Miracle-dz/UniFAR-FTUs huggingface dataset:
Building consistent transactions with inconsistent replication

Application programmers increasingly prefer distributed storage systems with strong consistency and distributed transactions (e.g., Google's Spanner) for their strong guarantees and ease of use. Unfortunately, existing transactional storage systems are expensive to use -- in part because they require costly replication protocols, like Paxos, for fault tolerance. In this paper, we present a new approach that makes transactional storage systems more affordable: we eliminate consistency from the replication protocol while still providing distributed transactions with strong consistency to applications. We present TAPIR -- the Transactional Application Protocol for Inconsistent Replication -- the first transaction protocol to use a novel replication protocol, called inconsistent replication, that provides fault tolerance without consistency. By enforcing strong consistency only in the transaction protocol, TAPIR can commit transactions in a single round-trip and order distributed transactions without centralized coordination. We demonstrate the use of TAPIR in a transactional key-value store, TAPIR-KV. Compared to conventional systems, TAPIR-KV provides better latency and throughput.
Study of subgridding in SAR computation for the cochlea

A 3D subgridding technique is used to model the specific absorption rate (SAR) distribution in the isolated cochlea exposed to mobile phone radiation at 1750 MHz using the FDTD method. The cochlea is modeled using an increasing spatial resolutions of 1, 1/3, 1/5, and 1/7 mm. First simulations were performed at 1 mm spatial resolution. The numerical resolution was then increased to 1/3, 1/5, and 1/7 using subgridding without changing the spatial resolution. A second set of simulations was then performed when both the spatial and numerical resolution were increased together. From the obtained results, we conclude that subgridding is important only when both the numerical resolution of the computational grid and the spatial resolution of the model are increased together. Bioelectromagnetics 26:520–522, 2005. © 2005 Wiley‐Liss, Inc.
Should the Use of Selective Serotonin Reuptake Inhibitors in Child and Adolescent Depression Be Banned?

Background: European and US pharmaceutical agencies have recently warned against the use of selective serotonin reuptake inhibitors (SSRIs) in child and adolescent depression. This came as a surprise to many practitioners, who had made treatment decisions based on data from pharmaceutical trials using adult samples. Method: The author reviews the recent literature relevant to the use of SSRIs in youth depression, including psychiatricclinical trials, pharmacology and drug safety data. Recommendations and rationales for the use of SSRIs in this context are offered. Results: Ten publications, comprising a total of 2,046 patients, evaluated the efficacy of four SSRIs (fluoxetine, paroxetine, sertraline and citalopram) in child and adolescent depression. It is noted that an additional 6 trials (with a total of 1,234 patients) were not reported by the industry because of a lack of efficacy or problematic side effects, including suicidal behaviors. Meta-analyses revealed no data supporting the use of SSRIs, except for fluoxetine. To formulate recommendations for clinical practice, it is necessary to examine specific issues such as (1) the link between SSRIs, depression and suicidal risk; (2) SSRI age-related specific effects, and (3) the high placebo response in child and adolescent depression. Conclusion: An SSRI prescription is still a second-line option in severe and resistant forms of youth depression. However, in children and adolescents only specialists well trained in child and adolescent psychiatry should prescribe SSRIs.
Lateral and vertical scaling of a QSA HBT for a 0.13/spl mu/m 200GHz SiGe:C BiCMOS technology

A 200 GHz F/sub t/ SiGe:C HBT has been integrated into a 0.13 /spl mu/m BiCMOS technology. A previous generation low complexity quasi self-aligned architecture (QSA) is scaled down both in a lateral and vertical way. Lateral sizing is obtained by using present-day step and scan tools. Vertical sizing is achieved by reducing the thermal budget of the active module and by an aggressive scaling of the SiGe:C base epitaxial layer. A deep trench module, featuring a thick oxide liner, has been developed. Excellent DC parameters and peak Ft/Fmax values of 200/160 GHz are demonstrated. The CMOS device characteristics remain unchanged by applying low thermal budget processing in the bipolar module.
Ability of the Photochemical Reflectance Index to Track Light Use Efficiency for a Sub-Tropical Planted Coniferous Forest

Light use efficiency (LUE) models are widely used to estimate gross primary productivity (GPP), a dominant component of the terrestrial carbon cycle. Their outputs are very sensitive to LUE. Proper determination of this parameter is a prerequisite for LUE models to simulate GPP at regional and global scales. This study was devoted to investigating the ability of the photochemical reflectance index (PRI) to track LUE variations for a sub-tropical planted coniferous forest in southern China using tower-based PRI and GPP measurements over the period from day 101 to 275 in 2013. Both half-hourly PRI and LUE exhibited detectable diurnal and seasonal variations, and decreased with increases of vapor pressure deficit (VPD), air temperature (Ta), and photosynthetically active radiation (PAR). Generally, PRI is able to capture diurnal and seasonal changes in LUE. However, correlations of PRI with LUE varied dramatically throughout the growing season. The correlation was the strongest (R2 = 0.6427, p 0.3) with moderate to high VPD (>20 hPa) and high temperatures (>31 C). Overall, we found that PRI is most sensitive to variations in LUE under stressed conditions, and the sensitivity decreases as the growing conditions become favorable when atmosphere water vapor, temperature and soil moisture are near the optimum conditions.
Time‐adaptive wind turbine model for an LES framework

Most large-eddy simulation studies related to wind energy have been carried out either by using a fixed pressure gradient to ensure that mean wind direction is perpendicular to the wind turbine rotor disk or by forcing the flow with a geostrophic wind and timely readjusting the turbines' orientation. This has not allowed for the study of wind farm characteristics with a time-varying wind vector. In this paper, a new time-adaptive wind turbine model for the large-eddy simulation framework is introduced. The new algorithm enables the wind turbines to dynamically realign with the incoming wind vector and self-adjust the yaw orientation with the incoming wind vector similar to real wind turbines. The performance of the new model is tested first with a neutrally stratified atmospheric flow forced with a time-varying geostrophic wind vector. A posteriori, the new model is used to further explore the interaction between a synthetic time-changing thermal atmospheric boundary layer and an embedded wind farm. Results show that there is significant potential power to be harvested during the unstable time periods at the cost of designing wind turbines capable of adapting to the enhanced variance of these periods. Stable periods provide less power but are more constant over time with an enhanced lateral shear induced by an increased change in wind direction with height. Copyright (c) 2015 John Wiley & Sons, Ltd.
Geomagnetism for Smartphone-Based Indoor Localization

Geomagnetism has recently attracted considerable attention for indoor localization due to its pervasiveness and independence from extra infrastructure. Its location signature has been observed to be temporally stable and spatially discernible for localization purposes. This survey examines and analyzes the recent challenges and advances in geomagnetism-based indoor localization using smartphones. We first study smartphone-based geomagnetism measurements. We then review recent efforts in database construction and computation reduction, followed by state-of-the-art schemes in localizing the target. For each category, we identify practical deployment challenges and compare related studies. Finally, we summarize future directions and provide a guideline for new researchers in this field.
Software quality prediction using mixture models with EM algorithm

The use of the statistical technique of mixture model analysis as a tool for early prediction of fault-prone program modules is investigated. The expectation-maximum likelihood (EM) algorithm is engaged to build the model. By only employing software size and complexity metrics, this technique can be used to develop a model for predicting software quality even without the prior knowledge of the number of faults in the modules. In addition, Akaike Information Criterion (AIC) is used to select the model number which is assumed to be the class number the program modules should be classified. The technique is successful in classifying software into fault-prone and non fault-prone modules with a relatively low error rate, providing a reliable indicator for software quality prediction.
Catheter Ablation of Fascicular Ventricular Tachycardia

Background—Fascicular ventricular tachycardia (FVT) is a common form of sustained idiopathic left ventricular tachycardia with an Asian preponderance. This study aimed to prospectively investigate long-term clinical outcomes of patients undergoing ablation of FVT and identify predictors of arrhythmia recurrence. Methods and Results—Consecutive patients undergoing FVT ablation at a single tertiary center were enrolled. Activation mapping was performed to identify the earliest presystolic Purkinje potential during FVT that was targeted by radiofrequency ablation. Follow-up with clinic visits, ECG, and Holter monitoring was performed at least every 6 months. A total of 120 consecutive patients (mean age, 29.3±12.7 years; 82% men; all patients with normal ejection fraction) were enrolled. FVT involved left posterior fascicle and left anterior fascicle in 118 and 2 subjects, respectively. VT was noninducible in 3 patients, and ablation was acutely successful in 117 patients. With a median follow-up of 55.7 months, VT of a similar ECG morphology recurred in 17 patients, and repeat procedure confirmed FVT recurrence involving the same fascicle. Shorter VT cycle length was the only significant predictor of FVT recurrence (P=0.03). Six other patients developed new-onset upper septal FVT that was successfully ablated. Conclusions—Ablation of FVT guided by activation mapping is associated with a single procedural success rate without the use of antiarrhythmic drugs of 80.3%. Arrhythmia recurrences after an initially successful ablation were caused by recurrent FVT involving the same fascicle in two thirds of patients or new onset of upper septal FVT in the remainder.
Individual music therapy for depression: randomised controlled trial

Background Music therapy has previously been found to be effective in the treatment of depression but the studies have been methodologically insufficient and lacking in clarity about the clinical model employed. Aims To determine the efficacy of music therapy added to standard care compared with standard care only in the treatment of depression among working-age people. Method Participants (n = 79) with an ICD–10 diagnosis of depression were randomised to receive individual music therapy plus standard care (20 bi-weekly sessions) or standard care only, and followed up at baseline, at 3 months (after intervention) and at 6 months. Clinical measures included depression, anxiety, general functioning, quality of life and alexithymia. Trial registration: ISRCTN84185937. Results Participants receiving music therapy plus standard care showed greater improvement than those receiving standard care only in depression symptoms (mean difference 4.65, 95% CI 0.59 to 8.70), anxiety symptoms (1.82, 95% CI 0.09 to 3.55) and general functioning (–4.58, 95% CI −8.93 to −0.24) at 3-month follow-up. The response rate was significantly higher for the music therapy plus standard care group than for the standard care only group (odds ratio 2.96, 95% CI 1.01 to 9.02). Conclusions Individual music therapy combined with standard care is effective for depression among working-age people with depression. The results of this study along with the previous research indicate that music therapy with its specific qualities is a valuable enhancement to established treatment practices.
The Price of Artificial Intelligence

Summary Introduction: Whilst general artificial intelligence (AI) is yet to appear, today’s narrow AI is already good enough to transform much of healthcare over the next two decades. Objective: There is much discussion of the potential benefits of AI in healthcare and this paper reviews the cost that may need to be paid for these benefits, including changes in the way healthcare is practiced, patients are engaged, medical records are created, and work is reimbursed. Results: Whilst AI will be applied to classic pattern recognition tasks like diagnosis or treatment recommendation, it is likely to be as disruptive to clinical work as it is to care delivery. Digital scribe systems that use AI to automatically create electronic health records promise great efficiency for clinicians but may lead to potentially very different types of clinical records and workflows. In disciplines like radiology, AI is likely to see image interpretation become an automated process with diminishing human engagement. Primary care is also being disrupted by AI-enabled services that automate triage, along with services such as telemedical consultations. This altered future may necessarily see an economic change where clinicians are increasingly reimbursed for value, and AI is reimbursed at a much lower cost for volume. Conclusion: AI is likely to be associated with some of the biggest changes we will see in healthcare in our lifetime. To fully engage with this change brings promise of the greatest reward. To not engage is to pay the highest price.
Testing Monotonicity

at arguments of its choice, the test always accepts a monotone f, and rejects f with high probability if it is ε-far from being monotone (i.e., every monotone function differs from f on more than an ε fraction of the domain). The complexity of the test is O(n/ε). The analysis of our algorithm relates two natural combinatorial quantities that can be measured with respect to a Boolean function; one being global to the function and the other being local to it. A key ingredient is the use of a switching (or sorting) operator on functions.
Maximum Likelihood Detection for Cooperative Molecular Communication

In this paper, symbol-by-symbol maximum likelihood (ML) detection is proposed for a cooperative diffusion-based molecular communication (MC) system. In this system, a fusion center (FC) chooses the transmitter's symbol that is more likely, given the likelihood of the observations from multiple receivers (RXs). We propose three different ML detection variants according to different constraints on the information available to the FC, which enables us to demonstrate trade- offs in their performance versus the information available. The system error probability for one variant is derived in closed form. Numerical and simulation results show that the ML detection variants provide lower bounds on the error performance of the simpler cooperative variants and demonstrate that majority rule detection has performance comparable to ML detection when the reporting is noisy.
SubdSH: Subdivision-based Spherical Harmonics Field for Real-time Shading-based Refinement under Challenging Unknown Illumination

This paper presents a spatial-varying illumination model for shading-based depth refinement that based on a smooth Spherical Harmonics (SH) lighting field. The proposed lighting model is able to recover shading under challenging unknown lighting conditions, thus improving the quality of recovered surface detail. To avoid over-parameterization, local lighting coefficients are treated as a vector-valued function which is represented by subdivided surfaces using Catmull-Clark subdivision. We solve our lighting model utilizing a highly parallelized scheme that recovers lighting in a few milliseconds. A real-time shading-based depth recovery system is implemented with the integration of our proposed lighting model. We conduct quantitative and qualitative evaluations on both synthetic and real world datasets under challenging illumination. The experimental results show our method outperforms the state-of-the-art real-time shading-based depth refinement system.
Observation of a Curve Crossing Mechanism in the Field Ionization of Inner-Shell Excited Single ${\rm Xe}^{33+}{(2\bar{\rm p})}$ and Double ${\rm Xe}^{34+}{(2\bar{\rm s}2\bar{\rm p})}$ Vacancy States

Anomalous intensity dependent quenching of the Xe(L) hollow atom emission from the single Xe<sup>33+</sup>(2p̅) and double Xe<sup>34+</sup>(2s̅2p̅) vacancy 3d→2p transition arrays indicates the presence of a state-selective curve crossing mechanism for the field ionization of the excited 3d<sup>4</sup> configuration by intense (2-3 × 10<sup>20</sup> × W/cm<sup>2</sup>) 248-nm radiation.
Vision Screening of Younger School Children by School Teachers: A Pilot Study in Udaipur City, Western India

Purpose: To assess the reliability of school teachers for vision screening of younger school children and to study the pattern of vision problems. Methods: In this cross-sectional study, trained school teachers screened 5,938 school children aged 3 to 8 years for vision and ocular disorders. Children were cross screened by professionals to assess the reliability of the teachers in vision screening and detecting ocular disorders in these children. The pattern of visual acuity, ametropia and ocular disorders was studied. Results: Sensitivity and specificity of the vision screening by school teachers was 69.2% (95% CI: 66.8-71.5%) and 95.3% (95% CI: 94.5-95.8%), respectively. The positive predictive value was 83.5% (95% CI: 81.4-85.6%) and negative predictive value was 89.8% (95% CI: 88.8-90.6%). The kappa statistic was 0.68 (95% CI: 0.66-0.7). Conclusion: School teachers could effectively screen younger school children for vision assessment and ocular disorders.
Robust Road Extraction for High Resolution Satellite Images

Automatic road extraction is a critical feature for an efficient use of remote sensing imagery in most contexts. This paper proposes a robust geometric method to provide a first step extraction level. These results can be used as an initialization for other algorithms or as a starting point for manual road extraction. Results of the extraction are vectorized for GIS integration and for a better interaction with human experts that can refine the results. The algorithm is fast, has very few parameters and is only slightly affected by the image properties (resolution, noise). The algorithm is available in the open-source Orfeo toolbox.
Asymptotic Optimality and Rates of Convergence of Quantized Stationary Policies in Stochastic Control

We consider the discrete approximation of stationary policies for a discrete-time Markov decision process with Polish state and action spaces under total, discounted, and average cost criteria. Deterministic stationary quantizer policies are introduced and shown to be able to approximate optimal deterministic stationary policies with arbitrary precision under mild technical conditions, thus demonstrating that one can search for ε-optimal policies within the class of quantized control policies. We also derive explicit bounds on the approximation error in terms of the quantization rate.
Where Does HIT Fit? An Examination of the Affective Response to High-Intensity Intervals in Comparison to Continuous Moderate- and Continuous Vigorous-Intensity Exercise in the Exercise Intensity-Affect Continuum

Affect experienced during an exercise session is purported to predict future exercise behaviour. Compared to continuous moderate-intensity exercise (CMI), the affective response to continuous vigorous-intensity exercise (CVI) has consistently been shown to be more aversive. The affective response, and overall tolerability to high-intensity interval training (HIT), is less studied. To date, there has yet to be a comparison between HIT, CVI, and CMI. The purpose of this study was to compare the tolerability and affective responses during HIT to CVI and CMI. This study utilized a repeated measures, randomized, counter-balanced design. Forty-four participants visited the laboratory on four occasions. Baseline fitness testing was conducted to establish peak power output in Watts (Wpeak). Three subsequent visits involved a single bout of a) HIT, corresponding to 1-minute at ∼100% Wpeak and 1-minute at ∼20% Wpeak for 20 minutes, b) CMI, corresponding to ∼40% Wpeak for 40 minutes, and c) CVI, corresponding to ∼80% Wpeak for 20 minutes. The order of the sessions was randomized. Affective responses were measured before, during and after each session. Task self-efficacy, intentions, enjoyment and preference were measured after sessions. Participants reported greater enjoyment of HIT as compared to CMI and CVI, with over 50% of participants reporting a preference to engage in HIT as opposed to either CMI or CVI. HIT was considered more pleasurable than CVI after exercise, but less pleasurable than CMI at these times. Despite this participants reported being just as confident to engage in HIT as they were CMI, but less confident to engage in CVI. This study highlights the utility of HIT in inactive individuals, and suggests that it may be a viable alternative to traditionally prescribed continuous modalities of exercise for promoting self-efficacy and enjoyment of exercise.
Dual-network memory model using a chaotic neural network

In neural networks, when new patterns are learned by a network, the new information radically interferes with previously stored patterns. This drawback is called catastrophic forgetting or catastrophic interference. In this paper, we propose a biologically inspired neural network model which overcomes this problem. The proposed model consists of two distinct networks: one is a Hopfield type of chaotic associative memory and the other is a multilayer neural network. We consider that these networks correspond to the hippocampus and the neocortex of the brain, respectively. Information given is firstly stored in the hippocampal network with fast learning algorithm. Then the stored information is recalled by chaotic behavior of each neuron in the hippocampal network. Finally, it is consolidated in the neocortical network by using pseudopatterns. Computer simulation results show that the proposed model has much better ability to avoid catastrophic forgetting in comparison with conventional models.