Miracle-dz/UniFAR-FTUs huggingface dataset:
Raman Imaging with a Fiber-Coupled Multichannel Spectrograph

Until now, spatially resolved Raman Spectroscopy has required to scan a sample under investigation in a time-consuming step-by-step procedure. Here, we present a technique that allows the capture of an entire Raman image with only one single exposure. The Raman scattering arising from the sample was collected with a fiber-coupled high-performance astronomy spectrograph. The probe head consisting of an array of 20 × 20 multimode fibers was linked to the camera port of a microscope. To demonstrate the high potential of this new concept, Raman images of reference samples were recorded. Entire chemical maps were received without the need for a scanning procedure.
Cellular Traces of Behavioral Classical Conditioning Can Be Recorded at Several Specific Sites in a Simple Nervous System

We used a behavioral learning paradigm followed by electrophysiological analysis to find sites in theLymnaea feeding network in which electrical changes could be recorded after appetitive conditioning. Specifically, we analyzed conditioning-induced changes in cellular responses in the mechanosensory conditioned stimulus (CS) pathway, in the central pattern generator (CPG) network, and in feeding motoneurons. During training, experimental animals received 15 pairings of lip touch (the CS) with sucrose (the unconditioned stimulus, US). Control animals received 15 random CS and US presentations. Electrophysiological tests on semi-intact preparations made from conditioned animals demonstrated a network correlate of the overall feeding conditioned response, a touch-evoked CPG-driven fictive feeding rhythm. At the motoneuronal level, we found significant conditioning-induced increases in the amplitude of an early touch-evoked EPSP and spike activity, recorded from the B3 feeding motoneuron. Increases in EPSP amplitude and motoneuronal spike activity could occur independently of conditioned fictive feeding. These changes in response recorded at the level of CPG interneurons, and motoneurons were preceded by changes recorded in the CS pathway. This was demonstrated by recording a conditioning-induced increase in the number of touch-evoked spikes in the cerebrobuccal connective, which forms part of the CS pathway. The finding that electrophysiological changes after conditioning can be recorded at multiple sites in this simple system provided an important intermediate level of analysis between whole animal behavior and cellular studies on the synaptic sites of plasticity.
Multi-Task Transfer Methods to Improve One-Shot Learning for Multimedia Event Detection

This paper proposes a new multi-task learning method with implicit intertask relevance estimation, and applies it to complex Internet video event detection, which is a challenging and important problem in practice, yet seldom has been addressed. In this paper, “detection” means to detect videos corresponding to the event of interest from a (large) video dataset, not to localize the event spatially or temporally in a video. In the problem definition, one positive and plenty of negative samples of one event are given as training data, and the goal is to return the videos of the same event from a large video dataset. In addition, we assume samples of other events are available. Fig. 1 shows an overview of the proposed methods. The widths of the lines between the one-exemplar event and others represent the inter-event relevance, which is unknown a priori in our problem settings. However, the proposed method can implicity infer the relevance and utilize the most relevant event(s) more in multi-task learning, where the shared information from the relevant events helps to build a better model from the one exemplar. The proposed method does not assume the relevance between other events, as indicated by the red line. Although the learning algorithm outputs models of all input events, only that of the one-exemplar event is applied to detect videos of the event of interest from the video set. Our method builds on the approach of graph-guided multi-task learning [1], which is described first. The training set {(xti,yti)∈R×{−1,+1}, t = 1,2, . ,T, i = 1,2, . ,Nt} is grouped into T related tasks, which are further organized as a graph G = . The tasks correspond to the elements in the vertex set V , and the pairwise relevance between Task t and k are represented by the weight rtk on edges etk ∈ E. The more relevant the two tasks are, the larger the edge weight is. The graph guided multi-task learning algorithm learns the corresponding T models jointly, by solving the optimization problem
Group Sparse Priors for Covariance Estimation

Recently it has become popular to learn sparse Gaussian graphical models (GGMs) by imposing l1 or group l1, 2 penalties on the elements of the precision matrix. This penalized likelihood approach results in a tractable convex optimization problem. In this paper, we reinterpret these results as performing MAP estimation under a novel prior which we call the group l1 and l1, 2 positive-definite matrix distributions. This enables us to build a hierarchical model in which the l1 regularization terms vary depending on which group the entries are assigned to, which in turn allows us to learn block structured sparse GGMs with unknown group assignments. Exact inference in this hierarchical model is intractable, due to the need to compute the normalization constant of these matrix distributions. However, we derive upper bounds on the partition functions, which lets us use fast variational inference (optimizing a lower bound on the joint posterior). We show that on two real world data sets (motion capture and financial data), our method which infers the block structure outperforms a method that uses a fixed block structure, which in turn outperforms baseline methods that ignore block structure.
Prioritization of test scenarios using hybrid genetic algorithm based on UML activity diagram

Software testing is an essential part of the SDLC(Software Development Life Cycle). Test scenarios are used to derive test cases for model based testing. However, with the software rapidly growing in size and complexity, the cost of software will be too high if we want to test all the test cases. So this paper presents an approach using Hybrid Genetic Algorithm(HGA) to prioritize test scenarios, which improves efficiency and reduces cost as well. The algorithm combines Genetic Algorithm(GA) with Particle Swarm Optimization(PSO) algorithm and uses Local Search Strategy to update the local and global best information of the PSO. The proposed algorithm can prioritize test scenarios so as to find a critical scenario. Finally, the proposed method is applied to several typical UML activity diagrams, and compared with the Simple Genetic Algorithm(SGA). The experimental results show that the proposed method not only prioritizes test scenarios, but also improves the efficiency, and further saves effort, time as well as cost.
Gender specific differences in auditory brain stem response in young patients with ADHD

Objective: The auditory brainstem response (ABR) is often affected in neurodevelopmental disorders. The aim of this study was to investigate gender differences in ABR between young females and young males with ADHD, compared to control subjects. Method: We studied 63 females with ADHD (mean 13.8 years), 26 female controls (mean 13.8years), 48 males with ADHD (mean 13.1 years), and 20 male controls (mean 12.8years). All patients were diagnosed according to the DSM-IV. An ABR consists of seven positive peaks (wave I–VII) 10 ms following a stimulus, recorded by electrodes on the mastoid processes of each ear and on the forehead. Results: When analysing the ABRs of the female ADHD patients 3 traits were identified; TR6, TR14 and TR15. The higher value in TR6 (p=0.000064) is explained as an aberrant thalamus profile. In TR14 (p=0.00059) presence of 3500 Hzfrequencies in the region from superior olivary complex to thalamus. TR15 (p=0.00035) represents more aberrant curve profiles in the region of the lateral leminiscus. In the ABR of the male patients we found we 3 traits; TR4, TR5 and TR14. TR 4 (p=0.00105) is a lower correlation to a norm curve in inferior colliculus and thalamic area. TR5 (p=0.00027) identifies irregular curve profiles representing the nucleus cochlea. TR14 (p=0.00013) presence of 3500 Hz-frequencies in the region from superior olivary complex to thalamus. Conclusion: Young females with ADHD exhibited a significantly different ABR in a region between cochlear nucleus and superior olivary complex and in the thalamic region. In the male ADHD group ABR aberrancies were found in the midbrain region and in the more peripheral part; nucleus cocleus. The only trait that was significantly different between the ADHD group and the control subjects, for both male and females, was TR14. These data indicate both gender specific aberrations in the ABR in ADHD subjects as well as specific differences between ADHD subjects and normal controls.
Proper Motions And Variability Of The H2 Emission In The HH 46/47 System

We report here on the first proper-motion measurements of molecular hydrogen emission features in the Herbig-Haro 46/47 outflow. Assuming a distance of 350 pc to this flow, the inferred tangential velocities range from a few tens to almost 500 km s-1. The highest velocities are observed for H2 knots either in, or close to, the jet/counterjet axes. Knots constituting the wings of the large-scale H2 bow are found to move much more slowly. These results appear to be in agreement with recent numerical simulations of H2 emission from pulsed jets. We also report the first detection of variability in H2 features for a young stellar object (YSO) outflow. It was found that several H2 knots significantly changed their luminosity over the 4 yr time base used to conduct our study. This is in line with current estimates for the cooling time of gas radiating shocked H2 emission in YSO environments.
INTERNET ADDICTION RESEARCH SITUATION AT HOME AND ABROAD

In the article,the author reviewed the research situation on epidemiological characteristics of internet addiction,addiction mechanism,diagnostic criteria and measurement tools as well as intervention study.We considered the lack of existed research and development directions of future research,so as to guide the individual of internet addiction by using rational of network to get rid of internet addiction behavior.
Noninvasive Genetic Sampling Tools for Wildlife Biologists : A Review of Applications and Recommendations for Accurate Data

Noninvasive genetic sampling provides great potential for research and management applications in wildlife biology. llesearchers can obtain DNA from a variety of sources including hair, feces, urine, feathers, shed skin, saliva, and egg shells without handling or observing animals. These samples can then be used to identify the presence of rare or elusive species, count and identify individuals, determine gender, and identify diet items, or samples can be used to evaluate genetic diversity, population structure, and mating system. We review the recent advancements and techniques used for identifying species, individuals, and gender. We also address the potential pitfalls of noninvasive genetic sampling and provide recommendations for laboratoryand field-based methods to improve the reliability and accuracy of data collected from noninvasive genetic samples. JOURNAL OF WILDLIFE MANAGEMENT 69(4):141F1433; 2005
A Small Surrogate for the Golden Angle in Time-Resolved Radial MRI Based on Generalized Fibonacci Sequences

In golden angle radial magnetic resonance imaging a constant azimuthal radial profile spacing of 111.246. ° guarantees a nearly uniform azimuthal profile distribution in k-space for an arbitrary number of radial profiles. Even though this profile order is advantageous for various real-time imaging methods, in combination with balanced steady-state free precession (SSFP) sequences the large azimuthal angle increment may lead to strong image artifacts, due to the varying eddy currents introduced by the rapidly switching gradient scheme. Based on a generalized Fibonacci sequence, a new sequence of smaller irrational angles is introduced ( 49.750.°, 32.039.°, 27.198.°, 23.628.°, . ). The subsequent profile orders guarantee the same sampling efficiency as the golden angle if at least a minimum number of radial profiles is used for reconstruction. The suggested angular increments are applied for dynamic imaging of the heart and the temporomandibular joint. It is shown that for balanced SSFP sequences, trajectories using the smaller golden angle surrogates strongly reduce the image artifacts, while the free retrospective choice of the reconstruction window width is maintained.
Voice and choral singing treatment: a new approach for speech and voice disorders in Parkinson's disease.

AIM The aim of this study was to propose a new voice rehabilitation program for Parkinson's Disease (PD) patients based on voice and choral singing treatment (VCST). METHODS The authors carried out a pilot test-retest non-controlled study with twenty PD patients that voluntarily took part to the speech rehabilitation treatment. Patients underwent 20 hours of speech therapy, two sessions of one hour every week, and 26 hours of choral singing, one session of two hours every week. The speech and choral activity were directed by a speech therapist expert in PD and choral singing. The pre- and post-treatment assessment included neurological and otolaryngological evaluation, voice and speech acoustic analysis, auditory quality of voice analysis, respiratory function evaluation, that were carried out within two weeks before and after VCST. RESULTS The authors observed a significant improvement (P<0.05) of functional residual capacity (FRC%), maximum inspiratory pressure (MIP), maximum expiratory pressure (MEP), maximum duration of sustained vowel phonation (MDPh), prosodia reading a passage, using paired t-test; and of fatigue reading a passage using Wilcoxon Signed Rank Test. No significant difference was found in the other variables. CONCLUSION VCST for PD patients can improve specific abnormalities with an amusing, agreeable, and collective approach, but a randomized controlled trial (RCT) is necessary to find evidence of efficacy.
Fast Algorithms For Mining Association Rules In Datamining

We consider the problem of discovering association rules between items in a large database of sales transactions. We present two new algorithms for solving this problem that are fundamentally di erent from the known algo-rithms. Empirical evaluation shows that these algorithms outperform the known algorithms by factors ranging from three for small problems to more than an order of mag-nitude for large problems. We also show how the best features of the two proposed algorithms can be combined into a hybrid algorithm, called AprioriHybrid. Scale-up experiments show that AprioriHybrid scales linearly with the number of transactions. AprioriHybrid also has ex-cellent scale-up properties with respect to the transaction size and the number of items in the database. ————————————————————
Effect of Dexamethasone Intraligamentary Injection on Post-Endodontic Pain in Patients with Symptomatic Irreversible Pulpitis: A Randomized Controlled Clinical Trial

Introduction: The aim of this randomized-controlled clinical trial was to assess the effect of intraligamentary (PDL) injection of dexamethasone on onset and severity of post-treatment pain in patients with symptomatic irreversible pulpitis. Methods and Materials: A total number of 60 volunteers were included according to the inclusion criteria and were assigned to three groups (n=20). After administration of local anesthesia and before treatment, group 1 (control) PDL injection was done with syringe containing empty cartridge, while in groups 2 and 3 the PDL injection was done with 0.2 mL of 2% lidocaine or dexamethasone (8 mg/2 mL), respectively. Immediately after endodontic treatment patients were requested to mark their level of pain on a visual analogue scale (VAS) during the next 48 h (on 6, 12, 24 and 48-h intervals). They were also asked to mention whether analgesics were taken and its dosage. Considering the 0-170 markings on the VAS ruler, the level of pain was scored as follows: score 0 (mild pain; 0-56), score 1 (moderate pain; 57-113) and score 3 (severe pain; 114-170). The data were analyzed using the Kruskal-Wallis and the Chi-square tests and the level of significance was set at 0.05. Results: After 6 and 12 h, group 1 and group 3 had the highest and lowest pain values, respectively (P<0.01 and P<0.001 for 6 and 12 h, respectively). However, after 24 and 48 h the difference in the pain was not significant between groups 1 and 2 (P<0.6) but group 3 had lower pain levels (P<0.01 and P<0.8 for 24 and 48 h, respectively). Conclusion: Pretreatment PDL injection of dexamethasone can significantly reduce the post-treatment endodontic pain in patients with symptomatic irreversible pulpitis.
T Cell Receptor and Cytokine Signaling Can Function at Different Stages to Establish and Maintain Transcriptional Memory and Enable T Helper Cell Differentiation

Experienced T cells exhibit immunological memory via a rapid recall response, responding to restimulation much faster than naïve T cells. The formation of immunological memory starts during an initial slow response, when naïve T cells become transformed to proliferating T blast cells, and inducible immune response genes are reprogrammed as active chromatin domains. We demonstrated that these active domains are supported by thousands of priming elements which cooperate with inducible transcriptional enhancers to enable efficient responses to stimuli. At the conclusion of this response, a small proportion of these cells return to the quiescent state as long-term memory T cells. We proposed that priming elements can be established in a hit-and-run process dependent on the inducible factor AP-1, but then maintained by the constitutive factors RUNX1 and ETS-1. This priming mechanism may also function to render genes receptive to additional differentiation-inducing factors such as GATA3 and TBX21 that are encountered under polarizing conditions. The proliferation of recently activated T cells and the maintenance of immunological memory in quiescent memory T cells are also dependent on various cytokine signaling pathways upstream of AP-1. We suggest that immunological memory is established by T cell receptor signaling, but maintained by cytokine signaling.
Star-Shaped and Linear POSS-Polylactide Hybrid Copolymers

Novel octakis-2[(6-hydroxyhexyl)thio]ethyl-octasilsesquioxane (POSS-S-OH) as well as heptaisobutyl-2[(6-hydroxyhexyl)thio]ethyl-octasilsesquioxane (iBu-POSS-S-OH) were synthesized. POSS structures, bearing both types of groups i.e., 2[(6-hydroxyhexyl)thio]ethyl and the vinyl ones, pendant from the octahedral cage are also described. The synthetic pathway involved thiol-ene click reaction of 6-mercapto-1-hexanol (MCH) to octavinyloctasilsesquioxane (POSS-Vi), and heptaisobutylvinyloctasilsesquioxane (iBu-POSS-Vi), in the presence of 2,2′-azobisisobutyronitrile. The functionalized silsesquioxane cages of regular octahedral structure were used further as initiators for ring opening polymerization of l,l-dilactide, catalyzed by tin (II) 2-ethylhexanoate. The polymerization afforded biodegradable hybrid star shape and linear systems with an octasilsesquioxane cage as a core, bearing polylactide arm(s).
On the importance of pair-wise feature correlations for image classification

We show that simple linear classification of pairwise products of convolutional features achieves near state-of-the-art performance on some standard labelled image databases. Specifically, we found test classification error rates on the MNIST handwritten digits image database of under 0.5%, and achieved under 19% and under 44% error rates on the CIFAR-10 and CIFAR-100 RGB image databases. Since the number of weights in such a classifier grows with the square of the number of features, we discuss how implementation of such a pair-wise products classifier can be achieved in an SLFN architecture where the hidden unit function is the simple quadratic nonlinearity: we can this a Quadratic Neural Network (QNN). We compare this method to setting the input weights in a QNN randomly, and find optimal performance can be achieved provided the hidden layer is sufficiently large. This analysis provides insight on why `extreme-learning machines' can achieve classification performance equal to or better than the use of backpropagation training.
Positive Psychology Intervention to Alleviate Child Depression and Increase Life Satisfaction

Purpose: The study aims to examine the effectiveness of a positive psychology group-based intervention program, incorporating elements of hope and gratitude, in decreasing depression and increasing life satisfaction among primary school students in Hong Kong. Method: A total of 68 children, with the Depression score of Chinese Hospital Anxiety and Depression Scale from 9 to 11, were randomly assigned to the intervention and control groups. An eight-session intervention group-based program was conducted in five primary schools. Results: Participants of the intervention groups showed a significant decrease in depression and significant increase in life satisfaction, partially mediated by hope and gratitude, after the intervention when compared with those of the control groups. Discussion: As positive psychology intervention teaches children ways to increase their positive cognition, emotions, and behaviors, it may help children cope with current emotional problems and enhance their capability to deal with future stress and adversities.
String-averaging projected subgradient methods for constrained minimization

We consider constrained minimization problems and propose to replace the projection onto the entire feasible region, required in the projected subgradient method, by projections onto the individual sets whose intersection forms the entire feasible region. Specifically, we propose to perform such projections onto the individual sets in an algorithmic regime of a feasibility-seeking iterative projection method. For this purpose we use the recently developed family of dynamic string-averaging projection methods wherein iteration-index-dependent variable strings and variable weights are permitted. This gives rise to an algorithmic scheme that generalizes, from the algorithmic structural point of view, earlier work of Helou Neto and De Pierro, of Nedić, of Nurminski, and of Ram et al.