bluuebunny/crossref_metadata_2025 huggingface dataset:
Focusing on the Place Model for Optometrists
Authors: McClelland Julie F , Breslin Karen
Published: July 2019

Background: The Place Model was developed in order to conceptualize the various roles and career pathways of the teaching profession. It can be used to evaluate long-term professional career trajectories and to encourage the student-teacher to visualize their future personal and professional development. Methods: In the present study, the Place Model has been applied to the Optometric profession. The four categories of the place model have been discussed in terms of Optometry and a survey of undergraduate Optometrists highlights the perception of the model amongst pre-qualified professionals. Results: The majority of participants placed qualified optometrists in the Professional area on the Place Model (87%, n = 88) with the remainder placing qualified optometrists in the De-Professional area on the Place Model (13%, n = 13). There was no statistically significant difference between responses from male and female participants (t-test, p = 0.38). There was also no statistically significant difference between responses from participants in year 1, 2 or 3 of their undergraduate program (one-way analysis of variance [ANOVA], p = 0.10). Conclusion: The Place Model may be an opportunity to discuss with Optometry students their future career pathways and to ensure that we maintain a highly skilled and caring profession that provides high quality eyecare for the public.
Adoption of a Serious Game in the Developing of Emotional Intelligence Skills
Authors: Almeida Fernando
Published: July 2019

Emotional intelligence is intrinsically associated with the ability to understand, manage, and express feelings and deal with other people’s emotions. This competence is essential for the formation, development, and maintenance of personal and professional relationships. Furthermore, emotional intelligence can be extensively worked out and developed over time, which allows each individual to become a better professional. Nevertheless, the perception that higher education students have about the importance of emotional intelligence remains residual and there are few contexts that allow them to develop emotional intelligence skills. In this sense, this study proposes the use of a serious game to assess and develop emotional intelligence skills in the context of an entrepreneurship discipline attended by multidisciplinary students from the courses of management and computer engineering. The performance of students is measured and discussed considering a mixed methods approach. The findings indicate the existence of a correlation between the player’s emotional intelligence skills and his performance in the game, and this occurrence is common to students regardless of their course, gender, age, and number of years of professional experience. The study also explores the importance of emotional intelligence considering the distinct profile of students.
Customized Vibration Generator for State of Health Monitoring of Prosthetic Implants and Pseudo-Bionic Machine–Human Feedbacks
Authors: Galkin Ilya , Vorobyov Maxim , Gainutdinovs Oskars , Studers Peteris
Published: July 2019

Modern industrial, household and other equipment include sophisticated power mechanisms and complicated control solutions that require tighter human–machine–human interactions to form the structures known as cyber–physical–human systems. Their significant parts are human–machine command links and machine–human feedbacks. Such systems are found in medicine, e.g., in orthopedics, where they are important for the operation and functional abilities of orthopedic devices—wheelchair, prosthesis, rehabilitation units, etc. The mentioned feedbacks may be implemented based on the haptic perceptions that requires vibration actuators. In orthopedics, such actuators can be used also for diagnostic purposes. This research brings forward the idea of the use of 3D printing in conjunction with high quality permanent magnets. This allows for the achievement of better efficiency, smaller size, and the developing of actuators individually for particular circumstances. The obtained simulation, experimental data, and data about 3D manufacturing generally confirm the above hypothesis. In particular, the stiffness coefficient of the actuator’s membrane and attached mass, which can be changed easily during 3D printing, affects the frequency of maximal power output. Secondly, the 3D manufacturing process is quick, tunable and rather cheap. Finally, an elaboration of the design of the actuator that allows for the real-time modification of stiffness and mass in a program way is planned for future works.
A Smart Binaural Hearing Aid Architecture Based on a Mobile Computing Platform
Authors: Li Yingdan , Chen Fei , Sun Zhuoyi , Weng Zhaoyang , Tang Xian , Jiang Hanjun , Wang Zhihua
Published: July 2019

This paper presents a new structure for hearing aids. Normally, the power consumption and user experience are contradictory. The proposed hearing aid structure mainly consists of three parts: the earpieces, the mobile computing platform, and the real-time speech-enhancement application. It can run complex algorithms without carrying out heavy calculations on the processors in the hearing aid. Thus, the binaural algorithm is utilized without being limited by complexity and power consumption to improve the user experience. Moreover, the speech-enhancement algorithm can be updated much more easily than in traditional built-in digital signal process hearing aids. A good level of user experience is achieved by combining the hearing aid and mobile computing platform with a 400-MHz transceiver; furthermore, the 400-MHz transceiver can reduce path loss around the body. The concept verification process showed that the overall usage of the central processing unit in the smartphone is around 16%, the signal-to-noise ratios show at least a 30% improvement in some environments, and the whole system delay is 8.8 ms. The presented objective and subjective results show significant improvements regarding user experience and usability brought about by the proposed structure.
A High-Accuracy Ultra-Low-Power Offset-Cancelation On-Off Bandgap Reference for Implantable Medical Electronics
Authors: Xu Jiangtao , Wang Yawei , Wu Minshun , Zhang Ruizhi , Wei Sufen , Zhang Guohe , Yang Cheng-Fu
Published: July 2019

An ultra-low-power and high-accuracy on-off bandgap reference (BGR) is demonstrated in this paper for implantable medical electronics. The proposed BGR shows an average current consumption of 78 nA under 2.8 V supply and an output voltage of 1.17 V with an untrimmed accuracy of 0.69%. The on-off bandgap combined with sample-and-hold switched-RC filter is developed to reduce power consumption and noise. The on-off mechanism allows a relatively higher current in the sample phase to alleviate the process variation of bipolar transistors. To compensate the error caused by operational amplifier offset, the correlated double sampling strategy is adopted in the BGR. The proposed BGR is implemented in 0.35 μm standard CMOS process and occupies a total area of 0.063 mm2. Measurement results show that the circuit works properly in the supply voltage range of 1.8–3.2 V and achieves a line regulation of 0.59 mV/V. When the temperature varies from −20 to 80 °C, an average temperature coefficient of 19.6 ppm/°C is achieved.
High-Throughput and Low-Latency Digital Baseband Architecture for Energy-Efficient Wireless VR Systems
Authors: Hwang Seokha , Moon Seungsik , Kam Dongyun , Oh Inn-Yeal , Lee Youngjoo
Published: July 2019

This paper presents a novel baseband architecture that supports high-speed wireless VR solutions using 60 GHz RF circuits. Based on the experimental observations by our previous 60 GHz transceiver circuits, the efficient baseband architecture is proposed to enhance the quality of transmission. To achieve a zero-latency transmission, we define an (106,920, 95,040) interleaved-BCH error-correction code (ECC), which removes iterative processing steps in the previous LDPC ECC standardized for the near-field wireless communication. Introducing the block-level interleaving, the proposed baseband processing successfully scatters the existing burst errors to the small-sized component codes, and recovers up to 1080 consecutive bit errors in a data frame of 106,920 bits. To support the high-speed wireless VR system, we also design the massive-parallel BCH encoder and decoder, which is tightly connected to the block-level interleaver and de-interleaver. Including the high-speed analog interfaces for the external devices, the proposed baseband architecture is designed in 65 nm CMOS, supporting a data rate of up to 12.8 Gbps. Experimental results show that the proposed wireless VR solution can transfer up to 4 K high-resolution video streams without using time-consuming compression and decompression, successfully achieving a transfer latency of 1 ms.
Optimal Scheduling Strategy of Distribution Network Based on Electric Vehicle Forecasting
Authors: Li Fenglei , Dou Chunxia , Xu Shiyun
Published: July 2019

Based on the Monte Carlo method, this paper simulates, predicts the load, and considers the travel chain of electric vehicles and different charging methods to establish a predictive model. Based on the results of electric vehicle simulation prediction, an optimal scheduling model of the distribution network considering the demand response side load is established. The firefly optimization algorithm is used to solve the optimal scheduling problem. The results show that the prediction model proposed in this paper has a certain reference value for the prediction of an electric vehicle load. The electric vehicle is placed in the optimal scheduling resource of the distribution network, which increases the dimension of the scheduling resources of the network and improves the economics of the distribution network operation.
Choosing the Best Locomotion Mode in Reconfigurable Rovers
Authors: Pérez del Pulgar Mancebo Carlos Jesús , Romeo Manrique Pablo , Paz Delgado Gonzalo Jesús , Sánchez Ibáñez José Ricardo , Azkarate Martin
Published: July 2019

The use of autonomous rovers for planetary exploration is crucial to traverse long distances and perform new discoveries on other planets. One of the most important issues is related to the interaction between the rover wheel and terrain, which would help to save energy and even avoid getting entrapped. The use of reconfigurable rovers with different locomotion modes has demonstrated improvement of traction and energy consumption. Therefore, the objective of this paper is to determine the best locomotion mode during the rover traverse, based on simple parameters, which would be obtained from propioceptive sensors. For this purpose, interaction of different terrains have been modelled and analysed with the ExoTeR, a scale prototype rover of the European ExoMars 2020 mission. This rover is able to perform, among others, the wheel walking locomotion mode, which has been demonstrated to improve traction in different situations. Currently, it is difficult to decide the instant time the rover has to switch from this locomotion mode to another. This paper also proposes a novel method to estimate the slip ratio, useful for deciding the best locomotion mode. Finally, results are obtained from an immersive simulation environment. It shows how each locomotion mode is suitable for different terrains and slopes and the proposed method is able to estimate the slip ratio.
On Performance Analysis of Underlay Cognitive Radio-Aware Hybrid OMA/NOMA Networks with Imperfect CSI
Authors: Do Dinh-Thuan , Le Anh-Tu , Lee Byung Moo
Published: July 2019

This study considers the outage and throughput performance of downlink in the secondary network of cognitive radio assisted non-orthogonal multiple access (NOMA) systems. Both orthogonal multiple access (OMA) mode and NOMA mode are investigated with respect to status of decoding operation of each user. Depending on the transmit signal-to-noise ratio (SNR) at the primary source and interference constraint from the primary network, the closed-form expressions of the outage probability for two users are obtained and compared in terms of performance. To obtain further insights, an asymptotic analysis of the outage probability in the high SNR regime is presented. Optimal throughput also provides insight in the computation of the power allocation factor. Furthermore, power allocation factor, target rates, and transmit SNR are evaluated to obtain reasonable outage performance. Monte Carlo simulations are conducted to confirm the analytical results.
Carbon Emission Evaluation Based on Multi-Objective Balance of Sewing Assembly Line in Apparel Industry
Authors: Zhang Xujing , Chen Yan
Published: July 2019

Apparel manufacturing is an industry with high energy consumption and carbon emissions. With the development of the low-carbon economy, low-carbon production in the apparel manufacturing industry become more and more imperative. The apparel industry is encountering great challenges in reducing carbon emissions. Garment sewing comprises a large number of processes, machines and operators. However, the existing studies lack quantitative analysis of carbon sources in the sewing process. This study analyzed the carbon emission characteristics in garment sewing production. Evaluation models of carbon emission were established for the sewing process in this research and the factors of fabrics, accessories, sewing machines and operators were included in the models. The results showed that fabrics and accessories were the main sources of carbon emissions in garment sewing production. The second largest carbon emission source was sewing machines, followed by operators. According to the evaluation models, the number of machines, operators and the utilization rate of the machines were related to the balance of the assembly line. A multi-objective optimization model aimed at minimizing the time loss rate and smoothness index of the assembly line was established, and a fast and elitist multi-objective genetic algorithm was used to obtain the solution for carbon emission reduction. The men’s shirt assembly lines, based on three types of workstation layouts (the order of processes, the type of machines and the components of the garment), were applied to verify the effectiveness of the model and algorithm. The results indicated that the total carbon emissions of the three assembly lines based on balance optimization were less than that of the normal assembly line. The assembly line of the workstations arranged in the order of processes was the best assembly line since it had the highest efficiency and the lowest carbon emissions.
Microcontroller-Based Strategies for the Incorporation of Solar to Domestic Electricity
Authors: Mabunda Nkateko E. , Joseph Meera K.
Published: July 2019

Microcontrollers have been largely used in applications that include reducing power consumption. Microcontroller development tools are now readily available. Many countries are faced with energy challenges such as lack of enough power capacity and growth in energy demand. It is therefore important to introduce innovative methods to reduce reliance on national grid energy and to supplement this source of energy with alternative methods. In this study, the microcontroller is used to monitor the energy consumed by household equipment and then decide, based on the power demand and available solar energy, the type of energy source to be used. In this research, a special circuit was also designed to control geyser power and align it to the capacity of the renewable energy source. This geyser control circuit includes a Dallas temperature sensor and a triode for alternating current (TRIAC) circuit that is included to control output current drawn from a low power, renewable energy source. Alternatively, two heating elements may be used instead of the TRIAC circuit. The first heating element is powered by solar to maintain the water temperature and to save energy. The second heating element is powered by national grid power and is used for the initial heating, and therefore saves water heating time. The strategy used was by adding a programmed microcontroller-based control circuit and a low power element or one current controlled element to a geyser whereby Photovoltaic (PV) energy was used to save the energy geysers consume from the domestic electricity source when they are not in use. A microcontroller, current sensor, battery level sensor, and relay board was used to incorporate solar-based renewable energy to the commercial energy supply.
Assessment of Remote Sensing Data to Model PM10 Estimation in Cities with a Low Number of Air Quality Stations: A Case of Study in Quito, Ecuador
Authors: Alvarez-Mendoza Cesar I. , Teodoro Ana Claudia , Torres Nelly , Vivanco Valeria
Published: July 2019

The monitoring of air pollutant concentration within cities is crucial for environment management and public health policies in order to promote sustainable cities. In this study, we present an approach to estimate the concentration of particulate matter of less than 10 µm diameter (PM10) using an empirical land use regression (LUR) model and considering different remote sensing data as the input. The study area is Quito, the capital of Ecuador, and the data were collected between 2013 and 2017. The model predictors are the surface reflectance bands (visible and infrared) of Landsat-7 ETM+, Landsat-8 OLI/TIRS, and Aqua-Terra/MODIS sensors and some environmental indexes (normalized difference vegetation index—NDVI; normalized difference soil index—NDSI, soil-adjusted vegetation index—SAVI; normalized difference water index—NDWI; and land surface temperature (LST)). The dependent variable is PM10 ground measurements. Furthermore, this study also aims to compare three different sources of remote sensing data (Landsat-7 ETM+, Landsat-8 OLI, and Aqua-Terra/MODIS) to estimate the PM10 concentration, and three different predictive techniques (stepwise regression, partial least square regression, and artificial neuronal network (ANN)) to build the model. The models obtained are able to estimate PM10 in regions where air data acquisition is limited or even does not exist. The best model is the one built with an ANN, where the coefficient of determination (R2 = 0.68) is the highest and the root-mean-square error (RMSE = 6.22) is the lowest among all the models. Thus, the selected model allows the generation of PM10 concentration maps from public remote sensing data, constituting an alternative over other techniques to estimate pollutants, especially when few air quality ground stations are available.
Contrasting Response to Drought and Climate of Planted and Natural Pinus pinaster Aiton Forests in Southern Spain
Authors: Rodriguez-Vallejo Carlos , Navarro-Cerrillo Rafael M.
Published: July 2019

Extreme drought events and increasing aridity are leading to forest decline and tree mortality, particularly in populations near the limits of the species distribution. Therefore, a better understanding of the growth response to drought and climate change could show the vulnerability of forests and enable predictions of future dieback. In this study, we used a dendrochronological approach to assess the response to drought in natural and planted forests of the maritime pine (Pinus pinaster Aiton) located in its southernmost distribution (south of Spain). In addition, we investigated how environmental variables (climatic and site conditions) and structural factors drive radial growth along the biogeographic and ecological gradients. Our results showed contrasting growth responses to drought of natural and planted stands, but these differences were not significant after repeated drought periods. Additionally, we found differences in the climate–growth relationships when comparing more inland sites (wet previous winter and late spring precipitation) and sites located closer to the coast (early spring precipitation). Response functions emphasized the negative effect of defoliation and drought, expressed as the June standard precipitation-evapotranspiration index calculated for the 12-month temporal scale and the mean temperature in the current February, on growth. The strong relationship between climatic variables and growth enabled acceptable results to be obtained in a modeling approach. The study and characterization of this tree species’ response to drought will help to improve the adaptive management of forests under climate change.
Mannoprotein Content and Volatile Molecule Profiles of Trebbiano Wines Obtained by Saccharomyces cerevisiae and Saccharomyces bayanus Strains
Authors: Braschi Giacomo , Ricci Arianna , Grazia Luigi , Versari Andrea , Patrignani Francesca , Lanciotti Rosalba
Published: July 2019

The production of volatile compounds has become one of the major technological features for yeast selection. In fact, although the aromatic profile of the wine is the sum of varietal-, pre-, post-, and fermentative-aroma compound, yeasts affect the quality of the grape from maturation throughout fermentation, metabolizing sugars and other components into alcohols, esters, organic acids, and aldehydes. Among the new technological features, the production of mannoproteins has gained interest. From this perspective, the main aim of this work was to characterize 9 strains of Saccharomyces cerevisiae and 1 of Saccharomyces bayanus for their volatile profiles and the release of mannoproteins. The strains were inoculated in Trebbiano musts and incubated at 15 °C; at the end of fermentation the wines were evaluated by GC/MS/SPME for their volatile profiles and mannoprotein content by enzymatic assay. The strains were inoculated at level ranging between 4.9 and 6.3 log CFU/mL but only the strains L318 and 12233X6167 were able to reach values of 7.5 log CFU/mL. The aromatic profiles resulted in a strain-specific fingerprinting. According to the principal component analysis, the wines produced by the strains L288, L234, and L318 were characterized by the presence of propanoic acid, butanol, octanoic acid, and 3 methyl pentanol while the wine obtained by the strain 12233x35G2 was characterized by the presence of propanoic acid, butanol, octanoic acid and 3 methyl pentanol while the strain 12233x35G2 was characterized by the presence of decanoic acid ethyl ester, heptanoic acid ethyl ester, and acetic acid 2 phenetyl ester. Regarding mannoproteins, the highest concentration was achieved by strain12233x6167 (104 mg/L). The data allowed to select the strains endowed with the best fermentation performances in terms of aroma and mannoproteins release.
Leveraging the Internet of Things and Blockchain Technology in Supply Chain Management
Authors: Rejeb Abderahman , Keogh John G. , Treiblmaier Horst
Published: July 2019

Modern supply chains have evolved into highly complex value networks and turned into a vital source of competitive advantage. However, it has become increasingly challenging to verify the source of raw materials and maintain visibility of products and merchandise while they are moving through the value chain network. The application of the Internet of Things (IoT) can help companies to observe, track, and monitor products, activities, and processes within their respective value chain networks. Other applications of IoT include product monitoring to optimize operations in warehousing‚ manufacturing, and transportation. In combination with IoT, Blockchain technology can enable a broad range of different application scenarios to enhance value chain transparency and to increase B2B trust. When combined, IoT and Blockchain technology have the potential to increase the effectiveness and efficiency of modern supply chains. The contribution of this paper is twofold. First, we illustrate how the deployment of Blockchain technology in combination with IoT infrastructure can streamline and benefit modern supply chains and enhance value chain networks. Second, we derive six research propositions outlining how Blockchain technology can impact key features of the IoT (i.e., scalability, security, immutability and auditing, information flows, traceability and interoperability, quality) and thus lay the foundation for future research projects.
Data-Driven Model Reduction for Coupled Flow and Geomechanics Based on DMD Methods
Authors: Bao Anqi , Gildin Eduardo , Narasingam Abhinav , Kwon Joseph S.
Published: July 2019

Learning reservoir flow dynamics is of primary importance in creating robust predictive models for reservoir management including hydraulic fracturing processes. Physics-based models are to a certain extent exact, but they entail heavy computational infrastructure for simulating a wide variety of parameters and production scenarios. Reduced-order models offer computational advantages without compromising solution accuracy, especially if they can assimilate large volumes of production data without having to reconstruct the original model (data-driven models). Dynamic mode decomposition (DMD) entails the extraction of relevant spatial structure (modes) based on data (snapshots) that can be used to predict the behavior of reservoir fluid flow in porous media. In this paper, we will further enhance the application of the DMD, by introducing sparse DMD and local DMD. The former is particularly useful when there is a limited number of sparse measurements as in the case of reservoir simulation, and the latter can improve the accuracy of developed DMD models when the process dynamics show a moving boundary behavior like hydraulic fracturing. For demonstration purposes, we first show the methodology applied to (flow only) single- and two-phase reservoir models using the SPE10 benchmark. Both online and offline processes will be used for evaluation. We observe that we only require a few DMD modes, which are determined by the sparse DMD structure, to capture the behavior of the reservoir models. Then, we applied the local DMDc for creating a proxy for application in a hydraulic fracturing process. We also assessed the trade-offs between problem size and computational time for each reservoir model. The novelty of our method is the application of sparse DMD and local DMDc, which is a data-driven technique for fast and accurate simulations.
Spurious PIV Vector Correction Using Linear Stochastic Estimation
Authors: Butcher Daniel , Spencer Adrian
Published: July 2019

Techniques for the experimental determination of velocity fields such as particle image velocimetry (PIV) can often be hampered by spurious vectors or sparse regions of measurement which may occur due to a number of reasons. Commonly used methods for detecting and replacing erroneous values are often based on statistical measures of the surrounding vectors and may be influenced by further poor data quality in the region. A new method is presented in this paper using Linear Stochastic Estimation for vector replacement (LSEVR) which allows for increased flexibility in situations with regions of spurious vectors. LSEVR is applied to PIV dataset to demonstrate and assess its performance relative to commonly used bilinear and bicubic interpolation methods. For replacement of a single vector, all methods performed well, with LSEVR having an average error of 11% in comparison to 14% and 18% for bilinear and bicubic interpolation respectively. A more significant difference was found in replacement of clusters of vectors which showed average vector angle errors of 10°, 9° and 6° for bilinear, bicubic and LSEVR respectively. Error in magnitude was 3% for both interpolation techniques and 1% for LSEVR showing a clear benefit to using LSEVR for conditions that require multiple clustered vectors to be replaced.
Structural Basis of Resistant Starch (RS) in Bread: Natural and Commercial Alternatives
Authors: Roman Laura , Martinez Mario M.
Published: July 2019

Bread is categorized as having a high amount of rapidly digested starch that may result in a rapid increase in postprandial blood glucose and, therefore, poor health outcomes. This is mostly the result of the complete gelatinization that starch undergoes during baking. The inclusion of resistant starch (RS) ingredients in bread formulas is gaining prominence, especially with the current positive health outcomes attributed to RS and the apparition of novel RS ingredients in the market. However, many RS ingredients contain RS structures that do not resist baking and, therefore, are not suitable to result in a meaningful RS increase in the final product. In this review, the structural factors for the resistance to digestion and hydrothermal processing of RS ingredients are reviewed, and the definition of each RS subtype is expanded to account for novel non-digestible structures recently reported. Moreover, the current in vitro digestion methods used to measure RS content are critically discussed with a view of highlighting the importance of having a harmonized method to determine the optimum RS type and inclusion levels for bread-making.
He Tātai Whenua: Environmental Genealogies
Authors: Forster Margaret
Published: July 2019

Whakapapa, an indigenous form of genealogy of the Māori people of Aotearoa New Zealand, is a powerful tool for understanding social phenomena. In this paper, the environmental histories of Aotearoa New Zealand are converted to whakapapa/genealogical sequences and kōrero tuku iho/narratives derived from whakapapa, to demonstrate this explanatory power. It is argued that whakapapa is much more than a method for mapping kinship relationships. Whakapapa enables vast amounts of information to be collated and analysed, to reveal a multitude of narratives. It also facilitates a critique of indigenous rights issues, revealing Māori agendas for environmental management. Therefore, the whakapapa sequences and narratives created as part of this paper provide an understanding that is not restricted to the grand narrative or the past as whakapapa is never-ending, dynamic, fluid and future-focused.
When Three Isn’t a Crowd: A Digyny Concept for Treatment-Resistant, Near-Triploid Human Cancers
Authors: Salmina Kristine , Gerashchenko Bogdan I. , Hausmann Michael , Vainshelbaum Ninel M. , Zayakin Pawel , Erenpreiss Juris , Freivalds Talivaldis , Cragg Mark S. , Erenpreisa Jekaterina
Published: July 2019

Near-triploid human tumors are frequently resistant to radio/chemotherapy through mechanisms that are unclear. We recently reported a tight association of male tumor triploidy with XXY karyotypes based on a meta-analysis of 15 tumor cohorts extracted from the Mitelman database. Here we provide a conceptual framework of the digyny-like origin of this karyotype based on the germline features of malignant tumors and adaptive capacity of digyny, which supports survival in adverse conditions. Studying how the recombinatorial reproduction via diploidy can be executed in primary cancer samples and HeLa cells after DNA damage, we report the first evidence that diploid and triploid cell sub-populations constitutively coexist and inter-change genomes via endoreduplicated polyploid cells generated through genotoxic challenge. We show that irradiated triploid HeLa cells can enter tripolar mitosis producing three diploid sub-subnuclei by segregation and pairwise fusions of whole genomes. Considering the upregulation of meiotic genes in tumors, we propose that the reconstructed diploid sub-cells can initiate pseudo-meiosis producing two “gametes” (diploid “maternal” and haploid “paternal”) followed by digynic-like reconstitution of a triploid stemline that returns to mitotic cycling. This process ensures tumor survival and growth by (1) DNA repair and genetic variation, (2) protection against recessive lethal mutations using the third genome.
Transcriptome Analysis of Landrace Pig Subcutaneous Preadipocytes during Adipogenic Differentiation
Authors: Zhao Xitong , Chen Shaokang , Tan Zhen , Wang Yuan , Zhang Fengxia , Yang Ting , Liu Yibing , Ao Hong , Xing Kai , Wang Chuduan
Published: July 2019

Fat deposition in pigs, which significantly contributes to meat quality, fattening efficiency, reproductive performance, and immunity, is critically affected by preadipocyte adipogenic differentiation. We elucidated adipogenesis in pigs using transcriptome analysis. Preadipocytes from subcutaneous adipose tissue (SAT) of Landrace piglets were differentiated into adipocytes in vitro. RNA sequencing (RNA-seq) used to screen differentially expressed genes (DEGs) during preadipocyte differentiation up to day 8 revealed 15,918 known and 586 novel genes. We detected 21, 144, and 394 DEGs, respectively, including 16 genes differentially expressed at days 2, 4 and 8 compared to day 0. Th number of DEGs increased time-dependently. Lipid metabolism, cell differentiation and proliferation, peroxisome proliferator-activated receptor (PPAR), wingless-type MMTV integration site (Wnt), tumor necrosis factor (TNF) signaling, and steroid biosynthesis were significant at days 2, 4, and 8 compared to day 0 (adjusted p < 0.05). Short time-series expression miner (STEM) analysis obtained 26 clusters of differential gene expression patterns, and nine were significant (p < 0.05). Functional analysis showed many significantly enriched lipid deposition- and cellular process-related biological processes and pathways in profiles 9, 21, 22, and 24. Glycerolipid and fatty-acid metabolism, PPAR signaling, fatty-acid degradation, phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt), and TNF signaling were observed during preadipocyte differentiation in vitro. These findings will facilitate the comprehension of preadipocyte differentiation and fat deposition in pigs.
Chromatin Interaction Analysis with Updated ChIA-PET Tool (V3)
Authors: Li Guoliang , Sun Tongkai , Chang Huidan , Cai Liuyang , Hong Ping , Zhou Qiangwei
Published: July 2019

Understanding chromatin interactions is important because they create chromosome conformation and link the cis- and trans- regulatory elements to their target genes for transcriptional regulation. Chromatin Interaction Analysis with Paired-End Tag (ChIA-PET) sequencing is a genome-wide high-throughput technology that detects chromatin interactions associated with a specific protein of interest. We developed ChIA-PET Tool for ChIA-PET data analysis in 2010. Here, we present the updated version of ChIA-PET Tool (V3) as a computational package to process the next-generation sequence data generated from ChIA-PET experiments. It processes short-read and long-read ChIA-PET data with multithreading and generates statistics of results in an HTML file. In this paper, we provide a detailed demonstration of the design of ChIA-PET Tool V3 and how to install it and analyze RNA polymerase II (RNAPII) ChIA-PET data from human K562 cells with it. We compared our tool with existing tools, including ChiaSig, MICC, Mango and ChIA-PET2, by using the same public data set in the same computer. Most peaks detected by the ChIA-PET Tool V3 overlap with those of other tools. There is higher enrichment for significant chromatin interactions from ChIA-PET Tool V3 in aggregate peak analysis (APA) plots. The ChIA-PET Tool V3 is publicly available at GitHub.
An Evaluation of Catchment Transit Time Model Parameters: A Comparative Study between Two Stable Isotopes of Water
Authors: Bansah Samuel , Andam-Akorful Samuel Ato , Quaye-Ballard Jonathan , Wilson Matthew Coffie , Gidigasu Solomon Senyo , Anornu Geophrey K.
Published: July 2019

Using δ18O and δ2H in mean transit time (MTT) modeling can ensure the verifiability of results across catchments. The main objectives of this study were to (i) evaluate the δ18O- and δ2H-based behavioral transit time distributions and (ii) assess if δ18O and δ2H-based MTTs can lead to similar conclusions about catchment hydrologic functioning. A volume weighted δ18O (or δ2H) time series of sampled precipitation was used as an input variable in a 50,000 Monte Carlo (MC) time-based convolution modeling process. An observed streamflow δ18O (or δ2H) time series was used to calibrate the model to obtain the simulated time series of δ18O (or δ2H) of the streamflow within a nested system of eight Prairie catchments in Canada. The model efficiency was assessed via a generalized likelihood uncertainty estimation by setting a minimum Nash–Sutcliffe Efficiency threshold of 0.3 for behavioral parameter sets. Results show that the percentage of behavioral parameter sets across both tracers were lower than 50 at the majority of the studied outlets; a phenomenon hypothesized to have resulted from the number of MC runs. Tracer-based verifiability of results could be achieved within five of the eight studied outlets during the model process. The flow process in those five outlets were mainly of a shallow subsurface flow as opposed to the other three outlets, which experienced other additional flow dynamics. The potential impacts of this study on the integrated use of δ18O and δ2H in catchment water storage and release dynamics must be further investigated in multiple catchments within various hydro-physiographic settings across the world.
Measuring Ganymede’s Librations with Laser Altimetry
Authors: Steinbrügge Gregor , Steinke Teresa , Thor Robin , Stark Alexander , Hussmann Hauke
Published: July 2019

Jupiter’s moon Ganymede might be in possession of a subsurface ocean located between two ice layers. However, from Galileo data it is not possible to unambiguously infer the thickness and densities of the individual layers. The upcoming icy satellite mission JUICE (JUpiter ICy moons Explorer) will have the possibility to perform more detailed investigations of Ganymede’s interior structure with the radio science experiment 3GM and the GAnymede Laser Altimeter (GALA). Here we investigate the possibility to derive the rotational state of the outer ice shell by using topography measured by laser altimetry. We discuss two different methods to invert synthetic laser altimetry data. Method 1 is based on a spherical harmonics expansion and Method 2 solves for B-splines on a rectangular grid. While Method 1 has significant limitations due to the omission of high degrees of the global expansion, Method 2 leads to stable results allowing for an estimate of the in-orbit measurement accuracy. We estimate that GALA can measure the amplitude of Ganymede’s librations with an accuracy of 2.5–6.6 μ rad (6.6–17.4 m at the equator). This allows for determining the thickness of an elastic ice shell, if decoupled from the deeper interior by a subsurface ocean, to about an accuracy of 24–65 km.
X-Ray Computed Tomography In Situ: An Opportunity for Museums and Restoration Laboratories
Authors: Albertin Fauzia , Bettuzzi Matteo , Brancaccio Rosa , Morigi Maria Pia , Casali Franco
Published: July 2019

X-ray Computed Tomography (X-ray CT) is a sophisticated non-destructive imaging technique to investigate structures and materials of complex objects, and its application can answer many conservation and restoration questions. However, for Cultural Heritage investigations, medical CT scanners are not optimized for many case-studies: These instruments are designed for the human body, are not flexible and are difficult to use in situ. To overcome these limitations and to safely investigate works of art on site—in a restoration laboratory or in a museum—the X-ray Tomography Laboratory of the University of Bologna designed several CT systems. Here we present two of these facilities and the results of important measurement campaigns performed in situ. The first instrument, light and flexible, is designed to investigate medium-size objects with a resolution of a few tens of microns and was used for the CT analysis of several Japanese theater masks belonging to the collection of the “L. Pigorini” Museum (Rome). The second is designed to analyze larger objects, up to 200 cm and was used to investigate the collection of the so-called “Statue Vestite” (devotional dressed statues) of the Diocesan Museum of Massa.
Planning for the Enhancement of the Modern Built Heritage in Thessaly Region: The Case of the “Konakia” Monuments
Authors: Papandreou Aikaterini , Papageorgiou Marilena
Published: July 2019

Built heritage constitutes an invaluable asset to be treasured and wisely managed in order to avoid loss of place identity, cultural and social degradation and loss of leisure and tourism opportunities. The present paper focuses on the modern built heritage of the Thessaly Region (Greece), giving special emphasis to the “konakia” monuments built during the late 19th and early 20th century that were once used as residences by the big landowners of the Thessalian agricultural plain (“tsiflikia”). Field research conducted, as well as a survey of secondary data, revealed that only fifteen (15) “konakia” remain in Thessaly, equally dispersed in Larisa, Trikala and Karditsa Prefectures. Given their use, all of the “konakia” are found within—or in the vicinity of—agricultural land and settlements. Most of them present severe signs of abandonment, while only four (4) of them are in use (either as second-homes or as spaces with cultural and administrative use). Starting in 1979 (until 2005), with the exception of the Averof “konakia”, all of the rest have been designated as part of the modern built heritage of Greece. Considering these facts—and that most of such properties are private—the paper proposes a six (6) step methodology, for their wise management and integration in the spatial and cultural landscape of Thessaly: (1) Selection of the proper type of (re)use of the monument(s), (2) selection (or reconsideration) of the protection status and zoning, (3) identification of the urban regeneration interventions, (4) introduction of the necessary amendments to the urban/local plan, (5) selection of the proper financial tools and (6) selection of the proper marketing strategy. The paper concludes by highlighting the need to address the “konakia” as a set of monuments, to achieve stakeholders’ engagement and local community involvement, without undermining either protection status or the private rights of owners over these cultural properties.
Types of Exposure Pesticide Poisoning in Jiangsu Province, China; The Epidemiologic Trend between 2006 and 2018
Authors: Wang Ning , Wang Boshen , Wen Jinbo , Li Xiuting , Pan Liping , Zhang Juan , Zhu Baoli
Published: July 2019

Background: Pesticide poisoning is an important issue in rural China, and is also a major public health problem that affects the health of farmers. The purpose of this paper is to explore the epidemiology of pesticide poisoning in Jiangsu Province, and to put forward the relevant suggestions on the logical and discerning utilization of the pesticides. Methods: According to the data of the pesticide poisoning report card established by the health hazard detection information system, the cases of pesticide poisoning in Jiangsu Province from 2006 to 2018 were exported to Excel, and the database of pesticide poisoning was established. Furthermore, the imported data was screened and collected. A descriptive statistical analysis had been employed on this data utilizing SPSS 20.0. Results: Between the years 2006 and 2018, 38,513 pesticide poisoning cases were registered in Jiangsu Province, with a downward trend. Meanwhile, 77.83% of poisoning cases involved insecticide poisoning, followed by herbicide and rodenticide. The greater part of the diverse sorts of studied insecticide poisoning cases involved people aged between 30 and 59 years (57.51%). Poisoning cases caused by rodenticide accounted for a large proportion of people aged between 0 and 14 years (23.72%) in non-occupational pesticide poisoning. Regarding seasons, it was distinguished that more insecticide cases were reported in autumn (46.95% of the total number of cases). Pesticide poisoning was reported in 13 cities of Jiangsu Province, and among these, insecticide poisoning was reported mainly from the northern Jiangsu area, which was the same as rodenticide and herbicide. Conclusions: Although there is a decreased risk for pesticide poisoning among farmworkers in Jiangsu Province, the number of farmworkers with pesticide poisoning is still high. Further management of the pesticide utilization is necessary, especially insecticide. More attention ought to be paid to the protection of vulnerable groups, including children and the elderly.
Detection of Hepatitis A Virus and Other Enteric Viruses in Shellfish Collected in the Gulf of Naples, Italy
Authors: Fusco Giovanna , Anastasio Aniello , Kingsley David H. , Amoroso Maria Grazia , Pepe Tiziana , Fratamico Pina M. , Cioffi Barbara , Rossi Rachele , La Rosa Giuseppina , Boccia Federica
Published: July 2019

To assess the quality of shellfish harvest areas, bivalve mollusk samples from three coastal areas of the Campania region in Southwest Italy were evaluated for viruses over a three-year period (2015–2017). Screening of 289 samples from shellfish farms and other locations by qPCR and RT-qPCR identified hepatitis A virus (HAV; 8.9%), norovirus GI (NoVGI; 10.8%) and GII (NoVGII; 39.7%), rotavirus (RV; 9.0%), astrovirus (AsV; 20.8%), sapovirus (SaV; 18.8%), aichivirus-1 (AiV-1; 5.6%), and adenovirus (AdV, 5.6%). Hepatitis E virus (HEV) was never detected. Sequence analysis identified HAV as genotype IA and AdV as type 41. This study demonstrates the presence of different enteric viruses within bivalve mollusks, highlighting the limitations of the current EU classification system for shellfish growing waters.
Application of Social Big Data to Identify Trends of School Bullying Forms in South Korea
Authors: Donnelly Hayoung , Han Yoonsun , Song Juyoung , Song Tae
Published: July 2019

As the contemporary phenomenon of school bullying has become more widespread, diverse, and frequent among adolescents in Korea, social big data may offer a new methodological paradigm for understanding the trends of school bullying in the digital era. This study identified Term Frequency-Inverse Document Frequency (TF-IDF) and Future Signals of 177 school bullying forms to understand the current and future bullying experiences of adolescents from 436,508 web documents collected between 1 January 2013, and 31 December 2017. In social big data, sexual bullying rapidly increased, and physical and cyber bullying had high frequency with a high rate of growth. School bullying forms, such as “group assault” and “sexual harassment”, appeared as Weak Signals, and “cyber bullying” was a Strong Signal. Findings considering five school bullying forms (verbal, physical, relational, sexual, and cyber bullying) are valuable for developing insights into the burgeoning phenomenon of school bullying.
Factors Influencing Technology Integration in the Curriculum for Taiwanese Health Profession Educators: A Mixed-Methods Study
Authors: Chen Hsiao-Jung , Liao Li-Ling , Chang Yu-Che , Hung Chung-Chih , Chang Li-Chun
Published: July 2019

In this study, we explored the considerations and the influencing factors for the technological integration of educational curricula based on the technological pedagogical content knowledge (TPCK) framework for health profession educators (HPEs). A mixed methodology was used that included semi-structured interviews with 15 HPEs and an online TPCK survey with a randomly selected sample of 319 HPEs from 217 Taiwanese universities. Five themes emerged, namely, supplementing traditional teaching methods, improving immediate educator–student interactions, tracking the learning process and improving the record-keeping, keeping up with technological trends, and advancing professional learning objectives for different student needs. The presence of pre-existing platforms and inspiration from colleagues and students were facilitators, whereas the risk of technological problems and the need to invest extra time into the preparation process were impediments to technology integration in the curriculum. Of the online respondents (n = 210), 64.2% have integrated at least one technological method into their curriculum. The logistic regression model revealed that gender, prior knowledge regarding how to incorporate technology with teaching, high mean TPCK scores, and relevant school policies were significant predictors of technology integration in the curriculum. Based on these results, recommendations for development in the health profession included efforts to equip HPEs with TPCK, in order to integrate technology into the curriculum effectively.