nils-herrmann/clean_scirepeval huggingface dataset:
PointConv: Deep Convolutional Networks on 3D Point Clouds
Venue: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2019

Unlike images which are represented in regular dense grids, 3D point clouds are irregular and unordered, hence applying convolution on them can be difficult. In this paper, we extend the dynamic filter to a new convolution operation, named PointConv. PointConv can be applied on point clouds to build deep convolutional networks. We treat convolution kernels as nonlinear functions of the local coordinates of 3D points comprised of weight and density functions. With respect to a given point, the weight functions are learned with multi layer perceptron networks and the density functions through kernel density estimation. A novel reformulation is proposed for efficiently computing the weight functions, which allowed us to dramatically scale up the network and significantly improve its performance. The learned convolution kernel can be used to compute translation invariant and permutation invariant convolution on any point set in the 3D space. Besides, PointConv can also be used as deconvolution operators to propagate features from a subsampled point cloud back to its original resolution. Experiments on ModelNet40, ShapeNet, and ScanNet show that deep convolutional neural networks built on PointConv are able to achieve state of the art on challenging semantic segmentation benchmarks on 3D point clouds. Besides, our experiments converting CIFAR 10 into a point cloud showed that networks built on PointConv can match the performance of convolutional networks in 2D images of a similar structure.
Molecular Dynamics Study of Thermal Energy Transport in Graphene Based Materials
Year: 2018

Self heating is a critical issue in micro and nano electronics, and efficient heat removal is crucial for the long term reliability and performance of micro and nano electronic devices. In many semiconductor devices, the power dissipation is non uniform, which results in hot spots in the device and makes the heat removal very complicated. When two dimensional materials are used for the electronic applications, heat dissipation problem can be aggregated because even a small amount of Joule heat can lead to a dramatic temperature rise in the ultrathin materials. In industrial practice, high performance site specific heat spreader and thermoelectric material based solid cooling component are two potential tools for the hot spot mitigation. Graphene, which has ultrahigh thermal conductivity, electrical conductivity and thermoelectric power factors, can potentially be used as the core material for these two applications. In my Ph.D. study, the thermal transport properties of graphene and its derivatives were investigated using classical molecular dynamics simulations. The research goal was to understand how the chemical functionalization, isotopic effects and structural modification to influence the phonon transport in graphene and across graphene metal interfaces, which could provide important insights to the thermal transport physics in graphene, and are of practical significance for graphene based devices in nano electronics and thermal management applications. Four projects have been finished in my Ph.D. study. In the first project, the phonon transport physics of pristine graphene, hydrogenated graphene and graphene oxide was investigated using large scale molecular dynamics simulations. For the pristine graphene, highly ballistic thermal transport was observed. As for the hydrogenated graphene and graphene oxide, the thermal conductivity was significantly reduced when the hydrogen and oxygen coverage increased. For example, an oxygen coverage of 5% could reduce the graphene's thermal conductivity by ~90% and a coverage of 20% oxygen could lower it to ~8.8 W/mK. This value is even smaller than the calculated thermal conductivity of graphene in amorphous limit ~11.6 W/mK) which is usually regarded as the lower boundary of graphene's thermal conductivity. The vibrational power spectral analyses showed that this large reduction in thermal conductivity was due to the significantly enhanced phonon scattering induced by the oxygen and hydrogen defects. In the second project, the thermal conductivity of oxidized polycrystalline graphene was studied. Grain boundaries and the spontaneous oxidization around grain boundary regions are the inherent features of graphene. Our study found the thermal conductivity of oxidized polycrystalline graphene decreased as oxygen coverage increased, which was due to the phonon defect scattering. However, the relative thermal conductivity reduction of oxidized polycrystalline graphene when the oxidization was localized at the grain boundary regions was much smaller compared.
[What is a "poison" Proposal of definition]
Venue: Medicina clinica
Year: 2012

We discuss different interpretations of the term poison as well as the need of bringing up to date the changes in this matter according to the science progress. A clear and exact definition is proposed after analysing the factors that affect the relativity of the concept and its boundaries. The proposal for a definition is presented taking into account the most broadly extended concepts concerning its significance. That is to say: "a poison is, for human beings and their non pathogenic and non harmful biological environment, an electromagnetic or corpuscular radiation, or a non infectious chemical agent, structured no larger in size than a small particle or fibre that, after being generated internally or after contact, penetration and/or absorption by a live organism, in sufficiently high dose, can produce or produces a direct or indirect adverse effect unrelated to its temperature or measurable electrical potential difference" The scientific knowledge needs accurate definitions to avoid ambiguities.
Prevalence of Gastrointestinal Tract Lesions in Patients with Iron Deficiency Anemia
Year: 2020

the Iron deficiency anemia (IDA) is a common cause of referral to medical departments. Chronic gastrointestinal (GI) blood loss is important cause of IDA and also an alarming sign of serious underlying disease. The information concerning ideal evaluation of the gastrointestinal tract in patients with the IDA is scant. We designed a prospective study to determine the frequency of GI tract lesions in patients with the IDA.  This cross sectional study was conducted since January 2006 to January 2008 at Imam Hospital, Urmia in the west of Iran. The study population was comprised of 227 patients including men over 40 years and post menopausal women with probable IDA. After identification of patients, we extracted detailed data via medical records, history taking, physical examination and laboratory. Data was analyzed by the chi square and student's t test.  the patients totally underwent 478 in 214 upper GI endoscopies, 179 colonoscopies, and 85 bariumenema. The mean age of subjects was 61 years (SD+ 15) and 55% were women. Upper GI lesions (esophagitis, gastritis, peptic ulcer and gastric cancer) accounted 32.1 (73 case) percent of cases. Colonoscopy findings include: polyps of colon were found in 10 (4.4% of cases and colon cancer in 15 (6.6% Etiology of IDA was not detected in 126 (55.5% of our patients.  We concluded despite relatively low rate of malignant gastrointestinal lesions that were found in our study, GI tract assessment is necessary in iron deficiency anemia, chiefly in the patients with symptoms related to upper or lower gastrointestinal tract.
Qualitative Evaluation of RFID Implementation on Warehouse Management System
Year: 2018

Logistic sector actors need innovation to improve competitiveness in providing their best services to consumers, one of them on Warehouse Management System (WMS) because the system is used to control the movement of the supply chain. There is a problem in one of Indonesia logistics companies on the process of selecting goods, so the warehouseman still difficulties in this process. Thus, RFID implementation on WMS becomes one of the solutions to handle the goods selection process. This research uses  which focuses on developing and improving the model performance of a system and using waterfall model for system development. Then the authors will analyze the test results with the validity test and reliability test of the questionnaire, and the results of the data analysis will determine the feasibility of this research to be applied.
Size distribution prediction of nanoparticle agglomerates in a fluidized bed
Year: 2016

Nanoparticles have acquired considerable attention from academia and industry due to their unique properties arising from the large surface area to volume ratio. A promising method to process these particles is fluidization. Furthermore, it is worth knowing that nanoparticles fluidize as clusters called agglomerates, formed by the relatively strong adhesion forces among the individual particles (1)
Showcasing the brightest minds from Australia and beyond: come to Melbourne for Sports Medicine Australia's annual conference (14 17 October 2020)
Venue: British Journal of Sports Medicine
Year: 2020

Sports Medicine Australia (SMA) is excited to announce that our 2020 annual conference is returning to Melbourne, the home of Australian rules football (figure 1) Fittingly, we begin this SMA British Journal of Sports Medicine (BJSM) edition by highlighting the landmark paper by PhD student Daniel Hoffman, who analysed 20 years of injury data to link injury incidence to Australian rules football team performance See page 475 While the injury team performance link is established in elite soccer, this paper is the first to establish how important effective injury risk reduction strategies are to team success in Australian rules football. Figure 1 Your invitation to the Sports Medicine Australia Conference, Melbourne, 14 17 October 2020. As you walk around Melbourne's Albert Park Lake to the 2020 SMA conference venue, contemplate the ever increasing scientific evidence on the importance of physical activity to our personal and professional lives. SMA is proud to play a key leadership role in the healthy performance and participation of Australians in physical activity and sport. Want up to date information? Dr Melody Ding's review paper See page 462
IMMUNOSUPPRESIVE EFFECTS OF THE METHANOLIC EXTRACT OF CHRYSOPHYLLUM CAINITO LEAVES ON MACROPHAGE FUNCTIONS
Venue: African journal of traditional, complementary, and alternative medicines AJTCAM
Year: 2017

The aim of this work was to evaluate the immunomodulatory effect of the methanol extract (MeOH) from Chrysophyllum cainito leaves on the MPhs functions.  Peritoneal murine MPhs isolated from Balb/c mice were treated with the MeOH extract and stimulated with LPS. The effect on the phagocytosis was evaluated by flow cytometry assay. The nitric oxide (NO) and hydrogen peroxide (H2O2) production was measured by the Griess reagent and phenol red reaction, respectively. Levels of IL 6 and TNF a was measured using an ELISA kit. Viability of MPhs and Vero cells was determined by the MTT method.  The MeOH extract of C. cainito leaves inhibited significantly the phagocytosis, and decreased IL 6 and TNF a production as well as NO and H2O2 released by the MPhs, in a concentration dependent manner. In addition, MeOH extract of C. cainito showed low cytotoxicity effect against the cells.  These results suggest that MeOH extract of C. cainito leaves has an immunosuppressive effect on murine MPhs, without effects on cell viability. GC MS chromatogram analysis of MeOH extract showed that lupeol acetate and alpha amyrin acetate are the principal compounds.
Management of Bovine Sub Clinical Mastitis with TANUVAS MASTI GUARD
Year: 2020

Mastitis has been recognized as a major disease affecting the dairy industry, especially in its subclinical form. Subclinical mastitis cause economic losses by decreasing milk production, cost of therapy and unused milk during the withdrawal period. Clinical mastitis can be detected by farmer but subclinical mastitis can only be detected by the measurement of inflammatory components and pathogens in the milk. Since somatic cell count (SCC) in milk has been shown to be an excellent marker for subclinical mastitis it can be used to detect the subclinical mastitis. The prevention of bovine mastitis is the most important component of a mastitis control programme. TANUVAS MASTI Guard will be used as most effective management strategy for preventing new intra mammary infection (IMI) The ingredients present in the spraying solution kill the bacteria present on the teat and controls occurrence of subclinical mastitis.
Transmission Electron Microscopy (TEM) and Scanning Electron Microscopy (SEM) for the Examination of Dental Hard Tissues.
Venue: Methods in molecular biology
Year: 2019

This chapter describes laboratory protocols for TEM and SEM approaches allowing the examination of the dental hard tissues' constituents at the ultrastructural level. TEM has the highest resolution power to examine the cellular and extracellular matrix ultrastructure inside a given sample, detecting the presence, location, and quantification of organelles related to the metabolism of the cell type as well as membrane specializations. SEM allows the observation of the sample surface, for examining dimensional topography and distribution of exposed features.
Confusion2Vec: towards enriching vector space word representations with representational ambiguities
Venue: PeerJ Comput. Sci.
Year: 2019

Word vector representations are a crucial part of natural language processing (NLP) and human computer interaction. In this paper, we propose a novel word vector representation, Confusion2Vec, motivated from the human speech production and perception that encodes representational ambiguity. Humans employ both acoustic similarity cues and contextual cues to decode information and we focus on a model that incorporates both sources of information. The representational ambiguity of acoustics, which manifests itself in word confusions, is often resolved by both humans and machines through contextual cues. A range of representational ambiguities can emerge in various domains further to acoustic perception, such as morphological transformations, word segmentation, paraphrasing for NLP tasks like machine translation, etc. In this work, we present a case study in application to automatic speech recognition (ASR) task, where the word representational ambiguities/confusions are related to acoustic similarity. We present several techniques to train an acoustic perceptual similarity representation ambiguity. We term this Confusion2Vec and learn on unsupervised generated data from ASR confusion networks or lattice like structures. Appropriate evaluations for the Confusion2Vec are formulated for gauging acoustic similarity in addition to semantic syntactic and word similarity evaluations. The Confusion2Vec is able to model word confusions efficiently, without compromising on the semantic syntactic word relations, thus effectively enriching the word vector space with extra task relevant ambiguity information. We provide an intuitive exploration of the two dimensional Confusion2Vec space using principal component analysis of the embedding and relate to semantic relationships, syntactic relationships, and acoustic relationships. We show through this that the new space preserves the semantic/syntactic relationships while robustly encoding acoustic similarities. The potential of the new vector representation and its ability in the utilization of uncertainty information associated with the lattice is demonstrated through small examples relating to the task of ASR error correction.
Climate change impacts on renewable energy generation. A review of quantitative projections
Year: 2019

Research on climate change impacts on renewable energy is becoming increasingly relevant due to the vulnerability of the sector and to the continual development of methodologies and availability of data. Public and private decision making needs specific research. However, many gaps still exist in certain geographical regions and technologies. Providing economic estimates with a value chain perspective are also missing from most papers. This paper addresses the most relevant studies that project quantitative estimates of climate change impacts on solar, wind, hydro and other renewable generation technologies.  of impacts and projections are provided so that researchers, governments and the private sector may have an accurate view of the state of the art on this topic.
Catalytic intense pulse light inactivation of Cronobacter sakazakii and other pathogens in non fat dry milk and wheat flour.
Venue: Food chemistry
Year: 2020

The outbreaks of Cronobacter sakazakii, Salmonella spp, and Bacillus cereus in powdered foods have been increasing in worldwide. However, an effective method to pasteurize powdered foods before consumption remains lacking. A prototype Intense Pulsed Light (IPL) system was developed to disinfect powdered foods under different IPL and environmental conditions. Synergistic effect of IPL and TiO2 photocatalysis on microbial inactivation was studied. The results show that high energy intensity of each pulse, high peak intensity, and short pulsed duration contributed to a high microbe inactivation. With TiO2 photocatalysis, one additional log10 reduction was achieved, bringing the total log reduction to 4.71 0.07 (C. sakazakii) 3.49 0.01 (E. faecium) and 2.52 0.10 (B. cereus) in non fat dry milk, and 5.42 0.10 (C. sakazakii) 4.95 0.24 (E. faecium) 2.80 0.23 (B. cereus) in wheat flour. IPL treatment combined with the TiO2 photocatalysis exhibits a strong potential to reduce the energy consumption in improving the safety of powdered foods.
Data Driven Robust Taxi Dispatch Under Demand Uncertainties
Venue: IEEE Transactions on Control Systems Technology
Year: 2019

In modern taxi networks, large amounts of taxi occupancy status and location data are collected from networked in vehicle sensors in realtime. They provide knowledge of system models on passenger demand and mobility patterns for efficient taxi dispatch and coordination strategies. Such approaches face new challenges: how to deal with uncertainties of predicted customer demand while fulfilling the system's performance requirements, including minimizing taxis' total idle mileage and maintaining service fairness across the whole city; how to formulate a computationally tractable problem. To address this problem, we develop a data driven robust taxi dispatch framework to consider spatial temporally correlated demand uncertainties. The robust vehicle dispatch problem we formulate is concave in the uncertain demand and convex in the decision variables. Uncertainty sets of random demand vectors are constructed from data based on theories in hypothesis testing, and provide a desired probabilistic guarantee level for the performance of robust taxi dispatch solutions. We prove equivalent computationally tractable forms of the robust dispatch problem using the minimax theorem and strong duality. Evaluations on four years of taxi trip data for New York City show that by selecting a probabilistic guarantee level at 75% the average demand supply ratio error is reduced by 31.7% and the average total idle driving distance is reduced by 10.13% or about 20 million miles annually, compared with nonrobust dispatch solutions.
Multiclass Object Detection in UAV Images Based on Rotation Region Network
Venue: IEEE Journal on Miniaturization for Air and Space Systems
Year: 2020

The object detection in UAV application is a challenging task due to the diversity of target scales, variation of views, and complex backgrounds. To solve several challenges, including dense objects, objects with arbitrary orientation, and diversity of aspect ratios, this article proposes an end to end object detection method based on the convolutional neural network. In this article, the feature extraction performance is enhanced by utilizing a deep residual neural network. Multiscale feature maps are obtained through fusion with different convolutional layers, thus combining the high level semantic information and low level detail information. A rotation region proposal network is adopted to generate rotated regions, which makes the bounding box sensitive to dense objects in aerial images. Meanwhile, the RoIAlign is used and a convolution layer is appended in the classification stage, and focal loss is used in the classification stage. The proposed method focuses on arbitrary oriented and dense objects in UAV images. After a comprehensive evaluation with several state of the art object detection algorithms, the proposed method is proved to be effective to detect multiclass artificial objects in aerial images. Extensive experiments are conducted on the DOTA, VEDAI, and the VisDrone UAV image datasets, which demonstrate that the proposed method can obtain discriminative features through the improved multiscale feature extraction and the rotating region network. The results on the above datasets show that our method obtains gains in mean average precision compared with several state of the art methods.
EVALUATING A CONSUMER DIRECTED HEALTH CARE PILOT FOR OLDER PEOPLE IN THE COMMUNITY
Venue: Innovation in Aging
Year: 2019

In an ageing society with a policy focus on community (Oireachtas 2017) providing choice and self determination in home care provision for older people is fundamental. Consumer directed care has increased in popularity in many countries (Low, Yap Brodaty, 2011) In 2016, planning began in Community Healthcare Organisation 3 to pilot a CDHC pilot for community based older people. This study presents the findings of this pilot project. The study used the Moore et al.'s (2015) evaluation approach. Data collection methods were via descriptive questionnaires with qualitative investigation of stakeholder experiences as well as an economic review. Findings demonstrated the need for additional clarity in understandings of the CDHC. Care recipients and caregivers did report satisfaction with care, however, it was the accessibility of care rather than choice that was considered important. There were also issues related to capacity to manage the CDHC as well as capacity to give a choice of providers, particularly in rural areas. Although, broadly cost neutral, processes and structures also require additional alignment to enhance both effectiveness and efficiency. Empowering care recipients and enabling greater choice, flexibility and autonomy in care organisation and delivery was a central focus of the CDHC pilot. However, additional consumer awareness and programme enhancement is needed to fully realize the potential of the CDHC. Study recommendations focus on areas of increased clarity about the CDHC, implementation enhancement, complementarity and incorporation of CDHC with existing home support service provision arrangements