nils-herrmann/clean_scirepeval huggingface dataset:
Journaling Interfaces to Support Knowledge Workers in Their Collaborative Tasks and Goals

Assisting teams of knowledge workers achieve common strategic and tactical goals is becoming an increasing priority as information analysis tasks become more complex. Tools to monitor and support individual workers, such as TaskTracer, demonstrated the potential for assisting individuals but there is a lack of tools for analyzing workflows and information needs at a collaborative level within enterprises. Providing assistance for collaboration is a current priority for the new generation of ‘smart digital assistants’ and presents unique challenges, in terms of associating collective goals with user activities in way that minimizes disruption to the user's workflow, and in generating useful summaries. To address these challenges, we have developed ‘Journaling’ interfaces to: capture a user or team's tasks and goals, associate them with information artifacts, assist in information recall, and display aggregate visualizations. These interfaces are supported by a passive instrumentation platform that aims to monitor user's consented activities in a minimally intrusive manner, including interactions with various applications, documents and URLs as part of collaborative workflows. We have deployed these interfaces in a production environment using heterogeneous workflows performed by groups of students and intelligence analysts. Evaluations based on user interviews and engagement metrics suggest that our approach is useful for understanding and supporting user collaboration, as well as being easy to work with and suitable for continuous use. In addition, the data gathered provides situational awareness for individuals, teams, educators and managers. Through our platform, we are enabling continuous collection of labelled user activity logs and document corpora that are enabling further research in this nascent field.
3D Reconstruction Based on Pseudo-Linearization and Errors-in-Variables Model

This paper proposes a general approach of 3D reconstruction, a major problem arising in computer vision and virtual reality, based on a combination of Pseudo-Linearization and Errors-in-Variables model. The proposed approach concerns a bunch of corrupted measurements under nonlinear constraints, and optimizes the estimation by taking errors into account. Furthermore, we set a synthetic projective model and adopt a standard deviation-expectation criterion to evaluate the performance or our method applied in 3D reconstruction. Also, some test images are picked from an image database to give this method a chance to demonstrate its performance in our experiments. Finally, as a successful application, this method is used in a calibration-free augmented reality system.
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

Point cloud is an important type of geometric data structure. Due to its irregular format, most researchers transform such data to regular 3D voxel grids or collections of images. This, however, renders data unnecessarily voluminous and causes issues. In this paper, we design a novel type of neural network that directly consumes point clouds, which well respects the permutation invariance of points in the input. Our network, named PointNet, provides a unified architecture for applications ranging from object classification, part segmentation, to scene semantic parsing. Though simple, PointNet is highly efficient and effective. Empirically, it shows strong performance on par or even better than state of the art. Theoretically, we provide analysis towards understanding of what the network has learnt and why the network is robust with respect to input perturbation and corruption.
Types of Hair Dye and Their Mechanisms of Action

Hair color change by dye application is a common procedure among women. Hair dyes are classified, according to color resistance, into temporary, semipermanent, demipermanent and permanent. The first two are based on molecules which are already colored. Temporary dyes act through dye deposition on cuticles, but semipermanent may penetrate a little into the cortex and so the color resists up to six washes. Demipermanent and permanent dyes are based on color precursors, called oxidation dyes, and the final shade is developed by their interactions with an oxidizing agent, but they differ from the alkalizing agent used. In oxidation systems, there is an intense diffusion of the molecules into the cortex, what promotes a longer color resistance. Dyes and color precursors present differences related to chromophore groups, hair fiber affinity, water solubility, and photo stability. The aim of this review is to discuss the differences among hair dye products available in the market and their action mechanisms, molecular structures, application methods, and some aspects of formulations.
Using Random Forests in conintegrated pairs trading

In this thesis we will use Random Forests to define a trading strategy. Using this powerful machine learning technique, we will try to predict the daily price changes of financial products that move similarly over the long term, so-called cointegrated pairs. We propose a way to adjust our portfolio based on these prediction, while limiting our risk. Firstly, we test our strategy on data generated from a model that mimics these kinds of financial products. After promising results, we test our strategy on the Dutch AEX index and the German DAX index. From our backtests we see that our strategy outperforms both indices in terms of Sharpe ratio. Using a backtesting period of 10 year up to mid 2017 we find an annualized Sharpe ratio of about 0.7, before transaction costs and ignoring the riskfree return rate.
Discourse analysis.

Discourse analysis is the study of language in use. It rests on the basic premise that language cannot be understood without reference to the context, both linguistic and extra-linguistic, in which it is used. It draws from the findings and methodologies of a wide range of fields, such as anthropology, philosophy, sociology, social and cognitive psychology, and artificial intelligence. It is itself a broad field comprised of a large number of linguistic subfields and approaches, including speech act theory, conversation analysis, pragmatics, and the ethnography of speaking. At the same time, the lines between certain linguistic subfields, in particular psycholinguistics, anthropological linguistics, and cognitive linguistics and discourse analysis overlap, and approaches to the study of discourse are informed by these subfields, and in many cases findings are independently corroborated. As a very interdisciplinary approach, the boundaries of this field are fuzzy. 1 The fundamental assumption underlying all approaches to discourse analysis is that language must be studied as it is used, in its context of production, and so the object of analysis is very rarely in the form of a sentence. Instead, written or spoken texts, usually larger than one sentence or one utterance, provide the data. In other words, the discourse analyst works with naturally occurring corpora, and with such corpora come a wide variety of features such as hesitations, non-standard forms, self-corrections, repetitions, incomplete clauses, words, and so—all linguistic material which would be relegated to performance by Chomsky (1965) and so stand outside the scope of analysis for many formal linguists. But for the discourse analyst, such " performance " data are 1 It is interesting, in this light, to compare the contents of several standard handbooks of discourse analysis. Brown and Yule (1986) focus heavily on pragmatics and information structure, while Schiffrin (1994) includes several chapters directly related to sociolinguistic methodologies (i.e. chapters on interactional sociolinguistics, ethnomethodology and variation analysis). Mey (1993) has three chapters on conversation analysis (a topic which Schiffrin also covers) and a chapter on " societal pragmatics. " Lenore Grenoble, Discourse Analysis 2 indeed relevant and may in fact be the focus of research. The focus on actual instances of language use also means that the analysis does not look at language only as an abstract system; this is a fundamental difference between formal work on syntax versus discourse analysis. This paper first provides an overview of discourse analysis and …
A novel compact wide-band planar antenna for mobile handsets

A novel printed compact wide-band planar antenna for mobile handsets is proposed and analyzed in this paper. The radiating patch of the proposed antenna is designed jointly with the shape of the ground plane. A prototype of the proposed antenna with 30 mm in height and 50 mm in width has been fabricated and tested. Its operating bandwidth with voltage standing wave ratio (VSWR) lower than 3:1 is 870-2450 MHz, which covers the global system for mobile communication (GSM, 890-960 MHz), the global positioning system (GPS, 1575.42 MHz), digital communication system (DCS, 1710-1880 MHz), personal communication system (PCS, 1850-1990 MHz), universal mobile telecommunication system (UMTS, 1920-2170 MHz), and wireless local area network (WLAN, 2400-2484 MHz) bands. Therefore, it could be applicable for the existing and future mobile communication systems. Design details and experimental results are also presented and discussed.
A Content-Addressable DNA Database with Learned Sequence Encodings

We present strand and codeword design schemes for a DNA database capable of approximate similarity search over a multidimensional dataset of content-rich media. Our strand designs address crosstalk in associative DNA databases, and we demonstrate a novel method for learning DNA sequence encodings from data, applying it to a dataset of tens of thousands of images. We test our design in the wetlab using one hundred target images and ten query images, and show that our database is capable of performing similarity-based enrichment: on average, visually similar images account for 30% of the sequencing reads for each query, despite making up only 10% of the database.
Large-scale production of foot-and-mouth disease virus (serotype Asia1) VLP vaccine in Escherichia coli and protection potency evaluation in cattle

Foot-and-mouth disease (FMD) is an acute, highly contagious disease that infects cloven-hoofed animals. Vaccination is an effective means of preventing and controlling FMD. Compared to conventional inactivated FMDV vaccines, the format of FMDV virus-like particles (VLPs) as a non-replicating particulate vaccine candidate is a promising alternative.



In this study, we have developed a co-expression system in E. coli, which drove the expression of FMDV capsid proteins (VP0, VP1, and VP3) in tandem by a single plasmid. The co-expressed FMDV capsid proteins (VP0, VP1, and VP3) were produced in large scale by fermentation at 10 L scale and the chromatographic purified capsid proteins were auto-assembled as VLPs in vitro. Cattle vaccinated with a single dose of the subunit vaccine, comprising in vitro assembled FMDV VLP and adjuvant, developed FMDV-specific antibody response (ELISA antibodies and neutralizing antibodies) with the persistent period of 6 months. Moreover, cattle vaccinated with the subunit vaccine showed the high protection potency with the 50 % bovine protective dose (PD50) reaching 11.75 PD50 per dose.



Our data strongly suggest that in vitro assembled recombinant FMDV VLPs produced from E. coli could function as a potent FMDV vaccine candidate against FMDV Asia1 infection. Furthermore, the robust protein expression and purification approaches described here could lead to the development of industrial level large-scale production of E. coli-based VLPs against FMDV infections with different serotypes.
A singular-value-based semi-fragile watermarking scheme for image content authentication with tamper localization

This paper presents a singular-value-based semi-fragile watermarking scheme for image content authentication. The proposed scheme generates secure watermark by performing a logical operation on content-dependent watermark generated by a singular-value-based sequence and contentindependent watermark generated by a private-key-based sequence. It next employs the adaptive quantization method to embed secure watermark in approximation subband of each 4 4 block to generate the watermarked image. The watermark extraction process then extracts watermark using the parity of quantization results from the probe image. The authentication process starts with regenerating secure watermark following the same process. It then constructs error maps to compute five authentication measures and performs a three-level process to authenticate image content and localize tampered areas. Extensive experimental results show that the proposed scheme outperforms five peer schemes and its two variant systems and is capable of identifying intentional tampering, incidental modification, and localizing tampered regions under mild to severe content-preserving modifications.
A 0.66erms− Temporal-Readout-Noise 3-D-Stacked CMOS Image Sensor With Conditional Correlated Multiple Sampling Technique

This paper presents a sub-electron temporal readout noise, 8.3 Mpixel and 1.1-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> pixel pitch 3-D-stacked CMOS image sensor (CIS). A conditional correlated multiple sampling (CMS) technique is introduced to selectively reduce the dark pixel noise by using a full-range ramp and a small-range ramp. In this way, a sub-electron temporal readout noise CIS is achieved without degrading the frame rate dramatically, compared to the conventional CMS method. A column-parallel single slope ADC with dark pixel detection function is proposed as well. A dynamic-dark-signal-region detection technique is used to mitigate differential nonlinearity (DNL) errors due to ramp slope mismatch. The implemented prototype in 45-nm CIS/65-nm CMOS occupies an area of 35.89 mm<sup>2</sup>. This paper achieves a 0.66e<sub>rms</sub><sup>−</sup> with 5-time sampling at a frame rate of 7.2 frames/s, which corresponds to a sample-rate frequency of 36.1 kHz for the column ADC. The DNL (11 b) is improved from +0.98 LSB/−0.94 LSB to +0.29 LSB/−0.39 LSB by using dynamic dark-signal region technique. The figure of merit of this paper is 2.02 nV<sub>rms</sub>/Hz.
The Effects of Diversity in Global, Distributed Collectives: A Study of Open Source Project Success

Diversity is a defining characteristic of global collectives facilitated by the Internet. Though substantial evidence suggests that diversity has profound implications for a variety of outcomes including performance, member engagement, and withdrawal behavior, the effects of diversity have been predominantly investigated in the context of organizational workgroups or virtual teams. We use a diversity lens to study the success of non-traditional virtual work groups exemplified by open source software (OSS) projects. Building on the diversity literature, we propose that three types of diversity (separation, variety and disparity) influence two critical outcomes for OSS projects: community engagement and market success. We draw on the OSS literature to further suggest that the effects of diversity on market success are moderated by the application development stage. We instantiate the operational definitions of three forms of diversity to the unique context of open source projects. Using archival data from 357 projects hosted on SourceForge, we find that disparity diversity, reflecting variation in participants' contribution-based reputation, is positively associated with success. The impact of separation diversity, conceptualized as culture and measured as diversity in the spoken language and country of participants, has a negative impact on community engagement but an unexpected positive effect on market success. Variety diversity, reflected in dispersion in project participant roles, positively influences community engagement and market success. The impact of diversity on market success is conditional on the development stage of the project. We discuss how the study's findings advance the literature on antecedents of OSS success, expand our theoretical understanding of diversity, and present the practical implications of the results for managers of distributed collectives.
Event-sampled adaptive neural network control of robot manipulators

Event based sampling of feedback signals and control inputs are shown to reduce computations. In this paper, the design of event-sampled adaptive neural network (NN) state feedback control of robot manipulators is presented in the presence of uncertain robot dynamics. The event-sampled NN approximation property is utilized to represent the uncertain nonlinear dynamics of the robotic manipulator which is subsequently employed to generate the control torque. A novel weight tuning rule is designed using the Lyapunov method. Further, the Lyapunov stability theory is utilized to develop the event-sampling condition and to demonstrate the tracking performance of the robot manipulator. Finally, simulation results are presented to verify the theoretical claims and to demonstrate the reduction in the computations with event-sampled control execution.
Association between functional connectivity hubs and brain networks.

Functional networks are usually accessed with "resting-state" functional magnetic resonance imaging using preselected "seeds" regions. Frequently, however, the selection of the seed locations is arbitrary. Recently, we proposed local functional connectivity density mapping (FCDM), an ultrafast data-driven to locate highly connected brain regions (functional hubs). Here, we used the functional hubs obtained from local FCDM to determine the functional networks of the resting state in 979 healthy subjects without a priori hypotheses on seed locations. In addition, we computed the global functional connectivity hubs. Seven networks covering 80% of the gray matter volume were identified. Four major cortical hubs (ventral precuneus/posterior cingulate, inferior parietal cortex, cuneus, and postcentral gyrus) were linked to 4 cortical networks (default mode, dorsal attention, visual, and somatosensory). Three subcortical networks were associated to the major subcortical hubs (cerebellum, thalamus, and amygdala). The networks differed in their resting activity and topology. The higher coupling and overlap of subcortical networks was associated to higher contribution of short-range functional connectivity in thalamus and cerebellum. Whereas cortical local FCD hubs were also hubs of long-range connectivity, which corroborates the key role of cortical hubs in network architecture, subcortical hubs had minimal long-range connectivity. The significant variability among functional networks may underlie their sensitivity/resilience to neuropathology.
Functional neuroimaging of autobiographical memory

Functional neuroimaging studies of autobiographical memory have grown dramatically in recent years. These studies are important because they can investigate the neural correlates of processes that are difficult to study using laboratory stimuli, including: (i) complex constructive processes, (ii) recollective qualities of emotion and vividness, and (iii) remote memory retrieval. Constructing autobiographical memories involves search, monitoring and self-referential processes that are associated with activity in separable prefrontal regions. The contributions of emotion and vividness have been linked to the amygdala and visual cortex respectively. Finally, there is evidence that recent and remote autobiographical memories might activate the hippocampus equally, which has implications for memory-consolidation theories. The rapid development of innovative methods for eliciting personal memories in the scanner provides the opportunity to delve into the functional neuroanatomy of our personal past.
Heavy metal poisoning and its laboratory investigation.

The term `heavy metal' is, in this context, imprecise. It should probably be reserved for those elements with an atomic mass of 200 or greater [e.g., mercury (200), thallium (204), lead (207), bismuth (209) and the thorium series]. In practice, the term has come to embrace any metal, exposure to which is clinically undesirable and which constitutes a potential hazard. Our intention in this review is to provide an overview of some general concepts of metal toxicology and to discuss in detail metals of particular importance, namely, cadmium, lead, mercury, thallium, bismuth, arsenic, antimony and tin. Poisoning from individual metals is rare in the UK, even when there is a known risk of exposure. Table 1 shows that during 1991±92 only 1 ́1% of male lead workers in the UK and 5 ́5% of female workers exceeded the legal limits for blood lead concentration. Collectively, however, poisoning with metals forms an important aspect of toxicology because of their widespread use and availability. Furthermore, hitherto unrecognized hazards and accidents continue to be described. The investigation of metal poisoning forms a distinct specialist area, since most metals are usually measured using atomic absorption techniques. Analyses require considerable expertise and meticulous attention to detail to ensure valid results. Different analytical performance standards may be required of assays used for environmental and occupational monitoring, or for solely toxicological purposes. Because of the high capital cost of good quality instruments, the relatively small numbers of tests required and the variety of metals, it is more cost-effective if such testing is carried out in regional, national or other centres having the necessary experience. Nevertheless, patients are frequently cared for locally, and clinical biochemists play a crucial role in maintaining a high index of suspicion and liaising with clinical colleagues to ensure the provision of correct samples for analysis and timely advice.
Community-level influences on women's experience of intimate partner violence and terminated pregnancy in Nigeria: a multilevel analysis

Intimate partner violence (IPV) is a major public health problem with serious consequences for women's physical, mental, sexual and reproductive health. Reproductive health outcomes such as unwanted and terminated pregnancies, fetal loss or child loss during infancy, non-use of family planning methods, and high fertility are increasingly recognized. However, little is known about the role of community influences on women's experience of IPV and its effect on terminated pregnancy, given the increased awareness of IPV being a product of social context. This study sought to examine the role of community-level norms and characteristics in the association between IPV and terminated pregnancy in Nigeria.



Multilevel logistic regression analyses were performed on nationally-representative cross-sectional data including 19,226 women aged 15-49 years in Nigeria. Data were collected by a stratified two-stage sampling technique, with 888 primary sampling units (PSUs) selected in the first sampling stage, and 7,864 households selected through probability sampling in the second sampling stage.



Women who had experienced physical IPV, sexual IPV, and any IPV were more likely to have terminated a pregnancy compared to women who had not experienced these IPV types.IPV types were significantly associated with factors reflecting relationship control, relationship inequalities, and socio-demographic characteristics. Characteristics of the women aggregated at the community level (mean education, justifying wife beating, mean age at first marriage, and contraceptive use) were significantly associated with IPV types and terminated pregnancy.



Findings indicate the role of community influence in the association between IPV-exposure and terminated pregnancy, and stress the need for screening women seeking abortions for a history of abuse.