nils-herrmann/clean_scirepeval huggingface dataset:
Obesity is associated with macrophage accumulation in adipose tissue.

Obesity alters adipose tissue metabolic and endocrine function and leads to an increased release of fatty acids, hormones, and proinflammatory molecules that contribute to obesity associated complications. To further characterize the changes that occur in adipose tissue with increasing adiposity, we profiled transcript expression in perigonadal adipose tissue from groups of mice in which adiposity varied due to sex, diet, and the obesity-related mutations agouti (Ay) and obese (Lepob). We found that the expression of 1,304 transcripts correlated significantly with body mass. Of the 100 most significantly correlated genes, 30% encoded proteins that are characteristic of macrophages and are positively correlated with body mass. Immunohistochemical analysis of perigonadal, perirenal, mesenteric, and subcutaneous adipose tissue revealed that the percentage of cells expressing the macrophage marker F4/80 (F4/80+) was significantly and positively correlated with both adipocyte size and body mass. Similar relationships were found in human subcutaneous adipose tissue stained for the macrophage antigen CD68. Bone marrow transplant studies and quantitation of macrophage number in adipose tissue from macrophage-deficient (Csf1op/op) mice suggest that these F4/80+ cells are CSF-1 dependent, bone marrow-derived adipose tissue macrophages. Expression analysis of macrophage and nonmacrophage cell populations isolated from adipose tissue demonstrates that adipose tissue macrophages are responsible for almost all adipose tissue TNF-alpha expression and significant amounts of iNOS and IL-6 expression. Adipose tissue macrophage numbers increase in obesity and participate in inflammatory pathways that are activated in adipose tissues of obese individuals.
Egovernment and web accessibility in South America

The number of e-government websites has increased greatly in recent years. Many countries have laws to ensure that e-government sites satisfy web accessibility requirements. The objective of web accessibility is to ensure that people with disabilities can access websites just like everyone else. However, laws that enforce web accessibility do not automatically guarantee compliance: e-government websites are not always prepared to provide a correct service to persons with disabilities. This paper analyses the accessibility of a group of e-government websites of all South American countries and Spain. Three official websites from each country has been analysed: the government, the Parliament and the Senate websites. Different automatic evaluation tools have been used to perform the analysis. The preliminary results of our research show that the majority of e-government websites do not provide adequate levels of web accessibility.
Syntax-based Alignment of Multiple Translations: Extracting Paraphrases and Generating New Sentences

We describe a syntax-based algorithm that automatically builds Finite State Automata (word lattices) from semantically equivalent translation sets. These FSAs are good representations of paraphrases. They can be used to extract lexical and syntactic paraphrase pairs and to generate new, unseen sentences that express the same meaning as the sentences in the input sets. Our FSAs can also predict the correctness of alternative semantic renderings, which may be used to evaluate the quality of translations.
Location and Time Aware Social Collaborative Retrieval for New Successive Point-of-Interest Recommendation

In location-based social networks (LBSNs), new successive point-of-interest (POI) recommendation is a newly formulated task which tries to regard the POI a user currently visits as his POI-related query and recommend new POIs the user has not visited before. While carefully designed methods are proposed to solve this problem, they ignore the essence of the task which involves retrieval and recommendation problem simultaneously and fail to employ the social relations or temporal information adequately to improve the results.
 In order to solve this problem, we propose a new model called location and time aware social collaborative retrieval model (LTSCR), which has two distinct advantages: (1) it models the location, time, and social information simultaneously for the successive POI recommendation task; (2) it efficiently utilizes the merits of the collaborative retrieval model which leverages weighted approximately ranked pairwise (WARP) loss for achieving better top-n ranking results, just as the new successive POI recommendation task needs. We conducted some comprehensive experiments on publicly available datasets and demonstrate the power of the proposed method, with 46.6% growth in Precision@5 and 47.3% improvement in Recall@5 over the best previous method.
Reward-estimation variance elimination in sequential decision processes

Policy gradient methods are very attractive in reinforcement learning due to their model-free nature and convergence guarantees. These methods, however, suffer from high variance in gradient estimation, resulting in poor sample efficiency. To mitigate this issue, a number of variance-reduction approaches have been proposed. Unfortunately, in the challenging problems with delayed rewards, these approaches either bring a relatively modest improvement or do reduce variance at expense of introducing a bias and undermining convergence. The unbiased methods of gradient estimation, in general, only partially reduce variance, without eliminating it completely even in the limit of exact knowledge of the value functions and problem dynamics, as one might have wished. In this work we propose an unbiased method that does completely eliminate variance under some, commonly encountered, conditions. Of practical interest is the limit of deterministic dynamics and small policy stochasticity. In the case of a quadratic value function, as in linear quadratic Gaussian models, the policy randomness need not be small. We use such a model to analyze performance of the proposed variance-elimination approach and compare it with standard variancereduction methods. The core idea behind the approach is to use control variates at all future times down the trajectory. We present both a model-based and model-free formulations.
Superficial dorsal penile vein thrombosis (penile Mondor's disease)

In our center between 1992 and 1994 penile Mondor's disease (superficial dorsal penile vein thrombosis) was diagnosed in 5 patients aged 20–39 years. In all patients the thromboses were noted 24–48 hours after a prolonged sexual act with or without an intercourse. The main symptom was a cord-like thickening of the superficial veins, which were painless or slightly painful. Doppler examination of the superficial dorsal vein revealed obstruction of the vessels. In 2 patients the retroglandular plexus was also involved. Patients were treated with anti-inflammatory medications (Tenoxicam or Ibuprofen). The resolution of the thrombosis occurred uneventfully within 4–6 weeks. No recurrence or erectile dysfunction was noted in any of the patients. Penile Mondor's disease is a benign pathology of the superficial dorsal penile vein and should be taken into account in the differential diagnosis of penile pathologies.
Underactuated robot hand for dual-arm manipulation

In this paper, we propose a novel robot hand called uGRIPP (Underactuated Gripper for Power and Precision Grasp) which has underactuated fingers for dual-arm manipulation tasks. A newly designed underactuated linkage enables the robot hand to achieve not only an adaptive grasp and a pinch grasp, but also manipulation by a palm of the hand. We introduce performance of the proposed linkage by a static analysis. A prototype of the robot hand which has the proposed linkage as fingers was developed. We conducted handling experiments by using the robot hand.
Seasonal Change in Oxidative Stress Markers in Blood Plasma of Tharparkar ( Bos indicus ) and Karan Fries ( Bos indicus x Bos taurus ) Cattle under Tropical Climate

Free radical reactions are the integral part of normal metabolism. Normally, oxidation is necessary to provide energy for maintenance of cellular integrity and functions (Miller et al., 1993). In normal cellular metabolism, low to moderate ROS is generated as part of the signaling pathways, and in innate and adaptive immune response against danger signals (Martins Chaves et al., 2000). When reactive forms of oxygen are produced faster than they can be safely neutralized by antioxidant mechanisms, oxidative stress results (Sies, 1991). OxS is considered as a part of the stress response to heat exposure (Lin et al., 2006). OxS can be induced by both exogenous and endogenous factors in living organisms (Cross et al., 1998; Lesser, 2006). Animals are exposed to a wide variety International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 6 Number 2 (2017) pp. 1720-1730  http://www.ijcmas.com
Query segmentation revisited

We address the problem of query segmentation: given a keyword query, the task is to group the keywords into phrases, if possible. Previous approaches to the problem achieve reasonable segmentation performance but are tested only against a small corpus of manually segmented queries. In addition, many of the previous approaches are fairly intricate as they use expensive features and are difficult to be reimplemented.
 The main contribution of this paper is a new method for query segmentation that is easy to implement, fast, and that comes with a segmentation accuracy comparable to current state-of-the-art techniques. Our method uses only raw web n-gram frequencies and Wikipedia titles that are stored in a hash table. At the same time, we introduce a new evaluation corpus for query segmentation. With about 50,000 human-annotated queries, it is two orders of magnitude larger than the corpus being used up to now.
Ferromagnetism in freestanding MoS2 nanosheets

Freestanding MoS2 nanosheets with different sizes were prepared through a simple exfoliated method by tuning the ultrasonic time in the organic solvent. Magnetic measurement results reveal the clear room-temperature ferromagnetism for all the MoS2 nanosheets, in contrast to the pristine MoS2 in its bulk form which shows diamagnetism only. Furthermore, results indicate that the saturation magnetizations of the nanosheets increase as the size decreases. Combining the X-ray photoelectron spectroscopy, transmission electron microscopy, and electron spin resonance results, it is suggested that the observed magnetization is related to the presence of edge spins on the edges of the nanosheets. These MoS2 nanosheets may find applications in nanodevices and spintronics by controlling the edge structures.
Compact ultra-wide stopband lowpass filter using transformed stepped impedance hairpin resonator

A compact microstrip lowpass filter (LPF) with ultra-wide stopband using transformed stepped impedance hairpin resonator is proposed. The transformed resonator consists of a stepped impedance hairpin resonator and an embedded hexagon stub loaded coupled-line structure. Without enlarging the size, the embedded structure is introduced to get a broad stopband. A prototype LPF has been simulated, fabricated and measured, and the measurements are in good agreement with simulations. The implemented lowpass filter exhibits an ultra-wide stopband up to 12.01fc with a rejection level of 14 dB. In addition, the proposed filter features a size of 0.071λg× 0.103λg, where λg is the waveguide length at the cutoff frequency 1.45 GHz.
Context and behavioral processes in extinction.

This article provides a selective review and integration of the behavioral literature on Pavlovian extinction. The first part reviews evidence that extinction does not destroy the original learning, but instead generates new learning that is especially context-dependent. The second part examines insights provided by research on several related behavioral phenomena (the interference paradigms, conditioned inhibition, and inhibition despite reinforcement). The final part examines four potential causes of extinction: the discrimination of a new reinforcement rate, generalization decrement, response inhibition, and violation of a reinforcer expectation. The data are consistent with behavioral models that emphasize the role of generalization decrement and expectation violation, but would be more so if those models were expanded to better accommodate the finding that extinction involves a context-modulated form of inhibitory learning.
Detecting topic evolution in scientific literature: how can citations help?

Understanding how topics in scientific literature evolve is an interesting and important problem. Previous work simply models each paper as a bag of words and also considers the impact of authors. However, the impact of one document on another as captured by citations, one important inherent element in scientific literature, has not been considered. In this paper, we address the problem of understanding topic evolution by leveraging citations, and develop citation-aware approaches. We propose an iterative topic evolution learning framework by adapting the Latent Dirichlet Allocation model to the citation network and develop a novel inheritance topic model. We evaluate the effectiveness and efficiency of our approaches and compare with the state of the art approaches on a large collection of more than 650,000 research papers in the last 16 years and the citation network enabled by CiteSeerX. The results clearly show that citations can help to understand topic evolution better.
Comparison of text mining tools

Most of the data is in the form of text these days. While databases store only structured data, most of the data is unstructured like text documents, web pages, emails etc. Text mining is what is required if useful information needs to be extracted from tons of text. But where to begin, what are the popular tools, which techniques are used, what are the features. Beginning is always the toughest, so this paper tries to explore the tools available for text mining to help new researchers and practitioners in the field of text mining.
An Internet of Things Platform for Real-World and Digital Objects

The vision of the Internet of Things (IoT) relies on the provisioning of real-world services, which are provided by smart objects that are directly related to the physical world. A structured, machine-processible approach to provision such real-world services is needed to make heterogeneous physical objects accessible on a large scale and to integrate them with the digital world. The incorporation of observation and measurement data obtained from the physical objects with the Web data, using information processing and knowledge engineering methods, enables the construction of ”intelligent and interconnected things”. The current research mostly focuses on the communication and networking aspects between the devices that are used for sensing amd measurement of the real world objects. There is, however, relatively less effort concentrated on creating dynamic infrastructures to support integration of the data into the Web and provide unified access to such data on service and application levels. This paper presents a semantic modelling and linked data approach to create an information framework for IoT. The paper describes a platform to publish instances of the IoT related resources and entities and to link them to existing resources on the Web. The developed platform supports publication of extensible and interoperable descriptions in the form of linked data.
Feasibility Study on Plant Chili Disease Detection Using Image Processing Techniques

Producing chili is a daunting task as the plant is exposed to the attacks from various micro-organisms and bacterial diseases and pests. The symptoms of the attacks are usually distinguished through the leaves, stems or fruit inspection. This paper discusses the effective way used in performing early detection of chili disease through leaf features inspection. Leaf image is captured and processed to determine the health status of each plant. Currently the chemicals are applied to the plants periodically without considering the requirement of each plant. This technique will ensure that the chemicals only applied when the plants are detected to be effected with the diseases. The image processing techniques are used to perform hundreds of chili disease images. The plant chili disease detection through leaf image and data processing techniques is very useful and inexpensive system especially for assisting farmers in monitoring the big plantation area.
Image Steganography Using LSB and Edge – Detection Technique

217  Abstract-Steganography is the technique of hiding the fact that communication is taking place, by hiding data in other data. Many different carrier file formats can be used, but digital images are the most popular because of their frequency on the Internet. For hiding secret information in images, there exist a large variety of steganographic techniques some are more complex than others and all of them have respective strong and weak points. Steganalysis, the detection of this hidden information, is an inherently difficult problem and requires a thorough investigation so we are using " Edge detection Filter ". In this paper search how the edges of the images can be used to hiding text message in Steganography .It give the depth view of image steganography and Edge detection Filter techniques.  In this paper search how the edges of the images can be used to hiding text message in Steganography. For that gray image has been presented. In this method tried to find binary value of each character of text message and then in the next stage, tried to find dark places of gray image (black) by converting the original image to binary image for labeling each object of image by considering on 8 pixel connectivity. Then these images have been converted to RGB image in order to find dark places. Because in this way each sequence of gray color turns into RGB color and dark level of grey image is found by this way if the Gary image is very light the histogram must be changed manually to find just dark places. In the final stage each 8 pixels of dark places has been considered as a byte and binary value of each character has been put in low bit of each byte that was created manually by dark places pixels for increasing security of the main way of least Significant bit steganography. Steganalysis then used to evaluate the hiding process to ensure the data can be hidden in best possible way.
Automotive hardware development according to ISO 26262

This paper briefly explains ISO 26262, the new automotive standard for functional safety. The standard is for electrical/electronic systems mounted on series of passenger cars. In the standard, Automotive Safety Integrity Level (ASIL) is classified into four levels according to the required safety level. Each of the ASIL has its own process and steps for item development. This paper focuses on the item development at hardware level, especially for ASIL C and D. The hardware development procedure includes the calculation of single point metric and latent fault metric. Furthermore, we present overall calculation steps of controlling random hardware failure.
A six degrees of freedom haptic interface for laparoscopic training

We present the novel kinematics, workspace characterization, functional prototype and impedance control of a six degrees of freedom haptic interface designed to train surgeons for laparoscopic procedures, through virtual reality simulations. The parallel kinematics of the device is constructed by connecting a 3RRP planar parallel mechanism to a linearly actuated modified delta mechanism with a connecting link. The configuration level forward and inverse kinematics of the device assume analytic solutions, while its workspace can be shaped to enable large end-effector translations and rotations, making it well-suited for laparoscopy operations. Furthermore, the haptic interface features a low apparent inertia with high structural stiffness, thanks to its parallel kinematics with grounded actuators. A model-based open-loop impedance controller with feed-forward gravity compensation has been implemented for the device and various virtual tissue/organ stiffness levels have been rendered.
A four-band dual-polarized cavity-backed antenna on LTCC technology for 60GHz applications

In this work, we present a 4-band dual-polarized antenna designed for 8-chanel applications. Based on LTCC technology, the antenna is a patch coupled aperture with a backed cavity. Each antenna element of a designated band contains two channels through two orthogonally polarized ports. Combining four dual-polarized antenna elements under different frequency, an 8-channel antenna for 60GHz applications can be achieved. The array antenna contains 8 feeding ports, which correspond to 8 independent channels. The isolation between each port can reach 20dB in most of the frequency band.
The effects of background music on word processed writing

College students often listen to music while they use a computer. This experiment investigated whether background music disrupts their ability to word process  ̄uently and eectively. Forty-®ve psychology undergraduates wrote brief expository essays. Background music signi®cantly disrupted writing  ̄uency (words generated per minute controlling for typing speed and including those words deleted before the ®nal draft) even though no response to the music was required. Those with some musical training and high working memory span wrote better essays with longer sentences and were also more likely to pause at clause boundaries. Even unattended music places heavy demands on working memory and disrupts word processed writing.
An Adaptive Implementation Case Study of Apriori Algorithm for a Retail Scenario in a Cloud Environment

Retail transactional databases are voluminous and traditional algorithmic approaches to mine pattern in them are time consuming. The current study presents an approach to scale Apriori a Frequent Item set Mining (FIM) algorithm, which is often used for market basket analysis. The study also compares the performance of scaled version of the algorithm (running on multiple on-demand simultaneous Azure cloud instances) with that of traditional setup (running on a fixed Azure cloud instances) using simulated data sets. The experimental results show that the response times were significantly lower and in favor of the scaled approach as the data volume increases.
Compact Zigzag-Shaped-Slit Microstrip Antenna With Circular Defected Ground Structure for Wireless Applications

In this letter, a compact zigzag-shaped-slit rectangular microstrip patch antenna with circular defected ground structure (DGS) is designed for wireless applications. The probe-fed antenna consisting of a zigzag-shaped slit, dual T-shaped slits on either sides of a rectangular patch, and circular dumbbell-shaped defected ground plane is optimized. The antenna was able to generate three separate resonances to cover both the 2.45/5.28-GHz WLAN bands and the 3.5-GHz WiMAX bands while maintaining a small overall size of 40 ×28 ×3.175 mm3. The return-loss impedance bandwidth values are enhanced significantly for three resonant frequencies. The designed antenna is characterized with better radiation patterns and potentially stable gain around 4-6 dBi over the working bands. Good agreement was obtained between measurements and simulations.