Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Honey-Bees Mating Optimizationalgorithm on Estimation of Suspended Sediment Concentration

2 Abstract: So far, many attempts have been made to identify the relation between discharge and suspended sediment load.Empirical relations such as sediment rating curves are often applied to determine the average relationship between discharge and suspended sediment load. This type of models generally underestimates or overestimateswhen sediment load are estimated from water discharge using least squares regression of log-transformed variables.To avoid this drawback, it is proposedto employthe HBMO algorithm as a new alternativetool foroptimization of this curve.Model obtained from this algorithmis compared with similar evolutionary algorithm,GA and two different sediment rating curves. The daily streamflow and suspended sediment concentration data from Mad River Catchment near Arcata, USA are used as a case study.Statistics and graphsindicate thatthe HBMO algorithmperforms better than other models in estimation of suspended sediment concentration in the particular datasets used in this study.
Study of Oseltamivir and Zanamivir Resistance-Related Mutations in Influenza Viruses Isolated from Wild Mallards in Sweden

Resistance to neuraminidase inhibitors (NAIs) is a growing problem in battle against influenza A virus. However, little is known about the resistance of viruses isolated from dabbling ducks, the natural reservoir of the influenza virus. To our knowledge, no low-pathogenic avian influenza (LPAI) virus resistant to NAIs has been detected. The aim of this study was to investigate mallard isolates of influenza A virus previously identified to carry oseltamivir carboxylate (OC) or zanamivir (ZA) resistance-related mutations. In this work, 21 viruses belonging to the N1, N3, N6 and N9 subtypes were analyzed using a colorimetric NA inhibition assay. The results of assay showed no NAIs-resistant phenotype for any of the viruses. The R118K mutation was the most recurrent, as it was observed in all subtypes except for N6. IC50 values confirmed the differences in sensitivity to OC or ZA observed in the N1 and N2 groups of NAs. Furthermore, both wild types (WTs) in the N6 and one WT in the N9 subtype were less sensitive to ZA than were genotypically related mutants with R152K and R118K change in the respective subtypes. This may indicate that these and probably even other NAIs resistance-related mutations found in our virus collection were not induced by NAIs residuals in the environment and that the impact of such mutations in an avian influenza could be dependent on subtype, strain and host species.
User Satisfaction Prediction with Mouse Movement Information in Heterogeneous Search Environment

Satisfaction prediction is one of the prime concerns in search performance evaluation. It is a non-trivial task for three major reasons: (1) The definition of satisfaction is subjective and different users may have different opinions in the process of satisfaction judgment. (2) Most existing studies on satisfaction prediction mainly rely on users’ click-through or query reformulation behaviors but there are many sessions without such interactions. (3) Most existing works primarily rely on the hypothesis that all results on search result pages (SERPs) are homogeneous, but a variety of heterogeneous search results have been aggregated into SERPs to improve the diversity and quality of search results recently. To shed light on these research questions, we construct an experimental search engine that could collect users’ satisfaction feedback as well as mouse click-through/movement data. Inspired by recent studies in predicting search result relevance based on mouse movement patterns (namely, motifs), we propose to estimate search satisfaction with motifs extracted from mouse movement data on SERPs. Besides the existing frequency-based motif selection method, two novel selection strategies (distance-based and distribution-based) are also adopted to extract high-quality motifs for satisfaction prediction. Experimental results show that the proposed strategies outperform existing methods and have promising generalization capability for unseen users and queries in both a homogeneous and heterogeneous search environment.
Propofol versus sevoflurane anesthesia in adults: a systematic review and meta-analysis

Objectives: We performed a systematic review and meta-analysis of relevant randomized controlled trials to assess the incidence of postoperative nausea and vomiting (PONV), intraoperative hypertension and hypotension of general anesthesia with propofol versus sevoflurane in adult patients. Methods: This meta-analysis was carried out at the Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China in August 2014. Medline, PubMed, EMBASE, and Cochrane databases were searched for randomized controlled trials using combinations of the search terms sevoflurane, propofol, adults, and randomized controlled trial. Two authors independently appraised the quality of the reference research and extracted the data. Meta-analysis was performed using the Cochrane Collaboration’s Review Manager 5.3. Results: A total of six studies (1,147 patients) met the inclusion criteria were analyzed. The results of the meta-analysis were expressed as risk ratio (RR), with their corresponding 95% confidence interval (CI). Propofol was associated with a similar rate of intraoperative hypertension (RR = 1.15, 95% CI = 0.88-1.49; P = 0.31) and a similar rate of intraoperative hypotension (RR = 0.84, 95% CI = 0.60-1.19; P = 0.33) compared to sevoflurane anesthesia groups, no statistical significance between the two anesthetic techniques. In addition, the results indicated that propofol anesthesia had significantly reduced the incidence of PONV (RR = 0.62, 95% CI = 0.46-0.83; P = 0.001). Conclusions: This meta-analysis provides evidence that propofol anesthesia was associated with a similar rate of intraoperative hypertension and hypotension compared to sevoflurane anesthesia, and results in a significant reduction of PONV in adults.
Parallel Graph Summarization for Knowledge Search

Querying heterogeneous and large-scale knowledge graphs are typically expensive. This paper studies a parallel graph summarization framework to facilitate knowledge graph search. (1) We propose a class of reduced summaries characterized by graph patterns, which are capable of summarizing entities in terms of their neighborhood similarity up to a certain hop. (2) We study a bi-criteria diversi ed summarization problem. Given a knowledge graph G, it is to discover top-k diversi ed reduced summaries with maximized quality in terms of both informativeness and diversity. (3) We show that diversi ed summarization is feasible for large knowledge graphs, by developing a parallel approximation algorithm with quality guarantees. We show that the algorithm is parallel scalable, which ensures the feasibility of summarization in large graphs. Using real-world graphs, we experimentally verify the efciency of our sequential and parallel summarization algorithms, and query evaluation guided by summarization.
SDSPM-based user interest prediction in collaborative graphics design systems under ubiquitous environment

Rapid advances in the enabling technologies for mobile and ubiquitous computing help portable devices to join collaborative graphics design conveniently. The limitation of display size and computational power of these embedded devices makes it hard for mobile users to browse large pattern that renewed in real time efficiently. We present a novel user interest region prediction algorithm and related system that use state duration based segmental probability model (SDSPM) to forecast user's intention in the near future. Related experiment was carried out to test the effectiveness of the algorithm. Based on the prediction, only sub-patterns that might be interested to user are issued to the embedded sites. The proposed user interest prediction system is effective and the feasibility of the collaborative graphics design system in ubiquitous environment is enhanced.
Non-systemic fungal endophytes in Carex brevicollis may influence the toxicity of the sedge to livestock

The sedge Carex brevicollis is a common component of semi-natural grasslands and forests in temperate mountains of Central and Southern Europe. The consumption of this species causes a severe toxicity to livestock, associated to high plant concentrations of the β-carbolic alkaloid brevicolline. This research was started to ascertain the origin of this toxicity. An exploratory survey of alkaloid content in plants growing in contrasting habitats (grasslands/forests) did not contribute to find a pattern of the variable contents of brevicolline in plants, and led us to address other possibilities, such as a potential role of fungal endophytism. Systemic, vertically-transmitted endophytes producers of herbivore-deterrent alkaloids are known to infect many known forage grasses. We did not detect systemic endophytes in C. brevicollis, but the sedge harboured a rich community of non-systemic fungi. To test experimentally whether non-systemic endophytes influenced the synthesis of the alkaloid, 24 plants were submitted to a fungicide treatment to remove the fungal assemblage, and the offspring ramets were analysed for alkaloid content. Brevicolline was the major β-carbolic alkaloid detected, and the contents were at least five times lower in the new ramets that developed from fungicide-treated plants than in the untreated plants. This result, although not conclusive about the primary source of the alkaloid (a plant or a fungal product) indicates that fungal endophytes may affect the contents of the toxic brevicolline in this sedge.
Asymmetric channel estimation for multi-user millimeter wave communications

In millimeter wave (mmWave) systems adopting large number of antennas at both the transmitter and the receiver, channel estimation is challenging due to the large number of antennas and low signal-to-noise ratio (SNR) before beamforming. Due to the sparse nature of mmWave channels, the channel estimation can be solved by beam search. While conventional beam search schemes rely on exhaustive training, it requires excessive overhead scaling proportional to the number of antennas. Compressed sensing (CS) is a promising approach to reduce the training overhead. However, CS shows poor recovery performance with low SNR. In this paper, we propose an asymmetric channel estimation scheme that combines an exhaustive beam training at the receiver side and a CS approach for transmit beam training. The hybrid scheme shows robust performance in a low SNR regime and can be applied for multi-user systems.
Energy expenditure and energy intake – Guidelines on Parenteral Nutrition, Chapter 3

The energy expenditure (24h total energy expenditure, TEE) of a healthy individual or a patient is a vital reference point for nutritional therapy to maintain body mass. TEE is usually determined by measuring resting energy expenditure (REE) by indirect calorimetry or by estimation with the help of formulae like the formula of Harris and Benedict with an accuracy of ±20%. Further components of TEE (PAL, DIT) are estimated afterwards. TEE in intensive care patients is generally only 0–7% higher than REE, due to a low PAL and lower DIT. While diseases, like particularly sepsis, trauma and burns, cause a clinically relevant increase in REE between 40–80%, in many diseases, TEE is not markedly different from REE. A standard formula should not be used in critically ill patients, since energy expenditure changes depending on the course and the severity of disease. A clinical deterioration due to shock, severe sepsis or septic shock may lead to a drop of REE to a level only slightly (20%) above the normal REE of a healthy subject. Predominantly immobile patients should receive an energy intake between 1.0–1.2 times the determined REE, while immobile malnourished patients should receive a stepwise increased intake of 1.1–1.3 times the REE over a longer period. Critically ill patients in the acute stage of disease should be supplied equal or lower to the current TEE, energy intake should be increased stepwise up to 1.2 times (or up to 1.5 times in malnourished patients) thereafter.
A Data Driven Analytic Strategy for Increasing Yield and Retention

As many Universities face the constraints of declining enrollment demographics, pressure from state governments for increased student success, as well as declining revenues, the costs of utilizing anecdotal evidence and intuition based on ‘gut’ feelings to make time and resource allocation decisions become significant. However, grasping advanced statistical methods and analytics for data driven decision making can be overwhelming to some staff making buy in difficult. This paper describes how we are using SAS® Enterprise Miner to develop a model to score university students based on their probability of enrollment and retention early in the enrollment funnel so that staff and administrators can work to recruit students that not only have an average or better chance of enrolling but also succeeding once they enroll. Incorporating these results into SAS® EBI will allow us to deliver easy-to-understand results to university personnel.
On the Relative Generalized Hamming Weights of Linear Codes and their Subcodes

We first present an equivalent definition of relative generalized Hamming weights of a linear code and its subcodes, and we develop a method using finite projective geometry. Making use of the equivalent definition and the projective-geometry method, all of the relative generalized Hamming weights of a 3-dimensional $q$-ary linear code and its subcodes will be determined.
The Welfare Effects of Involuntary Part-Time Work

Employed individuals in the U.S. are increasingly more likely to work part-time involuntarily than to be unemployed. Spells of involuntary part-time work are different from unemployment spells: a full-time worker who takes on a part-time job suffers an earnings loss while remaining employed, and is unlikely to receive income compensation from publicly-provided insurance programs.We analyze these differences through the lens of an incomplete-market, job-search model featuring unemployment risk alongside an additional risk of involuntary part-time employment.A calibration of the model consistent with U.S. institutions and labor-market dynamics shows that involuntary part-time work generates lower welfare losses relative to unemployment. This finding relies critically on the much higher probability to return to full-time employment from part-time work. We interpret it as a premium in access to full-time work faced by involuntary part-time workers, and use our model to tabulate its value in consumption-equivalent units.
A universal method for fishing target proteins from mixtures of biomolecules using isothermal titration calorimetry

The most challenging tasks in biology include the identification of (1) the orphan receptor for a ligand, (2) the ligand for an orphan receptor protein, and (3) the target protein(s) for a given drug or a lead compound that are critical for the pharmacological or side effects. At present, several approaches are available, including cell‐ or animal‐based assays, affinity labeling, solid‐phase binding assays, surface plasmon resonance, and nuclear magnetic resonance. Most of these techniques are not easy to apply when the target protein is unknown and the compound is not amenable to labeling, chemical modification, or immobilization. Here we demonstrate a new universal method for fishing orphan target proteins from a complex mixture of biomolecules using isothermal titration calorimetry (ITC) as a tracking tool. We took snake venom, a crude mixture of several hundred proteins/peptides, as a model to demonstrate our proposed ITC method in tracking the isolation and purification of two distinct target proteins, a major component and a minor component. Identities of fished out target proteins were confirmed by amino acid sequencing and inhibition assays. This method has the potential to make a significant advancement in the area of identifying orphan target proteins and inhibitor screening in drug discovery and characterization.
Space‐time fractional Dirichlet problems

This paper establishes explicit solutions for fractional diffusion problems on bounded domains. It also gives stochastic solutions, in terms of Markov processes time‐changed by an inverse stable subordinator whose index equals the order of the fractional time derivative. Some applications are given, to demonstrate how to specify a well‐posed Dirichlet problem for space‐time fractional diffusions in one or several variables. This solves an open problem in numerical analysis.
Nutrition Society Medal Lecture Energy expenditure , body composition , and disease risk in children and adolescents

The purpose of the present paper is to review recent studies in children which have: (1) examined differences in energy expenditure, especially as they relate to differences in body composition and risk of developing obesity; (2) enabled more accurate measurements of body composition (especially fat and fat-free mass) and body fat distribution (especially intra-abdominal adipose tissue); (3) examined the relationship between obesity (especially body fat distribution) and increased disease risk.
Distributed MAP Inference for Undirected Graphical Models

There have been recent advances in approximate inference and learning methods: FACTORIE [MCallum et al NIPS 2009] Lazy Inference [Poon et al AAAI 2008] Dual Decomposition [Rush et al EMNLP 2010] LP relaxation [Martins et al EMNLP 2010] These methods allow inference over models with global dependencies: Coreference Models [Culotta et al NAACL 2007] Relation Extraction [Riedel et al EMNLP 2010] Joint Inference of Multiple Tasks [Singh et al ECML 2009; Finkel & Manning NAACL 2009] However, without parallelization, the scalability of these methods is severely limited. Our Contribution: Distribute MCMC-based MAP Inference using Map-Reduce Related Work: GraphLab [Low et al UAI 2010] Splashing [Gonzalez et al UAI 2009] Topic Models [Smola & Narayanamurthy VLDB 2010; Asuncion et al NIPS 2009] Our method allows ease in specifying structure, distribution strategy and proposal function, which enables faster convergence.
Decentralized Control of Cooperative Systems: Categorization and Complexity Analysis

Decentralized control of cooperative systems captures the operation of a group of decision-makers that share a single global objective. The difficulty in solving optimally such problems arises when the agents lack full observability of the global state of the system when they operate. The general problem has been shown to be NEXP-complete. In this paper, we identify classes of decentralized control problems whose complexity ranges between NEXP and P. In particular, we study problems characterized by independent transitions, independent observations, and goal-oriented objective functions. Two algorithms are shown to solve optimally useful classes of goal-oriented decentralized processes in polynomial time. This paper also studies information sharing among the decision-makers, which can improve their performance. We distinguish between three ways in which agents can exchange information: indirect communication, direct communication and sharing state features that are not controlled by the agents. Our analysis shows that for every class of problems we consider, introducing direct or indirect communication does not change the worst-case complexity. The results provide a better understanding of the complexity of decentralized control problems that arise in practice and facilitate the development of planning algorithms for these problems.
SimBot-a simulation tool for autonomous robots

This paper describes an autonomous robot simulation tool called SimBot. This tool allows users to create scenarios containing multiple autonomous robots and to develop controller programs for these robots. The tool manages the physical modeling of the scenario and generates the multiple 3D views necessary for robot vision and user viewing. The user builds up each robot from a library of configurable body parts. The robot controller programs are implemented as Windows DCOM objects and can be distributed transparently over networks. to speed up robot development, we have begun implementing a few C++ classes for vision analysis and path planning.
Generating API Call Rules from Version History and Stack Overflow Posts

Researchers have shown that related functions can be mined from groupings of functions found in the version history of a system. Our first contribution is to expand this approach to a community of applications and set of similar applications. Android developers use a set of application programming interface (API) calls when creating apps. These API calls are used in similar ways across multiple applications. By clustering co-changing API calls used by 230 Android apps across 12k versions, we are able to predict the API calls that individual app developers will use with an average precision of 75% and recall of 22%. When we make predictions from the same category of app, such as Finance, we attain precision and recall of 81% and 28%, respectively. Our second contribution can be characterized as “programmers who discussed these functions were also interested in these functions. ” Informal discussions on Stack Overflow provide a rich source of information about related API calls as developers provide solutions to common problems. By grouping API calls contained in each positively voted answer posts, we are able to create rules that predict the calls that app developers will use in their own apps with an average precision of 66% and recall of 13%. For comparison purposes, we developed a baseline by clustering co-changing API calls for each individual app and generated association rules from them. The baseline predicts API calls used by app developers with a precision and recall of 36% and 23%, respectively.
Opqrst(U): Integrating Substance Use Disorders Or “Use” into the Medical History

Substance use disorders (SUDs) are pervasive in the United States, with 20.1 million cases in 2016, of which only 19% receive treatment. SUDs permeate all medical specialties and should be considered in the differential diagnosis of every chief complaint. Acknowledging the salience of SUDs provides a unique opportunity for early identification and intervention. Thus, SUDs should be reflected prominently in the history of the present illness rather than in the social history. To this effect, we propose the inclusion of Use (U) in the history of present illness and incorporating “U” into the pedagogical mnemonic of OPQRST that is commonly used in medical training. Obtaining this history will help determine if and which abused substances may be contributing to the chief complaint. We also suggest the incorporation of an additional acronym, SORTED, to account for the various domains of Use, including Street (illicit drugs), OTCs (over-the-counter medications), Rx (prescriptions, including nonmedicinal use of pharmaceutical drugs), Tobacco (including e-cigarettes), EtOH (alcohol), and Dietary (caffeine, vitamins, and herbal supplements) agents. We discuss how utilizing OPQRSTU will help reshape the way medical students think about SUDs and will facilitate detection and diagnosis of all domains of SUDs.