nils-herrmann/clean_scirepeval huggingface dataset:
The medical perspective of cupping therapy: Effects and mechanisms of action
Venue: Journal of traditional and complementary medicine
Year: 2019

Cupping Therapy (CT) is an ancient method and currently used in the treatment of a broad range of medical conditions. Nonetheless the mechanism of action of (CT) is not fully understood. This review aimed to identify possible mechanisms of action of (CT) from modern medicine perspective and offer possible explanations of its effects. English literature in PubMed, Cochrane Library and Google Scholar was searched using key words. Only 223 articles identified, 149 records screened, and 74 articles excluded for irrelevancy. Only 75 full text articles were assessed for eligibility, included studies in this review were 64. Six theories have been suggested to explain the effects produced by cupping therapy. Pain reduction and changes in biomechanical properties of the skin could be explained by "Pain Gate Theory" "Diffuse Noxious Inhibitory Controls" and "Reflex zone theory" Muscle relaxation, changes in local tissue structures and increase in blood circulation might be explained by "Nitric Oxide theory" Immunological effects and hormonal adjustments might be attributed to "Activation of immune system theory" Releasing of toxins and removal of wastes and heavy metals might be explained by "Blood Detoxification Theory" These theories may overlap or work interchangeably to produce various therapeutic effects in specific ailments and diseases. Apparently, no single theory exists to explain the whole effects of cupping. Further researches are needed to support or refute the aforesaid theories, and also develop innovative conceptualizations of (CT) in future.
A novel content based hyperspectral image retrieval system based on bag of end members
Venue: 2016 24th Signal Processing and Communication Application Conference (SIU)
Year: 2016

This paper proposes a bag of end members based novel method for content based hyperspectral image retrieval. The proposed system exploits high resolution spectral signatures of the distinct materials in the hyperspectral images and consists of two steps. In the first step, query and archive hyperspectral images are represented with a feature vector computed by a novel bag of end members based feature extraction method. In the second step, the similarities between the feature vector of the query image and those of the archive images are initially computed by the use of histogram intersection kernel and then the most similar images are retrieved. The proposed system is tested on a hyperspectral image archive created from an EO 1 Hyperion hyperspectral sensor image. The experimental results show that the proposed system increases hyperspectral image retrieval performance.
Lactobacillus Salivarius REN Inhibits Rat Oral Cancer Induced by 4 Nitroquioline 1 Oxide
Venue: Cancer Prevention Research
Year: 2013

Despite significant advances in cancer therapy, cancer related mobility and mortality are still rising. Alternative strategies such as cancer prevention thus become essential. Probiotics represent an emerging option for cancer prevention, but studies are limited to colon cancers. The efficiency of probiotics in the prevention of other cancers and the correlative mechanism remains to be explored. A novel probiotics Lactobacillus salivarius REN (L. salivarius REN) was isolated from centenarians at Bama of China, which showed highly potent antigenotoxicity in an initial assay. 4 nitroquioline 1 oxide (4NQO) induced oral cancer model was introduced to study the anticancer activity of L. salivarius REN in vivo. The results indicated that oral administration of probiotic L. salivarius REN or its secretions could effectively suppress 4NQO induced oral carcinogenesis in the initial and postinitial stage, and the inhibition was in a dose dependent manner. A significant decrease of neoplasm incidence (65% 0% was detected in rats fed with the high dose of L. salivarius REN [5 x 1010 CFU/kg body weight (bw)/d] In vivo evidences indicated that the probiotics inhibited 4NQO induced oral cancer by protecting DNA against oxidative damage and downregulating COX 2 expression. L. salivarius REN treatment significantly decreased the expression of proliferating cell nuclear antigen (PCNA) and induced apoptosis in a dose dependent manner. Our findings suggest that probiotics may act as potential agents for oral cancer prevention. This is the first report showing the inhibitory effect of the probiotics on oral carcinogenesis. Cancer Prev Res; 6(7) 686 94. (
Decision Support System for Visualization of Tree Plantation in Upper Sindh
Year: 2018

Due to the rapid change in climate, visualization of environmental factors over a Geo graphic map using machine learning techniques have become one of the active research area(s) of computer science. Since the trees are considered one of the biggest environmental cleaning contributing factor. Specially; tree plantation is one of the important problem around the globe to improve the environmental variables. For example, raise of temperature, impurity of water and many other problems are associated with the huge number of tree cuts and replantation of trees as per requirements will help to combat the ecological problems in upper Sindh, Pakistan. This paper attempts to get attention of concerned stockholders such as (government, NGOs (Non Government organizations) and so on) to properly formulate the policies for replantation of trees and to reestablish the ecological system. In order to address all above stated problems, this paper proposes a system for the restoration of environmental factors so called "Decision Support System for Visualization of Tree Plantation in Upper Sindh" which offers a forecasting system using machine learning techniques and visualization of results over a geographic map using Q GIS (Geographic information system) This paper contributes three contributions (1) a methodology to fill the missing values by constructing the decision model on historical data (2) forecasting of critical regions for tree plantation on geographic information system and (3) overall best accuracy for tree plantation problem which is estimated as 96.53% with 10 k fold cross validation.
Application of Kernel Density Estimation to Achieve Automated Near Real Time Antenna Pattern Data Processing and Analysis in an Anechoic Chamber
Venue: 2020 Antenna Measurement Techniques Association Symposium (AMTA)
Year: 2020

The Benefield Anechoic Facility (BAF) at Edwards Air Force Base is the world's largest known anechoic chamber. Due to its unmatched size and equipment inventory, the BAF hosts far field pattern measurements at all azimuth angles and multiple simultaneous elevations of installed antennas on large aircraft typically across the BAF's operating frequency range of 0.1 18 GHz. Antenna tests at the BAF rapidly produce copious data, which often require immediate analysis to allow system owners to make relevant improvements. Historically, the BAF had accomplished quality assurance manually. Analysis was accomplished post test by customers and the BAF team. Today, the BAF team has developed scripts that use kernel density estimation and basic machine learning to automatically check incoming data and highlight anomalies for review. During a 2019 test of installed antennas on a B 1B bomber, the BAF team used these scripts to process antenna patterns in near real time and bring unusual results to the customer's attention fast enough to allow modifications to be applied and re tested during the same test event highly significant as aircraft and BAF schedule times are limited and may be a one time opportunity to gather required data. This paper will explore the algorithm used to evaluate antenna patterns, as well as the expected characteristics of patterns that enable the selection of relevant data. Development of this algorithm found that using kernel density estimation to calculate the maxima in a pattern's distribution of gain values, then performing this recursively over the main lobe, can identify problems such as incorrect switching, mismatched transmission lines, and multipath. Algorithm optimization was achieved using generated data, then the algorithm was implemented as a prototype during the B 1B test by searching for data that deviated from a sample pattern. Finally, this paper will discuss the application and impact of this algorithm during a live test. All plotted data and numerical results included in this paper are based on training data generated in Python to represent generic directive antenna patterns, and do not correspond to the real world conditions or results of the B 1B test.
Forecasting at Scale
Year: 2018

Forecasting is a common data science task that helps organizations with capacity planning, goal setting, and anomaly detection. Despite its importance, there are serious challenges associated with producing reliable and high quality forecasts especially when there are a variety of time series and analysts with expertise in time series modeling are relatively rare. To address these challenges, we describe a practical approach to forecasting "at scale" that combines configurable models with analyst in the loop performance analysis. We propose a modular regression model with interpretable parameters that can be intuitively adjusted by analysts with domain knowledge about the time series. We describe performance analyses to compare and evaluate forecasting procedures, and automatically flag forecasts for manual review and adjustment. Tools that help analysts to use their expertise most effectively enable reliable, practical forecasting of business time series.
Rational design of an improved transglucosylase for production of the rare sugar nigerose.
Venue: Chemical communications
Year: 2019

The sucrose phosphorylase from Bifidobacterium adolescentis (BaSP) can be used as a transglucosylase for the production of rare sugars. We designed variants of BaSP for the efficient synthesis of nigerose from sucrose and glucose, thereby adding to the inventory of rare sugars that can conveniently be produced from bulk sugars.
Postoperative pain control after arthroscopic rotator cuff repair.
Venue: Journal of shoulder and elbow surgery
Year: 2016

Arthroscopic rotator cuff repair (ARCR) can provide excellent clinical results for patients who fail to respond to conservative management of symptomatic rotator cuff tears. ARCR, however, can be associated with severe postoperative pain and discomfort that requires adequate analgesia. As ARCR continues to shift toward being performed as an outpatient procedure, it is incumbent on physicians and ambulatory surgical centers to provide appropriate pain relief with minimal side effects to ensure rapid recovery and safe discharge. Although intravenous and oral opioids are the cornerstone of pain management after orthopedic procedures, they are associated with drowsiness, nausea, vomiting, and increased length of hospital stay. As health care reimbursements continue to become more intimately focused on quality, patient satisfaction, and minimizing of complications, the need for adequate pain control with minimal complications will continue to be a principal focus for providers and institutions alike. We present a review of alternative modalities for pain relief after ARCR, including cryotherapy, intralesional anesthesia, nerve blockade, indwelling continuous nerve block catheters, and multimodal anesthesia. In choosing among these modalities, physicians should consider patient and system based factors to allow the efficient delivery of analgesia that optimizes recovery and improves patient satisfaction.
Valuation Method of Equity based Security Token Offerings (STO) for Start Up Companies
Venue: The Journal of the British Blockchain Association
Year: 2019

The major difficulty to value equity security token offerings (STOs) is the gap in the corpus of finance theory to quantify the discount rate for start up companies. In this paper, we develop a novel valuation method of equity based securities token offerings (STO) for start up companies. The closed form discount rate function discovered in this paper is time dependent and piecewise. The first part of the function is exponential; the second part is a power function. The reason is that, in the early years, the probability of survival of start up firms descends more rapidly than in late years. The probability of survival function discovered has a remarkably good fit with empirical data for the total of firms and ten industry sectors for which data is available. For the total of firms, we found that the highest discount rate has a 27.0 to 31.8% range when the liquidation value of the non surviving start up project is zero; this is considerably higher than observed discount rates of projects for mature firms (7.5% but considerably less than some published discount rates for start up projects financed by Venture Capital firms (40.6 to 70% range) To demonstrate the model, we work a valuation example in section six. A valuation method for equity STOs will help to develop a more transparent market for start ups wanting to raise capital. Most importantly, our results show that for many start up firms, equity STOs could be an economical alternative to raise capital.
Electrical Load Forecast of Data Mining Model in Smart Grid
Year: 2011

Based on data mining theory to collect and integrate data,using improved BP neu ral network model to process the grid data,and a electrical load model was esta blished to forcast the short term electrical load.Through different precision experiments,the high precision forcast result is better than the low precisio n forcast result,the maximum error is reduced by 80%,it is proved that the mod el suits to the practical.
Electronic basis of hardness and phase transformations (covalent crystals)
Year: 2008

Several electronic parameters measure the stabilities of covalent crystals, including minimum energy band gap densities, inverse polarizabilities, plasma frequencies, transverse vibrational frequencies and elastic shear moduli. Convenient is the band gap density (energy/volume; called the 'bond modulus' For a given bonding type, the indentation hardness is proportional to the bond modulus. Examples are the group IV elements, III V compounds; and II VI compounds. The motion of dislocation kinks requires the excitation of bonding electrons into anti bonding states. The bond modulus measures this together with the work done by the applied stress when a kink moves.In addition to hardness, the bond modulus measures the compressive strain (pressure) needed to transform an ambient structure into a more dense structure. Activation of such transformations also requires the excitation of bonding electrons into anti bonding states together with the work done by the compressive stress.
Effect of imperfect interface on the dynamic response of a circular lined tunnel impacted by plane P waves
Year: 2016

A theoretical method for studying the dynamic response of a circular lined tunnel with an imperfectly bonded interface subjected to plane P waves is presented in the paper. The wave function expansion method was used and the imperfect interface was modeled with a spring model. Two cases were discussed in the paper. In the first case rock is harder than the lining and vice versa in the second case. The results indicated that the variation in the stiffness of the interface has much influence on the distribution of dynamic stress concentration factors (DSCF) in the rock and the lining. The imperfection of the interface has a more noticeable influence on the DSCF in the rock mass and the lining at high frequency incident wave's scenario than low frequency incident wave's scenario. The resonance scattering phenomena can be observed when the bond is extremely weak. Limiting cases were considered and a good agreement with the solutions available in the literature was obtained.
From Data Mining and Knowledge Discovery to Big Data Analytics and Knowledge Extraction for Applications in Science
Venue: J. Comput. Sci.
Year: 2014

"Data mining" for "knowledge discovery in databases " and associated computational operations first introduced in the mid 1990 s can no longer cope wit h the analytical issues relating to the so called " big data" The recent buzzword big data refers to large volumes of diverse, dynami c, complex, longitudinal and/or distributed data generated from instruments, sensors, Internet transactions, email, video, clic k streams, noisy, structured/unstructured and/or all other digital sources available today and in the fu ture at speeds and on scales never seen before in human his tory. The big data also being described using 3 Vs, volume, variety and velocity (with an additional 4t h V for "veracity" and more recently with a 5th V f or "value" requires a set of new technologies, such as high performance computing i.e. exascale, architectures (distributed or grid) algorithms (fo r data clustering and generating association rules) programming languages, automated and scalable softw are tools, to uncover hidden patterns, unknown correlations and other useful information lately re fe red to as "actionable knowledge" or "data produc ts" from the massive volumes of complex raw data. In vi ew of the above facts, the paper gives an introduct ion to the synergistic challenges in "data intensive" s cience and "exascale" computing for resolving "big data analytics" and "data science" issues in four main d sciplines namely, computer science, computational science, statistics and mathematics. For the realis ation of vital identified foundational aspects of a n effective cyber infrastructure, basic problems need to be add ressed adequately in the respective disciplines and are outlined. Finally, the paper looks at five scientif ic research projects that are urgently in need of h igh performance computing; this is in contrast to the e arli r situations where private business enterprise s w re the drivers of better modern and faster technologie s.
Information Technology and Art: Concepts and State of the Practice
Venue: Handbook of Multimedia for Digital Entertainment and Arts
Year: 2009

The interaction between information technology (IT) and art is an increasing trend. Science, art and technology have been connected since the 60's, when scientists, artists, and inventors started to cooperate and use electronic instruments to create art. In 1960 Marshall McLuhan predicted the idea that the era of "machine age" technology was next to close, and the electronic media were creating a new way to perform art  The literature is full with examples of artists applying mathematics, robotic technology, and computing to the creation of art. The work in  is a good introduction to the merge of IT and art and introduces genetic art, algorithmic art, applications of complex systems and artificial intelligence. The intersection is drawing attention of people from diverse background and it is growing in size and scope. For these reasons, it is beneficiary for people interested in art and technology to know each other's background and interests well. In a multidisciplinary collaboration, the success depends on how well the different actors in the project collaborate and understand each other.  for an introduction about multidisciplinary issues. Meyer and others in  explains the collaboration process between artists and technologists.
Egalite, discrimination, diversite GRH Une thematique transversale enrichissant la recherche en comportement organisationnel
Year: 2016

Avant d'etablir une rapide analyse du corpus academique en Gestion des Ressources Humaines (GRH) dans les domaines de l'egalite, la discrimination et la diversite (EDD) un preambule s'impose pour rappeler le lien indissociable entre droit et GRH lorsque l'on s'interesse a l'egalite et a la non discrimination. Nous chercherons ensuite a montrer que les questions de frontieres disciplinaires et thematiques rendent difficile l'exercice d'identification d'une production scientifique dans ce domaine. Enfin, nous tenterons de donner quelques pistes pour les recherches futures a l'aune des enseignements que nous pouvons tirer de l'analyse de ce corpus.
A multi domain fault localization model for submarine cable system
Venue: 2011 13th Asia Pacific Network Operations and Management Symposium
Year: 2011

International submarine cables play an important role of global communication backbone because they carry variety of important services. Recently, nature disasters such as earthquakes, undersea landslides happen frequently and often cause the interruption of submarine cables. After finding the fault location of submarine cable, telecommunication carriers will redistribute routes according to restoration plans to guarantee services for customers. At present, monitoring of the cable electricity power equipment is widely used for faults detection and concluding the faults location. However the investment cost of this method is high, most carriers would not put much effort on it. In this paper, we propose a new fault location analysis model to infer the submarine cable fault section from the characteristics that submarine cables carry multi service and multi domain network devices. Since submarine cables are broken, they will cause a mass of leased line alarms and voice circuit alarms. We make the correlation analysis from routes and alarms of circuits in the collection of submarine cables to analyze the possible submarine fault sections. We also use the alarms from dry contacts of submarine cable physical equipments to analyze other possible submarine fault sections. After converging and intersecting these possible submarine cable fault sections, we can conclude the real submarine cable fault sections. An extensive experimentation has demonstrated that the accuracy rate of this model is high as 83%
A preliminary heat transfer analysis of pulse detonation engines
Year: 2018

Detonation engines offer higher theoretical thermal efficiencies as compared to their deflagration based counterparts. Simultaneous pressure gain during heat addition through the detonation wave provides the superiority to the Zeldovich von Neumann Dring (ZND) cycle which is used to define the thermodynamic process of detonation engines. Combustion temperatures can rise as high as 3000 K across the detonation wave. The continuous exposure to such elevated temperature may risk the integrity of the structural components of the engines. Consequently, heat management of the detonation engines highlights an important parameter on the construction of a demonstrator. In order to be able to design an appropriate cooling system, both for pulse detonation and rotating detonation engines (PDE RDE) an accurate estimation of the heat load stands as an essential prerequisite. Hence, a preliminary numerical study of the heat transfer on a pulse detonation engine model was conducted to quantify the heat load. Conservation equations for deflagration to detonation transition (DDT) in detonation engines were solved through open source fluid dynamics solver OpenFOAM equipped with ddtFoam module. Reactive flow field of premixed mixtures (Hydrogen air) was modeled with a URANS second order approximate Riemann solver equipped with Weller combustion model, and Arrhenius equations of O'Connaire reaction scheme for Hydrogen air detonation. Multiple boundary conditions were tested to achieve the most appropriate model. Natural convection over the lateral combustor peripheries found to be the most realistic boundary condition for the problem. In order to observe cooling process better, PDE tubes in different length were also simulated. Finally, the transient heat transfer phenomenon across the pulse detonation tube is documented for various conditions investigated.