bluuebunny/crossref_metadata_2025 huggingface dataset:
Long-Term Lifestyle Habits and Quality of Life after Roux-in-Y Gastric Bypass in Brazilian Public versus Private Healthcare Systems: Beyond Weight Loss
Authors: Melendez-Araújo Mariana S. , do Carmo Ariene Silva , Vieira Flávio Teixeira , Lamarca Fernando , Nakano Eduardo Yoshio , Lima Ricardo M. , Dutra Eliane Said , de Carvalho Kênia Mara Baiocchi
Published: August 2023

Lifestyle and health-related quality of life (HRQoL) are good markers of surgical obesity treatment. This study aimed to investigate the lifestyle and HRQoL of patients at least five years after Roux-en-Y gastric bypass in public (SUS) and private (PVT) Brazilian healthcare systems. In this cross-sectional study, weight loss (WL), % of excess WL (%EWL), diet quality, physical activity, alcohol consumption, and HRQoL were evaluated. Analysis of covariance, binary and multinomial logistic regression, adjusted for confounders, were performed. The SUS group had more vulnerable socioeconomic statuses than the PVT group. Total %WL and % EWL were 24.64 ± 0.99% and 60.46 ± 2.41%, respectively, without difference between groups. In the Pain/Discomfort and Anxiety/Depression domains of HRQoL, more than 50% reported moderate problems without differences between groups. Processed food ingestion was higher in the PVT (132.10 ± 60.15 g/1000 kcal) than in the SUS (103.43 ± 41.72 g/1000 kcal), however, without statistical significance (p = 0.093). The PVT group showed lower physical activity (OR: 0.23; 95%CI: 0.87–0.63; p = 0.004) and a higher risk of alcohol-related problems (OR: 3.23; 95%CI; 1.03–10.10; p = 0.044) compared to SUS group. Participants generally achieved satisfactory WL, regardless of healthcare systems. However, PVT participants had unfavorable lifestyle characteristics, highlighting the need for studies investigating environmental issues post-bariatric surgery.
Malaria Risk Drivers in the Brazilian Amazon: Land Use—Land Cover Interactions and Biological Diversity
Authors: Gonzalez Daza William , Muylaert Renata L. , Sobral-Souza Thadeu , Lemes Landeiro Victor
Published: August 2023

Malaria is a prevalent disease in several tropical and subtropical regions, including Brazil, where it remains a significant public health concern. Even though there have been substantial efforts to decrease the number of cases, the reoccurrence of epidemics in regions that have been free of cases for many years presents a significant challenge. Due to the multifaceted factors that influence the spread of malaria, influencing malaria risk factors were analyzed through regional outbreak cluster analysis and spatio-temporal models in the Brazilian Amazon, incorporating climate, land use/cover interactions, species richness, and number of endemic birds and amphibians. Results showed that high amphibian and bird richness and endemism correlated with a reduction in malaria risk. The presence of forest had a risk-increasing effect, but it depended on its juxtaposition with anthropic land uses. Biodiversity and landscape composition, rather than forest formation presence alone, modulated malaria risk in the period. Areas with low endemic species diversity and high human activity, predominantly anthropogenic landscapes, posed high malaria risk. This study underscores the importance of considering the broader ecological context in malaria control efforts.
A Student-Centric Evaluation of a Program Addressing Prevention of Gender-Based Violence in Three African Countries
Authors: Cahill Helen , Dadvand Babak , Suryani Anne , Farrelly Anne
Published: August 2023

Studies investigating the effectiveness of school-related gender-based violence prevention programs seldom report on the extent to which students themselves value and recommend such programs. Yet, along with evidence about effectiveness in relation to shifts in knowledge, attitudes, or intentions, student-valuing is a significant indicator that the programs can make a positive contribution to students’ lives. This mixed-method study analyses survey and focus group data collected from ninety-two schools in three African countries (Tanzania, Zambia, and Eswatini). Students found the program contributed to improved peer relationships and identified the five most useful components as learning about gender equality and human rights, learning how to obtain help for those affected by violence, understanding and communicating about their emotions, strategies to avoid joining in with bullying and harassment, and understanding the effects of gender-based violence.
Guar Gum as an Eco-Friendly Corrosion Inhibitor for N80 Carbon Steel under Sweet Environment in Saline Solution: Electrochemical, Surface, and Spectroscopic Studies
Authors: Palumbo Gaetano , Święch Dominika , Górny Marcin
Published: August 2023

In this study, the corrosion inhibition performance of the natural polysaccharide guar gum (GG) for N80 carbon steel in CO2-saturated saline solution at different temperatures and immersion times was investigated by weight loss and electrochemical measurements. The results have revealed that GG showed good inhibition performance at lower and higher temperatures. The inhibition efficiency observed via weight loss measurements reached 76.16 and 63.19% with 0.4 g L−1 of GG, at 25 and 50 °C, respectively. The inhibition efficiency of GG increased as the inhibitor concentration and immersion time increased but decreased with increasing temperature. EIS measurements have shown that, even after prolonged exposure, GG was still able to protect the metal surface. Potentiodynamic measurements showed the mixed-type nature of GG inhibitive action. The Temkin and Dubinin–Radushkevich adsorption isotherm models give accurate fitting of the estimated data, and the calculated parameters indicated that the adsorption of GG occurred mainly via an electrostatic or physical adsorption process. The associated activation energy (Ea) and the heat of adsorption (Qa) supported the physical adsorption nature of GG. FTIR analysis was used to explain the adsorption interaction between the inhibitor and the N80 carbon steel surface. SEM-EDS and AFM confirmed the adsorption of GG and the formation of an adsorptive layer of GG on the metal surface.
Serum NMR-Based Metabolomics Profiling Identifies Lipoprotein Subfraction Variables and Amino Acid Reshuffling in Myeloma Development and Progression
Authors: Pedersen Shona , Mikkelstrup Morten Faarbæk , Kristensen Søren Risom , Anwardeen Najeha Rizwana , Elrayess Mohamed A. , Andreassen Trygve
Published: August 2023

Multiple myeloma (MM) is an incurable hematological cancer. It is preceded by monoclonal gammopathy of uncertain significance (MGUS)—an asymptomatic phase. It has been demonstrated that early detection increases the 5-year survival rate. However, blood-based biomarkers that enable early disease detection are lacking. Metabolomic and lipoprotein subfraction variable profiling is gaining traction to expand our understanding of disease states and, more specifically, for identifying diagnostic markers in patients with hematological cancers. This study aims to enhance our understanding of multiple myeloma (MM) and identify candidate metabolites, allowing for a more effective preventative treatment. Serum was collected from 25 healthy controls, 20 patients with MGUS, and 30 patients with MM. 1H-NMR (Nuclear Magnetic Resonance) spectroscopy was utilized to evaluate serum samples. The metabolite concentrations were examined using multivariate, univariate, and pathway analysis. Metabolic profiles of the MGUS patients revealed lower levels of alanine, lysine, leucine but higher levels of formic acid when compared to controls. However, metabolic profiling of MM patients, compared to controls, exhibited decreased levels of total Apolipoprotein-A1, HDL-4 Apolipoprotein-A1, HDL-4 Apolipoprotein-A2, HDL Free Cholesterol, HDL-3 Cholesterol and HDL-4 Cholesterol. Lastly, metabolic comparison between MGUS to MM patients primarily indicated alterations in lipoproteins levels: Total Cholesterol, HDL Cholesterol, HDL Free Cholesterol, Total Apolipoprotein-A1, HDL Apolipoprotein-A1, HDL-4 Apolipoprotein-A1 and HDL-4 Phospholipids. This study provides novel insights into the serum metabolic and lipoprotein subfraction changes in patients as they progress from a healthy state to MGUS to MM, which may allow for earlier clinical detection and treatment.
Expression and Regulatory Mechanisms of MicroRNA in Cholesteatoma: A Systematic Review
Authors: Dżaman Karolina , Czerwaty Katarzyna , Reichert Torsten E. , Szczepański Mirosław J. , Ludwig Nils
Published: August 2023

Cholesteatoma is a temporal bone disease characterized by dysfunctions of keratinocytes. MicroRNAs (miRNAs) are evolutionary conserved noncoding RNAs that regulate mRNA expression. They can be packaged into exosomes and transported to target cells that can be used in the future therapy of cholesteatoma. This study aimed to collect knowledge on the role of miRNAs and exosomal miRNAs in cholesteatoma and was conducted according to the PRISMA guidelines for systematic reviews. Four databases were screened: Pubmed/MEDLINE, Web of Science, Scopus, and the Cochrane Library. The last search was run on the 6th of June 2023. We included full-text original studies written in English, which examined miRNAs in cholesteatoma. The risk of bias was assessed using the Office of Health Assessment and Translation (OHAT) Risk of Bias Rating Tool, modified for the needs of this review. We identified 118 records and included 18 articles. Analyses revealed the downregulation of exosomal miR-17 as well as miR-10a-5p, miR-125b, miR-142-5p, miR34a, miR-203a, and miR-152-5p and the overexpression of exosomal miR-106b-5p as well as miR-1297, miR-26a-5p, miR-199a, miR-508-3p, miR-21-3p, miR-584-5p, and miR-16-1-3p in cholesteatoma. The role of differentially expressed miRNAs in cholesteatoma, including cell proliferation, apoptosis, the cell cycle, differentiation, bone resorption, and the remodeling process, was confirmed, making them a potential therapeutic target in this disease.
Phosphoproteome Reveals Extracellular Regulated Protein Kinase Phosphorylation Mediated by Mitogen-Activated Protein Kinase Kinase-Regulating Granulosa Cell Apoptosis in Broody Geese
Authors: Zhao Shuai , Gu Tiantian , Weng Kaiqi , Zhang Yu , Cao Zhengfeng , Zhang Yang , Zhao Wenming , Chen Guohong , Xu Qi
Published: August 2023

Geese have strong brooding abilities, which severely affect their egg-laying performance. Phosphorylation is widely involved in regulating reproductive activities, but its role in goose brooding behavior is unclear. In this study, we investigated differences in the phosphoprotein composition of ovarian tissue between laying and brooding geese. Brooding geese exhibited ovarian and follicular atrophy, as well as significant oxidative stress and granulosa cell apoptosis. We identified 578 highly phosphorylated proteins and 281 lowly phosphorylated proteins, and a KEGG pathway analysis showed that these differentially phosphorylated proteins were mainly involved in cell apoptosis, adhesion junctions, and other signaling pathways related to goose brooding behavior. The extracellular regulated protein kinase (ERK)–B-Cell Lymphoma 2(BCL2) signaling pathway was identified as playing an important role in regulating cell apoptosis. The phosphorylation levels of ERK proteins were significantly lower in brooding geese than in laying geese, and the expression of mitogen-activated protein kinase kinase (MEK) was downregulated. Overexpression of MEK led to a significant increase in ERK phosphorylation and BCL2 transcription in H2O2-induced granulosa cells (p < 0.05), partially rescuing cell death. Conversely, granulosa cells receiving MEK siRNA exhibited the opposite trend. In conclusion, geese experience significant oxidative stress and granulosa cell apoptosis during brooding, with downregulated MEK expression, decreased phosphorylation of ERK protein, and inhibited expression of BCL2.
Crystal Structure and Thermal Properties of Double-Complex Salts [M1(NH3)6][M2(C2O4)3] (M1, M2 = Co, Rh) and K3[Rh(NH3)6][Rh(C2O4)3]2∙6H2O
Authors: Smirnov Pavel , Filatov Evgeny , Kuratieva Natalia , Plyusnin Pavel , Korenev Sergey
Published: August 2023

Here, seven new double-complex salts, [M1(NH3)6][M2(C2O4)3] (M1, M2 = Co, Rh) and K3[Rh(NH3)6][Rh(C2O4)3]2∙6H2O types, are synthesised. The crystal structure and composition of DCS (double-complex salts) are studied by SCXRD, XRD, CHN and IR methods. The complex salts of the [M1(NH3)6][M2(C2O4)3] (M1, M2 = Co, Rh) type can be crystallised both as a crystalline hydrate [M1(NH3)6][M2(C2O4)3]·3H2O (sp. gr. P-3) and as an anhydrous complex (sp. gr. P-1) depending on the synthesis conditions. The process of [Rh(NH3)6][Rh(C2O4)3] formation is significantly dependent on the synthesis temperature. At room temperature, a mixture is formed comprising [Rh(NH3)6][Rh(C2O4)3] and K3[Rh(NH3)6][Rh(C2O4)3]2∙6H2O, while the [Rh(NH3)6][Rh(C2O4)3] target product crystallises at elevated temperatures. The thermal behaviour of double-complex salts is studied by the STA, EGA-MS, IR and XRD methods. The complete decomposition of complex salts in helium and hydrogen atmospheres resulting in metals or CoxRh1−x solid solutions is achieved at temperatures of 320–450 °C.
Whole-Exome and Transcriptome Sequencing Expands the Genotype of Majewski Osteodysplastic Primordial Dwarfism Type II
Authors: Marzano Flaviana , Chiara Matteo , Consiglio Arianna , D’Amato Gabriele , Gentile Mattia , Mirabelli Valentina , Piane Maria , Savio Camilla , Fabiani Marco , D’Elia Domenica , Sbisà Elisabetta , Scarano Gioacchino , Lonardo Fortunato , Tullo Apollonia , Pesole Graziano , Faienza Maria Felicia
Published: August 2023

Microcephalic Osteodysplastic Primordial Dwarfism type II (MOPDII) represents the most common form of primordial dwarfism. MOPD clinical features include severe prenatal and postnatal growth retardation, postnatal severe microcephaly, hypotonia, and an increased risk for cerebrovascular disease and insulin resistance. Autosomal recessive biallelic loss-of-function genomic variants in the centrosomal pericentrin (PCNT) gene on chromosome 21q22 cause MOPDII. Over the past decade, exome sequencing (ES) and massive RNA sequencing have been effectively employed for both the discovery of novel disease genes and to expand the genotypes of well-known diseases. In this paper we report the results both the RNA sequencing and ES of three patients affected by MOPDII with the aim of exploring whether differentially expressed genes and previously uncharacterized gene variants, in addition to PCNT pathogenic variants, could be associated with the complex phenotype of this disease. We discovered a downregulation of key factors involved in growth, such as IGF1R, IGF2R, and RAF1, in all three investigated patients. Moreover, ES identified a shortlist of genes associated with deleterious, rare variants in MOPDII patients. Our results suggest that Next Generation Sequencing (NGS) technologies can be successfully applied for the molecular characterization of the complex genotypic background of MOPDII.
Development of Technologies for the Detection of (Cyber)Bullying Actions: The BullyBuster Project
Authors: Orrù Giulia , Galli Antonio , Gattulli Vincenzo , Gravina Michela , Micheletto Marco , Marrone Stefano , Nocerino Wanda , Procaccino Angela , Terrone Grazia , Curtotti Donatella , Impedovo Donato , Marcialis Gian Luca , Sansone Carlo
Published: August 2023

Bullying and cyberbullying are harmful social phenomena that involve the intentional, repeated use of power to intimidate or harm others. The ramifications of these actions are felt not just at the individual level but also pervasively throughout society, necessitating immediate attention and practical solutions. The BullyBuster project pioneers a multi-disciplinary approach, integrating artificial intelligence (AI) techniques with psychological models to comprehensively understand and combat these issues. In particular, employing AI in the project allows the automatic identification of potentially harmful content by analyzing linguistic patterns and behaviors in various data sources, including photos and videos. This timely detection enables alerts to relevant authorities or moderators, allowing for rapid interventions and potential harm mitigation. This paper, a culmination of previous research and advancements, details the potential for significantly enhancing cyberbullying detection and prevention by focusing on the system’s design and the novel application of AI classifiers within an integrated framework. Our primary aim is to evaluate the feasibility and applicability of such a framework in a real-world application context. The proposed approach is shown to tackle the pervasive issue of cyberbullying effectively.
Detecting Abnormal Behaviors in Dementia Patients Using Lifelog Data: A Machine Learning Approach
Authors: Kim Kookjin , Jang Jisoo , Park Hansol , Jeong Jaeyeong , Shin Dongil , Shin Dongkyoo
Published: August 2023

In this paper, a proof-of-concept method for detecting abnormal behavior in dementia patients based on a single case study is proposed. This method incorporates the collection of lifelog data using affordable sensors and the development of a machine-learning-based system. Such an approach has the potential to enable the prompt detection of abnormal behavior in dementia patients within nursing homes and to send alerts to caregivers, which could potentially reduce their workload and decrease the risk of accidents and injuries. In a proof-of-concept experiment conducted on a single dementia patient in a Korean nursing home, the proposed system, specifically the multilayer perceptron model, demonstrated exceptional performance, achieving an accuracy of 0.99, a precision of 1.00, a recall of 1.00, and an F1 score of 1.00. While being cost-effective and adaptable to various nursing homes, these results should be interpreted as preliminary, being based on a limited sample. Future research is aimed at validating and improving the performance of the abnormal behavior detection system by expanding the experiments to include lifelog data from multiple nursing homes and a larger cohort of dementia patients. The potential application of this system extends beyond healthcare and medical fields, reaching into smart home environments and various other facilities. This study underscores the potential of this system to enhance patient safety, alleviate family concerns, and reduce societal costs, thereby contributing to the improvement of the quality of life for dementia patients.
A Revision of the Genus Argolis (Hemiptera: Reduviidae: Stenopodainae) from Asia
Authors: Chen Zhuo , Webb Michael D. , Cai Wanzhi
Published: August 2023

The assassin bug genus Argolis Stål, 1861 (Hemiptera: Reduviidae: Stenopodainae) has a disjunct distribution in Sub-Saharan Africa and Asia. In the present study, the Asian species of Argolis are revised. Two species are recognized, redescribed, and illustrated, with the following new subjective synonyms and new combination proposed: Argolis Stål, 1861 = Bardesanes Distant, 1909, syn. nov. = Neoklugia Distant, 1919, syn. nov.; A. farinator (Reuter, 1882) = N. typica Distant, 1919, syn. nov. = B. sericenotatus Livingstone & Ravichandran, 1989, syn. nov.; A. signata (Distant, 1909), comb. nov. (transferred from Bardesanes) = Caunus noctulus Hsiao, 1977, syn. nov. Lectotypes for C. farinator, B. signatus, and N. typica are designated. A key to separate the two Asian species of Argolis is provided. The sexual dimorphism, systematic relationships, and distribution of Argolis are discussed. Argolis is newly recorded from Laos, Pakistan, and Vietnam.
Using Gamma Irradiation to Predict Sperm Competition Mechanism in Bagrada hilaris (Burmeister) (Hemiptera: Pentatomidae): Insights for a Future Management Strategy
Authors: Mainardi Chiara Elvira , Peccerillo Chiara , Paolini Alessandra , Cemmi Alessia , Sforza René F. H. , Musmeci Sergio , Porretta Daniele , Cristofaro Massimo
Published: August 2023

The stink bug, Bagrada hilaris, is a pest of mainly Brassicaceae crops. It is native to Africa and Asia and was recently reported as invasive in the southwestern part of the USA and in South America. There are no mitigation programs in place that do not involve pesticides. Therefore, much attention has recently been paid to the study of this species in order to identify sustainable and effective control strategies, such as the Sterile Insect Technique (SIT). In order to evaluate the suitability of the SIT on this pest, the mechanism of post-copulatory sperm competition was investigated. This is a polyandrous species, and it is thus important to understand whether irradiated males are able to compete with wild, e.g., non-irradiated, males for sperm competition after matings. Sperm competition was studied by sequentially mating a healthy virgin female first with a non-irradiated male, and then with a γ-irradiated (Co-60) one, and again in the opposite order. Males were irradiated at three different doses: 60, 80, and 100 Gy. The fecundity and fertility of the females, in the two orders of mating, were scored in order to perform an initial assessment of the success of sperm competition with a P2 index. Sperm from the non-irradiated male were utilized at the lowest irradiation doses (60 and 80 Gy), whereas the irradiated sperm were preferentially utilized at the highest dose (100 Gy). Bagrada hilaris exhibited high variability in P2 indexes, indicating a sperm-mixing mechanism.
N′-(5-Bromofuran-2-carbonyl)isonicotinohydrazide
Authors: Ramadhani Ersya Yanu , Aijijiyah Nur Pasca , Santoso Eko , Atmaja Lukman , Santoso Mardi
Published: August 2023

N′-(5-bromofuran-2-carbonyl)isonicotinohydrazide (1) was obtained in the form of a colorless solid from the 2-methyl-6-nitrobenzoic anhydride (MNBA)/4-dimethylaminopyridine (DMAP)-catalyzed reaction of 5-bromofuran-2-carboxylic acid and isoniazid in dichloromethane at room temperature with a yield of 83%. The structure of N′-(5-bromofuran-2-carbonyl)isonicotinohydrazide (1) was elucidated using 1H NMR, 13C NMR, FTIR, and high-resolution mass spectrometry. Molecular docking screening of the title compound (1) on cyclooxygenase-2 (COX-2) protein (PDB ID: 5IKR) indicated that compound (1) has a good binding affinity, suggesting that further structure optimization and in-depth research can be carried out on compound (1) as a potential COX-2 inhibitor.
Effect of Rotary Swaging on Mechanical and Operational Properties of Zn–1%Mg and Zn–1%Mg–0.1%Ca Alloys
Authors: Martynenko Natalia , Anisimova Natalia , Rybalchenko Georgy , Rybalchenko Olga , Serebryany Vladimir , Zheleznyi Mark , Shinkareva Maria , Gorbenko Artem , Temralieva Diana , Lukyanova Elena , Sannikov Andrey , Koltygin Andrey , Kiselevskiy Mikhail , Yusupov Vladimir , Dobatkin Sergey
Published: August 2023

A study of microstructure, phase composition, mechanical properties, corrosion processes, and biocompatibility in vitro of the Zn–1%Mg and Zn–1%Mg–0.1%Ca alloys in an annealed state and after rotary swaging (RS) is presented. Partially recrystallized microstructure is formed in the studied alloys after RS at 200 °C. RS reduces the mass fraction of intermetallic phases in comparison with annealed states of the alloys. RS at 200 °C increases the strength of the Zn–1%Mg and Zn–1%Mg–0.1%Ca alloys up to 248 ± 9 and 249 ± 9 with the growth of ductility up to 10.3 ± 3% and 14.2 ± 0.9%, respectively. The structure after RS at 200 °C does not lead to a change in the corrosion resistance of the studied alloys. However, an increase in the incubation period of the alloys in a growth medium slows down the degradation process due to the formation of a film consisting of degradation products. Rotary swaging does not impair the biocompatibility of the Zn–1%Mg and Zn–1%Mg alloys, maintaining the viability and integrity of blood cells, preventing hemolysis, and ensuring the adhesion and proliferation of osteogenic cells on the surface of samples.
Interaction of Macromolecular Chain with Phospholipid Membranes in Solutions: A Dissipative Particle Dynamics Simulation Study
Authors: Wang Yuane , Mou Xuankang , Ji Yongyun , Pan Fan , Li Shiben
Published: August 2023

The interaction between macromolecular chains and phospholipid membranes in aqueous solution was investigated using dissipative particle dynamics simulations. Two cases were considered, one in which the macromolecular chains were pulled along parallel to the membrane surfaces and another in which they were pulled vertical to the membrane surfaces. Several parameters, including the radius of gyration, shape factor, particle number, and order parameter, were used to investigate the interaction mechanisms during the dynamics processes by adjusting the pulling force strength of the chains. In both cases, the results showed that the macromolecular chains undergo conformational transitions from a coiled to a rod-like structure. Furthermore, the simulations revealed that the membranes can be damaged and repaired during the dynamic processes. The role of the pulling forces and the adsorption interactions between the chains and membranes differed in the parallel and perpendicular pulling cases. These findings contribute to our understanding of the interaction mechanisms between macromolecules and membranes, and they may have potential applications in biology and medicine.
Multiheaded Cationic Surfactants with Dedicated Functionalities: Design, Synthetic Strategies, Self-Assembly and Performance
Authors: Lamch Łukasz , Szczęsna Weronika , Balicki Sebastian J. , Bartman Marcin , Szyk-Warszyńska Liliana , Warszyński Piotr , Wilk Kazimiera A.
Published: August 2023

Contemporary research concerning surfactant science and technology comprises a variety of requirements relating to the design of surfactant structures with widely varying architectures to achieve physicochemical properties and dedicated functionality. Such approaches are necessary to make them applicable to modern technologies, such as nanostructure engineering, surface structurization or fine chemicals, e.g., magnetic surfactants, biocidal agents, capping and stabilizing reagents or reactive agents at interfaces. Even slight modifications of a surfactant’s molecular structure with respect to the conventional single-head–single-tail design allow for various custom-designed products. Among them, multicharge structures are the most intriguing. Their preparation requires specific synthetic routes that enable both main amphiphilic compound synthesis using appropriate step-by-step reaction strategies or coupling approaches as well as further derivatization toward specific features such as magnetic properties. Some of the most challenging aspects of multicharge cationic surfactants relate to their use at different interfaces for stable nanostructures formation, applying capping effects or complexation with polyelectrolytes. Multiheaded cationic surfactants exhibit strong antimicrobial and antiviral activity, allowing them to be implemented in various biomedical fields, especially biofilm prevention and eradication. Therefore, recent advances in synthetic strategies for multiheaded cationic surfactants, their self-aggregation and performance are scrutinized in this up-to-date review, emphasizing their applications in different fields such as building blocks in nanostructure engineering and their use as fine chemicals.
Gallic-Acid-Loaded PLGA Nanoparticles: A Promising Transdermal Drug Delivery System with Antioxidant and Antimicrobial Agents
Authors: Aldawsari Mohammed F. , Alkholifi Faisal K. , Foudah Ahmed I. , Alqarni Mohammed H. , Alam Aftab , Salkini Mohamad Ayman , Sweilam Sherouk Hussein
Published: August 2023

The objective of this study was to develop an innovative gallic-acid (GA) drug delivery system that could be administered transdermally, resulting in enhanced therapeutic benefits and minimal negative consequences. The method employed involved the preparation of poly(lactic-co-glycolic acid) (PLGA) nanoparticles loaded with GA through nanoprecipitation-denoted GA@PLGANPs. The results reveal that this strategy led to perfectly spherical, homogeneous, and negatively charged particles, which are suitable for administration via skin patches or ointments. A further analysis indicates that these GA@PLGANPs exhibit remarkable antioxidant activity as well as potent antibacterial effects against a diverse range of microorganisms, making them ideal candidates for numerous applications. Additionally, it has been observed that these nanoparticles can effectively mitigate oxidative stress while also significantly inhibiting microbial growth by exerting detrimental effects on bacterial cell walls or membranes. In conclusion, on the basis of the findings presented in this study, there is strong evidence supporting the potential use of GA@PLGANPs as an effective therapy option with reduced side effects compared to conventional drug delivery methods.
Overview of Solid Lipid Nanoparticles in Breast Cancer Therapy
Authors: Mo Kyumin , Kim Ayoung , Choe Soohyun , Shin Miyoung , Yoon Hyunho
Published: August 2023

Lipid nanoparticles (LNPs), composed of ionized lipids, helper lipids, and cholesterol, provide general therapeutic effects by facilitating intracellular transport and avoiding endosomal compartments. LNP-based drug delivery has great potential for the development of novel gene therapies and effective vaccines. Solid lipid nanoparticles (SLNs) are derived from physiologically acceptable lipid components and remain robust at body temperature, thereby providing high structural stability and biocompatibility. By enhancing drug delivery through blood vessels, SLNs have been used to improve the efficacy of cancer treatments. Breast cancer, the most common malignancy in women, has a declining mortality rate but remains incurable. Recently, as an anticancer drug delivery system, SLNs have been widely used in breast cancer, improving the therapeutic efficacy of drugs. In this review, we discuss the latest advances of SLNs for breast cancer treatment and their potential in clinical use.
Estrogen Receptor β Isoforms Regulate Chemotherapy Resistance and the Cancer Stem Cell Population in Prostate Cancer Cells
Authors: Stevens Jessica H. , Bano Ayesha , Bensaoula Lamia , Strom Anders M. , Gustafsson Jan-Åke
Published: August 2023

Estrogen receptor beta 1 (ERβ1) is a ligand-activated nuclear receptor, which has been shown to maintain tissue differentiation in the normal prostate, and regulate androgen response and increase expression of tumor suppressors in prostate cancer cell lines. There are three shorter isoforms of ERβ expressed in the human prostate, ERβ2, ERβ4, and ERβ5, which have already been implicated in chemotherapy resistance and disease progression, suggesting a possible oncogenic role. Their ligand-binding domain (LBD) is truncated, so they are unable to activate canonical ERβ1 signaling pathways; however, they were shown to participate in hypoxic signaling and to induce a gene expression signature associated with stemness and hypoxia. To elucidate the role of the truncated ERβ isoforms in prostate cancer, we created a knockout of all isoforms, as well as a truncation of the LBD, to remove the function of ERβ1. We showed that the removal of all isoforms leads to a decrease in the expression of cancer stem cell (CSC)-associated genes, decreased chemotherapy resistance, and a decrease in the CSC population, based on sphere formation ability and SORE6 (CSC reporter) activity, while removing the LBD function only had the opposite effect. Our results suggest a more aggressive phenotype in prostate cancer cell lines expressing ERβ variants.
Decadal Stability and Trends in the Global Cloud Amount and Cloud Top Temperature in the Satellite-Based Climate Data Records
Authors: Devasthale Abhay , Karlsson Karl-Göran
Published: August 2023

Forty years of cloud observations are available globally from satellites, allowing derivation of climate data records (CDRs) for climate change studies. The aim of this study is to investigate how stable these cloud CDRs are and whether they qualify stability requirements recommended by the WMO’s Global Climate Observing System (GCOS). We also investigate robust trends in global total cloud amount (CA) and cloud top temperature (CTT) that are significant and common across all CDRs. The latest versions of four global cloud CDRs, namely CLARA-A3, ESA Cloud CCI, PATMOS-x, and ISCCP-HGM are analysed. This assessment finds that all three AVHRR-based cloud CDRs (i.e., CLARA-A3, ESA Cloud CCI and PATMOS-x) satisfy even the strictest GCOS stability requirements for CA and CTT when averaged globally. While CLARA-A3 is most stable in global averages when tested against MODIS-Aqua, PATMOS-x offers the most stable CDR spatially. While we find these results highly encouraging, there remain, however, large spatial differences in the stability of and across the CDRs. All four CDRs continue to agree on the statistically significant decrease in global cloud amount over the last four decades, although this decrease is now weaker compared to the previous assessments. This decreasing trend has been stabilizing or even reversing in the last two decades; the latter is seen also in MODIS-Aqua and CALIPSO GEWEX datasets. Statistically significant trends in CTT are observed in global averages in the AVHRR-based CDRs, but the spatial agreement in the sign and the magnitude of the trends is weaker compared to those in CA. We also present maps of Common Stability Coverage and Common Trend Coverage that could provide a valuable metric to carry out an ensemble-based analysis of the CDRs.
An Integrated Geophysical and Unmanned Aerial Systems Surveys for Multi-Sensory, Multi-Scale and Multi-Resolution Cave Detection: The Gravaglione Site (Canale di Pirro Polje, Apulia)
Authors: Romano Gerardo , Capozzoli Luigi , Abate Nicodemo , De Girolamo Michele , Liso Isabella Serena , Patella Domenico , Parise Mario
Published: August 2023

Gravaglione represents one of the main swallow holes of the Canale di Pirro, low Murge, Apulia region, Italy. Here, after an intense rainstorm, a huge volume of rainwater accumulates at the surface. The drainage dynamics suggest that the Gravaglione could be part of a large, and potentially unknown, karst system. To verify this hypothesis and to acquire useful information on the possible karst environment features, an integrated aerial and geophysical multiscale and multimethod approach was applied. In particular, aerial photogrammetry, ground penetrating radar measurements and electrical resistivity tomography surveys were hence conducted and integrated to potentially detect the caves, define the subsurface volume possibly affected by karst systems and to verify the existence of links between the surficial morphology and the subsoil structure. The results provided interesting insights regarding the presence of a complex karst system extending up to 200 m b.g.l. and with a marked 3D nature. Overall, the Gravaglione case study demonstrates the geophysical approach validity and poses the basis for the development of an expeditive and low-cost high-resolution strategy for detecting and characterizing karst caves.
Feature Enhancement Using Multi-Baseline SAR Interferometry-Correlated Synthesis Images for Power Transmission Tower Detection in Mountain Layover Area
Authors: Wu Baolong , Wang Haonan , Chen Jianlai
Published: August 2023

The detection performance of power transmission towers in mountainous areas using SAR amplitude images is obviously influenced by the strong layover background (mainly including vegetation and soil) clutter interference around the towers. In this paper, power transmission tower detection in a mountainous layover area, using single-baseline SAR interferometry coherence images, which show better feature enhancement effectiveness compared to SAR amplitude images, is presented. Moreover, a novel feature enhancement method, that of generating multi-baseline SAR interferometry-correlated synthesis images for power transmission tower detection in a mountain layover area, is proposed. It demonstrates better feature enhancement (layover background cluster suppression) than that using single-baseline SAR interferometry coherence images. Theoretical analysis illustrates that the mountainous layover background clutter interference can be suppressed in the proposed single-baseline/multi-baseline SAR interferometry-correlated synthesis image. Experiments including over 12 repeat-pass TerraSAR-X staring spotlight mode acquisitions were conducted, and the results demonstrate that the detection performance with the use of multi-baseline SAR interferometry-correlated synthesis images showed an improvement of more than 43.6%, compared with the traditional method of using SAR amplitude images when benchmark deep learning-based detectors are used, i.e., Faster RCNN and YOLOv7.
Coal Flow Foreign Body Classification Based on ESCBAM and Multi-Channel Feature Fusion
Authors: Kou Qiqi , Ma Haohui , Xu Jinyang , Jiang He , Cheng Deqiang
Published: August 2023

Foreign bodies often cause belt scratching and tearing, coal stacking, and plugging during the transportation of coal via belt conveyors. To overcome the problems of large parameters, heavy computational complexity, low classification accuracy, and poor processing speed in current classification networks, a novel network based on ESCBAM and multichannel feature fusion is proposed in this paper. Firstly, to improve the utilization rate of features and the network’s ability to learn detailed information, a multi-channel feature fusion strategy was designed to fully integrate the independent feature information between each channel. Then, to reduce the computational amount while maintaining excellent feature extraction capability, an information fusion network was constructed, which adopted the depthwise separable convolution and improved residual network structure as the basic feature extraction unit. Finally, to enhance the understanding ability of image context and improve the feature performance of the network, a novel ESCBAM attention mechanism with strong generalization and portability was constructed by integrating space and channel features. The experimental results demonstrate that the proposed method has the advantages of fewer parameters, low computational complexity, high accuracy, and fast processing speed, which can effectively classify foreign bodies on the belt conveyor.
Tightly Coupled LiDAR-Inertial Odometry and Mapping for Underground Environments
Authors: Chen Jianhong , Wang Hongwei , Yang Shan
Published: August 2023

The demand for autonomous exploration and mapping of underground environments has significantly increased in recent years. However, accurately localizing and mapping robots in subterranean settings presents notable challenges. This paper presents a tightly coupled LiDAR-Inertial odometry system that combines the NanoGICP point cloud registration method with IMU pre-integration using incremental smoothing and mapping. Specifically, a point cloud affected by dust particles is first filtered out and separated into ground and non-ground point clouds (for ground vehicles). To maintain accuracy in environments with spatial variations, an adaptive voxel filter is employed, which reduces computation time while preserving accuracy. The estimated motion derived from IMU pre-integration is utilized to correct point cloud distortion and provide an initial estimation for LiDAR odometry. Subsequently, a scan-to-map point cloud registration is executed using NanoGICP to obtain a more refined pose estimation. The resulting LiDAR odometry is then employed to estimate the bias of the IMU. We comprehensively evaluated our system on established subterranean datasets. These datasets were collected by two separate teams using different platforms during the DARPA Subterranean (SubT) Challenge. The experimental results demonstrate that our system achieved performance enhancements as high as 50–60% in terms of root mean square error (RMSE).
Three-Dimensional Separate and Joint Inversions of Multi-Component Frequency-Domain Airborne Electromagnetic Data: Synthetic Model Studies
Authors: Yang Jun , Huang Xin , Yan Liangjun , Cao Xiaoyue
Published: August 2023

Airborne electromagnetic (AEM) surveys using airborne mobile platforms enable rapid and efficient exploration of areas where groundwork is difficult. They have been widely used in fields such as shallow resource exploration and environmental engineering. Three-dimensional AEM inversion is the main technique used in fine structural interpretation. However, most current methods focus on separate component data inversions, which limit the kinds of structures that can be recovered in the inversion results. To address this issue, a method for the robust 3D joint inversion of multicomponent frequency-domain AEM data was developed in this study. First, a finite element method based on unstructured tetrahedral grids was used to solve the forward problem of frequency-domain AEM data for both isotropic and anisotropic media. During inversion, a limited-memory quasi-Newton (L-BFGS) method was used to reduce the memory requirements and enable the joint inversion of large-scale multicomponent AEM data. The effectiveness of our algorithm was demonstrated using synthetic models for both isotropic and anisotropic cases, with 5% Gaussian noise added to the modeling data to simulate the measured data for separate and joint inversions. The results of the synthetic models show that joint inversion has advantages over separate inversion in that it enables the recovery of finer underground structures and provides a novel approach for the fine interpretation of frequency-domain AEM data.
GACN: Generative Adversarial Classified Network for Balancing Plant Disease Dataset and Plant Disease Recognition
Authors: Wang Xiaotian , Cao Weiqun
Published: August 2023

Plant diseases are a critical threat to the agricultural sector. Therefore, accurate plant disease classification is important. In recent years, some researchers have used synthetic images of GAN to enhance plant disease recognition accuracy. In this paper, we propose a generative adversarial classified network (GACN) to further improve plant disease recognition accuracy. The GACN comprises a generator, discriminator, and classifier. The proposed model can not only enhance convolutional neural network performance by generating synthetic images to balance plant disease datasets but the GACN classifier can also be directly applied to plant disease recognition tasks. Experimental results on the PlantVillage and AI Challenger 2018 datasets show that the contribution of the proposed method to improve the discriminability of the convolution neural network is greater than that of the label-conditional methods of CGAN, ACGAN, BAGAN, and MFC-GAN. The accuracy of the trained classifier for plant disease recognition is also better than that of the plant disease recognition models studied on public plant disease datasets. In addition, we conducted several experiments to observe the effects of different numbers and resolutions of synthetic images on the discriminability of convolutional neural network.
LoRaWAN Meets ML: A Survey on Enhancing Performance with Machine Learning
Authors: Farhad Arshad , Pyun Jae-Young
Published: August 2023

The Internet of Things is rapidly growing with the demand for low-power, long-range wireless communication technologies. Long Range Wide Area Network (LoRaWAN) is one such technology that has gained significant attention in recent years due to its ability to provide long-range communication with low power consumption. One of the main issues in LoRaWAN is the efficient utilization of radio resources (e.g., spreading factor and transmission power) by the end devices. To solve the resource allocation issue, machine learning (ML) methods have been used to improve the LoRaWAN network performance. The primary aim of this survey paper is to study and examine the issue of resource management in LoRaWAN that has been resolved through state-of-the-art ML methods. Further, this survey presents the publicly available LoRaWAN frameworks that could be utilized for dataset collection, discusses the required features for efficient resource management with suggested ML methods, and highlights the existing publicly available datasets. The survey also explores and evaluates the Network Simulator-3-based ML frameworks that can be leveraged for efficient resource management. Finally, future recommendations regarding the applicability of the ML applications for resource management in LoRaWAN are illustrated, providing a comprehensive guide for researchers and practitioners interested in applying ML to improve the performance of the LoRaWAN network.
A New EWMA Control Chart for Monitoring Multinomial Proportions
Authors: Gan Shengjin , Yang Su-Fen , Chen Li-Pang
Published: August 2023

Control charts have been widely used for monitoring process quality in manufacturing and have played an important role in triggering a signal in time when detecting a change in process quality. Many control charts in literature assume that the in-control distribution of the univariate or multivariate process data is continuous. This research develops two exponentially weighted moving average (EWMA) proportion control charts to monitor a process with multinomial proportions under large and small sample sizes, respectively. For a large sample size, the charting statistic depends on the well-known Pearson’s chi-square statistic, and the control limit of the EWMA proportion chart is determined by an asymptotical chi-square distribution. For a small sample size, we derive the exact mean and variance of the Pearson’s chi-square statistic. Hence, the exact EWMA proportion chart is determined. The proportion chart can also be applied to monitor the distribution-free continuous multivariate process as long as each categorical proportion associated with specification limits of each quality variable is known or estimated. Lastly, we examine simulation studies and real data analysis to conduct the detection performance of the proposed EWMA proportion chart.
Heritage Enhancement through Digital Tools for Sustainable Fruition—A Conceptual Framework
Authors: Maietti Federica
Published: August 2023

Digital technologies are becoming increasingly relevant in the processes of documenting, surveying, enhancing, and preserving cultural heritage, including through applications that are becoming more and more optimized and oriented toward new data management and accessibility processes. This great potential can find significant levels of application in the tourism sector, seeking new strategies to access, discover, and understand cultural assets. In this direction, many digital applications have already found interesting outcomes in the tourism sector, but there is large room for improvement in the applications for “minor”, small, or neglected cultural sites, not included in conventional tourism routes, which play a key role in social inclusion and territorial cohesion, as well as for the development of social, economic, and environmental sustainability. The paper presents a conceptual framework or possible outline to foster the use of digital technologies through a set of integrated bottom-up and top-down actions, to facilitate connections of minor sites into larger networks, contributing to the search for new forms of sustainable and active fruition and social participation.