nils-herrmann/clean_scirepeval huggingface dataset:
Automation of the kidney function prediction and classification through ultrasound based kidney imaging using deep learning
Venue: npj Digital Medicine
Year: 2019

Prediction of kidney function and chronic kidney disease (CKD) through kidney ultrasound imaging has long been considered desirable in clinical practice because of its safety, convenience, and affordability. However, this highly desirable approach is beyond the capability of human vision. We developed a deep learning approach for automatically determining the estimated glomerular filtration rate (eGFR) and CKD status. We exploited the transfer learning technique, integrating the powerful ResNet model pretrained on an ImageNet dataset in our neural network architecture, to predict kidney function based on 4,505 kidney ultrasound images labeled using eGFRs derived from serum creatinine concentrations. To further extract the information from ultrasound images, we leveraged kidney length annotations to remove the peripheral region of the kidneys and applied various data augmentation schemes to produce additional data with variations. Bootstrap aggregation was also applied to avoid overfitting and improve the model's generalization. Moreover, the kidney function features obtained by our deep neural network were used to identify the CKD status defined by an eGFR of <60 ml/min/1.73 m2. A Pearson correlation coefficient of 0.741 indicated the strong relationship between artificial intelligence (AI) and creatinine based GFR estimations. Overall CKD status classification accuracy of our model was 85.6% higher than that of experienced nephrologists (60.3% 80.1% Our model is the first fundamental step toward realizing the potential of transforming kidney ultrasound imaging into an effective, real time, distant screening tool. AI GFR estimation offers the possibility of noninvasive assessment of kidney function, a key goal of AI powered functional automation in clinical practice.
LA RESPONSABILIDAD SOCIAL EMPRESARIAL (RSE) Y SU INFLUENCIA EN LOS RESULTADOS ECONOMICOS DE LAS EMPRESAS INDUSTRIALES DE LA CIUDAD DE TACNA, PERIODO: 2010 2011
Venue: Ciencia Desarrollo
Year: 2019

El presente articulo tiene por finalidad evaluar si la Responsabilidad Social Empresarial (RSE) que influye en los resultados economicos de las empresas industriales de la ciudad de Tacna,  Actualmente en la region Tacna existen empresas industriales en regular medida, por lo que resulta relevante la necesidad de contar con una estrategia de RSE que confirme el compromiso que las empresas tienen, el de contribuir y colaborar con su entorno. En la investigacion se elaboro un cuestionario a fin de verificar la influencia de la responsabilidad en los resultados economicos de la empresa. Luego se analizo si las empresas industriales aplican practicas o politicas RSE. Enfatizamos en la reputacion cuantia de inversion en la RSE, modalidad y medicion de sus programas y procesos. Finalmente, en como la empresa mide el impacto de sus operaciones a nivel economico, social y ambiental. Con este proposito se utilizo el metodo descriptivo, explicativo, cuantitativo.
The rapid supply chain appraisal approach: A case study of Pakistan mangoes to the United Kingdom
Year: 2011

Pakistan is the third largest exporter of mangoes in the world. However, the export market returns for Pakistan mangoes are among the lowest because of their low quality in terms of disease and physical damage, poor consistency and poor shelf life. The UK market is the second largest export market for Pakistan mangoes after the UAE. This paper reports on the limitations in current supply chain practices identified through a rapid supply chain appraisal of the UK mango chain. Under an Australian government aid initiative, considerable investments in improving postharvest practices, market feedback and capacity building have been made, which have resulted in improved product appearance and fruit quality. Unfortunately, there has been no appreciable improvement in market prices or commitment from the exporters involved. The reasons behind this include the large number of exporters, the costs associated in changing the current system, and the inability to quantify the benefits arising from the implementation of 'best practice'
AIDA: a Knowledge Graph about Research Dynamics in Academia and Industry
Year: 2020

Academia and industry share a complex, multifaceted, and symbiotic relationship. Analysing the knowledge flow between them, understanding which directions have the biggest potential, and discovering the best strategies to harmonise their efforts is a critical task for several stakeholders. While research publications and patents are an ideal media to analyse this space, current datasets of scholarly data can not be used for such a purpose since they lack a high quality characterization of the relevant research topics and industrial sectors. In this paper, we introduce the Academia/Industry DynAmics (AIDA) Knowledge Graph, which describes 14M publications and 8M patents according to the research topics drawn from the Computer Science Ontology. 4M publications and 5M patents are further characterized according to the type of the author's affiliations (academia, industry, or collaborative) and 66 industrial sectors (e.g. automotive, financial, energy, electronics) organized in a two level taxonomy. AIDA was generated by means of an automatic pipeline that integrates data from Microsoft Academic Graph, Dimensions, DBpedia, the Computer Science Ontology, and the Global Research Identifier Database. It is publicly available under CC BY 4.0 and can be downloaded as a dump or queried via a triplestore. We evaluated the parts of the AIDA pipeline on a manually crafted gold standard yielding competitive results.
An Alternative Method for Locating Faults in Transmission Line Networks Based on Time Reversal
Venue: IEEE Transactions on Electromagnetic Compatibility
Year: 2017

We present an alternative method based on the time reversal process to locate faults in transmission line networks. The proposed procedure considers different media for the forward and the backward propagation phases. Specifically, the transverse branch representing the fault is removed from the circuit in the backward propagation since its location represents the solution of the process and, therefore, is not known in advance. The advantage of the proposed method is twofold. First, the proposed backward model requires only one simulation for the time reversed backward propagation phase, thus reducing significantly the computational burden. Second, we demonstrate that this modified backward propagation medium satisfies a property such that the fault location can be identified by computing, in the frequency domain, the argument of the voltage along the line. The theory is first formulated for the case of a lossless homogeneous single phase transmission line; then, its applicability is extended to lossy inhomogeneous transmission line networks. A single phase inhomogeneous transmission line and an inhomogeneous Y shape network are specifically considered to support this claim. We show that the proposed procedure can provide high fault location accuracy (i.e. in the range of \pm 1$ m) using only one observation point. Furthermore, we propose a criterion to link the bandwidth of the sampling system to the desired fault location accuracy.
An Analysis of the New Employee Onboarding Process in Startup
Venue: 2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE)
Year: 2018

Turnover is one of the factors that can cause the development of a company to be hampered, especially for startup. The high level of employee turnover caused by many things, one of them is employee dissatisfaction. Onboarding process is one of the ways that can be used to introduce the new employee to the culture and work environment so that it can develop job satisfaction and convenience. However, to get an effective result, onboarding process should also be done well and systematically. This paper describes how the onboarding process is done by the startups, especially those that specialize in software engineering. The study used literature review, interview and questionnaire methods. The interview was conducted with the leaders of six startups in Yogyakarta, while questionnaires were distributed to employee in each startup who have worked for about one year. The data of the questionnaire were analyzed using descriptive statistics. Based on the results, it was found that all startups have done the five aspects of onboarding on their new employees. But the average value on these five aspects is below 80% The lowest average score of 67% is in the documentation aspect. While the lowest sub aspect is a sub aspect of developer oriented documentation with an average value of 58.22% and this is included in enough criteria.
Neural Scene De rendering
Venue: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2017

We study the problem of holistic scene understanding. We would like to obtain a compact, expressive, and interpretable representation of scenes that encodes information such as the number of objects and their categories, poses, positions, etc. Such a representation would allow us to reason about and even reconstruct or manipulate elements of the scene. Previous works have used encoder decoder based neural architectures to learn image representations, however, representations obtained in this way are typically uninterpretable, or only explain a single object in the scene. In this work, we propose a new approach to learn an interpretable distributed representation of scenes. Our approach employs a deterministic rendering function as the decoder, mapping a naturally structured and disentangled scene description, which we named scene XML, to an image. By doing so, the encoder is forced to perform the inverse of the rendering operation (a.k.a. de rendering) to transform an input image to the structured scene XML that the decoder used to produce the image. We use a object proposal based encoder that is trained by minimizing both the supervised prediction and the unsupervised reconstruction errors. Experiments demonstrate that our approach works well on scene de rendering with two different graphics engines, and our learned representation can be easily adapted for a wide range of applications like image editing, inpainting, visual analogy making, and image captioning.
Ultrahigh Water Content, Superelastic, and Shape Memory Nanofiber Assembled Hydrogels Exhibiting Pressure Responsive Conductivity.
Venue: Advanced materials
Year: 2017

High water content hydrogels that are both mechanically robust and conductive could have wide applications in fields ranging from bioengineering and electronic devices to medicine; however, creating such materials has proven to be extremely challenging. This study presents a scalable methodology to prepare superelastic, cellular structured nanofibrous hydrogels (NFHs) by combining alginate and flexible SiO2 nanofibers. This approach causes naturally abundant and sustainable alginate to assemble into 3D elastic bulk NFHs with tunable water content and desirable shapes on a large scale. The resultant NFHs exhibit the integrated properties of ultrahigh water content (99.8 wt% complete recovery from 80% strain, zero Poisson's ratio, shape memory behavior, injectability, and elastic responsive conductivity, which can detect dynamic pressure in a wide range >50 Pa) with robust sensitivity (0.24 kPa 1 and durability (100 cycles) The fabrication of such fascinating materials may provide new insights into the design and development of multifunctional hydrogels for various applications.
Besides population age structure, health and other demographic factors can contribute to understanding the COVID 19 burden
Venue: Proceedings of the National Academy of Sciences
Year: 2020

An insightful paper by Dowd et al. (1) highlights the importance of demography for analyzing coronavirus disease 2019 (COVID 19) related mortality. The authors underscore the role of population age structure and intergenerational contacts for understanding differences in cross country fatality and estimate the potential impact of the pandemic on different populations, acknowledging the need for additional information on the prevalence of comorbidities. We aim to interpret the proposed scenarios considering the widely different prevalence of chronic conditions by age in three of the countries discussed in the original paper. We argue that the burden of chronic diseases has the potential to offset the possible benefits of younger populations with different epidemiological characteristics. Age is fundamental to understanding differences in mortality risks. Indeed, age is a marker of the [1]1To whom correspondence may be addressed.  nepomuceno{at}demogr.mpg.de or acosta{at}demogr.mpg.de.  #xref corresp 1 1
Differential control of allo antigen specific regulatory T cells and effector T cells by anti CD4 and other agents in establishing transplantation tolerance.
Venue: International immunology
Year: 2009

Donor specific graft tolerance can be established by a combination of allo antigen exposure and manipulation of T cell function, for example by donor specific transfusion (DST) under the cover of a non depleting anti CD4 mAb. Yet, the cellular basis of this graft tolerance is still obscure. This report shows that T cell deficient BALB/c nude mice reconstituted with naive unfractionated T cells are specifically tolerized to DBA/2 skin grafts by DST and anti CD4 mAb treatment, whereas those transferred with T cell suspensions depleted of all Foxp3()CD25()CD4( natural regulatory T cells (Tregs) are not. The treatment inhibits Mls 1(a) allo antigen specific expansion of CD4( non Tregs expressing Vbeta6 TCR subfamily but leaves the expansion of Vbeta6 expressing Tregs unaffected, allowing the latter to selectively expand and establish donor specific tolerance. Furthermore, anti CD4 mAb inhibits in vitro the selective expansion of allo antigen specific CD4( non Tregs but not natural Tregs, as observed with in vitro anti CD154 [CD40 ligand (CD40L) mAb or rapamycin treatment. The results collectively indicate that the differential effect of biologicals and pharmacological substances on the expansion of allo antigen specific Tregs and effector T cells and resulting dominance of the former can be a key general mechanism underlying dominant transplantation tolerance.
A comparative performance evaluation of VP9, x265, SVT AV1, VVC codecs leveraging the VMAF perceptual quality metric
Venue: Optical Engineering Applications
Year: 2020

The prevalence of video driven applications, leveraging over the top video on demand services as well as live video streaming applications, dominate network traffic over today's internet landscape. As such, they necessitate efficient video compression methods to accommodate the desired quality of service and hence user experience. In this study, we compare the performances of the emerging versatile video coding (VVC) standard, the recently released AV1 encoder (using SVTAV1 instance) the established high efficiency video coding (HEVC) standard via its x265 implementation, and the earlier VP9 codec. We used selected videos coming from three different datasets, namely UT LIVE (432p) and HEVC test sequences (480p, 720p, 1080p) that provide diversity in video content, video resolutions, and frame rates. The experimental setup involved fixed quality encoding using four different rate points, and more specifically, QP values of 27, 35, 46, 55 for AV1 and VP9 and QP values of 22, 27, 32, 37 for VVC and x265 codecs. For estimating bitrate gains, we used the BD RATE algorithm using both PSNR and VMAF for objective video quality assessment (VQA) We found that VVC achieved the best video coding performance, significantly outperforming all other codecs. AV1 consistently outperformed x265, but with narrow margins in some video sequences, suggesting that a cautious selection between the two codecs needs to based on application specific criteria. Within the group of considered codecs, VP9 required the highest bitrates. Ongoing work involves extending the examined video datasets pool to different resolutions (e.g. 240p, 1600p) while investigating the correlation between subjective and objective VQA scores.
The Cultural Component in the First Language (L1) Teaching: Cultural Heritage, Identity and Motivation in Language Learning
Year: 2015

After almost three decades since the insertion of Catalan (Valencian) within the Valencian education system, its use hasn't spread through all of the geographical domains and social scopes. In a context of language minorisation, an actual usage of a language is not guaranteed by just acquiring a sounder language competence. For a start we take into consideration a hipothesis defending that even though a comprehension of the goal culture in L2 is not just necessary for a significant use of the language within its society, we also have to realise the importance of the cultural import when using L1. We've framed our working field within some research projects which focus on the value of cultural imput in L1 and L2 teaching learning areas Kramsch, 1996 Rusell, 1999, Areitzaga, 2005) Another important approach for us is the collective dimension of motivation and attitude as notions traditionally associated with personal factors Cambra, 2003 We aim at researching in a language representation basis in order to be able to understand the lecturer's approach to linguistic representations on the cultural imput when teaching a language Moore, 2001 Cambra Palou, 2007 We aply an ethnographic field work based on questionnaires conducted by lecturers from two education centres within Valencian central shires where students show a higher level of learning and usage of Valencian. These centres then propose crucial cross cutting projects, where the own culture and language have a significant weight, focusing on the relationship between cultural heritage, land and identity. Taking into account cultural and cross cultural communicative competence Byram, 1997 we conclude that it is not possible to get to know a different culure whithout realising one's own culture.
Robust Autonomous Landing of UAV in Non Cooperative Environments based on Dynamic Time Camera LiDAR Fusion
Venue: ArXiv
Year: 2020

Selecting safe landing sites in non cooperative environments is a key step towards the full autonomy of UAVs. However, the existing methods have the common problems of poor generalization ability and robustness. Their performance in unknown environments is significantly degraded and the error cannot be self detected and corrected. In this paper, we construct a UAV system equipped with low cost LiDAR and binocular cameras to realize autonomous landing in non cooperative environments by detecting the flat and safe ground area. Taking advantage of the non repetitive scanning and high FOV coverage characteristics of LiDAR, we come up with a dynamic time depth completion algorithm. In conjunction with the proposed self evaluation method of the depth map, our model can dynamically select the LiDAR accumulation time at the inference phase to ensure an accurate prediction result. Based on the depth map, the high level terrain information such as slope, roughness, and the size of the safe area are derived. We have conducted extensive autonomous landing experiments in a variety of familiar or completely unknown environments, verifying that our model can adaptively balance the accuracy and speed, and the UAV can robustly select a safe landing site.
CYCLING AS AN OPPORTUNITY FOR IMPROVING HEALTH TOURISM IN IZMIR
Year: 2018

Izmir has been a traditional tourism destination for holiday, culture and history seekers for many years, and however the city has many advantages for some other alternative tourism options. Cycling, as one of the major sport activities for health and a kind of special interest tourism, is getting popular among the city dwellers recently. Convenient and long cycling routes help to meet the basic requirements of local and external bikers in the region. The city has already been a member of the European Cycle Route Network (EuroVelo) with its projected 491 km long cycle routes. The basic objective of this study is to examine the bicycle tourism as an opportunity for local tourism. This study was designed as a qualitative descriptive research by interviewing some professional cyclists, experts and professionals in Izmir province in order to have their ideas about the development potential of bicycle tourism and then the effects of EuroVelo membership of Izmir. The results of the study explain that the bicycle tourism in Izmir has not sufficiently been developed yet, but the interest of local people and foreigners is still raising and bicycle tourism has much potential for the development of local tourism.
Tejiendo Cristales: Reflexiones desde la teoria psicoanalitica para el abordaje de las depresiones y su relacion con la teoria del apego a nivel teorico, clinico y cultural
Year: 2019

Este estudio tiene como proposito exponer, desde una perspectiva psicoanalitica, algunas reflexiones sobre el concepto de las depresiones, su concepcion teorica y tecnica interventiva, y el como estos conceptos estan relacionados con las propuestas clasicas y contemporaneas de la Teoria del Apego; con un recorrido de las propuestas de algunos autores que destacan el papel de la cultura como protagonico frente a la formacion y el mantenimiento de la sintomatologia. Asi mismo, se tuvieron en cuenta las propuestas de los psicoanalistas suscritos a la Asociacion Psicoanalitica Internacional y a la Sociedad Britanica de Psicoanalisis, lo que permitio en gran medida, delimitar las fuentes de trabajo. La metodologia fue una revision documental basada en los textos sugeridos por un grupo de expertos de diversas areas, los cuales fueron entrevistados de manera informal.
Entity Linking in 100 Languages
Venue: EMNLP
Year: 2020

We propose a new formulation for multilingual entity linking, where language specific mentions resolve to a language agnostic Knowledge Base. We train a dual encoder in this new setting, building on prior work with improved feature representation, negative mining, and an auxiliary entity pairing task, to obtain a single entity retrieval model that covers 100+ languages and 20 million entities. The model outperforms state of the art results from a far more limited cross lingual linking task. Rare entities and low resource languages pose challenges at this large scale, so we advocate for an increased focus on zero and few shot evaluation. To this end, we provide Mewsli 9, a large new multilingual dataset (this http URL) matched to our setting, and show how frequency based analysis provided key insights for our model and training enhancements.