Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring Outcomes and Initial Self-report of Client Motivation in a College Counseling Center

Abstract Objective: To explore the association between college counseling center clients’ initial self-report of motivation and counseling outcome. Participants: The sample was composed of 331 student clients who utilized a college counseling center from August 2007 to August 2009. The college is a public, mid-size, urban university in the Southeast. Methods: Motivation was measured at intake by a self-report of change readiness item. A quantitative study that employed a 5-group, pretest–posttest design included 331 student participants. Counseling outcome was measured using the Outcome Questionnaire 45.2. Results: As assigned by the clients’ self-report of change readiness, counseling outcome for 5 motivation groups differed significantly (p = .004; α < .05). Compulsory participation in counseling was treated as a possible confound and was not a significant factor in counseling outcome (p = .268; α < .05). Conclusions: Participants’ initial self-report of motivation was significantly associated with counseling outcome.
The financial burden of overweight and obesity among elderly Americans: the dynamics of weight, longevity, and health care cost.

OBJECTIVE To investigate the financial burdens attributed to overweight and obesity on the U.S. health care system among elderly Americans. DATA SOURCE Longitudinal Cost and Use files of the Medicare Current Beneficiary Survey from 1992 to 2001. STUDY DESIGN We constructed a simultaneous equation system to model the dynamic relationship between changes in body weight, chronic diseases, functional status, longevity, and health care expenditures using maximum likelihood estimation. Based on the estimation, we conducted a simulation of one cohort with different baseline weights at age 65 and followed to death or up to age 100 of their health outcomes and lifetime health care expenditures. PRINCIPAL FINDINGS The elderly men who were overweight or obese at age 65 had 6-13 percent more lifetime health care expenditures than the same age cohort within normal weight range at age 65. Elderly women who were overweight or obese at age 65 spent 11-17 percent more than those in a normal weight range. Both elderly men and women who were overweight or obese at age 65 had worse health outcomes than the normal weight cohorts. The average body mass index among survivors decreased by age. CONCLUSION Overweight and obesity could place significant financial burdens on the U.S. health care system.
Idiopathic Ventricular Arrhythmias Originating From the Parietal Band: Electrocardiographic and Electrophysiological Characteristics and Outcome of Catheter Ablation

Backgrounds— The parietal band is one of the muscle bands in the right ventricle. This study investigated the electrocardiographic and electrophysiological characteristics and ablation outcome of idiopathic ventricular arrhythmias (VAs) originating from the parietal band. Methods and Results— We studied 14 patients with idiopathic VA origins in the parietal band among 294 consecutive patients with VA origins in the right ventricle. The QRS morphologies of the parietal band VAs were characterized by a left bundle branch block and left inferior (n=12) or superior (n=2) axis pattern with the presence of a notch in the middle of the QRS in all cases, precordial transition at ⩽lead V3 in 7 patients, and a slow QRS onset in 4 patients. During parietal band VAs, a far-field ventricular electrogram with an early activation was always recorded in the His bundle region, regardless of the location of the VA origins. During the catheter ablation, a mean number of 10.4±7.4 radiofrequency applications with a duration of 1099±1034 seconds were delivered. Catheter ablation was successful in 10 patients, and VAs recurred in 4 during a mean follow-up period of 41±24 months. A change in the QRS morphology was observed spontaneously in 4 patients, immediately after the ablation in 4, and at the time of a VA recurrence in 2. Conclusions— Idiopathic VAs rarely originated from the parietal band. The catheter ablation of the parietal band VAs was always challenging, requiring a large amount of the radiofrequency energy delivery for a successful ablation with a relatively high recurrence rate.
Structured supervised dictionary learning based on class-specific and shared sub-dictionaries

In recent years, sparse representation and dictionary learning has been widely used in signal processing tasks, especially for classification aim. For the aim of high accuracy classification, sparse coefficients obtained based on learned dictionary should have high discrimination power, which common sparse representation techniques cannot well satisfy that because most techniques ignore the underlying structural information of the data. Instead, structured sparsity coding techniques capture the structural information of data and improve the classification accuracy accordingly. On the other hand, one should notice that data samples of different classes might share some similarities which can decrease the discrimination ability and the classification accuracy. This implies to use a shared dictionary among all classes to capture the similarities while class-specific sub-dictionaries describe the intra-class features properly. In this paper, inspired by DL-COPAR method, a structured sparse coding technique is proposed that learns discriminative class-specific sub-dictionaries and a shared dictionary which its atoms are shared among all classes and have no discrimination capability. Also, the proposed method is based on l2,1 norm to use the structure of the data too. The optimization function of the proposed method is solved by an efficient alternating iterative scheme. The proposed method is evaluated by conducting experiments on four datasets and the experimental results demonstrate the effectiveness of the proposed method.
Power optimization through peripheral circuit reusing integrated with loop tiling for RRAM crossbar-based CNN

Convolutional neural networks (CNNs) have been proposed to be widely adopted to make predictions on a large amount of data in modern embedded systems. Prior studies have shown that convolutional computations which consist of numbers of multiply and accumulate (MAC) operations, serve as the most computationally expensive portion in CNN. Compared to the manner of executing MAC operations in GPU and FPGA, CNN implementation in the RRAM crossbar-based computing system (RCS) demonstrates the outstanding advantages of high performance and low power. However, the current design is energy-unbalanced among the three parts of RRAM crossbar computation, peripheral circuits and memory accesses, the latter two factors can significantly limit the potential gains of RCS. Addressing the problem of high power overhead of peripheral circuits in RCS, the Peripheral Circuit Unit (PeriCU)-Reuse scheme has been proposed to meet given power budget. In this paper, it is further observed that memory accesses can be bypassed if two adjacent layers are assigned in different PeriCUs. In this way, memory accesses can be reduced and thus the performance and power can be improved. A loop tiling technique is proposed to save memory accesses. The experiments of two convolutional applications validate that the proposed loop tiling technique can reduce energy consumption by 61.7%.
Dating Violence among Youth Couples: Dyadic Analysis of the Prevalence and Agreement

Abstract Although dating violence takes place within the context of a couple, there are few studies exploring how the prevalence data change when violence is reported by one partner or both, and to what extent partners agree about the existence of violence. The aim of this study is therefore to analyze and compare the reports about the prevalence of violence obtained from participants and their partners, together with interpartner agreement concerning victimization and perpetration of threats, physical, verbal-emotional and sexual violence. A total of 105 young heterosexual couples answered a questionnaire about victimization and the perpetration of violence in their relationship during the previous year. The results indicated that prevalence rates varied, depending on who reported the violence -the man, the woman or the couple- perhaps because interpartner agreement was low, except for the occurrence of verbal-emotional violence and the absence of physical violence. These findings suggest the need to develop more systematic research, especially through the use of reports from both members of the couple.
Cryo-EM structure of a native, fully glycosylated, cleaved HIV-1 envelope trimer

A more complete look at the HIV-1 envelope HIV-1 uses its envelope protein (Env), a large glycoprotein present on the viral surface, to enter target cells. Env forms trimers on the viral surface. Structural studies of solubilized Env trimers have provided important insights into viral entry and antibody binding, but soluble trimers lack several important insoluble regions of the native protein. Lee et al. used cryo–electron microscopy to solve the structure of a trimeric Env protein of HIV-1, missing only its cytoplasmic tail, in complex with broadly neutralizing antibodies. A more complete understanding of Env's structure may aid in vaccine design ef orts. Science, this issue p. 1043 Interactions between the membrane proximal regions of the HIV-1 glycoprotein and two neutralizing antibodies are visualized. The envelope glycoprotein trimer (Env) on the surface of HIV-1 recognizes CD4+ T cells and mediates viral entry. During this process, Env undergoes substantial conformational rearrangements, making it difficult to study in its native state. Soluble stabilized trimers have provided valuable insights into the Env structure, but they lack the hydrophobic membrane proximal external region (MPER, an important target of broadly neutralizing antibodies), the transmembrane domain, and the cytoplasmic tail. Here we present (i) a cryogenic electron microscopy (cryo-EM) structure of a clade B virus Env, which lacks only the cytoplasmic tail and is stabilized by the broadly neutralizing antibody PGT151, at a resolution of 4.2 angstroms and (ii) a reconstruction of this form of Env in complex with PGT151 and MPER-targeting antibody 10E8 at a resolution of 8.8 angstroms. These structures provide new insights into the wild-type Env structure.
Phospholipid Fatty Acid Composition and Heavy Metal Tolerance of Soil Microbial Communities along Two Heavy Metal-Polluted Gradients in Coniferous Forests

The effects of long-term heavy metal deposition on microbial community structure and the level of bacterial community tolerance were studied along two different gradients in Scandinavian coniferous forest soils. One was near the Harjavalta smelter in Finland, and one was at Ronnskar in Sweden. Phospholipid fatty acid (PLFA) analysis revealed a gradual change in soil microbial communities along both pollution gradients, and most of the individual PLFAs changed similarly to metal pollution at both sites. The relative quantities of the PLFAs br18:0, br17:0, i16:0, and i16:1 increased with increasing heavy metal concentration, while those of 20:4 and 18:2(omega)6, which is a predominant PLFA in many fungi, decreased. The fungal part of the microbial biomass was found to be more sensitive to heavy metals. This resulted in a decreased fungal/bacterial biomass ratio along the pollution gradient towards the smelters. The thymidine incorporation technique was used to study the heavy metal tolerance of the bacteria. The bacterial community at the Harjavalta smelter, exposed mainly to Cu deposition, exhibited an increased tolerance to Cu but not to Cd, Ni, and Zn. At the Ronnskar smelter the deposition consisting of a mixture of metals increased the bacterial community tolerance to all tested metals. Both the PLFA pattern and the bacterial community tolerance were affected at lower soil metal concentrations than were bacterial counts and bacterial activities. At Harjavalta the increased Cu tolerance of the bacteria and the change in the PLFA pattern of the microbial community were found at the same soil Cu concentrations. This indicated that the altered PLFA pattern was at least partly due to an altered, more metal-tolerant bacterial community. At Ronnskar, where the PLFA data varied more, a correlation between bacterial community tolerance and an altered PLFA pattern was found up to 10 to 15 km from the smelter. Farther away changes in the PLFA pattern could not be explained by an increased community tolerance to metals.
Exploring Multimodal Watch-back Tactile Display using Wind and Vibration

A tactile display on the back of a smartwatch is an attractive output option; however, its channel capacity is limited owing to the small contact area. In order to expand the channel capacity, we considered using two perceptually distinct types of stimuli, wind and vibration, together on the same skin area. The result is a multimodal tactile display that combines wind and vibration to create "colored" tactile sensations on the wrist. As a first step toward this goal, we conducted in this study four user experiments with a wind-vibration tactile display to examine different ways of combining wind and vibration: Individual, Sequential, and Simultaneous. The results revealed the sequential combination of wind and vibration to exhibit the highest potential, with an information transfer capacity of 3.29 bits. In particular, the transition of tactile modality was perceived at an accuracy of 98.52%. The current results confirm the feasibility and potential of a multimodal tactile display combining wind and vibration.
A technique for rendering complex portals

We identify a general paradigm for portal-based rendering and present an image-space algorithm for rendering complex portals. Our general paradigm is an abstraction of portal-based rendering that is independent of scene geometry. It provides a framework for flexible and dynamic scene composition by connecting cells with transformative portals. Our rendering algorithm maintains a visible volume in image-space and uses fragment culling to discard fragments outside of this volume. We discuss our implementation in OpenGL and present results that show it provides correct rendering of complex portals at interactive rates on current hardware. We believe that our work is useful in many applications that require a means of creating dynamic and meaningful visual connections between different sets of data.
Vision Meets Drones: A Challenge

In this paper we present a large-scale visual object detection and tracking benchmark, named VisDrone2018, aiming at advancing visual understanding tasks on the drone platform. The images and video sequences in the benchmark were captured over various urban/suburban areas of 14 different cities across China from north to south. Specifically, VisDrone2018 consists of 263 video clips and 10,209 images (no overlap with video clips) with rich annotations, including object bounding boxes, object categories, occlusion, truncation ratios, etc. With intensive amount of effort, our benchmark has more than 2.5 million annotated instances in 179,264 images/video frames. Being the largest such dataset ever published, the benchmark enables extensive evaluation and investigation of visual analysis algorithms on the drone platform. In particular, we design four popular tasks with the benchmark, including object detection in images, object detection in videos, single object tracking, and multi-object tracking. All these tasks are extremely challenging in the proposed dataset due to factors such as occlusion, large scale and pose variation, and fast motion. We hope the benchmark largely boost the research and development in visual analysis on drone platforms.
Adaptive spatio-temporal context learning for visual target tracking

While visual target tracking is one of the noteworthy and the most active research areas in computer vision and machine learning, many challenges are still unresolved. In this paper, an adaptive generic target tracker is proposed that includes the adaptive determination of learning parameters from spatio-temporal context model, analysis of prior targets and confidence map for accurate target localization, and modified scale estimation scheme based on confidence map. According to spatio-temporal context model, the learning parameters are adaptively determined for achieving confidence map and target scale robustly. Moreover, analysis of the confidence map helps our tracker to change context feature set and accurately estimate target location in critical situations such as occlusion, appearance changes, and pose variation. Finally, we propose a modified scale estimation scheme based on confidence map that corrects adopted scale when the confidence map is not reliable. Experimental results on numerous video sequences show that the proposed adaptive generic tracker outperforms both the accuracy and robustness compared to the dense spatio-temporal context learning (STC) tracker effectively.
Effect of growth temperature on photosynthetic capacity and respiration in three ecotypes of Eriophorum vaginatum

Abstract Ecotypic differentiation in the tussock‐forming sedge Eriophorum vaginatum has led to the development of populations that are locally adapted to climate in Alaska's moist tussock tundra. As a foundation species, E. vaginatum plays a central role in providing topographic and microclimatic variation essential to these ecosystems, but a changing climate could diminish the importance of this species. As Arctic temperatures have increased, there is evidence of adaptational lag in E. vaginatum, as locally adapted ecotypes now exhibit reduced population growth rates. Whether there is a physiological underpinning to adaptational lag is unknown. Accordingly, this possibility was investigated in reciprocal transplant gardens. Tussocks of E. vaginatum from sites separated by ~1° latitude (Coldfoot: 67°15′N, Toolik Lake: 68°37′, Sagwon: 69°25′) were transplanted into the Toolik Lake and Sagwon sites and exposed to either an ambient or an experimental warming treatment. Five tussocks pertreatment combination were measured at each garden to determine photosynthetic capacity (i.e., V cmax and J max) and dark respiration rate (R d) at measurement temperatures of 15, 20, and 25°C. Photosynthetic enhancements or homeostasis were observed for all ecotypes at both gardens under increased growth temperature, indicating no negative effect of elevated temperature on photosynthetic capacity. Further, no evidence of thermal acclimation in R d was observed for any ecotype, and there was little evidence of ecotypic variation in R d. As such, no physiological contribution to adaptational lag was observed given the increase in growth temperature (up to ~2°C) provided by this study. Despite neutral to positive effects of increased growth temperature on photosynthesis in E. vaginatum, it appears to confer no lasting advantage to the species.
Lumped‐parameter models of the pulmonary vasculature during the progression of pulmonary arterial hypertension

A longitudinal study of monocrotaline‐induced pulmonary arterial hypertension (PAH) was carried out in Sprague‐Dawley rats to investigate the changes in impedance (comprising resistance and compliance) produced by elevated blood pressure. Using invasively measured blood flow as an input, blood pressure was predicted using 3‐ and 4‐element Windkessel (3WK, 4WK) type lumped‐parameter models. Resistance, compliance, and inductance model parameters were obtained for the five different treatment groups via least‐squares errors. The treated animals reached levels of hypertension, where blood pressure increased two folds from control to chronic stage of PAH (mean pressure went from 24 ± 5 to 44 ± 6 mmHg, P < 0.0001) but blood flow remained overall unaffected. Like blood pressure, the wave‐reflection coefficient significantly increased at the advanced stage of PAH (0.26 ± 0.09 to 0.52 ± 0.09, P < 0.0002). Our modeling efforts revealed that resistances and compliance changed during the disease progression, where changes in compliance occur before the changes in resistance. However, resistance and compliance are not directly inversely related. As PAH develops, resistances increase nonlinearly (Rd exponentially and R at a slower rate) while compliance linearly decreases. And while 3WK and 4WK models capture the pressure‐flow relation in the pulmonary vasculature during PAH, results from Akaike Information Criterion and sensitivity analysis allow us to conclude that the 3WK is the most robust and accurate model for this system. Ninety‐five percent confidence intervals of the predicted model parameters are included for the population studied. This work establishes insight into the complex remodeling process occurring in PAH.
An overview of data redundancy reduction schemes in WSNs

The major issue that arises in sensor networks is lifetime of the network. There are many reasons which are responsible for network lifetime reduction such as resource limitations, traffic unbalancing, data redundancy, network topologies and energy balance. Wireless sensor networks are used for many critical applications like pointing out a target in battle field and monitoring the environmental parameters in dense forests. The wireless sensor nodes are deployed densely in the provided area or with a very low proximity. These nodes cannot be reconfigured once deployed and apart from that the battery unit is also not rechargeable after deployment in such critical areas. This paper focuses on the data redundancy issue i.e. closely deployment of sensor nodes leads to highly redundant sensed data. There is high energy consumption by sensor nodes because of data redundancy issue. Many solutions have been proposed for data reduction in wireless sensor networks to increase the network lifetime. In this paper, we highlight the existing solutions for data reduction. Furthermore, we discuss the solutions and analyze the performance. Finally, we throw light upon future research directions and issues after analyzing the existing solutions.
Heart failure–concepts and significance. Birth of a prognostic model

Heart failure (HF) is a syndrome characterized by high prevalence in society, frequent hospitalization, reduced quality of life and high mortality (overall,50% of patients are dead at an interval of 4 years [1], annual mortality varying from 5% to 75%). Outcomes in heart failure are highly variable, prognosis of individual patients differs considerably and trial data, though valuable, does not often give an adequate direction. Taking into account the high prevalence of heart failure in society and its complexity physicians need a model to predict the risk of death, to estimate the survival of heart failure patients. A key element of interest in this area is the survival function, usually noted by S and defined as S(t)=exp(–H0(t)eaTx)=e–H0(t)eaTx
A new multi classifier system using entropy-based features in DDoS attack detection

Entropy-based features have been widely utilized for detecting DDoS attacks in recent years. However, existing approaches mainly focus on using a small number of entropy-based features to distinguish attack traffic from normal traffic. The drawback of this approach is that it limits the type of DDoS attacks that can be detected. To overcome this problem, we proposed a set of new entropy-based features that help to detect DDoS attacks accurately and introduced a novel multi classifier system based on the proposed set of multiple entropy-based features and machine learning classifiers to increase the generality and accuracy of detecting low-intensity and high-intensity DDoS attacks. We have tested and evaluated using datasets of different intensities. Experiment results showed that our approach achieved higher precision and higher recall values compared to several state-of-the-art approaches. Our approach generates consistent results as being the best or second best classifier in four different types of datasets containing different types of attack intensities.