Miracle-dz/UniFAR-FTUs huggingface dataset:
Named Series: Fatigue, Brain, Behavior, and Immunity Fatigue and herpesvirus latency in women newly diagnosed with breast cancer

Fatigue is a notable clinical problem in cancer survivors, and understanding its pathophysiology is important. The current study sought to determine biomarkers of fatigue that exist before cancer treatment. Relationships between the expression of latent Epstein–Barr virus (EBV) and cytomegalovirus (CMV) and fatigue were examined in 158 women newly diagnosed with breast cancer or awaiting a positive diagnostic result. Higher CMV antibody titers, but not EBV antibody titers, were associated with a greater likelihood of being fatigued. Associations between fatigue and higher CMV antibody titers remained after controlling for alcohol use, smoking, comorbidities, depressive symptoms, age, BMI, cancer stage, and sleep problems. More sleep problems and higher levels of depressive symptoms were also associated with a greater likelihood of being fatigued. CMV antibody titers, but not EBV antibody titers, were associated with higher levels of C-reactive protein (CRP), but CRP was not associated with fatigue. When the cellular immune system is compromised, reactivation of latent herpesviruses may fuel chronic inflammatory responses. Prior work has suggested that fatigue may be related to inflammation and its associated sickness behaviors; accordingly, our findings may be tapping into this same physiological substrate.
In vitro effects of increased temperature and decreased pH on blood oxygen affinity of 10 fish species of the Amazon.

Blood-O2 affinities (P50 ) were measured over a physiologically relevant pH range at 31 (highest temperature average of Rio Negro over the last 8 years), 33 and 35° C for 10 species of the Rio Negro, aiming to test the acute effects of temperature foreseen by the IPCC (Intergovernmental Panel on Climate Change) for coming years. The animals were collected during an expedition to the Anavilhanas Islands of the Rio Negro, 110 km upstream from Manaus (2° 23' 41″ S; 60° 55' 14″ W). Hoplias malabaricus showed higher blood-O2 sensitivity to pH changes (Bohr effect, Φ = Δlog10 P50 ΔpH(-1) ) at both 31° C (Φ = -0·44) and 35° C (Φ = -0·26) compared to Osteoglossum bicirrhosum (Φ = -0·54 at 31° C and Φ = -0·58 at 35° C), but lower P50 under most conditions, and a greater sensitivity of P50 to temperature. Two out of the 10 analysed species had significant increases of P50 (lower blood-O2 affinity) at the highest temperature throughout the pH range tested. For all other species, a minor increase of P50 over the assay-tested temperatures was observed, although all presented a normal Bohr effect. Overall, a diversity of intensities of pH and temperature effects on blood-O2 affinities was observed, which seems to be connected to the biological characteristics of the analysed species. Thermal disturbances in their habitats, likely to occur due to the global warming, would impair blood-O2 binding and unloading in some of the analysed fish species. Copyright © 2016 John Wiley & Sons, Ltd.
DEVELOPMENTAL THERMOENERGETICS OF THE DASYURID MARSUPIAL, ANTECHINUS STUARTII

Abstract Although conception-to-weaning times in dasyurid marsupials are extremely long and neonates very small, little is known about their growth and thermoenergetics. We studied the growth pattern of Antechinus stuartii from birth to after weaning in relation to thermoregulatory capabilities and energetic cost of lactation in the female. Litter size was 1–8 young. Growth rate was slow for age 0–40 days, increased until weaning at about 100 days of age, and then slowed again. At weaning, males were 18% heavier than females (t-test, P < 0.01). Energy expenditure of females increased significantly by about 30% during late lactation, compared with early or postlactation. Overall, maternal investment increased with increasing litter size. Total energy expenditure from birth to weaning was 2,373 kJ for small litters (1–3 young) and 4,580 kJ for large litters (8 young). However, at weaning, young from small litters were about 30% heavier than young from large litters. Ability of young A. stuartii to thermoregulate improved with age. At 60 days age, young were poikilothermic after cold exposure, but by 79 days, physiological thermoregulation was established.
Smart Surrogate Widgets for Direct Volume Manipulation

Interaction is an essential aspect in volume visualization, yet common manipulation tools such as bounding boxes or clipping plane widgets provide rather crude tools as they neglect the complex structure of the underlying data. In this paper, we introduce a novel volume interaction approach based on smart widgets that are automatically placed directly into the data in a visibility-driven manner. By adapting to what the user actually sees, they act as proxies that allow for goal-oriented modifications while still providing an intuitive set of simple operations that is easy to control. In particular, our method is well-suited for direct manipulation scenarios such as touch screens, where traditional user interface elements commonly exhibit limited utility. To evaluate out approach we conducted a qualitative user study with nine participants with various backgrounds.
Effect of a strength training program in young children with developmental coordination disorder

Background and purpose A strength training program was associated with changes in muscle strength, motor function, and proprioceptive position sense in a young child with poor body awareness and a diagnosis of developmental coordination disorder. Patients and methods This study included 80 children diagnosed with developmental coordination disorder. Their age ranged from 8 and 13 years. The children were divided randomly into two equal groups. The exercise group received a 3-month strength program that included upper limb, lower limb, and trunk and neck exercises as well as running three sessions per week The patients were evaluated and scored functionally, using the Behavior Rating Scale, and objectively, using a Biodex dynamometer, at different time intervals pretreatment and 3 months after the treatment program. Results The results showed a statistically significant improvement in the measured variables of both groups when comparing their pre-treatment and post-treatment mean values. A significant difference was found in favor of the study group (B) in comparison with group (A). Conclusion It can be concluded that a regular program of physical activities has a positive effect in improving the symptoms of developmental coordination disorder in children.
Extended compilation of autopsy-material measurements on lumbar ultimate compressive strength for deriving reference values in ergonomic work design: The Revised Dortmund Recommendations

Measures of human physical capacity are required in ergonomic work design. To avoid biomechanical low-back overload, criteria are needed to differentiate load and overload. With respect to the evaluation of manual materials handling and similar physical exposures regarding potential overload, the compression component of the forces transferred via lumbar discs or vertebrae are compared with the ultimate compressive strength of lumbar-spine segments in a common biomechanical approach. As mechanical load-bearing capacity cannot be quantified directly in vivo, forces are applied to dissected spinal elements up to failure, which is interpreted as a measure of ultimate strength or tolerance to compression. Corresponding autopsy-material measurements were collected from literature and examined regarding several conditions: At the very minimum, a specimen consists of a complete vertebra or a disc including the adjacent endplates; failure is identified definitely as lumbar; compressive-force application is quasi-static; results are given as single values etc. This study continues previous collations, the latest is dated on 2001 including 25 usable out of 47 investigations totally. Currently, 66 newly discovered seemingly appropriate studies were collected via a systematic literature search, 11 of them were added for subsequent analysis. Nearly 4,000 values were compiled, 1,192 remained for analysis. Human lumbar ultimate compressive strength varies between 0.6 and 15.6 kN, mean and standard deviation are 4.84 ± 2.50 kN. For data originating from donors of specified gender and aged 20 years or more, the distributions are characterised by 6.09 ± 2.69 kN for male adults (n=305) and 3.95 ± 1.79 kN for female adults (n=205). According to a linear regression model for donors aged 20 years or more, strength significantly decreases with age: 10.43 kN minus 0.923 kN per 10 years of age for males and 7.65 kN minus 0.685 kN per decade for females. Based on these gendered age relations, the “Revised Dortmund Recommendations” were derived ranging between 5.4 kN for males aged 20 years and 2.2 kN for males of 60 years or more. The corresponding recommended limits for females amount to 4.1 and 1.8 kN, respectively. A specific safety margin was implemented for young adults up to 25 years of age as skeletal strength may not be fully developed. Due to the compression-related and biomechanical nature of this approach, other influences like shear or torsion as well as psychological or psychosocial risk factors remain unconsidered despite their undoubted importance for initiating complaints, disorders and diseases at the low-back region.
LARECD: Low area overhead and reliable error correction DMR architecture

Recent HPC system generally is composed of enormous amounts of GPUs. GPU-based HPC system makes a reliability problem from the absence of error detection unit in GPUs. For improving the reliability of GPU, dual modular redundancy(DMR) architecture is presented. However, current DMR architectures do not care much to the correction sequence. Therefore, the data hazard can occur during the recovery sequence. We present LARECD (Low Area overhead and Reliable Error Correction DMR) architecture. This architecture can secure the error correction sequence from the data hazard. Experimental result demonstrates the efficiency of LARECD architecture.
Automatic detection of pulmonary nodules in low-dose screening thoracic CT examinations

Computed tomography of the chest can be used as a screening method for lung cancer in a high-risk population. However, the detection of lung nodules is a difficult and time-consuming task for radiologists. The developed technique should improve the sensitivity of the detection of lung nodules without showing too many false positive nodules. In a study, which should evaluate the feasibility of screening lung cancer, about 1400 thoracic studies were acquired. Scanning parameters were 120 kVp, 5 mm collimation pitch of 2, and a reconstruction index of 5 mm. This results in a data set of about 60 to 70 images per exam. In the images the detection technique first eliminates all air outside the patient, then soft tissue and bony structures are removed. In the remaining lung fields a three-dimensional region detection is performed and rule-based analysis is used to detect possible lung nodules. This technique was applied to a small subset (n equals 17) of above studies. Computation time is about 5 min on an O2 workstation. The use of low-dose exams proved not be a hindrance in the detection of lung nodules. All of the nodules (n equals 23), except one with a size of 3 mm, were detected. The false positive rate was less than 0.3 per image. We have developed a technique, which might help the radiologist in the detection of pulmonary nodules in CT exams of the chest.
Factors affecting the results of comprehensive pre-internship exam among medical students of Kermanshah University of Medical Sciences

Purpose This study was aimed to evaluate the factors affecting the results of comprehensive pre-internship exam (CPIE) among medicals students of Kermanshah University of Medical Sciences. Methods In this descriptive-analytical study, all students (n=240) participating in CPIE over a 3-year period (2012–2014) were selected. Data were gathered by a questionnaire, including the CPIE results and educational and demographic data. Spearman correlation coefficient, Mann-Whitney U-test, and analysis of variance were used to analyze the association of students’ success with study variables. Also, regression analysis was applied to determine the role of independent variables in students’ success. Results The frequency of the failed units in apprenticeship course was one of the most important risk factors associated with failure in CPIE. Average scores of pre-internship course were the most important factors of success in CPIE. The CPIE score had the highest direct relationship with grade point average (GPA) of apprenticeship course, total GPA of all three courses, GPAs of physiopathology and basic sciences courses, and score of comprehensive basic sciences examination, respectively. Conclusion CPIE showed the highest inverse correlation with the number of failed units in apprenticeship course. The most important factors influencing this exam were failure in apprenticeship course and GPA of previous educational stages.
Snow Water Equivalent of Dry Snow Derived From GNSS Carrier Phases

Snow water equivalent (SWE) is a key variable for various hydrological applications. It is defined as the depth of water that would result upon complete melting of a mass of snow. However, until now, continuous measurements of the SWE are either scarce, expensive, labor-intense, or lack temporal or spatial resolution especially in mountainous and remote regions. We derive the SWE for dry-snow conditions using carrier phase measurements from the Global Navigation Satellite System (GNSS) receivers. Two static GNSS receivers are used, whereby one antenna is placed below the snow and the other antenna is placed above the snow. The carrier phase measurements of both receivers are combined in double differences (DDs) to eliminate clock offsets and phase biases and to mitigate atmospheric errors. Each DD carrier phase measurement depends on the relative position between both antennas, an integer ambiguity due to the periodic nature of the carrier phase signal, and the SWE projected into the direction of incidence. The relative positions of the antennas are determined under snow-free conditions with millimeter accuracy using real-time kinematic positioning. Subsequently, the SWE and carrier phase integer ambiguities are jointly estimated with an integer least-squares estimator. We tested our method at an Alpine test site in Switzerland during the dry-snow season 2015–2016. The SWE derived solely by the GNSS shows very high correlation with conventionally measured snow pillow (root mean square error: 11 mm) and manual snow pit data. This method can be applied to dense low-cost GNSS receiver networks to improve the spatial and temporal information on snow.
How warm was Britain during the Last Interglacial? A critical review of Ipswichian (MIS 5e) palaeotemperature reconstructions

The Last Interglacial [LIG, equivalent to marine isotope stage (MIS) 5e] was a period of enhanced global warmth, with potential significance for understanding future climate warming. It has long been proposed that the LIG in Britain (the Ipswichian Interglacial) was significantly warmer than present, based on the occurrence of fossils of extant thermophilous plant and animal species intolerant of the current climate. Here, we review the evidence for palaeotemperatures that can be derived from such fossil taxa (beetles, ostracods, plant macrofossils and herpetiles) to assess the level of warmth that Britain experienced during the LIG. Quantified palaeotemperature reconstructions generated for eight British sequences indicate that the LIG was likely to have been warmer than the present but at only one site (Trafalgar Square) is there strong evidence for climates that were significantly warmer than those experienced during the Holocene. Consequently, while there is evidence to support the idea that the thermal regime of the LIG in Britain was different from that of the Holocene, this evidence is restricted to a single site. The paper concludes by discussing the thermal regime of the LIG in Britain in the context of its role as an analogue for future warming in the 21st century and beyond.
Underwater Fish Species Classification using Convolutional Neural Network and Deep Learning

The target of this paper is to recommend a way for Automated classification of Fish species. A high accuracy fish classification is required for greater understanding of fish behavior in Ichthyology and by marine biologists. Maintaining a ledger of the number of fishes per species and marking the endangered species in large and small water bodies is required by concerned institutions. Majority of available methods focus on classification of fishes outside of water because underwater classification poses challenges such as background noises, distortion of images, the presence of other water bodies in images, image quality and occlusion. This method uses a novel technique based on Convolutional Neural Networks, Deep Learning and Image Processing to achieve an accuracy of 96.29%. This method ensures considerably discrimination accuracy improvements than the previously proposed methods.
Adiponectin: A New Regulator of Female Reproductive System

Adiponectin is the hormone that belongs to the group of adipokines, chemical agents mainly derived from the white adipose tissue. The hormone plays pleiotropic roles in the organism, but the most important function of adiponectin is the control of energy metabolism. The presence of adiponectin and its receptors in the structures responsible for the regulation of female reproductive functions, such as hypothalamic-pituitary-gonadal (HPG) axis, indicates that adiponectin may be involved in the female fertility regulation. The growing body of evidence suggests also that adiponectin action is dependent on the actual and hormonal status of the animal. Present study presents the current knowledge about the presence and role of adiponectin system (adiponectin and its receptors: AdipoR1 and AdipoR2) in the ovaries, oviduct, and uterus, as well as in the hypothalamus and pituitary, the higher branches of HPG axis, involved in the female fertility regulation.
Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing

We introduce the Contextual Graph Markov Model, an approach combining ideas from generative models and neural networks for the processing of graph data. It founds on a constructive methodology to build a deep architecture comprising layers of probabilistic models that learn to encode the structured information in an incremental fashion. Context is diffused in an efficient and scalable way across the graph vertexes and edges. The resulting graph encoding is used in combination with discriminative models to address structure classification benchmarks.
Ambula: Build Communication Lifeline of Corporations During Emergency

Many corporations rely on Internet service provider (ISP) network to provide reliable communication services. However, the current communication networks are vulnerable to disruptive events, such as natural disaster or power outage. Such disastrous events may destroy multiple network facilities in a specific region and result in a long term recovery of ISP networks. The disconnected communication will lead to enormous economic loss even if corporation’s infrastructure is not directly destroyed during the disaster. Therefore, corporations need a self-rescue mechanism to actively respond to the emergency instead of simply relying on the ISP. This paper proposes Ambula, an easy-to-deploy platform to realize fast congestion-aware recovery for corporation’s communication lifeline. Our platform leverages current widely-deployed public cloud services to build a scalable peer-to-peer overlay routing system. By so doing, the corporation is capable of controlling the packets forwarding path to bypass the affected region and congested routes. To this end, Ambula first carefully selects a small set of virtual machines (VMs) from geographically distributed public clouds, and then apply the self-developed congestion-aware routing protocol to achieve automatic and fast routing recovery. Simulations on both random generated and real network topologies show that the high recovery ratio of 80% can be achieved. The congestion avoidance algorithm can significantly reduce the impact of congestion. Our prototype on Emulab shows it can recover within hundreds of milliseconds. To the best of our knowledge, no effective disaster recovery mechanism currently exists for corporations during emergency. Ambula will facilitate the business continuity management of corporations in present of hazard events.
Driving Maneuver Classification: A Comparison of Feature Extraction Methods

Driving maneuver classification has received increasing attention in recent years. Early work focused on car-based sensor systems, but recently the use of smartphone-based sensors has been increasingly favored. For a driving maneuver classification system, feature extraction often plays an important role. Previous studies have proposed various feature extraction methods for classifying driving maneuvers, however, a direct comparison of feature extraction methods using various data sets is missing. In this paper, we systematically compare three window-based feature extraction methods for driving maneuver classification: statistical values and automatically extracted features using principal component analysis and stacked sparse auto-encoders. Specifically, all sensor information from each data set is first segmented into windowed signals after preprocessing. Then, the three feature extraction methods are applied to those windowed signals. Finally, extracted features are fed into a random forest classifier. Maneuver classification performance is evaluated on three different data sets, demonstrating weighted classification F1-scores of 68.56%, 80.87%, and 87.26%. For all three data sets, statistical features achieve the best performance.
A Psychosocial Approach to Predicting Self-Harm in Heterogeneous Populations

Previous studies have demonstrated relationships between deliberate self-harm and psychological distress and social functioning (for a review see Nock, 2010). However, few studies have examined psychological distress and social functioning at the same time in order to compare these predictors of deliberate self-harm. Using a more comprehensive, psychosocial approach may allow more accurate predictions of deliberate self-harm. Accurate predictions could aid in the intervention and treatment of individuals who engage in deliberate self-harm, regardless of their population; that is, whether they are seeking treatment for symptoms of Borderline Personality Disorder, or if they are a member of the community. In the current study, we used a sample of individuals with Borderline Personality Disorder (N = 60) and a community sample of undergraduate college students (N = 116), all of whom reported engaging in deliberate self-harm at least once in the past year. Participants completed measures of deliberate self-harm (outcome variable), psychological distress (specifically depression, anxiety, obsessivecompulsion, and interpersonal sensitivity; predictor variables), and social functioning (positive support and negative interactions with family members, friends, and a romantic partner; predictor variables). We found that the population (or sample type) was the strongest predictor of deliberate self-harm, with individuals with Borderline Personality Disorder engaging in more deliberate self-harm than students. Additionally, anxiety predicted deliberate self-harm for individuals with Borderline Personality Disorder. No social functioning variables predicted deliberate self-harm. Explanations for findings and treatment implications are discussed.