Miracle-dz/UniFAR-FTUs huggingface dataset:
Examining Invasive Bedside Procedure Performance at an Academic Medical Center

Objectives Explore the performance patterns of invasive bedside procedures at an academic medical center, evaluate whether patient characteristics predict referral, and examine procedure outcomes. Methods This was a prospective, observational, and retrospective chart review of adults admitted to a general medicine service who had a paracentesis, thoracentesis, or lumbar puncture between February 22, 2013 and February 21, 2014. Results Of a total of 399 procedures, 335 (84%) were referred to a service other than the primary team for completion. Patient characteristics did not predict referral status. Complication rates were low overall and did not differ, either by referral status or location of procedure. Model-based results showed a 41% increase in the average length of time until procedure completion for those referred to the hospital procedure service or radiology (7.9 vs 5.8 hours; P < 0.05) or done in radiology instead of at the bedside (9.0 vs 5.8 hours; P < 0.001). The average procedure cost increased 38% ($1489.70 vs $1023.30; P < 0.001) for referred procedures and 56% ($1625.77 vs $1150.98; P < 0.001) for radiology-performed procedures. Conclusions Although referral often is the easier option, our study shows its shortcomings, specifically pertaining to cost and time until completion. Procedure performance remains an important skill for residents and hospitalists to learn and use as a part of patient care.
A Meaning-Based Statistical English Math Word Problem Solver

We introduce MeSys, a meaning-based approach, for solving English math word problems (MWPs) via understanding and reasoning in this paper. It first analyzes the text, transforms both body and question parts into their corresponding logic forms, and then performs inference on them. The associated context of each quantity is represented with proposed role-tags (e.g., nsubj, verb, etc.), which provides the flexibility for annotating an extracted math quantity with its associated context information (i.e., the physical meaning of this quantity). Statistical models are proposed to select the operator and operands. A noisy dataset is designed to assess if a solver solves MWPs mainly via understanding or mechanical pattern matching. Experimental results show that our approach outperforms existing systems on both benchmark datasets and the noisy dataset, which demonstrates that the proposed approach understands the meaning of each quantity in the text more.
Cognitive Coordination in Large-Scale Enterprise Architecting: A Case Study

Research on coordination in large-scale, long -- term collaboration has received limited attention in the IS literature. One difficulty of studying coordination in such contexts is that the current theoretical frameworks derived from coordination theory are often too generic for the specific task. We posit that it is important to develop a deep understanding of the technical task and adapt a generic model to incorporate the nuances of the task being investigated. In prior studies, we developed a research model for the study of coordination in enterprise architecting activities, further refined it, did some preliminary validation for the model, and provided empirical evidence of the central role of cognitive coordination. In the present study we provide further validation of the model by analyzing two more cases involving architecting in two large organizations -- a government agency and a private company.
Graph Entropy , Posets , and their applications in Sorting Under Partial Information

In traditional comparison sorting, we are given a set of n elements with no a priori information about their order. Uniquely identifying a permutation requires log2 n! ∼ n log n bits, and therefore Ω(n log n) comparisons. In the setting of sorting under partial information (SUPI), we are given some initial comparisons, and would like to minimize the number of additional “comparison oracle” calls required to sort, given our partial information. Similar to the traditional setting, we would like to lower-bound the query complexity of algorithms for SUPI, and exhibit algorithms which perform provably close to the lower-bound. In some sense this is an information-theoretic question: we are given some partial information about the ordering, and want to know how much additional information is required to determine the ordering. The bulk of our survey involves making this precise, which requires the concepts of posets (partially ordered sets) and “graph entropy” (an entropy-like functional on graphs): Our initial comparisons have the structure of a poset, and the lower-bound is related to the graph-entropy of this poset. In this survey, we review various fundamental properties of posets and graph-entropy, and eventually see their application in proving lower-bounds and optimality of algorithms for SUPI. We try to present all the required ideas from scratch, adding intuition and examples along the way.
Deception Improves Time Trial Performance in Well-trained Cyclists without Augmented Fatigue

Purpose To investigate the effects of feedback, in the form of a virtual avatar paced at 100% and 102% of baseline performance, on neuromuscular fatigue after a 4-km cycling time trial (TT). We hypothesized that improved cycling performance would occur because of the participants exceeding a previously established critical threshold and experiencing greater neuromuscular fatigue. Methods After familiarization, 10 well-trained cyclists performed a baseline 4-km TT without feedback (BASE), followed by two 4-km TT where they raced against an avatar (set at 100% accurate [ACC] and 102% deception [DEC] of baseline power output) in a randomized and counterbalanced order. Before and after each TT, neuromuscular fatigue was assessed using maximal isometric voluntary contractions (MVC) of the quadriceps, and supramaximal electrical stimulation of the femoral nerve, during and 2 s after MVCs to assess voluntary activation and potentiated twitch force. Blood lactate was taken pretrials and posttrials and RPE was taken throughout each TT. Results Time trial performance improved after deception of feedback compared with baseline performance (−5.8 s, P = 0.019). Blood lactate increased after DEC compared with BASE (+1.37 mmol·L−1, P = 0.019). Despite this, there was no difference in any measures of exercise-induced neuromuscular fatigue (P > 0.05). Similarly, RPE was not different between trials. Conclusions Well-trained male cyclists can improve cycling TT performance when competing against an avatar increased to 102% of a previously established best effort. However, this improvement is not associated with a measurable augmentation of neuromuscular fatigue.
ECG Signal Feature Selection for Emotion Recognition

This paper aims to study the selection of features based on ECG in emotion recognition. In the process of features selection, we start from existing feature selection algorithm, and pay special attention to some of the intuitive value on ECG waveform as well. Through the use of ANOVA and heuristic search, we picked out the different features to distinguish joy and pleasure these two emotions, then we combine this with pathological analysis of ECG signals by the view of the medical experts to discuss the logic corresponding relation between ECG waveform and emotion distinguish. Through experiment, using the method in this paper we only picked out five features and reached 92% of accuracy rate in the recognition of joy and pleasure. DOI: http://dx.doi. org/10.11591/telkomnika.v11i3. 2215
The Body Mass Index and Waist Circumference as Predictors Of Body Composition in Post CSCI Wheelchair Rugby Players

1 Department of Special Physical Education, Academy of Physical Education, Katowice. 2 Department of Geriatrics, Medical University of Silesia. 3Department of Sports Theory, Academy of Physical Education, Katowice. Authors submitted their contribution to the article to the editorial board. Accepted for printing in the Journal of Human Kinetics vol. 43/2014 on November 2014. The Body Mass Index and Waist Circumference as Predictors Of Body Composition in Post CSCI Wheelchair Rugby Players (Preliminary Investigations)
Prediction of marker genes associated with hypertension by bioinformatics analyses

This study aimed to explore the underlying marker genes associated with hypertension by bioinformatics analyses. A gene expression profile (GSE54015) was downloaded. The differentially expressed genes (DEGs) between the normotensive female (NF) and hypertensive female (HF), and between the normotensive male (NM) and hypertensive male (HM) groups were analyzed. Gene Ontology (GO) and pathway enrichment analyses were performed, followed by protein-protein interaction (PPI) network construction. The transcription factors (TFs), and the common DEGs between the HF and HM groups were then analyzed. In total, 411 DEGs were identified between the HF and NF groups, and 418 DEGs were identified between the HM and NM groups. The upregulated DEGs in the HF and HM groups were enriched in 9 GO terms, including oxidation reduction, such as cytochrome P450, family 4, subfamily b, polypeptide 1 (Cyp4b1) and cytochrome P450, family 4, subfamily a, polypeptide 31 Cyp4a31). The downregulated DEGs were mainly enriched in GO terms related to hormone metabolic processes. In the PPI network, cytochrome P450, family 2, subfamily e, polypeptide 1 (Cyp2e1) had the highest degree in all 3 analysis methods in the HF group. Additionally, 4 TFs were indentified from the 2 groups of data, including sterol regulatory element binding transcription factor 1 (Srebf1), estrogen receptor 1 (Esr1), retinoid X receptor gamma (Rxrg) and peroxisome proliferator-activated receptor gamma (Pparg). The intersection genes were mainly enriched in GO terms related to the extracellular region. On the whole, our data indicate that the DEGs, Cyp4b1, Cyp4a31 and Loxl2, and the TFs, Esr1, Pparg and Rxrg, are associated with the progression of hypertension, and may thus serve as potential therapeutic targets in this disease.
Enabling En-Route Filtering for End-to-End Encrypted CoAP Messages

IoT devices usually are battery-powered and directly connected to the Internet. This makes them vulnerable to so-called path-based denial-of-service (PDoS) attacks. For example, in a PDoS attack an adversary sends multiple Constrained Application Protocol (CoAP) messages towards an IoT device, thereby causing each IoT device along the path to expend energy for forwarding this message. Current end-to-end security solutions, such as DTLS or IPsec, fail to prevent such attacks since they only filter out inauthentic CoAP messages at their destination. This demonstration shows an approach to allow en-route filtering where a trusted gateway has all necessary information to check the integrity, decrypt and, if necessary, drop a message before forwarding it to the constrained mote. Our approach preserves precious resources of IoT devices in the face of path-based denial-of-service attacks by remote attackers.
2D Thin Film Temperature Sensors Fabricated onto 3D Nylon Yarn Surface for Smart Textile Applications

We report on micro fabrication methods used to integrate electronics into smart textiles. We have introduced a shadow mask fabrication method to pattern 2D thin film structures onto the 3D surface of yarn. We have demonstrated the fabrication of gold resistance temperature sensors (RTDs) onto 500 μm thick nylon yarn. The sensors are meander shaped and have lateral dimensions of 0.3 mm × 1 mm and the width and spacing of the meander is 20 μm. Two different fabrication methods are developed and evaluated: 1) a planar mask made of Kapton foil is patterned by dry etching and 2) a tube mask made of Kapton foil is patterned with a laser. Both methods have proven to be suitable for the fabrication of RTDs onto textile yarns. The fabricated sensors are measured in a climate chamber from 15 to 50°C. The temperature coefficient of the RTDs is 0.0026 ω/°C with a sensitivity of 0.74 ω/°C.
Age Dependent Hypothalamic and Pituitary Responses to Novel Environment Stress or Lipopolysaccharide in Rats

Previously, we have shown that the transcription factor nuclear factor interleukin (NF-IL)6 can be used as an activation marker for inflammatory lipopolysaccharide (LPS)-induced and psychological novel environment stress (NES) in the rat brain. Here, we aimed to investigate age dependent changes of hypothalamic and pituitary responses to NES (cage switch) or LPS (100 μg/kg) in 2 and 24 months old rats. Animals were sacrificed at specific time points, blood and brains withdrawn and analyzed using immunohistochemistry, RT-PCR and bioassays. In the old rats, telemetric recording revealed that NES-induced hyperthermia was enhanced and prolonged compared to the young group. Plasma IL-6 levels remained unchanged and hypothalamic IL-6 mRNA expression was increased in the old rats. Interestingly, this response was accompanied by a significant upregulation of corticotropin-releasing hormone mRNA expression only in young rats after NES and overall higher plasma corticosterone levels in all aged animals. Immunohistochemical analysis revealed a significant upregulation of NF-IL6-positive cells in the pituitary after NES or LPS-injection. In another important brain structure implicated in immune-to-brain communication, namely, in the median eminence (ME), NF-IL6-immunoreactivity was increased in aged animals, while the young group showed just minor activation after LPS-stimulation. Interestingly, we found a higher amount of NF-IL6-CD68-positive cells in the posterior pituitary of old rats compared to the young counterparts. Moreover, aging affected the regulation of cytokine interaction in the anterior pituitary lobe. LPS-treatment significantly enhanced the secretion of the cytokines IL-6 and TNFα into supernatants of primary cell cultures of the anterior pituitary. Furthermore, in the young rats, incubation with IL-6 and IL-10 antibodies before LPS-stimulation led to a robust decrease of IL-6 production and an increase of TNFα production by the pituitary cells. In the old rats, this specific cytokine interaction could not be detected. Overall, the present results revealed strong differences in the activation patterns and pathways between old and young rats after both stressors. The prolonged hyperthermic and inflammatory response seen in aged animals seems to be linked to dysregulated pituitary cytokine interactions and brain cell activation (NF-IL6) in the hypothalamus-pituitary-adrenal axis.
Context Adaptive Neural Network Based Acoustic Models for Rapid Adaptation

The adaptation of automatic speech recognition systems to a speaker or an environment is important if we are to achieve high speech recognition performance ubiquitously. Recently, deep neural network (DNN) based acoustic models have been made adaptive to speakers or environments by the addition of an auxiliary feature representing the acoustic context information such as speaker or noise characteristics to the network input. The addition of such auxiliary features to the input realizes only the adaptation of the bias term of the input layer. In this paper, we introduce “context adaptive neural networks,” which are an alternative approach for exploiting auxiliary features that can achieve adaptation of all the parameters of a layer including the linear transformation matrices and the bias terms. A context adaptive neural network is a neural network with one of its layers factorized into sublayers, each associated with an acoustic context class representing a class of speakers or noise conditions. The output of the factorized layer is obtained as a weighted sum of the contributions of all of the sublayers. The weighting coefficients, or context class weights, are derived from the auxiliary features, by transforming them through an auxiliary network. The auxiliary network and the main network can be trained jointly, which enables the context classes that optimize the training criterion to be learned automatically. We perform experiments on three tasks, i.e., two speaker adaptation experiments using DNN models with medium-sized (Wall Street Journal) and large (Continuous Spontaneous Japanese) training datasets, and one environmental adaptation of a convolutional neural network based acoustic model with CHiME3 data. These experiments confirm the potential of the proposed approach in various settings.
The transcriptional regulator of the chaperone response HSF1 controls hepatic bioenergetics and protein homeostasis

Metabolic energy reprogramming facilitates adaptations to a variety of stress conditions and cellular dysfunction, but how the energetic demands are monitored and met in response to physiological stimuli remains elusive. Our data support a model demonstrating that heat shock factor 1 (HSF1), a master transcriptional regulator of the chaperone response, has been coopted from its role as a critical protein quality-control regulator to having a central role in systemic energy sensing and for metabolic adaptation to nutrient availability. We found that in the absence of HSF1, levels of NAD+ and ATP are not efficiently sustained in hepatic cells, largely because of transcriptional repression of nicotinamide phosphoribosyltransferase in the NAD+ salvage pathway. Mechanistically, the defect in NAD+ and ATP synthesis linked to a loss of NAD+-dependent deacetylase activity, increased protein acetylation, and impaired mitochondrial integrity. Remarkably, the drop in ATP level caused by HSF1 loss invoked an adaptive response featuring the inhibition of energetically demanding processes, including gluconeogenesis, translation, and lipid synthesis. Our work identifies HSF1 as a central regulator of cellular bioenergetics and protein homeostasis that benefits malignant cell progression and exacerbates development of metabolic diseases.
Long‐term expansion of juniper populations in managed landscapes: patterns in space and time

Forest cover has increased world‐wide over the last decade despite continuous forest fragmentation. However, a lack of long‐term demographic data hinders our understanding of the spatial dynamics of colonization in remnant populations inhabiting recently protected areas or set‐aside rural lands. We investigated the population expansion of the Phoenician juniper (Juniperus phoenicea subsp. turbinata), which is an endozoochorous Mediterranean tree species inhabiting landscapes that have been managed for many centuries. By combining the photointerpretation of aerial photos that have been taken over the last 50 years with in situ sampling and spatial analyses of replicated plots, we estimated the population growth over the chronosequence; identified hotspots, coldspots and outliers of regeneration; and assessed the roles of key environmental factors in driving demographic expansion patterns, including elevation, initial density and distance to remnant forests. Ecological factors leading to seed limitation, such as initial plant density, are expected to drive colonization patterns at the early stages. Factors mediating the competition for limiting resources, such as water availability, would prevail at later stages of expansion. We further expect that nucleated colonization patterns emerge driven by vertebrate seed dispersal. The photointerpretation of aerial images in combination with in situ measurements has yielded reliable density data. Overall, our results show a marked demographic expansion during the first decade followed by a period of steady and heterogeneous population growth with signs of local population decline. We found evidence of nucleated establishment patterns as expected for an endozoochorous species. Hotspots and outliers of regeneration emerged throughout the study chronosequence, whereas coldspots of regeneration only appeared at advanced colonization stages. Factors influencing dispersal limitation had contrasting effects at different colonization stages, and the initial density influenced population growth at various spatial scales. Synthesis. The photointerpretation of aerial images shows that the influence of dispersal limitation versus factors mediating competitive responses changes throughout colonization stages. Whereas dispersal limitation is the main factor influencing colonization at early stages, competition for local resources controls population growth at later stages. Therefore, long‐term studies are required to capture the overall combined influence of key ecological factors in shaping long‐term spatial demographic trends.
Consolidation grouting technology for fire prevention in mined‐out areas of working face with large inclined angle and its application

The phenomenon of linear flow of slurry in mined‐out areas of working face with large inclined angle is a crucial issue that hinders grouting for fire prevention. The traditional way of grouting exerts a poor effect on inhibiting coal spontaneous combustion, so it is in urgent need of a suitable grouting technology for fire prevention in mined‐out areas with large inclined angle working face. This paper brings up the consolidation grouting method for fire prevention for the first time and conducts a systematic study on the flow characteristics of slurry and sedimentation characteristics of slurry in mined‐out areas with large inclined angle working face. Consolidation slurry materials and their ratio are optimized by experiments. Test platform has been established, and effectiveness of the consolidation grouting for fire prevention has been simulated. The results show that settling velocity of yellow mud increases at first and then decreases as the concentration of consolidation slurry materials ascends. The optimum mass concentration is 0.2%–0.8%. The flow speed of mud is greatly reduced by laying consolidation slurry materials (The decreasing range is approaching 50%). The retention of yellow mud in mined‐out areas has significantly increased. Finally, technology in working site has been developed; meanwhile, compressed air and spray between frames have been used during the period of working face, and the consolidated way of expansion bags in wood crib to lay consolidation slurry materials has been adopted during the period of stopping work. Field application shows that CO concentration at upper corner decreases significantly and eliminates signs of spontaneous combustion. Besides, the flowing water becomes clearer, and effectiveness of the consolidation grouting is remarkable after laying consolidation slurry material band. Research results can provide theoretical guidance to technology for fire hazard prevention in mined‐out areas with large inclined angle. Copyright © 2016 John Wiley & Sons, Ltd.
Impact of Cognitive Remediation Therapy on Neurocognitive Processing in Anorexia Nervosa

Background Anorexia nervosa (AN) is characterized by severe malnutrition as well as inefficiencies in neurocognitive functioning, which are believed to contribute to the maintenance of disordered eating. The aim of this study was to examine the impact of individual cognitive remediation therapy (CRT) on neurocognition in AN. Methods A total of 145 adult women from an eating disorders inpatient program took part in the present study. All participants were given individual CRT in addition to treatment as usual. Neurocognitive processes were assessed at baseline and at the end of treatment using task-based and self-report measures. The task-based measures included the Rey-Osterrieth Complex Figure test and the Brixton test, which were used to assess central coherence and set-shifting. The Detail and Flexibility Questionnaire was used to examine patients self-reported detail focus and cognitive flexibility. Results Participants showed significant improvement in task-based measures of neurocognition following CRT. There were no significant changes in self-report measures. Conclusion These findings suggest that CRT may be an effective intervention targeting inefficiencies in neurocognition in AN. Future studies may benefit from assessing neural changes associated with these improvements and conducting randomized controlled trials to replicate these findings.