bluuebunny/crossref_metadata_2025 huggingface dataset:
Fonoaudiólogos Egresados de una Universidad Pública Colombiana: Calidad del empleo
Authors: Castaño Rodríguez María Del Mar , Satizabal Reyes Melania
Published: April 2019

Las nuevas tendencias del mercado laboral se caracterizan por la incertidumbre, la precarización y la flexibilización del empleo; por su parte, las investigaciones sobre las condiciones laborales de los fonoaudiólogos son escasas. En este artículo se presenta un estudio que tuvo como objetivo describir la calidad del empleo de los egresados del 2010 al 2013 del Programa Académico de Fonoaudiología de la Universidad del Valle. Metodológicamente, se adoptó un enfoque cuantitativo, con una temporalidad transversal y un alcance descriptivo; se realizó un censo a una población definitiva de 99 egresados. Como resultados principales de la investigación se encontró que el 97% de la población se encuentra trabajando, un tercio de los egresados se desempeña en empleos con contratos a término indefinido y con garantías en términos de protección social, mientras el resto de los fonoaudiólogos tiene empleos que presentan características de trabajo flexible como el pluriempleo (42,4%), contratos bajo la modalidad de prestación de servicios (43,4%), jornadas laborales por debajo de las 48 horas semanales y pocas posibilidades de ascenso en los lugares de trabajo (43,4%). Con la investigación se identificaron oportunidades laborales para los egresados, sin embargo, en cuanto a la calidad, se encontró una diversidad de condiciones, en menor proporción egresados con empleos que les garantizan estabilidad laboral y en mayor proporción empleos con características de flexibilidad laboral que pueden conllevar a la instalación de condiciones de precariedad laboral y detrimento de la calidad de vida del trabajador.
Rehabilitación fisiológica de la voz: Terapia de resistencia en el agua
Authors: Manzano Aquiahuatl Carlos
Published: April 2019

La terapia de resistencia en el agua forma parte  del grupo de ejercicios de tracto vocal semiocluido que corresponden a la tendencia fisiológica de la rehabilitación vocal.  La  terapia de resistencia en el agua implica una constricción o alargamiento artificial del tracto vocal a través de popotes (pajitas) de uso comercial  o diferentes dispositivos como tubo finlandés, Lax Vox®, Doctor Vox®, Mask Vox®  y Pocket Vox® .  Los beneficios  acústicos, aerodinámicos y biomecánicos de la terapia de resistencia en el agua son producidos por el equilibrio obtenido entre la fonación, resonancia y respiración. El objetivo principal de la terapia de resistencia en el agua  no es el dispositivo ni el método; es  la obtención de una máxima economía vocal mediante el desarrollo de un aprendizaje sensoriomotor para la generación de un patrón vocal adecuado.
Vocología: Disciplina con potencialidad
Authors: Angel G. Luisa Fernanda
Published: April 2019

Editorial
Terapia vocal de cantantes: una reflexión sobre la práctica
Authors: Amin Elisabeth
Published: April 2019

Este artículo se destina a la reflexión sobre las habilidades y conocimientos necesarios para el trabajo del fonoaudiólogo interesado en terapia vocal para cantantes, que aquí denominamos “terapia de las delicadezas”. Desde el eje de la indagación sobre qué habita el espacio existente entre terapeuta y paciente, se discute que la comprensión de las complejas relaciones entre el cerebro y la laringe, entre el cuerpo y la voz, el comportamiento de la musculatura respiratoria, la fisiología vocal involucrada en los distintos estilos de canto es solo una pequeña parte del conocimiento necesario para el terapeuta que busca actuar en este campo. Esto es relevante porque son muchas las variables existentes en un problema que presenta un cantante o un actor, problema este que puede o no estar relacionado a su técnica artística. La discusión que plantea este texto es fruto de la sistematización del trabajo de habilitación y rehabilitación de cantantes y actores en la ciudad de São Paulo (Brasil), que viene siendo desarrollado hace 30 años. Constatamos que conocer el universo vocal de la voz cantada a través de la propia vivencia con el canto puede ayudar al terapeuta a tener más intimidad con su voz y así facilitar que se entable una relación de confianza con el paciente. Palabras clave: canto; voz; trastornos de la voz; entrenamiento de voz; laringe
The 3D Spatial Autocorrelation of the Branching Fractal Vasculature
Authors: Parker Kevin , Carroll-Nellenback Jonathan , Wood Ronald
Published: April 2019

The fractal branching vasculature within soft tissues and the mathematical properties of the branching system influence a wide range of important phenomena from blood velocity to ultrasound backscatter. Among the mathematical descriptors of branching networks, the spatial autocorrelation function plays an important role in statistical measures of the tissue and of wave propagation through the tissue. However, there are open questions about analytic models of the 3D autocorrelation function for the branching vasculature and few experimental validations for soft vascularized tissue. To address this, high resolution computed tomography scans of a highly vascularized placenta perfused with radiopaque contrast through the umbilical artery were examined. The spatial autocorrelation function was found to be consistent with a power law, which then, in theory, predicts the specific power law behavior of other related functions, including the backscatter of ultrasound.
Polymyxins: To Combine or Not to Combine?
Authors: Perez Federico , El Chakhtoura Nadim G. , Yasmin Mohamad , Bonomo Robert A.
Published: April 2019

Polymyxins have been a mainstay for the treatment of extensively drug resistant (XDR) Gram-negative bacteria for the past two decades. Many questions regarding the clinical use of polymyxins have been answered, but whether the administration of polymyxins in combination with other antibiotics leads to better outcomes remains unknown. This review discusses the limitations of observational studies that suggest a benefit of combinations of colistin and carbapenems to treat infections caused by carbapenem-resistant Enterobacteriaceae (CRE), especially Klebsiella pneumoniae carbapenemase (KPC)-producing K. pneumoniae, and summarizes the results of randomized controlled trials in which treatment with colistin in combination with meropenem or rifampin does not lead to better clinical outcomes than colisitn monotherapy in infections caused by carbapenem-resistant Acinetobacter baumannii (CRAB). Although the introduction of new antibiotics makes it possible to treat certain strains of CRE and carbapenem-resistant P. aeruginosa (CRPA) with polymyxin-sparing regimens, the use of polymyxins is, for now, still necessary in CRAB and in CRE and CRPA harboring metallo-beta-lactamases. Therefore, strategies must be developed to optimize polymyxin-based treatments, informed by in vitro hollow fiber models, careful clinical observations, and high-quality evidence from appropriately designed trials.
Review of VSG Control-Enabled Universal Compatibility Architecture for Future Power Systems with High-Penetration Renewable Generation
Authors: Yan Xiangwu , Zhang Weichao
Published: April 2019

Due to the irreversible energy substitution from fossil fuels to clean energy, the development trend of future power systems is based on renewable energy generation. However, due to the incompatibility of converter-based non-dispatchable renewable energy generation, the stability and reliability of traditional power systems deteriorate as more renewables are introduced. Since conventional power systems are dominated by synchronous machines (SM), it is natural to utilize a virtual synchronous generator (VSG) control strategy that intimates SM characteristics on integrated converters. The VSG algorithm developed in this paper originates from mimicking mathematic models of synchronous machines. Among the different models of implementation, the second-order model is simple, stable, and compatible with the control schemes of current converters in traditional power systems. The VSG control strategy is thoroughly researched and case studied for various converter-interfaced systems that include renewable generation, energy storage, electric vehicles (EV), and other energy demands. VSG-based integration converters can provide grid services such as spinning reserves and inertia emulation to the upper grids of centralized plants, distributed generation networks, and microgrids. Thus, the VSG control strategy has paved a feasible way for an evolutionary transition to a power electronics-based future power grid. By referring to the knowledge of traditional grids, a hierarchical system of operations can be established. Finally, generation and loads can be united in universal compatibility architecture under consolidated synchronous mechanisms.
Performance of Warm-Mixed Flame Retardant Modified Asphalt Binder
Authors: Li Ruixia , Zhang Kaiwei , Wu Jiahui , Liu Wenjuan
Published: April 2019

In order to analyze the effect of flame retardant and warm mix asphalt (WMA) additives-Sasobit on the flame-retardant performance and pavement performance of asphalt binder, the limiting oxygen index test, conventional performance test, and Superpave evaluation index tests were performed on asphalt binders in the study. The test results show that flame retardant can effectively improve the flame resistance of asphalt binder, while Sasobit has a certain combustion-supporting effect. Therefore, when warm-mixed flame-retardant technology is applied, the concentration of Sasobit should be controlled appropriately. These two modifiers can significantly enhance the high-temperature performance of asphalt binder, but both of them have a slight negative influence on the low-temperature cracking resistance. Sasobit can substantially reduce the high-temperature viscosity of asphalt binder, which helps to improve the construction workability of asphalt binder, while the flame retardant adversely affects the viscosity reduction effect of Sasobit to a certain extent, but the overall impact is not large.
Mechanical Behaviour of TRC Composites: Experimental and Analytical Approaches
Authors: Rampini Marco Carlo , Zani Giulio , Colombo Matteo , di Prisco Marco
Published: April 2019

Textile reinforced concrete (TRC) is a promising high-performance material that has been employed with success in new constructions, as well as a strengthening layer of existing structural components. In this work, we document the optimisation procedure of textile-based composites for new construction and for the seismic retrofitting of under-reinforced concrete elements and masonry buildings. The study, aimed at maximising the material performances avoiding waste of economic resources, was addressed by means of a series of uniaxial tensile tests conducted on a wide set of alkali-resistant (AR) glass fabrics and TRCs. The samples differed in terms of cement-based matrices, embedded textiles and addition of dispersed microfibers. The results highlight the effects of fabric characteristics and introduction of short fibres on the mechanical behaviour, proposing novel comparison parameters based upon the load bearing capacity and the deformation response of the composites. The application of simplified analytical models borrowed from the literature finally revealed the limitations of the available predictive approaches, suggesting future lines of investigation.
An Accuracy-Efficiency-Power Consumption Hybrid Optimization Method for CNC Milling Process
Authors: Wang Shih-Ming , Lee Chun-Yi , Gunawan Hariyanto , Yeh Chin-Cheng
Published: April 2019

This study proposes a hybrid optimization method which can help users to find optimal cutting parameters which will provide better efficiency and lower power consumption for a milling process. Empirical models including performance-power consumption characteristic curves of servo motors were built, and an optimization algorithm adopting the empirical models with procedure guiding function was developed. The empirical models were built based on the measurements from planned machining experiments with different combination of machining parameters including spindle speed, feedrate, and chip load, etc. After integrating the models and algorithm, an optimization system with human machine interface, which has procedure guiding function, was developed. The system can recommend optimal machining parameters for a milling process for shorter machining time and lower electricity costs based on the original machining parameters. Finally, cutting experiments were conducted to verify the proposed system, and the results showed that the proposed method can effectively enhance efficiency by 42.06% and save 34.74% in machining costs through reducing machining time and electrical power consumption.
Pruning Fuzzy Neural Network Applied to the Construction of Expert Systems to Aid in the Diagnosis of the Treatment of Cryotherapy and Immunotherapy
Authors: Junio Guimarães Augusto , Vitor de Campos Souza Paulo , Jonathan Silva Araújo Vinícius , Silva Rezende Thiago , Souza Araújo Vanessa
Published: April 2019

Human papillomavirus (HPV) infection is related to frequent cases of cervical cancer and genital condyloma in humans. Up to now, numerous methods have come into existence for the prevention and treatment of this disease. In this context, this paper aims to help predict the susceptibility of the patient to forms treatment using both cryotherapy and immunotherapy. These studies facilitate the choice of medications, which can be painful and embarrassing for patients who have warts on intimate parts. However, the use of intelligent models generates efficient results but does not allow a better interpretation of the results. To solve the problem, we present the method of a fuzzy neural network (FNN). A hybrid model capable of solving complex problems and extracting knowledge from the database will pruned through F-score techniques to perform pattern classification in the treatment of warts, and to produce a specialist system based on if/then rules, according to the experience obtained from the database collected through medical research. Finally, binary pattern-classification tests realized in the FNN and compared with other models commonly used for classification tasks capture results of greater accuracy than the current state of the art for this type of problem (84.32% for immunotherapy, and 88.64% for cryotherapy), and extract fuzzy rules from the problem database. It was found that the hybrid approach based on neural networks and fuzzy systems can be an excellent tool to aid the prediction of cryotherapy and immunotherapy treatments.
Impact of DARC rs12075 Variants on Liver Fibrosis Progression in Patients with Chronic Hepatitis C: A Retrospective Study
Authors: Jiménez-Sousa María Ángeles , Gómez-Moreno Ana Zaida , Pineda-Tenor Daniel , Sánchez-Ruano Juan José , Artaza-Varasa Tomas , Martin-Vicente María , Fernández-Rodríguez Amanda , Martínez Isidoro , Resino Salvador
Published: April 2019

The Duffy antigen receptor for chemokines (DARC) rs12075 polymorphism regulates leukocyte trafficking and proinflammatory chemokine homeostasis. Hepatitis C virus (HCV)-mediated liver fibrosis is associated with an uncontrolled inflammatory response. In this study, we evaluate the association between the DARC rs12075 polymorphism and liver stiffness progression in HCV-infected patients. We carried out a retrospective cohort study (repeated measures design) in 208 noncirrhotic patients with chronic hepatitis C (CHC) who had at least two liver stiffness measurements (LSM) with a separation of at least 12 months. We used generalized linear models to analyze the association between DARC rs12075 polymorphism and outcome variables. During a follow-up of 46.6 months, the percentage of patients with stages of fibrosis F0/F1 decreased (p < 0.001), while LSM values and the percentage of patients with cirrhosis increased (p < 0.001). This pattern of changes was maintained in each of the groups of patients analyzed according to their rs12075 genotypes (AA or AG/GG). However, the variations in liver stiffness characteristics were lower in patients with the rs12075 AG/GG genotype (AG/GG versus AA). Thereby, in the adjusted analysis, patients with the rs12075 AG/GG genotype had a lower risk of an increased value of LSM2/LSM1 arithmetic mean ratio (AMR = 0.83; p = 0.001) and of an increase in LSM ≥ 5 kPa (odds ratio (OR) = 0.28; p = 0.009). Besides, patients with rs12075 AG/GG had a lower risk of cirrhosis progression (OR = 0.24; p = 0.009). No significant associations were found for an increase in LSM ≥ 10 kPa. We found an association between the DARC rs12075 single nucleotide polymorphism (SNP) and CHC progression. Specifically, patients with the DARC rs12075 AG/GG genotype had a lower risk of liver fibrosis progression and development of cirrhosis.
Host-Microbiome Synergistic Control on Sphingolipid Metabolism by Mechanotransduction in Model Arthritis
Authors: Zhou Xiaoyuan , Devescovi Valentina , Liu Yuanhua , Dent Jennifer E. , Nardini Christine
Published: April 2019

Chronic inflammatory autoimmune disorders are systemic diseases with increasing incidence and still lack a cure. More recently, attention has been placed in understanding gastrointestinal (GI) dysbiosis and, although important progress has been made in this area, it is currently unclear to what extent microbiome manipulation can be used in the treatment of autoimmune disorders. Via the use of appropriate models, rheumatoid arthritis (RA), a well-known exemplar of such pathologies, can be exploited to shed light on the currently overlooked effects of existing therapies on the GI microbiome. In this direction, we here explore the crosstalk between the GI microbiome and the host immunity in model arthritis (collagen induced arthritis, CIA). By exploiting omics from samples of limited invasiveness (blood and stools), we assess the host-microbiome responses to standard therapy (methotrexate, MTX) combined with mechanical subcutaneous stimulation (MS) and to mechanical stimulation alone. When MS is involved, results reveal the sphingolipid metabolism as the trait d’union among known hallmarks of (model) RA, namely: Imbalance in the S1P-S1PR1 axis, expansion of Prevotella sp., and invariant Natural Killer T (iNKT)-penia, thus offering the base of a rationale to mechanically modulate this pathway as a therapeutic target in RA.
NMDA Receptor-Mediated Signaling Pathways Enhance Radiation Resistance, Survival and Migration in Glioblastoma Cells—A Potential Target for Adjuvant Radiotherapy
Authors: Müller-Längle Adriana , Lutz Henrik , Hehlgans Stephanie , Rödel Franz , Rau Kerstin , Laube Bodo
Published: April 2019

Glioblastoma is one of the most aggressive malignant brain tumors, with a survival time less than 15 months and characterized by a high radioresistance and the property of infiltrating the brain. Recent data indicate that the malignancy of glioblastomas depends on glutamatergic signaling via ionotropic glutamate receptors. In this study we revealed functional expression of Ca2+-permeable NMDARs in three glioblastoma cell lines. Therefore, we investigated the impact of this receptor on cell survival, migration and DNA double-strand break (DSB) repair in the presence of both, glutamate and NMDAR antagonists, and after clinically relevant doses of ionizing radiation. Our results indicate that treatment with NMDAR antagonists slowed the growth and migration of glutamate-releasing LN229 cells, suggesting that activation of NMDARs facilitate tumor expansion. Furthermore, we found that DSB-repair upon radiation was more effective in the presence of glutamate. In contrast, antagonizing the NMDAR or the Ca2+-dependent transcription factor CREB impaired DSB-repair similarly and resulted in a radiosensitizing effect in LN229 and U-87MG cells, indicating a common link between NMDAR signaling and CREB activity in glioblastoma. Since the FDA-approved NMDAR antagonists memantine and ifenprodil showed differential radiosensitizing effects, these compounds may constitute novel optimizations for therapeutic interventions in glioblastoma.
Treatment of a Malignant Soft Tissue Tumor Arising in the Vicinity of the Sciatic Nerve with an In-Situ Preparation Technique and Intensive Multidisciplinary Therapy
Authors: Aiba Hisaki , Hayashi Katsuhiro , Yamada Satoshi , Okamoto Hideki , Kimura Hiroaki , Miwa Shinji , Inatani Hiroyuki , Otsuka Takanobu , Murakami Hideki
Published: April 2019

Preservation of the sciatic nerve is difficult in cases of highly malignant soft tissuetumors closely surrounding the nerve. Herein, we present the first case of preservation of thisnerve by combining an in-situ preparation technique (ISP; a technique enabling the preparation ofneurovascular bundles without contamination by tumor cells) with intensive concurrent neoadjuvantchemo-radiotherapy with hyperthermia (RHC; radio-hyperthermo-chemotherapy). A 62-year-oldman presented with a soft tissue mass in the right thigh and was diagnosed with undifferentiatedpleomorphic sarcoma. The tumor arose in the multi-compartment areas of the posterior thigh musclesand was closely intertwined with the sciatic nerve. As preoperative therapy, RHC was performedfor surgical down-staging and the tumor partially responded. Afterwards, wide resection of thetumor with preservation of the sciatic nerve using ISP was performed. Following the surgery, therehas not been recurrence in the affected site and the functional outcomes of the lower extremityachieved 80% in the Musculoskeletal Tumor Society score. The patient is still alive with disease fiveyears postoperatively. This is the first case in which ISP and RHC procedures were combined forthe preservation of the neurovascular structure. Further study is needed for the validation of thefeasibility of this method.
Cancer Pain Assessment and Classification
Authors: Caraceni Augusto , Shkodra Morena
Published: April 2019

More than half of patients affected by cancer experience pain of moderate-to-severe intensity, often in multiple sites, and of different etiologies and underlying mechanisms. The heterogeneity of pain mechanisms is expressed with the fluctuating nature of cancer pain intensity and clinical characteristics. Traditional ways of classifying pain in the cancer population include distinguishing pain etiology, clinical characteristics related to pain and the patient, pathophysiology, and the use of already validated classification systems. Concepts like breakthrough, nociceptive, neuropathic, and mixed pain are very important in the assessment of pain in this population of patients. When dealing with patients affected by cancer pain it is also very important to be familiar to the characteristics of specific pain syndromes that are usually encountered. In this article we review methods presently applied for classifying cancer pain highlighting the importance of an accurate clinical evaluation in providing adequate analgesia to patients.
Statins Do Not Directly Inhibit the Activity of Major Epigenetic Modifying Enzymes
Authors: Bridgeman Stephanie , Northrop Wendy , Ellison Gaewyn , Sabapathy Thiru , Melton Phillip , Newsholme Philip , Mamotte Cyril
Published: April 2019

The potential anticancer effects of statins—a widely used class of cholesterol lowering drugs—has generated significant interest, as has the use of epigenetic modifying drugs such as HDAC and DNMT inhibitors. We set out to investigate the effect of statin drugs on epigenetic modifications in multiple cell lines, including hepatocellular carcinoma, breast carcinoma, leukemic macrophages, cervical adenocarcinoma, and insulin-secreting cells, as well as liver extracts from statin-treated C57B1/6J mice. Cells or cell extracts were treated with statins and with established epigenetic modulators, and HDAC, HAT, and DNMT activities were quantified. We also examined histone acetylation by immunoblotting. Statins altered neither HDAC nor HAT activity. Accordingly, acetylation of histones H3 and H4 was unchanged with statin treatment. However, statins tended to increase DNMT activity. These results indicate that direct inhibition of the major classes of epigenetic modifying enzymes, as previously reported elsewhere, is unlikely to contribute to any anticancer effects of statins. This study concerned global effects on epigenetic enzyme activities and histone acetylation; whether statins influence epigenetic modifications in certain genomic regions, cannot be ruled out and remains to be investigated.
The Effect of Potassium on Cobalt-Based Fischer–Tropsch Catalysts with Different Cobalt Particle Sizes
Authors: Gavrilović Ljubiša , Save Jonas , Blekkan Edd A.
Published: April 2019

The effect of K on 20%Co/0.5%Re/γ-Al2O3 Fischer–Tropsch catalysts with two different cobalt particle sizes (small, in the range 6–7 nm and medium size, in the range 12–13 nm) was investigated. The catalyst with the smaller cobalt particle size had a lower catalytic activity and C5+ selectivity while selectivities towards CH4 and CO2 were slightly higher than over the catalyst with larger particles. These effects are ascribed to lower hydrogen concentration on the surface as well as the lower reducibility of smaller cobalt particles. Upon potassium addition all samples showed decreased catalytic activity, reported as Site Time Yield (STY), increased C5+ and CO2 selectivities, and a decrease in CH4 selectivity. There was no difference in the effect of potassium between the sample with small cobalt particles compared to the sample with medium size particles). In both cases the specific activity (STY) fell and the C5+ selectivity increased in a similar fashion.
Creating a Pharmacotherapy Collaborative Practice Network to Manage Medications for Children and Youth: A Population Health Perspective
Authors: Parrish Richard H. , Casher Danielle , van den Anker Johannes , Benavides Sandra
Published: April 2019

Children with special health care needs (CSHCN) use relatively high quantities of healthcare resources and have overall higher morbidity than the general pediatric population. Embedding clinical pharmacists into the Patient-Centered Medical Home (PCMH) to provide comprehensive medication management (CMM) through collaborative practice agreements (CPAs) for children, especially for CSHCN, can improve outcomes, enhance the experience of care for families, and reduce the cost of care. Potential network infrastructures for collaborative practice focused on CSHCN populations, common language and terminology for CMM, and clinical pharmacist workforce estimates are provided. Applying the results from the CMM in Primary Care grant, this paper outlines the following: (1) setting up collaborative practices for CMM between clinical pharmacists and pediatricians (primary care pediatricians and sub-specialties, such as pediatric clinical pharmacology); (2) proposing various models, organizational structures, design requirements, and shared electronic health record (EHR) needs; and (3) outlining consistent documentation of CMM by clinical pharmacists in CSHCN populations.
Administrative Division Data of Grand Casablanca: Creation of a District Repository Using QGIS
Authors: Ajbal Khaoula , Housbane Samy , Mohammed Bennani Othmani
Published: April 2019

In the context of a public mental health study conducted in Casablanca, the economic capital of Morocco, we encountered a serious challenge regarding the availability of consistent and accurate administrative division data. Hence, using the Google Maps API in QGIS, we proceeded to geocode the Grand Casablanca districts and overlay them on the updated Morocco’s administrative regions shapefile. The district data were summarized and gathered creating an administrative division repository from the district level up. Thus, the main contribution of the current paper, is a table containing (District, District_CP, Commune, Type_com, Prefecture/Province (PR), PR_CP, Region) and the second output is the shapefile that generated the table. The GIS data and the map are useful to other researchers in Morocco and elsewhere who have had no opportunity to access administrative division data of the location. As for foreign researchers from other developing countries the paper’s approach can be applied in their studies to create other lacking geographic repositories.
Integrated Information as a Measure of Cognitive Processes in Coupled Genetic Repressilators
Authors: Abrego Luis , Zaikin Alexey
Published: April 2019

Intercellular communication and its coordination allow cells to exhibit multistability as a form of adaptation. This conveys information processing from intracellular signaling networks enabling self-organization between other cells, typically involving mechanisms associated with cognitive systems. How information is integrated in a functional manner and its relationship with the different cell fates is still unclear. In parallel, drawn originally from studies on neuroscience, integrated information proposes an approach to quantify the balance between integration and differentiation in the causal dynamics among the elements in any interacting system. In this work, such an approach is considered to study the dynamical complexity in a genetic network of repressilators coupled by quorum sensing. Several attractors under different conditions are identified and related to proposed measures of integrated information to have an insight into the collective interaction and functional differentiation in cells. This research particularly accounts for the open question about the coding and information transmission in genetic systems.
The Impact of Both Individual and Collaborative Job Crafting on Spanish Teachers’ Well-Being
Authors: Alonso Consuelo , Fernández-Salinero Samuel , Topa Gabriela
Published: April 2019

Current changes in social structures and political-economic systems directly affect teachers’ job performance. Among others, these changes include changes in communication and information technologies, the scientific revolution, changes in the structure of populations, the revolution of social relations, economic and political transformations, and revolutions in labor relations and leisure time. These changes all seem to have promoted educational revolutions, which encourage the development of autonomous individuals who are capable of making critical judgments, ready to dialogue and cooperate in problem solving, and who seek alternatives aimed at building a better society. Thus, teachers suffer daily from the impact of continual changes that affect the way they do their work. According to the job-demands resources model, each job environment has its own characteristics that can be grouped into two dimensions: job demands and job resources. However, the relationship between job demands and resources has serious implications for individuals’ lives and psychological well-being. While work provides us with the means to survive, develop social relationships, and experience control over our lives, an excess of demands and a shortage of resources to cope with them would adversely affect personal well-being. Hence, individuals can perform behaviors through job crafting to balance this relationship between demands and resources at work. Job crafting is a proactive behavior of the worker who improves his own working conditions in order to achieve a more meaningful and satisfactory job. This phenomenon allows individuals to play a certain role by “creating” their own job, changing the conditions in which they perform their tasks. In this study, 146 teachers participated to investigate the relationships between both individual and collaborative job crafting behaviors, on the one hand, and job satisfaction, work engagement, and teaching performance, on the other.
CCTV Video Processing Metadata Security Scheme Using Character Order Preserving-Transformation in the Emerging Multimedia
Authors: Kim Jinsu , Park Namje , Kim Geonwoo , Jin Seunghun
Published: April 2019

Intelligent video surveillance environments enable the gathering of various types of information about the object being recorded, through the analysis of real-time video data collected from CCTV systems and the automated processing that utilize the information. However, the surveillance environments face the risks of privacy exposure, which necessitates secure countermeasures. Video meta-data, in particular, contain various types of personal information that is analyzed based on big data and are thus fraught with high levels of confidentiality breaches. Despite such risks, it is not appropriate to implement encryption for video meta-data considering the efficiency issue. This paper proposes a character order preserving (COP)-transformation technique that allows the secure protection of video meta-data. The proposed technique has the merits of preventing the recovery of original meta information through meta transformation and allowing direct queries on the data transformed, increasing significantly both security and efficiency in the video meta-data processing.
Efficient-Scheduling Parallel Multiplier-Based Ring-LWE Cryptoprocessors
Authors: Nguyen Tan Tuy , Lee Hanho
Published: April 2019

This paper presents a novel architecture for ring learning with errors (LWE) cryptoprocessors using an efficient approach in encryption and decryption operations. By scheduling multipliers to work in parallel, the encryption and decryption time are significantly reduced. In addition, polynomial multiplications are conducted using radix-2 and radix-8 multiple delay feedback (MDF) architecture-based number theoretic transform (NTT) multipliers to speed up the multiplication operation. To reduce the hardware complexity of an NTT multiplier, three bit-reverse operations during the NTT and inverse NTT (INTT) processes are removed. Polynomial additions in the ring-LWE encryption phase are also arranged to work simultaneously to reduce the latency. As a result, the proposed efficient-scheduling parallel multiplier-based ring-LWE cryptoprocessors can achieve higher throughput and efficiency compared with existing architectures. The proposed ring-LWE cryptoprocessors are synthesized and verified using Xilinx VIVADO on a Virtex-7 field programmable gate array (FPGA) board. With security parameters n = 512 and q = 12,289, the proposed cryptoprocessors using radix-2 single-path delay feedback (SDF), radix-2 MDF, and radix-8 MDF multipliers perform encryption in 4.58 μ s, 1.97 μ s, and 0.89 μ s, and decryption in 4.35 μ s, 1.82 μ s, and 0.71 μ s, respectively. A comparison of the obtained throughput and efficiency with those of previous studies proves that the proposed cryptoprocessors achieve a better performance.
Correction: Salarkaleji, M. Frequency and Polarization-Diversified Linear Sampling Methods for Microwave Tomography and Remote Sensing Using Electromagnetic Metamaterials. Electronics 2017, 6, 85
Authors: Salarkaleji Mehdi , Eskandari Mohammadreza , Chen Jimmy Ching-Ming , Wu Chung-Tse Michael
Published: April 2019

The authors would like to change the affiliation for second author, Mohammadreza Eskandari, as listed in the original version of the article [...]
A Data-Driven Short-Term Forecasting Model for Offshore Wind Speed Prediction Based on Computational Intelligence
Authors: Panapakidis Ioannis P. , Michailides Constantine , Angelides Demos C.
Published: April 2019

Wind speed forecasting is an important element for the further development of offshore wind turbines. Due to its importance, many researchers have proposed different models for wind speed forecasting that differ in terms of the time-horizon of the forecast, types and number of inputs, complexity, structure, and others. Wind speed series present high nonlinearity and volatilities, and thus an effective model should successfully deal with those features. An approach to deal with the nonlinearities and volatilities is to utilize a time series processing technique such as the wavelet transform. In the present paper, an ensemble data-driven short-term wind speed forecasting model is developed, tested and applied. The term “ensemble” refers to the combination of two different predictors that run in parallel and the prediction is obtained by the predictor that leads to the lowest error. The proposed model utilizes the wavelet transform and is compared with other models that have been presented in the related literature and outperforms their accuracy. The proposed forecasting model can be used effectively for 1 min and 10 min ahead horizon wind speed predictions.
Control Strategy for a Grid Connected Converter in Active Unbalanced Distribution Systems
Authors: Dumnic Boris , Popadic Bane , Milicevic Dragan , Vukajlovic Nikola , Delimar Marko
Published: April 2019

The development in distributed energy resources technology has led to a significant amount of non-linear power electronics converters to be integrated in the power system. Although this leads to a more sustainable system, it also can have adverse impacts on system stability and energy power quality. More importantly, the majority of the distribution power systems currently are unbalanced (with asymmetrical voltages) due to load unbalance, while the most common fault types are unbalanced grid faults that can have many adverse effects on distributed resource operations. In that regard, proper control of the grid connected converters in active unbalanced distribution systems will become very important. This paper aims to present the behavior of the advanced grid connected converter control technique under different voltage states at the point of common coupling (according to the ABC classification). The main insufficiencies of the classical control technique will be highlighted, while the paper will propose an appropriate solution for mitigation of negative sequence currents under asymmetrical voltages at the point of common coupling. An extensive experimental verification of the proposed techniques is performed using an advanced laboratory prototype for research in grid integration of distributed resources. The experimental verification clearly demonstrates the benefits offered by the advanced control strategy.
Failure Detection by Signal Similarity Measurement of Brushless DC Motors
Authors: Fico Vito Mario , Rodríguez Vázquez Antonio Leopoldo , Martín Prats María Ángeles , Bernelli-Zazzera Franco
Published: April 2019

In recent years, Brushless DC (BLDC) motors have been gaining popularity as a solution for providing mechanical power, starting from low cost mobility solutions like the electric bikes, to high performance and high reliability aeronautical Electro-Mechanical Actuator (EMA). In this framework, the availability of fault detection tools suited to these types of machines appears necessary. There is already a vast literature on this topic, but only a small percentage of the proposed techniques have been developed to a sufficiently high Technology Readiness Level (TRL) to be implementable in industrial applications. The investigation on the state of the art carried out during the first phase of the present work, tried to collect the techniques which are closest to possible implementation. To fill a gap identified in the current techniques, a partial demagnetisation detection method is proposed in this paper. This technique takes advantage of the asymmetries generated in the current by the missing magnetic flux to detect the failure. Simulations and laboratory experiments have been carried out to validate the idea, showing the potential and the easy implementation of the method. The results have been examined in detail and satisfactory conclusions have been drawn.
Catalytic Coal Gasification Process Simulation with Alkaline Organic Wastewater in a Fluidized Bed Reactor Using Aspen Plus
Authors: Xiao Xianbin , Wang Xueying , Zheng Zongming , Qin Wu , Zhou Yumengqiu
Published: April 2019

A co-gasification process was proposed both for treating alkaline organic wastewater and to promote coal gasification by the alkaline substances in situ. A catalytic gasification model was developed by introducing a catalytic correction factor to describe the catalytic effects quantitatively. An integrated process simulation was carried out using Aspen Plus equipped with FORTRAN subroutines. The model was verified using the root mean square error between the simulation results and experimental data from the literature. Syngas composition, cold gas efficiency, and carbon conversion efficiency were analyzed with respect to different operating conditions (reaction temperature, steam/coal ratio, and equivalence ratio). The optimal conditions are summarized based on a self-sufficient system by using sensitivity analysis: Gasification temperature of 700 °C, steam/coal ratio = 1.0, and equivalence ratio = 0.4.
A Non-Intrusive Load Monitoring Algorithm Based on Non-Uniform Sampling of Power Data and Deep Neural Networks
Authors: Fagiani Marco , Bonfigli Roberto , Principi Emanuele , Squartini Stefano , Mandolini Luigi
Published: April 2019

Nowadays, measurement systems strongly rely on the Internet of Things paradigm, and typically involve miniaturized devices on purpose. In these devices, the computational resources and signal acquisition rates are limited in order to preserve battery life. In addition, the amount of streamed data is affected by the network capacity strictly related to the transmission protocol constraints and the environmental conditions. All those limitations are in contrast with the need of exploiting all possible signal details for the task under study. In the specific application of interest, i.e., Non-Intrusive Load Monitoring (NILM), they could lead to low performance in the energy disaggregation process. To overcome these issues, an ad hoc data reduction policy needs to be adopted, in order to reduce the acquisition and elaboration burden of the device, and, at the same time, to ensure compliance with network bandwidth limits while maintaining a reliable signal representation. Moved by these motivations, an extended evaluation study concerning the application of data reduction strategy to the aggregate signal is presented in this work. In particular, a non-uniform subsampling (NUS) scheme is defined together with a uniform subsampling (US) strategy and compared, in terms of disaggregation performance, with the use of data at original sampling (OS) rate. A Deep Learning based technique is used for disaggregation, having the aggregate active power signal sampled according to diverse sampling schema mentioned above as input. The approaches are tested on the UK-DALE and REDD datasets, and the combination of US+NUS configurations allows for achieving a good performance in terms of F 1 -score, even superior than the one obtained with the OS rate, and a remarkable data reduction at the same time.
A Single-Phase Buck and Boost AC-to-AC Converter with Bipolar Voltage Gain: Analysis, Design, and Implementation
Authors: Ashraf Naveed , Izhar Tahir , Abbas Ghulam , Balas Valentina E. , Balas Marius M. , Lin Tsung-Chih , Asad Muhammad Usman , Farooq Umar , Gu Jason
Published: April 2019

In this research, a new single-phase direct AC-to-AC converter, operating in buck and boost mode, with a bipolar voltage gain, is proposed. The operation is accomplished through high frequency direct and indirect PWM control of a single switch with low voltage stresses. This reduces, not only the control effort, but also the switching losses. The low voltage stresses across the high frequency switches, reduce the dv/dt problem significantly without any loss and bulky voltage snubber arrangement. The operation, in its all-operating modes, has a low inductor ripple current and switching current. The proposed converter may be employed as an AC voltage restorer in a power distribution system to cope with the voltage sag and swell issues. The detailed analysis of the proposed converter is carried out in order to compare its performance with the existing converters. The simulation results obtained using the MATLAB/Simulink environment are verified through experimental results.
Detection of Water Content in Transformer Oil Using Multi Frequency Ultrasonic with PCA-GA-BPNN
Authors: Yang Zhuang , Zhou Qu , Wu Xiaodong , Zhao Zhongyong , Tang Chao , Chen Weigen
Published: April 2019

The water content in oil is closely related to the deterioration performance of an insulation system, and accurate prediction of water content in oil is important for the stability and security level of power systems. A novel method of measuring water content in transformer oil using multi frequency ultrasonic with a back propagation neural network that was optimized by principal component analysis and genetic algorithm (PCA-GA-BPNN), is reported in this paper. 160 oil samples of different water content were investigated using the multi frequency ultrasonic detection technology. Then the multi frequency ultrasonic data were preprocessed using principal component analysis (PCA), which was implemented to obtain main principal components containing 95% of original information. After that, a genetic algorithm (GA) was incorporated to optimize the parameters for a back propagation neural network (BPNN), including the weight and threshold. Finally, the BPNN model with the optimized parameters was trained with a random 150 sets of pretreatment data, and the generalization ability of the model was tested with the remaining 10 sets. The mean squared error of the test sets was 8.65 × 10−5, with a correlation coefficient of 0.98. Results show that the developed PCA-GA-BPNN model is robust and enables accurate prediction of a water content in transformer oil using multi frequency ultrasonic technology.
OSeMOSYS-PuLP: A Stochastic Modeling Framework for Long-Term Energy Systems Modeling
Authors: Dreier Dennis , Howells Mark
Published: April 2019

Recent open-data movements give access to large datasets derived from real-world observations. This data can be utilized to enhance energy systems modeling in terms of heterogeneity, confidence, and transparency. Furthermore, it allows to shift away from the common practice of considering average values towards probability distributions. In turn, heterogeneity and randomness of the real-world can be captured that are usually found in large samples of real-world data. This paper presents a methodological framework for an empirical deterministic–stochastic modeling approach to utilize large real-world datasets in long-term energy systems modeling. A new software system—OSeMOSYS-PuLP—was developed and is available now.It adds the feature of Monte Carlo simulations to the existing open-source energy modeling system (the OSeMOSYS modeling framework). An application example is given, in which the initial application example of OSeMOSYS is used and modified to include real-world operation data from a public bus transport system.
Adaptive Phasor Estimation Algorithm Based on a Least Squares Method
Authors: Kim Woo-Joong , Nam Soon-Ryul , Kang Sang-Hee
Published: April 2019

This paper proposes an adaptive phasor estimation algorithm based on a least square method that can suppress the adverse effect of an exponentially decreasing DC offset component in a phasor estimation process. The proposed algorithm is composed of three stages: a basic least squares model, a time constant calculation, and an adaptive least squares model. First, we use the basic least squares model to estimate the parameter of the DC offset component in the fault current signal. This model is designed to incorporate fundamental frequency, and harmonic and constant components. Second, we use the estimated parameter to calculate the time constant of the DC offset component. Third, we redesign a least squares model that incorporates fundamental frequency, harmonic components, and exponential function of the DC offset component. Since this model incorporates the exponential function of the DC offset component contained in the fault current signal, it estimates the phasor of the correct fundamental frequency component without influence of the DC offset component. We evaluated the performance of the proposed algorithm using computer generated signals and EMTP simulation signals. The evaluation results show that the proposed algorithm can effectively suppress the adverse influence of the exponentially decaying DC offset component.