bluuebunny/crossref_metadata_2025 huggingface dataset:
HEVC’s Intra Mode Selection Using Odds Algorithm
Authors: Armghan Ammar , Tariq Junaid , Alenezi Fayadh , Alnaim Norah , Alfalou Ayman , Rehman Saad
Published: August 2021

The brute-force behaviour of High-Efficiency Video Coding (HEVC) is the biggest hurdle in the communication of the multimedia contents. Therefore, a novel method will be presented here to expedite the intra mode decision process of HEVC. In the first step, the feasibility of the odds-algorithm for the early intra mode decision is presented by using statistical evidence. Then, various elements of odds algorithm are analyzed and then mapped to the intra mode process (elements) of HEVC. Finally, the probability required by the odds algorithm is obtained by utilizing the correlation between the current and the neighboring blocks. The proposed algorithm accelerated the encoding process of the HEVC by 25% to 35%, while the Bjontegaard Delta Bit Rate (BD-BR) is 0.95% to 1.84%.
Special Issue on Computational Intelligence for Healthcare
Authors: Casalino Gabriella , Castellano Giovanna
Published: August 2021

The number of patient health data has been estimated to have reached 2314 exabytes by 2020 [...]
A Hybrid Control Scheme with Fast Transient and Low Harmonic for Boost PFC Converter
Authors: Wu Sen-Tung , Chen Fu-Yuan , Chien Min-Chu , Wang Jian-Min , Su Yan-Ying
Published: August 2021

In this study, a new control strategy was proposed to improve transient response and the input current harmonic distortion of power factor correction (PFC) regulators operating in an average current mode. The proposed technique required only two additional gain selectors and a peak detector circuit on the feedforward voltage loop and output voltage feedback loops. It provided a direct reading for the average voltage value of feedback control loops and the peak voltage of feedforward control loops, producing PFC boost regulators with fast dynamic responses and low-input current harmonic distortion. The use of digital potentiometers for directly changing the gain of control loops did not require any divider or squarer to reduce the complexity of control circuits. The operating principles and control strategies of 300 W boost PFC with the new control strategy are presented with detailed analysis and discussion. The experimental results were satisfactory.
A Study on the Variable Inductor Design by Switching the Main Paths and the Coupling Coils
Authors: Chiang Yen-Chung , Chen Juo-Chen , Chang Yu-Hsin
Published: August 2021

In a radio frequency (RF) system, it is possible to use variable inductors for providing tunable or selective frequency range. Variable inductors can be implemented by the microelectromechanical system (MEMS) process or by using transistors as switches to change the routing of coils or coupling quantities. In this paper, we investigated the design method of a variable inductor by using MOS transistors to switch the main coil paths and the secondary coupled coils. We observed the effects of different metal layers, turn numbers, and layout arrangements for secondary-coupled coils and compared their characteristics on the inductances and quality factors. We implemented two chips in the 0.18 μm CMOS process technology for each kind of arrangement for verification. One inductor can achieve inductance values from about 300 pH to 550 pH, and the other is between 300 pH and 575 pH, corresponding to 59.3% and 62.5%, respectively, inductance variation range at 4 GHz frequency. Additionally, their fine step sizes of the switched inductances are from 0.5% to 6% for one design, and 1% to 12.5% for the other. We found that both designs achieved a large inductance tuning range and moderate inductance step sizes with a slight difference behavior on the inductance variation versus frequency.
Evolutionary Convolutional Neural Network Optimization with Cross-Tasks Transfer Strategy
Authors: Wang Zhao , Lu Di , Wang Huabing , Liu Tongfei , Li Peng
Published: August 2021

Convolutional neural networks (CNNs) have shown great success in a variety of real-world applications and the outstanding performance of the state-of-the-art CNNs is primarily driven by the elaborate architecture. Evolutionary convolutional neural network (ECNN) is a promising approach to design the optimal CNN architecture automatically. Nevertheless, most of the existing ECNN methods only focus on improving the performance of the discovered CNN architectures without considering the relevance between different classification tasks. Transfer learning is a human-like learning approach and has been introduced to solve complex problems in the domain of evolutionary algorithms (EAs). In this paper, an effective ECNN optimization method with cross-tasks transfer strategy (CTS) is proposed to facilitate the evolution process. The proposed method is then evaluated on benchmark image classification datasets as a case study. The experimental results show that the proposed method can not only speed up the evolutionary process significantly but also achieve competitive classification accuracy. To be specific, our proposed method can reach the same accuracy at least 40 iterations early and an improvement of accuracy for 0.88% and 3.12% on MNIST-FASHION and CIFAR10 datasets compared with ECNN, respectively.
Comparison of the Radial Growth Response of Picea crassifolia to Climate Change in Different Regions of the Central and Eastern Qilian Mountains
Authors: Wu Xuan , Jiao Liang , Du Dashi , Qi Changliang , Xue Ruhong
Published: August 2021

It is important to explore the responses of radial tree growth in different regions to understand growth patterns and to enhance forest management and protection with climate change. We constructed tree ring width chronologies of Picea crassifolia from different regions of the Qilian Mountains of northwest China. We used Pearson correlation and moving correlation to analyze the main climate factors limiting radial growth of trees and the temporal stability of the growth–climate relationship, while spatial correlation is the result of further testing the first two terms in space. The conclusions were as follows: (1) Radial growth had different trends, showing an increasing followed by a decreasing trend in the central region, a continuously increasing trend in the eastern region, and a gradually decreasing trend in the isolated mountain. (2) Radial tree growth in the central region and isolated mountains was constrained by drought stress, and tree growth in the central region was significantly negatively correlated with growing season temperature. Isolated mountains showed a significant negative correlation with mean minimum of growing season and a significant positive correlation with total precipitation. (3) Temporal dynamic responses of radial growth in the central region to the temperatures and SPEI (the standardized precipitation evapotranspiration index) in the growing season were unstable, the isolated mountains to total precipitation was unstable, and that to SPEI was stable. The results of this study suggest that scientific management and maintenance plans of the forest ecosystem should be developed according to the response and growth patterns of the Qinghai spruce to climate change in different regions of the Qilian Mountains.
Low Cost Automatic Reconstruction of Tree Structure by AdQSM with Terrestrial Close-Range Photogrammetry
Authors: Dong Yanqi , Fan Guangpeng , Zhou Zhiwu , Liu Jincheng , Wang Yongguo , Chen Feixiang
Published: August 2021

The quantitative structure model (QSM) contains the branch geometry and attributes of the tree. AdQSM is a new, accurate, and detailed tree QSM. In this paper, an automatic modeling method based on AdQSM is developed, and a low-cost technical scheme of tree structure modeling is provided, so that AdQSM can be freely used by more people. First, we used two digital cameras to collect two-dimensional (2D) photos of trees and generated three-dimensional (3D) point clouds of plot and segmented individual tree from the plot point clouds. Then a new QSM-AdQSM was used to construct tree model from point clouds of 44 trees. Finally, to verify the effectiveness of our method, the diameter at breast height (DBH), tree height, and trunk volume were derived from the reconstructed tree model. These parameters extracted from AdQSM were compared with the reference values from forest inventory. For the DBH, the relative bias (rBias), root mean square error (RMSE), and coefficient of variation of root mean square error (rRMSE) were 4.26%, 1.93 cm, and 6.60%. For the tree height, the rBias, RMSE, and rRMSE were—10.86%, 1.67 m, and 12.34%. The determination coefficient (R2) of DBH and tree height estimated by AdQSM and the reference value were 0.94 and 0.86. We used the trunk volume calculated by the allometric equation as a reference value to test the accuracy of AdQSM. The trunk volume was estimated based on AdQSM, and its bias was 0.07066 m3, rBias was 18.73%, RMSE was 0.12369 m3, rRMSE was 32.78%. To better evaluate the accuracy of QSM’s reconstruction of the trunk volume, we compared AdQSM and TreeQSM in the same dataset. The bias of the trunk volume estimated based on TreeQSM was −0.05071 m3, and the rBias was −13.44%, RMSE was 0.13267 m3, rRMSE was 35.16%. At 95% confidence interval level, the concordance correlation coefficient (CCC = 0.77) of the agreement between the estimated tree trunk volume of AdQSM and the reference value was greater than that of TreeQSM (CCC = 0.60). The significance of this research is as follows: (1) The automatic modeling method based on AdQSM is developed, which expands the application scope of AdQSM; (2) provide low-cost photogrammetric point cloud as the input data of AdQSM; (3) explore the potential of AdQSM to reconstruct forest terrestrial photogrammetric point clouds.
Asymmetrical Lightning Fire Season Expansion in the Boreal Forest of Northeast China
Authors: Gao Cong , An Ran , Wang Wenqian , Shi Chunming , Wang Mingyu , Liu Kezhen , Wu Xiaoxu , Wu Guocan , Shu Lifu
Published: August 2021

All-season warming is assumed to advance snowmelt and delay snow accumulation; additionally, coupled with warming-induced drought stress, all-season warming could extend both the beginning and the end of the fire season. Using fire data updated for 1968–2018, we found an asymmetrical expansion of the lightning fire season in the boreal forest of Northeast China. Lightning fires have not advanced into the early fire season (May–June) but have largely extended into the snowless late fire season (July–September) since the late 1990s (mean end Julian date delayed by 51.1 days for 1998–2018 compared with 1968–1997, p < 0.001). Despite significant warming, the Julian days of snowmelt have changed only slightly, which has prohibited the fire season from advancing into early spring. The expansion of lightning fires into July–September was associated with a warming-induced significant increase in evapotranspiration and a decrease in soil/fuel moisture.
Impact of Storage Conditions on Shear Strength of Beech (Fagus sylvatica L.) and Sessile Oak (Quercus petraea (Matt.) Liebl.)
Authors: Vilkovský Peter , Vilkovská Tatiana , Klement Ivan , Čunderlík Igor
Published: August 2021

The structure of a bark as a component of a living tree is completely different from wood. Different structures significantly influence the physical and mechanical properties of the bark. In the processing of logs, it is in most cases necessary to separate the bark from the wood. Problems can arise mainly in the pulp and paper industry. The research focused on the impact of storage conditions on shear strength, showing that the value of shear strength decreased remarkably due to the storage. A decrease in strength can mainly be explained by the changes in the moisture content of bark, remarkably affected by the surrounding environment (climate). The research showed that three months of storage seemed to be the most appropriate and effective period for removing the bark in the case of beech logs and that a storage time of up to five months was the best in the case of oak logs.
A Human Machine Hybrid Approach for Systematic Reviews and Maps in International Development and Social Impact Sectors
Authors: Sartas Murat , Cummings Sarah , Garbero Alessandra , Akramkhanov Akmal
Published: August 2021

The international development and social impact evidence community is divided about the use of machine-centered approaches in carrying out systematic reviews and maps. While some researchers argue that machine-centered approaches such as machine learning, artificial intelligence, text mining, automated semantic analysis, and translation bots are superior to human-centered ones, others claim the opposite. We argue that a hybrid approach combining machine and human-centered elements can have higher effectiveness, efficiency, and societal relevance than either approach can achieve alone. We present how combining lexical databases with dictionaries from crowdsourced literature, using full texts instead of titles, abstracts, and keywords. Using metadata sets can significantly improve the current practices of systematic reviews and maps. Since the use of machine-centered approaches in forestry and forestry-related reviews and maps are rare, the gains in effectiveness, efficiency, and relevance can be very high for the evidence base in forestry. We also argue that the benefits from our hybrid approach will increase in time as digital literacy and better ontologies improve globally.
The Effects of Non-Directional Online Behavior on Students’ Learning Performance: A User Profile Based Analysis Method
Authors: Liang Kun , Liu Jingjing , Zhang Yiying
Published: August 2021

Network behavior analysis is an effective method to outline user requirements, and can extract user characteristics by constructing machine learning models. To protect the privacy of data, the shared information in the model is limited to non-directional network behavior information, such as online duration, traffic, etc., which also hides users’ unconscious needs and habits. However, the value density of this type of information is low, and it is still unclear how much student performance is affected by online behavior; in addition there is a lack of methods for analyzing the correlation between non-directed online behavior and academic performance. In this article, we propose a model for analyzing the correlation between non-directed surfing behavior and academic performance based on user portraits. Different from the existing research, we mainly focus on the public student behavior information in the campus network system and conduct in-depth research on it. The experimental results show that online time and online traffic are negatively correlated with academic performance, respectively, and student’s academic performance can be predicted through the study of non-directional online behavior.
Computer Vision for Fire Detection on UAVs—From Software to Hardware
Authors: Moumgiakmas Seraphim S. , Samatas Gerasimos G. , Papakostas George A.
Published: August 2021

Fire hazard is a condition that has potentially catastrophic consequences. Artificial intelligence, through Computer Vision, in combination with UAVs has assisted dramatically to identify this risk and avoid it in a timely manner. This work is a literature review on UAVs using Computer Vision in order to detect fire. The research was conducted for the last decade in order to record the types of UAVs, the hardware and software used and the proposed datasets. The scientific research was executed through the Scopus database. The research showed that multi-copters were the most common type of vehicle and that the combination of RGB with a thermal camera was part of most applications. In addition, the trend in the use of Convolutional Neural Networks (CNNs) is increasing. In the last decade, many applications and a wide variety of hardware and methods have been implemented and studied. Many efforts have been made to effectively avoid the risk of fire. The fact that state-of-the-art methodologies continue to be researched, leads to the conclusion that the need for a more effective solution continues to arouse interest.
Fractional Differential Equation-Based Instantaneous Frequency Estimation for Signal Reconstruction
Authors: Yazgaç Bilgi Görkem , Kırcı Mürvet
Published: August 2021

In this paper, we propose a fractional differential equation (FDE)-based approach for the estimation of instantaneous frequencies for windowed signals as a part of signal reconstruction. This approach is based on modeling bandpass filter results around the peaks of a windowed signal as fractional differential equations and linking differ-integrator parameters, thereby determining the long-range dependence on estimated instantaneous frequencies. We investigated the performance of the proposed approach with two evaluation measures and compared it to a benchmark noniterative signal reconstruction method (SPSI). The comparison was provided with different overlap parameters to investigate the performance of the proposed model concerning resolution. An additional comparison was provided by applying the proposed method and benchmark method outputs to iterative signal reconstruction algorithms. The proposed FDE method received better evaluation results in high resolution for the noniterative case and comparable results with SPSI with an increasing iteration number of iterative methods, regardless of the overlap parameter.
Mechanism Design for Demand Management in Energy Communities
Authors: Wei Xupeng , Anastasopoulos Achilleas
Published: August 2021

We consider a demand management problem in an energy community, in which several users obtain energy from an external organization such as an energy company and pay for the energy according to pre-specified prices that consist of a time-dependent price per unit of energy as well as a separate price for peak demand. Since users’ utilities are their private information, which they may not be willing to share, a mediator, known as the planner, is introduced to help optimize the overall satisfaction of the community (total utility minus total payments) by mechanism design. A mechanism consists of a message space, a tax/subsidy, and an allocation function for each user. Each user reports a message chosen from her own message space, then receives some amount of energy determined by the allocation function, and pays the tax specified by the tax function. A desirable mechanism induces a game, the Nash equilibria (NE), of which results in an allocation that coincides with the optimal allocation for the community. As a starting point, we design a mechanism for the energy community with desirable properties such as full implementation, strong budget balance and individual rationality for both users and the planner. We then modify this baseline mechanism for communities where message exchanges are allowed only within neighborhoods, and consequently, the tax/subsidy and allocation functions of each user are only determined by the messages from their neighbors. All of the desirable properties of the baseline mechanism are preserved in the distributed mechanism. Finally, we present a learning algorithm for the baseline mechanism, based on projected gradient descent, that is guaranteed to converge to the NE of the induced game.
Adding Some “Splice” to Stress Eating: Autophagy, ESCRT and Alternative Splicing Orchestrate the Cellular Stress Response
Authors: Habib Elias , Cook Allyson , Mathavarajah Sabateeshan , Dellaire Graham
Published: August 2021

Autophagy is a widely studied self-renewal pathway that is essential for degrading damaged cellular organelles or recycling biomolecules to maintain cellular homeostasis, particularly under cellular stress. This pathway initiates with formation of an autophagosome, which is a double-membrane structure that envelopes cytosolic components and fuses with a lysosome to facilitate degradation of the contents. The endosomal sorting complexes required for transport (ESCRT) proteins play an integral role in controlling autophagosome fusion events and disruption to this machinery leads to autophagosome accumulation. Given the central role of autophagy in maintaining cellular health, it is unsurprising that dysfunction of this process is associated with many human maladies including cancer and neurodegenerative diseases. The cell can also rapidly respond to cellular stress through alternative pre-mRNA splicing that enables adaptive changes to the cell’s proteome in response to stress. Thus, alternative pre-mRNA splicing of genes that are involved in autophagy adds another layer of complexity to the cell’s stress response. Consequently, the dysregulation of alternative splicing of genes associated with autophagy and ESCRT may also precipitate disease states by either reducing the ability of the cell to respond to stress or triggering a maladaptive response that is pathogenic. In this review, we summarize the diverse roles of the ESCRT machinery and alternative splicing in regulating autophagy and how their dysfunction can have implications for human disease.
Methylation of Host Genes Associated with Coronavirus Infection from Birth to 26 Years
Authors: Rathod Rutu , Rathod Aniruddha , Rahimabad Parnian Kheirkhah , Duan Jiasong , Zhang Hongmei , Arshad S. Hasan , Karmaus Wilfried
Published: August 2021

DNA methylation (DNAm) patterns over time at 1146 CpGs on coronavirus-related genes were assessed to understand whether the varying differences in susceptibility, symptoms, and the outcomes of the SARS-CoV-2 infection in children and young adults could be explained through epigenetic alterations in a host cell’s transcriptional apparatus to coronaviruses. DNAm data from the Isle of Wight birth cohort (IOWBC) at birth, 10, 18, and 26 years of age were included. Linear mixed models with repeated measurements stratified by sex were used to examine temporal patterns, and cluster analysis was performed to identify CpGs following similar patterns. CpGs on autosomes and sex chromosomes were analyzed separately. The association of identified CpGs and expression of their genes were evaluated. Pathway enrichment analyses of the genes was conducted at FDR = 0.05. DNAm at 635 of the 1146 CpGs on autosomes showed statistically significant time effects (FDR = 0.05). The 635 CpGs were classified into five clusters with each representing a unique temporal pattern of DNAm. Of the 29 CpGs on sex chromosomes, DNAm at seven CpGs in males and eight CpGs in females showed time effects (FDR = 0.05). Sex-specific and non-specific associations of DNAm with gene expression were found at 24 and 93 CpGs, respectively. Genes which mapped the 643 CpGs represent 460 biological processes. We suggest that the observed variability in DNAm with advancing age may partially explain differing susceptibility, disease severity, and mortality of coronavirus infections among different age groups.
Intellectual Disability and Brain Creatine Deficit: Phenotyping of the Genetic Mouse Model for GAMT Deficiency
Authors: Rossi Luigia , Nardecchia Francesca , Pierigè Francesca , Ventura Rossella , Carducci Claudia , Leuzzi Vincenzo , Magnani Mauro , Cabib Simona , Pascucci Tiziana
Published: August 2021

Guanidinoacetate methyltransferase deficiency (GAMT-D) is one of three cerebral creatine (Cr) deficiency syndromes due to pathogenic variants in the GAMT gene (19p13.3). GAMT-D is characterized by the accumulation of guanidinoacetic acid (GAA) and the depletion of Cr, which result in severe global developmental delay (and intellectual disability), movement disorder, and epilepsy. The GAMT knockout (KO) mouse model presents biochemical alterations in bodily fluids, the brain, and muscles, including increased GAA and decreased Cr and creatinine (Crn) levels, which are similar to those observed in humans. At the behavioral level, only limited and mild alterations have been reported, with a large part of analyzed behaviors being unaffected in GAMT KO as compared with wild-type mice. At the cerebral level, decreased Cr and Crn and increased GAA and other guanidine compound levels have been observed. Nevertheless, the effects of Cr deficiency and GAA accumulation on many neurochemical, morphological, and molecular processes have not yet been explored. In this review, we summarize data regarding behavioral and cerebral GAMT KO phenotypes, and focus on uncharted behavioral alterations that are comparable with the clinical symptoms reported in GAMT-D patients, including intellectual disability, poor speech, and autistic-like behaviors, as well as unexplored Cr-induced cerebral alterations.
Cloud Masks Derived from the Mars Daily Global Maps and an Application to the Tropical Cloud Belt on Mars
Authors: Wang Huiqun , González Abad Gonzalo
Published: August 2021

An image processing technique is used to derive cloud masks from the color Mars Daily Global Maps (MDGMs) that are composed from the Mars Reconnaissance Orbiter (MRO) Mars Color Imager (MARCI) wide-angle image swaths. The blue channel of each MDGM is used to select cloud candidates and the blue-to-red ratio map is compared with a reference ratio map to filter out false positives. Quality control is performed manually. The derived cloud masks cover 1 Mars year from the summer of Mars year (MY) 28 to the summer of MY 29. The product has a 0.1° longitude by 0.1° latitude resolution and is available each day. This makes it possible to characterize the evolution of the tropical cloud belt from several new perspectives. The tropical cloud belt steadily builds up during northern spring and early summer, peaks near the early- to mid-summer transitional period, and rapidly declines afterward. From the perspective of cloud occurrence frequency and time mean, the cloud belt appears meandrous and zonally discontinuous, with minima in the Amazonis Planitia and Arabia Terra longitudinal sectors. A pronounced cloud branch diverges from the main cloud belt and extends from the Valles Marineris towards the Noachis and Hellas region. The cloud belt exhibits noticeable oscillatory behavior whereby cloud brightening alternates between the western and eastern hemispheres near the equator with a periodicity between 20 and 30 sols. The cloud belt oscillation occurred each Mars year around Ls = 140°, except for the Mars years when intense dust storms made disruptions. The phenomenon appears to be associated with an eastward propagating equatorial Kelvin wave with zonal wavenumber 1. This wave has a much longer wave period than the diurnal and semidiurnal Kelvin waves discussed in most of the previous studies and may be an important factor for the intra-seasonal variability of the tropical cloud belt. The convolution of clouds’ local time variation with MRO’s orbit shift pattern results in a seemingly highly regular 5-day traveling wave in Hovmöller diagrams of cloud masks.
Fluid-Rock Interactions in a Paleo-Geothermal Reservoir (Noble Hills Granite, California, USA). Part 1: Granite Pervasive Alteration Processes away from Fracture Zones
Authors: Klee Johanne , Potel Sébastien , Ledésert Béatrice A. , Hébert Ronan L. , Chabani Arezki , Barrier Pascal , Trullenque Ghislain
Published: August 2021

Only few data from geothermal exploited reservoirs are available due to the restricted accessibility by drilling, which limits the understanding of the entire reservoir. Thus, analogue investigations are needed and were performed in the framework of the H2020 MEET project. The Noble Hills range, located along the southern branch of the Death Valley pull-apart (CA, USA), has been selected as a possible granitic paleo-reservoir. The aim is to characterize the pervasive alteration processes affecting this granite, away from the influence of the faults, in terms of mineralogical, petrophysical and chemical changes. Various methods were used as petrographic, geochemical and petrophysical analyses. Mineral changes, clay mineralogy, bulk rock chemical composition, calcite content and porosity were determined on different granite samples, collected in the Noble Hills granite, far from the faults and in the Owlshead Mountains, north of the Noble Hills, considered as its protolith. In order to complete the granite characterization, the metamorphic grade has been studied through the Noble Hills granite body. This complete characterization has allowed distinguishing the occurrence of three stages of alteration: (1) a pervasive propylitic alteration characterized by calcite-corrensite-epidote-K-white mica assemblage, (2) a more local one, only present in the Noble Hills granite, producing illite, kaolinite, illite/smectite, calcite and oxides, characteristic of the argillic alteration, which overprints the propylitic alteration and (3) weathering evidenced by the presence of montmorillonite in the Owlshead Mountains, which is considered as negligible in both granites. Alteration was also outlined by the correlation of the loss on ignition, representing the hydration rate, to porosity, calcite content and chemical composition. Moreover, the Kübler Index calculated from illite crystals allowed to identify a NW-SE temperature gradient in the Noble Hills.
Holocene Sea-Level Changes in Southern Brazil Based on High-Resolution Radar Stratigraphy
Authors: Barboza Eduardo Guimarães , Dillenburg Sergio Rebello , do Nascimento Ritter Matias , Angulo Rodolfo José , da Silva Anderson Biancini , da Camara Rosa Maria Luiza Correaa , Caron Felipe , de Souza Maria Cristina
Published: August 2021

This paper focuses on high-resolution coastal stratigraphy data, which were revealed by the Ground Penetrating Radar (GPR) system. Surveys performed with GPR on the surface of prograded barriers reveal patterns of reflections that allow the interpretation of the geometry and stratigraphy of coastal deposits in a continuous mode. At the Curumim prograded barrier in southern Brazil (29°30′ S–49°53′ W), a two-dimensional transverse GPR survey revealed, with high precision, a serial of contacts between aeolian deposits of relict foredunes and relict beach deposits that have a strong correlation with sea level. In a 4 km GPR profile, a total of 24 of these contacts were identified. The high accurate spatial positioning of the contacts combined with Optical Stimulated Luminescence dating resulted in the first confident sea-level curve that tells the history of sea-level changes during the last 7 ka on the southernmost sector of the Brazilian coast. The curve shows that sea-level was still rising before 6 ka BP, with a maximum level of 1.9 m reached close to 5 ka BP; after that, sea-level started to falling slowly until around 4 ka BP when fall accelerated.
Multimodal Early Alzheimer’s Detection, a Genetic Algorithm Approach with Support Vector Machines
Authors: Sánchez-Reyna Ana , Celaya-Padilla José , Galván-Tejada Carlos , Luna-García Huizilopoztli , Gamboa-Rosales Hamurabi , Ramirez-Morales Andres , Galván-Tejada Jorge ,   on behalf of the Alzheimer’s Disease Neuroimaging Initiative
Published: August 2021

Alzheimer’s disease (AD) is a neurodegenerative disease that mainly affects older adults. Currently, AD is associated with certain hypometabolic biomarkers, beta-amyloid peptides, hyperphosphorylated tau protein, and changes in brain morphology. Accurate diagnosis of AD, as well as mild cognitive impairment (MCI) (prodromal stage of AD), is essential for early care of the disease. As a result, machine learning techniques have been used in recent years for the diagnosis of AD. In this research, we propose a novel methodology to generate a multivariate model that combines different types of features for the detection of AD. In order to obtain a robust biomarker, ADNI baseline data, clinical and neuropsychological assessments (1024 features) of 106 patients were used. The data were normalized, and a genetic algorithm was implemented for the selection of the most significant features. Subsequently, for the development and validation of the multivariate classification model, a support vector machine model was created, and a five-fold cross-validation with an AUC of 87.63% was used to measure model performance. Lastly, an independent blind test of our final model, using 20 patients not considered during the model construction, yielded an AUC of 100%.
Longitudinal Associations of Marital, Parenting, and Employment Transitions with Weight Gain in a Multi-Ethnic Asian Population Aged 21 Years and Above
Authors: Whitton Clare , Wong Yvonne Hui Min , van Dam Rob M.
Published: August 2021

Identifying when most weight gain occurs throughout the life course can inform targeted public health interventions. We evaluated the association of childbirth, marriage, and employment changes with weight changes in a multi-ethnic Asian cohort. Singapore Multi-Ethnic Cohort participants ≥21 years (n = 9655) who identified as ethnic Chinese, Malay, or Indian were weighed and interviewed about marital status, employment, and number of children at baseline and after about four years. We used multivariable regression to evaluate life transitions in relation to weight change and major gain (≥5 kg), and adjusted for socio-demographic covariates. Weight gain was 3.55 kg (95% CI 3.17, 3.94) higher in young adults (21–30 years) compared with participants older than 60 years at baseline. Getting married was associated with weight gain in women, but not men (p interaction < 0.01). Women who got married gained 1.63 kg (95% CI 0.88, 2.38) more weight and were more likely to gain ≥5 kg (OR 1.99, 95% CI 1.35, 2.93) than those remaining unmarried. Having children was not associated with weight gain. Only among ethnic Indians, remaining a homemaker was associated with less weight gain than remaining employed. In this multi-ethnic Asian population, obesity prevention efforts should target young adulthood and, in women, the transition into marriage.
Adolescents’ Social Media Use and Their Voluntary Garbage Sorting Intention: A Sequential Mediation Model
Authors: Ai Pengya , Li Wu , Yang Wuyue
Published: August 2021

Encouraging adolescents to sort garbage is vital for the sustainable development of the ecological environment. This study investigates the relationship between adolescents’ social media use and their garbage sorting intention. A survey, in both online and paper-based versions, was distributed in 2020 in Shanghai and a total number of 605 valid responses were obtained. This study supports the proposed sequential mediation model, indicating that adolescents’ social media use increased their garbage sorting intention via the serial mediation effect of objective and subjective knowledge and the perceived importance of garbage sorting. The current study and its findings provide important insights into the link between adolescents’ social media use and their garbage sorting intention, particularly its underlying mechanism, by distinguishing knowledge into two specific types and introducing perceived importance into the conceptual model. Practical implications for improving adolescents’ intention to sort garbage are also discussed.
Impact of COVID-19 on the Health of the General and More Vulnerable Population and Its Determinants: Health Care and Social Survey–ESSOC, Study Protocol
Authors: Sánchez-Cantalejo Carmen , Rueda María del Mar , Saez Marc , Enrique Iria , Ferri Ramón , Fuente Miguel de La , Villegas Román , Castro Luis , Barceló Maria Antònia , Daponte-Codina Antonio , Lorusso Nicola , Cabrera-León Andrés
Published: August 2021

This manuscript describes the rationale and protocol of a real-world data (RWD) study entitled Health Care and Social Survey (ESSOC, Encuesta Sanitaria y Social). The study’s objective is to determine the magnitude, characteristics, and evolution of the COVID-19 impact on overall health as well as the socioeconomic, psychosocial, behavioural, occupational, environmental, and clinical determinants of both the general and more vulnerable population. The study integrates observational data collected through a survey using a probabilistic, overlapping panel design, and data from clinical, epidemiological, demographic, and environmental registries. The data will be analysed using advanced statistical, sampling, and machine learning techniques. The study is based on several measurements obtained from three random samples of the Andalusian (Spain) population: general population aged 16 years and over, residents in disadvantaged areas, and people over the age of 55. Given the current characteristics of this pandemic and its future repercussions, this project will generate relevant information on a regular basis, commencing from the beginning of the State of Alarm. It will also establish institutional alliances of great social value, explore and apply powerful and novel methodologies, and produce large, integrated, high-quality and open-access databases. The information described here will be vital for health systems in order to design tailor-made interventions aimed at improving the health care, health, and quality of life of the populations most affected by the COVID-19 pandemic.
Perceived Efficiency Outcomes, Sources and Awareness of Online Health Information among the Elderly during COVID-19
Authors: Green Gizell , Tesler Riki , Sharon Cochava
Published: August 2021

The Internet and social media are crucial platforms for health information. Factors such as the efficiency of online health information, the outcomes of seeking online health information and the awareness of reliable sources have become increasingly important for the elderly during the COVID-19 pandemic. This study aimed to examine differences between elderly individuals’ income above and below the average monthly wage in relation to their online health information efficiency and the outcomes of seeking online health information; to evaluate types of online information sources with online health information efficiency and the outcomes of seeking online health information; and to explore online health information efficiency as a mediator between health status and awareness of online sources. A cross-sectional study design was conducted with 336 elderly participants age 65 or older. The participants volunteered to complete a questionnaire. No differences were found between the two groups regarding efficiency in retrieving health information from official online health sites and Google. Perceived efficiency mediated health status and awareness of online sources. In these challenging times, it is important to provide a tailor-made education strategy plan for reliable sources of online health information for the elderly, in order to enhance their technology safety skills. It is also important to explore other mediating variables between health status and awareness of online sources.
Forecasting Diabetes Cases Prevented and Cost Savings Associated with Population Increases of Walking in the Greater Toronto and Hamilton Area, Canada
Authors: Kornas Kathy , Rosella Laura C. , Fazli Ghazal S. , Booth Gillian L.
Published: August 2021

Promoting adequate levels of physical activity in the population is important for diabetes prevention. However, the scale needed to achieve tangible population benefits is unclear. We aimed to estimate the public health impact of increases in walking as a means of diabetes prevention and health care cost savings attributable to diabetes. We applied the validated Diabetes Population Risk Tool (DPoRT) to the 2015/16 Canadian Community Health Survey for adults aged 18–64, living in the Greater Toronto and Hamilton area, Ontario, Canada. DPoRT was used to generate three population-level scenarios involving increases in walking among individuals with low physical activity levels, low daily step counts and high dependency on non-active forms of travel, compared to a baseline scenario (no change in walking rates). We estimated number of diabetes cases prevented and health care costs saved in each scenario compared with the baseline. Each of the three scenarios predicted a considerable reduction in diabetes and related health care cost savings. In order of impact, the largest population benefits were predicted from targeting populations with low physical activity levels, low daily step counts, and non active transport use. Population increases of walking by 25 min each week was predicted to prevent up to 10.4 thousand diabetes cases and generate CAD 74.4 million in health care cost savings in 10 years. Diabetes reductions and cost savings were projected to be higher if increases of 150 min of walking per week could be achieved at the population-level (up to 54.3 thousand diabetes cases prevented and CAD 386.9 million in health care cost savings). Policy, programming, and community designs that achieve modest increases in population walking could translate to meaningful reductions in the diabetes burden and cost savings to the health care system.
Assessing Ecosystem Services Supply-Demand (Mis)Matches for Differential City Management in the Yangtze River Delta Urban Agglomeration
Authors: Cai Wenbo , Jiang Wei , Du Hongyu , Chen Ruishan , Cai Yongli
Published: August 2021

With the global increase in population and urban expansion, the simultaneous rise of social demand and degradation of ecosystems is omnipresent, especially in the urban agglomerations of China. In order to manage environmental problems and match ecosystem supply and social demand, these urban agglomerations promoted regional socio-ecological integration but ignored differential city management during the process of integration. Therefore, it is necessary to design a general framework linking ecosystem supply and social demand to differential city management. In addition, in previous studies, ecosystem services supply–demand amount (mis)match assessment was emphasized, but ecosystem services supply–demand type (mis)match assessment was ignored, which may lead to biased decisions. To deal with these problems, this study presented a general ecosystem services framework with six core steps for differential city management and developed a double-indices (amount and type) method to identify ecosystem services supply–demand (mis)matches in an urban agglomeration. This framework and the double-indices method were applied in the case study of the Yangtze River Delta Urban Agglomeration. Ecosystem supply–demand amount and type (mis)match levels and spatial pattern of twenty-six cities were identified. Twenty-six cities in the YRDUA were classified into five kinds of cities with different levels of ES supply–demand (mis)matches for RS, three kinds of cities for PS, and four kinds of cities for CS. Differential city management strategies were designed. Despite its limitations, this study can be a reference to giving insights into ES supply–demand (mis)match assessment and management.
Filling the Gaps in the Pharmacy Workforce in Post-Conflict Areas: Experience from Four Countries in Sub-Saharan Africa
Authors: Wong Anabelle , Hung Kevin K. C. , Mabhala Mzwandile , Tenney Justin W. , Graham Colin A.
Published: August 2021

Background: While the pharmacy workforce is the third largest professional healthcare group worldwide, the pharmacy workforce landscape remains unclear in post-conflict areas in sub-Saharan Africa. Method: Key informants were selected for semi-structured interviews due to their role in providing pharmacy services in the selected country: the Central African Republic (CAR), the Democratic Republic of Congo (DRC), Ethiopia, and South Sudan. Transcripts from the interviews were anonymized, coded, and analyzed. Results: Nine participants were recruited (CAR: 2; DRC: 2; Ethiopia: 2; South Sudan: 3), and all except two were pharmacists. Conflict-specific challenges in pharmacy service delivery were identified as the following: unpredictable health needs and/or mismatched pharmaceutical supply, transport difficulties due to insecure roads, and shortage of pharmacy workforce due to brain drain or interrupted schooling. Barriers to health workforce retention and growth were identified to be brain drain as a result of suboptimal living and working conditions or remuneration, the perception of an unsafe work environment, and a career pathway or commitment duration that does not fit the diaspora or expatriate staff. Conclusion: To tackle the barriers of pharmacy health workforce retention and growth, policy solutions will be required and efforts that can bring about long-term improvement should be prioritized. This is essential to achieve universal health coverage and the targets of the sustainable development goals for conflict affected areas, as well as to “leave no one behind”.
A Cluster Analysis of Risk Factors for Cancer across EU Countries: Health Policy Recommendations for Prevention
Authors: Majcherek Dawid , Weresa Marzenna Anna , Ciecierski Christina
Published: August 2021

Cancer burden in the European Union (EU) is increasing and has stimulated the European Commission (EC) to develop strategies for cancer control. A common “one size fits all” prevention policy may not be effective in reducing cancer morbidity and mortality. The goal of this paper is to show that EU member states are not homogenous in terms of their exposure to risk factors for cancer (i.e., lifestyle, socio-economic status (SES), air pollution, and vaccination). Data from a variety of sources including Eurostat, the UNESCO Institute for Statistics, the European Health Interview Survey, Eurobarometer, and the European Environment Agency were merged across years 2013–2015 and used to develop a cluster analysis. This work identified four patterns of cancer prevention behaviors in the EU thus making it possible to group EU members states into four distinct country clusters including: sports-engaged countries, tobacco and pollutant exposed nations, unhealthy lifestyle countries, and a stimulant-enjoying cluster of countries. This paper finds that there is a need for closer collaboration among EU countries belonging to the same cluster in order to share best practices regarding health policy measures that might improve cancer control interventions locally and across the EU.
A Novel Internet of Energy Based Optimal Multi-Agent Control Scheme for Microgrid including Renewable Energy Resources
Authors: Alhasnawi Bilal Naji , Jasim Basil H. , Rahman Zain-Aldeen S. A. , Guerrero Josep M. , Esteban M. Dolores
Published: August 2021

The increasing integration of Renewable Energy Resources (RERs) in distribution networks forms the Networked Renewable Energy Resources (NRERs). The cooperative Peer-to-Peer (P2P) control architecture is able to fully exploit the resilience and flexibility of NRERs. This study proposes a multi-agent system to achieve P2P control of NRERs based Internet of Things (IoT). The control system is fully distributed and contains two control layers operated in the agent of each RER. For primary control, a droop control is adopted by each RER-agent for localized power sharing. For secondary control, a distributed diffusion algorithm is proposed for arbitrary power sharing among RERs. The proposed levels communication system is implemented to explain the data exchange between the distribution network system and the cloud server. The local communication level utilizes the Internet Protocol (IP)/Transmission Control Protocol (TCP), and Message Queuing Telemetry Transport (MQTT) is used as the protocol for the global communication level. The effectiveness of the proposed system is validated by numerical simulation with the modified IEEE 9 node test feeder. The controller proposed in this paper achieved savings of 20.65% for the system, 25.99% for photovoltaic, 35.52 for diesel generator, 24.59 for batteries, and 52.34% for power loss.