bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi‐population artificial bee colony algorithm for many‐objective cascade reservoir scheduling
Authors: Wang Shuai , Wang Hui , Liao Futao , Wei Zichen , Hu Min 
Published: July 2024

SummaryArtificial bee colony (ABC) is a popular intelligent algorithm that is widely applied to many optimization problems. However, it is challenging for ABC to solve many‐objective optimization problems (MaOPs). To tackle this issue, this article proposes a many‐objective ABC based on multi‐population (called MMaOABC) for MaOPs. In MMaOABC, the population is divided into multiple sub‐populations, and each sub‐population optimizes one objective. Three search strategies are constructed based on multiple sub‐populations to improve convergence and diversity. In the employed bee stage, some excellent solutions in multiple sub‐populations are used to guide the convergence. In the onlooker bee stage, new selection probabilities based on diversity metrics are designed to enhance the diversity. Dimensional learning is introduced in the scout bee stage to avoid falling into local minimum. In addition, environmental selection and external archives are utilized for communications among sub‐populations. To validate the performance of MMaOABC, two benchmark sets (DTLZ and MaF) with 3, 5, 8, and 15 objectives are tested. Computational results show that MMaOABC is competitive when compared with seven other many‐objective evolutionary algorithms (MaOEAs). Finally, MMaOABC is applied to many‐objective cascade reservoir scheduling. Simulation results show that MMaOABC still obtains promising performance.
Photocatalytic Upcycling of Different Types of Plastic Wastes: A Mini Review
Authors: Deng Yuan , Chen Jinxing , Zhang Qiao , Cao Muhan 
Published: July 2024

AbstractWith the escalating demand and utilization of plastics, considerable attention has been given to controlling plastic pollution. Among these methodologies, photocatalytic upcycling of plastic has emerged as a promising method for plastic management due to its energy‐saving and eco‐friendly properties. In the past several years, great efforts have been devoted to the photocatalytic conversion of a variety of commercial plastic types. These encouraging endeavors foreshadow the continued progression and application in this field. In this review, recent advancements in the photocatalytic upcycling of plastics are reviewed. The fundamentals and principles of photocatalytic deconstruction of plastics are first introduced. Then, we summarize the works on the reforming of different types of plastic, including polyolefins, polyesters, and other types. Finally, some challenges and possible solutions are provided for the development of photocatalytic upcycling of plastics.
Model‐Informed Reinforcement Learning for Enabling Precision Dosing Via Adaptive Dosing
Authors: Tosca Elena Maria , De Carlo Alessandro , Ronchi Davide , Magni Paolo 
Published: July 2024

Precision dosing, the tailoring of drug doses to optimize therapeutic benefits and minimize risks in each patient, is essential for drugs with a narrow therapeutic window and severe adverse effects. Adaptive dosing strategies extend the precision dosing concept to time‐varying treatments which require sequential dose adjustments based on evolving patient conditions. Reinforcement learning (RL) naturally fits this paradigm: it perfectly mimics the sequential decision‐making process where clinicians adapt dose administration based on patient response and evolution monitoring. This paper aims to investigate the potentiality of coupling RL with population PK/PD models to develop precision dosing algorithms, reviewing the most relevant works in the field. Case studies in which PK/PD models were integrated within RL algorithms as simulation engine to predict consequences of any dosing action have been considered and discussed. They mainly concern propofol‐induced anesthesia, anticoagulant therapy with warfarin and a variety of anticancer treatments differing for administered agents and/or monitored biomarkers. The resulted picture highlights a certain heterogeneity in terms of precision dosing approaches, applied methodologies, and degree of adherence to the clinical domain. In addition, a tutorial on how a precision dosing problem should be formulated in terms of the key elements composing the RL framework (i.e., system state, agent actions and reward function), and on how PK/PD models could enhance RL approaches is proposed for readers interested in delving in this field. Overall, the integration of PK/PD models into a RL‐framework holds great promise for precision dosing, but further investigations and advancements are still needed to address current limitations and extend the applicability of this methodology to drugs requiring adaptive dosing strategies.
High‐Efficiency Deep Red Fluorescent Material with Aggregation Induced Emission and the Application in Organic Light‐Emitting Diodes
Authors: Liu Hui , Zhang Hanyuan , Pu Yuanyuan , Li Zhi , Wan Liang , Ge Shuyuan , Ma Xiaobo , Liu Futong , Lu Ping 
Published: July 2024

AbstractThe development of highly efficient deep red materials with emission wavelength beyond 650 nm remains a big challenge due to the constraints imposed by the energy gap rule. In this work, a donor‐acceptor‐donor type emitter, 4,7‐bis (10‐(4‐(tert‐butyl) phenyl)‐10H‐phenothiazin‐3‐yl) benzo[c][1,2,5] thiadiazole (TBPPTZ) is designed and synthesized. Resulting from the slight twist angle between the donor and acceptor units, TBPPTZ exhibits nearly planar conformation and an extended conjugated structure. TBPPTZ shows a deep red emission peak at 687 nm and aggregation induced emission property with a high photoluminescence quantum yield of 45 % in neat thin film. The optimized organic light‐emitting diode (OLEDs) utilizing TBPPTZ as the non‐doped emissive layer obtains a high external quantum efficiency (EQE) up to 2.51 % with an electroluminescence (EL) peak at 676 nm, aligning with the Commission Internationale de L'Eclairage (CIE) coordinates (0.68, 0.31), which shows a small EQE roll‐off of only 5.6 % at 100 cd m−2. Additionally, the doped OLED achieves an EQE up to 5.09 %, with an EL peak at 656 nm and CIE coordinates of (0.65, 0.34). The findings of this research not only contribute to achieve highly efficient deep red OLEDs but also offer a novel and effective deep red molecular strategy to realize high‐quality OLEDs.
Gastric cancer detection based on cell‐free DNA in blood: A systematic review and meta‐analysis
Authors: Wang Mona , Fan Xiaohan , Huang Boyang , Pan Kaifeng , Gerhard Markus , Mejías‐Luque Raquel , Zhang Yang 
Published: July 2024

AbstractObjectiveScreening and early diagnosis of gastric cancer (GC) are crucial for improved prognosis. However, gastroscopic screening is not feasible in large populations due to its high cost and invasive nature. The detection of circulating cell‐free DNA (cfDNA) provides an attractive minimally‐invasive alternative for screening of GC. In this systematic review and meta‐analysis, we evaluate the diagnostic value of cfDNA‐based markers for GC, including the detection of total concentration, mutations, and methylation alterations.MethodsWe performed a systematic search of four literature databases (PubMed, Embase, Web of Science, and Cochrane Library) for articles published before November 2022. The revised tool for the Quality Assessment of Diagnostic Accuracy Studies (QUADAS‐2) was used to evaluate the quality of included studies. PROSPERO registration number: CRD42021210830.ResultsA total of 15 original articles involving 2849 individuals were included in this meta‐analysis, comprising five studies on concentration, nine studies on methylation alterations, and one study on mutation biomarkers of cfDNA. Among these studies, seven selected early‐stage GC subjects. For the diagnoses of overall stages and early‐stage GC, the pooled sensitivities with 95% confidence interval were 0.74 (0.66–0.82) and 0.64 (0.51–0.76), and the pooled specificities were 0.92 (0.84–0.96) and 0.94 (0.87–0.98) with summary areas under the curve (SAUCs) of 0.89 (0.86–0.91) and 0.86 (0.83–0.89), respectively.ConclusionsThis meta‐analysis suggests that cfDNA‐based biomarkers show diagnostic value for GC early detection.
Studies on the influence of titanium dioxide nanoparticles on thermal, flammability, and UV properties of PEG‐based phase change material composites
Authors: Tanwar Surya , Kaur Raminder 
Published: July 2024

AbstractThe current study is focused on the development of phase change material composites (PCCs), attained by the solvent‐casting method, comprising a hydrophilic polymer matrix (polyvinyl alcohol) enclosing polyethylene glycol (PEG600) as an active thermal energy storage (TES) component, and anchored with titanium dioxide nanoparticles (TDN). The impact of the integrated metal oxide nanoparticles at different loadings (0.25%‐1%) on the TES attributes, thermal stability, UV resistance, and flame retardancy of the fabricated composites has been studied. The Fourier‐transform infrared and field‐emission scanning electron microscopy techniques have been used to characterize the PCCs obtained. Phase change attributes and thermal stability of the resultant PCCs are evaluated by differential scanning calorimetry (DSC) and thermogravimatric analysis (TGA). The introduction of TDN particles in different concentrations to the PCCs considerably refines the phase change variables and thermal resistance of the reinforced film samples. PCCs film with 1% TDN concentration exhibited onset melting and crystallization temperatures at −9.9°C and 13.5°C, respectively, and peak melting and crystallization transitions occurred at 8.7°C and 3.6°C, with associated heat enthalpies of 25.57 and 22.22 J g−1, respectively. UV and flame‐retardant (FR) features of the PCCs were found to be improved with the presence of metal oxide particles in the composite films. The metal oxide nanoparticles enhance the FR behavior of fabricated composites by 11.45% as compared to unfilled films.
Anticancer potential of phytochemicals derived from mangrove plants: Comprehensive mechanistic insights
Authors: Chowdhury Raihan , Bhuia Md. Shimul , Al Hasan Md. Sakib , Hossain Snigdha Shadid , Afrin Sadia , Büsselberg Dietrich , Habtemariam Solomon , Sönmez Gürer Eda , Sharifi‐Rad Javad , Ahmed Aldahish Afaf , Аkhtayeva Nursulu , Islam Muhammad Torequl 
Published: July 2024

AbstractCancer is a collection of illnesses characterized by aberrant cellular proliferation that can infiltrate or metastasize to distant anatomical sites, posing a notable threat to human well‐being due to its substantial morbidity and death rates worldwide. The potential of plant‐derived natural compounds as anticancer medicines has been assessed owing to their favorable attributes of few side effects and significant antitumor activity. Mangrove plants and their derived compounds have been scientifically shown to exhibit many significant beneficial biological activities, such as anti‐inflammatory, immunomodulatory, antioxidant, neuroprotective, cardioprotective, and hepatoprotective properties. This study summarized mangrove plants and their derived compounds as potential anticancer agents, with an emphasis on the underlying molecular mechanisms. To explore this, we gathered data on the preclinical (in vivo and in vitro) anticancer effects of mangrove plants and their derived compounds from reputable literature spanning 2000 to 2023. We conducted thorough searches in various academic databases, including PubMed, ScienceDirect, Wiley Online, SpringerLink, Google Scholar, Scopus, and the Web of Science. The results demonstrated that mangrove plants and their derived compounds have promising anticancer properties in preclinical pharmacological test systems through various molecular mechanisms, including induction of oxidative stress and mitochondrial dysfunction, cytotoxicity, genotoxicity, cell cycle arrest, apoptosis, autophagy, antiproliferative, antimetastatic, and other miscellaneous actions. Upon thorough observation of the pertinent information, it is suggested that mangrove plants and their derived chemicals may serve as a potential lead in the development of novel drugs for cancer therapy.
Encapsulation of Lacticaseibacillus casei and Lactobacillus acidophilus using Elaeagnus angustifolia L. flour as encapsulating material by emulsion method
Authors: Karkar Büşra , Şahin Saliha , Yılmaz‐Ersan Lütfiye , Akça Bekir , Güneş Mesut Ertan , Özakın Cüneyt 
Published: July 2024

AbstractIn this study, Lacticaseibacillus casei and Lactobacillus acidophilus probiotic bacteria were encapsulated using oleaster flour, which is rich in phenolic compounds and has prebiotic properties as potential. The optimum conditions required for the encapsulation of L. casei and L. acidophilus bacteria with maximum efficiency using oleaster flour were determined by central composite design–response surface methodology. As a result of the optimization process, the encapsulation efficiency for L. casei and L. acidophilus capsules was 93.66 ± 2.58% and 74.97 ± 1.34%, respectively. The capsule sizes of L. casei and L. acidophilus encapsulated with oleaster flour were determined by scanning electron microscopy to be 104.8 ± 26.3 and 95.7 ± 12.1 μm, respectively. Fourier transform infrared spectroscopy analyses showed that there was no change in the structure of the encapsulation material, oleaster flour, after encapsulation. Also, the storage stability of free and encapsulated bacteria was investigated, and it was found that the viability losses of encapsulated probiotic bacteria were less than those of free probiotic bacteria. Finally, the effect of encapsulation on bacterial viability during in vitro gastrointestinal digestion was investigated, which is the main purpose of the study. While free probiotic bacteria cannot reach the intestinal environment alive after in vitro gastrointestinal digestion due to pH and enzyme effects, encapsulated L. casei and L. acidophilus bacteria largely preserved their viability, and their postdigestion viability was 39.59 ± 1.50% and 36.28 ± 0.01%, respectively. The results showed successful encapsulation of L. casei and L. acidophilus probiotic bacteria with oleaster flour.
Factors shaping the employment outcomes of neurodivergent and neurotypical people: Exploring the role of flexible and homeworking practices
Authors: Branicki Layla J. , Brammer Stephen , Brosnan Mark , Lazaro Aida Garcia , Lattanzio Susan , Newnes Linda 
Published: July 2024

AbstractSupporting neurodivergent‐inclusive workplaces is an increasingly important consideration in Human Resource Management (HRM). While a strengths‐based approach to neurodivergence has been advocated, empirical evidence regarding the effectiveness of HRM practices that support high‐quality employment outcomes for neurodivergent people is lacking. Drawing on a nationally representative sample of over 25,000 people in the United Kingdom, we examine the influence of neurodivergence on multiple employment outcomes, including employment status, underemployment, employment precarity, job tenure, and hourly wages. We theorize and empirically examine how flexible‐ and homeworking practices moderate the effects of neurodivergence on employment outcomes. Our findings show that neurodivergent people are twice as likely to be in precarious employment and more than 10 times as likely to be in temporary employment compared to neurotypical people. Neurodivergent individuals are also significantly more likely to experience underemployment and have lower employment tenure; however, controlling for other factors, we find no significant differences in hourly wages. We find that flexible working practices can substantially improve employment outcomes for neurodivergent people, raising significant questions regarding the role of HRM in enabling more neurodiverse workplaces. We critically reflect on the implications of our findings for policy, practice, and future research.
SARS‐CoV‐2 seroprevalence and associated factors among people living with HIV in Sierra Leone
Authors: Sun Wei , Song Jinwen , Lakoh Sulaiman , Chen Jinquan , Jalloh Abdulai T. , Sahr Foday , Sevalie Stephen , Jiba Darlinda F. , Kamara Ibrahim F. , Xin Yingrong , Ye Zhongyang , Ding Feng , Dai Li‐Zhong , Wang Ligui , Zheng Xishui , Yang Guang 
Published: July 2024

AbstractBackgroundHuman immunodeficiency virus (HIV) infection is an important risk factor for Coronavirus Disease 2019 (COVID‐19), but data on the prevalence of COVID‐19 among people living with HIV (PLWH) is limited in low‐income countries. Our aim was to assess the seroprevalence of the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) specific antibodies and associated factors among PLWH in Sierra Leone.MethodsWe conducted a cross‐sectional survey of PLWH aged 18 years or older in Sierra Leone between August 2022 and January 2023. Participants were tested for SARS‐CoV‐2 antibodies using a rapid SARS‐CoV‐2 antibody (immunoglobulin M/immunoglobulin G [IgG]) kits. Stepwise logistic regression was used to explore factors associated with SARS‐CoV‐2 antibody seroprevalence with a significance level of p < .05.ResultsIn our study, 33.4% (1031/3085) participants had received a COVID‐19 vaccine, and 75.7% were SARS‐CoV‐2 IgG positive. Higher IgG seroprevalence was observed in females (77.2% vs. 71.4%, p = .001), adults over 60 years (88.2%), those with suppressed HIV RNA (80.7% vs. 51.7%, p < .001), antiretroviral therapy (ART)‐experienced individuals (77.9% vs. 44.6%, p < .001), and vaccinated participants (80.7% vs. 73.2%, p < .001). Patients 60 years or older had the highest odds of IgG seroprevalence (adjusted odds ratio [aOR] = 2.73, 95% CI = 1.68–4.65). Female sex (aOR = 1.28, 95%CI = 1.05–1.56), COVID‐19 vaccination (aOR = 1.54, 95% CI = 1.27–1.86), and ART (aOR = 2.20, 95% CI = 1.56–3.11) increased the odds, whereas HIV RNA ≥ 1000 copies/mL (aOR = 0.32, 95% CI = 0.26–0.40) reduced the odds of IgG seroprevalence.ConclusionsWe observed a high seroprevalence of SARS‐CoV‐2 antibody among PLWH in Sierra Leone. We recommend the introduction of targeted vaccination for PLWH with a high risk of severe COVID‐19, especially those with an unsuppressed HIV viral load.
A New Herbal Source of Synthesizing Contrast Agents for Magnetic Resonance Imaging
Authors: Yazdani Ali , Okhovat Ahmadreza , Doosti Raheleh , Soltanian‐Zadeh Hamid 
Published: July 2024

ABSTRACTThis study explores the potential of halophytes, plants adapted to saline environments, as a novel source for developing herbal MRI contrast agents. Halophytes naturally accumulate various metals within their tissues. These metal ions, potentially complexed with organic molecules, are released into aqueous solutions prepared from the plants. We investigated the ability of these compounds to generate contrast enhancement in MRI using a sequential approach. First, aqueous extracts were prepared from seven selected halophytes, and their capacity to induce contrast in MR images was evaluated. Based on these initial findings, sample halophytes were chosen for further investigations. Second, chemical analysis revealed aluminum as the primary potent metal which enhances the contrast. Third, the halophyte extract was fractionated based on polarity, and the most polar fraction exhibited the strongest contrast‐generating effect. Finally, the relaxivity of this fraction, a key parameter for MRI contrast agents, was measured. We propose that aluminum, likely complexed with a polar molecule within the plant extract, is responsible for the observed contrast enhancement in MRI.
Transforming an irrigation system to a smart irrigation system: A case study from Türkiye (Turkey)
Authors: Balta Mehmet Akif , Kulat Muhammed Imran 
Published: July 2024

AbstractThe Imamoğlu Agricultural Irrigation Automation Project aims to revolutionize water management and allocation in agricultural irrigation through the establishment of a central management‐based system. By integrating modern irrigation technologies and systems, the project seeks to optimize water usage by monitoring key variables such as irrigation methods and plant–water–yield relationships. The electronic water management system (ESYS), at the core of this initiative, employs a geographic information system (GIS)‐based interface and real‐time data to facilitate active participation of farmers and water stakeholders. Through the utilization of deep learning technology and real‐time data analysis, the system enables timely and informed irrigation planning, resulting in significant water savings and increased productivity. The project's implementation, focused on the Imamoğlu Irrigation System, has gradually introduced a remote central management‐based agricultural irrigation automation system to 2,240 farmers. Integrated with the ESYS, this system offers benefits including enhanced water supply security, remote access to irrigation control, soil moisture monitoring, weather‐based irrigation planning and centralized plant pattern management. The project aims to promote efficient water usage, maximize food production and serve as a model for future irrigation projects. Key highlights include up to 65%–70% increase in water savings, up to 90% reduction in energy and fuel savings, up to 90% reduction in labour and personnel savings and more efficient irrigation management, among others.