nils-herrmann/clean_scirepeval huggingface dataset:
A Dual Band Low Profile Aperture Antenna With Substrate Integrated Waveguide Grooves
Venue: IEEE Transactions on Antennas and Propagation

This communication presents a new dual band low profile aperture antenna with relatively high gain using substrate integrated waveguide (SIW) corrugated structures. It consists of a cavity excited by a transmission line and four SIW grooves that produce good reflection coefficient and enhanced gain. By designing corrugated structure using constructive superposition of electric fields of patch and grooves, the antenna with high performance in both bands is achieved. In the proposed structure, three simple printed circuit boards (PCBs) for implementing a resonant transmission line and specific SIW structures are employed instead of waveguide feeder and grooves on metallic plate in conventional corrugated antennas. Removing the metallic plate reduces the weight and cost of the structure and provides ease of fabrication. Dual band characteristic is achieved using resonant slot (cavity) and resonant transmission line. Fabrication results show that the SIW grooves significantly increase the antenna gain with respect to the simple slot antenna.
Explaining Topical Distances Using Word Embeddings
Venue: 2016 27th International Workshop on Database and Expert Systems Applications (DEXA)

Word and document embeddings have gained a lot of attention recently, because they tend to work well in text mining tasks. Yet, they elude humans intuition. In this paper we are making the attempt to explain the arithmetic difference between two document embeddings by a series of word embeddings. We present an algorithm that iteratively picks words from a vocabulary that closes the topical gap between the documents. Moreover, we present the Econstor16 corpus that was used for the experiments. Although not all words that are found are great matches, the algorithm is able to find sets of words that are reasonable to a human that reads both documents. Remarkably, some of the well explaining words are mentioned in neither documents.
Multi agent based framework for person re identification in video surveillance
Venue: 2016 Future Technologies Conference (FTC)

Multi agent based systems have been used in a number of practical application domains. However their use in computer vision based systems that often provide solutions to automated video surveillance, remains in its infancy. Addressing this gap in research this paper proposes a novel design, based on multi agents, to address one of the most important open research problems in video surveillance, i.e. person re identification. The re design of a typical computer vision based solution for the problem is based on our analysis of the problem considering how a human observer would successfully carry out person re identification. Hence the proposed approach mimics human behavior and promises many advantages over the existing approaches that do not consider such a human behavior based approach. We provide preliminary experimental results to justify the contribution of the proposed novel approach to person re identification and conclude the paper with insights to future research that has potential for a new paradigm of research in person re identification in video surveillance.
Ecological networks are more sensitive to plant than to animal extinction under climate change
Venue: Nature communications

Impacts of climate change on individual species are increasingly well documented, but we lack understanding of how these effects propagate through ecological communities. Here we combine species distribution models with ecological network analyses to test potential impacts of climate change on >700 plant and animal species in pollination and seed dispersal networks from central Europe. We discover that animal species that interact with a low diversity of plant species have narrow climatic niches and are most vulnerable to climate change. In contrast, biotic specialization of plants is not related to climatic niche breadth and vulnerability. A simulation model incorporating different scenarios of species coextinction and capacities for partner switches shows that projected plant extinctions under climate change are more likely to trigger animal coextinctions than vice versa. This result demonstrates that impacts of climate change on biodiversity can be amplified via extinction cascades from plants to animals in ecological networks.
Progress to extinction: increased specialisation causes the demise of animal clades
Venue: Scientific reports

Animal clades tend to follow a predictable path of waxing and waning during their existence, regardless of their total species richness or geographic coverage. Clades begin small and undifferentiated, then expand to a peak in diversity and range, only to shift into a rarely broken decline towards extinction. While this trajectory is now well documented and broadly recognised, the reasons underlying it remain obscure. In particular, it is unknown why clade extinction is universal and occurs with such surprising regularity. Current explanations for paleontological extinctions call on the growing costs of biological interactions, geological accidents, evolutionary traps, and mass extinctions. While these are effective causes of extinction, they mainly apply to species, not clades. Although mass extinctions is the undeniable cause for the demise of a sizeable number of major taxa, we show here that clades escaping them go extinct because of the widespread tendency of evolution to produce increasingly specialised, sympatric, and geographically restricted species over time.
Fast revascularization of the injured area is essential to support zebrafish heart regeneration
Venue: Proceedings of the National Academy of Sciences

A heart attack occurs when blood flow to part of the heart is blocked, and oxygen and nutrients are unable to reach that tissue, irreversibly damaging cardiac muscle cells. Dead muscle cells are replaced by a noncontractile scar that affects cardiac function. Unlike humans, zebrafish can regenerate their heart after injury, replacing the scarred tissue with new cardiomyocytes. Understanding the mechanisms zebrafish deploy to regenerate their heart may help us design more efficient therapies for human heart disease. In this study, we show that to regenerate their heart, zebrafish quickly revascularize the damaged area, and that this ability to revascularize is temporally restricted. Zebrafish have a remarkable capacity to regenerate their heart. Efficient replenishment of lost tissues requires the activation of different cell types including the epicardium and endocardium. A complex set of processes is subsequently needed to support cardiomyocyte repopulation. Previous studies have identified important determinants of heart regeneration; however, to date, how revascularization of the damaged area happens remains unknown. Here, we show that angiogenic sprouting into the injured area starts as early as 15 h after injury. To analyze the role of vegfaa in heart regeneration, we used vegfaa mutants rescued to adulthood by vegfaa mRNA injections at the one cell stage. Surprisingly, vegfaa mutants develop coronaries and revascularize after injury. As a possible explanation for these observations, we find that vegfaa mutant hearts up regulate the expression of potentially compensating genes. Therefore, to overcome the lack of a revascularization phenotype in vegfaa mutants, we generated fish expressing inducible dominant negative Vegfaa. These fish displayed minimal revascularization of the damaged area. In the absence of fast angiogenic revascularization, cardiomyocyte proliferation did not occur, and the heart failed to regenerate, retaining a fibrotic scar. Hence, our data show that a fast endothelial invasion allows efficient revascularization of the injured area, which is necessary to support replenishment of new tissue and achieve efficient heart regeneration. These findings revisit the model where neovascularization is considered to happen concomitant with the formation of new muscle. Our work also paves the way for future studies designed to understand the molecular mechanisms that regulate fast revascularization.
Underwater acoustic networks testbed for ecological monitoring of Qinghai Lake
Venue: OCEANS 2016 Shanghai

The past few years have witnessed a significant progress in research of underwater acoustic networks. Some MAC and routing protocols tailored for underwater acoustic networks have been proposed. However, it is difficult and costly to build real underwater network systems as well as conduct field experiments, and most researches are based on theoretical analysis and simulations. To facilitate evaluating research work in real environment, we develop a testbed in Qinghai Lake based on Orthogonal Frequency Division Multiplexing (OFDM) modems and Micro ANP protocol stack. Based on the testbed, we conduct a number of tests including protocol evaluation and water quality monitoring of Qinghai Lake on real time.
Contact dependent mechanical properties of graphene nanoribbons: an ab initio study.
Venue: Nanotechnology

The mechanical properties of graphene nanoribbons on Ni(111) surfaces with different contact sizes are investigated by means of density functional theory. For finite contact sizes, the stress behavior of graphene nanoribbons on metal electrodes is likely to be similar to that of suspended graphene, however the critical strain is not reached due to the sliding friction at the interface. The competition between frictional and external forces is responsible for the nonmonotonic stress behavior. It is indicated that the stick slip motions of graphene on Ni(111) are as a result of applied external forces on the GNR/metal contact. Moreover, the effect of vacancies and chemical doping on the sliding friction are addressed. Graphene starts to slide on the surface under a much lower external force in the case of defected graphene, due to the weaker binding to the surface. For infinite contact sizes, a linear relationship between stress and strain are found until structural failure occurs by 11% applied strain. The corresponding critical strain for the suspended GNR (without electrodes) has been found to be 13%
Low Dose CT Screening for Lung Cancer: Computer aided Detection of Missed Lung Cancers.
Venue: Radiology

To update information regarding the usefulness of computer aided detection (CAD) systems with a focus on the most critical category, that of missed cancers at earlier imaging, for cancers that manifest as a solid nodule.  By using a HIPAA compliant institutional review board approved protocol where informed consent was obtained, 50 lung cancers that manifested as a solid nodule on computed tomographic (CT) scans in annual rounds of screening (time 1) were retrospectively identified that could, in retrospect, be identified on the previous CT scans (time 0) Four CAD systems were compared, which were referred to as CAD 1, CAD 2, CAD 3, and CAD 4. The total number of accepted CAD system detected nodules at time 0 was determined by consensus of two radiologists and the number of CAD system detected nodules that were rejected by the radiologists was also documented.  At time 0 when all the cancers had been missed, CAD system detection rates for the cancers were 56% 70% 68% and 60% (k 0.45) for CAD systems 1, 2, 3, and 4, respectively. At time 1, the rates were 74% 82% 82% and 78% (k 0.32) respectively. The average diameter of the 50 cancers at time 0 and time 1 was 4.8 mm and 11.4 mm, respectively. The number of CAD system detected nodules that were rejected per CT scan for CAD systems 1 4 at time 0 was 7.4, 1.7, 0.6, and 4.5 respectively.  CAD systems detected up to 70% of lung cancers that were not detected by the radiologist but failed to detect about 20% of the lung cancers when they were identified by the radiologist, which suggests that CAD may be useful in the role of second reader. (c) RSNA, 2016.
A Grid Connected PV System Integrated with Battery Energy Storage Through Three port Isolated DC DC Converter

It contains an inductor capacitor inductor (LCL) resonant circuit to achieve zero current switching (ZCS) for the main switch. The proposed converter has the advantage of using the least number of switches and soft switching for the main switch, which is realized by using an inductor capacitor inductor LCL resonant circuit. The converter is capable of interfacing sources of different voltage current characteristics with a load and/or a dc micro grid. This is a new isolated three port bidirectional dc dc converter, which uses the minimum number of switches The proposed converter is applied for simultaneous power management of a photovoltaic (PV) system with a battery. The PV system and the battery are connected to the unidirectional port and the bidirectional port of the converter, respectively. A maximum power point tracking (MPPT) algorithm is designed for the PV panel to generate the maximum power when solar radiation is available. A charge and discharge controller is designed to control the battery to either absorb the surplus power generated by the PV panel or supply the deficient power required by the load. The simulation results are presented by using Mat lab/Simulink software.
On the Use of Gaussian Mixture Model Framework to Improve Speaker Adaptation of Deep Neural Network Acoustic Models
Venue: INTERSPEECH

In this paper we investigate the Gaussian Mixture Model (GMM) framework for adaptation of context dependent deep neural network HMM (CD DNN HMM) acoustic models. In the previous work an initial attempt was introduced for efficient transfer of adaptation algorithms from the GMM framework to DNN models. In this work we present an extension, further detailed exploration and analysis of the method with respect to state of the art speech recognition DNN setup and propose various novel ways for adaptation performance improvement, such as, using bottleneck features for GMM derived feature extraction, combination of GMM derived with conventional features at different levels of DNN architecture, moving from monophones to triphones in the auxiliary GMM model in order to extend the number of adapted classes, and finally, using latticebased information and confidence scores in maximum a posteriori adaptation of the auxiliary GMM model. Experimental results on the TED LIUM corpus show that the proposed adaptation technique can be effectively integrated into DNN setup at different levels and provide additional gain in recognition performance.
Improved Multilingual Training of Stacked Neural Network Acoustic Models for Low Resource Languages
Venue: INTERSPEECH

This paper proposes several improvements to multilingual training of neural network acoustic models for speech recognition and keyword spotting in the context of low resource languages. We concentrate on the stacked architecture where the first network is used as a bottleneck feature extractor and the second network as the acoustic model. We propose to improve multilingual training when the amount of data from different languages is very different by applying balancing scalers to the training examples. We also explore how to exploit multilingual data to train the second neural network of the stacked architecture. An ensemble training method that can take advantage of both unsupervised pretraining as well as multilingual training is found to give the best speech recognition performance across a wide variety of languages, while system combination of differently trained multilingual models results in further improvements in keyword search performance.
Heavy Metal Contamination of Soils around a Hospital Waste Incinerator Bottom Ash Dumps Site
Venue: Journal of environmental and public health

Waste incineration is the main waste management strategy used in treating hospital waste in many developing countries. However, the release of dioxins, POPs, and heavy metals in fly and bottom ash poses environmental and public health concerns. To determine heavy metal (Hg, Pb, Cd, Cr, and Ag) in levels in incinerator bottom ash and soils 100 m around the incinerator bottom ash dump site, ash samples and surrounding soil samples were collected at 20 m, 40 m, 60 m, 80 m, 100 m, and 1,200 m from incinerator. These were analyzed using the absorption spectrophotometer method. The geoaccumulation (I geo) and pollution load indices (PLI) were used to assess the level of heavy metal contamination of surrounding soils. The study revealed high concentrations in mg/kg for, Zn (16417.69) Pb (143.80) Cr (99.30) and Cd (7.54) in bottom ash and these were above allowable limits for disposal in landfill. The study also found soils within 60 m radius of the incinerator to be polluted with the metals. It is recommended that health care waste managers be educated on the implication of improper management of incinerator bottom ash and regulators monitor hospital waste incinerator sites.
Learning cooking skills at different ages: a cross sectional study
Venue: International Journal of Behavioral Nutrition and Physical Activity

BackgroundCooking skills are increasingly included in strategies to prevent and reduce chronic diet related diseases and obesity. While cooking interventions target all age groups (Child, Teen and Adult) the optimal age for learning these skills on: 1) skills retention, 2) cooking practices, 3) cooking attitudes, 4) diet quality and 5) health is unknown. Similarly, although the source of learning cooking skills has been previously studied, the differences in learning from these different sources has not been considered. This research investigated the associations of the age and source of learning with the aforementioned five factors.MethodsA nationally representative (Northern/Republic of Ireland) cross sectional survey was undertaken with 1049 adults aged between 20 60 years. The survey included both measures developed and tested by the researchers as well as validated measures of cooking (e.g. chopping) and food skills (e.g. budgeting) cooking practices (e.g. food safety) cooking attitudes, diet quality and health. Respondents also stated when they learnt the majority of their skills and their sources of learning. The data was analysed using ANOVAs with post hoc analysis and Chi2 crosstabs with a significance level of 0.05.ResultsResults showed that child <12 years) and/or teen (13 18 years) learners had significantly greater numbers of, and confidence in, their cooking and food skills, cooking practices, cooking attitudes, diet quality (with the exception of fibre intake where adult learners were higher) and health. Mother was the primary source of learning and those who learnt only from this source had significantly better outcomes on 12 of the 23 measures.ConclusionsThis research highlights the importance of learning cooking skills at an early age for skill retention, confidence, cooking practices, cooking attitude and diet quality. Mother remained the primary source of learning, however, as there is a reported deskilling of domestic cooks, mothers may no longer have the ability to teach cooking skills to the next generation. A focus on alternative sources including practical cooking skills education starting at an early age is required. This study also highlights the need for further longitudinal research on the impact of age and source of learning on cooking skills.
Promoting physical activity for children and adolescents in low and middle income countries: An umbrella systematic review: A review on promoting physical activity in LMIC.
Venue: Preventive medicine

It is unknown how much previous reviews on promoting physical activity (PA) for children and adolescents (aged 6 18years) take into account studies from low and middle income countries (LMIC, based on the World Bank definition) and the level of evidence of the effect of PA interventions in this population. This study aims to answer such questions using an umbrella systematic review approach.  We searched for peer reviewed systematic reviews and original studies in eight electronic databases, screening of reference lists and expert contacts. Information in systematic reviews on PA interventions for children and adolescents from LMIC was discussed. Original studies on PA interventions (randomized controlled trials [RCT] cluster RCT and non RCT) with children and adolescents from LMIC were eligible. We assessed the methodological quality in all studies, and the evidence level of effect on PA in intervention studies.  Fifty systematic reviews (nine meta analyses) and 25 original studies (20 different interventions) met eligibility criteria. Only 3.1% of mentioned studies in previous reviews were from LMIC. Strong and LMIC specific evidence was found that school based, multicomponent, and short term (up to six months) interventions, focused on adolescents primarily (aged 13 18years) can promote PA in children and adolescents from LMIC. Other intervention characteristics had inconclusive evidence due to the low number of studies, low methodological quality, and/or small sample size.  A minimal part of PA interventions mentioned in previous reviews are from LMIC. Our LMIC specific analyses showed priorities of implementation and practical implication that can be used in public policies for PA promotion in LMIC.
Just Do It! Web 2.0 and the Breaking of the Tacit Dimension for Knowledge Acquisition

Does Web 2.0 facilitate the conversion of tacit knowledge to explicit knowledge? Prior research has focused on the conversion of tacit knowledge to explicit within the context of organizations and builds upon assumptions made during the period when information technologies were not readily available and accessible to the general population. Recently, there have been dramatic changes to the information technology landscape due to the advent of Web 2.0. A unique characteristic of the Web 2.0 era is the dissemination and absorption of knowledge and information by almost anyone at any time. This conceptual research in progress builds upon the theory that explicit and tacit knowledge are dichotomous constructs on a continuum scale. We use this theory to examine how features of Web 2.0 convert increasing kinds of tacit knowledge to explicit knowledge; allowing for greater dissemination and acquisition by the layman and artificial intelligence agents. For the layman, we discuss the current limitations we face in empirically documenting and measuring this phenomenon and the benefits of a randomized digital field experiment. We conclude with the implications of the research for academia and practitioners.
Obstacle detection for unmanned ground vehicle on uneven terrain

We propose an obstacle detection algorithm for unmanned ground vehicle on uneven terrain. The key ideas of the proposed algorithm are the use of two layer laser range data to calculate the gradient of a target, which is characterized as either ground or obstacles. The proposed obstacle detection algorithm includes 4 steps: 1) Obtain the distance data for each angle from multiple lidars or a multi layer scan lidar. 2) Calcualate the gradient for each angle of the uneven terrain. 3) Determine ground or obstacle for each angle on the basis of reference gradient. 4) Generate a new distance data for each angle for a virtual laser scanner. The proposed algorithm is verified by various experiments.