nils-herrmann/clean_scirepeval huggingface dataset:
Advocacy Planning in the Age of Trump: An Opportunity to Influence National Urban Policy
Venue: Planning Theory Practice
Year: 2019

In the years following World War II, the United States experienced a period of unmatched economic prosperity and political influence, which many scholars refer to as 'Pax Americana.'While the majority of Americans saw their employment status, household incomes, housing conditions, and overall quality of life significantly improve during this period, the majority of African American, Latino, and Native American communities did not (Lane, 2012) Growing disparities between rising economic expectations in the general population and limited educational, employment, and housing opportunities afforded to racial minorities reinforced by institutional racism based in white privilege laid the foundations for the American Civil Rights movement which grew in size and influence throughout the 1950s and 1960s. In 1965, Paul Davidoff, reflecting upon growing racial inequality in American society, wrote, 'Advocacy and Pluralism in Planning' which challenged several of the most important assumptions underlying the rational model of planning which dominated mid century professional practice in the United States and Europe (Davidoff, 1965) This article, which remains one of the most often cited in planning, argues against the existence of a unitary public interest in favor of multiple public interests based upon race, class, religion, ethnicity, and gender. The article also questions the objectivity of local planning agencies which Davidoff believed advanced policies and plans benefitting powerful economic elites at the expense of those living in poor and working class neighborhoods. Having identified these limitations of mid century planning, Davidoff proposed what William F. Whyte called a "social invention" to address the disturbing role planners were playing in promoting uneven patterns of metropolitan development at a time when African American youth were engaged in courageous acts of non violent civil disobedience to dismantle racial discrimination in education, employment, housing and transportation (Whyte, 1983) Davidoff urged social justice oriented planners to work with poor, racial minorities, immigrant communities, senior citizens and persons with disabilities to produce high quality plans featuring redistributive policies and participatory policymaking processes to serve as effective alternatives to those being proposed by centralized planning agencies privileging the needs of, what Logan and Molotch termed, urban growth machines (Logan Molotch, 1987) By working with groups frequently ignored by mainstream planning to generate oppositional plans, Davidoff believed advocacy planners could transform municipal planning commissions into deliberative bodies capable of critically assessing the underlying assumptions, theoretical frameworks, empirical evidence and planning recommendations of competing plans thereby producing more thoughtful and equitable planning decisions. Inspired by Davidoff's ideas and angered by
BundleFusion
Year: 2017

Real time, high quality, 3D scanning of large scale scenes is key to mixed reality and robotic applications. However, scalability brings challenges of drift in pose estimation, introducing significant errors in the accumulated model. Approaches often require hours of offline processing to globally correct model errors. Recent online methods demonstrate compelling results but suffer from (1) needing minutes to perform online correction, preventing true real time use; (2) brittle frame to frame (or frame to model) pose estimation, resulting in many tracking failures; or (3) supporting only unstructured point based representations, which limit scan quality and applicability. We systematically address these issues with a novel, real time, end to end reconstruction framework. At its core is a robust pose estimation strategy, optimizing per frame for a global set of camera poses by considering the complete history of RGB D input with an efficient hierarchical approach. We remove the heavy reliance on temporal tracking and continually localize to the globally optimized frames instead. We contribute a parallelizable optimization framework, which employs correspondences based on sparse features and dense geometric and photometric matching. Our approach estimates globally optimized (i.e. bundle adjusted) poses in real time, supports robust tracking with recovery from gross tracking failures (i.e. relocalization) and re estimates the 3D model in real time to ensure global consistency, all within a single framework. Our approach outperforms state of the art online systems with quality on par to offline methods, but with unprecedented speed and scan completeness. Our framework leads to a comprehensive online scanning solution for large indoor environments, enabling ease of use and high quality
A Multi Element Hybrid Location Recommendation Algorithm for Location Based Social Networks
Venue: IEEE Access
Year: 2019

In the environment of data explosion, how to make an effective and accurate personalized point of interest (POI) recommendation in location based social networks (LBSNs) is a challenging and meaningful task. Fortunately, there is a lot of information that we can use. We can make recommendations by mining the rich information hidden in user check in records. In this paper, we propose a recommend system named GFP LORE. Specifically, we have designed a framework, which integrates various influencing factors. First, we modeled friend sign in frequencies and POI popularity as a power law distribution and the experiment proved that it is effective. Then, we got the influence of geographic information by modeling it according to the longitude and latitude of the user's check in location. After that, we sorted the historical check in records of all users according to time and then mine an overall pattern of location transfer order pattern. Then, we combine it with each user's own unique location transfer record to get the possibility of the user going to the next POI. Finally, we synthesize the above four influence factors into a unified correlation probability rating and recommend a new location by this probability rating. We tested our system on the open real check in data set, and the results of our simulation experiments show that the recommendation effect of our system is better than those algorithms used in the contrast test.
The biology of human hair greying
Venue: Biological reviews of the Cambridge Philosophical Society
Year: 2020

Hair greying (canities) is one of the earliest, most visible ageing associated phenomena, whose modulation by genetic, psychoemotional, oxidative, senescence associated, metabolic and nutritional factors has long attracted skin biologists, dermatologists, and industry. Greying is of profound psychological and commercial relevance in increasingly ageing populations. In addition, the onset and perpetuation of defective melanin production in the human anagen hair follicle pigmentary unit (HFPU) provides a superb model for interrogating the molecular mechanisms of ageing in a complex human mini organ, and greying associated defects in bulge melanocyte stem cells (MSCs) represent an intriguing system of neural crest derived stem cell senescence. Here, we emphasize that human greying invariably begins with the gradual decline in melanogenesis, including reduced tyrosinase activity, defective melanosome transfer and apoptosis of HFPU melanocytes, and is thus a primary event of the anagen hair bulb, not the bulge. Eventually, the bulge MSC pool becomes depleted as well, at which stage greying becomes largely irreversible. There is still no universally accepted model of human hair greying, and the extent of genetic contributions to greying remains unclear. However, oxidative damage likely is a crucial driver of greying via its disruption of HFPU melanocyte survival, MSC maintenance, and of the enzymatic apparatus of melanogenesis itself. While neuroendocrine factors [e.g. alpha melanocyte stimulating hormone (a MSH) adrenocorticotropic hormone (ACTH) ss endorphin, corticotropin releasing hormone (CRH) thyrotropin releasing hormone (TRH) and micropthalmia associated transcription factor (MITF) are well known regulators of human hair follicle melanocytes and melanogenesis, how exactly these and other factors [e.g. thyroid hormones, hepatocyte growth factor (HGF) P cadherin, peripheral clock activity] modulate greying requires more detailed study. Other important open questions include how HFPU melanocytes age intrinsically, how psychoemotional stress impacts this process, and how current insights into the gerontobiology of the human HFPU can best be translated into retardation or reversal of greying.
PLIN: A Network for Pseudo LiDAR Point Cloud Interpolation
Venue: Sensors
Year: 2020

LiDAR sensors can provide dependable 3D spatial information at a low frequency (around 10 Hz) and have been widely applied in the field of autonomous driving and unmanned aerial vehicle (UAV) However, the camera with a higher frequency (around 20 Hz) has to be decreased so as to match with LiDAR in a multi sensor system. In this paper, we propose a novel Pseudo LiDAR interpolation network (PLIN) to increase the frequency of LiDAR sensor data. PLIN can generate temporally and spatially high quality point cloud sequences to match the high frequency of cameras. To achieve this goal, we design a coarse interpolation stage guided by consecutive sparse depth maps and motion relationship. We also propose a refined interpolation stage guided by the realistic scene. Using this coarse to fine cascade structure, our method can progressively perceive multi modal information and generate accurate intermediate point clouds. To the best of our knowledge, this is the first deep framework for Pseudo LiDAR point cloud interpolation, which shows appealing applications in navigation systems equipped with LiDAR and cameras. Experimental results demonstrate that PLIN achieves promising performance on the KITTI dataset, significantly outperforming the traditional interpolation method and the state of the art video interpolation technique.
Hydroxychloroquine and azithromycin as a treatment of COVID 19: results of an open label non randomized clinical trial
Venue: International Journal of Antimicrobial Agents
Year: 2020

Chloroquine and hydroxychloroquine have been found to be efficient on SARS CoV 2, and reported to be efficient in Chinese COV 19 patients. We evaluate the role of hydroxychloroquine on respiratory viral loads. Patients and methods French Confirmed COVID 19 patients were included in a single arm protocol from early March to March 16th, to receive 600mg of hydroxychloroquine daily and their viral load in nasopharyngeal swabs was tested daily in a hospital setting. Depending on their clinical presentation, azithromycin was added to the treatment. Untreated patients from another center and cases refusing the protocol were included as negative controls. Presence and absence of virus at Day6 post inclusion was considered the end point.  Six patients were asymptomatic, 22 had upper respiratory tract infection symptoms and eight had lower respiratory tract infection symptoms. Twenty cases were treated in this study and showed a significant reduction of the viral carriage at D6 post inclusion compared to controls, and much lower average carrying duration than reported of untreated patients in the literature. Azithromycin added to hydroxychloroquine was significantly more efficient for virus elimination.  Despite its small sample size our survey shows that hydroxychloroquine treatment is significantly associated with viral load reduction/disappearance in COVID 19 patients and its effect is reinforced by azithromycin.
Antisense oligonucleotides target a nearly invariant structural element from the SARS CoV 2 genome and drive RNA degradation
Year: 2020

The SARS CoV 2 virus contains an unusually large, single stranded RNA genome that is punctuated with structured elements of unknown function, such as the s2m element located in the 3 untranslated region. The evolutionary conservation of the s2m element and its occurrence in all viral subgenomic transcripts implicates a key role in the viral infection cycle. In order to exploit this element as a potential therapeutic target, we have designed antisense "gapmer" oligonucleotides that efficiently base pair to the s2m region. These oligonucleotides, composed of locked nucleic acids (LNA) flanking a central DNA core, successfully remodel the s2m structure and induce sequence specific RNA cleavage by RNase H in vitro. Gapmers are also effective in human cells as they reduce the fluorescence signal in GFP reporter assays and cause a dose dependent reduction in replication in a model replicon system based on a human astrovirus. Overall, these oligonucleotides show promise as anti viral agents and may serve as a helpful starting point to develop treatments for COVID 19.
Photorealistic Lip Sync with Adversarial Temporal Convolutional Networks
Venue: ArXiv
Year: 2020

Lip sync has emerged as a promising technique to generate mouth movements on a talking head. However, synthesizing a clear, accurate and human like performance is still challenging. In this paper, we present a novel lip sync solution for producing a high quality and photorealistic talking head from speech. We focus on capturing the specific lip movement and talking style of the target person. We model the seq to seq mapping from audio signals to mouth features by two adversarial temporal convolutional networks. Experiments show our model outperforms traditional RNN based baselines in both accuracy and speed. We also propose an image to image translation based approach for generating high resolution photoreal face appearance from synthetic facial maps. This fully trainable framework not only avoids the cumbersome steps like candidate frame selection in graphics based rendering methods but also solves some existing issues in recent neural network based solutions. Our work will benefit related applications such as conversational agent, virtual anchor, tele presence and gaming.
Factores marcadores asociados a la severidad de discapacidad aguda en pacientes con ataque cerebro vascular (ACV) isquemico
Year: 2019

The Stroke, defined according to the World Health Organization (WHO) as clinical signs of rapid development of focal or global alteration in brain function that lasts 24 hours or that leads to death with no other apparent cause than the vascular origin (1) this disease is a major generator of disability, both physical and cognitive and according to this, 15 to 30% of the population that suffers one of these events is left with severe long term functional impairment (2) considering the high impact of this pathology beyond the chronic phase (3) that has been a constant target of study, emerges with all the above the need to perform this work collecting data from the moment of the event in order to determine what are the factors that they are really associated with the severity of acute disability in ischemic stroke in order to establish an action plan aimed at the prompt handling of these identified factors and by this, achieve a positive impact on the clinical course of our patients.
Deep Learning Based Intrusion Detection System: Software Defined Network
Venue: 2021 Asian Conference on Innovation in Technology (ASIANCON)
Year: 2021

Software defined Networking (SDN) is the key catalyst in the next generation network. Cloud computing has shown rapid growth due to the development of SDN. Due to the growth in security difficulties and threats, SDN networks will have new security issues to overcome, and a new layer of security procedures, such as intrusion detection systems (IDS) is required. Nowadays, web services are flexible, economical, and user friendly. Although this may be true, they still seem to be more susceptible to security issues than legacy systems. Therefore, SDN architecture also incorporates several machine learning methods to find classify malicious attacks and legitimate traffic. We include a rigorous study of the current strategies for malicious traffic identification and we define the classical machine learning method's shortcomings, and a deep learning technique is also being investigated to reach higher levels of efficiency and accuracy. This article explores SDN security and IDS about security concerns. A dataset of IDS, publicly accessible, KDD CUP99, and NSL KDD Dataset are used to determine the possible behaviour of security flaws.
Hubungan Karakteristik Morfofisiologi Tanaman Kersen (Muntingia Calabura)
Venue: Agrovigor: Jurnal Agroekoteknologi
Year: 2019

Kersen (Muntingia calabura) merupakan salah satu tumbuhan liar yang belum dimanfaatkan secara optimal. Tumbuhan ini dapat dimanfaatkan sebagai tanaman obat dengan memanfaatkan daun atau buahnya. Penelitian ini bertujuan untuk mengidentifikasi karakteristik morfologi dan fisiologi daun, bunga, dan buah kersen. Penelitian dilakukan dengan mengambil sampel tanaman kersen di wilayah Cirebon dan Kuningan, Jawa Barat dengan ketinggian tempat yang berbeda. Lokasi pengambilan sampel tanaman kersen yaitu Pilang (4 mdpl) Bima (15 mdpl) Gronggong (135 mdpl) Cilimus (476 mdpl) dan Cigugur (960 mdpl).Penelitian dilaksanakan pada bulan November 2015 Maret 2016. Hasil pengamatan menunjukkan bahwa daun kersen memiliki karakteristik berdaun tunggal dengan panjang dan lebar daun berturut turut 10.67 cm dan 4 cm. Bunga kersen termasuk ke dalam bunga sempurna dengan mahkota berwarna putih dan kelopak berwarna hijau. Buah kersen berbentuk bulat dan ketika muda berwarna hijau dan merah ketika sudah matang. Bobot buah kersen yang sudah matang berkisar 1.71 g. Kadar vitamin C buah kersen berkisar 2.31 mg/g bobot basah dan tingkat kemanisan (padatan total terlarut) buah kersen yaitu 19.14 Brix. Berdasarkan hasil analisis korelasi, luas daun berkorelasi positif dengan diameter ovari dan bobot buah. Bobot buah kersen berkorelasi negatif dengan tingkat kemanisan buah.
Policy based Access Control for the IoT and Smart Cities
Venue: Open Identity Summit
Year: 2019

The Internet of Things (IoT) can revolutionize the interaction between users and technology. This interaction generates many sensitive and personal data. Therefore, access to the information they provide should be restricted to only authorized users. However, the limited storage and memory in IoT make it impractical to deploy traditional mechanisms to control access. In this paper, we propose a new access control mechanism based on trust policies adapted from LIGHTest. The proposed protocol also handles delegations in the IoT context elegantly. We provide the protocol overview and discuss its practical applications in the IoT environment.
Enhancer Predictions and Genome Wide Regulatory Circuits.
Venue: Annual review of genomics and human genetics
Year: 2020

Spatiotemporal control of gene expression during development requires orchestrated activities of numerous enhancers, which are cis regulatory DNA sequences that, when bound by transcription factors, support selective activation or repression of associated genes. Proper activation of enhancers is critical during embryonic development, adult tissue homeostasis, and regeneration, and inappropriate enhancer activity is often associated with pathological conditions such as cancer. Multiple consortia [e.g. the Encyclopedia of DNA Elements (ENCODE) Consortium and National Institutes of Health Roadmap Epigenomics Mapping Consortium] and independent investigators have mapped putative regulatory regions in a large number of cell types and tissues, but the sequence determinants of cell specific enhancers are not yet fully understood. Machine learning approaches trained on large sets of these regulatory regions can identify core transcription factor binding sites and generate quantitative predictions of enhancer activity and the impact of sequence variants on activity. Here, we review these computational methods in the context of enhancer prediction and gene regulatory network models specifying cell fate. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 21 is August 31, 2020. Please see http:/www.annualreviews.org/page/journal/pubdates for revised estimates.
Salient Region Extraction based on Global Contrast Enhancement and Saliency Cut for Image Information Recognition of the Visually Impaired
Venue: KSII Trans. Internet Inf. Syst.
Year: 2018

Saliency region extraction has become an important task and attracts much attention in numerous image processing application. Object of interest image segmentation from natural scene images for assisting the visually impaired people to access visual information is becoming more challenging research area for community. In this paper we propose a novel color contrast based saliency region extraction approach by adding pre processing contrast enhancement technique and using saliency cut method to get a high quality foreground object mask, could be used for assistive technology system for visually impaired people. A lot of research has focused on high quality segmentation, using color information and background or foreground prior, with surprisingly unnoticed image enhancement technique before region segmentation. Moreover, image enhancement is used to improve bad quality of picture into good picture, helpful for blind people's daily life since all randomly taken images might not be good quality. We evaluate our proposed method on the most known benchmark databases.  Saliency region extraction; visual attention; visually impaired people; saliency map; saliency cut; image enhancement;
Analisis del manejo de propiedad planta y equipo y bienes de control administrativo en aplicacion a la normativa vigente en el Centro de Especialidades Central Cuenca del I.E.S.S. en la ciudad de Cuenca
Year: 2018

En las empresas, publicas o privadas, los bienes de Propiedad, Planta y Equipo y bienes de Control Administrativo, representan un rubro significativo dentro de la estructura financiera, cuyo manejo y actualizacion debe aplicarse de acuerdo a las leyes y normas vigentes, ya que un control inadecuado de los bienes, afecta al patrimonio de las instituciones. Razon por la que nos motivamos a desarrollar el tema titulado: ANALISIS DEL MANEJO DE PROPIEDAD PLANTA Y EQUIPO Y BIENES DE CONTROL ADMINISTRATIVO EN APLICACION A LA NORMATIVA VIGENTE EN EL CENTRO DE ESPECIALIDADES CENTRAL CUENCA DEL I.E.S.S. EN LA CIUDAD DE CUENCA. Luego de analizar la informacion receptada y diagnosticar la situacion actual, hemos concluido que la Institucion, tiene ciertas deficiencias en el manejo, control, baja y actualizacion de los bienes, ademas no cuenta con un sistema de codificacion apropiado. Como propuesta de ayuda y mejora a la institucion se ha desarrollado las propuestas para la constatacion fisica, conciliacion contable, disminucion y baja de bienes obsoletos, un diferente sistema de codificacion, que permita una adecuada identificacion y ubicacion de los bienes de la Institucion.
Using effective hand hygiene practice to prevent and control infection.
Venue: Nursing standard (Royal College of Nursing (Great Britain) 1987)
Year: 2020

Decontamination using hand hygiene remains one of the most important and effective methods for reducing healthcare associated infections and cross infection between patients. In 1860, Florence Nightingale wrote that nurses should wash their hands frequently throughout the day, demonstrating an early awareness of the effectiveness of this simple procedure. The COVID 19 pandemic has demonstrated that effectively applied hand hygiene is a vital intervention that can be used to prevent the spread of disease. This article details the correct procedure required for effective hand hygiene and emphasises the need for nurses to keep up to date with evidence based guidelines. The article also outlines the differences between hand decontamination using alcohol based hand gels and soap and water, and the complex factors that can interfere with effective hand hygiene compliance.