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Sustainability has become the top priority for many businesses in the current era, and green marketing strategies are used to encourage the purchase of environmentally friendly goods. The research aims to analyze green marketing strategies and their impact on consumer behavior toward the environment in China. The study uses a logistic regression approach for data analysis. We found that environmental concerns and beliefs (ECB), Eco Labeling (EL), green packaging and branding (GPB), and green product, premium, and pricing (GPPP) have positive associations with consumers' attitudes and behaviors toward the environment. This study concludes that EL, ECB, EL, GBP, and GPPP are significant tools of green marketing strategies that considerably improve customers' environmental attitudes. The firm managers may adopt these green marketing strategies to achieve revenue and sustainable environmental goals. Furthermore, the government may provide incentives such as lower cooperate tax on green products industries, while private and public banks may provide subsidized loans to the green marking industries in the country. [ABSTRACT FROM AUTHOR]

Undoped, Fe, Sn doped and Fe/Sn co-doped copper oxides are prepared by precipitation synthesis. X-ray diffraction confirmed that the all synthesized powders show a monoclinic main CuO phase. The insertion of Fe or/and Sn within the CuO matrix moderately affects the preferential growth direction. Basically Fourier Transform Infrared (FTIR) confirmed about functional group and their vibrations in the CuO samples. The reflectance of the undoped sample is higher than that of the other samples. Compared to undoped CuO, the doped and co-doped NPs exhibit red-shifted gap energy. Indeed, the Fe-doped, and Sn-doped CuO NPs, exhibit a slight decrease of gap energy (1.47, 1.45 eV respectively) compared to the undoped CuO (1.49 eV), while the Fe/Sn co-doped sample has a lower gap energy of 1.06 eV. Additionally, the antibacterial efficiencies of the all-synthesized samples are tested against Staphyloccus species. Doped and undoped CuO nanopowders show important antibacterial activity on tested bacteria with MICs values ranged between 0.039 to 1.25 mg/ml. Minimum Inhibitory Concentration value of 0.039 mg/ml was obtained with Fe-doped CuO NPs (CuO:Fe NPs) against S.aureus ATCC33591, whereas the highest MIC value of 1.25 mg/ml was obtained with CuO:Sn nanopowder against the strain S. epidermidis, which was the most resistant strain. Moreover, all CuO NPs, except CuO:Fe/Sn showed important anti-adhesive and antibacterial activities against S. epidermidis when used as pellets. This was confirmed either by cell counts using the determination of CFU/ml of bacterial suspension inside the hole, or by using fluorescence microscopy. [ABSTRACT FROM AUTHOR]

This review article focuses on the impact of working fluid characteristics, geometrical parameters and the operating coefficients in thermal efficiencies of direct absorption solar collectors (DASCs). Regarding working fluid parameters, the review emphasized the importance of type of base fluid, nanoparticle properties, such as material, size, concentration and shape. Geometrical parameters, including the collector area, aspect ratio, tube diameter and collector panel design, were identified as crucial design considerations for maximizing DASC efficiency. Additionally, the review highlighted the significance of various operating parameters. Solar irradiance was identified as a critical factor, emphasizing the importance of optimizing the collector's orientation and tilt angle to maximize solar exposure. The fluid flow rate within DASCs was also recognized as a key parameter influencing heat transfer and overall performance. Increasing the thermal flow measurement of nanomaterials has been predicted to improve the heat transfer, ultimately leading to improved thermal efficiency. By carefully considering and optimizing these parameters, it is possible to maximize the efficiency and effectiveness of DASCs, thereby advancing the utilization of solar energy for sustainable and renewable power generation. [ABSTRACT FROM AUTHOR]

The availability of comprehensive datasets is a crucial challenge for developing artificial intelligence (AI) models in various applications and fields. The lack of large and diverse public fabric defect datasets forms a major obstacle to properly and accurately developing and training AI models for detecting and classifying fabric defects in real-life applications. Models trained on limited datasets struggle to identify underrepresented defects, reducing their practicality. To address these issues, this study suggests using a conditional generative adversarial network (cGAN) for fabric defect data augmentation. The proposed image-to-image translator GAN features a conditional U-Net generator and a 6-layered PatchGAN discriminator. The conditional U-Network (U-Net) generator can produce highly realistic synthetic defective samples and offers the ability to control various characteristics of the generated samples by taking two input images: a segmented defect mask and a clean fabric image. The segmented defect mask provides information about various aspects of the defects to be added to the clean fabric sample, including their type, shape, size, and location. By augmenting the training dataset with diverse and realistic synthetic samples, the AI models can learn to identify a broader range of defects more accurately. This technique helps overcome the limitations of small or unvaried datasets, leading to improved defect detection accuracy and generalizability. Moreover, this proposed augmentation method can find applications in other challenging fields, such as generating synthetic samples for medical imaging datasets related to brain and lung tumors. [ABSTRACT FROM AUTHOR]

This study focuses on the development of eco-friendly biobased adsorbents through a sustainable hydrothermal and freeze-drying synthesis process, utilizing cost-effective bio-sourced materials to minimize energy consumption and waste. The biobased adsorbents were elaborated using hydroxyethyl cellulose-ionic liquids and bentonite clay. The elaborated biocomposites were characterized using X-ray diffraction (XRD), Fourier-transform infrared spectroscopy/attenuated total reflection (FTIR/ATR), thermogravimetric analysis (TGA), and electron microscopy-energy dispersive X-ray (SEM–EDX), Brunauer–Emmett–Teller (BET) and zeta potential (ZP). Structural analysis confirms the intercalation and incorporation of HEC-ILs polymeric chains into Be-Na matrix and the formation of biocomposites. The [HEC-ILs/Be-Na] composite was subsequently employed for solid-phase extraction of Co(II) by investigating the effect of pH, initial Co(II) concentrations, time, temperature, and the presence of co-existing ions (Na(I), Li(I), Mn(II), Ni(II), and Al(III)). The adsorption kinetics of Co(II) metal ions were suitably characterized using the pseudo-second-order model (with R2 > 0.99). Furthermore, the adsorption isotherms conformed to the Langmuir model (with R2 > 0.97), suggesting a chemisorption process with an adsorption capacity of 69.8 mg/g. The thermodynamic study reveals that the adsorption process exhibits characteristics of spontaneity and endothermicity (ΔH° = 74.197 kJ mol−1, ΔG° < 0 kJ mol−1). The proposed mechanism for Co(II) adsorption on the developed biocomposite involves electrostatic interactions, ion exchange, and anion-π interactions. The biobased composite exhibited remarkable selectivity for Co(II) and demonstrated great potential as an adsorbent for industrial applications. [ABSTRACT FROM AUTHOR]

Finding a way to establish a sustainable cultivation system to produce celery as an important source of human being nutrition system due to its health and nutritional advantages is increasing by the day. Amino acids have a deep impact on plant metabolism; they improve mineral uptake and increase shoots and root growth, yield, chlorophyll biosynthesis, and photosynthesis rate as well as encouraging stimulation of several enzymes and coenzymes which lead to improved plant development and production besides quality. A two-year (2021/2022–2022/2023), trial was conducted to discuss two essential amino acids Glycine (GLY) and Tryptophan (TRP) effect on celery's growth, production, photosynthetic pigments, vitamin (C), total phenols, total flavonoids, total antioxidant activity, total indoles, nutritional status, and amino acids contents. During the winter season, three levels of each amino acid (0, 50, and 75 mg/l) were sprayed in two doses after 30 days of cultivation and 15 days from the first foliar. Results showed that the best performance of amino acids on plants vegetative growth characteristics, photosynthetic pigments, biochemical constituents, yield, and amino acids content was conducted by using (GLY + TRP) mix followed by TRP then GLY, while the best level of foliar applied amino acids was 75 mg/l in concentration. The best results on celery's vegetative growth, yield, chemical content, and amino acid content were recorded by using the (GLY + TRP) mix at the highest level of 75 mg/l in concentration. [ABSTRACT FROM AUTHOR]

Bacterial cellulose (BC) is a biopolymer synthesized extracellularly by certain bacteria through the polymerization of glucose monomers. This study aimed to produce BC using Enterobacter chuandaensis with fruit extracts from Phoenix dactylifera (D) and Musa acuminata (M) as carbon sources. Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy (ATR-FTIR) showed characteristic cellulose vibrations, while X-ray diffraction (XRD) identified distinct peaks at 15.34°, 19.98°, 22.58°, and 34.6°, confirming the cellulose structure. Whole-genome sequencing of E. chuandaensis identified key genes involved in BC production. The BC produced then exhibited a molecular weight of 1,857,804 g/mol, with yields of 2.8 g/L and 2.5 g/L for treatments D and M, respectively. The crystallinity index of the purified BC was 74.1, and 13C NMR analysis confirmed the dominant cellulose Iα crystalline form. The BC showed high biocompatibility in cytotoxicity assays, with cell viability between 92% and 100%, indicating its potential for use in biomedical applications. This investigation represents the first report of BC production by E. chuandaensis, which promises a new avenue for sustainable and efficient BC synthesis using fruit extracts as carbon sources. [ABSTRACT FROM AUTHOR]

Breast cancer remains a significant global health challenge, demanding innovative therapeutic approaches. Polyphenols, a class of natural compounds widely distributed in fruits, vegetables, and beverages, possess robust antioxidant and anti-inflammatory properties. They exhibit the potential to mitigate cancer cell proliferation and induce apoptosis. Nevertheless, their clinical utility is impeded by limited bioavailability and stability issues. These impediments find a solution through the advent of nanotechnology. Nano-carriers, owing to their diminutive dimensions and distinctive attributes, hold promise in enhancing the delivery of polyphenols to tumor sites, thereby augmenting bioavailability and therapeutic efficacy. Various nano-carriers, including liposomes, polymeric nanoparticles, and solid lipid nanoparticles, have been explored for polyphenol transport. These carriers safeguard polyphenols from degradation and enhance their solubility, facilitating targeted delivery to tumor sites and potentially reducing systemic adverse effects. This comprehensive review provides an in-depth examination of the current state of polyphenol-loaded nano-carriers in breast cancer therapy. It elucidates their potential as an innovative and precision-focused therapeutic modality to improve patient outcomes while mitigating side effects. [ABSTRACT FROM AUTHOR]

The clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) proteins are adaptive immune system found in bacteria and archaea. This system targets the genomes of invading pathogens in the bacteria for degradation and incorporates the fragments in the CRISPR cassettes. Because of its capacity to detect DNA and RNA, CRISPR/Cas system has emerged as a significant technique in molecular biology and has been adapted for genome editing. Also, it is been used in pathogen diagnostics, gene therapy, epigenetic regulation, and library construction. Although, CRISPR Cas system techniques have some limitations, they are the most promising diagnostic methods of the modern science and make it easy to use when combined with other techniques such as isothermal nucleic acid technique. Diagnostic methods such as real-time qPCR and isothermal nucleic acid amplification rely on a chain of reactions to detect pathogens. A single error in the preparation or experimental process can result in non-specific amplification. Furthermore, qPCR techniques are costly because they require skilled personnel and state-of-the-art equipment to carry out a series of procedures. Therefore, there is an urgent need to develop diagnostic methods that are simple and fast to utilize, particularly at the point of treatment. To answer this call, in the past decade, CRISPR/Cas system tools have been developing and actively used in detecting nucleic acids in pathogenic materials. In this review, we will shed light on the discovery of CRISPR/Cas and the CRISPR/Cas adaptive immune systems. Here, we will present a brief history of the classification of CRISPR/Cas systems, their applications in disease control, CRISPR/Cas13 nomenclature, and diagnostic tools. Additionally, we will discuss how the CRISPR/Cas13 system can detect noninfectious diseases. Further, we will conclude with the broader impact of CRISPR technologies on preventing pathogens, a serious human health threat. [ABSTRACT FROM AUTHOR]

Purpose: This study systematically reviews and meta-analyses the extent of ethnic minority representation in neuro-oncology Phase III and IV clinical trials, explores the effect of ethnicity on outcomes, and identifies predictors for the inclusion of ethnicity data in publications. Methods: Adhering to PRISMA guidelines, we conducted a comprehensive literature search across multiple databases, on Phase III and IV trials in neuro-oncology that reported on adult and/or paediatric subjects. Through meta-analysis, we synthesized information on overall survival, event-free survival, and the incidence of adverse outcomes across ethnicities. Results: From 448 identified articles, a fraction reported ethnicity data, with an even smaller number providing outcome data stratified by ethnicity. Most study participants were identified as White, underscoring a significant underrepresentation of minorities. Our meta-analysis did not reveal significant outcome differences by ethnicity, which may be attributed to the limited and inadequate reporting of data. Predictors for including ethnicity data were identified, including trials in North America(OR2.39, 95%CI 1.18–5.12, p < 0.02),trials of drugs or biologic agents(OR 5.28, 95%CI 1.43–3.42, p < 0.05),and trials funded by charities(OR 2.28, 95% CI 1.04–5.27, p < 0.05) or pharmaceutical companies(OR 3.98, 95% CI 1.60–10.0, p < 0.005). Conclusion: The underrepresentation of minorities in neuro-oncology clinical trials and the inadequately characterized impact of ethnicity on treatment outcomes highlight a critical need for more inclusive recruitment strategies and improved reporting standards. Change is necessary to ensure trials reflect the diversity of the patient population, which is essential for developing tailored strategies and improving outcomes. Future research should prioritize understanding the role of ethnicity in neuro-oncology to facilitate personalized treatment approaches. [ABSTRACT FROM AUTHOR]

Size hierarchy is a distinct feature of nanogold-catalysts as it can strongly affect their performance in various reactions. We developed a simple method to generate AunSm nanoclusters of different sizes by thermal treatment of an Au144(PET)60 (PET: phenylethanethiol) parent cluster. These clusters, deposited on activated carbon, exhibit excellent catalytic performance in the hydrochlorination of acetylene. In-situ ultraviolet laser dissociation high-resolution mass spectrometry of the parent cluster in the presence of acetylene revealed a remarkable cluster size-dependence of acetylene adsorption, which is a crucial step in the hydrochlorination. Systematic density functional theory calculations of the reaction pathways on the differently-sized clusters provide deeper insight into the cluster size dependence of the adsorption energies of the reactants and afforded a scaling relationship between the adsorption energy of acetylene and the co-adsorption energies of the reactants (C2H2 and HCl), which could enable a qualitative prediction of the optimal AunSm cluster for the hydrochlorination of acetylene. [ABSTRACT FROM AUTHOR]

El Qaa plain is one of the promising areas for agriculture projects, owing to its soil and groundwater resources. So, 14 groundwater samples were collected, chemically analyzed, hydrochemical (ratios, models and plots) and GIS techniques were applied, to evaluate the factors governing this water chemistry and suitability for irrigation. The results indicated the expansion of the agricultural area 8 times in the last 2 decades. The water can be divided into two groups; (A) freshwater (TDS ≤ 1000) in the eastern part of the study area within the clastic weathered basement rocks part of the aquifer, and (B) saline water (TDS > 1000) in the western part within the carbonates and evaporites rich sediments and close to the Gulf of Suez. The deduced factors controlling groundwater chemistry were precipitation, evaporites dissolution, seawater intrusion and ion exchange process. The calculated sodium absorption ratio (SAR) was < 10 indicating the good quality of this water for irrigation without sodicity hazard. Water of Group (A) (electric conductivity < 2250µS/cm) can be used safely for irrigation without any impact of salinity on all types of soil and plants. Group (B) water (electric conductivity > 2250µS/cm) has salinity hazard and can be used for irrigation on well-permeable soils and salt-tolerant plants. The concentrations of the studied potentially toxic elements (PTEs) were within the permissible limit for irrigation. Expansion in agricultural activities has adverse impact on groundwater quality. So, eco-friendly fertilizers should be applied in this promising area with the application of hydrologic pumping advises to safe aquifer quality from the degradation. [ABSTRACT FROM AUTHOR]

Purpose: To investigate functional, oncological and complication outcomes in women undergoing robot-assisted cystectomy (RARC) with intracorporeal orthotopic neobladder. Methods: From a multi-institutional database, we identified females with bladder cancer treated with RARC and intracorporeal orthotopic neobladder. We evaluated the continence rate, short-term oncological outcomes, and complication rates. Analyses were repeated and stratified by the status of preserving gynecological organs. Results: The study involved 146 patients with the median age 60 years (IQR, 51–66 years). Pelvic organ-preserving procedure (POP) was performed in 77 patients (53%). Overall daytime and nighttime continence rates were 54% and 53%, respectively. For POP, the continence rate was 58% for both daytime and nighttime continence. In the non-POP cohort, the continence rate was 50% for daytime and 49% for nighttime continence. Both groups had balanced positive surgical margin rates (5,3% for POP and 4,7% for non-POP). In the whole cohort, high-grade (Clavien-Dindo ≥3) early and late complication rate was 7,5% and 7,5%, respectively. Conclusions: Robot-assisted radical cystectomy with intracorporeal orthotopic neobladder in females demonstrate excellent functional and complication outcomes. Pelvic organ-preserving cystectomy enhances urinary continence rates without adversely affecting surgical margins. Orthotopic neobladder in selected women with bladder cancer, along with pelvic organ-preserving cystectomy may be used for improved functional outcomes without compromising oncological results. [ABSTRACT FROM AUTHOR]

In this paper, we prove the existence of at least two solutions to some semilinear elliptic equation defined in the whole euclidean space R 2. The nonlinearity consists of two terms: one presents a singularity at the origin and the other has a doubly exponential behavior at infinity. This new exponential behavior is governed by a recently established weighted inequality of Trudinger–Moser type. A combination of perturbation arguments and variational tools is employed to obtain our multiplicity result. [ABSTRACT FROM AUTHOR]

Device-to-device (D2D) communications, regarded as a crucial technology for the Beyond Fifth-Generation (B5G) wireless networks, provide substantial benefits including elevated spectrum effectiveness, improved coverage, and traffic offloading. The mode selection and channel allocation play an important role in ensuring the data rate and enhancing user experience in D2D communications. The dynamic switching of communication modes by D2D User Equipments (UEs) depends on the extent of shared resources among D2D pairs. In this paper, we examine the issue of joint mode selection and resource allocation for D2D communication within a cellular network in an uplink scenario. The main objective of this study is to optimize the overall sum rates of the network, while simultaneously guaranteeing the Quality of Service (QoS) requirements. Three communication modes are considered which are Direct Mode (MD), Relay-assisted Mode (RM), and Local route Mode (LM). In addition, each D2D pair has the option to be allocated either a dedicated channel or a reused channel. We present an innovative approach for the simultaneous determination of mode selection and channel allocation in D2D communication. The proposed approach is based on a greedy strategy and a modified many-to-many matching technique that effectively selects the best communication mode and assigns the optimal channel for each D2D pair, respectively. The simulation results illustrate that the presented approach exhibits a significant improvement in the network performance when compared to the benchmark algorithms. The proposed scheme is evaluated with perfect and imperfect Channel State Information (CSI) conditions. [ABSTRACT FROM AUTHOR]

Human comfort and safety are the most important criterion in the manufacturing of an automobile, for this reason, every manufacturing industry assures the reliability and quality of components utilized in the automobile industry. Air Conditioner (A/C) is an essential part of an automobile that significantly contributes to human comfort and safety. It is essential to remove the failures in the manufacturing of A/C to enhance quality and reliability. In this research, a fuzzy failure mode and effects analysis (Fuzzy-FMEA) technique has been established to analyze and eradicate the risks of 16 possible failures in suction hose manufacturing of automobile A/C. It starts from defining, categorizing, and evaluating all risk failures and then ranking them by assigning fuzzy linguistic variables by the team of experts. To validate the proposed technique, the air conditioner suction hose manufacturing process for automobiles is considered as a case study. The highest value of RPN was obtained for the multiple failure modes F1 (Fluxing on the outer surface of the flange), F2 (Coating having dust particles), F6 (Weak Sleeve locking), and F7 (hard locking and clamping dies) using conventional FMEA technique. The highest values of RPN were obtained for the potential failure modes F5 (coating length less than standard), F1, and F3 using Fussy-FMEA. The results show that this Fuzzy-FMEA technique is effective and reasonable to control quality and enhance productivity and reliability. [ABSTRACT FROM AUTHOR]

Background: While REIMS technology has successfully been demonstrated for the histological identification of ex-vivo breast tumor tissues, questions regarding the robustness of the approach and the possibility of tumor molecular diagnostics still remain unanswered. In the current study, we set out to determine whether it is possible to acquire cross-comparable REIMS datasets at multiple sites for the identification of breast tumors and subtypes. Methods: A consortium of four sites with three of them having access to fresh surgical tissue samples performed tissue analysis using identical REIMS setups and protocols. Overall, 21 breast cancer specimens containing pathology-validated tumor and adipose tissues were analyzed and results were compared using uni- and multivariate statistics on normal, WT and PIK3CA mutant ductal carcinomas. Results: Statistical analysis of data from standards showed significant differences between sites and individual users. However, the multivariate classification models created from breast cancer data elicited 97.1% and 98.6% correct classification for leave-one-site-out and leave-one-patient-out cross validation. Molecular subtypes represented by PIK3CA mutation gave consistent results across sites. Conclusions: The results clearly demonstrate the feasibility of creating and using global classification models for a REIMS-based margin assessment tool, supporting the clinical translatability of the approach. [ABSTRACT FROM AUTHOR]

Background: Both obesity and depression pose significant public health challenges. Understanding the age-gender differences in the BMI-depression associations is crucial, especially in the Saudi context, where cultural norms, lifestyle factors, and socio-economic conditions may significantly influence these associations. We aimed to explore and elucidate these associations in Saudi adults, considering age and gender as crucial factors. Methods: The research utilized a cross-sectional web-based survey to examine the impact of age and gender on the associations between BMI and depression. The study included 4,683 Saudi adults aged 18–60 years. The questionnaire assessed socio-demographics, lifestyle factors, chronic illnesses, and self-reported height and weight to calculate BMI. Depression Inventory-II (BDI-II), a self-reported scale, was used to evaluate depression, categorizing participants into depression and non-depression groups. A snowball convenience sampling was utilized, with clear inclusion and exclusion criteria established to mitigate potential biases. Data analysis was stratified by age and gender, and binary logistic regression was utilized to determine the associations between depression and BMI, incorporating odds ratios (ORs) in both crude and adjusted forms, along with 95% confidence intervals (CIs). Results: The prevalence of depression was found to be 43.3%, while 21% of participants were classified as obese. Notably, individuals in the depression group were significantly older, predominantly female, and more likely to reside in the Western and Southern regions of Saudi Arabia. They had lower family income, were more frequently non-smokers, had a higher prevalence of chronic diseases, and had higher BMI. Moreover, obese individuals had significantly higher depression scores (p < 0.05). After adjusting for confounding factors, OR for depression was significantly higher among obese individuals (1.92 [1.56–3.36]). Stratified analysis by age and gender revealed higher ORs for depression among obese participants in older age and among women. Conclusion: This study highlights a significant association between obesity and increased prevalence of depression, with notable age and gender differences in this association. The findings suggest that older adults and women, particularly those with obesity, are at a higher risk for depression. These insights emphasize the importance of tailoring public health strategies and mental health interventions to address the specific needs of these vulnerable groups in Saudi Arabia. [ABSTRACT FROM AUTHOR]

The increasing incidence of skin cancer necessitates advancements in early detection methods, where deep learning can be beneficial. This study introduces SkinNet-14, a novel deep learning model designed to classify skin cancer types using low-resolution dermoscopy images. Unlike existing models that require high-resolution images and extensive training times, SkinNet-14 leverages a modified compact convolutional transformer (CCT) architecture to effectively process 32 × 32 pixel images, significantly reducing the computational load and training duration. The framework employs several image preprocessing and augmentation strategies to enhance input image quality and balance the dataset to address class imbalances in medical datasets. The model was tested on three distinct datasets—HAM10000, ISIC and PAD—demonstrating high performance with accuracies of 97.85%, 96.00% and 98.14%, respectively, while significantly reducing the training time to 2–8 s per epoch. Compared to traditional transfer learning models, SkinNet-14 not only improves accuracy but also ensures stability even with smaller training sets. This research addresses a critical gap in automated skin cancer detection, specifically in contexts with limited resources, and highlights the capabilities of transformer-based models that are efficient in medical image analysis. [ABSTRACT FROM AUTHOR]

Strontium oxide nanostructures (SrO NSs) have garnered intensive research captivation among scientists owing to their higher specific energy, tunable material properties, and quick reversible reactions. However, low conductivity and poor cyclical stability hinder their use in energy storage devices, especially in supercapacitors. Since doping is an effective way to enhance the performance of electrodes for electrochemical energy storage devices. Therefore, in this study, we report the synthesis of Barium-doped Strontium Oxide nanostructures (Ba-doped SrO NSs) using a composite hydroxide-mediated approach. Pure SrO NSs delivered the specific capacitance of 178 F/g at the current density of 1 A/g. The doping of Ba into SrO drastically improves the storage capacity. The 4% Ba-SrO NSs delivered the specific capacitance of 826 F/g at the current density of 1 A/g along with a high-power density of 250 W/Kg at an energy density of 28.68 Wh/Kg. Compared to conventional materials, Ba-doped SrO NSs demonstrated improved electrochemical stability, enhanced rate capability, and reduced impedance. The additional electroactive sites and extra electrons from Ba doping are key to these improvements. This study underscores the potential of Ba-doped SrO NSs for high-performance energy storage, offering significant advancements in electrochemical performance and stability. [ABSTRACT FROM AUTHOR]

Background: Penicillin has remained the most effective treatment for syphilis for several decades. Syphilitic retinal manifestations may persist following treatment and cause visual problems. In this case series, we describe three syphilis patients with persistent posterior segment manifestations due to chronic inflammation, incomplete treatment, and reinfection. Case series: Recommended initial treatment for all patients was 14 days of intravenous penicillin. Oral prednisone was added 48 h after initiation of penicillin therapy. Case 1: A 48-year-old female presented with gradual vision loss for two months. Fundus imaging revealed syphilitic outer retinopathy (SOR), papillitis, and acute syphilitic posterior placoid chorioretinopathy (ASPPC). After treatment, she had persistent cystoid macular edema (CME) and was treated with intravitreal triamcinolone injections and ketorolac drops. Case 2. A 24-year-old male presented with sudden vision loss for two days. On imaging, he had ASPPC, papillitis, and SOR. IV penicillin treatment was given for 10 days only. He had persistent SOR and was retreated with doxycycline and prednisone. Case 3: A 52-year-old male presented with eye pain and visual loss for one week. There was evidence of ASPPC and papillitis on imaging. One month after treatment, he had persistent papillitis and was restarted on oral prednisone. One year later, he was found to have recurrent ASPPC and was confirmed to be reinfected with syphilis, for which he was retreated. Conclusion: When treating persistent syphilitic ocular manifestations, we recommend checking that the penicillin treatment was complete and the RPR titers are declining. If both hold true, then the affected eye should be treated with anti-inflammatory therapy. Other factors that contribute to poor visual prognosis include treatment delay, poor initial visual acuity, macular edema, and HIV coinfection. [ABSTRACT FROM AUTHOR]

This article introduces the Modified Al-Biruni Earth Radius (MBER) algorithm, which seeks to improve the precision of categorizing eye states as either open (0) or closed (1). The evaluation of the proposed algorithm was assessed using an available EEG dataset that applied preprocessing techniques, including scaling, normalization, and elimination of null values. The MBER algorithm's binary format is specifically designed to select features that can significantly enhance the accuracy of classification. The proposed algorithm and competing ones, namely, Al-Biruni Earth Radius (BER), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WAO), Grey Wolf Optimizer (GWO) and Genetic Algorithm (GA) were evaluated using predefined sets of assessment criteria. The statistical analysis employed the ANOVA and Wilcoxon signed-rank tests and assessed the effectiveness and significance of the proposed algorithm compared to the other five algorithms. Furthermore, A series of visual depictions were presented to validate the effectiveness and robustness of the proposed algorithm. Thus, the MBER algorithm outperformed the other optimizers on the majority of the unimodal benchmark functions due to these considerations. Different ML models were used for classification, e.g., DT, RF, KNN, SGD, GNB, SVC, and LR. The KNN model achieved the highest values of Precision (PPV) (0.959425), Negative Predictive Value (NPV) (0.964969), FScore (0.963431), accuracy (0.9612), Sensitivity (0.970578) and Specificity (0.949711). Thus, KNN serves as a fitness function and is optimized by the utilization of Modified Al-Biruni earth radius (MBER). Finally, the accuracy of eye state classification achieved 96.12% using the proposed algorithm. [ABSTRACT FROM AUTHOR]

The research objective in the context of the study relates to the major concern of corrosion affecting the wind turbines in operation to find materials with high durability in relation to environmental conditions of operation, strength, and cost. A method is an integration of the Analytical Hierarchy Process (AHP) and VIKOR Multi-Criteria Decision Making (MCDM) techniques that will assess seven different material options on sixteen criteria that comprise corrosion resistance, mechanical properties, cost, and a negative environmental impact. From this result, the AHP method calculated the weights for the indicators and chose potential materials, and finally, the VIKOR method used these materials and compared and ranked them to obtain a compromise solution. The research novelty integrates the AHP and VIKOR MCDM methods to address corrosion in wind turbines. By evaluating seven materials against challenging sixteen criteria—including corrosion resistance, mechanical properties, cost, and toxicity, AHP ranks and weights the criteria, while VIKOR identifies the optimal material choice. This dual approach enhances the selection process, ensuring the chosen material improves turbine performance and durability, offering a significant advancement in the sustainable development of wind energy technology. In conclusion, by integrating AHP and VIKOR, it comprehensively evaluates multiple material options based on corrosion resistance, mechanical properties, cost, and environmental impact. This methodology effectively identifies materials that enhance wind turbine performance and extend their lifespan, addressing a critical industry challenge. The alternative exhibits a similarity to the positive ideal solution (Si) of 0.3704 and a relative closeness to the ideal solution (Ri) of 0.0750. Additionally, its priority ranking (Qi) is 0.001, placing it in the first rank for Carbon Fiber Reinforced Polymers (CFRP) within the selection methodology. [ABSTRACT FROM AUTHOR]

This study was aimed to compare the clinical and radiographic outcomes of patients with intercondylar fractures of the humerus treated with orthogonal and parallel plating methods via precontoured plates. This was a retrospective comparative study conducted on 50 adult patients with intercondylar humerus fractures that were surgically treated over an eleven-year period. The patients were divided into two groups: Group A underwent internal fixation via parallel plating, whereas Group B received orthogonal plating. Clinical outcomes were evaluated via the Mayo Elbow Performance Score (MEPS), and the radiographic assessments included time to consolidation, pseudoarthrosis, malunion and hardware removal. Both groups presented similar demographic and preoperative characteristics. The functional outcomes assessed by the MEPS were not significantly different between the groups. Radiographically, comparable healing times and rates of complications, including pseudoarthrosis, malunion and hardware removal, were observed. The study findings suggest that both orthogonal and parallel plating methods yield comparable clinical and radiographic outcomes in the treatment of intercondylar humerus fractures. These results underscore the effectiveness of both techniques and emphasize the importance of further research to elucidate the optimal plating method for specific fracture patterns. [ABSTRACT FROM AUTHOR]

Ganoderma lucidum is an important medicinal mushroom with outstanding pharmaceutical properties, including anticancer, antioxidant, anti-inflammatory, and immunomodulatory activities due to its bioactive compounds. Such compounds could be suitably enhanced in mushrooms via an appropriate selection of growing substrates. This study aimed to evaluate the effect of phenolic-rich forest and agricultural wastes on the yield, antioxidant, and antimicrobial activities of G. lucidum. Oak sawdust (OS) (control) was used as a basal substrate to which phenolic-rich wastes, i.e., grape pomace (GP) and green walnut hulls (GWH), were mixed in percentages of 12.5, 25, and 50% each. Spawn running period (SRP), time to primordia initiation (DPI), time to first harvest (DFH), yield, and biological efficiency (BE) of G. lucidum were determined, and total phenolic content and antioxidant activity of the fruitbody were measured. The antimicrobial activity was assessed by examining extracts' effect on the growth of three Gram (+) and four Gram (−) bacteria and one yeast. Substrates supplemented with 12.5% GP significantly increased the yield and BE of G. lucidum (112.16 g/kg and 33%, respectively). Moreover, 12.5 and 25% GWH-supplemented substrates and 25% GP-supplemented ones resulted in a significant increase in the antioxidant capacity of the fruit bodies. The mushrooms cultivated on GP- and GWH-supplemented substrates exhibited higher antimicrobial activity when compared to those of OS. Our findings revealed that the incorporation of GP in the growing substrate of G. lucidum has the potential to improve its yield, antioxidant, and antimicrobial activities. Therefore, this agricultural waste can be successfully used as a good supplement in the production of G. lucidum. [ABSTRACT FROM AUTHOR]

Diabetes is a persistent health condition led by insufficient use or inappropriate use of insulin in the body. If left undetected, it can lead to further complications involving organ damage such as heart, lungs, and eyes. Timely detection of diabetes helps obtain the right medication, diet, and exercise plan to lead a healthy life. ML approach has been utilized to obtain rapid and reliable diabetes detection, however, existing approaches suffer from the use of limited datasets, lack of generalizability, and lower accuracy. This study proposes a novel feature extraction approach to overcome these limitations by using an ensemble of convolutional neural network (CNN) and long short-term memory (LSTM) models. Multiple datasets are combined to make a larger dataset for experiments and multiple features are utilized for investigating the efficacy of the proposed approach. Features from the extra tree classifier, CNN, and LSTM are also considered for comparison. Experimental results reveal the superb performance of CNN-LSTM-based features with random forest model obtaining a 0.99 accuracy score. This performance is further validated by comparison with existing approaches and k-fold cross-validation which shows the proposed approach provides robust results. [ABSTRACT FROM AUTHOR]

Lung cancer is an important global health problem, and it is defined by abnormal growth of the cells in the tissues of the lung, mostly leading to significant morbidity and mortality. Its timely identification and correct staging are very important for proper therapy and prognosis. Different computational methods have been used to enhance the precision of lung cancer classification, among which optimization algorithms such as Greylag Goose Optimization (GGO) are employed. These algorithms have the purpose of improving the performance of machine learning models that are presented with a large amount of complex data, selecting the most important features. As per lung cancer classification, data preparation is one of the most important steps, which contains the operations of scaling, normalization, and handling gap factor to ensure reasonable and reliable input data. In this domain, the use of GGO includes refining feature selection, which mainly focuses on enhancing the classification accuracy compared to other binary format optimization algorithms, like bSC, bMVO, bPSO, bWOA, bGWO, and bFOA. The efficiency of the bGGO algorithm in choosing the optimal features for improved classification accuracy is an indicator of the possible application of this method in the field of lung cancer diagnosis. The GGO achieved the highest accuracy with MLP model performance at 98.4%. The feature selection and classification results were assessed using statistical analysis, which utilized the Wilcoxon signed-rank test and ANOVA. The results were also accompanied by a set of graphical illustrations that ensured the adequacy and efficiency of the adopted hybrid method (GGO + MLP). [ABSTRACT FROM AUTHOR]

The objective is to demonstrate that omitting ureteral stent placement in robotic intracorporeal urinary diversion does not lead to increased risk of perioperative complications, namely ureteral strictures or anastomotic leaks. We retrospectively reviewed the records of 68 consecutive patients who underwent robotic radical cystectomy with ileal conduit creation or orthotopic neobladder by a single surgeon between January 2020 and September 2023. Chronologically, the first cohort of patients had ureteral stents placed to bridge the ureteroenteric anastomosis, and in the second cohort, stenting was omitted. Cohort 1 consisted of 28 patients with surgeries performed between January 2020 and April 2021, while cohort 2 had 40 patients who underwent surgery from April 2021 to September 2023. The cohorts were well matched with regard to patient age, gender, ASA score and rate of neoadjuvant chemotherapy. The choice of urinary diversion was left to surgeon and patient preference, and there was no significant difference in the proportion of ileal conduits versus orthotopic neobladders within each cohort. Estimated blood loss, total operative time, inpatient length of stay and pathologic T and N staging did not statistically differ between the cohorts. Overall, there was no difference in the rates of postoperative ileus, ureteral stricture, anastomotic leak, infectious complications, and 30-day readmission rates between the groups. Tubeless ureteroenteric anastomosis in patients undergoing robotic radical cystectomy with intracorporeal diversion does not appear to increase the risk of anastomotic strictures or postoperative complications. Further prospective evaluation is warranted. [ABSTRACT FROM AUTHOR]

Graphene-based nanomaterials have been proved to be robust sorbents for efficient removal of environmental contaminants including arsenic (As). Biobased graphene oxide (bGO-P) derived from sugarcane bagasse via pyrolysis, GO-C via chemical exfoliation, and magnetite nanoparticles (FeNPs) via green approach using Azadirachta indica leaf extract were synthesized and characterized by Ultraviolet-Visible Spectrophotometer (UV-vis.), Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), mean particle size and Scanning electron microscopy (SEM) along with Energy dispersive spectroscopy (EDX) analysis. Compared to cellulose and hemicellulose, the lignin fraction was less in the precursor material. The GOC, bGO-P and FeNPs displayed maximum absorption at 230, 236, and 374 nm, respectively. FTIR spectrum showed different functional groups (C-OH, C-O-C, COOH and O-H) modifying the surfaces of synthesized materials. Graphene based nanomaterials showed clustered dense flakes of GO-C and thin transparent flakes of bGO-P. Elemental composition by EDX analysis of GO-C (71.26% C and 27.36% O), bGO-P (74.54% C and 24.61% O) and FeNPs (55.61% Fe, 4.1% C and 35.72% O) confirmed the presence of carbon, oxygen, and iron in synthesized nanomaterials. Sorption study was conducted with soil amended with different doses of synthesized nanomaterials (10, 50 and 250 mg) and exposed to 100, 300 and 500 ppm of As. Arsenic concentrations were estimated by colorimetry and atomic absorption spectroscopy (AAS). GO-C, bGO-P, and FeNPs showed substantial As removal efficiency i.e., 81 to 99.3%, 65 to 98.8% and 73.1–89.9%, respectively. Green synthesis of bGO-P and magnetite nanoparticles removed substantial amounts of As compared to GO-C and can be effectively deployed for As removal or immobilization. Higher and medium sorbent doses (250 and 50 mg) exhibited greater As removal and data was best fitted for Freundlich isotherm evidencing favorable sorption. Nevertheless, at low sorbent doses, data was best fitted for both models. Newly synthesized nanomaterials emerged as promising materials for As removal strategy for soil nano-remediation and can be effectively deployed in As contaminated soils. [ABSTRACT FROM AUTHOR]

Mechanistic reasoning about an artifact or system involves thinking about its underlying entities and the properties, activities, and cause-effect relationships of those entities. Previous studies of children's mechanistic reasoning about engineering solutions have mostly focused on specific mechanical systems such as gear trains. Yet there is growing interest in more contextualized, community-connected engineering design experiences for elementary students. Important questions remain about how the specific features of community contexts influence student opportunities for engineering design practice and reasoning. In this study, we explore whether comparisons in students' mechanistic reasoning can be made across a range of five different community design contexts. For this qualitative descriptive study, we focus on interview data collected after each of five community-connected engineering-enriched science curriculum units: accessible playground design (3rd grade, N = 8, district A, schools 1 and 2), displaced animal relocation design (3rd grade, N = 10, district A, school 1), migration stopover site design (4th grade, N = 4, district A, school 2), retaining wall design (4th grade, N = 13, district B, school 1), and water filter design (5th grade, N = 9 students, district A, school 3). The findings showed that all students named entities and described entity factors for the design solutions for all five units. For the playground, displaced animals, and stopover sites units, some students described the design artifacts without explicitly expressing connections between entity factors and/or the way factors linked up to the design performance. We argue that particular features of the design tasks influenced students' approaches to explaining their design solutions. Therefore, we can claim that comparisons can be made across different community-connected engineering design contexts in terms of children's mechanistic reasoning. [ABSTRACT FROM AUTHOR]

The relationships between metallogenic capacity and geochemical features of adakitic rocks along the South Tan-Lu Fault (STLF) remain unclear. In this study, the ore-barren adakitic rocks (Tuncang, Guandian and Wawuliu) exhibit higher K2O/Na2O ratios and lower Sr/Y ratios than the ore-bearing adakitic rocks (Chuzhou and Shangyaopu). These differences strongly suggest that the ore-barren adakitic rocks originated from the thickened lower continental crust (LCC), whereas the ore-bearing adakitic rocks were derived from oceanic slabs. Notably, the Tuncang granite exhibits higher Y/Yb and (Ho/Yb)N ratios than the Guandian granodiorite and Wawuliu intrusion. Accordingly, we suggest that the Tuncang granite likely originated from a delaminated eclogitic LCC, whereas the Guandian and Wawuliu intrusions were derived from a thickened basaltic LCC sources. The occurrence of diorite and gabbro mafic microgranular enclaves (MMEs) within the Tuncang granite strongly suggests a magma-mixing process. Considering their MgO contents and εNd(t) and (87Sr/86Sr)i values, we suggest that the gabbro MMEs were likely derived from an enriched mantle source previously metasomatized by subduction-related components and that the diorite MMEs were subsequently formed by magma mixing. Due to the slightly younger ages of the ore-bearing adakitic rocks, we propose a model in which the ore-barren adakitic rocks formed through LCC delamination at 130 Ma and the ore-bearing adakitic rocks formed through oceanic slab remelting at 125 Ma. Consequently, the exploration of Cu–Au mineralization along the STLF should focus on younger oceanic slab-derived adakitic rocks. [ABSTRACT FROM AUTHOR]

Understanding sedimentary deposits in wetlands is crucial for their effective management. In this study, we used an integrated approach to estimate the radiocarbon (14C) chronology, sedimentation rate, and nutrient dynamics of the Khushalsar wetland in the Kashmir Himalaya. A UWITEC gravity corer was used to retrieve a 60 cm sediment core from the wetland. Accelerator mass spectrometer (AMS) facilitated 14C dating of core sediments revealed that the age of the sediments ranged from 248 ± 30 BP at 15–16 cm depth to 889 ± 27 BP at 59–60 cm depth. The linear increase in 14C age with depth revealed steady depositional conditions. According to the Constant Rate of Supply model applied to 14C ages, the sedimentation rate for Khushalsar wetland averaged 0.10 cm per year over the past 829 years, spanning from 1189 to 2018. Physicochemical analysis revealed a high concentration of ionic components in the sediments, wherein the electrical conductivity (EC) ranged from 2230 to 2970 µS cm−1, and organic matter (OM) ranged from 6.6 to 19.8%. The regression model demonstrated significant (p < 0.05) positive and negative associations between the physicochemical parameters. EC explained 91% of the variation in total dissolved solids (TDS) and 89% of the variation in salinity, whereas organic carbon (OC) explained 44% of the variation in nitrogen and 20% of the variation in phosphorus. Depth exhibited a strong positive association with C/N ratio (explaining 17% of the variation) and a negative association with OC, nitrogen, and phosphorus (explaining 59%, 56%, and 50% of the variation, respectively). The study concluded that primary productivity, stormwater runoff, anthropogenic inputs (domestic sewage, raw fecal matter, slaughterhouse wastes), and deforestation in the catchment area are responsible for the increased nutrient concentration and high sedimentation rate in the wetland. [ABSTRACT FROM AUTHOR]

In the current work, the sensing of nitrite (NO2–) in drinking water was analyzed by a simple and fast colorimetric method, with outstanding sensitivity and selectivity. For this purpose, we have fabricated the three-dimensional (3D) hierarchical flower-like acetic acid-capped NiO nanosheets (NSs) with enhanced surface area and exposed active sites. Different characterization techniques were carried out to elaborate the formation and structural analysis of prepared NiO NSs-based colorimetric sensor, which includes SEM imaging, AFM analysis, XRD, FTIR and BET analysis. The prepared colorimetric sensor was effectively used for the highly sensitive and selective detection of NO2– in drinking water, which exhibit excellent performance including a wide linear nitrite range of 1 × 10–8–3.6 × 10–6 M, where limit of detection (LOD) value is 2.0 × 10–7 M (0.2 μM) and limit of quantification (LOQ) is 6.8 × 10–7 M (0.68 μM) having R2 of 0.999. Moreover, the sensor also suggests strong selectivity toward nitrite as compared to other interfering species present in water sample. Further, different parameters were applied for experimental optimization to obtain the optimal performance of colorimetric sensor, which includes (a) amount of acetic acid-capped NiO NSs, (b) different pH values, (c) different exposure times, (d) different TMB concentrations and (e) different H2O2 concentrations. As a result, we analyzed that the prepared colorimetric nitrite sensing method can be reliably used in real-time analysis for future research work. [ABSTRACT FROM AUTHOR]

Increasing atmospheric CO2 levels change the elemental composition in plants, altering their nutritional quality and affecting consumers and ecosystems. Ecological stoichiometry provides a framework for investigating how CO2-driven nutrient dilution in pollen affects bees by linking changes in pollen chemical element proportions to the nutritional needs of bees. We investigated the consequences of five years of Free Air CO2 Enrichment (FACE) in a mature oak-dominated temperate forest on the elemental composition of English oak (Quercus robur) pollen. We measured the concentrations and proportions of 12 elements (C, N, P, S, K, Na, Ca, Mg, Cu, Zn, Fe, and Mn) in Q. robur pollen-bearing flowers collected from the Birmingham Institute for Forest Research (BIFoR) FACE facility. An elevated CO2 (eCO2) level of 150 ppm above ambient significantly reduced the S, K, and Fe levels and altered the multi-element ratio, with different elements behaving differently. This shift in pollen multi-element composition may have subsequent cascading effects on higher trophic levels. To assess the impact on bees, we calculated the stoichiometric mismatch (a measure of the discrepancy between consumer needs and food quality) for two bee species, Osmia bicornis (red mason bee) and Apis mellifera (honey bee), that consume oak pollen in nature. We observed stoichiometric mismatches for P and S, in pollen under eCO2, which could negatively affect bees. We highlight the need for a comprehensive understanding of the changes in pollen multi-element stoichiometry under eCO2, which leads to nutrient limitations under climate change with consequences for bees. [ABSTRACT FROM AUTHOR]

Diagenetically modified carbonate rocks are more common in the rock record. These modifications, have altered the carbonate rocks significantly. The Middle Jurassic carbonates of the SSF are extensively altered by the diagenetic evolution and several dolomitization process in the Kahi Section, Nizampur Basin. The primary objective of this study is to investigate the diagenetic evolution and multiphase dolomitization through cathodoluminescence petrography and stable isotopic studies. Field investigations show both host limestone (oolitic, fossiliferous and massive) and dolomites. Different types of dolomites were recognized on the basis of color contrast as dark grey color replacive dolomite, light grey dolomite, brownish dolomite and yellowish dolomite. Beside replacive phase voids and fracture filling cementing saddle dolomite, and cementing calcites are also recognized in the field. Petrographic studies show the complex diagenetic history of Samana Suk Formation from near surface diagenesis including micritization, neomorphism and several varities of dolomites. These verities are: RD1 is very fine to fine grained dolomite, RD2 is medium to coarse grained and anhedral to subhedral dolomite, RD3 is coarse to very coarse grained and planner euhedral zoned dolomite, and RD4 is coarse grained euhedral to subhedral ferroan dolomite. In addition, cementing saddle dolomite SD have large crystal, curved faces with sweeping extinction. cementing calcite phases are CC1 is granular mosaic, CC2 is twin, CC3 is fracture filling, and CC4 is ferroan calcite. The stable isotope values of limestone (δ18O: –7.13 to –0.73‰ V-PDB and δ13C: –0.05 to 1.32‰ V-PDB) showing depletion in from the Jurassic marine signature. The multiphase dolomites RD1–RD4, SD values (δ18O: –8.65 to –3.16‰ and δ13C: –3.56 to +2.09‰) indicate multiphase dolomitization. The C1–C3 values (δ18O: –11.07 to –8.97‰ and δ13C: –2.14 to +0.76‰) indicate highly depleted values of δ18O showing its source from the hydrothermal origin. From field, petrography and stable isotopic geochemistry data it is deduced that possible source of the Mg for hydrothermal dolomites is through activation of faults and fractures during active tectonic regime in the area and can be related to activation and reactivation of Kahi Thrust system. [ABSTRACT FROM AUTHOR]

This study assesses the potential of using multispectral images collected by an unmanned aerial system (UAS) on machine learning (ML) frameworks to estimate cereal rye (Secale cereal L.) biomass. Multispectral images and ground-truth cereal rye biomass data were collected from 15 farmers' fields up to three times between March and May in northwest Ohio. Images were processed to derive 13 vegetation indices (VIs). Out of 13 VIs, six optimal sets of VIs, including excess green (ExG), normalized green red difference index (NGRDI), soil adjusted vegetation index (SAVI), blue green ratio (B_G_ratio), red-edge triangular vegetation index (RTVI), and normalized difference red-edge (NDRE) were selected using the variance inflation factor (VIF) based feature selection approach. Six regression models including a multiple linear regression (MLR), elastic net (ENET), multivariate adaptive regression splines (MARS), support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGB) were investigated for estimation of cereal rye biomass based on the VIs. For most of the models, the six selected VIs performed better than or similar to the full set of 13 VIs with R2 ranging from 0.24 to 0.59 and RMSE ranging from 83.13 to 91.89 g/m2 during 10-fold cross-validation. During independent accuracy assessment with the selected set of VIs, XGB exhibited the highest R2 (0.67) and lowest RMSE (83.13 g/m2) and MAE (48.13 g/m2) followed by RF and ENET. For all the models, the agreement between observed and predicted biomass was high for biomass less than or equal to 200 g/m2 but decreased for biomass greater than 200 g/m2. When field-collected structural features were integrated with the selected VIs, the models showed improved performance, with R2 and RMSE of the models reaching up to 0.82 and 61.67 g/m2 respectively. Among the six VIs, SAVI showed the strongest impact on the model prediction for the best-performing RF and XGB regression models. The findings of this study demonstrate the potential of precisely estimating and mapping cereal rye biomass based on UAS-captured multispectral images. Timely information on cover crop growth can facilitate numerous decision-making processes, including planning the planting operations, and management of nutrients, weeds, and soil moisture to improve agronomic and environmental outcomes. [ABSTRACT FROM AUTHOR]

Electronic nose (eNose) is a modern bioelectronic sensor for monitoring biological processes that convert CO2 into value-added products, such as products formed during photosynthesis and microbial fermentation. eNose technology uses an array of sensors to detect and quantify gases, including CO2, in the air. This study briefly introduces the concept of eNose technology and potential applications thereof in monitoring CO2 conversion processes. It also provides background information on biological CO2 conversion processes. Furthermore, the working principles of eNose technology vis-à-vis gas detection are discussed along with its advantages and limitations versus traditional monitoring methods. This study also provides case studies that have used this technology for monitoring biological CO2 conversion processes. eNose-predicted measurements were observed to be completely aligned with biological parameters for R2 values of 0.864, 0.808, 0.802, and 0.948. We test eNose technology in a variety of biological settings, such as algae farms or bioreactors, to determine its effectiveness in monitoring CO2 conversion processes. We also explore the potential benefits of employing this technology vis-à-vis monitoring biological CO2 conversion processes, such as increased reaction efficiency and reduced costs versus traditional monitoring methods. Moreover, future directions and challenges of using this technology in CO2 capture and conversion have been discussed. Overall, we believe this study would contribute to developing new and innovative methods for monitoring biological CO2 conversion processes and mitigating climate change. [ABSTRACT FROM AUTHOR]

The detrimental effects of nitrite (NO2−) on environment as well as living organisms have attracted immense interest to sensitively detect it in the drinking water system. So, for this purpose, we have developed a highly sensible and portable colorimetric NO2− sensor based on the CZ-2 nanocomposite (NC). The three dimensional (3D) with large hierarchical structure CZ-2 NC sensor was formed by the coupling of g-C3N4 nanosheets (NSs) and ZIF-67 nanoparticles (NPs) by a simple hydrothermal process. The prepared sensor was successfully employed to detect NO2−, which manifests higher sensing characteristics like extensive sensitivity with large detection linear range of (1 × 10−3–7.20 × 10−1 μM) having a R2 of 0.999 and a lowest limit of detection (LOD) value of 0.16 ± 0.05 nM. Further, it also manifests excellent reversibility, better stability and durability, optimal reproducibility and superior repeatability. In addition, the sensor also depicts large selectivity towards NO2− and improved practicability in real water sampling. These commendable sensing properties were mainly ascribed to the large conductive structure and highest surface area of the CZ-2 NC structure. Thus, as a result, we analyzed that our fabricated colorimetric sensor was highly potent, its applications in the sensing fields can be explored for future perspective. [ABSTRACT FROM AUTHOR]

Background: The phase 3 NEURO-TTRansform trial showed eplontersen treatment for 65 weeks reduced transthyretin (TTR), halted progression of neuropathy impairment, and improved quality of life (QoL) in adult patients with hereditary TTR-mediated amyloidosis with polyneuropathy (ATTRv-PN), vs. historical placebo. Methods: NEURO-TTRansform enrolled patients with ATTRv-PN. A subset of patients were randomized to receive subcutaneous inotersen 300 mg weekly (Weeks 1–34) and subsequently switched to subcutaneous eplontersen 45 mg every 4 weeks (Weeks 37–81). Change in serum TTR and treatment-emergent adverse events (TEAEs) were evaluated through Week 85. Effects on neuropathy impairment, QoL, and nutritional status were also evaluated. Results: Of 24 patients randomized to inotersen, 20 (83%) switched to eplontersen at Week 37 and four discontinued due to AEs/investigator decision. Absolute change in serum TTR was greater after switching from inotersen (−74.3%; Week 35) to eplontersen (−80.6%; Week 85). From the end of inotersen treatment, neuropathy impairment and QoL were stable (i.e., did not progress) while on eplontersen, and there was no deterioration in nutritional status. TEAEs were fewer with eplontersen (Weeks 37–85; 19/20 [95%] patients) compared with inotersen (up to Week 35; 24/24 [100%] patients). Mean platelet counts decreased during inotersen treatment (mean nadir reduction ‒40.7%) and returned to baseline during eplontersen treatment (mean nadir reduction, ‒3.2%). Conclusions: Switching from inotersen to eplontersen further reduced serum TTR, halted disease progression, stabilized QoL, restored platelet count, and improved tolerability, without deterioration in nutritional status. This supports a positive benefit-risk profile for patients with ATTRv-PN who switch from inotersen to eplontersen. [ABSTRACT FROM AUTHOR]

Phosphorus chemistry occupies a pivotal position in contemporary organic chemistry but significant synthetic challenges still endure. In this report, a class of electrophilic phosphiranium salts, bearing fluorinated benzyl quaternizing groups, is introduced for the direct synthesis of diversely β-functionalized phosphines. We show that, in comparison with regular quaternary phosphiranium salts, these species display the sought balance of excellent stability and high electrophilic reactivity that allow the unlocking of the C-centered ring-opening reactions with different classes of weak nitrogen-, sulfur- and oxygen protic nucleophiles. In the arena of strained heterocyclic chemistry, phosphacycles as appealing electrophilic P-containing building blocks are underestimated. Here, the authors report a class of electrophilic phosphiranium salts bearing fluorinated benzyl quaternizing groups for the direct synthesis of diverselyβ-functionalized phosphines. [ABSTRACT FROM AUTHOR]

Purpose: This systematic review aims to comprehensively assess the safety and efficacy of transvaginal morcellation within an enclosed bag in gynecological surgeries, with a focus on its benefits, potential risks, and recommendations for its use. Methods: We conducted a comprehensive search of Epistemonikos, Web of Science, Medline (PubMed), Scopus, and Cochrane databases for studies on transvaginal contained morcellation in adult patients undergoing gynecological surgeries. The review included 22 studies that met the inclusion criteria, encompassing diverse surgical procedures, patient profiles, and outcomes. These studies were thoroughly reviewed and analyzed to assess the safety and efficacy of the morcellation technique. Results: Key findings from the selected studies indicate that transvaginal morcellation within an enclosed bag offers several advantages in gynecological surgeries, including reduced invasiveness, shorter operative times, and minimal blood loss when compared to conventional methods. The risk of tumor recurrence or dissemination appears to be low when appropriate precautions are taken, emphasizing the technique's safety, especially when performed by experienced surgical teams. While some studies reported complications, these were generally not directly associated with the morcellation technique. Conclusion: Transvaginal morcellation within an enclosed bag demonstrates potential as a safe and effective option for gynecological surgeries. The technique offers the benefits of minimally invasive procedures, including reduced bleeding, shorter recovery times, and improved cosmetic outcomes. This review also highlights the need for standardization in study methodologies and reporting, as the heterogeneity in outcomes across the selected studies poses challenges in drawing definitive conclusions. [ABSTRACT FROM AUTHOR]

Secondary amyloidosis (AA) is a disorder of protein conformation associated with inflammatory disorders. Detailed reports of patients diagnosed with AA and inflammatory bowel disease (IBD) are limited. This study reports the cases of eight patients, across three tertiary medical centers, diagnosed with both IBD and AA between 2000 and 2020. Seven patients had a diagnosis of Crohn disease (CD), while one had ulcerative colitis (UC). All patients were diagnosed with AA after being diagnosed with IBD (median: 15 years later). The small bowel (62.5%) and the colon (62.5%) were the most common IBD locations. 4 patients had undergone TNF-alpha inhibitor therapy and all CD patients required surgical treatment of their IBD. A history of fistula or abscess was identified in 5 patients. The most common initial site of AA was the kidney (75%). All 8 patients presented with some form of renal dysfunction and proteinuria (median: 1500 mg/24 h). Hypoalbuminemia was found in most patients. Six patients developed chronic kidney disease and 4 required dialysis. Anti TNF-alpha antibody therapy led to rapid improvement of renal function in one of four patients who received it. Three patients required a renal transplant. Four patients had died upon the latest follow-up (5-year survival: 75%). The presence of proteinuria, fistula, or abscess should serve as indicators for potentially increased AA risk in CD patients. [ABSTRACT FROM AUTHOR]

The aim of this study was to analyze the pregnancy process, especially the Familial Mediterranean fever (FMF) disease course and attack types during pregnancy, and to examine the relationship between disease-related factors and female infertility in FMF patients. The study, which was planned in a multicenter national network, included 643 female patients. 435 female patients who had regular sexual intercourse were questioned in terms of infertility. Pregnancy and delivery history, FMF disease severity and course during pregnancy were evaluated. The relationship between demographic and clinical findings, disease severity, genetic analysis results and infertility was investigated. 401 patients had at least 1 pregnancy and 34 patients were diagnosed with infertility. 154 patients had an attack during pregnancy. 61.6% of them reported that attacks during pregnancy were similar to those when they were not pregnant. The most common attack symptoms were fever, fatigue and abdominal pain-peritonitis (96%, 87%, and 83%, respectively) in the pregnancy period. The disease-onset age, disease activity score, gene mutation analyses, and regular colchicine use (> 90%) were similar between the fertile and infertile groups, while the frequency of previous appendectomy and alcohol consumption rates were higher in individuals with infertility. Our results indicated no significant change in the frequency and severity of attacks during pregnancy. The low rate of infertility (7.8%) in our patients was noted. It has been suggested that the risk of FMF-related infertility may not be as high as thought in patients who are followed up regularly and received colchicine. [ABSTRACT FROM AUTHOR]

Background: Pregnant persons are susceptible to significant complications following COVID-19, even death. However, worldwide COVID-19 vaccination coverage during pregnancy remains suboptimal. Objective: This study assessed the safety and effectiveness of COVID-19 vaccines administered to pregnant persons and shared this evidence via an interactive online website. Methods: We followed Cochrane methods to conduct this living systematic review. We included studies assessing the effects of COVID-19 vaccines in pregnant persons. We conducted searches every other week for studies until October 2023, without restrictions on language or publication status, in ten databases, guidelines, preprint servers, and COVID-19 websites. The reference lists of eligible studies were hand searched to identify additional relevant studies. Pairs of review authors independently selected eligible studies using the web-based software COVIDENCE. Data extraction and risk of bias assessment were performed independently by pairs of authors. Disagreements were resolved by consensus. We performed random-effects meta-analyses of adjusted relative effects for relevant confounders of comparative studies and proportional meta-analyses to summarize frequencies from one-sample studies using R statistical software. We present the GRADE certainty of evidence from comparative studies. Findings are available on an interactive living systematic review webpage, including an updated evidence map and real-time meta-analyses customizable by subgroups and filters. Results: We included 177 studies involving 638,791 participants from 41 countries. Among the 11 types of COVID-19 vaccines identified, the most frequently used platforms were mRNA (154 studies), viral vector (51), and inactivated virus vaccines (17). Low to very low-certainty evidence suggests that vaccination may result in minimal to no important differences compared to no vaccination in all assessed maternal and infant safety outcomes from 26 fewer to 17 more events per 1000 pregnant persons, and 13 fewer to 9 more events per 1000 neonates, respectively. We found statistically significant reductions in emergency cesarean deliveries (9%) with mRNA vaccines, and in stillbirth (75–83%) with mRNA/viral vector vaccines. Low to very low-certainty evidence suggests that vaccination during pregnancy with mRNA vaccines may reduce severe cases or hospitalizations in pregnant persons with COVID-19 (72%; 95% confidence interval [CI] 42–86), symptomatic COVID-19 (78%; 95% CI 21–94), and virologically confirmed SARS-CoV-2 infection (82%; 95% CI 39–95). Reductions were lower with other vaccine types and during Omicron variant dominance than Alpha and Delta dominance. Infants also presented with fewer severe cases or hospitalizations due to COVID-19 and laboratory-confirmed SARS-CoV-2 infection (64%; 95% CI 37–80 and 66%; 95% CI 37–81, respectively). Conclusions: We found a large body of evidence supporting the safety and effectiveness of COVID-19 vaccines during pregnancy. While the certainty of evidence is not high, it stands as the most reliable option available, given the current absence of pregnant individuals in clinical trials. Results are shared in near real time in an accessible and interactive format for scientists, decision makers, clinicians, and the general public. This living systematic review highlights the relevance of continuous vaccine safety and effectiveness monitoring, particularly in at-risk populations for COVID-19 impact such as pregnant persons, during the introduction of new vaccines. Clinical Trial Registration: PROSPERO: CRD42021281290. [ABSTRACT FROM AUTHOR]

Bioplastics such as polylactic acid are actually promoted as eco-friendly alternatives to fossil fuel-derived plastics, yet bioplastic toxicity remains poorly known. Here we studied the acute and multigenerational effects of polylactic acid microplastics on the copepod Eurytemora affinis, a bioindicator species of zooplankton. Results on acute toxicity revealed that lethal concentration values are higher for adult males, of 134.6 mg microplastic/L, than for adult females, of 106.9 mg/L. In multigeneration exposure, 400 µg/L polylactic acid microplastics induced higher mortality, production of smaller-sized eggs, elongation of the naupliar phase, and offspring with lower fitness. This led to reduction in female body size, including prosome length, width, and volume. Noteworthy, we also observed a recovery in copepod survival and reproductive parameters in the fifth filial generation. [ABSTRACT FROM AUTHOR]

With the rapid growth of the Internet of Things (IoT), the Internet of Medical Things (IoMT) has emerged as a critical sector that enhances convenience and plays a vital role in saving lives. IoMT devices facilitate remote access and control of various medical tools, significantly improving accessibility in the healthcare field. However, the connectivity of these devices to the internet makes them vulnerable to adversarial attacks. Safeguarding medical data becomes a paramount concern, particularly when precise biometric readings are required without compromising patient safety. This paper proposes a fast encryption mechanism to protect the color information in medical videos utilized within the IoMT environment. Our approach involves scrambling medical video frames using a rapid block-splitting method combined with simple operations. Subsequently, the scrambled frames are encrypted using different keys generated from the logistic map. To ensure the practicality of our proposed method in the IoMT setting, we implement the encryption mechanism on a cost-effective Raspberry Pi platform. To evaluate the effectiveness of our proposed mechanism, we conduct comprehensive simulations and security analyses. Notably, we investigate medical test videos during the evaluation process, further validating the applicability of our method. The results confirm our proposed mechanism's robustness by hiding patterns in original videos, achieving high entropy to increase randomness in encrypted videos, reducing the correlation between adjacent pixels in encrypted videos, and resisting various attacks. [ABSTRACT FROM AUTHOR]