bluuebunny/crossref_metadata_2025 huggingface dataset:
The correlation between posttraumatic growth and social support in people with breast cancer: A meta-analysis
Authors: Ma Xiaojing , Wan Xiao , Chen Chaoran
Published: December 2022

Posttraumatic growth (PTG) is consistently reported to be associated with social support among people with breast cancer. But so far there is no consensus on the size and direction to which social support are related to PTG in people with breast cancer. Thus, a meta-analysis was performed by us to quantitatively synthesize the previous results. This meta-analysis followed the PRISMA 2020 guidelines. We searched PubMed, PsycINFO, Web of Science, Embase, Chongqing VIP Information Co., Ltd. (VIP), China National Knowledge Infrastructure (CNKI), and WANFANG DATA databases prior to 1 June 2022. A random effects model of Stata software (version 17.0) was employed to compute the pooled association coefficient and examine a series of moderating factors: economic level, publication type, region, year of publication, participants’ age, and social support measurement tools. Ultimately, 31 studies including 6,380 breast cancer patients were identified. This meta-analysis offers evidence of a highly positive correlation between PTG and social support among people with breast cancer (r = 0.425). Economic level, region, and social support measurement tools moderated the link between PTG and social support among people with breast cancer. Whether variables such as disease stage, time since diagnosis, and disease treatment moderate the link between PTG and social support among people with breast cancer can be further investigated in the future.
Burnout among general practitioners, a systematic quantitative review of the literature on determinants of burnout and their ecological value
Authors: Verhoef Nicolaas Cornelis , Blomme Robert Jan
Published: December 2022

Burnout is a major social and economic problem, specifically among general practitioners (GPs). The amount of literature on generic determinants of burnout is impressive. However, the size of the library on occupation-specific determinants of burnout among GPs are minimal. With the present study, we aim to gain insight into the existing academic literature on generic and occupation-specific determinants of burnout among GPs. Moreover, we aim to contribute to the ecological validity of this study by emphasizing occupation-specific determinants. We conducted a systematic quantitative literature review in which we followed the PRISMA statement and performed quality assessments according to the AXIS, CASP, MMAT, and 3-MIN procedures. Furthermore, we assessed frequency effect sizes (FES) and intensity effect sizes (IES). By performing Fisher’s exact tests, we investigated whether the quality of the studies influenced the outcomes. An extensive literature search revealed 60 eligible studies among which 28 strong studies, 29 moderate studies, and 3 weak studies were identified. Analyzing those studies delivered 75 determinants of burnout, of which 33 were occupation-specific for GPs. According to the average FES, occupation-specific determinants play a significant role in acquiring burnout compared to the generic determinants. The results of the Fisher exact tests provided evidence that the quality of the 60 studies did not affect the outcomes. We conclude that it is surprising that a profession with such an important social position and such a high risk of burnout has been so little researched.
Off-target pharmacological profiling of synthetic cannabinoid receptor agonists including AMB-FUBINACA, CUMYL-PINACA, PB-22, and XLR-11
Authors: Kevin Richard C. , Cairns Elizabeth A. , Boyd Rochelle , Arnold Jonathon C. , Bowen Michael T. , McGregor Iain S. , Banister Samuel D.
Published: December 2022

Introduction

Synthetic cannabinoid receptor agonists (SCRAs) are a diverse class of new psychoactive substances that have been associated with multiple instances and types of toxicity. Some SCRAs appear to carry a greater toxicological burden than others, or compared to the prototypical cannabis-derived agonist Δ9-tetrahydrocannabinol (Δ9-THC), despite a common primary mechanism of action via cannabinoid 1 (CB1) receptors. “Off-target” (i.e., non-CB1 receptor) effects could underpin this differential toxicity, although there are limited data around the activity of SCRAs at such targets.

Methods

A selection of 7 SCRAs (AMB-FUBINACA, XLR11, PB-22, AKB-48, AB-CHMINICA, CUMYL-PINACA, and 4F-MDMB-BUTINACA), representing several distinct chemotypes and toxicological profiles, underwent a 30 μM single-point screen against 241 G protein-coupled receptor (GPCR) targets in antagonist and agonist mode using a cellular β-arrestin recruitment assay. Strong screening “hits” at specific GPCRs were followed up in detail using concentration-response assays with AMB-FUBINACA, a SCRA with a particularly notable history of toxicological liability.

Results

The single-point screen yielded few hits in agonist mode for any compound aside from CB1 and CB2 receptors, but many hits in antagonist mode, including a range of chemokine receptors, the oxytocin receptor, and histamine receptors. Concentration-response experiments showed that AMB-FUBINACA inhibited most off-targets only at the highest 30 μM concentration, with inhibition of only a small subset of targets, including H1 histamine and α2B adrenergic receptors, at lower concentrations (≥1 μM). AMB-FUBINACA also produced concentration-dependent CB1 receptor signaling disruption at concentrations higher than 1 μM, but did not produce overt cytotoxicity beyond CP55,940 or Δ9-THC in CB1 expressing cells.

Discussion

These results suggest that while some “off-targets” could possibly contribute to the SCRA toxidrome, particularly at high concentrations, CB1-mediated cellular dysfunction provides support for hypotheses concerning on-target, rather than off-target, toxicity. Further investigation of non-GPCR off-targets is warranted.
A story-telling cloth approach to motivating cervical cancer screening in Mali
Authors: Crippin Tiffani , Tounkara Karamoko , Squibb Eliza , Beseme Sarah , Barry Katherine , Sangare Kotou , Coulibaly Saidou , Fané Pinda , Bagayoko Aliou , Koita Ousmane A. , Teguété Ibrahima , De Groot Anne S.
Published: December 2022

Ninety percent of deaths from Cervical cancer (CC) caused by Human Papilloma Virus (HPV) occur in low- and middle-income countries. CC is the 2nd most common cause of cancer in women in West Africa, where 12,000 women develop cervical cancer and more than 6,000 die from the disease, annually. While HPV vaccination and CC screening have dramatically reduced the incidence of CC and mortality from CC in developed countries, prevention of CC in West Africa is often limited to visual inspection of the cervix and surgical intervention. In previous studies of CC in Mali, we demonstrated that knowledge about the link between HPV and CC is limited, and that screening for CC is often delayed until women are symptomatic. For this intervention, a story-telling cloth (West African-style printed pagne) was designed for use as a starting point for educational sessions run by community health workers. Community outreach using the cloth during 6 months of 2015 resulted in a 5-fold higher uptake of cervical cancer screening and increased awareness of the potential to vaccinate adolescents against CC. 3,271 women were motivated to visit one of five participating clinics for CC screening, where a mere 600 women had been screened during the previous year. This study shows that a comprehensive, visual, community-centered education campaign coupled with coordinated support for local clinics improves uptake of CC screening.
Paycheck Protection Program (PPP) COVID-19 relief funding for veteran-, minority-, and women- owned dental businesses: A cross-sectional study
Authors: Alpert Elizabeth , Boynes Sean G. , Shaver Amber , Cothron Annaliese
Published: December 2022

Background

The Covid-19 pandemic exacerbated dental staffing shortages, which impact care delivery and ultimately oral health equity. Federal funding efforts like the Paycheck Protection Program (PPP) sought to aid traditionally underserved businesses including those owned by veterans, minority racial and ethnic groups, and women.

Objectives

(1) To examine differences in PPP funding between veteran- and nonveteran-owned dental care delivery businesses and organizations and (2) to analyze other relevant factors associated with variation in PPP funding levels for dental businesses.

Methods

Using publicly available PPP data, we ran unadjusted bivariable and adjusted multivariable linear regression models to estimate associations between loan approval amount and forgiveness amount, veteran status, and relevant covariates.

Results

Minority racial and ethnic groups and women received less PPP funding and less loan forgiveness, on average, compared with non-minority groups. In the adjusted model with no missing self-reported demographic observations atp < 0.10, veterans received more PPP funding and loan forgiveness, on average, compared to non-veterans.

Conclusion

To our knowledge, this is the first comprehensive analysis of all dental recipients of PPP funding throughout the United States. Despite PPP program intentions and strategies, traditionally underserved dental businesses did not receive increased funding to support employment.
What Does Math Have to Do With Patterns in Fish?
Authors: Shirman Blake , Volkening Alexandria
Published: December 2022

When you think of fish, what comes to mind? Maybe you think of pet goldfish, movie characters like Dory or Nemo, or trout in a local river. One of the things that all these fish have in common is patterns in their skin. Nemo sports black and white stripes in his orange skin, and trout have spots. Even goldfish have a pattern—but it is just plain gold (and kinda boring). Why do some fish have stripes, others have spots, and others have plain patterns? It turns out that this is a tricky question, so scientists need tools from several subjects to answer it. In this paper, we use biology, math, and computer coding to help figure out how fish get different skin patterns.
Variations in differential rotation and meridional flow within the Sun’s surface shear layer 1996–2022
Authors: Hathaway David H. , Upton Lisa A. , Mahajan Sushant S.
Published: December 2022

We measure differential rotation and meridional flow in the Sun’s surface shear layer by tracking the motions of the magnetic network seen in magnetograms from SOHO/MDI and SDO/HMI over solar cycles 23, 24, and the start of 25 (1996–2022). We examine the axisymmetric flows derived from 15 to 24 daily measurements averaged over individual 27-day Carrington rotations. Variations in the differential rotation include the equatorial torsional oscillation—cyclonic flows centered on the active latitudes with slower flows on the poleward sides of the active latitudes and faster flows equatorward. The fast flow band starts at ∼45° latitude during the declining phase of the previous cycle and drifts equatorward, terminating at the equator at about the time of cycle minimum. Variations in the differential rotation also include a polar oscillation above 45° with faster rotation at cycle maxima and slower rotation at cycle minima. The equatorial variations were stronger in cycle 24 than in cycle 23 but the polar variations were weaker. Variations in the meridional flow include a slowing of the poleward flow in the active latitudes during cycle rise and maximum and a speeding up of the poleward flow during cycle decline and minimum. The slowing in the active latitudes was less pronounced in cycle 24 than in cycle 23. Polar countercells (equatorward flow) extend from the poles down to ∼60° latitude from time to time (1996–2000 and 2016–2022 in the south and 2001–2011 and 2017–2022 in the north). Both axisymmetric flows vary in strength with depth. The rotation rate increases inward while the meridional flow weakens inward.
The future of auroral E-region plasma turbulence research
Authors: Huyghebaert Devin , Billett Daniel , Chartier Alex , Chau Jorge L. , Hussey Glenn C. , Hysell David L. , Ivarsen Magnus F. , Mesquita Rafael L. A. , Rojas Enrique , Vierinen Juha , Young Matthew
Published: December 2022

The heating caused by ionospheric E-region plasma turbulence has documented global implications for the energy transfer from space into the terrestrial atmosphere. Traveling atmospheric disturbances, neutral wind motion, energy deposition rates, and ionospheric conductance have all been shown to be potentially affected by turbulent plasma heating. Therefore it is proposed to enhance and expand existing ionospheric radar capabilities and fund research into E-region plasma turbulence so that it is possible to more accurately quantify the solar-terrestrial energy budget and study phenomena related to E-region plasma turbulence. The proposed research funding includes the development of models to accurately predict and model the E-region plasma turbulence using particle-in-cell analysis, fluid-based analysis, and hybrid combinations of the two. This review provides an expanded and more detailed description of the past, present, and future of auroral E-region plasma turbulence research compared to the summary report submitted to the National Academy of Sciences Decadal Survey for Solar and Space Physics (Heliophysics) 2024–2033 (Huyghebaert et al., 2022a).
In Vitro Screening of the Foliage of Eucalyptus Species Harvested in Different Seasons for Modulating Rumen Fermentation and Methane Production
Authors: Horst Egon Henrique , Ammar Hajer , Khouja Mohamed Larbi , Vargas Julio Ernesto , Andrés Sonia , López Secundino
Published: December 2022

The aim of this study was to assess the effects of five eucalyptus species (Eucalyptus camaldulensis, E. leucoxylon, E. astringens, E. sideroxylon, and E. lehmannii), harvested in spring, autumn, or winter from two Tunisian arboretums, on in vitro rumen fermentation and methanogenesis. Batch cultures were performed to determine rumen fermentation kinetics and end-product formation after 24 h of incubation. The foliage of the species E. sideroxylon and E. lehmannii showed the greatest digestibility coefficients, whereas E. leucoxylon was the least digestible. Acetate-to-propionate ratio was reduced when E. sideroxylon and E. lehmannii were incubated, and these species were also the most efficient at reducing methane emission. Foliage harvested in winter showed greater digestibility and an increase in the acetate-to-propionate ratio than in other seasons, without an increase in methane emission. Foliage from E. sideroxylon and E. lehmannii showed a potential to decrease enteric methane production without depressing effects on ruminal fermentation. In vivo studies would be necessary to conclusively validate these effects as the first step towards proposing the inclusion of eucalyptus leaves in ruminant diets.
Comparison of Droplet Distribution and Control Effect of Wheat Aphids under Different Operation Parameters of the Crop Protection UAV in the Wheat Flowering Stage
Authors: Sun Tao , Zhang Songchao , Xue Xinyu , Jiao Yuxuan
Published: December 2022

Aphid is one of the main insect pests of wheat in the flowering stage, so timely and effective control of wheat aphids plays an important role in ensuring wheat yield. The crop protection Unmanned Aerial Vehicle (UAV) is widely used in the control of wheat pests and diseases nowadays. In order to screen out the suitable operation parameters of the crop protection UAV to control the wheat aphids, this study conducted wheat aphid distribution investigation tests and droplet distribution tests. With the P20 electric four-rotor crop protection UAV (Guangzhou Jifei Technology Co., Ltd., Guangzhou, China) as the test equipment, four levels of flight speed (FS: 3, 4, 5, 6 m/s) and three levels of flight height (FH: 1.5, 2, 2.5 m) were combined as operation parameters, tests were carried out to compare the density and uniformity of droplet coverage, and the wheat aphid control tests were carried out by using the optimized operation parameters. The results of the wheat aphid distribution investigation test showed that aphids mainly distributed in the lower layer of the wheat plant canopy, accounting for more than 90.61%. The results of the droplet distribution test showed that with the increase in FS and FH, the coverage density and the droplet distribution uniformity in the upper and lower layers of wheat showed a downward trend under the condition of considering the boundary overlap of spraying width (SW) in multi-routes. Through the comparison of operation efficiency and droplet distribution quality, two combinations of parameters A1 (FS: 3 m/s, FH: 1.5 m) and B1 (FS: 4 m/s, FH: 1.5 m) were selected for the aphid control effect test. The results of the control test showed that the average control effect of A1 (92.05%) on aphids was 10.3% higher than that of B1 (81.75%) 7 days after pesticide application, which indicated that improving the droplet distribution uniformity in the lower layer of wheat could significantly improve the control effect of aphids. This study result could provide reference for the same type of crop protection UAV to control the same type of wheat diseases and insect pests in the same growing stage.
Development and Validation of an Allele-Specific Marker for Resistance to Bacterial Halo Blight in Coffea arabica
Authors: Ariyoshi Caroline , Sera Gustavo Hiroshi , Rodrigues Lucas Mateus Rivero , Carvalho Filipe Gimenez , Shigueoka Luciana Harumi , Mendonça Ana Ester Socatelli , Pereira Carlos Theodoro Motta , Destéfano Suzete Aparecida Lanza , Pereira Luiz Filipe Protasio
Published: December 2022

Bacterial halo blight (BHB) is a bacterial disease, caused by Pseudomonas syringae pv. garcae, which has been gaining prominence in the main coffee-producing regions. Chemical control of this disease increases production costs and is environmentally undesirable. In this scenario, the development of new cultivars resistant to BHB is the most economical and sustainable alternative. Marker-Assisted Selection (MAS) is an appropriate strategy to assist breeding programs for resistant genotype selection. In a previous Genome-Wide Association Study (GWAS) for C. arabica and P. syringae pv. garcae interaction, we identified a locus, probably linked to qualitative resistance to the pathogen. In this work, we developed and validated a pair of Allele-Specific-Polymerase Chain Reaction (AS-PCR) primers for this locus in C. arabica breeding populations. This pair of AS-PCR primers, called Psg_QL1, was tested both in a backcross (BC) (n = 38) and in an F2 population (n = 138) segregating for resistance to BHB. The linkage between the Psg_QL1 marker and qualitative resistance showed an accuracy of 93.75%. Our results demonstrated that the Psg_QL1 marker can be applied in MAS in a robust, simple, fast, and low-cost way.
Harnessing the Rhizosphere Soil Microbiome of Organically Amended Soil for Plant Productivity
Authors: Ayangbenro Ayansina Segun , Chukwuneme Chinenyenwa Fortune , Ayilara Modupe Stella , Kutu Funso Raphael , Khantsi Motlagomang , Adeleke Bartholomew Saanu , Glick Bernard R. , Babalola Olubukola Oluranti
Published: December 2022

Soil degradation remains an ongoing process that is exacerbated by the effects of climate change. Consequently, these processes decrease soil organic matter and nutrient contents, soil biological functions, and plant productivity. The addition of organic amendments (OAs) to the soil is a widespread practice to enhance soil quality and the health of agricultural soils. One of the most significant microbial hotspots controlling the processes, dynamics, and cycling of nutrients, carbon and water in terrestrial ecosystems is the rhizosphere. Understanding the continuing transformations of OAs and the distribution of different factors (C, nutrients, and microbial activities) across and along roots is crucial in the rhizosphere. The application of OAs to soil increases soil organic matter and nutrients, water holding capacity, improves soil structure and stimulates soil microbial activity and biomass. This review evaluates the role of the rhizosphere microbial community in organically amended soils for promoting plant growth and health. The diversity of the rhizosphere microbiome and the mechanisms used in plant protection are discussed.
Evaluation of Two Practical Tools to Assess Cognitive Impairment in Aged Dogs
Authors: Le Brech Susana , Amat Marta , Temple Déborah , Manteca Xavier
Published: December 2022

Cognitive dysfunction syndrome is the most common cause of cognitive decline in aged dogs. Early diagnosis is crucial because the sooner treatment is implemented, the greater the chance of slowing the progression of the disease. Assessment tools to assess cognitive decline may differ depending on the environment in which the dogs live. The aims of this study were threefold, first, to describe two feasible methods to evaluate cognitive impairment in aged dogs living in different environments: (i) a Canine Cognitive Assessment Scale (CCAS) for dogs living in a home environment and (ii) a practical cognitive test (PCT) potentially useful for dogs not living in a home environment (NHE); second, to assess the effect of age on the outcome of both tools and, finally, to compare the results of the CCAS with those of the PCT. Both methods were found to be practical to perform. Age was found to significantly predict the score obtained by the CCAS (p = 0.0011) and the outcome of the PCT (p = 0.009). However, the reversal phase from the PCT did not significantly predict the outcomes of the CCAS (p = 0.97). Taken together, these findings suggest that the CCAS is a practical method to evaluate age related cognitive changes in owned dogs. The fact that the PCT has not been proven to be related with the CCAS calls into question the use of the PCT as a sensitive tool to assess cognitive impairment. Further studies in this field are suggested.
Potential of Agroindustrial By-Products to Modulate Ruminal Fermentation and Reduce Methane Production: In Vitro Studies
Authors: Marcos Carlos Navarro , Evan Trinidad de , Jiménez Christian , Carro María Dolores
Published: December 2022

The effects of including wine lees (WL), exhausted olive cake (EOC) and a 1:1 mixture of EOC and tomato pomace (EOCTP) in diets for fattening ruminants on in vitro fermentation parameters and CH4 production were analysed. Ten diets were studied, containing either none of the tested by-products (control), or 6.0, 12.0 or 18.0% of WL, EOC and ECOTP formulated to have similar protein and fiber content. Diets were incubated in vitro with sheep ruminal fluid to measure gas production kinetics and fermentation parameters. Increasing the level of WL, EOC and EOCTP decreased linearly (p ≤ 0.009) the potential gas production, but other gas production parameters were unaffected (p > 0.05), excepting that EOCTP increased the gas production rate. No differences (p ≥ 0.0.05) among diets were observed in total volatile fatty acid (VFA) production at 24 h of incubation for EOC and EOCTP, but NH3-N concentration decreased (p ≤ 0.003). In contrast, WL at 12.0 and 18.0% decreased (p < 0.05) total VFA production and increased the acetate/propionate ratio (p < 0.05). None of the by-products had an effect on CH4 production (p ≥ 0.0.05). Results indicate that EOC and EOCTP could be included up to 18.0% in fattening diets, but lower levels of WL are recommended.
Disaster Precursor Identification and Early Warning of the Lishanyuan Landslide Based on Association Rule Mining
Authors: Xu Junwei , Bai Dongxin , He Hongsheng , Luo Jianlan , Lu Guangyin
Published: December 2022

It is the core prerequisite of landslide warning to mine short-term deformation patterns and extract disaster precursors from real-time and multi-source monitoring data. This study used the sliding window method and gray relation analysis to obtain features from multi-source, real-time monitoring data of the Lishanyuan landslide in Hunan Province, China. Then, the k-means algorithm with particle swarm optimization was used for clustering. Finally, the Apriori algorithm is used to mine strong association rules between the high-speed deformation process and rainfall features of this landslide to obtain short-term deformation patterns and precursors of the disaster. The data mining results show that the landslide has a high-speed deformation probability of more than 80% when rainfall occurs within 24 h and the cumulative rainfall is greater than 130.60 mm within 7 days. It is of great significance to extract the short-term deformation pattern of landslides by data mining technology to improve the accuracy and reliability of early warning.
Bio-Sourced and Biodegradable Membranes
Authors: Ehsani Masoume , Kalugin Denis , Doan Huu , Lohi Ali , Abdelrasoul Amira
Published: December 2022

Biodegradable membranes with innovative antifouling properties are emerging as possible substitutes for conventional membranes. These types of membranes have the potential to be applied in a wide range of applications, from water treatment to food packaging and energy production. Nevertheless, there are several existing challenges and limitations associated with the use of biodegradable membranes in large scale applications, and further studies are required to determine the degradation mechanisms and their scalability. Biodegradable membranes can be produced from either renewable natural resources or synthesized from low-molecular monomers that increase the number of possible structures and, as a result, greatly expand the membrane application possibilities. This study focused on bio-sourced and synthesized biodegradable polymers as green membrane materials. Moreover, the article highlighted the excellent antifouling properties of biodegradable membranes that assist in improving membrane lifetime during filtration processes, preventing chemical/biological disposal due to frequent cleaning processes and ultimately reducing the maintenance cost. The industrial and biomedical applications of biodegradable membranes were also summarized, along with their limitations. Finally, an overview of challenges and future trends regarding the use of biodegradable membranes in various industries was thoroughly analyzed.
Integrating a LiDAR Sensor in a UAV Platform to Obtain a Georeferenced Point Cloud
Authors: Del Savio Alexandre Almeida , Luna Torres Ana , Chicchón Apaza Miguel Angel , Vergara Olivera Mónica Alejandra , Llimpe Rojas Sara Rocío , Urday Ibarra Gianella Tania , Reyes Ñique José Luis , Macedo Arevalo Rolando Issac
Published: December 2022

The combination of light detection and ranging (LiDAR) sensors and unmanned aerial vehicle (UAV) platforms have garnered considerable interest in recent years because of the wide range of applications performed through the generation of point clouds, such as surveying, building layouts and infrastructure inspection. The attributed benefits include a shorter execution time and higher accuracy when surveying and georeferencing infrastructure and building projects. This study seeks to develop, integrate and use a LiDAR sensor system implemented in a UAV to collect topography data and propose a procedure for obtaining a georeferenced point cloud that can be configured according to the user’s needs. A structure was designed and built to mount the LiDAR system components to the UAV. Survey tests were performed to determine the system’s accuracy. An open-source ROS package was used to acquire data and generate point clouds. The results were compared against a photogrammetric survey, denoting a mean squared error of 17.1 cm in survey measurement reliability and 76.6 cm in georeferencing reliability. Therefore, the developed system can be used to reconstruct extensive topographic environments and large-scale infrastructure in which a presentation scale of 1/2000 or more is required, due to the accuracy obtained in the work presented.
Elastoplastic Analysis of Plates with Radial Point Interpolation Meshless Methods
Authors: Belinha Jorge , Aires Miguel
Published: December 2022

For both linear and nonlinear analysis, finite element method (FEM) software packages, whether commercial or in-house, have contributed significantly to ease the analysis of simple and complex structures with various working conditions. However, the literature offers other discretization techniques equally accurate, which show a higher meshing flexibility, such as meshless methods. Thus, in this work, the radial point interpolation meshless method (RPIM) is used to obtain the required variable fields for a nonlinear elastostatic analysis. This work focuses its attention on the nonlinear analysis of two benchmark plate-bending problems. The plate is analysed as a 3D solid and, in order to obtain the nonlinear solution, modified versions of the Newton–Raphson method are revisited and applied. The material elastoplastic behaviour is predicted assuming the von Mises yield surface and isotropic hardening. The nonlinear algorithm is discussed in detail. The analysis of the two benchmark plate examples allows us to understand that the RPIM version explored is accurate and allows to achieve smooth variable fields, being a solid alternative to FEM.
An Earthquake Early Warning Method Based on Bayesian Inference
Authors: Yang Jingsong , He Fulin , Li Zhitao , Zhang Yinzhe
Published: December 2022

Earthquake early warning (EEW) systems can give people warnings before damaging ground motions reach their site and can reduce earthquake-related losses. It has been shown that Bayesian reference can be used to estimate earthquake magnitude, location, and the distribution of peak ground motion using observed ground-motion amplitudes, predefined prior information, and appropriate attenuation relationships. In this article, we describe a Bayesian approach to earthquake early warning (EEW) systems for the estimation of magnitude (M) and peak ground-motion velocity (PGV) using the Gutenberg–Richter relation as a priori probability derived from statistical historical earthquake information from the Japanese KiK-net. Moreover, using the magnitude Mj = 4.5 and PGV = 0.4 cm/s as the warning threshold, an earthquake hazard discrimination model was established. Following this, the proposed approach was compared with the traditional fitting method to analyze the earthquake hazard discrimination using an Mj = 4.3 earthquake in the Mt. Fuji area and an Mj = 5.5 earthquake in the Ibaraki area of Japan as examples. The results are as follows: (1) The probabilistic algorithm founded on the predictive model of the magnitude from the average period (τc) and PGV from the displacement amplitude (Pd) from the initial 3 s of the P wave is able to provide a fast and accurate estimation of the final magnitude and location. (2) The Bayesian inference approach for the earthquake hazard discrimination model has a 2.94% miss rate and a 5.88% false alarm rate, which is lower than that of the traditional fitting method, thus increasing the accuracy and reliability of earthquake hazard estimation.
Research on the Tooth Surface Integrity of Non-Circular Gear WEDM Based on HPSO Optimization SVR
Authors: Zhao Jiali , Wang Qing , Wang Yazhou , Wu Dan , Zhang Liang , Shen Bobo
Published: December 2022

Non-circular gears have the characteristics of gear ratio accuracy, good dynamic performance, and wide application prospects but are difficult to manufacture. Wire electrical discharge machining (WEDM) can process almost all kinds of non-circular gear. In order to solve the problem that the process parameters are mainly adjusted using the operator’s experience and to improve the surface quality of non-circular gears machined using WEDM, this research took Pascal gears processed with a fast-walking WEDM machine as the object, conducted orthogonal tests, and used hybrid particle swarm optimization (HPSO) to optimize support vector regression (SVR) with different kernel functions, to predict various surface integrity indicators. The results showed that the rbf kernel function had a better performance in the prediction model of surface integrity indicators, which can provide a reference for the parameter selection of non-circular gear machining using WEDM. The final predicted results were R2 = 0.9978, MAPE = 0.4534 for surface roughness, R2 = 0.9483, MAPE = 3.1673 for surface residual stress, and R2 = 0.9786, MAPE = 0.4779 for surface microhardness.
Community Solar Operation Strategy for Smart Energy Communities Considering Resource Fairness
Authors: Oh Eunsung
Published: December 2022

This study proposes a community solar operation strategy for smart energy communities (SECs), which comprise members of an energy consumption group, to minimize the electricity bill of its members. When sharing resources within a group, resource distribution is a critical problem, and fairness in resource sharing is the main constraint for operation. The proposed community solar operation is formulated as a mixed-integer liner problem that can be optimally solved using centralized control and future time information. However, obtaining information of a future time is not causal. By decomposing the problem into individual problems that are solved by each member at each decision time, the proposed strategy operates the community solar in a distributed manner with partial information. The simulation results using the real dataset recorded in Korea show that the use of the proposed operation strategy results in a fair distribution of electricity bill savings with a marginal benefit reduction of 10% compared to the optimal operation that requires a centralized control and information on the future time. Moreover, a discussion on the tradeoff between the benefits of electricity bill savings and guarantee of fairness is provided. Based on the results, this study can serve as a reference for the design of community solar operations for SECs.
Semi-Active Control of Seismic Response on Prestressed Concrete Continuous Girder Bridges with Corrugated Steel Webs
Authors: Zheng Shangmin , Shen Qiang , Guan Chong , Cheng Haigen , Zhuang Haiyan , Zhou Man
Published: December 2022

To improve the seismic capacity of prestressed concrete (PC) continuous girder bridges with corrugated steel webs (CSWs), suitable damping control measures can be used to effectively reduce the seismic response of the bridge. Based on the semi-active control theory, the semi-active control system of a three-span PC continuous girder bridge with CSWs is designed, and the semi-active control system program of the three-span PC continuous girder bridge with CSWs is compiled by MATLAB. The time–history curves of damper energy consumption of active optimal control algorithm and three different semi-active control algorithms are compared and analyzed, as are the time–history curves of main girder displacement, acceleration, and pier internal force with or without semi-active control. The study shows that the rational determination of the weight matrix coefficient can make the active control achieve a better vibration absorption effect and economy. The semi-active control algorithm of Hrovat has the best vibration absorption effect, which is closest to that of the active optimal control algorithm. Under the state of semi-active control, the average vibration absorption rate of displacement and acceleration of the main girder with CSWs are 71% and 20%, respectively. The time–history curve of bending moment and shear force in the pier bottom is similar, and the average vibration absorption rate of bending moment and shear force at the bottom of pier #2 is 70%. At the same time, the average vibration absorption rate of bending moment and shear force at the bottom of pier #3 is between 42% and 48%. The semi-active control measure has a good vibration absorption effect on the overall seismic response of the PC continuous girder bridges with CSWs. This study provides a certain reference for the seismic reduction and isolation design of composite structure bridge with CSWs.
What Is (Not) Big Data Based on Its 7Vs Challenges: A Survey
Authors: González García Cristian , Álvarez-Fernández Eva
Published: December 2022

Big Data has changed how enterprises and people manage knowledge and make decisions. However, when talking about Big Data, so many times there are different definitions about what it is and what it is used for, as there are many interpretations and disagreements. For these reasons, we have reviewed the literature to compile and provide a possible solution to the existing discrepancies between the terms Data Analysis, Data Mining, Knowledge Discovery in Databases, and Big Data. In addition, we have gathered the patterns used in Data Mining, the different phases of Knowledge Discovery in Databases, and some definitions of Big Data according to some important companies and organisations. Moreover, Big Data has challenges that sometimes are the same as its own characteristics. These characteristics are known as the Vs. Nonetheless, depending on the author, these Vs can be more or less, from 3 to 5, or even 7. Furthermore, the 4Vs or 5Vs are not the same every time. Therefore, in this survey, we reviewed the literature to explain how many Vs have been detected and explained according to different existing problems. In addition, we detected 7Vs, three of which had subtypes.
Anti-Inflammatory Property of 5-Demethylnobiletin (5-Hydroxy-6, 7, 8, 3′, 4′-pentamethoxyflavone) and Its Metabolites in Lipopolysaccharide (LPS)-Induced RAW 264.7 Cells
Authors: Guo Shanshan , Wu Xian , Zheng Jinkai , Song Mingyue , Dong Ping , Xiao Hang
Published: December 2022

Hydroxylated polymethoxyflavones (PMFs) are a unique class of flavonoid compounds mainly found in citrus plants. We investigated the anti-inflammatory effects of one major 5-hydroxy PMF, namely 5-demethylnobiletin (5DN) and its metabolites 5, 3′-didemethylnobiletin (M1), 5, 4′-didemethylnobiletin (M2), and 5, 3′, 4′-tridemethylnobiletin (M3) in lipopolysaccharide (LPS)-stimulated RAW 264.7 macrophage cells. The results showed that M2 and M3 produced stronger inhibitory effects on the production of nitric oxide (NO) than their parent compound at non-cytotoxic concentrations. Western blotting and real-time PCR analyses demonstrated that M2 and M3 significantly decreased iNOS and COX-2 gene expression. The results also showed that M1 and M3 induced heme oxygenase-1(HO-1) gene expression. Overall, our results demonstrated that metabolites of 5DN significantly inhibited LPS-induced inflammation in RAW 264.7 macrophage cells and generally possessed more potent anti-inflammatory activity than the parent compound, 5DN.
Spatiotemporal Variation of Urban Plant Diversity and above Ground Biomass in Haikou, China
Authors: Zhang Hai-Li , Nizamani Mir Muhammad , Cubino Josep Padullés , Guo Lin-Yuan , Zhou Jing-Jiang , Wang Hua-Feng
Published: December 2022

Understanding the drivers of urban plant diversity (UPD) and above ground biomass (AGB) in urbanized areas is critical for urban ecosystem services and biodiversity protection. The relationships between UPD and AGB have been investigated simultaneously. However, the drivers of UPD and AGB have been explored independently in tropical coastal areas at different time points. To fill this gap, we conducted a remote sensing interpretation, field plant plot surveys, and compiled socioeconomic and urban greening management survey data. We conducted spatial analyses to investigate the relationships among UPD and socioeconomic variables across different primary and secondary urban functional units (UFUs) in the tropical urban ecosystems of the coastal city of Haikou, China. The primary UFUs with the highest AGB were the recreation and leisure districts in 2015 and 2021. In 2015, AGB was mainly correlated with the number of herb species in undeveloped land and the districts of industry, business, recreation, and leisure. In 2021, AGB was affected primarily by the frequency of fertilizing, maintenance, and watering. Our study found that the relationship between UPD and AGB varied across time and space in Haikou. The plant diversity and AGB’s response to human activities and socioeconomics appear to have a time-lag effect. These results provide new insights in understanding how management decisions affect urban vegetation and could be used to guide future urban green space planning in Haikou.
Spectral Method in Epidemic Time Series: Application to COVID-19 Pandemic
Authors: Demongeot Jacques , Magal Pierre
Published: December 2022

Background: The age of infection plays an important role in assessing an individual’s daily level of contagiousness, quantified by the daily reproduction number. Then, we derive an autoregressive moving average model from a daily discrete-time epidemic model based on a difference equation involving the age of infection. Novelty: The article’s main idea is to use a part of the spectrum associated with this difference equation to describe the data and the model. Results: We present some results of the parameters’ identification of the model when all the eigenvalues are known. This method was applied to Japan’s third epidemic wave of COVID-19 fails to preserve the positivity of daily reproduction. This problem forced us to develop an original truncated spectral method applied to Japanese data. We start by considering ten days and extend our analysis to one month. Conclusion: We can identify the shape for a daily reproduction numbers curve throughout the contagion period using only a few eigenvalues to fit the data.
Drug Repurposing Using Gene Co-Expression and Module Preservation Analysis in Acute Respiratory Distress Syndrome (ARDS), Systemic Inflammatory Response Syndrome (SIRS), Sepsis, and COVID-19
Authors: Mailem Ryan Christian , Tayo Lemmuel L.
Published: December 2022

SARS-CoV-2 infections are highly correlated with the overexpression of pro-inflammatory cytokines in what is known as a cytokine storm, leading to high fatality rates. Such infections are accompanied by SIRS, ARDS, and sepsis, suggesting a potential link between the three phenotypes. Currently, little is known about the transcriptional similarity between these conditions. Herein, weighted gene co-expression network analysis (WGCNA) clustering was applied to RNA-seq datasets (GSE147902, GSE66890, GSE74224, GSE177477) to identify modules of highly co-expressed and correlated genes, cross referenced with dataset GSE160163, across the samples. To assess the transcriptome similarities between the conditions, module preservation analysis was performed and functional enrichment was analyzed in DAVID webserver. The hub genes of significantly preserved modules were identified, classified into upregulated or downregulated, and used to screen candidate drugs using Connectivity Map (CMap) to identify repurposed drugs. Results show that several immune pathways (chemokine signaling, NOD-like signaling, and Th1 and Th2 cell differentiation) are conserved across the four diseases. Hub genes screened using intramodular connectivity show significant relevance with the pathogenesis of cytokine storms. Transcriptomic-driven drug repurposing identified seven candidate drugs (SB-202190, eicosatetraenoic-acid, loratadine, TPCA-1, pinocembrin, mepacrine, and CAY-10470) that targeted several immune-related processes. These identified drugs warrant further study into their efficacy for treating cytokine storms, and in vitro and in vivo experiments are recommended to confirm the findings of this study.
Noninvasive Monitoring of Simulated Hemorrhage and Whole Blood Resuscitation
Authors: Gupta Jay F. , Arshad Saaid H. , Telfer Brian A. , Snider Eric J. , Convertino Victor A.
Published: December 2022

Hemorrhage is the leading cause of preventable death from trauma. Accurate monitoring of hemorrhage and resuscitation can significantly reduce mortality and morbidity but remains a challenge due to the low sensitivity of traditional vital signs in detecting blood loss and possible hemorrhagic shock. Vital signs are not reliable early indicators because of physiological mechanisms that compensate for blood loss and thus do not provide an accurate assessment of volume status. As an alternative, machine learning (ML) algorithms that operate on an arterial blood pressure (ABP) waveform have been shown to provide an effective early indicator. However, these ML approaches lack physiological interpretability. In this paper, we evaluate and compare the performance of ML models trained on nine ABP-derived features that provide physiological insight, using a database of 13 human subjects from a lower-body negative pressure (LBNP) model of progressive central hypovolemia and subsequent progressive restoration to normovolemia (i.e., simulated hemorrhage and whole blood resuscitation). Data were acquired at multiple repressurization rates for each subject to simulate varying resuscitation rates, resulting in 52 total LBNP collections. This work is the first to use a single ABP-based algorithm to monitor both simulated hemorrhage and resuscitation. A gradient-boosted regression tree model trained on only the half-rise to dicrotic notch (HRDN) feature achieved a root-mean-square error (RMSE) of 13%, an R2 of 0.82, and area under the receiver operating characteristic curve of 0.97 for detecting decompensation. This single-feature model’s performance compares favorably to previously reported results from more-complex black box machine learning models. This model further provides physiological insight because HRDN represents an approximate measure of the delay between the ABP ejected and reflected wave and therefore is an indication of cardiac and peripheral vascular mechanisms that contribute to the compensatory response to blood loss and replacement.
Estimation of Respiratory Rate from Functional Near-Infrared Spectroscopy (fNIRS): A New Perspective on Respiratory Interference
Authors: Hakimi Naser , Shahbakhti Mohammad , Sappia Sofia , Horschig Jörn M. , Bronkhorst Mathijs , Floor-Westerdijk Marianne , Valenza Gaetano , Dudink Jeroen , Colier Willy N. J. M.
Published: December 2022

Objective: Respiration is recognized as a systematic physiological interference in functional near-infrared spectroscopy (fNIRS). However, it remains unanswered as to whether it is possible to estimate the respiratory rate (RR) from such interference. Undoubtedly, RR estimation from fNIRS can provide complementary information that can be used alongside the cerebral activity analysis, e.g., sport studies. Thus, the objective of this paper is to propose a method for RR estimation from fNIRS. Our primary presumption is that changes in the baseline wander of oxygenated hemoglobin concentration (O2Hb) signal are related to RR. Methods: fNIRS and respiratory signals were concurrently collected from subjects during controlled breathing tasks at a constant rate from 0.1 Hz to 0.4 Hz. Firstly, the signal quality index algorithm is employed to select the best O2Hb signal, and then a band-pass filter with cut-off frequencies from 0.05 to 2 Hz is used to remove very low- and high-frequency artifacts. Secondly, troughs of the filtered O2Hb signal are localized for synthesizing the baseline wander (S1) using cubic spline interpolation. Finally, the fast Fourier transform of the S1 signal is computed, and its dominant frequency is considered as RR. In this paper, two different datasets were employed, where the first one was used for the parameter adjustment of the proposed method, and the second one was solely used for testing. Results: The low mean absolute error between the reference and estimated RRs for the first and second datasets (2.6 and 1.3 breaths per minute, respectively) indicates the feasibility of the proposed method for RR estimation from fNIRS. Significance: This paper provides a novel view on the respiration interference as a source of complementary information in fNIRS.