Miracle-dz/UniFAR-FTUs huggingface dataset:
A repeated measures approach to the detection of the acute behavioral effects of toluene at low concentrations.

Acute behavioral effects of solvents are frequently the critical parameter considered for the recommendation of exposure limit values. Studies of toluene's acute effects on animal behavior during exposure have not been particularly sensitive; increasing the number of observations at low concentrations and the number of animals studied is a reasonable approach to increasing the ability to detect small acute effects. The effects of toluene (178-3000 ppm) were determined in 12 rats trained to nose poke on a probabilistic schedule of food delivery in a small exposure chamber that was highly ventilated with air or a toluene test atmosphere. Animals served as their own controls and were exposed to toluene twice a week for 2 hr during behavioral evaluation. At least six determinations of the effects of toluene were made at concentrations of 178, 300, and 560 ppm, and at least three determinations at 1000, 1780, and 3000 ppm. Biphasic concentration-effect, time-effect, and concentration-response functions were observed. Rates of nose poking increased in 4 of 12 animals at 178 ppm and in 9 of 12 animals at 300 ppm; all animals were affected at 560 ppm. The concentration at which a 10% rate increase occurred was determined by regression analysis to be 156 ppm with the lower 95% confidence limit or "benchmark" concentration being 116 ppm. Weighted regression analysis produced slightly higher estimates of these parameters, 182 and 157 ppm, respectively, while conventional logistic regression revealed that 10% of animals would be affected at a concentration of 114 ppm with a lower confidence limit of 63 ppm. (ABSTRACT TRUNCATED AT 250 WORDS)
On the Validity of the Decoupling Assumption for Analyzing the 802.11 MAC Protocol

Performance evaluation of the 802.11 MAC protocol is classically based on the decoupling assumption, which hypothesizes that the backoff processes at different nodes are independent. A necessary condition for the validity of this approach is the existence and uniqueness of a solution to a fixed point equation. However, it was also recently pointed out that this condition is not sufficient; in contrast, a necessary and sufficient condition is a global stability property of the associated ordinary differential equation. Such a property was established only for a specific case, namely for a homogeneous system (all nodes have the same parameters) and when the number of backoff stages is either 1 or infinite and with other restrictive conditions. In this paper, we give a simple condition that establishes the validity of the decoupling assumption for the homogeneous case. We also discuss the heterogeneous and the differentiated service cases and show that the uniqueness condition is not sufficient; we exhibit one case where the fixed point equation has a unique solution but the decoupling assumption is not valid.
Leader Group Prototypicality and Employee Well-Being: The Mediate Effect of Group Commitment and the Moderate Effect of Openness

According to the social identity Theory, leadership group prototypicality have an important effect in employee’s group identity, work attitude and employee well-being. In this article, we explore the mechanism between leadership group prototypicality and employee well-being to understand how leadership group prototypicality works. We had a sample of 336 employees to test our hypothesis in communication carriers in Guangdong. We used the longitudinal survey and collected the data in three different time point. At last, regression method was used to analyze the data. The results showed that: 1) leadership group prototypicality group could predict employee well-being; 2) mediating effect of group commitment was proud between leadership group prototypicality and employee well-being; 3) moderating effects of openness were found upon the relationship between leadership group prototypicality and group commitment. Finally, this study proposed management practice for leadership group prototypicality, and proposed future research prospects.
Functional analysis of linker-scan mutants spanning the -376, -308, -244, and -238 polymorphic sites of the TNF-alpha promoter.

Tumor necrosis factor alpha (TNF-alpha) promoter polymorphisms have been linked to a large number of diseases but studies examining the possible direct functional effects of these polymorphisms have been contradictory. Previous studies compared TNF-alpha promoter constructs containing single nucleotide changes. We have now made a series of mutant constructs in which regions of the TNF-alpha promoter containing suspected functional single nucleotide polymorphisms, including -376, -308, -244 and -238, were replaced by a 10 bp linker scan sequence. These constructs were transiently transfected into the T cell line Jurkat, the B cell line Raji, and the monocytic cell line U937, and tested for basal and induced transcriptional activity. Mutant constructs covering both the -308 and -376 polymorphisms showed no significant differences in either basal or induced transcriptional activity. Constructs covering the -244/-238 region showed a small increase in basal activity in the U937 cell line. These results indicate (i) that the -308 and -376 regions are of no functional relevance for TNF-alpha promoter transcription, and (ii) that the -244/-238 region does not influence transcription in some cell lines but may have some role in transcription in others.
Epitaxial growth and critical currents in (013)/(103)- and (110)-oriented YBa2Cu3Ox films.

Thin films of YBa{sub 2}Cu{sub 3}O{sub {ital x}} were grown epitaxially on (110)-oriented SrTiO{sub 3} crystals using {ital in} {ital situ}, off-axis, rf magnetron sputter deposition. The films were investigated by x-ray diffraction, reflection high-energy electron diffraction, scanning electron microscopy, resistance-temperature, and critical current measurements. Depending on growth conditions, the films formed platelets oriented with YBa{sub 2}Cu{sub 3}O{sub {ital x}} (110) or (013)/(103) parallel to the (110) substrates. Direct comparison of simultaneous growth on (110)- and (100)-oriented substrates showed that the critical temperature was significantly less for growth on the (100) surface for the same growth conditions. This is ascribed to the more open structure of the (110) and (013)/(103) planes which allow more complete oxidation of the film during growth and cool down. For growth on (110) substrates and substrate temperatures below about 650 {degree}C the (110) orientation dominated; above 650 {degree}C the films were mainly (013) or (103) oriented. The critical current density for the (013)/(103)-oriented films was 0.25 MA cm{sup {minus}2} at 77 K. This compares with about 5 MA cm{sup {minus}2} for {ital J}{sub {ital c}} parallel to the {ital ab} plane and 10 kA cm{sup {minus}1} for {ital J}{sub {ital c}} parallel to the {italmore » c} axis. The temperature dependence of the (013)/(103) films was {ital J}{sub {ital c}}{proportional_to}(1{minus}{ital T}/{ital T}{sub {ital c}}){sup 3/2}, 0.9{ital T}{sub {ital c}}{lt}{ital T}{lt}{ital T}{sub {ital c}}. This suggests that the measured critical currents correspond to the depairing current, although intergranular twinning gives a similar temperature dependence. The overall results are discussed in relation to the nucleation and growth kinetics of the different epitaxial modes and also the effects of energetic particles on sputter deposition. « less
Effects of once weekly NMES training on knee extensors fatigue and body composition in a person with spinal cord injury

Study design: Single-subject case (male, 33 years of age, T6 SCI AIS A). Objectives: To determine the effect of surface neuromuscular electrical stimulation (NMES) training conducted once weekly on improving fatigue resistance as well as regional and whole body composition in an individual with spinal cord injury (SCI). Setting: Laboratory setting within a SCI Center. Methods: Surface NMES resistance training (RT) of the paralyzed knee extensors was conducted once weekly for 12 weeks using ankle weights. Knee extensor fatigue index was determined by the number of repetitions (reps) achieved out of 30 reps. Total and regional body composition including percentage body fat (%BF), fat mass (FM), lean mass (LM) were conducted before the first session and one week after the last training session using whole-body dual-energy X-ray absorptiometry. Results: The participant had a compliance rate of 83% and he was able to lift 6 and 2 lbs on the right and left legs, respectively. Right knee extensors showed greater fatigue resistance compared to the left one. Leg LM increased by 6% accompanied with decrease in arm, trunk and total body LM by −4.7%, −13%, −5%, respectively. The %BF increased by 8%, 7.3%, 15.5%, 11.5% for arm, legs, trunk and total body. Conclusion: Once weekly of NMES RT evokes local positive changes in leg LM without reciprocating the continuous loss in LM or gain in FM in other regions and total body. Training was effective in increasing strength as well as fatigue resistance of the trained knee extensors.
A QoE supportive distributed caching management for vehicular video streaming in cellular networks

The distributed caching management enabled wireless networking technology can greatly improve the data storage and transmission efficiency of wireless users and correspondingly the users' quality of experience (QoE). How to alleviate the pressure on network access while ensuring the content consistency is still a challenge. In this paper, we investigate the vehicular users oriented caching management scenario which focuses on the in-motion video streaming in cellular networks. Specifically, we propose a QoE supportive distributed caching management approach considering the cache constraint of cellular networks, to fulfill more mobile users' requests for video streaming while ensuring the basic service experience of users. By introducing the QoE evaluation model using the verified empirical data, and establishing the mathematic relationship between the associated streaming bit-rate and actual storage space, we formulate the dynamic caching management for in-motion video streaming in cellular networks into a constrained optimization problem which is capable to be solved by the Lagrange Multiplier method. Simulation results indicate that the proposed dynamic caching approach can improve the users' satisfaction ratio by up to 40%.
[Effects of lumbar peridural anesthesia on tissue pO2 of the large intestine in man].

AIM The aim of this study was to investigate the effect of 15 ml bupivacaine 0.25%, given via an epidural catheter, on the tissue-PO2 of the colon wall in humans. METHODS Nine patients were studied during elective colorectal surgery. The tissue-PO2 was measured by polarography, using a multiwire surface probe. RESULTS There was no significant change in cardiac index and arterial oxygen delivery after the injection of bupivacaine. At the serosal side of the colon wall the tissue-PO2 increased from 34 to 51 mmHg after epidural bupivacaine, which is statistically significant. Spinal nerve block produces sympathetic denervation of the bowel with an increase of regional nutritive blood flow. CONCLUSION It is concluded that epidural bupivacaine has a favourable effect on tissue oxygenation of the colon during colorectal surgery.
A FAST AND RELIABLE MOTION HUMAN DETECTION AND TRACKING BASED ON BACKGROUND SUBTRACTION

According to the result of moving object detection research on video sequences, this paper proposes a new method to detect moving object based on background subtraction. First of all, we establish a reliable background updating model based on statistical and use a dynamic optimization threshold method to obtain a more complete moving object. And then,morphological filtering is introduced to eliminate the noise and solve the background disturbance problem. At last, contour projection analysis is combined with the shape analysis to remove the effect of shadow, the moving human body are accurately and reliably detected. The experiment results show that the proposed method runs quickly, accurately and fits for the real-time detection. The occlusion is one of the most common events in object tracking and object centroid of each object is used for detecting the occlusion and identifying each object separately. Video sequences have been captured in the laboratory and tested with the proposed algorithm. The algorithm works efficiently in the event of occlusion in the video sequences. Keywords-background subtraction; background model; moving object detection , shadow removal and occlusion detection.
Drug‐based helminth control in Western Pacific countries: a general perspective

Helminthiases still have a relevant detrimental role in the health of large groups of human population. Where poor hygiene and lack of access to education, health services and essential care characterize living conditions, parasitic infections dramatically affect essential aspects of individual life, such as nutrition, cognitive performance, susceptibility to infections and micronutrient deficiency. Severe illness is associated with schistosomiasis, lymphatic filariasis and food‐borne trematode infections. Drugs are the cornerstone of control strategies for such infections, the World Health Organization (WHO) list of essential drugs contains several highly efficacious anthelmintics which are all safe, single‐dose and cheap. If given regularly to infected communities, these drugs effectively control the morbidity related to the major endemic helminth infections. New strategies for mass drug administration to human populations have been tested, and several endemic Western Pacific countries have achieved excellent results in reducing morbidity in spite of continuous transmission. In this region, experience over the last decades proves the feasibility of helminth control, but also shows the need for long‐term commitment and continuous support.
catena-Poly[[(1,10-phenanthroline-κ2 N,N′)cadmium(II)]-μ-oxalato-κ4 O 1,O 2:O 1′,O 2′]

In the title complex, [Cd(C2O4)(C12H8N2)]n, the CdII atom has a distorted octahedral coordination, defined by four O atoms from two symmetry-related oxalate ligands and by two N atoms from a bidentate 1,10-phenanthroline ligand. Each oxalate ligand bridges two CdII atoms, generating a zigzag chain structure propagating along [100]. The packing of the structure is consolidated by non-classical C—H⋯O hydrogen-bonding interactions.
BASED ENSEMBLE ACOUSTIC MODELLING

In this paper, we propose a novel technique of using Cross Validation (CV) data sampling to construct an ensemble of acoustic models for conversational speech recognition. We further propose using Hierarchical Gaussian Mixture Model (HGMM) and repartition training data to increase the ensemble size and diversity. The proposed methods are found to work well together for ensemble acoustic modeling. We also evaluated the quality of the ensemble acoustic models by using the measures of classification margin, average correct score and variance of correct score. We have found that the ensemble of acoustic models increases the margin and the average correct score, and reduces the variance. We compared the performance of our proposed method with a recently reported method of CV Expectation Maximization (CVEM) for single acoustic models. Our experimental results on a telemedicine automatic captioning task showed that the proposed ensemble acoustic modeling has led to significant improvements in word recognition accuracy.
Mining, Representation and Reasoning with Temporal Expressions in the Legal Domain

Reasoning on temporal references present in free text documents is a challenging problem demanding the synergy of several disciplines in Artiﬁcial Intelligence. First, Natural Language Processing (NLP) techniques are necessary to mine temporal expressions (referring to instants and events) and their relations; then, knowledge representation systems able to support more than trivial temporal information must be deﬁned; ﬁnally, temporal logic systems exposing practical functionality are much demanded. Documents in the legal domain are rich in temporal expressions, often linked to a norm. Permissions, obligations and prohibitions are often bounded by temporal constraints. While there exist diﬀerent rules and policy languages capable of representing temporal constraints to some extent, they are far from being able to express the complex temporal relations present in these legal texts. Reaching a formalized expression of temporal rules able to accommodate the ﬁndings of the NLP algorithms and enabling temporal reasoning in an integrated manner would unleash new possibilities in the area of legal reasoning. As this thesis is still in an early phase, Doctoral Consortium feedback will be extremely valuable for topic delimitation and additional research lines.
A Robust Approach for Action Recognition Based on Spatio-Temporal Features in RGB-D Sequences

Recognizing human action is attractive research topic in computer vision since it plays an important role on the applications such as human-computer interaction, intelligent surveillance, human actions retrieval system, health care, smart home, robotics and so on. The availability the low-cost Microsoft Kinect sensor, which can capture real-time high-resolution RGB and visual depth information, has opened an opportunity to significantly increase the capabilities of many automated vision based recognition tasks. In this paper, we propose new framework for action recognition in RGB-D video. We extract spatiotemporal features from RGB-D data that capture both visual, shape and motion information. Moreover, the segmentation technique is applied to present the temporal structure of action. Firstly, we use STIP to detect interest points both of RGB and depth channels. Secondly, we apply HOG3D descriptor for RGB channel and 3DS-HONV descriptor for depth channel. In addition, we also extract HOF2.5D from fusing RGB and Depth to capture human’s motion. Thirdly, we divide the video into segments and apply GMM to create feature vectors for each segment. So, we have three feature vectors (HOG3D, 3DS-HONV, and HOF2.5D) that represent for each segment. Next, the max pooling technique is applied to create a final vector for each descriptor. Then, we concatenate the feature vectors from the previous step into the final vector for action representation. Lastly, we use SVM method for classification step. We evaluated our proposed method on three benchmark datasets to demonstrate generalizability. And, the experimental results shown to be more accurate for action recognition compared to the previous works. We obtain overall accuracies of 93.5%, 99.16% and 89.38% with our proposed method on the UTKinect-Action, 3D Action Pairs and MSR-Daily Activity 3D dataset, respectively. These results show that our method is feasible and superior performance over the-state-of-the-art methods on these datasets.
Voltage-mode grid-connected solar inverter with high frequency isolated transformer

A voltage-mode grid-connected solar inverter with high frequency isolated transformer is proposed in this paper. Besides, the functions of MPPT (maximum power point tracking) and the islanding detection are incorporated into the controller of this voltage-mode grid-connected solar inverter. The experimental results show that the performance of this isolated voltage-mode grid-connected photovoltaic generation system is as expected.
On the convergence of adaptive sequential Monte Carlo methods

In several implementations of Sequential Monte Carlo (SMC) methods it is natural and important, in terms of algorithmic efficiency, to exploit the information of the history of the samples to optimally tune their subsequent propagations. In this article we provide a carefully formulated asymptotic theory for a class of such adaptive SMC methods. The theoretical framework developed here will cover, under assumptions, several commonly used SMC algorithms [Chopin, Biometrika 89 (2002) 539-551; Jasra et al., Scand. J. Stat. 38 (2011) 1-22; Schafer and Chopin, Stat. Comput. 23 (2013) 163- 184]. There are only limited results about the theoretical underpinning of such adaptive methods: We will bridge this gap by providing a weak law of large numbers (WLLN) and a central limit theorem (CLT) for some of these algorithms. The latter seems to be the first result of its kind in the literature and provides a formal justification of algorithms used in many real data contexts [Jasra et al. (2011); Schafer and Chopin (2013)]. We establish that for a general class of adaptive SMC algorithms [Chopin (2002)], the asymptotic variance of the estimators from the adaptive SMC method is identical to a "limiting" SMC algorithm which uses ideal proposal kernels. Our results are supported by application on a complex high-dimensional posterior distribution associated with the Navier-Stokes model, where adapting highdimensional parameters of the proposal kernels is critical for the efficiency of the algorithm.
A neural network approach to microwave imaging

We present a neural network approach to microwave imaging for medical diagnosis. The problem is to reconstruct the complex permittivity of the biological tissues illuminated by the transverse magnetic (TM) incident waves. In order to avoid the inherent ill‐posedness of the inverse scattering problem, we introduce a stochastic process based on Markov random field and a priori knowledge. A coupled gradient neural network is proposed to deal with the mixed‐variable problem because the reconstructed dielectric permittivities are continuous complex variables and the line processes, which can preserve the edges of the reconstructed image, are binary variables. We report the numerical results of a simple human forearm model. We also point out the advantages and the limitations of this method. © 2001 John Wiley & Sons, Inc. Int J Imaging Syst Technol 11, 159–163, 2000
The ShanghAI Lectures: A Global Education Project on Artificial Intelligence

We present a global education project in Artificial Intelligence (AI) called the "ShanghAI Lectures": A lecture series held annually via videoconference among 15 to 20 universities around the globe. The lectures are complemented by a novel three-dimensional collaborative virtual environment for international student teamwork, and a web-based resource designed as a knowledge base and for community building. This paper summarizes the lessons learned from the first edition of the ShanghAI Lectures, which may guide future global teaching and learning projects of this kind.
Dynamic capabilities development of new technology ventures — A longitudinal study in China

Scholars suggest that dynamic capabilities would bring a new lens for new technology venture research. However, little empirical research of dynamic capabilities in new technology ventures, in particular in the context of emerging economy, has been found so far. In order to contribute to this line of research, this study conducts deductive case studies on two new technology ventures in China in a longitudinal way. Results firstly, confirm the conceptual speculation that dynamic capabilities do help studying new ventures. Secondly, our results also show dynamic capabilities development of new ventures are different from those of established firms from the aspects of sensing opportunities, seizing opportunities and transforming dynamic capabilities. Thirdly our research shows that for a new venture, dynamic capabilities are mostly not manifested in the forms of routine, which is different with those of established firms.