nils-herrmann/clean_scirepeval huggingface dataset:
Increasing the Capacities of Cable Cars for Use in Public Transport

This paper examines the advantages and disadvantages of cable cars in public transport within urban areas. The advantages of cable car transport compared to other modes of transport are its quiet operation with an environmentally acceptable electric drive and the possibility of transporting passengers above the ground, which can provide additional transport dimensions within urban centers. However, cable cars have some disadvantages, especially their smaller capacities in relation to other modes of transport within the urban environment. Today's built cable cars have capacities up to 2,000 persons/h for aerial tramways (or jig back ropeways) and up to 4,000 persons/h for gondolas. Solutions are introduced in this paper as to how the current cable car technologies can increase the capacities of these devices. This can be achieved by concentrating on the vehicles (cabins) on gondola lines and by using multiple platforms at starting stations and final stations. It also provides a solution for intermediate stations, at which vehicles can be stopped independent of other vehicles on the line.
Teaching UV Vis Spectroscopy with a 3D Printable Smartphone Spectrophotometer

Visible absorbance spectroscopy is a widely used tool in chemical, biochemical, and medical laboratories. The theory and methods of absorbance spectroscopy are typically introduced in upper division undergraduate chemistry courses, but could be introduced earlier with the right curriculum and instrumentation. A major challenge in teaching spectroscopy is gaining access to laboratory equipment, which can be expensive. Even common educational spectrophotometers still carry a substantial cost and have the disadvantage of being inherently closed designs. We report on a 3D printable smartphone spectrophotometer that is very inexpensive to build, yet retains the functionality and analytical accuracy necessary to teach concepts like the Beer Lambert Law. The optical components are arranged in an intuitive, accessible way so that students can see each relevant part and experiment with the parameters. Here, we describe the device and provide exercises to teach different concepts in analytical spectrophotometry.
Lung ultrasound: a promising tool to monitor ventilator associated pneumonia in critically ill patients
Venue: Critical Care

Ventilator associated pneumonia (VAP) is the most frequent intensive care unit (ICU) acquired infection that is independently associated with mortality. Accurate diagnosis and timely treatment have been shown to improve the prognosis of VAP. Chest X ray or computed tomography imaging are used for conventional assessment of VAP, but these methods are impractical for real time measurement in critical patients. Therefore, lung ultrasound (LUS) has been increasingly used for the assessment of VAP in the ICU. Traditionally, LUS has seemed unsuitable for the detection of lung parenchyma owing to the high acoustic impedance of air; however, the fact that the reflection and reverberation in the detection region of the ultrasound reflect the underlying pathology of lung diseases has led to the increased use of ultrasound imaging as a standard of care supported by evidence based and expert consensus in the ICU. Considering that any type of pneumonia causes air volume changes in the lungs, accumulating evidence has shown that LUS effectively measures the presence of VAP as well as dynamic changes in VAP. This review offers evidence for ultrasound as a noninvasive, easily repeatable, and bedside means to assess VAP; in addition, it establishes a protocol for qualitative and quantitative monitoring of VAP.
Adaptive learning rate CNN for SAR ATR
Venue: 2016 CIE International Conference on Radar (RADAR)

A new approach is developed for synthetic aperture radar (SAR) automatic target recognition based on convolutional neural network (CNN) In order to improve the low efficiency caused by fixed learning rate in CNN, the AdaDelta method is introduced to adjust the learning rate adaptively. The experimental results on Moving and Stationary Target Acquisition and Recognition (MSTAR) data sets show that convergence is significantly faster in proposed method than CNN with fixed learning rate.
Bit Interleaving Enabled 8T SRAM With Shared Data Aware Write and Reference Based Sense Amplifier
Venue: IEEE Transactions on Circuits and Systems II: Express Briefs

This brief proposes the design of a low voltage static random access memory (SRAM) for biomedical chip applications. The SRAM is designed using a standard 8T bit cell, featuring a shared data aware write scheme and a differential reference based sense amplifier. The proposed techniques make it possible for the 8T SRAM to use bit interleaving architecture and address the half select problem, achieving area efficiency and power reduction. A 96 kb 8T SRAM test chip is implemented in a 65 nm CMOS process to verify the proposed schemes, which operates functionality at a VDDmin of 0.36 V and has a power consumption of 5.1 mW.
Stress, Coping Strategies, and Academic Performance of Dentistry Students

The purpose of the study was to determine dentistry students' stress level and coping mechanisms and their relationship to academic performance. The study used descriptive correlational design and purposive sampling technique. The respondents were 120 Dental Proper students from Adventist University of the Philippines; 75 (63% of which are female and 45 (37% are males. Adapted survey questionnaires that measure the stress variable by Gumarao (2011) and COPE questionnaire by De Leon (2013) for the coping strategies were used. The academic performance was measured by determining the overall GPA of the respondents. The questionnaires were distributed and retrieved. The data were encoded, treated, and analyzed by the statistician. The results show that the respondents have average stress level. Most of the respondents experienced high physical stress, moderately high behavioral stress, and average emotional stress in general. Among the coping strategies, emotion focused coping and problem focused coping were often exhibited by the respondents while avoidant coping was rarely exhibited. In general, the respondents used coping strategies in an average level. The overall Grade Point Average (GPA) of the respondents was good. There is no significant relationship between stress and academic performance but there is a significant negative relationship between avoidant coping strategy used and academic performance implying that the more avoidant coping strategy is used, the lower is the academic performance of the respondents.
The Compulsive Online Shopping Scale (COSS) Development and Validation Using Panel Data
Venue: International Journal of Mental Health and Addiction

The Internet is one of the most influential forms of mass media having revolutionized human behavior, with people spending more and more time online. However, excessive Internet use, which is also termed as "Internet Addiction" can have negative consequences for an individual as well as the society in which they reside. This type of addiction is classified as behavioral addiction (DSM 5, American Psychiatric Association 2013) However, a group of American Psychiatric Association (APA) working members deemed insufficient research to consider additional behavioral addictions (e.g. compulsive buying) to be included in psychiatric nosology. Henceforth, one of the goals of this study is to shed light on what is considered "compulsive online shopping" to further support future DSM behavioral addiction classification modifications. The second goal of this study was to develop a compulsive online shopping scale (COSS) that is consistent with addiction criteria established in the DSM 5. And finally, we explored a few characteristic features related to compulsive online shoppers; both demographically and psychologically.
From HMMS to DNNS: Where do the improvements come from?
Venue: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Deep neural networks (DNNs) have recently been the focus of much text to speech research as a replacement for decision trees and hidden Markov models (HMMs) in statistical parametric synthesis systems. Performance improvements have been reported; however, the configuration of systems evaluated makes it impossible to judge how much of the improvement is due to the new machine learning methods, and how much is due to other novel aspects of the systems. Specifically, whereas the decision trees in HMM based systems typically operate at the state level, and separate trees are used to handle separate acoustic streams, most DNN based systems are trained to make predictions simultaneously for all streams at the level of the acoustic frame. This paper isolates the influence of three factors (machine learning method; state vs. frame predictions; separate vs. combined stream predictions) by building a continuum of systems along which only a single factor is varied at a time. We find that replacing decision trees with DNNs and moving from state level to frame level predictions both significantly improve listeners' naturalness ratings of synthetic speech produced by the systems. No improvement is found to result from switching from separate stream to combined stream predictions.
Deep neural network guided unit selection synthesis
Venue: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Vocoding of speech is a standard part of statistical parametric speech synthesis systems. It imposes an upper bound of the naturalness that can possibly be achieved. Hybrid systems using parametric models to guide the selection of natural speech units can combine the benefits of robust statistical models with the high level of naturalness of waveform concatenation. Existing hybrid systems use Hidden Markov Models (HMMs) as the statistical model. This paper demonstrates that the superiority of Deep Neural Network (DNN) acoustic models over HMMs in conventional statistical parametric speech synthesis also carries over to hybrid synthesis. We compare various DNN and HMM hybrid configurations, guiding the selection of waveform units in either the vocoder parameter domain, or in the domain of embeddings (bottleneck features)
Singing Voice Synthesis Based on Deep Neural Networks
Venue: INTERSPEECH

Singing voice synthesis techniques have been proposed based on a hidden Markov model (HMM) In these approaches, the spectrum, excitation, and duration of singing voices are simultaneously modeled with context dependent HMMs and waveforms are generated from the HMMs themselves. However, the quality of the synthesized singing voices still has not reached that of natural singing voices. Deep neural networks (DNNs) have largely improved on conventional approaches in various research areas including speech recognition, image recognition, speech synthesis, etc. The DNN based text to speech (TTS) synthesis can synthesize high quality speech. In the DNN based TTS system, a DNN is trained to represent the mapping function from contextual features to acoustic features, which are modeled by decision tree clustered context dependent HMMs in the HMM based TTS system. In this paper, we propose singing voice synthesis based on a DNN and evaluate its effectiveness. The relationship between the musical score and its acoustic features is modeled in frames by a DNN. For the sparseness of pitch context in a database, a musical note level pitch normalization and linear interpolation techniques are used to prepare the excitation features. Subjective experimental results show that the DNN based system outperformed the HMM based system in terms of naturalness.
Treatment and Survival of Small bowel Adenocarcinoma in the United States: A Comparison With Colon Cancer
Venue: Diseases of the colon and rectum

Small bowel adenocarcinoma is rare and fatal. Because of data paucity, there is a tendency to extrapolate treatment from colon cancer, particularly in the adjuvant stetting.  The purpose of this study was to evaluate the current surgical and adjuvant treatments of small bowel adenocarcinoma and compare with colon cancer.  This was a retrospective cohort study.  The linked Surveillance, Epidemiology, and End Results and Medicare database was used at a tertiary referral hospital.  Patients with small bowel adenocarcinoma and colon cancer identified from 1992 to 2010, using International Classification of Diseases for Oncology, 3rd Revision, site, behavior, and histology codes were included.  Overall survival and cancer specific survival were estimated using the Kaplan Meier method and competing risk analysis.  A total of 2123 patients with small bowel adenocarcinoma and 248,862 patients with colon cancer were identified. Five year overall survival rates for patients with small bowel adenocarcinoma and colon cancer were 34.9% and 51.5% (p 0.0001) A total of 1550 patients with small bowel adenocarcinoma (73.0% underwent surgery, compared with 177,017 patients with colon cancer (71.1% The proportion of patients who received chemotherapy was similar, at 21.3% for small bowel and 20.0% for colon. In contrast to colon cancer, chemotherapy did not improve overall or cancer specific survival for patients with small bowel adenocarcinoma, regardless of stage. Predictors of poor survival for small bowel adenocarcinoma on multivariate analysis included advanced age, black race, advanced stage, poor tumor differentiation, high comorbidity index, and distal location. Chemotherapy did not confer additional survival benefit compared with surgery alone (HR, 1.04 (95% CI, 0.90 1.22)  This was a retrospective review. The reliance on Medicare data limited granularity and may have affected the generalizability of the results.  The prognosis for small bowel adenocarcinoma is worse than that for colon cancer, and only surgery improves survival. In contrast to colon cancer, a survival benefit from current chemotherapy regimens for small bowel adenocarcinoma is not seen, suggesting that it may be overused and needs more rigorous study.
Impact of Social Media Applications on Small Business Entrepreneurs

The main objective of this paper is to investigate the impact of social media applications on small business entrepreneurs. It is also examined how small business owners are motivated to use social media applications. Social media completely transformed the way of businesses. Social media applications in the present time have become most efficient and effective tool for small business entrepreneurs and normally all small business use social media platform for the advertising and publicity of their products and services, they make fan pages for the followers and they warmly welcome the suggestions and opinions which help in improving their business. However, based on literature review I concluded that there is a positive impact of social media applications on small business entrepreneurs as well as they are highly motivated to use this platform.
Impact of Social Media Applications on Small Business Entrepreneurs

The main objective of this paper is to investigate the impact of social media applications on small business entrepreneurs. It also examines how small business owners are motivated to use social media applications. Social media has completely transformed the way businesses are done. Social media applications in the present time have become the most efficient and effective tool for small business entrepreneurs, and normally all small businesses use social media platforms for the advertising and publicity of their products and services. They make fan pages for their followers, and they warmly welcome their suggestions and opinions, which help in improving their businesses. However, based on literature review, we conclude that there is a positive impact of social media applications on small business entrepreneurs as well as they are highly motivated to use these platforms.
Using Evidence Based Practices to Teach Writing to Children With Autism Spectrum Disorders

Writing is a powerful tool that can be used for multiple purposes. Students demonstrate their knowledge through writing, and it is the primary means by which teachers evaluate their students' performance. Despite its importance, many students, including those with autism spectrum disorders (ASD) struggle with writing. Teachers, often unaware of what writing practices are considered evidence based, do not always know the best way to teach struggling writers, specifically those with ASD. In this article, the author reviews the characteristics of students with ASD that may affect their writing. The author also examines evidence based practices for students with ASD and how these practices can be implemented in writing instruction.
Genre Based Approach: What and How to Teach and to Learn Writing

In Indonesian education context, recently the word 'genre' seems to gain its most popular and hot issue to teaching and learning English, particularly writing skill. However, many of them the students, teachers, or university students, or even lecturers in universities apparently are not good at understanding and are not truly well informed about the genre itself. It could be said that the word 'genre' is still a kind of mystery to uncover. This paper is an attempt to present the nature of genre, genre writing, genre as a product of writing, and genre as an approach to teaching and learning writing.
Genre Based Approach: What and How to Teach and to Learn Writing.

In Indonesian education context, recently the word 'genre' seems to gain its most popular and hot issue to teaching and learning English, particularly writing skill. However, many of them the students, teachers, or university students, or even lecturers in universities apparently are not good at understanding and are not truly well informed about the genre itself. It could be said that the word 'genre' is still a kind of mystery to uncover. This paper is an attempt to present the nature of genre, genre writing, genre as a product of writing, and genre as an approach to teaching and learning writing.
"Mercados tradicionales" en los procesos de gentrificacion/recualificacion. Consensos, disputas y conflictos

Este articulo problematiza el tema de los "mercados tradicionales" en las ciudades latinoamericanas, recientemente calificados en declive y/o patrimonializados por su contenido (alimentos locales) o contenedor (edificios) Tambien analiza el vinculo entre los procesos de gentrificacion/recualificacion y el rol de los mercados en relacion con ellos. Aqui, los sujetos y grupos sociales locales y localizados, aparentemente afectados, negocian y disputan esos procesos de recualificacion publica y/o privada.
Abastecer o ser abastecido: la influencia de los mercados tradicionales sobre el tejido de Lima

El trabajo de investigacion propone que a partir de los mercados de formato tradicional se puede entender la estructuracion de barrios en la ciudad de Lima, tanto desde el punto de vista de su desarrollo urbanistico como de la progresiva materializacion espacial de la actividad, observando un vinculo entre mercado y barrio, desde los primeros descubiertos en plazas y explanadas hasta los ultimos mercados de las periferias urbanas. Asi, los mercados tradicionales en Lima constituyen un tipo de espacio actividad colectiva peculiar paradigmatico para explicar el crecimiento de la ciudad, relacionado por ejempo: (1) las estructuras espaciales construidas con (2) la coyuntura economica que las impulsa, (3) la mentalidad de los comerciantes que las emplea y (4) los habitantes que las preservan.
Additive Manufacturing Offers New Opportunities in UAV Research

Multi rotors vehicles have become a consolidated reality in modern aeronautical field. These small helicopters consist in a fuselage "hanged" under a set of fixed pitch propellers each powered by an electric motor. These vehicles have great potentials and research in this topic is increasing aimed to reduce the structure weight to maximize flight time, range and payload. Multi rotor components represent a key challenge for 3D modeling, optimization and additive manufacturing: they mainly consist in complex shapes where the most important feature are robustness and lightweight. Usually produced in small series, for example, eight parts for a single prototype, they almost need to be able to interface different materials. The work here presented shows the advanced research conducted in cooperation between Altair Engineering and Politecnico di Torino to develop vital components for the structure of a multi rotor: they represent a challenge because the main need is to interface arms, consisting in carbon fiber tubes, with motor or frame, both made in 7075 Alloy. The use of topology optimization techniques plays a key role to minimize the weight of the components and to improve the productivity of the machines. Moreover, Additive manufacturing (FDM with Sharebot NG) allows producing more parts in less time improving the cost effectiveness of the project. The process will be described from a simple characterization of the anisotropic properties of 3 D printed specimens to FEM analysis of the preliminary design of the component and to the optimization phase performed with Altair Optistruct code. An important role is played from the Altair tool used for the preliminary design: Inspire. This tool is conceived to generate structural efficient concepts quickly and easily to obtain lighter designs and eliminate structural design problems and finally provide input files for 3 D printers.
Whole Transcriptome Analysis of Verocytotoxigenic Escherichia coli O157:H7 (Sakai) Suggests Plant Species Specific Metabolic Responses on Exposure to Spinach and Lettuce Extracts
Venue: Front. Microbiol.

Verocytotoxigenic Escherichia coli (VTEC) can contaminate crop plants, potentially using them as secondary hosts, which can lead to food borne infection. Currently, little is known about the influence of the specific plant species on the success of bacterial colonization. As such, we compared the ability of the VTEC strain, E. coli O157:H7 'Sakai, to colonize the roots and leaves of four leafy vegetables: spinach (Spinacia oleracea) lettuce (Lactuca sativa) vining green pea (Pisum sativum) and prickly lettuce (Lactuca serriola) a wild relative of domesticated lettuce. Also, to determine the drivers of the initial response on interaction with plant tissue, the whole transcriptome of E. coli O157:H7 Sakai was analyzed following exposure to plant extracts of varying complexity (spinach leaf lysates or root exudates, and leaf cell wall polysaccharides from spinach or lettuce) Plant extracts were used to reduce heterogeneity inherent in plant microbe interactions and remove the effect of plant immunity. This dual approach provided information on the initial adaptive response of E. coli O157:H7 Sakai to the plant environment together with the influence of the living plant during bacterial establishment and colonization. Results showed that both the plant tissue type and the plant species strongly influence the short term (1 h) transcriptional response to extracts as well as longer term (10 days) plant colonization or persistence. We show that propagation temperature (37 vs. 18degC) has a major impact on the expression profile and therefore pre adaptation of bacteria to a plant relevant temperature is necessary to avoid misleading temperature dependent wholescale gene expression changes in response to plant material. For each of the plant extracts tested, the largest group of (annotated) differentially regulated genes were associated with metabolism. However, large scale differences in the metabolic and biosynthetic pathways between treatment types indicate specificity in substrate utilization. Induction of stress response genes reflected the apparent physiological status of the bacterial genes in each extract, as a result of glutamate dependent acid resistance, nutrient stress, or translational stalling. A large proportion of differentially regulated genes are uncharacterized (annotated as hypothetical) which could indicate yet to be described functional roles associated with plant interaction for E. coli O157:H7 Sakai.