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Enhancing the nanosized‐electrolyte's characteristics in Lithium‐driven micro‐batteries (LIMBs) is indispensable to improve the overall efficiency, security, and lifespan of these energy devices, designing nano‐sized electrolyte with a wide electrochemical stability window while keeping them compatible with electrode materials is one of the improvement goals. Battery technologies must go through this optimization process in order to be used practically. A sensing mechanism to keep an eye on the health of Li‐ion energy devices through the magnetization. Magnetic micro‐fluidic patterns that change could be a sign of battery deterioration or other problems with performance. Li‐ion battery health is one application of magnetic sensing that you can do with magnetic sensing. Battery health variations and other performance problems can be found using magnetic mass transport patterns. Present study examines the effects of magnetic field on Eyring–Powel mass transport in nano‐porous channels over a stretching sheet. The principal equations exhibiting the phenomenon are transformed into non‐linear differential equation by second‐order approximation by using a similarity transformation. Furthermore, a semi‐analytic technique named optimal homotopy asymptotic method (OHAM) is used to solve the transformed Eyring–Powell model. The numerical results demonstrated the impact of variations in velocity, skin‐friction coefficient and Sherwood number for the proposed scheme. [ABSTRACT FROM AUTHOR]

Gallic acid is a widely recognized bioactive compound that falls under the category of secondary polyphenolic metabolites and is fairly found in mango fruit waste, specifically in mango seed kernel (MSK). This study aimed to adopt a green extraction approach to extract this valuable compound via ultrasound‐assisted extraction (UAE) without using organic solvents but only water to obtain hazard‐free extracts, and the cost of extraction can be minimal. pH (2–8), solvent ratio (20–60 mL/g), temperature (30–60°C) and time (30–60 min) of extraction were the independent variables used for extraction optimization. Single‐factor experiments to obtain working ranges for selected extraction variables were carried out. A central composite design using response surface methodology was used to determine the optimum condition to obtain the maximum yield of gallic acid from MSK. The optimized extraction conditions were 3.9 pH, 36.25 mL/g solvent ratio, and 39.4°C of extraction temperature for 21.3 min. As a result, the optimized yield was 5.76 ± 0.41 mg/g, which was comparably equal to and/or better than the other solvent extraction systems. The results showed that gallic acid could efficiently be extracted via UAE under these optimal conditions. It is safer than extraction systems involving hazardous solvents that can be feasibly used for its nutraceutical and therapeutic applications. [ABSTRACT FROM AUTHOR]

Objective: To investigate the potential of deep learning for automatically delineating (segmenting) laryngeal cancer superficial extent on endoscopic images and videos. Methods: A retrospective study was conducted extracting and annotating white light (WL) and Narrow‐Band Imaging (NBI) frames to train a segmentation model (SegMENT‐Plus). Two external datasets were used for validation. The model's performances were compared with those of two otolaryngology residents. In addition, the model was tested on real intraoperative laryngoscopy videos. Results: A total of 3933 images of laryngeal cancer from 557 patients were used. The model achieved the following median values (interquartile range): Dice Similarity Coefficient (DSC) = 0.83 (0.70–0.90), Intersection over Union (IoU) = 0.83 (0.73–0.90), Accuracy = 0.97 (0.95–0.99), Inference Speed = 25.6 (25.1–26.1) frames per second. The external testing cohorts comprised 156 and 200 images. SegMENT‐Plus performed similarly on all three datasets for DSC (p = 0.05) and IoU (p = 0.07). No significant differences were noticed when separately analyzing WL and NBI test images on DSC (p = 0.06) and IoU (p = 0.78) and when analyzing the model versus the two residents on DSC (p = 0.06) and IoU (Senior vs. SegMENT‐Plus, p = 0.13; Junior vs. SegMENT‐Plus, p = 1.00). The model was then tested on real intraoperative laryngoscopy videos. Conclusion: SegMENT‐Plus can accurately delineate laryngeal cancer boundaries in endoscopic images, with performances equal to those of two otolaryngology residents. The results on the two external datasets demonstrate excellent generalization capabilities. The computation speed of the model allowed its application on videolaryngoscopies simulating real‐time use. Clinical trials are needed to evaluate the role of this technology in surgical practice and resection margin improvement. Level of Evidence: III Laryngoscope, 134:2826–2834, 2024 [ABSTRACT FROM AUTHOR]

We investigate the role of financial policy uncertainty in climate change risk. We use the financial policies uncertainty index to estimate its composite effectiveness on climate change. We test the financial development role from two perspectives covering the credit channel and market liquidation facilities for climate change. We also test the role of financial policy uncertainty through moderating channels of renewable energy production and financial development. Our sample comprises 42 developing economies from 1991 to 2020. We apply the fixed‐effects estimation, feasible generalized least squares (FGLS) method and bootstrap quantile to analyze the results. The empirical results reveal that financial policy uncertainty plays a significant role in climate change risk. We conclude that climate change risk management policies and financial policy uncertainties should be considered as key indicators of financial development. [ABSTRACT FROM AUTHOR]

This study aligns with the 2030 United Nations Sustainable Development Goals 3 and 11, which aim to "ensure healthy lives and promote well‐being for all at all ages" and "make cities and human settlements inclusive, safe, resilient, and sustainable". The study objectives are to (i) explore the impact of different sources of carbon emissions on life expectancy; (ii) evaluate if the impact differs across income groups, and (iii) determine if life expectancy is persistent. It contributes to the health‐environment literature but differs from two standpoints. First, it uses two essential sources of carbon emissions: liquid and solid fuels. Second, it engages robust analyses comprising the full sample and sub‐samples of income groups to further interrogate this intrinsic relationship. For this purpose, an unbalanced sample of 36 countries from Asia and the Pacific region (2005–2010) is used, and for robust analyses, three econometric methods: bootstrap ordinary least squares (BOLS), instrumental variables (IV), and system generalized method of moments (GMM) are implemented. Empirical results reveal that: (1) liquid and solid fuel emissions exert significant negative outcomes, (2) liquid fuel emissions exhibit the most adverse effect, (3) life expectancy is persistent, and (4) impact of liquid and solid fuel emissions on life expectancy across the income groups is diverse. These findings suggest that the management authorities of Asia and the Pacific region need to devise prudent and effective policies concerning human health and carbon emissions while allocating sufficient budget to the health sector to rescue more lives and, thereby, lengthen the life expectancy in the region. [ABSTRACT FROM AUTHOR]

Objective: The endoscopic and laryngoscopic examination is paramount for laryngeal, oropharyngeal, nasopharyngeal, nasal, and oral cavity benign lesions and cancer evaluation. Nevertheless, upper aerodigestive tract (UADT) endoscopy is intrinsically operator‐dependent and lacks objective quality standards. At present, there has been an increased interest in artificial intelligence (AI) applications in this area to support physicians during the examination, thus enhancing diagnostic performances. The relative novelty of this research field poses a challenge both for the reviewers and readers as clinicians often lack a specific technical background. Data Sources: Four bibliographic databases were searched: PubMed, EMBASE, Cochrane, and Google Scholar. Review Methods: A structured review of the current literature (up to September 2022) was performed. Search terms related to topics of AI, machine learning (ML), and deep learning (DL) in UADT endoscopy and laryngoscopy were identified and queried by 3 independent reviewers. Citations of selected studies were also evaluated to ensure comprehensiveness. Conclusions: Forty‐one studies were included in the review. AI and computer vision techniques were used to achieve 3 fundamental tasks in this field: classification, detection, and segmentation. All papers were summarized and reviewed. Implications for Practice: This article comprehensively reviews the latest developments in the application of ML and DL in UADT endoscopy and laryngoscopy, as well as their future clinical implications. The technical basis of AI is also explained, providing guidance for nonexpert readers to allow critical appraisal of the evaluation metrics and the most relevant quality requirements. [ABSTRACT FROM AUTHOR]

Exhibiting outstanding optoelectronic properties, antimony selenide (Sb2Se3) has attracted considerable interest and has been developed as a light absorber layer for thin‐film solar cells over the decade. However, current state‐of‐the‐art Sb2Se3 devices suffer from unsatisfactory "cliff‐like" band alignment and severe interface recombination loss, which deteriorates device performance. In this study, the heterojunction interface of an Sb2Se3 solar cell is improved by introducing effective aluminum (Al3+) cation into the CdS buffer layer. Then, the energy band alignment of Sb2Se3/CdS:Al heterojunction is modified from a "cliff‐like" structure to a "spike‐like" structure. Finally, heterojunction interface engineering suppresses recombination losses and strengthens carrier transport, resulting in a high efficiency of 8.41% for the substrate‐structured Sb2Se3 solar cell. This study proposes a facile strategy for interfacial treatment and elucidates the related carrier transport enhancement mechanism, paving a bright avenue to overcome the efficiency bottleneck of Sb2Se3 thin‐film solar cells. [ABSTRACT FROM AUTHOR]

Summary: Isoflavones are a class of secondary metabolites produced by legumes and play important roles in human health and plant stress tolerance. The C2H2 zinc‐finger transcription factor (TF) functions in plant stress tolerance, but little is known about its function in isoflavone regulation in soybean (Glycine max).Here, we report a C2H2 zinc‐finger TF gene, GmZFP7, which regulates isoflavone accumulation in soybean. Overexpressing GmZFP7 increased the isoflavone concentration in both transgenic hairy roots and plants. By contrast, silencing GmZFP7 expression significantly reduced isoflavone levels. Metabolomic and qRT‐PCR analysis revealed that GmZFP7 can increase the flux of the phenylpropanoid pathway. Furthermore, dual‐luciferase and electrophoretic mobility shift assays showed that GmZFP7 regulates isoflavone accumulation by influencing the expression of Isoflavone synthase 2 (GmIFS2) and Flavanone 3 β‐hydroxylase 1 (GmF3H1).In this study, we demonstrate that GmZFP7 contributes to isoflavone accumulation by regulating the expression of the gateway enzymes (GmIFS2 and GmF3H1) of competing phenylpropanoid pathway branches to direct the metabolic flux into isoflavone. A haplotype analysis indicated that important natural variations were present in GmZFP7 promoters, with P‐Hap1 and P‐Hap3 being the elite haplotypes.Our findings provide insight into how GmZFP7 regulates the phenylpropanoid pathway and enhances soybean isoflavone content. [ABSTRACT FROM AUTHOR]

Achieving sustainable development is the prime objective of every government. Based on Solow's theoretical proposition, this study attempts to explore empirically the linkages between tourism, energy consumption, and economic growth, for the top nine Asian travel and tourism countries including Indonesia between 1995 and 2018. The fully modified ordinary least squares method and Granger's causality approaches are implemented for empirical analysis. The empirical result reveals that tourism has a statistically positive impact on economic growth in Asia's top nine travel and tourist countries. Moreover, energy consumption, exports, and savings have also a positive and statistically significant impact on economic growth. The results of panel Granger causality tests demonstrate that there is a mutual interdependence between tourism, energy consumption, and economic growth in the selected panel country group. The empirical finding indicates the positive influences of tourism on economic growth; therefore, the government must strive to formulate a policy that would help to build infrastructural adequacy and promote tourism development in Asian countries. [ABSTRACT FROM AUTHOR]

The present study analyzes the boundary layer flow behavior of single‐walled Titania nanotube (SWTNT)–water nanofluid over a rotating disk. The main motivation behind such an investigation is that single‐walled Titania nanotubes (SWTNTs) exhibit significant results due to their extensive applications, low cost, high thermal conductivity, dielectric properties, and photocatalytic activities compared to prevalently existing single‐walled carbon nanotubes. The radial and azimuthal slip conditions are implemented. Fourth order Runge–Kutta method along with the shooting technique is applied to obtain the appropriate numerical solution. The relevant outcomes include the fact that the Casson fluid parameter controls the radial velocity of SWTNT‐water nanofluid and radial and tangential slip parameters exhibit the same trend of radial velocity in the presence of SWTNT in the base fluid. The descending trend of radial velocity is due to a rise in the Casson fluid parameter β $\beta $ in the range 0.1≤β≤10 $0.1\le \beta \le 10$. The ranges of other parameters influencing the flow behavior are 0.1≤ε≤0.9, $0.1\le \varepsilon \le 0.9,$0.1≤L1≤0.5, $0.1\le {L}_{1}\le 0.5,$0.1≤L2≤0.9,0.1≤L3≤0.9,0.1≤L4≤2 $0.1\le {L}_{2}\le 0.9,0.1\le {L}_{3}\le 0.9,0.1\le {L}_{4}\le 2$. The non‐Newtonian fluid model helps in controlling the momentum transfer of SWTNT‐water nanofluid. Boundary layer flow of SWTNT‐water nanofluid due to radial stretching is the novelty of our study. The present work may be extended to the Darcy and non‐Darcy medium, which is beyond the scope of our work. [ABSTRACT FROM AUTHOR]

We re‐evaluate empirically the threshold effect of inflation on economic growth for 27 countries (16 developing and 11 developed economies) over 1975–2018. Our research differs from the previous one in that it employs non‐average inflation data with a balanced panel for a longer period of time. The methods of fixed effects and feasible generalized least squares (FGLS) are used to estimate the inflation threshold and its effects on growth. The empirical estimates show a significant negative association between inflation and growth above the threshold level of inflation. The empirical estimate indicates that inflation impede growth when inflation exceeds the turning point 12.23% and 5.36% in Panel‐1 and Panel‐2, respectively, and with the greatest negative effects in Panel‐2. In addition, our findings provide evidence that gross fixed capital formation, government spending, household spending and real exports stimulate economic growth while the growth rate of the population is detrimental to the growth of the regions. Overall, the empirical result of this study could be of use in providing policy direction to governments and management authorities. In developing and developed economies, the management authorities need to cogitate a maximum rate of 12.3% and 5.4%, respectively, as an inflation target to avoid the detrimental effects of high inflation on economic growth for sustaining macroeconomic stability. [ABSTRACT FROM AUTHOR]

Objectives: To assess a new application of artificial intelligence for real‐time detection of laryngeal squamous cell carcinoma (LSCC) in both white light (WL) and narrow‐band imaging (NBI) videolaryngoscopies based on the You‐Only‐Look‐Once (YOLO) deep learning convolutional neural network (CNN). Study Design: Experimental study with retrospective data. Methods: Recorded videos of LSCC were retrospectively collected from in‐office transnasal videoendoscopies and intraoperative rigid endoscopies. LSCC videoframes were extracted for training, validation, and testing of various YOLO models. Different techniques were used to enhance the image analysis: contrast limited adaptive histogram equalization, data augmentation techniques, and test time augmentation (TTA). The best‐performing model was used to assess the automatic detection of LSCC in six videolaryngoscopies. Results: Two hundred and nineteen patients were retrospectively enrolled. A total of 624 LSCC videoframes were extracted. The YOLO models were trained after random distribution of images into a training set (82.6%), validation set (8.2%), and testing set (9.2%). Among the various models, the ensemble algorithm (YOLOv5s with YOLOv5m—TTA) achieved the best LSCC detection results, with performance metrics in par with the results reported by other state‐of‐the‐art detection models: 0.66 Precision (positive predicted value), 0.62 Recall (sensitivity), and 0.63 mean Average Precision at 0.5 intersection over union. Tests on the six videolaryngoscopies demonstrated an average computation time per videoframe of 0.026 seconds. Three demonstration videos are provided. Conclusion: This study identified a suitable CNN model for LSCC detection in WL and NBI videolaryngoscopies. Detection performances are highly promising. The limited complexity and quick computational times for LSCC detection make this model ideal for real‐time processing. Level of Evidence: 3 Laryngoscope, 132:1798–1806, 2022 [ABSTRACT FROM AUTHOR]

The COVID‐19 pandemic has appeared as the predominant disease of the 21st century at the end of 2019 and was a drastic start with thousands of casualties and the COVID‐19 victims in 2020. Due to the drastic effect, COVID‐19 scientists are trying to work on pandemic diseases and Governments are interested in the development of methodologies that will minimize the losses and speed up the process of cure by providing vaccines and treatment for such pandemics. The development of a new vaccine for any pandemic requires long in vitro and in vivo trials to use. Thus the strategies require understanding how the pandemic is spreading in terms of affected cases and casualties occurring from this disease, here we developed a forecasting model that can predict the no of cases and deaths due to pandemic and that can help the researcher, government, and other stakeholders to devise their strategies so that the damages can be minimized. This model can also be used for the judicial distribution of resources as it provides the estimates of the number of casualties and number of deaths with high accuracy, Government and policymakers on the basis of forecasted value can plan in a better way. The model efficiency is discussed on the basis of the available dataset of John Hopkins University repository in the period when the disease was first reported in the six countries till the mid of May 2020, the model was developed on the basis of this data, and then it is tested by forecasting the no of deaths and cases for next 7 days, where the proposed strategy provided excellent forecasting. The forecast models are developed for six countries including Pakistan, India, Afghanistan, Iran, Italy, and China using polynomial regression of degrees 3–5. But the models are analyzed up to the 6th‐degree and the suitable models are selected based on higher adjusted R‐square (R2) and lower root‐mean‐square error and the mean absolute percentage error (MAPE). The values of R2 are greater than 99% for all countries other than China whereas for China this R2 was 97%. The high values of R2 and Low value of MAPE statistics increase the validity of proposed models to forecast the total no cases and total no of deaths in all countries. Iran, Italy, and Afghanistan also show a mild decreasing trend but the number of cases is far higher than the decrease percentage. Although India is expected to have a consistent result, more or less it depicts some other biasing factors which should be figured out in separate research. [ABSTRACT FROM AUTHOR]

Bounded support Gaussian mixture model (BGMM) has been proposed for data modelling as an alternative to unbounded support mixture models for the cases when the data lies in bounded support. In this paper, we propose applications of multivariate BGMM in data clustering for more insightful analysis of the model. We also propose minimum message length (MML) criterion for model selection in data clustering using multivariate BGMM. The presented model is applied to data clustering in several speech (TSP and Spoken Digits) and image databases (MNIST and Fashion MNIST). We also propose the application of BGMM in code‐book generation at feature extraction phase. Inspired by the success of bag of visual words approach in computer vision, it is also introduced in speech data representation and validated through experiments presented in this paper. For validation of model selection criterion, MML is applied to different medical, speech and image datasets. Experimental results obtained during the model selection through MML are further compared with seven different model selection criteria. The results presented in the paper demonstrate the effectiveness of BGMM for clustering speech and image databases, code‐book generation through clustering for feature representation and model selection. [ABSTRACT FROM AUTHOR]

In this paper, a resubmitted sampling‐based successive sampling over two successive occasions control chart is proposed to monitor the underlying characteristic of interest. Auxiliary information of the first occasion is utilized to monitor the relative change in the study variable over the second occasion successively despite high degree of correlation. The structural and operational design is presented along with the comparative performance evaluation. The average run length is used as a performance evaluation measure and proved the argument in favor of the presented concept in comparison with the other auxiliary data control charts. The implementation is explained through two real examples. [ABSTRACT FROM AUTHOR]

Modern and emerging techniques of technology have brought a revolution in quality inspection of products. When events in highly efficient production processes occur rarely, it requires to inspect and monitor the time between occurrence of these events (TBE). The exponential and gamma distributions are commonly used models for time between events (TBE) data. In this article, a new monitoring scheme has been established for TBE data based on exponential and gamma distributions. In a previous research, transformation‐based control charts have been developed for TBE. The proposed study is aimed to use the exact probability distribution of charting statistic rather than applying transformations to data and this has remained still unaddressed. Average run length (ARL) and percentage decrease in ARL (ΔARL) have been calculated using Monte Carlo simulations and the proposed monitoring method has been compared with existing techniques applied to transformed data. The proposed scheme provides a simpler design structure and better performance on different sample sizes in identifying annoying process variations. Further, the technique has been applied to simulated and real‐life data sets of time between manufacturing plant accidents to highlight the worth and particle applicability of the proposed work. [ABSTRACT FROM AUTHOR]

Antimony sulfide (Sb2S3) is emerging as a popular photovoltaic candidate for thin‐film solar cells due to its large absorption coefficient, suitable bandgap, nontoxic, and earth‐abundant nature. The performance of thermally evaporated Sb2S3 devices is severely restricted by interfacial recombination leading to high open‐circuit voltage (VOC) losses. CdS as electron transport layer (ETL) has overcome this problem, but triggered lower JSC issues due to parasitic absorption loss conceding to its smaller bandgap. Herein, a spray pyrolysis method is adopted for the deposition of a uniform and compact Zn‐doped TiO2 film with tuned energy levels to facilitate charge extraction and transport. The solar cell fabricated with a modified TiO2 ETL holds superior interface quality, high build‐in potential, and suppressed recombination losses, therefore pronouncedly improves the VOC. As a result, the efficiency of the device is boosted from 4.41% to 5.16%, a record VOC of 702 mV for Cd‐free full‐inorganic Sb2S3 solar cell is achieved. These findings are expected to be implemented in other Sb‐chalcogenide solar cells to further enhance the device performance. [ABSTRACT FROM AUTHOR]

Vitamin D lost its functionality during processing and storage, thus, encapsulation with proteins is desirable to preserve bioactivity. The aim of the current study was to develop encapsulated vitamin D fortified mayonnaise (VDFM) using whey protein isolates (WPI) and soy protein isolates (SPI) as encapsulating materials in three different formulations, that is, 10% WPI, 10% SPI, and 5/5% WPI/SPI. Increased shear stress decreased the apparent viscosity along with significant effects on the loss modulus of VDFM. WPI encapsulates showed better results as compared to SPI. WPI based VDFM (M1) depicted the best results in terms of size and dispersion uniformity of oil droplets. Hue angle and total change differed significantly among treatments. The highest value for overall acceptability was acquired by M3 (5:5%WPI:SPI‐encapsulates) thus proceed for in vivo trials. Serum vitamin D level was significantly higher in the encapsulated VDFM rat group (58.14 ± 6.29 nmol/L) than the control (37.80 ± 4.98 nmol/L). Conclusively, WPI and SPI encapsulates have the potential to improve the stability and bioavailability of vitamin D. [ABSTRACT FROM AUTHOR]

In perovskite solar cells (PSCs), the interfaces between perovskite film and charge transport layers have an enormous influence on the device performance and stability. Recently, it has been proven that the surface defect passivation of perovskite layer is an effective strategy to improve the device efficiency. Herein, an organic ammonium salt benzyltriethylammonium chloride ([BZTAm]Cl) is used as an ultra‐thin modification layer in perovskite films in MAPbI3 PSCs for passivating the surface defects. The obtained results demonstrate that the [BZTAm]Cl modifier improves the crystallization/morphology of perovskite film and effectively aligns the energy levels with the corresponding charge‐transporting layers, suppressing the nonradiative recombination and reducing the trap state density. As a result, a champion device efficiency of 20.45% is achieved for optimized concentration of [BZTAm]Cl in comparison with 17.87% for the control device. Moreover, the unencapsulated device presents a good long‐term stability after aging in an ambient environment with 40–50% relative humidity conditions for 30 days. [ABSTRACT FROM AUTHOR]

Many bacterial small RNAs (sRNAs) efficiently inhibit translation of target mRNAs by forming a duplex that sequesters the Shine‐Dalgarno (SD) sequence or start codon and prevents formation of the translation initiation complex. There are a growing number of examples of sRNA–mRNA binding interactions distant from the SD region, but how these mediate translational regulation remains unclear. Our previous work in Escherichia coli and Salmonella identified a mechanism of translational repression of manY mRNA by the sRNA SgrS through a binding interaction upstream of the manY SD. Here, we report that SgrS forms a duplex with a uridine‐rich translation‐enhancing element in the manY 5ʹ untranslated region. Notably, we show that the enhancer is ribosome‐dependent and that the small ribosomal subunit protein S1 interacts with the enhancer to promote translation of manY. In collaboration with the chaperone protein Hfq, SgrS interferes with the interaction between the translation enhancer and ribosomal protein S1 to repress translation of manY mRNA. Since bacterial translation is often modulated by enhancer‐like elements upstream of the SD, sRNA‐mediated enhancer silencing could be a common mode of gene regulation. [ABSTRACT FROM AUTHOR]

The thermomechanical behavior of micro/nano‐alumina (Al2O3) ceramics reinforced with 1‐5 wt.% of acid‐treated oil fly ash (OFA) was investigated. Composites were sintered using spark plasma sintering (SPS) technique at a temperature of 1400°C by applying a constant uniaxial pressure of 50 MPa. It was evaluated that the fracture toughness of micro‐ and nanosized composites improved in contrast with the monolithic alumina. Highest fracture toughness value of 4.85 MPam1/2 was measured for the nanosized composite reinforced with 5 wt.% OFA. The thermal conductivity of the composites (nano‐/microsized) decreased with the increase in temperature. However, the addition of OFA (1‐5 wt.%) in nanosized alumina enhanced the thermal conductivity at an evaluated temperature. Furthermore, a minimum thermal expansion value of 6.17 ppm*K−1 was measured for nanosized Al2O3/5 wt.% OFA composite. Microstructural characterization of Al2O3‐OFA composites was done by x‐ray diffraction and Raman spectroscopy. Oil fly ash particles were seen to be well dispersed within the alumina matrix. Moreover, the comparative analysis of the nano‐/microsized Al2O3/OFA composites shows that the mechanical and thermal properties were improved in nanosized alumina composites. [ABSTRACT FROM AUTHOR]

Control charts are developed to make the specific quality measures for a successful production process and follow normal distribution behaviors. But some real‐life practices do not match such practices and exhibit some positively skewed behavior like lognormal distribution. The present study has considered this situation and proposed a monitoring control chart based on lognormal process variation using a repetitive sampling scheme. This concept proved better for detecting shifts as quickly as possible, and compared with the existing concept, results are elaborated through extensive tables. The average run lengths and standard deviations of the run lengths are being used as a performance evaluation measures and computed by using Monte Carlo simulations performed in R language. A real‐life situation has been discussed in the example section to strengthen the proposed control chart concept in a real‐life situation. [ABSTRACT FROM AUTHOR]

In this paper, successive sampling (SS) mean monitoring control chart is proposed for two successive occasions using multiple dependent state (MDS) sampling and characterized as MDS‐SS control chart. The sample size is selected on the basis of SS for the control statistic in two pairs of the control limits. The average run length is evaluated, and the performance of the proposed concept over the existing SS control chart is presented using a real‐life example. The SS monitoring chart concept is compiled with MDS, and it becomes more sophisticated in detection of warning signs. [ABSTRACT FROM AUTHOR]

A control chart based on double exponentially weighted moving average and Benjamini‐Hochberg multiple testing procedure is proposed that controls the false discovery rate (FDR). The proposed control chart is based on probabilities (or P values) to accept or reject the null hypothesis of the underlying process is in control. To make a decision, instead of using only the current probability, previous "m" probabilities are considered. The performance of the control chart is evaluated in terms of average run length (ARL) using Monte Carlo simulations. Procedure for estimation of parameters used in the control chart is also discussed. The proposed control chart is compared with previous control charts and found to be more efficient in controlling the false discovery rate. [ABSTRACT FROM AUTHOR]

Summary: Small RNA (sRNA) regulators promote efficient responses to stress, but the mechanisms for prioritizing target mRNA regulation remain poorly understood. This study examines mechanisms underlying hierarchical regulation by the sRNA SgrS, found in enteric bacteria and produced under conditions of metabolic stress. SgrS posttranscriptionally coordinates a nine‐gene regulon to restore growth and homeostasis. An in vivo reporter system quantified SgrS‐dependent regulation of target genes and established that SgrS exhibits a clear target preference. Regulation of some targets is efficient even at low SgrS levels, whereas higher SgrS concentrations are required to regulate other targets. In vivo and in vitro analyses revealed that RNA structure and the number and position of base pairing sites relative to the start of translation impact the efficiency of regulation of SgrS targets. The RNA chaperone Hfq uses distinct modes of binding to different SgrS mRNA targets, which differentially influences positive and negative regulation. The RNA degradosome plays a larger role in regulation of some SgrS targets compared to others. Collectively, our results suggest that sRNA selection of target mRNAs and regulatory hierarchy are influenced by several molecular features and that the combination of these features precisely tunes the efficiency of regulation of multi‐target sRNA regulons. [ABSTRACT FROM AUTHOR]

A significant loss of p53 protein, an anti‐tumour agent, is observed in early cancerous cells. Induction of small molecules based drug is by far the most prominent technique to revive and maintain wild‐type p53 to the desired level. In this study, a sliding mode control (SMC) based robust non‐linear technique is presented for the drug design of a control‐oriented p53 model. The control input generated by conventional SMC is discontinuous; however, depending on the physical nature of the system, drug infusion needs to be continuous. Therefore, to obtain a smooth control signal, a dynamic SMC (DSMC) is designed. Moreover, the boundedness of the zero‐dynamics is also proved. To make the model‐based control design possible, the unknown states of the system are estimated using an equivalent control based, reduced‐order sliding mode observer. The robustness of the proposed technique is assessed by introducing input disturbance and parametric uncertainty in the system. The effectiveness of the proposed control scheme is witnessed by performing in‐silico trials, revealing that the sustained level of p53 can be achieved by controlled drug administration. Moreover, a comparative quantitative analysis shows that both controllers yield similar performance. However, DSMC consumes less control energy. [ABSTRACT FROM AUTHOR]

A significant loss of p53 protein, an anti-tumour agent, is observed in early cancerous cells. Induction of small molecules based drug is by far the most prominent technique to revive and maintain wild-type p53 to the desired level. In this study, a sliding mode control (SMC) based robust non-linear technique is presented for the drug design of a control-oriented p53 model. The control input generated by conventional SMC is discontinuous; however, depending on the physical nature of the system, drug infusion needs to be continuous. Therefore, to obtain a smooth control signal, a dynamic SMC (DSMC) is designed. Moreover, the boundedness of the zero-dynamics is also proved. To make the model-based control design possible, the unknown states of the system are estimated using an equivalent control based, reduced-order sliding mode observer. The robustness of the proposed technique is assessed by introducing input disturbance and parametric uncertainty in the system. The effectiveness of the proposed control scheme is witnessed by performing in-silico trials, revealing that the sustained level of p53 can be achieved by controlled drug administration. Moreover, a comparative quantitative analysis shows that both controllers yield similar performance. However, DSMC consumes less control energy. [ABSTRACT FROM AUTHOR]

The authors have proposed a systems theory‐based novel drug design approach for the p53 pathway. The pathway is taken as a dynamic system represented by ordinary differential equations‐based mathematical model. Using control engineering practices, the system analysis and subsequent controller design is performed for the re‐activation of wild‐type p53. p53 revival is discussed for both modes of operation, i.e. the sustained and oscillatory. To define the problem in control system paradigm, modification in the existing mathematical model is performed to incorporate the effect of Nutlin. Attractor point analysis is carried out to select the suitable domain of attraction. A two‐loop negative feedback control strategy is devised to drag the system trajectories to the attractor point and to regulate cellular concentration of Nutlin, respectively. An integrated framework is constituted to incorporate the pharmacokinetic effects of Nutlin in the cancerous cells. Bifurcation analysis is also performed on the p53 model to see the conditions for p53 oscillation. [ABSTRACT FROM AUTHOR]

The objective of the study is to empirically examine the effects of urbanization, energy consumption, and per capita GDP on CO2 emissions for all member countries from BRICS. Panel data over the period 1990-2014 and the STRIPAT model are used. After panel unit root tests, the method of fully modified Ordinary Least Squares (FMOLS) is applied as an analytical technique. Empirical results reveal that urbanization has a positive and significant relationship with CO2 emissions in all BRICS countries with the exception of Russia. Results also show that GDP per capita in cases of Brazil, Russia, and South Africa will help to mitigate CO2 emissions, while the results are opposite in the cases of India and China. Likewise, energy consumption is positively and significantly causing CO2 emissions in cases of Brazil, India, and China, whereas, it is helping to reduce CO2 emission in Russia, while energy consumption has no impact in the case of South Africa. The findings of the study suggest important policy implications. This study recommends introducing less pollution emission of transport, and constructing long-term and effective system in renewable energy development in order to mitigate side effects of urbanization on the environment. © 2016 American Institute of Chemical Engineers Environ Prog, 36: 523-531, 2017 [ABSTRACT FROM AUTHOR]

The broad aim of this study is to evaluate empirically the impacts of urbanization along with some other explanatory variables on environmental degradation measured by carbon dioxide emissions for four countries from the South Asian Association for Regional Cooperation (SAARC) region namely India, Bangladesh, Sri Lanka, and Pakistan. Annual time series data over the period of 1982-2013 are used. After, employing various relevant and required statistical tests, the method of least squares has been employed as an analytical technique for parameters estimation. The least squares estimate reveals that the impact of urbanization on the environment found is blended. In cases of Bangladesh and India, the relationship between urbanization growth and environment found is significantly negative, while, the impact of urbanization on environment is significantly positive in case of Sri Lanka and insignificantly positive for Pakistan during the period under the study. The findings of the study suggest that policy makers need to formulate appropriate policy for long term urban planning which can certainly help to mitigate largely CO2 emissions/environmental pollution. [ABSTRACT FROM AUTHOR]

In this paper, we propose a control chart using exponentially weighted moving average (EWMA) statistic for count data based on the Conway-Maxwell-Poisson (called COM-Poisson) distribution. Repetitive sampling is considered by constructing two pairs of control limits for the proposed control chart. The performance of the proposed control chart is evaluated using the average run length (ARL) for various values of specified parameters. It has been observed that the proposed control chart is more efficient in terms of ARLs as compared to the existing control charts. The tables are provided and explained with the help of example. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this manuscript, three repetitive types of sampling plans using the generalized process capability index of multiple characteristics are presented, which include a repetitive sampling plan, a resubmitted sampling plan and a multiple dependent state repetitive sampling plan. The plan parameters of these sampling schemes are determined through the nonlinear optimization solution. The comparison among these proposed plans is made in terms of the average sample number required. The use of the proposed plans is given with the help of an industrial example. [ABSTRACT FROM AUTHOR]

When Francis Crick first proposed the central dogma, he predicted that genetic information flows from DNA to RNA and finally to proteins. By this classical concept, the sole purpose of mRNA is to serve as a template for translation. Recent work has expanded our understanding of the function of mRNA well beyond this singular definition. A paper published in this issue sheds more light on the myriad roles mRNAs can play in genetic regulation. Miyakoshi et al () report an intriguing scenario in Salmonella where a small RNA molecule derived from a larger polycistronic mRNA promotes cross talk between physically unlinked mRNAs via controlling turnover of a global small RNA repressor. [ABSTRACT FROM AUTHOR]

Highlights from the article: Mode Modulation: Realization of Perovskite-Nanowire-Based Plasmonic Lasers Capable of Mode Modulation (Laser Photonics Rev. 13(7)/2019) In article number 1800306, Zhijie Wang, Peng Jin, Shengchun Qu, and co-workers construct plasmonic lasers based on the structure of metal/dielectric layer/perovskite nanowires via an electrochemically assisted growth method for the high-quality perovskite nanowires. The purple light represents the pumping input energy; the green-light emission of the plasmonic laser is mainly constrained to the dielectric layer; the variations of the green spectra indicate the possibility of mode modulation of perovskite-nanowire-based plasmonic lasers.

Manipulating stimulated‐emission processes and overcoming the ohmic loss of metals in plasmonic lasers are of significance for the according applications in biological sensors, data storage, photolithography, and optical communications. Herein, through utilizing an electrochemical‐assisted growth method for high‐quality perovskite nanowires, plasmonic lasers based on the structure of metal/dielectric layer/perovskite nanowires are constructed. The plasmonic lasers demonstrate a threshold of 62 µJ cm−2, a high quality factor of Q ≈ 655, and a fast lasing decay time of 1.6 ps. Interestingly, the plasmonic lasers present an attractive capability in transformation from single mode to multiple modes just by adjusting the pumping energy. In addition to the broad stoichiometry‐dependent tunability of the perovskite materials, the proposed plasmonic lasers have great promise in real applications. [ABSTRACT FROM AUTHOR]

Passivation Moisture penetration through surface defects into the active layer is responsible for degradation of device performance in humid environments. In article no. 1800327, Zhijie Wang, Huiqiong Zhou, Shengchun Qu, and coworkers show that the interaction of the perovskite material with DRCN5T increases the durability of the device in ambient conditions, because the passivated defect sites on the film surface suppresses the transit of moisture or oxygen through the defects. [ABSTRACT FROM AUTHOR]

In the title mol-ecule, C(23)H(16)ClNO, the quinoline and naphthalene ring systems are individually planar, with maximum deviations of 0.020 (2) and 0.033 (2) Å, respectively, and are inclined at a dihedral angle of 30.01 (4)°. Intra-molecular C-H⋯O and C-H⋯Cl inter-actions occur. The crystal structure is devoid of any classical hydrogen bonds, but symmetry-related mol-ecules are linked via weak C-H⋯Cl inter-actions, forming chains propagating in [001].

In the title mol-ecule, C(21)H(16)ClNO(3), the quinoline and benzene rings are inclined at 56.96 (6)° with respect to each other and the dioxine ring is in a twist-chair conformation. The structure is devoid of any classical hydrogen bonds. Rather weak inter-molecular hydrogen-bonding inter-actions of the types C-H⋯N and C-H⋯O are present, consolidating the crystal structure.

In the title compound, C(15)H(11)NO(4)S, the benzothia-zole unit is essentially planar [maximum deviation = 0.0644 (14) Å for the N atom] and forms a dihedral angle 54.43 (6)° with the phenyl ring. In the crystal structure, weak bifurcated C-H⋯O hydrogen bonds involving the carbonyl O atoms as acceptors result in R(2) (2)(7) ring motifs.

In the title compound, C(16)H(13)NO(5)S, the benzothia-zole unit is essentially planar [maximum deviation = 0.0501 (10) Å for the S atom] and is oriented at a dihedral angle of 67.85 (5)° with respect to the meth-oxy-substituted benzene ring. The mean plane of the meth-oxy group is oriented at 14.3 (3)° with respect to the benzene ring to which it is attached. In the crystal structure, weak C-H⋯O hydrogen bonds form macrocyclic rings with R(2) (2)(10) and R(2) (2)(12) motifs.

In the title compound, C(15)H(11)ClN(2)O(4)S, there are two independent mol-ecules in the asymmetric unit, in which the heterocyclic thia-zine rings in both mol-ecules adopt half-chair conformations. The conformations about the C-C and C-N bonds in the central C-C-N-C chain in both mol-ecules are all EZ. There are strong intra-molecular O-H⋯O and N-H⋯N hydrogen bonds resulting in graph-set patterns S(6) and S(5) for the oxo and amino rings, in addition to intra-molecular N-H⋯Cl inter-actions. In the crystal structure, mol-ecules are linked by inter-molecular O-H⋯O and N-H⋯O hydrogen bonds into chains along [100].

IN THE TITLE COMPOUND [SYSTEMATIC NAME: 2-(2-oxoprop-yl)-1,2-benzothia-zol-3(2H)-one 1,1-dioxide], C(10)H(9)NO(4)S, the benzo-thia-zole unit is essentially planar [maximum deviation = 0.0490 (9) Å for the S atom] and the oxopropyl group is inclined at an angle 75.61 (8)° with respect to its mean plane. In the crystal, mol-ecules are held together by weak inter-molecular C-H⋯O non-classical hydrogen bonds, resulting in centrosymmetric dimeric units, forming 14-membered ring systems which may be described as R(2) (2)(14) ring motifs. Moreover, mol-ecules lying about inversion centers show π-π inter-actions, with centroid-centroid separations between the benzene rings of 3.676 (2) Å.