Miracle-dz/UniFAR-FTUs huggingface dataset:
Kinematics of the Pelvis, Torso, and Lower Limb During Obstacle Negotiation While Under Temporal Constraints

Biomechanics of unobstructed locomotion consists of synchronized complex movements of the pelvis, torso, and lower limbs. These movement patterns become more complex as individuals encounter obstacles or negotiate uneven terrain. To date, limited research has explored how specifically the pelvis, torso, and lower limb segments relate to obstacle negotiation of varying sized objects combined with temporal constraints to perform the task. Understanding pelvis and adjoining segment movements during object negotiation will provide necessary information in identifying abnormal mechanics and potential fall risk characteristics in balance compromised patient populations. In this prospective cohort study, we aimed to compare pelvic, torso, and lower limb kinematics during unobstructed locomotion with obstacle negotiation of varying heights. Ten healthy young adults (7 females and 3 males, mean age 28.4 ± 4.1 years, mean body mass index 22.5 ± 3.6 kg/m2) enrolled in this study. Analysis of within‐subject differences revealed a significant increase in sagittal (posterior tilt) and frontal (ipsilateral hike) plane pelvic angular displacement and higher sagittal plane posterior torso lean angular displacement with increased obstacle height. Furthermore, both sagittal plane hip and knee maximum joint flexion were significantly higher with increasing heights of the obstacles during negotiation. These data provide insight on segment mechanics within a non‐mobility‐impaired population; therefore, providing a baseline to understand the kinematic demands necessary for safe and effective gait in mobility‐compromised populations. Anat Rec, 300:732–738, 2017. © 2017 Wiley Periodicals, Inc.
MK2 and ETV1 Are Prognostic Factors in Esophageal Adenocarcinomas

Background. Esophageal cancer is ranked in the top ten of diagnosed tumors worldwide. Even though improvements in survival could be noticed over the last years, prognosis remains poor. ETS translocation variant 1 (ETV1) is a member of a family of transcription factors and is phosphorylated by mitogen-activated protein kinase (MAPK)-activated protein kinase 2 (MK2). Aim of this study was to evaluate the prognostic role of MK2 and ETV1 in esophageal cancer. Methods. Consecutive patients that underwent surgical resection at the department of surgery at the Medical University of Vienna between 1991 and 2012 were included into this study. After microscopic analysis, tissue micro arrays (TMAs) were created and immunohistochemistry was performed with antibodies against MK2 and ETV1. Results. 323 patients were included in this study. Clinical data was achieved from a prospective patient data base. Nuclear overexpression of MK2 was observed in 143 (44.3%) cases for nuclear staining and in 142 (44.0%) cases a cytoplasmic overexpression of MK2 was observed. Nuclear and cytoplasmic ETV1 overexpression was detected in 20 cases (6.2%) and 30 cases (9.3%), respectively. In univariate survival analysis, cMK2 and nETV1 were found to be significantly associated with patients' overall survival. Whereas overexpression of cMK2 was associated with shorter, nETV1 was associated with longer overall survival. In multivariate survival analysis, both cMK2 and nETV1 were found to be independent prognostic factors for the subgroup of EAC as well. Discussion. Expression of MK2 and ETV1 are prognostic factors in patients, with esophageal adenocarcinoma.
Disinformation in Multimedia Annotation: Misleading Metadata Detection on YouTube

Popularity of online videos is increasing at a rapid rate. Not only the users can access these videos online, but they can also upload video content on platforms like YouTube and Myspace. These videos are indexed by user generated multimedia annotation, also known as metadata, which is usually rich contextual information added by users about the content of the videos to facilitate access to their videos. Metadata plays a crucial role in techniques for video search and retrieval. However, this freedom of choosing annotation causes some uploaders to provide additional tags which are not even related to the content of the videos. Therefore, it is essential to verify the relevance of user-generated tags with the content of the video. Given the sheer volume of video content uploaded everyday, manual tag validation can be a highly labor intensive task. In this paper, we propose a method to automatically analyze user generated tags against video content to identify relevance of these tags and to detect irrelevant and misleading metadata for online videos. Our contributions are three-fold: First, we study nature of user-assigned tags and characterize them in two categories-generic and specific tags. Second, we propose a novel hierarchical graph based approach to identify tags which are relevant to content of the video. Third, we present a way to use user-generated comments for multimedia annotation verification. We demonstrate results of our method and evaluation on 300 YouTube videos for three different categories. The results show that we are able to identify relevant tags with average recall of 0.813 and average precision of 0.97.
Blood Glucose Levels of Subelite Athletes During 6 Days of Free Living

Background: Continuous glucose monitoring (CGM) devices, with their 1-5 min measurement interval, allow blood glucose (BG) concentration dynamics to be captured more frequently and less invasively than traditional BG measures. One cohort CGM could provide insight is athletes. This study investigates what impact their heightened energy expenditure and dietary intake may have on their ability to achieve optimal BG. Methods: Ten subelite athletes (resting HR<60 bpm, training>6 hrs per week) were recruited. Two Ipro2 CGM devices (Medtronic Minimed, Northridge, CA) were inserted into the abdomen and remained in place for ~6 days. Time in band was calculated as the percentage of CGM BG measurements with in the 4.0-6.0 mmol/L. Fasting glucose was calculated using CGM calibration BG measurements and postprandial glucose response was also calculated using the CGM values. Results: 4/10 athletes studied spent more than 70% of the total monitoring time above 6.0 mmol/L even with the 2-hour period after meals is excluded. Fasting BG was also in the ADA defined prediabetes range for 3/10 athletes. Only 1 participant spent substantial time below 4.0 mmol/L which was largely due to significantly lower energy intake compared to recommendations. Conclusions: Contrary to expectations high BG appears to be more of a concern for athletes then low BG even in those with the highest energy expenditure and consuming below the recommended carbohydrate intake. This study warrants further investigation on the recommended diets and the BG of athletes to better determine the causes and impact of this hyperglycemia on overall athlete health.
Flexible Retrieval: When True Inferences Produce False Memories

Episodic memory involves flexible retrieval processes that allow us to link together distinct episodes, make novel inferences across overlapping events, and recombine elements of past experiences when imagining future events. However, the same flexible retrieval and recombination processes that underpin these adaptive functions may also leave memory prone to error or distortion, such as source misattributions in which details of one event are mistakenly attributed to another related event. To determine whether the same recombination-related retrieval mechanism supports both successful inference and source memory errors, we developed a modified version of an associative inference paradigm in which participants encoded everyday scenes comprised of people, objects, and other contextual details. These scenes contained overlapping elements (AB, BC) that could later be linked to support novel inferential retrieval regarding elements that had not appeared together previously (AC). Our critical experimental manipulation concerned whether contextual details were probed before or after the associative inference test, thereby allowing us to assess whether (a) false memories increased for successful versus unsuccessful inferences, and (b) any such effects were specific to after compared with before participants received the inference test. In each of 4 experiments that used variants of this paradigm, participants were more susceptible to false memories for contextual details after successful than unsuccessful inferential retrieval, but only when contextual details were probed after the associative inference test. These results suggest that the retrieval-mediated recombination mechanism that underlies associative inference also contributes to source misattributions that result from combining elements of distinct episodes.
Granger-causal Attentive Mixtures of Experts

Several methods have recently been proposed to detect salient input features for outputs of neural networks. Those methods offer a qualitative glimpse at feature importance, but they fall short of providing quantifiable attributions that can be compared across decisions and measures of the expected quality of their explanations. To address these shortcomings, we present an attentive mixture of experts (AME) that couples attentive gating with a Granger-causal objective to jointly produce accurate predictions as well as measures of feature importance. We demonstrate the utility of AMEs by determining factors driving demand for medical prescriptions, comparing predictive features for Parkinson's disease and pinpointing discriminatory genes across cancer types.
The Guidance of Visual Search by Shape Features and Shape Configurations

Representations of target features (attentional templates) guide attentional object selection during visual search. In many search tasks, targets objects are defined not by a single feature but by the spatial configuration of their component shapes. We used electrophysiological markers of attentional selection processes to determine whether the guidance of shape configuration search is entirely part-based or sensitive to the spatial relationship between shape features. Participants searched for targets defined by the spatial arrangement of two shape components (e.g., hourglass above circle). N2pc components were triggered not only by targets but also by partially matching distractors with one target shape (e.g., hourglass above hexagon) and by distractors that contained both target shapes in the reverse arrangement (e.g., circle above hourglass), in line with part-based attentional control. Target N2pc components were delayed when a reverse distractor was present on the opposite side of the same display, suggesting that early shape-specific attentional guidance processes could not distinguish between targets and reverse distractors. The control of attention then became sensitive to spatial configuration, which resulted in a stronger attentional bias for target objects relative to reverse and partially matching distractors. Results demonstrate that search for target objects defined by the spatial arrangement of their component shapes is initially controlled in a feature-based fashion but can later be guided by templates for spatial configurations.
DP-GAN: Diversity-Promoting Generative Adversarial Network for Generating Informative and Diversified Text

Existing text generation methods tend to produce repeated and "boring" expressions. To tackle this problem, we propose a new text generation model, called Diversity-Promoting Generative Adversarial Network (DP-GAN). The proposed model assigns low reward for repeated text and high reward for "novel" text, encouraging the generator to produce diverse and informative text. Moreover, we propose a novel language-model based discriminator, which can better distinguish novel text from repeated text without the saturation problem compared with existing classifier-based discriminators. The experimental results on review generation and dialogue generation tasks demonstrate that our method can generate substantially more diverse and informative text than existing baseline methods. The code is available at this https URL
Sex differences in obesity and cognitive function in a cognitively normal aging Chinese Han population

Background Sex differences in Alzheimer’s disease and mild cognitive impairment have been well recognized. However, sex differences in cognitive function and obesity in cognitively normal aging Chinese Han population have not attracted much attention. Objective The aim of this study was to investigate the relationship between sex, obesity, and cognitive function in an elderly Chinese population with normal cognitive function. Subjects and methods A total of 228 cognitively normal aging participants (males/females =93/135) entered this study. Their general demographic information (sex, age, and education) was collected by standardized questionnaire. Apolipoprotein E (APOE) genotype and serum lipid levels were measured. The Montreal Cognitive Assessment (MoCA) was used to assess participants’ cognitive function. Results The prevalence of obesity in elderly women (18/133, 13.5%) was significantly higher than that in men (5/92, 5.4%, P=0.009). Regression analyses showed that obesity was associated with drinking alcohol (OR =13.695, P=0.045) and triglyceride (OR =1.436, P=0.048) in women and limited to low-density lipoprotein (OR =11.829, P=0.023) in men. Women performed worse on the naming score for MoCA than men (P<0.01). Stepwise linear regression analysis showed that education (t=3.689, P<0.001) and smoking (t=2.031, P=0.045) were related to the score of naming in female, while high-density lipoprotein (t=−2.077, P=0.041) was related to the score of naming in male; however, no correlation was found between body mass index and cognitive function in both male and female (P>0.05). Conclusion Our finding suggests that there are significant sex differences in obesity and specific cognitive domains in aging Chinese Han population with normal cognitive function.
Research and Application of Squeeze Cast Brake Pump for Automobile

According to the structure and property of the brake pump used on automobile, two squeeze casting technologies are studied by using one set of squeezing mold in this paper. The best mold structure and technological parameters are determined and simplified, and the hydraulic system for the side oil cylinder is designed based on the study result. It is shown by investigating the microstructure of the squeeze cast Al alloy brake pump that the squeezing casting can obviously refine the eutectic structure and the primary phases (primary α Al or Si phase) of Al alloy, and improve the morphology and distribution of the precipitated inter metal compound phases.
Impact of Relational Coordination on Nurse Job Satisfaction, Work Engagement and Burnout: Achieving the Quadruple Aim

AIM To explore how relational coordination, known to enhance quality and efficiency outcomes for patients and hospitals, impacts direct care nurse outcomes such as burnout, work engagement, and job satisfaction, addressing the “Quadruple Aim,” to improve the experience of providing care. BACKGROUND Hospitals are complex organizations in which multiple providers work interdependently, under conditions of uncertainty and time constraints, to deliver safe quality care despite differences in specialization, training, and status. Relational coordination—communicating and relating for the purpose of task integration—is known to improve quality, safety, and efficiency under these conditions, but less is known about its impact on the well-being of direct care providers themselves. METHODS Surveys measuring relational coordination among nurses and other types of providers as well as job-related outcomes in 5 acute care community hospitals were completed by direct care RNs. RESULTS Relational coordination was significantly related to increased job satisfaction, increased work engagement, and reduced burnout. CONCLUSIONS Relational coordination contributes to the well-being of direct care nurses, addressing the Quadruple Aim by improving the experience of providing care.
Involvement of Conserved Amino Acids in the C-Terminal Region of LINE-1 ORF2p in Retrotransposition

Long interspersed element 1 (L1) is the only currently active autonomous retroelement in the human genome. Along with the parasitic SVA and short interspersed element Alu, L1 is the source of DNA damage induced by retrotransposition: a copy-and-paste process that has the potential to disrupt gene function and cause human disease. The retrotransposition process is dependent upon the ORF2 protein (ORF2p). However, it is unknown whether most of the protein is important for retrotransposition. In particular, other than the Cys motif, the C terminus of the protein has not been intensely examined in the context of retrotransposition. Using evolutionary analysis and the Alu retrotransposition assay, we sought to identify additional amino acids in the C terminus important for retrotransposition. Here, we demonstrate that Gal4-tagged and untagged C-terminally truncated ORF2p fragments possess residual potential to drive Alu retrotransposition. Using sight-directed mutagenesis we identify that while the Y1180 amino acid is important for ORF2p- and L1-driven Alu retrotransposition, a mutation at this position improves L1 retrotransposition. Even though the mechanism of the contribution of Y1180 to Alu and L1 mobilization remains unknown, experimental evidence rules out its direct involvement in the ability of the ORF2p reverse transcriptase to generate complementary DNA. Additionally, our data support that ORF2p amino acids 1180 and 1250–1262 may be involved in the reported ORF1p-mediated increase in ORF2p-driven Alu retrotransposition.
Learning-based time-sensitive re-ranking for web search

To model time-dependent user intent for Web search, this paper proposes a novel method using machine learning techniques to exploit temporal features for effective time-sensitive search result re-ranking. We propose models to incorporate users' click through information for queries that are seen in the training data, and then further extend the model to deal with unseen queries considering the relationship between queries. Experiment shows significant improvement on search result ranking over original search outputs.
Poly(lactic-co-glycolic acid)-loaded nanoparticles of betulinic acid for improved treatment of hepatic cancer: characterization, in vitro and in vivo evaluations

Purpose The application of betulinic acid (B), a potent antineoplastic agent, is limited due to poor bioavailability, short plasma half-life and inappropriate tissue distribution. Thus, we aimed to prepare novel 50:50 poly(lactic-co-glycolic acid) (PLGA)-loaded B nanoparticles (BNP) and to compare its anti-hepatocellular carcinoma (HCC) activity with parent B. Methods BNP were synthesized and characterized using different methods such as scanning electron microscopy (SEM), fourier-transform infrared (FTIR) spectrometry and particle size analyses. Particle size of BNP was optimized through the application of the stabilizer, polyvinyl alcohol (PVA). The anti-HCC response was evaluated through in vitro cell line study using Hep-G2 cells, confocal microscopy, in vivo oral pharmacokinetics and animal studies. Further, quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis was conducted to observe the changes in the expression of specific genes. Results Particle size of BNP was optimized through the application of the stabilizer, polyvinyl alcohol. Physicochemical characterization exhibited particle size of 257.1 nm with zeta potential −0.170 mV (optimized batch B, BNP). SEM and FTIR analyses of BNP showed that cylindrical particles of B converted to spherical particles in BNP and there were no interaction between B and used polymers. The release study of optimized BNP was highest (≥80%) than any other formulation. Later, in vitro cell culture analysis using Hep-G2 cells and confocal microscopy studies revealed that BNP had the highest inhibition and penetration properties than parent B. Oral pharmacokinetics studies using albino Wistar rats at single 100 mg dose again exhibited BNP had the higher 50% of plasma concentration (t1/2), a higher maximum plasma concentration (Cmax) and took longer to reach the maximum plasma concentration (Tmax) than parent B. Next, our in vivo study using nitrosodiethyl amine (NDEA)-induced HCC model documented BNP decreased in number of nodules, restored body weight, oxidative stress parameters, liver marker enzymes and histological architecture than parent B. Lastly, qRT-PCR studies further demonstrated that anti-HCC properties of BNP may be due to over expression of antiapoptotic caspases i.e., caspase 3 and 8. Conclusion The prepared BNP showed a better therapeutic response against HCC and could be attributed as future candidate molecule for HCC treatment.
Running Distributed and Dynamic IoT Choreographies

IoT systems are growing larger and larger and are becoming suitable for basic automationtasks. One of the features IoT automation systems can provide is dealing with a dynamicsystem – devices leaving and joining the system during operation. Additionally, IoT automation systems can operate in adistributed manner. Current commercial automation systems have difficulty providing these features. Integrating new devices into an automation system takes manual intervention. Additionally, automation systems also require central entities to orchestrate the operation of participants. With smarter sensors and actuators, we can move control operations into software deployed on a decentralized network of devices, and provide supportfor dynamic systems. In this paper, we present a framework for automation systems that demonstrates these two properties (distributed and dynamic). We represent applications as semantically described data flows that are run decentrally on participating devices and connected at runtime via rules. This allows integrating new devices into applications without manual interaction and removes central controllers from the equation. This approach provides similar features to current automation systems (central engineering, multiple instantiation of applications), but enables distributed and dynamic operation. We demonstrate adequate performance of the systemvia a quantitative evaluation.
Uplink Channel Estimation and Data Transmission in Millimeter-Wave CRAN With Lens Antenna Arrays

Millimeter-wave (mmWave) communication and network densification hold great promise for achieving high-rate communication in next-generation wireless networks. Cloud radio access network (CRAN), in which low-complexity remote radio heads (RRHs) coordinated by a central unit (CU) are deployed to serve users in a distributed manner, is a cost-effective solution to achieve network densification. However, when operating over a large bandwidth in the mmWave frequencies, the digital fronthaul links in a CRAN would be easily saturated by the large amount of sampled and quantized signals to be transferred between the RRHs and the CU. To tackle this challenge, we propose in this paper a new architecture for the mmWave-based CRAN with advanced lens antenna arrays at the RRHs. Due to the energy focusing property, the lens antenna arrays are effective in exploiting the angular sparsity of mmWave channels, and thus help in substantially reducing the fronthaul rate and simplifying the signal processing at the multi-antenna RRHs and the CU, even when the channels are frequency-selective. We consider the uplink transmission in a mmWave CRAN with lens antenna arrays and propose a low-complexity quantization bit allocation scheme for multiple antennas at each RRH to meet the given fronthaul rate constraint. Furthermore, we propose a channel estimation technique that exploits the energy focusing property of the lens array and can be implemented at the CU with low complexity. Finally, we compare the proposed mmWave CRAN using lens antenna arrays with a conventional CRAN using uniform planar arrays at the RRHs, and show that the proposed design achieves significant throughput gains, yet with much lower complexity.