Miracle-dz/UniFAR-FTUs huggingface dataset:
Do Subtoxic levels of chlorate influence the desiccation tolerance of Egeria densa?

Among the different factors hypothesized to be responsible for the virtual disappearance of Egeria densa, once a dominant aquatic macrophyte in a southern Chile wetland ecosystem, are the negative effects of certain chemical compounds (mainly chlorate) and harsh environmental conditions (desiccation caused by prolonged atmospheric exposure). The authors performed an integrated experiment in which E. densa plants were first exposed for four weeks inside a mesocosm system to levels of chlorate that existed in the wetland at the time of the plant's demise and then exposed to desiccation conditions that also resembled those that the system had experienced. Hence, the authors tested the hypothesis that E. densa plants exposed to sublethal levels of chlorate are more susceptible to the deleterious effect of desiccation compared with plants that had not been exposed to chlorate. This hypothesis was tested by means of quantifying physiologically related parameters in plants right after the four weeks under water and then after the desiccation period of 6 h. Their results rejected this hypothesis, because all plants, regardless of their history, are equally affected by desiccation. Environ. Toxicol. Chem. 2013;32:417–422. © 2012 SETAC
Test structures for characterization and comparative analysis of CMOS image sensors

A set of test structures designed to characterize and compare the performance of CMOS passive and active pixel image sensors is presented. The test structures are deigned so that they can be rapidly ported from one process to another. They are also designed so that individual photodetectors and pixel circuits as well as entire image sensor arrays can be characterized and compared based on: quantum efficiency, spectral response, fixed pattern noise, sensitivity, blooming, input referred read noise, reduction of quantum efficiency caused by silicide/salicide, lag, digital switching noise sensitivity, impact ionization noise sensitivity, dynamic range, and temperature dependency of all measured parameters. Four test chips that include a variety of these structures have been built in two different 0.35 micrometer CMOS processes. The test chips include nineteen types of individual photodetectors and thirty eight types of 64 by 64 pixel arrays. The test methodology and preliminary test results from these chips are presented.
High-level verification of multi-object segmentation

In this paper we present a relational analysis and verification of multi-labeled images as a result fo semantic segmentation. In semantic segmentation the result is a set of labeled regions but rarely this result is subject to verification that would allow to determine induce the reliability of this segmentation. We show that using shape measure, co-occurrence statistics and specially crafted weighted function we can estimate the correctness of a semantic segmentation up to 92%.
YSDA Participation in the WMT’16 Quality Estimation Shared Task

This paper describes Yandex School of Data Analysis (YSDA) submission for WMT2016 Shared Task on Quality Estimation (QE) / Task 1: Sentence-level prediction of post-editing effort. We solve the problem of quality estimation by using a machine learning approach, where we try to learn a regressor from feature space to HTER score. By enriching the baseline features with the syntactical features and additional translation system based features, we achieve Pearson correlation of 0.525 on the test set.
High-accuracy connected digit recognition for mobile applications

We present a connected digit recognition system with low storage and computational complexity which achieves good performance in car noise. Our system uses the TI-DIGITS database with additive car noise for training whole-word digit and background models. A digit accuracy of 96.1% is obtained on a 15-speaker database collected in a car using an open microphone with an average SNR of approximately 2 dB. There is a further error reduction of almost 35% if the top two candidate strings are considered using a traceback based N-best algorithm. The system can be implemented on a currently available fixed-point DSP chip. We show that significant performance improvements are obtained by using two-level cepstral mean subtraction (CMS), gender-dependent models and a decoding grammar constraining the possible lengths of digit strings.
Does Central Bank Intervention Influence the Probability of a Speculative Attack? Evidence from the EMS

This paper studies the effects of central bank intervention during the 1992- 1993 EMS crises on the D-mark/peseta and D-mark/French franc exchange rate. In particular, it is analyzed how interventions affected the probability of a speculative attack and market participants’ expectations about realignments. The findings provide evidence that interventions seem to have increased both the expected realignment rate and the probability of a speculative attack. Furthermore, there is some evidence that this effect arises for publicly known but not for secret interventions.
Fluoroscopic Video to Identify Aberrant Lumbar Motion

Study Design. A prospective, case-control design. Objectives. To develop a kinematic model that characterizes frequently observed movement patterns in patients with low back pain (LBP). Summary of Background Data. Understanding arthrokinematics of lumbar motion in those with LBP may provide further understanding of this condition. Methods. Digital fluoroscopic video (DFV) was used to quantify the magnitude and rate of attainment of sagittal plane intersegmental angular and linear displacement from 20 individuals with LBP and 20 healthy control subjects during lumbar flexion and extension. Three fellowship-trained spine surgeons subsequently qualitatively analyzed the DFVs to determine normality of movement. Final classification was based on agreement between their symptom and motion status (11 with LBP and aberrant motion and 14 healthy controls without aberrant motion). Independent t tests, receiver operator characteristic curves, and accuracy statistics were calculated to determine the most parsimonious set of kinematic variables able to distinguish patients with LBP. Results. Eight kinematic variables had a positive likelihood ratio ≥2.5 and entered the model. Six of the variables described a disruption in the rate of attainment of angular or linear displacement during midrange postures. When 4 or more of these variables were present, the positive likelihood ratio was 14.0 (confidence interval 3.2–78.5), resulting in accurately identifying 96% of participants. Conclusions. DFV was useful for discriminating between individuals with and without LBP based on kinematic parameters. Disruptions in how the motion occurred during midrange motions were more diagnostic for LBP than range of motion variables. Cross validation of the model is required.
[The relationship between objective and subjective evaluation criteria in lumbar spinal stenosis].

OBJECTIVES We evaluated the relationship between functional objective and patient-based subjective assessments and quality of life in patients with lumbar spinal stenosis (LSS). METHODS Thirty patients (25 females, 5 males; mean age 62+/-9 years; range 41-78 years) were prospectively studied. All were diagnosed as having LSS by clinical and radiological evaluations. Pain was assessed by a visual analog scale. The patients were evaluated by the two-staged treadmill exercise tolerance (TET) test, SF-36 health status survey, and Oswestry Disability Index (ODI). The relationships between the TET test, which is an objective functional assessment, and patient-based assessments (SF-36 and ODI), pain and age were investigated. RESULTS There were significant differences between the functional grades of the patients at the speed of 1.9 km/hour with respect to ODI scores, the physical component scale of SF-36, age, and the preferred speed of the patients (p<0.05). These differences emerged from the fourth functional stage (p<0.01). Oswestry disability scores and the physical component scores of SF-36 worsened in parallel with the stages of the TET test. The preferred speed of the patients at the TET test was positively correlated with the physical component scores of SF-36 and negatively correlated with Oswestry disability scores (p<0.05). There was a negative correlation between the physical component scores of SF-36 and Oswestry disability scores (p<0.05). CONCLUSION The TET test used to determine the functional capacity seems to be correlated well with subjective patient-based assessments. This objective tool, when combined with subjective assessments, may be helpful in the evaluation and treatment of patients with LSS.
Using Highly Detailed Administrative Data to Predict Pneumonia Mortality

Background Mortality prediction models generally require clinical data or are derived from information coded at discharge, limiting adjustment for presenting severity of illness in observational studies using administrative data. Objectives To develop and validate a mortality prediction model using administrative data available in the first 2 hospital days. Research Design After dividing the dataset into derivation and validation sets, we created a hierarchical generalized linear mortality model that included patient demographics, comorbidities, medications, therapies, and diagnostic tests administered in the first 2 hospital days. We then applied the model to the validation set. Subjects Patients aged ≥18 years admitted with pneumonia between July 2007 and June 2010 to 347 hospitals in Premier, Inc.’s Perspective database. Measures In hospital mortality. Results The derivation cohort included 200,870 patients and the validation cohort had 50,037. Mortality was 7.2%. In the multivariable model, 3 demographic factors, 25 comorbidities, 41 medications, 7 diagnostic tests, and 9 treatments were associated with mortality. Factors that were most strongly associated with mortality included receipt of vasopressors, non-invasive ventilation, and bicarbonate. The model had a c-statistic of 0.85 in both cohorts. In the validation cohort, deciles of predicted risk ranged from 0.3% to 34.3% with observed risk over the same deciles from 0.1% to 33.7%. Conclusions A mortality model based on detailed administrative data available in the first 2 hospital days had good discrimination and calibration. The model compares favorably to clinically based prediction models and may be useful in observational studies when clinical data are not available.
Diversity-multiplexing tradeoff over correlated Rayleigh fading channels: a non-asymptotic analysis

Zouheir Rezki1∗,†, David Haccoun2, François Gagnon3 and Wessam Ajib4 1Department of Electrical and Computer Engineering, University of British Columbia, 2329 West Mall, Vancouver BC, V6T 1Z4, Canada 2Department of Electrical Engineering, Polytechnique Montréal, 2900, boul. Édouard-Montpetit, Campus de l’Université de Montréal, 2500, chemin de Polytechnique, Montréal, QC, H3T 1J4, Canada 3Department of Electrical Engineering, École de technologie supérieure, 1100, rue Notre-Dame Ouest, Montréal, QC, H3C 1K3, Canada 4Department of Computer Sciences, Université du Québec à Montréal, 201, avenue du President-Kennedy, Montréal, QC, H2X 3Y7, Canada
Efficient transient simulation for transistor-level analysis

In this paper, we introduce an efficient transistor level simulation tool with SPICE-accuracy for deep-submicron (DSM) VLSI circuits with strong coupling effects. The new approach uses multigrid for large networks of power/ground, clock and signal interconnect. Transistor devices are integrated using a novel two-stage Newton-Raphson method to dynamically model the linear network and nonlinear devices interface. Orders of magnitude speedup over Berkeley SPICE3 is observed for sets of DSM design circuits.
HULTECH at the NTCIR-11 IMine Task: Mining Intents with Continuous Vector Space Models

In this paper, we present our participation in the Subtopic Mining subtask of the NTCIR-11 IMine task, for the En-glish language. Our participation presents a novel strategy for intent mining given a list of candidates for a specific query topic. This strategy is based on a topic exploration through the use of continuous vector space models for each of the candidates based on classical vectorial operations. Our best run outperforms the other participants' submissions in terms of F-score and achieves a high position in the general ranking.
Linear-Time FPT Algorithms via Network Flow

In the area of parameterized complexity, to cope with NP-Hard problems, we introduce a parameter k besides the input size n, and we aim to design algorithms (called FPT algorithms) that run in O(f(k)nd) time for some function f(k) and constant d. Though FPT algorithms have been successfully designed for many problems, typically they are not sufficiently fast because of huge f(k) and d. In this paper, we give FPT algorithms with small f(k) and d for many important problems including Odd Cycle Transversal and Almost 2-SAT. More specifically, we can choose f(k) as a single exponential (4k) and d as one, that is, linear in the input size. To the best of our knowledge, our algorithms achieve linear time complexity for the first time for these problems. To obtain our algorithms for these problems, we consider a large class of integer programs, called BIP2. Then we show that, in linear time, we can reduce BIP2 to Vertex Cover Above LP preserving the parameter k, and we can compute an optimal LP solution for Vertex Cover Above LP using network flow. Then, we perform an exaustive search by fixing half-integral values in the optimal LP solution for Vertex Cover Above LP. A bottleneck here is that we need to recompute an LP optimal solution after branching. To address this issue, we exploit network flow to update the optimal LP solution in linear time.
Direct Load Control of Thermostatically Controlled Loads Based on Sparse Observations Using Deep Reinforcement Learning

This paper considers a demand response agent that must find a near-optimal sequence of decisions based on sparse observations of its environment. Extracting a relevant set of features from these observations is a challenging task and may require substantial domain knowledge. One way to tackle this problem is to store sequences of past observations and actions in the state vector, making it high dimensional, and apply techniques from deep learning. This paper investigates the capabilities of different deep learning techniques, such as convolutional neural networks and recurrent neural networks, to extract relevant features for finding near-optimal policies for a residential heating system and electric water heater that are hindered by sparse observations. Our simulation results indicate that in this specific scenario, feeding sequences of time-series to an LSTM network, which is a specific type of recurrent neural network, achieved a higher performance than stacking these time-series in the input of a convolutional neural network or deep neural network.
A meta‐analysis of epidemiological studies on the combined effect of hepatitis B and C virus infections in causing hepatocellular carcinoma

The aim of the study was to assess whether co‐infection by hepatitis‐B virus (HBV) and hepatitis‐C virus (HCV) is associated with a higher risk of developing hepatocellular carcinoma (HCC) than each infection alone. A meta‐analysis of data published up to June 1997 was performed. HBsAg and anti‐HCV antibodies or HCV RNA (anti‐HCV/HCV RNA) were considered as serological markers of current HBV and HCV infection respectively. A total of 32 case‐control studies were suitable for a quantitative overview. The summary odds ratios (OR) were 13.7 for HBsAg positivity and 11.5 for anti‐HCV/HCV RNA positivity. The OR for anti‐HCV was lower among studies using second‐ or third‐generation anti‐HCV or HCV RNA (OR, 8.2) with respect to studies with first‐generation anti‐HCV test (OR, 19.1). When combining data from the studies with second‐ or third‐generation anti‐HCV or HCV RNA, the OR for HBsAg positivity and anti‐HCV/HCV RNA negativity was 22.5 (95% confidence interval (CI), 19.5–26.0), the OR for anti‐HCV/HCV RNA positivity and HBsAg negativity was 17.3 (95% CI, 13.9–21.6), and the OR for both markers positivity was 165 (95% CI: 81.2–374, based on 191 cases and 8 controls exposed). A synergism was found between HBV and HCV infections, the OR for co‐infection being greater than the sum and lower than the product of those for each infection alone. The interaction was therefore negative according to the multiplicative model, providing epidemiological evidence both of an independent effect and of interference between the 2 viruses in the carcinogenic process. Int. J. Cancer 75:347–354, 1998. © 1998 Wiley‐Liss, Inc.
Low-Complexity Image Processing for Real-Time Detection of Neonatal Clonic Seizures

In this paper, we consider a novel low-complexity real-time image-processing-based approach to the detection of neonatal clonic seizures. Our approach is based on the extraction, from a video of a newborn, of an average luminance signal representative of the body movements. Since clonic seizures are characterized by periodic movements of parts of the body (e.g., the limbs), by evaluating the periodicity of the extracted average luminance signal it is possible to detect the presence of a clonic seizure. The periodicity is investigated, through a hybrid autocorrelation-Yin estimation technique, on a per-window basis, where a time window is defined as a sequence of consecutive video frames. While processing is first carried out on a single window basis, we extend our approach to interlaced windows. The performance of the proposed detection algorithm is investigated, in terms of sensitivity and specificity, through receiver operating characteristic curves, considering video recordings of newborns affected by neonatal seizures.
Neuropsychological functioning in end-stage renal disease

Aims: To compare the neuropsychological functioning and behaviour of children with non-syndromic end-stage renal disease (ESRD) and sibling controls. Methods: The study was carried out at two tertiary care paediatric teaching hospitals, in Halifax and Vancouver, Canada. Children with ESRD were on a renal transplant waiting list and either pending dialysis or on dialysis therapy. Twenty two patient-sibling pairs were evaluated. Neuropsychological assessments consisting of measures of intelligence, academic achievement, memory, and motor abilities were carried out. Maternal ratings of behaviour and self-report rating of self-esteem were collected. Results: The Verbal, Performance, and Full Scale IQs of patients with ESRD were significantly lower than the IQs of the sibling controls. The mean differences were 8.6, 11.7, and 10.9 points, respectively. ESRD patients also had significantly more difficulty on measures of fine motor coordination and ability to copy geometric designs than sibling controls. There were no differences between groups on measures of academic achievement, memory, behaviour, or self-esteem. Conclusions: Although children with ESRD exhibited mild deficits on measures of intelligence and some measures of motor abilities, their neuropsychological outcome was more favourable than earlier reports indicated.
Performance of the Shallow Water Equations on the CM-200 and CM-5 Parallel Supercomputers

Abstract : We describe the implementation of a fluid dynamical benchmark on two Thinking Machines Corporation parallel computers - the 65,536 processor CM-200 computer and the 1024-node CM-5 computer. The benchmark, the Shallow Water Equations, is frequently used as a model for both oceanographic and atmospheric circulation. We describe the steps involved in implementing the algorithm on the computers and we provide details of resulting performance. We have measured 5.2 Gflops (64-bit arithmetic) and 8.1 Gflops (32-bit) on the CM-200 while the CM-5 delivers 22.1 Gflops (64-bit) and 24 Gflops (32-bit). For comparison, performance of 1.53 Gflops was measured for the same algorithm on the CRAY Y-MP/8, 1.28 Gflops on the 256-node SUPRENUM-1 and 0.54 Gflops was measured on the 128-node Intel iPSC/860.
Treatment of angioma serpiginosum using a pulsed tunable dye laser

Angioma serpiginosum (AS) is a rare vascular naevoid disorder due to ectatic dilation of capillaries in the papillary dermis. The condition is found almost exclusively in females who have grouped erythematous punctate lesions usually on the lower limbs or buttocks, which may be unsightly. We report five patients with AS treated using a Candela SPLTl pulsed tunable dye laser. All patients had a good to excellent response. The lesion resolved in tine patient, virtually resolved in two and is considerably improved in a further patient in whom treatment is continuing. In one patient, the angiomatous lesion improved but the patient developed hyperpigmentation at the treatment site and the treatment has been temporarily suspended. The results suggest that treatment using the pulsed dye laser is very effective for AS and, in most patients, produces an excellent cosmetic result.
Design and Characterization of a Portable Ultrasonic Indoor 3-D Positioning System

In this paper, an ultrasonic positioning system is presented and characterized, based on the usage of a portable grid of beacons and of a few fixed anchors. Since the beacon grid can be moved to guarantee line-of-sight transmissions, the proposed strategy is potentially suitable for accurate positioning of a mobile object in an environment with a complex geometry. The system was tested experimentally, exhibiting a subcentimeter positioning accuracy in a range up to 4 m.
A compact printed UWB MIMO antenna with WLAN band rejection

In this paper, a two element ultra-wideband (UWB) multiple input multiple output (MIMO) antenna with local area network (WLAN) rejection is presented. A T-shaped slot is etched on the ground to improve the impedance matching characteristic in the low-frequency and reduce the mutual coupling. A line slot is introduced in the ground plane to further enhance isolation. The UWB MIMO band notched antenna has a very compact size of 22mm × 30 mm. This compact size along with good UWB characteristics make this antenna good candidate for UWB MIMO systems.
Central Inflammation and Leptin Resistance Are Attenuated by Ginsenoside Rb1 Treatment in Obese Mice Fed a High-Fat Diet

A low-grade pro-inflammatory state is at the pathogenic core of obesity and type 2 diabetes. We tested the hypothesis that the plant terpenoid compound ginsenoside Rb1 (Rb1), known to exert anti-inflammatory effects, would ameliorate obesity, obesity-associated inflammation and glucose intolerance in the high-fat diet-induced obese mouse model. Furthermore, we examined the effect of Rb1 treatment on central leptin sensitivity and the leptin signaling pathway in the hypothalamus. We found that intraperitoneal injections of Rb1 (14 mg/kg, daily) for 21 days significantly reduced body weight gain, fat mass accumulation, and improved glucose tolerance in obese mice on a HF diet compared to vehicle treatment. Importantly, Rb1 treatment also reduced levels of pro-inflammatory cytokines (TNF-α, IL-6 and/or IL-1β) and NF-κB pathway molecules (p-IKK and p-IκBα) in adipose tissue and liver. In the hypothalamus, Rb1 treatment decreased the expression of inflammatory markers (IL-6, IL-1β and p-IKK) and negative regulators of leptin signaling (SOCS3 and PTP1B). Furthermore, Rb1 treatment also restored the anorexic effect of leptin in high-fat fed mice as well as leptin pSTAT3 signaling in the hypothalamus. Ginsenoside Rb1 has potential for use as an anti-obesity therapeutic agent that modulates obesity-induced inflammation and improves central leptin sensitivity in HF diet-induced obesity.