nils-herrmann/clean_scirepeval huggingface dataset:
Severe Gestational Gigantomastia: from Mastectomy to Staged Autologous Breast Reconstruction. A Case Report
Venue: JPRAS open
Year: 2021

Gestational gigantomastia (GGM) is a rare condition characterized by a massive overgrowth of breast tissue during pregnancy. Surgical sanction may be required when conservative measures fail. In this study, we report the case of a 29 year old woman who presented with an evolutive GGM responsible for physical and emotional distress, despite medical treatment. A multidisciplinary decision was made to induce delivery at 32 weeks. In the postdelivery period, the patient developed breast wounds, complicated with septic cardiomyopathy. An emergency bilateral mastectomy was then carried out, together with banking of both nipple areola complexes. Thereafter, delayed bilateral 2 stage breast reconstruction was started at 12 months with subcutaneous tissue expanders, later on followed by implants removal and autologous reconstruction with bilateral deep inferior epigastric artery perforator flaps and bilateral nipple replantation.
Predicting Parkinson's Disease using Latent Information extracted from Deep Neural Networks
Venue: 2019 International Joint Conference on Neural Networks (IJCNN)
Year: 2019

This paper presents a new method for medical diagnosis of neurodegenerative diseases, such as Parkinson's, by extracting and using latent information from trained Deep convolutional, or convolutional recurrent Neural Networks (DNNs) In particular, our approach adopts a combination of transfer learning, k means clustering and k Nearest Neighbour classification of deep neural network learned representations to provide enriched prediction of the disease based on MRI and/or DaT Scan data. A new loss function is introduced and used in the training of the DNNs, so as to perform adaptation of the generated learned representations between data from different medical environments. Results are presented using a recently published database of Parkinson's related information, which was generated and evaluated in a hospital environment.
Feature Combination Based on Receptive Fields and Cross Fusion Feature Pyramid for Object Detection
Venue: ICONIP
Year: 2019

Currently, the state of the art method about object detector in image mainly depends on deep backbones, such as ResNet 50, DarkNet 53, ResNet 101 and DenseNet 169, which benefits for their powerful capability of feature representations but suffers from high computational cost. On the basis of fast lightweight backbone network (i.e. VGG 16) this paper improves the capability of feature representations by combining features of different receptive fields and cross fusing feature pyramids, and finally establishes a fast and accurate detector. The architecture of our model is designed to integrate FC CF Net with two sub modules: FC module and CF module. Inspired by the structure of receptive fields in visual systems of human, we propose a novel method about Feature Combination Based on Receptive Fields module (FC module) which takes the relationship between the size and eccentricity of receptive fields into account, and then combine them with original features for increasing the receptive field and information of the feature map. Furthermore, based on the structure of FPN (Feature Pyramid Network) we design a novel Cross Fusion Feature Pyramid module (CF module) which combines top down and bottom up connections to fuse features across scales, and achieves high level semantic feature map at all scales. Extensive experiments on PASCAL VOC 2007 and 2012 demonstrate that FC CF Net achieves state of the art detection accuracy (i.e. 82.4% mAP, 80.5% mAP) with high efficiency (i.e. 69 FPS, 35 FPS)
Studi Eksperimental Pengaruh Jumlah Sudu terhadap Daya pada Turbin Angin Sumbu Vertikal Tipe Rotor Crossflow untuk Optimalisasi Angin di Wilayah Pantai Kota Balikpapan
Year: 2020

Wind energy was one of the renewable energy alternatives with the biggest potential in Indonesia to be used as a power plant. Balikpapan is an area with extensive coastal areas with great wind potential. Vertical Axis Wind Turbine (VAWT) is an upright axis wind turbine whose movement of the shaft and rotor is parallel to the direction of the wind so that the rotor can rotate in all wind directions. Crossflow type VAWTis a type of VAWT that can operate at low wind speeds have a starting torque and a high value of power efficiency. VAWT is designed with specifications of rotor diameter 500 mm, rotor height 500 mm, 1:1 aspect ratio, 90 o curvature angle, and length of blade 75 mm. The variations of the number of blades used are 8, 12, and 16 blades. The results showed that the number of blades affected the power produced by the wind turbine. VAWT with the number of blades 16 is the best performing turbine with the highest power value of 10,325 mW at a wind speed of 3,05 m/s. The best and optimal performance found in the variation of the number of blades 16. It is obtained a maximum C P value of 0,00273 at Tip Speed Ratio 0,578 and maximum C T value of 0,00485 at Tip Speed Ratio 0,496 so VAWT with the number of blades 16 is the most optimal wind turbine to be applied at Manggar Beach, Balikpapan City.
Classification of the crystallization tendency of active pharmaceutical ingredients (APIs) and nutraceuticals based on their nucleation and crystal growth behaviour in solution state
Venue: Drug Delivery and Translational Research
Year: 2019

Supersaturated drug delivery systems are commonly used to address the problems of poor aqueous solubility posed by most of the active pharmaceutical ingredients (APIs) However, the supersaturated systems are highly unstable due to their high free energy levels and demonstrate a tendency to precipitate. Understanding the crystallization tendency based on the mechanisms of crystallization, that is nucleation and crystal growth, is imperative to design formulation strategies and select appropriate precipitation inhibitors. This study aims to provide a classification system, based on both the nucleation and crystal growth tendency in the solution state of 60 APIs and nutraceuticals (in absence of polymer) from their desupersaturation profiles monitored by UV Visible spectroscopy. The APIs and nutraceuticals are divided into four classes based on their induction time t ind and crystal growth rate as fast nucleators fast crystal growth (class I) fast nucleators slow crystal growth (class II) slow nucleators fast crystal growth (class III) and slow nucleators slow crystal growth (class IV) Most of the molecules fall in the class I and class IV. An easy to use protocol for nucleation and crystal growth studies has been optimized. This protocol will find application to assess the crystallization tendency of the molecules in the preliminary screening stages, enabling appropriate formulation strategies to inhibit crystallization.
An Analysis of David J. Teece's Dynamic Capabilites and Strategic Management: Organizing for Innovation and Growth
Year: 2018

Dynamic Capabilities and Strategic Management is a pioneering book in business studies, one of the most succinct and in depth examinations of dynamic capabilities, explaining both their foundations and the strategic implications they hold for both academics and practitioners in the field of business strategy, innovation, entrepreneurship and economics. In contrast to earlier works, Teece explains, using the theory of the dynamic capabilities framework, the ways in which companies shape competition itself.
Pen Mid Air Gestures: Eliciting Contextual Gestures
Venue: ICMI
Year: 2018

Combining mid air gestures with pen input for bi manual input on tablets has been reported as an alternative and attractive input technique in drawing applications. Previous work has also argued that mid air gestural input can cause discomfort and arm fatigue over time, which can be addressed in a desktop setting by allowing users to gesture in alternative restful arm positions (e.g. elbow rests on desk) However, it is unclear if and how gesture preferences and gesture designs would be different for alternative arm positions. In order to inquire these research question we report on a user and choice based gesture elicitation study in which 10 participants designed gestures for different arm positions. We provide an in depth qualitative analysis and detailed categorization of gestures, discussing commonalities and differences in the gesture sets based on a "think aloud" protocol, video recordings, and self reports on user preferences.
Learning Sparse PCA with Stabilized ADMM Method on Stiefel Manifold
Venue: IEEE Transactions on Knowledge and Data Engineering
Year: 2021

Sparse principal component analysis (SPCA) produces principal components with sparse loadings, which is very important for handling data with many irrelevant features and also critical to interpret the results. To deal with orthogonal constraints, most previous approaches address SPCA with several components using techniques such as deflation technique and convex relaxations. However, the deflation technique usually suffers from suboptimal solutions due to poor approximations. On the other hand, the convex relaxations are often computationally expensive. To address the above issues, in this paper, we propose to address SPCA over the Stiefel manifold directly, and develop a stabilized Alternating Direction Method of Multipliers (SADMM) to handle the nonconvex orthogonal constraints. Compared to traditional ADMM, the proposed SADMM method converges well with a wide range of parameters and obtains a better solution. We also theoretically study the convergence property of the proposed SADMM method. Furthermore, most existing methods ignore an inherent drawback of SPCA the importance of different components is not considered when doing feature selection, which often makes the selected features nonoptimal. To address this, we further propose a two stage method which considers the importance of different components to select the most important features. Empirical studies on both synthetic and real world datasets show that the proposed algorithms achieve better performance compared to existing state of the art methods.
Design Optimization and Analysis of a Connecting Rod using ANSYS
Year: 2013

The main Objective of this work is to explore weight reduction opportunities in the connecting rod of an I.C. engine by examining various materials such as Genetic Steel, Aluminum, Titanium and Cast Iron. This was entailed by performing a detailed load analysis. Therefore, this study has dealt with two subjects, first, static load and stress analysis of the connecting rod and second, Design Optimization for suitable material to minimize the deflection. In the first of the study the loads acting on the connecting rod as a function of time are obtained. The relations for obtaining the loads for the connecting rod at a given constant speed of crank shaft are also determined. It can be concluded from this study that the connecting rod can be designed and optimized under a comprising tensile load corresponding to 360 crank angle at the maximum engine speed as one extreme load, and the crank pressure as the other extreme load. Furthermore, the existing connecting rod can be replaced with a new connecting rod made of Genetic Steel.
Tardive dyskinesia from atypical antipsychotic agents in patients with mood disorders in a clinical setting.
Venue: Journal of affective disorders
Year: 2013

There is a paucity of information on the risks and clinical characteristics of tardive dyskinesia with atypical antipsychotic agents in patients with mood and anxiety disorders in clinical practice.  The authors retrospectively screened the charts of 268 patients with a mood or anxiety disorder treated with atypical antipsychotic agents from a psychiatric practice. Fifteen patients who developed tardive dyskinesia were identified and further data was collected on these patients.  Tardive dyskinesia occurred in 5.9% of patients after exposure to an atypical antipsychotic agent for a mean of 28.7 months (range: 1 83) The average dosage of the offending agent in chlorpromazine equivalents was 350 mg/day (range: 67 969) All patients experienced oral buccal lingual stereotypy, which was frequently severe in nature, but completely resolved in all but one patient. Most patients (90.9% who consented to a second trial of an atypical antipsychotic did not experience a relapse of TD.  All patients were treated in a clinical practice setting by a single psychiatrist, which may limit the generalizability of the findings.  The observed rate of TD represents a real world estimate of the risk of TD with atypical antipsychotic agents in patients with mood disorders. Fortunately, with early recognition symptoms appear to be reversible and further treatment with another atypical antipsychotic does not necessarily lead to relapse.
Revisiting Faster R CNN: A Deeper Look at Region Proposal Network
Venue: ICONIP
Year: 2017

Currently, state of the art object detectors are based on Faster R CNN. We firstly revisit Faster R CNN and explore problems in it, e.g. coarseness of feature maps for accurate localization, fixed window feature extraction in RPN and insensitivity for small scale objects. Then a novel object detection network is proposed to address these problems. Specifically, we utilize a two stage cascade multi scale proposal generation network to get high accurate proposals: an original RPN is adopted to initially generate coarse proposals, then another network with multi layer features and RoI pooling layer are introduced to refine these proposals. We also generate small scale proposals in the second stage simultaneously. After that, a detection network with multi layer features further classifies and refines proposals. A novel 3 step joint training algorithm is introduced to optimize our model. Experiments on PASCAL VOC 2007 and 2012 demonstrate the effectiveness of our network.
Walking On Broken Mesh: Defect Tolerant Geodesic Distances and Parameterizations
Venue: Comput. Graph. Forum
Year: 2011

Efficient methods to compute intrinsic distances and geodesic paths have been presented for various types of surface representations, most importantly polygon meshes. These meshes are usually assumed to be well structured and manifold. In practice, however, they often contain defects like holes, gaps, degeneracies, non manifold configurations or they might even be just a soup of polygons. The task of repairing these defects is computationally complex and in many cases exhibits various ambiguities demanding tedious manual efforts. We present a computational framework that enables the computation of meaningful approximate intrinsic distances and geodesic paths on raw meshes in a way which is tolerant to such defects. Holes and gaps are bridged up to a user specified tolerance threshold such that distances can be computed plausibly even across multiple connected components of inconsistent meshes. Further, we show ways to locally parameterize a surface based on geodesic distance fields, easily facilitating the application of textures and decals on raw meshes. We do all this without explicitly repairing the input, thereby avoiding the costly additional efforts. In order to enable broad applicability we provide details on two implementation variants, one optimized for performance, the other optimized for memory efficiency. Using the presented framework many applications can readily be extended to deal with imperfect meshes. Since we abstract from the input applicability is not even limited to meshes, other representations can be handled as well.
Constraints on cosmic neutrino fluxes from the Antarctic Impulsive Transient Antenna experiment.
Venue: Physical review letters
Year: 2006

We report new limits on cosmic neutrino fluxes from the test flight of the Antarctic Impulsive Transient Antenna (ANITA) experiment, which completed an 18.4 day flight of a prototype long duration balloon payload, called ANITA lite, in early 2004. We search for impulsive events that could be associated with ultrahigh energy neutrino interactions in the ice and derive limits that constrain several models for ultrahigh energy neutrino fluxes and rule out the long standing burst model.
Methodology for wear mapping error quantification
Year: 2020

The purpose of this paper is to propose a methodology to quantify the error on wear volume evaluation using optical interferometry with image analysis (OI+IA) to establish a lower threshold for wear mapping in practical applications.,A three dimensional surface wear map is quantified by measuring the same area of a surface before and after a wear process using optical interferometry. Then, by subtracting the matching images, the wear map (volume of wear) is obtained. To access the error related to wear mapping, the difference between several consecutive measurements of the same unworn surface was performed and deeply investigated.,The paper shows that the difference between two consecutive measurements of the same unworn surface, which ideally should be zero, is not. Thus, the magnitude of this "wear map" is the error. The main causes of such uncertainties are because of sample motion in a subpixel scale; a combination between surface roughness with the selected resolution; and numerical errors on the relocation process that is used to match the surfaces before subtracting them.,The proposed methodology allows one to define the lower threshold for wear map analysis using OI+IA. To know the limitation of OI+IA for wear mapping prevents misevaluation of the so called almost zero wear.,This paper covers and identifies main uncertainties and numerical errors related to optical interferometry assisted by image analysis for wear mapping. Several other papers deal with uncertainties of OI; however, this paper proposes a simple methodology to evaluate the lower threshold for wear mapping.,The peer review history for this article is available at: https:/publons.com/publon/10.1108/ILT 08 2019 0354
Advances in Cryptology ASIACRYPT 2019: 25th International Conference on the Theory and Application of Cryptology and Information Security, Kobe, Japan, December 8 12, 2019, Proceedings, Part III
Venue: ASIACRYPT
Year: 2019

We study a relaxed notion of lattice trapdoor called approximate trapdoor, which is defined to be able to invert Ajtai's one way function approximately instead of exactly. The primary motivation of our study is to improve the efficiency of the cryptosystems built from lattice trapdoors, including the hash and sign signatures. Our main contribution is to construct an approximate trapdoor by modifying the gadget trapdoor proposed by Micciancio and Peikert [Eurocrypt 2012] In particular, we show how to use the approximate gadget trapdoor to sample short preimages from a distribution that is simulatable without knowing the trapdoor. The analysis of the distribution uses a theorem (implicitly used in past works) regarding linear transformations of discrete Gaussians on lattices. Our approximate gadget trapdoor can be used together with the existing optimization techniques to improve the concrete performance of the hash and sign signature in the random oracle model under (Ring )LWE and (Ring )SIS assumptions. Our implementation shows that the sizes of the public key signature can be reduced by half from those in schemes built from exact trapdoors.
Divergences in Perceptions as for Oral Activity in Morocco
Year: 2018

This article tries to find out the few discrepancies between the teachers and their scholars as to oral activity, which shows that scholars' expectations and needs are not quite responded to. The versions chosen as a sample for this study come from different schools in the academy of Rabat Sale Zemmour Zaer area and belong to three different educational levels including common core, first year, and second year in addition to a total number of 40 teachers who have contributed to this research throughout the whole process. This research has relied on different instruments to collect the data including questionnaires, interviews, and class observation grids. Results showed that scholars' perceptions highly favour thematic variety. Findings also reported match findings of previous research in highlighting the importance of using tech facilities and multimedia to improve oral activity.
Implementing throwaway prototyping model in web development life cycle (WDLC)
Year: 2009

The purpose of this study is to analyze the relationship between web development life cycle (WDLC) and system development life cycle (SDLC) Even though the two terms WDLC and SDLC are similar in a sense that both discuss about development lifecycle but they have differences in term of its scope. From the term WDLC itself has shows that it is focusing on website development meanwhile SDLC is focusing on software at large. Website can be considered as a subset of software. Therefore, the study is about analyzing how far WDLC relevancy compares to SDLC. SDLC comprises of methodologies such as structured development, rapid application development, and agile development. In each methodology comprises of many SDLC models which complying with specific software development trends. Hence by analyzing typical website development trends and characteristic will allows to identify the suitable SDLC model. Introducing the model only will not sufficient if there is no guideline of how to apply it. Therefore the study also covers the implementation of the model with the web development processes.
EditR: A novel base editing quantification software using Sanger sequencing
Year: 2017

CRISPR/Cas9 Cytidine deaminase fusion enzymes termed Base Editors allow targeted editing of genomic deoxcytidine to deoxthymidine (C T) without the need for double stranded break induction. Base editors represent a paradigm shift in gene editing technology, due to their unprecedented efficiency to mediate targeted, single base conversion; however, current analysis of base editing outcomes rely on methods that are either imprecise or expensive and time consuming. To overcome these limitations, we developed a simple, cost effective, and accurate program to measure base editing efficiency from fluorescence based Sanger sequencing, termed EditR. We provide EditR as a free online tool or downloadable desktop application requiring a single Sanger sequencing file and guide RNA sequence (baseeditr.com) EditR is more accurate than enzymatic assays, and provides added insight to the position, type and efficiency of base editing. Collectively, we demonstrate that EditR is a robust, inexpensive tool that will facilitate the broad application of base editing technology, thereby fostering further innovation in this burgeoning field.