nils-herrmann/clean_scirepeval huggingface dataset:
A Quarter Century of APOE and Alzheimer's Disease: Progress to Date and the Path Forward
Venue: Neuron
Year: 2019

Alzheimer's disease (AD) is considered a polygenic disorder. This view is clouded, however, by lingering uncertainty over how to treat the quasi "monogenic" role of apolipoprotein E (APOE) The APOE4 allele is not only the strongest genetic risk factor for AD, it also affects risk for cardiovascular disease, stroke, and other neurodegenerative disorders. This review, based mostly on data from human studies, ranges across a variety of APOE related pathologies, touching on evolutionary genetics and risk mitigation by ethnicity and sex. The authors also address one of the most fundamental question pertaining to APOE4 and AD: does APOE4 increase AD risk via a loss or gain of function? The answer will be of the utmost importance in guiding future research in AD.
HIV Prevention in Gay Family and House Networks: Fostering Self Determination and Sexual Safety
Venue: AIDS and Behavior
Year: 2017

Many gay, bisexual, and transgender (GBT) people of color (POC) join house and/or constructed family communities, which serve as support networks composed mostly of other non biologically related GBT/POC. These networks can decrease or increase the risk of exposure to HIV via multiple mechanisms (e.g. providing informal sexual safety education versus stigmatizing family members with HIV, encouraging sexual safety practices versus unsafe escorting, teaching self care versus substance use) but act to support family members in the face of social and economic hardship. Researchers interviewed ten members of these social networks in the Boston metro area of the US and produced a saturated grounded theory analysis to explore the role of gay family/house networks in HIV risk management. While network members utilized HIV prevention resources, interviewees described how their efficacy was related to the intentions of leadership and strength of kinship boundaries within their community, economic opportunities, and communication skills. Clinical and research implications are discussed.ResumenMuchos individuales gay, bisexual, o transgenero (GBT) que al igual son personas de color (PDC) se unen a comunidades caseras o de familias construidas, las cuales sirven como redes de apoyo compuestas mayormente de otros individuales GBT/PDC que no estan relacionados biologicamente. A traves de varios mecanismos, estas redes pueden disminuir o aumentar el riesgo de ser expuesto al VIH (por ejemplo, ofreciendo educacion informal sobre sexo seguro, estigmatizando familiares con VIH, alentando practicas sexuales seguras en vez de "escorting" ensenando a cuidar de si mismo en vez de usar sustancias) pero tambien funcionan como apoyo para familiares al estos enfrentarse con dificultades sociales y economicas. Los investigadores entrevistaron a diez personas pertenecientes a estas redes sociales en el area metropolitana de Boston en los EUA, y llevaron a cabo un analisis saturado de teoria fundamentada explorando el rol de redes familiares/caseras gay en el manejo de riesgo de VIH. Miembros de estas redes utilizaban recursos de prevencion de VIH, pero los participantes del estudio pudieron describir como la eficacia de los mismos estaba asociada a: la fuerza del liderazgo y los limites de afinidad dentro de su comunidad, oportunidades economicas y destrezas de comunicacion. Finalmente, se discuten las connotaciones clinicas e investigativas.
TOKEN PAIRING TO IMPROVE NEURAL PROGRAM SYNTHESIS MODELS
Year: 2020

In neural program synthesis (NPS) a network is trained to output or aid in the output of code that satisfies a given program specification. In our work, we make modifications upon the simple sequence to sequence (Seq2Seq) LSTM model. Extending the most successful techniques from previous works, we guide a beam search with an encoder decoder scheme augmented with attention mechanisms and a specialized syntax layer. But one of the withstanding difficulties of NPS is the implicit tree structure of programs, which makes it inherently more difficult for linearly structured models. To address this, we experiment with a novel technique we call token pairing. Our model is trained and evaluated on AlgoLisp, a dataset of English description to code programming problems paired with example solutions and test cases on which to evaluate programs. We also create a new interpreter for AlgoLisp that fixes the bugs present in the builtin executor. In the end, our model achieves 99.24% accuracy at evaluation, which greatly improves on the previous state of the art of 95.80% while using fewer of parameters.
Effects of the COVID 19 Pandemic on Classrooms: A Case Study on Foreigners in South Korea Using Applied Machine Learning
Year: 2021

In this study, we qualitatively and quantitatively examine the effects of COVID 19 on classrooms, students, and educators Using a new Twitter dataset specific to South Korea during the pandemic, we sample the sentiment and strain on students and educators using applied machine learning techniques in order to identify various topical pain points emerging during the pandemic Our contributions include a novel and open source geo fenced dataset on student and educator opinion within South Korea that we are making available to other researchers as well We also identify trends in sentiment and polarity over the pandemic timeline, as well as key drivers behind the sentiments Moreover, we provide a comparative analysis of two widely used pre trained sentiment analysis approaches with TextBlob and VADER using statistical significance tests Ultimately, we analyze how public opinion shifted on the pandemic in terms of positive sentiments about accessing course materials, online support communities, access to classes, and creativity, to negative sentiments about mental fatigue, job loss, student concerns, and overwhelmed institutions We also initiate initial discussions about the concept of actionable sentiment analysis by overlapping polarity with the concept of trigger management to assist users in coping with negative emotions We hope that insights from this preliminary study can promote further utilization of social media datasets to evaluate government messaging, population sentiment, and multi dimensional analysis of pandemics
Recent development of ortho C H functionalization of aryl sulfoxides through [3,3] sigmatropic rearrangement
Year: 2018

Sulfoxide promoted ortho C H functionalization reactions of aromatic compounds have emerged as powerful tools for organic synthesis. Among them,  sigmatropic rearrangement induced by interrupted Pummerer reaction or electrophilic activation of sulfoxides has proved to be a fruitful strategy due to its versatility and high reaction efficiency. This digest paper mainly focuses on recent progress on C H functionalization reactions of aryl sulfoxides via [3,3] sigmatropic rearrangement of sulfonium tethered intermediates.
Intelligent Real Time Systems for Managing Catastrophe through Scenario Shift Paradigm
Year: 2015

intelligent real time system design needs to incorporate autonomic features in their operations to achieve the unexpected criticalities of systems and its environment. Catastrophic scenarios can emerge in systems, challenging the traditional role of real time systems where the temporal rigidity is the essential design feature. The priorities and its management scheme given for a normal operation by the conventional real time systems need not be the ultimate format to meet the requirements of a catastrophic environment. Hence, usual real time system is supplemented with a layer of intelligence to deal with the emerging catastrophic environment. Intelligent real time systems can have hybrid schedulers with some additional features that can guarantee risk mitigation performance even with the occurrence of extreme, unusual variations of external conditions. This approach addresses intelligence in systems by making a real time system schedule itself to adapt meaningfully even if the environment changes, by assigning intelligent priorities. This paper introduces the design of Intelligent Real Time System (IRTS) that keep shifting the boundaries of the original hybrid scheduler with cognitive features aiding the intelligence by increasing the possibility to make a dynamically reconfigured system while increasing the fairness of the scheduling. Intelligent scheduler can be used in embedded critical systems in order to cope with the unexpected problems like nuclear power plants and hazardous installations. Theoretical analysis shows that the proposed design performs the operation of IRTS, which can be advantageously applied to pragmatic systems and show how intelligence works with priority. Keywords time system, catastrophe, intelligent, cognitive, priority
Description and distribution of Desmacella hyalina sp. nov. (Porifera, Desmacellidae) a new cryptic demosponge in glass sponge reefs from the western coast of Canada
Venue: Marine Biodiversity
Year: 2020

Glass sponges (Porifera, Hexactinellida) form globally unique reefs that support deep sea biodiversity in the Canadian northeast Pacific. In February 2017, the largest known reefs were protected within the Hecate Strait and Queen Charlotte Sound Glass Sponge Reefs Marine Protected Area (HSQCS MPA) Many studies that have established baseline biodiversity data for the MPA have focused on describing the crustaceans and fish living in the reefs, but the relationship between glass sponges and sponge epibionts has often been overlooked. We studied one of the more conspicuous sponge epibionts of the genus Desmacella Schmidt, 1870, a demosponge that encrusts the surface of reef forming glass sponges. Using a remotely operated vehicle, samples of an encrusting sponge with three color morphotypes (yellow, white, and mauve) were collected from the northern reef complex of the HSQCS MPA. Spicule and DNA analyses of COI sequences revealed the white morphotype to be distinct from the previously described species, D. austini Lehnert, Conway, Barrie Krautter, 2005. Comparisons with other Desmacella samples collected from other regions in British Columbia waters since 1976 confirmed this to be a new species, which we describe here as Desmacella hyalina sp. nov. We also mapped the spatial distribution of the color morphotypes on the reefs and found that Desmacella spp. formed nearly 20% of live sponge cover at some sampling sites indicating its potential importance in the reefs. Our results expand on knowledge of the diversity of sponge epibionts in glass sponge reefs and highlight the importance of understanding cryptic species diversity especially for future monitoring in marine protected areas.
Multi robot task allocation for collaborative adaptive informative sampling in structured environments
Venue: ICRA 2018
Year: 2018

We look to improve the efficiency of teams of autonomous robots for information gathering approaches. These approaches are useful for environmental modeling, persistent monitoring, or mapping chemical signals in the air. An effective way of creating spatial models is by using Gaussian Process (GP) regression. Information theoretic metrics, such as entropy or mutual information, can be used on top of the GP model's predictions to decide where to place sensors or robots. In such case we speak of informative sampling. When the robot is creating such a model while sampling data this is called on line or adaptive informative sampling. In this work we present our late breaking results extending our prior work  on multi robot adaptive information gathering in structured indoor environments. This previous work implemented an information gathering rate adaptive algorithm to task robots with sensing an environment and building a GP model of RSSI signal readings. Multiple robots were coordinated by partitioning the environment into a number of segments equal to the number of robots and assigning each robot to its own region. In this paper we present a method for oversegmenting the sampling space into more regions than robots. A task assignment algorithm allows a central controller to dynamically task robots to different partition regions.
Physical and MAC Cross Layer Analysis of Energy Efficient Cooperative MIMO Networks
Venue: IEEE Transactions on Communications
Year: 2018

We study the cross layer energy efficiency of cooperative MIMO networks. At the physical layer, the transmit power determines the outage probability and the number of contending nodes per unit area. At the medium access control (MAC) layer, accessing the channel takes additional time and energy, which impacts the throughput and the energy efficiency. Then, we propose a new cooperative MAC protocol based on IEEE 802.11 in order to coordinate cooperation and to improve the energy efficiency. Moreover, we focus on slow fading scenarios and we analyze the performance of antenna selection (AS) singular value decomposition (SVD) diversity beamforming, and spatial multiplexing (SM) transmission schemes. Results show that SVD and SM have smaller delay and, consequently, larger throughput; however, AS is more energy efficient.
Speech and language delay in children: a review and the role of a pediatric dentist.
Venue: Journal of the Indian Society of Pedodontics and Preventive Dentistry
Year: 2012

Speech and language development is a useful indicator of a child's overall development and cognitive ability. Identification of children at a risk for developmental delay or related problems may lead to intervention and assistance at a young age, when the chances for improvement are the best. This rationale supports screening of preschool children for speech and language delay or primary language impairment or disorder, which needs to be integrated into routine developmental surveillance practices of clinicians caring for children.
Learning by leading: Integrating leadership in public relations education for an enhanced value
Year: 2013

Twin surveys of senior public relations executives and public relations majors compared perceptual similarities and differences in leadership qualities, skill development sources, and unique features of public relations leadership. The perceptual gap revealed what students believe to be important or less important in the self actualization process as future leaders. The results offered pedagogical recommendations on how to integrate leadership training in public relations education to prepare students with a sustainable competitive advantage.
Low temperature thermal expansion measurements in PrV2Al20
Year: 2016

We have measured thermal expansion of PrV2Al20 and LaV2Al20 from room temperature down to 2 K, using a capacitance dilatometer. Linear thermal expansion DL/L along [111] direction decreases monotonically on cooling in both materials. The extracted 4f electrons contribution of the linear thermal expansion coefficient a clearly shows a broad peak at 30 K which may correspond to the crystal electric field excited state at 40 K suggested in the previous specific heat study.
An interesting case of 'diabetic foot ulcer' in an HIV positive patient
Venue: International journal of STD AIDS
Year: 2015

Kaposi sarcoma is a highly vascularised tumour affecting the skin, lymph nodes and viscera. Kaposi sarcoma is most common in HIV infected homosexual or bisexual men. We present here a 70 year old white British male patient, who was under the care of the podiatric team for longstanding 'diabetic foot ulcers' He was later referred to the Dermatology team who took a biopsy; this revealed features of Kaposi sarcoma which prompted an HIV test which was positive. This patient had previously presented to several healthcare professionals with symptoms suggestive of HIV infection. He was started on antiretroviral therapy and the HIV and human herpesvirus 8 viral loads became undetectable in the blood within weeks and he showed significant clinical improvement. This case report is a reminder to clinicians to have a high index of suspicion in patients presenting with symptoms and signs suggestive of HIV infection.
Review on Removal of Phenol from Wastewater Using Low Cost Adsorbent I
Year: 2016

Phenol is a major pollutant in the wastewater because of its presence in the effluent of petroleum refining, coal conversion, plastics, textiles, iron and steel manufacturing as well as pulp and paper manufacturing. It is very important to remove phenol from contaminated water before discharge into any natural water because of their toxicity to aquatic organisms. It has severe effect on human being, both short term and long term. The methods such as adsorption, polymerization, electrocoagulation, extraction, photodecomposition, advanced oxidation and ion exchange are used for removal of phenol from waste water. Among them, physical adsorption method is generally considered to be the best, effective, low cost and most frequently used method for the removal of phenolic pollutions. This method is suitable for phenol removal can be selected based on availability of the material, extent of separation required and properties of phenolic effluent. Locally available sawdust, easily and abundantly available material is tested experimentally as an adsorbent, after carbonization, for the removal of phenol from industrial waste waters for a safe disposal. The experiments are performed batch wise to remove phenol from synthesized aqueous solutions. The aim of the present work is to investigate the capability of sawdust used as an adsorbent for removal of phenol from wastewater and to study the effects of initial phenol concentration, adsorbent dosage, pH value and contact time on the adsorption process, then workout optimum conditions for removal. The efficiency of adsorbents is described and correlated with the usual Langmuir and Freundlich isotherm equations. Index TermAdsorption, Langmuir and Freundlich, Phenol, Removal. Sonawane B. K, PG Student, Department of Civil Engineering, SRES COE Kopargaon, Savatribai Phule Pune University,Pune, Maharashtra, India. Korake S. R, Asst. Professor, Department of Civil Engineering, SRES COE Kopargaon, Dist. Ahmednagar, India.
An Approach to Generate Topic Similar Document by Seed Extraction Based SeqGAN Training for Bait Document
Venue: 2018 IEEE Third International Conference on Data Science in Cyberspace (DSC)
Year: 2018

In recent years, topic similar document generation has drawn more and more attention in both academia and industry. Especially, bait document generation is very important for security. For more like and fast bait document generation, we proposed the topic similar document generation model based on SeqGAN model (TSDG SeqGAN) In the training phrase, we used jieba word segmentation tool for training text to greatly reduce the training time. In the generation phrase, we extract keywords and key sentence from the subject document as seeds, and then enter the seeds into the trained generation network. Next, we get keyword based documents and documents based on key sentences from generation network. Finally, we output documents that are most similar to the subject document as the final result. Experiments show the effectiveness of our model.
Writing to Learn by Learning to Write in the Disciplines
Year: 2007

The traditional distinction between writing across the curriculum and writing in the disciplines (WID) as writing to learn versus learning to write understates WID's focus on learning in the disciplines. Advocates of WID have described learning as socialization, but little research addresses how writing disciplinary discourses in disciplinary settings encourages socialization into the disciplines. Data from interviews with students who wrote lab reports in a biology lab suggest five ways in which writing promotes learning in scientific disciplines. Drawing on theories of situated learning, the authors argue that apprenticeship genres can encourage socialization into disciplinary communities.
Sociology in the Era of Big Data: The Ascent of Forensic Social Science
Year: 2016

The rise of big data data that are not only large and massively multivariate but concern a dizzying array of phenomena represents a watershed moment for the social sciences. These data have created demand for new methods that reduce/simplify the dimensionality of data, identify novel patterns and relations, and predict outcomes, from computational ethnography and computational linguistics to network science, machine learning, and in situ experiments. Such developments have led scholars to begin new lines of social inquiry. Company engineers, computer scientists, and social scientists have all converged on big data, creating the possibility of a vibrant "trading zone" for collaboration. However, strong differences in research frameworks help explain why big data may not be an egalitarian trading zone across fields, but rather at least in the short term a moment when engineering colonizes sociology more than vice versa. In the long term, however, we suggest there may be the possibility of a constructive synthesis across paradigms in what we term 'forensic social science.
Assessing the market potential of electric bicycles and ICT for low carbon school travel: a case study in the smart city of Agueda
Year: 2016

Electric bikes (e bikes) may help in transport decarbonisation in European cities. To fully assess the market potential of e bikes, further research is needed to understand users' preferences and the range of factors that can contribute for people to shift from car use to low carbon vehicles such as e bikes. This paper is built on the Be4Schools R&D project implemented in the city of Agueda which is considered the first smart city in Portugal. It comprised the former study in the country that examined the willingness of students (aged 15 21 years) to use e bikes for daily trips to school and that gathered their preferences towards specific ICT related attributes. The methodology comprised a mobility survey and a stated choice experiment (SC) The SC experiment gathered 2232 observations which were able to provide the relevant attribute trade off information between car travel and e bike (with or without specific ICT equipment) An extensive econometric analysis was performed to assess the nature and extent of students' heterogeneity of preferences which also considered gender issues. The study aimed to contribute to the regional economic cluster on powered two wheels' industry innovation. Research results are interesting for city mobility policies and the regional industry as the possible integration of ICT equipment in e bikes may speed up the market uptake of this technology.