Miracle-dz/UniFAR-FTUs huggingface dataset:
Blue-noise sampling for human retinal cone spatial distribution modeling

This paper proposes a novel method for modeling retinal cone distribution in humans. It is based on Blue-noise sampling algorithms being strongly related with the mosaic sampling performed by cone photoreceptors in the human retina. Here we present the method together with a series of examples of various real retinal patches. The same samples have also been created with alternative algorithms and compared with plots of the center of the inner segments of cone photoreceptors from imaged retinas. Results are evaluated with different distance measure used in the field, like nearest-neighbor analysis and pair correlation function. The proposed method can effectively describe features of a human retinal cone distribution by allowing to create samples similar to the available data. For this reason, we believe that the proposed algorithm may be a promising solution when modeling local patches of retina.
SPoC: Search-based Pseudocode to Code

We consider the task of mapping pseudocode to long programs that are functionally correct. Given test cases as a mechanism to validate programs, we search over the space of possible translations of the pseudocode to find a program that passes the validation. However, without proper credit assignment to localize the sources of program failures, it is difficult to guide search toward more promising programs. We propose to perform credit assignment based on signals from compilation errors, which constitute 88.7% of program failures. Concretely, we treat the translation of each pseudocode line as a discrete portion of the program, and whenever a synthesized program fails to compile, an error localization method tries to identify the portion of the program responsible for the failure. We then focus search over alternative translations of the pseudocode for those portions. For evaluation, we collected the SPoC dataset (Search-based Pseudocode to Code) containing 18,356 programs with human-authored pseudocode and test cases. Under a budget of 100 program compilations, performing search improves the synthesis success rate over using the top-one translation of the pseudocode from 25.6% to 44.7%.
GENOMIC PROFILE OF A NEW NOVEL FUNGAL ISOLATE, COCHLIOBOLUS Sp. FROM HUMAN EYE INFECTIONS

Identification of fungi by morphological traits alone is often difficult because mycelial pigmentation, shape and size of conidia are unstable and highly dependent on composition of media and environmental conditions. Molecular techniques such as Internal Transcribed Spacer (ITS) ribosomal DNA (rDNA) have been reliable and are highly suitable tool for identifying fungal species and for assessing genetic variation within populations. The correct identification of fungal isolates from infected eye will help to develop drug against those microbes and also to avoid the possible source of such infections. From the ocular sample collected from infected patients, Cochliobolus sp was identified by basic culture techniques and its genomic profile was evaluated ITS r DNA technology.
Preparation and Photocatalytic Properties of LnBaCo2O5+δ (Ln = Eu, Gd, and Sm)

A new type of photocatalytic material, double-perovskite oxides, LnBaCo2O5+δ (Ln = Eu, Gd, and Sm) was synthesized via a conventional solid-state reaction process using Ln2O3, BaCO3 and Co2O3 as raw materials. X-ray diffraction results show that the crystalline structures are a pure orthorhombic lattice and are consistent with LnBaCo2O5+δ microparticles. The photocatalytic activity of the LnBaCo2O5+δ (Ln = Eu, Gd, and Sm) powders was further demonstrated in the degradation of Congo red (CR) under ultraviolet light irradiation with the dye solution concentration of 25 or 50 mg·L-1. The double-perovskite oxides LnBaCo2O5+δ show a certain photocatalytic activity during the degradation of CR under ultraviolet light, which means that they are one kind of the promising photocatalytic materials for the degradation of the azo dyes.
Simulation of Minimum Path Estimation in Software Defined Networking Using Mininet Emulator

Software-Defined Networking (SDN) has become a significant topic of discussion among the network service providers, operators, and equipment vendors where control planes are separated from the data plane in networking devices. This paper implements Bellman-Ford algorithm for computing the shortest path in Software-Defined Networking using Mininet emulator. Bellman–Ford algorithm computes shortest paths from a single source vertex to all of the other vertices in a weighted digraph. This algorithm is versatile, as it is capable of handling graphs in which some of the edge weights are negative numbers. All the simulation has been done using POX as an OpenFlow controller, OpenvSwitch (OVS) as a forwarding function and Mininet which installed on Ubuntu Virtual Machine (VM). The result of this paper shows that the simulation of SDN with OpenvSwitch (OVS) and POX controller runs Bellman-Ford algorithm for finding the minimum path among the designed network topology.
Arterial spin labeling at 3T in semantic dementia: Perfusion abnormalities detection

Arterial Spin Labeling (ASL) is a non invasive perfusion imaging technique which has shown great diagnosis potential in dementia. However, it has never been applied to semantic dementia (SD), a rare subtype of frontotemporal lobar degeneration characterized by the gradual loss of conceptual knowledge, which is actually explored by a now well established marker of SD: 18fluorodeoxyglucose-positron emission tomography (FDG-PET) imaging. Although ASL and FDG-PET respectively measure perfusion and metabolism, they have been shown to be strongly correlated. We propose to explore the ability of ASL to detect perfusion abnormalities in SD in comparison with FDG-PET. Using patients and healthy subjects data from an ongoing clinical study, we apply our analysis framework starting with visual comparison of ASL and FDG-PET, and focusing on ASL data preprocessing and statistical analysis at the individual and group level. Preliminary results yield concordant observations between ASL and FDG-PET as well as expected hypoperfusions in SD, namely in the left temporal lobe, thus suggesting the potential of ASL to assess perfusion impairments in SD.
Evolution of intermetallic GaPd2/SiO2 catalyst and optimization for methanol synthesis at ambient pressure

ABSTRACT The CO2 hydrogenation to methanol is efficiently catalyzed at ambient pressure by nanodispersed intermetallic GaPd2/SiO2 catalysts prepared by incipient wetness impregnation. Here we optimize the catalyst in terms of metal content and reduction temperature in relation to its catalytic activity. We find that the intrinsic activity is higher for the GaPd2/SiO2 catalyst with a metal loading of 13 wt. % compared to catalysts with 23 wt. % and 7 wt. %, indicating that there is an optimum particle size for the reaction of around 8 nm. The highest catalytic activity is measured on catalysts reduced at 550°C. To unravel the formation of the active phase, we studied calcined GaPd2/SiO2 catalysts with 23 wt. % and 13 wt. % using a combination of in situ techniques: X-ray diffraction (XRD), X-ray absorption near edge fine structure (XANES) and extended X-ray absorption fine structure (EXAFS). We find that the catalyst with higher metal content reduces to metallic Pd in a mixture of H2/Ar at room temperature, while the catalyst with lower metal content retains a mixture of PdO and Pd up to 140°C. Both catalysts form the GaPd2 phase above 300°C, albeit the fraction of crystalline intermediate Pd nanoparticles of the catalyst with higher metal loading reduces at higher temperature. In the final state, the catalyst with higher metal loading contains a fraction of unalloyed metallic Pd, while the catalyst with lower metal loading is phase pure. We discuss the alloying mechanism leading to the catalyst active phase formation selecting three temperatures: 25°C, 320°C and 550°C. Graphical abstract
A review on the effect of mechanical drilling on polymer nanocomposites

Over the past decade, polymer nanocomposites have undergone intensive research and development ensued by its increasing implementation within commercial applications. Consequently, the full life-cycle performance and any health risks associated with these materials have become of major interest. Throughout its use, a nanocomposite will undergo industrial machining where drilling can lead to material damage and/or exposure to the potentially toxic nanoparticles. This study assesses the existing and perspective research on nanocomposite drilling. Currently, although considerable amount of studies have investigated machining on conventional composite materials, there is a lack in knowledge on the effect of drilling on nanocomposites. The data underlines the various drilling parameters that will affect and influence the damage to the material and nano-sized particles released. Importantly, previous studies have identified potential mechanical damage caused by drilling and the release-ability of toxic nanoparticles from nanocomposites. It is therefore crucial to develop a full understanding and characterization on the effect of drilling on polymer nanocomposites.
Validation of two automatic devices, Omron HEM-6232T and HEM-6181, for self-measurement of blood pressure at the wrist according to the ANSI/AAMI/ISO 81060-2:2013 protocol and the European Society of Hypertension International Protocol revision 2010 [Corrigendum]

Vascular Health and Risk Management is an international, peerreviewed journal of therapeutics and risk management, focusing on concise rapid reporting of clinical studies on the processes involved in the maintenance of vascular health; the monitoring, prevention and treatment of vascular disease and its sequelae; and the involvement of metabolic disorders, particularly diabetes. This journal is indexed on PubMed Central and MedLine. The manuscript management system is completely online and includes a very quick and fair peerreview system, which is all easy to use. Visit http://www.dovepress. com/testimonials.php to read real quotes from published authors.
The validity of breath collection bags method in detecting Helicobacter pylori using the novel BreathID®Hp Lab System: a multicenter clinical study in 257 subjects

Background and Aim: The BreathID®Hp urea breath test provides several advantages over other 13C breath analyzers for the detection of Helicobacter pylori. We evaluated the sensitivity and specificity of a new BreathID®Hp Lab System (Exalenz Bioscience Ltd, Israel), a 13C-urea breath test system using breath sampling bags that facilitates multiple testing in a multicenter international clinical study. Methods: A total of 257 subjects with evaluable results for urea breath test, rapid urease test, and histology were enrolled into two study groups: 189 naïve subjects were included in the pre-therapy group, and 68 subjects comprised the post-eradication therapy group. Analytical studies were conducted to evaluate the stability, reproducibility, and repeatability of the 13C-urea breath test results using a delta over baseline cut-off value of 5. Results: Among the pre-therapy subjects evaluated with the composite results from the rapid urease test and histology/immunohistochemistry, 176 results matched those of the urea breath test, resulting in an overall agreement of 98.3% with a sensitivity of 100% and specificity of 97.9%. In the post-eradication therapy cohort, the overall agreement between the urea breath test and the biopsy diagnosis was 98.5%; the sensitivity of the urea breath test in this cohort was 92.3% and the specificity was 100%. There was uniformly high overall reproducibility (99.48%) of the test results over different batches of breath sample bags, when analyzed on different days and under different storage conditions, showing stability of the breath samples in the breath collection bags Conclusion: The BreathID®Hp Lab System is a highly accurate and dependable method for the diagnosis of H. pylori infection.
Using a Health Economic Framework to Prioritize Quality Indicators: An Example With Smoking Cessation in Chronic Obstructive Pulmonary Disease

Background. Health care performance monitoring is a major focus of the modern quality movement, resulting in widespread development of quality indicators and making prioritizations an increasing focus. Currently, few prioritization methods of performance measurements give serious consideration to the association of performance with expected health benefits and costs. We demonstrate a proof-of-concept application of using a health economic framework to prioritize quality indicators by expected variations in population health and costs, using smoking cessation in chronic obstructive pulmonary disease (COPD) as an example. Methods. We developed a health state transition, microsimulation model to represent smoking cessation practices for adults with COPD from the health care payer perspective in Ontario, Canada. Variations in life years, quality-adjusted life years (QALYs), and lifetime costs were associated with changes in performance. Incremental net health benefit (INHB) was used to represent the joint variation in mortality, morbidity, and costs associated with the performance of each quality indicator. Results. Using a value threshold of $50,000/QALY, the indicators monitoring assessment of smoking status and smoking cessation interventions were associated with the largest INHBs. Combined performance variations among groups of indicators showed that 81% of the maximum potential INHB could be represented by three out of the six process indicators. Conclusions. A health economic framework can be used to bring dimensions of population health and costs into explicit consideration when prioritizing quality indicators. However, this should not preclude policymakers from considering other dimensions of quality that are not part of this framework.
Targeting Amyloid Aggregation: An Overview of Strategies and Mechanisms

Amyloids result from the aggregation of a set of diverse proteins, due to either specific mutations or promoting intra- or extra-cellular conditions. Structurally, they are rich in intermolecular β-sheets and are the causative agents of several diseases, both neurodegenerative and systemic. It is believed that the most toxic species are small aggregates, referred to as oligomers, rather than the final fibrillar assemblies. Their mechanisms of toxicity are mostly mediated by aberrant interactions with the cell membranes, with resulting derangement of membrane-related functions. Much effort is being exerted in the search for natural antiamyloid agents, and/or in the development of synthetic molecules. Actually, it is well documented that the prevention of amyloid aggregation results in several cytoprotective effects. Here, we portray the state of the art in the field. Several natural compounds are effective antiamyloid agents, notably tetracyclines and polyphenols. They are generally non-specific, as documented by their partially overlapping mechanisms and the capability to interfere with the aggregation of several unrelated proteins. Among rationally designed molecules, we mention the prominent examples of β-breakers peptides, whole antibodies and fragments thereof, and the special case of drugs with contrasting transthyretin aggregation. In this framework, we stress the pivotal role of the computational approaches. When combined with biophysical methods, in several cases they have helped clarify in detail the protein/drug modes of interaction, which makes it plausible that more effective drugs will be developed in the future.
Endogenizing the Scope of the Stigma of Failure

This paper provides an explanation for varying outcomes of the stigma of failure on capital markets. Agents of different unknown entrepreneurial skills need credit for a project that they can run at different risk levels. Two types of equilibria coexist for a sufficiently large share of high skill entrepreneurs: in a conservative equilibrium, only agents who never failed have access to the credit market; whereas in an experimental equilibrium, entrepreneurs can start projects even after repeated failures. In a perfect information setting, only the experimental equilibrium is subgame perfect. However, as soon as entrepreneurs' risk choice becomes unobservable, subgame perfection is restored and the multiplicity of equilibria is robust. This considerably hampers policy's impact on the nature of the equilibrium.
A MAPREDUCE-BASED PARALLEL DATA CLEANING ALGORITHM IN WEB USAGE MINING

Data cleaning plays an important role in Web usage mining process as it reduces the complexity of later phases of KDD (Knowledge Discovery in Databases) process. It incorporates the removal of those log entries and fields that are not relevant for the purpose of Web usage mining. Generally, Data cleaning includes the removal of unsuccessful requests, irrelevant files’ requests, inappropriate access methods’ requests, and robots’ requests. With the enormous increase of log data, traditional Data cleaning algorithm has become highly data intensive task. In the last few years, MapReduce has emerged as most widely used parallel programming framework to compute data intensive application on a cluster of nodes. In this article, we have proposed a MapReduce-based Parallel Data cleaning (PDC) algorithm that considers all aspect of the traditional Data cleaning algorithm. There are two modifications to exiting Data cleaning algorithm i.e. first is an efficient robot detection approach, and other is consideration of internal dummy connections’ requests . We have performed experiments on real Web server log and observed that log file is reduced to significant amount after considering these two modifications. Moreover, we have compared parallel data algorithm with its sequential version and found that our proposed MapReduce-based PDC algorithm is scalable and efficient than traditional Data cleaning algorithm for larger datasets.
Exact Moderate and Large Deviations for Linear Processes

Large and moderate deviation probabilities play an important role in many applied areas, such as insurance and risk analysis. This paper studies the exact moderate and large deviation asymptotics in non-logarithmic form for linear processes with independent innovations. The linear processes we analyze are general and therefore they include the long memory case. We give an asymptotic representation for probability of the tail of the normalized sums and specify the zones in which it can be approximated either by a standard normal distribution or by the marginal distribution of the innovation process. The results are then applied to regression estimates, moving averages, fractionally integrated processes, linear processes with regularly varying exponents and functions of linear processes. We also consider the computation of value at risk and expected shortfall, fundamental quantities in risk theory and finance.
Ability emotional intelligence versus trait emotional intelligence in academic achievement

Emotional intelligence, EI has been popularly discussed over the past decades. It is the ability of an individual in self-awareness, self-management, social awareness, and relationship management (Goleman, 2001). The term “emotional intelligence” is derived from social intelligence which was discovered by E. L. Thorndike (Bharwaney, 2006), who described social intelligence as the ability to get along with other people. Later, it provoked the research on multiple intelligences done by Howard Gardner, who suggested “intrapersonal intelligence” and “interpersonal intelligence” as two types of intelligences. Daniel Goleman then popularized EI by publishing his best-seller book named “Emotional Intelligence: Why It Can Matter More Than IQ? ” (Bharwaney, 2006) that mentioned on “personal competence” and “social competence” in his book, which are similar to the concepts of intrapersonal intelligence and intrapersonal intelligence stated by Gardner where VanderVoort (2006) stated that intrapersonal and interpersonal intelligences are incorporated in the EI. The relationship between EI and academic achievement had been studied in many countries. However, the influences of both ability EI and trait EI towards academic achievement remained an interesting topic under investigation. The comparison between ability EI and trait EI become a concern to improve students’ academic achievement.
Stability windows and unstable root-loci for linear fractional time-delay systems

The main point of this paper is on the formulation of a numerical algorithm to find the location of all unstable poles, and therefore the characterization of the stability as a function of the delay, for a class of linear fractional-order neutral systems with multiple commensurate delays. We start by the asymptotic position of the chains of poles and conditions for their stability, for a small delay. When these conditions are met, we continue by means of the root continuity argument, and using a simple substitution, we can find all the locations where roots cross the imaginary axis. We can extend the method to provide the location of all unstable poles as a function of the delay. Before concluding, some examples are presented.
Conceptualizing anhedonias and implications for depression treatments

Anhedonia has been implicated as a core symptom of depression and schizophrenia, and studying anhedonia has yielded a wide array of important findings aiding the understanding and identification of psychological disorders. However, anhedonia is a complex and multifaceted construct; indeed, the term anhedonia has been defined in psychological and psychiatric research as many different concepts, a number of which are theoretically and methodologically independent of one another. In this review alone, we discuss research that separates social aspects of anhedonia from the physical contexts of anhedonia, with the former emphasizing interpersonal relationships as important to anhedonic symptoms, and the latter emphasizing biological and brain-related impairment as potential causes of chronic anhedonia states. We highlight research that distinguishes between interest in (wanting) or experience of (liking) potential pleasure as definitions of anhedonia and also disambiguate methodologically and theoretically distinct ways of assessing 1) trait-level dispositional tendencies, 2) state-level cross-sectional assessments, and 3) symptom-based recent changes from baseline, all of which have been used to indicate anhedonia. Lastly, we describe cutting-edge translations of basic anhedonia research into treatment and discuss how different conceptualizations of anhedonia, guided by recent theoretical and methodological advances, have begun to usher in a science of anhedonia that is consistent with increasingly personalized assessment and treatment. We conclude with a note for future research, emphasizing that continued application of theoretically based operationalizations of anhedonia and sound design are paramount to continue the recent progress toward meaningful and specific use of the anhedonia construct in clinical research.
Composable Primitives for SDN Measurements

Measurement is a crucial concern for network operation. Rather than a principled approach, we see that measurement in SDN has been mostly an ad-hoc activity with poor reuse of abstractions that are hard to combine efficiently. We argue that network measurements should be supported with first-class artifacts able to address a wide range of measurements tasks in an efficient, flexible and reusable manner. We have identified a set of primitives that can be easily combined to express well-known techniques and used them to solve three measurement problems that have not been addressed in the literature: monitoring path changes, measuring the latency to flow steering and identifying the top-k congested flows.