Miracle-dz/UniFAR-FTUs huggingface dataset:
Strategies for Introducing Wolbachia to Reduce Transmission of Mosquito-Borne Diseases

Certain strains of the endosymbiont Wolbachia have the potential to lower the vectorial capacity of mosquito populations and assist in controlling a number of mosquito-borne diseases. An important consideration when introducing Wolbachia-carrying mosquitoes into natural populations is the minimisation of any transient increase in disease risk or biting nuisance. This may be achieved by predominantly releasing male mosquitoes. To explore this, we use a sex-structured model of Wolbachia-mosquito interactions. We first show that Wolbachia spread can be initiated with very few infected females provided the infection frequency in males exceeds a threshold. We then consider realistic introduction scenarios involving the release of batches of infected mosquitoes, incorporating seasonal fluctuations in population size. For a range of assumptions about mosquito population dynamics we find that male-biased releases allow the infection to spread after the introduction of low numbers of females, many fewer than with equal sex-ratio releases. We extend the model to estimate the transmission rate of a mosquito-borne pathogen over the course of Wolbachia establishment. For a range of release strategies we demonstrate that male-biased release of Wolbachia-infected mosquitoes can cause substantial transmission reductions without transiently increasing disease risk. The results show the importance of including mosquito population dynamics in studying Wolbachia spread and that male-biased releases can be an effective and safe way of rapidly establishing the symbiont in mosquito populations.
Caregiver involvement in behavioural health services in the context of child welfare service referrals: a qualitative study

Human service agencies serve a growing number of adults with behavioral health needs. Despite these agencies' key role in identifying need and facilitating services, many individuals do not receive care or end services prematurely. Few studies have explored the experiences of families referred to behavioral health services by such agencies or the extent to which families' perceptions of service need align with those of treatment providers and frontline workers. This study presents findings from a qualitative study of caregivers involved with child welfare agencies who were referred to behavioral health services. Researchers reviewed agencies' case records and conducted in-depth interviews with 16 caregivers, 9 child welfare caseworkers, and 12 behavioral health treatment counselors. Findings suggest that when deciding to engage in services, caregivers weigh not only their individual and family behavioral health needs but also potential agency intervention, including loss of child custody. Many professionals reported that involvement with a child welfare agency hindered the caregiver's disclosure of behavioral health care needs. Implications for managers and practitioners are discussed.
Content offloading via D2D communications based on user interests and sharing willingness

As a promising solution to offload cellular traffic, device-to-device (D2D) communication has been adopted to help disseminate contents. In this paper, the D2D offloading utility is maximized by proposing an optimal content pushing strategy based on the user interests and sharing willingness. Specifically, users are classified into groups by their interest probabilities and carry out D2D communications according to their sharing willingness. Although the formulated optimization problem is nonconvex, the optimal solution is obtained in closed-form by applying Karush-Kuhn-Tucker conditions. The theoretical and simulation results show that more contents should be pushed to the user group that is most willing to share, instead of the group that has the largest number of interested users.
Genetic dissection of Down syndrome-associated congenital heart defects using a new mouse mapping panel

Down syndrome (DS), caused by trisomy of human chromosome 21 (Hsa21), is the most common cause of congenital heart defects (CHD), yet the genetic and mechanistic causes of these defects remain unknown. To identify dosage-sensitive genes that cause DS phenotypes, including CHD, we used chromosome engineering to generate a mapping panel of 7 mouse strains with partial trisomies of regions of mouse chromosome 16 orthologous to Hsa21. Using high-resolution episcopic microscopy and three-dimensional modeling we show that these strains accurately model DS CHD. Systematic analysis of the 7 strains identified a minimal critical region sufficient to cause CHD when present in 3 copies, and showed that it contained at least two dosage-sensitive loci. Furthermore, two of these new strains model a specific subtype of atrio-ventricular septal defects with exclusive ventricular shunting and demonstrate that, contrary to current hypotheses, these CHD are not due to failure in formation of the dorsal mesenchymal protrusion.
Varanus: More-with-less fault localization in data centers

Detecting and localizing performance faults is crucial for operating large enterprise data centers. This problem is relatively straightforward to solve if each entity (applications, servers, business processes) within the data center can be instrumented and monitored explicitly. Unfortunately, such instrument-everything approach is often not tenable because of the limits imposed by enterprises on the permissible amounts of instrumentation intrusiveness and monitoring overhead. In this paper, we address the problem of achieving high accuracy of detecting and localizing performance faults in data centers, while minimizing the required instrumentation intrusiveness and overhead. We present novel algorithms for solving three key subproblems: (1) How many monitors are required and where should they be placed within the data center? (2) Given the proposed instrumentation plan, how to detect the existence of performance faults accurately? and (3) How to localize the root-cause of the fault? We demonstrate the effectiveness of our approach for a real-world data center topology as well as through extensive simulations.
Robust trajectory tracking controller for XY table

This paper proposed a robust controller that can control non-minimum phase servo systems at high speed frequency. Feedforward adaptive Zero Phase Error Tracking Control (ZPETC) with model reference is applied. This technique can expand the bandwidth for high frequency closed to unity gain. Two non-minimum phase systems with different location of zero are considered in this paper. The systems are a difficult system which posses an unstable zero very near to the critical point and an unstable system that have a zero far from the unity. The system models are obtained via system identification technique using Matlab Toolbox by varying the sampling time. The performance of the controller in reducing the tracking error using high frequency input is analyzed through simulation. The proposed controller shows tremendous tracking performance.
Discussion on Principle and Application of Hypoxic Body Exercise

The purpose of this study was to discuss the principle of hypoxic body exercise and its application in national fitness program.Through using the method of comprehensive review,this paper explained the concept and principle of hypoxic body exercise as well as the significance and application in the fields of body exercise and recovery,put forwarded the problems that need to be solved urgently in the development of hypoxic body exercise.The result showed that with the application of artificial hypoxic technique in athletic training,this kind of technique is widely used in hypoxic body exercise.The hypoxic body exercise can help to improve the national fitness and health level.
Perception of emotion in musical performance in adolescents with autism spectrum disorders

Individuals with autism spectrum disorders (ASD) are impaired in understanding the emotional undertones of speech, many of which are communicated through prosody. Musical performance also employs a form of prosody to communicate emotion, and the goal of this study was to examine the ability of adolescents with ASD to understand musical emotion. We designed an experiment in which each musical stimulus served as its own control while we varied the emotional expressivity by manipulating timing and amplitude variation. We asked children and adolescents with ASD and matched controls as well as individuals with Williams syndrome (WS) to rate how emotional these excerpts sounded. Results show that children and adolescents with ASD are impaired relative to matched controls and individuals with WS at judging the difference in emotionality among the expressivity levels. Implications for theories of emotion in autism are discussed in light of these findings.
Fast Independent Component Analysis Based Digital Modulation Recognition Method

This paper proposes an efficient Independent Component Analysis (ICA) based modulation feature extraction method applied in digital modulation identification. In modulation identification, important information may be contained in the high-order relationship among sampling points. ICA is sensitive to high-order statistic in the data and finds not-necessarily orthogonal bases, so it may better identify and reconstruct high-dimensional communication signal data than traditional time and frequency domain features. ICA algorithms are time-consuming and sometimes converge difficultly. So a modified FastICA algorithm is developed in this paper, which only need to computer Jacobian Matrix once time in one iteration and achieves the correspondent effect of FastICA. After obtaining all independent components, a genetic algorithm is introduced to select optimal independent components (ICs). The experiment results show that modified FastICA algorithm fast convergence speed and genetic algorithm optimize recognition performance. ICA based features extraction method is innovative and promising for digital modulation identification.
Executive compensation regulation and the dynamics of the pay-performance sensitivity

A substantial number of empirical studies on the linear relationship between executive compensation and firm performance for European firms suggest that the pay-performance sensitivity is not significantly positive. We argue that a nonlinear structure fits the data better, because compensation contracts provide for minimum performance benchmarks and an upper limit to the variable component of compensation. We test for such discontinuities in the pay performance relationship, and confirm their existence, using hand collected data from German Prime All Share firmsâ€™ CEO bonus compensation. It turns out that there is a significant positive relationship between return on assets and CEO bonus for ROA between -3% and +20%. Performance sensitivity is then tested for changes over time between 2006 and 2009. Results reveal that during the first three years after the introduction of a statutory transparency rule in 2005 governing the disclosure of individual CEO compensation, significant changes to compensation contracts did not occur; but that in 2009 the pay-performance sensitivity exhibited a significant increase, which coincides with the passing of a law that requires supervisory boards to ensure that new CEO employment contracts provide for â€™reasonableâ€™ compensation.
An Abstract Interpretation Algorithm for Residuating Logic Programs

Residuation is an operational mechanism for the integration of functions into logic programming languages. The residuation principle delays the evaluation of functions during the unification process until the arguments are sufficiently instantiated. This has the advantage that the deterministic nature of functions is preserved but the disadvantage of incompleteness: if the variables in a delayed function call are not instantiated by the logic program, this function can never be evaluated and some answers which are logical consequences of the program are lost. In order to detect such situations at compile time, we present an abstract interpretation algorithm for this kind of programs. The algorithm approximates the possible residuations and instantiation states of variables during program execution. If the algorithm computes an empty residuation set for a goal, then it is ensured that the concrete execution of the goal does not end with a nonempty set of residuations which cannot be evaluated due to insufficient instantiation of argument variables.
Natural video matting using camera arrays

We present an algorithm and a system for high-quality natural video matting using a camera array. The system uses high frequencies present in natural scenes to compute mattes by creating a synthetic aperture image that is focused on the foreground object, which reduces the variance of pixels reprojected from the foreground while increasing the variance of pixels reprojected from the background. We modify the standard matting equation to work directly with variance measurements and show how these statistics can be used to construct a trimap that is later upgraded to an alpha matte. The entire process is completely automatic, including an automatic method for focusing the synthetic aperture image on the foreground object and an automatic method to compute the trimap and the alpha matte. The proposed algorithm is very efficient and has a per-pixel running time that is linear in the number of cameras. Our current system runs at several frames per second, and we believe that it is the first system capable of computing high-quality alpha mattes at near real-time rates without the use of active illumination or special backgrounds.
Real-Time Power System Control Using Synchrophasors

To date, synchronized phasor measurements have been used mainly for power system model validation, postevent analysis, real-time display, and other similar activities. However, synchrophasors have a greater potential than monitoring and visualization. Synchrophasors will increasingly contribute to the reliable and economical operation of power systems as real-time control and protection schemes become broadly used. Synchronous phasor measurements are now available in relays and meters; however, a practical means of processing the data in real time had been lacking. This paper describes a synchronous vector processor and several practical applications, including automated diagnostics, remedial action schemes, direct state measurement, and stability assessment.
Seeing the invisible: forensic uses of anomaly detection and machine learning

Anti-forensics is the practice of circumventing classical forensics analysis procedures making them either unreliable or impossible. In this paper we propose the use of machine learning algorithms and anomaly detection to cope with a wide class of definitive anti-forensics techniques. We test the proposed system on a dataset we created through the implementation of an innovative technique of anti-forensics, and we show that our approach yields promising results in terms of detection.
A two-channel training algorithm for hidden Markov model to identify visual speech elements

A novel two-channel algorithm is proposed in this paper for discriminative training of Hidden Markov Models (HMMs). It adjusts the symbol emission coefficients of an existing HMM to maximize the separable distance between a pair of confusable training samples. The method is applied to identify the visemes of visual speech. The results indicate that the two-channel training method provides better accuracy on separating similar visemes than the conventional Baum-Welch estimation.
Transition dynamics in the neoclassical growth model: the case of South Korea

Abstract Many successful examples of economic development, such as South Korea, exhibit long periods of sustained capital accumulation. This process is characterized by a gradually rising investment rate along with a moderate rate of return to capital, both of which are strongly at odds with the standard neoclassical growth model that predicts an initially high and then declining investment rate with an extremely high return to capital. We show that minor modifications of the neoclassical model go a long way toward accounting for the capital accumulation path of the South Korean economy. Our modifications recognize that (i) agriculture (which makes up a large share of the aggregate economy in the early stage of development) does not rely much on capital and (ii) the relative price of capital declined substantially during the transition period.
High-Resolution Functional MRI at 3 T: 3D/2D Echo-Planar Imaging with Optimized Physiological Noise Correction

High‐resolution functional MRI (fMRI) offers unique possibilities for studying human functional neuroanatomy. Although high‐resolution fMRI has proven its potential at 7 T, most fMRI studies are still performed at rather low spatial resolution at 3 T. We optimized and compared single‐shot two‐dimensional echo‐planar imaging (EPI) and multishot three‐dimensional EPI high‐resolution fMRI protocols. We extended image‐based physiological noise correction from two‐dimensional EPI to multishot three‐dimensional EPI. The functional sensitivity of both acquisition schemes was assessed in a visual fMRI experiment. The physiological noise correction increased the sensitivity significantly, can be easily applied, and requires simple recordings of pulse and respiration only. The combination of three‐dimensional EPI with physiological noise correction provides exceptional sensitivity for 1.5 mm high‐resolution fMRI at 3 T, increasing the temporal signal‐to‐noise ratio by more than 25% compared to two‐dimensional EPI. Magn Reson Med, 2013. © 2012 The Authors. Magnetic Resonance in Medicine Published by Wiley Periodicals, Inc. on behalf of International Society of Medicine in Resonance.
Exact finite-size-scaling corrections to the critical two-dimensional Ising model on a torus: II. Triangular and hexagonal lattices

We compute the finite-size corrections to the free energy, internal energy and specific heat of the critical two-dimensional spin-1/2 Ising model on triangular and hexagonal lattices wrapped on a torus. We find the general form of the finite-size corrections to these quantities, as well as explicit formulae for the first coefficients of each expansion. We analyse the implications of these findings for the renormalization-group description of the model.
Software Engineering Meets Control Theory

The software engineering community has proposed numerous approaches for making software self-adaptive. These approaches take inspiration from machine learning and control theory, constructing software that monitors and modifies its own behavior to meet goals. Control theory, in particular, has received considerable attention as it represents a general methodology for creating adaptive systems. Control-theoretical software implementations, however, tend to be ad hoc. While such solutions often work in practice, it is difficult to understand and reason about the desired properties and behavior of the resulting adaptive software and its controller. This paper discusses a control design process for software systems which enables automatic analysis and synthesis of a controller that is guaranteed to have the desired properties and behavior. The paper documents the process and illustrates its use in an example that walks through all necessary steps for self-adaptive controller synthesis.
Detection of Mycobacterium leprae by PCR Testing of Sputa from a Patient with Pulmonary Cryptococcus Coinfection in Northern Australia

ABSTRACT A case of fever, sepsis, and chest lesions evident on a computed tomography scan of an indigenous man in northern Australia following burns to the feet is described. Sputum PCR testing revealed Mycobacterium leprae, and a fine-needle aspirate of the chest lesions demonstrated Cryptococcus coinfection.
Energy Minimization in Machine-to-Machine Systems with Energy Harvesting

In this paper, we investigate the sum energy minimization problem in an uplink machine-to- machine (M2M) system with energy harvesting. To solve this nonconvex sum energy minimization problem, we first transform it into an equivalent convex problem and provide the optimal condition of the original problem. Then, we propose a low- complexity iterative scheme, which yields the optimal solution. The complexity of the proposed scheme is also analyzed. Numerical results show that the proposed scheme can achieve good performance.
Glue-Nail: a deductive database system

Glue is a procedural language for deductive databases. It is designed to complement the purely declarative NAIL! language, firstly by performing system functions impossible to write in NAIL! , and secondly by allowing the procedural specification of algorithms for critical code sections. The two languages together are sufficient to write a complete application. Glue was designed to be as close to NAIL! as possible, hence minimizing the impedance mismatch problem. In this paper we concentrate on Glue. Pseudo-higher order programming is used in both languages, in the style of HiLog [1]. In particular Glue-Nail can handle set valued attributes (non1NF schemas) in a clean and efficient manner. NAIL! code is compiled into Glue code, simplifying the system design. An experimental implementation has been written, a more efficient version is under design.
Cost-effectiveness of Intravitreous Ranibizumab Compared With Panretinal Photocoagulation for Proliferative Diabetic Retinopathy: Secondary Analysis From a Diabetic Retinopathy Clinical Research Network Randomized Clinical Trial

Importance The Diabetic Retinopathy Clinical Research Network Protocol S randomized clinical trial results suggest that ranibizumab is a reasonable treatment alternative to panretinal photocoagulation (PRP) when managing proliferative diabetic retinopathy (PDR), with or without concomitant baseline diabetic macular edema (DME). However, ranibizumab injections are costly. Thus, it would be useful to examine the relative cost-effectiveness of these 2 treatment modalities. Objective To evaluate incremental cost-effectiveness ratios of 0.5-mg ranibizumab therapy vs PRP for PDR. Design, Setting, and Participants Preplanned secondary analysis using efficacy, safety, and resource utilization data through 2 years of follow-up at 55 US sites for 213 adults with PDR. Data were collected from February 2012 to January 2015. Interventions Intravitreous 0.5-mg ranibizumab at baseline and as frequently as every 4 weeks based on a structured retreatment protocol or PRP at baseline for PDR. Eyes in both groups could receive ranibizumab for concomitant DME. Main Outcomes and Measures Incremental cost-effectiveness ratios of ranibizumab compared with PRP evaluated within 2 prespecified subgroups for the study eye: with baseline vision-impairing (Snellen equivalent 20/32 or worse) DME and without baseline vision-impairing DME. Results The study included 305 adults with PDR, the mean age was 52 years, 44% were women, and 52% were white. Of the 46 participants with PDR and vision-impairing DME at baseline, 21 were assigned to the ranibizumab group and 25 to the PRP group (plus ranibizumab for DME). Among the remaining participants without baseline vision-impairing DME, 80 and 87 were in the ranibizumab and PRP groups, respectively. For participants with and without baseline vision-impairing DME, the incremental cost-effectiveness ratios of ranibizumab therapy compared with PRP were $55 568/quality-adjusted life-year and $662 978/quality-adjusted life-year, respectively, over 2 years. Conclusions and Relevance Over 2 years, compared with PRP, 0.5-mg ranibizumab as given in this trial is within the $50 000/quality-adjusted life-year to $150 000/quality-adjusted life-year range frequently cited as cost-effective in the United States for eyes presenting with PDR and vision-impairing DME, but not for those with PDR without vision-impairing DME. Trial Registration Clinicaltrials.gov Identifier: NCT01489189.