nils-herrmann/clean_scirepeval huggingface dataset:
A Review on the Ayurvedic Management of Causes and Symptoms of Bronchial Asthma

Ayurvedic medicine is an ancient Indian form of healing. It is gaining popularity as part of the growing interest in New Age spirituality and in complementary and alternative medicine (CAM). There is no cure for Asthma as per the Conventional Medical Science. Ayurvedic medicines can be a potential and effective alternative for the treatment against the bronchial asthma. Ayurvedic medicines are used for the treatment of diseases globally. The present study was a review on the management of Tamaka-Shwasa based on Ayurvedic drugs including the respiratory tonics and naturally occurring bronchodilator and immune-modulators. This study result concluded that a systematic combination of herbal and allopathic medicines is required for management of asthma.
Workplace bullying and the risk of cardiovascular disease and depression.

To examine exposure to workplace bullying as a risk factor for cardiovascular disease and depression in employees.



Logistic regression models were related to prospective data from two surveys in a cohort of 5432 hospital employees (601 men and 4831 women), aged 18-63 years. Outcomes were new reports of doctor diagnosed cardiovascular disease and depression during the two year follow up among those who were free from these diseases at baseline.



The prevalence of bullying was 5% in the first survey and 6% in the second survey. Two per cent reported bullying experiences in both surveys, an indication of prolonged bullying. After adjustment for sex, age, and income, the odds ratio of incident cardiovascular disease for victims of prolonged bullying compared to non-bullied employees was 2.3 (95% CI 1.2 to 4.6). A further adjustment for overweight at baseline attenuated the odds ratio to 1.6 (95% CI 0.8 to 3.5). The association between prolonged bullying and incident depression was significant, even after these adjustments (odds ratio 4.2, 95% CI 2.0 to 8.6).



A strong association between workplace bullying and subsequent depression suggests that bullying is an aetiological factor for mental health problems. The victims of bullying also seem to be at greater risk of cardiovascular disease, but this risk may partly be attributable to overweight.
Principles of protein-protein interactions.

This review examines protein complexes in the Brookhaven Protein Databank to gain a better understanding of the principles governing the interactions involved in protein-protein recognition. The factors that influence the formation of protein-protein complexes are explored in four different types of protein-protein complexes--homodimeric proteins, heterodimeric proteins, enzyme-inhibitor complexes, and antibody-protein complexes. The comparison between the complexes highlights differences that reflect their biological roles.
MyBehavior: automatic personalized health feedback from user behaviors and preferences using smartphones

Mobile sensing systems have made significant advances in tracking human behavior. However, the development of personalized mobile health feedback systems is still in its infancy. This paper introduces MyBehavior, a smartphone application that takes a novel approach to generate deeply personalized health feedback. It combines state-of-the-art behavior tracking with algorithms that are used in recommendation systems. MyBehavior automatically learns a user's physical activity and dietary behavior and strategically suggests changes to those behaviors for a healthier lifestyle. The system uses a sequential decision making algorithm, Multi-armed Bandit, to generate suggestions that maximize calorie loss and are easy for the user to adopt. In addition, the system takes into account user's preferences to encourage adoption using the pareto-frontier algorithm. In a 14-week study, results show statistically significant increases in physical activity and decreases in food calorie when using MyBehavior compared to a control condition.
Multi-sensor Self-Quantification of Presentations

Presentations have been an effective means of delivering information to groups for ages. Over the past few decades, technological advancements have revolutionized the way humans deliver presentations. Despite that, the quality of presentations can be varied and affected by a variety of reasons. Conventional presentation evaluation usually requires painstaking manual analysis by experts. Although the expert feedback can definitely assist users in improving their presentation skills, manual evaluation suffers from high cost and is often not accessible to most people. In this work, we propose a novel multi-sensor self-quantification framework for presentations. Utilizing conventional ambient sensors (i.e., static cameras, Kinect sensor) and the emerging wearable egocentric sensors (i.e., Google Glass), we first analyze the efficacy of each type of sensor with various nonverbal assessment rubrics, which is followed by our proposed multi-sensor presentation analytics framework. The proposed framework is evaluated on a new presentation dataset, namely NUS Multi-Sensor Presentation (NUSMSP) dataset, which consists of 51 presentations covering a diverse set of topics. The dataset was recorded with ambient static cameras, Kinect sensor, and Google Glass. In addition to multi-sensor analytics, we have conducted a user study with the speakers to verify the effectiveness of our system generated analytics, which has received positive and promising feedback.
Software for performance prediction and matching of tractor-implement system

The matching of tractor-implement system is very difficult task in India because variety of tractor models ranging from 10 to 45kW is prevalent here. To overcome the problem of matching tractor-implement system, a decision support system (DSS) was developed in Visual Basic 6.0 programming language for 2-wheel drive (2WD) tractors. The DSS provides intuitive user interfaces by linking databases such as tractor parameters, tire and implement specifications, soil and operating conditions to support the decision for selection of tractor-implement system. DSS was validated for three different implements (2×30cm moldboard plow; 9-23cm field cultivator and 7-7 offset disc harrow (1.6m)). DSS which calculates draft, drawbar power, slip, tractive efficiency, coefficient of rolling resistance, coefficient of net traction, PTO power required, power utilization efficiency, specific fuel consumption based etc. on input data, can be used effectively in matching of tractor-implement system of various makes and models commercially available in India.
Matrix assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) for direct visualization of plant metabolites in situ.

Direct visualization of plant tissues by matrix assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) has revealed key insights into the localization of metabolites in situ. Recent efforts have determined the spatial distribution of primary and secondary metabolites in plant tissues and cells. Strategies have been applied in many areas of metabolism including isotope flux analyses, plant interactions, and transcriptional regulation of metabolite accumulation. Technological advances have pushed achievable spatial resolution to subcellular levels and increased instrument sensitivity by several orders of magnitude. It is anticipated that MALDI-MSI and other MSI approaches will bring a new level of understanding to metabolomics as scientists will be encouraged to consider spatial heterogeneity of metabolites in descriptions of metabolic pathway regulation.
Fingertip Pulse Wave ( PPG signal ) Analysis and Heart Rate Detection

To study heart beat pulse wave propagation in real time and to evaluate the vascular blood flow resistance an important physiological parameter for vascular diagnostics. Photoplethysmography is a non-invasive technique that measures relative blood volume changes in the blood vessels close to the skin. PPG analysis emphasizes the importance of early evaluation of the diseases We present the results of analysis of photoplethysmography (PPG) signal having motion artifacts which are as alike Gaussian noise in nature. We have proposed a methodology in detecting Heart rate and respiration rate after performing noise cancellation i.e. removing the motion artifacts of the PPG signal. Significance of different Wavelets such as db4, bior3.3, coif1, sym2, haar discussed for removing the motion artifacts. A novel beat rate extraction algorithm (BREA) is implemented monitor the heart rate and respiratory rate of peripheral pulse which has a steep rise and notch on falling slope in the subjects and a more gradual rise and fall and very small dicrotic notch.
A 3D Poly(ethylene glycol)-based Tumor Angiogenesis Model to Study the Influence of Vascular Cells on Lung Tumor Cell Behavior

Tumor angiogenesis is critical to tumor growth and metastasis, yet much is unknown about the role vascular cells play in the tumor microenvironment. In vitro models that mimic in vivo tumor neovascularization facilitate exploration of this role. Here we investigated lung adenocarcinoma cancer cells (344SQ) and endothelial and pericyte vascular cells encapsulated in cell-adhesive, proteolytically-degradable poly(ethylene) glycol-based hydrogels. 344SQ in hydrogels formed spheroids and secreted proangiogenic growth factors that significantly increased with exposure to transforming growth factor beta 1 (TGF-β1), a potent tumor progression-promoting factor. Vascular cells in hydrogels formed tubule networks with localized activated TGF-β1. To study cancer cell-vascular cell interactions, we engineered a 2-layer hydrogel with 344SQ and vascular cell layers. Large, invasive 344SQ clusters (area > 5,000 μm(2), circularity < 0.25) developed at the interface between the layers, and were not evident further from the interface or in control hydrogels without vascular cells. A modified model with spatially restricted 344SQ and vascular cell layers confirmed that observed cluster morphological changes required close proximity to vascular cells. Additionally, TGF-β1 inhibition blocked endothelial cell-driven 344SQ migration. Our findings suggest vascular cells contribute to tumor progression and establish this culture system as a platform for studying tumor vascularization.
Multi-armed bandits with application to 5G small cells

Due to the pervasive demand for mobile services, next generation wireless networks are expected to be able to deliver high data rates while wireless resources become more and more scarce. This requires the next generation wireless networks to move toward new networking paradigms that are able to efficiently support resource-demanding applications such as personalized mobile services. Examples of such paradigms foreseen for the emerging 5G cellular networks include very densely deployed small cells and device-to-device communications. For 5G networks, it will be imperative to search for spectrum and energy-efficient solutions to the resource allocation problems that i) are amenable to distributed implementation, ii) are capable of dealing with uncertainty and lack of information, and iii) can cope with users' selfishness. The core objective of this article is to investigate and establish the potential of the MAB framework to address this challenge. In particular, we provide a brief tutorial on bandit problems, including different variations and solution approaches. Furthermore, we discuss recent applications as well as future research directions. In addition, we provide a detailed example of using an MAB model for energy-efficient small cell activation in 5G networks.
Identifying Suicide Ideation and Suicidal Attempts in a Psychiatric Clinical Research Database using Natural Language Processing

Research into suicide prevention has been hampered by methodological limitations such as low sample size and recall bias. Recently, Natural Language Processing (NLP) strategies have been used with Electronic Health Records to increase information extraction from free text notes as well as structured fields concerning suicidality and this allows access to much larger cohorts than previously possible. This paper presents two novel NLP approaches – a rule-based approach to classify the presence of suicide ideation and a hybrid machine learning and rule-based approach to identify suicide attempts in a psychiatric clinical database. Good performance of the two classifiers in the evaluation study suggest they can be used to accurately detect mentions of suicide ideation and attempt within free-text documents in this psychiatric database. The novelty of the two approaches lies in the malleability of each classifier if a need to refine performance, or meet alternate classification requirements arises. The algorithms can also be adapted to fit infrastructures of other clinical datasets given sufficient clinical recording practice knowledge, without dependency on medical codes or additional data extraction of known risk factors to predict suicidal behaviour.
Key-Policy Attribute-Based Encryption With Equality Test in Cloud Computing

The privacy of users must be considered as the utmost priority in distributed networks. To protect the identities of users, attribute-based encryption (ABE) was presented by Sahai et al. ABE has been widely used in many scenarios, particularly in cloud computing. In this paper, public key encryption with equality test is concatenated with key-policy ABE (KP-ABE) to present KP-ABE with equality test (KP-ABEwET). The proposed scheme not only offers fine-grained authorization of ciphertexts but also protects the identities of users. In contrast to ABE with keyword search, KP-ABEwET can test whether the ciphertexts encrypted by different public keys contain the same information. Moreover, the authorization process of the presented scheme is more flexible than that of Ma et al.’s scheme. Furthermore, the proposed scheme achieves one-way against chosen-ciphertext attack based on the bilinear Diffie-Hellman (BDH) assumption. In addition, a new computational problem called the twin-decision BDH problem (tDBDH) is proposed in this paper. tDBDH is proved to be as hard as the decisional BDH problem. Finally, for the first time, the security model of authorization is provided, and the security of authorization based on the tDBDH assumption is proven in the random oracle model.
Multiple-attribute decision making methods for plant layout design problem

The layout design problem is a strategic issue and has a significant impact on the efficiency of a manufacturing system. Much of the existing layout design literature that uses a surrogate function for flow distance or for simplified objectives may be entrapped into local optimum; and subsequently lead to a poor layout design due to the multiple-attribute decision making (MADM) nature of a layout design decision. The present study explores the use of MADM approaches in solving a layout design problem. The proposed methodology is illustrated through a practical application from an IC packaging company. Two methods are proposed in solving the case study problem: Technique for order preference by similarity to ideal solution (TOPSIS) and fuzzy TOPSIS. Empirical results showed that the proposed methods are viable approaches in solving a layout design problem. TOPSIS is a viable approach for the case study problem and is suitable for precise value performance ratings. When the performance ratings are vague and imprecise, the fuzzy TOPSIS is a preferred solution method.
Thermal resistance evaluation of die-attachment made of nano-composite Cu/Sn TLPS paste in SiC power module

In this paper, we demonstrate a high heat resistant bonding method by Cu/Sn transient liquid phase sintering (TLPS) method can be applied to die-attachment of silicon carbide (SiC)-MOSFET in high temperature operation power module. The die-attachment is made of nano-composite Cu/Sn TLPS paste. The die shear strength was 40 MPa for 3 × 3 mm2 SiC chip after 1,000 cycles of thermal cycle testing between −40 °C and 250 °C. This indicated a high reliability of Cu/Sn die-attachment. The thermal resistance of the Cu/Sn die-attachment was evaluated by transient thermal analysis using a sample in which the SiC-MOSFET (die size: 4.04 × 6.44 mm2) was bonded with Cu/Sn die-attachment. The thermal resistance of Cu/Sn die-attachment was 0.13 K/W, which was comparable to the one of Au/Ge die-attachment (0.12 K/W). The validity of nano-composite Cu/Sn TLPS paste as a die-attachment for high-temperature operation SiC power module is confirmed.
Evolving Boids : Using a Genetic Algorithm to Develop Boid Behaviors

The detection and analysis of clusters has become commonplace within geographic information science and has been applied in epidemiology, crime prevention, ecology, demography and other fields. One of the many methods for detecting and analyzing these clusters involves searching the dataset with a flock of boids (bird objects). While boids are effective at searching the dataset once their behaviors are properly configured, it can be difficult to find the proper configuration. Since genetic algorithms have been successfully used to configure neural networks, they may also be useful for configuring parameters guiding boid behaviors. In this paper, we develop a genetic algorithm to evolve the ideal boid behaviors. Preliminary results indicate that, even though the genetic algorithm does not return the same configuration each time, it does converge on configurations that improve over the parameters used when boids were initially proposed for geographic cluster detection. Also, once configured, the boids perform as well as other cluster detection methods. Continued work with this system could determine which parameters have a greater effect on the results of the boid system and could also discover rules for configuring a flock of boids directly from properties of the dataset, such as point density, rather than requiring the time-consuming process of optimizing the parameters for each new dataset.
Measurement of the Anisotropy of Young's Modulus in Single-Crystal Silicon

In (100) silicon wafers, the most commonly used in microelectromechanical systems (MEMS) fabrication, the value of Young's modulus of a MEMS structure can vary by over 20%, depending on the structure's orientation on the wafer surface. This anisotropy originates from the crystal structure of silicon. We have directly measured the anisotropy of Young's modulus in the (100) plane of silicon from the measured resonance frequencies of a “wagon-wheel” test structure comprising an arc of identical microcantilevers fabricated in the structural layer of a (100) silicon-on-insulator wafer. The direction of the principal axis of the cantilevers increased from 0° to 180 ° in 10° steps with respect to the [110] direction, allowing the angular dependence of Young's modulus to be experimentally mapped out. The Young's modulus was measured to have a value of 170 GPa ± 3 GPa at 0° and 90 ° to the [110] direction and a value of 131 GPa ± 3 GPa at ±40° and ±50° to the [110] direction. The measured values of Young's modulus and their angular dependence agree very well with the theoretical values that were recently reported, thereby experimentally verifying the theoretical calculations.
Toward parallel continuum manipulators

In this paper, we investigate continuum manipulators that are analogous to conventional rigid-link parallel robot designs. These “parallel continuum manipulators” have the potential to inherit some of the compactness and compliance of continuum robots while retaining some of the precision, stability, and strength of rigid-link parallel robots, yet they represent a relatively unexplored area of the broad manipulator design space. We describe the construction of a prototype manipulator structure with six compliant legs connected in a parallel pattern similar to that of a Stewart-Gough platform. We formulate the static forward and inverse kinematics problems for such manipulators as the solution to multiple Cosserat-rod models with coupled boundary conditions, and we test the accuracy of this approach in a set of experiments, including the prediction of leg buckling. An inverse kinematics simulation of slices through the 6 degree-of-freedom (DOF) workspace illustrates the kinematic mapping, range of motion, and force required for actuation, which sheds light on the potential advantages and tradeoffs that parallel continuum manipulators may bring. Potential applications include miniature wrists and arms for endoscopic medical procedures, and lightweight compliant arms for safe interaction with humans.
Normalized metal artifact reduction (NMAR) in computed tomography.

While modern clinical CT scanners under normal circumstances produce high quality images, severe artifacts degrade the image quality and the diagnostic value if metal prostheses or other metal objects are present in the field of measurement. Standard methods for metal artifact reduction (MAR) replace those parts of the projection data that are affected by metal (the so-called metal trace or metal shadow) by interpolation. However, while sinogram interpolation methods efficiently remove metal artifacts, new artifacts are often introduced, as interpolation cannot completely recover the information from the metal trace. The purpose of this work is to introduce a generalized normalization technique for MAR, allowing for efficient reduction of metal artifacts while adding almost no new ones. The method presented is compared to a standard MAR method, as well as MAR using simple length normalization.



In the first step, metal is segmented in the image domain by thresholding. A 3D forward projection identifies the metal trace in the original projections. Before interpolation, the projections are normalized based on a 3D forward projection of a prior image. This prior image is obtained, for example, by a multithreshold segmentation of the initial image. The original rawdata are divided by the projection data of the prior image and, after interpolation, denormalized again. Simulations and measurements are performed to compare normalized metal artifact reduction (NMAR) to standard MAR with linear interpolation and MAR based on simple length normalization.



Promising results for clinical spiral cone-beam data are presented in this work. Included are patients with hip prostheses, dental fillings, and spine fixation, which were scanned at pitch values ranging from 0.9 to 3.2. Image quality is improved considerably, particularly for metal implants within bone structures or in their proximity. The improvements are evaluated by comparing profiles through images and sinograms for the different methods and by inspecting ROIs. NMAR outperforms both other methods in all cases. It reduces metal artifacts to a minimum, even close to metal regions. Even for patients with dental fillings, which cause most severe artifacts, satisfactory results are obtained with NMAR. In contrast to other methods, NMAR prevents the usual blurring of structures close to metal implants if the metal artifacts are moderate.



NMAR clearly outperforms the other methods for both moderate and severe artifacts. The proposed method reliably reduces metal artifacts from simulated as well as from clinical CT data. Computationally efficient and inexpensive compared to iterative methods, NMAR can be used as an additional step in any conventional sinogram inpainting-based MAR method.