nils-herrmann/clean_scirepeval huggingface dataset:
An empirical exploration of CTC acoustic models
Venue: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

The connectionist temporal classification (CTC) loss function has several interesting properties relevant for automatic speech recognition (ASR) applied on top of deep recurrent neural networks (RNNs) CTC learns the alignments between speech frames and label sequences automatically, which removes the need for pre generated frame level labels. CTC systems also do not require context decision trees for good performance, using context independent (CI) phonemes or characters as targets. This paper presents an extensive exploration of CTC based acoustic models applied to a variety of ASR tasks, including an empirical study of the optimal configuration and architectural variants for CTC. We observe that on large amounts of training data, CTC models tend to outperform state of the art hybrid approach. Further experiments reveal that CTC can be readily ported to syllable based languages, and can be enhanced by employing improved feature front ends.
Optimal heat exchanger network synthesis with operability and safety considerations
Venue: Clean Technologies and Environmental Policy

Research on the optimal design of heat exchanger networks (HENs) has primarily revolved around trading off technical design requirements for aspects of economy, such as capital cost of heat exchangers and utilities. As a result, considerations for safety, operability, and flexibility have received much less attention. This study presents a Pinch Analysis based methodology that considers the inherent safety and operability aspects of an optimal HEN design. The procedure begins with data extraction, followed by utility targeting that gives due consideration to how each process stream impacts the inherent safety of the HEN. This is made possible via the use of a hot and cold Stream Temperature versus Enthalpy Plot (STEP) that prioritises the inherent safety index (ISI) on top of the heat capacity flow rate (CPs) during simultaneous targeting and design of the HEN. The Pinch temperatures and minimum utilities were determined using STEP. At the same time, the hot and cold stream pairs with higher ISIs and those with lower ISIs were matched together so that safety considerations could be emphasised and precautions taken with a particular heat exchanger. The disturbance propagation path through the HEN and the affected streams were also analysed. Network modification was performed using the downstream path concept in order to reduce disturbance propagation downstream of the HEN. The Tmin violations and energy penalties from network changes were assessed. Flexibility and structural controllability of each network option were compared. The highest percentage of change in every stream of the network indicates that network is the most flexible, while the index of structural controllability closest to 1 demonstrates that the network is most controllable. Application of this method within an illustrative case study showed that network 3 was the most flexible as it yielded the highest percentage of change at 22 It was also the most controllable as it had a controllability index closest to 1.0, i.e. at 0.917.
Structural RNN: Deep Learning on Spatio Temporal Graphs
Venue: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Deep Recurrent Neural Network architectures, though remarkably capable at modeling sequences, lack an intuitive high level spatio temporal structure. That is while many problems in computer vision inherently have an underlying high level structure and can benefit from it. Spatiotemporal graphs are a popular tool for imposing such high level intuitions in the formulation of real world problems. In this paper, we propose an approach for combining the power of high level spatio temporal graphs and sequence learning success of Recurrent Neural Networks (RNNs) We develop a scalable method for casting an arbitrary spatio temporal graph as a rich RNN mixture that is feedforward, fully differentiable, and jointly trainable. The proposed method is generic and principled as it can be used for transforming any spatio temporal graph through employing a certain set of well defined steps. The evaluations of the proposed approach on a diverse set of problems, ranging from modeling human motion to object interactions, shows improvement over the state of the art with a large margin. We expect this method to empower new approaches to problem formulation through high level spatio temporal graphs and Recurrent Neural Networks.
CNN RNN: A Unified Framework for Multi label Image Classification
Venue: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

While deep convolutional neural networks (CNNs) have shown a great success in single label image classification, it is important to note that real world images generally contain multiple labels, which could correspond to different objects, scenes, actions and attributes in an image. Traditional approaches to multi label image classification learn independent classifiers for each category and employ ranking or thresholding on the classification results. These techniques, although working well, fail to explicitly exploit the label dependencies in an image. In this paper, we utilize recurrent neural networks (RNNs) to address this problem. Combined with CNNs, the proposed CNN RNN framework learns a joint image label embedding to characterize the semantic label dependency as well as the image label relevance, and it can be trained end to end from scratch to integrate both information in a unified framework. Experimental results on public benchmark datasets demonstrate that the proposed architecture achieves better performance than the state of the art multi label classification models.
Generation of BiKEs and TriKEs to Improve NK Cell Mediated Targeting of Tumor Cells.
Venue: Methods in molecular biology

Cancer immunotherapies have gained significant momentum over the past decade, particularly with the advent of checkpoint inhibitors and CAR T cells. While the latter personalized targeted immunotherapy has revolutionized the field, a need for off the shelf therapies remains. The ability of NK cells to quickly lyse antibody coated tumors and potently secrete cytokines without prior priming has made NK cells ideal candidates for antigen specific immunotherapy. NK cells have been targeted to tumors through two main strategies: mono specific antibodies and bi/tri specific antibodies. Mono specific antibodies drive NK cell antibody dependent cell mediated cytotoxicity (ADCC) of tumor cells. Bi/tri specific antibodies drive re directed lysis of tumor cells through binding of a tumor antigen and direct binding and crosslinking of the CD16 receptor on NK cells, thus bypassing the need for binding of the Fc portion of mono specific antibodies. This chapter focuses on the generation of bi and tri specific killer engagers (BiKEs and TriKEs) meant to target NK cells to tumors. BiKEs and TriKEs are smaller molecules composed of 2 3 variable portions of antibodies with different specificities, and represent a novel and more versatile strategy compared to traditional bi and tri specific antibody platforms.
A Coherent Framework for Understanding the Success of an Information System Project

This paper elucidates the sequential revisions of an information system (IS) project framework across the research model development and its examinations. The authors adopted, adapted, and combined five concepts of the project management discipline and the information processing theory to revise the framework. Besides the use of this multi dimensional perspective, the authors were also succeeded to present an interrelation between the framework and the examined model within a coherent representation. It was one of the essential points of this model development study, in particular for presenting the research focus. It may be trivial issue for the experts in the research fields, but the coherent illustration is one of the critical issues in the validity measurement of a model, whereas the inexpert ones may need a guideline to represent the interrelationship. Such points became the main contribution of this study to fill the gap in the literatures, particularly in the lack of comprehensive detail of a research model development.
Chapter 13 Axel Hagerstrom at the Origins of the Uppsala School

The problem of consciousness became thorny from Descartes onward. His infamous interactionist dualism (Seager 2007, 9) between res cogitans (mind) and res extensa (matter) was at the origin of a host of philosophical problems and eventually gave rise to a number of different trends in epistemology and ontology, among which the two basic, all embracing, and opposite kinds of monism, that is, philosophical idealism and philosophical realism.
All solid state battery using layered oxide cathode, lithium carbon composite anode and thio LISICON electrolyte

The investigation of a lithium carbon composite (Li C) anode for application in all solid state battery, based on (Li2S)(0.75) (P2S5)(0.25) glassy thio LISICON electrolyte (Li2S P2S5) is herein reported. The Li C anode material is prepared by a mechanochemical, single step synthesis procedure. The Li C/electrolyte interface is characterized in terms of cyclic voltammetry, electrochemical impedance spectroscopy and galvanostatic cycling in comparison with lithium metal, in order to evaluate the improvements in terms of resistance and lithium stripping deposition ability. Li C anode powder is pressed into a pellet together with the Li2S P2S5 electrolyte and Li2ZrO3 coated, Li[Ni0.8Co0.15Al0.05]O 2 cathode powder (NCA LZO) to form a new type of solid state battery operating at room temperature. The Li C/Li2S P2S5/NCA LZO battery shows remarkable cycling performance under galvanostatic conditions, particularly if compared to a more conventional configuration employing lithium metal as the anode. In addition, the all solid state battery is characterized at various current densities, showing satisfactory rate capability. Under long term cycling condition, performed at low current and prolonged to more than 250 days, the cell shows a stability over 100 cycles without fading. This is considered a remarkable result suggesting the solid state cell here studied as suitable candidate for efficient and safe energy storage.
Subpopulation Treatment Effect Pattern Plot (STEPP) analysis for continuous, binary, and count outcomes
Venue: Clinical trials

For the past few decades, randomized clinical trials have provided evidence for effective treatments by comparing several competing therapies. Their successes have led to numerous new therapies to combat many diseases. However, since their conclusions are based on the entire cohort in the trial, the treatment recommendation is for everyone, and may not be the best option for an individual. Medical research is now focusing more on providing personalized care for patients, which requires investigating how patient characteristics, including novel biomarkers, modify the effect of current treatment modalities. This is known as heterogeneity of treatment effects. A better understanding of the interaction between treatment and patient specific prognostic factors will enable practitioners to expand the availability of tailored therapies, with the ultimate goal of improving patient outcomes. The Subpopulation Treatment Effect Pattern Plot (STEPP) approach was developed to allow researchers to investigate the heterogeneity of treatment effects on survival outcomes across values of a (continuously measured) covariate, such as a biomarker measurement.  Here, we extend the Subpopulation Treatment Effect Pattern Plot approach to continuous, binary, and count outcomes, which can be easily modeled using generalized linear models. With this extension of Subpopulation Treatment Effect Pattern Plot, these additional types of treatment effects within subpopulations defined with respect to a covariate of interest can be estimated, and the statistical significance of any observed heterogeneity of treatment effect can be assessed using permutation tests. The desirable feature that commonly used models are applied to well defined patient subgroups to estimate treatment effects is retained in this extension.  We describe a simulation study to confirm that the proper Type I error rate is maintained when there is no treatment heterogeneity, and a power study to show that the statistics have power to detect treatment heterogeneity under alternative scenarios. As an illustration, we apply the methods to data from the Aspirin/Folate Polyp Prevention Study, a clinical trial evaluating the effect of oral aspirin, folic acid, or both as a chemoprevention agent against colorectal adenomas. The pre existing R software package stepp has been extended to handle continuous, binary, and count data using Gaussian, Bernoulli, and Poisson models, and it is available on the Comprehensive R Archive Network.  The extension of the method and the availability of new software now permit STEPP to be applied to the full range of clinical trial end points.
Meta STEPP: subpopulation treatment effect pattern plot for individual patient data meta analysis.
Venue: Statistics in medicine

We have developed a method, called Meta STEPP (subpopulation treatment effect pattern plot for meta analysis) to explore treatment effect heterogeneity across covariate values in the meta analysis setting for time to event data when the covariate of interest is continuous. Meta STEPP forms overlapping subpopulations from individual patient data containing similar numbers of events with increasing covariate values, estimates subpopulation treatment effects using standard fixed effects meta analysis methodology, displays the estimated subpopulation treatment effect as a function of the covariate values, and provides a statistical test to detect possibly complex treatment covariate interactions. Simulation studies show that this test has adequate type I error rate recovery as well as power when reasonable window sizes are chosen. When applied to eight breast cancer trials, Meta STEPP suggests that chemotherapy is less effective for tumors with high estrogen receptor expression compared with those with low expression.
Subpopulation Treatment Effect Pattern Plot (STEPP) analysis of Ki67 assay according to histology: prognostic relevance for resected early stage 'pure' and 'mixed' lobular breast cancer
Venue: Journal of experimental clinical cancer research CR

BackgroundThe aim of this analysis was to investigate the potential impact of Ki67 assay in a series of patients affected by early stage invasive lobular carcinoma (ILC) undergone surgery.MethodsClinical pathological data were correlated with disease free and overall survival (DFS/OS) The maximally selected Log Rank statistics analysis was applied to the Ki67 continuous variable to estimate appropriate cut offs. The Subpopulation Treatment Effect Pattern Plot (STEPP) analysis was performed to assess the interaction between 'pure' or 'mixed' histology ILC and Ki67.ResultsAt a median follow up of 67 months, 10 years DFS and OS of 405 patients were 67.8 and 79.8 respectively. Standardized Log Rank statistics identified 2 optimal cut offs (6 and 21 10 years DFS and OS were 75.1, 66.5, and 30.2 (p 0.01) and 84.3, 76.4 and 59 (p 0.003) for patients with a Ki67 6 between 6 and 21 and >21 respectively. Ki67 and lymph node status were independent predictor for longer DFS and OS at the multivariate analysis, with radiotherapy (for DFS) and age (for OS) Ki67 highly replicated at the internal cross validation analysis (DFS 85 OS 100 The STEPP analysis showed that DFS rate decreases as Ki67 increases and those patients with 'pure' ILC performed worse than 'mixed' histology.ConclusionsDespite the retrospective and exploratory nature of the study, Ki67 was able to significantly discriminate the prognosis of patients with ILC, and the effect was more pronounced for patients with 'pure' ILC.
Shape memory alloy thin films and heterostructures for MEMS applications: A review

In recent years, shape memory alloy (SMA) thin films have attracted significant attention from the scientific community and industry for their potential applications in the field of smart sensors and actuators, micro and nano electromechanical systems, aerospace, automobile, and biomedical. The present article focuses on the recent developments in the field of SMA thin films and their heterostructures with other materials for potential microelectromechanical systems (MEMS) applications. Various microdevices such as microgrippers, micropumps, microvalves, and cantilevers fabricated from binary and ternary SMA films have been discussed in detail. SMA thin films combined with various nitrides, oxides, and ferroelectric layers offer excellent surface modification and vibration damping at microscale for their use in harsh environments. The article encompasses the new paradigms in the field of SMA thin films that have been essentially developed by the authors and co workers during the past 6 years.
A high power density drivetrain integrated electric vehicle charger
Venue: 2016 IEEE Energy Conversion Congress and Exposition (ECCE)

This paper presents a new architecture for an isolated level 2 on board electric vehicle (EV) battery charger which is integrated with the EV's drivetrain dc dc boost converter. The proposed charger leverages many of the existing stages of a highly efficient and power dense composite architecture based drivetrain boost converter. This composite boost converter comprises a buck, a boost and a dc transformer (DCX) stage. In selecting the proposed charging architecture, four alternative approaches to drivetrain integration are identified, explored and compared quantitatively in terms of added weight and charging losses. Out of the considered approaches, the proposed charging architecture provides an effective tradeoff between additional weight and charging losses. This drivetrain integrated charger adds only a bridgeless boost based power factor correction (PFC) ac dc stage, plus an H bridge and a single winding to the composite boost converter, to achieve high power on board charging functionality without substantial additional weight. A 6.6 kW prototype of the proposed charger has been designed and its PFC stage built and tested. The PFC stage uses a digital implementation of a current sensor less control strategy and employs effective ways of mitigating zero crossing distortion. The proposed charger architecture reduces the additional weight required for the onboard charging functionality, while achieving greater than 97% peak efficiency for the added charger module PFC stage.
Effect of Pretreatments and Storage Conditions on Shelf life Extension of Sapota (Achras zapota) Fruit and on Quality of Osmo Dehydrated Slices

The aim of the present study pertains to the extension of shelf life of fresh sapota pretreated with varying concentrations of calcium chloride at low temperature (LT) storage and thereafter to appraise stored sapota for the development of osmodehydrated slices using hypertonic sugar syrup. In the present study, an attempt was made to prolong the shelf life of Sapota fruits by maintain the initial fruit quality attributes under the influence of surface coatings with fruit hardening chemical agent and low temperature (LT) storage condition and to find out its suitability for processed product development. Optimally matured (13.30Brix) Sapota (var.Cricket ball) fruits pretreated with solutions of calcium chloride at various levels (3.0, 4.0 and 4.5% and were stored at LT (12+ 1degC, 90 95% RH) condition. Results indicated that optimally matured, LT (12+ 1degC, 90 95% RH) stored sapota fruits, pretreated with Calcium chloride treatments (T2 4 Calcium chloride and T3 4.5% Calcium chloride) were most effective surface hardening chemical agents. Only these treatments were effective with better retention of the fruit quality attributes such as, fruit texture, acidity, ascorbic acid, total soluble solids, total sugar and reducing sugars, without fruit spoilage, with effective shelf life of 32 days as compared 24 days in untreated control sapota fruits stored at same storage condition. Both the Initial and final dehydrated sapota slices prepared from these treatments(T2 4 Calcium chloride and T3 4.5% Calcium chloride) were found to be excellent in terms of all the product quality parameters evaluated with the shelf stability of 4 months at RT (29+ 2degC, 60 75%RH) condition. Moisture sorption studies of these dehydrated sapota slices revealed that flexible packaging materials such as 75 mm LDPE or 50mm cast PP or 25mm HDPE can give the required protection. The osmo dehydrated sapota slices developed in this study represents an innovative and natural processed products from sapota fruits pretreated with T2 4 Calcium chloride and T3 4.5% Calcium chloride after effective storage life of 32 days at LT(12+ 1degC, 90 95% RH) which can be incorporated into different food products due to its high nutritional and sensory quality attributes.
Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud
Venue: Manag. Sci.

Consumer reviews are now part of everyday decision making. Yet, the credibility of these reviews is fundamentally undermined when businesses commit review fraud, creating fake reviews for themselves or their competitors. We investigate the economic incentives to commit review fraud on the popular review platform Yelp, using two complementary approaches and datasets. We begin by analyzing restaurant reviews that are identified by Yelp's filtering algorithm as suspicious, or fake and treat these as a proxy for review fraud (an assumption we provide evidence for) We present four main findings. First, roughly 16% of restaurant reviews on Yelp are filtered. These reviews tend to be more extreme (favorable or unfavorable) than other reviews, and the prevalence of suspicious reviews has grown significantly over time. Second, a restaurant is more likely to commit review fraud when its reputation is weak, i.e. when it has few reviews, or it has recently received bad reviews. Third, chain restaurants which benefit less from Yelp are also less likely to commit review fraud. Fourth, when restaurants face increased competition, they become more likely to receive unfavorable fake reviews. Using a separate dataset, we analyze businesses that were caught soliciting fake reviews through a sting conducted by Yelp. These data support our main results, and shed further light on the economic incentives behind a business's decision to leave fake reviews.
Turkish Pre Service Teachers' Reflective Practices in Teaching English to Young Learners.

The course 'Teaching English to Young Learners' is the first stage where pre service teachers are introduced to a child's world, developmental characteristics, needs, interests as well as teaching and learning techniques for these learners in English language teaching pre service teacher education programmes in Turkey. This action research study identifies the gap that pre service teachers experience between the theoretical considerations and realities of teaching, and the problems they face in this course. It provides the opportunity for monitoring and evaluating themselves in a pre service teacher education programme in Turkey. Hence, this piece of research aims to promote reflective practice at the preservice level in teaching English to young learners through video recorded microteaching sessions, reflective journals, and lesson plans of pre service teachers. The study reports on the results by highlighting the contribution of these reflective tools to pre service teachers' professional development, self and peer reflections and the preparedness to teach English to young learners. Finally, insights and recommendations concerning teacher educators and pre service programmes are offered to promote reflective practice and make methodology courses more beneficial before pre service teachers embark on their practicum experience.