Miracle-dz/UniFAR-FTUs huggingface dataset:
Summarization and Information Loss in Network Analysis ∗

The increasing availability of large-scale network data makes the problem of network summarization especially relevant. In any data summarization, however, it is important to remain aware of the information not being presented. As such, we present a mathematical framework within which to consider the problem of network summarization. Using that framework, the concept of information entropy is applied in the context of network summarization. Finally, an O(—E—) algorithm is presented for computing information entropy in the case of simple deterministic network summarizations.
Nephrological abnormalities in patients with transaldolase deficiency.

BACKGROUND Transaldolase deficiency (OMIM 606003) is a multisystem disorder first described in 2001. Transaldolase is an enzyme of the reversible part of the pentose phosphate pathway. Affected patients have abnormal polyol concentrations in body fluids, mostly in urine. The clinical presentation is variable. The leading symptoms are coagulopathy, thrombocytopenia, hepatosplenomegaly, hepatic fibrosis and dysmorphic features. The objective of our study was to attempt to characterize the renal phenotype of patients with transaldolase deficiency. METHODS Clinical and laboratory data of all nine patients with transaldolase deficiency presently known were gathered by retrospective chart analysis. RESULTS Nephrological abnormalities were present in seven of the nine patients. The most common findings were low molecular weight (LMW) proteinuria and hypercalciuria. The two oldest patients had moderate chronic kidney failure. In two patients, generalized aminoaciduria was found, two patients had renal phosphate wasting and three patients had hyperchloremic metabolic acidosis. Three patients had anatomical abnormalities. CONCLUSIONS Renal tubular dysfunction is present in the majority of patients with transaldolase deficiency and may lead to chronic renal failure. The combination of unexplained liver dysfunction with LMW proteinuria should prompt metabolic screening for transaldolase deficiency by measuring urinary polyols. In patients with transaldolase deficiency, monitoring of kidney function is mandatory.
Vlock: Lock virtualization mechanism for exploiting fine-grained parallelism in graph traversal algorithms

For graph traversal applications, fine synchronization is required to exploit massive fine parallelism. However, in the conventional solution using fine-grained locks, locks themselves suffer huge memory cost as well as poor locality for inherent irregular access to vertices. In this paper, we propose a novel fine lock solution-vLock. The key idea is lock virtualization that maps the huge logical lock space to a much smaller physical lock space that can reside in cache during the program life cycle. Lock virtualization effectively reduces lock incurred overheads of both memory cost and cache misses. It also achieves high usability in legacy graph programs, as from users's view vLock is the same as lock methods in Pthreads. We implement vLock as a Pthreads-like library and evaluate its performance in four classical graph algorithms (BFS, SSSP, CC, PageRank). Experiments on a SMP system with two Intel Westemere six-core processors show that, compared to conventional fine locks, vLock significantly reduces locks' cache misses and has competitive performance. Particularly, PageRank with vLock has about 20% performance improvement.
Socioeconomic Status, Frailty, and All-Cause Mortality in Korean Older Adults: A 3-Year Population-Based Prospective Study

Background Little is known regarding the effects of socioeconomic status (SES) and frailty on mortality in Korea. Objective This study investigated the combined impact of low SES and frailty on all-cause mortality in Korean older adults. Methods Study sample at baseline comprised 7,960 community-dwelling adults (56.8% women) aged 65 years and older. The Cox proportional hazards model was used to estimate the hazard ratio (HR) and 95% confidence interval (CI) of low SES and frailty for all-cause mortality. Results Overall, low SES plus frailty resulted in an increased risk of all-cause mortality (HR = 1.56, 95% CI = 1.09–2.23, P = 0.015) even after adjustments for all the measured covariates, as compared with high SES plus nonfrailty (HR = 1). Among older adults aged 65–75 years, the increased mortality risk of either low SES plus nonfrailty (HR = 1.37, 95% CI = 1.02–1.84, P = 0.038) or high SES plus frailty (HR = 2.09, 95% CI = 1.12–3.91, P = 0.021) remained significant even after adjustments for all the covariates, as compared with high SES plus nonfrailty (HR = 1). Conclusion The current findings suggest that either low SES or frailty is significantly associated with increased all-cause mortality in Korean older adults.
Pulmonary disorders: ventilation-perfusion MR imaging with animal models.

PURPOSE To demonstrate the capability of magnetic resonance (MR) imaging to assess alteration in regional pulmonary ventilation and perfusion with animal models of airway obstruction and pulmonary embolism. MATERIALS AND METHODS Airway obstruction was created by inflating a 5-F balloon catheter into a secondary bronchus. Pulmonary emboli were created by injecting thrombi into the inferior vena cava. Regional pulmonary ventilation was assessed with 100% oxygen as a T1 contrast agent. Regional pulmonary perfusion was assessed with a two-dimensional fast low-angle shot, or FLASH, sequence with short repetition and echo times after intravenous administration of gadopentetate dimeglumine. RESULTS Matched ventilation and perfusion abnormalities were identified in all animals with airway obstruction. MR perfusion defects without ventilation abnormalities were seen in all animals with pulmonary emboli. CONCLUSION Ventilation and perfusion MR imaging are able to provide regional pulmonary functional information with high spatial and temporal resolution. The ability of MR imaging to assess both the magnitude and regional distribution of pulmonary functional impairment could have an important effect on the evaluation of lung disease.
Joint Spatial-Spectral Feature Space Clustering for Speech Activity Detection from ECoG Signals

Brain-machine interfaces for speech restoration have been extensively studied for more than two decades. The success of such a system will depend in part on selecting the best brain recording sites and signal features corresponding to speech production. The purpose of this study was to detect speech activity automatically from electrocorticographic signals based on joint spatial-frequency clustering of the ECoG feature space. For this study, the ECoG signals were recorded while a subject performed two different syllable repetition tasks. We found that the optimal frequency resolution to detect speech activity from ECoG signals was 8 Hz, achieving 98.8% accuracy by employing support vector machines as a classifier. We also defined the cortical areas that held the most information about the discrimination of speech and nonspeech time intervals. Additionally, the results shed light on the distinct cortical areas associated with the two syllables repetition tasks and may contribute to the development of portable ECoG-based communication.
Exploring Critical Success Factors of Mobile Learning as Perceived by Students of the College of Computer Studies – National University

This study sought to determine the critical success factors affecting the behavioral intention of the learners to use M-Learning. Though studies have been conducted to explore and understand students’ and teachers’ acceptance in M-Learning, the literature states that the result varies as culture, technology, infrastructure, etc. vary from one country to another. It is the role of the paper to determine which success factors affect the students’ behavioral intention to use M-Learning as perceived by students in one university in the Philippines. The different critical success factors were taken from the literature in M-learning and E-Learning. These critical success factors were encapsulated into six (6) distinct dimensions (predictors) embodying the two (2) theoretical framework, namely the Technology Acceptance Model and the Information Success Model. The respondents of the study were from the College of Computer Studies – National University and were selected through convenience sampling. To test the predictors, regression was used to denote association to the Learners’ behavioral intention to use M-Learning. The result showed that the different dimensions distinctively predict the Learners’ behavioral intention to make use of M-Learning. Moreover, the demographics of the respondents were tested to determine whether it is closely associated with their intention to use M-learning. The tests revealed that age and gender do not predict the behavioral intention of the learners to use M-Learning. However, it can be noted that those who use their mobile phones to study their lessons have positive association towards M-Learning. It was a good predictor to determine the learners’ behavioral intention to use M-Learning. The result of the study with regards to the critical success factors was confirmatory to other researchers that identified critical success factors for both e-learning and M-Learning. However, since the study was done in the college of computer studies, the majority if not all the respondents are inclined to technology. It would be recommended that students under the different colleges also be considered in this study.
Can Symbol Grounding Improve Low-Level NLP? Word Segmentation as a Case Study

We propose a novel framework for improving a word segmenter using information acquired from symbol grounding. We generate a term dictionary in three steps: generating a pseudo-stochastically segmented corpus, building a symbol grounding model to enumerate word candidates, andfiltering them according to the grounding scores. We applied our method to game records of Japanese chess with commentaries. The experimental results show that the accuracy of a word segmenter can be improved by incorporating the generated dictionary.
Exploring the applicability of Reservoir methods for Classifying Punctual Sports Activities Using On-body Sensors

This paper explores the use of a reservoir computing (RC) method, Echo State Networks (ESN) to classify inertial sensor motion data collected from sensors worn by horse riders into punctual activities of interest within a scripted movement environment. RC methods incorporate both temporal and spatial aspects within the model and therefore may have applicability classifying signals with the varying temporal signatures often seen across activity instances even when performed by the same subject. ESN's, as one of a number of RC methods has a potential advantage in this case of being able to directly incorporate the inertial data into the reservoir without the need to segment this data into sliding windows. This is part of a wider set of work to build a wearable coach for technique feedback for Equestrian sport. Our use of RC methods on inertial data to classify punctual human activities is novel.
Registration and Matching of Perspective Surface Normal Maps

We present a method for the registration and matching of perspective surface normal maps. Registration of two maps consists of optimally aligning their normals through a 2-D warping in the image plane in conjunction with a 3-D rotation of the normals. Once aligned, the average dot-product then serves as a match metric for automatic target recognition (ATR). We conduct an ATR experiment using synthesized views of 25 commercial vehicles, and obtain perfect recognition results when the test azimuth is within [-6deg,+10deg] of the reference pose, even when the normals are corrupted by up to 20deg uniform random noise. The results suggest that needle maps are a rich yet compact representation of an object, which may be useful for exploiting information from stereo images, shape from shading algorithms, or sensors which obtain the normals from polarization information.
Scalable Pixel-based Visual Interfaces: Challenges and Solutions

The information revolution is creating and publishing vast data sets, such as records of business transactions, environmental statistics and census demographics. In many application domains, this data is collected and indexed by geo-spatial location. The discovery of interesting patterns in such databases through visual analytics is a key to turn this data into valuable information. Challenges arise because newly available geo-spatial data sets often have millions of records, or even far more, they are from multiple and heterogeneous data sources, and the output devices have significantly changed, e.g. high-resolution pixilated displays are increasingly available in both wall-sized and desktop units. New techniques are needed to cope with this scale. In this paper, we focus on ways to increase the scalability of pixel-based visual interfaces by adding task on hands scenarios that tightly integrate the data analyst into the exploration of geo-spatial data sets
Approximation algorithms for the Earth mover's distance under transformations using reference points

An introducing catheter for use in placing a large guidewire after a small guidewire is in position. The catheter has a tapered distal tip, decreased lumen size at the distal end, a side port and a ramp disposed within the tube at the distal end of the side port. The ramp is inclined distally toward the side port, the distal end of the ramp being fixed to the tube adjacent to the side port and the proximal end of the ramp being disposed adjacent the inner wall of the tube in the region opposite the side port in the manner that the small guidewire can move proximally past the ramp. The ramp deflects the distally moving larger wire so that it exists through the side port. In the embodiment shown, the ramp is formed integrally of low friction thermoplastic (PTFE) and the upper surface of the proximal end of the ramp has a convex, wire-deflecting contour as a result of thermoforming pressure.
Experimental studies for bearings degradation monitoring at an early stage using analysis of variance

This work presents a procedure for bearing degradation monitoring at an early stage. The analysis of variance (ANOVA) coupled with Tukey’s test is used to single out the suitable parameters to follow the fault size evolution ranging from 50 μm to 150μm. The Tukey's criterion is adopted in this case to study the ability of time and frequency indicators. The rotational speed, centrifugal load and fault size are considered as independent variables while the time and frequency indicators are taken as dependent variables. The experiments are performed on bearings having a fault on outer race. Based on the results of this study, the Kurtosis and Skewness show a good ability to assess the evolution of degradation in the bearings at an early stage. The paper discusses the weakness of the time and frequency indicators.
Comparison of Lead, Copper and Aluminium as Gamma Radiation Shielding Material through Experimental Measurements and Simulation Using MCNP Version 4c

The paper compares Lead, Copper and Aluminium as gamma radiation shielding material using both experimental and simulation techniques. Cs- 137 (662KeV), Na-22 (511KeV) and Na- 22(1274KeV) were used as gamma radiation sources and a sodium iodide (NaI) detector was used to detect the radiation. Variations were noted for detected gamma count rates by changing shielding material thickness. In the experimental approach, thickness was varied by placing sheets of a particular test material one by one. For simulation, Monte Carlo n- Particle (MCNP) code version 4c was used and the geometry of the whole experimental setup was plotted in it. The results were then compared for each test material and it was found that lead is the best shielding material for gamma radiation followed by copper and aluminium.
A Short-term Rat Mammary Carcinogenesis Model for the Prevention of Hormonally Responsive and Nonresponsive In situ Carcinomas

Preclinical models that accurately reproduce specific aspects of human disease etiology are invaluable for the initial development and evaluation of chemopreventive agents. We developed a novel, short-term prevention model, which is particularly useful for assessing the efficacy of a compound to prevent hormonally responsive and nonresponsive in situ carcinomas. In this model, carcinogenesis is induced by a high titer of neu-containing, replication-defective retrovirus. The multiplicity and size of the resulting in situ carcinomas are scored in whole-mounted, aluminum carmine–stained mammary glands at 15 days postinfusion. These in situ carcinomas represent a distinct biological time point in the development of neu-induced mammary cancer in the rat. They are characterized by high rates of proliferation (40.0%; P < 0.0001) and apoptosis (2.8%; P < 0.005) compared with mammary carcinomas. The majority of in situ carcinomas regress spontaneously after 20 days postinfusion. The in situ carcinomas at 15 days postinfusion exhibit hormonal responsiveness. The effects of the chemoprevention agents tamoxifen, celecoxib, and targretin on hormonally responsive and nonresponsive in situ carcinomas recapitulate those observed on mammary carcinomas at 12 and 18 weeks postinfusion for intact and ovariectomized rats, respectively. Neu-induced in situ carcinomas in the rat represent etiologically relevant intermediate time points of mammary carcinogenesis. Our prevention model represents a cost-efficient in vivo system to determine whether the preventive effects of a compound extend to hormonally nonresponsive mammary lesions, for which new chemoprevention approaches are needed.
CIIPro: a new read‐across portal to fill data gaps using public large‐scale chemical and biological data

Summary: We have developed a public Chemical In vitro‐In vivo Profiling (CIIPro) portal, which can automatically extract in vitro biological data from public resources (i.e. PubChem) for user‐supplied compounds. For compounds with in vivo target activity data (e.g. animal toxicity testing results), the integrated cheminformatics algorithm will optimize the extracted biological data using in vitro‐in vivo correlations. The resulting in vitro biological data for target compounds can be used for read‐across risk assessment of target compounds. Additionally, the CIIPro portal can identify the most similar compounds based on their optimized bioprofiles. The CIIPro portal provides new powerful assessment capabilities to the scientific community and can be easily integrated with other cheminformatics tools. Availability and Implementation: ciipro.rutgers.edu. Contact: danrusso@scarletmail.rutgers.edu or hao.zhu99@rutgers.edu
Identification of molecular and functional patterns of p53 alterations in chronic lymphocytic leukemia patients in different phases of the disease

We analyzed TP53 mutations in 483 chronic lymphocytic leukemia patients at different phases of the disease and found a higher incidence of mutations at the later phases and a distinctive mutation profile in each phase. p53 function evaluated by immunoblotting and flow cytometry after cell irradiation was impaired in 28 of 109 cases. Three phenotypically different dysfunctions were observed: type I, associated with heterozygous missense TP53 mutations (typically present at diagnosis) and partially resistant to radiation-induced killing; types II and III, with a higher incidence of microdeletions, nonsense mutations and bi-allelic TP53 defects (common in progressive and chemoresistant cases) and a complete radioresistance. Furthermore, in 4 of 28 patients, all chemoresistant, we found p53 dysfunctions without TP53 mutations. In chronic lymphocytic leukemia patients, a disease phase-specific variability in the p53 mutation profile and function takes place, and both analyses could be useful to guide treatment choices.
Predictive Low-Glucose Insulin Suspension Reduces Duration of Nocturnal Hypoglycemia in Children Without Increasing Ketosis

OBJECTIVE Nocturnal hypoglycemia can cause seizures and is a major impediment to tight glycemic control, especially in young children with type 1 diabetes. We conducted an in-home randomized trial to assess the efficacy and safety of a continuous glucose monitor–based overnight predictive low-glucose suspend (PLGS) system. RESEARCH DESIGN AND METHODS In two age-groups of children with type 1 diabetes (11–14 and 4–10 years of age), a 42-night trial for each child was conducted wherein each night was assigned randomly to either having the PLGS system active (intervention night) or inactive (control night). The primary outcome was percent time <70 mg/dL overnight. RESULTS Median time at <70 mg/dL was reduced by 54% from 10.1% on control nights to 4.6% on intervention nights (P < 0.001) in 11–14-year-olds (n = 45) and by 50% from 6.2% to 3.1% (P < 0.001) in 4–10-year-olds (n = 36). Mean overnight glucose was lower on control versus intervention nights in both age-groups (144 ± 18 vs. 152 ± 19 mg/dL [P < 0.001] and 153 ± 14 vs. 160 ± 16 mg/dL [P = 0.004], respectively). Mean morning blood glucose was 159 ± 29 vs. 176 ± 28 mg/dL (P < 0.001) in the 11–14-year-olds and 154 ± 25 vs. 158 ± 22 mg/dL (P = 0.11) in the 4–10-year-olds, respectively. No differences were found between intervention and control in either age-group in morning blood ketosis. CONCLUSIONS In 4–14-year-olds, use of a nocturnal PLGS system can substantially reduce overnight hypoglycemia without an increase in morning ketosis, although overnight mean glucose is slightly higher.
Accelerated microarchitectural Fault Injection-based reliability assessment

Statistical Fault Injection on microarchitectural simulators can provide early and accurate reliability characterization for array based hardware components. Besides, microarchitectural fault injectors are easily configurable (facilitating many reliability studies) and orders of magnitude faster than RTL fault injectors, rendering them appropriate tools for early reliability estimation using large and realistic benchmarks. However, the throughput of the fault injection campaigns on microarchitectural simulators remains a bottleneck when a batch of campaigns must run for early reliability estimation of a processor (different microarchitectural characteristics, different workloads). This paper presents two different operation modes on top of a baseline framework for statistical fault injection campaigns, trading off between accuracy and speedup of the injection campaigns with a state-of-the-art out-of-order full-system ×86-64 simulator as experimental vehicle. In the first mode, the injection experiments are stopped and classified as masked due to the following conditions: (i) the fault is over-written after the injection and it hasn't been read earlier, (ii) or the fault is injected on an invalid entry. The second mode has the same termination conditions as the first mode, but the injection experiments can also be terminated when an instruction that has read the faulty entry passes through the commit stage of the ×86-64 out-of-order architecture. In the first mode, we observed a speedup up to 2.92× with no loss of accuracy in the vulnerability measurements for all structures. In the second mode an even higher speedup of up to 4.06× has been obtained with small loss in the accuracy of the vulnerability measurements.