nils-herrmann/clean_scirepeval huggingface dataset:
A Life-Course View of the Development of Crime

In this article, the authors present a life-course perspective on crime and a critique of the developmental criminology paradigm. Their fundamental argument is that persistent offending and desistance—or trajectories of crime—can be meaningfully understood within the same theoretical framework, namely, a revised agegraded theory of informal social control. The authors examine three major issues. First, they analyze data that undermine the idea that developmentally distinct groups of offenders can be explained by unique causal processes. Second, they revisit the concept of turning points from a time-varying view of key life events. Third, they stress the overlooked importance of human agency in the development of crime. The authors’ life-course theory envisions development as the constant interaction between individuals and their environment, coupled with random developmental noise and a purposeful human agency that they distinguish from rational choice. Contrary to influential developmental theories in criminology, the authors thus conceptualize crime as an emergent process reducible neither to the individual nor the environment.
Circuit camouflage integration for hardware IP protection

Circuit camouflage technologies can be integrated into standard logic cell developments using traditional CAD tools. Camouflaged logic cells are integrated into a typical design flow using standard front end and back end models. Camouflaged logic cells obfuscate a circuit's function by introducing subtle cell design changes at the GDS level. The logic function of a camouflaged logic cell is extremely difficult to determine through silicon imaging analysis preventing netlist extraction, clones and counterfeits. The application of circuit camouflage as part of a customer's design flow can protect hardware IP from reverse engineering. Camouflage fill techniques further inhibit Trojan circuit insertion by completely filling the design with realistic circuitry that does not affect the primary design function. All unused silicon appears to be functional circuitry, so an attacker cannot find space to insert a Trojan circuit. The integration of circuit camouflage techniques is compatible with standard chip design flows and EDA tools, and ICs using such techniques have been successfully employed in high-attack commercial and government segments. Protected under issued and pending patents.
BlendCAC: A Smart Contract Enabled Decentralized Capability-Based Access Control Mechanism for the IoT

While the Internet of Things (IoT) technology has been widely recognized as the essential part of Smart Cities, it also brings new challenges in terms of privacy and security. Access control (AC) is among the top security concerns, which is critical in resource and information protection over IoT devices. Traditional access control approaches, like Access Control Lists (ACL), Role-based Access Control (RBAC) and Attribute-based Access Control (ABAC), are not able to provide a scalable, manageable and efficient mechanism to meet the requirements of IoT systems. Another weakness in today’s AC is the centralized authorization server, which can be the performance bottleneck or the single point of failure. Inspired by the smart contract on top of a blockchain protocol, this paper proposes BlendCAC, which is a decentralized, federated capability-based AC mechanism to enable an effective protection for devices, services and information in large scale IoT systems. A federated capability-based delegation model (FCDM) is introduced to support hierarchical and multi-hop delegation. The mechanism for delegate authorization and revocation is explored. A robust identity-based capability token management strategy is proposed, which takes advantage of the smart contract for registering, propagating and revocating of the access authorization. A proof-of-concept prototype has been implemented on both resources-constrained devices (i.e., Raspberry PI node) and more powerful computing devices (i.e., laptops), and tested on a local private blockchain network. The experimental results demonstrate the feasibility of the BlendCAC to offer a decentralized, scalable, lightweight and fine-grained AC solution for IoT systems.
Exploiting FrameNet for Content-Based Book Recommendation

Adding semantic knowledge to a content-based recommender helps to better understand the items and user representations. Most recent research has focused on examining the added value of adding semantic features based on structured web data, in particular Linked Open Data (LOD). In this paper, we focus in contrast on semantic feature construction from text, by incorporating features based on semantic frames into a book recommendation classifier. To this purpose we leverage the semantic frames based on parsing the plots of the items under consideration with a state-of-theart semantic parser. By investigating this type of semantic information, we show that these frames are also able to represent information about a particular book, but without the need of having explicitly structured data describing the books available. We reveal that exploiting frame information outperforms a basic bag-of-words approach and that especially the words relating to those frames are beneficial for classification. In a final step we compare and combine our system with the LOD features from a system leveraging DBpedia as knowledge resource. We show that both approaches yield similar results and reveal that combining semantic information from these two di↵erent sources might even be beneficial.
Improved streamflow forecasting using self-organizing radial basis function artificial neural networks

Streamflow forecasting has always been a challenging task for water resources engineers and managers and a major component of water resources system control. In this study, we explore the applicability of a Self Organizing Radial Basis (SORB) function to one-step ahead forecasting of daily streamflow. SORB uses a Gaussian Radial Basis Function architecture in conjunction with the Self-Organizing Feature Map (SOFM) used in data classification. SORB outperforms the two other ANN algorithms, the well known Multi-layer Feedforward Network (MFN) and Self-Organizing Linear Output map (SOLO) neural network for simulation of daily streamflow in the semi-arid Salt River basin. The applicability of the linear regression model was also investigated and concluded that the regression model is not reliable for this study. To generalize the model and derive a robust parameter set, cross-validation is applied and its outcome is compared with the split sample test. Crossvalidation justifies the validity of the nonlinear relationship set up between input and output data.
A single-chip encrypted wireless 12-lead ECG smart shirt for continuous health monitoring

An electrocardiography SoC is integrated into a form-fitting textile along with flexible electrodes, battery and antenna. Clinically standard 12-lead ECG is recorded from this “smart shirt.” The data is encrypted and wirelessly transmitted via an on-chip ISM band radio and flexible antenna allowing secure, continuous cardiac monitoring on a smartphone while dissipating less than 1mW.
Tri-Rank: An Authority Ranking Framework in Heterogeneous Academic Networks by Mutual Reinforce

Recently, authority ranking has received increasing interests in both academia and industry, and it is applicable to many problems such as discovering influential nodes and building recommendation systems. Various graph-based ranking approaches like PageRank have been used to rank authors and papers separately in homogeneous networks. In this paper, we take venue information into consideration and propose a novel graph-based ranking framework, Tri-Rank, to co-rank authors, papers and venues simultaneously in heterogeneous networks. This approach is a flexible framework and it ranks authors, papers and venues iteratively in a mutually reinforcing way to achieve a more synthetic, fair ranking result. We conduct extensive experiments using the data collected from ACM Digital Library. The experimental results show that Tri-Rank is more effective and efficient than the state-of-the-art baselines including PageRank, HITS and Co-Rank in ranking authors. The papers and venues ranked by Tri-Rank also demonstrate that Tri-Rank is rational.
The potentiality of computer-assisted instruction towards ameliorating Iranian EFL learners' reading level

The fundamental objective behind the present study is to demonstrate the visible effect of ComputerAssisted Instruction upon Iranian EFL learners' reading performance, and to see if it has any impact upon this skill in the Iranian EFLeducational settings. To this end, a sample of 50 male and female EFL learners was drawn from an English language institute in Iran. After participating in a proficiency pretest, these participants were assigned into two experimental and control groups, 25 and 25, respectively. An independent sample t-test was administered to find out if there were salient differences between the findings of the two selected groups in their reading test. The key research question was to see providing learners with computer-assisted instruction during the processes of learning and instruction for learners would have an affirmative influence upon the improvement and development of their reading skill. The results pinpointed computer-assisted instruction users' performance was meaningfully higher than that of nonusers (DF 1⁄4 48, P < 05). The consequences revealed that computer-assisted language learning and computer technology application have resulted in a greater promotion of students' reading improvement. In other words, computer-assisted instruction users outperformed the nonusers. The research, therefore, highlights the conclusion that EFL learners' use of computer-assisted instruction has the potential to promote more effective reading ability.
Contextualized and Localized Teaching as a Technique in Teaching Basic Statistics

Problems on students’ diversity with diverse needs still persist nowadays. To address this problem, the teacher need to be conscious on their socio-cultural background so as to benefits everyone in the classroom. This study determined the effect of teaching statistics using contextualized and localized (indigenized) information on the performance of students. The study was carried out using pretestposttest control group single blind experimental research design. Two intact classes were used and this was done by random assignment. There are thirty four students exposed to contextualized and localized teaching (experimental) and thirty students exposed to contextualize but not localized teaching (control). Ttest for independent samples and ANCOVA was utilized in comparing the pretest and posttest performances of the two groups. Concerning on the result, it was found out that the performance of the experimental group was significantly different to the performance of the control group on the empirical probability, but they were not significantly different on the theoretical probability. The finding indicates that the use of indigenous data in teaching statistics along empirical probability is an effective teaching and learning strategy. Additionally, the study recommends developing an authentic, contextualized and localized instructional material in statistics subject to improve the performance of the students.
Community Discovery in Dynamic Networks: A Survey

Several research studies have shown that complex networks modeling real-world phenomena are characterized by striking properties: (i) they are organized according to community structure, and (ii) their structure evolves with time. Many researchers have worked on methods that can efficiently unveil substructures in complex networks, giving birth to the field of community discovery. A novel and fascinating problem started capturing researcher interest recently: the identification of evolving communities. Dynamic networks can be used to model the evolution of a system: nodes and edges are mutable, and their presence, or absence, deeply impacts the community structure that composes them.
 This survey aims to present the distinctive features and challenges of dynamic community discovery and propose a classification of published approaches. As a “user manual,” this work organizes state-of-the-art methodologies into a taxonomy, based on their rationale, and their specific instantiation. Given a definition of network dynamics, desired community characteristics, and analytical needs, this survey will support researchers to identify the set of approaches that best fit their needs. The proposed classification could also help researchers choose in which direction to orient their future research.
Comparison of two battery equivalent circuit models for state of charge estimation in electric vehicles

This study compares two battery equivalent circuits for state of charge (SOC) estimation in electric vehicles (EVs), namely the RC circuit and Thevenin circuit. The state space representations of each circuit are used to develop the adaptive gain sliding mode observers (AGSMO) for the SOC estimations, which are compared with the true SOC. The results show that the Thevenin circuit provides more accurate SOC estimation than the RC circuit. A lithium-ion battery is chosen for experimental verification under constant current discharge and variable current discharge based on EV driving cycles.
Peeking Beneath the Hood of Uber

Recently, Uber has emerged as a leader in the "sharing economy". Uber is a "ride sharing" service that matches willing drivers with customers looking for rides. However, unlike other open marketplaces (e.g., AirBnB), Uber is a black-box: they do not provide data about supply or demand, and prices are set dynamically by an opaque "surge pricing" algorithm. The lack of transparency has led to concerns about whether Uber artificially manipulate prices, and whether dynamic prices are fair to customers and drivers. In order to understand the impact of surge pricing on passengers and drivers, we present the first in-depth investigation of Uber. We gathered four weeks of data from Uber by emulating 43 copies of the Uber smartphone app and distributing them throughout downtown San Francisco (SF) and midtown Manhattan. Using our dataset, we are able to characterize the dynamics of Uber in SF and Manhattan, as well as identify key implementation details of Uber's surge price algorithm. Our observations about Uber's surge price algorithm raise important questions about the fairness and transparency of this system.
Clinical characteristics of children presenting with a suspicion or allegation of historic sexual abuse.

Police-recorded sexual offences against children and young people (CYP) increased 85% in the UK between 2010/2011 and 2014/2015. Many children delay disclosure, but little data are available regarding characteristics of CYP presenting with historic child sexual abuse (CSA).



To identify the clinical and CSA-related characteristics of CYP presenting with a suspicion or allegation of historic CSA.



Data were collected on all CYP<17 years presenting with suspected or alleged historic CSA (ie, >3 days since last sexual assault in prepubertal children, >7 days pubertal girls) between October 2009 and November 2014.


 COLLECTED
source and indication for referral, alleged perpetrator, physical findings. Findings supportive of CSA were peer reviewed for consensus agreement.



χ2 test, Fisher's exact test and logistic regression.



Among 249 CYP, presentation with physical/behavioural symptoms was associated with age <13 years (p<0.01), and alleged penetration with ages 13-17 years (p<0.01). Where known, time since alleged CSA ranged from 1 week to 13 months. Anogenital findings supportive of CSA were present in 7% of examined children (16/233), significantly associated with alleged penetration (p<0.01) and more likely with increasing age (OR 1.46, 95% CI 1.23 to 1.72). Additionally, where tested, sexually transmitted infections (STI) were detected in 2.6% CYP (3/116). Alleged perpetrators were intrafamilial in 66% (126/190). No associations were identified between perpetrator type and gender (p=1.0), age (p=0.7) or indication for referral (p=0.35).



Despite significant time delay since the alleged CSA, this study highlights the persistence of anogenital findings supportive of CSA in 7% and STIs in 2.6% of CYP.
Intrusion Detection Systems : Technologies, Weaknesses and Trends

Traditionally, firewalls and access control have been the most important components used in order to secure servers, hosts and computer networks. Today, intrusion detection systems (IDSs) are gaining attention and the usage of these systems is increasing. This thesis covers commercial IDSs and the future direction of these systems. A model and taxonomy for IDSs and the technologies behind intrusion detection is presented. Today, many problems exist that cripple the usage of intrusion detection systems. The decreasing confidence in the alerts generated by IDSs is directly related to serious problems like false positives. By studying IDS technologies and analyzing interviews conducted with security departments at Swedish banks, this thesis identifies the major problems within IDSs today. The identified problems, together with recent IDS research reports published at the RAID 2002 symposium, are used to recommend the future direction of commercial intrusion detection systems. Intrusion Detection Systems – Technologies, Weaknesses and Trends
The Complete Design of Microstrip Directional Couplers Using the Synthesis Technique

A symmetrical microstrip directional coupler design using the synthesis technique without prior knowledge of the physical geometry of the directional coupler is analytically given. The introduced design method requires only the information of the port impedances, the coupling level, and the operational frequency. The analytical results are first validated by using a planar electromagnetic simulation tool and then experimentally verified. The error between the experimental and analytical results is found to be within 3% for the worst case. The design charts that give all the physical dimensions, including the length of the directional coupler versus frequency and different coupling levels, are given for alumina, Teflon, RO4003, FR4, and RF-60, which are widely used in microwave applications. The complete design of symmetrical two-line microstrip directional couplers can be obtained for the first time using our results in this paper.
Association of a presenilin 1 S170F mutation with a novel Alzheimer disease molecular phenotype.

To report an ataxic variant of Alzheimer disease expressing a novel molecular phenotype.



Description of a novel phenotype associated with a presenilin 1 mutation.



The subject was an outpatient who was diagnosed at the local referral center.



A 28-year-old man presented with psychiatric symptoms and cerebellar signs, followed by cognitive dysfunction. Severe beta-amyloid (Abeta) deposition was accompanied by neurofibrillary tangles and cell loss in the cerebral cortex and by Purkinje cell dendrite loss in the cerebellum. A presenilin 1 gene (PSEN1) S170F mutation was detected.



We analyzed the processing of Abeta precursor protein in vitro as well as the Abeta species in brain tissue.



The PSEN1 S170F mutation induced a 3-fold increase of both secreted Abeta(42) and Abeta(40) species and a 60% increase of secreted Abeta precursor protein in transfected cells. Soluble and insoluble fractions isolated from brain tissue showed a prevalence of N-terminally truncated Abeta species ending at both residues 40 and 42.



These findings define a new Alzheimer disease molecular phenotype and support the concept that the phenotypic variability associated with PSEN1 mutations may be dictated by the Abeta aggregates' composition.
Rotating analysis of 18-slot/16-pole Permanent Magnet Synchronous Motor for Light Electric Vehicle using FEM

This paper discusses the rotating analysis for 18-slot/16-pole Permanent Magnet Synchronous Motor (PMSM) using Finite Element Method. The PMSM is applied for Light Electric Vehicle (LEV) which has about 200 kg net mass and maximum velocity of 30 km/h. The motor is located in the wheels of the LEV. The motor is built using three main components i.e. laminated steel iron, coils, and Neodymium-Iron-Boron permanent magnet. The permanent magnet is attached to the surface of the rotor. The motor have 360 winding turns per phase and 10 A maximum current is flowing into the coils. The induced back-emf, cogging torque, and magnetic flux of the motor are analyzed. The results show that the motor is capable to generate an approximately 550 V back-emf, low cogging torque less than 0.5 Nm, maximum power of 5.5 kW and average torque of 81 Nm. The value of back-emf can be adjusted by changing the motor parameters such as coil turns per phase, rotor radius, axial length or magnet thickness. These values will determine the motor parameters required to design the power electronics converter for LEV.
Antenatal physical activity: a qualitative study exploring women’s experiences and the acceptability of antenatal walking groups

Regular physical activity (PA) can be beneficial to pregnant women, however, many women do not adhere to current PA guidelines during the antenatal period. Patient and public involvement is essential when designing antenatal PA interventions in order to uncover the reasons for non-adherence and non-engagement with the behaviour, as well as determining what type of intervention would be acceptable. The aim of this research was to explore women's experiences of PA during a recent pregnancy, understand the barriers and determinants of antenatal PA and explore the acceptability of antenatal walking groups for further development.



Seven focus groups were undertaken with women who had given birth within the past five years. Focus groups were transcribed and analysed using a grounded theory approach. Relevant and related behaviour change techniques (BCTs), which could be applied to future interventions, were identified using the BCT taxonomy.



Women's opinions and experiences of PA during pregnancy were categorised into biological/physical (including tiredness and morning sickness), psychological (fear of harm to baby and self-confidence) and social/environmental issues (including access to facilities). Although antenatal walking groups did not appear popular, women identified some factors which could encourage attendance (e.g. childcare provision) and some which could discourage attendance (e.g. walking being boring). It was clear that the personality of the walk leader would be extremely important in encouraging women to join a walking group and keep attending. Behaviour change technique categories identified as potential intervention components included social support and comparison of outcomes (e.g. considering pros and cons of behaviour).



Women's experiences and views provided a range of considerations for future intervention development, including provision of childcare, involvement of a fun and engaging leader and a range of activities rather than just walking. These experiences and views relate closely to the Health Action Process Model which, along with BCTs, could be used to develop future interventions. The findings of this study emphasise the importance of involving the target population in intervention development and present the theoretical foundation for building an antenatal PA intervention to encourage women to be physically active throughout their pregnancies.