Miracle-dz/UniFAR-FTUs huggingface dataset:
The ADELE Corpus of Dyadic Social Text Conversations:Dialog Act Annotation with ISO 24617-2

Social or interactional dialog is less well described than task-based or instrumental dialog, although there is increasing interest in the genre, particularly in light of new spoken and text dialog applications which aim to relate to the user as well as perform tasks. Dialog act annotation aids understanding of interaction structure; essential to the design of sucessful artiﬁcial dialog. Much social text interaction may be closer to social talk than to traditional written language. In this paper we brieﬂy describe social or casual talk, and review how current dialog annotation schemes and particularly the ISO standard 24617-2 (Semantic annotation framework, Part 2: Dialogue Acts) treat non-task elements of dialog. To aid in training a casual talk system, we collected a corpus of 193 dyadic text dialogs, based on a novel ‘getting to know you’ social dialog elicitation paradigm. We describe the annotation of the dialogs, and propose additional acts to better cover greeting and leavetaking. We report on preliminary analyses of the corpus, and provide an overview of the corpus content and its relationship to spoken language. The corpus, coding manual, and annotations are being packaged and will be made available to interested researchers.
Direction-of-Arrival Estimation With ULA: A Spatial Annihilating Filter Reconstruction Perspective

Direction-of-arrival (DOA) estimation under low signal-to-noise ratio (SNR) and snapshot deficient scenarios has practical application value. Since the array output of the uniform linear array (ULA) can be viewed as a linear combination of the equal interval sampling complex exponentials, it can be annihilated by a spatial annihilating filter and the DOAs are able to be obtained from the filter coefficients. To reconstruct the spatial annihilating filter, a multiple measurement vectors structured total least norm approach is used under the structured total least squares framework, along with a spatial fast Fourier transform based initialization method. It is proved that the new method is equivalent to the deterministic maximum likelihood estimator of DOA. It can resolve up to <inline-formula> <tex-math notation="LaTeX">$M-1$ </tex-math></inline-formula> sources using <inline-formula> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula>-element ULA and is capable of both incoherent and coherent signals. Numerical results show that the proposed method surpasses the representative methods largely in resolution and estimation performance under the low SNR, snapshot deficient, and closely spaced signals scenarios.
The Association Between Gene Polymorphisms of Homocysteine Metabolism-Related Enzymes and Ischemic Cerebrovascular Diseases in Chinese Henan Han population

Background and Purpose—During the last years, several studies suggested a role for genetic factors predisposing to thrombophilia and for moderate hyperhomocysteinemia.The mutations in homocysteine (Hcy) metabolism-related enzyme genes including methylenetetrahydrofolate reductase (MTHFR) C677T, cystathionine b-synthase (CBS) 844ins68, and methionine synthase (MS) A2756G have been identified as genetic risk factors for thromboembolic events. The evidence of a role for these gene variants in the risk of ischemic stroke is controversial and it has been noticed that these gene mutations have heterogeneous distributions among different ethnic groups or geographic areas. The data on the prevalence of the gene mutations in Chinese population is not yet available. The aim of the present study was to investigate the association between these gene polymorphisms and ischemic cerebrovascular diseases in Chinese Henan Han population in a large case-control study. Methods—We investigated 512 cases (310 males, 202 females; mean_SD age, 60.58 years) as patient group with ischemic cerebrovascular disease in department of neurology in Henan province hospital were enrolled from December 2004 to July 2007 and 500 healthy subjects (274 males, 226 females; mean_SD age, 56.28 years) as control group in the study. All people are Henan Han Chinese and without cancer, epilepsy and hepatic or renal diseases. MTHFR C677T and MS A2756G polymorphism was genotyped by polymerase chain reaction and HinfI digestion and HaeIII respectively, while the genotypes of CBS 844ins68 was detected by polymerase chain reaction. Results—This investigation showed that MTHFR C677T TT-type 40%, CT-type 42.6% in patient group and TT-type 32.8%, CT-type 34.6%, in control group,and the T allele frequency was 61.3% versus 51.1% in the two groups. The frequencies of the three genetypes were significantly different between patient groups and controls (χ2=30.36, P<0.01). The frequency of T allele was significantly higher in patient groups than that in controls (χ2=24.29, P<0.01). But there were no significant differences in the frequencies of CBS 844ins 68 (χ2=0.093, P>0.05), MS A2756G (χ2=4.101, P>0.05) between the patient the and control groups. Conclusion—The C677T polymorphism of the MTHFR gene was associated with increased risk of ischemic cerebrovascular diseases and MTHFR C677T may be independent risk factors for ischemic cardiovascular diseases. However, the mutations of CBS844ins68 and MS A2756G was no associated with the ischemic cerebrovascular diseases in Chinese Henan Han population. The prevalences of MTHFR C677T, CBS 844ins68 and MS A2756G may vary with different ethnic groups or geographic regions. [Li AF, Zheng H, Xu YM, Zhao XJ, Zhang XM. The Association Between Gene Polymorphisms of Homocysteine Metabolism-Related Enzymes and Ischemic Cerebrovascular Diseases in Chinese Henan Han population. Life Sci J 2012; 9(3):403-408]. (ISSN: 1097-8135). http://www.lifesciencesite. com. 56
Energy efficiency maximization for MIMO-OFDMA systems with imperfect CSI

Unlike the previous work on efficiency (EE) for multiple input multiple output (MIMO) orthogonal frequency division multiple access (OFDMA) systems with assuming the availability of perfect channel state information (CSI), this paper investigates robust resource allocation to improve the system EE under imperfect CSI. Considering the estimation error and the feedback delay, we formulate a combinatorial problem involving subcarrier assignment and power allocation to maximize the EE subject to a transmit power constraint and a minimum rate constraint. By relaxing the integral constraints, we develop a joint subcarrier and power allocation algorithm which can be implemented by one-dimension search. The simulation results demonstrate that the proposed algorithm can achieve a comparable EE performance with the optimal algorithm. Moreover, with taking imperfect CSI into account, the proposed algorithm can achieve higher EE when compared with a nonrobust algorithm.
Research on compressed sensing reconstruction algorithm in complementary space

Complementary matching pursuit algorithm (CMP) is a complementary form of the matching pursuit algorithm (MP). The CMP algorithm eliminates N-1 mismatched atoms and retains the remaining matching atoms, thus achieving the purpose of selecting atoms. The existing orthogonal complementary matching algorithm (OCMP), which is an improved form of the complementary matching algorithm can more accurately reconstruct the signal. But the algorithm for increasing the orthogonal processing get only one atom per iteration so that the algorithm increases execution time. This paper proposes an algorithm to solve the above problem. The proposed algorithm which is based on the framework of complementary matching pursuit algorithm and combined the sparse adaptive matching pursuit algorithm selects multiple atoms by setting the iterative step size which is adjusted according to the execution of the algorithm. The proposed algorithm selects multiple atoms in each iteration so that it not only guarantees the reconstruction precision, but also reduces the running time of the algorithm. Experiments show that the proposed algorithm can reconstruct the signal in a shorter time and improve the reconstruction efficiency of the algorithm.
An SVD based algorithm to estimate the parameters of vibration

Micro-Doppler features induced by micromotions of an object or structures of an object are a unique signature which is very useful in target identification and recognition. This paper introduces an algorithm based on singular value decomposition (SVD) to estimate the parameters of vibration. Firstly, the modulation induced by vibration is derived to be sinusoidal frequency modulation (SFM). Then, the modulation frequency is determinated through singular value ratio (SVR) spectrum. Afterwards, the frequency modulation index and the initial phase are estimated through two-dimension searching. Finally, this algorithm is demonstrated to be effective through several simulations under different SNRs (signal to noise ratio). Compared to the Hough transform (HT), the SVD based algorithm performs better in terms of computational complexity, computer storage and so on.
State-Level Measures of Institutional Budgetary Influence from the American State Administrators Project

The American State Administrators Project is a half-century long research program surveying the attitudes and behavior of state agency leaders. The project has produced a voluminous number of publications and conference papers. At the same time it has also faced several difficulties in making its data more widely available to the scholarly community. This paper describes the Project, some of the data difficulties it has faced, and the portion of the data being distributed with this article.
NON-NEGATIVE MATRIX FACTORIZATION BASED ON LOCALLY LINEAR EMBEDDING

In this paper, we proposed a novel method called Nonnegative Matrix Factorization based on Locally Linear Embedding (LLE-NMF). This idea is to factorize the nonnegative matrix considering the intrinsic geometric structure of the high dimensional data. Instead of the need to estimate pairwise distances between widely separated data points, LLE-NMF is able to find a compact representation recovering the global nonlinear structure from locally linear fits. We proposed updating rules and simulation results. In the experiments, we show the encouraging results of the method in comparison to the state-of-the-art algorithms on face image clustering.
The Effect of Mckenzie Approach and Mulligan's Mobilisation (SNAGS) in Lumbar Disc Prolapse with Unilateral Radiculopathy

Introduction: Disc related disorders of spine are estimated to compromise high percentage of low back pain Indian population with incidence of 23.09% with lifetime prevalence of 60-85%. The significant cost in management often require surgical intervention so study was carried out to find out cost effective physical therapy interventions along with manual therapy. Objective: To study & compare the effect of McKenzie approach and Mulligan's mobilisation (SNAGS) in lumbar disc prolapse with unilateral radiculopathy. Method: 30 participants between 25 to 45 years classified according to Qubec Task Force (QTF) classification & divided into group A & B. Baseline treatment of shortwave diathermy, intermittent lumbar traction & interferential therapy for both groups along with McKenzie approach for Group A & Mulligan's (SNAGS) for Group B. Outcome measures visual analogue scale (VAS), Modified Oswestry Disability Index (MOLBPDI) & lumbar range of motion (ROM) were assessed pre & post treatment. Result: Result showed improvement in VAS, MOLBPDI & ROM except rotation ROM in both groups. But there was better improvement in Group B. Conclusion: McKenzie approach and Mulligan's mobilisation (SNAGS) are effective in improving pain, functional ability & ROM in prolapse intervertebral disc with unilateral radiculopathy, later is more effective.
Linear time-varying control law for stabilization of hopping robot during flight phase

The well-known Brocket's theorem revealed that nonholonomic systems, hopping robots, for example, can not be stabilized by smooth time-invariant state feedback controllers. In this manuscript, we propose a linear time-varying state feedback controller for stabilizing a nonholonomic hopping robot during flight mode in finite time. The current approach is novel in the sense that we modify the Pontryagin's minimum principle to formulate the linear state feedback control law. The existence of such a control law and its necessary conditions are presented in detail. The theoretical results are also validated through computer simulations.
DETECTION USING SPATIAL FEATURES AND CONVOLUTIONAL RECURRENT NEURAL NETWORK

This paper proposes to use low-level spatial features extracted from multichannel audio for sound event detection. We extend the convolutional recurrent neural network to handle more than one type of these multichannel features by learning from each of them separately in the initial stages. We show that instead of concatenating the features of each channel into a single feature vector the network learns sound events in multichannel audio better when they are presented as separate layers of a volume. Using the proposed spatial features over monaural features on the same network gives an absolute F-score improvement of 6.1% on the publicly available TUT-SED 2016 dataset and 2.7% on the TUT-SED 2009 dataset that is fifteen times larger.
Angle-Dependent Distortions in the Perceptual Topology of Acoustic Space

By moving sounds around the head and asking listeners to report which ones moved more, it was found that sound sources at the side of a listener must move at least twice as much as ones in front to be judged as moving the same amount. A relative expansion of space in the front and compression at the side has consequences for spatial perception of moving sounds by both static and moving listeners. An accompanying prediction that the apparent location of static sound sources ought to also be distorted agrees with previous work and suggests that this is a general perceptual phenomenon that is not limited to moving signals. A mathematical model that mimics the measured expansion of space can be used to successfully capture several previous findings in spatial auditory perception. The inverse of this function could be used alongside individualized head-related transfer functions and motion tracking to produce hyperstable virtual acoustic environments.
Joint Minimization of the Energy Costs From Computing, Data Transmission, and Migrations in Cloud Data Centers

We propose a novel model, called joint computing, data transmission and migration energy costs (JCDME), for the allocation of virtual elements (VEs), with the goal of minimizing the energy consumption in a software-defined cloud data center (SDDC). More in detail, we model the energy consumption by considering the computing costs of the VEs on the physical servers, the costs for migrating VEs across the servers, and the costs for transferring data between VEs. In addition, JCDME introduces a weight parameter to avoid an excessive number of VE migrations. Specifically, we propose three different strategies to solve the JCDME problem with an automatic and adaptive computation of the weight parameter for the VEs migration costs. We then evaluate the considered strategies over a set of scenarios, ranging from a small sized SDDC up to a medium-sized SDDC composed of hundreds of VEs and hundreds of servers. Our results demonstrate that JCDME is able to save up to an additional 7% of energy with respect to previous energy-aware algorithms, without a substantial increase in the solution complexity.
Liver enzyme abnormalities of inpatients with rheumatic diseases: A 10‐year retrospective study in a Korean medicine hospital

Herbal medicines have been used as a treatment option for rheumatic disease (RD), but they often produce liver enzyme abnormality. This study examines the incidence of herb‐induced liver injury (HILI) and the relationship between risk factors and liver enzyme abnormality (LEA) in inpatients with RD. HILI was analyzed using the Roussel Uclaf causality assessment method liver injury criteria and causality assessment. Multivariable analysis was performed to assess the relationship between patient characteristics and LEA in RD. The features of LEA were also examined in each RD. Among 352 patients included in this study, 105 patients showed LEA on admission, of which 6 had fulfilled the Roussel Uclaf causality assessment method criteria. The incidence risks of LEA and HILI were 12.55% and 0.58%, respectively. Multivariable analysis showed that LEA on admission and occasional use of alcohol could be risk factors for LEA on follow‐up. In an additional analysis with each RD, all rheumatoid arthritis patients with LEA were taking nonsteroidal anti‐inflammatory drugs, steroids, and disease‐modifying antirheumatic drugs, and 4 out of 5 gout patients with LEA were taking steroids. The use of herbal medicine in RD is relatively safe. However, regular monitoring of liver enzyme tests and examination of alcohol consumption are required.
Lutein prevents osteoarthritis through Nrf2 activation and downregulation of inflammation

Introduction Osteoarthritis is an inflammatory disorder associated with oxidative stress and apoptosis leading to cartilage destruction and impairment of cartilage formation. In the present study, we studied the protective effect of lutein against monosodium iodoacetate (MIA)-induced osteoarthritis in primary chondrocyte cells. Material and methods Oxidative stress was determined through testing antioxidant status, reactive oxygen species levels and lipid peroxide content. Also, Nrf2 expression and its downstream target genes HO-1 and NQO-1 were determined. Inflammation was analyzed through NF-κB, COX-2 and pro-inflammatory cytokines (IL-6, TNF-α, IL-1β). In addition, the effects of MIA and lutein on mitochondrial membrane potential and caspase-3 levels were analyzed. Results The results showed that lutein treatment significantly increased the cell viability of chondrocytes and offered significant cytoprotection by enhancing the antioxidant defense mechanisms and reducing oxidative stress (reactive oxygen species and lipid peroxidation). Lutein treatment showed anti-inflammatory effects by downregulating inflammatory proteins (NF-κB, COX-2) and pro-inflammatory cytokines (IL-6, TNF-α, IL-1β). Lutein reduced MIA-induced apoptosis through maintaining mitochondrial membrane potential and downregulating caspase-3 activity. Conclusions The present study shows significant cytoprotection offered by lutein against MIA-induced oxidative stress, inflammation and apoptosis by the modulatory effect of NF-κB and Nrf2 activation.
Middle Cerebral Artery Occlusion / Reperfusion Model in Monkeys

This study was designed to develop a reversible middle cerebral artery (MCA) occlusion/reperfusion model in monkeys. By inserting a Cordis steerable guidewires balloon catheter (595-E014) from the femoral artery of 12 male adult monkeys (Macaca mulatta) weighting 5.5±0.5Kg, the balloon catheter could be inserted into the MCA and occluded the blood flow. Magnetic resonance T1, T2 and DWI showed ischemic signals in MCA supplied area. Neurological evaluation demonstrated neurological deficits in the ischemic group. Neuropathological examinations were consistent with the neurological evaluations. The results suggested that this monkey MCAO model seemed close to human stroke.
Effects of Gelidium amansii extracts on in vitro ruminal fermentation characteristics, methanogenesis, and microbial populations

Objective Gelidium amansii (Lamouroux) is a red alga belonging to the family Gelidaceae and is commonly found in the shallow coasts of many East Asian countries, including Korea, China, and Japan. G. amansii has traditionally been utilized as an edible alga, and has various biological activities. The objective of this study was to determine whether dietary supplementation of G. amansii could be useful for improving ruminal fermentation. Methods As assessed by in vitro fermentation parameters such as pH, total gas, volatile fatty acid (VFA) production, gas profile (methane, carbon dioxide, hydrogen, and ammonia), and microbial growth rate was compared to a basal diet with timothy hay. Cannulated Holstein cows were used as rumen fluid donors and 15 mL rumen fluid: buffer (1:2) was incubated for up to 72 h with four treatments with three replicates. The treatments were: control (timothy only), basal diet with 1% G. amansii extract, basal diet with 3% G. amansii extract, and basal diet with 5% G. amansii extract. Results Overall, the results of our study indicate that G. amansii supplementation is potentially useful for improving ruminant growth performance, via increased total gas and VFA production, but does come with some undesirable effects, such as increasing pH, ammonia concentration, and methane production. In particular, real-time polymerase chain reaction indicated that the methanogenic archaea and Fibrobacter succinogenes populations were significantly reduced, while the Ruminococcus flavefaciens populations were significantly increased at 24 h, when supplemented with G. amansii extracts as compared with controls. Conclusion More research is required to elucidate what G. amansii supplementation can do to improve growth performance, and its effect on methane production in ruminants.
Depth stream compression for enhanced real time fall detection by multiple sensors

A fall detection system using depth data acquired from a single Kinect sensor could be expanded by addition of more devices. The idea consists in equipping each sensor with an embedded board, in order to stream the collected depth data over a network, towards a central system, able to retrieve the data and process them. A preliminary evaluation of a low-complexity compression algorithm for depth streams is performed, and some encouraging results are presented.
Quantifying Qualitative Data for Understanding Controversial Issues

Understanding public opinion on complex controversial issues such as ‘Legalization of Marijuana’ and ‘Gun Rights’ is of considerable importance for a number of objectives such as identifying the most divisive facets of the issue, developing a consensus, and making informed policy decisions. However, an individual’s position on a controversial issue is often not just a binary support-or-oppose stance on the issue, but rather a conglomerate of nuanced opinions and beliefs on various aspects of the issue. These opinions and beliefs are often expressed qualitatively in free text in issue-focused surveys or on social media. However, quantifying vast amounts of qualitative information remains a significant challenge. The goal of this work is to provide a new approach for quantifying qualitative data for the understanding of controversial issues. First, we show how we can engage people directly through crowdsourcing to create a comprehensive dataset of assertions (claims, opinions, arguments, etc.) relevant to an issue. Next, the assertions are judged for agreement and strength of support or opposition, again by crowdsourcing. The collected Dataset of Nuanced Assertions on Controversial Issues (NAoCI dataset) consists of over 2,000 assertions on sixteen different controversial issues. It has over 100,000 judgments of whether people agree or disagree with the assertions, and of about 70,000 judgments indicating how strongly people support or oppose the assertions. This dataset allows for several useful analyses that help summarize public opinion. Across the sixteen issues, we find that when people judge a large set of assertions they often do not disagree with the individual assertions that the opposite side makes, but that they differently judge the relative importance of these assertions. We show how assertions that cause dissent or consensus can be identified by ranking the whole set of assertions based on the collected judgments. We also show how free-text assertions in social media can be analyzed in conjunction with the crowdsourced information to quantify and summarize public opinion on controversial issues.