to the understanding of the invasion mechanism of alien invasive species.In this study,the spatial patterns of alien invasive plants in China and their relationship with native plants were investigated based on flora information in large scale.A decreasing trend of species density was observed with increasing latitude and with increasing longitude.Relatively abundant species diversity of alien invasive plants was found in Southeast China,while less species diversity was observed in Northwest China.Probably,alien invasive plants invaded China from Southeast to Northwest.Both environmental and anthropological factors significantly affected the spatial patterns of invasive plants.Mean annual temperature,spatial variation of mean annual precipitation per unit area and mean annual precipitation played the leading roles.There was a significant positive correlation between species density of alien invasive plants and that of native plants,resulting probably from similar affecting factors.In large scale,regions with richer species diversity of native plants may be much more easily invaded by alien invasive species.
Water Use Characteristics of Alternately Irrigated Wheat/Maize Intercropping in Oasis Region of Northwestern China

In oasis irrigation region of northwestern China,the decreasing of multiple cropping areas may lead to significant reduction of land and light use efficiencies due to serious water shortage.Therefore,water-saving irrigation is a priority in the research on theory and technology for intercropping system.Alternate irrigation is a technique to save water and enhance water use efficiency(WUE) simultaneously in common cropping systems.However,its effect is not clear on intercropping system.In 2006-2008 cropping years,we carried out a field experiment in oasis region of Hexi Corridor,Gansu province,China under wheat/maize intercropping to disclose the effects of alternate irrigation on crop yields,water consumption,and WUE.The results showed that,compared to sole cropping treatments,there was a significant increase of land equivalent ratio(LER) in the alternately irrigated wheat/maize intercropping treatment with the LER values ranging from 1.22 to 1.52 under different irrigation levels of the intercropping treatments.However,the difference of LERs between conventionally irrigated and alternately irrigated intercropping systems was not significant at the same irrigation quota.Compared to the conventionally irrigated intercropping treatment,there was no significant change of wheat yield in the alternately irrigated intercropping treatment,but significant increase by 11.4-36.4% in maize yield.Therefore,the total yield of wheat and maize in the alternately irrigated intercropping treatment was increased by 12.9 averagely.The water consumption in the alternately irrigated intercropping treatment had no significant increase compared to that of the conventionally irrigated intercropping treatment,with 1.2-19.4% higher than the weighted average of monoculture of both crops.The WUE of alternatiely irrigated intercropping treatment was 0.9-22.5% higher than that of the conventionally irrigated intercropping treatment,and 12.0-71.4% and 10.6-37.8% higher than that of wheat and maize monoculture,respectively.These results suggest that alternate irrigation is feasible in intercropping systems in arid oasis regions with the purpose of saving water and increasing WUE.
Effects and Mechanism of Copper and Zinc Elements on Controlling Fusarium-wilt Disease of Banana

In order to find the measure of controlling the fusarium wilt disease of banana,through pot experiments and laboratory experiments,we investigated the applied effects of EDTA-Cu and EDTA-Zn on the physiological characteristics of Fusarium oxysporum f.sp. cubense,and the combined application of Zn2+and the fungal antagonist of the No.21 bacteria(SQR21#,Paenibacillus polymyxa)on the suppression on the disease.The results were as follows:(1)Time of 96 hours after treatment the banana seedlings with crude toxin of Fusarium oxysporum f.sp. cubense,the seedlings of the control treatment wilted severely.However,the treatments of application of EDTA-Cu and EDTA-Zn significantly reduced the disease stress on banana. (2)Application of EDTA-Cu and EDTA-Zn significantly increased the total biomass and the microconidium number of Fusarium oxysporum f.sp. cubense,but significantly reduced the production of fusaric acid of Fusarium oxysporum f.sp. cubense.Compared with the control treatment,the fusaric acid production with treatments of EDTA-Cu and EDTA-Zn were reduced by 73% and 96%,respectively(.3)In pot experiments,only Zn2+addition significantly reduced the banana fusarium wilt disease index.Furthermore,combined application of Zn2+and the No.21 bacteria had a good effect of cotrolling the disease,and after 75 days of inoculation of banana seedlings,the banana fusarium wilt disease indices were all reduced by 62% compared with the only fungi-inoculated treatment. (4)Only addition of the No.21 bacteria reduced the spore number by 18% compared to the only fungi-inoculated treatment.However,when combined application of Zn and No.21 bacteria,the number of the spores was increased significantly by 30%. It was concluded that Zn application might effectively reduce the occurrence of fusarium wilt disease of banana though reducing the fusaric acid production of the pathogen and enhancing the No.21 bacteria biocontrol activity.
Action Recognition Using Motion History Image and Static History Image-based Local Binary Patterns

Human action recognition is an important yet challenging task. In this paper, we propose a robust and effective framework to largely improve the performance of human action recognition using depth maps. The key contribution is the Motion History Image (MHI) and Static History Image (SHI) is used to represent depth sequence. And we optimize the condition to construct the MHI and SHI; it allows us to capture more critical information. The local binary pattern (LBP) are then computed to gain the compact feature representation of an action. We evaluate the proposed framework on MSR Action3D dataset. Experimental results indicate that the proposed approach outperforms the state-of-the-art methods and demonstrate the effectiveness of the proposed approaches.
Source and channel coding for speech transmission and remote speech recognition

This dissertation addresses the issue of designing source and channel coding techniques for two types of speech processing applications: speech transmission and remote speech recognition. In the first part, adaptive multi-rate (AMR) speech transmission systems that switch between operating modes depending on channel conditions are presented. We address the design of such an adaptive scheme using variable bit rate embedded source encoders and rate-compatible channel coders providing unequal error protection. A novel technique, the rate-compatible punctured trellis code (RCPT) for obtaining unequal error protection via progressive puncturing of symbols in a trellis, is presented and compared with the rate-compatible punctured convolutional code with and without bit-interleaved coded modulation. The perceptually-based speech coder proposed displays a wide range of bit error sensitivities, and is used in combination with rate-compatible punctured channel codes providing adequate levels of protection. The resulting system operates over a wide range of channel conditions with graceful performance degradation as the channel signal-to-noise ratio decreases. In the second part, we present a framework for developing source coding, channel coding, channel decoding, and frame erasure concealment techniques adapted for remote speech recognition applications. It is shown that speech recognition, as opposed to speech coding, is more sensitive to channel errors than channel erasures. Appropriate channel coding design criteria are determined. For channel decoding, we introduce a novel technique for combining soft decision decoding with error detection. The technique outperforms the often used hard decision strategy. In addition, frame erasure concealment techniques are used at the decoder to deal with unreliable frames. At the recognition stage, we present a technique to modify the recognition engine to take into account the time-varying reliability of the decoded feature after channel transmission. The resulting engine, referred to as weighted Viterbi recognition (WVR), further improves recognition accuracy. Together, source coding, channel coding and the modified recognition engine are shown to provide good recognition accuracy over a wide range of communication channels at very low bit rates.
Adjuvant Treatment of Hepatocellular Carcinoma: Prospect of Immunotherapy

Although patients undergo procedures with curative intent for early‐stage hepatocellular carcinoma (HCC), up to 70% of patients may have disease recurrence in the liver at 5 years. Thus far, no therapy has proven to be effective in the adjuvant setting. Here, we discuss the application of immune‐based therapies in the adjuvant setting for HCC, focusing on the underlying rationale for immunotherapies, which patients may benefit from an immune‐based therapy, and what type of immune therapy should be implemented.
MicroRNA-9 enhances chemotherapy sensitivity of glioma to TMZ by suppressing TOPO II via the NF-κB signaling pathway

Glioma is the most common primary tumor of the central nervous system (CNS) that develops chemotherapy resistance. The microRNA (miRNA) miR-9 is a tissue-specific miRNA of the CNS that may serve a key role in the modulation of chemotherapy sensitivity. The aim of the present study was to investigate the effect of miR-9 on glioma chemotherapy sensitivity by altering the expression of miR-9 in U251 glioma cells by viral transfection and subsequently treating with gradient concentrations of temozolomide (TMZ). Cell viability, apoptosis and the cell cycle were examined, and drug resistance genes were analyzed by western blotting. The role of nuclear factor κB (NF-κB) in this regulation was also examined. The results revealed that the susceptibility of glioma cells to TMZ was enhanced by miR-9 overexpression. When miR-9 and TMZ were applied together, the apoptotic rate and percentage of cells arrested at the G2/M stage were significantly higher compared with either treatment alone. Topoisomerase II expression was suppressed by miR-9 via the NF-κB signaling pathway, which may be responsible for the sensitization. The results of the present study suggested that miR-9 may be a potential target for glioma chemotherapy.
Heart-Brain Coherence; Heart-Rate Variability (HRV); Reading Anxiety; TestEdge Program

Based on psychophysiological research, coherent heart-brain interaction can change afferent cardiac signal pattern sent to the brain. Accordingly, the present study aimed at facilitating the emotion-cognition interaction through HeartMath Institute self-regulated emotional techniques to investigate the efficacy of heart-brain coherence on reading anxiety reduction that significantly enhances attention, memory, comprehension, and efficiency in learning. Participants were 63 Iranian university and high school students. In order to enable the participants to self-generate high psychophysiological state and optimal heart rate variability (HRV), TestEdge program, a biofeedback remedy that teaches students skills to self-regulate negative emotional learning impediments, was administered. Findings indicated that the combination of intentional heart focus with the generation of sustained positive feelings increased heart-brain coherence and resulted in a beneficial mode of psychophysiological state. This heart-brain coherence affected and controlled the HRV patterns significantly among the participants on average which, in turn, reduced reading anxiety. Particularly, this study found significant differences among the EFL students with high, mid, and low levels of coherence and their reading anxiety level.
Physiotherapy Exercises Evaluation using a Combined Approach based on sEMG and Wearable Inertial Sensors

The efficacy of home-based physiotherapy depends on the correct and systematic execution of prescribed exercises. Biofeedback systems enable to accurately track exercise execution and prevent patients from unconsciously introduce incorrect postures or improper muscular loads on the prescribed exercises. This is often achieved using inertial and surface electromyography (sEMG) sensors, as they can be used to monitor human motion variables and muscular activation. In this work, we propose to use machine learning techniques to automatically assess if a given exercise was properly executed. We present two major contributions: (1) a novel sEMG segmentation algorithm based on a syntactic approach and (2) a feature extraction and classification pipeline. The proposed methodology was applied to a controlled laboratory trial, for a set of 3 different exercises often prescribe by physiotherapists. The findings of this study support it is possible to automatically segment and classify exercise repetitions according to a given set of common deviations.
Reducing Computational Complexity of Real-Time Stereoscopic Ray Tracing with Spatiotemporal Sample Reprojection

Sample reprojection is a computationally inexpensive way of increasing the quality of real-time ray tracing, where the number of samples that can be traced per pixel within the time budget is limited often to just one. Stereoscopic rendering further doubles the amount of rays to be traced, although it exhibits significant correlation not only temporally between frames, but also spatially between the viewpoints of the two eyes. We explore various reprojection schemes taking advantage of these correlations, and propose to quantify their contributions on the improved quality in terms of effective sample per pixel counts. We validate that sample reprojection is an effective way of reducing the computational complexity of real-time stereoscopic ray tracing, bringing potential benefits especially to lower-end devices.
Rangiranje ekipa i prognoziranje ishoda u rukometu korištenjem PageRank algoritma

Sažetak – Rad pridonosi poznavanju primjene matematičkih modela u analitici sportskih rezultata. U radu rangiramo ekipe koje su igrale na Europskom rukometnom prvenstvu u Poljskoj od 15. do 31. siječnja 2016. i prognoziramo pobjednike rukometnih utakmica. Dominaciju među ekipama modeliramo metodom za rangiranje web stranica – PageRank algoritam – koju ukratko opisujemo. Rezultati modela služe za rangiranje i prognoziranje. Rangiranje dobiveno algoritmom uspoređujemo s ostvarenim plasmanom na kraju prvenstva. Preciznost prognoziranja provjeravamo uspoređujući prognoze s ishodima odigranih utakmica.
Multiple Face Detection and Recognition in Real-Time using Open CV

technologies for video content analytics are playing an increasingly essential role in the Abstract:With the pervasiveness of monitoring cameras installed in public places, schools, hospitals and homes, video analytics technologies for interpreting the generated video content are becoming more and more relevant to people’s lives. Along this context, we develop a human-centric video surveillance system that identifies and tracks people in a given scene. In this paper, Multiple human face detection and recognition in real time application is implemented to detect and recognize the faces in real time using a open source computer vision called Open CV which is a library of programming functions mainly aimed at real time computer vision and with the help of EMGU CV.The application runs efficiently and smoothly, so that multiple people can be simultaneously tracked in real time. Furthermore, significant innovations are involved in this work in making each of the major image analysis modules both fast and robust to variations in pose, occlusions and so on. A software has been implemented that supports finding, tagging, identifying people in live or recorded videos.
GDTM: A Gaussian Dynamic Topic Model for Forwarding Prediction Under Complex Mechanisms

Forwarding is the keyway for information propagation in social networks that affected by complex factors. Due to the fact that the forwarding mechanisms are essentially unclear, this paper focuses on the formation and evolution of the external as well as internal driving mechanisms and develops a Gaussian dynamic topic model for forwarding prediction by incorporating all the information of nodes and edges. First, based on the diversity of communities each user located in, latent Dirichlet allocation (LDA) traditional text modeling method is applied to user following relationships modeling that leads to the initial formation of communities, and user interacting relationships modeling that leads to the evolution of communities. Taking the advantage of LDA topic model in dealing with the problem of polysemy and synonym, we can mine user latent distribution over communities and analyze the external community driving effects. Second, considering the differences in individual habits, time factor is introduced and the dynamic topic model is proposed to model user behavioral attributes. Meanwhile, in regard to continuous user attributes modeling, the parameter of topic-word distribution in the topic model is replaced by multivariate Gaussian distributions, which shown to be effective at capturing the regularities of individual behavioral habits and analyzing the internal individual driving effects. Finally, combining with external and internal factors, a probabilistic graph model is used to modeling forwarding behavior. We propose methods based on Gibbs sampling and an expectation–maximization algorithm to estimate model parameters and fit our model to predict user forwarding actions. Experimental results indicate that the model can not only detect the latent communities but also can improve the performance of forwarding prediction effectively.
Agreement between patients and nurses of neurobehavioral disability following stroke in an inpatient rehabilitation setting

Abstract Purpose: To investigate the level of agreement of neurobehavioral disability following stroke. Methods: Stroke patients and nurses were recruited from an inpatient neurorehabilitation facility. In total, 58 stroke patient–nurse pairs completed the St Andrew’s–Swansea Neurobehavioral Outcome Scale questionnaire. Results: Agreement levels of neurobehavioral disability varied across five behavior subdomains. Cognition and Interpersonal behaviors were reported as more prevalent according to nurses (39% and 36%) versus patients (14% and 7%). Agreement levels between the two groups was fair for these domains (ICC <0.60). Percentage category agreement methods revealed high patient–nurse agreement for Communication, Inhibition, and Aggression behaviors but overall reporting of these problems was very low or absent. Patient demographics and stroke variables did not predict the pattern of results. Lower patient–nurse agreement was moderately associated with older age (rs = 0.37, p = 0.01) and increased experience of nurse (rs = 0.38, p = 0.01) but only for the Cognition-related domain. Agreement of impact of neurobehavioral disability was none to slight for both groups across all neurobehavioral domains (κ <0.20). Conclusions: Neurobehavioral disability is common in the early recovery phase after stroke and is viewed differently with regards to frequency, type, and impact between patients and their nurses. Research and clinical training in the management of stroke-related neurobehavioral disability is required. Implications for rehabilitation Neurobehavioral disability (NBD) following stroke is commonly seen in the early stages of recovery and requires careful evaluation by stroke survivors and rehabilitation staff. Many patients may disagree with their clinician that they are exhibiting NBD, which may compromise the therapeutic relationship. We need to better understand factors underlying lower reporting of NBD by patients (denial or reduced self-awareness) to help guide management in stroke rehabilitation settings.
Effects of Dietary Lysine to Methionine Ratio on Growth Performance,Nutrient Digestibility,and Metabolism in Weaned Calves

【Objective】 This trial was designed to study the effects of dietary lysine to methionine ratio on growth performance,nutrient digestibility and nitrogen metabolism in weaned calves. 【Method】 Twenty four weaned calves were randomly allocated into four treatments either fed a control diet containing 14.76%DM CP or one of the three trial diets containing 12.02% DM CP and the dietary lysine/ methionine ratios were 2.5﹕1,3.0﹕1 or 3.5﹕1,respectively,for 8 weeks.The calves were weighed and blood samples were collected on the initial and final day of the experiment.Four calves were selected from each group and metabolism trials were conducted from the third week of the feeding experiment by total feces collection method. 【Result】 The results indicated that the gain of calves in group 3.0﹕1 was higher than that of calves in other groups numerically(P0.05). Serum concentrations of urea nitrogen in calves fed test diets was lower than that in the control(P0.01). The concentrations of free amino acid in serum were lower(except methionine) in calves fed test diets than those in control group(P0.05). No difference was observed in serum concentration of urea nitrogen and free amino acids(except arginine and valine) among test groups.The utilization and apparent biological value of nitrogen in group 3.0﹕1 and group 3.5﹕1 were higher than group 2.5﹕1 and control group numerically(P0.05). 【Conclusion】 The gain of calves fed diet addition of RPLys and RPMet with a crude protein level of 12.02% was higher than that fed diet with a crude protein level of 14.67%. The ratio of lysine and methionine at 3.0﹕1 in diets could enhance growth performance and utilization of nitrogen in weaned calves.
A Lightweight Secure and Efficient Authentication and Key Agreement Protocol for VANET

The vehicular ad hoc network (VANET), as an important part of the intelligent transportation system, has a crucial impact on traffic safety and efficiency. And its security issues have attracted many researchers. The secure communication among entities is particularly important due to the openness of the VANET environment. In this paper, we propose a lightweight secure and efficient authentication and key agreement protocol for VANET in order to implement secure communication. The scheme only uses lightweight computation to achieve anonymity, integrity and mutual authentication among entities.
The role of Rab proteins in vesicular membrane trafficking and cell signalling

The Rab family belongs to the Ras superfamily of small GTPases, members of which are found in all eukaryotes, including yeast, plants and mammals. There are almost 70 Rab proteins and Rab-like proteins in human cells. Each Rab protein can regulate different effectors and be regulated by some upstream effectors, so as to confer directionality to vesicle budding, vesicle delivery, vesicle tethering, and fusion of the vesicle membrane with that of the target compartment. Recently, several studies have demonstrated some of Rab proteins and their effectors were potential regulators of intracellular signaling pathways, and directed a variety of cellular processes, including cell growth, differentiation, proliferation, and apoptosis.