Search

This study investigates the impact of post-annealing time duration on the structural, electrical, and thermoelectric properties of BiSnTe alloy thin films grown using a simple thermal evaporation route. X-ray diffraction (XRD) analysis revealed that grown samples exhibited a cubic rock-salt structure, with enhanced crystallinity and increased lattice parameters as post-annealing time extended from 1 to 4 h. Raman spectroscopy indicated shifts in vibrational modes toward lower wavelengths, attributed to the redistribution of Bi atoms within the SnTe matrix during annealing. Scanning electron microscopy (SEM) demonstrated uniform surface morphology with grain growth corresponding to longer annealing times. Electrical measurements showed a decrease in charge carrier concentration from 7.62 × 1019 cm−3 to 6.34 × 1019 cm−3 and a reduction in mobility from 202.21 cm2V−1 s−1 to 126.89 cm2V−1 s−1. This was correlated with grain growth, defect formation, and strain relaxation. The Seebeck coefficient increased the as-grown BiSnTe alloy thin film to 4 h post-annealed sample from 13.30 to 81.3 mV/K due to the reduction of carrier concentration with increasing the post-annealing duration. The corresponding thermoelectric power factor reached 1461 µWm−1 K−2, demonstrating the material's potential for thermoelectric applications. [ABSTRACT FROM AUTHOR]

Despite several studies on corporate social responsibility (CSR) and innovation on firm performance, the extent to which different CSR practices interacts with distinct innovation types in enhancing firm performance remains underexplored. We draw on contingency theory to examine how internal and external CSR interacts with exploitative and explorative innovation to improve firm performance. We discuss the interaction effects using a panel dataset of 1156 publicly listed Chinese firms that disclosed CSR and innovation information from 2008 to 2019. The results indicate that firms with high‐internal CSR benefit to a greater extent from explorative innovation than from exploitative innovation as a means of enhancing performance. In contrast, firms with high‐external CSR benefit to a greater extent from exploitative innovation than from explorative innovation to improve performance. We contribute to strategy and CSR literature by revealing how firms match specific CSR practices with distinct innovation types to enhance firm performance. [ABSTRACT FROM AUTHOR]

Purpose: This research seeks to identify ethical leadership and sustainable performance from a theoretical perspective. Theoretical Framework: Based on what researchers (Kyalo, 2019) reported, these organizations must adopt one of the leadership styles that helps them enhance their reputation from an ethical standpoint in the society within which they operate. Design/Methodology/Approach: The study analyses hospital data (2023-2024), using the ethical leadership model with its three components (justice, power sharing, and role clarification) in enhancing sustainable performance with its three components (social performance, economic performance, and environmental performance). Findings: The results confirmed the existence of a vital role for ethical leadership in enhancing the sustainable performance of Al-Muqdadiya Hospital, and therefore the hypotheses of this research (main and subsidiary) were accepted. Research Implications: The results confirm the need for Al-Muqdadiya Hospital to form a work team of leaders who are distinguished by ethical principles and adhere to them when carrying out the tasks and duties assigned to them, in a way that enhances their role in investing the resources available to the hospital when meeting the standards and indicators of sustainable performance that it seeks. Originality/Value: This study confirms that modern business organizations of all types, as well as the sector in which they operate, need to strengthen their relationship with the environment in which they operate, due to the wide wave of environmental transformations, as well as the rapid changes that the world is witnessing, specifically in the ethical and social aspects. [ABSTRACT FROM AUTHOR]

BACKGROUND: This study used four different apricot (Prunus armeniaca) kernels cultivated in Malatya during two consecutive years. The varieties were Hacihaliloglu, Hasanbey, Kabaasi, and Zerdali. The physicochemical properties of the kernels were determined, and the bioactive content of the kernels was evaluated using kernel hydrolysates prepared using trypsin. RESULTS: With regard to the physicochemical properties of the kernels, the dry matter ratio and protein content were the highest in the Hacihaliloglu variety; the ash ratio was the highest in the Kabaasi variety, and the free oil ratio was the highest in the Hasanbey variety. The bioactive compound content changed according to kernel variety. Angiotensin‐converting enzyme inhibitors activity was found to be the highest in the Hacihaliloglu and Hasanbey varieties, which had the lowest amygdalin content, and Zerdali had the highest amygdalin content. The antioxidant and antimicrobial effects of the kernels varied, with Hasanbey and Kabaasi generally having the highest content in both analyses. Moreover, a concentration of 20 mg mL−1 of the hydrolysate was determined to have a destructive effect for the microorganisms used in this study. The storage protein of the kernels, except Hacihaliloglu, was found to be Prunin 1, with the longest matching protein chain in the kernels being R.QQQGGQLMANGLEETFCSLRLK.E. CONCLUSION: The results suggest that the peptide sequences identified in the kernels could have antihypertensive, antioxidative, and Dipeptidyl peptidase IV (DPP‐IV) inhibitory effects. Consequently, apricot kernels show potential for use in the production of functional food products. Of the kernels evaluated in this study, Hacihaliloglu and Hasanbey were deemed the most suitable varieties due to their higher bioactive content and lower amygdalin content. © 2024 The Author(s). Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

This study presents the design and implementation of a piezoelectric power harvesting device to capture vibrational energy from pipelines to self-powered IoT devices. The device utilizes key components along with the PPA-1001 piezoelectric sensor, the STM32F103C8T6 microcontroller, and LTC-3588 energy harvesting power supply. Experimental results verified the system's performance in harvesting power within a specific frequency range of 10 Hz to 50 Hz, with the foremost overall performance at 30 Hz. The device generated the highest voltage of 3.3 V, delivering a power output of 2.18 mW, which is sufficient to power low-power electronic devices. The device maintained solid performance across a temperature range of 40 °C to 50 °C, underscoring its robustness in various environmental situations. The findings highlight the capacity of this form of generation to offer a sustainable power source for remote pipeline tracking, contributing to stronger protection and operational efficiency. [ABSTRACT FROM AUTHOR]

Vehicular ad hoc networks (VANETs) is an important topic nowadays. A lot of research deal and attracts consideration owing to potential for increasing traffic and travel efficiency, improving road safety for vehicles, providing convenience and comfort to both drivers and passengers. The need for a packet delivery ratio (PDR) and low delivery delay time in communication are the key elements in modern life especially when traveling in vehicles. To satisfy these demands; researchs in VANET systems aims to develop some new technologies. One of these technologies is using software-definednetwork (SDN) to enhance communication between vehicles on the road. Because of this, project evaluates using SDN protocol with two most viable VANET protocols which are ad hoc on demand distance vector (AODV) and optimized link state routing (OLSR) in LTE communication. Two performance metrics are used to evaluate the performances, the PDR and the delivery delay time. The simulation is performed in the varying density network and varying speed vehicles. The simulation results show that SDN displays better performance than AODV and OLSR in both PDR and delivery delay time. SDN uses global views of SDN controller to determine the shortest route with the highest vehicle density. Additionally, it solves the local maximum issue and adds dense connectivity. [ABSTRACT FROM AUTHOR]

Although herbicides are essential for global agriculture and controlling weeds, they impact soil microbial communities and CO2 emissions. However, the effects of herbicides, tillage systems, and nitrogen fertilisation on CO2 emissions under different environmental conditions are poorly understood. This review explores how various agricultural practices and inputs affect CO2 emissions and addresses the impact of pest-management strategies, tillage systems, and nitrogen fertiliser usage on CO2 emissions using multiple databases. Key findings indicate that both increased and decreased tendencies in greenhouse gas (GHG) emissions were observed, depending on the herbicide type, dose, soil properties, and application methods. Several studies reported a positive correlation between CO2 emissions and increased agricultural production. Combining herbicides with other methods effectively controls emissions with minimal chemical inputs. Conservation practices like no-tillage were more effective than conventional tillage in mitigating carbon emissions. Integrated pest management, conservation tillage, and nitrogen fertiliser rate optimisation were shown to reduce herbicide use and soil greenhouse gas emissions. Fertilisers are similarly important; depending on the dosage, they may support yield or harm the soil. Fertiliser benefits are contingent on appropriate management practices for specific soil and field conditions. This review highlights the significance of adaptable management strategies that consider local environmental conditions and can guide future studies and inform policies to promote sustainable agriculture practices worldwide. [ABSTRACT FROM AUTHOR]

The present study is focused on the synthesis of zero-valent iron/cellulose acetate (Fe0-x/CA) membranes by phase inversion route for the activation of peroxymonosulfate (PMS). The generated •OH and SO4•− effectively degraded methylene blue (MB) dye in water to give comparatively non-toxic byproducts. The SEM investigations revealed that Fe0 nanoparticles are evenly dispersed into the CA membrane resulting in decline of agglomeration and enhancing the roughness of the composite surface. Moreover, the catalytic degradation of MB demonstrated that M5-alone showed 85% and was further boosted to 97% when coupled with PMS (M5/HSO5−). The catalytic degradation of degradation of MB by M5/HSO5− membrane system in acidic, neutral, and basic media indicated that the degradation was 99.5%, 98.0%, 97.0%, 86.0% and 70.0% when the pH of the medium was 3, 5, 7, and 11, respectively. Furthermore, the degradation performance of M5/HSO5− membrane system was evaluated in de-ionized water (DIW), tape water (TPW) and industrial wastewater (IWW) and the results indicated that MB catalytic degradation was in the order of DIW (97%) > TPW (84%) > IWW (68%). Besides, various parameters like water flux permeability, contact angle, porosity, and fouling performance were also investigated. In addition, the degradation products were evaluated, and the degradation pathways were proposed accordingly. [ABSTRACT FROM AUTHOR]

The technology of reconfigurable optical networks (RONs) is growing to be a promising solution to effectively cater to the rapidly increasing traffic generated by the digital society. The present study offers an overview of the datacenter technology and optical datacenter with details of its concepts and technologies. First, the optical data center systems are described and the components that describe it are network operations. Then, we detail the specific technologies that are important to data center networks throughout wide-area networks, analyzing them deeply. Finally, we make a comprehensive between some related works with an analysis of the algorithmic challenges faced by these technologies. In addition, we examine the solutions that have been developed to address these challenges and explore the relevant systems and implementation considerations. [ABSTRACT FROM AUTHOR]

The highly abundant and stable antiviral small RNA derived from honeysuckle, known as miR2911, has been shown to play a key role in inhibiting influenza virus infection and SARS-CoV-2 infection. However, whether miR2911 inhibits the replication of porcine reproductive and respiratory syndrome virus (PRRSV) remains unknown. Hence, this study investigated the mechanisms underlying the action of miR2911 during PRRSV infection. Six targets of miR2911 within the PRRSV orf1 (Nsp2: 2459 to 2477, 1871 to 1892, 954 to 977, and 1271 to 1292; Nsp1: 274 to 296 and 822 to 841) were successfully identified by using the miRanda v1.0b software. The miR2911 target sequence was analyzed by target sequence comparison, and only individual base mutations existed in different prevalent strains, and the miR2911 target region was highly conserved among different strains. Subsequently, through the dual luciferase reporter gene assay and miR2911 overexpression assay, it was demonstrated that miR2911 significantly inhibits the replication of PRRSV by targeting regions of PRRSV Nsp1 and Nsp2. These findings offer new insights for the development of novel anti-PRRSV drugs. [ABSTRACT FROM AUTHOR]

In this paper, in order to detect 25 classes of malware, with the aim of increasing the detection accuracy, we used the pre-trained convolutional neural network of Alex Net and combined it with the perceptron neural network optimized with the Worm Shabbat algorithm. In fact, Alex Net's convolutional neural network automatically extracted 1000 feature vectors for each input image using the convolutional layer in its architecture. In the next step, we used the transfer learning method to classify the extracted features. In this thesis, we transferred the learning done by the Alex net convolutional neural network to a multi-layer perceptron neural network that was optimized using the firefly meta-heuristic algorithm for classification. In this work, we optimized the optimal weight and bias of the neural network by meta-heuristic algorithm. Finally, we were able to achieve 99.8% accuracy, which showed that the proposed method was superior in terms of accuracy compared to the compared methods. [ABSTRACT FROM AUTHOR]

Objectives: Coronary artery calcifications (CACs) indicate the presence of coronary artery disease. CAC can be found on thoracic computed tomography (CT) conducted for non-cardiac reasons. This systematic review and meta-analysis of non-gated thoracic CT aims to assess the clinical impact and prevalence of CAC. Methods: Online databases were searched for articles assessing prevalence, demographic characteristics, accuracy and prognosis of incidental CAC on non-gated thoracic CT. Meta-analysis was performed using a random effects model. Results: A total of 108 studies (113,406 patients) were included (38% female). Prevalence of CAC ranged from 2.7 to 100% (pooled prevalence 52%, 95% confidence interval [CI] 46–58%). Patients with CAC were older (pooled standardised mean difference 0.88, 95% CI 0.65–1.11, p < 0.001), and more likely to be male (pooled odds ratio [OR] 1.95, 95% CI 1.55–2.45, p < 0.001), with diabetes (pooled OR 2.63, 95% CI 1.95–3.54, p < 0.001), hypercholesterolaemia (pooled OR 2.28, 95% CI 1.33–3.93, p < 0.01) and hypertension (pooled OR 3.89, 95% CI 2.26–6.70, p < 0.001), but not higher body mass index or smoking. Non-gated CT assessment of CAC had excellent agreement with electrocardiogram-gated CT (pooled correlation coefficient 0.96, 95% CI 0.92–0.98, p < 0.001). In 51,582 patients, followed-up for 51.6 ± 27.4 months, patients with CAC had increased all cause mortality (pooled relative risk [RR] 2.13, 95% CI 1.57–2.90, p = 0.004) and major adverse cardiovascular events (pooled RR 2.91, 95% CI 2.26–3.93, p < 0.001). When CAC was present on CT, it was reported in between 18.6% and 93% of reports. Conclusion: CAC is a common, but underreported, finding on non-gated CT with important prognostic implications. Clinical relevance statement: Coronary artery calcium is an important prognostic indicator of cardiovascular disease. It can be assessed on non-gated thoracic CT and is a commonly underreported finding. This represents a significant population where there is a potential missed opportunity for lifestyle modification recommendations and preventative therapies. This study aims to highlight the importance of reporting incidental coronary artery calcium on non-gated thoracic CT. Key Points: • Coronary artery calcification is a common finding on non-gated thoracic CT and can be reliably identified compared to gated-CT. • Coronary artery calcification on thoracic CT is associated with an increased risk of all cause mortality and major adverse cardiovascsular events. • Coronary artery calcification is frequently not reported on non-gated thoracic CT. [ABSTRACT FROM AUTHOR]

This study investigated the effect of molasses addition on the fermentation quality, chemical composition, and bacterial community of seed pumpkin peel residue (SPPR) mixed with sunflower straw (SS) in microstorage feed. Molasses additions on a dry matter basis (DM) were divided into three groups: 0% control (CON), 1% (MA), and 2% (MB), and the raw materials underwent mixed microstorage for a period of 60 days. MA exhibited the highest content of dry matter (DM), the lowest content of neutral detergent fiber (NDF), acid detergent fiber (ADF), and ammoniacal nitrogen (NH3-N), as well as the lowest microbial diversity abundance and the highest relative abundance of lactobacilli (p < 0.05). MB demonstrated the highest crude protein (CP) content and acetic acid (AA) and propionic acid (PA) concentrations, with the lowest pH. In conclusion, the addition of molasses could enhance the quality of mixed microsilage feeds composed of seeded pumpkin peel pomace (SPPR) and sunflower straw (SS), with the optimal addition of molasses being 1% on a DM basis. [ABSTRACT FROM AUTHOR]

This study was conducted to evaluate the effect of two distances: close (0–10 m) and far (60 m) from the heavy traffic roadside, at three different cultivation sites (MS: Mevlanakapi–Silivrikapi, SB: Silivrikapi–Belgradkapi, and BY: Belgradkapi–Yedikule kapi) along the road line. First, the phenolic compounds, antioxidant activity, and physicochemical properties in kale and arugula vegetables were examined. Second, heavy metal concentrations in vegetables, soil, and irrigated water were investigated. In both vegetables, the highest total phenolic content was detected in samples obtained from far distance in SB site (3880.3 mg/kg) for kale and in BY site (1459.9 mg/kg) for arugula, whereas the lowest content was found at the close distance in MS site for both kale (448.5 mg/kg) and arugula (586.4 mg/kg). The antioxidant activity values [mg Trolox/kg (dw)] ranged from 366.74 to 586.10 and 2349.00 to 3757.4 for kale and from 520.00 to 945.60 and 3323.00 to 5814.70 for arugula in 2,2′‐azino‐bis (3‐ethylbenzothiazoline‐6‐sulfonic acid) and 2,2‐diphenyl‐1‐picrylhydrazyl methods, respectively. The levels of Cd and Hg in kale and arugula and Fe content in arugula exceeded FAO/WHO permissible limits, making them unsafe for human consumption. Meanwhile, the Pb content in kale and arugula and Fe content in kale were observed to be within acceptable limits set by FAO/WHO. In the irrigated water, the Pb value was below the permissible limit, whereas the Cd value was above it and no Hg and Fe were detected. In the soil samples, the Pb and Fe values were below the limit, whereas the Cd and Hg values were higher. [ABSTRACT FROM AUTHOR]

Purple-spotted bigeyes Priacanthus tayenus Richardson (Priacanthidae) and bartail flathead Platycephalus indicus (Linnaeus) (Platycephalidae) were collected from the Arabian Gulf and examined for species of Monogenoidea (Polyonchoinea) from February to December 2020. Diplectanum robustitubum Wu & Li, 2003 and an undescribed species of Platycephalotrema Kritsky & Nitta, 2019 were recovered from the gill lamellae of these hosts, respectively. Diplectanum robustitubum from Iraq was redescribed and transferred to Oliveriplectanum Domingues & Boeger, 2008 (Diplectanidae) as Oliveriplectanum robustitubum (Wu & Li, 2003) n. comb. Platycephalotrema parile n. sp. (Dactylogyridae) from Iraq and Kuwait was described and differentiated from the similar species, Haliotrema indicum Tripathi, 1959, Platycephalotrema ogawai Kritsky & Nitta, 2019, and Platycephalotrema platycephali (Yin & Sproston, 1948) Kritsky & Nitta, 2019, based primarily on the comparative morphologies of the vaginal sclerites. Haliotrema indicum was transferred to Platycephalotrema as Platycephalotrema indicum (Tripathi, 1959) n. comb. and Haliotrema swatowense Yao, Wang, Xia, & Chen, 1998 was considered a junior subjective synonym of P. indicum. The finding of O. robustitubum in the Arabian Gulf represents a new geographic record for the species. Background: The present paper represents the third installment concerning the monogenoids collected during surveys to explore their diversity on the marine and freshwater fishes of Iraq. Previous installments on the monogenoids emanating from the surveys included the dactylogyrid and gyrodactylid species parasitizing mugilid fishes. Purpose: The purpose of this paper is to further document the diversity of monogenoids infecting the fishes of Iraq. Methods: Marine fishes were necropsied for parasites, and standard procedures for collecting, mounting, drawing, and measuring of monogenoids were employed. Results: Oliveriplectanum robustitubum n. comb. (Diplectanidae) and Platycephalotrema parile n. sp. (Dactylogyridae) were collected. The occurrence of O. robustitubum in the Arabian Gulf represented a new locality record for the species. Conclusion: The recorded presence of O. robustitubum and P. parile n. sp. suggests that the diversity of monogenoids in Iraq is under estimated in the literature. [ABSTRACT FROM AUTHOR]

Cyclization of substituted thiosemicarbazones with 3‐bromo‐1,1,1‐trifluoroacetone affords new 2‐(arylidenehydrazinyl)‐4‐trifluoromethylthiazoles (3 a–m, 13 examples, 71–89 %). These compounds were synthesized in two steps and characterized using 1H‐, 13C‐NMR, FTIR spectroscopy, and HRMS. All of these compounds show potent activity against both Escherichia coli (E. coli) and Klebsiella pneumonia (K. pneumonia) bacterial strains. The compounds 2‐(2‐(1‐(4‐fluorophenyl)ethylidene)hydrazinyl)‐4(trifluoromethyl)thiazole (3 b), 2‐(2‐(2‐hydroxy‐3‐methylbenzylidene)hydrazinyl)‐4‐(trifluoromethyl)thiazole (3 c), and 2‐(2‐(3‐fluorobenzylidene)hydrazinyl)‐4‐(trifluoromethyl)thiazole (3 k) show optimal minimum inhibitory concentration (MIC) values of 16 μg/mL against E. coli and (32, 32, and 8 μg/ml) against K. pneumonia, respectively. Using a qRT‐PCR technique the gene expression of two different genes (FLU and mexB) was determined. Most of these compounds (3 a, d–j, l, m) exhibited downregulation of these genes for both types of bacteria, whereas the gene expressions were unaffected after treating 3 b, 3 c and 3 k. This means that although these compounds were able to inhibit bacterial growth, they did not target the FLU and mexB genes in both types of bacteria. These findings suggest further investigations for lead optimization could provide viable antibiotics due to their structural similarity with some commercially available antibiotics. [ABSTRACT FROM AUTHOR]

Information processing theory was applied to explore how external information processing and internal information sharing affect a firm's choice of a green strategy. Analyses of two datasets from Chinese manufacturing firms reveal that environment scanning and inter‐functional coordination are important drivers for the adoption of a green strategy. Specifically, firms that engage in extensive environment scanning tend to adopt reactive as opposed to proactive green strategies, whereas firms with effective inter‐functional coordination mechanisms tend to adopt proactive rather than reactive green strategies. An entrepreneurial orientation plays a complementary role in a firm's choice of green strategy. It increases the likelihood that a firm will adopt proactive rather than reactive green strategies, and it further strengthens the influences of environment scanning and inter‐functional coordination. Overall, these findings offer significant implications for firms regarding how and under what conditions they should adopt green strategies. [ABSTRACT FROM AUTHOR]

Southeast Asian countries have experienced a significant level of economic growth over the years but have not managed to safeguard their environmental attributes in tandem. The shadow economy is seen as one of the main factors which can significantly affect environmental quality. However, bringing the shadow economy in the picture, the institutional quality plays a critical role on environmental pollution. This study explores the effects of the shadow economy and institutions on environmental pollution in ASEAN-9 countries by applying the second-generation panel techniques using annual data. The second-generation panel unit root tests show the unique order of integration in series. The long-run cointegrating association exists among variables using Pedroni, Kao, and Westerlund panel cointegration tests. Moreover, the long-run elasticity is estimated using the ARDL approach and confirms an N-shaped EKC hypothesis in ASEAN-9 countries. Our empirical results also reveal that financial development and energy consumption significantly and positively effect environmental pollution. However, institution quality has an insignificant impact and the shadow economy significantly lessen environmental pollution. Finally, the causal interaction pathways are identified by using the D-H panel causality test. In addition, a unidirectional causality has been found from financial development to ecological footprint, shadow economy, and economic growth. Furthermore, institutional quality causes an ecological footprint. Consequently, robust regulating policies should be implemented to reduce the size of the informal economy to prevent environmental degradation. Furthermore, the ASEAN governments should finance energy infrastructure development to improve renewable production capacities with zero emissions. [ABSTRACT FROM AUTHOR]

This study investigates the impact of the agriculture and industrial production in the carbon emission function respectively using the quarterly data. The study applied the novel FARDL to identify the evidence of cointegration among the variables of the study. The robustness of the FARDL was investigated using the Bayer-Hanck combine cointegration and ARDL bounds test. Both the tests reinforce the results obtained from the FARDL. Furthermore, the long-run elasticity was identified under the framework of ARDL. The evidence of inverted N-shaped and N-shaped EKC has been identified using industry value added and agriculture production in the carbon emission functions. Financial development has a positive and significant impact on the carbon emissions. Inflation has a positive and significant effect on carbon emission in CO2-agricultural production nexus model only. Additionally, the causal results have been investigated by applying the Breitung and Candelon (Journal of Econometrics 132(2), 363–378, 2006) spectral Granger causality. It was found that agriculture and forestry affected CO2 emissions in the short run, medium run, and long run. The study recommended that the government of Pakistan should focus on the efficient and environment-friendly growing of crops and fertilizers, reducing the scarcity of food and improving the sustainable development. Moreover, the government must impose a carbon tax on the industries, which may finance renewable energy-related projects and forestation. [ABSTRACT FROM AUTHOR]

The study aims to explore a novel approach for fabricating plasmonic nanostructures to enhance the optical properties and performance of various optoelectronic devices. The research begins by employing a piezo-inkjet printing technique to deposit drops containing Ag nanoparticles (NPs) onto a glass substrate at a predefined equidistance, with the goal of obtaining arrays of Ag microdots (Ag-µdots) on the glass substrate. This process is followed by a thermal annealing treatment. The printing parameters are first optimized to achieve uniform deposition of different sizes of Ag-µdots arrays by controlling the number of Ag ink drops. Subsequently, the printed arrays undergo thermal annealing at various temperatures in air for 60 min, enabling precise and uniform control over nanoparticle formation. The printed Ag nanoparticles are characterized using field emission scanning electron microscopy and atomic force microscopy to analyze their morphological features, ensuring their suitability for plasmonic applications. UV–Vis spectrophotometry is employed to investigate the enhanced surface-plasmonic-resonance properties of the printed AgNPs. Measurements confirm that the equidistant arrays of AgNPs obtained from annealing Ag microdots exhibit enhanced light-matter interaction, leading to a surface plasmon resonance response dependent on the Ag NPs' specific surface area. These enhanced surface plasmonic resonances open avenues for developing cutting-edge optoelectronic devices that leverage the benefits of plasmonic nanostructures, thereby enabling new opportunities for future technological developments across various fields. [ABSTRACT FROM AUTHOR]

Processing extensive and diverse data in real-time is a significant challenge in the context of smart cities. Timely access to information and efficient analytics is essential for smart city services to make data-driven decisions and enhance urban living. Scheduling algorithms play a crucial role in ensuring the prompt delivery of services and efficient task completion. This paper explores various scheduling techniques, including static, dynamic, and hybrid schedulers, and compares their objectives and performance. Additionally, the study examines two prominent data processing frameworks, Hadoop and Spark, and compares their capabilities in handling big data in smart cities. With its ability to process large amounts of data quickly and efficiently, Spark has shown superiority over Hadoop in realtime data processing and performance optimization. The paper concludes by highlighting the strengths and limitations of each framework. It discusses the need for further research in optimizing scheduling techniques and exploring hybrid artificial intelligence scheduling for Spark. Overall, the findings contribute to a better understanding of data processing in real-time and provide insights for researchers and practitioners in smart cities. [ABSTRACT FROM AUTHOR]

In the year 2019 specifically, on March 11th, the coronavirus illness two thousand nineteen (COVID-19) was announced a worldwide epidemic due to its rapid spread and lack of treatment options. As a result, infected individuals must be identified and quarantined quickly to prevent the illness from spreading. The method used to test for COVID-19 is called real-timepolymerase chain reaction (RT-PCR), which has problems with having low sensitivity and taking an extended amount of time. Because chest computed tomography (CT) scans are more sensitive than RT-PCR, it follows that such scans can be employed for diagnostic purposes. This study developed a deep convolutional neural network (CNN) approach to detect COVID-19 using CT scan images. An architecture of deep learning (DL) called convolutional neural network computed tomography scans (CT-CNN) was utilized to efficiently identify COVID-19. The findings of our suggested model are highly encouraging, with an accuracy of 96.14%, an F1 score of 96.21%, and a recall of 97.53% when it comes to classifying CT scans as either infected or not infected by COVID-19. [ABSTRACT FROM AUTHOR]

In this research, we analyzed the impact that the optical characteristics of dielectric surface passivation and antireflection coating schemes have on the performance of passivated emitter and rear cell (PERC) silicon solar cells. We employed wafer ray tracer (WRT) and automate for simulation of heterostructure (AFORS‐HET) simulations, as well as experimental characterization of fabricated thin film coatings. We investigated three distinct front surface morphologies: planar surface, upright pyramids, and inverted pyramids. Using WRT, we calculated the photogeneration current densities (JG) for PERC devices with three schemes: (i) SiNx/AlOx as antireflection coating and passivation stacks on both the front and rear sides, (ii) SiNx antireflection coating on the front side and AlOx passivation layer on the rear side, and (iii) SiNx/AlOx as antireflection coating and passivation stacks on the front side with an AlOx passivation layer on the rear side. Following simulation with optimal JG, two schemes are experimentally evaluated: PECVD SiNx (70 nm) and atomic layer deposition (ALD) AlOx (15 and 25 nm). We confirmed the growth effects and optical properties using X‐ray diffraction, Raman spectroscopy, effective lifetime, and refractive index measurements. The most favorable electrical properties were obtained with SiNx (70 nm, front) and AlOx (25 nm, front and rear), where the AlOx can be deposited via ALD bifacially on a single step, minimizing processing while maintaining passivation performance. Finally, we used AFORS‐HET to simulate the maximum performance of PERC bearing such films. The results showed a Voc = 0.688 V, Jsc = 41.42 mA/cm2, FF = 84%, and packing conversion efficiency (PCE) = 24.12% as the optimal solar cell performance values. [ABSTRACT FROM AUTHOR]

Copyright of Iraqi Journal of Science is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An experimental study of the behavior of sandy soils having different densities was conducted under the action of a single impulsive load. Dry silica sands of different densities and saturated sand were tested. Different falling masses from different heights were conducted using the falling weight deflectometer to provide the single pulse energy. Variation of damping with different parameters was examined, these are; footing embedment, depth to diameter ratios, diameter of the impact plate, the applied energy and soil density (dense, medium, and loose) in addition to moisture content (dry or saturated sands). The variation of soil density leads to increase the damping ratio increases by about 20-80% when the soil density is varied from loose to dense. [ABSTRACT FROM AUTHOR]

Introduction: The Hippo pathway and its transcriptional effectors yes-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ) are targets for cancer therapy. It is important to determine if the activation of one factor compensates for the inhibition of the other. Moreover, it is unknown if YAP/TAZ-directed perturbation affects cell–cell communication of non-malignant liver cells. Materials and Methods: To investigate liver-specific phenotypes caused by YAP and TAZ inactivation, we generated mice with hepatocyte (HC) and biliary epithelial cell (BEC)-specific deletions for both factors (YAPKO, TAZKO and double knock-out (DKO)). Immunohistochemistry, single-cell sequencing, and proteomics were used to analyze liver tissues and serum. Results: The loss of BECs, liver fibrosis, and necrosis characterized livers from YAPKO and DKO mice. This phenotype was weakened in DKO tissues compared to specimens from YAPKO animals. After depletion of YAP in HCs and BECs, YAP expression was induced in non-parenchymal cells (NPCs) in a cholestasis-independent manner. YAP positivity was detected in subgroups of Kupffer cells (KCs) and endothelial cells (ECs). The secretion of pro-inflammatory chemokines and cytokines such as C-X-C motif chemokine ligand 11 (CXCL11), fms-related receptor tyrosine kinase 3 ligand (FLT3L), and soluble intercellular adhesion molecule-1 (ICAM1) was increased in the serum of YAPKO animals. YAP activation in NPCs could contribute to inflammation via TEA domain transcription factor (TEAD)-dependent transcriptional regulation of secreted factors. Conclusion: YAP inactivation in HCs and BECs causes liver damage, and concomitant TAZ deletion does not enhance but reduces this phenotype. Additionally, we present a new mechanism by which YAP contributes to cell–cell communication originating from NPCs. [ABSTRACT FROM AUTHOR]

Copyright of Gharee for Economics & Administration Sciences is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Iraqi Journal of Science is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The emergency of tyrosine kinase inhibitors has remarkably enhanced the clinical outcomes of cancer therapy, especially the use of EGFR inhibitors for non‐small cell lung cancer (NSCLC). However, acquired resistance is inevitable after 8–12 months treatment. New agents or treatments are urgently required to resolve this problem. In this study, we identified that compound ZYZ384 can selectively inhibit the growth of gefitinib‐resistant (G‐R) lung cancer cells, without affecting that of normal lung epithelial cells. ZYZ384 induced G2 arrest in G‐R NSCLC cells, decreasing the expression of Cyclin B1 and increasing the expression of P21. Meanwhile, ZYZ384 also induced apoptosis in NSCLC cells and correspondingly increased the expression of cleaved Caspase 3, 8, and 9 proteins. The expression of p‐JNK, p‐P38, and p‐ERK were also increased in H1975 NSCLC cells treated with ZYZ384. Finally, we observed that the JNK inhibitor effectively reversed the pro‐apoptotic effect of ZYZ384. In conclusion, ZYZ384 is a potential therapeutic agent to inhibit the growth of NSCLCs with EGFR mutations through activating JNK, which will help the development of related anticancer drugs. [ABSTRACT FROM AUTHOR]

This study provides a review of the literature and an overview of optical fibers, as it is considered the highest class of intelligent materials, and there are many varieties and divisions based on the requirements of the manufacturer, it will review Optic Fiber Sensors (OFS) for measuring temperature and humidity. It has been divided into four main sections: The end user, and the environment. OFS Application in Healthcare, Impact OFS Qatar, Effect of chemical and mechanical properties of OFS Effect of external temperature changes in Surface Plasmon Resonance (SPR) for OFS Due to its unique characteristics, such as small size, lack of electromagnetic interference, high sensitivity, weights that allow sensing, accuracy, and very high dynamic range, it generates a fiber-optic sensor that is easy to manufacture and operate at the lowest possible cost. In addition, the development of Dispersive Sensor Systems (DSS) and OFS has found applications in both healthcare settings and strategies in biomedical research and structural Health Care Monitoring (HCM) to enhance the adoption of fiber-based medical equipment. Optics are two areas in which OFS has yet to realize its huge potential fully. The most recent published studies (2010-2023) were our main focus except for a few cases. [ABSTRACT FROM AUTHOR]

Multimodal text summarization is a complex and challenging task in the field of natural language processing. Its objective is to use a combination of features from various modalities to create a concise yet informative summary from a given set of input data. In our research, we conducted a thorough survey of various techniques and methods used for multimodal text summarization and analyzed their implications on both research and industry. Moreover, we have developed a straightforward yet efficient model to address the challenges associated with this task. Our model has achieved state-of-the-art performance on the MMSS dataset. Additionally, we have proposed a semantic-based evaluation technique to measure the quality of the generated summaries. The effectiveness of our proposed technique has been substantiated through empirical evidence and appropriate analysis and discussion. Our goal is to make the code and models we have developed for our system publicly accessible. [ABSTRACT FROM AUTHOR]

The effects of poor air quality on people are profound. Air pollution and health issues are linked to millions of deaths. The World Health Organization (WHO) and the environmental protection agency (EPA) have produced several regulations and guidelines to control and enhance air quality. Several authors have recently suggested low-cost tools for instantly assessing air quality. the abundance of inexpensive ways to assess air quality and collect sensor data. The design and employment of remote safety monitoring for humidity, temperature, and carbon monoxide has been merged into a single tool in this work. The results findings can be observed on the actual measured instrument's organic light-emitting diode (OLED) show and the liquid crystal display (LCD) remote monitoring system. This device uses ESP32 microcontroller with long range (LoRa) wireless communication technology. The DHT22 sensor is used to detect humidity and temperature, while the MQ-7 sensor is used to monitor carbon monoxide levels. Testing measurements are calibrated using instruments that meet industrial standards (AS8700A CO meter and 4,000 NV weather tracker) used in environmental station. If the abnormalities in the recorded parameters are detected, then alert will be triggered. This instrument can help patients and workers to check their surroundings and provide remote monitoring to health service providers. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Spammer detection is to identify and block malicious activities performing users. Such users should be identified and terminated from social media to keep the social media process organic and to maintain the integrity of online social spaces. Previous research aimed to find spammers based on hybrid approaches of graph mining, posted content, and metadata, using small and manually labeled datasets. However, such hybrid approaches are unscalable, not robust, particular dataset dependent, and require numerous parameters, complex graphs, and natural language processing (NLP) resources to make decisions, which makes spammer detection impractical for real-time detection. For example, graph mining requires neighbors' information, posted content-based approaches require multiple tweets from user profiles, then NLP resources to make decisions that are not applicable in a real-time environment. To fill the gap, firstly, we propose a REal-time Metadata based Spammer detection (REMS) model based on only metadata features to identify spammers, which takes the least number of parameters and provides adequate results. REMS is a scalable and robust model that uses only 19 metadata features of Twitter users to induce 73.81% F1-Score classification accuracy using a balanced training dataset (50% spam and 50% genuine users). The 19 features are 8 original and 11 derived features from the original features of Twitter users, identified with extensive experiments and analysis. Secondly, we present the largest and most diverse dataset of published research, comprising 211 K spam users and 1 million genuine users. The diversity of the dataset can be measured as it comprises users who posted 2.1 million Tweets on seven topics (100 hashtags) from 6 different geographical locations. The REMS's superior classification performance with multiple machine and deep learning methods indicates that only metadata features have the potential to identify spammers rather than focusing on volatile posted content and complex graph structures. Dataset and REMS's codes are available on GitHub (www.github.com/mhadnanali/REMS). [ABSTRACT FROM AUTHOR]

Copyright of Journal of Economics & Administrative Sciences is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Drowsy driving is a major cause of road accidents worldwide, necessitating the development of effective drowsiness detection systems. Each year, there are more accidents and fatalities than ever before for a variety of causes. For instance, there were 22,952 fatalities and 79,545 injuries as a result of nearly 66,500 vehicle accidents in the last 10 years. In this paper, we propose a novel approach for detecting drowsiness based on behavioral cues captured by a digital camera and utilizing the multi-task cascaded convolutional neural network (MTCNN) deep learning algorithm. A high-resolution camera records visual indications like closed or open eye movement to base the technique on the driver's behavior. In order to measure a car user's weariness in the present frame of reference, eyes landmarks are evaluated, which results in the identification of a fresh constraint known as "eyes aspect ratio." A picture with a frame rate of 60 frames per second (f/s) and a resolution of 4,320 eyeballs was used. The accuracy of sleepiness detection was more than 99.9% in excellent lighting and higher than 99.8% in poor lighting, according to testing data. The current study did better in terms of sleepiness detection accuracy than a lot of earlier investigations. [ABSTRACT FROM AUTHOR]

On holidays and weekends, we can notice a large rush at shopping centres in metro areas. This is exacerbated when there are substantial discounts and deals. By applying the notion of internet of thing (IoT) for concerning all things in the grocery store, an automated smart shopping system is created. Each product within such scheme had an economical radio frequency identification (RFID) tag positioned with it. Once an item has been added to a smart cart, the information about the merchandise is quickly read by the RFID reader on the cart. The outcome is, direct invoicing is done out from shopping cart, saving clients from having to wait in a long line at the checkout. The product's expiration date is also displayed and broken products can be determined by their weight. As a result, expired and damaged products will not be taken into account when calculating the cost. Furthermore, this system gains the addition of smart shelves incorporating RFID readers which may check stock and possibly update a central server. Inventory control becomes simpler as a result. Finally, cashier stations could verify a customer's purchase. As a result, billing may be done right in the trolley, saving clients a lot of time. [ABSTRACT FROM AUTHOR]

The finance and natural resources revenue nexus play a critical role in an economy. The recent development and significant increase in academic literature regarding the resource-finance nexus are the primary motivations for conducting this study. This study aims to conduct a bibliometric analysis of 363 documents published between 1976 and 2021 collected from the Scopus database. The results have been demonstrated via graphs, tables, knowledge maps about the past trends, growth, and prospects using co-occurrence, co-authorship, and co-citation analysis via the VOSviewer tool. This study has identified prolific authors, journals, countries, academic institutions, and future pathways. The findings indicate that China has the highest share of publications (88, 24.2%), followed by Pakistan (58, 15.9%) and Turkey (37, 10.2%). The most productive academic institution is the Beijing Institute of Technology in China (13, 3.6%). This study proposes new avenues for further research concerning the resource-finance nexus, such as ecological footprint, sustainability, fiscal decentralization, green investment, energy prices, environmental quality, technological innovation, financial resource curse (especially the stock market resource curse), human capital, and renewable energy in policy development and sustainability towards the achievement of the SDGs. [ABSTRACT FROM AUTHOR]

Wastewater irrigation may reintroduce fecal pathogens to households and cause drinking water contamination. The aim of this study was to assess the effect of wastewater irrigation on the quality of drinking water among wastewater-irrigating urban farming households. Drinking water samples from 52 households of farming communities in 19 sampling sites were collected twice at PoS and PoC. The microbial quality of the water was assessed using E. coli counted by membrane filtration. Samples collected from exposed households at PoC were 100% positive for E. coli with mean E. coli at PoC increased 10× from the PoS and 3× higher compared to PoC in the unexposed households. The absence of hand washing water (ATE = 8.14), water storing (ATE = 7.75) and intermittent water supply (ATE = 6.25) were significant factors for the increased E. coli at PoC. Breaking the path of the pathogens from the farm to the house and from PoS to PoC needsintervention. [ABSTRACT FROM AUTHOR]

With the growing nature of the ecological footprint, research studies focus on exploring new determinants of environmental degradation. Moreover, the role of natural resources and energy consumption in environmental quality has gained much attention in the literature. However, tourism raises the demand for energy consumption and extraction of natural resources. This research study investigates the influence of natural resources, tourism, and renewable energy in MINT countries, using novel Cross-Sectional Auto Regressive Distributive Lag (CS-ARDL) methodological techniques and employing yearly data from 1995 to 2018. The study also applied recently developed Kónya (Econ Model 23:978–992, 2006) causality to identify the causal relationship between the variables of the heterogenous panel. The result shows that tourism, natural resources, and economic growth are positively associated with the ecological footprint in the long-run. However, renewable energy consumption negatively impacts ecological footprint in both in short-run and the long-run. Further, the study explored a bidirectional causality between economic growth and ecological footprint in MINT countries. Finally, based on the empirical results, the study recommends that the authorities in MINT countries revisit their tourism, natural resources, and economic activities policies to enhance the environmental quality and reduce the ecological footprint. [ABSTRACT FROM AUTHOR]