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In this study, we derive multiple incomplete matrix Mittag-Leffler (ML) functions. We systematically investigate several properties of these incomplete matrix ML functions, which include some general properties and distinct representations of integral transforms. We further study the properties of the Riemann–Liouville fractional integrals and derivatives related to the incomplete matrix ML functions. Additionally, some interesting special cases of this work are highlighted. Finally, we establish the solution to the kinetic equations as an application. [ABSTRACT FROM AUTHOR]

In this paper, a stabilized Stokes–Stokes system with Nitsche's type interface conditions is presented. These conditions are commonly employed in many multi-physical fields, including fluid–fluid interaction, fluid–structure interaction, oceanographic modeling, and atmospheric forecasting. For multi-physical domain modeling purposes, Nitsche's interface conditions provide useful benefits over classical conditions via addressing the complicated nature of fluid phase interface mathematical modeling, phase boundary tracking, interface interactions, and mass and energy transportation. It is not easy to find analytical and numerical solutions for models with these characteristics. We use more accurate interface conditions to solve the fluid–fluid interaction model to accomplish this numerically. This is achieved by including new terms at the interface and decoupling the domain through the two-grid technique, which ultimately reduces the main issue into several smaller problems. Comparing this method to existing models, we find that it is computationally feasible because it uses less memory and operates with a coarse grid instead of a fine grid and thus improves convergence rates for complex and nonlinear problems. Furthermore, it shows mesh independence, supports potential parallelization, and is crucial for advanced multigrid techniques. The optimality of the error is confirmed both theoretically and numerically. The numerical experimental section validates the model through three types of numerical experiments. [ABSTRACT FROM AUTHOR]

In this research, a two-step hydrothermal technique is used to fabricate a NO 2 gas sensor based on MoS 2 nanoflowers with SnO 2 nanoparticles. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS) , were used to determine the morphologies, nanostructures, and compositions of the materials. The nanocomposites consisting of MoS 2 /SnO 2 demonstrated a remarkable sensing response (38.6) towards 100 ppm of NO 2. Moreover, the nanocomposites showed a rapid response and recovery time (42/147 S) when exposed to 100 ppm at temperature (250 °C). The MoS 2 /SnO 2 nanocomposites demonstrated exceptional selectivity to NO 2 against CO, NH 3 , and H 2 S, as well as demonstrated good repeatability. The significant gas detection characteristics could potentially be controlled by the distinctive structures of thin layers assembled into flower-like formations of two-dimensional MoS 2. The multi-joint nanostructures promote the process of transferring the electrical charge of the carrier and the response to MoS 2 /SnO 2 and NO 2. The fabricated sensors are considered as potential candidates for the commercial in the nitrogen dioxide gas-sensing applications. [Display omitted] [ABSTRACT FROM AUTHOR]

In this work, polypyrrole (PPy) is synthesized, characterized, and employed as an active sensing material for the fabrication of humidity sensors. An 80 nm thick layer of PPy is spin coated on the pre-patterned thermally deposited silver (Ag) electrodes spaced 50 µm apart to fabricate Ag/PPy/Ag surface-type sensor. Atomic force microscopy analysis revealed granular microstructure morphology in the thin films of PPy. Additionally, X-ray diffraction (XRD), ultraviolet–visible (UV-Vis) and Fourier transformed infrared (FTIR) spectra of PPy are analyzed to study its crystallinity, optical bandgap and bond dynamics to confirm the molecular composition of PPy. The fabricated Ag/PPy/Ag sensor is characterized by varying the humidity levels between a broad range [0–95% relative humidity (RH)] at different frequencies of 120 Hz and 1 kHz. The prepared sensor showed promising sensing features such as higher sensitivity 233 nF/%RH (at 120 Hz), 83 pF/%RH (at 1 kHz), quick response time (5.20 ± 0.2 s) and recovery times (6.43 ± 0.2 s), a wide working range of relative humidity (20–95%RH) and low hysteresis gap (1.57%) with outstanding recyclability. This study reveals the potential of PPy as the best candidate for humidity sensing applications. [ABSTRACT FROM AUTHOR]

The objective of this article is to examine, stabilize, and linearize the incompressible magnetohydrodynamic model equations. The approximate solutions are carried out through the lowest equal order mixed finite element (FE) approach, involving variables such as fluid velocity, hydro pressure, magnetic field, and magnetic pressure. The formulation of the variational form for the approximate solution necessitates the use of a pair of approximating spaces. However, these spaces cannot be arbitrarily chosen; they must adhere to strict stability conditions, notably the Ladyzhenskaya–Babuska–Brezzi (LBB) or inf-sup condition. This study addresses the absence of stabilization and linearization techniques in the incompressible magnetohydrodynamic model equations using the lowest equal order mixed finite element approach. The article introduces a stabilization technique to meet two stability conditions, proving its existence and uniqueness. This novel approach was not previously explored in the literature. The proposed stabilized technique does not necessitate parameters or computing higher-order derivatives, making it computationally efficient. The study offers numerical tests demonstrating optimal convergence and effectiveness of the revised approach in two-dimensional settings. [ABSTRACT FROM AUTHOR]

The current study, accurately designed and created a two-dimensional (2D) structure of SnO 2 nano-flowers and In 2 O 3 nanoparticles using a simple hydrothermal technique and sol-gel method, respectively. On the outer surface of SnO 2 nanoflowers the In 2 O 3 nanoparticles were uniformly growing, clearly revealed by field emission scanning electron microscopic. Besides, crystal phase structure, surface area and elementals composition were characterized by XRD, BET, TEM, EDS, XPS and the gas sensing properties of In 2 O 3 @SnO 2 NFs. The results exhibited that 2 wt% In 2 O 3 @SnO 2 NFs sensor is highly sensitive to NO 2 , the response (R g /R a) to 30 ppm NO 2 is 94.5, and at 50 ppb the response measured 0.61 at 150 °C, the response time is 32 and 51s, respectively, along with good moisture resistance. Besides along with excellent selectivity, long-term stability, and relative humidity (RH) in high-humidity environment, the 2 wt% In 2 O 3 @SnO 2 NFs still maintain high response 91 at 30 ppm. More importantly, at room temperature the response was (Rg/Ra = 1.01) at detection limit 300 ppb towards NO 2 , which could use be for trace NO 2 gas detection. The large specific surface areas of SnO 2 , the abundance of oxygen species adsorbed on the surface, the distinctive electron transformation between heterojunction materials, and high electron transmission channel of SnO 2 and In 2 O 3 transition layer were all considered to have a synergistic effect thatin2 contributed to excellent sensing properties of In 2 O 3 @SnO 2 NFs. [ABSTRACT FROM AUTHOR]

Hydrogen sulfide (H 2 S) gas is a dual menace since it is not only hazardous to human health and the environment, but it is also flammable. Given these crucial considerations, the need for competent gas sensors for H 2 S detection becomes apparent. In this endeavor, an investigation of the gas-sensing prowess inherent in sensors made from assembled nanosheets of ZnO–NiO arranged into intricate flower-like structures. The sensing materials were prepared using a straightforward solvothermal process. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) were used to thoroughly examine the sensor's chemical properties and structural composition. The gas-sensing abilities of the sensing materials were rigorously assessed, which included a close examination of their electrical response to varied concentrations of H 2 S. The efficacy of the sensors may be due to the synergistic interactions between their distinct flower-like design, endowing them with an expansive surface area for optimum gas adsorption, and the significant catalytic impact supplied by the composition of ZnO–NiO. The results show that the ZnO–NiO flower-like sensors have high sensitivity, selectivity, and stability to H 2 S gas. Within the studied range, the response and recovery times were 51.43 s and 38.11 s respectively at 250 °C in 100 ppm H 2 S. This amalgamation of attributes manifests as an enhancement in the sensors' gas-sensing capabilities, highlighting their suitability for such an application. This research complements the explanation offered by first-principles calculations based on Density Functional Theory (DFT) to dive into the fundamentals of this gas-sensing mechanism. [ABSTRACT FROM AUTHOR]

Unsupervised anomaly detection in multivariate time series sensor data is a complex task with diverse applications in different domains such as livestock farming and agriculture (LF&A), the Internet of Things (IoT), and human activity recognition (HAR). Advanced machine learning techniques are necessary to detect multi-sensor time series data anomalies. The primary focus of this research is to develop state-of-the-art machine learning methods for detecting anomalies in multi-sensor data. Time series sensors frequently produce multi-sensor data with anomalies, which makes it difficult to establish standard patterns that can capture spatial and temporal correlations. Our innovative approach enables the accurate identification of normal, abnormal, and noisy patterns, thus minimizing the risk of misinterpreting models when dealing with mixed noisy data during training. This can potentially result in the model deriving incorrect conclusions. To address these challenges, we propose a novel approach called "TimeTector-Twin-Branch Shared LSTM Autoencoder" which incorporates several Multi-Head Attention mechanisms. Additionally, our system now incorporates the Twin-Branch method which facilitates the simultaneous execution of multiple tasks, such as data reconstruction and prediction error, allowing for efficient multi-task learning. We also compare our proposed model to several benchmark anomaly detection models using our dataset, and the results show less error (MSE, MAE, and RMSE) in reconstruction and higher accuracy scores (precision, recall, and F1) against the baseline models, demonstrating that our approach outperforms these existing models. [ABSTRACT FROM AUTHOR]

The hydroxyapatite (HA) powder has been successfully prepared by using calcined Indian clam seashells through the hydrothermal technique. Initially, the clam seashell is calcined at 900 ℃ to achieve calcium oxide (CaO). The obtained seashell-based calcium oxide is mixed properly with pre-determined tri-calcium phosphate in demineralized water. Further, the colloidal solution is heat-treated at a temperature of 1000 ℃ for various time durations (1 h, 1:30 h, 1:45 h, 2 h, 2:30 h, and 3 h) to perform the hydrothermal reactions. Quantification of HA and different phases present in the synthesized powders is carried out with the help of the Rietveld refinement method. The phases, crystallite size, and crystallinity of synthesized powder are evaluated by the X-ray diffraction (XRD) technique. The microstructure of the powder is analyzed through Field Emission Scanning Electron Microscopy (FESEM). The Ca/P ratio and particle size of the prepared powder are estimated by energy-dispersive X-ray spectroscopy (EDS) and the image analysis technique, respectively. The results indicate that the heating duration of the hydrothermal reaction is a crucial parameter in modifying the various properties, specifically the phase quantity of prepared HA. All six synthesized powders show the presence of the HA phase, along with a few secondary phases in those. Spherical and cylindrical nano-crystals of HA are observed to form. With an increase in time duration, coarsening of crystallite is observed. The average particle size and crystallinity of HA are also noticed to be increased with increased time duration. [ABSTRACT FROM AUTHOR]

This study investigates the local governance system in Pakistan during the tenure of General Pervez Musharraf and Imran Khan, addressing the persistent void created by political uncertainty in the structural framework. Throughout history, both civilian and military regimes have sought to shape the local governance system, introducing concepts and laws to enhance grassroots-level governance. The research critically examines these efforts, considering challenges and opportunities in establishing an effective local governance structure. Additionally, it assesses three rounds of local government elections under the devolution plan, exploring whether they empowered political figures at the expense of local development. The study probes reasons for continued authority centralization in military and civilian regimes, emphasizing the need for a comprehensive evaluation by an educated committee. Such oversight can monitor local governance activities from diverse perspectives. Given Pakistan's decentralization history, the study highlights central authorities' strategies to retain power, resisting governance shifts to the grassroots through amendments aimed at bringing government closer to the common people. [ABSTRACT FROM AUTHOR]

Context: Arsenic (As) is a noxious metalloid for plants, animals and humans. Elevated levels of As in soils may cause it to accumulate to above-permissible levels in wheat grains, posing a threat to human health. Moreover, vulnerable population groups in developing countries have inadequate dietary zinc (Zn) linked to cereal-based diets. Aims: The present study evaluated the effect of soil Zn application on accumulation of As and Zn in grains of two Zn-biofortified wheat (Triticum aestivum L.) cultivars (Akbar-2019 and Zincol-2016). Methods: Wheat plants were grown on an alkaline calcareous soil spiked with three levels of As (0, 5 and 25 mg kg−1). Before sowing, two rates of Zn (0 and 8 mg kg−1) were also applied to the soil. Key results: Arsenic spiking in soil decreased plant dry matter yield, chlorophyll pigments, and phosphorus (P) and Zn accumulation, and increased As accumulation in wheat. By contrast, soil Zn application enhanced crop yield and increased P and Zn accumulation, with a simultaneous decrease in As accumulation in both cultivars. Compared with the Zn control, soil Zn application decreased grain As concentration by 26%, 30% and 32% for plants grown in soil spiked with 0, 5 and 25 mg As kg−1, respectively. Conclusions: Applying Zn to As-spiked soil mitigates the harmful effects of As by increasing Zn and decreasing As concentrations in wheat, resulting in improved grain quality for human consumption. Implications: Zinc application to crop plants should be recommended for addressing the health implications associated with As-contaminated crops and human Zn deficiency. Wheat grown on soils contaminated by arsenic (As) may accumulate toxic levels of As in grains, allowing As to enter the human food chain. The study evaluated the effect of soil zinc (Zn) application on grain As and grain accumulation of Zn in two Zn-biofortified wheat cultivars grown on As-contaminated soil. Soil Zn application decreased grain As accumulation to below the permissible limit of 0.15 mg As kg−1 and simultaneously increased grain Zn accumulation. [ABSTRACT FROM AUTHOR]

In this paper, we explore a study focused on a two-variable extension of matrix Bessel polynomials. We initiate the discussion by introducing the matrix Bessel polynomials involving two variables and derive specific differential formulas and recurrence relations associated with them. Additionally, we present a segment detailing integral formulas for the extended matrix Bessel polynomials. Lastly, we introduce the Laplace–Carson transform for the two-variable matrix Bessel polynomial analogue. [ABSTRACT FROM AUTHOR]

The global incidence of lung cancer is marked by a considerably elevated mortality rate. MicroRNAs (miRNAs) exert pivotal influence in the intricate orchestration of gene regulation, and their dysregulation can precipitate dire consequences, notably cancer. Within this context, miRNAs encapsulated in exosomes manifest a diversified impact on the landscape of lung cancer, wherein their actions may either foster angiogenesis, cell proliferation, and metastasis, or counteract these processes. This comprehensive review article discerns potential targets for the prospective development of therapeutic agents tailored for lung cancer. Tumor-suppressive miRNAs, such as miR204, miR-192, miR-30a, miR-34a, miR-34b, miR-203, and miR-212, exhibit heightened expression and demonstrate the capacity to inhibit cellular proliferation and invasiveness. Conversely, the deleterious effects of tumor-promoting miRNAs like miR-21, miR-106a, miR-155, miR-205, and miR-210 can be attenuated through the application of their respective inhibitors. Distinct miRNAs selectively target various oncogenes, including NUAK Family Kinase 1 (NUAK1), Snail Family Transcriptional Repressor 1 (Snai1), Astrocyte elevated gene-1 (AEG-1), Vimentin, Proliferation and apoptosis adaptor protein 15 (PEA-15/PED), Hypoxia-inducible factor 1-alpha (HIF1), as well as tumor suppressor genes such as phosphatase and tensin homolog (PTEN), Suppressor of cytokine signaling 1 (SOCS1), Tumor protein P53 binding protein 1 (TP53BP1), and PH Domain and Leucine Rich Repeat Protein Phosphatase 2 (PHLP22). This investigative approach proves invaluable in elucidating the specific miRNAs implicated in the deregulation of crucial genes pivotal to the pathogenesis of cancer. [ABSTRACT FROM AUTHOR]

Brown rot Polypores are ecologically significant as they play a crucial role in maintaining the carbon cycle and contribute to humus formation in forest ecosystems through their lignocellulose degradation ability. It is important to note that some species can significantly impact timber, potentially causing decay in economically valuable wood. Many Asian countries including Pakistan are still under the exploratory phase and have undocumented species diversity in Polypore fungi. In the current study, collections representing five different species belonging to two families, Postiaceae and Adustoporiaceae, were subjected to detailed morphoanatomical and molecular analyses. A combined matrix of two gene datasets (ITS and nrLSU) was analyzed using three different phylogenetic methods viz. Maximum Parsimony (MP), Maximum Likelihood (ML), and Bayesian inference (BI). Our study presents descriptions of five previously undocumented brown rot Polypore species from the country including Fuscopostia fragilis (Fr.) B.K. Cui, L.L. Shen & Y.C. Dai, Amaropostia stiptica (Pers.) B.K. Cui, L.L. Shen & Y.C. Dai, Cyanosporus piceicola B.K. Cui, L.L. Shen & Y.C. Dai, Spongiporus balsameus (Peck) A. David, Rhodonia placenta (Fr.) Niemelä, K.H. Larss. & Schigel. Regarding the molecular data, nodes of our subject sequences were substantially supported and fell under their respective species clades with high ML bootstrap values (≥ 95), MP bootstrap ≥ 74 and BI probabilities ≥ 0.98. Findings of the study will not only contribute to our understanding of local Polypores species diversity but also enhance knowledge of geographical distribution in global context. [ABSTRACT FROM AUTHOR]

This research studies how recent Finnish smart mobility innovation projects have addressed sustainability in their objectives. A framework and a coding scheme were built upon scientific literature and was used for analysing documented project materials. A truth table was generated that quantifies how the different aspects of sustainability have been addressed in the projects' objectives. The observed differences between the projects were analysed from two directions: in terms of funding sources (European Union vs. national) and project location (urban vs. rural areas). The results of qualitative comparative analysis showed that while sustainability was by and large present in the projects, some of the aspects of sustainability were more dominantly addressed than others. Also, there were differences in how sustainability was addressed between the projects in urban areas and the projects in rural areas. [ABSTRACT FROM AUTHOR]

Objective: To see the type and frequency of lymphomas. Study Design: Prospective longitudinal study. Place and Duration of Study: Department of Medical Oncology at Jinnah Postgraduate Medical Centre, Karachi from Jan 2019 to Dec 2019. Methodology: Total of 150 patients with histopathological diagnoses of lymphoma of 17 to 71 years of age of either gender were included in the study using non-probability consecutive sampling technique. Prior to initiation of study ethics review committee has approved the study (NO.F.2-81-IRB/2019-GENL/10261/JPMC). The data regarding lymphoma type, histology, stage of disease, site, involvement of bone marrow, presence of B-symptoms were recorded. Results: Majority of the patients were male i.e., (n=104, 69.3%) with the mean age of 45.29±17.76 years. Non-Hodgkin's Lymphoma presented as the most common type of lymphoma i.e., (n=107, 71.3%) whereas Hodgkin's lymphoma (HL) contributed for (n=43, 28.7%) cases. Assessment of clinicopathological features of lymphomas revealed that (n=58, 38.7%) cases had bone marrow involvement. B-symptoms appeared in (n=102, 68%) cases, (n=61, 40.7%) cases were stage IV and the most common site were Neck lymph nodes (n=82, 58.3%), followed by abdomen (n=20, 13.3%). There was statistically significant difference between type of lymphoma with respect to age (p=0.001) and gender(p=0.015) Conclusion: Among lymphomas the most common type of lymphoma was Non-Hodgkin's Lymphoma, most common in patients >45 years of age showing relationship of its occurence with age and DLBCL is major subtype and among Hodgkin's lymphoma Classical type is the predominant type Epidemiologic characteristics and distribution of the disease varies with geographical region, racial & environmental factors. [ABSTRACT FROM AUTHOR]

Objective: To see the association between dietary habits in the development of oesophageal carcinoma. Study Design: Case control study. Place and Duration of Study: Department of Medical Oncology at Jinnah Postgraduate Medical Centre, Karachi Pakistan, from Feb 2019 to Dec 2019. Methodology: Patients from age 15-80 years of either gender were included in the study. All the patients presenting to hospital OPD with histopathologically confirmed of oesophagus carcinoma were included. Controls were the healthy attendants coming at the same hospital. The data was collected through pre-designed questionnaire. Results: Total of 173 cases and 173 controls were included in the study. The mean age of the cases and controls were reported as 48.07±14.13 years and 48.86±15.32 years. After adjusting odds in multivariate analysis family history of cancer (OR=3.76; 95% CI: 1.76-7.90, p<0.05), the consumption of chicken (OR=5.22; 95% CI: 3.01-9.056, p<0.05), red meat (OR=5.06; 95% CI: 2.70-9.46, p<0.05) & smoked food (OR=3.36; 95% CI: 1.76-6.44, p<0.05) more than three times per week remained positively associated with oesophagus carcinoma. Conclusion: The study showed association between consumption of chicken, red meat, hot drinks & smoked food with oesophageal carcinoma. [ABSTRACT FROM AUTHOR]

ZIF-8 and ZIF-67 are the most investigated zeolitic imidazolate frameworks (ZIFs) materials that have aroused enormous scientific interests in numerous areas of application including electrochemistry, gas storage, separation, and sensors by reason of their fascinating structural properties. Recently, there is a rapidly growing demand for chemical gas sensors for the detection of various analytes in widespread applications including environmental pollution monitoring, clinical analysis, wastewater analysis, industrial applications, food quality, consumer products, and automobiles. In general, the key to the development of superior gas sensors is exploring innovative sensing materials. ZIF-X (8, 67) based nanostructures have demonstrated great potential as ideal sensing materials for high-performance sensing applications. In this review, the general properties and applications of ZIF-X (8, 67) including gas storage and gas adsorption are first summarized, and then the recent progress of ZIF-X (8, 67) based nanostructures for gas-sensing applications and the structure-property correlations are summarized and analyzed. [ABSTRACT FROM AUTHOR]

The hydroxyapatite (HA) powder is successfully synthesized from calcined eggshell by the hydrothermal reaction method. The colloidal solution made of calcined eggshell powder, tricalcium phosphate powder, and demineralized water is kept in a closed ceramic vessel to perform hydrothermal reactions. For this purpose, different temperatures (700 - 1000 °C) for various time durations (1, 2, and 3 h) are applied to the solution. X-ray diffraction (XRD) analysis, field emission scanning electron microscopy (FESEM), and energy-dispersive X-ray spectroscopy (EDS) are employed to characterize the prepared powders. The synthesized powders are further assessed in terms of crystalline phase, microstructure, crystallite size, particle size, Ca/P ratio, and crystallinity. In all the reaction products, majorly the HA powders are obtained. The spherical HA grains are found to have a tendency to agglomerate at higher reaction temperatures and times. The applied temperature and heating duration are found to be the crucial parameters that control the properties of the synthesized HA. The HA with the largest crystallite size is obtained from 1000 oC of heating temperature applied for 3 h. However, the HA with high crystallinity is obtained from 800 oC temperature applied for 1 h of time. Non-stoichiometric HAs are obtained from all different reaction temperatures and time durations. Mostly Ca-rich (Ca/P > 1.67) HAs are formed in all powders except the one prepared at 900 ° C, where the formation of Ca-deficient (Ca/P < 1.67) HA is noticed. The near-stoichiometric HA can be produced from 900 oC of reaction temperature applied for 1 h. The study illustrates that HA can be synthesized successfully from chicken eggshell by hydrothermal reaction method in less time by applying high heating temperature. [ABSTRACT FROM AUTHOR]

During the synthesis of hydroxyapatite (HA) powder by hydrothermal reaction via Indian clam seashell, different phases are noticed to form along with HA. This is due to the incomplete forward reaction resulting in the retention of the reactants, absorption of moisture, or backward reaction. In the present work, the weight fraction of different phases for synthesized powders has been calculated through the Rietveld refinement method by using X-ray diffraction data. The reactions are carried out at different temperatures (700°C, 800°C, 900°C, 1000°C, and 1100°C) for several time durations (1 h, 2 h, and 3 h) in various independent hydrothermal reactions. The different phases formed in the synthesized powders were examined by the X-ray diffraction (XRD) technique in our previous study. In the present work, through Rietveld refinement, it is revealed that the powders synthesized at 700, 800, and 900°C for 2 h duration contain the highest amount of HA phase among the various time durations. On the other hand, highly pure HA powders can be prepared at 1000°C, and 1100°C applied for 3 h time. The vibration modes of PO43- tetrahedral for all the synthesized powders are studied through Raman spectroscopy. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) or 3D printing has opened up new opportunities for researchers in the field of electrical machines, as it allows for more flexibility in design and faster prototyping, which can lead to more efficient and cost-effective production. An overview of the primary AM techniques utilized for designing electrical machines is presented in this paper. AM enables the creation of complex and intricate designs that are difficult or impossible to achieve using traditional methods. Topology Optimization (TO) can be used to optimize the design of parts for various purposes such as weight, thermal, material usage and structural performance. This paper primarily concentrates on the most recent studies of the AM and TO of the reluctance machines. The integration of AM with TO can enhance the design and fabrication process of magnetic components in electrical machines by overcoming current manufacturing limitations and enabling the exploration of new design possibilities. The technology of AM and TO both have limitations and challenges which are discussed in this paper. Overall, the paper offers a valuable resource for researchers and practitioners working in the field of AM and TO of electrical machines. [ABSTRACT FROM AUTHOR]

Context: Cadmium (Cd) is a toxic metal for both plants and humans. Wheat grown on Cd-contaminated soils may accumulate toxic levels of Cd in grains. Aim: This study aimed to compare soil zinc (Zn) application and seed Zn-priming for decreasing grain Cd concentration in standard and Zn-biofortified wheat cultivars grown on Cd-spiked soil. Methods: Standard (Jauhar-2016) and Zn-biofortified (Zincol-2016) wheat cultivars were grown in pots filled with Cd-spiked soil (8 mg Cd kg−1). The tested Zn treatments were un-primed, hydro-primed, and Zn-primed seeds with and without soil Zn application at 8 mg kg−1. Key results: Zinc treatments significantly mitigated the toxic effects of Cd on the growth and physiological parameters of both cultivars. As compared to control, all Zn treatments significantly increased Zn and decreased Cd concentration in grains of the cultivars. On average, the maximum increase in grain Zn concentration over control was approximately 36% with Zn-priming + soil Zn. The same treatment, as compared to control, decreased grain Cd concentration by 42% in Zincol-2016 and 35% in Jauhar-2016. Grain Cd concentration was within the permissible level (≤0.2 mg kg−1) in Jauhar-2016 at all Zn treatments and in Zincol-2016 at Zn-priming + soil Zn. Conclusion: Soil Zn application, seed Zn-priming, and their combination were effective in decreasing grain Cd accumulation in wheat grown on Cd-contaminated soil. Implication: Zinc treatments, especially the combination of soil Zn application and seed Zn-priming, should be recommended for wheat grown on Cd-contaminated soil. Wheat grown on Cd contaminated soils may accumulate toxic levels of Cd that may enter the human food chain. This study compared Zn treatments for standard and Zn-biofortified wheat cultivars grown on Cd-spiked soil. Seed Zn-priming, soil Zn application and their combination were effective in decreasing grain Cd concentration below the permissible limit of 0.2 mg Cd kg−1. [ABSTRACT FROM AUTHOR]

Lung cancer is a high-risk disease that causes mortality worldwide; nevertheless, lung nodules are the main manifestation that can help to diagnose lung cancer at an early stage, lowering the workload of radiologists and boosting the rate of diagnosis. Artificial intelligence-based neural networks are promising technologies for automatically detecting lung nodules employing patient monitoring data acquired from sensor technology through an Internet-of-Things (IoT)-based patient monitoring system. However, the standard neural networks rely on manually acquired features, which reduces the effectiveness of detection. In this paper, we provide a novel IoT-enabled healthcare monitoring platform and an improved grey-wolf optimization (IGWO)-based deep convulution neural network (DCNN) model for lung cancer detection. The Tasmanian Devil Optimization (TDO) algorithm is utilized to select the most pertinent features for diagnosing lung nodules, and the convergence rate of the standard grey wolf optimization (GWO) algorithm is modified, resulting in an improved GWO algorithm. Consequently, an IGWO-based DCNN is trained on the optimal features obtained from the IoT platform, and the findings are saved in the cloud for the doctor's judgment. The model is built on an Android platform with DCNN-enabled Python libraries, and the findings are evaluated against cutting-edge lung cancer detection models. [ABSTRACT FROM AUTHOR]

A suitable mixture of Ba(NO3)2 and Al powders, known as pyrotechnic mixture, was burned to deposit pure BaAl2O4 and Ni-BaAl2O4 coatings on low-carbon steel by a new explosive spray coating method. Ni-5Al is a bonding coating material commonly used in thermal spraying to deposit ceramics on metal substrates to achieve strong coating-substrate adhesion. In addition, because it is hard in nature, this material has the potential to impart toughness to a brittle composite. Therefore, Ni-5Al powder was added to the explosive spray charge to deposit a Ni-BaAl2O4 composite coating. Various characterization techniques, such as x-ray diffraction, field emission scanning electron microscopy with energy-dispersive spectroscopy analysis, transmission electron microscopy (TEM), Vickers hardness test, scratch test, image analysis, and roughness estimation were used to compare various properties of the two coatings. It was found that the Ni-based globules are uniformly distributed in the Ni-BaAl2O4 coating. BaAl2O4 and Ba phases were observed in the pure BaAl2O4 coating, while Ni, BaAl2O4 and Ba2Al2O5 phases were mainly formed in the Ni-BaAl2O4 coating. The formation of Ni-Fe and Ni-Al based compounds and the interdiffusion of materials in the interface region of this type of coating significantly improved the coating-substrate adhesion. The TEM analysis confirmed the presence of brittle crystalline and amorphous phases in both coatings. The overall crystallinity of Ni-BaAl2O4 was higher than that of the pure BaAl2O4 coating material. The increase in hardness and reduction in crack formation in the Ni-BaAl2O4 composite also suggests an improvement in toughness. In addition, the average surface roughness and porosity of the Ni-BaAl2O4 coating were lower than that of the pure BaAl2O4 coating. The addition of Ni-5Al to the feedstock improved the mechanical properties of the explosively deposited BaAl2O4-based coating. [ABSTRACT FROM AUTHOR]

The invasive polyphagous pest Fall armyworm (FAW) Spodoptera frugiperda, (Lepidoptera: Noctuidae) is a migratory pest of maize crops in Asia and other countries including Pakistan. It is mostly fed on leaves at the larval stage this pest can be controlled by various types of pesticides globally but now resistance has come in pest against insecticides. So, we can also control this pest by other control strategies including physical, biological, and mechanical Eco-friendly Mycoinsecticides fungus Beauveria bassiana, Trichoderma, and Metarhizium anisopliae instead of chemical control method. By this, we can save our ecosystem and nature from the hazardous effects of chemicals. According to in vitro bioassay of entomopathogenic fungi like Beauveria bassiana Trichoderma and Metarhizium anisopliae under control conditions Metarhizium anisopliae was found very effective on fall armyworm 1st 2nd 3rd and 4th instar larvae and mortality percent was recorded 85.5% on 1st 2nd and 3rd instar larvae at 40ppm dose while minimum mortality was recorded 18.6% on 10ppm dose of Trichoderma during bioassay under control condition. During the second instar larvae of bioassay entomopathogenic fungi, Metarhizium anisopliae was recorded as very effective and showed mortality of FAW up to 83.3% at a dose of 40ppm after exposure of three days at 25℃ approximately. While minimum mortality of FAW was recorded at 10 ppm after exposure for three days. In 2nd instar larvae, exposer Metarhizium anisopliae was found to have entomopathogenic potentials and Couse highest mortality of FAW the minimum mortality was recorded at 48% on 10 ppm dose exposure of M. anisopliae after three days at 25℃ and approximately 53% humidity. The studies show that the entomopathogenic potentials of fungi decrease with increasing larval instars. On 3rd and 4th instar larvae only M. anisopliae was recorded as effective and mitigated the larvae population 78.5% at 40 ppm and 55.8% mortality was observed on 4th instar larvae after exposure of three days among all Metarhizium anisopliae was found potential insecticidal properties as compare to Beauveria bassiana and Trichoderma. This comparative study shows that M. anisopliae was found highest insecticidal properties as compared to Beauveria bassiana and Trichoderma. So, M. anisopliae was found broad spectrum insecticidal potentials on FAW multiple larval stages under control conditions. Among all only Metarhizium anisopliae was found with exophytic sporulation characters and dynamic insecticidal potentials while Beauveria bassiana and Trichoderma were recorded as endo sporulation characters. [ABSTRACT FROM AUTHOR]

Laetiporus is a cosmopolitan genus of the "Antrodia clade" in the order Polyporales that causes brown rot in many hardwood trees and some conifers. In the current study, we examined specimens of Laetiporus zonatus collected from Quercus semecarpifolia (Fagaceae) at three different localities in the district Swat, KP, Pakistan. The specimen's identity was determined through extensive morphoanatomical examination and molecular characterization. For reconstruction of the phylogenetic relationships of the species, the study applied three methods: maximum parsimony (MP), maximum likelihood (ML), and Bayesian analyses to the concatenated dataset (ITS + nrLSU + rpb2). The mean character difference approach was utilized to create a phenetic cladogram through morphometric analysis. Our sample sequence grouped together with Laetiporus zonatus showing significant support values of 87% for MP, 98% for ML and 1.0 for Bayesian analyses. The morphological data matrix showed a high degree of similarity (Bray-curtis similarity = 0.925, Euclidean distance = 3.81) between our specimen and L. zonatus. Our study also provides habitat characteristics and in vitro cultural characteristics of the isolates. Laetiporus zonatus is characterized by yellow pileal surface, become pale buff to creamy when dry and whitish cream pore surface, distinctly zonate, radially furrowed upper surface and undulating white margin, 2-3 pores mm-1, ellipsoid to ovoid basidiospores (5.6-8.7 × 4.2-5.9 µm) with Q value of 1.16-1.55 and is found exclusively on Quercus spp. in temperate forests. [ABSTRACT FROM AUTHOR]

The current study investigates the MHD flow of nanofluid across an elongating surface while taking into account non-uniform heat flux. For this, we have considered the flow of a boundary layer over a stretched sheet containing (water-based) Al2O3 nanoparticles. The convective boundary conditions for temperature have been invoked. The flow created by a surface that is exponentially expanding in the presence of a magnetic field and a non-uniform heat flux has been mathematically formulated by using laws of conservation. Transformed non-dimensional systems of governing equations have been analyzed numerically by using Adam's Bashforth predictor corrector approach. The effects of emerging parameters on the fluid velocity and temperature profiles have been further described by plotting graphs. An experimental design and a sensitivity analysis based on Response Surface Methodology (RSM) are used to examine the effects of various physical factors and the dependence of the response factors of interest on the change of the input parameter. To establish the model dependencies of the output response variables, which include the skin friction coefficient and the local Nusselt number, on the independent input parameters, which include the magnetic field parameter, the nanoparticle volume fraction, and the heat transfer Biot number, RSM is used. On the basis of statistical measures such as Q - Q residual plots, adjusted and hypothesis testing using p values, it is observed that both of our models for Skin Friction Coefficient (SFC) and the Local Nusselt Number (LNN) are best fitted. Further, it is concluded that the sensitivity of the SFC, as well as the LNN through heat transfer Biot number, is greater than that of nanoparticle volume fraction and magnetic field parameter. The SFC is sensitive to all combinations of the input parameters. At high levels of heat transfer Biot number, the LNN displays negative sensitivity via magnetic field parameters. [ABSTRACT FROM AUTHOR]

• An optimization framework is introduced to determine the new electricity rate, considering demand-side power capacity limitations. • An EV connection matrix was developed to make charging/discharging scheduling algorithm implementation much easier. • The modified particle swarm optimization (PSO) algorithm increases the convergence rate of the algorithm. • Simulation results revealed that the TOU rates should be applied according to a specific pattern, depending on the location. This paper introduces a framework to yield an electricity rate for vehicle-to-grid (V2G) charging station (CS) to minimize installation capacity of a charging station considering electric vehicle (EV) arrival/departure time distribution. Two different layers are designed to avoid an obstacle encountered when formulating the problem as a convex optimization and to represent an EV aggregator and an electricity rate decision maker – a regulator. The EV aggregator layer focuses on increasing the profit and the regulator minimizes the peak load of the V2G CS. Linear programming was formulated for the former layer, and a modified particle swarm optimization (PSO) method was developed for the latter. Modification of the PSO approach allowed for easier escape of local minima, resulting in a new electricity rate for the V2G CS based on the EV arrival/departure time distribution data. The algorithm employs new matrices devised in this paper to accommodate EV information in the optimization process. In a simulation study, two distinct CSs with V2G operations were evaluated, each with a different EV arrival/departure time distribution. The simulation revealed that the peak load and the profit of the aggregator vary dramatically depending on the arrival/departure time distributions. [ABSTRACT FROM AUTHOR]

Ammonia (NH 3) is an odorless gas with a pungent smell that can affect health differently based on exposure and concentration. In this study, indium oxide was decorated with cobalt oxide (In 2 O 3 /Co 3 O 4) flower-like nanocomposites (NFs) as gas-sensitive materials, revealing p-type semiconducting characteristics. The detection of ammonia (NH 3) at low concentrations is a significant challenge for chemoresistive gas sensors. Porous Co 3 O 4 nanoflowers were combined with In 2 O 3 nanoparticles to form p-n heterojunctions for NH 3 detection. The p-n heterojunction effect and the capability of the sub-valent band to hold vacancies within In 2 O 3 nanoparticles effectively inhibit electron-hole recombination and extend the carrier lifetime. The In 2 O 3 /Co 3 O 4 = 0.04 ratio-based gas sensor exhibited excellent selectivity, achieving a low detection limit of 500 ppb for NH 3 at 250 °C. The rapid diffusion of gas within the porous Co 3 O 4 NSs and In 2 O 3 nanoparticles accounted for the high response (7.72) and fast response/recovery time (92 s/51 s) of the In 2 O 3 /Co 3 O 4 -based gas sensor to 10 ppm NH 3. This study presents a method for fabricating NH 3 gas sensors with trace-level detection capabilities by adjusting the band structure of nanoparticles and three-dimensional metal-oxide nanostructures. [ABSTRACT FROM AUTHOR]

The most well-known, effective medicines for acne therapy are clindamycin phosphate and tretinoin. For the first time, we have developed and validated a reversed-phase HPLC stability-indicating technique for the detection of clindamycin phosphate (CLP), tretinoin (TRN), and two preservatives, methylparaben (MP) and imidazolidinyl urea (IU), simultaneously in this work. Most of the chromatographic conditions in the present study were optimized to achieve better separation. The best separation results were obtained using gradient elution on a C-18 (250 × 4.6 mm), 5 µm column, with a mobile phase consisting of solution A (1 mL/L ortho-phosphoric acid in water) and solution B (methanol), at a flow rate of 1.0 mL/min, with UV detection at wavelengths of 200 nm and 353 nm. Standard parameters such as system suitability, precision, accuracy, specificity, robustness, linearity, range, detection limit, quantification limit, and reagent stability were used to validate the developed technique. According to the standards of the International Council for Harmonization, all of the experimental parameters were found to be within allowable bounds (ICH). The simultaneous concentrations of clindamycin phosphate, tretinoin, methylparaben, and imidazolidinyl urea in pharmaceutical formulations were successfully determined using the suggested approach. The proposed RP-HPLC method detected no interfering peaks in the chromatogram. We may conclude from the data that the new RP-HPLC method can be utilized in pharmaceutical laboratories to simultaneously assess clindamycin phosphate, tretinoin, and two preservatives, methylparaben and imidazolidinyl urea, for both qualitative and quantitative analyses. [ABSTRACT FROM AUTHOR]

Methyl jasmonate (MeJA) is a potent player that fine-tunes growth and developmental activities under salinity stress. In this study, we investigated the influence of MeJA on two rice cultivars (NJ9108 and XD22) subjected to different salinity stresses. Following stress treatment, reduction in the water use efficiency, relative water contents, and membrane stability index in both cultivars were observed, whereas MeJA treatment partially alleviated the negative effects. MeJA treatment significantly increased the maximum photochemical efficiency (Fv/Fm) and electron transfer to photosystem II (Fv/Fo). Under salinity stress, MeJA treatment significantly triggered the H2O2 and APX accumulation, while POD and SOD remained unchanged in both cultivars. Salt stress increased Na+ concentration in the roots and leaves but decreased K+ concentration and the K+/Na+ ratio in both cultivars. However, MeJA-treated plants had the maximum K+ accumulation in both leaves and roots under saline conditions. The differential expression pattern of OsHKT and OsHAK genes implied that ion homeostasis is crucial to growth under salt stress. These findings suggest that the application of MeJA can be an alternative source of reducing salinity without compromising growth and yield. [ABSTRACT FROM AUTHOR]

The high-affinity potassium transporter (HKT) genes are key ions transporters, regulating the plant response to salt stress via sodium (Na+) and potassium (K+) homeostasis. The main goal of this research was to find and understand the HKT genes in rice and their potential biological activities in response to brassinosteroids (BRs), jasmonic acid (JA), seawater, and NaCl stress. The in silico analyses of seven OsHKT genes involved their evolutionary tree, gene structures, conserved motifs, and chemical properties, highlighting the key aspects of OsHKT genes. The Gene Ontology (GO) analysis of HKT genes revealed their roles in growth and stress responses. Promoter analysis showed that the majority of the HKT genes participate in abiotic stress responses. Tissue-specific expression analysis showed higher transcriptional activity of OsHKT genes in roots and leaves. Under NaCl, BR, and JA application, OsHKT1 was expressed differentially in roots and shoots. Similarly, the induced expression pattern of OsHKT1 was recorded in the seawater resistant (SWR) cultivar. Additionally, the Na+ to K+ ratio under different concentrations of NaCl stress has been evaluated. Our data highlighted the important role of the OsHKT gene family in regulating the JA and BR mediated rice salinity tolerance and could be useful for rice future breeding programs. [ABSTRACT FROM AUTHOR]

In SPC, the most effective and magnificent tool is the control chart. The structure of control charting schemes required the assumption that the process is free from disturbances with known parameters or correctly estimated from the in-control process. These assumptions need to full fill for monitoring location parameter with mean control charts. But in practical, these assumptions are not always true, due to occasionally presence of outliers. That is why the median is a suitable measure as compared to the mean in the presence of disturbances. The ranked and neoteric ranked set samplings are suggested in this study to monitor the location parameter of the process by using median estimator for CUSUM , EWMA and Shewhart type control charts. The run-length profile is used as a performance measure for proposed median based control charts. The results reveal that for median control charts based on neoteric ranked set sampling scheme yield excellent outcomes. The real-life application is provided of the new charting schemes. [ABSTRACT FROM AUTHOR]

Simple Summary: Altered nuclear receptor signaling is well-established to contribute to a range of hormone-dependent cancers and therefore they are therapeutic targets, for example in breast and prostate cancer. However, nuclear receptor signaling in the cancer, and in response to therapeutic targeting is frequently altered in part by changes to the expression and function of the large numbers of coregulators that modulate sensitivity of the receptor, change their protein-protein interaction and alter the transcriptional consequences. These coregulators perform numerous roles in terms of regulating nuclear receptor responses and the functional diversity of these interactions is an area of emerging insight. Coregulator interactions, functions, and impacts on nuclear receptor signaling across hormone dependent cancers are the topic of this review. Nuclear receptors (NRs) function collectively as a transcriptional signaling network that mediates gene regulatory actions to either maintain cellular homeostasis in response to hormonal, dietary and other environmental factors, or act as orphan receptors with no known ligand. NR complexes are large and interact with multiple protein partners, collectively termed coregulators. Coregulators are essential for regulating NR activity and can dictate whether a target gene is activated or repressed by a variety of mechanisms including the regulation of chromatin accessibility. Altered expression of coregulators contributes to a variety of hormone-dependent cancers including breast and prostate cancers. Therefore, understanding the mechanisms by which coregulators interact with and modulate the activity of NRs provides opportunities to develop better prognostic and diagnostic approaches, as well as novel therapeutic targets. This review aims to gather and summarize recent studies, techniques and bioinformatics methods used to identify distorted NR coregulator interactions that contribute as cancer drivers in hormone-dependent cancers. [ABSTRACT FROM AUTHOR]

• Synthesis of unique porous NiO@CuO NFs derived by porous Ni-MOF and CuO nanosphere by an accessible template-assisted method. • High specific surface area, porosity and bi-metallic ions sustenance with 3D sharp-tip and nanosphere nanostructures. • Heterojunction aided high selectivity and response of fabricated sensor towards reducing gas H 2. Nickel oxide (NiO) is an optimal material for precise detection of hydrogen (H 2) gas due to its high catalytic activity and low resistivity. However, the solid structure of NiO imposes limitations on the gas response kinetics of H 2 gas molecules, resulting in a slower electron–hole transit and reduced gas response value. Herein, a unique NiO@CuO NFs with porous sharp-tip and nanospheres morphology was successfully synthesized by using a metal–organic framework (MOF) as a precursor. The fabricated porous 2 wt% NiO@CuO NFs describes outstanding selectivity towards H 2 gas, including a high sensitivity of response value (170–20 ppm at 150 °C), is almost 28.3 % higher than that of porous Ni-MOF, low detection limit (300 ppb) with a notable response (21), short response and recovery times at (300 ppb, 40/63 s and 20 ppm, 100/167 s), exceptional long-term stability and repeatability. The study also explored the impact of relative humidity to evaluate the sensor performance under real-world conditions. The boosted hydrogen dioxide sensing properties may be attributed to synergistic effects of numerous factors including p-p heterojunction at the interface between NiO and CuO nanoflowers, especially a porous sharp-tip MOF structure and rough surface of nanospheres as well as the chemical sensitization effect of NiO. This research offers a viable method for creating unique MOS heterostructures from Ni-MOF and CuO that have unique morphologies and compositions that could be used for H 2 gas sensing applications. [Display omitted] [ABSTRACT FROM AUTHOR]

Hydrogen sulfide (H 2 S) is a colorless toxic acidic gas, so the development of gas sensors that can effectively detect H 2 S in the environment is critical to protecting human health. Metal-organic frameworks (MOFs) are emerging as promising template for semiconductor materials in gas sensor technology, offering unique structural advantages for various sensing applications. This study aimed to understand the properties of Indium-doped ZIF-67 nanoflowers by analyzing their crystal structure, surface morphology, and chemical composition. It also investigated the hydrogen sulfide (H 2 S) gas-sensitive properties of these materials to fully comprehend their capabilities and limitations. It is demonstrated that the Co 3 O 4 sensor doped with 5 % In displays excellent stability, gas selectivity, and responsiveness. Specifically, the Co 3 O 4 sensor doped with 5 % In showed a response of 19–50 ppm H 2 S at an operating temperature of 180 °C, which was significantly higher than that of the pure Co 3 O 4 sensor. This is mainly due to the high content of oxygen vacancy (11.26 %). In the 5 % In doped sample, and the relatively large specific surface area (60.58 m2g-1). [ABSTRACT FROM AUTHOR]

This study reports the synthesis and modification of hexagonal ZnO to face-centered cubic (Fcc) Zn 2 SnO 4 via a single hydrothermal method. We systematically investigated the synthesized materials' structural, morphological, surface area, and sensing properties. X-ray diffraction (XRD) analysis confirmed the Fcc structure of the Sn-modified ZnO samples. X-ray photoelectron spectroscopy (XPS) was employed to elucidate the influence of Sn modified on defect levels in these chemical sensors. Remarkably, Zn 2 SnO 4 exhibited outstanding NO 2 sensing properties, including high response, selectivity, and recovery characteristics. The sensor demonstrated a rapid response time of less than 18s and an optimal operating temperature of 260 °C. Furthermore, the cubic face-centered Zn 2 SnO 4 displayed a wide detection range of 1–100 ppm for NO 2. The synergistic effects of chemical sensitization and catalytic activity are responsible for the enhanced sensing mechanism in Zn 2 SnO 4. [Display omitted] [ABSTRACT FROM AUTHOR]

Carbon monoxide (CO) is one of the most dangerous gases owing to its dual threat, role in global warming, and severe impact on human health. Metal-organic framework (MOF) gas-sensing materials have drawn the interest of many different sectors due to their unique structural characteristics. This study used a solvothermal technique and subsequent annealing to create a hierarchical, yeast-shaped Mo-Co 3 O 4 material from a Co-MOF precursor. The prepared materials have been employed in the development of a CO-detection gas sensor. Gas-sensing experiments revealed that Mo-Co 3 O 4 exhibited significantly improved sensing capabilities compared to pure Co 3 O 4. Notably, at 200 °C, 2 mol% Mo-Co 3 O 4 showed high response levels of about 136 at 100 ppm CO concentrations, approximately 50.4 times higher than pure Co 3 O 4. Furthermore, the Mo-doped material exhibited a low detection threshold, excellent reproducibility, long-term stability, good selectivity, and rapid response and recovery times (78.5/55.3 s). Introducing Mo dopants into the Co 3 O 4 material and the hierarchical yeast-like nanostructure are responsible for these improvements in gas-sensing capability. • Utilizing the solvothermal synthesis, a yeast-like Mo-Co 3 O 4 nanostructure for gas sensors. • Remarkable selectivity and effectiveness in detecting CO gas at 200 °C. • Mo dopants and hierarchical structure contribute to improved gas-sensing performance. • Exceptional stability and low detection limits, ensuring reliable long-term gas sensing performance. [ABSTRACT FROM AUTHOR]

Metal-organic frameworks (MOF)-based gas sensors have garnered significant interest and are highly desirable for monitoring indoor air quality and mitigating various environmental reclamation challenges. Herein, we describe a unique approach for fabricating hydrogen sulfide (H 2 S) gas sensors based on MOF-derived cobalt oxide nanosheets (Co 3 O 4 Ns) nanostructures. The surface morphology and porosity of the fabricated material were confirmed through comprehensive Brunauer-Emmett-Teller (BET) and electron microscopy analyses. Chemical composition and phase purity were identified using Energy-dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), and X-ray diffraction (XRD). The sensor exhibited remarkable sensitivity towards hydrogen sulfide in the range of 0.5–100 ppm, reaching a maximum response of 1702.61 % at an operating temperature of 250 °C for 100 ppm H 2 S gas. Furthermore, the sensor demonstrated a detection limit of 500 ppb with a response rate of 78.22 %. A consistent stability over 30 days was observed, validating its suitability for real-world applications. The response and recovery times of the H 2 S gas sensors were assessed with τ res /τ rec = 63.56/103.34 s, offering valuable insights into their real-world applicability. [Display omitted] • Simple Coprecipitation synthesis technique producing Co 3 O 4 nanosheets for gas sensors. • Co 3 O 4 nanosheets show high selectivity and efficiency in H 2 S gas at 250 °C. • CTAB concentration improves ZIF-67-derived-Co 3 O 4 nanomaterials porous topologies, improving gas sensing properties. • Co 3 O 4 nanomaterials exhibit exceptional stability, ensuring long-term gas sensing reliability. [ABSTRACT FROM AUTHOR]

The proliferation of electric vehicle (EV) adoption strains low-voltage distribution networks, particularly in aggregated charging scenarios, prompting utility companies to incentivize charging aggregators for optimizing load balancing within thermal limits. These aggregators utilize machine learning algorithms to understand electricity price signals and orchestrate the optimization of the EV charging process. However, conventional machine learning approaches fall short when dealing with the dynamic and volatile nature of electricity prices, emphasizing the necessity for advanced ensemble models. This paper introduces a novel Deep-Weighted Ensemble Model (DWEM) rooted in standard and stacked Long Short-Term Memory (LSTM) networks designed for wholesale electricity price forecasting, to manage the EV charging at the aggregator level. The ensemble development process involves developing an architecture that highlights the significance of the DWEM model in supporting aggregators for the charging optimization of EVs. The charging optimization problem of aggregated EVs is formulated, and the heuristic mechanism is systematically presented, evaluating various weight configurations, and selecting those characterized by the highest levels of accuracy to comprise the ensemble model. Moreover, we incorporated a standard deviation mechanism to evaluate the impact of the proposed DWEM on forecasting accuracy, mean squared error, and mean absolute error across various standard deviation levels. We leveraged a publicly available Houston electricity dataset and performed a detailed data engineering mechanism, accounting for data both with and without outliers. Subsequently, we applied the proposed DWEM to this dataset and conducting three types of comparative analysis: (a) evaluating model performance in terms of accuracy, mean square error, and mean absolute error; (b) assessing aggregator charging analysis focusing on charging load and cost; and (c) analyzing computational complexity and execution time. The simulation results demonstrated a improvement in accuracy and reduction in charging load and cost compared to state-of-the-art methods, while maintaining competitive computational complexity. • Developed a Deep-Weighted Ensemble Model for wholesale electricity price forecasting. • Formulated a charging optimization problem for aggregated electric vehicles. • Introduced a heuristic mechanism for determining optimal weights in the ensemble model. • Enhanced charging efficiency at the aggregator level. [ABSTRACT FROM AUTHOR]

The detection of small quantities of hazardous and flammable gases at room temperature is crucial for protecting human health and the environment. In this study, the indium oxide (In 2 O 3) and MXene (Ti 3 C 2) were prepared separately using different techniques and then combined to form a composite through sonication in an ethanol solution. The findings from the gas-sensing performance revealed that the In 2 O 3 /Ti 3 C 2 nanocomposites had very high response values of 3785.01 and 33.84 towards 100 and 10 ppm NO 2 gas at the optimal working temperature (150 °C) respectively. The In 2 O 3 /Ti 3 C 2 -1 composite has a strong linear relation (R2 = 0.9869), it is reproducible and has prolonged detection stability. The occurrence of oxygen vacancies and the creation of Schottky barriers are principally responsible for the outstanding gas-sensing capabilities reported. The computed response and recovery times were 24 and 56 s respectively under 100 ppm NO 2 environment showing strong selectivity toward the gas. This research combines density function theory (DFT) to investigate the room-temperature gas sensitivity of indium oxide-MXene nanocomposites, shedding new light on how to optimize the materials for practical applications in wearable and low-energy consumption devices. [Display omitted] • Facile synthesis of In 2 O 3 @MXens nanosheets for efficient detection of NO 2 gas with ultimate senor stability. • High specific surface area, porosity and multi-metallic ions sustenance with 2D nanostructures. • DFT simulation for adsorption energy to fully understand gas-sensing mechanism. • The fabricated gas sensor proved to be potential practical applicant in low-energy consumption devices. [ABSTRACT FROM AUTHOR]

Hydroxyapatite (HA) powder has been successfully synthesized from low-cost Indian clam seashells by using hydrothermal method. The mixture of tri-calcium phosphate [Ca 3 (PO 4) 2 ], heat-treated ball-milled clam seashell, and demineralized water are heat-treated at several temperatures (700 °C, 800 °C, 900 °C, 1000 °C, and 1100 °C) for various time periods (1 h, 2 h, and 3 h) to perform the hydrothermal reactions. The phases and microstructure of the solid-state reaction products are analyzed through X-ray diffraction (XRD) method and field emission scanning electron microscopy (FESEM) respectively. The crystallite size of all the synthesized powders is calculated by using Scherrer's model. Mainly HA phase is obtained in all the different reaction products. However, these HAs are found to be non-stoichiometric in nature. As per the literature, non-stoichiometric HA is a more biologically active material compared to the stoichiometric one. Almost pure HA is formed with any selected reaction temperature applied for 2 h time duration. The crystallinity and Ca/P ratio of the synthesized pure HA are estimated by using standard model and energy-dispersive X-ray spectroscopy (EDS) analysis, respectively. The highest amount of near stoichiometric crystalline HA has been obtained at 900 °C of reaction temperature applied for 2 h time duration. With raising reaction temperature, the grain size of pure HA is found to be increased. Needle/rod shaped nano grains are noticed to form at lower reaction temperature whereas; beyond 1000 oC of temperature globular/spherical shaped grains are also observed to form. At 3 h reaction time agglomeration of grains is found to occur in all the synthesized powders. [ABSTRACT FROM AUTHOR]

This is the third and the last part of the special issue on Mineral Biofortification and Metal/Metalloid Accumulation in Food Crops. A brief description of the research articles included in this part of the special issue is provided. [ABSTRACT FROM AUTHOR]

Depth estimation from a single image frame is a fundamental challenge in computer vision, with many applications such as augmented reality, action recognition, image understanding, and autonomous driving. Large and diverse training sets are required for accurate depth estimation from a single image frame. Due to challenges in obtaining dense ground-truth depth, a new 3D pipeline of 100 synthetic virtual human models is presented to generate multiple 2D facial images and corresponding ground truth depth data, allowing complete control over image variations. To validate the synthetic facial depth data, we propose an evaluation of state-of-the-art depth estimation algorithms based on single image frames on the generated synthetic dataset. Furthermore, an improved encoder–decoder based neural network is presented. This network is computationally efficient and shows better performance than current state-of-the-art when tested and evaluated across 4 public datasets. Our training methodology relies on the use of synthetic data samples which provides a more reliable ground truth for depth estimation. Additionally, using a combination of appropriate loss functions leads to improved performance than the current state-of-the-art network performances. Our approach clearly outperforms competing methods across different test datasets, setting a new state-of-the-art for facial depth estimation from synthetic data. [ABSTRACT FROM AUTHOR]

Introduction: CBD injury is one of the serious complications after open or laparoscopic cholecystectomy. It increases the morbidity & mortality of patients as well as impairs their quality of life. Objectives: To find out the type of CBD injury in open & laparoscopic cholecystectomy and early post-operative complications after surgical management of CBD injury. Study design: Descriptive, case series study. Settings: Department of General Surgery, Bahawal Victoria Hospital, Bahawalpur. Study duration: 1st January, 2014 to 31st December, 2020 Material & Methods: All patients who had iatrogenic common bile duct injury during open or laparoscopic cholecystectomy of any age and gender were included in this study. CBD injuries due to other causes were excluded from the study. A well-constructed predesigned performa including demographic profile, mode of admission, clinical presentation, place of surgery, type of surgery (open or laparoscopic), investigations, operative findings, and post-operative complications were recorded. Results: A total of 35 patients were presented to the Surgical Department with CBD injuries. 20 patients had CBD injury after open cholecystectomy & 15 patients after laparoscopic cholecystectomy. The age range in this study was from 20 to 60 years with a mean age of 42.84±8.83 years. The male to female ratio was 1:4.84. 23-patients had their cholecystectomy in some private hospitals, 9-patients had been operated on in District Headquarter (DHQ) Hospital and 3-patients were operated in a teaching hospital. In 82.85% of patients, CBD injury was of class III type according to Stewart way classification & the commonly performed operative procedure was Roux-en Y choledocho-jejunostomy. The common post-operative complication was wound infection and intra-abdominal abscess in 51.5% of patients. Conclusion: Iatrogenic CBD injury is a serious complication during cholecystectomy. The important point for successful treatment is characterized by early recognition of injury, control of infection, drainage of abdominal collection, nutritional support & repair of CBD by an experienced surgeon. [ABSTRACT FROM AUTHOR]

Software requirements play a vital role in ensuring a software product's success. However, it remains a challenging task to implement all of the user requirements, especially in a resource-constrained development environment. To deal with this situation, a requirements prioritization (RP) process can help determine the sequence for the user requirements to be implemented. However, existing RP techniques are suffered from some major challenges such as lack of automation, excessive effort, and reliance on stakeholders' involvement to initiate the process. This study intends to propose an automated requirements prioritization approach called association rule mining-oriented (ARMO) to address these challenges. The automation process of the ARMO approach incorporates activities to first pre-process the requirements description and extract features. The features are then examined and analyzed through the applied rule mining technique to prioritize the requirements automatically and efficiently without the involvement of stakeholders. In this work, an evaluation model was further developed to assess the effectiveness of the proposed ARMO approach. To validate the efficacy of ARMO approach, a case study was conducted on real-world software projects grounded on the accuracy, precision, recall, and f1-score measures. The promising experimental results demonstrate the ability of the proposed approach to prioritize user requirements. The proposed approach can successfully prioritize user requirements automatically without requiring a significant amount of effort and stakeholders' involvement to initiate the RP process. [ABSTRACT FROM AUTHOR]

Toxicant testing is a major component of the environmental solution testing program. This test system aims to evaluate the sensitivity of the test species, evaluate comparability between laboratory test results, and classify possible variability sources such as healthy organisms, organism batches, laboratory water, and food quality changes. For the continuous assessment of sensitivity and accuracy of laboratory toxicity tests, control charts are often used. The cumulative sum (CUSUM) charting structure is a popular monitoring tool that is often used due to its outstanding ability in recognizing small‐to‐moderate unusual changes in process parameters. The CUSUM control charts have now been widely accepted/applied for monitoring the process dispersion under the assumption that the process does not have outliers. In practice, most of the processes have outliers. Therefore, the use of the interquartile range (IQR) as a plotting statistic is an attractive choice for dispersion monitoring. Hence, in this study, the CUSUM control chart with auxiliary information‐based IQR estimators is proposed and employed to monitor dispersion or variation in the variable LC50 by using quantitative structure–activity relationship (QSAR) aquatic toxicity data set. The proposed IQR‐CUSUM charts are compared to its counterparts by using a variety of main output run‐length functions, such as average run length (ARL), standard deviation of run length (SDRL), and extra quadratic loss (EQL), derived from the distribution of run‐length. Further, results revealed that the proposed CUSUM charts have better detection ability as compared to existing counterpart charts, both in theoretical and practical considerations. Control charts are often used for process monitoring. Cumulative sum (CUSUM) charts are popular monitoring tool. The use of the interquartile range (IQR) as a plotting statistic is an attractive choice for dispersion monitoring. In this study, the CUSUM control chart with auxiliary information‐based IQR estimators is proposed and employed to monitor dispersion or variation in LC50 by using quantitative structure‐activity relationship (QSAR) aquatic toxicity data set. The results revealed that the proposed charts outer performed as compared to existing counterpart charts. [ABSTRACT FROM AUTHOR]