Miracle-dz/UniFAR-FTUs huggingface dataset:
Rationale and design of the PHYSICALFAV trial: a randomized controlled trial to evaluate the effect of preoperative isometric exercise on vascular calibre and maturation of autologous arteriovenous fistulas

ABSTRACT Background A good vascular access (VA) is vital for haemodialysis (HD) patients. HD with an autologous arteriovenous fistula (AVF) is associated with higher survival, lower health care costs and fewer complications. Although a distal forearm AVF is the best option, not all patients are good candidates for this approach and the primary failure rate ranges from 20% to 50%. The optimal AVF depends mainly on the anatomical and haemodynamic characteristics of the artery and the vein chosen for the anastomosis. These characteristics can be modified by performing physical exercise. VA guidelines suggest that isometric exercises should be performed both before and after the AVF is created. While the literature contains few data on the potential efficacy of preoperative exercise, small observational studies point to an improvement in venous and arterial calibre. Postoperative exercise also seems to improve maturation, although there is no consensus on the appropriate exercise protocol. Methods The PHYSICALFAV trial (NCT03213756) is an open-label, multicentre, prospective, controlled, randomized trial designed to evaluate the usefulness of preoperative isometric exercise (PIE) in pre-dialysis patients or in prevalent HD patients who are candidates for a new AVF. Patients are randomized 1:1 to the PIE group (isometric exercises for 8 weeks) or the control group (no exercise). The main endpoint is whether the rate of primary failure is lower in the PIE group than in the control group. Results The trial has already started, with 40 patients having been enrolled as of 21 March 2018; 26.5% of the estimated sample.
Mining the Most Influential <inline-formula><tex-math notation="LaTeX">$k$</tex-math> <alternatives><inline-graphic xlink:href="li-ieq1-2717978.gif"/></alternatives></inline-formula>-Location Set from Massive Trajectories

Mining the most influential location set finds <inline-formula><tex-math notation="LaTeX">$k$</tex-math> <alternatives><inline-graphic xlink:href="li-ieq2-2717978.gif"/></alternatives></inline-formula> locations, traversed by the maximum number of unique trajectories, in a given spatial region. These influential locations are valuable for resource allocation applications, such as selecting charging stations for electric automobiles and suggesting locations for placing billboards. This problem is NP-hard and usually calls for an interactive mining processes involving a user's input, e.g., changing the spatial region and <inline-formula><tex-math notation="LaTeX">$k$ </tex-math><alternatives><inline-graphic xlink:href="li-ieq3-2717978.gif"/></alternatives></inline-formula>, or removing some locations (from the results in the previous round) that are not eligible for an application according to the domain knowledge. Efficiency is the major concern in conducting this human-in-the-loop mining. To this end, we propose a complete mining framework, which includes an optimal method for the light setting (i.e., small region and <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives> <inline-graphic xlink:href="li-ieq4-2717978.gif"/></alternatives></inline-formula>) and an approximate method for the heavy setting (i.e., large region and <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives> <inline-graphic xlink:href="li-ieq5-2717978.gif"/></alternatives></inline-formula>). The optimal method leverages <italic>vertex grouping</italic> and <italic>best-first pruning</italic> techniques to expedite the mining process. The approximate method can provide the performance guarantee by utilizing the greedy heuristic, and it is comprised of <italic>efficient updating strategy</italic>, <italic>index partition</italic> and <italic>workload-based optimization </italic> techniques. We evaluate the efficiency and effectiveness of our methods based on two taxi datasets from China, and one check-in dataset from New York.
EvoMSA: A Multilingual Evolutionary Approach for Sentiment Analysis

Sentiment analysis (SA) is a task related to understanding people's feelings in written text; the starting point would be to identify the polarity level (positive, neutral or negative) of a given text, moving on to identify emotions or whether a text is humorous or not. This task has been the subject of several research competitions in a number of languages, e.g., English, Spanish, and Arabic, among others. In this contribution, we propose an SA system, namely EvoMSA, that unifies our participating systems in various SA competitions, making it domain-independent and multilingual by processing text using only language-independent techniques. EvoMSA is a classifier, based on Genetic Programming that works by combining the output of different text classifiers to produce the final prediction. We analyzed EvoMSA on different SA competitions to provide a global overview of its performance. The results indicated that EvoMSA is competitive obtaining top rankings in several SA competitions. Furthermore, we performed an analysis of EvoMSA's components to measure their contribution to the performance; the aim was to facilitate a practitioner or newcomer to implement a competitive SA classifier. Finally, it is worth to mention that EvoMSA is available as open-source software.
Software-Defined Virtual Testbed for IoT Systems

The Internet of Things concept has found applications in a wide range of solutions, including smart homes, smart cities, enterprise systems, and others. Due to the limited resources available on physical devices and the intermittent availability of wireless networks, IoT may hugely benefit from Mobile Cloud Computing as it may provide the necessary processing power and the storage. This, however, increases the complexity of IoT systems and calls for a flexible testing environment to simplify the development process. In this paper we propose the concept of a software-defined IoT testbed which enables an IoT system to be immersed and tested in a virtual environment in order to evaluate its behavior under controllable conditions. Additionally, the features of the implemented testbed prototype are discussed on the basis of a specific use case.
Trial watch: Peptide-based vaccines in anticancer therapy

ABSTRACT Peptide-based anticancer vaccination aims at stimulating an immune response against one or multiple tumor-associated antigens (TAAs) following immunization with purified, recombinant or synthetically engineered epitopes. Despite high expectations, the peptide-based vaccines that have been explored in the clinic so far had limited therapeutic activity, largely due to cancer cell-intrinsic alterations that minimize antigenicity and/or changes in the tumor microenvironment that foster immunosuppression. Several strategies have been developed to overcome such limitations, including the use of immunostimulatory adjuvants, the co-treatment with cytotoxic anticancer therapies that enable the coordinated release of damage-associated molecular patterns, and the concomitant blockade of immune checkpoints. Personalized peptide-based vaccines are also being explored for therapeutic activity in the clinic. Here, we review recent preclinical and clinical progress in the use of peptide-based vaccines as anticancer therapeutics.Abbreviations: CMP: carbohydrate-mimetic peptide; CMV: cytomegalovirus; DC: dendritic cell; FDA: Food and Drug Administration; HPV: human papillomavirus; MDS: myelodysplastic syndrome; MHP: melanoma helper vaccine; NSCLC: non-small cell lung carcinoma; ODD: orphan drug designation; PPV: personalized peptide vaccination; SLP: synthetic long peptide; TAA: tumor-associated antigen; TNA: tumor neoantigen
K-Pg: Shared State in Differential Dataflows

Many of the most popular scalable data-processing frameworks are fundamentally limited in the generality of computations they can express and efficiently execute. In particular, we observe that systems' abstractions limit their ability to share and reuse indexed state within and across computations. These limitations result in an inability to express and efficiently implement algorithms in domains where the scales of data call for them most. In this paper, we present the design and implementation of K-Pg, a data-processing framework that provides high-throughput, low-latency incremental view maintenance for a general class of iterative data-parallel computations. This class includes SQL, stratified Datalog with negation and non-monotonic aggregates, and much of graph processing. Our evaluation indicates that K-Pg's performance is either comparable to, or exceeds, that of specialized systems in multiple domains, while at the same time significantly generalizing their capabilities.
Recent Advances in Tunable and Reconfigurable Metamaterials

Metamaterials are composed of nanostructures, called artificial atoms, which can give metamaterials extraordinary properties that cannot be found in natural materials. The nanostructures themselves and their arrangements determine the metamaterials’ properties. However, a conventional metamaterial has fixed properties in general, which limit their use. Thus, real-world applications of metamaterials require the development of tunability. This paper reviews studies that realized tunable and reconfigurable metamaterials that are categorized by the mechanisms that cause the change: inducing temperature changes, illuminating light, inducing mechanical deformation, and applying electromagnetic fields. We then provide the advantages and disadvantages of each mechanism and explain the results or effects of tuning. We also introduce studies that overcome the disadvantages or strengthen the advantages of each classified tunable metamaterial.
The reproducibility of cardiac magnetic resonance imaging measures of aortic stiffness and their relationship to cardiac structure in prevalent haemodialysis patients

ABSTRACT Background Aortic stiffness is one of the earliest signs of cardiovascular disease (CVD) in patients with chronic kidney disease and an independent predictor of mortality. It is thought to drive left ventricular (LV) remodelling, an established biomarker for mortality. The relationship between direct and indirect measures of aortic stiffness and LV remodelling is not defined in dialysis patients, nor are the reproducibility of methods used to assess aortic stiffness using cardiac magnetic resonance (CMR) imaging. Methods Using 3T CMR, we report the results of (i) the interstudy, interobserver and intra-observer reproducibility of ascending aortic distensibility (AAD), descending aortic distensibility (DAD) and aortic pulse wave velocity (aPWV) in 10 haemodialysis (HD) patients and (ii) the relationship between AAD, DAD and aPWV and LV mass index (LVMi) and LV remodelling in 70 HD patients. Results Inter- and intra-observer variability of AAD, DAD and aPWV were excellent [intraclass correlation (ICC) > 0.9 for all]. Interstudy reproducibility of AAD was excellent {ICC 0.94 [95% confidence interval (CI) 0.78–0.99]}, but poor for DAD and aPWV [ICC 0.51 (−0.13–0.85) and 0.51 (−0.31–0.89)]. AAD, DAD and aPWV associated with LVMi on univariate analysis (β = −0.244, P = 0.04; β =−0.315, P < 0.001 and β = 0.242, P = 0.04, respectively). Only systolic blood pressure, serum phosphate and a history of CVD remained independent determinants of LVMi on multivariable linear regression. Conclusions AAD is the most reproducible CMR-derived measure of aortic stiffness in HD patients. CMR-derived measures of aortic stiffness were not independent determinants of LVMi in HD patients. Whether one should target blood pressure over aortic stiffness to mitigate cardiovascular risk still needs determination.
Degradation of Polycyclic Aromatic Hydrocarbons by Moderately Halophilic Bacteria from Luzon Salt Beds

Background. Polycyclic aromatic hydrocarbons (PAHs) are common environmental contaminants which are highly toxic due to their carcinogenic and mutagenic effects. They are released into the environment by incomplete combustion of solid and liquid fuels, accidental spillage of oils and seepage from industrial activities. One of the promising processes mitigating PAHs is through biodegradation. However, conventional microbiological treatment processes do not function well at high salt concentrations. Hence, utilization of halophilic bacteria should be considered. Objectives. This study aimed to assess the ability of halophilic bacteria isolated from local salt beds in Pangasinan and Cavite, the Philippines, to degrade PAHs pyrene, fluorene and fluoranthene. Methods. Polycyclic aromatic hydrocarbon-tolerant halophilic bacteria collected from two sampling sites were phenotypically characterized, molecularly identified and tested to determine their potential to degrade the PAHs pyrene, fluorene and fluoranthene at a hypersaline condition. Best PAH degraders were then assayed to identify the optimal degradation using such parameters as pH, temperature and PAH concentration. Testing for enzyme degradation was also done to determine their baseline information. Extraction and analysis of degraded PAHs were performed using centrifugation and UV-vis spectrophotometry. Results. Twelve isolates from both collection sites tolerated and grew in culture with selected PAHs. These were identified into four genera (Halobacillus, Halomonas, Chromohalobacter, and Pontibacillus). Selected best isolates in a series of biodegradation assays with the above-mentioned parameters were Halobacillus B (Collection of Microbial Strains (CMS) 1802) (=trueperi) (Gram-positive) for pyrene and fluoranthene, and Halomonas A (CMS 1901) (Gram-negative) for fluorene. Degrader biomass and PAH degradation were invariably negatively correlated. Qualitative tests with and without peptone as a nitrogen source implied enzymatic degradation. Discussion. Polycyclic aromatic hydrocarbons utilized by these halophilic bacteria served as a sole source of carbon and energy. Implications of biodegradation of the two best isolates show that high molecular weight (HMW) (4-ring) pyrene tends to be degraded better by Gram-positive bacteria and low molecular weight (3-ring) fluorene by Gram-negative degraders. Conclusions. Halophilic bacteria constitute an untapped natural resource for biotechnology in the Philippines. The present study demonstrated their potential use in bioremediation of recalcitrant hydrocarbons in the environment. Competing Interests. The authors declare no competing financial interests.
AsyncQVI: Asynchronous-Parallel Q-Value Iteration for Reinforcement Learning with Near-Optimal Sample Complexity

In this paper, we propose AsyncQVI, an asynchronous-parallel Q-value iteration for Reinforcement Learning problems. Given such a problem with $|\mathcal{S}|$ states, $|\mathcal{A}|$ actions, and a discounted factor $\gamma\in(0,1)$, AsyncQVI uses memory of size $\mathcal{O}(|\mathcal{S}|)$ and returns an $\varepsilon$-optimal policy with probability at least $1-\delta$ using $$\tilde{\mathcal{O}}\bigg(\frac{|\mathcal{S}||\mathcal{A}|}{(1-\gamma)^5\varepsilon^2}\log\Big(\frac{1}{\delta}\Big)\bigg)$$ samples. AsyncQVI is also the first asynchronous-parallel algorithm for reinforcement learning with a convergence rate and a sample complexity. Its sample complexity nearly matches the theoretical lower bound. The relatively low memory footprint and parallel ability of AsyncQVI make it suitable for large-scale applications. In numerical tests, we compare AsyncQVI with four sample-based value iteration methods. The test results show AsyncQVI is highly efficient and achieves linear parallel speedup.
Fast and Accurate Person Re-Identification with RMNet

In this paper we introduce a new neural network architecture designed to use in embedded vision applications. It merges the best working practices of network architectures like MobileNets and ResNets to our named RMNet architecture. We also focus on key moments of building mobile architectures to carry out in the limited computation budget. Additionally, to demonstrate the effectiveness of our architecture we evaluate the RMNet backbone on Person Re-identification task. The proposed approach is in top 3 of state of the art solutions on Market-1501 challenge, however our method significantly outperforms them by the inference speed.
Association of Copy Number Variation at Intron 3 of HMGA2 With Navel Length in Bos indicus

Navel injuries caused by friction against the pasture can promote infection, reproductive problems and costly treatments in beef cattle raised in extensive systems. A haplotype-based genome-wide association study (GWAS) was performed for visual scores of navel length at yearling in Nellore cattle (Bos indicus) using data from 2,016 animals and 503,088 single nucleotide polymorphism (SNP) markers. The strongest signal (p = 1.01 × 10-9) was found on chromosome 5 spanning positions 47.9-48.2 Mbp. This region contains introns 3 and 4 and exons 4 and 5 of the high mobility group AT-hook 2 gene (HMGA2). Further inspection of the region with whole genome sequence data of 21 Nellore bulls revealed correlations between counts of the significant haplotype and copy number gains of a ∼6.2 kbp segment of intron 3 of HMGA2. Analysis of genome sequences from five African B. indicus and four European Bos taurus breeds revealed that the copy number variant (CNV) is indicine-specific. This intronic CNV was then validated through quantitative polymerase chain reaction (qPCR) using Angus animals as copy neutral controls. Importantly, the CNV was not detectable by means of conventional SNP-based GWAS or SNP probe intensity analyses. Given that HMGA2 affects the expression of the insulin-like growth factor 2 gene (IGF2) together with the pleomorphic adenoma gene 1 (PLAG1), and that the latter has been repeatedly shown to be associated with quantitative traits of economic importance in cattle, these findings highlight the emerging role of variants impacting the insulin-like growth factor pathway to cattle breeding.
CD5, an Undercover Regulator of TCR Signaling

T cells are critical components of adaptive immunity. As such, their activation is regulated by the T cell receptor (TCR) that constantly scan peptides associated with major histocompatibility complexes (MHC). TCR engagement initiates a series of molecular events leading to cytokine secretion, proliferation, and differentiation of T cells. As a second coincident event, activation of co-stimulatory molecules, such as CD28, synergize with the TCR in order to prolong and/or amplify intracellular signals. With the recent advances in immunotherapies targeting T cells, co-inhibitory receptors are of growing interest for immunologists due to their potential modulatory properties on T cell functions. However, special attention should be dedicated to avoid unwanted clinical outcomes (1). In particular, Manichean categorization of receptors based on incomplete functional knowledge can lead to an over-simplistic view of complex cellular regulations. Thus, analysis of the functions that characterize these receptors in diverse physiological contexts remains essential for their rational use in therapeutic protocols. Here we focus on CD5, a transmembrane receptor that regulates T cell functions and development but remains poorly characterized at the molecular level. We will review its roles in physiological conditions and suggest potential molecular effectors that could account for CD5-dependent regulation of TCR signaling.
CD27 stimulation unveils the efficacy of linked class I/II peptide vaccines in poorly immunogenic tumors by orchestrating a coordinated CD4/CD8 T cell response

ABSTRACT Despite their promise, tumor-specific peptide vaccines have limited efficacy. CD27 is a costimulatory molecule expressed on CD4+ and CD8+ T cells that is important in immune activation. Here we determine if a novel CD27 agonist antibody (αhCD27) can enhance the antitumor T cell response and efficacy of peptide vaccines. We evaluated the effects of αhCD27 on the immunogenicity and antitumor efficacy of whole protein, class I-restricted, and class II-restricted peptide vaccines using a transgenic mouse expressing human CD27. We found that αhCD27 preferentially enhances the CD8+ T cell response in the setting of vaccines comprised of linked class I and II ovalbumin epitopes (SIINFEKL and TEWTSSNVMEERKIKV, respectively) compared to a peptide vaccine comprised solely of SIINFEKL, resulting in the antitumor efficacy of adjuvant αhCD27 against intracranial B16.OVA tumors when combined with vaccines containing linked class I/II ovalbumin epitopes. Indeed, we demonstrate that this efficacy is both CD8- and CD4-dependent and αhCD27 activity on ovalbumin-specific CD4+ T cells is necessary for its adjuvant effect. Importantly for clinical translation, a linked universal CD4+ helper epitope (tetanus P30) was sufficient to instill the efficacy of SIINFEKL peptide combined with αhCD27, eliminating the need for a tumor-specific class II-restricted peptide. This approach unveiled the efficacy of a class I-restricted peptide vaccine derived from the tumor-associated Trp2 antigen in mice bearing intracranial B16 tumors. CD27 agonist antibodies combined with peptide vaccines containing linked tumor-specific CD8+ epitopes and tumor-specific or universal CD4+ epitopes enhance the efficacy of active cancer immunotherapy.
Humanoid gait generation in complex environments based on template models and optimality principles learned from human beings

In this paper, we present an inverse optimal control-based transfer of motions from human experiments to humanoid robots and apply it to walking in constrained environments. To this end, we introduce a 3D template model, which describes motion on the basis of center-of-mass trajectory, foot trajectories, upper-body orientation, and phase duration. Despite its abstract architecture, with prismatic joints combined with damped series elastic actuators instead of knees, the model (including dynamics and constraints) is suitable for describing both human and humanoid locomotion with appropriate parameters. We present and apply an inverse optimal control approach to identify optimality criteria based on human motion capture experiments. The identified optimal strategy is then transferred to a humanoid robot template model for gait generation by solving an optimal control problem, which takes into account the properties of the robot and differences in the environment. The results of this step are the center-of-mass trajectory, the foot trajectories, the torso orientation, and the single and double support phase durations for a sequence of steps, allowing the humanoid robot to walk within a new environment. In a previous paper, we have already presented one computational cycle (from motion capture data to an optimized robot template motion) for the example of walking over irregular stepping stones with the aim of transferring the motion to two very different humanoid robots (iCub@Heidelberg and HRP-2@LAAS). This study represents an extension, containing an entirely new part on the transfer of the optimized template motion to the iCub robot by means of inverse kinematics in a dynamic simulation environment and also on the real robot.