Miracle-dz/UniFAR-FTUs huggingface dataset:
Bmc Medicine Developing Optimal Search Strategies for Detecting Clinically Sound Prognostic Studies in Medline: an Analytic Survey

Background: Clinical end users of MEDLINE have a difficult time retrieving articles that are both scientifically sound and directly relevant to clinical practice. Search filters have been developed to assist end users in increasing the success of their searches. Many filters have been developed for the literature on therapy and reviews but little has been done in the area of prognosis. The objective of this study is to determine how well various methodologic textwords, Medical Subject Headings, and their Boolean combinations retrieve methodologically sound literature on the prognosis of health disorders in MEDLINE.
The Role of Weight on Community Structure of Networks

The role of weight on the weighted networks is investigated by studying the effect of weight on community structures. We use weighted modularity Q w to evaluate the partitions and Weighted Extremal Optimization algorithm to detect communities. Starting from idealized and empirical weighted networks, the distribution or matching between weights and edges are disturbed. Using dissimilarity function D to distinguish the diﬀerence between community structures, it is found that the redistribution of weights does strongly aﬀect the community structure especially in dense networks. This indicates that the community structure in networks is a suitable property to reﬂect the role of weight.
Characteristics of the surface water DMS and pCO2 distributions and their relationships in the Southern Ocean, southeast Indian Ocean, and northwest Pacific Ocean

Oceanic dimethyl sulfide (DMS) is of interest due to its critical influence on atmospheric sulfur compounds in the marine atmosphere and its hypothesized significant role in global climate. High‐resolution shipboard underway measurements of surface seawater DMS and the partial pressure of carbon dioxide (pCO2) were conducted in the Atlantic Ocean and Indian Ocean sectors of the Southern Ocean (SO), the southeast Indian Ocean, and the northwest Pacific Ocean from February to April 2014 during the 30th Chinese Antarctic Research Expedition. The SO, particularly in the region south of 58°S, had the highest mean surface seawater DMS concentration of 4.1 ± 8.3 nM (ranged from 0.1 to 73.2 nM) and lowest mean seawater pCO2 level of 337 ± 50 μatm (ranged from 221 to 411 μatm) over the entire cruise. Significant variations of surface seawater DMS and pCO2 in the seasonal ice zone (SIZ) of SO were observed, which are mainly controlled by biological process and sea ice activity. We found a significant negative relationship between DMS and pCO2 in the SO SIZ using 0.1° resolution, [DMS] seawater = −0.160 [pCO2] seawater + 61.3 (r2 = 0.594, n = 924, p < 0.001). We anticipate that the relationship may possibly be utilized to reconstruct the surface seawater DMS climatology in the SO SIZ. Further studies are necessary to improve the universality of this approach.
Joint interpolation of multi-sensor sea surface geophysical fields using non-local and statistical priors

This work addresses the joint analysis of multi-source and multi-resolution remote sensing data for the interpolation of high-resolution geophysical fields. As case-study application, we consider the interpolation of sea surface temperature fields. We propose a novel statistical model, which combines two key features: an exemplar-based prior and second-order statistical priors. The exemplar-based prior, referred to as a non-local prior, exploits similarities between local patches (small field regions) to interpolate missing data areas from previously observed exemplars. This non-local prior also sets an explicit conditioning between the multi-sensor data. Two complementary statistical priors, namely a prior on the spatial covariance and a prior on the marginal distribution of the high-resolution details, are considered as sea surface geophysical fields are expected to depict specific spectral and marginal features in relation to the underlying turbulent ocean dynamics. We report experiments on both synthetic data and real SST data. These experiments demonstrate the contributions of the proposed combination of non-local and statistical priors to interpolate visually-consistent and geophysically-sound SST fields from multi-source satellite data. We further discuss the key features and parameterizations of this model as well as its relevance with respect to classical interpolation techniques.
Data Analysis and Knowledge Discovery

: [ Objective ] This paper aims to automatically recognize key sentences describing the research topics of scientific papers. [ Methods ] First, we used paper sections as the unit to organize sentence sets. Then, we calculated the WMD distance between sentences by trained domain word embeddings. Third, we optimized the iterative process of TextRank algorithm, and used external features to adjust sentence’s weights. Finally, we identified the core topic sentences according to the sentence’s weights descendingly. [ Results ] We examined the proposed method with scientific papers on climate changes and compared it with the traditional TextRank algorithm. The recognition efficiency (F-value) was about 5% higher than that of the TextRank algorithm. [ Limitations ] The extraction of sentence features needs to be improved, and word embedding training and related parameters of the proposed method need to be further optimized. [ Conclusions ] The improved TextRank algorithm, could effectively recognize inner core sentences of scientific paper sections. It could recognize core topic sentences of a paper with the adjusted weights of external features.
D-S evidence theory based trust ant colony routing in WSN

This paper proposes a trust ant colony routing algorithm by introducing a node trust evaluation model based on the D-S evidence theory into the ant colony routing protocol to improve the security of wireless sensor networks. To reduce the influence of conflict evidences caused by malicious nods, the consistent intensity is introduced to preprocess conflict evidences before using the D-S combination rule to improve the reliability of the D-S based trust evaluation. The nodes with high trust values will be selected as the routing nodes to insure the routing security, and the trust values are used as heuristic functions of the ant colony routing algorithm. The simulation tests are conducted by using the network simulator NS2 to observe the outcomes of performance metrics of packets loss rate and average end-to-end delay etc. to indirectly evaluate the security issue under the attack of inside malicious nodes. The simulation results show that the proposed trust routing algorithm can efficiently resist malicious attacks in terms of keeping performances of the average end-to-end delay, the throughtput and the routing packet overhead under attacking from malicious nodes.
Past Our Prime: A Study of Age and Play Style Development in Battlefield 3

In recent decades, video games have come to appeal to people of all ages. The effect of age on how people play games is not fully understood. In this paper, we delve into the question how age relates to an individual's play style. “Play style” is defined as any (set of) patterns in game actions performed by a player. Based on data from 10 416 Battlefield 3 players, we found that age strongly correlates to how people start out playing a game (initial play style), and to how they change their play style over time (play style development). Our data shows three major trends: 1) correlations between age and initial play style peak around the age of 20; 2) performance decreases with age; and 3) speed of play decreases with age. The relationship between age and play style may be explained by the neurocognitive effects of aging: as people grow older, their cognitive performance decays, their personalities shift to a more conscientious style, and their gaming motivations become less achievement-oriented.
Optimal Policies Tend to Seek Power.

Some researchers have speculated that capable reinforcement learning agents are often incentivized to seek resources and power in pursuit of their objectives. While seeking power in order to optimize a misspecified objective, agents might be incentivized to behave in undesirable ways, including rationally preventing deactivation and correction. Others have voiced skepticism: human power-seeking instincts seem idiosyncratic, and these urges need not be present in reinforcement learning agents. We formalize a notion of power within the context of Markov decision processes. With respect to a class of neutral reward function distributions, we provide sufficient conditions for when optimal policies tend to seek power over the environment.
Uncertainties in MODIS‐Based Cloud Liquid Water Path Retrievals at High Latitudes Due to Mixed‐Phase Clouds and Cloud Top Height Inhomogeneity

Combined A‐train remote sensing measurements from Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR‐E), CloudSat, and Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) are used to study MODIS liquid water path (LWP) uncertainties at high latitudes. The focus is on quantifying uncertainties due to mixed‐phase clouds and solar zenith angle‐dependent bias, both of which disproportionately affect the MODIS data set in the polar regions. Multisensor LWP retrievals in stratiform mixed‐phase clouds show that treating mixed‐phase clouds as liquid clouds result in LWP bias that is related to the ice water path (IWP) on average and reaches close to 15% at IWP of 150 g/m2 and can reach 40% or higher when IWP is greater than 400 g/m2. Moreover, A‐train measurements and radiative transfer modeling are used to further understand the well‐known yet unresolved solar zenith angle‐dependent high bias in MODIS LWP. It is shown that the cloud top height variation is one of the main factors that contribute to this bias due to three‐dimensional radiative interactions with cloud top inhomogeneity. Excluding only 0.5% of data points that show significant three‐dimensional errors reduces the bias by 25 g/m2 at solar zenith angle of 80° and improves agreement with the AMSR‐E LWP trends. Three‐dimensional radiative transfer simulations confirm that cloud top inhomogeneity is primarily responsible for the solar zenith angle‐dependent LWP bias as observed by the MODIS measurements. This study provides a framework to guide future improvements of MODIS LWP data set, which is a key data source to constrain climate models.
Surface Normals 3 . Align Point Cloud Image Depth Map Segmentation RGB Image Point Cloud Regions Feature Extraction Features Support Classification

We present an approach to interpret the major surfaces, objects, and support relations of an indoor scene from an RGBD image. Most existing work ignores physical interactions or is applied only to tidy rooms and hallways. Our goal is to parse typical, often messy, indoor scenes into floor, walls, supporting surfaces, and object regions, and to recover support relationships. One of our main interests is to better understand how 3D cues can best inform a structured 3D interpretation. We also contribute a novel integer programming formulation to infer physical support relations. We offer a new dataset of 1449 RGBD images, capturing 464 diverse indoor scenes, with detailed annotations. Our experiments demonstrate our ability to infer support relations in complex scenes and verify that our 3D scene cues and inferred support lead to better object segmentation.
Special Section on Transporters in Toxicity and Disease Selective and Cytokine-Dependent Regulation of Hepatic Transporters and Bile Acid Homeostasis during Infectious Colitis in Mice s

Various disease models have been shown to alter hepatic drugmetabolizing enzyme (DME) and transporter expression and to induce cholestasis through altered enzyme and transporter expression. Previously, we detailed the regulation of hepatic DMEs during infectious colitis caused by Citrobacter rodentium infection. We hypothesized that this infection would also modulate hepatic drug transporter expression and key genes of bile acid (BA) synthesis and transport. Mice lacking Toll-like receptor 4 (TLR4), interleukin-6 (IL-6), or interferon-gamma (IFNg) and appropriate wild-type animals were orally infected with C. rodentium and sacrificed 7 days later. In two wild-type strains, drug transporter mRNA expression was significantly decreased by infection for Slc22a4, Slco1a1, Slco1a4, Slco2b1, and Abcc6, whereas the downregulation of Abcc2, Abcc3, and Abcc4 were strain-dependent. In contrast, mRNA expressions of Slco3a1 and Abcb1b were increased in a strain-dependent manner. Expression of Abcb11, Slc10a1, the two major hepatic BA transporters, and Cyp7a1, the rate-limiting enzyme of BA synthesis, was also significantly decreased in infected animals. None of the above effects were caused by bacterial lipopolysaccharide, since they still occurred in the absence of functional TLR4. The downregulation of Slc22a4 and Cyp7a1 was absent in IFNg-null mice, and the downregulation of Slco1a1 was abrogated in IL-6-null mice, indicating in vivo roles for these cytokines in transporter regulation. These data indicate that C. rodentium infection modulates hepatic drug processing through alteration of transporter expression as well as DMEs. Furthermore, this infection downregulates important genes of BA synthesis and transport and may increase the risk for
Real-time Fundamental Frequency Estimation by Least-square Fitting

The real-time performance of a fundamental frequency estimation algorithm depends not only on its computational eeciency but also on its ability to obtain accurate estimates from short signal segments. Previous frequency-domain algorithms make use of spectral analysis algorithms that require the application of a window function, which cause them to fail when signal segments are short and their fundamental frequencies are low. A new spectral analysis algorithm based on least-square tting, which does not require the application of a window function, is introduced. This algorithm operates by minimizing the square error of tting a sinusoid to the signal segment. Special properties of the shape of the error function allow the spectrum of the signal segment to be deduced from it and the algorithm to be implemented eeciently. The proofs of these properties are given. A fundamental frequency estimation algorithm based on this spectral analysis algorithm is then described. Its computation time is analyzed and we demonstrate its real-time performance by a set of experiments using actual sound data.
Adoption of mGovernment service initiative in developing countries: A citizen-centric public service delivery perspective

The phenomenal advancement of mobile technologies and the large penetration of mobile phones in developing countries have provided alternative solutions to re-engineer public service delivery mechanism. Governments are now challenged to deliver an expanding set of services to citizen given the general pervasiveness and ubiquity of mobile devices. This development has given a growing focus on modernizing public service delivery to improve the efficiency and effectiveness of services. The devices have become the world's most common means of interpersonal communication and constituting the new frontier that is beginning to transform governance; making government more accessible and more citizen-centric by extending the dividends of governance. This emerging trend in public service delivery has been named mGovernment. This new paradigm shift of governance is the latest innovation and practice in developed countries. mGovernment has emerged as an appropriate form of governments' initiatives using mobile devices within the purview of government administration to deliver public services to citizens and organizations in a transparent, accountable, efficient and effective manner on mobile devices. The Public Private Partnership (PPP) model has been advocated because of the budgetary constraints of governments. This paper examines some of the factors for its successful implementation and the policy directions for governments and other stakeholders. The paper draws on concepts from multiple theoretical perspectives using the theory of diffusion and grounded theory to understand the proposition of the new initiative. The paper explores mGovernment potentials for transforming governance by increasing their accessibility and citizen-centricity. This study contributes to the literature on mGovernment by synthesizing best practices solutions for public service delivery and suggests a new business model for its sustenance. The paper also suggests policy direction to governments and stakeholders.
Emotion recognition of conversational affective speech using temporal course modeling

In a natural conversation, a complete emotional expression is typically composed of a complex temporal course representing temporal phases of onset, apex, and offset. In this study, sub-emotional states are defined to model the temporal course of an emotional expression in natural conversation. Hidden Markov Models (HMMs) are adopted to characterize the sub-emotional states; each represents one temporal phase. A sub-emotion language model, which considers the temporal transition between sub-emotional states (HMMs), is further constructed to provide a constraint on allowable temporal structures to determine an optimal emotional state. Experimental results show that the proposed approach yielded satisfactory results on the MHMC conversation-based affective speech corpus, and confirmed that considering the complex temporal structure in natural conversation is useful for improving the emotion recognition performance from speech.
Ability of Micrococcus Isolated from Soil in Biodegradation Diesel

The study include investigation types of Micrococcus for degradation diesel. The results showed an increase in the growth rates for most strain of M. roesus, M. luteus and M. varians as the mean count were 31×10 and 30.4×10 for M. roseus and M. luteus respectively, at the beginning and reached 36×10 and 28.5×10 for mentioned species respectively at the end, An increase in photoabsorption was recorded during the experimental period which were corresponding with increased viable counts of bacteria belonging to the genera of Micrococcus whereas one strain of M. luteus didn't grow in the media containing Diesel. Gas chromatography (GC) and Infrared-IR techniques was used for dictation hydrolysis of Diesel as indicators as disappearance of number of bands on diesel treated with the bacterial isolates used in the study, and the disappearance of number of bonds was observed using IR technique, the carboxylic acid, amid and ester bonds appeared in bacterial treated sample.
1 SQANTI : extensive characterization of long read transcript sequences for quality control in 1 full-length transcriptome identification and quantification 2 3

292 words) 22 High-throughput sequencing of full-length transcripts using long reads has paved the way for the discovery of 23 thousands of novel transcripts, even in very well annotated organisms as mice and humans. Nonetheless, there is a 24 need for studies and tools that characterize these novel isoforms. Here we present SQANTI, an automated pipeline 25 for the classification of long-read transcripts that computes 47 descriptors that can be used to assess the quality of 26 the data and of the preprocessing pipelines. We applied SQANTI to a neuronal mouse transcriptome using PacBio 27 long reads and illustrate how the tool is effective in readily describing the composition of and characterizing the full28 length transcriptome. We perform extensive evaluation of ToFU PacBio transcripts by PCR to reveal that an 29 important number of the novel transcripts are technical artifacts of the sequencing approach, and that SQANTI 30 quality descriptors can be used to engineer a filtering strategy to remove them. Most novel transcripts in this curated 31 transcriptome are novel combinations of existing splice sites, result more frequently in novel ORFs than novel UTRs 32 and are enriched in both general metabolic and neural specific functions. We show that these new transcripts have a 33 major impact in the correct quantification of transcript levels by state-of-the-art short-read based quantification 34 algorithms. By comparing our iso-transcriptome with public proteomics databases we find that alternative isoforms 35 . CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi. org/10.1101/118083 doi: bioRxiv preprint first posted online Mar. 18, 2017;
Bottom-Up meets Top-Down: A New Paradigm for Software Engineering Instruction

Abstract – College curricula for computer programming has been developed from a bottom up, primitive to system-levelapproach. Although efficient from a task centric viewpoint, this methodology leaves crucial learning tasks until afterbehavioral habits are reinforcedthrough several courses of instruction. These habits are inadequate to meet the needs ofcurrent programming standards. The current learning process deemphasizes important issues such as security and testability, sacrificing them in the name of time. This paper outlines anew approach to provide a more comprehensive, systems engineering based education approach in an attempt to correctthese deficiencies in the current instructional methodology.  Index terms – Software Engineering, ComputerProgramming Curriculum I. I NTRODUCTION There has been significant interest in the development ofsecure software, programs that by definition do not sufferfrom the multitude of software vulnerabilities that are common in today’s programs [1]. One avenue of attack isin the addition of secure coding classes into computerscience and information systems curriculums. This paperapproaches the problem from a different direction, from asystems point of view and holistic fashion. Currentcurriculums place security classes after basic coding classes. Rather than addingsecurity instruction after coding habits have been formed, the concept ofincorporating security related material from day one is examined. This information is targeted to the software engineering or computer programming instructor who isnot a security specialist.One method of addressing change in an organization is toanswer four questions concerning the desired change.The four questions are; where are we now? , where do we want to be? , how will we get there? and how will wemeasure progress? Understanding the answers to thesequestions assists in the change process. These fourquestions will be used to guide the reader through anexamination of an alternative approach that will transformcomputer programming classes into a software
Analysis of Poly(methyl methacrylate) Hydrogel Intradermal Irritation Test

To investigate the potential skin irritation response of domestically produced medical poly(methyl methacrylate) hydrogel, the intradermal injection method was used. Healthy white rabbits were selected for intradermal injection of 0.5% sodium chloride solution as a control, 0.5% sodium chloride extract, and olive oil extract for the test samples. The rabbits were observed for erythema and edema at 24 and 72 hours, and the primary irritation index was calculated. The primary irritation index of the domestically produced poly(methyl methacrylate) hydrogel was 0, indicating no skin irritation response.