bluuebunny/crossref_metadata_2025 huggingface dataset:
Preparation of CO2‐based poly(carbonate‐co‐lactide) with different porphyrin aluminum (III) catalysts
Authors: Li Tao , Liu Zhijian , Chen Yao , Sun Na , Shu Haozhou , Wu Lili , Zhang Chaocan , Xie Dong
Published: May 2023

Two‐component catalysts composed of tetra (para‐X substituted) phenylporphyrin aluminum (III) chloride, T (p‐X‐P)PAlCl, (where X = H, F, Cl, Br, CH3, OCH3, tert‐butyl), and cocatalyst bis(triphenylphosphine)imminium chloride (PPN+Cl−), could initiate the polymerization of propylene oxide (PO). And they could react with rac‐lactide, (rac‐LA), in the presence of propylene oxide (PO), to yield chains of enriched isotactic polylactide (PLA) with trace polyether segment. Also, these catalysts displayed different catalytic activity in the copolymerization of CO2 and PO, resulting in poly(carbonate‐co‐ether) copolymer with different carbonate unit content (CU%). Further, these catalysts could initiate one‐pot regio‐ and stereo‐ selective terpolymerization of rac‐LA, CO2 and rac‐PO, resulting in multi‐blocky poly(carbonate‐co‐lactide) with trace polyether segment. The structure of the products was verified by 1H NMR, 13C NMR, GPC, and DSC analysis, and it was found that variation of substitution groups in the periphery of porphyrin ligand would affect on the catalytic efficiency of ter‐polymerization, and the relative polymerization reaction ratio of the ring‐opening polymerization of LA (ROP) to the ring‐opening copolymerization of PO and CO2 (ROCOP), resulting in ter‐polymer with different contents of PLA segment and PPC segment. However, H‐T% in polycarbonate unit and Pi% in polylactide unit did not vary much with the change of catalysts.
Miniature mass spectrometer signal processing based on ensemble empirical mode decomposition feature enhancement
Authors: Li Ming , Zhan Chenrui , Lv Yueguang , Chen Jiwen , Wang Yutian , Lu Sixian , Wan Yingqi , Ma Qiang
Published: May 2023

Rationale

The high sensitivity of the miniature mass spectrometer plays an irreplaceable role in rapid on‐site detection. However, its analysis accuracy and stability should be improved due to the influence of sample pretreatment and use environment. The present study investigates the processing effects of ensemble empirical mode decomposition (EEMD) feature enhancement methods on the determination coefficient (R2) and relative standard deviation (RSD) of caffeine mass spectrometry (MS) signals.

Methods

This paper employs the EEMD method combined with polynomial curve fitting to enhance the characteristics of seven caffeine mass spectrum signals with different concentrations and 15 groups of caffeine mass spectrum signals with the same concentration, and the wavelet analysis method was used for comparative verification. The determination coefficient and RSD of the two methods were compared.

Results

We found the EEMD method's capability in adaptively decomposing caffeine mass spectrum signals is better than wavelet analysis method. The determination coefficient of the EEMD enhanced feature is better than 0.999, and the RSD is better than 2%, and both are better than wavelet analysis methods.

Conclusions

The feature enhancement processing using the EEMD method has significantly improved the determination coefficient and RSD of the sample curve, improving the accuracy and stability of the data and providing a new way for miniature mass spectrometer signal processing.
Triangular formation control with mixed distance and bearing measurements under limited field of view constraints
Authors: Zhao Xinyue , Yang Qingkai , Pan Yunlong , Fang Hao
Published: May 2023

This article addresses the problem of triangular formation control for a three‐agent group with different measuring capabilities: agent 1 can measure local bearings but with limited field of view (FOV), and agents 2 and 3 can only obtain distance measurements. For agent 1, an orientation controller is first designed to steer its heading to the expected direction. Furthermore, a type of switching control law utilizing pure bearing measurements is proposed to reach the desired angle with respect to the other two agents. Concurrently, it is guaranteed that the flip ambiguity of the formation can be excluded. For agents 2 and 3, the extended distance‐based control algorithm is proposed by invoking the so‐called signed area strategy to determine their actuation. With this control scheme, it is proven that the triangular formation is stabilized globally even in the presence of FOV constraints. The effectiveness is validated through numerical simulations and physical experiments on three nano quadrotors.
Crude Polysaccharide Produces Silver Nanoparticles with Inherent Antioxidant and Antibacterial Activity
Authors: Sana Siva Sankar , Hou Tianyu , Li Huizhen , Vadde Ramakrishna , Basavegowda Nagaraj , Chakravorty Arghya , Kumbhakar Divya Vishambhar , Zhang Zhijun , Mamidi Narsimha
Published: May 2023

We present an efficient and biologically based process for producing silver nanoparticles (Ag‐NPs) using crude polysaccharides extracted from Perilla frutiscences plants (PFCPS). The PFCPS serves as both a reducing agent and a capping agent during Ag‐NP formation. Characterization of the synthesized Ag‐NPs was performed through various techniques such as Ultraviolet‐Visible (UV‐Vis) absorption spectroscopy, X‐ray diffraction (X‐RD), Fourier transform infrared spectroscopy (FT‐IR), and high‐resolution transmission electron microscopy (HR‐TEM). Antioxidant properties of the Ag‐NPs were evaluated using DPPH, reducing power, and ABTS free radical assays, revealing their potential use as antioxidants. Additionally, Ag‐NPs displayed promising antibacterial activity against Escherichia coli and Klebsiella pneumonia, suggesting their potential for application in medical and healthcare products for the prevention and treatment of infections.
Design, Synthesis, and Molecular Modeling of New and Safe Azole Oxime Esters with Promising Antifungal Activity
Authors: Yurtoğlu Sibel , Sari Suat , Kart Didem , Sabuncuoğlu Suna , Saraç Selma
Published: May 2023

Fungal infections have become a major public health issue with dramatically increasing morbidity, mortality and cost of hospitalization. Azole antifungals are first‐in‐line medications against most types of mycoses and azoles having an oxime moiety, although not extensively investigated, were reported to have great antifungal potential, as well as, activity against Gram‐positive bacteria. In the current study, a new series of 2‐(1H‐imidazol‐1‐yl)‐1‐phenylethanone oxime esters (5 a–l) were synthesized and tested for their antimicrobial activities. The sorbic acid ester (5 c) was found to be highly promising against Candida albicans and Candida parapsilosis (MIC=4 μg/ml). In addition, 5 c was not toxic to the healthy murine fibroblast. Molecular modelling suggested that the compounds were druglike, orally available, not substrates of efflux pumps, and probably acted through fungal CYP51 inhibition, which is the major action mechanism of azole antifungals.
Highly Dispersed Pt‐Au/rGO Catalysts Prepared by Hyperbranched Polyglycerols for Efficient Electrooxidation of Methanol
Authors: Ren Guohong , Chen Yuting , Liu Chunyu , Zhang Shenhang , Li Haotian , Chen Hong , Dong Xingzheng , Chu Ruixia , Qiu Fangyuan , Liu Zhongsu
Published: May 2023

Recently, fuel cells especially direct methanol fuel cells (DMFCs), have attracted great interest because of their high energy density, their pollution‐free operation mode and thus their prospect for use in convenient transportation. Although platinum (Pt) catalyst is an efficient catalysts for DMFCs, it has some problems such as high price, poor stability and durability. Therefore, the research of high performance Pt catalysts becomes the focus. Firstly, the hyperbranched polyglycerols (HPG) were synthesized by the one‐step anionic ring‐opening polymerization. The Pt‐Au bimetallic catalysts supported on reduced graphene oxide (Pt‐Au‐HPG/rGO) were synthesized via a hydrothermal method, using HPG as the template and stabilizer. The electrocatalytic performances for the electrooxidation of methanol were investigated by electrochemical methods. Compared with commercial Pt/C (10 wt %) catalysts, Pt‐Au‐HPG/rGO has the larger electrochemically active surface area (ECSA, 108.8 m2 g−1), higher catalytic performance (0.498 A mgmetal−1) and better stability. This excellent performance is attributed to the good dispersion and conductivity of Pt‐Au‐HPG/rGO for the addition of HPG, rGO and Au. Meanwhile, the bifunctional and electronic effects between Au and Pt improved the electrochemical performance of the samples.
Synthesis of Chiral Tricyclic Pyrone Molecules via Palladium(0)‐Catalyzed Displacement Reactions of Chiral Tricyclic Pyrone Acetate With Azide or Amine
Authors: Morita Shunya , Ren Zhaoyang , Fan Huafang , Hua Duy H.
Published: May 2023

Tricyclic pyrone (TP) molecules have shown protection of MC65 neuroblastoma cells death induced by amyloid‐β proteins through SβC gene, a decrease of amyloid‐β peptide levels, and improvement of motor functions and memory in Alzheimer's disease mouse and rat models. Mechanistic studies suggest TP molecules modulate N‐methyl‐D‐aspartate receptor. A short synthesis of chiral TP analogs was sought using a Pd(0)‐catalyzed displacement of TP allylic acetate intermediate with sodium azide or substituted benzylamines. A three‐step sequence of reactions by the treatment of 2‐{(5aS,7S)‐3‐methyl‐1‐oxo‐1,5a,6,7,8,9‐hexahydropyrano[4,3‐b]chromen‐7‐yl}allyl acetate (9) with (Ph3P)4Pd and sodium azide, followed by reduction with Zn‐NH4OCHO and coupling with 3‐fluoro‐4‐hydroxybenzaldehyde and NaCNBH3 was found to give TP coupling molecule, (5aS,7S)‐7‐(1‐(3‐fluoro‐4‐hydroxybenzylamino)prop‐2‐en‐2‐yl)‐3‐methyl‐6,7,8,9‐tetrahydropyrano[4,3‐b]chromen‐1(5aH)‐one (2), in a good yield. An alternative shorter pathway – a two‐step sequence of reactions – by the displacement of 9 by 4‐(t‐butyldimethylsilyloxy)‐3‐fluoro‐benzylamine with a catalytic amount of (Ph3P)4Pd in THF followed by removal of the silyl ether protecting group gave 2, albeit in a lower chemical yield. The described syntheses should provide general procedures for the synthesis of a library of TP molecules for the discovery of anti‐Alzheimer drugs.
Bioinspired Strong and Tough Organic–Inorganic Hybrid Fibers
Authors: Xiao Yao , Yang Chenjing , Guo Baoling , Zhai Xiaowei , Lao Shuxing , Zhao Peng , Ruan Jian , Lu Xingyu , Liu Kai , Chen Dong
Published: May 2023

High‐strength and high‐toughness bio‐based fibers attract broad interest in biomechanical applications. Herein, strong and tough organic–inorganic regenerated silk fibroin/hydroxyapatite (RSF/HAP) hybrid fibers are prepared using a single‐channel microfluidic device. Calcium phosphate oligomers (CPOs) dispersed in the RSF matrix first grow into spherical amorphous calcium phosphates (ACPs), which then crystallize into needle‐like HAPs under a humidity condition, mimicking the biomineralization in collagen bundles. HAPs are better aligned along the RSF/HAP fiber direction after poststretching, forming a highly ordered and densely packed microstructure within the fiber and thus facilitating highly dense noncovalent interactions between rigid inorganic HAP nanocrystals and flexible organic RSF matrix. The highly dense noncovalent interactions endow the organic–inorganic hybrid fibers with superior mechanical properties and twisted RSF/HAP fiber bundles demonstrate a remarkable tensile strength of 778 MPa, a high Young's modulus of 17.8 GPa, a large tensile strain of 19.9%, and an excellent toughness of 121 MJ m−3 after proper twisting treatments. RSF/HAP hybrid fibers also show good performances against static loading, dynamic impact, and extreme cold condition and they can maintain their mechanical properties down to −50 °C. Therefore, the fibers are strong and tough and the strategy is facile and efficient.
Quantum chemical modeling of organic enhanced atmospheric nucleation: A critical review
Authors: Elm Jonas , Ayoubi Daniel , Engsvang Morten , Jensen Andreas Buchgraitz , Knattrup Yosef , Kubečka Jakub , Bready Conor J. , Fowler Vance R. , Harold Shannon E. , Longsworth Olivia M. , Shields George C.
Published: May 2023

Aerosol particles are important for our global climate, but the mechanisms and especially the relative importance of various vapors for new particles formation (NPF) remain uncertain. Quantum chemical (QC) studies on organic enhanced nucleation has for the past couple of decades attracted immense attention, but very little remains known about the exact organic compounds that potentially are important for NPF. Here we comprehensively review the QC literature on atmospheric cluster formation involving organic compounds. We outline the potential cluster systems that should be further investigated. Cluster formation involving complex multi‐functional organic accretion products warrant further investigations, but such systems are out of reach with currently applied methodologies. We suggest a “cluster of functional groups” approach to address this issue, which will allow for the identification of the potential structure of organic compounds that are involved in atmospheric NPF.

This article is categorized under:

Theoretical and Physical Chemistry > Reaction Dynamics and Kinetics

Software > Quantum Chemistry

Theoretical and Physical Chemistry > Thermochemistry

Molecular and Statistical Mechanics > Molecular Interactions
Hilbert series and higher-order Lagrangians for the O(N) model
Authors: Bijnens Johan , Gudnason Sven Bjarke , Yu Jiahui , Zhang Tiantian
Published: May 2023

Abstract

We compare the Hilbert series approach with explicit constructions of higher-order Lagrangians for the O(N) nonlinear sigma model. We use the Hilbert series to find the number and type of operators up to mass dimension 16, for spacetime dimension D up to 12 and N up to 12, and further classify the operators into spacetime parity and parity of the internal symmetry group O(N). The explicit construction of operators is done up to mass dimension 12 for both parities even and dimension 10 for the other three cases. The results of the two methods are in full agreement. This provides evidence for the Hilbert series conjecture regarding co-closed but not co-exact k-forms, which takes into account the integration-by-parts relations.
What is the link between temperature, carbon dioxide and methane? A multivariate Granger causality analysis based on ice core data from Dome C in Antarctica
Authors: Larsson Rolf , Persson Erik K.
Published: May 2023

This paper continues the work of Kang and Larsson Theoretical and Applied Climatology 116:537–548 (2014) What is the link between temperature and carbon dioxide levels? A Granger causality analysis based on ice core data. Theoretical and Applied Climatology 116:537-548, by adding methane to the study of causality between temperature and carbon dioxide. The data used goes 800,000 years back in time which is possible due to it being extracted from ice cores located at Dome C in Antarctica. First we use linear interpolation to make the three data sets equidistant to be able to employ statistical methods. We adjust for a deterministic trend and find the best model fit to be an autoregressive model with lag two and a piecewise quadratic trend. By employing multivariate Granger causality tests we find strong evidence that temperature, carbon dioxide and methane all Granger cause each other in both directions i.e. carbon dioxide Granger causes temperature and temperature Granger causes carbon dioxide, etc. This is in accordance with the findings of Kang and Larsson, with the extension that we can add methane to establish a trivariate feedback system between temperature, carbon dioxide and methane.
Tracking social provenance in chains of retweets
Authors: Migliorini Sara , Gambini Mauro , Quintarelli Elisa , Belussi Alberto
Published: May 2023

In the era of massive sharing of information, the term social provenance is used to denote the ownership, source or origin of a piece of information which has been propagated through social media. Tracking the provenance of information is becoming increasingly important as social platforms acquire more relevance as source of news. In this scenario, Twitter is considered one of the most important social networks for information sharing and dissemination which can be accelerated through the use of retweets and quotes. However, the Twitter API does not provide a complete tracking of the retweet chains, since only the connection between a retweet and the original post is stored, while all the intermediate connections are lost. This can limit the ability to track the diffusion of information as well as the estimation of the importance of specific users, who can rapidly become influencers, in the news dissemination. This paper proposes an innovative approach for rebuilding the possible chains of retweets and also providing an estimation of the contributions given by each user in the information spread. For this purpose, we define the concept of Provenance Constraint Network and a modified version of the Path Consistency Algorithm. An application of the proposed technique to a real-world dataset is presented at the end of the paper.
A machine learning-based optimization approach for pre-copy live virtual machine migration
Authors: Haris Raseena M. , Khan Khaled M. , Nhlabatsi Armstrong , Barhamgi Mahmoud
Published: May 2023

Organizations widely use cloud computing to outsource their computing needs. One crucial issue of cloud computing is that services must be available to clients at all times. However, the cloud services may be temporarily unavailable due to maintenance of the cloud infrastructure, load balancing of services, defense against cyber attacks, power management, proactive fault tolerance, or resource usage. The unavailability of cloud services impacts negatively on the business model of cloud providers. One solution to tackle the service unavailability is Live Virtual Machine Migration (LVM), that is, moving virtual machines (VMs) from the source host machine to the destination host without disrupting the running application. Pre-copy memory migration is a common LVM approach used in most networked systems such as the cloud. The main difficulty with this approach is the high rate of frequently updating memory pages, referred to as "dirty pages. Transferring these updated or dirty pages during the pre-copy migration approach prolongs the total migration time. After a predefined iteration, the pre-copy approach enters the stop-and-copy phase and transfers the remaining memory pages. If the remaining pages are huge, the downtime or service unavailability will be very high -resulting in a negative impact on the availability of the running services. To minimize such service downtime, it is critical to find an optimal time to migrate a virtual machine in the pre-copy approach. To address the issue, this paper proposes a machine learning-based method to optimize pre-copy migration. It has mainly three stages (i) Feature selection (ii) Model generation and (iii) Application of the proposed model in pre-copy migration. The experiment results show that our proposed model outperforms other machine learning models in terms of prediction accuracy and it significantly reduces downtime or service unavailability during the migration process.
“The rich will always be able to dispose of their waste”: a view from the frontlines of municipal failure in Makhanda, South Africa
Authors: Kalina Marc , Makwetu Ncebakazi , Tilley Elizabeth
Published: May 2023

A significant proportion of South African municipalities, who hold the mandate for providing solid waste management (SWM) services for millions of South Africans, appear to be on the brink of collapse. On the frontlines of municipal failure, the city of Makhanda, following two decades of poor governance and mismanagement, has found itself unable to fulfil its mandate, with the state retreating on SWM service provision, and disruptions to waste management services becoming a daily reality. Drawing on embedded, qualitative fieldwork, this article examines how differently placed residents have experienced disruptions to SWM services. This work explores how residents of Makhanda’s two halves: the affluent and predominantly white neighbourhoods in the west, and the poor, non-white townships in the east, have (or have not) adapted to manage and dispose of their own waste during periods of disruption. Findings suggest that disruptions to waste management service provision have been broadly experienced by residents. However, the consequences of interruptions to municipal collection have not been evenly borne, as more resourced, western residents have been more successful at managing their own waste disposal, while the residents of Makhanda’s townships are less capable of coping, with affected communities coming to resemble a dumping ground, and residents having to adopt unsafe or environmentally harmful disposal practices. These findings are important because they shed light on the challenges of creating cleaner, more equal communities without healthy municipal participation in waste management services, while raising important considerations for a South Africa facing the possibility of widespread municipal collapse.
Nintedanib Ameliorates Bleomycin-Induced Pulmonary Fibrosis, Inflammation, Apoptosis, and Oxidative Stress by Modulating PI3K/Akt/mTOR Pathway in Mice
Authors: Pan Lin , Cheng Yiju , Yang Wenting , Wu Xiao , Zhu Honglan , Hu Meigui , Zhang Yuquan , Zhang Menglin
Published: May 2023

Abstract

Idiopathic pulmonary fibrosis (IPF) seriously threatens human life and health, and no curative therapy is available at present. Nintedanib is the first agent approved by the US Food and Drug Administration (FDA) in order to treat IPF; however, its mechanism of inhibition of IPF is still elusive. According to recent studies, nintedanib is a potent inhibitor. It can antagonize platelet-derived growth factor (PDGF), basic fibroblast growth factor (b-FGF), vascular endothelial growth factor (VEGF), etc., to inhibit pulmonary fibrosis. Whether there are other signaling pathways involved in IPF remains unknown. This study focused on investigating the therapeutic efficacy of nintedanib in bleomycin-mediated pulmonary fibrosis (PF) mice through PI3K/Akt/mTOR pathway. Following the induction of pulmonary fibrosis in C57 mice through bleomycin (BLM) administration, the mice were randomized into five groups: (1) the normal control group, (2) the BLM model control group, (3) the low-dose Nintedanib administration model group, (4) the medium-dose nintedanib administration model group, and (5) the high-dose nintedanib administration model group. For lung tissues, morphological changes were found by HE staining and Masson staining, ELISA method was used to detect inflammatory factors, alkaline water method to estimate collagen content, and western blotting for protein levels. TUNEL staining and immunofluorescence methods were used to analyze the effect of nintedanib on lung tissue and the impacts and underlying mechanisms of bleomycin-induced pulmonary fibrosis. After 28 days, bleomycin-treated mice developed significant pulmonary fibrosis. Relative to bleomycin-treated mice, nintedanib-treated mice had markedly reduced degrees of PF. In addition, nintedanib showed lung-protective effects by up-regulating antioxidant levels, down-regulating inflammatory protein expression, and reducing collagen accumulation. We demonstrated that nintedanib ameliorated bleomycin-induced lung injury by inhibiting the P13K/Akt/mTOR pathway as well as apoptosis. In addition, significant improvement in pulmonary fibrosis was seen after nintedanib (30/60/120 mg/kg body weight/day) treatment through a dose-dependent way. Histopathological results further corroborated the effect of nintedanib treatment on remarkably attenuating bleomycin-mediated mouse lung injury. According to our findings, nintedanib restores the antioxidant system, suppresses pro-inflammatory factors, and inhibits apoptosis. Nintedanib can reduce bleomycin-induced inflammation by downregulating PI3K/Akt/mTOR pathway, PF, and oxidative stress (OS).
Devo-Aging: Intersections Between Development and Aging
Authors: Silva-García Carlos Giovanni
Published: May 2023

There are two fundamental questions in developmental biology. How does a single fertilized cell give rise to a whole body? and how does this body later produce progeny? Synchronization of these embryonic and postembryonic developments ensures continuity of life from one generation to the next. An enormous amount of work has been done to unravel the molecular mechanisms behind these processes, but more recently, modern developmental biology has been expanded to study development in wider contexts, including regeneration, environment, disease, and even aging. However, we have just started to understand how the mechanisms that govern development also regulate aging. This review discusses examples of signaling pathways involved in development to elucidate how their regulation influences healthspan and lifespan. Therefore, a better knowledge of developmental signaling pathways stresses the possibility of using them as innovative biomarkers and targets for aging and age-related diseases.
Development and Characterization of Soy Lecithin Liposome as Potential Drug Carrier Systems for Doxorubicin
Authors: Ahmed Shaimaa A. , Salama Aida A. , Gaber Mohamed H. , Ali Said A.
Published: May 2023

Purpose

The phospholipids from plant origins play an important role in different techniques, especially in drug delivery applications. The purpose of this study is to investigate the effect of liposomes prepared from plant origin as a cheap source of lipids as drug carriers.

Methods

Soy lecithin liposomes (SLP) were prepared and loaded with doxorubicin (DOX) to use as a drug delivery system. DOX was used as the model drug and DOX/SLP was successfully combined. The characteristics of these liposomes, zeta potential, size distribution, drug encapsulation efficiency (EE%), drug release, Fourier transform infrared (FTIR), and transmission electron microscopy (TEM) were checked followed by in vitro study. The cytotoxicity study by using free DOX and DOX/SLP is done on Mcf-7, human breast cancer as a cell line.

Results

The optimal DOX/SLP formulation had a mean size of 342 nm, a negative zeta potential of −22.3 mV, the loaded DOX/SLP showed EE% (83.68%), and a drug release profile of 35 h, all are recorded. Cytotoxicity assay showed that the IC50 of DOX/SLP is smaller than that of free DOX.

Conclusion

These results give evidence of the efficacy of using drug carriers from plant origin combined with drugs to increase the effective therapies against cancer medically and economically.

Graphical Abstract
Swarm Exploration Mechanism-Based Distributed Water Wave Optimization
Authors: Li Haotian , Yang Haichuan , Zhang Baohang , Zhang Han , Gao Shangce
Published: May 2023

Using sparrow search hunting mechanism to improve water wave algorithm (WWOSSA), which combines the water wave optimization (WWO) algorithm and the sparrow search algorithm (SSA), has good optimization ability and fast convergence speed. However, it still suffers from insufficient exploration ability and is easy to fall into local optimum. In this study, we propose a new algorithm for distributed population structure, called swarm exploration mechanism-based distributed water wave optimization (DWSA). In DWSA, an information exchange component and an optimal individual evolution component are designed to improve information exchange between individuals. This multi-part information interaction and distributed population structure algorithm can help the population algorithm to establish a balance between exploitation and exploration more effectively. We contrast DWSA with the original algorithms WWOSSA and other meta-heuristics in order to show the effectiveness of DWSA. The test set consists of 22 actual optimization issues from the CEC2011 set and 29 benchmark functions from the CEC2017 benchmark functions. In addition, an experimental comparison of the parameter values introduced in DWSA is included. According to experimental results, the proposed DWSA performs substantially better than its competitors. Assessments of the population diversity and landscape search trajectory also confirmed DWSA’s outstanding convergence.
Host Genetic Factors, Comorbidities and the Risk of Severe COVID-19
Authors: Zhu Dongliang , Zhao Renjia , Yuan Huangbo , Xie Yijing , Jiang Yanfeng , Xu Kelin , Zhang Tiejun , Chen Xingdong , Suo Chen
Published: May 2023

Background

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was varied in disease symptoms. We aim to explore the effect of host genetic factors and comorbidities on severe COVID-19 risk.

Methods

A total of 20,320 COVID-19 patients in the UK Biobank cohort were included. Genome-wide association analysis (GWAS) was used to identify host genetic factors in the progression of COVID-19 and a polygenic risk score (PRS) consisted of 86 SNPs was constructed to summarize genetic susceptibility. Colocalization analysis and Logistic regression model were used to assess the association of host genetic factors and comorbidities with COVID-19 severity. All cases were randomly split into training and validation set (1:1). Four algorithms were used to develop predictive models and predict COVID-19 severity. Demographic characteristics, comorbidities and PRS were included in the model to predict the risk of severe COVID-19. The area under the receiver operating characteristic curve (AUROC) was applied to assess the models’ performance.

Results

We detected an association with rs73064425 at locus 3p21.31 reached the genome-wide level in GWAS (odds ratio: 1.55, 95% confidence interval: 1.36–1.78). Colocalization analysis found that two genes (SLC6A20 and LZTFL1) may affect the progression of COVID-19. In the predictive model, logistic regression models were selected due to simplicity and high performance. Predictive model consisting of demographic characteristics, comorbidities and genetic factors could precisely predict the patient’s progression (AUROC = 82.1%, 95% CI 80.6–83.7%). Nearly 20% of severe COVID-19 events could be attributed to genetic risk.

Conclusion

In this study, we identified two 3p21.31 genes as genetic susceptibility loci in patients with severe COVID-19. The predictive model includes demographic characteristics, comorbidities and genetic factors is useful to identify individuals who are predisposed to develop subsequent critical conditions among COVID-19 patients.
Neuromodulation and Opioid Use Disorder: Ethical Opportunities for Canada
Authors: Boyle Quinn , Illes Judy
Published: May 2023

Despite increased efforts of government and non-government organisations to intervene via harm reduction and education initiatives, the opioid crisis has continued to worsen and has been exacerbated by the COVID-19 pandemic. In British Columbia, Canada, opioid overdose deaths in 2021 are the highest ever recorded. Neuromodulation procedures such as deep brain stimulation and repetitive transcranial magnetic stimulation have gained traction as treatments for opioid use disorder in various countries such as Germany, the Netherlands, the United States and China. However, these treatment options have been met with apprehension from both clinicians and patients, likely owing to fear, stigma and reluctance to label addiction as a brain disorder. Further complicating this landscape are socio-demographic factors, as marginalised communities are disproportionately burdened by addiction, while having poor access to care and a history of distrust in the health system. This multifactorial challenge involving many sociocultural factors requires culturally sensitive, interdisciplinary approaches to ensure direct-to-brain innovations are implemented ethically and equitably. This review summarises the state of the science for using neuromodulation to treat opioid use disorder, as well as the available ethical discourse surrounding the expansion of clinical trials and eventual widespread clinical implementation. Additional ethics discussions highlight opportunities for the engineering and clinical evolution of neuromodulation for opioid use disorder trials.
Interventional Psychiatry and Neurotechnologies: Education and Ethics Training
Authors: Giacobbe Peter , Burhan Amer M. , Waxman Robyn , Ng Enoch
Published: May 2023

The last two decades have seen dramatic growth in the application of procedurally based interventions for treating refractory psychiatric conditions, leading to interest in developing the foundations for the subspecialty of “Interventional Psychiatry.” However, there is cause for concern that the rate of expansion of clinical advances in this field may be outpacing the ability of postgraduate curricula to provide sufficient exposure to and teaching and supervision of these treatments. The paucity of adequately trained practitioners in Interventional Psychiatry further exacerbates inequities in the ability of eligible patients to access and benefit from these approaches. This paper explores the rates of utilization of Interventional Psychiatry treatments, the current state of education in these treatments, and the role that training can play in translating scientific advances in this area to ensure equitable access and maximum impact at a population level. The majority of the discussion is centered on electroconvulsive therapy (ECT), the most established and available of these treatments, highlighting how enhancing education and training in ECT can reduce barriers to its utilization. It is argued that innovations in pedagogical approaches for disseminating the learning of these procedures are needed to increase the current low rates of competency in these treatments and can facilitate the more rapid dissemination of other Interventional Psychiatry approaches and neurotechnologies, such as repetitive transcranial magnetic stimulation, ketamine, deep brain stimulation, and focused ultrasound.
Populist Memory Politics and the Performance of Victimhood: Analysing the Political Exploitation of Historical Injustice in Central Europe
Authors: Meijen Jens , Vermeersch Peter
Published: May 2023

Right-wing populists often mobilize popular support by employing a people-versus-elite dichotomy in which they cast ‘the people’ as the underdog, or by ‘performing’ crisis to discredit the elite. Such ‘underdogism’, and the reliance on crisis more broadly, remains an effective strategy for as long as populists are in opposition. But what happens when populists gain power? One would expect that they would not be able to exploit their position as effectively and their appeal would weaken drastically. In certain cases, however, they still manage to sustain the underdog illusion. This article argues that memory politics are an important locus for populists to maintain their underdog rhetoric, and within that field the performance of victimhood is key. Building on theories about the performance of crisis and recent trends in research on memory politics in Central Europe, we propose a framework for understanding how governing right-wing populists justify vindictive policies and thus try to cement their power.
The Kunming–Montreal Global Biodiversity Framework
Authors: Stephens Tim
Published: May 2023

The Kunming–Montreal Global Biodiversity Framework (the Framework) was adopted at the Fifteenth Meeting of the Conference of the Parties (COP15) to the 1992 Convention on Biological Diversity (CBD) on December 19, 2022. Despite the efforts made under the CBD, biodiversity loss has continued at an alarming rate, and the targets set under the Convention's Strategic Plan for Biodiversity 2011–2020 were not fully achieved. In 2018, the CBD Parties therefore adopted a decision to develop a post-2020 global biodiversity framework to guide international efforts towards the conservation and sustainable use of biodiversity over the next decade. The Framework, the adoption of which was delayed by two years by the COVID-19 pandemic, succeeds and replaces the 2011–2020 Strategic Plan for Biodiversity and its accompanying Aichi Targets. The Framework includes four overarching goals and twenty-three accompanying targets to be achieved by 2030, together with four long-term goals to achieve the 2050 Vision for Biodiversity.
Populism and emotions: a comparative study using Machine Learning
Authors: Caiani Manuela , Di Cocco Jessica
Published: May 2023

This study aims to unpack the mobilization of emotions in the political discourse of populist and non-populist parties and above all, across ‘varieties of populism’ (right wing vs. left wing or hybrid). Is there an empirical connection between emotions and populism? Are all types of populisms alike with regards to the emotional appeals within their political discourse? Focusing on Italy as a crucial case for populist communication and using a novel methodological approach based on supervised machine learning, it systematically investigates the intensity and trends of specific emotions in political discourses (institutional and informal, i.e. leaders’ speeches) of all Italian political parties over the last 20 years, for a corpus of more than 13,000 sentences analysed. The findings confirm that (i) populists tend to use more (and a broader repertoire of) emotional appeals than non-populist parties; however (ii) overall, there is an increase in the use of these appeals in the Italian political party discourse over time, especially in terms of negative emotions; and, most importantly, (iii) different types of emotions are mobilized by different types of populisms. Right wing populism mainly uses negative emotions while left wing or hybrid populism employs positive emotional appeals. The communication arena (party manifestoes vs. speeches) nevertheless does matter in the degree and types of emotions mobilized by political actors. This study identifies important implications for research on emotional appeals in politics, populist communication and political campaigning, and populist contagion from an emotion-based perspective.
Military Intimacies: Peruvian Veterans and Narratives about Sex and Violence
Authors: Boesten Jelke , Gavilán Lurgio
Published: May 2023

This article explores how sex and violence were part of the everyday making of the soldier in the Peruvian armed forces during the internal armed conflict between 1980 and 2000. In-depth interviews with Peruvian veterans indicate the importance of sex and violence in soldiers’ experience of becoming a combatant. The article analyzes the ambiguity in soldiers’ narratives about sex and violence, coercion, and consent, and how they are implicated in both receiving and enacting sexualized violence. In particular, authors discuss veterans’ accounts of collective experiences of sexualized hazing, abuse of women and girls, porn and prostitution, and references to gang rape. Soldiers, while in the army, experience intimacy through performative practices of sex and violence—which profoundly affect their interactions with one another—and the violence they perpetrate against enemy populations. These military intimacies, encouraged through institutional as well as cultural practices, help explain the prevalence of widespread sexual violence during the conflict.
Creating Value Out of Waste: The Transformation of the Swedish Waste and Recycling Sector, 1970s–2010s
Authors: Bergquist Ann-Kristin , Lindmark Magnus , Petrusenko Nadezda
Published: May 2023

This article examines the growth of the waste and recycling sector in Sweden since the 1970s and seeks to identify the conditions for market growth and underlying business dynamics. The article identifies a slow growth pattern at aggregate level in the 1970s, while a major shift toward higher growth rates took place only in the mid-1990s. Resembling the findings of existing studies of German and US industry counterparts, Swedish recycling companies grew larger in the 1970s and more knowledge-intensive from the 1980s. Our study concludes that the growth of the Swedish recycling industry has been driven not only by government policies addressing household waste but even more so by large manufacturing firms that have increasingly demanded more complex recycling services over time.
Factual and counterfactual learning in major adolescent depressive disorder, evidence from an instrumental learning study
Authors: Shen Qiang , Fu Shiguang , Jiang Xiaoying , Huang Xiaoyu , Lin Doudou , Xiao Qingyan , Khadijah Sitti , Yan Yaping , Xiong Xiaoxing , Jin Jia , Ebstein Richard P. , Xu Ting , Wang Yiquan , Feng Jun
Published: May 2023

Background

The incidence of adolescent depressive disorder is globally skyrocketing in recent decades, albeit the causes and the decision deficits depression incurs has yet to be well-examined. With an instrumental learning task, the aim of the current study is to investigate the extent to which learning behavior deviates from that observed in healthy adolescent controls and track the underlying mechanistic channel for such a deviation.

Methods

We recruited a group of adolescents with major depression and age-matched healthy control subjects to carry out the learning task with either gain or loss outcome and applied a reinforcement learning model that dissociates valence (positive v. negative) of reward prediction error and selection (chosen v. unchosen).

Results

The results demonstrated that adolescent depressive patients performed significantly less well than the control group. Learning rates suggested that the optimistic bias that overall characterizes healthy adolescent subjects was absent for the depressive adolescent patients. Moreover, depressed adolescents exhibited an increased pessimistic bias for the counterfactual outcome. Lastly, individual difference analysis suggested that these observed biases, which significantly deviated from that observed in normal controls, were linked with the severity of depressive symoptoms as measured by HAMD scores.

Conclusions

By leveraging an incentivized instrumental learning task with computational modeling within a reinforcement learning framework, the current study reveals a mechanistic decision-making deficit in adolescent depressive disorder. These findings, which have implications for the identification of behavioral markers in depression, could support the clinical evaluation, including both diagnosis and prognosis of this disorder.
What works in co-producing assistive technology solutions with older people: a scoping review of the evidence
Authors: Rolfe Steve , McCall Vikki , Gibson Grant , Pusram Angela , Robertson Jane
Published: May 2023

Assistive technology for older people promises much, but the research evidence suggests that it delivers little. One hypothesis to explain the lack of positive impact is that assistive technology is often implemented with little involvement of older people or other stakeholders, such as family members or care staff. The suggestion is that co-production may ensure that assistive technology solutions are better tailored to people's needs, capacities and living situations. In this article, we review existing studies to examine what works in co-production in relation to processes of design and implementation of assistive technology for older people. Our results show a growing interest in co-production as an approach in this field, with a wide range of approaches being employed. We highlight a number of key lessons from the research, including key issues around who needs to be engaged in the co-production, as well as essential elements of the process itself. Our review suggests that there is considerable potential in using co-production to improve effectiveness of technological solutions to the challenges of age-related impairments. However, we also emphasise the need for more longitudinal research in this area, to examine whether such collaborative approaches can truly deliver the promise of assistive technology for older people.
Performance on the African neuropsychology battery using the learning ratio in a sample of healthy Congolese
Authors: Ikanga Jean , Taiwo Zinat , Lengu Ketrin , Epenge Emmanuel , Esambo Herve , Gikelekele Guy , Esselakoy Christian , Kavugho Immaculée , Mampunza Samuel M. , Hammers Dustin , Stringer Anthony , Spencer Robert J.
Published: May 2023

Objective:

Using the African Neuropsychology Battery (ANB), we seek to develop normative data by examining the demographic effects for two learning process scores: initial learning (Trial One) and learning ratio (LR, the percentage of items learned relative of to-be-learned material following Trial 1).

Methods:

Healthy participants from the Democratic Republic of Congo completed the four memory tests of the ANB: the African Story Memory Test (ASMT), African List Memory Test (ALMT), African Visuospatial Memory Test (AVMT), and African Contextual Visuospatial Memory Test (ACVMT). We developed indices of learning for each subtest, as well as aggregate learning indices for Trial 1 and LR, and composite indices examining verbal, visual, contextual, and noncontextual learning, and grand indices comprising all four subtests.

Results:

Trial 1 and LR scores each demonstrated acceptable intercorrelations across memory tests. We present normative data for Trial 1 and LR by age and education.

Conclusion:

These data provide normative standards for evaluating learning in Sub-Saharan Africa.
Characterizing the Role of Moisture and Smoke on the 2021 Santa Coloma de Queralt Pyroconvective Event Using WRF‐Fire
Authors: Eghdami Masih , Juliano Timothy W. , Jiménez Pedro A. , Kosovic Branko , Castellnou Marc , Kumar Rajesh , Vila‐Guerau de Arellano Jordi
Published: May 2023

Smoke from wildfires or burning biomass directly affects air quality and weather through modulating cloud microphysics and radiation. A simple wildfire emission coupling of black carbon (BC) and organic carbon (OC) with microphysics was implemented using the Weather Research and Forecasting model's fire module. A set of large‐eddy simulations inspired by unique surface and upper atmospheric observations from the 2021 Santa Coloma de Queralt Fire (Spain) were conducted to investigate the influence of background conditions and interactions between atmospheric and fire processes such as fire smoke, ambient moisture, and latent heat release on the formation and evolution of pyroconvective clouds. While the microphysical impact of BC and OC emissions on the dynamics of fire behavior is minimal on short time scales (<6 hr), their presence increased the cloud water content and decreased the rain rates in our case study. In our case study, atmospheric moisture played an important role in the formation and development of pyroconvective clouds, which in turn enhanced the surface winds (8%) and fire spread rate (25%). The influence of fuel moisture on the pyroconvective cloud formation is smaller when compared with the atmospheric moisture content. A better representation of cloud processes can improve the mesoscale forecasts, which is important for better fire behavior modeling.
Agrivoltaics in Color: Going From Light Spectra to Biomass
Authors: Katul Gabriel G.
Published: May 2023

Agrivoltaics (AV), conceived in the early 1980s, promise to ameliorate competition between solar energy generation and crop production for arable land. The premise behind AV is that excess light not used in photosynthesis can be used for energy production. There are opportunities for maximizing photosynthesis by targeting particular wavelengths (e.g., red) to be transmitted through semi‐transparent photovoltaic (PV) cells depending on crop type and environmental conditions. Camporese and Abou Najm (2022, https://doi.org/10.1029/2022EF002900) developed a numerical model that accommodates the various wavelengths of the incoming light spectrum to predict photosynthesis, stomatal conductance, and transpiration. This commentary seeks to place those and other recent findings about the modifications to the plant micro‐environment by PV cells in the context of maximum attainable aboveground biomass.
Eavesdropping on the Vibrations of Earth’s Magnetic Bubble
Authors: Martin-Jones Erin
Published: May 2023

A NASA-funded crowdsourced science project has converted the unheard sounds resonating inside Earth’s magnetic shield into audible tracks, revealing an orchestra of whistles, wooshes, and chirps.