bluuebunny/crossref_metadata_2025 huggingface dataset:
Prebiotic inulin ameliorates SARS-CoV-2 infection in hamsters by modulating the gut microbiome
Authors: Song Isaiah , Yang Jiayue , Saito Misa , Hartanto Tenagy , Nakayama Yasunori , Ichinohe Takeshi , Fukuda Shinji
Published: March 2024

Current treatment options for COVID-19 are limited, with many antivirals and immunomodulators restricted to the most severe cases and preventative care limited to vaccination. As the SARS-CoV-2 virus and its increasing variants threaten to become a permanent fixture of our lives, this new reality necessitates the development of cost-effective and accessible treatment options for COVID-19. Studies have shown that there are correlations between the gut microbiome and severity of COVID-19, especially with regards to production of physiologically beneficial short-chain fatty acids (SCFAs) by gut microbes. In this study, we used a Syrian hamster model to study how dietary consumption of the prebiotic inulin affected morbidity and mortality resulting from SARS-CoV-2 infection. After two weeks of observation, we discovered that inulin supplementation attenuated morbid weight loss and increased survival rate in hamster subjects. An analysis of microbiome community structure showed significant alterations in 15 genera. Notably, there were also small increases in fecal DCA and a significant increase in serum DCA, perhaps highlighting a role for this secondary bile acid in conferring protection against SARS-CoV-2. In light of these results, inulin and other prebiotics are promising targets for future investigation as preventative treatment options for COVID-19.
Strategies for mitigating challenges associated with trace organic compound removal by high-retention membrane bioreactors (HR-MBRs)
Authors: Mahlangu Oranso T. , Nkambule Thabo I. , Mamba Bhekie B. , Hai Faisal I.
Published: March 2024

Due to the limitations of conventional ultrafiltration/microfiltration-based membrane bioreactors (UF/MF-MBRs) in removing trace organic compounds (TrOCs), the concept of high-retention membrane bioreactors (HR-MBRs) was introduced. Despite the benefits, HR-MBRs still suffer several drawbacks. Therefore, this paper critically reviews the effectiveness and feasibility of the proposed strategies to alleviate fouling, salinity build-up and incomplete biodegradation of TrOCs during wastewater treatment by HR-MBRs. The severity of each challenge is compared amongst the various configurations together with the associated capital and operational expenditure to determine the most cost-effective set-up. Guidance is provided on strategies and/or lessons that could be adopted from well-established processes used at municipal scale. Chemical cleaning as mitigation for fouling degrades membranes leading to poor TrOCs removal, while pre-treatment and membrane surface modification increase operational expenditure (OpEX). However, there are other environmentally-friendly pretreatment and cleaning options which hold great potential for future application. These options such as advanced oxidation processes (AOPs) are critically discussed in this work. Further, in-depth discussion is made on the pros and cons of the various approaches (such as frequent sludge withdrawal, intermittent UF/MF filtration and using organic salts) to alleviate salt build-up. Finally, incomplete biodegradation of rejected TrOCs in the bioreactor transfers problems of toxic pollutants from wastewater treatment to sludge management. Herein mitigation strategies including using stronger biological agents and coupling HR-MBRs with other techniques are debated. Despite the challenges, HR-MBRs are a promising solution for clean water production from TrOCs impaired wastewater. Therefore, more research is needed to improve the performance of HR-MBRs.
Ion solvation kinetics in bipolar membranes and at electrolyte–metal interfaces
Authors: Rodellar Carlos G. , Gisbert-Gonzalez José M. , Sarabia Francisco , Roldan Cuenya Beatriz , Oener Sebastian Z.
Published: March 2024

Ion (de)solvation at solid–electrolyte interfaces is pivotal for energy and chemical conversion technology, such as (electro)catalysis, batteries and bipolar membranes. For example, during the electrocatalytic hydrogen evolution reaction in alkaline media, water needs to be dissociated and hydroxide ions solvated—a process that is not well understood. Here we study water dissociation and ion solvation kinetics in isolation at polymeric bipolar membrane and electrolyte–metal interfaces. We discover bias-dependent relationships between the activation entropy and enthalpy, which we link to a bias-dependent dispersion of interfacial capacitance. Furthermore, our results indicate that OH− solvation is kinetically slower than H+ solvation and that the solvation kinetics display characteristics that are independent of the catalyst structure. We attribute this to a universal amount of excess charge needed to induce electric fields that alter the interfacial entropy of water. Of fundamental interest, these results are critical to enable knowledge-driven bipolar membrane and electrocatalyst design.
Design, synthesis and in vitro anticancer activity of some new lomefloxacin derivatives
Authors: Adly Mina E. , Gedawy Ehab M. , El-Malah Afaf A. , Khalil Omneya M.
Published: March 2024

Our main goal was to design and synthesize novel lomefloxacin derivatives that inhibit the topoisomerase II enzyme, leading to potent anticancer activity. Lomefloxacin derivatives substituted at position 3 and 7 were synthesized and screened for cytotoxic activity utilizing 60 different human cancer cell lines. Furthermore, compounds 3a,b,c,e that revealed potent broad-spectrum anticancer activity (with mean percent GI more than 47%) were further evaluated using five dose concentrations and calculating the GI50. Compound 3e was then evaluated for cell cycle analysis and demonstrated cell cycle arrest at the G2-M phase. Moreover, the mechanism of action was determined by determining the topoisomerase inhibitory activity and the molecular modeling study. Compounds 3a,b,c,e showed broad spectrum anticancer activity. Lomefloxacin derivative 5f showed selective cytotoxic activity against melanoma SK-MEL-5 cell line. Compound 3e demonstrated comparable topoisomerase II inhibition to doxorubicin with IC50 of 0.98 µM.
DIEANet: an attention model for histopathological image grading of lung adenocarcinoma based on dimensional information embedding
Authors: Wang Zexin , Gao Jing , Li Min , Zuo Enguang , Chen Chen , Chen Cheng , Liang Fei , Lv Xiaoyi , Ma Yuhua
Published: March 2024

Efficient and rapid auxiliary diagnosis of different grades of lung adenocarcinoma is conducive to helping doctors accelerate individualized diagnosis and treatment processes, thus improving patient prognosis. Currently, there is often a problem of large intra-class differences and small inter-class differences between pathological images of lung adenocarcinoma tissues under different grades. If attention mechanisms such as Coordinate Attention (CA) are directly used for lung adenocarcinoma grading tasks, it is prone to excessive compression of feature information and overlooking the issue of information dependency within the same dimension. Therefore, we propose a Dimension Information Embedding Attention Network (DIEANet) for the task of lung adenocarcinoma grading. Specifically, we combine different pooling methods to automatically select local regions of key growth patterns such as lung adenocarcinoma cells, enhancing the model's focus on local information. Additionally, we employ an interactive fusion approach to concentrate feature information within the same dimension and across dimensions, thereby improving model performance. Extensive experiments have shown that under the condition of maintaining equal computational expenses, the accuracy of DIEANet with ResNet34 as the backbone reaches 88.19%, with an AUC of 96.61%, MCC of 81.71%, and Kappa of 81.16%. Compared to seven other attention mechanisms, it achieves state-of-the-art objective metrics. Additionally, it aligns more closely with the visual attention of pathology experts under subjective visual assessment.
Acting pre-emptively reduces the long-term costs of managing herbicide resistance
Authors: Varah Alexa , Ahodo Kwadjo , Childs Dylan Z. , Comont David , Crook Laura , Freckleton Robert P. , Goodsell Rob , Hicks Helen L. , Hull Richard , Neve Paul , Norris Ken
Published: March 2024

Globally, pesticides improve crop yields but at great environmental cost, and their overuse has caused resistance. This incurs large financial and production losses but, despite this, very diversified farm management that might delay or prevent resistance is uncommon in intensive farming. We asked farmers to design more diversified cropping strategies aimed at controlling herbicide resistance, and estimated resulting weed densities, profits, and yields compared to prevailing practice. Where resistance is low, it is financially viable to diversify pre-emptively; however, once resistance is high, there are financial and production disincentives to adopting diverse rotations. It is therefore as important to manage resistance before it becomes widespread as it is to control it once present. The diverse rotations targeting high resistance used increased herbicide application frequency and volume, contributing to these rotations’ lack of financial viability, and raising concerns about glyphosate resistance. Governments should encourage adoption of diverse rotations in areas without resistance. Where resistance is present, governments may wish to incentivise crop diversification despite the drop in wheat production as it is likely to bring environmental co-benefits. Our research suggests we need long-term, proactive, food security planning and more integrated policy-making across farming, environment, and health arenas.
A novel solution to optimal power flow problems using composite differential evolution integrating effective constrained handling techniques
Authors: Ali Aamir , Hassan Ali , Keerio M. U. , Mugheri Noor H. , Abbas Ghulam , Hatatah Mohammed , Touti Ezzeddine , Yousef Amr
Published: March 2024

Optimal power flow is a complex and highly non-linear problem in which steady-state parameters are needed to find a network’s efficient and economical operation. In addition, the difficulty of the Optimal power flow problem becomes enlarged when new constraints are added, and it is also a challenging task for the power system operator to solve the constrained Optimal power flow problems efficiently. Therefore, this paper presents a constrained composite differential evolution optimization algorithm to search for the optimum solution to Optimal power flow problems. In the last few decades, numerous evolutionary algorithm implementations have emerged due to their superiority in solving Optimal power flow problems while considering various objectives such as cost, emission, power loss, etc. evolutionary algorithms effectively explore the solution space unconstrainedly, often employing the static penalty function approach to address the constraints and find solutions for constrained Optimal power flow problems. It is a drawback that combining evolutionary algorithms and the penalty function approach requires several penalty parameters to search the feasible space and discard the infeasible solutions. The proposed a constrained composite differential evolution algorithm combines two effective constraint handling techniques, such as feasibility rule and ɛ constraint methods, to search in the feasible space. The proposed approaches are recognized on IEEE 30, 57, and 118-bus standard test systems considering 16 study events of single and multi-objective optimization functions. Ultimately, simulation results are examined and compared with the many recently published techniques of Optimal power flow solutions owing to show the usefulness and performance of the proposed a constrained composite differential evolution algorithm.
Benchmarking long-read aligners and SV callers for structural variation detection in Oxford nanopore sequencing data
Authors: Helal Asmaa A. , Saad Bishoy T. , Saad Mina T. , Mosaad Gamal S. , Aboshanab Khaled M.
Published: March 2024

Structural variants (SVs) are one of the significant types of DNA mutations and are typically defined as larger-than-50-bp genomic alterations that include insertions, deletions, duplications, inversions, and translocations. These modifications can profoundly impact the phenotypic characteristics and contribute to disorders like cancer, response to treatment, and infections. Four long-read aligners and five SV callers have been evaluated using three Oxford Nanopore NGS human genome datasets in terms of precision, recall, and F1-score statistical metrics, depth of coverage, and speed of analysis. The best SV caller regarding recall, precision, and F1-score when matched with different aligners at different coverage levels tend to vary depending on the dataset and the specific SV types being analyzed. However, based on our findings, Sniffles and CuteSV tend to perform well across different aligners and coverage levels, followed by SVIM, PBSV, and SVDSS in the last place. The CuteSV caller has the highest average F1-score (82.51%) and recall (78.50%), and Sniffles has the highest average precision value (94.33%). Minimap2 as an aligner and Sniffles as an SV caller act as a strong base for the pipeline of SV calling because of their high speed and reasonable accomplishment. PBSV has a lower average F1-score, precision, and recall and may generate more false positives and overlook some actual SVs. Our results are valuable in the comprehensive evaluation of popular SV callers and aligners as they provide insight into the performance of several long-read aligners and SV callers and serve as a reference for researchers in selecting the most suitable tools for SV detection.
Geologically-constrained GANomaly network for mineral prospectivity mapping through frequency domain training data
Authors: Sabbaghi Hamid , Tabatabaei Seyed Hassan , Fathianpour Nader
Published: March 2024

Generative adversarial networks (GAN) and various deep autoencoders have been frequently executed to recognize multi-element geochemical anomalies linked to different ore resources in recent decade. Efficient recognition of multi-element geochemical anomaly patterns is a significant issue in mineral exploration targeting. Traditional procedures have not sufficient capability to perform efficient pattern recognition. While, deep learning algorithms as influential subset of machine learning algorithms can present magnificent conclusions in classification and pattern recognition. Because those have robust ability in extracting high-level features of complex inputs. Although, many deep learning algorithms were used to recognize geochemical anomalies but the GANs have demonstrated specific dignity in recognizing multi-element geochemical anomaly patterns. But, these frameworks should be constrained to learn geological knowledge and yield reasonable potential maps. In this regard, a novel geologically-constrained GANomaly was trained with frequency domain training data to recognize multi-element geochemical anomalies. Application of the geologically-constrained GANomaly network with considering mineral system parameters of the Au–Cu mineralization in the Feyzabad district, NE Iran was eventuated to suitable results. The success-rate curves demonstrated that produced map of frequency domain geochemical data has traced 86.68% Au–Cu occurrences via 30% corresponded area while produced map of spatial domain geochemical data has traced 80.13% Au–Cu occurrences via 30% corresponded area.
Prognostic model revealing pyroptosis-related signatures in oral squamous cell carcinoma based on bioinformatics analysis
Authors: Qi Lu , Tang Zhangui
Published: March 2024

One of the most common oral carcinomas is oral squamous cell carcinoma (OSCC), bringing a heavy burden to global health. Although progresses have been made in the intervention of OSCC, 5 years survival of patients suffering from OSCC is poor like before regarding to the high invasiveness of OSCC, which causes metastasis and recurrence of the tumor. The relationship between pyroptosis and OSCC remains to be further investigated as pyroptosis in carcinomas has gained much attention. Herein, the key pyroptosis-related genes were identified according to The Cancer Genome Atlas (TCGA) dataset. Additionally, a prognostic model was constructed based upon three key genes (CTLA4, CD5, and IL12RB2) through least absolute shrinkage and selection operator (LASSO) analyses, as well as univariate and multivariate COX regression in OSCC. It was discovered that the high expression of these three genes was associated with the low-risk group. We also identified LAIR2 as a hub gene, whose expression negatively correlated with the risk score and the different immune cell infiltration. Finally, we proved that these three genes were independent prognostic factors linked to overall survival (OS), and reliable consequences could be predicted by this model. Our study revealed the relationship between pyroptosis and OSCC, providing insights into new treatment targets for preventing and treating OSCC.
A 17-level quadruple boost switched-capacitor inverter with reduced devices and limited charge current
Authors: Hosseinpour Majid , Derakhshandeh Masoumeh , Seifi Ali , Shahparasti Mahdi
Published: March 2024

In this paper, a quadruple boost switched-capacitor multi-level inverter is proposed. The proposed structure utilizes a DC source, 11 switches, and a diode to achieve 17-level output voltage levels. This structure consists of three capacitors with the ability for self-balancing voltages. The capacitors achieve automatic voltage balancing through a series/parallel connection with the input voltage source. To control the switching pulses of the switches, level-shifted pulse width modulation (LS-PWM) strategy has been employed. A comparative evaluation has been performed between the proposed structure and structures presented in recent articles, considering various parameters such as voltage gain, number of DC sources, number of semiconductor devices, maximum blocking voltage (MBV), and total standing voltage (TSV). Considering this comparison, the lower number of semiconductor devices for generating a 17-level output with suitable voltage gain, and especially the cost-effectiveness of the structure, are the main advantages of the proposed configuration. In addition, a soft charging method has been employed to limit the inrush current of capacitors. Moreover, the power losses of the proposed structure have been investigated, indicating its acceptable efficiency. Finally, for the analysis and validation of the proposed structure's performance, an experimental prototype has been implemented and evaluated under various conditions. The results indicate satisfactory performance of the proposed structure under various stable and dynamic operating conditions.
A fast-flexible strategy based approach to solving employee scheduling problem considering soft work time
Authors: Ma Kangxin , Yang Changchun , Xu Haojie , Lv Hexin , Hong Feng
Published: March 2024

Employee scheduling aims to assign employees to shifts to satisfy daily workload and constraints. Some employee scheduling problems and their variants have been proven NP-hard, and a series of works have been done. However, the existing algorithms consider the fixed work time, which may cause plenty of overstaffing and understaffing phenomenons. Hence, this paper proposes a fast-flexible strategy based approach (FFS) to solve it. FFS introduces the idea of soft work time, which allows the work time of employees can be adjusted in a range. Based on this, we set the flextime strategy to decide the specific work time of each employee every day. Besides, FFS adopts a pairwise-allocated strategy and proficiency average matrix to boost its efficiency and effectiveness. Finally, the extensive experimental evaluation shows that FFS is more effective and efficient than the baselines for solving the employee scheduling problem considering soft work time.
Changing of mechanical property and bearing capacity of strongly chlorine saline soil under freeze-thaw cycles
Authors: Ding Shijun , Li Shaomin , Kong Sen , Li Qiuyang , Yang Taohui , Nie Zhibao , Zhao Gaowen
Published: March 2024

Freeze-thaw cycles and compactness are two critical factors that significantly affect the engineering properties and safety of building foundations, especially in seasonally frozen regions. This paper investigated the effects of freeze-thaw cycles on the shear strength of naturally strongly chlorine saline soil with the compactness of 85%, 90% and 95%. Three soil samples with different compactness were made. Size and mass changes were measured and recorded during freeze-thaw cycles. Shear strength under different vertical pressures was determined by direct shear tests, and the cohesion and friction angle were measured and discussed. Microstructure characteristic changes of saline soil samples were observed using scanning electron microscopy under different freeze-thaw cycles. Furthermore, numerical software was used to calculate the subsoil-bearing capacity and settlement of the electric tower foundation in the Qarhan Salt Lake region under different freeze-thaw cycles. Results show that the low-density soil shows thaw settlement deformation, but the high-density soil shows frost-heaving deformation with the increase in freeze-thaw cycles. The shear strength of the soil samples first increases and then decreases with the increase in freeze-thaw cycles. After 30 freeze-thaw cycles, the friction angle of soil samples is 28.3%, 29.2% and 29.6% lower than the soil samples without freeze-thaw cycle, the cohesion of soil samples is 71.4%, 60.1% and 54.4% lower than the samples without freeze-thaw cycle, and the cohesion and friction angle of soil samples with different compactness are close to each other. Microstructural changes indicate that the freeze-thaw cycle leads to the breakage of coarse particles and the aggregation of fine particles. Correspondingly, the structure type of soil changes from a granular stacked structure to a cemented-aggregated system. Besides, the quality loss of soil samples is at about 2% during the freeze-thaw cycles. Results suggest that there may be an optimal compactness between 90 and 95%, on the premise of meeting the design requirements and economic benefits. This study can provide theoretical guidance for foundation engineering constructions in seasonally frozen regions.
Skillful prediction of length of day one year ahead in multiple decadal prediction systems
Authors: Yoon Hyunsuk , Choi Jung , Son Seok-Woo , Scaife Adam A.
Published: March 2024

Despite a small amplitude, Length of Day (LOD) change, which varies from one year to another due to changes in Atmospheric Angular Momentum (AAM), determines the accuracy of Global Positioning System (GPS) time calculation. In this study, we examine the prediction skill of LOD and AAM in nine decadal prediction systems archived for the Decadal Climate Prediction Project. A persistence and rebound in LOD prediction skill at one year or longer lead time is found in most models. A poleward propagation of AAM anomaly via wave-mean flow interaction is also qualitatively well reproduced. This long-lead prediction of LOD and AAM is attributed to reliable predictions of the El Niño–Southern Oscillation (ENSO) and the Quasi-Biennial Oscillation (QBO), the former being more systematically related than the latter. This result indicates that the improved ENSO prediction and atmospheric wave-mean flow interaction may lead to better prediction of LOD, AAM and related extratropical climate in the decadal prediction systems.
Informing immunotherapy with multi-omics driven machine learning
Authors: Li Yawei , Wu Xin , Fang Deyu , Luo Yuan
Published: March 2024

Progress in sequencing technologies and clinical experiments has revolutionized immunotherapy on solid and hematologic malignancies. However, the benefits of immunotherapy are limited to specific patient subsets, posing challenges for broader application. To improve its effectiveness, identifying biomarkers that can predict patient response is crucial. Machine learning (ML) play a pivotal role in harnessing multi-omic cancer datasets and unlocking new insights into immunotherapy. This review provides an overview of cutting-edge ML models applied in omics data for immunotherapy analysis, including immunotherapy response prediction and immunotherapy-relevant tumor microenvironment identification. We elucidate how ML leverages diverse data types to identify significant biomarkers, enhance our understanding of immunotherapy mechanisms, and optimize decision-making process. Additionally, we discuss current limitations and challenges of ML in this rapidly evolving field. Finally, we outline future directions aimed at overcoming these barriers and improving the efficiency of ML in immunotherapy research.
An optrode array for spatiotemporally-precise large-scale optogenetic stimulation of deep cortical layers in non-human primates
Authors: Clark Andrew M. , Ingold Alexander , Reiche Christopher F. , Cundy Donald , Balsor Justin L. , Federer Frederick , McAlinden Niall , Cheng Yunzhou , Rolston John D. , Rieth Loren , Dawson Martin D. , Mathieson Keith , Blair Steve , Angelucci Alessandra
Published: March 2024

Optogenetics has transformed studies of neural circuit function, but remains challenging to apply to non-human primates (NHPs). A major challenge is delivering intense, spatiotemporally-precise, patterned photostimulation across large volumes in deep tissue. Such stimulation is critical, for example, to modulate selectively deep-layer corticocortical feedback circuits. To address this need, we have developed the Utah Optrode Array (UOA), a 10×10 glass needle waveguide array fabricated atop a novel opaque optical interposer, and bonded to an electrically addressable µLED array. In vivo experiments with the UOA demonstrated large-scale, spatiotemporally precise, activation of deep circuits in NHP cortex. Specifically, the UOA permitted both focal (confined to single layers/columns), and widespread (multiple layers/columns) optogenetic activation of deep layer neurons, as assessed with multi-channel laminar electrode arrays, simply by varying the number of activated µLEDs and/or the irradiance. Thus, the UOA represents a powerful optoelectronic device for targeted manipulation of deep-layer circuits in NHP models.
A neural network-based model framework for cell-fate decisions and development
Authors: Paczkó Mátyás , Vörös Dániel , Szabó Péter , Jékely Gáspár , Szathmáry Eörs , Szilágyi András
Published: March 2024

Gene regulatory networks (GRNs) fulfill the essential function of maintaining the stability of cellular differentiation states by sustaining lineage-specific gene expression, while driving the progression of development. However, accounting for the relative stability of intermediate differentiation stages and their divergent trajectories remains a major challenge for models of developmental biology. Here, we develop an empirical data-based associative GRN model (AGRN) in which regulatory networks store multilineage stage-specific gene expression profiles as associative memory patterns. These networks are capable of responding to multiple instructive signals and, depending on signal timing and identity, can dynamically drive the differentiation of multipotent cells toward different cell state attractors. The AGRN dynamics can thus generate diverse lineage-committed cell populations in a robust yet flexible manner, providing an attractor-based explanation for signal-driven cell fate decisions during differentiation and offering a readily generalizable modelling tool that can be applied to a wide variety of cell specification systems.
Glutamine suppresses senescence and promotes autophagy through glycolysis inhibition-mediated AMPKα lactylation in intervertebral disc degeneration
Authors: Zhang Yangyang , Huang Zhengqi , Han Weitao , Wu Jiajun , Li Shuangxing , Qin Tianyu , Zhang Chao , Shi Ming , Han Shun , Gao Bo , Jin Song , Xiao Yin , Xu Kang , Ye Wei
Published: March 2024

Regulating metabolic disorders has become a promising focus in treating intervertebral disc degeneration (IDD). A few drugs regulating metabolism, such as atorvastatin, metformin, and melatonin, show positive effects in treating IDD. Glutamine participates in multiple metabolic processes, including glutaminolysis and glycolysis; however, its impact on IDD is unclear. The current study reveals that glutamine levels are decreased in severely degenerated human nucleus pulposus (NP) tissues and aging Sprague-Dawley (SD) rat nucleus pulposus tissues, while lactate accumulation and lactylation are increased. Supplementary glutamine suppresses glycolysis and reduces lactate production, which downregulates adenosine-5’-monophosphate-activated protein kinase α (AMPKα) lactylation and upregulates AMPKα phosphorylation. Moreover, glutamine treatment reduces NP cell senescence and enhances autophagy and matrix synthesis via inhibition of glycolysis and AMPK lactylation, and glycolysis inhibition suppresses lactylation. Our results indicate that glutamine could prevent IDD by glycolysis inhibition-decreased AMPKα lactylation, which promotes autophagy and suppresses NP cell senescence.
The future is local? Contextualizing municipal agendas on climate change in Chile
Authors: Lehmann Rosa , Irigoyen Rios Alejandra
Published: March 2024

Social science literature on the political strategies used to mitigate and adapt to climate change has discussed the possibilities of local administrations and the multifaceted obstacles in their path. This case study looks at Chile, where debates about local climate agendas and policies have gained political relevance in recent years. It considers municipal administrations, with a focus on their agendas and the (potential) challenges they face. Building on the evaluation of literature, policy documents, and semi-structured interviews, the study concludes that local administrations have gained leeway for action due to changes in national regulation and integration into wider networks, but tight budgets for dedicated climate policies persist. The governance structures in which local climate agendas are embedded, as well as contextual constraints, reflect Chile’s institutional and neoliberal politeconomic arrangements.
Emerging lead-free all inorganic perovskite single crystals K7Bi3X16 (X = Cl, Br) toward photodetector application
Authors: Yang Wenjian , Zhang Jingshen , Xiong Hui , Lan Jing , Yuan Songyang , Zhan Mengdi , Tan Ziyu , Li Wenzhe , Fan Jiandong
Published: March 2024

Lead-free inorganic perovskites have attracted intensive attention in the field of photodetectors owing to their high stability, non-toxicity, and remarkable photoelectric characteristics.
Thermodynamics of the Eu(iii)–Mg–SO4–H2O and Eu(iii)–Na–SO4–H2O systems. Part I: solubility experiments and the full dissociation Pitzer model
Authors: dos Santos P. F. , Lassin A. , Gaona X. , Garbev K. , Altmaier M. , Madé B.
Published: March 2024

A thermodynamic description of complex sulfate systems of relevance for nuclear waste disposal is provided. A full dissociation Pitzer model is derived for the system Eu(iii)–Mg/Na–SO4–H2O based on solubility experiments and comprehensive solid phase characterization.
Towards standardized grid emission factors: methodological insights and best practices
Authors: Schäfer Malte , Cerdas Felipe , Herrmann Christoph
Published: March 2024

Grid emission factors from official sources vary. Nine relevant aspects were identified and their influence quantified. The recommended set of aspects best represents emissions from grid electricity consumption.
Effects of quercetin on the DNA methylation pattern in tumor therapy: an updated review
Authors: Wang Qin , Ma Chen , Wang Nan , Mao Huixian
Published: March 2024

Quercetin reverses the expression of abnormal genes by regulating DNA methylation, and is an important regulator of gene transcription in tumorigenesis. The use of nanoscale delivery of quercetin increases its bioavailability in cancer therapy.
Ameliorative effect of bound polyphenols in mung bean coat dietary fiber on DSS-induced ulcerative colitis in mice: the intestinal barrier and intestinal flora
Authors: Ao Tianxiang , Huang Hairong , Zheng Bing , Chen Yi , Xie Jianhua , Hu Xiaobo , Yu Qiang
Published: March 2024

Bound polyphenols in mung bean coat dietary fiber alleviate ulcerative colitis in mice by protecting intestinal barrier and regulating intestinal flora.
The role of PAT in the development of telescoped continuous flow processes
Authors: Kearney Aoife M. , Collins Stuart G. , Maguire Anita R.
Published: March 2024

This review highlights the advantages of incorporating Process Analytical Technologies into continuous flow processes, especially in the context of telescoped multistep flow sequences.
Mn2+-induced structural flexibility enhances the entire catalytic cycle and the cleavage of mismatches in prokaryotic argonaute proteins
Authors: Zheng Lirong , Zhou Bingxin , Yang Yu , Zan Bing , Zhong Bozitao , Wu Banghao , Feng Yan , Liu Qian , Hong Liang
Published: March 2024

Prokaryotic Argonaute (pAgo) proteins, a class of DNA/RNA-guided programmable endonucleases, have been extensively utilized in nucleic acid-based biosensors.
Novel Mn–Bi–S hybrid mesoporous nanosheets as an efficient electrocatalyst for nitrogen reduction reaction
Authors: Ban Yining , Ma Zizai , Wan Zihao , Yuan Hefeng , Wang Xiaoguang
Published: March 2024

A non-precious and efficient catalyst was developed to enhance N2 adsorption by electronic interaction and ideal synergistic effect to improve the NRR activity.
The future of self-driving laboratories: from human in the loop interactive AI to gamification
Authors: Hysmith Holland , Foadian Elham , Padhy Shakti P. , Kalinin Sergei V. , Moore Rob G. , Ovchinnikova Olga S. , Ahmadi Mahshid
Published: March 2024

Self-driving laboratories (SDLs) are the future for scientific discovery in a world growing with artificial intelligence. The interaction between scientists and automated instrumentation are leading conversations about the impact of SDLs on research.
Optimising the acid–base ratio of Mg–Al layered double oxides to enhance CO2 capture performance: the critical role of calcination conditions
Authors: Leung D. W. Justin , Laney Katherine R. , Kenyon Philip , Rees Nicholas H. , Buffet Jean-Charles , Chen Chunping , O'Hare Dermot
Published: March 2024

We investigated the impact of calcination conditions of layered double hydroxide on the formation of layered double oxides and its relationship with CO2 capture.
A fluorescence approach for an online measurement technique of atmospheric microplastics
Authors: Gratzl Jürgen , Seifried Teresa M. , Stolzenburg Dominik , Grothe Hinrich
Published: March 2024

The autofluorescence of airborne microplastics is detected online on a single particle level down to 500 nm particle size.
Fast access of the lattice thermal conductivity and phonon quasiparticle spectra of Mo2TiC2T2 (T = –O and –F) and Janus Mo2TiC2OF MXenes from machine learning potentials
Authors: Qiu Yiding , Jing Ziang , Liu Haoliang , He Huaxuan , Wu Kai , Cheng Yonghong , Xiao Bing
Published: March 2024

The presence of strong anharmonic effects in surface functionalized MXenes greatly challenges the use of harmonic lattice dynamics calculations to predict their phonon spectra and lattice thermal conductivity at finite temperatures.
Development of a H-bond donor–Lewis basic anion bifunctional organocatalyst for ring-opening polymerizations
Authors: Liu Bo , Kang Peng , Li Zhenjiang , Shi Na , Xin Qi , Liu Ziqi , Cai Tao , He Jun , Li Chunyu , Guo Kai
Published: March 2024

Squaramide–phenolate exemplified one-component H-bond donor–anion bifunctional catalyst for ring-opening polymerizations of various cyclic esters, where the Lewis basic phenolate activated initiator and the H-bond donor squaramide activated monomer.
Participation of electrochemically inserted protons in the hydrogen evolution reaction on tungsten oxides
Authors: Spencer Michael A. , Holzapfel Noah P. , You Kyung-Eun , Mpourmpakis Giannis , Augustyn Veronica
Published: March 2024

Tungsten oxides undergo a significant increase in their hydrogen evolution reaction activity upon proton-insertion coupled electron transfer.
On the origin of cooperativity effects in the formation of self-assembled molecular networks at the liquid/solid interface
Authors: Rinkovec Tamara , Kalebic Demian , Dehaen Wim , Whitelam Stephen , Harvey Jeremy N. , De Feyter Steven
Published: March 2024

By synergy of STM results and statistical thermodynamics, we provide a novel framework for free energy assessment of monolayer formation at the liquid/solid interface.
Cobalt- or rhodium-catalyzed synthesis of 1,2-dihydrophosphete oxides via C–H activation and formal phosphoryl migration
Authors: Xu Shengbo , Mi Ruijie , Zheng Guangfan , Li Xingwei
Published: March 2024

1,2-Dihydrophosphete oxides have been accessed in excellent yields via the merger of metal-catalyzed C–H bond activation and formal 1,2-migration of a phosphoryl group.
Multinuclear systems for photo-induced production of green fuels: an overview of homogeneous catalysts based on transition metals
Authors: Amadeo Alessandro , La Mazza Emanuele , Arrigo Antonino , La Ganga Giuseppina , Cancelliere Ambra M.
Published: March 2024

Schematic representation of light-induced processes in artificial photosinthetic systems composed by multinuclear metal complexes.
In silico design of misfolding resistant proteins: the role of structural similarity of a competing conformational ensemble in the optimization of frustration
Authors: Saikia Bondeepa , Baruah Anupaul
Published: March 2024

The degree of similarity of the non-native conformations to the target plays a prominent role in designing misfolding resistant protein sequences.
Why we need to decolonize the biosciences curriculum
Authors: Joshi Lovleen Tina , Mansfield Catherine , Ting Isaiah J. , Hubbard Katharine
Published: March 2024

Bioscience has a history linked to exploitation, colonialism and marginalization. Biology has been dominated by white European perspectives, and pseudoscientific ‘biological’ arguments have been used to justify discrimination and oppression, particularly on the basis of disability and ethnicity. Addressing this legacy within bioscience education is challenging, particularly as many bioscientists are unaware of this history and its on-going influence on the discipline. In this article, we explore what decolonization of the curriculum means within the context of bioscience. To demystify terminology for those new to the subject, we first consider the differences between diversification and decolonization. We then explore the historical connections between colonial activity and bioscience, including scientific racism, bioprospecting and eugenics. Additionally, we highlight where white western biases are still present in bioscience, from the dominance of European samples in genomic studies to the lack of Black and Asian academics in UK bioscience. Multiple barriers to decolonization are also considered, from individual lack of knowledge to structural and societal issues. We call on bioscience educators to actively decolonize their curricula, ensuring the discipline is presented in its appropriate historical and cultural context and is inclusive for all.
Improved Complex Convolutional Neural Network Based on SPIRiT and Dense Connection for Parallel MRI Reconstruction
Authors: Duan Jizhong , Ren Xinmin
Published: March 2024

To accelerate the data acquisition speed of magnetic resonance imaging (MRI) and improve the reconstructed MR images’ quality, we propose a parallel MRI reconstruction model (SPIRiT‐Net), which combines the iterative self‐consistent parallel imaging reconstruction model (SPIRiT) with the cascaded complex convolutional neural networks (CCNNs). More specifically, this model adopts the SPIRiT model for reconstruction in the k‐space domain and the cascaded CCNNs with dense connection for reconstruction in the image domain. Meanwhile, this model introduces the data consistency layers for better reconstruction in both the image domain and the k‐space domain. The experimental results on two clinical knee datasets as well as the fastMRI brain dataset under different undersampling patterns show that the SPIRiT‐Net model achieves better reconstruction performance in terms of visual effect, peak signal‐to‐noise ratio, and structural similarity over SPIRiT, Deepcomplex, and DONet. It will be beneficial to the diagnosis of clinical medicine.
Microscopic bell-shape nonlocality: The case of proton scattering off 40Ca at 200 MeV
Authors: Blanchon Guillaume , Arellano Hugo F.
Published: March 2024

This work is part of an ongoing effort to build microscopicallydriven nonlocal optical potentials easily tracktable in scattering codes. Based on the separable ‘JνH’ structure proposed recently [1], where the potential can be cast as the product of a radial and nonlocality form factors, we investigate its angular dependence in momentum space. We find that scattering observables have a weak angular dependence between the momentum transfer q = k − k′, and K = (k + k′)/2. The study is focussed on proton elastic scattering off 40Ca at 200 MeV, where the JνH structure is found to be inadequate. We conclude that any improvement of the JνH structure of the potential can be made to the lowest order in multipole expansions in Kq−representation of the potential.
The multichannel experimental and theoretical study of the 12C(18O,18F)12B single charge exchange reaction mechanism
Authors: Spatafora Alessandro , Carbone Diana , Cappuzzello Francesco , Cavallaro Manuela , Acosta Luis E. , Agodi Clementina , Amador-Valenzuela Paulina , Borello-Lewin Thereza , Brischetto Giuseppe A. , Calvo Daniela , Chávez-Lomelí Efrain R. , Ciraldo Irene , De Gregorio Giovanni , Delaunay Franck , Djapo Haris , Eke Canel , Finocchiaro Paolo , Firat Suna , Fisichella Maria , Gargano Angela , Hacisalihoglu Aylin , Lay Josè A. , Linares Roberto , Lubian Jesus , Medina Nilberto , Moralles Maurício , Oliveira Josè R.B. , Pakou Athena , Pandola Luciano , Petrascu Horia , Sgouros Onoufrios , da Silveira Marcilei A.G. , Solakci Selçuk O. , Soukeras Vasilis , Souliotis George A. , Torresi Domenico , Tudisco Salvatore , Yıldırım Aydın , Zagatto Vinicius A.B.
Published: March 2024

The study of a network of nuclear reactions populated in the 18O + 12C collision is the main topic of the present paper. It was performed to test nuclear structure and reaction theories in describing the full reaction mechanism occurring in the (18O, 18F) single charge exchange nuclear reaction. From the experimental side, an 18O beam was produced at 275 MeV incident energy by the K800 superconducting cyclotron and the MAGNEX magnetic spectrometer was used at the Laboratori Nazionali del Sud of the Istituto Nazionale di Fisica Nucleare to momentum analyse the ejectiles produced in the nuclear reactions within the same experimental setup. From the theoretical side, the proposed approach consists of analysing the whole network of nuclear reactions in the framework of a unique comprehensive and coherent theoretical calculation. This holistic approach, applied both to the experimental and theoretical analysis, is the main feature and novelty of the work presented here.
Understanding heavy-ion fusion cross section data using novel artificial intelligence approaches
Authors: Dell’Aquila Daniele , Gnoffo Brunilde , Lombardo Ivano , Redigolo Luigi , Porto Francesco , Russo Marco
Published: March 2024

We modeled an unprecedentedly large dataset of complete fusion cross section data using a novel artificial intelligence approach. Our analysis aims especially to unveil, in a data-driven way, nuclear structure effects on the fusion between heavy ions and to suggest a universal formula capable to describe all previously available data. The study focused on light-to-mediummass nuclei, where incomplete fusion phenomena are more difficult to occur and less likely to contaminate the data. The method used to derive the models exploits a state-of-the-art hybridization of genetic programming and artificial neural networks and is capable to derive an analytical expression that serves to predict integrated cross section values. For the first time, we analyzed a comprehensive set of nuclear variables, including quantities related to the nuclear structure of projectile and target. In this manuscript, we describe the derivation of two computationally simple models that can satisfactorily describe, with a reduced number of variables and only a few parameters, a large variety of lightto- intermediate-mass collision systems in an energy domain ranging approximately from the Coulomb barrier to the oncet of multi-fragmentation phenomena. The underlying methods are particularly innovative and are of potential use for a broad domain of applications in the nuclear field.
Study of highly excited states in 16O with 3He+13C reactions at low energies
Authors: Lombardo Ivano , Dell’Aquila Daniele , Vigilante Mariano , Aytekin Mualla , Redigolo Luigi , Baldesi Lucia , Barlini Sandro , Camaiani Alberto , Casini Giovanni , Ciampi Caterina , Cicerchia Magda , Fabris Daniela , Frosin Catalin , Gramegna Fabiana , Marchi Tommaso , Ordine Antonio , Ottanelli Pietro , Pasquali Gabriele , Piantelli Silvia , Russo Marco , Stefanini Andrea , Valdre Simone , Verde Giuseppe
Published: March 2024

We report some preliminary experimental results on 13C(3He,α)12C reactions at low bombarding energies, in the range 1.4 – 2.2 MeV. The reconstruction of kinematic quantities in the final channel was performed by using a high-performance, low-threshold hodoscope, allowing for the particle identification even for low energy ejectiles. We succeeded in measuring detailed angular distributions, in absolute values, even for the transition leading to the emission of 12C in the Hoyle state, then resulting into 4 α particles in the final channel. The analysis of angular distributions as a function of energy suggests the occurrence of two low-spin resonant states, respectively with Jπ = 1− and 2+, at excitation energies of ≈ 24.1 and 24.5 MeV.
Photon energy dependence of photoneutron production from heavy targets
Authors: Nguyen Thuong T.H. , Sanami Toshiya , Yamazaki Hirohito , Lee Eunji , Sugihara Kenta , Itoga Toshiro , Kirihara Yoichi , Miyamoto Shuji , Hashimoto Satoshi , Asano Yoshihiro
Published: March 2024

The double differential cross-sections (DDXs) of photoneutron production via the photonuclear reaction on tantalum, tungsten, and bismuth for 13 and 17 MeV linearly polarized photon beams were measured using the time-of-flight method at the NewSUBARU-BL01 facility. Polarized photons were obtained by the Laser Compton backscattering (LCS) technique. Two distinct components were observed on the spectra: the lowenergy component up to 4 MeV and the high-energy above 4 MeV. The angular distribution of the low-energy component was isotropic, whereas the high-energy was distributed anisotropically and influenced by the angle between direction of photon polarization and neutron emission, especially for 17 MeV photon energy. These phenomena were similar to those of 197Au target observed in the previous studies. The low-energy neutron distributions at 13 and 17 MeV photon energies were almost identical for all three targets. The DDX energy integration was calculated and compared among the three targets for two-photon energies. Given the horizontal polarization (plane parallel to the x-axis) of the incident photons, the emission angles of 90° on the x-axis and y-axis recorded the maximum and minimum photoneutron yield, respectively. The differences between these two positions were minor for 181Ta and natW at 13 MeV photon energy and noticeable for other cases. An underestimation of the TENDL nuclear data library was observed on the photoneutron DDXs compared to the experimental results for 181Ta and 209Bi.