On curve fitting between topological indices and Gibb's energy for semiconducting carbon nitrides network.

Quantitative structure relationships linked to a chemical structure that shed light on its properties and chemical reactions are called topological indices. This structure is upset by the addition of silicon (Si) doping, which changes the electrical and optical characteristics. In this article, we examine the connection between a chemical structure's Gibbs energy (GE) and K-Banhatti indices. In this article, we compute the K-Banhatti indices and then show the correlation between the indices and Gibb's energy of the molecule using curve fitting. Through the curve fitting, we see that there is a strong correlation between indices and Gibb's energy of a molecule. We use the polynomial curve fitting approach to see the correlation between indices and Gibb's energy.

Precision enhancement in variance estimation for complex environmental populations using adaptive cluster sampling.

Estimating dispersion in populations that are extremely rare, hidden, geographically clustered, and hard to access is a well-known challenge. Conventional sampling approaches tend to overestimate the variance, even though it should be genuinely reduced. In this environment, adaptive cluster sampling is considered to be the most efficient sampling technique as it provides generally a lower variance than the other conventional probability sampling designs for the assessment of rare and geographically gathered population parameters like mean, total, variance, etc. The use of auxiliary data is very common to obtain the precise estimates of the estimators by taking advantage of the correlation between the survey variable and the auxiliary data. In this article, we introduced a generalized estimator for estimating the variance of populations that are rare, hidden, geographically clustered and hard-to-reached. The proposed estimator leverages both actual and transformed auxiliary data through adaptive cluster sampling. The expressions of approximate bias and mean square error of the proposed estimator are derived up to the first-order approximation using Taylor expansion. Some special cases are also obtained using the known parameters associated with the auxiliary variable. The proposed class of estimators is compared with available estimators using simulation and real data applications.

Efficacy and Safety of Bempedoic Acid in Patients With Hyperlipidemia and Non-alcoholic Fatty Liver Disease.

Hyperlipidemia and its association with cardiovascular diseases have been significant public health concerns for many decades. Statins have long been the primary therapeutic option for lowering cholesterol levels and reducing cardiovascular mortality. However, a substantial number of patients either do not achieve optimal lipid goals with maximally tolerated statin doses or experience statin intolerance. In recent years, there have been remarkable developments in the field of hyperlipidemia management, leading to the approval of novel hypolipidemic drugs in North America and Europe. This article reviews the clinical development of bempedoic acid, a promising new drug, alone and in combination with ezetimibe, as an alternative approach to managing hyperlipidemia. The Phase I trials established the safety and tolerability of bempedoic acid, paving the way for further investigation in Phase II and Phase III trials. Multiple phase II studies evaluated the lipid-lowering efficacy of bempedoic acid as monotherapy or in combination with other hypolipidemic agents, showing significant improvements in lipid levels and inflammatory markers. The recently approved fixed drug combination of bempedoic acid and ezetimibe presents a viable option for patients who need additional LDL-C lowering alongside dietary modifications and maximally tolerated statin therapy.

Using multi-label ensemble CNN classifiers to mitigate labelling inconsistencies in patch-level Gleason grading.

This paper presents a novel approach to enhance the accuracy of patch-level Gleason grading in prostate histopathology images, a critical task in the diagnosis and prognosis of prostate cancer. This study shows that the Gleason grading accuracy can be improved by addressing the prevalent issue of label inconsistencies in the SICAPv2 prostate dataset, which employs a majority voting scheme for patch-level labels. We propose a multi-label ensemble deep-learning classifier that effectively mitigates these inconsistencies and yields more accurate results than the state-of-the-art works. Specifically, our approach leverages the strengths of three different one-vs-all deep learning models in an ensemble to learn diverse features from the histopathology images to individually indicate the presence of one or more Gleason grades (G3, G4, and G5) in each patch. These deep learning models have been trained using transfer learning to fine-tune a variant of the ResNet18 CNN classifier chosen after an extensive ablation study. Experimental results demonstrate that our multi-label ensemble classifier significantly outperforms traditional single-label classifiers reported in the literature by at least 14% and 4% on accuracy and f1-score metrics respectively. These results underscore the potential of our proposed machine learning approach to improve the accuracy and consistency of prostate cancer grading.

Multi-granularity prior networks for uncertainty-informed patient-specific quality assurance.

Deep Learning Automated Patient-Specific Quality Assurance (PSQA) aims to reduce clinical resource requirements. It is vital to ensure the safety and effectiveness of radiation therapy by predicting the dose difference metric (Gamma passing rate) and its distribution. However, current research overlooks uncertainty quantification in model predictions, limiting their trustworthiness in real clinical environments. This paper proposes a Multi-granularity Uncertainty Quantification (MGUQ) framework. A Bayesian framework that quantifies uncertainties at multiple granularities for multi-task PSQA, specifically Gamma Passing Rate (GPR) prediction and Dose Difference Prediction (DDP), integrates visualization-based interactive components. Using Bayesian theory, we derive a comprehensive multi-granularity loss function that comprises granularity-specific loss and coherence loss components. Additionally, we proposed Multi-granularity Prior Networks, a dual-stream network architecture, to infer the distributions of DDP (modeled as t-distributions) and GPR (modeled as Gaussian distributions) under specific statistical assumptions. Comprehensive evaluations are conducted on a dataset from ''Peeking Union Medical College Hospital'', and results show that our proposed method achieves a minimum MAE loss of 0.864 with a 2%/3 mm criterion and realizes the uncertainty visualization of dose difference. Further, it also achieves 100% Clinical Accuracy (CA) with a workload of 67.2%. Experiments demonstrate that the proposed framework can enhance the trustworthiness of deep learning applications in PSQA.

Lipase-copper complex/chitosan microspheres; loaded with attapulgite used for the treatment of E. coli-induced diarrhea.

Diarrhea is a globally major problem especially Escherichia coli induced diarrhea becoming fatal nowadays in developing countries. Colon-targeted chitosan microspheres (Ms) comprising of lipase­zinc and lipase­copper complexes were prepared, loaded with Attapulgite (Cts-Li-Zn-ATG/Ms and Cts-Li-Cu-ATG/Ms) for the treatment of bacterial diarrhea. Thin layer chromatography (TLC) and Fourier-transform infrared spectroscopy (FTIR) studies were used for confirmation of proposed lipase-metal complexes. Ms showed particle size range 18 ±â€¯0.24 to 23 ±â€¯0.83 µm, zeta potential -13.7 ±â€¯0.71 to -29.3 ±â€¯1.34 mV, PDI 0.5 ±â€¯0.04 to 1.0 ±â€¯0.07 and hemolytic activity was found to be <5 ±â€¯1.25 %. After coating with Eudragit S-100 for colon targeting, in-vitro % drug release of ATG at pH 7.4 was 80 ±â€¯0.21 % for Eud-Cts-Li-Zn-ATG/Ms while it was increased to 83 ±â€¯0.54 % for Eud-Cts-Li-Cu-ATG/Ms within 7 h, respectively. In-vivo anti-diarrheal activity of Eud-Cts-Li-Zn-ATG/Ms and Eud-Cts-Li-Cu-ATG/Ms was performed by oral challenge on albino mice having infectious diarrhea colonized with E. coli. Results revealed significant anti-diarrheal effect of proposed Eud-Cts-Li-Cu-ATG/Ms in terms of weight gain from 24 ±â€¯0.12 g to 26.05 ±â€¯0.31 g, which was 2-fold increase as compared to Eud-Cts-Li-Zn-ATG/Ms. Conclusively, Eud-Cts-Li-Cu-ATG/Ms provides an innovative alternate for the treatment of bacterial diarrhea with additional support of chitosan and lipase for nutritional support and immunity which was compromised in diarrheal patients.

Myocardial Infarction and Complete Heart Block in a Patient With Anomalous Origin of the Left Coronary Artery From the Pulmonary Artery (ALCAPA).

Anomalous origin of the left coronary artery from the pulmonary artery (ALCAPA) is a rare congenital malformation. We present a case of an elderly patient with ALCAPA presenting with complete heart block and non-ST-elevation myocardial infarction years after diagnosis and surgical correction. An 81-year-old female with a history of ALCAPA presented to the emergency department with chest pain and progressive mental deterioration. She was bradycardic and hypotensive. An electrocardiogram revealed a complete heart block. Troponin was 4.04 ng/mL. She received atropine and underwent transcutaneous pacing. Left heart catheterization revealed complete occlusion of the mid-left circumflex artery, which was intervened with balloon angioplasty and chronic total occlusion of the right coronary artery. She was supported with temporary transvenous pacing, did not require further pacing support, and was discharged home. Previous records unearthed that in 1988 she had presented with syncope and was diagnosed with ALCAPA, filling from right-to-left collaterals with large and ectatic coronaries. At the time, she underwent surgical correction with excision of the left coronary from the pulmonary artery and reimplantation in the left coronary cusp along the posterior aorta. She had remained asymptomatic after her surgery until this presentation. ALCAPA is extremely rare in adults. Insufficient collaterals to the left ventricle cause inadequate blood supply, leading to ischemia in adults, predisposing them to arrhythmias and risk of sudden death. Adults with ALCAPA remain at increased risk of adverse cardiac events later in life, requiring long-term monitoring.

Giardia lamblia Immunoassay: Systematic review and meta-analysis.

Immunoassays are important tools in diagnosing giardiasis, though there are several controversies inherent in the existing methods. We conducted a systematic review and meta-analysis to assess the pooled diagnostic accuracy of immunoassays in detecting the gastrointestinal disease-causing parasite Giardia lamblia. Our comprehensive search, which included PubMed, Scopus, and ScienceDirect from 2000 up until 2023, resulted in 34 studies reporting the performance of 24 different immunoassays. The overall pooled sensitivity and specificity of immunoassays and subgroup analyses were determined. Notably, ImmunoCardSTAT® and RIDASCREEN® Giardia were the most used assays (n = 6 studies each). They exhibited sensitivity and specificity of 84 % and 99 % and 93 % and 99 %, respectively. Sub-group analysis on the type of immunoassays (without the case-control studies) showed that commercial ELISA had higher sensitivity (96 %) compared to a commercial immunochromatographic (88 %), which justifies the difference of sensitivity between ImmunoCardSTAT® and RIDASCREEN® Giardia. However, the applicability between these two in clinical settings, replacing the gold standard, should be considered including the time, equipment requirement, and budget. Samples from symptomatic patients showed higher sensitivity (92 %) compared to asymptomatic patients (79 %). Overall, immunoassays can be a practical replacement for the current gold standard, but more information should be gathered regarding the cost of providing more conclusive suggestions on these findings.

Unravelling the kinetics, isotherms, thermodynamics, and mass transfer behaviours of Zeolite Socony Mobil - 5 in removing hydrogen sulphide resulting from a dark fermentative biohydrogen production process.

Research into the speciation of sulfur and hydrogen molecules produced through the complex process of thermophilic dark fermentation has been conducted. Detailed surface studies of solid-gas systems using real biogas (biohydrogen) streams have unveiled the mechanisms and specific interactions between these gases and the physicochemical properties of a zeolite as an adsorbent. These findings highlight the potential of zeolites to effectively capture and interact with these molecules. In this study, the hydrogen sulphide removal analysis was conducted using 0.8 g of the adsorbent and at various reaction temperatures (25-125 °C), a flow rate of 100 mL min-1, and an initial concentration of approximately 5000 ppm hydrogen sulphide. The reaction temperature has been observed to be an essential parameter of Zeolite Socony Mobil - 5 adsorption capacity. The optimum adsorption capacity attains a maximum value of 0.00890 mg g-1 at an optimal temperature of 25 °C. The formation of sulphur species resulting from the hydrogen sulphide adsorption on the zeolite determines the kinetics, thermodynamics, and mass transfer behaviours of Zeolite Socony Mobil - 5 in hydrogen sulphide removal and Zeolite Socony Mobil - 5 is found to improve the quality of biohydrogen produced in thermophilic environments. Biohydrogen (raw gas) yield was enhanced from 2.48 mol H2 mol-1 hexose consumed before adsorption to 2.59 mol H2 mol-1 hexose consumed after adsorption at a temperature of 25 °C. The Avrami kinetic model was fitted for hydrogen sulphide removal on Zeolite Socony Mobil - 5. The process is explained well and fitted using the Temkin isotherm model and the investigation into thermodynamics reveals that the adsorption behaviour is exothermic and non-spontaneous. Furthermore, the gas molecule's freedom of movement becomes random. The adsorption phase is restricted by intra-particle diffusion followed by film diffusion during the transfer of hydrogen sulphide into the pores of Zeolite Socony Mobil - 5 prior to adsorption on its active sites. The utilisation of Zeolite Socony Mobil - 5 for hydrogen sulphide removal offers the benefit of reducing environmental contamination and exhibiting significant applications in industrial operations.

On analysis of topological indices and heat of formation for benzyl sulfamoyl network via curve fitting model.

The study explores the intricate relationship between topological indices and the heat of formation in the benzyl sulfamoyl network. Topological indices of benzyl sulfamoyl networks are studied and also emphasize their properties statistically. The benzyl sulfamoyl has unique properties due to its crystalline structure and it is used in the form of artificial substance. We analyze the distributions and correlations of the benzyl sulfamoyl network with others by using statistical methods and also build a computational analysis for topological indices. The findings show a strong association between the variables, indicating that topological indices may be used to accurately predict thermodynamic characteristics and improve the effectiveness of molecular modelling and simulation procedures.

On comparative analysis of a two dimensional star gold structure via regression models.

In this research, the star gold structure with beta graphene is thoroughly examined. We mainly focus on computing degree-based topological indices, which provide information about the network's connectivity and complexity as well as structural features. In addition, we compute an entropy measure to represent the uncertainty, information richness, and degree of unpredictability in the network. Furthermore, this study explores the relationships between topological descriptors and entropy using regression models that are logarithmic, linear, and quadratic. By merging these regression models, we uncover hidden patterns and understand the underlying ideas governing the network's behaviour. Our findings shed light on the connection between topological indices and entropy. This work improves our understanding of star gold structure dynamics and provides a visual framework for interpreting their behaviour.

Prevalence of De Quervain disease in infant caregivers and its association with risk factors.

De Quervain's disease (DQD) is commonly reported in mothers during pregnancy up to delayed postpartum period. A cross-sectional study was conducted to assess infant caregivers who visited the paediatric outpatient department or vaccination centre in two hospitals of Lahore, during the months of May and June, 2021. A total of 190 subjects were interviewed directly and assessed by applying Finkelstein's test on both hands. Data was collected using Numeric Pain Rating Scale (NPRS) and Patient Rated Wrist Evaluation (PRWE) from positive subjects. They were asked to report their pain and difficulty level of the affected hand with worsened symptoms. The results exhibited 26.8% prevalence of DQD in a sample size of 190. Infant's age, lifting frequency and hand dominance were proved significant risk factors. However, caregiver's age, history of wrist pain, infant weight and relationship with infant were proved insignificant. Mean PRWE pain and functional scores were 23.14±7.72 and 18.53±6.09, respectively.

Discharge of rice-shaped particles from a monolayer flat-bottom silo.

In this work, we performed experiments regarding the outflow of spheres and two different types of rice-shaped particles in a quasi-two-dimensional monolayer silo with a flat bottom. We investigate the velocity and solid fraction profiles at the orifice and test whether the profiles for nonspherical particles have similar self-similar properties as in the spherical case. We find that the magnitude and shape of the velocity profiles for all three particle types are in a similar range. In contrast, the solid fraction at the orifice has a dome-shaped profile for both rice particles, whereas the profile for spherical particles is rather flat. The discharge rate determined from the velocity and solid fraction profiles describes the independently measured experimental discharge rate very well for all three investigated particle types.

Evaluating water-related health risks in East and Central Asian Islamic Nations using predictive models (2020-2030).

This paper presents a thorough evaluation of health outcomes linked to water-related challenges in Islamic nations across East Asia and Central Asia from 2020 to 2030. It has been examined carefully that the trajectory of deaths and disability-adjusted life years associated with unsafe water sources, lack of sanitation, and absence of handwashing facilities is showing a potential rise in negative health impacts due to water pollution. The direct health influences of water-related problems are thoughtful. The increase in deaths and DALYs due to poor water quality and sanitation leads to a higher occurrence of waterborne diseases such as cholera, diarrhea, and dysentery. These conditions not only cause instant health disasters but also subsidize to long-term health issues which include chronic gastrointestinal disorders and malnutrition that is particularly among susceptible populations like children and the elderly. Employing various predictive models including autoregressive integrated moving average, exponential smoothing, support vector machines, and neural networks. The study evaluates their predictive capabilities by using mean absolute percentage error. Support vector machines is found to be the most accurate in forecasting deaths and disability-adjusted life years which is outperforming autoregressive integrated moving average, exponential smoothing, and neural networks. This research aims to inform stakeholders by providing insights into effective strategies for improving water resource management and public health interventions in the targeted regions.

Stable and Lead-Safe Polyphenol-Encapsulated Perovskite Solar Cells.

Lead (Pb) halide perovskite solar cells (PSCs) exhibit impressive power conversion efficiencies close to those of their silicon counterparts. However, they suffer from moisture instability and Pb safety concerns. Previous studies have endeavoured to address these issues independently, yielding minimal advancements. Here, a general nanoencapsulation platform using natural polyphenols is reported for Pb-halide PSCs that simultaneously addresses both challenges. The polyphenol-based encapsulant is solution-processable, inexpensive (≈1.6 USD m-2), and requires only 5 min for the entire process, highlighting its potential scalability. The encapsulated devices with a power conversion efficiency of 20.7% retained up to 80% of their peak performance for 2000 h and up to 70% for 7000 h. Under simulated rainfall conditions, the encapsulant rich in catechol groups captures the Pb ions released from the degraded perovskites via coordination, keeping the Pb levels within the safe drinking water threshold of 15 ppb.

Topological indices and patterns in iron telluride networks.

This paper explores the complex interplay between topological indices and structural patterns in networks of iron telluride (FeTe). We want to analyses and characterize the distinct topological features of (FeTe) by utilizing an extensive set of topological indices. We investigate the relationship that these indicators have with the network's physical characteristics by employing sophisticated statistical techniques and curve fitting models. Our results show important trends that contribute to our knowledge of the architecture of the (FeTe) network and shed light on its physiochemical properties. This study advances the area of material science by providing a solid foundation for using topological indices to predict and analyses the behavior of intricate network systems. More preciously, we study the topological indices of iron telluride networks, an artificial substance widely used with unique properties due to its crystal structure. We construct a series of topological indices for iron telluride networks with exact mathematical analysis and determine their distributions and correlations using statistical methods. Our results reveal significant patterns and trends in the network structure when the number of constituent atoms increases. These results shed new light on the fundamental factors that influence material behavior, thus offering a deeper understanding of the iron telluride network and may contribute to future research and engineering of these materials.

Laparoscopic excision of a large retroperitoneal cyst: Case report and literature review.

Retroperitoneal cysts, a rare surgical phenomenon, present diagnostic challenges due to their typically asymptomatic nature. A 62-year-old male presented with a 4-month history of abdominal distension and increased burping. Upon clinical examination, a soft, distended, nontender abdomen with a palpable mass extending from the epigastric region to 3 cm below the umbilicus was revealed. Imaging revealed a 14.6 cm × 15.8 cm × 16.4 cm nonenhancing retroperitoneal lesion, compressing the right ureter and causing mild right hydronephrosis. Multiple gall bladder calculi, an umbilical hernia, and lipomatous lesions associated with adrenal glands were also discovered. Laparoscopic retroperitoneal cystectomy, cholecystectomy, and umbilical hernia repair were performed. Intraoperatively, 150 ml ascitic fluid and 1200 ml cystic fluid were found. This case highlights the intricate clinical presentation of a retroperitoneal cyst, emphasizing the need for surgical exploration. Successful laparoscopic management contributes to the evolving understanding of optimal treatment strategies.

Synthesis, Invitro Cytotoxic Activity and Optical Analysis of Substituted Schiff Base Derivatives.

Fluorescent cytotoxic compounds with readout delivery are crucial in chemotherapy. The growing demands of these treatment strategies require the novel heterocyclic molecules with better selectivity alongside fluorescence marker potential. In this context, a series of nine isatin Schiff base derivatives 4a-i were synthesized, characterized and evaluated for UV-visible, fluorescence, thermal and bioanalysis in order to explore the effect of structure on their bioprofiles. The analogue 4d exhibited maximum cytotoxic activity on Hella cells with percentage inhibition of 83% at 50 µM and 100% at 150 µM concentrations while 4c showed minimum cytotoxic activity with the value of 19% at 50 µM and 22% at 150 µM concentrations. Meanwhile, 4g was found to exhibit maximum inhibition potential towards Vero Cells with the percentage inhibition values of 83 at 50 µM concentration. The overall SAR study showed that the para-fluoro-substituted isatin moieties exhibited the appreciable percentage inhibition while the least activity was delivered by the isatin derivatives with para-bromo substitution.

Joint monitoring of mean and variance using Max-EWMA control chart under lognormal process with application to engine oil data.

The control charts are frequently employed in process monitoring to assess the average and variability of a process, assuming a normal distribution. However, it is worth noting that some process distributions tend to exhibit a positively skewed distribution, such as the lognormal distribution. This article proposed a maximum exponential weighted moving average control chart for joint monitoring of mean and variance under a lognormal process. The proposed control chart is evaluated by using the run length profile such as ARL and SDRL. The Monte Carlo simulation is conducted by using the R language to find the run length profile. An application is presented to demonstrate the design of the proposed control chart.

Microplastics in agroecosystems: Soil-plant dynamics and effective remediation approaches.

Increasing microplastic (MP) pollution, primarily from anthropogenic sources such as plastic film mulching, waste degradation, and agricultural practices, has emerged as a pressing global environmental concern. This review examines the direct and indirect effects of MPs on crops, both in isolation and in conjunction with other contaminants, to elucidate their combined toxicological impacts. Organic fertilizers predominantly contain 78.6% blue, 9.5% black, and 8.3% red MPs, while irrigation water in agroecosystems contains 66.2% white, 15.4% blue, and 8.1% black MPs, ranging from 0-1 mm to 4-5 mm in size. We elucidate five pivotal insights: Firstly, soil MPs exhibit affinity towards crop roots, seeds, and vascular systems, impeding water and nutrient uptake. Secondly, MPs induce oxidative stress in crops, disrupting vital metabolic processes. Thirdly, leachates from MPs elicit cytotoxic and genotoxic responses in crops. Fourthly, MPs disrupt soil biotic and abiotic dynamics, influencing water and nutrient availability for crops. Lastly, the cumulative effects of MPs and co-existing contaminants in agricultural soils detrimentally affect crop yield. Thus, we advocate agronomic interventions as practical remedies. These include biochar input, application of growth regulators, substitution of plastic mulch with crop residues, promotion of biological degradation, and encouragement of crop diversification. However, the efficacy of these measures varies based on MP type and dosage. As MP volumes increase, exploring alternative mitigation strategies such as bio-based plastics and environmentally friendly biotechnological solutions is imperative. Recognizing the persistence of plastics, policymakers should enact legislation favoring the mitigation and substitution of non-degradable materials with bio-derived or compostable alternatives. This review demonstrates the urgent need for collective efforts to alleviate MP pollution and emphasizes sustainable interventions for agricultural ecosystems.