Miracle-dz/UniFAR-FTUs huggingface dataset:
Platelet-rich plasma versus hyaluronic acid injections for knee osteoarthritis: a propensity-score analysis

Background and Aims: Intra-articular injections of viscosupplements have been an option in the treatment of knee osteoarthritis. Platelet-rich plasma is an experimental treatment in osteoarthritis. Previous studies have shown that platelet-rich plasma reduces osteoarthritis symptoms in similar proportions as viscosupplements. The aim of this study was to compare platelet-rich plasma versus viscosupplements in terms of symptoms’ relief and time to arthroplasty. Material and Methods: A total of 190 patients included in this retrospective study received either intra-articular injections of platelet-rich plasma (94 patients) or hyaluronic acid (86 patients) between January 2014 and October 2017. Western Ontario and McMaster Universities Osteoarthritis Index, Visual Analogue Scale, and range of motion were measured before injection, at 15 days, 6 months, 12 months, and at last follow-up. We compared outcomes between these two groups using propensity score analysis for risk adjustment in multivariate analysis and for one-to-one matching. Results: Hyaluronic acid–treated patients experienced a higher arthroplasty rate (36.0% vs 5.3%, p < 0.001), lower range of motion, worse Visual Analogue Scale and Western Ontario and McMaster Universities Osteoarthritis Index scores, and increased risk of any arthroplasty occurrence (log-rank < 0.001) than platelet-rich plasma patients. Cox proportional hazards analysis revealed a tendency to decrease the risk of knee arthroplasty for the patients treated by platelet-rich plasma (hazard ratio = 0.23, 95% confidence interval, 0.05–1.05, p = 0.058). When the treatment method was adjusted for propensity score in the propensity score–matched pairs (n = 78), we found that platelet-rich plasma group still showed significant improvement over the hyaluronic acid group in arthroplasty rate (12.8% vs 41.0%, p = 0.010), Visual Analogue Scale and Western Ontario and McMaster Universities Osteoarthritis Index scores, but not in the range of motion, during the mean follow-up of 16.7 months. Conclusion: Intra-articular injections of platelet-rich plasma associated with better outcomes than hyaluronic acid in knee osteoarthritis. Platelet-rich plasma might prolong the time to arthroplasty and provide a valid therapeutic option in selected patients with knee osteoarthritis not responding to conventional treatments. Further larger studies are needed to validate this promising treatment modality.
Automated Algorithm Selection: Survey and Perspectives

It has long been observed that for practically any computational problem that has been intensely studied, different instances are best solved using different algorithms. This is particularly pronounced for computationally hard problems, where in most cases, no single algorithm defines the state of the art; instead, there is a set of algorithms with complementary strengths. This performance complementarity can be exploited in various ways, one of which is based on the idea of selecting, from a set of given algorithms, for each problem instance to be solved the one expected to perform best. The task of automatically selecting an algorithm from a given set is known as the per-instance algorithm selection problem and has been intensely studied over the past 15 years, leading to major improvements in the state of the art in solving a growing number of discrete combinatorial problems, including propositional satisfiability and AI planning. Per-instance algorithm selection also shows much promise for boosting performance in solving continuous and mixed discrete/continuous optimisation problems. This survey provides an overview of research in automated algorithm selection, ranging from early and seminal works to recent and promising application areas. Different from earlier work, it covers applications to discrete and continuous problems, and discusses algorithm selection in context with conceptually related approaches, such as algorithm configuration, scheduling, or portfolio selection. Since informative and cheaply computable problem instance features provide the basis for effective per-instance algorithm selection systems, we also provide an overview of such features for discrete and continuous problems. Finally, we provide perspectives on future work in the area and discuss a number of open research challenges.
Lead in Spices, Herbal Remedies, and Ceremonial Powders Sampled from Home Investigations for Children with Elevated Blood Lead Levels — North Carolina, 2011–2018

The number of pediatric cases of elevated blood lead levels (BLLs) are decreasing in North Carolina. However, one county reported an increase in the number of children with confirmed BLLs ≥5 μg/dL (CDC reference value, https://www.cdc.gov/nceh/lead/acclpp/blood_lead_levels.htm), from 27 in 2013 to 44 in 2017. Many children with elevated BLLs in this county lived in new housing, but samples of spices, herbal remedies, and ceremonial powders from their homes contained high levels of lead. Children with chronic lead exposure might suffer developmental delays and behavioral problems (https://www.cdc.gov/nceh/lead/). In 1978, lead was banned from house paint in the United States (1); however, children might consume spices and herbal remedies daily. To describe the problem of lead in spices, herbal remedies, and ceremonial powders, the North Carolina Childhood Lead Poisoning Prevention Program (NCCLPPP) retrospectively examined properties where spices, herbal remedies, and ceremonial powders were sampled that were investigated during January 2011-January 2018, in response to confirmed elevated BLLs among children. NCCLPPP identified 59 properties (6.0% of all 983 properties where home lead investigations had been conducted) that were investigated in response to elevated BLLs in 61 children. More than one fourth (28.8%) of the spices, herbal remedies, and ceremonial powders sampled from these homes contained ≥1 mg/kg lead. NCCLPPP developed a survey to measure child-specific consumption of these products and record product details for reporting to the Food and Drug Administration (FDA). Lead contamination of spices, herbal remedies, and ceremonial powders might represent an important route of childhood lead exposure, highlighting the need to increase product safety. Setting a national maximum allowable limit for lead in spices and herbal remedies might further reduce the risk for lead exposure from these substances.
A Game Theoretic Approach to Estimate Fair Cost of VM Placement in Cloud Data Center

Pricing of virtual machines (VMs) with different dimensions is a challenging task. VM pricing involves both capital and operational expenditures. Capital expenditure is fixed in nature, while operational expenditure is variable. A fraction of capital expenditure is included for VM pricing. An individual pays the cloud service provider (CSP) for his requested VM. If the users cooperate among themselves they may end up paying less to CSP for their requested VMs vis-a-vis they would have paid had they requested individually. In this paper, an n-person cooperative game is adopted to determine the price that users would pay for their requested VMs under a cooperative environment. Shapley value is used to estimate the fraction of capital expenditure that would be included in the VM price. An integer linear programming is proposed for energy-efficient placement. For evaluation, VM configurations and pricing of popular CSPs—Microsoft Azure and Amazon EC2—are considered. Results show that users would pay less for their requested VMs if they cooperate. The energy consumed by the proposed VM placement technique is compared with first fit decreasing (FFD) and enhanced first fit decreasing (EFFD). It is observed that the proposed technique consumes lesser energy compared to FFD and EFFD.
Visual Font Pairing

This paper introduces the problem of automatic font pairing. Font pairing is an important design task that is difficult for novices. Given a font selection for one part of a document (e.g., header), our goal is to recommend a font to be used in another part (e.g., body) such that the two fonts used together look visually pleasing. There are three main challenges in font pairing. First, this is a fine-grained problem, in which the subtle distinctions between fonts may be important. Second, rules and conventions of font pairing given by human experts are difficult to formalize. Third, font pairing is an asymmetric problem in that the roles played by header and body fonts are not interchangeable. To address these challenges, we propose automatic font pairing through learning visual relationships from large-scale human-generated font pairs. We introduce a new database for font pairing constructed from millions of PDF documents available on the Internet. We propose two font pairing algorithms: dual-space $k$-NN and asymmetric similarity metric learning (ASML). These two methods automatically learn fine-grained relationships from large-scale data. We also investigate several baseline methods based on the rules from professional designers. Experiments and user studies demonstrate the effectiveness of our proposed dataset and methods.
A Concept-Centered Hypertext Approach to Case-Based Retrieval

The goal of case-based retrieval is to assist physicians in the clinical decision making process, by finding relevant medical literature in large archives. We propose a research that aims at improving the effectiveness of case-based retrieval systems through the use of automatically created document-level semantic networks. The proposed research tackles different aspects of information systems and leverages the recent advancements in information extraction and relational learning to revisit and advance the core ideas of concept-centered hypertext models. We propose a two-step methodology that in the first step addresses the automatic creation of document-level semantic networks, then in the second step it designs methods that exploit such document representations to retrieve relevant cases from medical literature. For the automatic creation of documents' semantic networks, we design a combination of information extraction techniques and relational learning models. Mining concepts and relations from text, information extraction techniques represent the core of the document-level semantic networks' building process. On the other hand, relational learning models have the task of enriching the graph with additional connections that have not been detected by information extraction algorithms and strengthening the confidence score of extracted relations. For the retrieval of relevant medical literature, we investigate methods that are capable of comparing the documents' semantic networks in terms of structure and semantics. The automatic extraction of semantic relations from documents, and their centrality in the creation of the documents' semantic networks, represent our attempt to go one step further than previous graph-based approaches.
PZT-Based Ultrasonic Guided Wave Frequency Dispersion Characteristics of Tubular Structures for Different Interfacial Boundaries

For tubular structures, ultrasonic guided waves (UGWs) which are closely related to interfacial boundary conditions such as gas, liquid and solid materials, are usually used in damage detection. Due to the different phase materials inside tubes, the interfacial boundary (connection) conditions are variable, which has a great influence on the dispersion-related UGW propagation characteristics. However, most UGW-based damage detection methods only consider the pipeline structures as hollow tubes, ignoring the interfacial boundary condition influences on the UGW propagation. Based on the UGW theory, this paper aims to propose a novel method for describing the UGW propagation characteristics for different interfaces, and lay a foundation for the UGW-based tubular structure damage detection. Based on the Navier’s equation of motion and combined with interfacial boundary conditions and coordinate conditions, the dispersion equations for a hollow steel tube, a tube filled with liquid, and a concrete filled steel tube (CFST) were established, respectively. Under the given conditions of both materials and geometric parameters, the transcendental dispersion equations were established and solved by using a numerical method. The UGW propagation characteristics in different interfaces were classified and discussed, and the dispersion curves of both group and phase velocities are drawn. To validate the efficiency of theoretical and numerical results, three kinds of model tubular structure experiments filled in air (hollow), water and concrete, respectively, were performed based on lead zirconate titanate (PZT) transducer UGWs. The results showed that the UGWs propagation in different interfaces has the dispersion and multi-modes characters, which are not only related to the product of frequency and thickness, but also to the internal dielectric material parameters and interfacial boundary conditions.
Modeling Topic Evolution in Twitter: An Embedding-Based Approach

In last two decades, online social networks have grown vertically as well as horizontally. Due to various users activities in these networks, huge amount of data, mainly textual, is being generated that can be analyzed at different levels of granularity for various purposes, including behavior analysis, sentiment analysis, and predictive modeling. In this paper, we propose a word embedding-based approach to analyze users-centric tweets to observe their behavior evolution in terms of the topics discussed by them over a period of time. We also present a word embedding-based proximity measure to monitor temporal transitions between the topics using five topic evolution events– emergence, persistence, convergence, divergence, and extinction. The proximity between a pair of topics is defined as a function of the content and contextual similarity between their word distributions, wherein the contextual similarity is calculated using word embedding. The proposed approach is evaluated over three Twitter datasets in line with the existing state-of-the-art approaches in literature and the experimental results are encouraging.
A Two-Stage Fuzzy Multiobjective Optimization for Phase-Sensitive Day-Ahead Dispatch of Battery Energy Storage System

Operation and management of unbalanced distribution network (UDN) is challenging and complex for optimum utilization of active resources such as distributed generation and battery energy storage systems (BESSs). In order to exploit the inherent unbalancing of UDNs as an advantage in exploiting the most benefits from BESS, a phase-sensitive day-ahead dispatch strategy for BESS is proposed. The objectives incorporated in the proposed multiobjective, multiperiod optimization include a) maximizing peak shaving, b) improving voltage profile, c) loss minimization, d) reducing tap changer operations of voltage regulators, and e) minimizing discharge–recharge cycles. A two-stage fuzzy multiobjective optimization platform is developed to 1) represent uncertainty in load demand, 2) incorporate a human-friendly linguistic interface, and 3) provide flexibility to operator for changing priorities as a function of time. A novel application of max-average and max-product compositions in fuzzy systems is employed for multiperiod optimization. The effectiveness of the proposed approach is tested on an IEEE 37-node standard test feeder with comparative results of phase-balanced and phase-sensitive BESS dispatch. It is further validated on a feeder in Northwest USA with an existing BESS. Single-objective and multiobjective optimization results with multiple Pareto solutions demonstrate the stability and robustness of the proposed approach.
An Analytical Approach to Improving Time Warping on Multidimensional Time Series

Dynamic time warping ($\texttt{DTW}$) is one of the most used distance functions to compare time series, e. $\,$g. in nearest neighbor classifiers. Yet, fast state of the art algorithms only compare 1-dimensional time series efficiently. One of these state of the art algorithms uses a lower bound ($\texttt{LB}_\texttt{Keogh}$) introduced by E. Keogh to prune $\texttt{DTW}$ computations. We introduce $\texttt{LB}_\texttt{Box}$ as a canonical extension to $\texttt{LB}_\texttt{Keogh}$ on multi-dimensional time series. We evaluate its performance conceptually and experimentally and show that an alternative to $\texttt{LB}_\texttt{Box}$ is necessary for multi-dimensional time series. We also propose a new algorithm for the dog-keeper distance ($\texttt{DK}$) which is an alternative distance function to $\texttt{DTW}$ and show that it outperforms $\texttt{DTW}$ with $\texttt{LB}_\texttt{Box}$ by more than one order of magnitude on multi-dimensional time series.
Validation of the Marijuana Effect Expectancies Questionnaire (MEEQ) in a Non-Clinical French-Speaking Adolescent Sample

Teenagers commonly use cannabis. Expectancies related to the effects of cannabis play an important role in its consumption and are frequently measured with the Marijuana Effect Expectancies Questionnaire (MEEQ). This study aims to assess the psychometric properties (factor structure, internal consistency reliability, criterion validity) of the French MEEQ. A sample of 1,343 non-clinical teenagers (14–18 years) were recruited to answer a self-report questionnaire; 877 of them responded twice (one-year interval). A four-factor structure was obtained: Cognitive Impairment and Negative, Relaxation and Social Facilitation, Perceptual Enhancement and Craving and Negative Behavioral Effect Expectancies. It is concluded that the French MEEQ constitutes an appropriate tool to measure cannabis effect expectancies among adolescents.
The Full Can Exercise as the Recommended Exercise for Strengthening the Supraspinatus While Minimizing Impingement

THE PURPOSE OF THIS COLUMN IS TO SHOW THAT CURRENT RESEARCH SUPPORTS THE USE OF THE FULL CAN EXERCISE OVER THE EMPTY CAN IN STRENGTHENING THE SUPRASPINATUS EFFECTIVELY WITHOUT INCREASING IMPINGEMENT BY LIMITING REDUCTION OF THE SUBACROMIAL SPACE.
Very-compact Waveguide Bandpass Filter based on Dual-Mode TM Cavities for Satellite Applications in Ku-band

The design of a Ku-band bandpass filter for satellite applications centered at 14.25GHz with 500 MHz bandwidth $(\mathbf{FBW}=3.5\%)$ is presented in this paper. The filter is based on TM dual-band resonator technology allowing for a reduction of about 50% of the filter length with respect to regular TE dual-mode filters resonators while maintaining a high Q-factor $(> \mathbf{4000})$. The filter is composed of a total of 4 dual-mode TM cavities. Dimensions are $\mathbf{43}\mathbf{x}\mathbf{45}\mathbf{x}\mathbf{47}\mathbf{mm}^{3}$, mass is 110g and the Insertion Loss is below 0.35dB in the passband. Measurements show good correlation with the design.
Immunodiagnosis of Visceral Leishmaniasis: Current Status and Challenges: A Review Article

Background: Diagnosis of Visceral Leishmaniasis (VL) is still challenging. This review highlighted current status and challenges in the serological diagnosis of VL. Furthermore, the drawback of currently available serological tests and the most recent advancement in the designing and application of these assays for the diagnosis of VL are addressed. Methods: All the published literature cited within PubMed, ISI Web of Science, Google Scholar, Scopus, and IranMedex, regarding the immunodiagnosis of VL in human were sought from 2000 till Mar 2017. The search terms were “visceral leishmaniasis”, or “kala-azar” subsequently combined with the search terms “diagnosis”, “serodiagnosis”, “human”, “serological”, “antigen detection” or “antibody detection”. Data were extracted from literature which fulfilled our eligibility criteria. Results: Direct agglutination test (DAT) and rk39 dipstick have made a great improvement in the serological diagnosis of VL. Besides, other kinesin-related protein including K26, K28, and KE16 provided promisingly diagnostic accuracy in the diagnosis of VL. The Latex Agglutination Test for the diagnosis of VL (KAtex), with moderate sensitivity but high specificity, made a substantial contribution to the field. Moreover, a range of protein antigens has recently been detected in the urine of VL patients with encouraging diagnostic value. Conclusion: The suboptimal diagnostic accuracy of the currently available serological assays for the diagnosis of human VL necessitates further research and development in this field. Outcomes of immunodiagnostic tests based on recombinant antigens are favorable. These proteins might be the most appropriate antigens to be further evaluated and utilized for the diagnosis of human VL.
A Meta-Objective Approach for Many-Objective Evolutionary Optimization

Abstract Pareto-based multi-objective evolutionary algorithms experience grand challenges in solving many-objective optimization problems due to their inability to maintain both convergence and diversity in a high-dimensional objective space. Exiting approaches usually modify the selection criteria to overcome this issue. Different from them, we propose a novel meta-objective (MeO) approach that transforms the many-objective optimization problems in which the new optimization problems become easier to solve by the Pareto-based algorithms. MeO converts a given many-objective optimization problem into a new one, which has the same Pareto optimal solutions and the number of objectives with the original one. Each meta-objective in the new problem consists of two components which measure the convergence and diversity performances of a solution, respectively. Since MeO only converts the problem formulation, it can be readily incorporated within any multi-objective evolutionary algorithms, including those non-Pareto-based ones. Particularly, it can boost the Pareto-based algorithms' ability to solve many-objective optimization problems. Due to separately evaluating the convergence and diversity performances of a solution, the traditional density-based selection criteria, for example, crowding distance, will no longer mistake a solution with poor convergence performance for a solution with low density value. By penalizing a solution in term of its convergence performance in the meta-objective space, the Pareto dominance becomes much more effective for a many-objective optimization problem. Comparative study validates the competitive performance of the proposed meta-objective approach in solving many-objective optimization problems.
Onlay Technique in Incisional Hernia Repair—A Systematic Review

Introduction: A meta-analysis that compared the onlay vs. sublay technique in open incisional hernia repair identified better outcomes for the sublay operation. Nonetheless, an Expert Consensus Guided by Systematic Review found the onlay mesh location useful in certain settings. Therefore, all studies on the onlay technique were once again collated and analyzed. Materials and Methods: A systematic search of the available literature was performed in August 2018 using Medline, PubMed, Scopus, Embase, Springer Link, and the Cochrane Library. For the present analysis 42 publications were identified as relevant. Results: In five prospective randomized trials and 17 observational studies the postoperative complication rates ranged between 5 and 76%, with a mean value of 33.5%. The recurrence rates in these studies also ranged between 0 and 32%, with a mean value of 9.9%. Hence, compared with the literature data on the sublay operation, more post-operative complications, in particular wound complications and seroma, with a comparable recurrence rate, were identified. Conclusion: When the onlay technique is used in certain settings for incisional hernia repair, a careful dissection technique and prophylactic measures (drainage, abdominal binders, fibrin sealant) should be employed to prevent wound complications and seroma formation.