nils-herrmann/clean_scirepeval huggingface dataset:
Security Analysis on One-to-Many Order Preserving Encryption-Based Cloud Data Search

For ranked search in encrypted cloud data, order preserving encryption (OPE) is an efficient tool to encrypt relevance scores of the inverted index. When using deterministic OPE, the ciphertexts will reveal the distribution of relevance scores. Therefore, Wang et al. proposed a probabilistic OPE, called one-to-many OPE, for applications of searchable encryption, which can flatten the distribution of the plaintexts. In this paper, we proposed a differential attack on one-to-many OPE by exploiting the differences of the ordered ciphertexts. The experimental results show that the cloud server can get a good estimate of the distribution of relevance scores by a differential attack. Furthermore, when having some background information on the outsourced documents, the cloud server can accurately infer the encrypted keywords using the estimated distributions.
Explaining gender differences in jurors' reactions to child sexual assault cases.

In three experiments, we investigated the influence of juror, victim, and case factors on mock jurors' decisions in several types of child sexual assault cases (incest, day care, stranger abduction, and teacher-perpetrated abuse). We also validated and tested the ability of several scales measuring empathy for child victims, children's believability, and opposition to adult/child sex, to mediate the effect of jurors' gender on case judgments. Supporting a theoretical model derived from research on the perceived credibility of adult rape victims, women compared to men were more empathic toward child victims, more opposed to adult/child sex, more pro-women, and more inclined to believe children generally. In turn, women (versus men) made more pro-victim judgments in hypothetical abuse cases; that is, attitudes and empathy generally mediated this juror gender effect that is pervasive in this literature. The experiments also revealed that strength of case evidence is a powerful factor in determining judgments, and that teen victims (14 years old) are blamed more for sexual abuse than are younger children (5 years old), but that perceptions of 5 and 10 year olds are largely similar. Our last experiment illustrated that our findings of mediation generalize to a community member sample.
Characterizing and quantifying human movement patterns using GPS data loggers in an area approaching malaria elimination in rural southern Zambia

In areas approaching malaria elimination, human mobility patterns are important in determining the proportion of malaria cases that are imported or the result of low-level, endemic transmission. A convenience sample of participants enrolled in a longitudinal cohort study in the catchment area of Macha Hospital in Choma District, Southern Province, Zambia, was selected to carry a GPS data logger for one month from October 2013 to August 2014. Density maps and activity space plots were created to evaluate seasonal movement patterns. Time spent outside the household compound during anopheline biting times, and time spent in malaria high- and low-risk areas, were calculated. There was evidence of seasonal movement patterns, with increased long-distance movement during the dry season. A median of 10.6% (interquartile range (IQR): 5.8-23.8) of time was spent away from the household, which decreased during anopheline biting times to 5.6% (IQR: 1.7-14.9). The per cent of time spent in malaria high-risk areas for participants residing in high-risk areas ranged from 83.2% to 100%, but ranged from only 0.0% to 36.7% for participants residing in low-risk areas. Interventions targeted at the household may be more effective because of restricted movement during the rainy season, with limited movement between high- and low-risk areas.
Principles of genetic circuit design

Cells navigate environments, communicate and build complex patterns by initiating gene expression in response to specific signals. Engineers seek to harness this capability to program cells to perform tasks or create chemicals and materials that match the complexity seen in nature. This Review describes new tools that aid the construction of genetic circuits. Circuit dynamics can be influenced by the choice of regulators and changed with expression 'tuning knobs'. We collate the failure modes encountered when assembling circuits, quantify their impact on performance and review mitigation efforts. Finally, we discuss the constraints that arise from circuits having to operate within a living cell. Collectively, better tools, well-characterized parts and a comprehensive understanding of how to compose circuits are leading to a breakthrough in the ability to program living cells for advanced applications, from living therapeutics to the atomic manufacturing of functional materials.
Multicriteria decision aid in Classification problems

Classification problems refer to the assignment of some alt ern tives into predefined classes (groups, categories). Such problems often arise in several application fields. For instance, in assessing credit card applications the loan officer must evaluate the charact eristics of each applicant and decide whether an application should be accepted or rejected. Simil ar situations are very common in fields such as finance and economics, production management (fault diagnosis) , medicine, customer satisfaction measurement, data base management and retrieval, etc.
Comparative Analysis of Global Feature Extraction Methods for Off-line Signature Recognition

In this paper, a method is proposed for feature extraction of offline signature recognition system. The proposed method is based on global features to identify forgeries and also median filter is introduces for noise reduction. The Proposed feature extraction method is compared with Discrete Radon Transform (DRT). Both the feature extraction method extracts one dimensional global features and the alignment between features is performed by Dynamic Time Warping (DTW). When being trained using 6 genuine signatures of each person and 250 forgeries taken from our database, the proposed method obtained an equal error rate (EER) of 8. 40%. The false acceptance rate (FAR) for proposed method was also kept as low as 8. 80%.
OMWEdit - The Integrated Open Multilingual Wordnet Editing System

Wordnets play a central role in many natural language processing tasks. This paper introduces a multilingual editing system for the Open Multilingual Wordnet (OMW: Bond and Foster, 2013). Wordnet development, like most lexicographic tasks, is slow and expensive. Moving away from the original Princeton Wordnet (Fellbaum, 1998) development workflow, wordnet creation and expansion has increasingly been shifting towards an automated and/or interactive system facilitated task. In the particular case of human edition/expansion of wordnets, a few systems have been developed to aid the lexicographers’ work. Unfortunately, most of these tools have either restricted licenses, or have been designed with a particular language in mind. We present a webbased system that is capable of multilingual browsing and editing for any of the hundreds of languages made available by the OMW. All tools and guidelines are freely available under an open license.
A Low-Power Full-Band Low-Noise Amplifier for Ultra-Wideband Receivers

In this paper, a low-power full-band low-noise amplifier (FB-LNA) for ultra-wideband applications is presented. The proposed FB-LNA uses a stagger-tuning technique to extend the full bandwidth from 3.1 to 10.6 GHz. A current-reused architecture is employed to decrease the power consumption. By using an input common-gate stage, the input resistance of 50 Ω can be obtained without an extra input-matching network. The output matching is achieved by cascading an output common-drain stage. FB-LNA was implemented with a TSMC 0.18-μm CMOS process. On-wafer measurement shows an average power gain of 9.7 dB within the full operation band. The input reflection coefficient and the output reflection coefficient are both less than -10 dB over the entire band. The noise figure of the full band remained under 7 dB with a minimum value of 5.27 dB. The linearity of input third-order intercept point is -2.23 dBm. The power consumptions at 1.5-V supply voltage without an output buffer is 4.5 mW. The chip area occupies 1.17 × 0.88 mm2.
Query-based debugging

data structure queries (A). Some queries check properties of abstract data struct [11][131] such as stacks, hash tables, trees, and so on. These queries are not domain because the data structures can hold data of any domain. These queries are also differ the programming construct queries, because they check the constraints of well-defined a data structures. For example, a query about a binary tree may find the number of its nod have only one child. On the other hand, programming construct queries usually span di data structures. Abstract data structure queries can usually be expressed as class invar could be packaged with the class that implements an ADT. However, the queries that p information rather than detect violations are best answered by dynamic queries. For ex monitoring B+ trees using queries may indicate whether this data structure is efficient f underlying problem. Program construct queries (P). Program construct queries verify object relationships that related to the program implementation and not directly to the problem domain. Such q verify and visualize groups of objects that have to conform to some constraints because lower level of program design and implementation. For example, in a graphical user int implementation, every window object has a parent window, and this window referenc children widgets through the widget_collection collection (section 5.2.2). Such construct is n
Radio module for fast real-time control of inverse triple pendulum

The paper demonstrates use of wireless sensor as input data source for fast real-time automatic control. Fast, underactuated and highly unstable inverse triple pendulum system is controlled on the basis of values measured on the pendulum arms and wirelessly transmitted to the controller. The presented solution working in 2.4 GHz band and based on Atmel SAM R21 SoC on the sensor side and Atmel AT86RF233 transceiver on the controller side delivers data from 2 IRC sensors and 3-axis gyroscope with latency as low as 350 us.
The Effect of Information Communication Technology Interventions on Reducing Social Isolation in the Elderly: A Systematic Review.

The aging of the population is an inexorable change that challenges governments and societies in every developed country. Based on clinical and empirical data, social isolation is found to be prevalent among elderly people, and it has negative consequences on the elderly's psychological and physical health. Targeting social isolation has become a focus area for policy and practice. Evidence indicates that contemporary information and communication technologies (ICT) have the potential to prevent or reduce the social isolation of elderly people via various mechanisms.



This systematic review explored the effects of ICT interventions on reducing social isolation of the elderly.



Relevant electronic databases (PsycINFO, PubMed, MEDLINE, EBSCO, SSCI, Communication Studies: a SAGE Full-Text Collection, Communication & Mass Media Complete, Association for Computing Machinery (ACM) Digital Library, and IEEE Xplore) were systematically searched using a unified strategy to identify quantitative and qualitative studies on the effectiveness of ICT-mediated social isolation interventions for elderly people published in English between 2002 and 2015. Narrative synthesis was performed to interpret the results of the identified studies, and their quality was also appraised.



Twenty-five publications were included in the review. Four of them were evaluated as rigorous research. Most studies measured the effectiveness of ICT by measuring specific dimensions rather than social isolation in general. ICT use was consistently found to affect social support, social connectedness, and social isolation in general positively. The results for loneliness were inconclusive. Even though most were positive, some studies found a nonsignificant or negative impact. More importantly, the positive effect of ICT use on social connectedness and social support seemed to be short-term and did not last for more than six months after the intervention. The results for self-esteem and control over one's life were consistent but generally nonsignificant. ICT was found to alleviate the elderly's social isolation through four mechanisms: connecting to the outside world, gaining social support, engaging in activities of interests, and boosting self-confidence.



More well-designed studies that contain a minimum risk of research bias are needed to draw conclusions on the effectiveness of ICT interventions for elderly people in reducing their perceived social isolation as a multidimensional concept. The results of this review suggest that ICT could be an effective tool to tackle social isolation among the elderly. However, it is not suitable for every senior alike. Future research should identify who among elderly people can most benefit from ICT use in reducing social isolation. Research on other types of ICT (eg, mobile phone-based instant messaging apps) should be conducted to promote understanding and practice of ICT-based social-isolation interventions for elderly people.
Amlexanox Suppresses Osteoclastogenesis and Prevents Ovariectomy-Induced Bone Loss

The activity of protein kinases IKK-ε and TANK-binding kinase 1 (TBK1) has been shown to be associated with inflammatory diseases. As an inhibitor of IKK-ε and TBK1, amlexanox is an anti-inflammatory, anti-allergic, immunomodulator and used for treatment of ulcer, allergic rhinitis and asthma in clinic. We hypothesized that amlexanox may be used for treatment of osteoclast-related diseases which frequently associated with a low grade of systemic inflammation. In this study, we investigated the effects of amlexanox on RANKL-induced osteoclastogenesis in vitro and ovariectomy-mediated bone loss in vivo. In primary bone marrow derived macrophages (BMMs), amlexanox inhibited osteoclast formation and bone resorption. At the molecular level, amlexanox suppressed RANKL-induced activation of nuclear factor-κB (NF-κB), mitogen-activated protein kinase (MAPKs), c-Fos and NFATc1. Amlexanox decreased the expression of osteoclast-specific genes, including TRAP, MMP9, Cathepsin K and NFATc1. Moreover, amlexanox enhanced osteoblast differentiation of BMSCs. In ovariectomized (OVX) mouse model, amlexanox prevented OVX-induced bone loss by suppressing osteoclast activity. Taken together, our results demonstrate that amlexanox suppresses osteoclastogenesis and prevents OVX-induced bone loss. Therefore, amlexanox may be considered as a new therapeutic candidate for osteoclast-related diseases, such as osteoporosis and rheumatoid arthritis.
Climate change decreases aquatic ecosystem productivity of Lake Tanganyika, Africa

Although the effects of climate warming on the chemical and physical properties of lakes have been documented, biotic and ecosystem-scale responses to climate change have been only estimated or predicted by manipulations and models. Here we present evidence that climate warming is diminishing productivity in Lake Tanganyika, East Africa. This lake has historically supported a highly productive pelagic fishery that currently provides 25–40% of the animal protein supply for the populations of the surrounding countries. In parallel with regional warming patterns since the beginning of the twentieth century, a rise in surface-water temperature has increased the stability of the water column. A regional decrease in wind velocity has contributed to reduced mixing, decreasing deep-water nutrient upwelling and entrainment into surface waters. Carbon isotope records in sediment cores suggest that primary productivity may have decreased by about 20%, implying a roughly 30% decrease in fish yields. Our study provides evidence that the impact of regional effects of global climate change on aquatic ecosystem functions and services can be larger than that of local anthropogenic activity or overfishing.
Diagnosis and classification of rheumatoid arthritis.

Rheumatoid arthritis (RA) is a systemic chronic inflammatory disease of unclear etiology that is manifested in by a progressive and destructive polyarthritis in association with serological evidence of autoreactivity. Its diagnosis is based on the classification criteria that involve four parameters: joint involvement, serology (rheumatoid factor and anti-cyclic citrullinated peptide--anti-CCP), levels of acute phase reactants and the duration of the symptoms Aletaha, et al. . This classification simplifies the categorization of the patients with early RA; however, the diagnosis requires highly trained specialists who are able to differentiate early symptoms of RA from other pathologies.
Processing nested complex sequence pattern queries over event streams

Complex event processing (CEP) has become increasingly important for tracking and monitoring applications ranging from health care, supply chain management to surveillance. These monitoring applications submit complex event queries to track sequences of events that match a given pattern. As these systems mature the need for increasingly complex nested sequence queries arises, while the state-of-the-art CEP systems mostly focus on the execution of flat sequence queries only. In this paper, we now introduce an iterative execution strategy for nested CEP queries composed of sequence, negation, AND and OR operators. Lastly we have introduced the promising direction of applying selective caching of intermediate results to optimize the execution. Our experimental study using real-world stock trades evaluates the performance of our proposed iterative execution strategy for different query types.
Applications of psychological science for actionable analytics

According to psychological scientists, humans understand models that most match their own internal models, which they characterize as lists of "heuristic"s (i.e. lists of very succinct rules). One such heuristic rule generator is the Fast-and-Frugal Trees (FFT) preferred by psychological scientists. Despite their successful use in many applied domains, FFTs have not been applied in software analytics. Accordingly, this paper assesses FFTs for software analytics. 
 We find that FFTs are remarkably effective in that their models are very succinct (5 lines or less describing a binary decision tree) while also outperforming result from very recent, top-level, conference papers. Also, when we restrict training data to operational attributes (i.e., those attributes that are frequently changed by developers), the performance of FFTs are not effected (while the performance of other learners can vary wildly). 
 Our conclusions are two-fold. Firstly, there is much that software analytics community could learn from psychological science. Secondly, proponents of complex methods should always baseline those methods against simpler alternatives. For example, FFTs could be used as a standard baseline learner against which other software analytics tools are compared.
Alloy: Clustering with Crowds and Computation

Crowdsourced clustering approaches present a promising way to harness deep semantic knowledge for clustering complex information. However, existing approaches have difficulties supporting the global context needed for workers to generate meaningful categories, and are costly because all items require human judgments. We introduce Alloy, a hybrid approach that combines the richness of human judgments with the power of machine algorithms. Alloy supports greater global context through a new "sample and search" crowd pattern which changes the crowd's task from classifying a fixed subset of items to actively sampling and querying the entire dataset. It also improves efficiency through a two phase process in which crowds provide examples to help a machine cluster the head of the distribution, then classify low-confidence examples in the tail. To accomplish this, Alloy introduces a modular "cast and gather" approach which leverages a machine learning backbone to stitch together different types of judgment tasks.
A 1.66 mV FOM Output Cap-Less LDO With Current-Reused Dynamic Biasing and 20 ns Settling Time

A fully integrated output capacitor-less, nMOS regulation FET low-dropout (LDO) regulator with fast transient response for system-on-chip power regulation applications is presented. The error amplifier (EA) consists of a differential cross-coupled common-gate (CG) input stage achieving twice the transconductance and unity-gain-bandwidth in comparison to a conventional differential common-source stage. The low input resistance of the CG EA improves stability of the LDO over a wide range of load currents. The LDO employs a current-reused dynamic biasing technique to further improve the load transient response, with no extra quiescent current. It is designed and fabricated in a 0.18-<inline-formula> <tex-math notation="LaTeX">${\mu }\text{m}$ </tex-math></inline-formula> CMOS technology for an input voltage range of 1.6–1.8 V, and an output voltage range of 1.4–1.6 V. Measured undershoot is 158 mV and settling time is 20 ns for 9–40 mA load change in 250 ps edge-time with zero load capacitance. The LDO core consumes 130 <inline-formula> <tex-math notation="LaTeX">${\mu }\text{A}$ </tex-math></inline-formula> of quiescent current, occupies 0.21 mm<sup>2</sup> die area, and sustains 0–50 pF of on-chip load capacitance.
Discrete cuckoo search for traveling salesman problem

Cuckoo search (CS) belongs to a class of novel nature-inspired algorithm inspired by the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds (of other species). CS has been successfully applied to solve continuous optimization problems, however, its potential in discrete problems has not been sufficiently explored. Basing on the present algorithm of CS, this paper construct an discrete cuckoo search (DCS) to solve traveling salesman problem (TSP). Two schemes are studied, i.e. discrete step size and the cuckoo's updating scheme. DCS is evaluated on the TSP problem, comparing performance to other methods. Experimental results shows that the proposed algorithm performs very well to solve some simple TSP instances, but it can be trapped into local optimum solutions for some other instances.
Hierarchical Bayesian Inverse Reinforcement Learning

Inverse reinforcement learning (IRL) is the problem of inferring the underlying reward function from the expert's behavior data. The difficulty in IRL mainly arises in choosing the best reward function since there are typically an infinite number of reward functions that yield the given behavior data as optimal. Another difficulty comes from the noisy behavior data due to sub-optimal experts. We propose a hierarchical Bayesian framework, which subsumes most of the previous IRL algorithms as well as models the sub-optimality of the expert's behavior. Using a number of experiments on a synthetic problem, we demonstrate the effectiveness of our approach including the robustness of our hierarchical Bayesian framework to the sub-optimal expert behavior data. Using a real dataset from taxi GPS traces, we additionally show that our approach predicts the driving behavior with a high accuracy.