bluuebunny/crossref_metadata_2025 huggingface dataset:
An analytical multicriteria model based on graph theory for reliability enhancement in distribution electrical networks
Authors: Lekbich Anass , Belfqih Abdelaziz , Ouaderhman Tayeb , Boukherouaa Jamal , El Mariami Faissal
Published: October 2019

The electrical distribution network is a critical and complex system in terms of safety and reliability, because it is composed of different components (switches, reclosers, etc.). The improvement of its reliability is therefore one of the most important tasks through the good management of remote-controlled switches and reclosers in this network. This paper presents an analytical model based on graph theory to evaluate SAIDI and SAIFI indices based on the network architecture and the location of remote-controlled reclosers and switches. These indicators have been used to formalize a multi-objective mathematical model that respects the real operation constraints of equipments in smart grid. The applied model, in this article, was evaluated on an IEEE 13 bus network using the TOPSIS method to determine the optimal location of the switches and reclosers and to improve the overall reliability of the distribution network.
Full On-chip low dropout voltage regulator with an enhanced transient response for low power systems
Authors: Ameziane Hatim , Zared Kamal , Akhamal Hicham , Qjidaa Hassan
Published: October 2019

A full on chip low Dropout Voltage Regulator (LDO) with fast transient response and small capacitor compensation circuit is proposed. The novel technique is implemented to detect the variation voltage at the output of LDO and enable the proposed fast detector amplifier (FDA) to improve load transient response of 50mA load step. The large external capacitor used in Conventional LDO Regulators is removed allowing for greater power system integration for system-on-chip (SoC) applications. The 1.6-V Full On-Chip LDO voltage regulator with a power supply of 1.8 V was designed and simulated in the 0.18µm CMOS technology, consuming only 14 µA of ground current with a fast settling-time LNR(Line Regulation) and LOR(Load regulation) of 928ns and 883ns respectively while the rise and fall times in LNR and LOR is 500ns.
Performance of compliant mechanisms applied to a modified shape accelerometer of single and double layer
Authors: Tecpoyotl-Torres Margarita , Cabello-Ruiz Ramon , Vargas-Chable Pedro , Vera-Dimas Jose Gerardo , Ocampo-Diaz Alejandra
Published: October 2019

Accelerometers are widely used in several mechanisms of high sensitivity. They are employed for example in tilt-control in spacecraft, inertial navigation, oil exploration, seismic monitoring, etc. In order to improve the sensitivity of the measurements, implementation of Displacement-amplifying Compliant Mechanisms (DaCMs) in a capacitive accelerometer have been reported in the literature. In this paper, a system composed of two elements; capacitive accelerometer with extended beams (CAEB) and a DaCM geometry, of single and souble layer, are analysed. Three materials were considered, in the case, for the second layer. The DaCM implementation improves the operation frequency and displacement sensitivity, under different proportions, at the same time. Furthermore, three sweeps were performed: a range of thickness from 25 µm up to 30 µm (to determine the appropriate silicon mass value, using SOI technology), a range of second layer thickness (to choose the more appropriate material and its thickness) and a range of gravity values (to determine the maximum normal stress in the beams, which defines the superior value of the g operation range). The in-plane mode (y-axis) was considered in all analysed cases. This characterization was developed using the Finite Element Method. Structural and modal analysis responses were under study.
DC-AC power inverter controlled analogically with zero hysteresis
Authors: Hoyos Velasco Fredy E. , Hoyos Velasco Carlos I. , Candelo-Becerra John E.
Published: October 2019

This paper presents the design and experimental validation of a DC-AC power inverter, controlled analogically with zero hysteresis. A control circuit was built using analog electronics components, and optocoupler devices are used to couple the control module with the power stage. The design of DC-AC inverter with electronics circuit and implementation are shown in detail.  Experimental results show the effectiveness of control technique and implementation, leading to a robust system concerning load disturbances. The developed inverter offers the possibility of generating regulated output voltages of different signal types, both DC and AC, variable in frequency and in amplitude, useful for feeding a load with various AC signals.
Development of driving cycle under real world traffic conditions: A case study
Authors: A. Geetha , C. Subramani
Published: October 2019

The modeling of a car is essentially done by taking into consideration the driving terrain, traffic conditions, driver’s behavior and various other factors which may directly or indirectly affect the vehicle’s performance. A vehicle is modeled for given specifications and constraints like maximum speed, maximum acceleration, and braking time, appropriate suspension for the gradient of the road and fuel consumption. Henceforth, a profound study and analysis of different drive cycles are essential. A time dependent drive cycle is a condensed form of data that helps us to determine the time taken to conduct the driving test on the road. This article highlights the development of a real driving cycle in the area of Tamilnadu, India. On-road vehicle’s speeds versus time data were obtained along the selected route. The data obtained were analyzed first and then a new driving cycle was developed.
Congestion bottleneck avoid routing in wireless sensor networks
Authors: Thomas Sanu , Mathew Thomaskutty
Published: October 2019

A new efficient method for detecting congested bottleneck nodes and avoiding them in the route formation in a wireless sensor network is described. Sensor nodes with a higher degree of congestion are excluded while determining the best routing path from a given source to destination in a multi-hop transmission. In a scenario where different communication paths have different maximum congestion levels, selecting that path which has least maximum congestion, is a challenging task. A modified Bellman-Ford algorithm is proposed to solve this problem efficiently. The proposed technique is very much useful for the optimal route selection for vehicles in metropolitan cities that avoids high traffic density junctions. Once the desired destination is specified, the traffic control system can use this algorithm to provide the least congested routes to the intra-city vehicles.
An enhanced particle swarm optimization algorithm
Authors: Abdul-Adheem Wameedh Riyadh
Published: October 2019

In this paper, an enhanced stochastic optimization algorithm based on the basic Particle Swarm Optimization (PSO) algorithm is proposed. The basic PSO algorithm is built on the activities of the social feeding of some animals. Its parameters may influence the solution considerably. Moreover, it has a couple of weaknesses, for example, convergence speed and premature convergence. As a way out of the shortcomings of the basic PSO, several enhanced methods for updating the velocity such as Exponential Decay Inertia Weight (EDIW) are proposed in this work to construct an Enhanced PSO (EPSO) algorithm. The suggested algorithm is numerically simulated established on five benchmark functions with regards to the basic PSO approaches. The performance of the EPSO algorithm is analyzed and discussed based on the test results.
A reliable approach to customizing linux kernel using custom build tool-chain for ARM architecture and application to agriculture
Authors: Swain Mahendra , Singh Rajesh , Gehlot Anita , Hashmi Md Farukh , Kumar Shiv , Parmar Manish
Published: October 2019

ARM processors are receiving more attention as per IoT customized devices are concerned. A novel framework design tool for Linux kernel customization on ARM architecture has been illustrated. The tool is best suit from ARM based platformss like Raspberry pi, Beagle Bone, Intel Edison etc. The proposed techniques uses different tool chains for the kernel customization. The paper represents an integral framework that integrates all the cross compiling tools and simplifies the overall process. The framework has been used for the development of a customized kernel for Raspberry Pi on Ubuntu 14.04 host computer. The custom kernel has been ported in to Raspberry Pi and the performance evaluation has been done. Furthermore, the analysis aims to help users choose and configure their tracers based on their specific requirements to reduce their overhead and get the most of out of them. The testing of customized OS with raspberry Pi device in the field of agriculture. The smart node/mote is designed based on it to deploy in the agriculture field to test its feasibility. The group of nodes data is gathered using ThingSpeak cloud server. The gathered sensory data is analyzed and forecast on farmer’s mobile phone in the form of APP or handheld device for farmer.
Hybrid approach of the fuzzy C-Means and the K-Nearest neighbors methods during the retrieve phase of dynamic case based reasoning for personalized Follow-up of learners in real time
Authors: Nihad EL Ghouch , El Mokhtar En-Naimi , Abdelhamid Zouhair , Mohammed Al Achhab
Published: October 2019

The goal of adaptive learning systems is to help the learner achieve their goals and guide their learning. These systems make it possible to adapt the presentation of learning resources according to learners' needs, characteristics and learning styles, by offering them personalized courses. We propose an approach to an adaptive learning system that takes into account the initial learning profile based on Felder Silverman's learning style model in order to propose an initial learning path and the dynamic change of his behavior during the learning process using the Incremental Dynamic Case Based Reasoning approach to monitor and control its behavior in real time, based on the successful experiences of other learners, to personalize the learning. These learner experiences are grouped into homogeneous classes at the behavioral level, using the Fuzzy C-Means unsupervised machine learning method to facilitate the search for learners with similar behaviors using the supervised machine learning method K- Nearest Neighbors.
IOT based application for monitoring electricity power consumption in home appliances
Authors: Luechaphonthara Korakot , A Vijayalakshmi
Published: October 2019

Internet of Things is one of the emerging techniques that help in bridging the gap between the physical and cyber world. In the Internet of Things, the different smart objects connected, communicate with each other, data is gathered from the smart objects and based on the need of the users, and the data gathered are queried and sent back to the user. IoT helps in monitoring electrical and physical parameters. Electricity consumption from electronic devices is one among such parameters that need to be monitored. The development of energy efficient schemes for the IoT is a challenging issue as the IoT becomes more complex due to its large scale the current techniques of wireless sensor networks cannot be applied directly to the IoT. To achieve the green networked IoT, this paper proposes a Wi-Fi enabled simple low cost electricity monitoring device that can monitor the electricity consumption on home appliances which helps to analyses the consumption of electricity on a daily and weekly basis. 
A Graph-based approach for text query expansion using pseudo relevance feedback and association rules mining
Authors: Jabri Siham , Dahbi Azzeddine , Gadi Taoufiq
Published: October 2019

Pseudo-relevance feedback is a query expansion approach whose terms are selected from a set of top ranked retrieved documents in response to the original query.  However, the selected terms will not be related to the query if the top retrieved documents are irrelevant. As a result, retrieval performance for the expanded query is not improved, compared to the original one. This paper suggests the use of documents selected using Pseudo Relevance Feedback for generating association rules. Thus, an algorithm based on dominance relations is applied. Then the strong correlations between query and other terms are detected, and an oriented and weighted graph called Pseudo-Graph Feedback is constructed. This graph serves for expanding original queries by terms related semantically and selected by the user. The results of the experiments on Text Retrieval Conference (TREC) collection are very significant, and best results are achieved by the proposed approach compared to both the baseline system and an existing technique.
A novel approach to sensor implementation for healthcare systems using internet of things
Authors: Mitra Rishabh , Ganiga Raghavendra
Published: October 2019

The Internet of Things is touching all spheres of life, be it in connecting cities together, making agricultural farms and health care smarter, predictable and more secure, and in industries it is set out to bring about changes that are similar to those of the industrial revolution that took place in the 19th and 20th century. It is estimated by pundits that in next 5 to 10 years, the Internet of Things will become a 50 billion dollar industry by itself, encompassing everything that it touches and goes upon. In order to get healthcare enabled into the IoT ecosystem, the sensors and the actuators related to it must be able to support the protocols that is required for the acquisition, processing and storing of data from the sensors to the IoT based infrastructure. Here, for a proposed model for a health care monitor using Internet of Things, the sensors characteristics, working principal, the protocol associated with it, its internal mechanism, and the results obtained when interfaced using a Raspberry Pi are
discussed, laying the framework for the future of the sensors that need to be adapted to stay relevant in the future, when IoT transitions from concept to reality.
Proposal and design methodology of switching mode low dropout regulator for Bio-medical applications
Authors: Kondo Kenya , Tamura Hiroki , Tanno Koichi
Published: October 2019

The switching operation based low dropout (LDO) regulator utilizing on-off control is pre-sented. It consists of simple circuit elements which are comparator, some logic gates, switched capacitor and feedback circuit. In this study, we target the application to the power supply circuit for the analog front end (AFE) of bio-medical system (such as daily-used bio-monitoring devices) whose required maximum load current is 50 A. In this paper, the design procedure of the proposed LDO has been clarified and actual circuit design using the procedure has been done. The proposed LDO has been evaluated by SPICE simulation using 1P 2M 0.6 m CMOS process device parameters. From simulation results, we could confirm that the low quiescent current of 1 A with the output ripple of 5 mVpp. The circuit area is 0.0173 mm2 in spite of using 0.6 m design rules. The proposed circuit is suitable for adopting to the light load and low frequency applications.
Torque improvement of PM motor with semi-cycle stator design using 2D-finite element analysis
Authors: C. Kwang T. , Mohd Jamil Mohd Luqman , Jidin Auzani
Published: October 2019

This paper presents sizing approaches to improve output torque performance in PM motor when partial stator body is removed. As the output torque performance is directly proportional to the electric loading, Q, modification on stator geometry affects the output torque performance and special procedures have to be taken to restore the desired output torque capability. Influences of split ratio, tooth body width, airgap and magnet thickness of  magnet in PM motor with asymmetry stator design are carried out and the performance verification are referred to the back-emf, average output torque, torque ripple as well as cogging torque. From the investigation using 2D-Finite Element Analysis, optimum size of tooth body width and optimum number of coil turns result better output torque while other sizing approaches result no significant change as quick saturation took place.
IoT based heart monitoring and alerting system with cloud computing and managing the traffic for an ambulance in India
Authors: Bhagchandani Khushboo , Augustine D. Peter
Published: October 2019

Global Burden of Disease Report, released in Sept 2017, shows that Cardio- vascular Diseases caused 1.7 million deaths (17.8%) in 2016 and it is the leading cause of deaths in India [1]. According to the Indian Heart Association, 25% of all heart attacks happen under the age of 40. In most cases, the initial heart attacks are often ignored. Even post-diagnosis, as per government data [2], 50% of heart attack cases reach the hospital in more than 400 minutes against the ideal window time of 180 minutes; post which damage is irreversible. The delay is often attributed to delay in reaching a hospital or receiving primary aid. In India, traffic conditions also add to the grimace of the situation. Although the government is taking various measures; a holistic solution is required to minimize the delay at each of the steps like accessing the patient situation, contacting the Medical aid or making available the nearest aid possible. In this paper, we aim at providing the holistic solution using the Internet of Things technology (IOT) along with data analytics. IoT enables real-time capturing and computation of medical data from smart sensors built-in wearable devices. The amalgamation of Internet-based services with Medical Things (Smart sensors) enhance the chances of survival of patients. The proposed system analyses the inputs collected from the sensors fit with the patients prone to cardiovascular diseases to ascertain the emergency situation. In addition, to these data, the system also considers age, maximum and minimum heart rate. Based on computational results received from the input parameters, the system triggers the alert to emergency contacts such as the close relatives of the patient, doctors, the hospitals and nearby ambulance. The proposed system combines with the optimized navigation platform to guide the medical assistance to find the fastest route.
Research methods of V/F control for matrix converter use direct space vector modulation
Authors: Vasilev Bogdan , Tung Le Van
Published: October 2019

Matrix converter (MC) is direct AC to AC converter built on bidirectional switches with more outstanding advantages compared to the indirect AC - DC-AC converter such as power exchange in two directions, allowing regenerative braking performance amount returned grid. However, the modulation method for Matrix converter has the disadvantage of low voltage transmission ratio, current at the input and output current, the voltage of converter has many high-order harmonic components. The paper presents the technique of directly modulating the space vector which will improve the quality of matrix converter such as input and output currents with sine form, power factor input is nearly 1 and can be adjusted. Also, build V/F control method for matrix converter to control three-phase alternating current induction motors. Research results are tested by Matlab & Simulink software.
Estimation of object location probability for object detection using brightness feature only
Authors: Park Hyun Jun , Kim Kwang Baek
Published: October 2019

Most existing object detection methods use features such as color, shape, and contour. If there are no consistent features can be used, we need a new object detection method. Therefore, in this paper, we propose a new method for estimating the probability that an object can be located for object detection and generating an object location probability map using only brightness in a gray image. To evaluate the performance of the proposed method, we applied it to gallbladder detection. Experimental results showed 98.02% success rate for gallbladder detection in ultrasonogram. Therefore, the proposed method accurately estimates the object location probability and effectively detected gallbladder.
Optimizing PEMFC model parameters using ant lion optimizer and dragonfly algorithm: A comparative study
Authors: Isa Zainuddin Mat , Nayan Norkharziana Mohd , Arshad Mohd Hafiz , Kajaan Nor Ashbahani Mohamad
Published: October 2019

This paper introduced two optimization algorithms which are Ant Lion Optimizer (ALO) and Dragonfly Algorithm (DA) for extracting the Proton Exchange Membrane Fuel Cell (PEMFC) polarization curve parameters. The results produced by both algorithms are being compared to observe their performance. As a results, the ALO shows great performance compared to DA. Furthermore, these results also being compared with the results of the other reported metaheuristics algorithms. The ALO and DA presented competitive results.
Decentralized collaborative TTP free approach for privacy preservation in location based services
Authors: Rathod Ajaysinh Devendrasinh , Shah Saurabh , Jariwala Vivaksha J.
Published: October 2019

In recent trends, growth of location based services have been increased due to the large usage of cell phones, personal digital assistant and other devices like location based navigation, emergency services, location based social networking, location based advertisement, etc. Users are provided with important information based on location to the service provider that results the compromise with their personal information like user’s identity, location privacy etc. To achieve location privacy of the user, cryptographic technique is one of the best technique which gives assurance. Location based services are classified as Trusted Third Party (TTP) & without Trusted Third Party that uses cryptographic approaches. TTP free is one of the prominent approach in which it uses peer-to-peer model. In this approach, important users mutually connect with each other to form a network to work without the use of any person/server. There are many existing approaches in literature for privacy preserving location based services, but their solutions are at high cost or not supporting scalability.  In this paper, our aim is to propose an approach along with algorithms that will help the location based services (LBS) users to provide location privacy with minimum cost and improve scalability.
Implementation of voyage data recording device using a digital forensics-based hash algorithm
Authors: Seong Ki-Taek , Kim Gwan-Hyung
Published: October 2019

Identifying the causes of marine accidents is difficult because of problems in scene preservation, reenactment, and procuring of witnesses. Thanks to new regulations, larger vessels are now required to carry voyage data recorders (VDRs) and automatic identification systems (AISs). However, the content of these devices, which is created, stored, and managed digitally, has security vulnerabilities such as the potential for data modification. Therefore, when managing digital records it is important to guarantee reliability. To this end, we suggest a digital forensics-based digital records migration method using a hash algorithm to guarantee the integrity and authenticity of digital records.
A review on cloud based knowledge management in higher education institutions
Authors: Noor Ahmad Shukri Mohd , Younas Muhammad , Arshad Muhammad
Published: October 2019

Knowledge Management (KM) is widely discussed by researcher and attracts many enterprisers to extract, dispense and use information in a systematic way under Knowledge Management System (KMS). New technology adoption within the knowledge management system is one of the core issue, identified by researcher and underlined as future research agenda. Cloud computing becomes the most adoptable choice for enterprisers to reduce infrastructure and maintenance cost by shifting business on the cloud. Higher Education Institutions (HEIs) are more enthusiastic about knowledge management due to its primary goal of knowledge creation and sharing. Cloud based knowledge management attract higher education institutions by changing the educational method and objectives due to innovative trends in technology. This exploratory research based on literature review for cloud-based knowledge management, targeting higher education institutions. This study highlights the benefits and challenges associated with cloud-based knowledge management system and its impact on knowledge.
A performance of comparative study for semi-structured web data extraction model
Authors: Sabri Ily Amalina Ahmad , Man Mustafa
Published: October 2019

The extraction of information from multi-sources of web is an essential yet complicated step for data analysis in multiple domains. In this paper, we present a data extraction model based on visual segmentation, DOM tree and JSON approach which is known as Wrapper Extraction of Image using DOM and JSON (WEIDJ) for extracting semi-structured data from biodiversity web. The large number of information from multiple sources of web which is image’s information will be extracted using three different approach; Document Object Model (DOM), Wrapper image using Hybrid DOM and JSON (WHDJ) and Wrapper Extraction of Image using DOM and JSON (WEIDJ). Experiments were conducted on several biodiversity website. The experiment results show that WEIDJ approach promising results with respect to time analysis values. WEIDJ wrapper has successfully extracted greater than 100 images of data from the multi-source web biodiversity of over 15 different websites.
Comparative between optimization feature selection by using classifiers algorithms on spam email
Authors: Rawashdeh Ghada , Mamat Rabiei , Bakar Zuriana Binti Abu , Rahim Noor Hafhizah Abd
Published: October 2019

Spam mail has become a rising phenomenon in a world that has recently witnessed high growth in the volume of emails. This indicates the need to develop an effective spam filter. At the present time, Classification algorithms for text mining are used for the classification of emails. This paper provides a description and evaluation of the effectiveness of three popular classifiers using optimization feature selections, such as Genetic algorithm, Harmony search, practical swarm optimization, and simulating annealing. The research focuses on a comparison of the effect of classifiers using K-nearest Neighbor (KNN), Naïve Bayesian (NB), and Support Vector Machine (SVM) on spam classifiers (without using feature selection) also enhances the reliability of feature selection by proposing optimization feature selection to reduce number of features that are not important.
Assessing the intelligence of a student through TIC-TAC-TOE game for career guidance
Authors: Jammalamadaka Sastry Kodanda Rama , Vudatha Chandra Prakash
Published: October 2019

In order to provide Career Guidance by an expert system to a student, apart from his/her academic record, it is necessary to assess various psychological factors of the student like Intelligence, patience and perseverance, Learning ability and Speed of solving problem, etc. The outcome of this research work is an expert system called Tic-Tac-Toe Game Playing Career Guidance System (TTT-GP-CGS) that is useful to assess the psychological factors of the student through Tic-Tac-Toe Game Playing, build the cognitive model of the student and predict the appropriate career(s) for the student. The system plays Tic-Tac-Toe game with the student several times. The average score obtained by the student reflects his/her intelligence. The average time taken by the student for playing the game reflects student's speed of solving problem. The number of attempts the student makes reflects the students patience and perseverance. When the student plays the game with the spaystem every day, if the student's  score increases day by day, it reflects that the student has good learning ability. In this way the system will assess the psychological factors of the student and builds the cognitive model of the student. Internally the system converts the quantitative scores into qualitative scores. The system maintains a table of careers and the expected levels of psychological factors that are required from student's side to carry out the career successfully. The system invokes a matching process  by considering the cognitive model of the student and the table of careers, and predicts the career(s) suitable  to the student.
Retinex theory for color image enhancement: A systematic review
Authors: Hussein Ruaa Riyadh , Hamodi Yaser Issam , Sabri Rooa Adnan
Published: October 2019

A short but comprehensive review of Retinex has been presented in this paper. Retinex theory aims to explain human color perception. In addition, its derivation on modifying the reflectance components has introduced effective approaches for images contrast enhancement. In this review, the classical theory of Retinex has been covered. Moreover, advance and improved techniques of Retinex, proposed in the literature, have been addressed. Strength and weakness aspects of each technique are discussed and compared. An optimum parameter is needed to be determined to define the image degradation level. Such parameter determination would help in quantifying the amount of adjustment in the Retinex theory. Thus, a robust framework to modify the reflectance component of the Retinex theory can be developed to enhance the overall quality of color images.
Afastamento laboral de gestantes aeronautas no Brasil
Authors: Oliveira Maria Carolina Barra de , Gianvecchio Daniele Muñoz , Gianvecchio Víctor , Muñoz Daniel
Published: October 2019

Resumo: Restrições médicas ao trabalho das mulheres aeronautas no período gestacional são estabelecidas no mundo todo. No Brasil, mudanças recentes na avaliação médico pericial dessas profissionais geraram conflitos entre as partes envolvidas e colocaram o assunto em voga. O presente estudo tem por finalidade apresentar o cenário atual que envolve o afastamento laboral das gestantes aeronautas no Brasil. Desenvolvimento:   Os aeronautas no Brasil possuem uma regulamentação própria desenvolvida pela Agência Nacional da Aviação Civil (ANAC) que considera como inapta a gestante a partir do momento do diagnóstico da gravidez. Esta legislação era levada em conta nas perícias realizadas pelas Juntas Mistas do Instituto Nacional do Seguro Social (INSS), que deferiam benefício auxílio-doença nesses casos. Contudo, a partir de maio de 2017 esses profissionais passaram a ser avaliados como os demais segurados do Regime Geral de Previdência Social (RGPS), e, por isso, as gestantes começaram a ter seus benefícios indeferidos, ficando no chamado limbo trabalhista previdenciário. Após decisão judicial emitida em novembro de 2017, esta situação foi modificada e os mesmos pedidos voltaram a ser deferidos, mas agora somente com avaliação documental administrativa, ou seja, sem realização de perícia médica. Conclusão: Existe uma divergência entre as leis que regulamentam a aviação e as que regem a Previdência Social resolvida, até o momento, por decisão judicial após reivindicação do sindicato, a qual deferiu o pagamento de auxílio-doença por incapacidade para essas profissionais de forma administrativa, algo até então sem precedentes.
A elaboração do relatório pericial de avaliação de prática médica no âmbito do Direito Civil
Authors: Leal Lucas
Published: October 2019

No âmbito do Direito Civil, em casos que envolvem discussão sobre a assistência à saúde e se pleiteia indenização por danos, a prova pericial é essencialmente médica. O laudo técnico deve ser completo e fazer compreender a situação real do indivíduo. A função do perito é saber dar resposta ao objeto da perícia, procurando traduzir a complexidade da avaliação técnica em um conjunto de conclusões fundamentadas. É fundamental, na prática pericial, que se conheçam conceitos médico-legais bastante úteis para a elaboração de relatório médico bem circunstanciado. O fornecimento adequado à autoridade competente de esclarecimentos sobre o caso em tela, com base em conhecimentos científicos e sopesando-se aspectos jurídicos, é responsável pela formação do convencimento do magistrado, contribuindo para que se faça Justiça.
Distributed Patterns of Functional Connectivity Predict Working Memory Performance in Novel Healthy and Memory-impaired Individuals
Authors: Avery Emily W. , Yoo Kwangsun , Rosenberg Monica D. , Greene Abigail S. , Gao Siyuan , Na Duk L. , Scheinost Dustin , Constable Todd R. , Chun Marvin M.
Published: October 2019

Individual differences in working memory relate to performance differences in general cognitive ability. The neural bases of such individual differences, however, remain poorly understood. Here, using a data-driven technique known as connectome-based predictive modeling, we built models to predict individual working memory performance from whole-brain functional connectivity patterns. Using n-back or rest data from the Human Connectome Project, connectome-based predictive models significantly predicted novel individuals' 2-back accuracy. Model predictions also correlated with measures of fluid intelligence and, with less strength, sustained attention. Separate fluid intelligence models predicted working memory score, as did sustained attention models, again with less strength. Anatomical feature analysis revealed significant overlap between working memory and fluid intelligence models, particularly in utilization of prefrontal and parietal regions, and less overlap in predictive features between working memory and sustained attention models. Furthermore, showing the generality of these models, the working memory model developed from Human Connectome Project data generalized to predict memory in an independent data set of 157 older adults (mean age = 69 years; 48 healthy, 54 amnestic mild cognitive impairment, 55 Alzheimer disease). The present results demonstrate that distributed functional connectivity patterns predict individual variation in working memory capability across the adult life span, correlating with constructs including fluid intelligence and sustained attention.
The Human Medial Temporal Lobe Is Necessary for Remembering Durations within a Sequence of Events but Not Durations of Individual Events
Authors: Palombo Daniela J. , Reid Allison G. , Thavabalasingam Sathesan , Hunsberger Renée , Lee Andy C. H. , Verfaellie Mieke
Published: October 2019

Recent interest in the role of the hippocampus in temporal aspects of cognition has been fueled, in part, by the observation of “time” cells in the rodent hippocampus—that is, cells that have differential firing patterns depending on how long ago an event occurred. Such cells are thought to provide an internal representation of elapsed time. Yet, the hippocampus is not needed for processing temporal duration information per se, at least on the order of seconds, as evidenced by intact duration judgments in rodents and humans with hippocampal damage. Rather, it has been proposed that the hippocampus may be essential for coding higher order aspects of temporal mnemonic processing, such as those needed to temporally organize a sequence of events that form an episode. To examine whether (1) the hippocampus uses duration information in the service of establishing temporal relations among events and (2) its role in memory for duration is unique to sequences, we tested amnesic patients with medial-temporal lobe damage (including the hippocampus). We hypothesized that medial-temporal lobe damage should impair the ability to remember sequential duration information but leave intact judgments about duration devoid of a sequential demand. We found that amnesics were impaired in making judgments about durations within a sequence but not in judging single durations. This impairment was not due to higher cognitive load associated with duration judgments about sequences. In convergence with rodent and human fMRI work, these findings shed light on how time coding in the hippocampus may contribute to temporal cognition.
Perception of Rhythmic Speech Is Modulated by Focal Bilateral Transcranial Alternating Current Stimulation
Authors: Zoefel Benedikt , Allard Isobella , Anil Megha , Davis Matthew H.
Published: October 2019

Several recent studies have used transcranial alternating current stimulation (tACS) to demonstrate a causal role of neural oscillatory activity in speech processing. In particular, it has been shown that the ability to understand speech in a multi-speaker scenario or background noise depends on the timing of speech presentation relative to simultaneously applied tACS. However, it is possible that tACS did not change actual speech perception but rather auditory stream segregation. In this study, we tested whether the phase relation between tACS and the rhythm of degraded words, presented in silence, modulates word report accuracy. We found strong evidence for a tACS-induced modulation of speech perception, but only if the stimulation was applied bilaterally using ring electrodes (not for unilateral left hemisphere stimulation with square electrodes). These results were only obtained when data were analyzed using a statistical approach that was identified as optimal in a previous simulation study. The effect was driven by a phasic disruption of word report scores. Our results suggest a causal role of neural entrainment for speech perception and emphasize the importance of optimizing stimulation protocols and statistical approaches for brain stimulation research.
Scale-invariant Characteristics of Forgetting: Toward a Unifying Account of Hippocampal Forgetting across Short and Long Timescales
Authors: Sadeh Talya , Pertzov Yoni
Published: October 2019

After over 100 years of relative silence in the cognitive literature, recent advances in the study of the neural underpinnings of memory—specifically, the hippocampus—have led to a resurgence of interest in the topic of forgetting. This review draws a theoretically driven picture of the effects of time on forgetting of hippocampus-dependent memories. We review evidence indicating that time-dependent forgetting across short and long timescales is reflected in progressive degradation of hippocampal-dependent relational information. This evidence provides an important extension to a growing body of research accumulated in recent years, showing that—in contrast to the once prevailing view that the hippocampus is exclusively involved in memory and forgetting over long timescales—the role of the hippocampus also extends to memory and forgetting over short timescales. Thus, we maintain that similar rules govern not only remembering but also forgetting of hippocampus-dependent information over short and long timescales.
Chamaecrista pauciflora (Fabaceae) a new species from the lowlands of the state of Tocantins, Brazil

Authors: MATOS RAMON GUEDES , SOUZA ALESSANDRO OLIVEIRA , SILVA MARCOS JOSÉ DA
Published: October 2019

Taxonomic studies in the genus Chamaecrista based on botanical collections from its endemic area, detailed analysis of our own collections and of herbaria, and in specialized literature enabled the discovery of a new species in the State of Tocantins, Brazil. The new species Chamaecrista pauciflora is herein described, illustrated, assigned to Chamaecrista sect. Absus subsect. Absus ser. Rigidulae and compared with C. azulana and C. filicifolia. The geographical distribution, conservation status, period of flowering and fruiting, morphological relationships, and environmental preferences of the new species are also provided. Additionally, a key to the species of Chamaecrista ser. Rigidulae occurring in Tocantins is presented.
Stachytarpheta kriegeriana (Verbenaceae), a new species from São Paulo State, Brazil

Authors: CARDOSO PEDRO HENRIQUE , MENINI NETO LUIZ , BERNACCI LUÍS CARLOS , SALIMENA FÁTIMA REGINA GONÇALVES
Published: October 2019

Stachytarpheta kriegeriana, a new species of Verbenaceae exclusively known from the type specimens collected at the municipality of Monte Alto, São Paulo state, is here described and illustrated. The new species is similar to S. hirsutissima due to its densely hirsute indumentum, but can be differentiated by its leaves and bracts morphology, and by the bract/calyx ratio. Stachytarpheta kriegeriana belongs to the informal group “Cayennensis” due to its inflorescences up to 6 mm wide and its calyx embedded in the rachis excavations. An identification key for the species within the “Cayennensis” group is provided, together with a map highlighting the collection site, habitat information, illustration, and conservation assessment for the new species.
Agave garciaruizii (Asparagaceae) a new species from the Chorros del Varal State Reserve in western Mexico

Authors: HERNÁNDEZ-VERA GERARDO , VÁZQUEZ-GARCÍA J. ANTONIO , PADILLA-LEPE JESÚS , NIEVES-HERNÁNDEZ GREGORIO
Published: October 2019

A new species named Agave garciaruizii is described and illustrated here. A. garciaruizii is endemic to tropical dry forest in the Itzícuaro and Apupátaro river canyons in the Chorros del Varal State Reserve, at the southern border of the states of Jalisco and Michoacán, México. It belongs to the subgenus Littaea and to the Marginatae species group and is morphologically related to A. angustiarum and A. impressa, but differs from these species in some features of leaves, inflorescences and infructescences. Its conservation status was assessed as Endangered (EN). Additionally, morphological evidence was provided in support of A. arcedianoensis as a species distinct from A. angustiarum. A key to morphologically and geographically closely related species in the Marginatae group is presented.
Nomenclatural and taxonomic notes on Carex lazarei nom. nov. (Cyperaceae)

Authors: KOOPMAN JACOB , NIKETIĆ MARJAN , WIĘCŁAW HELENA , GOVAERTS RAFAËL
Published: October 2019

Carex bulgarica (Domin) Lazare 1986 is a younger homonym of C. bulgarica Velen. 1889, the latter being validly published as an alternative name along with C. digitata var. bulgarica Velen. Therefore we publish here a replacement name, Carex lazarei, for the species previously called C. bulgarica by Lazare. Carex lazarei belongs to the C. sempervirens Vill. complex and its occurrence  is restricted to acidophilous habitats of the Balkan mountains. Although it is often regarded as conspecific with C. sempervirens, we are of the view that this entity needs the status of species. A type specimen is designated here as the second-step lectotype of the name C. sempervirens var. bulgarica Domin.
The first record of Euthiconus Reitter in Japan, with comparative notes on remaining Palaearctic species (Coleoptera, Staphylinidae, Scydmaeninae)
Authors: JAŁOSZYŃSKI PAWEŁ
Published: October 2019

Two species of Euthiconus Reitter were previously known to occur in the Palaearctic region, distributed in Europe (E. conicicollis (Fairmaire & Laboulbène)) and in the Russian Far East (E. lustrificus Kurbatov). A description of the first Japanese species, Euthiconus nopporoensis sp. n., is given, based on specimens collected on Hokkaido. The new species shares with E. lustrificus unmodified male protrochanters and a similar shape of the pronotum; it differs in a bottle-shaped aedeagus, sparser setae on the pronotum, and a shorter antennomere III. Key morphological structures of all Palaearctic species of Euthiconus are illustrated, to facilitate identifications.
Araneibatrus phuphaphet sp. nov., a new cavernicolous Pselaphinae from Satun Geopark, southern Thailand (Coleoptera: Staphylinidae: Pselaphinae)
Authors: YIN ZI-WEI , JANTARIT SOPARK
Published: October 2019

A new cavernicolous species of the genus Araneibatrus Yin & Li, 2010, A. phuphaphet sp. nov., is described from Phu Pha Phet Cave, Satun Province, southern Thailand. The discovery extends the known distributional range of Araneibatrus for more than 1,500 km southwards. The conspicuously spinose pronotum, sexually modified profemur of the male, and unique configuration of the aedeagus serve to readily separate the new species from all known congeners.
Variability of the Stratospheric Quasi-Biennial Oscillation and Its Wave Forcing Simulated in the Beijing Climate Center Atmospheric General Circulation Model
Authors: Lu Yixiong , Wu Tongwen , Jie Weihua , Scaife Adam A. , Andrews Martin B. , Richter Jadwiga H.
Published: October 2019

It is well known that the stratospheric quasi-biennial oscillation (QBO) is forced by equatorial waves with different horizontal/vertical scales, including Kelvin waves, mixed Rossby–gravity (MRG) waves, inertial gravity waves (GWs), and mesoscale GWs, but the relative contribution of each wave is currently not very clear. Proper representation of these waves is critical to the simulation of the QBO in general circulation models (GCMs). In this study, the vertical resolution in the Beijing Climate Center Atmospheric General Circulation Model (BCC-AGCM) is increased to better represent large-scale waves, and a mesoscale GW parameterization scheme, which is coupled to the convective sources, is implemented to provide unresolved wave forcing of the QBO. Results show that BCC-AGCM can spontaneously generate the QBO with realistic periods, amplitudes, and asymmetric features between westerly and easterly phases. There are significant spatiotemporal variations of parameterized convective GWs, largely contributing to a great degree of variability in the simulated QBO. In the eastward wind shear of the QBO at 20 hPa, forcing provided by resolved waves is 0.1–0.2 m s−1 day−1 and forcing provided by parameterized GWs is ~0.15 m s−1 day−1. On the other hand, westward forcings by resolved waves and parameterized GWs are ~0.1 and 0.4–0.5 m s−1 day−1, respectively. It is inferred that the eastward forcing of the QBO is provided by both Kelvin waves and mesoscale convective GWs, whereas the westward forcing is largely provided by mesoscale GWs. MRG waves barely contribute to the formation of the QBO in the model.
Sexual Objectification, Internalization, and College Women’s Depression: The Role of Shame
Authors: Szymanski Dawn M.
Published: October 2019

This study examined potential mediators, a moderator, and a moderated mediation of the link between sexual objectification experiences and depression among 489 young adult college women. Findings from the mediation analyses revealed that sexual objectification was directly and indirectly related to depression via greater body surveillance and self-blame. Shame moderated the direct effect of sexual objectification on body surveillance. Sexual objectification predicted body surveillance for women with low but not high or moderate levels of shame. Shame also moderated the direct effect of sexual objectification on self-blame and provided support for moderated mediation via conditional process analyses. Sexual objectification predicted self-blame for women with high and moderate but not low levels of shame. The findings underscore the importance of attending to experiences of objectification when working with women clients presenting with depression and to help them lessen habitual body monitoring, blaming themselves for being sexually objectified, and feelings of shame.