bluuebunny/crossref_metadata_2025 huggingface dataset:
Demographic and clinical characteristics associated with variations in antibody response to BNT162b2 COVID-19 vaccination among healthcare workers at an academic medical centre: a longitudinal cohort analysis
Authors: Ebinger Joseph E , Joung Sandy , Liu Yunxian , Wu Min , Weber Brittany , Claggett Brian , Botting Patrick G , Sun Nancy , Driver Matthew , Kao Yu Hung , Khuu Briana , Wynter Timothy , Nguyen Trevor-Trung , Alotaibi Mona , Prostko John C , Frias Edwin C , Stewart James L , Goodridge Helen S , Chen Peter , Jordan Stanley C , Jain Mohit , Sharma Sonia , Fert-Bober Justyna , Van Eyk Jennifer E , Minissian Margo B , Arditi Moshe , Melmed Gil Y , Braun Jonathan G , McGovern Dermot P B , Cheng Susan , Sobhani Kimia
Published: May 2022

Objectives

We sought to understand the demographic and clinical factors associated with variations in longitudinal antibody response following completion of two-dose regiment of BNT162b2 vaccination.

Design

This study is a 10-month longitudinal cohort study of healthcare workers and serially measured anti-spike protein IgG (IgG-S) antibody levels using mixed linear models to examine their associations with participant characteristics.

Setting

A large, multisite academic medical centre in Southern California, USA.

Participants

A total of 843 healthcare workers met inclusion criteria including completion of an initial two-dose course of BNT162b2 vaccination, complete clinical history and at least two blood samples for analysis. Patients had an average age of 45±13 years, were 70% female and 7% with prior SARS-CoV-2 infection.

Results

Vaccine-induced IgG-S levels remained in the positive range for 99.6% of individuals up to 10 months after initial two-dose vaccination. Prior SARS-CoV-2 infection was the primary correlate of sustained higher postvaccination IgG-S levels (partial R2=0.133), with a 1.74±0.11 SD higher IgG-S response (p<0.001). Female sex (beta 0.27±0.06, p<0.001), younger age (0.01±0.00, p<0.001) and absence of hypertension (0.17±0.08, p=0.003) were also associated with persistently higher IgG-S responses. Notably, prior SARS-CoV-2 infection augmented the associations of sex (−0.42 for male sex, p=0.08) and modified the associations of hypertension (1.17, p=0.001), such that infection-naïve individuals with hypertension had persistently lower IgG-S levels whereas prior infected individuals with hypertension exhibited higher IgG-S levels that remained augmented over time.

Conclusions

While the IgG-S antibody response remains in the positive range for up to 10 months following initial mRNA vaccination in most adults, determinants of sustained higher antibody levels include prior SARS-CoV-2 infection, female sex, younger age and absence of hypertension. Certain determinants of the longitudinal antibody response appear significantly modified by prior infection status. These findings offer insights regarding factors that may influence the ‘hybrid’ immunity conferred by natural infection combined with vaccination.
Venerable vulnerability or remarkable resilience? A prospective study of the impact of the first wave of the COVID-19 pandemic and quarantine measures on loneliness in Swedish older adults with home care
Authors: Gustafsson Per E , Nilsson Ingeborg , San Sebastian Miguel
Published: May 2022

Objectives

To examine the early impact of the pandemic and of quarantine measures targeting older adults introduced in March 2020 on loneliness among older adults in Sweden.

Design Prospective pretest–posttest and controlled interrupted time series designs.

Setting

The population of older adults receiving home care before and during the emergence of the first COVID-19 pandemic wave in Sweden in Spring 2020.

Participants

Respondents (n=45 123, mean age 85.6 years, 67.6% women) came from two waves of a total population survey targeting all community-dwelling older adults receiving home care for older adults in Sweden in Spring 2019 and 2020.

Outcome

Self-reported loneliness.

Results

Results estimated 14% (95% CI: 10 to 19) higher loneliness in Spring 2020 compared with 2019, taking covariates into account. No impact of the quarantine measure was found (1% increase, 95% CI: −1 to 4).

Conclusions

The results illustrate the broader public health consequences of the COVID-19 pandemic for older adults, but also suggest a relative resilience among older adults in home care to quarantine measures, at least during the first months of the pandemic. Future studies should examine the long-term effects of sustained pandemic and social distancing measures on loneliness among older adults.
Assessing a norming intervention to promote acceptance of HIV testing and reduce stigma during household tuberculosis contact investigation: protocol for a cluster-randomised trial
Authors: Armstrong-Hough Mari , Ggita Joseph , Gupta Amanda J , Shelby Tyler , Nangendo Joanita , Ayen Daniel Okello , Davis J L , Katamba Achilles
Published: May 2022

Introduction

HIV status awareness is important for household contacts of patients with tuberculosis (TB). Home HIV testing during TB contact investigation increases HIV status awareness. Social interactions during home visits may influence perceived stigma and uptake of HIV testing. We designed an intervention to normalise and facilitate uptake of home HIV testing with five components: guided selection of first tester; prosocial invitation scripts; opt-out framing; optional sharing of decisions to test; and masking of decisions not to test.

Methods and analysis

We will evaluate the intervention effect in a household-randomised controlled trial. The primary aim is to assess whether contacts offered HIV testing using the norming strategy will accept HIV testing more often than those offered testing using standard strategies. Approximately 198 households will be enrolled through three public health facilities in Kampala, Uganda. Households will be randomised to receive the norming or standard strategy and visited by a community health worker (CHW) assigned to that strategy. Eligible contacts ≥15 years will be offered optional, free, home HIV testing. The primary outcome, proportion of contacts accepting HIV testing, will be assessed by CHWs and analysed using an intention-to-treat approach. Secondary outcomes will be changes in perceived HIV stigma, changes in perceived TB stigma, effects of perceived HIV stigma on HIV test uptake, effects of perceived TB stigma on HIV test uptake and proportions of first-invited contacts who accept HIV testing. Results will inform new, scalable strategies for delivering HIV testing.

Ethics and dissemination

This study was approved by the Yale Human Investigation Committee (2000024852), Makerere University School of Public Health Institutional Review Board (661) and Uganda National Council on Science and Technology (HS2567). All participants, including patients and their household contacts, will provide verbal informed consent. Results will be submitted to a peer-reviewed journal and disseminated to national stakeholders, including policy-makers and representatives of affected communities.

Trial registration number

ClinicalTrials.gov Identifier: NCT05124665.
Intravenous lipo-prostaglandin E1 administration for patients with acute central retinal artery occlusion
Authors: Suzuki Takafumi , Obata Ryo , Inoue Tatsuya , Ueta Yoshiki , Azuma Keiko , Tate Hideo , Kitamoto Kohdai , Otaki Chisato , Hashimoto Yoshihiro , Aihara Makoto , Tachi Naoko
Published: May 2022

Objective

This study aimed to investigate the anatomical and functional changes in patients with central retinal artery occlusion (CRAO) (n=21) treated with 10 µg/day intravenous liposomal prostaglandin E1 (lipo-PGE1).

Methods and analysis

We used best-corrected visual acuity (BCVA), central retinal thickness with spectral domain optical coherence photography, optical intensity ratio (OIR) with imageJ software and retinal vessel diameter with fundus photography as indicators. Data were analysed using Tukey’s multiple comparisons, Wilcoxon test or Spearman’s correlation analysis as appropriate.

Results

BCVA was significantly improved at 1 month and 3 months after the initial visit (from 2.18±0.60 to 1.54±0.84 and 1.53±0.88, p=0.030 and p=0.027, respectively). The ratio of retinal vein diameter to optic disc diameter increased in the first month (from 0.40%±0.13% to 0.52%±0.16%, p=0.005). In addition, the OIR at the initial visit was significantly correlated with BCVA at 3 months (p=0.006, r=0.58). No severe adverse effects were observed.

Conclusion

The results showed that visual acuity and retinal vein constriction improved after lipo-PGE1 therapy. In addition, the OIR in the initial phase can be an indicator of visual prognosis after treatment with PGE1 in patients with CRAO.
Redesigning care to support earlier discharge from a neonatal intensive care unit: a design thinking informed pilot
Authors: Bardach Shoshana H , Perry Amanda N , Kapadia Nirav S , Richards Kathryn E , Cogswell Laura K , Hartman Tyler K
Published: May 2022

Background

Preterm infants may remain in neonatal intensive care units (NICUs) to receive proper nutrition via nasogastric tube feedings. However, prolonged NICU stays can have negative effects for the patient, the family and the health system.

Aim

To demonstrate how a patient-centred, design thinking informed approach supported the development of a pilot programme to enable earlier discharge of preterm babies.

Method

We report on our design thinking-empathy building approach to programme design, initial outcomes and considerations for ongoing study.

Results

Through the use of design thinking methods, we identified unique needs, preferences and concerns that guided the development of our novel early discharge programme. We found that stable, preterm infants unable to feed by mouth and requiring nasogastric tubes can be cared for at home with remote patient monitoring and telehealth support. In addition, novel feeding strategies can help address parental preferences without compromising infant growth.

Conclusion

A patient-centred, design thinking informed approach supported the development of a pilot programme to enable earlier discharge of preterm babies. The programme resulted in a reduced length of stay, thereby increasing NICU bed capacity and limiting hospital turn-aways.
Widening of inequalities in COVID-19 years of life lost from 2020 to 2021: a Scottish Burden of Disease Study
Authors: Wyper Grant M A , Fletcher Eilidh , Grant Ian , Harding Oliver , de Haro Moro Maria Teresa , McCartney Gerry , Stockton Diane L
Published: May 2022

Background

Previous studies have highlighted the large extent of inequality in adverse COVID-19 health outcomes. Our aim was to monitor changes in overall, and inequalities in, COVID-19 years of life lost to premature mortality (YLL) in Scotland from 2020 and 2021.

Methods

Cause-specific COVID-19 mortality counts were derived at age group and area deprivation level using Scottish death registrations for 2020 and 2021. YLL was estimated by multiplying mortality counts by age-conditional life expectancy from the Global Burden of Disease 2019 reference life table. Various measures of absolute and relative inequality were estimated for triangulation purposes.

Results

There were marked inequalities in COVID-19 YLL by area deprivation in 2020, which were further exacerbated in 2021; confirmed across all measures of absolute and relative inequality. Half (51%) of COVID-19 YLL was attributable to inequalities in area deprivation in 2021, an increase from 41% in 2020.

Conclusion

Despite a highly impactful vaccination programme in preventing mortality, COVID-19 continues to represent a substantial area of fatal population health loss for which inequalities have widened. Tackling systemic inequalities with effective interventions is required to mitigate further unjust health loss in the Scottish population from COVID-19 and other causes of ill-health and mortality.
Ccl3 enhances docetaxel chemosensitivity in breast cancer by triggering proinflammatory macrophage polarization
Authors: Sheng Dandan , Ma Wei , Zhang Rui , Zhou Lei , Deng Qiaodan , Tu Juchuanli , Chen Weilong , Zhang Fuchuang , Gao Nailong , Dong Mengxue , Wang Dong , Li Fengkai , Liu Yin , He Xueyan , Duan Shengzhong , Zhang Lixing , Liu Tong , Liu Suling
Published: May 2022

Background

Although the antitumor efficacy of docetaxel (DTX) has long been attributed to the antimitotic activities, its impact on the tumor microenvironment (TME) has recently gained more attention. Macrophages are a major component of the TME and play a critical role in DTX efficacy; however, the underlying action mechanisms remain unclear.

Methods

DTX chemotherapeutic efficacy was demonstrated via both macrophage depletion and C–C motif chemokine ligand 3 (Ccl3)-knockout transgenic allograft mouse model. Ccl3-knockdown and Ccl3-overexpressing breast cancer cell allografts were used for the in vivo study. Combination therapy was used to evaluate the effect of Ccl3 induction on DTX chemosensitivity. Vital regulatory molecules and pathways were identified using RNA sequencing. Macrophage phagocytosis of cancer cells and its influence on cancer cell proliferation under DTX treatment were assessed using an in vitro coculture assay. Serum and tumor samples from patients with breast cancer were used to demonstrate the clinical relevance of our study.

Results

Our study revealed that Ccl3 induced by DTX in macrophages and cancer cells was indispensable for the chemotherapeutic efficacy of DTX. DTX-induced Ccl3 promoted proinflammatory macrophage polarization and subsequently facilitated phagocytosis of breast cancer cells and cancer stem cells. Ccl3 overexpression in cancer cells promoted proinflammatory macrophage polarization to suppress tumor progression and increase DTX chemosensitivity. Mechanistically, DTX induced Ccl3 by relieving the inhibition of cAMP-response element binding protein on Ccl3 via reactive oxygen species accumulation, and Ccl3 then promoted proinflammatory macrophage polarization via activation of the Ccl3–C-C motif chemokine receptor 5–p38/interferon regulatory factor 5 pathway. High CCL3 expression predicted better prognosis, and high CCL3 induction revealed better DTX chemosensitivity in patients with breast cancer. Furthermore, both the Creb inhibitor and recombinant mouse Ccl3 significantly enhanced DTX chemosensitivity.

Conclusions

Our results indicate that Ccl3 induced by DTX triggers proinflammatory macrophage polarization and subsequently facilitates phagocytosis of cancer cells. Ccl3 induction in combination with DTX may provide a promising therapeutic rationale for increasing DTX chemosensitivity in breast cancer.
Thromboembolic events in left ventricular non-compaction: comparison between children and adults – a systematic review and meta-analysis
Authors: Hirono Keiichi , Takarada Shinya , Miyao Nariaki , Nakaoka Hideyuki , Ibuki Keijiro , Ozawa Sayaka , Origasa Hideki , Ichida Fukiko
Published: May 2022

Objective

Left ventricular non-compaction (LVNC) is morphologically characterised by excessive trabeculations and deep recesses in the ventricular wall. The risk of thromboembolic disease in the paediatric patients with LVNC has not been clearly established. We conducted this systematic review to evaluate the prevalence and incidence of thromboembolism (TE) in paediatric and adult patients with LVNC and searched for risk factors for TE to explore management strategies.

Methods

The primary outcome was the prevalence and incidence of TE in the patients with LVNC. The secondary outcome was the TE and mortality and heart transplantation rates between paediatric and adult patients with LVNC. We searched for studies published in MEDLINE, Embase and Cochrane Central Register of Controlled Trials between January 1950 and December 2020. A systematic search of keywords related to LVNC, anticoagulants/antiplatelets and TE was conducted. Studies that did not present original research, non-human studies, duplicated studies were excluded.

Results

Fifty-seven studies met the inclusion criteria. A total of 726 paediatric and 3862 adult patients were included. The mean prevalence rates of TE in the paediatric and adult patients with LVNC were 2.6% and 6.2% (I2=0%; p<0.450 and I2=73.7%; p<0.001), respectively. The mean annual incidences of TE in paediatric and adult patients with LVNC were 1.4% and 2.9% (I2=99.4%; p<0.001 and I2=99.5%; p<0.001), respectively. Multivariate logistic regression analysis showed that TE was associated with left ventricular ejection fraction in <40% of paediatric patients (OR, 9.47; 95% CI, 1.35 to 188.23; p=0.0225).

Conclusions

The prevalence and incidence rates in paediatric patients were lower than those in adult patients. TE was associated with a reduced systolic function in paediatric patients with LVNC.
Canonical description of exotic general massive gravity
Authors: Rodríguez-Tzompantzi Omar
Published: May 2022

Exotic General Massive Gravity is the next-to-simplest gravitational theory fulfilling the so-called third-way consistency, the simplest being Minimal Massive Gravity. We investigate the canonical structure of the first-order formulation of Exotic General Massive Gravity. By using the Dirac Hamiltonian formalism, we systematically discover the complete set of physical constraints, including primary, secondary, and tertiary ones, and explicitly compute the Poisson bracket algebra between them. In particular, we demonstrate that the consistency condition for the tertiary constraints provides explicit expressions which can be solved algebraically for the auxiliary fields f and h in terms of the dreibein e. In this configuration, to confirm that the theory is ghost-free, the whole set of constraints is classified into first and second-class ones showing the existence of only two physical degrees of freedom corresponding to one massive graviton. Furthermore, we identify the transformation laws for all of the dynamical variables corresponding essentially to gauge symmetries, generated by the first-class constraints. Finally, by taking into account all the second-class constraints, we explicitly compute the Dirac matrix together with the Dirac’s brackets.
MONG: An extension to galaxy clusters
Authors: Rebecca Louise , Kenath Arun , Sivaram C.
Published: May 2022

The presence of dark matter (DM), though well established by indirect evidence, is yet to be observed directly. Various DM detection experiments running for several years have yielded no positive results. In view of these negative results, we had earlier proposed alternate models by postulating a minimum gravitational field strength (minimum curvature) and a minimum acceleration. These postulates led to the modified Newtonian dynamics and modified Newtonian gravity (MONG). The observed flat rotation curves of galaxies were also accounted for through these postulates. Here, we extend these postulates to galaxy clusters and model the dynamical velocity-distance curve for a typical cluster such as the Virgo cluster. The radial velocities of galaxies in the Virgo cluster are also obtained through this model. Observations show an inconsistency in the Hubble flow at a mean cluster distance of 17 Mpc, which is expected in regions of high matter density. This decrease in velocity is predicted by our model of modified gravity (MONG). The radial velocity versus distance relation for galaxies in the Virgo cluster obtained using MONG is in agreement with observations.
Differential elastic nucleus–nucleus scattering in complete Glauber theory
Authors: Shabelski Yu. M. , Shuvaev A. G.
Published: May 2022

The differential elastic cross-sections of [Formula: see text]C–[Formula: see text]C and [Formula: see text]Li–[Formula: see text]C nuclei are calculated in the complete Glauber theory. The role of the possible correlations connected to the shell effects in [Formula: see text]Li nucleus is considered.
Effects of diatomaceous earth mixing amount on the performance of curing materials for waste leachate treatment
Authors: Gao Rongze , Gao Wenyuan , Niu Meihong
Published: May 2022

With cement as a cementitious material, fly ash, diatomaceous earth, sugar filter mud, and river sand as materials, and waste leachate instead of water, orthogonal experiments were designed to derive the preliminary formulation of curing materials and to explore the effect of different diatomaceous earth mixing amount on the performance of curing material test blocks. The experimental results showed that as the amount of diatomaceous earth increased from 12.5% to 13.58%, the 28d compressive strength of the cured material test block decreased from 9.85 MPa to 7.35 MPa, the dry density decreased from 1012 kg/m3 to 912 kg/m3, the porosity of the test block increased from 18.94% to 23.34% and the water absorption increased from 43.91% to 66.36%. Comparison of the best formulation of curing materials selected for cement, fly ash, diatomaceous earth and sugar filter mud mass ratio of 31.09 wt.%, 51.82 wt.%, 12.94 wt.%, 4.15 wt.%, external mixing river sand 15 wt.%, with a water–solid ratio of 0.8 was added to the waste leachate to prepare the curing material test blocks.
Topic Sentiment Analysis for Twitter Data in Indian Languages Using Composite Kernel SVM and Deep Learning
Authors: Maity Shuverthi , Sarkar Kamal
Published: May 2022

Sentiment analysis of public opinions on social networks, such as Twitter or Facebook, can provide us with valuable information, which has a wide range of applications. But the efficiency and accuracy of the automated methods for Twitter sentiment analysis are hindered by the special characteristics of the Twitter data. The Twitter data is generally noisy, high-dimensional, and it has complex syntactic and semantic structures. Sentiment analysis of Twitter data in Indian languages is more challenging because the data is multilingual and code-mixed. In this article, we propose various composite kernel functions, each of which is used with Support Vector Machines (SVM) for developing a model for topic sentiment analysis of Twitter data in Indian languages. Each composite kernel function is constructed by taking the weighted summation of multiple single kernel functions defined by us. In addition to our proposed composite kernel SVM method, we use several state-of-the-art deep learning classifiers for topic sentiment classification. Since any suitable Twitter dataset in Indian languages is not available for conducting our experiments, we have developed our own datasets by collecting tweets related to five different Twitter trending topics in India. To prove the robustness and generalization capability of the proposed models, they are also evaluated on the US airline Twitter dataset which is a publicly available benchmark English dataset. The empirical study exhibits that the proposed composite kernel SVM method is effective for the sentiment classification task. In the case of Indian language datasets, the proposed composite kernel SVM method achieves the highest average accuracy of 74% and the highest average F-score of 0.73. On the other hand, the deep learning-based method achieves the average accuracy and the average F-score of 71.31% and 0.70, respectively. In the case of the US airline Twitter dataset, the proposed composite kernel SVM method achieves the average accuracy of 83% and the average F-score of 0.82, which are higher than that of the deep learning-based method.
Crowning Touches in Positive-Strand RNA Virus Genome Replication Complex Structure and Function
Authors: Nishikiori Masaki , den Boon Johan A. , Unchwaniwala Nuruddin , Ahlquist Paul
Published: May 2022

Positive-strand RNA viruses, the largest genetic class of eukaryotic viruses, include coronaviruses and many other established and emerging pathogens. A major target for understanding and controlling these viruses is their genome replication, which occurs in virus-induced membrane vesicles that organize replication steps and protect double-stranded RNA intermediates from innate immune recognition. The structure of these complexes has been greatly illuminated by recent cryo-electron microscope tomography studies with several viruses. One key finding in diverse systems is the organization of crucial viral RNA replication factors in multimeric rings or crowns that among other functions serve as exit channels gating release of progeny genomes to the cytosol for translation and encapsidation. Emerging results suggest that these crowns serve additional important purposes in replication complex assembly, function, and interaction with downstream processes such as encapsidation. The findings provide insights into viral function and evolution and new bases for understanding, controlling, and engineering positive-strand RNA viruses.
Photoluminescence Properties and Energy Transfers in the Novel LiYMgWO6: Dy3+, Tm3+
Authors: Wu Lina , Wu Yelong , Fan Yufan , Sun Bei , Li Qiangxian , Yu Jinying
Published: May 2022

A series of Dy3+/Tm3+ single doped and co-doped double perovskite-structure compound LiYMgWO6 (LYMW) are prepared by a solid-state route. The structure and photoluminescence properties have been unraveled by combining experiments and first-principles calculations. The crystal structure was determined to be a monoclinic structure with space groups P21. Under the ultraviolet (UV) excitation, Dy3+ and Tm3+ single doped LYMW samples emit yellowish-white and blue light, respectively. For Dy3+ and Tm3+ co-doped LYMW, the emission can be tuned from blue to white light and eventually to yellow through energy transfers by varying the Dy3+ and Tm3+ concentrations. The sample with 3%Dy3+ and 3%Tm3+ has chromaticity coordinates (0.3405, 0.3378), which are nearest to the ideal white light (0.33,0.33). The energy transfer mechanism is verified to be the quadrupole-quadrupole interaction. The temperature-dependent photoluminescence (PL) spectra show that LYMW: Dy3+, Tm3+ exhibits good thermal stability.
Proteoglycans and glycosaminoglycans in central nervous system injury
Authors: Siddiqui Noah , Oshima Kaori , Hippensteel Joseph A.
Published: May 2022

The brain and spinal cord constitute the central nervous system (CNS), which when injured, can be exceedingly devastating. The mechanistic roles of proteoglycans (PGs) and their glycosaminoglycan (GAG) side chains in such injuries have been extensively studied. CNS injury immediately alters endothelial and extracellular matrix (ECM) PGs and GAGs. Subsequently, these alterations contribute to acute injury, postinjury fibrosis, and postinjury repair. These effects are central to the pathophysiology of CNS injury. This review focuses on the importance of PGs and GAGs in multiple forms of injury including traumatic brain injury, spinal cord injury, and stroke. We highlight the causes and consequences of degradation of the PG and GAG-enriched endothelial glycocalyx in early injury and discuss the pleiotropic roles of PGs in neuroinflammation. We subsequently evaluate the dualistic effects of PGs on recovery: both PG/GAG-mediated inhibition and facilitation of repair. We then report promising therapeutic strategies that may prove effective for repair of CNS injury including PG receptor inhibition, delivery of endogenous, pro-repair PGs and GAGs, and direct degradation of pathological GAGs. Finally, we discuss the importance of two PG- and GAG-containing ECM structures (synapses and perineuronal nets) in CNS injury and recovery.
An Overview of Energy Resource and Future Concerns for Ghana’s Electricity Generation Mix
Authors: Nyasapoh Mark Amoah , Debrah Seth Kofi , Twerefou Daniel Kwabena , Gyamfi Samuel , Kholi Foster Kwame
Published: May 2022

Energy supply is a critical indicator for the global United Nations initiatives because of its immense contribution to economic development. In essence, identifying the required energy resource coupled with effective policy strategies is essential to sustainable electricity generation. Nevertheless, future electricity supply requires a range of options that must be robust and workable. Globally, the challenge of harnessing the energy resources sustainably needed for effective electricity generation is alarming. Therefore, the ability to supply a country’s electricity based on the availability and affordability of resources is vital for effective governance. In this study, Ghana’s energy resourcefulness and the profound effects on the future mix of electricity generation are qualitatively reviewed. In particular, the study covers the existing and potential energy resources available for sustainable electricity generation. The study revealed that Ghana mainly uses hydro, natural gas, and solar energy, among others, for electricity generation. Additionally, a framework explores a well-diversified generation mix using nuclear, coal, and more renewable energy sources in the long-term. Key issues that emerged for national consideration include the need for effective policy direction and implementation, appropriate financing concepts, fuel availability, political will, and setting. By far, this review sought to emphasize literature gaps by providing a rich and fertile ground as a template for industry operators, policymakers, and future research direction.
Empowering Reconfigurable Intelligent Surfaces for Security of Downlink NOMA
Authors: Nguyen Nhan Duc , Van Nguyen Minh-Sang , Munochiveyi Munyaradzi
Published: May 2022

Reconfigurable intelligent surfaces (RIS) and non-orthogonal multiple access (NOMA) are promising techniques to develop next-generation wireless systems. While RIS has huge potential to create massive device connectivity, NOMA exhibits its spectrum efficient communication among multiple access approaches. RIS is a passive device made up of low-cost meta-surfaces which can control the propagation of radio waves, and it is easily deployable in lots of applications in the Internet of Things. The full-duplex nature of RIS has also been a major reason for its consideration of major emerging and trending technologies. In this paper, we aim to investigate the secrecy performance of the RIS-NOMA-assisted Internet of Things (IoT) systems in the presence of two legitimate users who belong to a cluster, and those devices are associated with the existence of an eavesdropper situated close to such a cluster. This paper considers the devices in the presence of RIS and an eavesdropper. As main performance metrics, the closed-form expressions for secrecy outage probability (SOP) and strictly positive secrecy capacity (SPSC) are derived to evaluate the performance of legitimate users. Simulations are performed in support of the Monte-Carlo method, and the obtained results show that in most of the cases, the number of meta-surfaces in RIS and signal-to-noise ratio (SNR) levels at the source also plays a pivotal role in influencing the secure performance of the system.
Traditional Ceramic Sculpture Feature Recognition Based on the Machine Learning Algorithm
Authors: Zhu XiaoLei
Published: May 2022

Aiming at the problems of low recognition accuracy, high line noise, and high time cost of feature recognition in traditional ceramic sculpture modeling feature recognition methods, this paper designed a traditional ceramic sculpture modeling feature recognition method based on the machine learning algorithm. By constructing the sparse representation model of a traditional ceramic sculpture image, the posterior probability of a traditional ceramic sculpture image was determined and Gaussian distribution of pixels in the image was carried out to determine the distribution law of pixels in the image and the super-resolution reconstruction of the traditional ceramic sculpture image was realized. The feature of the line state of a traditional ceramic sculpture image was determined and classified by the kernel classification method. Finally, the machine learning algorithm red BP neural network is introduced to construct the traditional ceramic sculpture modeling feature recognition algorithm and the error threshold is constantly iterated to realize the traditional ceramic sculpture modeling feature recognition. The experimental results show that the recognition algorithm designed in this paper has high accuracy in identifying the traditional ceramic sculpture features, can effectively suppress the line noise, and has a short recognition time overhead, which has a certain feasibility.
A Bayesian Prediction Spatial Model for Confirmed Dengue Cases in the State of Chiapas, Mexico
Authors: Solís-Navarro Manuel , Vargas-De-León Cruz , Gúzman-Martínez María , Corzo-Gómez Josselin
Published: May 2022

Dengue is one of the major health problems in the state of Chiapas. Consequently, spatial information on the distribution of the disease can optimize directed control strategies. Therefore, this study aimed to develop and validate a simple Bayesian prediction spatial model for the state of Chiapas, Mexico. This is an ecological study that uses data from a range of sources. Dengue cases occurred from January to August 2019. The data analysis used the spatial correlation of dengue cases (DCs), which was calculated with the Moran index statistic, and a generalized linear spatial model (GLSM) within a Bayesian framework, which was considered to model the spatial distribution of DCs in the state of Chiapas. We selected the climatological, geographic, and sociodemographic variables related to the study area. A prediction of the model on Chiapas maps was carried out based on the places where the cases were registered. We find a spatial correlation of 0.115

p
 value
=
0.001

between neighboring municipalities using the Moran index. The variables that have an effect on the number of confirmed cases of dengue are the maximum temperature (

Coef
=
0.110

;

95
%
 
CrI

:

0.076
−
0.215

), rainfall (

Coef
=
0.013

;

95
%
 
CrI

:

0.008
−
0.028

), and altitude (

Coef
=
0.00045

;

95
%
 
CrI

:

0.00002
−
0.00174

) of each municipality. The predicting power is notably better in regions that have a greater number of municipalities where DCs are registered. The model shows the importance of considering these variables to prevent future DCs in vulnerable areas.
Financial Risk Avoidance Based on the Sensor Network and Edge Computing
Authors: Yu Yong , Yin Xiaoguo
Published: May 2022

In order to improve the effect of financial risk aversion, this paper studies the financial risk aversion system combined with the edge computing method of the sensor network and proposes a sensor data anomaly detection algorithm based on the offset distance. Moreover, this paper divides the sensor data into several sliding windows according to the time series, analyzes the offset between the data object and other data in the sliding window by calculating the offset distance, and uses the abnormal level to indicate the possibility of data abnormality. In addition, this paper analyzes the single-layer linear network model for the data with high abnormal level and constructs a financial risk aversion model based on the edge computing of the sensor network. The simulation test results show that the financial risk aversion model based on sensor network and edge computing proposed in this paper meets the actual needs of financial risk analysis.
Dermoscopic Image Classification Using Deep Belief Learning Network Architecture
Authors: Farhi Lubna , Kazmi Saadia Mansoor , Imam Hassan , Alqahtani Mejdal , Rehman Farhan Ur
Published: May 2022

In this paper, deep belief learning network architecture (DBL) is proposed for medical image classification in a bid to improve the diagnostics of dermal melanoma as an alternative to traditional dermoscopy. Preprocessing was carried out by using a linear Gaussian filter by eliminating high-frequency artifacts and distortion. The

K

-means segmentation technique was used to extract the region of interest. The DBL network was then applied to the segmented image for classification. The DBL architecture disperses the weights and hyperparameters to all positions in an image, making it possible to scale to various image sizes. The effects of overfitting were mitigated for small datasets and were achieved by optimizing the proposed network. The algorithm works effectively by fine-tuning constraints. The results showed an increase in the accuracy between the proposed model and AlexNet and LeeNet for segmented images from 8% to 47%, respectively. Similarly, an increase for nonsegmented images was observed between 2% and 48%. An average reduction of 47.8% and 41.5% in error for both segmented and nonsegmented images was recorded for dermal images. The execution time also decreased in comparison with the other architectures averaged by 8-13%, since the weights were distributed only on the clustered regions in the segmented image, as compared to the whole image thus allowing the network to classify it faster with improved accuracy.
The Computer-Aided Design Algorithm of Dyeing and Weaving Graphics from the Perspective of Public Art
Authors: Cui Yan
Published: May 2022

With the acceleration of economic development, people put forward higher requirements for clothing style. In this context, the application of traditional patterns has good artistic effects, can show a unique style, and can also express the artistic beauty of clothing through deformation, color distribution, and other forms, and occupies a relatively large position in the design process of dyeing and weaving art. Aiming at the problem of inaccurate extraction of image information from known visual scenes in the original art-aided design, resulting in unclear output images, this paper proposes a computer-aided design algorithm for dyeing and weaving graphics in the field of public art by color segmentation of the known visual scene images according to the set threshold, morphological processing of the segmented images, reducing noise and fractures affecting the acquired connected areas, and formulating extraction rules to screen candidate areas. Furthermore, dense sampling form is used to extract more scale invariant feature transform (SIFT) target features in the candidate area, match the feature points, integrate the coordinate system of known image information into a unified coordinate system, output the design image, and complete the auxiliary design of dyeing and weaving graphics. The results of simulation experiments show that the computer-aided design algorithm of dyeing and weaving graphics in the public art field is more accurate than the original method in extracting information from known images, which helps to solve the problem of clear output dyeing and weaving images, and improves the quality of dyeing and weaving images.
Spatial‐Temporal Analysis of Crash Severity: Multisource Data Fusion Approach
Authors: Taheri Amirhossein , Rasaizadi Arash , Seyedabrishami Seyedehsan
Published: May 2022

High severity crashes are one of the negative consequences of suburban transportation for a range of factors. Fatalities, injuries, and medical costs, as well as road and car damage and mental side effects, are more important consequences of severe crashes. The goal of this research is to figure out what factors contribute to different crash severity levels, in order to reduce the likelihood of such crashes. This study is unique in that it tries to investigate the capabilities of various discrete choice methods in order to explore which one performs best given the current database and research restrictions. Furthermore, the data fusion approach allows this study to take advantage of a wide range of characteristics that influence crash severity. To achieve this objective, the current study used several types of discrete choice models, such as ordered logit (OL), multinominal logit (MNL), and mixed logit (ML) models, to examine the factors influencing the severity of crashes in the suburban highway area. The data are related to crashes and traffic counters in Khorasan Razavi province in the northeast of Iran. Spatial‐temporal analysis of crash data with a data fusion approach has been conducted to prepare a multisource data set with a wide spectrum of independent variables to acquire reliable results using logit models. Independent descriptive variables include geometric design, time‐related, weather and environmental conditions, land use, traffic attributes, vehicle characteristics, and driver characteristics. ML provided the best fit with the available data set when compared to other discrete choice techniques. In addition, in all three logit models, coefficients of geometric design, vehicle characteristics, driver characteristics, land use, and weather and environmental conditions are significant, demonstrating the significance of using multisource data in defining factors impacting crash severity.
Application of Watson Visual Perception Model in Nanchang VI Visual Image Recognition Design
Authors: Huang Jianfeng
Published: May 2022

To shape a complete city image, it is necessary to find the first characteristic of the city so as to further improve the easy identification of the city image, create a good city image, and make the city more competitive. This paper combines the Watson visual perception model to carry out the visual image recognition design of Nanchang VI to improve the communication effect of the urban VI visual image. Moreover, this paper proposes a video watermarking algorithm based on MPEG-4 encoding using the open-source Xvid codec. In addition, this paper proves that the proposed algorithm has good application value in imperceptibility and robustness through a large number of experiments and data analysis. Finally, this paper verifies the reliability of the method proposed in this paper through the study of multiple sets of data.
Intelligent Algorithm-Based Ultrasound for Evaluating the Anesthesia and Nursing Intervention for Elderly Patients with Femoral Intertrochanteric Fractures
Authors: Li Zhen , Peng Yimei , Zou Liping , He Yanfang
Published: May 2022

This study was aimed to explore the anesthesia, analgesia, and nursing intervention scheme for elderly patients undergoing the operation of intertrochanteric fracture of femur under the guidance of ultrasound optimized by blind deblurring algorithm. Fifty elderly patients undergoing intertrochanteric femoral surgery were randomly enrolled into control group (tracheal intubation intravenous anesthesia + routine nursing) and experimental group (ultrasound-guided nerve block anesthesia + comprehensive nursing based on blind deblurring algorithm), with 25 patients in each group. The effects of anesthesia and recovery were evaluated in the two groups. The results showed that the image evaluation index of blind deblurring algorithm was superior to other algorithms (BM3D, DnCNN, and Red-Net), which improved the quality of ultrasound imaging and was more conducive to intraoperative anesthesia guidance. At the beginning and end of intubation and operation, the fluctuation range of mean arterial pressure (MAP) and heart rate (HR) in the experimental group was lower than that in the control group. The maintenance time of sensory and motor anesthesia block (7.53 ± 1.47 h, 5.45 ± 1.36 h) was longer than that of control group (3.38 ± 1.26 h, 3.02 ± 1.31 h). Visual Analogue Scale/Score (VAS) scores at 6 h, 12 h, and 24 h after surgery were lower than those in the control group. The effective rate of nursing and the incidence of complications (92% and 8%) were better than the control group (80% and 16%), and the difference was statistically significant (

P
<
0.05

). In summary, the optimization effect of blind deblurring algorithm was good, which can improve the quality of ultrasound-guided surgery and help in the smooth implementation of surgery. Moreover, nerve block anesthesia and comprehensive nursing were of great value in postoperative analgesia and recovery of patients.
HIF-1α Regulates the Progression of Cervical Cancer by Targeting YAP/TAZ
Authors: Abudoukerimu Azierguli , Hasimu Axiangu , Abudoukerimu Abudouhabaer , Tuerxuntuoheti Gulijiannaiti , Huang Yixin , Wei Jie , Yu Tao , Ma Hong , Yimiti Delixiati
Published: May 2022

Cervical carcinoma is one of the serious pernicious cancers that influence women’s health. Invasion and metastasis are the chief reason of poor prognosis of cervical carcinoma. Hypoxia-inducible factor-1α (HIF-1α) is a significant regulatory factor of intracellular oxygen supersession, and its expression or increased activity is closely related to the arise and expansion of various human tumors. However, the relationship between HIF-1α (hypoxia-inducible factor 1) and Hippo pathway target gene Yes-related protein (YAP) and transcriptional coactivator (TAZ) in cervical carcinoma remains unclear. Here, we studied the clinical correlation of HIF-1α and YAP/TAZ expression in normal tissues, cervical intraepithelial neoplasia (CIN), and cervical squamous cell carcinoma (CSCC). In order to analyze the role of HIF-1α in CCSC in vitro, SiHa cells with high expression of HIF-1α and C33a cells with low expression of HIF-1α were screened by detection. After transfection with lentivirus, HIF-1α levels were downregulated in SiHa cells and upregulated in C33a Cells, respectively. Then, the expression of HIF-1α in transfected cervical cancer cells Siha and C33a was detected by qRT-PCR and Western blot, and the expression of YAP/TAZ was detected in cervical squamous cell carcinoma cells after HIF-1α expression was altered. To explore HIF-1α role in cell proliferation, invasion, and metastasis, we examined the changes of cell function in cervical cancer cells with HIF-1α overexpression and inhibition by MTT assay, wound healing assay, Transwell test, and other cell function tests. At the same time, HIF-1α overexpression and HIF-1α inhibition cervical cancer cells were transplanted into nude mice, and tumors were isolated from the nude mice, and tumor volume and weight were observed. In conclusion, HIF-1α significantly promotes the proliferation, invasion, and migration of cervical carcinoma cells by upregulating YAP/TAZ. In addition, YAP/TAZ, the target gene of Hippo pathway, plays an important role in CCSC cells, pointing out that HIF-1α is provided with treatment potential for the treatment of CCSC.
The Targeting of Noncoding RNAs by Quercetin in Cancer Prevention and Therapy
Authors: Wang Man , Chen Xinzhe , Yu Fei , Zhang Lei , Zhang Yuan , Chang Wenguang
Published: May 2022

The dietary flavonoid quercetin is ubiquitously distributed in fruits, vegetables, and medicinal herbs. Quercetin has been a focal point in recent years due to its versatile health-promoting benefits and high pharmacological values. It has well documented that quercetin exerts anticancer actions by inhibiting cell proliferation, inducing apoptosis, and retarding the invasion and metastasis of cancer cells. However, the exact mechanism of quercetin-mediated cancer chemoprevention is still not fully understood. With the advances in high-throughput sequencing technologies, the intricate oncogenic signaling networks have been gradually characterized. Increasing evidence on the close association between noncoding RNA (ncRNAs) and cancer etiopathogenesis emphasizes the potential of ncRNAs as promising molecular targets for cancer treatment. Available experimental studies indicate that quercetin can dominate multiple cancer-associated ncRNAs, hence repressing carcinogenesis and cancer development. Thus, modulation of ncRNAs serves as a key mechanism responsible for the anticancer effects of quercetin. In this review, we focus on the chemopreventive effects of quercetin on cancer pathogenesis by targeting cancer-relevant ncRNAs, supporting the viewpoint that quercetin holds promise as a drug candidate for cancer chemoprevention and chemotherapy. An in-depth comprehension of the interplay between quercetin and ncRNAs in the inhibition of cancer development and progression will raise the possibility of developing this bioactive compound as an anticancer agent that could be highly efficacious and safe in clinical practice.