nils-herrmann/clean_scirepeval huggingface dataset:
Modified Titanium Implant as a Gateway to the Human Body: The Implant Mediated Drug Delivery System
Venue: BioMed research international
Year: 2014

The aim of this study was to investigate the efficacy of a proposed new implant mediated drug delivery system (IMDDS) in rabbits. The drug delivery system is applied through a modified titanium implant that is configured to be implanted into bone. The implant is hollow and has multiple microholes that can continuously deliver therapeutic agents into the systematic body. To examine the efficacy and feasibility of the IMDDS, we investigated the pharmacokinetic behavior of dexamethasone in plasma after a single dose was delivered via the modified implant placed in the rabbit tibia. After measuring the plasma concentration, the areas under the curve showed that the IMDDS provided a sustained release for a relatively long period. The result suggests that the IMDDS can deliver a sustained release of certain drug components with a high bioavailability. Accordingly, the IMDDS may provide the basis for a novel approach to treating patients with chronic diseases.
nayi Concrete yeongusil
Year: 2011

This chapter describes the methodology used in EPA's Waste Reduction Model (WARM) to estimate streamlined life cycle greenhouse gas (GHG) emission factors for concrete beginning at the point of waste generation. The WARM GHG emission factors are used to compare the net emissions associated with concrete in the following two waste management alternatives: recycling and landfilling. Exhibit 1 shows the general outline of materials management pathways for concrete in WARM. For background information on the general purpose and function of WARM emission factors, see the Introduction Overview chapter. For more information on Recycling and Landfilling, see the chapters devoted to these processes. WARM also allows users to calculate results in terms of energy, rather than GHGs. The energy results are calculated using the same methodology described here but with slight adjustments, as explained in the Energy Impacts chapter.
Audio Visual Scene Analysis with Self Supervised Multisensory Features
Venue: ECCV
Year: 2018

The thud of a bouncing ball, the onset of speech as lips open when visual and audio events occur together, it suggests that there might be a common, underlying event that produced both signals. In this paper, we argue that the visual and audio components of a video signal should be modeled jointly using a fused multisensory representation. We propose to learn such a representation in a self supervised way, by training a neural network to predict whether video frames and audio are temporally aligned. We use this learned representation for three applications: (a) sound source localization, i.e. visualizing the source of sound in a video; (b) audio visual action recognition; and (c) on/off screen audio source separation, e.g. removing the off screen translator's voice from a foreign official's speech. Code, models, and video results are available on our webpage: this http URL
A COMPARATIVE STUDY OF COST OF PRODUCTION AND DECISION MAKING ANALYSIS IN CASE OF ONION AND SUNFLOWER CROPS IN QUETTA DISTRICT
Year: 2008

The agricultural economy of Pakistan is facing seve re challenges due to the rapidly growing demand for water resources. Efficient water management is becoming the single most important regional and global resource management challenge, which not only increases the availability of water for ag riculture but also saves it for other uses. In Balo chistan, the situation is worse; the farmers of tube well irrigated agriculture are paying only Rs.4000 per month as electricity tariff which discourages farmers to use more water. This study aims how by transforming the existing cropping pattern, we can ensure th e efficient use of available water resources. Onion and other high del ta corps are growing in the tube well irrigated are as extensively; on the other hand farmers can grow low delta crops like sunflower successfully. According to the study results the benefit cost ratio of sunflower (1.99:1) is higher than that of the onion crop (1.43:1) The results of expected value appro ach model revealed that growing sunflower with an expected value of Rs. 8,5 66 per acre and low water requirement is a recommended decision as compared with the onion's, for which expected value is Rs.7,502 acre, with high water requirements.
Pain perception and depression in patients with hidradenitis suppurativa
Year: 2020

Hidradenitis suppurativa (HS) is a chronic skin disease. It causes painful boils in specific body areas such as the armpits and the groins. This disease affects about 1% of people in the U.K. It is more common in women. HS causes pain, but few studies have looked at this aspect. Depression and anxiety affects how pain is experienced. The patient's age and sex can also influence the experience of pain.
Molecular Biomarkers Related to Oral Carcinoma: Clinical Trial Outcome Evaluation in a Literature Review
Venue: Disease markers
Year: 2019

The objective of the present research was to systematically revise the international literature about the genetic biomarkers related to oral cancer (OC) evaluating the recent findings in clinical studies.  A comprehensive review of the current literature was conducted according to the PRISMA guidelines by accessing the NCBI PubMed database. The authors conducted the search of articles in the English language published from 2008 to 2018. The present systematic review included only papers with significant results about correlation between wound healing, genetic alteration, and OC. Prognostic capacity of genetic markers was not evaluated in vivo.  The first analysis with filters recorded about 1884 published papers. Beyond reading and consideration of suitability, only 20 and then 8 papers, with case report exclusion, were recorded for the revision.  All the researches recorded the proteomic and genetic alterations in OC human biopsy cells. The gene modification level in the different studies, compared with samples of healthy tissues, has always been statistically significant, but it is not possible to associate publications with each other because each job is based on the measurement of different biomarkers and gene targets. Further investigations should be required in order to state scientific evidence about a clear advantage of using these biomarkers for diagnostic purpose.
Enhancing the Electrocatalytic Activity of Pd/M (M Ni, Mn) Nanoparticles for the Oxygen Reduction Reaction in Alkaline Media through Electrochemical Dealloying
Year: 2020

We have developed a facile and effective electrochemical dealloying strategy to enhance the electrocatalytic activity of Pd M (M Ni, Mn) nanoparticles for the oxygen reduction reaction (ORR) in a.
OSW CTST: A Developing Study of Oscillation and Sound Wave Critical Thinking Skills Test
Venue: Journal of Physics: Conference Series
Year: 2019

Nowadays, the main goal of education in the world is required to promote critical thinking skills for junior high school students in term of being better future live. To analyze students' critical thinking skills, we developed critical thinking test items on Oscillation and Sound Wave named Oscillation and Sound Wave Critical Thinking Skills Test (OSW CTST) The aim of this study is to develop the test of critical thinking skills through the development model. The development model which is utilized is ADDIE (Analyze, Design, Development, Implementation, and Evaluation) The OSW CTST items have already been developed through Ennis's indicators of critical thinking skills. The critical thinking indicators which were utilized in this study are: (1) identifying/formulating the criteria of possible answers, (2) identifying reasons or premises, (3) explaining the hypotheses, (4) defining the scientific terms and considering the definitions, and (5) choosing the possible criteria as a solution to the problems. On validity test to experts, the OSW CTST get the score greater than 4.3 of 5. The test items difficulty, distinguishing power, validity, and reliability value and criteria are good enough. In conclusion, critical thinking skills test on oscillation and sound wave could be well developed though ADDIE model and it could measure the junior high school students' critical thinking skills.
ANALISIS KAJIAN TEORITIS PERBEDAAN, PERSAMAAN DAN INKLUSI DALAM PELAYANAN PENDIDIKAN DASAR BAGI ANAK BERKEBUTUHAN KHUSUS (ABK)
Year: 2017

ABSTRACK Inclusion as an education service for children with spesial need thoroughly. The purpose of education inclusion to develop potential in limitations of the person. Study of the theory about the difference or diversity, equity and inclusion or equations must be understood before it hosts the educational inclusion. The implementation of inclusion ranging from basic education will contribution positively to the planting base of life for the person. Key words Diversity, Equality and Inclusion
Lifting the Curse of Multidimensional Data with Learned Existence Indexes
Year: 2018

Bloom filters are a form of existence index which offer compressed representations of sets at the cost of some false positives. Recent work has introduced the notion of learned Bloom filters, which can leverage salient differences between in index elements and out of index queries to offer further compression. In this extended abstract, we show that learned filters can handle multidimensional data particularly well, giving space savings of up to 72% in our experiments. We show how to maximize performance by leveraging three key optimizations: separate modeling of high cardinality versus low cardinality dimensions, Bloom filter sandwiching, and robust learning.
Value capture beyond municipalities: transit oriented development and inter city passenger rail investment in China's Pearl River Delta
Year: 2013

Existing research rarely systematically reviews how China has funded or will fund expanding transit systems. We argue that fiscal regulations have shaped how China's municipal governments plan for and invest in passenger rail services and land development around stations, and that policy reforms are necessary to bring successful transit oriented development and transit operation for China's next round of urbanization. Using Pearl River Delta (PRD) as the study case, we review the planning and funding processes for an inter city passenger rail services, and reveal how a new funding and planning framework has been developed out of pre existing organizational and legal constraints. The central piece of this innovation is a value capture framework beyond municipal boundaries, which tighten the connection between transit funding and transit oriented development. The PRD experience has implications for other megaregions in China.
A Z of nutritional supplements: dietary supplements, sports nutrition foods and ergogenic aids for health and performance: Part 43
Venue: British Journal of Sports Medicine
Year: 2013

Part 43 reviews three more noteworthy W's: wheat germ oil, whey protein and wolfberry. Wheat germ and the oil extracted from it, albeit by products from flour milling, contain significant quantities of tocopherols. A succinct review follows on whey protein, a very popular dietary supplement, particularly with resistance trained individuals wanting to gain lean muscle mass. The issue finishes with a close look at wolfberry, also known as goji berry, an important herbal component of traditional Chinese medicine, but also frequently found in sports supplements. The next instalment of our A Z series is dedicated to a review on nutritional supplements used in the sporting world for weight loss. This includes a special focus on the supplements marketed as having 'thermogenic' properties, which frequently contain a wide array of interesting herbs a review not to be missed! Wheat germ oil MK Ranchordas SJ Stear The wheat germ Triticum vulgare Gramineae) a by product of the flour milling industry, represents about 2.5 3.8% of the total seed weight. Wheat germ and the oil extracted from wheat germ contain significant quantities of bioactive compounds and, in particular, are known to be the richest plant origin source of tocopherols (vitamin E),1 with the antioxidant activity of tocopherols being well documented. Wheat germ contains mainly a tocopherols and b tocopherols,1 alongside other bioactive compounds such as phytosterols, polycosanols (POC) carotenoids, particularly lutein and zeaxanthin, thiamine (vitamin B1) and riboflavin (vitamin B2).2 Wheat germ is also a source of a linolenic rich polyunsaturated fatty acids,3 and contains several minerals, principally potassium, magnesium, calcium, zinc and manganese. Wheat germ contains about 10 15% lipids (oil) with oil extraction being primarily achieved by mechanical pressing or solvent extraction, which retrieves about 50% or >90% of the total lipids, respectively.2 Crude wheat
The Effects of the European Union Enlargement on Foreign Trade of Bosnia and Herzegovina
Year: 2018

In times of globalization, there is a worldwide trend of creating various regional economic integrations which aim to benefit for their members. Almost all of the countries belong to or aspire to belong to a group. One of them is Bosnia and Herzegovina. As a member of CEFTA since 2006, Bosnia and Herzegovina has built its foreign trade position together with other members, with which it has had exceptionally immense level of cooperation. Bosnia and Herzegovina is committed to joining the European Union, but the accession process is facing a lot of difficulties and going slowly, so that the time of receiving full membership is completely uncertain. Croatian withdrawal from the zone of free trade for the sake of joining the European Union has had inevitably serious consequences for the rest of the countries, reflected in decreasing the volume of mutual trade, stricter standards for export and differences in tariff and non tariff barriers relative to those that existed during the membership in the same integration. At the same time, there is a change for the new member of the European Union, which improves its trade relations with for
Teachers' competence, school policy and social context HIV prevention needs of primary schools in Kagera, Tanzania
Venue: Health education research
Year: 2018

Sub Saharan Africa carries a high burden of the HIV epidemic, with young adults being particularly affected. Well designed school based HIV prevention interventions can contribute to establishing protective behaviour. The aim of this study was to explore the needs of primary school students and teachers in the region of Kagera, Tanzania, regarding an HIV prevention intervention in the primary school setting. The needs assessment was structured according to the PRECEDE component of the PRECEDE PROCEED model. Qualitative data was collected in six focus group discussions with primary school students and teachers. Key informant interviews with seven experts were conducted. We employed qualitative content analysis to analyse data in MAXQDA. The findings suggest that teachers need to be adequately trained to provide HIV and sex education and to support HIV positive students. Enabling structural factors, such as an appropriate syllabus, are required. Stigmatization has been reported a major barrier to HIV prevention in schools. Teachers and students identified a more trustful relationship between each other as well as to legal guardians of children as a basis for HIV prevention. These findings will inform the development of a tailored HIV prevention intervention.
Constrained Partial Group Decoding With Max Min Fairness for Multi Color Multi User Visible Light Communication
Venue: IEEE Transactions on Communications
Year: 2019

Consider a fixed orientation multi user visible light communication (VLC) system with multi color light emitting diodes (LEDs) where each transmitter serves a user with limited coordination impeding transmitter side beamforming. In this paper, a multi layer coding and constrained partial group decoding (CPGD) method is proposed to tackle strong color interference and increase the system throughput. After channel model formulation, user information rates are allocated and decoding order for all the received data layers is obtained by solving a max min fairness problem using a greedy algorithm. An achievable rate is derived under the truncated Gaussian input distribution. To reduce the decoding complexity, a map on the decoding order and rate allocation is constructed for all positions of interest on the receiver plane parallel to the transmitter plane, and its size is reduced by a clustering algorithm. Meanwhile, the symmetrical geometry of LED arrays is exploited. Finally, the transmitter user association problem is formulated and solved by a genetic algorithm. It is observed that the system throughput increases as the receivers are slightly misaligned with corresponding LED arrays due to the reduced interference level, but decreases afterwards due to the weakened link gain.
Catalytic properties of transition metals modified nanoscale zero valent iron for simultaneous removal of 4 chlorophenol and Cr(VI) Efficacy, descriptor and reductive mechanisms.
Venue: Journal of hazardous materials
Year: 2021

Since chlorophenols (CPs) and Cr(VI) are two types of common pollutants in the environment, developing an effective approach to remove these contaminants has important benefits for public health. However, few efforts have been made so far. In this study, we prepared nanoscale zero valent iron (nZVI) and a series of bimetallic nanoparticles (transition metal modified nZVI) to investigate their catalytic properties for the simultaneous removal of 4 chlorophenol (4 CP) and Cr(VI) While nZVI enabled a fast removal of Cr(VI) it had a poor dechlorination ability. However, effective simultaneous removal of 4 CP and Cr(VI) was achieved with the transition metal modified nZVI, especially in the Pd/Fe bimetallic system. The enhanced catalytic activity of transition metal modified nZVI was primarily attributed to the formations of numerous nano galvanic cells and atomic hydrogen species that facilitated electron transfer in the reaction system and played a key role in triggering the C Cl bond cleavage, respectively. According to the dechlorination ability, the transition metal catalysts examined in this study can be divided into three groups in descending order: the first being Pd and Ni, the second including Cu and Pt, while the last consisting of Au and Ag. The catalytic hydrodechlorination activity of bimetals can be well described by the volcano curve and rationally explained by the hydrogen adsorption energies on the metals, and was severely impaired by increasing Cr(VI) concentrations. Characterization results validated the formations of Fe(III) Cr(III) hydroxide/oxyhydroxide on the bimetals surface after reacting with 4 CP and Cr(VI) This work provides the first insight into the catalytic properties of transition metal modified nZVI for the effective removal of combined pollutants.
Case Studies of a Machine Learning Process for Improving the Accuracy of Static Analysis Tools
Year: 2016

Static analysis tools analyze source code and report suspected problems as warnings to the user. The use of these tools is a key feature of most modern software development processes; however, the tools tend to generate large result sets that can be hard to process and prioritize in an automated way. Two particular problems are (a) a high false positive rate, where warnings are generated for code that is not problematic and (b) a high rate of non actionable true positives, where the warnings are not acted on or do not represent significant risks to the quality of the source code as perceived by the developers. Previous work has explored the use of machine learning to build models that can predict legitimate warnings with logistic regression [38] against Google Java codebase.  experimented with 15 machine learning algorithms on two open source projects to classify actionable static analysis alerts. In our work, we seek to replicate these ideas on different target systems, using different static analysis tools along with more machine learning techniques, and with an emphasis on security related warnings. Our experiments indicate that these models can achieve high accuracy in actionable warning classification. We found that in most cases, our models outperform those of Heckman [19]
Automotive Data Certification Problem: A View on Effective Blockchain Architectural Solutions
Venue: 2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)
Year: 2020

The automotive industry is evolving with connected, autonomous, and electric vehicles handling huge amounts of data exchanges between participants in its ecosystem. These data transactions should be certified and valid for the ecosystem to function in an efficient and trusted manner. To address the data integrity and provenance issues, we adopt blockchain technology. In this paper, we propose a consortium blockchain architecture to solve the popular use case of odometer fraud in the automotive industry. We design the architecture from two approaches: a non wallet and wallet based vehicle data certification followed by its Qualitative and Quantitative evaluation.
Efficient Deep CNN Based Fire Detection and Localization in Video Surveillance Applications
Venue: IEEE Transactions on Systems, Man, and Cybernetics: Systems
Year: 2019

Convolutional neural networks (CNNs) have yielded state of the art performance in image classification and other computer vision tasks. Their application in fire detection systems will substantially improve detection accuracy, which will eventually minimize fire disasters and reduce the ecological and social ramifications. However, the major concern with CNN based fire detection systems is their implementation in real world surveillance networks, due to their high memory and computational requirements for inference. In this paper, we propose an original, energy friendly, and computationally efficient CNN architecture, inspired by the SqueezeNet architecture for fire detection, localization, and semantic understanding of the scene of the fire. It uses smaller convolutional kernels and contains no dense, fully connected layers, which helps keep the computational requirements to a minimum. Despite its low computational needs, the experimental results demonstrate that our proposed solution achieves accuracies that are comparable to other, more complex models, mainly due to its increased depth. Moreover, this paper shows how a tradeoff can be reached between fire detection accuracy and efficiency, by considering the specific characteristics of the problem of interest and the variety of fire data.
Finding rigid sub structure patterns from 3D point sets
Venue: 2016 23rd International Conference on Pattern Recognition (ICPR)
Year: 2016

In this paper, we study the following rigid substructure pattern reconstruction problem: given a set of n input structures (i.e. point sets) partition each structure into k rigid sub structures so that the nk rigid substructures can be grouped into k clusters with each of them containing exact one rigid substructure from every input structure and the total clustering cost is minimized, where the clustering cost of a cluster is the total distance between a pattern reconstructed for this cluster and every member rigid substructure. Different from most of the existing models for pattern reconstruction (where each input point set is often treated as a single structure) our model views each input point set as a collection of k rigid substructures, and aims to extract similar rigid substructures from each input point set to form k rigid clusters. The problem is motivated by an interesting biological application for determining the topological structure of chromosomes inside the cell nucleus. We propose a highly effective and practical solution based on a number of new insights to pattern reconstruction, clustering, and motion detection. We validate our method on synthetic, biological and motion tracking datasets. Experimental results suggest that our approach yields a near optimal solution.