nils-herrmann/clean_scirepeval huggingface dataset:
Mitochondrial DNA polymorphism, phylogeography, and conservation genetics of the brown bear Ursus arctos in Europe.

Some small European populations of the brown bear (Ursus arctos) are threatened by the risk of extinction in the near future. The reinforcement of these populations with bears from other regions might provide a solution to their future survival. However, before any population transfer, the different conservation units must be identified. The phylogeographic approach has been advocated for this purpose. The different European populations were assayed for mitochondrial (mt) DNA polymorphism. A remarkable degree of concordance was found between the geographic distribution and the mtDNA haplotypes. Two clearly distinct lineages differing by more than 7% in mtDNA control region sequences were found and, furthermore, the western lineage appears to be organized into two clades which correspond to two different ancestral refugia. The potential conservation units can be deduced from these results, and a management policy can consequently be inferred. This study clearly demonstrates the relevance of the molecular phylogeographic approach to the identification of conservation units.
Academic Procrastination : Frequency and Cognitive-Behavioral Correlates

This study investigated the frequency of college students' procrastination on academic tasks and the reasons for procrastination behavior. A high percentage of students reported problems with procrastination on several specific academic tasks. Self-reported procrastination was positively correlated with the number of self-paced quizzes students took late in the semester and with participation in an experimental session offered late in the semester. A factor analysis of the reasons for procrastination indicated that the factors Fear of Failure and Aversiveness of the Task accounted for most of the variance. A small but very homogeneous group of subjects endorsed items on the Fear of Failure factor that correlated significantly with self-report measures of depression, irrational cognitions, low self-esteem, delayed study behavior, anxiety, and lack of assertion. A larger and relatively heterogeneous group of subjects reported procrastinating as a result of aversiveness of the task. The Aversiveness of the Task factor did not correlate significantly with anxiety or assertion, but it did correlate significantly with'depression, irrational cognitions, low self-esteem, and delayed study behavior. These results indicate that procrastination is not solely a deficit in study habits or time management, but involves a complex interaction of behavioral, cognitive, and affective components;
Using machine learning techniques for sentiment analysis

The Natural language processing is the discipline that studies how to make the machines read and interpret the language that the people use, the natural language. But in the machines world, the words not exist and they are represented by sequences of numbers that the machine represents with a character when displaying them on screen. The Sentiment Analysis is the name of the problem that with a sentence or text the machine gets capable to analyze and predict with the maximum precision possible the sentiment that will be obtained by a person when reads it or the contextual opinion related to something. This document wants to show what we can obtain using the most used machine learning tools.  Sentiment Analysis, Data Mining, Machine Learning, Natural Language, Support Vector Machines, Decision Trees, Recurrent Neural Networks, Naive Bayes
Physico‐chemical stability of docetaxel premix solution and docetaxel infusion solutions in PVC bags and polyolefine containers

We assessed the physical and chemical stability of docetaxel infusion solutions. Stability of the antineoplastic drug was determined 1.) after reconstitution of the injection concentrate and 2.) after further dilution in two commonly used vehicle‐solutions, 0.9% sodium chloride and 5% dextrose, in PVC bags and polyolefine containers. Chemical stability was measured by using a stability‐indicating HPLC assay with ultraviolet detection. Physical stability was determined by visual inspection. The stability tests revealed that reconstituted docetaxel solutions (= premix solutions) are physico‐chemically stable (at a level ≥ 95% docetaxel) for a minimum of four weeks, independent of the storage temperature (refrigerated, room temperature). Diluted infusion solutions (docetaxel concentration 0.3 mg/ml and 0.9 mg/ml), with either vehicle‐solution, proved physico‐chemically stable (at a level ≥ 95% docetaxel) for a minimum of four weeks, when prepared in polyolefine containers and stored at room temperature. However, diluted infusion solutions exhibited limited physical stability in PVC bags, because docetaxel precipitation occured irregularly, though not before day 5 of storage. In addition, time‐dependent DEHP‐leaching from PVC infusion bags by docetaxel infusion solutions must be considered.
A study of flip-chip direct attachment LED COBs with metal core print circuit boards

One of the most critical reliability problems that the LED COBs are facing is the failure of wire bonding connections. The LED COBs would easily break down due to the mechanical shocks or material stress on the gold wire in conventional package roadmaps. Flip chip technologies are excellent options for solving this problem. This paper has been focused on the challenges during the design and manufacturing of flip chip LED COBs based on metal core print circuit boards (MCPCBs). The properties of solder paste, Au/Sn eutectic, and ceramic buffer die-bonding structures are studied. It is found out that the former two COBs have better thermal and optical performance, while the last COB shows good reliability with low leakage current.
Healable capacitive touch screen sensors based on transparent composite electrodes comprising silver nanowires and a furan/maleimide diels-alder cycloaddition polymer.

A healable transparent capacitive touch screen sensor has been fabricated based on a healable silver nanowire-polymer composite electrode. The composite electrode features a layer of silver nanowire percolation network embedded into the surface layer of a polymer substrate comprising an ultrathin soldering polymer layer to confine the nanowires to the surface of a healable Diels-Alder cycloaddition copolymer and to attain low contact resistance between the nanowires. The composite electrode has a figure-of-merit sheet resistance of 18 Ω/sq with 80% transmittance at 550 nm. A surface crack cut on the conductive surface with 18 Ω is healed by heating at 100 °C, and the sheet resistance recovers to 21 Ω in 6 min. A healable touch screen sensor with an array of 8×8 capacitive sensing points is prepared by stacking two composite films patterned with 8 rows and 8 columns of coupling electrodes at 90° angle. After deliberate damage, the coupling electrodes recover touch sensing function upon heating at 80 °C for 30 s. A capacitive touch screen based on Arduino is demonstrated capable of performing quick recovery from malfunction caused by a razor blade cutting. After four cycles of cutting and healing, the sensor array remains functional.
Privacy-preserving logistic regression training

Logistic regression is a popular technique used in machine learning to construct classification models. Since the construction of such models is based on computing with large datasets, it is an appealing idea to outsource this computation to a cloud service. The privacy-sensitive nature of the input data requires appropriate privacy preserving measures before outsourcing it. Homomorphic encryption enables one to compute on encrypted data directly, without decryption and can be used to mitigate the privacy concerns raised by using a cloud service. In this paper, we propose an algorithm (and its implementation) to train a logistic regression model on a homomorphically encrypted dataset. The core of our algorithm consists of a new iterative method that can be seen as a simplified form of the fixed Hessian method, but with a much lower multiplicative complexity. We test the new method on two interesting real life applications: the first application is in medicine and constructs a model to predict the probability for a patient to have cancer, given genomic data as input; the second application is in finance and the model predicts the probability of a credit card transaction to be fraudulent. The method produces accurate results for both applications, comparable to running standard algorithms on plaintext data. This article introduces a new simple iterative algorithm to train a logistic regression model that is tailored to be applied on a homomorphically encrypted dataset. This algorithm can be used as a privacy-preserving technique to build a binary classification model and can be applied in a wide range of problems that can be modelled with logistic regression. Our implementation results show that our method can handle the large datasets used in logistic regression training.
DevOps: Making It Easy to Do the Right Thing

Wotif Group used DevOps principles to recover from the downward spiral of manual release activity that many IT departments face. Its approach involved the idea of "making it easy to do the right thing." By defining the right thing (deployment standards) for development and operations teams and making it easy to adopt, Wotif drastically improved the average release cycle time. This article is part of a theme issue on DevOps.
Frustum-traced raster shadows: revisiting irregular z-buffers

We present a real-time system that renders antialiased hard shadows using irregular z-buffers (IZBs). For subpixel accuracy, we use 32 samples per pixel at roughly twice the cost of a single sample. Our system remains interactive on a variety of game assets and CAD models while running at 1080p and 2160p and imposes no constraints on light, camera or geometry, allowing fully dynamic scenes without precomputation. Unlike shadow maps we introduce no spatial or temporal aliasing, smoothly animating even subpixel shadows from grass or wires.
 Prior irregular z-buffer work relies heavily on GPU compute. Instead we leverage the graphics pipeline, including hardware conservative raster and early-z culling. We observe a duality between irregular z-buffer performance and shadow map quality; this allows common shadow map algorithms to reduce our cost. Compared to state-of-the-art ray tracers, we spawn similar numbers of triangle intersections per pixel yet completely rebuild our data structure in under 2 ms per frame.
An STS-based map of the human genome.

A physical map has been constructed of the human genome containing 15,086 sequence-tagged sites (STSs), with an average spacing of 199 kilobases. The project involved assembly of a radiation hybrid map of the human genome containing 6193 loci and incorporated a genetic linkage map of the human genome containing 5264 loci. This information was combined with the results of STS-content screening of 10,850 loci against a yeast artificial chromosome library to produce an integrated map, anchored by the radiation hybrid and genetic maps. The map provides radiation hybrid coverage of 99 percent and physical coverage of 94 percent of the human genome. The map also represents an early step in an international project to generate a transcript map of the human genome, with more than 3235 expressed sequences localized. The STSs in the map provide a scaffold for initiating large-scale sequencing of the human genome.
Make E-Learning Effortless! Impact of a Redesigned User Interface on Usability through the Application of an Affordance Design Approach

Given that a user interface interacts with users, a critical factor to be considered in improving the usability of an e-learning user interface is user-friendliness. Affordances enable users to more easily approach and engage in learning tasks because they strengthen positive, activating emotions. However, most studies on affordances limit themselves to an examination of the affordance attributes of e-learning tools rather than determining how to increase such attributes. A design approach is needed to improve affordances for e-learning user interfaces. Using Maier and Fadel’s Affordance-Based Design methodology as a framework, the researchers in this study identified affordance factors, suggested affordance design strategies for the user interface, and redesigned an affordable user interface prototype. The identified affordance factors and strategies were reviewed and validated in Delphi meetings whose members were teachers, e-learning specialists, and educational researchers. The effects of the redesigned user interface on usability were evaluated by fifth-grade participating in the experimental study. The results show that affordances led users to experience positive emotions, and as a result, use the interface effectively, efficiently, and satisfactorily. Implications were discussed for designing strategies to enhance the affordances of the user interfaces of e-learning and other learning technology tools.
iSensestress: Assessing stress through human-smartphone interaction analysis

Stress condition, if experienced for an extended amount of time, can negatively affect individual's health. Several external sensors monitoring different physiological states correlated with stress, or smartphone apps that monitor individuals context, have been leveraged to assess stress state in everyday life. The less intrusive “human-smartphone interaction” have been under-investigated so far. In our research we leverage `swipe', `scroll' and `text input' interactions to assess the stress state of smartphone users. Based on data collected from 13 participants, we leverage `swipe' and `scroll' data to assess stress with an average F-measure of 79-85% for a within-subject model, and of 70-80% when building a global model. Moreover, `text input' via a virtual keyboard has been analyzed, showing how several easy to calculate features enable to differentiate between stress and no-stress state. To the best of our knowledge, this is the first attempt to leverage human-smartphone interaction, and in particular `swipe', `scroll' and `text input' interactions, to accurately assess stress state in individuals without using any external sensor or leveraging privacy-sensitive context information.
Global causes of maternal death: a WHO systematic analysis.

Data for the causes of maternal deaths are needed to inform policies to improve maternal health. We developed and analysed global, regional, and subregional estimates of the causes of maternal death during 2003-09, with a novel method, updating the previous WHO systematic review.



We searched specialised and general bibliographic databases for articles published between between Jan 1, 2003, and Dec 31, 2012, for research data, with no language restrictions, and the WHO mortality database for vital registration data. On the basis of prespecified inclusion criteria, we analysed causes of maternal death from datasets. We aggregated country level estimates to report estimates of causes of death by Millennium Development Goal regions and worldwide, for main and subcauses of death categories with a Bayesian hierarchical model.



We identified 23 eligible studies (published 2003-12). We included 417 datasets from 115 countries comprising 60 799 deaths in the analysis. About 73% (1 771 000 of 2 443 000) of all maternal deaths between 2003 and 2009 were due to direct obstetric causes and deaths due to indirect causes accounted for 27·5% (672 000, 95% UI 19·7-37·5) of all deaths. Haemorrhage accounted for 27·1% (661 000, 19·9-36·2), hypertensive disorders 14·0% (343 000, 11·1-17·4), and sepsis 10·7% (261 000, 5·9-18·6) of maternal deaths. The rest of deaths were due to abortion (7·9% [193 000], 4·7-13·2), embolism (3·2% [78 000], 1·8-5·5), and all other direct causes of death (9·6% [235 000], 6·5-14·3). Regional estimates varied substantially.



Between 2003 and 2009, haemorrhage, hypertensive disorders, and sepsis were responsible for more than half of maternal deaths worldwide. More than a quarter of deaths were attributable to indirect causes. These analyses should inform the prioritisation of health policies, programmes, and funding to reduce maternal deaths at regional and global levels. Further efforts are needed to improve the availability and quality of data related to maternal mortality.
Problem Set 3 General Instructions

You should submit your answers via GradeScope and your code via Snap submission site.  Prepare answers to your homework into a single PDF file and submit it via http://gradescope.com. Make sure that answer to each question is on a separate page. This means you should submit a 14-page PDF (1 page for the cover sheet, 4 pages for the answers to question 1, 3 pages for answers to question 2, and 6 pages for question 3). On top of each page write the number of the question you are answering. Please find the cover sheet and the recommended templates located here: Not including the cover sheet in your submission will result in a 2-point penalty. Put all the code for a single question into a single file and upload it.  We strongly encourage you to use Snap.py for Python. However, you can use any other graph analysis tool or package you want (SNAP for C++, NetworkX for Python, JUNG for Java, etc.). A question that occupied sociologists and economists as early as the 1900's is how do innovations (e.g. ideas, products, technologies, behaviors) diffuse (spread) within a society. One of the prominent researchers in the field is Professor Mark Granovetter who among other contributions introduced along with Thomas Schelling threshold models in sociology. In Granovetter's model, there is a population of individuals (mob) and for simplicity two behaviours (riot or not riot). • Threshold model: each individual i has a threshold t i that determines her behavior in the following way. If there are at least t i individuals that are rioting, then she will join the riot, otherwise she stays inactive. Here, it is implicitly assumed that each individual has full knowledge of the behavior of all other individuals in the group. Nodes with small threshold are called innovators (early adopters) and nodes with large threshold are called laggards (late adopters). Granovetter's threshold model has been successful in explain classical empirical adoption curves by relating them to thresholds in
Nacre from mollusk shells: a model for high-performance structural materials.

Nacre is the iridescent layer found inside a large number of mollusk shells. This natural composite has a very high mineral content, which makes it hard and stiff. However it is the toughness of nacre which is the most impressive: it is three orders of magnitude tougher than the mineral it is made of. No manmade composite material can boast such amplification in toughness, and for this reason nacre has become a biomimetic model material. The mineral in nacre comes in the form of microscopic polygonal tablets, which have the ability to 'slide' on one another in large numbers when the material is loaded in tension. This key mechanism makes nacre a quasi-ductile material, which in turn greatly increases its toughness and makes it damage tolerant. Numerous 'artificial nacres' were developed in the past but none of them can truly duplicate the remarkable mechanism of tablet sliding. In this work selected structural features of nacre were implemented in a PMMA-based composite, which for the first time could replicate the collective tablet sliding mechanism. This material demonstrates that the powerful toughening mechanism operating in natural nacre can be duplicated and harnessed in engineering materials.
Using Word Embeddings for Improving Statistical Machine Translation of Phrasal Verbs

We examine the employment of word embeddings for machine translation (MT) of phrasal verbs (PVs), a linguistic phenomenon with challenging semantics. Using word embeddings, we augment the translation model with two features: one modelling distributional semantic properties of the source and target phrase and another modelling the degree of compositionality of PVs. We also obtain paraphrases to increase the amount of relevant training data. Our method leads to improved translation quality for PVs in a case study with English to Bulgarian MT system.
Optimal Multi-Meeting-Point Route Search

Real-time ride-sharing applications (e.g., Uber and Lyft) are very popular in recent years. Motivated by the ride-sharing application, we propose a new type of query in road networks, called the optimal multi-meeting-point route (OMMPR) query. Given a road network G, a source nodes, a target node t, and a set of query nodes U, the OMMPR query aims at finding the best route starting from s and ending at t such that the weighted average cost between the cost of the route and the total cost of the shortest paths from every query node to the route is minimized. We show that the problem of computing the OMMPR query is NP-hard. To answer the OMMPR query efficiently, we propose two novel parameterized solutions based on dynamic programming (DP), with the number of query nodes l (i.e., l = |U|) as a parameter, which is typically very small in practice. The two proposed parameterized algorithms run in O(3l · m + 2l · n · (l + log (n))) and O(2l · (m + n · (l + log (n)))) time, respectively, where n and m denote the number of nodes and edges in graph G, thus they are tractable in practice. To reduce the search space of the DP-based algorithms, we propose two novel optimized algorithms based on bidirectional DP and a carefully-designed lower bounding technique. We conduct extensive experimental studies on four large real-world road networks, and the results demonstrate the efficiency of the proposed algorithms.
VizDSL: Towards a Graphical Visualisation Language for Enterprise Systems Interoperability

In response to the rise of Big Data, modern enterprise architecture has become significantly more complex. Model driven engineering (MDE) has been proposed as a methodology for developing software to deal with complex integration and interoperability. Domain specific languages (DSLs) play a crucial role in MDE and represent languages for a specific purpose that are highly abstract and easy to use. In this paper we propose a new language VizDSL for creating interactive visualisations that facilitate the understanding of complex data and information structures for enterprise systems interoperability. In comparison to existing visualisation languages VizDSL provides the benefits of visualising the semantics of data using a graphical notation. VizDSL is based on the Interaction Flow Modelling Language (IFML) and Agile Visualisation and has been implemented in a prototype. The prototype has been applied on an open data set and results show that interactive visualisation can be implemented quickly using the VizDSL language without writing code which makes it easier to design for non- programmers.