Miracle-dz/UniFAR-FTUs huggingface dataset:
Uterine RGS2 expression is regulated by exogenous estrogen and progesterone in ovariectomized mice, and downregulation of RGS2 expression in artificial decidualized ESCs inhibits trophoblast spreading in vitro

Embryo implantation is a complicated event that relies on two critical factors: the competent blastocyst and the receptive uterus. Successful implantation results from tight coordination of these two factors. The maternal hormone environment of the uterus and molecular cross‐talk between the embryo and uterine tissue play pivotal roles in implantation. Here we showed that regulator of G‐protein signaling 2 (RGS2), a member of ubiquitous family of proteins that regulate G‐protein activation, plays an important role in embryo implantation by interfering in the cross‐talk between the embryo and uterine tissue. RGS2 expression increased during the implantation process, and was higher in the implant site than at the nonimplantation site. Meanwhile, ovariectomized (OVX) mice exhibited higher expression of RGS2 in the uterus. Exogenous 17β‐estradiol and progesterone in OVX mice downregulated the expression of RGS2. Treatment with exogenous 17β‐estradiol alone caused uterine RGS2 messenger RNA levels of OVX mice to return to those of normal female mice; when these mice were treated with progesterone or 17β‐estradiol plus progesterone, RGS2 levels rose. Downregulation of Rgs2 by small interfering RNA in an in vitro coculture system of decidualized endometrial stromal cells and blastocysts inhibited blastocyst outgrowth by restricting trophoblast spreading, suggesting a mechanism by which RGS2 regulates embryo implantation.
Mucosal adhesion and anti-inflammatory effects of Lactobacillus rhamnosus GG in the human colonic mucosa: A proof-of-concept study

AIM To investigate the adhesion and anti-inflammatory effects of Lactobacillus rhamnosus GG (LGG) in the colonic mucosa of healthy and ulcerative colitis (UC) patients, both in vivo and ex vivo in an organ culture model. METHODS For the ex vivo experiment, a total of 98 patients (68 UC patients and 30 normal subjects) were included. Endoscopic biopsies were collected and incubated with and without LGG or LGG-conditioned media to evaluate the mucosal adhesion and anti-inflammatory effects [reduction of tumor necrosis factor alpha (TNFα) and interleukin (IL)-17 expression] of the bacteria, and extraction of DNA and RNA for quantification by real-time (RT)-PCR occurred after the incubation. A dose-response study was performed by incubating biopsies at “regular”, double and 5 times higher doses of LGG. For the in vivo experiment, a total of 42 patients (20 UC patients and 22 normal controls) were included. Biopsies were taken from the colons of normal subjects who consumed a commercial formulation of LGG for 7 d prior to the colonoscopy, and the adhesion of the bacteria to the colonic mucosa was evaluated by RT-PCR and compared with that of control biopsies from patients who did not consume the formulation. LGG adhesion and TNFα and IL-17 expression were compared between UC patients who consumed a regular or double dose of LGG supplementation prior to colonoscopy. RESULTS In the ex vivo experiment, LGG showed consistent adhesion to the distal and proximal colon in normal subjects and UC patients, with a trend towards higher concentrations in the distal colon, and in UC patients, adhesion was similar in biopsies with active and quiescent inflammation. In addition, bioptic samples from UC patients incubated with LGG conditioned media (CM) showed reduced expression of TNFα and IL-17 compared with the corresponding expression in controls (P < 0.05). Incubation with a double dose of LGG increased mucosal adhesion and the anti-inflammatory effects (P < 0.05). In the in vivo experiment, LGG was detectable only in the colon of patients who consumed the LGG formulation, and bowel cleansing did not affect LGG adhesion. UC patients who consumed the double LGG dose had increased mucosal concentrations of the bacteria and reduced TNFα and IL-17 expression compared with patients who consumed the regular dose (48% and 40% reduction, respectively, P < 0.05). CONCLUSION In an ex vivo organ culture model, LGG showed consistent adhesion and anti-inflammatory effects. Colonization by LGG after consumption for a week was demonstrated in vivo in the human colon. Increasing the administered dose increased the adhesion and effectiveness of the bacteria. For the first time, we demonstrated that LGG effectively adheres to the colonic mucosa and exerts anti-inflammatory effects, both ex vivo and in vivo.
Microsphere rapid positioning and contour evaluation in a microvisual environment

Abstract. In microvision, the efficiency of image analysis is reduced by low signal-to-noise ratios, large amounts of data, and target over-concentration. Processing speeds can be optimized by introducing a biomimetic visual attention mechanism; however, the most mature attention mechanisms are not fully applicable to microvision environments. They rely on pixels, and this reliance significantly limits processing speeds. Therefore, we propose a fast attention mechanism based on the visual-entropy value and a method of evaluating the difference-entropy convergence of the target contour. We have performed a theoretical analysis, a large quantity of data sampling, and comparisons of multiple experiments. Given a fixed field of view, the visual-entropy attention mechanism can quickly locate the target area, and thus is highly suitable to a microvision environment. The difference-entropy convergence evaluation method can effectively distinguish a special, damaged target.
Patients’ perceived needs for medical services for non-specific low back pain: A systematic scoping review

Background An improved understanding of patients’ perceived needs for medical services for low back pain (LBP) will enable healthcare providers to better align service provision with patient expectations, thus improving patient and health care system outcomes. Thus, we aimed to identify the existing literature regarding patients’ perceived needs for medical services for LBP. Methods A systematic scoping review was performed of publications identified from MEDLINE, EMBASE, CINAHL and PsycINFO (1990–2016). Descriptive data regarding each study, its design and methodology were extracted and risk of bias assessed. Aggregates of patients’ perceived needs for medical services for LBP were categorised. Results 50 studies (35 qualitative, 14 quantitative and 1 mixed-methods study) from 1829 were relevant. Four areas of perceived need emerged: (1) Patients with LBP sought healthcare from medical practitioners to obtain a diagnosis, receive management options, sickness certification and legitimation for their LBP. However, there was dissatisfaction with the cursory and superficial approach of care. (2) Patients had concerns about pharmacotherapy, with few studies reporting on patients’ preferences for medications. (3) Of the few studies which examined the patients’ perceived need of invasive therapies, these found that patients avoided injections and surgeries (4) Patients desired spinal imaging for diagnostic purposes and legitimation of symptoms. Conclusions Across many different patient populations with data obtained from a variety of study designs, common themes emerged which highlighted areas of patient dissatisfaction with the medical management of LBP, in particular, the superficial approach to care perceived by patients and concerns regarding pharmacotherapy. Patients perceive unmet needs from medical services, including the need to obtain a diagnosis, the desire for pain control and the preference for spinal imaging. These issues need to be considered in developing approaches for the management of LBP in order to improve patient outcomes.
Reduction of Open-Circuit DC-Winding-Induced Voltage in Wound Field Switched Flux Machines by Skewing

In this paper, the open-circuit dc-winding-induced voltage in a wound field switched flux (WFSFs) machines is analyzed. The phenomenon of open-circuit dc-winding-induced voltage is illustrated and the mechanism is explained. Rotor skewing is proposed to reduce the open-circuit dc-winding-induced voltage, and the optimal skewing angle is analytically derived based on the analytically deduced harmonic orders of the open-circuit dc-winding-induced voltage. Finite-element (FE) analyses show that the open-circuit dc-winding-induced voltages in the analyzed 12-stator-pole partitioned stator WFSF machines having 10-, 11-, 13-, and 14-rotor-pole rotors can be effectively reduced by >94%, while the ac-winding phase-fundamental back-EMFs can be maintained by >95%. Twelve/ten-stator/rotor-pole prototypes with skewed and nonskewed rotors are built and tested to verify the analytical and FE results.
The utility/futility of medications for neuropathic pain – an observational study

Abstract Background and aims The RELIEF (Real Life) study by AstraZeneca was designed as an observational study to validate a series of Patient Reported Outcome (PRO) questionnaires in a mixed population of subjects with neuropathic pain (NP) coming from diabetes, neurology and primary care clinics. This article is an analysis of a subset of the information to include the medications used and the effects of pharmacological treatment over 6 months. The RELIEF study was performed during 2010–2013. Methods Subjects were recruited from various specialty clinics and one general practice clinic across Canada. The subjects were followed for a total of 2 years with repeated documentation of their status using 10 PROs. A total of 210 of the recruited subjects were entered into the data base and analyzed. Of these, 123 had examination-verified painful diabetic neuropathy (PDN) and 87 had examination-verified post-traumatic neuropathy (PTN). To evaluate the responsiveness of the PROs to change, several time points were included and this study focusses primarily on the first 6 months. Subjects also maintained a diary to document all medications, both for pain and other medical conditions, including all doses, start dates and stop dates, that could be correlated to changes in the PRO parameters. Results RELIEF was successful in being able to correlate the validity of the PROs and this data was used for further AstraZeneca Phase 1, 2, and 3 clinical trials of NP. To our surprise, there was very little change in pain and low levels of patient satisfaction with treatment during the trial. Approximately 15% of the subjects reported improvement, 8% worsening of pain, the remainder reported pain unchanged despite the use of multiple medications at multiple doses, alone or in combination with frequent changes of medications and doses over the study. Those taking predominantly NSAIDs (COX-inhibitors) did no worse than those taking the standard recommended medications against NP. Conclusions Since this is a real-life study, it reflects the clinical utility of a variety of internationally recommended medications for the treatment of NP. In positive clinical trials of these medications in selected “ideal” subjects, the effects are not overwhelming – 30% are 50% improved on average. This study shows that in the real world the results are not nearly as positive and reflects information from non-published negative clinical trials. Implications We still do not have very successful medications for NP. Patients probably differ in many respects from those subjects in clinical trials. This is not to negate the use of recommended medications for NP but an indication that success rates of treatment are likely to be worse than the data coming from those trials published by the pharmaceutical industry.
Emergent Dirac Gullies and Gully-Symmetry-Breaking Quantum Hall States in ABA Trilayer Graphene.

We report on quantum capacitance measurements of high quality, graphite and hexagonal boron nitride encapsulated Bernal stacked trilayer graphene devices. At zero applied magnetic field, we observe a number of electron density- and electrical displacement-tuned features in the electronic compressibility associated with changes in Fermi surface topology. At a high displacement field and low density, strong trigonal warping gives rise to three new emergent Dirac cones in each valley, which we term "gullies. " The gullies are centered around the corners of a hexagonal Brillouin zone and related by threefold rotation symmetry. At low magnetic fields of B=1.25 T, the gullies manifest as a change in the degeneracy of the Landau levels from two to three. Weak incompressible states are also observed at integer filling within these triplet Landau levels, which a Hartree-Fock analysis indicates are associated with Coulomb-driven nematic phases that spontaneously break rotation symmetry.
Real-time contrast preserving decolorization

Decolorization, also known as color-to-gray, plays a vital role in digital printing, monotone e-paper display and single channel image processing. While recent research focuses on retaining as much as possible meaningful visual features and color contrast, less attention has been paid to the speed issue of the conversion. Consequently, the resulting decolorization methods are typically orders of magnitude slower than standard procedures such as matlab rgb2gray function, which largely hinders their practical use.
Composition of mappings given by embedded dependencies

Composition of mappings between schemas is essential to support schema evolution, data exchange, data integration, and other data management tasks. In many applications, mappings are given by embedded dependencies. In this article, we study the issues involved in composing such mappings. Our algorithms and results extend those of Fagin et al. [2004], who studied the composition of mappings given by several kinds of constraints. In particular, they proved that full source-to-target tuple-generating dependencies (tgds) are closed under composition, but embedded source-to-target tgds are not. They introduced a class of second-order constraints, SO tgds, that is closed under composition and has desirable properties for data exchange. We study constraints that need not be source-to-target and we concentrate on obtaining (first-order) embedded dependencies. As part of this study, we also consider full dependencies and second-order constraints that arise from Skolemizing embedded dependencies. For each of the three classes of mappings that we study, we provide: (a) an algorithm that attempts to compute the composition; and (b) sufficient conditions on the input mappings which guarantee that the algorithm will succeed. In addition, we give several negative results. In particular, we show that full and second-order dependencies that are not limited to be source-to-target are not closed under composition (for the latter, under the additional restriction that no new function symbols are introduced). Furthermore, we show that determining whether the composition can be given by these kinds of dependencies is undecidable.
High-speed switch scheduling for local-area networks

Current technology trends make it possible to build communication networks that can support high-performance distributed computing. This paper describes issues in the design of a prototype switch for an arbitrary topology point-to-point network with link speeds of up to 1 Gbit/s. The switch deals in fixed-length ATM-style cells, which it can process at a rate of 37 million cells per second. It provides high bandwidth and low latency for datagram traffic. In addition, it supports real-time traffic by providing bandwidth reservations with guaranteed latency bounds. The key to the switch's operation is a technique called parallel iterative matching, which can quickly identify a set of conflict-free cells for transmission in a time slot. Bandwidth reservations are accommodated in the switch by building a fixed schedule for transporting cells from reserved flows across the switch; parallel iterative matching can fill unused slots with datagram traffic. Finally, we note that parallel iterative matching may not allocate bandwidth fairly among flows of datagram traffic. We describe a technique called statistical matching, which can be used to ensure fairness at the switch and to support applications with rapidly changing needs for guaranteed bandwidth.
Parallel Algorithms for Multidimensional Data Streams Analysis with Tensor Subspace Models

In this paper the parallel models for processing of the multi-dimensional data streams are discussed. Stream analysis is performed by tensor models and a fitness measure. The method was tested on the problem of video shot detection showing good accuracy. In this paper efficient algorithms for tensor model construction and model update in the parallel processing framework are presented. Also the parallel version for the off-line stream processing is proposed.
Towards understanding modern web traffic

As Web sites move from relatively static displays of simple pages to rich media applications with heavy client-side interaction, the nature of the resulting Web traffic changes as well. Understanding this change is necessary in order to improve response time, evaluate caching effectiveness, and design intermediary systems, such as firewalls, security analyzers, and reporting/management systems. Unfortunately, we have little understanding of the underlying nature of today's Web traffic. In this paper, we analyze five years (2006-2010) of real Web traffic from a globally-distributed proxy system, which captures the browsing behavior of over 70,000 daily users from 187 countries. Using this data set, we examine major changes in Web traffic characteristics that occurred during this period. We also present a new Web page analysis algorithm that is better suited for modern Web page interactions by grouping requests into streams and exploiting the structure of the pages. Using this algorithm, we analyze various aspects of page-level changes, and characterize modern Web pages. Finally, we investigate the redundancy of this traffic, using both traditional object-level caching as well as content-based approaches.
Mobile Data Science: Towards Understanding Data-Driven Intelligent Mobile Applications

Due to the popularity of smart mobile phones and context-aware technology, various contextual data relevant to users' diverse activities with mobile phones is available around us. This enables the study on mobile phone data and context-awareness in computing, for the purpose of building data-driven intelligent mobile applications, not only on a single device but also in a distributed environment for the benefit of end users. Based on the availability of mobile phone data, and the usefulness of data-driven applications, in this paper, we discuss about mobile data science that involves in collecting the mobile phone data from various sources and building data-driven models using machine learning techniques, in order to make dynamic decisions intelligently in various day-to-day situations of the users. For this, we first discuss the fundamental concepts and the potentiality of mobile data science to build intelligent applications. We also highlight the key elements and explain various key modules involving in the process of mobile data science. This article is the first in the field to draw a big picture, and thinking about mobile data science, and it's potentiality in developing various data-driven intelligent mobile applications. We believe this study will help both the researchers and application developers for building smart data-driven mobile applications, to assist the end mobile phone users in their daily activities.
Vitamin D supplementation during pregnancy and the risk of wheezing in offspring: a systematic review and dose-response meta-analysis

Abstract Background: In the past few years, growing evidence supports a preventive role of vitamin D supplementation during pregnancy for wheezing or asthma in offspring. However, the optimal dose of vitamin D intake is unclear. We conducted a meta-analysis to examine the linear and nonlinear dose-response pattern of vitamin D intake during pregnancy and asthma or wheezing in offspring. Questions/purposes: The purpose of this study was to answer the following question: Which dose of vitamin D is more effective in preventing wheezing in offspring? Method: We identified relevant studies by searching PubMed, EMBASE and CENTRAL up to December 2017 and by hand-searching reference lists. Meta-analysis and subgroup analysis were performed. Fixed or random effects model linear trends analyses were conducted based on the heterogeneity test. Then, if the data did not show linear trends, we considered a nonlinear trend analysis instead. Results: A total of 6068 participants were included in the study. Our analysis showed an inverse relationship between the intake of vitamin D during pregnancy and the occurrence of wheezing in offspring (pooled OR = 0.68, 95% CI = 0.55–0.83, I2 = 24%, Z statistic = 3.64, p < 0.01). We found a nonlinear U-shaped association between vitamin D supplementation during pregnancy and asthma or wheezing in offspring, with the lowest risk at approximately 800 IU/d. Publication bias was shown in a funnel plot without Egger’s test. Conclusions: Vitamin D intake during pregnancy is inversely related to wheezing or asthma in offspring. Furthermore, the trend analysis indicates that offspring may benefit from approximately 800 IU/d vitamin D intake during pregnancy.
TrafficPredict: Trajectory Prediction for Heterogeneous Traffic-Agents

To safely and efficiently navigate in complex urban traffic, autonomous vehicles must make responsible predictions in relation to surrounding traffic-agents (vehicles, bicycles, pedestrians, etc.). A challenging and critical task is to explore the movement patterns of different traffic-agents and predict their future trajectories accurately to help the autonomous vehicle make reasonable navigation decision. To solve this problem, we propose a long short-term memory-based (LSTM-based) realtime traffic prediction algorithm, TrafficPredict. Our approach uses an instance layer to learn instances’ movements and interactions and has a category layer to learn the similarities of instances belonging to the same type to refine the prediction. In order to evaluate its performance, we collected trajectory datasets in a large city consisting of varying conditions and traffic densities. The dataset includes many challenging scenarios where vehicles, bicycles, and pedestrians move among one another. We evaluate the performance of TrafficPredict on our new dataset and highlight its higher accuracy for trajectory prediction by comparing with prior prediction methods.