Miracle-dz/UniFAR-FTUs huggingface dataset:
Text Retrieval for Systematic Reviews

The past decade has seen an exponential growth in the amount of information published on the web. This increase in the amount of data published is directly proportional to the steady growth in the number of data publishing sources. As a result one of the oldest problems in Information Retrieval(IR) the “Vocabulary Mismatch problem” has taken center stage. Over the years a lot of techniques have been proposed to tackle the Vocabulary Mismatch problem faced in various domains. In this work we explore the utility of the different types of latent semantic models for retrieval purposes in the medical domain. Our work focuses on the process of Systematic Reviews 2.3 . Systematic reviews is a high-recall oriented process i.e recall is of higher precedence as compared to precision for this system. An ideal retrieval scenario for Systematic Reviews is the retrieval of all relevant articles at the top of the rankings. The following work is a comparative study of three semantic techniques namely Latent Dirichlet Allocation, Relevance-based Language Models and Query expansion using OvidSP’s [5] inbuilt Basic search utility to explore the possibility of obtaining a high-recall system without compromising much on precision. It was noted that pseudo-relevance feedback(PRF) based algorithms showed relatively better performance as compared to the other techniques mentioned above. It was also noted that the PRF based algorithms performed better than the OvidSP Natural Language(NL) search which can be considered as the current standard in NL search for medical literature.
Optimization of the enzymatic hydrolysis of starch in sugarcane juice ( Saccharum spp hybrid )

, a natural component of sugarcane juice, causes losses and operational problems in the sugar industry, due to the increase in juice viscosity, which inhibits crystallization and increases sucrose loss. This research aimed to optimize the enzymatic hydrolysis process of starch by the action of Bacillus licheniformis alpha-amylase. Enzyme concentration and reaction time were optimized for maximizing maltose concentration, determined as reducing sugar by the Dinitrosalicylic Acid method; starch hydrolysis percentage and productivity
Activity of megestrol acetate in postmenopausal women with advanced breast cancer after nonsteroidal aromatase inhibitor failure: a phase II trial.

BACKGROUND As novel treatments carry substantial price tags and are mostly cost-prohibitive in low- and middle-income countries, there is an urgent need to develop alternatives, such as off-patent drugs. Megestrol acetate (MA) has a longstanding history in the treatment of breast cancer, but recently it is being used less often due to the advent of newer agents. PATIENTS AND METHODS This two-stage phase II trial evaluated the antitumor activity and toxicity of MA in postmenopausal women with hormone-sensitive advanced breast cancer who had experienced disease progression on a third-generation nonsteroidal aromatase inhibitor (NSAI). Eligible patients had metastatic breast cancer treated with a NSAI with at least 6-month progression-free survival (PFS), or relapse after ≥1 year on adjuvant NSAI. Patients received MA at a single daily oral dose of 160 mg. Primary end point was clinical benefit rate (CBR). RESULTS Forty-eight patients were enrolled. The CBR was 40% [95% confidence interval (CI) 25% to 55%], and the median duration of clinical benefit was 10.0 (95% CI 8.0-14.2) months. The median PFS was 3.9 (95% CI 3.0-4.8) months. The most common grade 3 adverse events were anemia (2%), dyspnea (2%), fatigue (2%), musculoskeletal pain (4%), deep vein thrombosis (10%), and weight gain (2%). CONCLUSIONS This is the first study to prospectively evaluate the efficacy and safety of MA in postmenopausal women with hormone-sensitive disease progressing on a NSAI. MA has demonstrated activity and acceptable tolerability in this setting, and therefore remains a reasonable treatment option in a cost-sensitive environment. These results also provide the background for further evaluation of progestins in the treatment of breast cancer. CLINICAL TRIALS local trial number, related to the approval by the IRB: CEP 108/06.
Inventario de metas de acción de aprendizaje para construir conocimientos basados en texto y tema

This research is based on ESL reading comprehension. Its purpose is to identify which purpose-built learning actions for constructing text-based and topic-based knowledge first-semester students from the English Language Teaching Program at Universidad de Cordoba applied more often while reading. Data was gathered through a reading platform called knockWhy? , along with a reading activity in which students brought up purpose-built learning actions. After using the platform, the students answered a questionnaire in order to evaluate their experience and opinion about the platform’s design. Results showed that students brought a significant amount of purpose-built learning actions, which mainly concerned textual-based knowledge, rather than topic-based. Results also revealed that students’ experience with the platform and its design was significant when bringing up purpose-built learning actions.
Lateral control of an articulated bus for lane guidance and curbside precision docking

This paper presents the design, implementation, and field testing of a lane assist system that provides lane guidance and curbside precision docking functions for a 60 ft articulated bus. The challenges in this lateral control design include the extra lightly-damped mode from the articulated section, the relatively large disturbance due to the sharp S-curves for precision docking, and the uncertainties introduced by public roads and live traffic. To tackle these challenges, the control problem is formulated as a mixed H2/H∞ synthesis problem and solved by LMI optimization. Extensive field tests were conducted in live traffic and the results show adequate and consistent performances.
TinyML Olive Fruit Variety Classiﬁcation by Means of Convolutional Neural Networks on IoT Edge Devices

: Machine learning (ML) within the edge internet of things (IoT) is instrumental in making signiﬁcant shifts in various industrial domains, including smart farming. To increase the efﬁciency of farming operations and ensure ML accessibility for both small and large-scale farming, the need for a low-cost ML-enabled framework is more pressing. In this paper, we present an end-to-end solution that utilizes tiny ML (TinyML) for the low-cost adoption of ML in classiﬁcation tasks with a focus on the post-harvest process of olive fruits. We performed dataset collection to build a dataset that consists of several varieties of olive fruits, with the aim of automating the classiﬁcation and sorting of these fruits. We employed simple image segmentation techniques by means of morphological segmentation to create a dataset that consists of more than 16,500 individually labeled fruits. Then, a convolutional neural network (CNN) was trained on this dataset to classify the quality and category of the fruits, thereby enhancing the efﬁciency of the olive post-harvesting process. The goal of this study is to show the feasibility of compressing ML models into low-cost edge devices with computationally constrained settings for tasks like olive fruit classiﬁcation. The trained CNN was efﬁciently compressed to ﬁt into a low-cost edge controller, maintaining a small model size suitable for edge computing. The performance of this CNN model on the edge device, focusing on metrics like inference time and memory requirements, demonstrated its feasibility with an accuracy of classiﬁcation of more than 97.0% and minimal edge inference delays ranging from 6 to 55 inferences per second. In summary, the results of this study present a framework that is feasible and efﬁcient for compressing CNN models on edge devices, which can be utilized and expanded in many agricultural applications and also show the practical insights for implementing the used CNN architectures into edge IoT devices and show the trade-offs for employing them using TinyML.
Low density lipoprotein metabolism by human macrophages activated with low density lipoprotein immune complexes. A possible mechanism of foam cell formation

Human macrophages play a key role in atherogenesis and are believed to be the progenitors of the cholesteryl ester (CE)-laden foam cells present in early atherosclerotic lesions. Several mechanisms by which macrophages accumulate CE have been recently described. One involves a perturbation in LDL metabolism subsequent to macrophage activation. Thus, we decided to study the effect of macrophage activation by immune complexes on N-LDL metabolism. Initially, LDL-containing immune complexes (LDL-IC) were chosen, since increased plasma levels of these IC have been reported in patients with coronary heart disease. Human macrophages stimulated for 22 h with LDL-IC (250 micrograms/ml) and incubated afterwards for 20 h with 10 micrograms/ml 125I-N-LDL showed a six- and fourfold increase in the accumulation and degradation, respectively, of 125I-N-LDL over the values observed in nonstimulated cells. Scatchard analysis of 125I-N-LDL-specific binding suggests an increase (20-fold) in the number of LDL receptors in macrophages stimulated with LDL-IC. We studied other immune complexes varying in size and antigen composition. Some of the IC were able to stimulate, although to a lesser degree, the uptake of N-LDL by macrophages. Lipoprotein IC are more efficient and have the greatest capacity to increase N-LDL uptake and CE accumulation. We conclude that human macrophage activation by LDL-IC leads to an increase in LDL receptor activity and promotes in vitro foam cell formation.
Achieving Optimal Throughput and Near-Optimal Asymptotic Delay Performance in Multichannel Wireless Networks With Low Complexity: A Practical Greedy Scheduling Policy

In this paper, we focus on the scheduling problem in multichannel wireless networks, e.g., the downlink of a single cell in fourth-generation (4G) OFDM-based cellular networks. Our goal is to design practical scheduling policies that can achieve provably good performance in terms of both throughput and delay, at a low complexity. While a class of O(n2.5 log n)-complexity hybrid scheduling policies is recently developed to guarantee both rate-function delay optimality (in the many-channel many-user asymptotic regime) and throughput optimality (in the general non-asymptotic setting), their practical complexity is typically high. To address this issue, we develop a simple greedy policy called Delay-based Server-Side-Greedy (D-SSG) with a lower complexity 2n2+2n, and rigorously prove that D-SSG not only achieves throughput optimality, but also guarantees near-optimal asymptotic delay performance. Specifically, the rate-function of the delay-violation probability attained by D-SSG for any fixed integer delay threshold b > 0 is no smaller than the maximum achievable rate-function by any scheduling policy for threshold b-1. Thus, we are able to achieve a reduction in complexity (from O(n2.5 logn) of the hybrid policies to 2n2 + 2n) with a minimal drop in the delay performance. More importantly, in practice, D-SSG generally has a substantially lower complexity than the hybrid policies that typically have a large constant factor hidden in the O(·) notation. Finally, we conduct simulations to validate our theoretical results in various scenarios. The simulation results show that in all scenarios we consider, D-SSG not only guarantees a near-optimal rate-function, but also empirically has a similar delay performance to the rate-function delay-optimal policies.
SIFT Vs SURF: Quantifying the Variation in Transformations

This paper studies the robustness of SIFT and SURF against different image transforms (rigid body, similarity, affine and projective) by quantitatively analyzing the variations in the extent of transformations. Previous studies have been comparing the two techniques on absolute transformations rather than the specific amount of deformation caused by the transformation. The paper establishes an exhaustive empirical analysis of such deformations and matching capability of SIFT and SURF with variations in matching parameters and the amount of tolerance. This is helpful in choosing the specific use case for applying these techniques.
Contribution of Neonatal Amniotic Fluid Testing to Diagnosis of Congenital Toxoplasmosis

ABSTRACT We evaluated the molecular diagnosis of congenital toxoplasmosis (CT) on neonatal amniotic fluid samples from 488 mother-child pairs. Maternal infection during pregnancy was diagnosed and dated or could not be ruled out. Forty-six cases of CT were defined according to the European Research Network on CT classification system and case definitions. Neonatal amniotic fluid testing had an overall sensitivity of 54% (95% confidence interval [95% CI], 39 to 69%) and a specificity of 100% (95% CI, 99 to 100%). Its sensitivity was 33% (95% CI, 13 to 59%) when antenatal diagnosis was positive and 68% (95% CI, 48 to 84%) when antenatal diagnosis was negative or lacking. This difference in sensitivity may have been due to treatment of antenatally diagnosed cases. Relative to postnatal serology, neonatal amniotic fluid testing allowed an earlier diagnosis to be made in 26% of the cases (95% CI, 9 to 51%).
Asymmetric semi-supervised boosting for SVM active learning in CBIR

Support vector machine (SVM) based active learning technique has played a key role to alleviate the burden of labeling in relevance feedback. However, most SVM-based active learning algorithms are challenged by the small example problem and the asymmetric distribution problem. This paper proposes a novel scheme that combines semi-supervised learning, ensemble learning and active learning in a uniform framework. Concretely, unlabeled data is exploited to facilitate ensemble learning by helping augment the diversity among the base SVM classifiers, and then the learned SVM ensemble model is used to identify the most informative examples for active learning. In particular, a bias-weighting mechanism is developed to guide the ensemble model to pay more attention on the positive examples than the negative ones. An empirical study shows that the proposed scheme is significantly more effective than some existing approaches.
RESEARCH OVERVIEW ON RECOVERY OF WASTE HEAT FROM HIGH TEMPERATURE SLAG PARTICLES

The high temperature slag discharged from metallurgical industry has the characteristics of high temperature and large discharge. In 2017, the total amount of liquid slag produced by the world iron and steel industry is about 913 million tons and the amount of waste heat resources contained in liquid slag is equivalent to about 38 million tons of oil equivalent. It has great value of waste heat recovery and resource utilization. Among all kinds of slag treatment methods, dry centrifugal granulation has the advantages of small particle size and high vitrification, which is a developmental slag treatment process. The slag particles produced by centrifugal granulation are typical semi-melt and wide-screening particles. This paper reviews the current status of basic scientific research of gas-solid heat transfer, solid-solid heat transfer and phase evolution of semi-melt particles by scholars all over the world. On this basis, in order to achieve efficient waste heat recovery and resource utilization of centrifugal granulated blast furnace slag particles, this paper puts forward specific research contents and technical development ideas about the heat transfer mechanism of semi-melt and wide-screening particles and the high-temperature waste heat recovery technology of high-temperature slag particles.
DigitalCommons@SHU DigitalCommons@SHU

Two laboratory experiments documented the effects of mesograzer feeding (i.e., the gastropod Crepidula ustulatulina and the isopod Paracerceis caudata ) on phenolic acid and condensed tannin production in two regionally abundant seagrasses ( Thalassia testudinum (turtlegrass) and Halodule wrightii (shoalgrass)). Subsequent paired choice experiments tested the hypothesis that phenolic acids and condensed tannins produced by these seagrasses deter mesograzer feeding. At the scale of the shoot, grazing by gastropods and isopods led to ~40-50% decreases in concentrations of some phenolic acids and ~20% decreases in condensed tannins in turtlegrass leaves. At a more refined spatial scale, concentrations of two of these compounds increased by 25-85% in areas near tissues damaged by C. ustulatulina and P. caudata in turtlegrass . In contrast, isopod feeding increased concentrations of some shoalgrass phenolic acids by about 30-50%, while gastropod grazing led to approximately 25-50% higher concentrations of condensed tannins in shoalgrass leaves, suggesting that grazer identity and seagrass species play important roles in seagrass deterrent production. Amphipods ( Batea catharinensis ) consistently preferred agar food made from seagrass leaves with low phenolic concentrations in choice feeding experiments, indicating that phenolics can act as feeding deterrents to these mesograzers.
Gammatone Features and Feature Combination for Large Vocabulary Speech Recognition

In this work, an acoustic feature set based on a gammatone filterbank is introduced for large vocabulary speech recognition. The gammatone features presented here lead to competitive results on the EPPS English task, and considerable improvements were obtained by subsequent combination to a number of standard acoustic features, i.e. MFCC, PLP, MF-PLP, and VTLN plus voicedness. Best results were obtained when combining gammatone features to all other features using weighted ROVER, resulting in a relative improvement of about 12% in word error rate compared to the best single feature system. We also found that ROVER gives better results for feature combination than both log-linear model combination and LDA.
Voice Communication Across the Internet: A Network Voice Terminal

Voice conferencing has attracted interest as a useful and viable rst real-time application on the Internet. This report describes Nevot a network voice terminal meant to support multiple concurrent both two-party and multi-party conferences on top of a variety of transport protocols and using audio encodings o ering from vocoder to multi-channel CD quality. As it is to be used as an experimental tool, it o ers extensive con guration, trace and statistics options. The design is kept modular so that additional audio encodings, transport and real-time protocols as well as user interfaces can be added readily. In the rst part, the report describes the Xbased graphical user interface, the con guration and operation. The second part describes the individual components of Nevot and compares alternate implementations. An appendix covers the installation of Nevot.
A Step Forward in Studying the Compact Genetic Algorithm

The compact Genetic Algorithm (cGA) is an Estimation of Distribution Algorithm that generates offspring population according to the estimated probabilistic model of the parent population instead of using traditional recombination and mutation operators. The cGA only needs a small amount of memory; therefore, it may be quite useful in memory-constrained applications. This paper introduces a theoretical framework for studying the cGA from the convergence point of view in which, we model the cGA by a Markov process and approximate its behavior using an Ordinary Differential Equation (ODE). Then, we prove that the corresponding ODE converges to local optima and stays there. Consequently, we conclude that the cGA will converge to the local optima of the function to be optimized.
Effectiveness trial of an intensive communication structure for families of long-stay ICU patients.

BACKGROUND Formal family meetings have been recommended as a useful approach to assist in goal setting, facilitate decision making, and reduce use of ineffective resources in the ICU. We examined patient outcomes before and after implementation of an intensive communication system (ICS) to test the effect of regular, structured formal family meetings on patient outcomes among long-stay ICU patients. METHODS One hundred thirty-five patients receiving usual care and communication were enrolled as the control group, followed by enrollment of intervention patients (n = 346), from five ICUs. The ICS included a family meeting within 5 days of ICU admission and weekly thereafter. Each meeting discussed medical update, values and preferences, and goals of care; treatment plan; and milestones for judging effectiveness of treatment. RESULTS Using multivariate analysis, there were no significant differences between control and intervention patients in length of stay (LOS), the primary end point. Similarly, there were no significant differences in indicators of aggressiveness of care or treatment limitation decisions (ICU mortality, LOS, duration of ventilation, treatment limitation orders, or use of tracheostomy or percutaneous gastrostomy). Exploratory analysis suggested that in the medical ICUs, the intervention was associated with a lower prevalence of tracheostomy among patients who died or had do-not-attempt-resuscitation orders in place. CONCLUSIONS The negative findings of the main analysis, in combination with preliminary evidence of differences among types of unit, suggest that further examination of the influence of patient, family, and unit characteristics on the effects of a system of regular family meetings may be warranted. Despite the lack of influence on patient outcomes, structured family meetings may be an effective approach to meeting information and support needs. TRIAL REGISTRY ClinicalTrials.gov; No.: NCT01057238 ; URL: www.clinicaltrials. gov.
A review of design and adaptation of embankment infrastructure built on permafrost under a changing climate

Arctic regions are sensitive to climate warming, where increasing climatic temperatures and alterations in weather impact permafrost stability and place both existing and future infrastructure at risk. Permafrost thaw impacts industrial and residential infrastructure from unacceptable settlement to complete failure, where linear infrastructure is susceptible to damage. This paper summarizes the current knowledge about adapting and designing infrastructure built on permafrost, focusing on the railway embankments. First, a review of permafrost degradation effects on infrastructure and some examples are presented. The state-of-the-art reliability analysis in permafrost regions is summarized, emphasizing railway embankments design and maintenance. In addition, this paper notes the knowledge gaps regarding the reliability of embankment infrastructure in permafrost regions, which shows that the long-term effects of climate change on infrastructure are not considered. At the end, suggestions for future research ideas are presented. RÉSUMÉ Les régions arctiques sont sensibles au changement climatique, où l'augmentation des températures climatiques et les modifications du temps ont un impact sur la stabilité du pergélisol et mettent en danger les infrastructures existantes et futures. Le dégel du pergélisol a des répercussions sur les infrastructures industrielles et résidentielles, allant d'un tassement inacceptable à une défaillance complète, les infrastructures linéaires étant susceptibles d'être endommagées. Cet article résume les connaissances actuelles sur l'adaptation et la conception des infrastructures construites sur le pergélisol, en se concentrant