bluuebunny/crossref_metadata_2025 huggingface dataset:
92.5% Average Power Efficiency Fully Integrated Floating Buck Quasi-Resonant LED Drivers Using GaN FETs
Authors: Soh Mei Yu , Selvaraj S. Lawrence , Peng Lulu , Yeo Kiat Seng
Published: March 2020

LEDs are highly energy efficient and have substantially longer lifetimes compared to other existing lighting technologies. In order to facilitate the new generation of LED devices, approaches to improve power efficiency with increased integration level for lighting device should be analysed. This paper proposes a fully on-chip integrated LED driver design implemented using heterogeneous integration of gallium nitride (GaN) devices atop BCD circuits. The performance of the proposed design is then compared with the conventional fully on-board integration of power devices with the LED driver integrated circuit (IC). The experimental results confirm that the fully on-chip integrated LED driver achieves a consistently higher power efficiency value compared with the fully on-board design within the input voltage range of 4.5–5.5 V. The maximal percentage improvement in the efficiency of the on-chip solution compared with the on-board solution is 18%.
A Novel Hybrid IDS Based on Modified NSGAII-ANN and Random Forest
Authors: Golrang Anahita , Golrang Alale Mohammadi , Yildirim Yayilgan Sule , Elezaj Ogerta
Published: March 2020

Machine-learning techniques have received popularity in the intrusion-detection systems in recent years. Moreover, the quality of datasets plays a crucial role in the development of a proper machine-learning approach. Therefore, an appropriate feature-selection method could be considered to be an influential factor in improving the quality of datasets, which leads to high-performance intrusion-detection systems. In this paper, a hybrid multi-objective approach is proposed to detect attacks in a network efficiently. Initially, a multi-objective genetic method (NSGAII), as well as an artificial neural network (ANN), are run simultaneously to extract feature subsets. We modified the NSGAII approach maintaining the diversity control in this evolutionary algorithm. Next, a Random Forest approach, as an ensemble method, is used to evaluate the efficiency of the feature subsets. Results of the experiments show that using the proposed framework leads to better outcomes, which could be considered to be promising results compared to the solutions found in the literature.
An Accurate and Efficient Timing Prediction Framework for Wide Supply Voltage Design Based on Learning Method
Authors: Cao Peng , Bao Wei , Guo Jingjing
Published: March 2020

The wide voltage design methodology has been widely employed in the state-of-the-art circuit design with the advantage of remarkable power reduction and energy efficiency enhancement. However, the timing verification issue for multiple PVT (process–voltage–temperature) corners rises due to unacceptable analysis effort increase for multiple supply voltage nodes. Moreover, the foundry-provided timing libraries in the traditional STA (static timing analysis) approach are only available for the nominal supply voltage with limited voltage scaling, which cannot support timing verification for low voltages down to near- or sub-threshold voltages. In this paper, a learning-based approach for wide voltage design is proposed where feature engineering is performed to enhance the correlation among PVT corners based on a dilated CNN (convolutional neural network) model, and an ensemble model is utilized with two-layer stacking to improve timing prediction accuracy. The proposed method was verified with a commercial RISC (reduced instruction set computer) core under the supply voltage nodes ranging from 0.5 V to 0.9 V. Experimental results demonstrate that the prediction error is limited by 4.9% and 7.9%, respectively, within and across process corners for various working temperatures, which achieves up to 4.4× and 3.9× precision enhancement compared with related learning-based methods.
Ultra-Compact Reconfigurable Band Reject UWB MIMO Antenna with Four Radiators
Authors: Khan Muhammad Saeed , Iftikhar Adnan , Shubair Raed M. , Capobianco Antonio-Daniele , Asif Sajid Mehmood , Braaten Benjamin D. , Anagnostou Dimitris E.
Published: March 2020

A compact reconfigurable UWB MIMO antenna with four radiators that accomplish on-demand band rejection from 4.9 to 6.3 GHz is presented. An LC stub is connected to the ground plane by activating the PIN diode for each radiator. Two radiators are placed perpendicular to each other to exploit the polarization diversity on a compact 25 × 50 mm 2 FR4 laminate. Two additional radiators are then fixed obliquely on the same laminate (without increasing size) in angular configuration at ±45 ∘ perpendicular to the first two planar radiators still exploiting polarization diversity. The design is validated by prototyping and comparing the results with the simulated ones. On demand band rejection through the use of PIN diodes, wide impedance matching (2–12 GHz), high isolation amongst the radiators, compactness achieved by angular placement of the radiators, low gain variation over the entire bandwidth, band rejection control achieved by adjusting the gap between stub and ground plane, and low TARC values makes the proposed design very suitable for commercial handheld devices (i.e., Huawei E5785 and Netgear 815S housings). The proposed configuration of the UWB MIMO radiators has been investigated first time as per authors’ knowledge.
An Overview of FIR Filter Design in Future Multicarrier Communication Systems
Authors: Jiang Lei , Zhang Haijian , Cheng Shuai , Lv Hengwei , Li Pandong
Published: March 2020

Future wireless communication systems are facing with many challenges due to their complexity and diversification. Orthogonal frequency division multiplexing (OFDM) in 4G cannot meet the requirements in future scenarios, thus alternative multicarrier modulation (MCM) candidates for future physical layer have been extensively studied in the academic field, for example, filter bank multicarrier (FBMC), generalized frequency division multiplexing (GFDM), universal filtered multicarrier (UFMC), filtered OFDM (F-OFDM), and so forth, wherein the prototype filter design is an essential component based on which the synthesis and analysis filters are derived. This paper presents a comprehensive survey on the recent advances of finite impulse response (FIR) filter design methods in MCM based communication systems. Firstly, the fundamental aspects are examined, including the introduction of existing waveform candidates and the principle of FIR filter design. Then the methods of FIR filter design are summarized in details and we focus on the following three categories—frequency sampling methods, windowing based methods and optimization based methods. Finally, the performances of various FIR design methods are evaluated and quantified by power spectral density (PSD) and bit error rate (BER), and different MCM schemes as well as their potential prototype filters are discussed.
A Novel Autoencoder with Dynamic Feature Enhanced Factor for Fault Diagnosis of Wind Turbine
Authors: Nie Xiaoyin , Liu Shaoguang , Xie Gang
Published: March 2020

Due to the complicated operating environment and variable operating conditions, wind turbines (WTs) are extremely prone to failure and the frequency of fault increases year by year. Therefore, the solutions of effective condition monitoring and fault diagnosis are urgently demanded. Since the vibration signals contain a lot of health condition information, the fault diagnosis based on vibration signals has received extensive attention and achieved impressive progress. However, in practice, the collected health condition signals are very similar and contain a lot of noise, which makes the fault diagnosis of WTs more challenging. In order to handle this problem, this paper proposes a model called denoising stacked feature enhanced autoencoder with dynamic feature enhanced factor (DSFEAE-DF). Firstly, a feature enhanced autoencoder (FEAE) is constructed through feature enhancement so that the discriminative features can be extracted. Secondly, a feature enhanced factor which is independent of manual judgments is proposed and embedded into the training process. Finally, the DSFEAE-DF, combining one noise adding scheme, stacked FEAEs and dynamic feature enhanced factor, is established. Through experimental comparisons, the superiorities of the proposed DSFEAE-DF are verified.
Modeling the Carbon Cycle of a Subtropical Chinese Fir Plantation Using a Multi-Source Data Fusion Approach
Authors: Hu Longwei , He Honglin , Shen Yan , Ren Xiaoli , Yan Shao-kui , Xiang Wenhua , Ge Rong , Niu Zhongen , Xu Qian , Zhu Xiaobo
Published: March 2020

Process-based terrestrial ecosystem models are increasingly being used to predict carbon (C) cycling in forest ecosystems. Given the complexity of ecosystems, these models inevitably have certain deficiencies, and thus the model parameters and simulations can be highly uncertain. Through long-term direct observation of ecosystems, numerous different types of data have accumulated, providing valuable opportunities to determine which sources of data can most effectively reduce the uncertainty of simulation results, and thereby improve simulation accuracy. In this study, based on a long-term series of observations (biometric and flux data) of a subtropical Chinese fir plantation ecosystem, we use a model–data fusion framework to evaluate the effects of different constrained data on the parameter estimation and uncertainty of related variables, and systematically evaluate the uncertainty of parameters. We found that plant C pool observational data contributed to significant reductions in the uncertainty of parameter estimates and simulation, as these data provide information on C pool size. However, none of the data effectively constrained the foliage C pool, indicating that this pool should be a target for future observational activities. The assimilation of soil organic C observations was found to be important for reducing the uncertainty or bias in soil C pools. The key findings of this study are that the assimilation of multiple time scales and types of data stream are critical for model constraint and that the most accurate simulation results are obtained when all available biometric and flux data are used as constraints. Accordingly, our results highlight the importance of using multi-source data when seeking to constrain process-based terrestrial ecosystem models.
Options for Optimizing the Drying Process and Reducing Dry Matter Losses in Whole-Tree Storage of Poplar from Short-Rotation Coppices in Germany
Authors: Pecenka Ralf , Lenz Hannes , Hering Thomas
Published: March 2020

For sustainable production of wood in short-rotation coppices and agroforestry systems, it is necessary to optimize the storage processes to achieve low dry matter losses together with low-cost drying. The harvesting of the trees can be carried out very efficiently with modified forage harvesters or tractor-powered mower-chippers. The wood chips produced can be dried naturally at low cost in open-air piles. However, this type of storage is connected with high dry matter losses of up to about one fourth in the course of seven-month storage. Although harvesting whole trees is connected with significantly higher costs, lower dry matter losses are to be expected from storing the trees in piles. Consequently, in this study, the storage and drying behavior of poplar under different German weather conditions and depending on the structure of the storage piles has been examined in detail. After a seven-months storage period, the trees still displayed moisture contents of 41–44% following an initial moisture content of 56% but achieved very low dry matter losses of only 4–7%. Moisture contents of 35–39% could only be achieved in October after a further two-months drying period under favorable weather conditions. All storage piles were built up on approximately 30 cm high support timbers for better ventilation. Additionally, covering the ground with a fleece did not have any influence on the drying behavior, nor did different pile heights. Smaller tree trunk diameters are not only connected with a higher share of bark or ash, but also thinner trunks tend to become damp again more quickly after rainfall. That is why whole-tree storage is suitable above all for medium or longer rotation periods with which, under favorable conditions, the higher harvesting costs can be compensated by a higher wood chip quality and lower storage losses.
Impacts of Global Warming on the Radial Growth and Long-Term Intrinsic Water-Use Efficiency (iWUE) of Schrenk Spruce (Picea schrenkiana Fisch. et Mey) in the Sayram Lake Basin, Northwest China
Authors: Qin Li , Yuan Yujiang , Shang Huaming , Yu Shulong , Liu Weiping , Zhang Ruibo
Published: March 2020

Global warming and the sharp rise in atmospheric CO2 concentrations have a profound impact on forest ecosystems. To better manage these changes, a comprehensive understanding of forest ecosystem responses to global change is essential. There is a lack of knowledge about the growth response of Schrenk spruce (Picea schrenkiana Fisch. et Mey)—an endemic tree species found in the arid Central Asian region—to climate change and rising atmospheric CO2 concentrations. In this study, core samples of Schrenk spruce were collected in the Sayram Lake Basin, Xinjiang. Tree-ring radial growth and long-term intrinsic water-use efficiency (iWUE) chronologies were established based on standard tree-ring width and stable carbon isotope methods. The relationships between atmospheric CO2 concentrations, climate, radial growth, and iWUE were analyzed. Our results indicate that the iWUE of trees in this region has continued to rise rapidly but that radial growth has not increased over the past 160 years. The main factor affecting iWUE is atmospheric CO2 concentrations (Ca), whereas the radial growth is much more sensitive to water availability. This may explain why the increase Ca has not had a fertilizer effect on the radial growth of trees.
Geoecological Assessment of Anthropogenic Impacts on the Osetr River Basin
Authors: Yurova Yuliya , Shirokova Vera
Published: March 2020

This paper presents the results of a geoecological assessment of the human-induced impact on the geosystem components of the Osetr river basin in the Moscow region. To assess the surface water quality of this river basin, hydrochemical surveys were conducted which included the determination of parameters such as the pH index, water temperature, the amount of dissolved oxygen (O2), electrical conductivity, salt content, COD (chemical oxygen demand), BOD5 (biochemical oxygen demand for 5 days), etc. Within the framework of ecological monitoring, a reconnaissance survey of the dam in Zaraysk was conducted, during which the basic ecological indicators were determined. The assessment was performed to assess the radiation, chemical, sanitary, epidemiological, and physical–ecological risk factors. The work resulted in geoecological zoning of the middle part of the Osetr river basin based on water pollution levels (WPI—water pollution index, SCWPI—specific combinatorial water pollution index), the amount of human-induced impact, and the human-induced load (point-rating method), using definitions of five categories of river channel sections with human-induced load and ecosystem conditions.
Groundwater Storage Changes Derived from GRACE and GLDAS on Smaller River Basins—A Case Study in Poland
Authors: Rzepecka Zofia , Birylo Monika
Published: March 2020

In the era of global climate change, the monitoring of water resources, including groundwater, is of fundamental importance for nature, agriculture, economy and society. The purpose of this paper is to check compliance of changes in groundwater level obtained from direct measurements in wells with groundwater storage (GWS) anomalies calculated using gravity recovery and climate experiment (GRACE) observations in Poland. Data from the global land data assimilation (GLDAS), in the form of soil moisture (SM) and snow water equivalence (SWE), were used to convert GRACE observations into a series of GWS changes. It was found that very high consistency occurs between GRACE observations and changes in water level in wells, while the GWS series obtained from GRACE and GLDAS do not provide adequate compatibility. Further research presented in the paper was devoted to attempts to explain this phenomenon. In addition, time series of GRACE, GLDAS and groundwater head series were analyzed.
“Look at Me, I Plan to Quit Smoking”: Bayesian Hierarchical Analysis of Adolescent Smokers’ Intention to Quit Smoking
Authors: Ng’ombe John N. , Nedson N. Rodgers , Tembo Novan F. P.
Published: March 2020

The tobacco epidemic is one of the most prominent public health threats the world has ever faced. Public health policy that seeks to limit the problem may have to target not only the price of tobacco but also the initiation stage in a smoker’s life—the adolescent stage. Most research on teen smoking focuses on initiation and other stories. Moreover, what determines the desire to quit smoking among teens is not well understood, even though planning to quit smoking is an important stage toward successful cessation. This research contributes to healthcare literature by using Bayesian hierarchical techniques, estimated using Hamiltonian Monte Carlo (HMC) and its extension, the No-U-Turn Sampler (NUTS), to empirically identify what drives the intention to quit smoking among teen smokers in Zambia. Results suggest that, among the junior secondary school-going adolescent smokers in Zambia, about 63% have plans to quit smoking. We find socio-demographic characteristics and several tobacco-smoking-related factors as salient drivers of adolescent smokers’ plans to quit smoking. For policymaking, we recommend that school-going teen smokers should have access to smoking cessation aids to help them quit smoking. Most importantly, increased awareness of dangers of smoking, advice by health professionals, stringent public policies on smoking, as well as parental guidance could be useful to help adolescent smokers realize their quitting plans.
Cultural Heritage as a Means for Local Development in Mediterranean Historic Cities—The Need for an Urban Policy
Authors: Theodora Yiota
Published: March 2020

Urban and regional development have not stopped engaging, troubling, and dividing the international scientific community and national and regional policy-making bodies. The wide range of consequences brought on by the current multifaceted downturn at all geographical scales requires the continuous investigation of practices and the designation of innovative mechanisms or tools to formulate new developmental axes for action, able to respond to contemporary needs and challenges. This holds true particularly in an age, such as the one we are currently experiencing, of network organization of infrastructures and functions dominated by the knowledge economy. Within this framework, we estimate that the response to an attempt to restructure production in Greece and increase support for its cities and regions could be sought by setting up collaboration networks with cultural heritageand support creative entrepreneurship as key developmental “elements”, focusing on strategies for recovery, modernization, and a return to historic cities and regional settlements. Specifically, using inputs from a collaboration project among historic cities in the Mediterranean, and an ongoing research in fragmented insular regions with many historic cities and settlements in the Aegean, we maintain that the goal of restoring local communities could be sought though initiatives or actions to preserve and diffuselocal traditions and know-how in the framework of an overall urban developmental policy capable of ensuring ongoing collaboration and networking at all geographical levels and categories of space. In this rationale, this article attempts to contribute to the debate by stating proposals in the framework of principles and guidelines that should govern the formulation of this urban policy, which is still missing in Greece.
What Protects Youth Residential Caregivers from Burning Out? A Longitudinal Analysis of Individual Resilience
Authors: Kind Nina , Bürgin David , Fegert Jörg M. , Schmid Marc
Published: March 2020

Background: Professional caregivers are exposed to multiple stressors and have high burnout rates; however, not all individuals are equally susceptible. We investigated the association between resilience and burnout in a Swiss population of professional caregivers working in youth residential care. Methods: Using a prospective longitudinal study design, participants (n = 159; 57.9% women) reported on burnout symptoms and sense of coherence (SOC), self-efficacy and self-care at four annual sampling points. The associations of individual resilience measures and sociodemographic variables, work-related and personal stressors, and burnout symptoms were assessed. Cox proportional hazards regressions were calculated to compute hazard ratios over the course of three years. Results: Higher SOC, self-efficacy and self-care were related to lower burnout symptoms in work-related and personal domains. Higher SOC and self-efficacy were reported by older caregivers and by those with children. All three resilience measures were highly correlated. A combined model analysis weakened the protective effect of self-efficacy, leaving only SOC and self-care negatively associated with burnout. Conclusion: This longitudinal analysis suggests that SOC and self-caring behaviour in particular protect against burnout. Our findings could have implications for promoting self-care practices, as well as cultivating a meaningful, comprehensible and manageable professional climate in all facets of institutional care.
Comparing Paclitaxel–Carboplatin with Paclitaxel–Cisplatin as the Front-Line Chemotherapy for Patients with FIGO IIIC Serous-Type Tubo-Ovarian Cancer
Authors: Huang Chen-Yu , Cheng Min , Lee Na-Rong , Huang Hsin-Yi , Lee Wen-Ling , Chang Wen-Hsun , Wang Peng-Hui
Published: March 2020

The use of weekly chemotherapy for the treatment of patients with advanced-stage serous-type epithelial Tubo-ovarian cancer (ETOC), and primary peritoneal serous carcinoma (PPSC) is acceptable as the front-line postoperative chemotherapy after primary cytoreductive surgery (PCS). The main component of dose-dense chemotherapy is weekly paclitaxel (80 mg/m2), but it would be interesting to know what is the difference between combination of triweekly cisplatin (20 mg/m2) or triweekly carboplatin (carboplatin area under the curve 5-7 mg/mL per min [AUC 5-7]) in the dose-dense paclitaxel regimen. Therefore, we compared the outcomes of women with Gynecology and Obstetrics (FIGO) stage IIIC ETOC and PPSC treated with PCS and a subsequent combination of dose-dense weekly paclitaxel and triweekly cisplatin (paclitaxel–cisplatin) or triweekly carboplatin using AUC 5 (paclitaxel–carboplatin). Between January 2010 and December 2016, 40 women with International Federation of Gynecology and Obstetrics (FIGO) stage IIIC EOC, FTC, or PPSC were enrolled, including 18 treated with paclitaxel–cisplatin and the remaining 22 treated with paclitaxel–carboplatin. There were no statistically significant differences in disease characteristics of patients between two groups. Outcomes in paclitaxel–cisplatin group seemed to be little better than those in paclitaxel–carboplatin (median progression-free survival [PFS] 30 versus 25 months as well as median overall survival [OS] 58.5 versus 55.0 months); however, neither reached a statistically significant difference. In terms of adverse events (AEs), patients in paclitaxel–carboplatin group had more AEs, with a higher risk of neutropenia and grade 3/4 neutropenia, and the need for a longer period to complete the front-line chemotherapy, and the latter was associated with worse outcome for patients. We found that a period between the first-time chemotherapy to the last dose (6 cycles) of chemotherapy >21 weeks was associated with a worse prognosis in patients compared to that ≤21 weeks, with hazard ratio (HR) of 81.24 for PFS and 9.57 for OS. As predicted, suboptimal debulking surgery (>1 cm) also contributed to a worse outcome than optimal debulking surgery (≤1 cm) with HR of 14.38 for PFS and 11.83 for OS. Based on the aforementioned findings, both regimens were feasible and effective, but maximal efforts should be made to achieve optimal debulking surgery and following the on-schedule administration of dose-dense weekly paclitaxel plus triweekly platinum compounds. Randomized trials validating the findings are warranted.
Screen Exposure during Early Life and the Increased Risk of Astigmatism among Preschool Children: Findings from Longhua Child Cohort Study
Authors: Huang Lihua , Yang Gui-You , Schmid Katrina L. , Chen Jing-Yi , Li Chen-Guang , He Guan-Hao , Ruan Zeng-Liang , Chen Wei-Qing
Published: March 2020

Screen media usage has become increasingly prevalent in daily life with children being exposed to screens at an early age. This is a growing public health concern with evidence linking screen exposure to detrimental health outcomes, whereas relationship between screen exposure and the presence of astigmatism among preschoolers remains unknown, thus we aimed to resolve this issue. During the 2017 survey of the Longhua Child Cohort Study, data of 29,595 preschoolers were collected via a caregiver-reported questionnaire regarding socio-demographics, screen exposure and refraction. Cox regression models were adopted to generate adjusted prevalence ratios (APR) and 95% confidence intervals (CI) to estimate the association between early screen exposure and astigmatism. 28,029 preschoolers were included in the final analysis. After adjustment for potential confounders, screen exposure during early life was significantly associated with the increased risk of astigmatism (APR and 95% CI: 2.25, 1.76–2.88), and the greatest risk was observed in the period from birth to 1-year (APR and 95% CI: 3.10, 2.41–3.98). The risk of astigmatism increased with both the total years of exposure and the average daily duration of screen exposure. Our findings suggested that preschoolers who were exposed to screens during early life might have an increased risk of astigmatism.
Health Care and Productivity Costs of Non-Fatal Traffic Injuries: A Comparison of Road User Types
Authors: van der Vlegel Marjolein , Haagsma Juanita A. , de Munter Leonie , de Jongh Mariska A. C. , Polinder Suzanne
Published: March 2020

This study aimed to provide a detailed overview of the health care and productivity costs of non-fatal road traffic injuries by road user type. In a cohort study in the Netherlands, adult injury patients admitted to a hospital as a result of a traffic accident completed questionnaires 1 week and 1, 3, 6, 12 and 24 months after injury, including the iMTA Medical Consumption and Productivity Cost Questionnaire. In-hospital, post-hospital medical costs and productivity costs were calculated up to two years after traffic injury. In total, 1024 patients were included in this study. The mean health care costs per patient were € 8200. The mean productivity costs were € 5900. Being female, older age, with higher injury severity and having multiple comorbidities were associated with higher health care costs. Higher injury severity and being male were associated with higher productivity costs. Pedestrians aged ≥ 65 years had the highest mean health care costs (€ 18,800) and motorcyclists the highest mean productivity costs (€ 9000). Bicycle injuries occurred most often in our sample (n = 554, 54.1%) and accounted for the highest total health care and productivity costs. Considering the high proportion of total costs incurred by bicycle injuries, this is an important area for the prevention of traffic injuries.
Effects of Different Environmental Factors on the Growth and Bioactive Substance Accumulation of Porphyridium purpureum
Authors: Lu Xudan , Nan Fangru , Feng Jia , Lv Junping , Liu Qi , Liu Xudong , Xie Shulian
Published: March 2020

Genus Porphyridium is a primitive single-celled red algae widely distributed in seawater, freshwater, and moist soil. It can synthesize bioactive substances such as phycoerythrin, extracellular polysaccharides and polyunsaturated fatty acids during the growth process. In this paper, the culture and bioactive substance yield of Porphyridium purpureum were studied by setting salinity, nitrogen-to-phosphorus ratio, and pH at different gradient levels. The results showed that the optimal conditions for the growth of P. purpureum were salinity 34 ppt, nitrogen-to-phosphorus ratio 169:1, and pH 8; the optimal conditions for obtaining the polysaccharides were salinity 17 ppt, nitrogen-to-phosphorus ratio 14:1, and pH 8; the optimal conditions for obtaining phycoerythrin were salinity 17 ppt, nitrogen-to-phosphorus ratio 68:1, and pH 8; the optimal conditions for obtaining the lipids were salinity 34 ppt, nitrogen-to-phosphorus ratio 1:1, and pH 8. In actual production applications, culture conditions should be set according to different product accumulation purposes in order to achieve the optimal production efficiency.
Psychological and Sleep Effects of Tryptophan and Magnesium-Enriched Mediterranean Diet in Women with Fibromyalgia
Authors: Martínez-Rodríguez Alejandro , Rubio-Arias Jacobo Á. , Ramos-Campo Domingo J. , Reche-García Cristina , Leyva-Vela Belén , Nadal-Nicolás Yolanda
Published: March 2020

Anxiety, mood disturbance, eating and sleep disorders, and dissatisfaction with body image are prevalent disorders in women with fibromyalgia. The authors of this study aimed to determine the effects of tryptophan (TRY) and magnesium-enriched (MG) Mediterranean diet on psychological variables (trait anxiety, mood state, eating disorders, self-image perception) and sleep quality in women with fibromyalgia (n = 22; 49 ± 5 years old). In this randomized, controlled trial, the participants were randomly assigned to the experimental group and the placebo group. The intervention group received a Mediterranean diet enriched with high doses of TRY and MG (60 mg of TRY and 60 mg of MG), whereas the control group received the standard Mediterranean diet. Pittsburgh Sleep Quality Questionnaire, Body Shape Questionnaire, State–Trait Anxiety Inventory (STAI), Profile of Mood States (POMS-29) Questionnaire, Eating Attitudes Test-26, and Trait Anxiety Inventory were completed before and 16 weeks after the intervention. Significant differences were observed between groups after the intervention for the mean scores of trait anxiety (p = 0.001), self-image perception (p = 0.029), mood disturbance (p = 0.001), and eating disorders (p = 0.006). This study concludes that tryptophan and magnesium-enriched Mediterranean diet reduced anxiety symptoms, mood disturbance, eating disorders, and dissatisfaction with body image but did not improve sleep quality in women with fibromyalgia.
Contextualising the 2019 E-Cigarette Health Scare: Insights from Twitter
Authors: Ahmed Wasim , Marin-Gomez Xavier , Vidal-Alaball Josep
Published: March 2020

A health scare can be described as a campaign that attempts to alert the public of a particular substance or activity that can lead to a negative effect on health. A recent health scare to emerge relates to the health hazards associated with the use of e-cigarettes, which has caused widespread debate, which peaked towards the end of 2019. Health scares need to be studied in the context in which they occur, and one method of studying them is through social media. This paper identifies two key topics of discussion on Twitter, which consisted of pro-vaping and anti-vaping views. The paper then identifies influential users, frequently occurring words, hashtags, and websites related to this time period in order to gain insight into e-cigarette perceptions. The paper then reviews current scientific evidence and develops a flowchart for the general public, which can be used to for public reassurance and guidance.
Respiratory Health in a Community Living in Close Proximity to Gold Mine Waste Dumps, Johannesburg, South Africa
Authors: Iyaloo Samantha , Kootbodien Tahira , Naicker Nisha , Kgalamono Spo , Wilson Kerry S. , Rees David
Published: March 2020

The effects on respiratory health in populations living close to silica-rich gold mine dumps are unknown. This pilot study related respiratory health and exposure to mine dump dust using two measures of exposure: exposure group, based on distance lived from the mine dump—high (n = 93) (home <500 m from a mine dump), moderate (n = 133) (500–1.5 km), and low (n = 84) (>15 km, control group); and cumulative exposure index (CEI) derived from exposure group and number of years of residence in each exposure group. Participants were interviewed about respiratory symptoms and had chest X-rays and spirometry. We adjusted for key respiratory confounders. No subject had radiological features of silicosis. The high relative to low exposure group had significantly elevated adjusted odds ratios (aORs) for upper respiratory symptoms (aOR: 2.76, 95% CI: 1.28–5.97), chest wheezing (aOR: 3.78; 95% CI: 1.60–8.96), and spirometry-diagnosed chronic obstructive pulmonary disease (COPD) (aOR: 8.17; 95%CI: 1.01–65.85). These findings were similar for the high relative to medium exposure group, but no significant associations were found for the medium versus low exposure group. Chronic bronchitis and tuberculosis risks did not differ significantly among groups. CEI and exposure group produced similar results. In conclusion, residents residing <500 m from mine dumps had elevated adverse respiratory health effects.
Comment on Hardacker, C.T.; Baccellieri, A.; Mueller, E.R.; Brubaker, L.; Hutchins, G.; Zhang, J.L.Y.; Hebert-Beirne, J. Bladder Health Experiences, Perceptions and Knowledge of Sexual and Gender Minorities. Int. J. Environ. Res. Public Health 2019, 16, 3170
Authors: Jue Joshua S. , Alameddine Mahmoud
Published: March 2020

Our knowledge of voiding is derived from studies comprised of cisgender males and females, with relatively little known about the impact of sexual and gender minority status on voiding perceptions, symptoms, and function [...]
Landslide Image Captioning Method Based on Semantic Gate and Bi-Temporal LSTM
Authors: Cui Wenqi , He Xin , Yao Meng , Wang Ziwei , Li Jie , Hao Yuanjie , Wu Weijie , Zhao Huiling , Chen Xianfeng , Cui Wei
Published: March 2020

When a landslide happens, it is important to recognize the hazard-affected bodies surrounding the landslide for the risk assessment and emergency rescue. In order to realize the recognition, the spatial relationship between landslides and other geographic objects such as residence, roads and schools needs to be defined. Comparing with semantic segmentation and instance segmentation that can only recognize the geographic objects separately, image captioning can provide richer semantic information including the spatial relationship among these objects. However, the traditional image captioning methods based on RNNs have two main shortcomings: the errors in the prediction process are often accumulated and the location of attention is not always accurate which would lead to misjudgment of risk. To handle these problems, a landslide image interpretation network based on a semantic gate and a bi-temporal long-short term memory network (SG-BiTLSTM) is proposed in this paper. In the SG-BiTLSTM architecture, a U-Net is employed as an encoder to extract features of the images and generate the mask maps of the landslides and other geographic objects. The decoder of this structure consists of two interactive long-short term memory networks (LSTMs) to describe the spatial relationship among these geographic objects so that to further determine the role of the classified geographic objects for identifying the hazard-affected bodies. The purpose of this research is to judge the hazard-affected bodies of the landslide (i.e., buildings and roads) through the SG-BiTLSTM network to provide geographic information support for emergency service. The remote sensing data was taken by Worldview satellite after the Wenchuan earthquake happened in 2008. The experimental results demonstrate that SG-BiTLSTM network shows remarkable improvements on the recognition of landslide and hazard-affected bodies, compared with the traditional LSTM (the Baseline Model), the BLEU1 of the SG-BiTLSTM is improved by 5.89%, the matching rate between the mask maps and the focus matrix of the attention is improved by 42.81%. In conclusion, the SG-BiTLSTM network can recognize landslides and the hazard-affected bodies simultaneously to provide basic geographic information service for emergency decision-making.
An Approach Based on Landsat Images for Shoreline Monitoring to Support Integrated Coastal Management—A Case Study, Ezbet Elborg, Nile Delta, Egypt
Authors: Elnabwy Mohamed T. , Elbeltagi Emad , El Banna Mahmoud M. , Elshikh Mohamed M.Y. , Motawa Ibrahim , Kaloop Mosbeh R.
Published: March 2020

Monitoring the dynamic behavior of shorelines is an essential factor for integrated coastal management (ICM). In this study, satellite-derived shorelines and corresponding eroded and accreted areas of coastal zones have been calculated and assessed for 15 km along the coasts of Ezbet Elborg, Nile Delta, Egypt. A developed approach is designed based on Landsat satellite images combined with GIS to estimate an accurate shoreline changes and study the effect of seawalls on it. Landsat images for the period from 1985 to 2018 are rectified and classified using Supported Vector Machines (SVMs) and then processed using ArcGIS to estimate the effectiveness of the seawall that was constructed in year 2000. Accuracy assessment results show that the SVMs improve images accuracy up to 92.62% and the detected shoreline by the proposed method is highly correlated (0.87) with RTK-GPS measurements. In addition, the shoreline change analysis presents that a dramatic erosion of 2.1 km2 east of Ezbet Elborg seawall has occurred. Also, the total accretion areas are equal to 4.40 km2 and 10.50 km2 in between 1985-and-2000 and 2000-and-2018, respectively, along the southeast side of the study area.
DM-SLAM: A Feature-Based SLAM System for Rigid Dynamic Scenes
Authors: Cheng Junhao , Wang Zhi , Zhou Hongyan , Li Li , Yao Jian
Published: March 2020

Most Simultaneous Localization and Mapping (SLAM) methods assume that environments are static. Such a strong assumption limits the application of most visual SLAM systems. The dynamic objects will cause many wrong data associations during the SLAM process. To address this problem, a novel visual SLAM method that follows the pipeline of feature-based methods called DM-SLAM is proposed in this paper. DM-SLAM combines an instance segmentation network with optical flow information to improve the location accuracy in dynamic environments, which supports monocular, stereo, and RGB-D sensors. It consists of four modules: semantic segmentation, ego-motion estimation, dynamic point detection and a feature-based SLAM framework. The semantic segmentation module obtains pixel-wise segmentation results of potentially dynamic objects, and the ego-motion estimation module calculates the initial pose. In the third module, two different strategies are presented to detect dynamic feature points for RGB-D/stereo and monocular cases. In the first case, the feature points with depth information are reprojected to the current frame. The reprojection offset vectors are used to distinguish the dynamic points. In the other case, we utilize the epipolar constraint to accomplish this task. Furthermore, the static feature points left are fed into the fourth module. The experimental results on the public TUM and KITTI datasets demonstrate that DM-SLAM outperforms the standard visual SLAM baselines in terms of accuracy in highly dynamic environments.
CostNet: A Concise Overpass Spatiotemporal Network for Predictive Learning
Authors: Sun Fengzhen , Li Shaojie , Wang Shaohua , Liu Qingjun , Zhou Lixin
Published: March 2020

Predicting the futures from previous spatiotemporal data remains a challenging topic. There have been many previous works on predictive learning. However, mainstream models suffer from huge memory usage or the gradient vanishing problem. Enlightened by the idea from the resnet, we propose CostNet, a novel recursive neural network (RNN)-based network, which has a horizontal and vertical cross-connection. The core of this network is a concise unit, named Horizon LSTM with a fast gradient transmission channel, which can extract spatial and temporal representations effectively to alleviate the gradient propagation difficulty. In the vertical direction outside of the unit, we add overpass connections from unit output to the bottom layer, which can capture the short-term dynamics to generate precise predictions. Our model achieves better prediction results on moving-mnist and radar datasets than the state-of-the-art models.
Spatial Analysis of the Rural-Urban Structure of the Spanish Municipalities
Authors: Nieto Masot Ana , Cárdenas Alonso Gema , Engelmo Moriche Ángela
Published: March 2020

The rural–urban dichotomy is one of the most debated topics by the scientific community in territorial issues. In addition, many public entities and scientific studies have established the distinctive elements of rural and urban spaces by relating the decline of the rural ones with factors such as aging, low birthrate, the primary sector, unemployment, or poverty, among others. Therefore, the purpose of this paper is to spatially study the current model of territorial organization of Spanish urban and rural municipalities as well as their demographic and socioeconomic characteristics. To this end, GIS (Geographic Information System) tools were used to carry out a spatial autocorrelation (SA) analysis and to identify homogeneous groups of the variables considered. In conclusion, there are different demographic and socioeconomic realities in Spain, an urban one located on the coast with a positive situation and, on the other hand, a regressive reality composed of rural municipalities, among which there are villages whose situation is worrying, mainly located in the north of Spain.
Multilingual Transformer-Based Personality Traits Estimation
Authors: Leonardi Simone , Monti Diego , Rizzo Giuseppe , Morisio Maurizio
Published: March 2020

Intelligent agents have the potential to understand personality traits of human beings because of their every day interaction with us. The assessment of our psychological traits is a useful tool when we require them to simulate empathy. Since the creation of social media platforms, numerous studies dealt with measuring personality traits by gathering users’ information from their social media profiles. Real world applications showed how natural language processing combined with supervised machine learning algorithms are effective in this field. These applications have some limitations such as focusing on English text only and not considering polysemy in text. In this paper, we propose a multilingual model that handles polysemy by analyzing sentences as a semantic ensemble of interconnected words. The proposed approach processes Facebook posts from the myPersonality dataset and it turns them into a high-dimensional array of features, which are then exploited by a deep neural network architecture based on transformer to perform regression. We prove the effectiveness of our work by comparing the mean squared error of our model with existing baselines and the Kullback–Leibler divergence between the relative data distributions. We obtained state-of-the-art results in personality traits estimation from social media posts for all five personality traits.
Preliminary Study on the Knowledge Graph Construction of Chinese Ancient History and Culture
Authors: Liu Shuang , Yang Hui , Li Jiayi , Kolmanič Simon
Published: March 2020

The domestic population has paid increasing attention to ancient Chinese history and culture with the continuous improvement of people’s living standards, the rapid economic growth, and the rapid advancement of information science and technology. The use of information technology has been proven to promote the spread and development of historical culture, and it is becoming a necessary means to promote our traditional culture. This paper will build a knowledge graph of ancient Chinese history and culture in order to facilitate the public to more quickly and accurately understand the relevant knowledge of ancient Chinese history and culture. The construction process is as follows: firstly, use crawler technology to obtain text and table data related to ancient history and culture on Baidu Encyclopedia (similar to Wikipedia) and ancient Chinese history and culture related pages. Among them, the crawler technology crawls the semi-structured data in the information box (InfoBox) in the Baidu Encyclopedia to directly construct the triples required for the knowledge graph, crawls the introductory text information of the entries in Baidu Encyclopedia, and specialized historical and cultural websites (history Chunqiu.com, On History.com) to extract unstructured entities and relationships. Secondly, entity recognition and relationship extraction are performed on an unstructured text. The entity recognition part uses the Bidirectional Long Short-Term Memory-Convolutional Neural Networks-Conditions Random Field (BiLSTM-CNN-CRF) model for entity extraction. The relationship extraction between entities is performed by using the open source tool DeepKE (information extraction tool with language recognition ability developed by Zhejiang University) to extract the relationships between entities. After obtaining the entity and the relationship between the entities, supplement it with the triple data that were constructed from the semi-structured data in the existing knowledge base and Baidu Encyclopedia information box. Subsequently, the ontology construction and the quality evaluation of the entire constructed knowledge graph are performed to form the final knowledge graph of ancient Chinese history and culture.
Virtual Offenses: Role of Demographic Factors and Personality Traits
Authors: Sudzina Frantisek , Pavlicek Antonin
Published: March 2020

A number of positive and negative trends are becoming more prevalent, along with the widespread use of information and communication technologies in everyday life—negative ones being virtual offences such as stalking, bullying, identity theft, scamming and abuse or harassment. The article discusses the relations between demographic factors, the occurrence of virtual offenses and personality traits. The next Big Five Inventory (BFI-2) was used for assessment of personality traits. As for the findings, more extraversion, less agreeableness, more negative emotionality, less consciousness and being a man have been found to be associated with at least one of the investigated types of virtual offenses.