nils-herrmann/clean_scirepeval huggingface dataset:
Water Footprint of Wheat in Iraq
Venue: Water
Year: 2019

The water footprint (WF) is an indicator of indirect and direct fresh water use. In respect of facilitating decision making processes, WF gives an excellent perspective on how and where fresh water is used in the supply chain. More than 39 million people live in Iraq and, with a growing population, there is a water shortage and a rising demand for food that cannot be met in the future. In this study, the WF of wheat production is estimated for the year 2016 2017 for 15 Iraqi provinces. The WF was calculated using the method of Mekonnen and Hoekstra (2011) and the CROPWAT and CLIMWAT softwares' crop water requirement option. It was found that the WF in m3/ton was 1876 m3/ton. The 15 provinces showed variations in WFs, which can be ascribed to the difference in climate and production values. The highest wheat WF was found in Nineveh province, followed by Muthanna, Anbar, and Basra. The last three provinces produce little and have a high WF so, in these provinces, wheat can be replaced with crops that need less water and provide more economic benefit. There is an opportunity to reduce the green WF by increasing production from the 4 rain fed provinces, which will reduce the need for production from the irrigated provinces and, therefore, reduce the use of blue water.
ImaGINator: Conditional Spatio Temporal GAN for Video Generation
Venue: 2020 IEEE Winter Conference on Applications of Computer Vision (WACV)
Year: 2020

Generating human videos based on single images entails the challenging simultaneous generation of realistic and visual appealing appearance and motion. In this context, we propose a novel conditional GAN architecture, namely ImaGINator, which given a single image, a condition (label of a facial expression or action) and noise, decomposes appearance and motion in both latent and high level feature spaces, generating realistic videos. This is achieved by (i) a novel spatio temporal fusion scheme, which generates dynamic motion, while retaining appearance throughout the full video sequence by transmitting appearance (originating from the single image) through all layers of the network. In addition, we propose (ii) a novel transposed (1+2)D convolution, factorizing the transposed 3D convolutional filters into separate transposed temporal and spatial components, which yields significantly gains in video quality and speed. We extensively evaluate our approach on the facial expression datasets MUG and UvA NEMO, as well as on the action datasets NATOPS and Weizmann. We show that our approach achieves significantly better quantitative and qualitative results than the state of the art. The source code and models are available under https:/github.com/wyhsirius/ImaGINator.
High operating temperature pBn barrier mid wavelength infrared photodetectors and focal plane array based on InAs/InAsSb strained layer superlattices.
Venue: Optics express
Year: 2020

Improving the operation temperature of the focal plane array (FPA) imagers is critical in meeting the demands to reduce the size, weight, and power (SWaP) for mid infrared detection systems. In this work, we report the demonstration of a 15 um pitch 640x512 middle format pBn FPA device with a 50% cutoff wavelength of 4.8 um based on short period of InAs/InAsSb based "Ga free" type II strained layer superlattices, which achieves a high operating temperature (HOT) reaching 185 K. The pBn FPA exhibits a mean noise equivalent differential temperature (NETD) of 39.5 mK and an operability of 99.6% by using f/2.0 optics for a 300 K background at 150 K. The mean quantum efficiency is 57.6% without antireflection coating and dark current density is 5.39x10 5 A/cm2 at an operation bias of 400 mV, by which the mean specific detectivity(D* is calculated as high as 4.43x1011 cm.Hz 1/2 /W.
Gait Training With Visual Feedback and Proprioceptive Input to Reduce Gait Asymmetry in Adults With Cerebral Palsy: A Case Series
Venue: Pediatric physical therapy the official publication of the Section on Pediatrics of the American Physical Therapy Association
Year: 2017

The purpose of this case series was to investigate the feasibility of using visual feedback on gait asymmetry during gait retraining and whether this leads to reduced asymmetry, improvement in gait speed, cost of walking, and dynamic balance in ambulant adults with cerebral palsy (CP)  Five adults with CP, who were ambulatory and had step length or stance time asymmetry, trained for 18 sessions on a split belt treadmill with concurrent visual feedback from a virtual environment. Training also included overground gait training to encourage transfer of learning.  All participants reduced gait asymmetry and improved on outcomes at posttest and follow up.  Outcome measures and training protocols were feasible in this sample of convenience of adults with CP who were ambulatory and who did not have visual impairment. The adults with CP in this study demonstrated individual improvements in gait and balance following training.
M ay 2 01 8 Engineering of Band Crossings in Honeycomb layered Transition Metal Compounds
Year: 2018

Two dimensional electron dispersions with peculiar band crossings provide a platform for realizing topological phases of matter. Here we theoretically show that the eg orbital manifold of honeycomb layered transition metal compounds accommodates a plethora of peculiar band crossings, such as multiple Dirac point nodes, quadratic band crossings, and line nodes. From the tight binding analysis, we find that the band topology is systematically changed by the orbital dependent transfer integrals on the honeycomb network of edge sharing octahedra, which can be modulated by distortions of the octahedra as well as chemical substitutions. The band crossings are gapped out by the spin orbit coupling, which brings about a variety of topological phases distinguished by the spin Chern numbers. The results provide a comprehensive understanding of the previous studies on various honeycomb compounds. We also propose another candidate materials by ab initio calculations.
Studies on Effect of Corrosion for the Selection of Material of Self Compensated Capacitive Type Liquid Level Sensor
Venue: Applied Mechanics and Materials
Year: 2019

This work deals with the design of fringe capacitance based non contact type liquid level sensor employing self compensation feature. The existing capacitive type sensors require additional compensation to overcome the problem of various stray capacitances, specifically due to atmospheric corrosion. This paper emphasizes on the selection of suitable material to accomplish the self compensation feature in corrosive environment. Rate of attack of corrosion is studied on Copper (Cu) and Aluminium (Al) samples under drizzling environment. Visual Analysis of SEM images of samples exposed for different durations reveal that Al protects itself from the corrosion. Further, performance evaluation of two sensor units with Cu and Al electrodes under the same drizzling environment beside the respective samples indicate that sensor with Al electrodes facilitates the feature of self compensation in corrosive environment. Further, the sensor is interfaced with Siemens PLC S200 for liquid threshold level monitoring.
The impact of lighting and table linen as ambient factors on meal intake and taste perception
Year: 2020

Many ambient variables appear to impact amount and duration of food intake as well as taste perception. Two studies were conducted to determine whether changing light intensity has an impact on meal duration and volume as well as sensory and qualitative aspects of tomato soup in an experimental setting. Using a randomized crossover design in study 1, 66 participants were served tomato soup twice, under dimmed and bright light. In study 2, 159 participants were assigned to one of four randomization groups. A 2 x 2 design as a group setting was chosen adding a tablecloth as another ambient component. In both studies, participants assessed the soups' appearance, sensory attributes, and the overall taste, quality and consistency on 100 mm visual analog scales. Meal duration and amount were also assessed. In study 1, there were no significant differences in amount, duration and sensory attributes between lighting conditions, except for the saltiness of the soup which was perceived as saltier under the low light condition (p 0.019) In study 2, participants ate more, longer and rated sensory attributes and quality higher when seated with tablecloth. The longest duration, highest amount and quality were observed in the dimmed light condition with tablecloth. The tablecloth seemed to have a higher impact on food amount, meal duration and overall taste perception than lighting condition. The results suggest that single ambience factors such as lighting might only play a role in food intake and perception in combination with other ambient factors, such as decorative aspects.
Comparative Evaluation of Credit Card Fraud Detection Using Machine Learning Techniques
Venue: 2019 Global Conference for Advancement in Technology (GCAT)
Year: 2019

Credit card fraud is a serious and growing problem with the increase in e commerce and online transactions in this modern era. With this identity theft and loss of money, such mischievous practices can affect millions of people around the world. Criminal activity is a rising threat to the financial sector with reaching implications.Information extraction seemed to have assumed a basic job in recognition of online payment fraud, fraud detection efficiency in credit card purchases is significantly affected by the data set measuring strategy, the choice of variable and the detection techniques used.This publication inspects execution of, Support Vector Machine, Naive Bayes, Logistic Regression and K Nearest Neighbor on exceptionally distorted data on credit card fraud.The execution of these techniques is assessed dependent on accuracy, sensitivity, precision, specificity. The outcomes show an ideal accuracy for logistic regression, Naive Bayes, k nearest neighbor and Support vector machine classifiers are 99.07% 95.98% 96.91% and 97.53% respectively. The relative outcomes demonstrate that logistic regression performs superior to other algorithms.
The role of trade and sustainable intensification to achieve global food security with less carbon emission and more carbon sequestration. G20 Insights
Year: 2018

Lower carbon emissions per unit of product can be achieved by a global initiative to expand sustainable intensification of production especially in the more productive lands of the world. This will require: a) better estimates on carbon emission and sequestration in different agricultural lands b) a strong international initiative to develop, promote and finance the development and adoption of new technologies that support and make possible a global sustainable intensification strategy and c) an efficient and open agricultural trade system that addresses the growing geographical imbalances between food production and food needs contributing to lower global carbon emission by agriculture.
Supervised Intra embedding of Fisher Vectors for Histopathology Image Classification
Venue: MICCAI
Year: 2017

In this paper, we present a histopathology image classification method with supervised intra embedding of Fisher vectors. Recently in general computer vision, Fisher encoding combined with convolutional neural network (ConvNet) has become popular as a highly discriminative feature descriptor. However, Fisher vectors have two intrinsic problems that could limit their performance: high dimensionality and bursty visual elements. To address these problems, we design a novel supervised intra embedding algorithm with a multilayer neural network model to transform the ConvNet based Fisher vectors into a more discriminative feature representation. We apply this feature encoding method on two public datasets, including the BreaKHis image dataset of benign and malignant breast tumors, and IICBU 2008 lymphoma dataset of three malignant lymphoma subtypes. The results demonstrate that our supervised intra embedding method helps to enhance the ConvNet based Fisher vectors effectively, and our classification results largely outperform the state of the art approaches on these datasets.
DIMENSI PELAYANAN PUBLIK DALAM PENGADUAN MASYARAKAT LAPOR HENDI DI KOTA SEMARANG
Year: 2020

Kota Semarang dengan layanan pengaduan Lapor Hendi merupakan salah satu kota dengan tingkat penyelesaian pengaduan masyarakat dengan 95,73% ketuntasan laporan dari total laporan sebanyak 12.019 laporan. Tujuan penelitian ini adalah menganalisis dimensi pelayanan publik dalam pengaduan masyarakat Lapor Hendi Kota Semarang menggunakan teori pelayanan publik berdasarkan pada, yaitu Kesederhanaan, Kejelasan, Kepastian Waktu, Sumber Daya Manusia, Sarana dan Prasarana, Keadilan, Komitmen, Keamanan, Kemudahan Akses, Pencatatan dan Pemulihan Layanan. Penelitian ini adalah penelitian deskriptif kualitatif. Hasil penelitian menunjukkan, pengelolaan pengaduan sudah cukup baik dengan pengenalan program yang efektif serta akses pengaduan berbagai kanal sosial media yang mempermudah masyarakat untuk melapor. Kecepatan dari program Lapor Hendi cukup baik sesuai dengan SOP yang ada namun masih ada kekurangan pada aspek sumber daya manusia pengelolaan sehingga masih adanya pengaduan yang belum terproses. Adanya pencatatan pengaduan yang dibuat berdasarkan kategori aduan serta adanya pemeriksaan dari Walikota Semarang untuk mengawasi OPD yang paling banyak pelaporannya. Diharapkan kedepannya Lapor Hendi dapat meningkatkan pelayanan publik dengan memaksimalkan personalia pegawai pengelola Lapor Hendi serta untuk pengaduan melalui sosial media bisa lebih memberikan keamanan akan privasi pelapor dan juga penindaklanjutan laporan pengaduan yang lebih baik lagi.
Urea for preventing nozzle clogging systematic approach scr
Year: 2013

A method for preventing species urea SCR system nozzle clogging. Method for the urea selective catalytic reduction (SCR) system operation to prevent auto ignition operation of urea nozzle clogging, which is stored in the urea tank by the supply module, and a nozzle connected to said urea supply module and the urea a nozzle for supplying urea and the line, the method may comprise: an evacuation step and the pressure equalization step, the evacuation step, by generating a negative pressure in the supply module and will be returned to the urea in the urea tank; the the pressure equalization step, and the supply pressure is restored by stopping module generating a negative pressure in the supply module, wherein, in said step of pressure equalization, starting from the pressure equalization step on after a predetermined time pressure force controlling whether the injection of urea.
Neural Code Search Revisited: Enhancing Code Snippet Retrieval through Natural Language Intent
Venue: ArXiv
Year: 2020

In this work, we propose and study annotated code search: the retrieval of code snippets paired with brief descriptions of their intent using natural language queries. On three benchmark datasets, we investigate how code retrieval systems can be improved by leveraging descriptions to better capture the intents of code snippets. Building on recent progress in transfer learning and natural language processing, we create a domain specific retrieval model for code annotated with a natural language description. We find that our model yields significantly more relevant search results (with absolute gains up to 20.6% in mean reciprocal rank) compared to state of the art code retrieval methods that do not use descriptions but attempt to compute the intent of snippets solely from unannotated code.
Decreased A to I RNA editing as a source of keratinocytes' dsRNA in psoriasis.
Venue: RNA
Year: 2018

Recognition of dsRNA molecules activates the MDA5 MAVS pathway and plays a critical role in stimulating type I interferon responses in psoriasis. However, the source of the dsRNA accumulation in psoriatic keratinocytes remains largely unknown. A to I RNA editing is a common co or post transcriptional modification that diversifies adenosine in dsRNA, and leads to unwinding of dsRNA structures. Thus, impaired RNA editing activity can result in an increased load of endogenous dsRNAs. Here we provide a transcriptome wide analysis of RNA editing across dozens of psoriasis patients, and we demonstrate a global editing reduction in psoriatic lesions. In addition to the global alteration, we also detect editing changes in functional recoding sites located in the IGFBP7, COPA, and FLNA genes. Accretion of dsRNA activates autoimmune responses, and therefore the results presented here, linking for the first time an autoimmune disease to reduction in global editing level, are relevant to a wide range of autoimmune diseases.
A semi automated approach for analyzing collages to inform the design of a family health information management system for Hispanic dementia caregivers
Venue: J. Biomed. Informatics
Year: 2019

Culturally and linguistically tailored health communication is needed for vulnerable populations to manage their health and the health of their families. This presents a significant design challenge. The use of collages is an increasingly popular technique with the flexibility to capture the needs and experiences of individuals with various cultural and language preferences. Collage analysis has typically remained qualitative in nature. We introduce a novel, objective, semi automated approach that enhances collage analysis to elucidate pattern differences that may not be detectable by natural perception. We present a case scenario of collage analysis based on the expressed experience and self management needs of Hispanic dementia caregivers (n=24) We demonstrate how our innovative approach may reveal cultural differences between language groups that could have otherwise been missed using traditional techniques.
Exploring teacher student interactions: communities of practice, ecological learning systems or something else?
Year: 2017

A small scale action research project was used to consider the policy and rhetoric surrounding development of the 'expert learner' and how this might be further explored to provide opportunities for learners to have greater direct involvement in reflection and discussion with teachers. The research was based within a further education setting, using participants from an 'HE in FE' curriculum area: teacher education. It sought to explore how involving students as partners in the peer observation process might be used to engage with student voice and enhance the teaching and learning experience for all involved. To evaluate the creation, sharing and development of teaching and learning that might be generated in such circumstances, the research used two theoretical frameworks to analyse the data: communities of practice and ecological learning systems. This article reviews the literature around these two frameworks and critically reflects on the influences of these approaches in communities of teaching and learning. Analysis of interviews, and the interactions and dialogue contained within these, revealed something else happening within these connections. As such, it considers the opportunities facilitated in this context and how development of a newly devised continuum of practice may be used to enable professional dialogue to enhance student teacher interactions.
Fast Training of a Convolutional Neural Network for Brain MRI Classification
Venue: ACM Southeast Regional Conference
Year: 2019

The increase in AD population calls for an automated and accurate method for efficiently diagnosing AD through MRI, preferably at the stage of Early MCI (EMCI) Graphics Processing Unit (GPU) ReLU, Dropout contribute to better performance of Artificial Neural Network (ANN) resulting in a considerable decline in error rates for computer vision tasks like MRI based diagnosis through classification. CNN based architectures such as AlexNet have become dominant in image classification challenges. VGG like architectures emerged as improved variants of AlexNet but the large numbers of kernels and layers in VGG tend to slow down the training process. VoxCNN has been designed for binary AD/LMCI/EMCI/Normal classification of 3D MRI images, incorporating batch normalization, Dropout and Adam for training. Although VoxCNN output decent results with a relatively small dataset as input, the fact that 150 epochs have to be performed for each run of classification is prone to yield a lengthy training process. We tweaked Dropout probability and managed to reduce training time of VoxCNN by 49% while maintaining the same level of prediction performance in binary AD/LMCI/EMCI/Normal classification. Both ROC AUC and accuracy exhibited minor loss, i.e. 0.3% and 1.4% respectively. Standard deviation of both ROC AUC and accuracy at Epoch 75 was improved on the whole after adjustment of Dropout probability.
Isometric hip abduction using a Thera Band alters gluteus maximus muscle activity and the anterior pelvic tilt angle during bridging exercise.
Venue: Journal of electromyography and kinesiology official journal of the International Society of Electrophysiological Kinesiology
Year: 2015

The purpose of this study was to investigate the effects of bridging with isometric hip abduction (IHA) using the Thera Band on gluteus maximus (GM) hamstring (HAM) and erector spinae (ES) muscle activity; GM/HAM and GM/ES ratios; and the anterior pelvic tilt angle in healthy subjects. Twenty one subjects participated in this study. Surface EMG was used to collect EMG data of GM, HAM, and ES muscle activities, and Image J software was used to measure anterior pelvic tilt angle. A paired t test was used to compare GM, HAM, and ES muscle activity; the GM/HAM and GM/ES ratios; and the anterior pelvic tilt angle with and without IHA during the bridging exercise. GM muscle activity increased significantly and the anterior pelvic tilt angle decreased significantly during bridging with IHA using the Thera Band (p 0.05) However, there were no significant differences in the activity of the HAM and ES and the GM/HAM and GM/ES ratios between bridging with and without IHA (p 0.05) The results of this study suggest that bridging with IHA using the Thera Band can be implemented as an effective method to facilitate GM muscle activity and reduce the anterior pelvic tilt angle.
Fundraising campaigns via social media platforms for mitigating the impacts of the COVID 19 epidemic
Year: 2020

The rapid outbreak of coronavirus 2019 (COVID 19) has triggered unprecedented restrictions on not only human movement but also a wide sphere of economic activities, disrupting livelihood, welfare and business worldwide In response, some Muslim communities have launched fundraising campaigns to mitigate the socio economic impacts of the virus on the front liners and the most affected segments of vulnerable populations The purpose of this study is to explore the intrinsic and extrinsic motivations of donors to these campaigns who contribute via social media platforms (SMPs)  This study adopts a cross sectional research design using an online survey conducted in a typical Muslim community such as Kuwait A total of 565 samples of data (356 women, 209 men) were used for analysis Partial least squares structural equation modeling was used to estimate the research model and extract meaningful conclusions  The results show that charitable projects, internet technology features, SMP features and religiosity are significant motivations that influence attitudes toward online donations related to COVID 19 response All these relationships are indirectly related to intentions to donate via SMP through a significant mediating effect of attitude  The outcome of this study could support the efforts of governments, non profit organizations and communities to focus attention on suitable proactive strategies to boost online fundraising campaigns for those affected by epidemic diseases  This study enriches the literature by integrating both intrinsic and extrinsic motivations of online donations into a new and unique related context such as SMP, especially amid the COVID 19 crisis (c) 2020, Emerald Publishing Limited