bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of swarm intelligence algorithms to energy management of prosumers with wind power plants
Authors: Matrenin P. V. , Manusov V. Z. , Khasanzoda N. , Antonenkov D. V.
Published: September 2020

The paper considers the problem of optimal control of a prosumer with a wind power plant in smart grid. It is shown that control can be performed in non-deterministic conditions due to the impossibility of accurate forecasting of the generation from renewable plants. A control model based on a priority queue of logical rules with structural-parametric optimization is applied. The optimization problem is considered from a separate prosumer, not from the entire distributed system. The solution of the optimization problem is performed by three swarm intelligence algorithms. Computational experiments were carried out for models of wind energy systems on Russky Island and Popov Island (Far East). The results obtained showed the high effectiveness of the swarm intelligence algorithms that demonstrated reliable and fast convergence to the global extreme of the optimization problem under different scenarios and parameters of prosumers. Also, we analyzed the influence of accumulator capacity on the variability of prosumers. The variability, in turn, affects the increase of the prosumer benefits from the interaction with the external global power system and neighboring prosumers.
Visual control system for grip of glasses oriented to assistance robotics
Authors: Jimenez-Moreno Robinson , Rubiano Astrid , Ramirez Jose L.
Published: September 2020

Assistance robotics is presented as a means of improving the quality of life of people with disabilities, an application case is presented in assisted feeding. This paper presents the development of a system based on artificial intelligence techniques, for the grip of a glass, so that it does not slip during its manipulation by means of a robotic arm, as the liquid level varies. A faster R-CNN is used for the detection of the glass and the arm's gripper, and from the data obtained by the network, the mass of the beverage is estimated, and a delta of distance between the gripper and the liquid. These estimated values are used as inputs for a fuzzy system which has as output the torque that the motor that drives the gripper must exert. It was possible to obtain a 97.3% accuracy in the detection of the elements of interest in the environment with the faster R-CNN, and a 76% performance in the grips of the glass through the fuzzy algorithm.
Design and implementation of proposed 320 bit RC6-cascaded encryption/decryption cores on altera FPGA
Authors: Hashim Ashwaq T. , Hasan Ahmed M. , Abbas Hayder M.
Published: September 2020

This paper attempts to build up a simple, strong and secure cryptographic algorithm. The result of such an attempt is “RC6-Cascade” which is 320-bits RC6 like block cipher. The key can be any length up to 256 bytes. It is a secret-key block cipher with precise characteristics of RC6 algorithm using another overall structure design. In RC6-Cascade, cascading of F-functions will be used instead of rounds. Moreover, the paper investigates a hardware design to efficiently implement the proposed RC6-Cascade block cipher core on field programmable gate array (FPGA). An efficient compact iterative architecture will be designed for the F-function of the above algorithm. The goal is to design a more secure algorithm and present a very fast encryption core for low cost and small size applications.
A decentralized consensus application using blockchain ecosystem
Authors: Pujari Chetana , Muniyal Balachandra , C. B. Chandrakala
Published: September 2020

The consensus is a critical operation of any decision-making process.

It involves a set of eligible members; whose decision need to be honored by taking their acknowledgment before making any decision. The traditional consensus process follows centralized architecture, the members need to rely on and trust this architecture. The proposed system aims to develop a secure decentralized consensus application in the untrusted environment by making use of blockchain technology along with smart contract and interplanetary file system (IPFS).
The effect of technology-organization-environment on adoption decision of big data technology in Thailand
Authors: Saetang Wanida , Tangwannawit Sakchai , Jensuttiwetchakul Tanapon
Published: September 2020

Big data technology (BDT) is being actively adopted by world-leading organizations due to its expected benefits. However, most of the organizations in Thailand are still in the decision or planning stage to adopt BDT. Many challenges exist in encouraging the BDT diffusion in businesses. Thus, this study develops a research model that investigates the determinants of BDT adoption in the Thai context based on the technology-organization-environment (TOE) framework and diffusion of innovation (DOI) theory. Data were collected through an online questionnaire. Three hundred IT employees in different organizations in Thailand were used as a sample group. Structural equation modeling (SEM) was conducted to test the hypotheses. The result indicated that the research model was fitted with the empirical data with the statistics: Normed Chi-Square=1.651, GFI=0.895, AFGI=0.863, NFI=0.930, TLI=0.964, CFI=0.971, SRMR=0.0392, and RMSEA=0.046. The research model could, at 52%, explain decision to adopt BDT. Relative advantage, top management support, competitive pressure, and trading partner pressure show significant positive relation with BDT adoption, while security negatively influences BDT adoption.
Recent advances in passive cooling methods for photovoltaic performance enhancement
Authors: Ahmad Emy Zairah , Sopian Kamaruzzaman , Jarimi Hasila , Fazlizan Ahmad , Elbreki Abdelnaser , Abd Hamid Ag Sufiyan , Rostami Shirin , Ibrahim Adnan
Published: September 2020

The electrical output performance of photovoltaic (PV) modules are sensitive to temperature variations and the intensity of solar irradiance under prolonged exposure. Only 20% of solar irradiance is converted into useful electricity, and the remaining are dissipated as heat which in turns increases the module operating temperature. The increase in module operating temperature has an adverse impact on the open-circuit voltage (Voc), which results in the power conversion efficiency reduction and irreversible cell degradation rate. Hence, proper cooling methods are essential to maintain the module operating temperature within the standard test conditions (STC). This paper presents an overview of passive cooling methods for its feasibility and economic viability in comparison with active cooling. Three different passive cooling approaches are considered, namely phase change material (PCM), fin heat sink, and radiative cooling covering the discussions on the achieved cooling efficiency. The understanding of the above-mentioned state-of-the-art cooling technologies is vital for further modifications of existing PV modules to improve the efficiency of electrical output.
Computational and experimental study of air-core HTS transformer electrothermal behaviour at current limiting mode
Authors: Manusov V. Z. , Kriukov D. O. , Semenov A. V.
Published: September 2020

The paper provides the results of the experimental and computational study of the processes occurring in high temperature superconducting transformer windings while secondary winding is short-circuited. The obtained mathematical simulation matches closely with the experimental results. The temperature variation curves for superconducting windings were analysed, and conclusions were made on the necessity of changes in HTS transformer design, namely the necessity of windings heat-insulation from each other and adding a high-resistance coating material for HTS wire in HTS transformer primary winding.
FPGA configuration of an alloyed correlated branch predictor used with RISC processor for educational purposes
Authors: Mahmood Hadeel SH.
Published: September 2020

Instructions pipelining is one of the most outstanding techniques used in improving processor speed; nonetheless, these pipelined stages are constantly facing stalls that caused by nested conditional branches. During the execution of nested conditional branches, the behavior of the running branch depends on the history information of the previous ones; therefore, these branches have the greatest effect in reducing the prediction accuracy of a branch predictor among conditional branches. The purpose of this research is to reduce the stall cycles caused by correlated branches misprediction by introducing a hardware model of a branch predictor that combines both local and global prediction techniques. This predictor integrates the prediction characteristics of the alloyed predictor with those of the correlated predictor. the predictor design which implemented in VHDL (Very high-speed IC hardware description language) was inserted in previously designed MIPS (microprocessor without interlocked pipelined stages) processor and its prediction accuracy was confirmed by executing a program using the selection sort algorithm to sort 100 input numbers of different combinations ascendingly.
Application of particle swarm optimization with ANFIS model for double scroll chaotic system
Authors: Wali W. A.
Published: September 2020

The predictions for the original chaos patterns can be used to correct the distorted chaos pattern which has changed due to any changes whether from undesired disturbance or additional information which can hide under chaos pattern. This information can be recovered when the original chaos pattern is predicted. But unpredictability is most features of chaos, and time series prediction can be used based on the collection of past observations of a variable and analysis it to obtain the underlying relationships and then extrapolate future time series. The additional information often prunes away by several techniques. This paper shows how the chaotic time series prediction is difficult and distort even if Neuro-Fuzzy such as Adaptive Neural Fuzzy Inference System (ANFIS) is used under any disturbance. The paper combined particle swarm (PSO) and (ANFIS) to exam the prediction model and predict the original chaos patterns which comes from the double scroll circuit. Changes in the bias of the nonlinear resistor were used as a disturbance. The predicted chaotic data is compared with data from the chaotic circuit.
Hardware based cryptography: technological advances for applications in Colombia using embedded systems
Authors: Gomez Edwar Jacinto , Gutierrez Caterinne Perilla , Murillo Lina Uyasaba
Published: September 2020

To have totally independent systems that offer a sufficient security scheme has become a necessity in Colombia, this because of the proliferation of IoT type systems and similar; In general, it is required to make stand-alone systems totally independent and distributed to offer users a solution to this need, this work offers the analysis and comparison of two security schemes type digital signature and/or hardware security module (HSM) and its variations, made on embedded platforms type microcontroller software, which shows the strategy to provide information protection, In addition, it is analyzed how each implementation was executed, in which devices and metrics of interest, in the first application the cryptography schemes were made using a deep programming that describes the algorithms in C++ language and in the second implementation the use of the dedicated hardware that the embedded platform type microcontroller had is detailed; In both cases, solutions with an acceptable throughput were generated, allowing to obtain comparable solutions and the same style as those made in a PC or similar hardware. On the other hand, an exhaustive review of this type of solutions in the country-region was made, in order to have a reference as to the possible use of this type of applications.
Stochastic local search: a state-of-the-art review
Authors: Kastrati Muhamet , Biba Marenglen
Published: September 2020

The main objective of this paper is to provide a state-of-the-art review, analyze and discuss stochastic local search techniques used for solving hard combinatorial problems. It begins with a short introduction, motivation and some basic notation on combinatorial problems, search paradigms and other relevant features of searching techniques as needed for background. In the following a brief overview of the stochastic local search methods along with an analysis of the state-of-the-art stochastic local search algorithms is given. Finally, the last part of the paper present and discuss some of the most latest trends in application of stochastic local search algorithms in machine learning, data mining and some other areas of science and engineering. We conclude with a discussion on capabilities and limitations of stochastic local search algorithms.
Low power pseudo-random number generator based on lemniscate chaotic map
Authors: Saber Mohamed , Eid Marwa M.
Published: September 2020

Lemniscate chaotic map (LCM) provides a wide range of control parameters, canceling the need for several rounds of substitutions, and excellent performance in the confusion process. Unfortunately, the hardware model of LCM is complex and consumes high power. This paper presents a proposed low power hardware model of LCM called practical lemniscate chaotic map (P-LCM) depending on trigonometric identities to reduce the complexity of the conventional model. The hardware model designed and implement into the field programmable gate array (FPGA) board, Spartan-6 SLX45FGG484-3. The proposed model achieves a 48.3 % reduction in used resources and a 34.6 % reduction in power consumption compared to the conventional LCM. We also introduce a new pseudo-random number generator based on a proposed low power P-LCM model and perform the randomization tests for the proposed encryption system.
How Music AI Is Useful: Engagements with Composers, Performers and Audiences
Authors: Ben-Tal Oded , Harris Matthew Tobias , Sturm Bob L.T.
Published: September 2020

Critical but often overlooked research questions in artificial intelligence applied to music involve the impact of the results for music. How and to what extent does such research contribute to the domain of music? How are the resulting models useful for music practitioners? This article describes work arising from research engaging with composers, musicians and audiences to address such questions: two websites that make their AI models accessible to a wide audience and a professionally recorded album released to expert reviewers to gauge the plausibility of AI-generated material. The authors describe the use of their models as tools for cocreation. Evaluating AI research and music models in such ways illuminates their impact on music-making.
Performing WIKI-PIANO.NET: Strategies for Realizing Alexander Schubert's Ever-Changing Internet-Composed Piano Work
Authors: Kanga Zubin
Published: September 2020

This article explores strategies for interpreting Alexander Schubert's WIKI-PIANO.NET, a composition commissioned and performed by the author in an international tour in 2018 and 2020. Schubert's score is a website, all sections of which can be edited by the public, similar to a Wikipedia page. The author's strategies for interpreting the huge range of content added to the website-score draw upon Schubert's suggestions, the interdisciplinary rigor advocated by Jennifer Walshe, Henri Bergson's theories of comedy and the author's own experience as a composer-performer. These strategies are devised so that, despite the hundreds of compositional contributors, in performance, the final piece is perceived as an “Alexander Schubert work.”
Analyzing and Accelerating the Bottlenecks of Training Deep SNNs With Backpropagation
Authors: Chen Ruizhi , Li Ling
Published: September 2020

Spiking neural networks (SNNs) with the event-driven manner of transmitting spikes consume ultra-low power on neuromorphic chips. However, training deep SNNs is still challenging compared to convolutional neural networks (CNNs). The SNN training algorithms have not achieved the same performance as CNNs. In this letter, we aim to understand the intrinsic limitations of SNN training to design better algorithms. First, the pros and cons of typical SNN training algorithms are analyzed. Then it is found that the spatiotemporal backpropagation algorithm (STBP) has potential in training deep SNNs due to its simplicity and fast convergence. Later, the main bottlenecks of the STBP algorithm are analyzed, and three conditions for training deep SNNs with the STBP algorithm are derived. By analyzing the connection between CNNs and SNNs, we propose a weight initialization algorithm to satisfy the three conditions. Moreover, we propose an error minimization method and a modified loss function to further improve the training performance. Experimental results show that the proposed method achieves 91.53% accuracy on the CIFAR10 data set with 1% accuracy increase over the STBP algorithm and decreases the training epochs on the MNIST data set to 15 epochs (over 13 times speed-up compared to the STBP algorithm). The proposed method also decreases classification latency by over 25 times compared to the CNN-SNN conversion algorithms. In addition, the proposed method works robustly for very deep SNNs, while the STBP algorithm fails in a 19-layer SNN.
Dynamic community detection reveals transient reorganization of functional brain networks across a female menstrual cycle
Authors: Mueller Joshua M. , Pritschet Laura , Santander Tyler , Taylor Caitlin M. , Grafton Scott T. , Jacobs Emily Goard , Carlson Jean M.
Published: September 2020

Sex steroid hormones have been shown to alter regional brain activity, but the extent to which they modulate connectivity within and between large-scale functional brain networks over time has yet to be characterized. Here, we applied dynamic community detection techniques to data from a highly sampled female with 30 consecutive days of brain imaging and venipuncture measurements to characterize changes in resting-state community structure across the menstrual cycle. Four stable functional communities were identified, consisting of nodes from visual, default mode, frontal control, and somatomotor networks. Limbic, subcortical, and attention networks exhibited higher than expected levels of nodal flexibility, a hallmark of between-network integration and transient functional reorganization. The most striking reorganization occurred in a default mode subnetwork localized to regions of the prefrontal cortex, coincident with peaks in serum levels of estradiol, luteinizing hormone, and follicle stimulating hormone. Nodes from these regions exhibited strong intranetwork increases in functional connectivity, leading to a split in the stable default mode core community and the transient formation of a new functional community. Probing the spatiotemporal basis of human brain–hormone interactions with dynamic community detection suggests that hormonal changes during the menstrual cycle result in temporary, localized patterns of brain network reorganization.
An Approach Towards Hotel Recommender System
Authors: Yadav Dharminder , Maheshwari Himani , Chandra Umesh
Published: September 2020

Recommendation Systems (RS) suggest the right item to the right user. It predicts the user’s rating to an item and based on this rating RS provides the suggestion to users. In today’s world many online applications are already using the Recommendation system that provides a recommendation for a particular item like books, movies, music etc. in an automated fashion. This paper proposed a system that helps to find the best suitable hotel in a given geographical area according to the user query by using library “recommenderlab” in R. This study proposed a system that gives the best hotel available according to the user rating available in database. User makes their decision according to their recommendation provides by the proposed system for finding best suitable hotel from available database and shows on the map by using a leaflet map package.
Big Data Security Based Framework Using Metaheuristic Approaches in Cloud Environment
Authors: Parashar Jyoti , Rai Munishwar
Published: September 2020

Security is the main concern in Big Data analysis. In the security analysis, most of the approaches that provide an effective security yet uses high amount of resources like memory or storage and time delay in order to increase the cost of processing. This paper emphasis on improvement
based on utilization of resources by means of optimization of encryption approach. The optimisation approach uses a convex optimization with minimum amount of time or storage and such factors effects the total cost of processing. The proposed approach uses GWO optimization of Blow fish slices.
The experiment involves the use of two types of dataset such as tweet and scientific workflow. The exper- imental analysis shows how effectively blow fish improves Grey wolf optimization (GWO). In addition, the other experiment uses particle swarm optimization (PSO) and flower pollination
approach (FPA). Although the analysis represents that these approaches are not very much effective as compared to GWO.
Comparative Analysis of Routing Protocols on Lossy Networks with Less Power
Authors: Das Debashreet , Sharma Avinash , Patel Lipson
Published: September 2020

The wide range of applications of Wireless Sensor Networks has a great impact in today’s generation. The Wireless Sensor Networks has helped us to actually make an observation and thereby, understand the various environmental factors. The rapid growth of these sensor devices in
the form of Wireless Sensor Networks has led to the evolution of an emerging technology called Internet of Things. The sensor and the IoT devices automate the process of monitoring the environment. Hence, proper evaluation of performance factors of these devices and sensors is of utmost importance
as it enhances their use in real world applications. We have simulated the motes in different scenarios using Cooja simulator to evaluate the performance.
Optimized Hybridization of Ant Colony Optimization and Genetic Algorithm (HACOGA) Based Interpretable Intuitive and Correlated-Contours Fuzzy Neural Network Classifier for Abalone
Authors: Patro Pramoda , Kumar Krishna , Suresh Kumar G.
Published: September 2020

Classification generally assigns objects to enormous predefined categories and it is pervasive crisis that covers various application. Preparing the data for Classification and Prediction is the major problem in classification. In order to rectify this issue, an approximate function
is proposed using Interpretable intuitive and Correlated-contours Fuzzy Neural Network (IC-FNN). For acquiring cor- related fuzzy rules and non-separable rules that comes under proper optimization problem. The extracted fuzzy rule’s parameter was fine-tuned sourced on hierarchical Levenberg
Marquardt (LM) learning method for enhancing performance. But here parameters of fuzzy rules aren’t tuned per- fectly. Hybridization of Ant Colony Optimization Genetic Algorithm (HACOGA) is proposed here to rectify these issues. It tunes the parameters of the extracted fuzzy rules. Hybridization
is enforced to certain factors and ACO and GA variables that share same characteristics in the computation. Experimental results shows that proposed HACOGA assist in enhancing the performance of FNN with recall, precision, accuracy and F -measure for the Abalone age prediction dataset.
Minimum Spanning Tree Structure Based Routing Technique for Homogeneous Wireless Sensor Network
Authors: Poonam Rani , Avinash Sharma
Published: September 2020

The Sensor Nodes (SN’s) utilized in Wireless Sensor Networks (WSN) works on short proximity detecting adverse circumstances and are small light-weight gadgets equipped with limited, irreplaceable power source. The system output and efficiency relies upon the routing conventions
in the network layer and at the data link layer. In this paper proposes a routing scheme is proposed which is based on forming a Minimum Spanning Tree (MST) and works on basis of flat based routing technique to perfectly utilise vitality and improves the overall life span of the system along
with minimising the transmission delay. Transmission between the clusters via Cluster Heads (CH’s) has been suggested dependent on the gap of separation among sensors. This proposal forms a linear chain among the nodes and connect them in such a fashion that reduces overall cost of the
governing system. Simulation of the proposed technique shows healthy improvement over existing techniques.
Evaluation of High-Resolution Precipitation Products over Southwest China
Authors: Nie Yanbo , Sun Jianqi
Published: September 2020

The evaluation of gridded high-resolution precipitation products (HRPPs) is important in areas with complex topography, because rain gauges that are unevenly and sparsely distributed over an area cannot effectively reflect the spatial variabilities of the precipitation and related extremes in detail. In this study, the applicability of six satellite-based precipitation products (TMPA 3B42V7, IMERG, GSMaP-Gauge, CMORPH-CRT, PERSIANN-CDR, and GPCP) and five gauge-based precipitation products (APHRODITE, CN05.1, GPCC-D, GPCC-M, and CRU) over southwest China from 1998 to 2016 is evaluated by performing a comparison with meteorological station observations. The results show that GPCC-M exhibits the best performances for annual, seasonal, and monthly precipitation, which is supported by the lowest root-mean-square errors (RMSEs) for annual and seasonal precipitation and the lowest normalized root-mean-square error (NRMSE) for monthly precipitation. According to the NRMSE and critical success index (CSI), CN05.1 outperforms the other HRPPs at detecting daily precipitation; however, CN05.1 tends to overestimate the frequencies of light precipitation and underestimate the frequencies of heavy precipitation, which is reflected by the probability density function (PDF) for daily precipitation. The bias ratio (BIAS) and extreme precipitation indices show that IMERG shows numerous advantages over the other HRPPs in detecting extreme precipitation and estimating the precipitation intensity. Such results are helpful for future research on precipitation/extremes and related hydrometeorological disasters that occur throughout southwest China.
The Neutrophil to Lymphocyte Ratio (NLR) Is Associated With Residual Syntax Score in Patients With ST-Segment Elevation Myocardial Infarction
Authors: Kahraman Serkan , Agus Hicaz Zencirkiran , Avci Yalcin , Serbest Nail Guven , Guner Ahmet , Erturk Mehmet
Published: September 2020

The neutrophil to lymphocyte ratio (NLR) predicts adverse clinical outcomes in several cardiovascular diseases. Our aim was to investigate the association of residual SYNTAX score (rSS) with the NLR in patients (n = 613) with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention. Patients were divided into 2 groups: group 1 with low NLR (<2.59) and group 2 with high NLR (>2.59). Coronary artery disease severity was calculated for both groups besides baseline clinical and demographic variables. Receiver operating characteristic curve analysis demonstrated that NLR with a cutoff value of 2.59 had good predictive value for increased rSS (area under the curve = 0.707, 95% CI: 0.661-0.752, P < .001). The median rSS value of group 2 was higher (2.0 [0-6.0]; 4.0 [0-10.0], P < .001) compared with group 1; the number of patients with high rSS was also higher in group 2 (26 [9.7%]; 107 [31.0%], P < .001). In multivariate logistic regression analysis, the NLR (odds ratio = 3.933; 95% CI: 2.419-6.393; P < .001) was an independent predictor of high rSS. Additionally, there was a positive correlation between NLR and rSS (r = 0.216, P < .001). In conclusion, higher NLR was an independent predictor of increased rSS in patients with STEMI.
Trends in Sentencing of Federal Drug Offenders: Findings From U.S. District Courts 2002–2017
Authors: Testa Alexander , Lee Jacqueline G.
Published: September 2020

This study uses 16 years (2002–2017) of federal criminal drug sentences from the U.S. Sentencing Commission (USSC) to examine trends in two criminal sentencing outcomes: whether a defendant received a prison sentence and the length of a prison sentence. Logistic and ordinary least squares regression analyses were used to assess criminal sentencing outcomes. Moderation analyses are conducted to assess variation in sentencing for specific drug offenses over time. Results demonstrate that sentencing for federal drug crimes has become less severe over time. However, there is substantial heterogeneity in sentencing across different drug types, with pharmaceutical opioid cases receiving the least leniency over time regarding the incarceration decision and methamphetamine cases experiencing the lowest reduction in the length of prison sentences from 2002 to 2017. Finally, our analysis stratified by race/ethnicity suggested that there is heterogeneity in sentencing outcomes for federal drug offenders, conditional on racial and ethnic background.
Knowledge of Evidence-Based Practices and Frequency of Selection Among School-Based Professionals of Students With Autism
Authors: Morin Kristi L. , Sam Ann , Tomaszewski Brianne , Waters Victoria , Odom Samuel L.
Published: September 2020

Autism Focused Intervention Resources and Modules (AFIRM) are a set of self-paced, online learning modules designed to disseminate information about the 27 evidence-based practices identified through a large-scale review of focused intervention practices for individuals with autism. In this study, we used descriptive statistics and an analysis of variance to analyze more than 67,000 pre-tests completed by over 22,000 school-based AFIRM users to determine whether there are differences by occupation in the (a) selection of evidence-based practices, (b) knowledge of evidence-based practices, and (c) average number of evidence-based practices selected. Results reveal statistically significant differences between groups and have implications for providers and administrators responsible for designing and delivering professional development for school-based professionals working with students with autism.
The role of family-of-origin environment and discrepancy in conflict behavior on newlywed marital quality
Authors: Monk J. Kale , Ogolsky Brian G. , Rice TeKisha M. , Dennison Renee Peltz , Ogan Matthew
Published: September 2020

How partners handle conflict may be transmitted across generations and contribute to relationship quality. Using a sample of 220 newlywed couples ( N = 440) we examined the associations between destructive family-of-origin conflict patterns and discrepancies in current conflict behaviors (e.g., conflict engagement, withdrawal, negative problem solving) with marital quality. Destructive conflict mediated the relationship between destructive family-of-origin conflict and subsequent marital quality. We found actor and partner effects for the association between destructive conflict behavior and marital quality. Moreover, discrepancies in spousal use of negative problem solving was associated with lower marital quality for husbands, although we found limited evidence of partner discrepancy overall.
Reported Sexual-offense Incidents in the United States: Arrest Disparities between Women and Men
Authors: Dara Shaw Callie , J. Vaughan Tyler , M. Vandiver Donna
Published: September 2020

This study examined the effect of an offender’s sex (male/female) on whether sexual-offense incidents reported to law enforcement culminated in an arrest. Two hypotheses, chivalry and evil woman, are relied upon and suggest that the probability of arrest differs for women and men, yet in differing directions. The chivalry hypothesis suggests women are treated more leniently than men and, therefore, less likely to be arrested. The evil woman hypothesis, however, suggests the opposite: Women are treated more harshly than men and, therefore, more likely to be arrested. Seven years of National Incident-based Reporting System [NIBRS] data were relied upon ( National Archive of Criminal Justice Data, 2010–2016 , National Incident-based Reporting System: Extract Files); all of the reported sexual-offense incidents committed by women were included, along with a matched sample of reported sexual-offense incidents committed by men, culminating in a sample of 22,744. Overall, women were 42% significantly less likely than men to be arrested when controlling for other known offense, offender, and victim characteristics. The odds for women to be arrested increased, however, when specific offender demographics, offense characteristics, and victim characteristics were taken into account. The implications of these findings are discussed in regard to their application of the chivalry and evil woman hypotheses.
Bidirectional Violence Is Associated with Poor Engagement in HIV Care and Treatment in Malawian Couples
Authors: Conroy Amy A. , Leddy Anna M. , Darbes Lynae A. , Neilands Torsten B. , Mkandawire James , Stephenson Rob
Published: September 2020

Growing evidence suggests that intimate partner violence (IPV) is a barrier to engagement in HIV care. Bidirectional IPV—being both a perpetrator and victim—may be the most common pattern of IPV, yet no research has examined its effect on engagement in care, which could identify couples in most need of interventions. Married couples ( N = 211) with at least one partner on antiretroviral therapy were recruited from HIV clinic waiting rooms in Zomba, Malawi. Partners completed separate surveys on physical, sexual, and emotional IPV, medication adherence, and appointment attendance. We created categorical variables indicating no violence, perpetrator-only, victim-only, and bidirectional violence. Generalized estimating equation regression models tested for associations between IPV and engagement in care. The bidirectional pattern represented 25.4%, 35.5%, and 34.0% of all physical, sexual, and emotional IPV. Physical IPV victimization-only (adjusted odds ratio [AOR]: 0.28, 95% confidence interval [CI]: 0.08, 0.92) was associated with lower adherence, but the association was stronger for bidirectional physical IPV (AOR: 0.10, 95% CI: 0.02, 0.51). Bidirectional sexual IPV was also associated with lower adherence (AOR: 0.14, 95% CI: 0.02, 0.80). Bidirectional physical IPV (AOR: 4.04, 94% CI: 1.35, 12.14) and emotional IPV (AOR: 3.78, 95% CI: 1.78, 8.05) were associated with missing 1+ appointment. Interventions to address the health effects of bidirectional IPV, which may be greater than victim-only or perpetrator-only IPV, should intervene with both partners to break cycles of violence. Couple-based interventions may be a viable option by intervening on both partners’ trauma and aggression simultaneously.
Better Me Within Randomized Trial: Faith-Based Diabetes Prevention Program for Weight Loss in African American Women
Authors: Kitzman Heather , Mamun Abdullah , Dodgen Leilani , Slater Donna , King George , King Alene , Slater J. Lee , DeHaven Mark
Published: September 2020

Purpose:

Previous DPP translations in African American women have been suboptimal. This trial evaluated a community-based participatory research developed faith-based diabetes prevention program (DPP) to improve weight loss in African American women.

Design:

This cluster randomized trial allocated churches to faith-based (FDPP) or standard (SDPP) DPP interventions. Setting. African American churches. Subjects. Eleven churches with 221 African American women (aged 48.8 ± 11.2 years, BMI = 36.7 ± 8.4) received the FDPP (n = 6) or SDPP (n = 5) intervention.

Intervention:

FDPP incorporated 5 faith-based components, including pastor involvement, into the standard DPP curriculum. The SDPP used the standard DPP curriculum. Lay health leaders facilitated interventions at church sites.

Measures:

Weight and biometrics were collected by blinded staff at baseline, 4- and 10-months.

Analysis:

A multilevel hierarchical regression model compared the FDPP and SDPP groups on outcomes.

Results:

FDPP and SDPP churches significantly lost weight at 10-months (overall −2.6%, p < .01). Women in FDPP churches who attended at least 15 sessions lost an additional 6.1 pounds at 4-months compared to SDPP corresponding to a 5.8% reduction at 10-months (p < .05). Both groups had significant improvements in health behaviors and biometrics.

Conclusions:

Faith-based and standard DPP interventions led by lay health leaders successfully improved weight, health behaviors, and chronic disease risk. However, the faith-based DPP when fully implemented met the CDC’s recommendation for weight loss for diabetes prevention in African American women.
Liquid crystalline hyperbranched polyesters with phosphorus functional groups
Authors: Serbezeanu Diana , Macsim Ana-Maria , Carja Ionela-Daniela , Hamciuc Corneliu , Pislaru Marius , Vlad-Bubulac Tăchiţă
Published: September 2020

Liquid crystalline hyperbranched poly(aryl ester)s (A2B3) were prepared by polycondensation reaction of 2-(6-oxido-6H-dibenz<1,2>oxaphosphorin-6-yl)1,4-naphthalene diol with 1,3,5-benzenetricarbonyl trichloride, taken in two different molar ratios. The chemical structure of the newly synthesized hyperbranched polymers was confirmed by FTIR, 1H NMR, 13C NMR spectroscopy. The polymers exhibited high thermal stability with initial decomposition temperature above 410–435°C and char yield at 700°C higher than 40%. Combined differential scanning calorimetry, polarized optical microscopy and wide-angle X-ray diffraction measurements were carried out to closely examine their thermal behavior and phase transitions.
Accounting as an instrument of power: The case of an Italian hospital in the late nineteenth century
Authors: Lazzini Simone , Nicoliello Mario
Published: September 2020

During the past few years, scholars have investigated accounting practices from different perspectives and in different contexts; however, the topics of accounting and fraud-corruption appear to be underresearched areas in accounting history literature. This article examines the case of Galliera Hospital of Genoa, established as Opera Pia De Ferrari Brignole Sale in 1877 by the Duchess Maria Brignole Sale. Currently, the Galliera Hospital is an important and specialised Italian hospital with 450 beds and almost 2,000 employees. Using the lens of Foucault’s governmentality and discipline power framework, this article explores how unforeseen events and misconduct can deeply change governance and control mechanisms, implying the adoption of empowered accounting practices. Thus, this article shows that accounting practices, when perceived as a real technology of government, allow the exercise of power. The study offers a relevant contribution to the extant accounting history literature by examining how accounting can be used as an instrument of power in the presence of misconduct.
Context Regulation of Mind Wandering in ADHD
Authors: Bozhilova Natali , Michelini Giorgia , Jones Christopher , Kuntsi Jonna , Rubia Katya , Asherson Philip
Published: September 2020

Objective

We aimed to understand the association between MW frequency and clinical measures, context regulation of MW and group differences in task performance.

Method

27 adults with ADHD and 29 controls performed tasks manipulating demand on working memory and sustained attention, and recorded their MW frequency using probes.

Results

A significant association between MW frequency and the clinical measures was demonstrated. Along with increased MW frequency, individuals with ADHD reported decreasing MW frequency during increasing demands on working memory (context regulation), but not on sustained attention (deficient context regulation). Controls, however, maintained continuous task focus across all conditions. Group differences in task performance were no longer significant after adding MW frequency as a covariate.

Conclusion

Deficient context regulation during increasing demands on sustained attention suggests that sustained attention deficits may play a more important role in regulation of MW in ADHD. MW frequency might also underpin performance deficits in ADHD.
Alcohol use among older adults: A comparative study across four European countries
Authors: Rossow Ingeborg , Træen Bente
Published: September 2020

Aims:

(i) To examine whether mean consumption and prevalence of at-risk drinking are highly correlated across samples of older adults, and (ii) to explore whether sociodemographic and health characteristics of alcohol use differ across countries.

Method:

Cross-sectional surveys were conducted in four European countries, Norway, Denmark, Belgium, and Portugal, applying identical data collection methods and survey instruments in general population samples of older adults aged 60 to 75 years. Alcohol consumption was measured as units of alcohol per week, which provided the basis for categorising the two outcome measures: abstention (0 units/week) and at-risk drinking (8+ units/week). Cross-tabulations and logistic regression models were estimated to examine associations between sociodemographic and health characteristics on the one hand and alcohol abstention and at-risk drinking on the other.

Results:

Prevalence of abstention was highest in Portugal and lowest in Denmark, whereas at-risk drinking was more prevalent in Denmark and Belgium compared to Norway and Portugal. Among country- and gender-specific samples of drinkers, there was a strong positive correlation between mean consumption and prevalence of at-risk drinkers. Female gender characterised abstention, whereas male gender characterised at-risk drinking in all four countries. Other sociodemographic characteristics and indicators of health and wellbeing were differently associated with abstention and at-risk drinking across the four countries.

Conclusions:

A strong regularity in the distribution of alcohol consumption was observed in the samples of older adults. Gender was the only common factor associated with drinking behaviour across the four countries.
Social media in ophthalmology: An analysis of use in the professional sphere
Authors: Al-khersan Hasenin , Lazzarini Thomas A , Fan Kenneth C , Patel Nimesh A , Tran Ann Q , Tooley Andrea A , Lee Wendy W , Alfonso Eduardo , Sridhar Jayanth
Published: September 2020

To characterize how ophthalmologists are using social media in their practice. A survey regarding ophthalmologists’ personal and professional use of social media was distributed online through a university alumni listserv. Data collection occurred over 4 weeks from January to February 2020. In total, 808 ophthalmologists opened the survey email, and 160 responded (19.8%). Of 160 respondents, 115 (71.9%) participated in social media for personal use. Professional use of social media was noted by 63 (39.4%) respondents. Age >40 years old correlated with less personal ( X2 = 5.06, p = 0.025) but not professional use ( p = 0.065). Private practice was associated with more use of social media professionally compared to those in an academic or Veteran’s Affairs hospital ( X2 = 6.58, p = 0.037). A majority of respondents (58.7%) were neutral regarding the effect of social media on their practice. The present survey showed that nearly 40% of respondents are involved in social media in a professional context. Private practice correlated with increased use of social media professionally, but providers were most commonly neutral regarding the impact of social media on their practice. This finding suggests further avenues of research including how providers using social media professionally are defining and assessing successful use.
Multirobot searching method of natural gas leakage sources on offshore platform using ant colony optimization
Authors: Ma Tao , Liu Shuhai , Xiao Huaping
Published: September 2020

Natural gas leakage on offshore platforms has a great impact on safety production, and effective and reasonable leakage detection methods can prevent the harm caused by natural gas leakage. This article proposes a method based on ant colony optimization (ACO) for multirobots to collaboratively search for leaking natural gas sources on offshore platforms. First, analyze the structure and environment of the offshore platform, use Fluent software to simulate the diffusion process of natural gas leaked from the platform, and establish a diffusion model of natural gas leaked from various aspects, such as the layout of different platforms, the number of leaked gas sources, and the concentration of leaked gas sources. In terms of multirobot cooperative control, we analyzed and improved the ant colony algorithm and proposed a multirobot cooperative search strategy for gas search, gas tracking, and gas source positioning. The multirobot search process was simulated using MATLAB software, and the robot on the detection effect of multirobots was analyzed in many aspects, such as quantity, location of leak source, and a number of leak sources, which verified the feasibility and effectiveness of the multirobot control strategy based on optimized ACO. Finally, we analyze and compare the two control algorithms based on ACO and cuckoo search algorithm (CSA). The results show that the ACO-based multirobot air source positioning effect is significantly better than CSA.
The mitochondrion as a hammer
Authors: Cole Logan W.
Published: September 2020

This is a review of Mitonuclear Ecology by Geoffrey E. Hill, which discusses the potential role of mitochondrial-nuclear (mitonuclear) interactions in key evolutionary processes.
Assessing the genetic diversity of cowpea [Vigna unguiculata (L.) Walp.] germplasm collections using phenotypic traits and SNP markers
Authors: Nkhoma Nelia , Shimelis Hussein , Laing Mark D. , Shayanowako Admire , Mathew Isack
Published: September 2020

Background

Productivity of cowpea [Vigna unguiculata(L.)Walp] in sub-Sahara Africa is curtailed by a lack of farmer-preferred and improved cultivars and modern production technologies. The objectives of the study were to determine the extent of genetic diversity present among a collection of cowpea accessions from Zambia and Malawi using phenotypic traits and single nucleotide polymorphism (SNP) markers and, to select distinct and complementary parental lines for cultivar development. One hundred cowpea genotypes were evaluated for agronomic traits in two selected sites in Zambia, using a 10 × 10 alpha lattice design with two replications. Ninety-four of the test genotypes were profiled with 14,116 SNP markers.

Results

Number of pods plant− 1(NPP), pod length (PDL), and number of seeds pod− 1(NSP), were significantly (p < 0.05) affected by genotype × environment interaction effects. Genotypes such as CP411, CP421, CP645, CP732, Chimponongo, and MS1–8–1-4 exhibited higher grain yield of > 1200 kg/ha with excellent performance in yield components such as NSP, PDL, HSW and GYD. Grain yield had significant (p < 0.05) associations with NPP (r = 0.50), NSP (r = 0.46) and PDL (r = 0.42) useful for simultaneous selection for yield improvement in cowpea. The SNP markers revealed gene diversity and polymorphic information content of 0.22 and 0.17, respectively, showing that the tested cowpea accessions were genetically diverse. Test genotypes were classified into four genetic groups irrespective of source of collection allowing selection and subsequent crosses to develop breeding populations for cultivar development.

Conclusions

Genotypes Bubebe, CP411, CP421, CP645, Chimponogo and MS1–8–1-4 were identified to be the most genetically divergent and high yielding making them ideal parental lines for breeding. This study provided a baseline information and identified promising cowpea genetic resources for effective breeding and systematic conservation.