Structural, Optical, Electrical and Photocatalytic Investigation of n-Type Zn2+-Doped α-Bi2O3 Nanoparticles for Optoelectronics Applications.

Herein, n-type pure and Zn2+-doped monoclinic bismuth oxide nanoparticles were synthesized by the citrate sol-gel method. X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), photoluminescence (PL) analysis, ultraviolet-visible (UV-vis) spectroscopy, and Hall effect measurements were used to study the effect of Zn2+ on the structural, optical, and electrical properties of nanoparticles. XRD revealed the monoclinic stable phase (α-Bi2O3) of all synthesized samples and the crystallite size of nanoparticles increased with increasing concentration of dopant. Optical analysis illustrated the red shift of absorption edge and blue shift of band gap with increasing concentration of dopant. Hall Effect measurements showed improved values (2.79 × 10-5 S cm-1 and 6.89 cm2/V·s) of conductivity and mobility, respectively, for Zn2+-doped α-Bi2O3 nanoparticles. The tuned optical band gap and improved electrical properties make Zn2+-doped α-Bi2O3 nanostructures promising candidates for optoelectronic devices. The degradation of methylene blue (MB, organic dye) in pure and zinc-doped α-Bi2O3 was investigated under solar irradiation. The optimum doping level of zinc (4.5% Zn2+-doped α-Bi2O3) reveals the attractive photocatalytic activity of α-Bi2O3 nanostructures due to electron trapping and detrapping for solar cells.

Intermodal travel planning and decision support integrated with transportation and energy systems.

The fast urbanization in China makes it all the more important to find sustainable solutions that are both comprehensive and energy-efficient. Because of its important role in lowering logistical expenses and pollutant emissions, intermodal transport is generally seen as an effective method of coordinating transportation operations, helping to address the growing economic and environmental issues. Considering the characteristics of a growing city, this article lays out a multi-criteria method for selecting which new initiatives for China's public transportation system should be prioritized. "Electric municipality bus," "light rail system," and "modernization to the current fleet and optimization" are the three enhancement initiatives that are outlined. Using transportation-related economic, social, and environmental sub-criteria, this research applies TOPSIS, an analytic hierarchy method and fuzzy approach for order preference by resemblance to ideal circumstance application, to prioritize transportation projects. The study aims to improve city life in Chongqing, China, by identifying the most environmentally friendly development projects. Applying the analytical hierarchy method (AHP), the relative importance of several sustainability criteria was established for use in making strategic decisions. The alternative projects for the given city have been ranked using the fuzzy TOPSIS approach. However, the investigated results show the supportive response of hybrid to environmental sustainability and vice versa for non-hybrid vehicles. However, the energy consumption in public transport remains a leading hurdle in sustainability across the three modes of transport: taxis, rail transit and buses. Finally, computer trains in public transport also surprisingly deal with environmental sustainability to keep the current & forthcoming generation from ecological harm. However, theoretical and empirical policy suggestions have been proposed to become clean & green shortly.

Carbon reduction through renewable energy and digitalization in emerging economies: Moderating role of public debt.

Utilizing renewable energy (RE) and embracing the digital economy (DIG) can significantly contribute to achieving economic, energy, and climate goals by promoting carbon reduction. In this regard, public debt (DEB) is particularly important since it provides the funds required to achieve these goals by investing in renewable energy and digital economy projects. This study examines the impact of public debt on the link between renewable energy and carbon emissions (CE), as well as the association between the digital economy and carbon emissions in emerging economies from 2003 to 2022. The study employed cross-sectional augmented autoregressive distributed lag (CS-ARDL) estimation to check the relationship between the variables. The findings of our study suggest that the integration of renewable energy sources and the growth of the digital economy have a positive impact on reducing carbon emissions. On the other hand, public debt has a positive effect on carbon emissions. In addition, the findings support the notion that interaction terms (RE × DEB) and (DIG × DEB) have a diminishing effect on carbon emissions. It can be concluded that the reduction of carbon emissions is contingent upon the utilization of public debt to promote the growth of renewable energy and the digital economy. Based on our study, it is recommended that emerging economies' needs focus on boosting renewable energy usage and digital economy initiatives. Additionally, it is necessary for these economies to maintain a sustainable level of debt.

The Efficacy of Intra-articular Platelet-Rich Plasma Injection Versus Corticosteroid Injection in the Treatment of Knee Osteoarthritis: A Prospective Comparative Analysis.

Background Knee osteoarthritis (KOA) is the most typical cause of knee pain and impairment worldwide. It is typified by slow and progressive degeneration of the articular cartilage of the knee joint. Although KOA is being managed with a variety of therapies, the comparison of the effectiveness of different intra-articular injections in KOA treatment in Pakistan is still not thoroughly investigated. Therefore, the purpose of this current study is to compare the efficacy of intra-articular administration of platelet-rich plasma (PRP) and corticosteroids (CSs) in the treatment of KOA. Methods This prospective comparative study was performed among one hundred patients diagnosed with KOA in Benazir Bhutto Hospital, Rawalpindi, for one year from April 2022 to March 2023. Specified inclusion and exclusion criteria were employed for patient enrollment. Patients were divided into two equal groups through simple random sampling. Group A patients received an intra-articular injection of PRP solution whereas group B patients received an intra-articular injection of CSs. Informed consent and ethical approval were also acquired prior to data collection. A self-designed proforma based on interviews was used to collect data. The data analysis in Statistical Package for the Social Sciences (IBM SPSS Statistics for Windows, IBM Corp., Version 25.0, Armonk, NY) was carried out via descriptive statistics and an independent t-test. Results Women (N=71, 71%) had a higher prevalence of KOA than men (N=29, 29%). The means of study variables like age, Visual Analog Scale (VAS) score, and Western Ontario and McMaster Universities (WOMAC) score were 56.10 ± 8.70 years, 8.08 ± 1.6, and 70.08 ± 8.76 respectively. The frequency of KOA on the right side was 62% (N=62) while it was 38% (N=38) on the left side. In the study population, 69% (N=69) patients had grade II KOA, and 31% (N=31) patients had grade III KOA. At the first-month, second-month, and third-month follow-up visits, there were statistically significant differences in the mean scores of the WOMAC and VAS between the study groups. However, at the first-month follow-up visit, mean scores of VAS and WOMAC were lower in group B than in group A while these were lower in group A as compared to group B, at the second-month and third-month follow-up appointments. Conclusions Intra-articular infiltration of both PRP and CSs was efficacious in the treatment of KOA-related pain and functional limitations; however, overall improvement in the PRP group was higher than CS group.

Assessing stress causing factors and language related challenges among first year students in higher institutions in Pakistan.

This mixed-methods study delves into stress factors among first-year undergraduate students in universities across Punjab, Pakistan. Five hundred students underwent evaluation for stress levels and academic achievement, with 10 selected for further analysis. The Perceived Stress Scale (Cohen et al., 1983) and demographic sheets were utilized for data collection. Analysis revealed a significant negative correlation between perceived stress and academic achievement. While women exhibited higher stress levels but better academic performance, students from public sector universities reported greater stress and lower academic success. In-depth interviews identified key stressors including heavy academic workload, financial constraints, limited support systems, competitive academic environments, and language-related challenges, notably weak English-speaking skills. These findings underscore the urgent need for enhanced support services, increased financial aid accessibility, a balanced academic culture, and the implementation of language support programs in Southern Punjab's higher education institutions. Addressing these stressors is crucial for fostering the well-being and academic success of first-year students, emphasizing the importance of creating a supportive learning environment during this transitional phase. The study offers insights into the multifaceted nature of stress experienced by first-year students and highlights the imperative of addressing these stressors to promote a nurturing learning environment conducive to academic success. Future research should explore the effectiveness of interventions aimed at reducing stress among first-year students and investigate additional factors that may contribute to stress in this population.

Appraisal of potentially toxic metals contamination in protein supplements for muscle growth: A chemometric approach and associated human health risks.

BACKGROUND: The use of protein supplements by athletes has risen due to their effectiveness in meeting dietary needs. However, there is a growing concern about the presence of potentially toxic metals (PTMs. Al, Cr, Mn, Ni, Cu, Zn, Cd, and Pb) in these supplements. Consequently, it is crucial to evaluate the levels of these PTMs to ensure the safety of the supplements. METHODS: The objective of the current study was to assess the PTMs concentrations in protein supplements and examine any possible health hazards. Twenty-five samples of protein supplements were purchased from different pharmacies to screen them for metals. Inductively coupled plasma-optical emission spectrometry (ICP-OES) was utilized to analyze metal content. Additionally, chemometric methods such as Pearson's correlation coefficient (PCC), principal component analysis (PCA), and hierarchical cluster analysis (HCA) were employed to identify possible sources of PTMs contamination in protein supplements. RESULTS: Concentration ranges for PTMs were found as, Al (0.03-3.05 mg/kg), Cr (0.11-0.89 mg/kg), Mn (1.13-8.40 mg/kg), Ni (0.06-0.71 mg/kg), Cu (1.05-5.51 mg/kg), Zn (2.14-27.10 mg/kg), Cd (0.01-0.78 mg/kg), and Pb (0.06-0.57 mg/kg). The weekly intake of Cd exceeded the level of tolerable weekly intake (TWI) set by the European Food Safety Authority (EFSA). CONCLUSION: Athletes, bodybuilders, fitness enthusiasts, dieters, young adults and adolescents, and health-conscious individuals should be conscious of Cd concentration as it does not compliance the TWI set by EFSA. Target hazard quotient (THQ < 1), hazard index (HI < 1), margin of exposure (MOE ≥ 1), percentile permitted daily exposure (% PDE < 100), and cumulative cancer risk (CCR < 1 × 10-3) analyses revealed that there are no appreciable non-carcinogenic and carcinogenic health risks associated with the use of these products.

Investigation of Pharmacologically Important Polyphenolic Secondary Metabolites in Plant-based Food Samples Using HPLC-DAD.

Polyphenolic compounds are vital components of plants. However, their analysis is particularly difficult and challenging due to their similar chemical and structural properties. In this study, we developed a simple and reproducible HPLC-DAD protocol for determining nineteen pharmacologically important polyphenols in plant-based food samples, including fruits (apple, banana, grapefruit, peach, grapes, plum, and pear), vegetables (onion, cabbage, capsicum, garlic, lemon, tomato, potato, and spinach), and other edible items (corn, kidney beans, green tea, black tea, and turmeric). The reference standards were pooled into four different groups based on logP values and expected retention time to avoid compound co-elution. These developed methods will be useful for the qualitative and quantitative analysis of biologically important polyphenolic compounds in various food samples and botanicals.

Unravelling the nexus between energy prices and exchange rate in Malaysia: Fresh insights from a non-linear perspective using threshold cointegration analysis.

This paper proposes a nonlinear threshold cointegration framework to study how energy prices affect Malaysia's nominal exchange rate, considering the money supply, income, and interest rate. The study employs a threshold cointegration approach utilizing threshold autoregressive and momentum threshold autoregressive models. The momentum threshold vector error correction model determines the short-run adjustment of exchange rate deviation from the long-run equilibrium level. The findings reveal that the nonlinear adjustment process to capture the short-run deviation in the long-run equilibrium path is primarily influenced by energy prices, money supply, and interest rates. These results highlight the importance of considering the impact of energy prices on exchange rate policies when formulating and implementing economic policies in Malaysia. The findings can also be valuable for decision-makers to comprehend the future dynamics of exchange rates and make well-informed decisions.

Percutaneous Transhepatic Sphincterotome-Guided Management of Post-Living Donor Liver Transplant Biliary Anastomotic Stricture: An Innovative Approach.

Post-liver transplantation biliary complications remain a serious concern and are associated with reduced patient and graft survival. Among various biliary complications, anastomotic stricture (AS) is the most frequent and challenging one. The frequency of AS after living donor liver transplantation (LDLT) is higher as compared to deceased donor liver transplantation. The management involves endoscopic retrograde cholangiopancreatography and/or percutaneous transhepatic biliary drainage, but refractory cases necessitate surgical revision. We present a case of complex biliary AS in a 63-year-old man after LDLT. The conventional approaches including endoscopic retrograde cholangiopancreatography, percutaneous transhepatic cholangiography, and cholangioscope-guided interventions remained unsuccessful. An innovative approach using a wire-guided sphincterotome through percutaneous transhepatic route successfully managed the complex post-LDLT AS. This is perhaps the first reported case of novel utilization of sphincterotome through transhepatic route for the management of AS in LDLT, averting major surgical interventions with related morbidity and mortality.

Impact of induced magnetic field on Darcy-Forchheimer nanofluid flows comprising carbon nanotubes with homogeneous-heterogeneous reactions.

The appealing traits of carbon nanotubes (CNTs) encompassing mechanical and chemical steadiness, exceptional electrical and thermal conductivities, lightweight, and physiochemical reliability make them desired materials in engineering gadgets. Considering such stimulating characteristics of carbon nanotubes, our goal in the current study is to scrutinize the comparative analysis of Darcy-Forchheimer nanofluid flows containing CNTs of both types of multi and single-wall carbon nanotubes (MWCNTs, SWCNTs) immersed into two different base fluids over a stretched surface. The originality of the model being presented is the implementation of the induced magnetic field that triggers the electric conductivity of carbon nanotubes. Moreover, the envisioned model is also analyzed with homogeneous-heterogeneous (h-h) chemical reactions and heat source/sink. The second-order slip constraint is assumed at the boundary of the surface. The transmuted high-nonlinearity ordinary differential equations (ODEs) are attained from the governing set of equations via similarity transformations. The bvp4c scheme is engaged to get the numerical results. The influence of different parameters is depicted via graphs. For both CNTs, the rate of heat flux and the surface drag coefficient are calculated using tables. It is highlighted that an increase in liquid velocity is witnessed for a varied counts volume fraction of nanoparticles. Also, Single-wall water-based carbon nanotube fluid has comparatively stronger effects on concentration than the multi-walled carbon nanotubes in water-based liquid. The analysis also indicates that the rate of heat flux and the surface drag coefficient are augmented for both SWCNTs and MWCNTs for different physical parameters. The said model is also validated by comparing it with a published result.

Neurokinin B Administration Induces Dose Dependent Proliferation of Seminal Vesicles in Adult Rats.

BACKGROUND: Neurokinin B; an endogenous decapeptide, mediates its reproductive physiological actions through gonadotropin releasing hormone. Despite the potential role of Neurokinin B on seminal vesicles, its effects on seminal vesicles in adult male mammals remain elusive. We aimed to investigate the potentials of variable doses of Neurokinin B, its agonist and antagonist on histomorphology and expression of NK3R on seminal vesicles, and secretory activity of seminal vesicles in adult male rats. METHODS: Adult male Sprague Dawley rats (n=10 in each group) were administered intraperitoneally with Neurokinin B in three variable doses: 1 µg, 1 ηg and 10 ρg while, Senktide (Neurokinin B agonist) and SB222200 (Neurokinin B antagonist) in 1 µg doses consecutively for 12 days. After 12 days of peptide treatment, half of the animals (n=05) in each group were sacrificed while remaining half (n=05) were kept for another 12 days without any treatment to investigate treatment reversal. Seminal vesicles were dissected and excised tissue was processed for light microscopy, immunohistochemistry and estimation of seminal fructose levels. RESULTS: Treatment with Neurokinin B and Senktide significantly increased while SB222200 slightly decrease the seminal vesicles weight, epithelial height and seminal fructose levels as compared to control. Light microscopy revealed increased epithelial height and epithelial folding as compared to control in all Neurokinin B and Senktide treated groups while decreased in SB222200. Effects of various doses of Neurokinin B, Senktide and SB222200 on seminal vesicles weight, epithelial height, seminal fructose levels and histomorphology were reversed when rats were maintained without treatments. Immuno-expression of Neurokinin B shows no change in treatment and reversal groups. CONCLUSION: Continuous administration of Neurokinin B and Senktide effect positively while SB222200 have detrimental effects on cellular morphology, epithelial height and seminal fructose levels in seminal vesicles. Effects of peptide treatments depicted a reversal towards control group when rats were kept without any treatment.

Serum metallomics reveals insights into the associations of elements with the progression of preleukemic diseases toward acute leukemia.

Acute leukemia (AL) is a critical neoplasm of white blood cells with two main subtypes: acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML). This study is focused on understanding the association of the preleukemic disease aplastic anemia (APA) with ALL and AML at metallomic level, using healthy subjects as a control. In this study, a validated and efficient inductively coupled plasma-mass spectrometry/MS-based workflow was employed to profile a total of 13 metallomic features. The study encompassed 41 patients with AML, 62 patients with ALL, 46 patients with APA, and 55 age-matched healthy controls. The metallomic features consisted of eight essential elements (Ca, Co, Cu, Fe, Mg, Mn, Se, and Zn) and five non-essential/toxic elements (Ag, Cd, Cr, Ni, and Pb). Six out of the 13 elements were found to be substantially different (P < .05) using absolute concentrations between serum samples of AL (ALL and AML) and preleukemia (APA) patients in comparison with healthy subjects. Elements including magnesium, calcium, iron, copper, and zinc were upregulated and only one element (chromium) was downregulated in serum samples of disease when compared with healthy subjects. Through the utilization of both univariate tests and multivariate classification modeling, it was determined that chromium exhibited a progressive behavior among the studied elements. Specifically, chromium displayed a sequential upregulation from healthy individuals to preleukemic disease (APA), and ultimately in patients diagnosed with ALL. Overall, metallomic-based biomarkers may have the utility to predict the association of APA with ALL.

Development of Data-driven Machine Learning Models and their Potential Role in Predicting Dengue outbreak.

ABSTRACT: Dengue fever is one of the most widespread vector-borne viral infections in the world, resulting in increased socio-economic burdens. The WHO has reported that 2.5 billion people are infected with dengue fever across the world, resulting in high mortalities in tropical and subtropical regions. The current article endeavors to present an overview of predicting dengue outbreaks through data-based machine-learning models. This artificial intelligence model uses real-world data such as dengue surveillance, climatic variables, and epidemiological data and combines big data with machine learning algorithms to forecast dengue. Monitoring and predicting dengue incidences have been significantly enhanced through innovative approaches. This involves gathering data on various climatic factors, including temperature, rainfall, relative humidity, and wind speed, along with monthly records of dengue cases. The study functions as an efficient warning system, enabling the anticipation of dengue outbreaks. This early warning system not only alerts communities but also aids relevant authorities in implementing crucial preventive measures.

Correction: Gastrointestinal tract disorders classification using ensemble of InceptionNet and proposed GITNet based deep feature with ant colony optimization.

[This corrects the article DOI: 10.1371/journal.pone.0292601.].

Revealing Melatonin's Mysteries: Receptors, Signaling Pathways, and Therapeutics Applications.

Melatonin (5-methoxy-acetyl tryptamine) is a sleep-inducing hormone, and the pineal gland produces it in response to the circadian clock of darkness. In the body, MT1 and MT2 receptors are mostly found, having an orthosteric pocket and ligand binding determinants. Melatonin acts by binding on melatonin receptors, intracellular proteins, and orphan nuclear receptors. It inhibits adenyl cyclase and activates phospholipase C, resulting in gene expression and an intracellular alteration environment. Melatonin signaling pathways are also associated with other intracellular signaling pathways, i. e., cAMP/PKA and MAPK/ERK pathways. Relative expression of different proteins depends on the coupling profile of G protein, accounting pharmacology of the melatonin receptor bias system, and mediates action in a Gi-dependent manner. It shows antioxidant, antitumor, antiproliferative, and neuroprotective activity. Different types of melatonin agonists have been synthesized for the treatment of sleeping disorders. Researchers have developed therapeutics that target melatonin signaling, which could benefit a wide range of medical conditions. This review focuses on melatonin receptors, pharmacology, and signaling cascades; it aims to provide basic mechanical aspects of the receptor's pharmacology, melatonin's functions in cancer and neurodegenerative diseases, and any treatments and drugs designed for these diseases. This will allow a basic comparison between the receptors in question, highlighting any parallels and differences that may exist and providing fundamental knowledge about these receptors to future researchers.

BRICS and the climate challenge: navigating the role of factor productivity and institutional quality in CO2 emissions.

The BRICS countries are important contributors to global efforts aimed at preventing a climate catastrophe. These countries account for half of the total emissions generated by the G20 nations. In this context, this paper examines the relationship between total factor productivity (TFP) and CO2 emissions (CE) in BRICS countries from 1996 to 2022, with institutional quality serving as a moderating factor. Moreover, a diverse range of methodologies was employed to address the problem of cross-sectional dependence; i.e., the CS-ARDL technique is used to analyze the relationship between variables in both the long and short-run. The AMG and CCEMG methods are employed for robustness analysis, while the Dumitrescu-Hurlin causality test is used to assess causality. Our empirical analysis demonstrates that TFP is positively associated with CE. Conversely, we find that institutional quality has a negative impact on CE. Furthermore, the study confirms that the interaction between TFP and institutional quality has a negative effect on CE. This implies that an improvement in institutional quality leads to a decrease in CE, as it strengthens the regulatory system governing CE and reduces pollution. Environmental policy must include economic flexibility and policy unpredictability in order to meet CO2 reduction targets. In addition, the study has identified bidirectional causal links between CE and variables such as TFP, institutional quality, and other control variables. According to our study, the BRICS countries should encourage digitalization and renewable energy production while preserving a reasonable standard of institutional quality since they have significant resource advantages in the renewable energy sector.

Strained Monolayer MoTe2 as a Photon Absorber in the Telecom Range.

To achieve the atomistic control of two-dimensional materials for emerging technological applications, such as valleytronics, spintronics, and single-photon emission, it is of paramount importance to gain an in-depth understanding of their structure-property relationships. In this work, we present a systematic analysis, carried out in the framework of density-functional theory, on the influence of uniaxial strain on the electronic and optical properties of monolayer MoTe2. By spanning a ±10% range of deformation along the armchair and zigzag direction of the two-dimensional sheet, we inspect how the fundamental gap, the dispersion of the bands, the frontier states, and the charge distribution are affected by strain. Under tensile strain, the system remains a semiconductor but a direct-to-indirect band gap transition occurs above 7%. Compressive strain, instead, is highly direction-selective. When it is applied along the armchair edge, the material remains a semiconductor, while along the zigzag direction a semiconductor-to-metal transition happens above 8%. The characteristics of the fundamental gap and wave function distribution are also largely dependent on the strain direction, as demonstrated by a thorough analysis of the band structure and of the charge density. Additional ab initio calculations based on many-body perturbation theory confirm the ability of strained MoTe2 to absorb radiation in the telecom range, thus suggesting the application of this material as a photon absorber upon suitable strain modulation.

Gastrointestinal tract disorders classification using ensemble of InceptionNet and proposed GITNet based deep feature with ant colony optimization.

Computer-aided classification of diseases of the gastrointestinal tract (GIT) has become a crucial area of research. Medical science and artificial intelligence have helped medical experts find GIT diseases through endoscopic procedures. Wired endoscopy is a controlled procedure that helps the medical expert in disease diagnosis. Manual screening of the endoscopic frames is a challenging and time taking task for medical experts that also increases the missed rate of the GIT disease. An early diagnosis of GIT disease can save human beings from fatal diseases. An automatic deep feature learning-based system is proposed for GIT disease classification. The adaptive gamma correction and weighting distribution (AGCWD) preprocessing procedure is the first stage of the proposed work that is used for enhancing the intensity of the frames. The deep features are extracted from the frames by deep learning models including InceptionNetV3 and GITNet. Ant Colony Optimization (ACO) procedure is employed for feature optimization. Optimized features are fused serially. The classification operation is performed by variants of support vector machine (SVM) classifiers, including the Cubic SVM (CSVM), Coarse Gaussian SVM (CGSVM), Quadratic SVM (QSVM), and Linear SVM (LSVM) classifiers. The intended model is assessed on two challenging datasets including KVASIR and NERTHUS that consist of eight and four classes respectively. The intended model outperforms as compared with existing methods by achieving an accuracy of 99.32% over the KVASIR dataset and 99.89% accuracy using the NERTHUS dataset.