bluuebunny/crossref_metadata_2025 huggingface dataset:
Social Vulnerability Indicators for Flooding in Aotearoa New Zealand
Authors: Mason Kylie , Lindberg Kirstin , Haenfling Carolin , Schori Allan , Marsters Helene , Read Deborah , Borman Barry
Published: April 2021

Social vulnerability indicators are a valuable tool for understanding which population groups are more vulnerable to experiencing negative impacts from disasters, and where these groups live, to inform disaster risk management activities. While many approaches have been used to measure social vulnerability to natural hazards, there is no single method or universally agreed approach. This paper proposes a novel approach to developing social vulnerability indicators, using the example of flooding in Aotearoa New Zealand. A conceptual framework was developed to guide selection of the social vulnerability indicators, based on previous frameworks (including the MOVE framework), consideration of climate change, and a holistic view of health and wellbeing. Using this framework, ten dimensions relating to social vulnerability were identified: exposure; children; older adults; health and disability status; money to cope with crises/losses; social connectedness; knowledge, skills and awareness of natural hazards; safe, secure and healthy housing; food and water to cope with shortage; and decision making and participation. For each dimension, key indicators were identified and implemented, mostly using national Census population data. After development, the indicators were assessed by end users using a case study of Porirua City, New Zealand, then implemented for the whole of New Zealand. These indicators will provide useful data about social vulnerability to floods in New Zealand, and these methods could potentially be adapted for other jurisdictions and other natural hazards, including those relating to climate change.
Analysis of China’s Industrial Green Development Efficiency and Driving Factors: Research Based on MGWR
Authors: Liu Ke , Qiao Yurong , Zhou Qian
Published: April 2021

With increasingly severe constraints on resources and the environment, it is the mainstream trend of economic development to reduce industrial pollution emissions and promote green industrial development. In this paper, a super-efficiency slacks-based measure (SBM) model is adopted to measure the industrial green development efficiency (IGDE) of 289 cities in China from 2008 to 2018. Moreover, we analyze their spatiotemporal differentiation pattern. On this basis, the multiscale geographical weighted regression (MGWR) model is used to analyze the scale differences and spatial differences of the driving factors. The results show that the IGDE is still at a low level in China. From 2008 to 2018, the overall polarization of IGDE was relatively serious. The number of high- and low-efficiency cities increased, while that of medium-efficiency cities greatly decreased. Secondly, the IGDE presented an obvious spatial positive correlation. MGWR regression results show that the technological innovation, government regulation, and consumption level belonged to the global scale, and there was almost no spatial heterogeneity. Other driving factors were urbanization, industrial structure, economic development, and population density according to their spatial scale. Lastly, the influence of economic development and technological innovation had a certain circular structure in space; the influence of population size mainly occurred in the cities of the southeast coast and northeast provinces; the influence of urbanization was more obvious in the most northern provinces of the Yangtze River, while that of industrial structure was mainly concentrated in the most southern cities of the Yangtze River Economic Belt (YREB). Spatially, the influence of consumption was manifested as a distribution trend of decreasing from north to south, and the government regulation was manifested as increasing from west to east and then to northeast.
Trends of Nursing Research on Accidental Falls: A Topic Modeling Analysis
Authors: Seo Yeji , Kim Kyunghee , Kim Ji-Su
Published: April 2021

This descriptive study analyzed 1849 international and 212 Korean studies to explore the main topics of nursing research on accidental falls. We extracted only nouns from each abstract, and four topics were identified through topic modeling, which were divided into aspects of fall prevention and its consequences. “Fall prevention program and scale” is popular among studies on the validity of fall risk assessment tools and the development of exercise and education programs. “Nursing strategy for fall prevention” is common in studies on nurse education programs and practice guidelines to improve the quality of patient safety care. “Hospitalization by fall injury” is used in studies about delayed discharge, increased costs, and deaths of subjects with fall risk factors hospitalized at medical institutions due to fall-related injuries. “Long-term care facility falls” is popular in studies about interventions to prevent fall injuries that occur in conjunction with dementia in long-term care facilities. It is necessary to establish a system and policy for fall prevention in Korean medical institutions. This study confirms the trends in domestic and international fall-related research, suggesting the need for studies to address insufficient fall-related policies and systems and translational research to be applied in clinical trials.
Adolescent Attachment to Parents and Peers and the Use of Instagram: The Mediation Role of Psychopathological Risk
Authors: Ballarotto Giulia , Volpi Barbara , Tambelli Renata
Published: April 2021

Several studies have shown an association between adolescents’ attachment relationships and social media use. Instagram is the social media platform most used by teenagers and recent studies have shown an association between Instagram use and increased psychopathological risk. The present study aims to verify whether psychopathological risk mediates the relationship between an adolescent’s attachment to their parents and peers and their Instagram addiction. N = 372 adolescents are assessed through self-report questionnaires evaluating Instagram addiction, the adolescents’ attachments to parents and peers, and their psychopathological risk. The Bergen Instagram Addiction Scale (BIAS) is developed by adapting the Bergen Social Media Addiction Scale. Results show the validity and reliability of the BIAS, confirming a one-factor structure. Findings show that a worse attachment to parents and peers is associated with adolescents’ psychopathological risk, which is associated with Instagram addiction. This finding has important clinical implications. Being able to intervene in adolescents’ relationships with parents and peers and the ways in which adolescents feel in relation to others could allow for a reduction in adolescents’ psychological difficulties, involving reduced Instagram use as a vehicle for the expression of their psychopathological symptoms.
Does Physical Activity Predict Obesity—A Machine Learning and Statistical Method-Based Analysis
Authors: Cheng Xiaolu , Lin Shuo-yu , Liu Jin , Liu Shiyong , Zhang Jun , Nie Peng , Fuemmeler Bernard F. , Wang Youfa , Xue Hong
Published: April 2021

Background: Obesity prevalence has become one of the most prominent issues in global public health. Physical activity has been recognized as a key player in the obesity epidemic. Objectives: The objectives of this study are to (1) examine the relationship between physical activity and weight status and (2) assess the performance and predictive power of a set of popular machine learning and traditional statistical methods. Methods: National Health and Nutrition Examination Survey (NHANES, 2003 to 2006) data were used. A total of 7162 participants met our inclusion criteria (3682 males and 3480 females), with average age ranging from 48.6 (normal weight) to 52.1 years old (overweight). Eleven classifying algorithms—including logistic regression, naïve Bayes, Radial Basis Function (RBF), local k-nearest neighbors (k-NN), classification via regression (CVR), random subspace, decision table, multiobjective evolutionary fuzzy classifier, random tree, J48, and multilayer perceptron—were implemented and evaluated, and they were compared with traditional logistic regression model estimates. Results: With physical activity and basic demographic status, of all methods analyzed, the random subspace classifier algorithm achieved the highest overall accuracy and area under the receiver operating characteristic (ROC) curve (AUC). The duration of vigorous-intensity activity in one week and the duration of moderate-intensity activity in one week were important attributes. In general, most algorithms showed similar performance. Logistic regression was middle-ranking in terms of overall accuracy, sensitivity, specificity, and AUC among all methods. Conclusions: Physical activity was an important factor in predicting weight status, with gender, age, and race/ethnicity being less but still essential factors associated with weight outcomes. Tailored intervention policies and programs should target the differences rooted in these demographic factors to curb the increase in the prevalence of obesity and reduce disparities among sub-demographic populations.
Maladaptive Personality Traits and Their Interaction with Outcome Expectancies in Gaming Disorder and Internet-Related Disorders
Authors: Müller Kai W. , Werthmann Jennifer , Beutel Manfred E. , Wölfling Klaus , Egloff Boris
Published: April 2021

Gambling disorder and gaming disorder have recently been recognized as behavioral addictions in the ICD-11 (International Classification of Diseases, 11th edition). The association between behavioral addictions and personality has been examined before, yet there is a lack of studies on maladaptive traits and their relationship to specific outcome expectancies. In study 1, we recruited a community sample (n = 365); in study 2 a sample of treatment-seekers was enrolled (n = 208). Maladaptive personality traits were assessed by the brief form of the Personality Inventory for DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, 5th edition). Internet-related outcome expectancies were measured by the Virtual Expectancy Questionnaire. In the clinical sample, the Global Assessment of Functioning was additionally administered. Behavioral Addictions were closely associated with maladaptive traits that in turn were related to a poorer level of psychosocial functioning. There is evidence for an exacerbated risk of internet-related disorders when specific outcome expectancies and maladaptive traits interact. Implications for phenomenology and treatment are discussed.
Profiles of Loneliness and Social Isolation in Physically Active and Inactive Older Adults in Rural England
Authors: de Koning Jolanthe , Richards Suzanne H , Wood Grace E R , Stathi Afroditi
Published: April 2021

Objective: Loneliness and social isolation are associated with higher risk of morbidity and mortality and physical inactivity in older age. This study explored the socioecological context in which both physically active and inactive older adults experience loneliness and/or social isolation in a UK rural setting. Design: A mixed-methods design employed semi structured interviews and accelerometer-measured moderate-to-vigorous physical activity (MVPA). Interviews explored the personal, social and environmental factors influencing engagement with physical activities, guided by an adapted-socioecological model of physical activity behaviour. Findings: Twenty-four older adults (Mean Age = 73 (5.8 SD); 12 women) were interviewed. Transcripts were thematically analysed and seven profiles of physical activity, social isolation and loneliness were identified. The high-MVPA group had established PA habits, reported several sources of social contact and evaluated their physical environment as activity friendly. The low MVPA group had diverse experiences of past engagement in social activities. Similar to the high MVPA, they reported a range of sources of social contact but they did not perceive the physical environment as activity friendly. Conclusions: Loneliness and/or social isolation was reported by both physically active and inactive older adults. There is wide diversity and complexity in types and intensity of PA, loneliness and social isolation profiles and personal, social and environmental contexts.
Callous–Unemotional Traits among Adolescents with Autism Spectrum Disorder, Attention-Deficit/Hyperactivity Disorder, or Typical Development: Differences between Adolescents’ and Parents’ Views
Authors: Chang Chen-Lin , Liu Tai-Ling , Hsiao Ray C. , Yang Pinchen , Chen Yi-Lung , Yen Cheng-Fang
Published: April 2021

This study examined parent–adolescent agreement on the callous, uncaring, and unemotional dimensions of callous–unemotional (CU) traits and the differences in adolescent-reported and parent-reported CU traits among 126 adolescents with autism spectrum disorder (ASD), 207 adolescents with attention-deficit/hyperactivity disorder (ADHD), and 203 typically developing (TD) adolescents. Adolescent-reported and parent-reported CU traits on the three dimensions of the Inventory of Callous and Unemotional Traits were obtained. The strength of CU traits and the differences between adolescent-reported and parent-reported traits were compared among the three groups using analysis of covariance. Parent–adolescent agreement was examined using intraclass correlation. The results reveal that both adolescent-reported and parent-reported callousness and uncaring traits in the ASD and ADHD groups were significantly stronger than those in the TD group. Parent–adolescent agreement on the uncaring trait was fair across the three groups, whereas that on callousness was poor across all three groups. Parent–adolescent agreement on unemotionality was fair in the TD group but poor in the ADHD and ASD groups. ASD and ADHD groups had significantly greater differences in scores reported by parents and adolescents on the callousness trait than the TD group. The parent–adolescent score differences in the uncaring trait were also larger in the ASD group than in the TD group. Thus, these results support the application of a multi-informant approach in CU trait assessment, especially for adolescents with ASD or ADHD.
Food Security, Dietary Intake, and Foodways of Urban Low-Income Older South African Women: An Exploratory Study
Authors: Odunitan-Wayas Feyisayo A , Faber Mieke , Mendham Amy E , Goedecke Julia H , Micklesfield Lisa K , Brooks Naomi E , Christensen Dirk L , Gallagher Iain J , Myburgh Kathryn H , Hunter Angus M , Lambert Estelle V
Published: April 2021

This cross-sectional study explored the differences in sociodemographics, dietary intake, and household foodways (cultural, socioeconomic practices that affect food purchase, consumption, and preferences) of food secure and food insecure older women living in a low-income urban setting in South Africa. Women (n = 122) aged 60–85 years old were recruited, a sociodemographic questionnaire was completed, and food security categories were determined. The categories were dichotomised into food secure (food secure and mild food insecurity) and food insecure (moderate and severe). A one-week quantified food frequency questionnaire was administered. Height and weight were measured to calculate body mass index (BMI, kg/m2). Most participants (>90%) were overweight/obese, unmarried/widowed, and breadwinners with a low monthly household income. Food insecure participants (36.9%) more frequently borrowed money for food (57.8% vs. 39.0%, p = 0.04), ate less so that their children could have more to eat (64.4%. vs. 27.3%, p = 0.001), and had higher housing density (1.2 vs. 1.0, p = 0.03), compared to their food-secure counterparts. Overall, <30% of participants met the WHO (Geneva, Switzerland) recommended daily servings of healthy foods (fruits, vegetables, and dairy products), but >60% perceived that they consumed an adequate amount of healthy foods. The overall low-quality diet of our cohort was associated with poor nutritional perceptions and choices, coupled with financial constraints.
The Association of Social Support and Symptomatic Remission among Community-Dwelling Schizophrenia Patients: A Cross-Sectional Study
Authors: Fan Chi-Hsuan , Hsu Shih-Chieh , Hsiao Fei-Hsiu , Chang Chia-Ming , Liu Chia-Yih , Lai Yu-Ming , Chen Yu-Ting
Published: April 2021

Schizophrenia is a mental disease that often leads to chronicity. Social support could reduce the severity of psychotic symptoms; therefore, its influence on remission should be examined. This study investigated the remission rates in community-dwelling schizophrenia patients and examined the association between social support and remission status. A cross-sectional study was conducted in 129 schizophrenia patients in Taiwan. Remission rates were evaluated, and the level of social support, clinical characteristics, sociodemographic variables, and healthy lifestyle status were compared between the remission and nonremission groups. The association between social support and remission was analyzed after adjusting for confounding factors. The mean illness duration is 12.9 years. More than 95% of the participants lived with their families, 63% were unemployed, and 43% achieved remission. Higher social support was observed in the remission group, and a significant correlation was observed between family domain of social support and remission status. Family support was a protective factor of symptomatic remission in community-dwelling schizophrenia patients in Taiwan. The results reflect the effects of a family-centered culture on patients during illness. Consequently, reinforcing family relationships and the capacity of families to manage the symptoms of patients and providing support to families are recommended.
Analysis of DnaK Expression from a Strain of Mycoplasma fermentans in Infected HCT116 Human Colon Carcinoma Cells
Authors: Curreli Sabrina , Tettelin Hervé , Benedetti Francesca , Krishnan Selvi , Cocchi Fiorenza , Reitz Marvin , Gallo Robert C. , Zella Davide
Published: April 2021

Several species of mycoplasmas, including Mycoplasma fermentans, are associated with certain human cancers. We previously isolated and characterized in our laboratory a strain of human mycoplasma M. fermentans subtype incognitus (MF-I1) able to induce lymphoma in a Severe Combined Immuno-Deficient (SCID) mouse model, and we demonstrated that its chaperone protein, DnaK, binds and reduces functions of human poly-ADP ribose polymerase-1 (PARP1) and ubiquitin carboxyl-terminal hydrolase protein-10 (USP10), which are required for efficient DNA repair and proper p53 activities, respectively. We also showed that other bacteria associated with human cancers (including Mycoplasmapneumoniae, Helicobacterpylori, Fusobacteriumnucleatum, Chlamydiathrachomatis, and Chlamydia pneumoniae) have closely related DnaK proteins, indicating a potential common mechanism of cellular transformation. Here, we quantify dnaK mRNA copy number by RT-qPCR analysis in different cellular compartments following intracellular MF-I1 infection of HCT116 human colon carcinoma cells. DnaK protein expression in infected cells was also detected and quantified by Western blot. The amount of viable intracellular mycoplasma reached a steady state after an initial phase of growth and was mostly localized in the cytoplasm of the invaded cells, while we detected a logarithmically increased number of viable extracellular bacteria. Our data indicate that, after invasion, MF-I1 is able to establish a chronic intracellular infection. Extracellular replication was more efficient while MF-I1 cultured in cell-free axenic medium showed a markedly reduced growth rate. We also identified modifications of important regulatory regions and heterogeneous lengths of dnaK mRNA transcripts isolated from intracellular and extracellular MF-I1. Both characteristics were less evident in dnaK mRNA transcripts isolated from MF-I1 grown in cell-free axenic media. Taken together, our data indicate that MF-I1, after establishing a chronic infection in eukaryotic cells, accumulates different forms of dnaK with efficient RNA turnover.
Higher Mutation Burden in High Proliferation Compartments of Heterogeneous Melanoma Tumors
Authors: Grzywa Tomasz M. , Koppolu Agnieszka A. , Paskal Wiktor , Klicka Klaudia , Rydzanicz Małgorzata , Wejman Jarosław , Płoski Rafał , Włodarski Paweł K.
Published: April 2021

Melanoma tumors are the most heterogeneous of all tumor types. Tumor heterogeneity results in difficulties in diagnosis and is a frequent cause of failure in treatment. Novel techniques enable accurate examination of the tumor cells, considering their heterogeneity. The study aimed to determine the somatic variations among high and low proliferating compartments of melanoma tumors. In this study, 12 archival formalin-fixed paraffin-embedded samples of previously untreated primary cutaneous melanoma were stained with Ki-67 antibody. High and low proliferating compartments from four melanoma tumors were dissected using laser-capture microdissection. DNA was isolated and analyzed quantitatively and qualitatively. Libraries for amplicon-based next-generation sequencing (NGS) were prepared using NEBNext Direct Cancer HotSpot Panel. NGS detected 206 variants in 42 genes in melanoma samples. Most of them were located within exons (135, 66%) and were predominantly non-synonymous single nucleotide variants (99, 73.3%). The analysis showed significant differences in mutational profiles between high and low proliferation compartments of melanoma tumors. Moreover, a significantly higher percentage of variants were detected only in high proliferation compartments (39%) compared to low proliferation regions (16%, p < 0.05). Our results suggest a significant functional role of genetic heterogeneity in melanoma.
Erk1/2 Inactivation-Induced c-Jun Degradation Is Regulated by Protein Phosphatases, UBE2d3, and the C-Terminus of c-Jun
Authors: Ouyang Weiming , Frucht David M.
Published: April 2021

Constitutive photomorphogenic 1 (COP1) is the ubiquitin E3 ligase that mediates degradation of c-Jun protein upon Erk1/2 inactivation. It remains unknown how this protein degradation pathway is regulated. In this study, we investigated the roles of protein phosphatases, ubiquitin-conjugating E2 enzymes (UBE2), and an intrinsic motif of c-Jun in regulating this degradation pathway. By using pharmacological inhibitors and/or gene knockdown techniques, we identified protein phosphatase 1 (PP1) and PP2A as the phosphatases and UBE23d as the UBE2 promoting c-Jun degradation, triggered by Erk1/2 inactivation. In addition, we report that the C-terminus of c-Jun protein facilitates its degradation. The addition of a C-terminal tag or deletion of the last four amino acid residues from the C-terminus of c-Jun protects it from degradation under Erk1/2-inactivating conditions. Taken together, this study reveals that the Erk1/2 inactivation-triggered and COP1-mediated c-Jun degradation is extrinsically and intrinsically regulated, providing a new understanding of the mechanisms underlying this protein degradation pathway.
Proliferation to Apoptosis Tumor Cell Ratio as a Biomarker to Improve Clinical Management of Pre-Malignant and Symptomatic Plasma Cell Neoplasms
Authors: Vasco-Mogorrón María A. , Campillo José A. , Periago Adela , Cabañas Valentin , Berenguer Mercedes , García-Garay María C. , Gimeno Lourdes , Soto-Ramírez María F. , Martínez-Hernández María D. , Muro Manuel , Minguela Alfredo
Published: April 2021

Proliferation and apoptosis of neoplastic cells are prognostic biomarkers in plasma cell neoplasms (PCNs). The prognostic capacity of proliferation to apoptosis ratio (Ratio-PA) in the era of immunomodulatory treatments is re-evaluated in 316 gammopathy of undetermined significance (MGUS), 57 smoldering multiple myeloma (SMM), and 266 multiple myeloma (MM) patients. Ratio-PA of 0.77 ± 0.12, 1.94 ± 0.52, and 11.2 ± 0.7 (p < 0.0001) were observed in MGUS, SMM, and MM patients. Ten-year overall survival (10y-OS) rates for patients with low/high Ratio-PA were 93.5%/77.3% p < 0.0001) for MGUS, 82.5%/64.7% (p < 0.05) for SMM, and 62.3%/47.0% (p < 0.05) for MM. For patients with low, intermediate, and high risk, 10y-OS for low/high Ratio-PA were 95.5%/72.9% (p < 0.0001), 74.2%/50.4% (p < 0.0001), and 35.3%/20.0% (p = 0.836), respectively. Ratio-PA was an independent prognostic factor for OS (HR = 2.119, p < 0.0001, Harrell-C-statistic = 0.7440 ± 0.0194) when co-analyzed with sex, age, and standard risk. In patients with Ratio-PAhigh, only first-line therapy with VRd/VTd, but not PAD/VCD, coupled with ASCT was associated with high 10y-OS (82.7%). Tumor cell Ratio-PA estimated at diagnosis offers a prognostic biomarker that complements standard risk stratification and helps to guide the clinical management of pre-malignant and symptomatic PCNs. Every effort should be made to provide first-line therapies including VTd or VRd associated with ASCT to patients with Ratio-PAhigh at higher risk of progression and death.
Detection of Genomic Uracil Patterns
Authors: Békési Angéla , Holub Eszter , Pálinkás Hajnalka Laura , Vértessy Beáta G.
Published: April 2021

The appearance of uracil in the deoxyuridine moiety of DNA is among the most frequently occurring genomic modifications. Three different routes can result in genomic uracil, two of which do not require specific enzymes: spontaneous cytosine deamination due to the inherent chemical reactivity of living cells, and thymine-replacing incorporation upon nucleotide pool imbalances. There is also an enzymatic pathway of cytosine deamination with multiple DNA (cytosine) deaminases involved in this process. In order to describe potential roles of genomic uracil, it is of key importance to utilize efficient uracil-DNA detection methods. In this review, we provide a comprehensive and critical assessment of currently available uracil detection methods with special focus on genome-wide mapping solutions. Recent developments in PCR-based and in situ detection as well as the quantitation of genomic uracil are also discussed.
Effect of Seawater Environment on the Structure and Performance of Basalt Continuous Fiber
Authors: Wang Qingwei , Yan Tan , Ding Linfeng
Published: April 2021

Basalt continuous fibers (BFs) have been widely applied in the construction industry including marine applications, however, the corrosion mechanism of BFs in a seawater environment is still not well understood. In this work, we explored the effect of the seawater environment on the weight loss, tensile strength, surface morphology, and microstructure structure of BFs via soaking the BFs in seawater solutions at different temperatures and durations. Results show that the weight loss ratio of BFs decreases at the first stage (around 18 h) of soaking at 80 °C, 85 °C, and 90 °C and then increases for longer soaking durations, while the tensile strength has the opposite change. This enhancement of tensile strength and chemical resistance (at the first stage of seawater soaking) is dominated by the ion-exchange induced ‘blunting’ mechanism, even though the results from a Fourier transform infrared (FT-IR) spectrometer and energy-dispersive spectroscopy (EDS) revealed the damaging of the Si–O–Si tetrahedral structure during the corrosion process. This work revealed the full corrosion process and corresponding mechanism of BFs in a seawater environment.
Analytical Modelling of Temperature Distribution in SLM Process with Consideration of Scan Strategy Difference between Layers
Authors: Cai Linger , Liang Steven Y.
Published: April 2021

In the practical selective laser melting (SLM) manufacturing process, the scan strategy often varies between layers to avoid overlapping of the melted area, which affects the residual stress and deflection of the final build. Yet not much modelling work has been done to accommodate the angle between layers. The paper proposed an analytical thermal model to address the scan strategy difference, such as laser scan direction difference between layers, which brings the model closer to the practical scan situation. The analytical transient moving point heat solution is adopted in this model. The laser movement is first considered in a laser coordinates, which originates at the laser radiation spot, and then transferred into a stationary coordinate, which originates at the starting point of the build. The model takes account of multi-track and multi-layer effect by considering thermal property changes caused by remaining heat, which is further adopted for temperature distribution calculation. The scan direction difference leads to different laser path at each layer, and alters heating and cooling time for a specific point on the build. The proposed model is validated by comparing the predicted melt pool geometries to documented experimental data. The effect of scan direction difference between layers is further discussed in the later part. It is found that the uni- and bi- directional scan leads to diverse temperature profile but its effect on melt depth is not significant. Although the laser rotation angle between layers leads to changes in the melt depth, it is not in a large scale. The proposed model shows that scan strategy does not change melt pool geometry in a significant scale but affects the thermal profile as well as thermal history. It can be used as a step for further modelling work for porosity and deflection.
Mechanical and Microstructural Properties of Ordinary Concrete with High Additions of Crushed Glass
Authors: Belebchouche Cherif , Moussaceb Karim , Bensebti Salah-Eddine , Aït-Mokhtar Abdelkarim , Hammoudi Abdelkader , Czarnecki Slawomir
Published: April 2021

This study investigates the use of crushed glass waste as partial cement replacement in ordinary concretes. Six concrete mixes were designed and prepared: a reference without substitution and five substitution percentages of crushed glass waste ranging from 5% to 25%. The made concrete mix design underwent different tests, namely: slump test, mechanical strength, thermogravimetric analysis (TGA), X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET) determination and finally, water porosimetry, in order to evaluate the influence of the use of crushed glass waste on the properties of fresh and hardened concrete. Mechanical strengths results show that the use of 15% of the crushed glass waste improves the mechanical strength. TGA analysis confirms this result by highlighting a higher hydration degree. The latter contributes to the reduction of the porosity and, consequently, the mechanical strength increases. Also, it can be caused by the increasing amount of chromium which, if added a little, accelerates the hydration of C3S and leads to an increase of the mechanical strength. The BET technique and porosimetry tests showed that the use of crushed glass waste reduces the global porosity of concrete. This is due to the filling effect of the glass powder.
Depositing a Titanium Coating on the Lithium Neutron Production Target by Magnetron Sputtering Technology
Authors: Qiao Zhaopeng , Li Xiaobo , Lv Yongsheng , Xie Yupeng , Hu Yaocheng , Wang Jie , Li Haipeng , Wang Sheng
Published: April 2021

Lithium (Li) is one of the commonly used target materials for compact accelerator-based neutron source (CANS) to generate neutrons by 7Li(p, n)7 Be reaction. To avoid neutron yield decline caused by lithium target reacting with the air, a titanium (Ti) coating was deposited on the lithium target by magnetron sputtering technology. The color change processes of coated and bare lithium samples in the air were observed and compared to infer the chemical state of lithium qualitatively. The surface topography, thickness, and element distribution of the coating were characterized by SEM, EDS and XPS. The compositions of samples were inferred by their XRD patterns. It was found that a Ti coating with a thickness of about 200 nanometers could effectively isolate lithium from air and stabilize its chemical state in the atmosphere for at least nine hours. The Monte Carlo simulations were performed to estimate the effects of the Ti coating on the incident protons and the neutron yield. It turned out that these effects could be ignored. This research indicates that depositing a thin, titanium coating on the lithium target is feasible and effective to keep it from compounds’ formation when it is exposed to the air in a short period. Such a target can be installed and replaced on an accelerator beam line in the air directly.
A Pilot Study on the Metabolic Impact of Mediterranean Diet in Type 2 Diabetes: Is Gut Microbiota the Key?
Authors: Ismael Shámila , Silvestre Marta P. , Vasques Miguel , Araújo João R. , Morais Juliana , Duarte Maria Inês , Pestana Diogo , Faria Ana , Pereira-Leal José B. , Vaz Joana , Ribeiro Pedro , Teixeira Diana , Marques Cláudia , Calhau Conceição
Published: April 2021

The Mediterranean diet (MD) has been recommended for type 2 diabetes (T2D) treatment. The impact of diet in shaping the gut microbiota is well known, particularly for MD. However, the link between MD and diabetes outcome improvement is not completely clear. This study aims to evaluate the role of microbiota modulation by a nonpharmacological intervention in patients with T2D. In this 12-week single-arm pilot study, nine participants received individual nutritional counseling sessions promoting MD. Gut microbiota, biochemical parameters, body composition, and blood pressure were assessed at baseline, 4 weeks, and 12 weeks after the intervention. Adherence to MD [assessed by Mediterranean Diet Adherence Screener (MEDAS) score] increased after the intervention. Bacterial richness increased after 4 weeks of intervention and was negatively correlated with fasting glucose levels and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR). Prevotella to Bacteroides ratio also increased after 4 weeks. In contrast, glycated haemoglobin (HbA1c) and HOMA-IR were only decreased at the end of study. Alkaline phosphatase activity was assessed in fecal samples and was negatively correlated with HbA1c and positively correlated with bacterial diversity. The results of this study reinforce that MD adherence results in a better glycemic control in subjects with T2D. Changes in gut bacterial richness caused by MD adherence may be relevant in mediating the metabolic impact of this dietary intervention.
Assessing the Effect of Training Sampling Design on the Performance of Machine Learning Classifiers for Land Cover Mapping Using Multi-Temporal Remote Sensing Data and Google Earth Engine
Authors: Shetty Shobitha , Gupta Prasun Kumar , Belgiu Mariana , Srivastav S. K.
Published: April 2021

Machine learning classifiers are being increasingly used nowadays for Land Use and Land Cover (LULC) mapping from remote sensing images. However, arriving at the right choice of classifier requires understanding the main factors influencing their performance. The present study investigated firstly the effect of training sampling design on the classification results obtained by Random Forest (RF) classifier and, secondly, it compared its performance with other machine learning classifiers for LULC mapping using multi-temporal satellite remote sensing data and the Google Earth Engine (GEE) platform. We evaluated the impact of three sampling methods, namely Stratified Equal Random Sampling (SRS(Eq)), Stratified Proportional Random Sampling (SRS(Prop)), and Stratified Systematic Sampling (SSS) upon the classification results obtained by the RF trained LULC model. Our results showed that the SRS(Prop) method favors major classes while achieving good overall accuracy. The SRS(Eq) method provides good class-level accuracies, even for minority classes, whereas the SSS method performs well for areas with large intra-class variability. Toward evaluating the performance of machine learning classifiers, RF outperformed Classification and Regression Trees (CART), Support Vector Machine (SVM), and Relevance Vector Machine (RVM) with a >95% confidence level. The performance of CART and SVM classifiers were found to be similar. RVM achieved good classification results with a limited number of training samples.
Remote Sensing of Lake Water Clarity: Performance and Transferability of Both Historical Algorithms and Machine Learning
Authors: Rubin Hannah J. , Lutz David A. , Steele Bethel G. , Cottingham Kathryn L. , Weathers Kathleen C. , Ducey Mark J. , Palace Michael , Johnson Kenneth M. , Chipman Jonathan W.
Published: April 2021

There has been little rigorous investigation of the transferability of existing empirical water clarity models developed at one location or time to other lakes and dates of imagery with differing conditions. Machine learning methods have not been widely adopted for analysis of lake optical properties such as water clarity, despite their successful use in many other applications of environmental remote sensing. This study compares model performance for a random forest (RF) machine learning algorithm and a simple 4-band linear model with 13 previously published empirical non-machine learning algorithms. We use Landsat surface reflectance product data aligned with spatially and temporally co-located in situ Secchi depth observations from northeastern USA lakes over a 34-year period in this analysis. To evaluate the transferability of models across space and time, we compare model fit using the complete dataset (all images and samples) to a single-date approach, in which separate models are developed for each date of Landsat imagery with more than 75 field samples. On average, the single-date models for all algorithms had lower mean absolute errors (MAE) and root mean squared errors (RMSE) than the models fit to the complete dataset. The RF model had the highest pseudo-R2 for the single-date approach as well as the complete dataset, suggesting that an RF approach outperforms traditional linear regression-based algorithms when modeling lake water clarity using satellite imagery.
Quantifying the Impact of Solar Spectra on the Inter-Calibration of Satellite Instruments
Authors: Bhatt Rajendra , Doelling David R. , Coddington Odele , Scarino Benjamin , Gopalan Arun , Haney Conor
Published: April 2021

In satellite-based remote sensing applications, the conversion of the sensor recorded top-of-atmosphere reflectance to radiance, or vice-versa, is carried out using a reference spectral solar irradiance (SSI) dataset. The choice of reference SSI spectrum has consistently changed over the past four decades with the increasing availability of more accurate SSI measurements with greater spectral coverage. Considerable differences (up to 15% at certain wavelengths) exist between the numerous SSI spectra that are currently being used in satellite ground processing systems. The aim of this study is to quantify the absolute differences between the most commonly used SSI datasets and investigate their impact in satellite inter-calibration and environmental retrievals. It was noted that if analogous SNPP and NOAA-20 VIIRS channel reflectances were perfectly inter-calibrated, the derived channel radiances can still differ by up to 3% due to the utilization of differing SSI datasets by the two VIIRS instruments. This paper also highlights a TSIS-1 SIM-based Hybrid Solar Reference Spectrum (HSRS) with an unprecedented absolute accuracy of 0.3% between 460 and 2365 nm, and recommends that the remote sensing community use it as a common reference SSI in satellite retrievals.
The 3D Modeling System for Bioaerosol Distribution Based on Planar Laser-Induced Fluorescence
Authors: Chen Siying , Chen Yuanyuan , Zhang Yinchao , Guo Pan , Chen He , Wu Huiyun
Published: April 2021

Although it is quite challenging to image and analyze the spatial distribution of bioaerosols in a confined space, a three-dimensional (3D) modeling system based on the planar laser-induced fluorescence (PLIF) technique is proposed in this paper, which is designed to analyze the temporal and spatial variations of bioaerosol particles in a confined chamber. The system employs a continuous planar laser source to excite the fluoresce, and a scientific complementary metal oxide semiconductor (sCMOS) camera to capture images of 2048 × 2048 pixels at a frame rate of 12 Hz. While a sliding platform is moving back and forth on the track, a set of images are captured at different positions for 3D reconstruction. In this system, the 3D reconstruction is limited to a maximum measurement volume of about 50 cm × 29.7 cm × 42 cm, with a spatial resolution of about 0.58 mm × 0.82 mm × 8.33 mm, and a temporal resolution of 5 s. Experiments were carried out to detect the PLIF signals from fluorescein aerosols in the chamber, and then 3D reconstruction was used to visualize and analyze the diffusion of aerosol particles. The results prove that the system can be applied to clearly reconstruct the 3D distribution and record the diffusion process of aerosol particles in a confined space.
Fuzzy Logic for Intelligent Control System Using Soft Computing Applications
Authors: Dumitrescu Catalin , Ciotirnae Petrica , Vizitiu Constantin
Published: April 2021

When considering the concept of distributed intelligent control, three types of components can be defined: (i) fuzzy sensors which provide a representation of measurements as fuzzy subsets, (ii) fuzzy actuators which can operate in the real world based on the fuzzy subsets they receive, and, (iii) the fuzzy components of the inference. As a result, these elements generate new fuzzy subsets from the fuzzy elements that were previously used. The purpose of this article is to define the elements of an interoperable technology Fuzzy Applied Cell Control-soft computing language for the development of fuzzy components with distributed intelligence implemented on the DSP target. The cells in the network are configured using the operations of symbolic fusion, symbolic inference and fuzzy–real symbolic transformation, which are based on the concepts of fuzzy meaning and fuzzy description. The two applications presented in the article, Agent-based modeling and fuzzy logic for simulating pedestrian crowds in panic decision-making situations and Fuzzy controller for mobile robot, are both timely. The increasing occurrence of panic moments during mass events prompted the investigation of the impact of panic on crowd dynamics and the simulation of pedestrian flows in panic situations. Based on the research presented in the article, we propose a Fuzzy controller-based system for determining pedestrian flows and calculating the shortest evacuation distance in panic situations. Fuzzy logic, one of the representation techniques in artificial intelligence, is a well-known method in soft computing that allows the treatment of strong constraints caused by the inaccuracy of the data obtained from the robot’s sensors. Based on this motivation, the second application proposed in the article creates an intelligent control technique based on Fuzzy Logic Control (FLC), a feature of intelligent control systems that can be used as an alternative to traditional control techniques for mobile robots. This method allows you to simulate the experience of a human expert. The benefits of using a network of fuzzy components are not limited to those provided distributed systems. Fuzzy cells are simple to configure while also providing high-level functions such as mergers and decision-making processes.
Improved Mask R-CNN for Aircraft Detection in Remote Sensing Images
Authors: Wu Qifan , Feng Daqiang , Cao Changqing , Zeng Xiaodong , Feng Zhejun , Wu Jin , Huang Ziqiang
Published: April 2021

In recent years, remote sensing images has become one of the most popular directions in image processing. A small feature gap exists between satellite and natural images. Therefore, deep learning algorithms could be applied to recognize remote sensing images. We propose an improved Mask R-CNN model, called SCMask R-CNN, to enhance the detection effect in the high-resolution remote sensing images which contain the dense targets and complex background. Our model can perform object recognition and segmentation in parallel. This model uses a modified SC-conv based on the ResNet101 backbone network to obtain more discriminative feature information and adds a set of dilated convolutions with a specific size to improve the instance segmentation effect. We construct WFA-1400 based on the DOTA dataset because of the shortage of remote sensing mask datasets. We compare the improved algorithm with other state-of-the-art algorithms. The object detection AP50 and AP increased by 1–2% and 1%, respectively, objectively proving the effectiveness and the feasibility of the improved model.
Understanding Covalent Grafting of Nanotubes onto Polymer Nanocomposites: Molecular Dynamics Simulation Study
Authors: Yang Seunghwa
Published: April 2021

Here, we systematically interrogate the effects of grafting single-walled (SWNT) and multi-walled carbon nanotubes (MWNT) to polymer matrices by using molecular dynamics (MD) simulations. We specifically investigate key material properties that include interfacial load transfer, alteration of nanotube properties, and dispersion of nanotubes in the polymer matrix. Simulations are conducted on a periodic unit cell model of the nanocomposite with a straight carbon nanotube and an amorphous polyethylene terephthalate (PET) matrix. For each type of nanotube, either 0%, 1.55%, or 3.1% of the carbon atoms in the outermost nanotubes are covalently grafted onto the carbon atoms of the PET matrix. Stress-strain curves and the elastic moduli of nanotubes and nanocomposites are determined based on the density of covalent grafting. Covalent grafting promotes two rivalling effects with respect to altering nanotube properties, and improvements in interfacial load transfer in the nanocomposites are clearly observed. The enhanced interface enables external loads applied to the nanocomposites to be efficiently transferred to the grafted nanotubes. Covalent functionalization of the nanotube surface with PET molecules can alter the solubility of nanotubes and improve dispersibility. Finally, we discuss the current limitations and challenges in using molecular modelling strategies to accurately predict properties on the nanotube and polymers systems studied here.
Combining Ground Based Remote Sensing Tools for Rockfalls Assessment and Monitoring: The Poggio Baldi Landslide Natural Laboratory
Authors: Romeo Saverio , Cosentino Antonio , Giani Francesco , Mastrantoni Giandomenico , Mazzanti Paolo
Published: April 2021

Nowadays the use of remote monitoring sensors is a standard practice in landslide characterization and monitoring. In the last decades, technologies such as LiDAR, terrestrial and satellite SAR interferometry (InSAR) and photogrammetry demonstrated a great potential for rock slope assessment while limited studies and applications are still available for ArcSAR Interferometry, Gigapixel imaging and Acoustic sensing. Taking advantage of the facilities located at the Poggio Baldi Landslide Natural Laboratory, an intensive monitoring campaign was carried out on May 2019 using simultaneously the HYDRA-G ArcSAR for radar monitoring, the Gigapan robotic system equipped with a DSLR camera for photo-monitoring purposes and the DUO Smart Noise Monitor for acoustic measurements. The aim of this study was to evaluate the potential of each monitoring sensor and to investigate the ongoing gravitational processes at the Poggio Baldi landslide. Analysis of multi-temporal Gigapixel-images revealed the occurrence of 84 failures of various sizes between 14–17 May 2019. This allowed us to understand the short-term evolution of the rock cliff that is characterized by several impulsive rockfall events and continuous debris production. Radar displacement maps revealed a constant movement of the debris talus at the toe of the main rock scarp, while acoustic records proved the capability of this technique to identify rockfall events as well as their spectral content in a narrow range of frequencies between 200 Hz to 1000 Hz. This work demonstrates the great potential of the combined use of a variety of remote sensors to achieve high spatial and temporal resolution data in the field of landslide characterization and monitoring.