bluuebunny/crossref_metadata_2025 huggingface dataset:
Online Control of Smart Inverter for Photovoltaic Power Generation Systems in a Smart Grid
Authors: Huang Kuo-Hua , Chao Kuei-Hsiang , Sun Zhi-Yao , Liao Yu-Hsiang
Published: July 2022

The main purpose of this study is to engage in research on a grid-connected photovoltaic (PV) power generation system smart inverter. The research content includes a smart maximum power point tracking (MPPT) controller and an inverter with power regulation. First, use the PSIM software package to establish the simulation environment of the grid-connected photovoltaic power generation system and use the Sanyo HIP-186BA19 photovoltaic module to form a 744 W system for simulation. In order to enable the photovoltaic module array (PVMA) to output the maximum power under different solar insolation and ambient temperature, the architecture is based on the extension theory-based smart MPPT method to improve the dynamic response and steady-state performance of photovoltaic power generation systems compared to perturb and observed (P&O) MPPT. When the sunshine is 1,000 W/m2, the photovoltaic power generation system adopts the extension theory-based maximum power tracking method. The time required to track the maximum power point is only 0.32 s, and the steady-state ripple is only 4.127 W. However, using the traditional P&O method requires 0.741 s to track the maximum power point, and the steady-state ripple reaches 18.131 W. Thus, the dynamic response speed of the maximum power tracking method proposed is 50% faster than that of the P&O method. The steady-state performance is also better compared to the P&O method. At the same time, a simple proportional-integral (PI) controller is used to regulate the DC-link voltage, output voltage, and current of the inverter to make the voltage of the grid-connected point stable at an effective value of 220 V. Then, the voltage-power control technology is added to the photovoltaic grid-connected inverter, and a simple proportional-integral controller is used to regulate the output of the smart inverter reactive power to improve the power quality of grid voltage. Finally, simulation and experimental results are used to verify the effectiveness of the regulation performance of the developed smart inverter.
Soil Mapping Using Electromagnetic Induction to Assess the Suitability of Land for Growing Leptospermum nitens in Western Australia
Authors: Shaukat Hira , Flower Ken C. , Leopold Matthias
Published: July 2022

Leptospermum sp. with dihydroxyacetone in their nectar are a source of high-value medicinal honey production and can provide income from agriculturally marginal lands. The current study was from two newly planted Leptospermum nitens sites, one with duplex soil and the other in deep sandy soil, in the low rainfall areas of the south-west of Western Australia, with the aim of identifying key soil parameters influencing the plantation’s survival and growth. Electromagnetic induction (EMI) at different depths was used to investigate the possible impact of soil variability on the Leptospermum nitens plantations. Two EMI surveys were conducted at each site, at different times of the year, to account for soil moisture variability (relatively dry and wet conditions). A least-square inversion algorithm was used to determine true electrical conductivities at three different soil depths (0–0.5, 0.5–0.8, and 0.8–1.6 m) to produce quasi-3D maps of soil inverted electrical conductivity. Corresponding soil samples from each depth were used for the physico-chemical analysis of soil parameters and to develop laboratory-based electrical resistivity to soil volumetric moisture calibrations with R2 values between 0.95 and 0.99. Shrub survival and growth (canopy diameter) were estimated using unmanned aerial vehicle (UAV) images and machine learning. Comparing EMI soil mapping with UAV imagery results showed significantly greater shrub survival and growth (p < 0.001) in areas with higher ECa ranges of 12–24 mS m−1 at the variable textured site and 6–9 mS m−1 at the uniformly sandy site. Overall, the variable textured site, with an 82% survival rate, had a significantly higher shrub count and larger plants than the uniformly sandy site, with a 75% survival rate. A principal component analysis (PCA) identified inverted EC to be strongly correlated with soil moisture > pH > soil texture. Such soil mapping may be a robust and effective method for risk assessment of new shrub plantations.
Research of the Impact of Heterogeneous Environmental Regulation on the Performance of China’s Manufacturing Enterprises
Authors: Chen Wenzhi , Chen Shi , Wu Tingting
Published: July 2022

Promoting high-quality economic development with high-level ecological protection is one of the most important tasks in China’s new stage of development. The improvement of enterprise performance is the micro-foundation of high-quality economic development, while environmental regulations aim to reduce the negative effect of economic development on the environment. Consequently, the microeconomic effects of environmental regulation have received widespread attention in academia. Previous studies have emphasized the effect of environmental regulations on firm performance but have not reached a consensus and lack of insight on the combined effects of different types of environmental regulation. This study aims to fill this gap by considering the heterogeneity of environmental regulations and the effect of the interaction between heterogeneous environmental regulations on enterprise performance. To reveal the relationship between the different types of environmental regulations and the performance of manufacturing enterprises, and the possible impact mechanism, this study uses the fixed effect model to test the impact of different environmental regulations on the performance of manufacturing enterprises, the mediation effect model is used to check whether or not an environmental regulation affects the performance of manufacturing enterprises by improving the level of technological innovation of enterprises, and the moderating effect model is used to examine the impact of the interaction between different environmental regulations on the performance of manufacturing enterprises. The results show that command-and-control environmental regulation inhibits the performance improvement of manufacturing enterprises, while a market-based environmental regulation enhances performance by improving the technological innovation level of enterprises. Market-based environmental regulation will alleviate the disincentive effect of command-control environmental regulation on the performance of manufacturing enterprise.
Spatial effects of climate change on tourism development in china: An analysis of tourism value chains
Authors: Xiong Na , Sun Bingteng , Jiang Linli , Cui Haitao
Published: July 2022

Tourism value chains is scattered across the economic fields. This paper seeks to carry out an empirical analysis of the relationship between climate change and tourism development in China. We used relevant data from 31 provinces in China, and analyzed the spatial effects of climate change on tourism development using a spatial Durbin model. In the development of tourism in Chinese provinces, the research results show that the high-high agglomeration areas of inbound overnight tourists are widely distributed in the coastal areas of eastern China, while the low-low agglomeration areas are mainly distributed in western China, showing an unreasonable bipolar distribution. In terms of climate change, the increase of annual precipitation contributes to the enhancement of the number of inbound overnight tourists in local areas, but reduces the number of inbound overnight tourists in adjacent areas; the increase of annual average temperature raises the number of inbound overnight tourists in local areas, but decreases the number of inbound overnight tourists in adjacent areas; which indicates that there is a spatial spillover effect of climate change on tourism development. Therefore, we propose that western China should receive further policy support, the positive spatial spillover effect of the number of inbound overnight visitors among provinces should be fully utilized, and the tourist attractions should be enriched and developed. However, there are some limitations in the construction of the spatial weight matrix, the consideration of sample size, and the selection of factors affecting tourism development.
Recent Advances in the Molecular Design and Delivery Technology of mRNA for Vaccination Against Infectious Diseases
Authors: Yang Lu , Tang Lin , Zhang Ming , Liu Chaoyong
Published: July 2022

Vaccines can prevent many millions of illnesses against infectious diseases and save numerous lives every year. However, traditional vaccines such as inactivated viral and live attenuated vaccines cannot adapt to emerging pandemics due to their time-consuming development. With the global outbreak of the COVID-19 epidemic, the virus continues to evolve and mutate, producing mutants with enhanced transmissibility and virulence; the rapid development of vaccines against such emerging global pandemics becomes more and more critical. In recent years, mRNA vaccines have been of significant interest in combating emerging infectious diseases due to their rapid development and large-scale production advantages. However, their development still suffers from many hurdles such as their safety, cellular delivery, uptake, and response to their manufacturing, logistics, and storage. More efforts are still required to optimize the molecular designs of mRNA molecules with increased protein expression and enhanced structural stability. In addition, a variety of delivery systems are also needed to achieve effective delivery of vaccines. In this review, we highlight the advances in mRNA vaccines against various infectious diseases and discuss the molecular design principles and delivery systems of associated mRNA vaccines. The current state of the clinical application of mRNA vaccine pipelines against various infectious diseases and the challenge, safety, and protective effect of associated vaccines are also discussed.
Forgetting Details in Visual Long-Term Memory: Decay or Interference?
Authors: García-Rueda Laura , Poch Claudia , Campo Pablo
Published: July 2022

Two main explanations for memory loss have been proposed. On the one hand, decay theories consider that over time memory fades away. On the other hand, interference theories sustain that when similar memories are encoded, they become more prone to confusion. The interference is greater as the degree of similarity between memories increases, and as the number of similar traces increases too. To reduce interference, the pattern separation process allows the brain to separate similar memories and build detailed memory representations that are less easily confused. Nonetheless, with time, we tend to remember more general aspects of experiences, which also affects our ability to discriminate. We present the results of one experiment in which brain activity was recorded by EEG while two groups of healthy participants performed a visual memory discrimination task. This task assesses the ability to differentiate new but similar information from previously learned information and thus avoid interference. Unlike previous studies, we used a paradigm that was specifically designed to assess the impact of the number of items (2 or 6) of each category stored in memory, as well as the time elapsed after the study phase (20 min or 24 h), on recognition memory for objects. Behaviorally, our results suggest that mnemonic discrimination is not modulated by the passage of time, but by the number of stored events. ERP results show a reduced amplitude in posterior regions between 500 and 700 ms when comparing short and long delays. We also observe a more positive activity in a centro-posterior region in the 500–700 ms window at retrieval when participants store more items. Interestingly, amplitudes for old hits and similar false alarms were greater than amplitudes for correctly rejected new items between 500 and 700 ms. This finding indicates that a recollection-based process operates in both true and false recognition. We also found that the waveforms for correct rejections of similar lures and the waveforms for correct rejections of new items were comparable.
Long-Term Intranasal Nerve Growth Factor Treatment Favors Neuron Formation in de novo Brain Tissue
Authors: Colitti Nina , Desmoulin Franck , Le Friec Alice , Labriji Wafae , Robert Lorenne , Michaux Amandine , Conchou Fabrice , Cirillo Carla , Loubinoux Isabelle
Published: July 2022

Objective

To date, no safe and effective pharmacological treatment has been clinically validated for improving post-stroke neurogenesis. Growth factors are good candidates but low safety has limited their application in the clinic. An additional restraint is the delivery route. Intranasal delivery presents many advantages.

Materials and Methods

A brain lesion was induced in twenty-four rats. Nerve growth factor (NGF) 5 μg/kg/day or vehicle was given intranasally from day 10 post-lesion for two periods of five weeks, separated by a two-week wash out period with no treatment. Lesion volume and atrophy were identified by magnetic resonance imaging (MRI). Anxiety and sensorimotor recovery were measured by behavior tests. Neurogenesis, angiogenesis and inflammation were evaluated by histology at 12 weeks.

Results

Remarkable neurogenesis occurred and was visible at the second and third months after the insult. Tissue reconstruction was clearly detected by T2 weighted MRI at 8 and 12 weeks post-lesion and confirmed by histology. In the new tissue (8.1% of the lesion in the NGF group vs. 2.4%, in the control group at 12 weeks), NGF significantly increased the percentage of mature neurons (19% vs. 7%). Angiogenesis and inflammation were not different in the two groups. Sensorimotor recovery was neither improved nor hampered by NGF during the first period of treatment, but NGF treatment limited motor recovery in the second period.

Interpretation

The first five-week period of treatment was very well tolerated. This study is the first presenting the effects of a long treatment with NGF and has shown an important tissue regeneration rate at 8 and 12 weeks post-injury. NGF may have increased neuronal differentiation and survival and favored neurogenesis and neuron survival through subventricular zone (SVZ) neurogenesis or reprogramming of reactive astrocytes. For the first time, we evidenced a MRI biomarker of neurogenesis and tissue reconstruction with T2 and diffusion weighted imaging.
Chemosensory Contributions of E-Cigarette Additives on Nicotine Use
Authors: Johnson Natalie L. , Patten Theresa , Ma Minghong , De Biasi Mariella , Wesson Daniel W.
Published: July 2022

While rates of smoking combustible cigarettes in the United States have trended down in recent years, use of electronic cigarettes (e-cigarettes) has dramatically increased, especially among adolescents. The vast majority of e-cigarette users consume “flavored” products that contain a variety of chemosensory-rich additives, and recent literature suggests that these additives have led to the current “teen vaping epidemic.” This review, covering research from both human and rodent models, provides a comprehensive overview of the sensory implications of e-cigarette additives and what is currently known about their impact on nicotine use. In doing so, we specifically address the oronasal sensory contributions of e-cigarette additives. Finally, we summarize the existing gaps in the field and highlight future directions needed to better understand the powerful influence of these additives on nicotine use.
The cumulative therapeutic effect of acupuncture in patients with migraine without aura: Evidence from dynamic alterations of intrinsic brain activity and effective connectivity
Authors: Chen Yilei , Kang Yingjie , Luo Shilei , Liu Shanshan , Wang Bo , Gong Zhigang , Huang Yanwen , Wang Hui , Zhan Songhua , Tan Wenli
Published: July 2022

We explored the dynamic alterations of intrinsic brain activity and effective connectivity after acupuncture treatment to investigate the underlying neurological mechanism of acupuncture treatment in patients with migraine without aura (MwoA). The Functional Magnetic Resonance Imaging (fMRI) scans were separately obtained at baseline, after the first and 12th acupuncture sessions in 40 patients with MwoA. Compared with the healthy controls (HCs), patients with MwoA mostly showed a decreased dynamic amplitude of low-frequency fluctuation (dALFF) variability in the rostral ventromedial medulla (RVM), superior lobe of left cerebellum (Cerebellum_Crus1_L), right precuneus (PCUN.R), and so on. The decreased dALFF variability of RVM, Cerebellum_Crus1_L, and PCUN.R progressively recovered after the first and 12th acupuncture treatment sessions as compared to the baseline. There was gradually increased dynamic effective connectivity (DEC) variability in RVM outflow to the right middle frontal gyrus, left insula, right precentral gyrus, and right supramarginal gyrus, and gradually enhanced DEC variability from the right fusiform gyrus inflow to RVM. Furthermore, the gradually increased DEC variability was found from Cerebellum_Crus1_L outflow to the left middle occipital gyrus and the left precentral gyrus, from PCUN.R outflow to the right thalamus. These dALFF variabilities were positively correlated with the frequency of migraine attacks and negatively correlated with disease duration at baseline. The dynamic Granger causality analysis (GCA) coefficients of this DEC variability were positively correlated with Migraine-Specific Quality of Life Questionnaire scores and negatively correlated with the frequency of migraine attacks and visual analog scale (VAS) scores after 12th acupuncture sessions. Our results were analyzed by a longitudinal fMRI in the absence of a sham acupuncture control group and provided insight into the dynamic alterations of brain activity and effective connectivity in patients with MwoA after acupuncture intervention. Acupuncture might relieve MwoA by increasing the effective connectivity of RVM, Cerebellum_Crus1_L, and PCUN.R to make up for the decreased dALFF variability in these brain areas.
Aberrant Dynamic Functional Connectivity of Posterior Cingulate Cortex Subregions in Major Depressive Disorder With Suicidal Ideation
Authors: Li Weicheng , Wang Chengyu , Lan Xiaofeng , Fu Ling , Zhang Fan , Ye Yanxiang , Liu Haiyan , Wu Kai , Lao Guohui , Chen Jun , Li Guixiang , Zhou Yanling , Ning Yuping
Published: July 2022

Accumulating evidence indicates the presence of structural and functional abnormalities of the posterior cingulate cortex (PCC) in patients with major depressive disorder (MDD) with suicidal ideation (SI). Nevertheless, the subregional-level dynamic functional connectivity (dFC) of the PCC has not been investigated in MDD with SI. We therefore sought to investigate the presence of aberrant dFC variability in PCC subregions in MDD patients with SI. We analyzed resting-state functional magnetic resonance imaging (fMRI) data from 31 unmedicated MDD patients with SI (SI group), 56 unmedicated MDD patients without SI (NSI group), and 48 matched healthy control (HC) subjects. The sliding-window method was applied to characterize the whole-brain dFC of each PCC subregion [the ventral PCC (vPCC) and dorsal PCC (dPCC)]. In addition, we evaluated associations between clinical variables and the aberrant dFC variability of those brain regions showing significant between-group differences. Compared with HCS, the SI and the NSI groups exhibited higher dFC variability between the left dPCC and left fusiform gyrus and between the right vPCC and left inferior frontal gyrus (IFG). The SI group showed higher dFC variability between the left vPCC and left IFG than the NSI group. Furthermore, the dFC variability between the left vPCC and left IFG was positively correlated with Scale for Suicidal Ideation (SSI) score in patients with MDD (i.e., the SI and NSI groups). Our results indicate that aberrant dFC variability between the vPCC and IFG might provide a neural-network explanation for SI and may provide a potential target for future therapeutic interventions in MDD patients with SI.
Effect of high-protein vs. high-fat snacks before lunch on glycemic variability in prediabetes: A study protocol for a randomized controlled trial
Authors: Liu Yupeng , Jiang Huinan , Ruan Binye , Liu Yi , Le Siyu , Fu Xiaoyi , Wang Shuran
Published: July 2022

Background

China has the largest number of patients with Type 2 Diabetes Mellitus (T2DM), and it tends to increasingly grow in the future, putting an enormous burden on disease control and prevention in China. While glycemic variability (GV) came to be an important indicator of blood glucose control in diabetic patients, studies suggested that premeal snacks may help blood glucose control, but there are still some problems to be researched. Therefore, we designed this trial to evaluate which kind of premeal snacks would lead to better effects on GV under two diet patterns in pre-diabetes subjects and to evaluate assessments of acceptability and compliance, behavior, and metabolism changes in individuals will be described.

Methods and analysis

The study is a single-center, open-label, multiparallel group, randomized controlled trial. A total of 32 male and female volunteers will be randomized into 4 groups in a single allocated ratio of soy milk (powder) snack, milk (powder) snack, almonds snack, and placebo control with 250 ml of water taken 30 min before lunch, respectively. The study consists of two intervention periods over 11 days. The first intervention period under habitual diet conditions from D3 to D6 (4 days), during which all subjects are asked to maintain their habitual eating and daily activities similar to the run-in period. The second intervention consists of prelunch snacks with standard meals. We will examine both the effect of GV and various metabolic and behavioral outcomes potentially associated with the interventions. At the end of this study, we will assess the acceptability and maintainability of the intervention through interviews.

Clinical trial registration

Chinese Clinical Trial Registry, identifier ChiCTR2200058935.
Investigation of Concurrent Pneumococcal Meningitis in Two Children Attending the Same Day-Care Center
Authors: Rybak Alexis , Varon Emmanuelle , Masson Elodie , Etchevers Anne , Levy-Brühl Daniel , Ouldali Naïm , Levy Corinne , Cohen Robert
Published: July 2022

Only a few clusters of invasive pneumococcal disease have been described globally in children, and most of these cases occurred before pneumococcal vaccination implementation. Two unusual cases of pneumococcal meningitis, occurring in the same daycare center over a 3-day period, were reported. Both cerebrospinal fluid (CSF) were sent to the National reference center for pneumococci. In addition, we decided to perform a pneumococcal carriage study on all children and staff of the daycare center to analyze the pneumococcal serotypes circulating in this DCC and to discuss an antibiotic chemoprophylaxis. CSF culture was positive for pneumococcus, and serotype 25A was identified by latex agglutination. The second case had negative CSF culture, but CSF antigen test and gene amplification results were positive for Streptococcus pneumoniae. Serotype 12F was identified by using molecular biology. The absence of correlation between these strains was confirmed by multi-locus sequence typing. In the carriage study, we included 29 children (median age 1.9 years, interquartile range 1.4–2.5) and 10 adults. Among the children, 24 carried Streptococcus pneumoniae (83%). The main serotypes isolated were 23A for 6 children and 25A for 5 children; serotypes were non-typeable for 3 children. Only 1 of 10 adults tested carried Streptococcus pneumoniae (serotype 12F). Despite this temporo-spatial pattern, the cases were unrelated and not due to carriage of a particular serotype. No specific action has been taken for the other children attending this DCC, and no other case of bacterial meningitis occurred.
The Herbal Combination of Radix astragali, Radix angelicae sinensis, and Caulis lonicerae Regulates the Functions of Type 2 Innate Lymphocytes and Macrophages Contributing to the Resolution of Collagen-Induced Arthritis
Authors: Feng Guiyu , Li Dongyang , Liu Juan , Sun Song , Zhang Pingxin , Liu Wei , Zhang Yingkai , Meng Boyang , Li Jinyu , Chai Limin
Published: July 2022

Type 2 innate lymphocytes (ILC2s), promoting inflammation resolution, was a potential target for rheumatoid arthritis (RA) treatment. Our previous studies confirmed thatR.astragaliandR.angelicae sinensiscould intervene in immunologic balance of T lymphocytes.C.loniceraealso have anti-inflammatory therapeutic effects. In this study, the possible molecular mechanisms of the combination of these three herbs for the functions of ILC2s and macrophages contributing to the resolution of collagen-induced arthritis (CIA) were studied. Therefore, we usedR.astragali,R.angelicae sinensis, andC.loniceraeas treatment. The synovial inflammation and articular cartilage destruction were alleviated after herbal treatment. The percentages of ILC2s and Tregs increased significantly. The differentiation of Th17 cells and the secretion of IL-17 and IFN-γ significantly decreased. In addition, treatment by the combination of these three herbs could increase the level of anti-inflammatory cytokine IL-4 secreted, active the STAT6 signaling pathway, and then contribute to the transformation of M1 macrophages to M2 phenotype. The combination of the three herbs could promote inflammation resolution of synovial tissue by regulating ILC2s immune response network. The synergistic effects of three drugs were superior to the combination ofR.astragaliandR.angelicae sinensisorC.loniceraealone.
Identification of Intestinal NaCl Absorptive-Anion Secretory Cells: Potential Functional Significance
Authors: Donowitz Mark , Sarker Rafiquel , Lin Ruxian , McNamara George , Tse Chung Ming , Singh Varsha
Published: July 2022

Use of human enteroids studied in the undifferentiated and differentiated state that mimic the intestinal crypt and villus, respectively, has allowed studies of multiple enterocyte populations, including a large population of enterocytes that are transitioning from the crypt to the villus. This population expresses NHE3, DRA, and CFTR, representing a combination of Na absorptive and anion secretory functions. In this cell population, these three transporters physically interact, which affects their baseline and regulated activities. A study of this cell population and differentiated Caco-2 cells transduced with NHE3 and endogenously expressing DRA and CFTR has allowed an understanding of previous studies in which cAMP seemed to stimulate and inhibit DRA at the same time. Understanding the contributions of these cells to overall intestinal transport function as part of the fasting and post-prandial state and their contribution to the pathophysiology of diarrheal diseases and some conditions with constipation will allow new approaches to drug development.
Differences in post-traumatic growth: Individual quarantine, COVID-19 duration and gender
Authors: Cohen-Louck Keren
Published: July 2022

Objective

This study focuses on positive effects of the COVID-19 pandemic and aims to identify associations between gender, individual quarantine and duration of the COVID-19 (short- medium- and long-term pandemic), and posttraumatic growth (PTG).

Method

The data was collected via an online survey in Israel, and included 1,301 participants, 543 participants experienced short-term pandemics, 428 participants experienced medium-term pandemics and 330 participants experienced long-term pandemics. Most of the participants were female (73.6%), ranging from 18 to 89 years-old. The participants answered questions about their demographic background, individual quarantine experiences and ranked their PTG level.

Results

The results indicate a significant main effect of gender and pandemic duration (short-, medium- and long-term pandemic). Women reported higher PTG levels than men, and participants experiencing short-term pandemic reported significantly lower PTG levels than participants experiencing medium- or long-term pandemic. There was also a significant interaction between gender and pandemic duration regarding PTG and a significant interaction in PTG by gender, pandemic duration and individual quarantine.

Conclusion

The discussion addresses the findings in the context of traditional gender roles and gender differences in finding meaning and worth in home confinement situations.
Towards sustainable development in China: How do green technology innovation and resource misallocation affect carbon emission performance?
Authors: Du Mingyue , Zhou Qingjie , Zhang Yunlai , Li Feifei
Published: July 2022

Green technology innovation is an effective way through which to achieve carbon neutrality and sustainable development. Based on provincial panel data of 30 provinces in China from 2005 to 2018, this work examines the tripartite relationship among green technology innovation, resource misallocation, and carbon emission performance by constructing panel regression models and a dynamic threshold panel model. The research results show that green technology innovation significantly improves carbon emission performance. Further analysis shows that both capital and labour misallocation have a negative impact on carbon emission performance and hinder the contribution of green technology innovation to the improvement of carbon emission performance. The regression results show that there is a threshold effect of green technology innovation on carbon emission performance: as the degree of resource misallocation increases, the positive impact of green technology innovation on carbon emission performance gradually decreases. This study provides an important reference for policy-makers in implementing policies to improve carbon emission performance. Policy-makers should continue to promote the level of green technology innovation and improve the efficiency of labour and capital allocation.
Can sports events improve residents’ psychic income?
Authors: Cai Jie
Published: July 2022

To better understand the positive impact of sports events on host cities, this study uses social capital and social identity theories combined with structural equation modeling (SEM) to explain the psychic income that sports events may bring to residents. The investigation and analysis of the Qingdao Marathon in 2021 show that (1) sports events can generate social capital; (2) social capital can positively influence social identity; and (3) social identity can significantly impact event excitement, city attachment, and city pride in psychic income.
Quality and quantity of serious violent suicide attempts during the COVID-19 pandemic
Authors: Maleitzke Tazio , Zocholl Dario , Topp Tobias , Dimitrov-Discher Annika , Daus Elly , Reaux Gabriel , Zocholl Malin , Conze Rolf Nicolas , Kolster Moritz , Weber Philipp , Fleckenstein Florian Nima , Scheutz Henriksen Louise , Stöckle Ulrich , Fuchs Thomas , Gümbel Denis , Spranger Nikolai , Ringk Alexander , Märdian Sven
Published: July 2022

Background

While repeated shutdown and lockdown measures helped contain the spread of SARS-CoV-2 during the COVID-19 pandemic, social distancing and self-isolation negatively impacted global mental health in 2020 and 2021. Although suicide rates did reportedly not increase during the first months of the pandemic, long-term data, and data on the quality of serious violent suicide attempts (SVSAs) are not available to date.

Materials and methods

Orthopaedic trauma patient visits to the emergency department (ED), ED trauma team activations, and SVSAs were retrospectively evaluated from January 2019 until May 2021 in four Level-I Trauma Centers in Berlin, Germany. SVSAs were assessed for suicide method, injury pattern and severity, type of treatment, and length of hospital stay.

Results

Significantly fewer orthopaedic trauma patients presented to EDs during the pandemic (n = 70,271) compared to the control (n = 84,864) period (p = 0.0017). ED trauma team activation numbers remained unchanged. SVSAs (corrected for seasonality) also remained unchanged during control (n = 138) and pandemic (n = 129) periods, and no differences were observed for suicide methods, injury patterns, or length of hospital stay.

Conclusion

Our data emphasize that a previously reported rise in psychological stress during the COVID-19 pandemic does not coincide with increased SVSA rates or changes in quality of SVSAs.
Zimbabwe's emergency response to COVID-19: Enhancing access and accelerating COVID-19 testing as the first line of defense against the COVID-19 pandemic
Authors: Gudza-Mugabe Muchaneta , Sithole Kenny , Sisya Lucia , Zimuto Sibongile , Charimari Lincoln S. , Chimusoro Anderson , Simbi Raiva , Gasasira Alex
Published: July 2022

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) spreads rapidly, causing outbreaks that grow exponentially within a short period before interventions are sought and effectively implemented. Testing is part of the first line of defense against Corona Virus Disease of 2019 (COVID-19), playing a critical role in the early identification and isolation of cases to slow transmission, provision of targeted care to those affected, and protection of health system operations. Laboratory tests for COVID-19 based on nucleic acid amplification techniques were rapidly developed in the early days of the pandemic, but such tests typically require sophisticated laboratory infrastructure and skilled staff. In March 2020, Zimbabwe confirmed its first case of COVID-19; this was followed by an increase in infection rates as the pandemic spread across the country, thus increasing the demand for testing. One national laboratory was set to test all the country's COVID-19 suspect cases, building pressure on human and financial resources. Staff burnout and longer turnaround times of more than 48 h were experienced, and results were released late for clinical relevance. Leveraging on existing PCR testing platforms, including GeneXpert machines, eased the pressure for a short period before facing the stockout of SARs-CoV-2 cartridges for a long time, leading to work overload at a few testing sites contributing to long turnaround times. On September 11, WHO released the interim guidance to use antigen rapid diagnostic test as a diagnostic tool. The Zimbabwe laboratory pillar quickly adopted it and made plans for its implementation. The National Microbiology Reference Laboratory verified the two emergency-listed kits, the Panbio Abbott and the Standard Q, Biosensor, and they met the WHO minimum performance of ≥97% specificity and ≥80% sensitivity. Decentralizing diagnostic testing leveraging existing human resources became a game-changer in improving COVID-19 containment measures. Task shifting through training on Antigen rapid diagnostic tests (Ag-RDT) commenced, and testing was decentralized to all the ten provinces, from 1 central testing laboratory to more than 1,000 testing centers. WhatsApp platforms made it easier for data to be reported from remote areas. Result turnaround times were improved to the same day, and accessibility to testing was enhanced.
Effectiveness and Cost-Effectiveness of Inactivated Vaccine to Address COVID-19 Pandemic in China: Evidence From Randomized Control Trials and Real-World Studies
Authors: Fu Yaqun , Zhao Jingyu , Wei Xia , Han Peien , Yang Li , Ren Tao , Zhan Siyan , Li Liming
Published: July 2022

Objective

This study aimed to determine the efficacy, effectiveness, and cost-effectiveness of inactivated COVID-19 vaccines (CoronaVac and BBIBP-CorV) in China using existing international clinical trials and real-world evidence.

Methods

Through a search of PubMed, Embase, Web of Science, and CNKI, studies investigating the effectiveness of inactivated COVID-19 vaccines were identified, and a meta-analysis was undertaken to synthesize the vaccine efficacy and effectiveness data. Moreover, a decision-analytic model was developed to estimate the cost-effectiveness of inactivated vaccines for combating the COVID-19 pandemic in the Chinese context from a societal perspective. Results of the meta-analysis, along with cost data from official websites and works of literature were used to populate the model. Sensitivity analysis was performed to test the robustness of the model results.

Results

A total of 24 studies were included in the meta-analysis. In comparison to no immunization, the effectiveness of inactivated vaccine against COVID-19 infection, hospitalization, ICU admission and death were 65.18% (95% CI 62.62, 67.75), 79.10% (95% CI 71.69, 86.51), 90.46% (95% CI 89.42, 91.50), and 86.69% (95% CI 85.68, 87.70); and the efficacy against COVID-19 infection and hospitalization were 70.56% (95% CI 57.87, 83.24) and 100% (95% CI 61.72, 100). Inactivated vaccine vaccination prevented more infections, hospitalizations, ICU admissions, and deaths with lower total costs, thus was cost-saving from a societal perspective in China. Base-case analysis results were robust in the one-way sensitivity analysis, and the percentage of ICU admission or death and direct medical cost ranked the top influential factors in our models. In the probabilistic sensitivity analysis, vaccination had a 100% probability of being cost-effective.

Conclusion

Inactivated vaccine is effective in preventing COVID-19 infection, hospitalization, ICU admission and avoiding COVID-19 related death, and COVID-19 vaccination program is cost-saving from societal perspective in China.
Willingness to pay for social health insurance among public civil servants: A cross-sectional study in Dessie City Administration, North-East Ethiopia
Authors: Amilaku Eshetie Meseret , Fentaye Fasil Walelign , Mekonen Asnakew Molla , Bayked Ewunetie Mekashaw
Published: July 2022

Background

The readiness to pay for health insurance has an impact on universal health care. This study investigated the willingness of public civil servants in Dessie City Administration, North-East Ethiopia, to pay for social health insurance and associated factors.

Methods

From April to May 2021, a cross-sectional study was undertaken. The sectors from which the samples were proportionately allocated were chosen using a multistage sampling procedure. Using their payroll list as a sampling frame, simple random sampling was done to recruit them. A semi-structured self-administered questionnaire was used to collect data. Epi Data version 3.1 was used to enter, code, and clean the data, which was then exported to SPSS version 23 for analysis. To determine relationships, bi-variable and multivariable analyses were utilized. Candidates for multivariable analysis were variables with a p-value ≤ 0.3 in bi-variable analysis. AOR with a 95% CI was used to determine the strength and direction of association. Statistical significance was defined at p-value < 0.05.

Results

A total of 796 employees took part in the study, with a 94.42% response rate. Overall, 29.60% of them were willing to pay for the scheme (95% CI: 26.4, 33%). The decision to pay was influenced by favorable perception (AOR = 2.43, 95% CI: 1.72, 3.44), household income < Birr 5,000 (AOR = 0.26, 95% CI: 0.14, 0.48), acute illness (AOR = 0.48, 95% CI: 0.32, 0.72), bachelor level education (AOR = 0.44, 95% CI: 0.28, 0.70), master and above level education (AOR = 0.26, 95% CI: 0.14, 0.49), and age 25–29 years (AOR = 1.97, 95 % CI: 1.08, 3.57).

Conclusion

The willingness of the civil servants to pay for social health insurance was low, and it was influenced by their attitudes toward the scheme, the occurrence of severe illness, income level, educational status, and age.
COVID-19 Prediction With Machine Learning Technique From Extracted Features of Photoplethysmogram Morphology
Authors: Nayan Nazrul Anuar , Jie Yi Choon , Suboh Mohd Zubir , Mazlan Nur-Fadhilah , Periyasamy Petrick , Abdul Rahim Muhammad Yusuf Zawir , Shah Shamsul Azhar
Published: July 2022

At present, COVID-19 is spreading widely around the world. It causes many health problems, namely, respiratory failure and acute respiratory distress syndrome. Wearable devices have gained popularity by allowing remote COVID-19 detection, contact tracing, and monitoring. In this study, the correlation of photoplethysmogram (PPG) morphology between patients with COVID-19 infection and healthy subjects was investigated. Then, machine learning was used to classify the extracted features between 43 cases and 43 control subjects. The PPG data were collected from 86 subjects based on inclusion and exclusion criteria. The systolic-onset amplitude was 3.72% higher for the case group. However, the time interval of systolic-systolic was 7.69% shorter in the case than in control subjects. In addition, 12 out of 20 features exhibited a significant difference. The top three features included dicrotic-systolic time interval, onset-dicrotic amplitude, and systolic-onset time interval. Nine features extracted by heatmap based on the correlation matrix were fed to discriminant analysis, k-nearest neighbor, decision tree, support vector machine, and artificial neural network (ANN). The ANN showed the best performance with 95.45% accuracy, 100% sensitivity, and 90.91% specificity by using six input features. In this study, a COVID-19 prediction model was developed using multiple PPG features extracted using a low-cost pulse oximeter.
Research hotspots and emerging trends of deep learning applications in orthopedics: A bibliometric and visualized study
Authors: Feng Chengyao , Zhou Xiaowen , Wang Hua , He Yu , Li Zhihong , Tu Chao
Published: July 2022

Background

As a research hotspot, deep learning has been continuously combined with various research fields in medicine. Recently, there is a growing amount of deep learning-based researches in orthopedics. This bibliometric analysis aimed to identify the hotspots of deep learning applications in orthopedics in recent years and infer future research trends.

Methods

We screened global publication on deep learning applications in orthopedics by accessing the Web of Science Core Collection. The articles and reviews were collected without language and time restrictions. Citespace was applied to conduct the bibliometric analysis of the publications.

Results

A total of 822 articles and reviews were finally retrieved. The analysis showed that the application of deep learning in orthopedics has great prospects for development based on the annual publications. The most prolific country is the USA, followed by China. University of California San Francisco, and Skeletal Radiology are the most prolific institution and journal, respectively. LeCun Y is the most frequently cited author, and Nature has the highest impact factor in the cited journals. The current hot keywords are convolutional neural network, classification, segmentation, diagnosis, image, fracture, and osteoarthritis. The burst keywords are risk factor, identification, localization, and surgery. The timeline viewer showed two recent research directions for bone tumors and osteoporosis.

Conclusion

Publications on deep learning applications in orthopedics have increased in recent years, with the USA being the most prolific. The current research mainly focused on classifying, diagnosing and risk predicting in osteoarthritis and fractures from medical images. Future research directions may put emphasis on reducing intraoperative risk, predicting the occurrence of postoperative complications, screening for osteoporosis, and identification and classification of bone tumors from conventional imaging.
On Distributed Cognition While Designing an AI System for Adapted Learning
Authors: Aarset Magne V. , Johannessen Leiv Kåre
Published: July 2022

When analyzing learning, focus has traditionally been on the teacher, but has in the recent decades slightly moved toward the learner. This is also reflected when supporting systems, both computer-based and more practical equipment, has been introduced. Seeing learning as an integration of both an internal psychological process of acquisition and elaboration, and an external interaction process between the learner and the rest of the learning environment though, we see the necessity of expanding the vision and taking on a more holistic view to include the whole learning environment. Specially, when introducing an AI (artificial intelligence) system for adapting the learning process to an individual learner through machine learning, this AI system should take into account both the learner and the other agents and artifacts being part of this extended learning system. This paper outlines some lessons learned in a process of developing an electronic textbook adapting to a single learner through machine learning, to the process of extracting input from and providing feedback both to the learner, the teacher, the learning institution, and the learning resources provider based on a XAI (explainable artificial intelligence) system while also taking into account characteristics with respect to the learner's peers.
An innovative active learning module on snow and climate modeling
Authors: Roundy Joshua K. , Gallagher Melissa A. , Byrd Jenny L.
Published: July 2022

The interaction between climate and the hydrologic cycle is complex due to intricate feedback mechanisms that can have multiple impacts on key hydrologic variables. Under a changing climate, it is becoming increasingly important for undergraduate engineering students to have a better understanding of climate and the hydrologic cycle to ensure future engineering systems are more climate resilient. One way of teaching undergraduate students about these key interactions between climate and the hydrologic cycle is through numerical models that mimic these relationships. However, this is difficult to do in an undergraduate engineering course because these models are complex, and it is not feasible to devote class time and resources to teaching students the knowledge base required to run and analyze these numerical models. In addition, the recent COVID-19 pandemic required a rapid change to flexible teaching methods that can be implemented in online, hybrid, or in-person courses. To overcome these limitations, a backward design and constructive alignment approach was used to develop an active learning module in the HydroLearn framework that allows students to explore the connection between snow processes and streamflow and how this will change under different climate scenarios using numerical models and analysis. This learning module provides learning activities and tools that help the student develop a basic knowledge of snow formation and terminology, snow measurements, numerical models of snow processes, and changes in snow and streamflow under future climate. This module is particularly innovative in that it uses Google Colabs and an interactive user interface to facilitate the students' active learning in an environment that is accessible for all students and is sustainable for continued use and adaptation. This paper describes the approach, best practices and lessons learned in developing and implementing this active learning module in a remote and in-person course. In addition, it presents the results from motivation and student self-assessment surveys and discusses opportunities for improvement and further implementation that have implications for the future of hydrologic education.