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Spoken dialogue systems (SDS) heavily rely on dialogue state tracking (DST) for success. However, providing sufficient computational power for training proves challenging, given that DST involves tracking states from both user and system utterances. While machine learning approaches have improved DST, they have notable limitations. These approaches often overlook unseen slot values during training and use two separate modules to extract, generate, or match slot values, leading to high time and resource consumption. Moreover, learning and deducing relevant values for related slots remain understudied challenges. To address these gaps, this paper introduces UTMGAT-a Unified Transformer with Memory Encoder and Graph Attention Networks (GAT) for Multidomain DST. UTMGAT employs a BERT tokenizer to construct user utterances and a candidate sets vocabulary, reducing the need for constant retraining when dealing with unseen values. It utilizes a single transformer to gather dialogue context for slots and generate slot values, enhancing prediction accuracy while reducing memory and computation time. UTMGAT incorporates an embedding layer aggregator to filter out unnecessary values, identify required nodes for GAT, and establish relationships among relevant values associated with related slots. This approach simplifies graph representation and diminishes required computation power. The input to the GAT maintains equal size with batch sizes, generated through padding. Finally, we have experimentally evaluated our model against several models including LLM approaches over four popular datasets with our approach outperforming all competing models except two approaches on one dataset. [ABSTRACT FROM AUTHOR]

We evaluate the structural, optoelectronic, and mechanical characteristics of the novel Rb2CaSnCl6 and Rb2CaSnI6 through density functional theory within the WIEN2K framework. The formation energies and volume optimization provide evidence for the structural stability of these compounds. The optimized lattice constants for Rb2CaSnCl6 and Rb2CaSnI6 are found to be 11.21 Å and 12.45 Å, respectively while their respective formation energies are calculated as − 2.5 Ry and − 1.6 Ry. Similarly, the grounds state energies are calculated − 31,184.32 Ry and − 111,074.60 Ry. We find that Rb2CaSnCl6 is an insulator with a bandgap energy of 3.50 eV when the modified Becke-Johnson (mBJ) approximation is applied and that Rb2CaSnI6 is directly semiconducting with a wide bandgap energy of 2.70 eV. Evaluations of mechanical stability show that both materials are mechanically stable and their constituent atoms are bound together by ionic interactions, indicated by the positive value of Cauchy's pressure: 46. 32 and 21.93 for Rb2CaSnCl6 and Rb2CaSnI6, respectivley. Nevertheless, our investigation showed that Rb2CaSnI6 behaves as a ductile material while Rb2CaSnCl6 is brittle. We also investigate a variety of optical characteristics such as dielectric function, refraction, reflectivity, energy loss function, and extinction coefficient. The static dielectric function was found to be 2.9 and 4.3 for Rb2CaSnCl6 and Rb2CaSnI6, respectively. Rb2CaSnI6 exhibited greater optical conductivity, indicative of it being a better metallic than the Rb2CaSnCl6. The optical investigation suggests that these materials have a great deal of promise for cutting-edge optoelectronic applications, especially in the ultraviolet (UV) spectrum due to their large electronic band gap. These results offer a solid basis for future research into these intriguing materials by experimentalists. [ABSTRACT FROM AUTHOR]

Currently, China has entered a stage of high-quality development due to innovations and improving capabilities of the cities. Being the most valuable urban brand, civilized cities are a symbol of the city's comprehensive ability. Their construction blueprint coincides with the realization of high-quality development. Therefore, exploring the relationship between civilized cities' construction and urban innovative development is a matter of great significance for improving national high-quality development policies and strengthening civilized cities' construction. This paper examined the data from 242 cities from 2003 to 2016, applying the multi-period difference-in-difference model to test the established hypothesis. The results indicate that the pilot policy for civilized cities has effectively improved the level of urban innovation. The results also validate that the title of the civilized city effectively promotes the urban innovation level by promoting the agglomeration of human capital, improving the level of informatization, and increasing investment in scientific as well as technological innovation. At the same time, there are significant differences in policy effectiveness for cities with different urban levels and geographical locations. The construction of future civilized cities should focus on attracting and cultivating high-quality talents, strengthening investment and support in information infrastructure construction, and scientific and technological innovation research and development to adapt to local conditions and resultantly achieve the improvement in urban innovation level. [ABSTRACT FROM AUTHOR]

This key article seeks to empirically examine the impact of geopolitical risk, economic policy uncertainty (EPU), natural resources, and renewable energy on a country's ecological footprint, a proxy for environmental sustainability on a national scale. We conducted a quantitative study using the cross-sectional autoregressive distributive lag, augmented mean group, and common correlated effect mean group estimation models, as well as a few tests such as the CD test, Westerlund's co-integration, and CIPS and CADF unit root tests, beginning in January 2000 and ending in January 2021, to determine the data's reliability. The findings indicate that while GPR and renewable energy sources lessen the ecological footprint (EF), EPU and the use of non-renewable energy enhance the EF. The study's scope is narrowed to the BRICS nations, but its implications for expanding existing knowledge and shaping policy are enormous. The results can aid decision-makers in preparing for the possibility of unexpected events causing harm to the economy. The reliability of the evidence can be strengthened by employing more stringent research methods. This study's dimensions reflect the current research paradigm. The research has policy implications for achieving sustainable development goals in emerging economies. [ABSTRACT FROM AUTHOR]

Nanoparticle-based therapies are emerging as a pivotal frontier in biomedical research, showing their potential in combating infections and facilitating wound recovery. Herein, selenium-tellurium dopped copper oxide nanoparticles (SeTe-CuO NPs) with dual photodynamic and photothermal properties were synthesized, presenting an efficient strategy for combating bacterial infections. In vitro evaluations revealed robust antibacterial activity of SeTe-CuO NPs, achieving up to 99% eradication of bacteria and significant biofilm inhibition upon near-infrared (NIR) irradiation. Moreover, in vivo studies demonstrated accelerated wound closure upon treatment with NIR-activated SeTe-CuO NPs, demonstrating their efficacy in promoting wound healing. Furthermore, SeTe-CuO NPs exhibited rapid bacterial clearance within wounds, offering a promising solution for wound care. Overall, this versatile platform holds great promise for combating multidrug-resistant bacteria and advancing therapeutic interventions in wound management. Metal-based nanoparticles are promising agents used for photothermal and photodynamic therapy, and as an efficient strategy against multi-drug resistant bacteria. Here, the authors report a one-pot synthesis of SeTe-CuO nanoparticles for such dual-mode therapy, achieving near-infrared activated eradication of bacteria and inhibition of biofilm formation in vitro, as well as promoting wound healing in vivo. [ABSTRACT FROM AUTHOR]

Drought, a highly detrimental natural disaster, poses significant threats to both human populations, wildlife, and vegetation. Traditional methods of monitoring soil moisture levels rely on ground-based measurements from meteorological stations. However, these stations often lack comprehensive coverage in certain agricultural areas, necessitating the use of alternative methods such as satellite remote sensing. This technique provides a reliable means of measuring soil moisture, a critical factor in effective agricultural management. This paper investigates variations in soil moisture and drought using data from the Cyclone Global Navigation Satellite System (CYGNSS) and the Soil Moisture Active and Passive (SMAP) system. To evaluate the accuracy of these data products, we compared both datasets with the Global Land Data Assimilation System (GLDAS) NOAH model from 2018 to 2019. Our findings reveal a strong correlation between the datasets and the model, with Pearson correlation coefficients (r) and Root Mean Square Errors (RMSE) of approximately r = 0.98 and RMSE = 0.03 for SMAP, and r = 0.97 and RMSE = 0.02 for CYGNSS, respectively. We further compared these measurement datasets with drought indicators such as the Standardized Precipitation Index over three months (SPI3), the Normalized Difference Vegetation Index (NDVI), and Total Water Storage (TWS). The correlation coefficients between SMAP and the three indicators (NDVI, SPI3, and TWS) were 0.93, 0.84, and 0.047, respectively, while the coefficients between CYGNSS and the same indicators were 0.86, 0.78, and 0.56, respectively. All the variables also exhibited significant p-values. Despite minor differences, the results demonstrate excellent agreement. Our findings underscore the sensitivity of space-based sensors to drought conditions, highlighting their effectiveness as tools for detecting and monitoring drought (e.g. agricultural drought), particularly in the short term. [ABSTRACT FROM AUTHOR]

The tomography results reveal not only distinct velocity structures in different tectonic zones but can also provide valuable insights into the geological features of the area. This study presents the results of 2D Rayleigh wave tomographic maps obtained in NE Iran. For this purpose, we used the recorded waveforms of more than 500 earthquakes with M > 4 that occurred between January 2000 and October 2020 at 165 stations. The calculated tomographic maps cover a period range of 3 to 36 s, providing the 3D VS model to analyze crustal structure at depths ranging from 2 to 30 km. At shorter periods, the tomographic maps are primarily influenced by sediment thickness, with the presence of thick sediment layers (~ 10 km) responsible for the observed low VS anomalies (< 3.1 km/s) in the study area. At longer periods, the tomographic maps highlight the structural characteristics of the middle-lower crustal layers and, somewhere, the depth variations of the Moho discontinuity. The VS model also confirms the correlation between tectonic fractures and known faults in the study area as boundaries of seismotectonic provinces. Moreover, a distinct area was observed beneath the Binalud foreland, which we interpreted as a suture zone, as suggested by previous studies. The reliability of the resolved anomalies was supported through a series of tests, including checkerboard and earthquake location uncertainties. These tests demonstrated the robustness of the results and provided confidence in the accuracy of the findings. [ABSTRACT FROM AUTHOR]

The current study investigated wild plant resources and health risk assessment along with northern Pakistan's mafic and ultramafic regions. Ethnobotanical data was collected through field visits and semi-structured questionnaire surveys conducted from local inhabitants and healers. Six potentially toxic elements (PTEs) such as lead (Pb), cadmium (Cd), nickel (Ni), chromium (Cr), manganese (Mn), and zinc (Zn) were extracted with acids and analyzed using atomic absorption spectrophotometer (AAS, Perkin Elmer-7000) in nine selected wild medicinal plants. Contamination factor (CF), pollution load index (PLI), estimated daily intake (EDI), target hazard quotient (THQ), and hazard index (HI) were used to determine the health risk assessment of the studied medicinal plants. The results showed that the selected medicinal plants were used for the treatments of cough, joint swelling, cardiovascular disorders, toothaches, diabetes, and skin pimples by the local inhabitants due to their low-cost and easy accessibility. The concentrations of Pb (3.4–53 mg kg–1), Cd (0.03–0.39 mg kg–1), Ni (17.5–82 mg kg–1), Cr (29–315 mg kg–1), Mn (20–142 mg kg–1), and Zn (7.4–64 mg kg–1) in the studied medicinal plants were found above the safe limits (except Zn) set by WHO/FAO/USEPA (1984/2010). The Pb contamination factor was significantly (p < 0.05) higher in A. modesta (7.84) and D. viscosa (6.81), and Cd contamination factor was significantly higher in C. officinalis (26.67), followed by A. modesta (8.0) mg kg–1. Based on PTE concentrations, the studied plants are considered not suitable for human consumption purposes. Pollution load index values for A. modesta, A. barbadensis, A. caudatus, A. indica, C. procera (2.93), D. viscosa (2.79), and C. officinalis (2.83), R. hastatus (3.12), and Z. armatum were observed as 1.00, 2.80, 2.29, 2.29, 2.93, 2.79, 2.83, 3.12 and 2.19, respectively. Hazard index values were in order of R. hastatus (1.32 × 10–1) ˃ C. procera (1.21 × 10–1) ˃ D. viscosa (1.10 × 10–1) ˃ A. caudatus (9.11 × 10–2) ˃ A. barbadensis (8.66 × 10–2) ˃ Z. armatum (7.99 × 10–2) ˃ A. indica (6.87 × 10–2) ˃ A. modesta (5.6 × 10–2) ˃ C. officinalis (5.42 × 10–2). The health risk index values suggested that consumption of these plants individually or in combination would cause severe health problems in the consumers. Pearson's correlation results showed a significant correlation (p ≤ 0.001) between Zn and Mn in the studied medicinal plants. The current study suggests that wild medicinal plants should be adequately addressed for PTEs and other carcinogenic pollutants before their uses in the study area. Open dumping of mining waste should be banned and eco-friendly technology like organic amendments application should be used to mitigate PTEs in the study area. [ABSTRACT FROM AUTHOR]

The present study's aim is to find the prevalence of two of the common indicators of mental health - depression and anxiety – and any correlation with socio-demographic indicators in the Pakistani population during the lockdown from 5 May to 25 July 2020. A cross-sectional survey was conducted using an online questionnaire sent to volunteer participants. A total of 1047 participants over 18 were recruited through convenience sampling. The survey targeted depression and anxiety levels, which were measured using a 14 item self-reporting Hospital Anxiety and Depression Scale (HADS). Out of the total sample population (N=354), 39.9% suffered from depression and 57.7% from anxiety. Binary logistical regressions indicated significant predictive associations of gender (OR=1.410), education (OR=9.311), residence (OR=0.370), household income (OR=0.579), previous psychiatric problems (OR=1.671), and previous psychiatric medication (OR=2.641). These were the key factors e associated with a significant increase in depression. Increases in anxiety levels were significantly linked to gender (OR=2.427), residence (OR=0.619), previous psychiatric problems (OR=1.166), and previous psychiatric medication (OR=7.330). These results suggest depression and anxiety were prevalent among the Pakistani population during the lockdown. Along with other measures to contain the spread of COVID-19, citizens' mental health needs the Pakistani government's urgent attention as well as that of mental health experts. Further large-scale, such as healthcare practitioners, should be undertaken to identify other mental health indicators that need to be monitored. [ABSTRACT FROM AUTHOR]

Asthma is a chronic inflammatory disease triggered by allergic reactions in the bronchia. These reactions lead to swelling of mucous membranes, hypersecretion of mucus, and bronchoconstriction, resulting in a restricted opening of the lung airway. Allergic pulmonary inflammation and airway hyperresponsiveness are induced when Th2 cytokines, such as interleukin (IL)-4 and IL-13, bind to their cognate receptors on lung epithelial cells. Specifically, IL-13 stimulates inflammation through a multi-subunit receptor, mainly the alpha chain of the IL-4 receptor (IL-4Rα), which also plays a role in IL-4 signaling. In this study, we employed a lung epithelial cell-targeting siRNA carrier composed of a rabies virus glycoprotein-derived small peptide coupled with cationic nona-arginine and trileucine before cysteine peptide (RVG9R3LC). This carrier was complexed with siRNA, enabling targeted delivery of therapeutic siRNA to IL-4Rα (siIL4Rα) expressed in lung epithelial cells within an asthma model in vivo. Our approach demonstrated efficient gene knockdown in cultured lung epithelial cells and in vivo. Furthermore, two administrations of therapeutic siIL4Rα protected the ovalbumin-sensitized and challenged asthma mouse model from airway inflammation and excessive mucus secretion. Our findings suggest that the peptide-siRNA carrier system presents a promising therapeutic approach for respiratory inflammation. [ABSTRACT FROM AUTHOR]

Query expansion (QE) has been studied extensively in traditional search settings due to its efficacy in improving retrieval performance. However, the level of performance achieved in the traditional settings has not been reported in the literature on the federated search. Some of the possible reasons include the lack of complete information regarding the corpus statistics of the databases and their diverse content. Nevertheless, several studies have experimented with different QE approaches and reported mixed results. This paper extends the findings of these publications by studying the impact of using a different source for selecting terms to be used in QE on the federated search. Specifically, the expansion terms are extracted from uniform resource locators (URLs) of the documents returned by each database. The retrieval experiments with TREC 2013 FedWeb dataset demonstrates that the expanded query using the proposed approach performs better in many instances than the unexpanded query. [ABSTRACT FROM AUTHOR]

Extracted cane juice from Saccharum officinarum L. was employed as a major source of sugar acting as major input in various food industries. Current genotypes are yielding lower quantities of sugar posing a major challenge for sugarcane producers and plant biotechnologists. Discovery of novel sucrose isomerases (SI) derived from multiple microbial sources enlightened a great hope for molecular food scientists to introduce slowly digestible sucrose isomers not only to make up deficiencies of reduced sugar recovery but also produce healthful sugars. Modified Synthetic Sucrose Isomerase Gene 1 (SySIG1) cloned in plant expression vector pCAMBIA1301 under the combined influence of two promoters (CmYMV and Zm-Ubi) to produce high sugar yielding sugarcane genotypes. The expression of the transgene was terminated finally by nopaline synthase gene (Nos). The genetic construct pCEMBIA1301-1 was archestrated with transgene SySIGI having size 2180 bp integrated to plant expression vector. The vacoule targeted sequence (VTS) as signal peptide was also added in the vector so that the product could be directed and stored in the vacoular region. Transgene expression regulation was increased with enhancers to clone highly expressed gene construct. Transgene incorporation into genome was confirmed by PCR amplifications and dot blot analysis. Stem expression profile via qPCR indicated multiple fold magnification in transgene expression which was translated gorgeously into increased sugar recovery percentages in various tested transgenic lines comparative to control counterparts. Further quantifications by HPLC showed much high isomaltulose production in transgenic sugarcane lines as compared to control non-transgenic sugarcane lines. Different categories of sugarcane lines on the basis of sugar yields were developed and classified as super sugar lines (SSLs), elite sugar lines (ESLs), and good sugar lines (GSLs). Stem-based transgene expression and leaf-based expression quantifications were originated from real-time PCR. [ABSTRACT FROM AUTHOR]

Juglans regia is an important perennial crop cultivated for its high-quality nuts and wood. It is generally believed that J. regia survived and expanded in almost completely isolated stands in Asia after the last glaciation. Humans subsequently dispersed J. regia through cultural expansion and trade. We evaluated the spatial genetic structure and genetic diversity of 2,929 J. regia samples from 150 populations using 14 Simple Sequence Repeats (SSRs) markers. Our study revealed that regions with the highest genetic diversity included Southern Asia, Western Asia, Western Europe, and China, as illustrated using a Geostatistical Inverse Distance Weighting (IDW) interpolation of observed heterozygosity (HO), expected (HE) heterozygosity (HE), percentage of polymorphic loci (PPL), the total number of alleles (NA), and Allelic richness (RS) in Arc Geographic Information System (ArcGIS). The ecological Niche Model (ENM) showed J. regia had a high probability of association with Central Asian and Eastern Asian habitats. Population genetic structure, phylogeny, and Principal Coordinate Analysis (PCoA) identified three genetic groups corresponding to three geographic sources. Turkish and Georgian populations served as a bridge between Asian populations and Europe populations. We suggest that J. regia evolved in central Asian mountain ranges ~ 65 million years ago (Mya) and dispersed across Eurasia during climate shifts (~ 65 to 3Mya). The population contracted into multiple refugia during the Last Glacial Maximum. The current distribution of J. regia across Eurasia was shaped by the cumulative effects of contraction or expansion of different refugia and human exploitation after LGM. [ABSTRACT FROM AUTHOR]

Antibiotic-resistant bacterial strains and the consequent surge in infections caused by them have become major public health concerns. Silver nanoparticles (AgNPs) exhibit antibacterial properties and have wide applications in biomedical sciences. In this study, AgNPs were synthesized in the presence of antibiotics: Ceftazidime (Cft), Cefotaxime (Cef), Ceftriaxone (Cfx), and Cefepime (Cpm), along with the extract of Mentha longifolia. Mentha longifolia-based AgNPs were kept as the control for all experiments. The associated metabolites, structural properties, surface charges, and antibacterial activity of the AgNPs were also evaluated. Overall, a blue-shift of SPR peaks was observed for control AgNPs (λmax = 421 nm, 422 nm, 426 nm, and 406 nm for Cft-AgNPs, Cef-AgNPs, Cfx-AgNPs, and Cpm-AgNPs, respectively), compared to the control (λmax = 438 nm). Fourier-transform infrared spectroscopy showed that antibiotic-based AgNPs had distinct peaks that corresponded to the respective antibiotics, which were not observed in the control. XRD analysis showed that there were observed changes in crystallinity in antibiotic-based AgNPs compared to the control. TEM images revealed that all samples had spherical nanoparticles with different sizes and distributions compared to the control. The Zeta potential for extract-based AgNPs was − 33.6 mV, compared to -19.6 mV for Cft-AgNPs, -2 mV for Cef-AgNPs, -21.1 mV for Cfx-AgNPs, and − 24.2 mV for Cpm-AgNPs. The increase in the PDI value for antibiotic-based AgNPs also showed a highly polydisperse distribution. However, the antibiotic-AgNPs conjugates showed significantly higher activity against pathogenic bacteria. The addition of antibiotics to AgNPs brought significant changes in structural properties and antibacterial activities. [ABSTRACT FROM AUTHOR]

The role of formulating a well-defined query in the retrieval of relevant search results is well-known to the users of an Information Retrieval (IR) system. Researchers have experimented with various approaches to formulating a search query, e.g., using topic fields in different combinations, reducing verbose queries, and query expansion to name a few. These approaches have been tested in various domain-specific IR applications. However, to the best of our knowledge, no survey or review article reviews the current state of query formulation in the domain of book search. This paper fills this gap in the literature by reviewing research publications on query formulation, published during 2007–2022. These publications have been selected through a rigorous search and selection strategy, where the findings have been summarized using a well-defined theoretical framework. It identifies the current trends and presents a cross-comparison for identifying the best-performing methods. The paper has implications for researchers working in IR in general and book search in specific. [ABSTRACT FROM AUTHOR]

The manuscript describes coherent control of the anomalous optical drag in a three-levels atomic medium driven by probe and control fields. Generally, anomalous optical drag occurs in a medium with a negative group index and faster group velocity. The condition for anomalous optical drag is that the group index is less than the inverse of the refractive index. The group index is negative and its maximum negative value is measured to − 10,000. The study investigates the effect of probe field detuning, decay rates, and Rabi frequency of the control field on the anomalous optical drag. The results show that a maximum of − 100 μm linear anomalous photon drag is achieved with a control field in a medium moving with a velocity of 10 m/s. The maximum linear anomalous photon drag is found to be sensitive to probe detuning and decay rate, with a minimum value of − 0.8 μm. The modified results of this study could be useful for spatial modes imaging coding and sensing technology. The ability to control and manipulate the anomalous optical drag can enable the design of novel optical devices and systems with enhanced performance. [ABSTRACT FROM AUTHOR]

The Internet Disorder Scale–Short Form (IDS9-SF) is a validated instrument assessing internet disorder which modified the internet gaming disorder criteria proposed in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). However, the relationships between the nine items in the IDS9-SF are rarely investigated. The present study used network analysis to investigate the features of the IDS9-SF among three populations in Bangladesh, Iran, and Pakistan. Data were collected (N = 1901; 957 [50.3%] females; 666 [35.0%] Pakistani, 533 [28.1%] Bangladesh, and 702 [36.9%] Iranians) using an online survey platform (e.g., Google Forms). All the participants completed the IDS9-SF. The central-stability-coefficients of the nine IDS9-SF items were 0.71, 0.89, 0.96, 0.98, 0.98, 1.00, 0.67, 0.79, and 0.91, respectively. The node centrality was stable and interpretable in the network. The Network Comparison Test (NCT) showed that the network structure had no significant differences among Pakistani, Bangladeshi, and Iranian participants (p-values = 0.172 to 0.371). Researchers may also use the IDS9-SF to estimate underlying internet addiction for their target participants and further explore and investigate the phenomenon related to internet addiction. [ABSTRACT FROM AUTHOR]

The loss of or impairment in vision makes it challenging for blind and visually impaired people (BVIP) to navigate easily in their surroundings. Several solutions were proposed to address this challenge and assist BVIP in navigation by exploiting existing technologies. However, their reliance on pre-installed infrastructure and costly dedicated hardware made them less practical. As an alternative, pedestrian dead reckoning techniques were proposed. However, the slow walking pace of BVIP, the required contact with un-intended obstacles, and the false recognition of activities increase error accumulation, making these techniques less applicable. Therefore, solutions are needed to accurately recognize the walking patterns of BVIP so that efficient navigation solutions can be developed. This article fills this research gap by extending traditional white cane with smartphone sensors. Specifically, a smartphone is used with a conventional white cane to collect data through its sensors on a time-based data window. For smooth recording, a revolving tire is attached at the bottom of the white cane. The collected data is processed by employing the computational resources of the smartphone using our designed app, which identifies the user's walking patterns such as walking, stairs up/down, sit/stand, and collision. As a case study, these activities were classified using Naïve Bayes, Random Forests, J48, Decision Table, and LibSVM. Among these, Random Forests gave a higher accuracy. These results suggest that the proposed solution is more practical in designing navigation applications for BVIP and may yield better accuracy if tested with more advanced classifiers. [ABSTRACT FROM AUTHOR]

The Fear of COVID-19 Scale (FCV-19S) assesses the fear of the novel coronavirus disease 2019 (COVID-19) and has been translated and validated into over 20 languages. The present study conducted confirmatory factor analysis (CFA) and item response theory (IRT) analyses on the FCV-19S among a sample of 937 Pakistani adults (mean [SD] age of 25.83 [11.80] years; 537 [57.3%] females). The CFA and IRT confirmed the unidimensionality of the FCV-19S. The Likert-type scale used in the FCV-19S was supported by the proper threshold orderings. Additionally, no DIF contrast had an absolute value larger than 0.5 regarding the participants' characteristics of gender, age, living status, and education in the IRT findings. The FCV-19S was found to be valid and reliable with strong psychometric properties among the Pakistani adult population. [ABSTRACT FROM AUTHOR]

The present study uses observation-based gridded air temperature and precipitation datasets to investigate the spatiotemporal changes in meteorological drought from 1981 to 2020 in South Asia (SA). The drought characteristics i.e., duration, area, frequency, intensity, and severity are calculated using Run theory and the Standardized Precipitation Evapotranspiration Index (SPEI) on annual and seasonal timescales. SA is divided into four homogeneous subregions using the k-means clustering algorithm, while the trends were estimated using Sen's Slope estimator and modified Mann-Kendall (MMK) test. A state-of-the-art Bayesian Dynamic Linear (BDL) model was employed to assess the sub-regional drought variability and their possible links with large-scale atmospheric drivers such as the Indian Ocean Dipole (IOD), El Niño Southern Oscillation (ENSO), and the Pacific Decadal Oscillation (PDO). It is found that the SA winter season experienced a significant drying long-term trend, especially southwestern and northeastern parts of SA. Drought durations show dipolar patterns with longer drought duration in the southwestern compared to the northern parts of SA. Notably, arid and semi-arid regions have shown significant drying trends in terms of their area, frequency, and severity, implying that meteorological droughts are relatively more severe in those regions. Similarly, the relationship varies over time between drought variability and climate drivers. In particular, the IOD has an impact on drought episodes over southwest SA relative to the northern parts and is mostly affected by the Sea surface temperature (SST) variability. The study results contribute to a better understanding of the meteorological drought characteristics over SA, which is important for disaster risk managers and policymakers to mitigate drought impacts. [ABSTRACT FROM AUTHOR]

The Mentha species of family Lamiaceae are famous for their flavor and are commercially used in many food products worldwide. They are widely used to cure digestive problems as well as a natural source of antioxidants and antimicrobials. In this report, the essential oils (EOs) of five Mentha species, namely Mentha citrata, Mentha x piperita, Mentha pulegium, Mentha spicata, and Mentha suaveolens were extracted and their chemical diversity was investigated through gas chromatography-mass spectroscopy (GC–MS). The differential doses (5, 10, and 15 µl) of EOs were tested for antimicrobial potential against two gram-positive bacteria (Staphylococcus aureus and Bacillus subtilis), five gram-negative bacteria (Escherichia coli, Pseudomonas aeroginosa, Salmonella typhi, Proteus mirabilis and Klebsiella pneumoniae) and a fungal strain (Candida albicans). The GC–MS results revealed the major components in the EOs were Carvone, Linalool, Hotrienol, Menthol, Isopulegone, Furanone, Piperitone, and Thymol. Moreover, the higher dose (15 µl) of EOs of M. citrata inhibited the growth of S. typhi and C. albicans (35.8 ± 2.4 and 35.2 ± 2.5 mm), M. x piperita inhibited E. coli, B. subtilis, and C. albicans (28.5 ± 3.5, 26.1 ± 2.1, and 25.4 ± 1.1 mm), M. pulegium inhibited K. pneumoniae, B. subtilis, and C. albicans (26.8 ± 1.8, 24.2 ± 2.2, and 25.3 ± 0.9 mm), M. spicata significantly inhibited S. typhi and B. subtilis (35.7 ± 2.7 and 36.3 ± 2.1 mm), and M. suaveolens inhibited K. pneumoniae, C. albicans, and S. typhi (30.8 ± 1.9, 26.9 ± 1.1, and 20.1 ± 0.8 mm) respectively. This study concluded that the EOs of M. citrata was effective against S. typhi and C. albicans. The M. x piperita exhibited strong activities against E. coli, B. subtilis, and C. albicans. Furthermore, the M. pulegium strongly inhibited the growth of K. pneumoniae and C. albicans. The EO of M. spicata was more potent against S. typhi and B. subtilis, while the M. suaveolens was comparatively more effective against S. typhi, K. pneumoniae, and C. albicans. These EOs offer a natural source of antimicrobial agents with high commercial values and social acceptance and could be scale up by food and pharmaceutical industries to control pathogenic diseases. [ABSTRACT FROM AUTHOR]

Social Book Search (SBS) studies how the Social Web impacts book retrieval. This impact is studied in two steps. In this first step, called the baseline run, the search index having bibliographic descriptions or professional metadata and user-generated content or social metadata is searched against the search queries and ranked using a retrieval model. In the second step, called re-ranking, the baseline search results are re-ordered using social metadata to see if the search relevance improves. However, this improvement in the search relevance can only be justified if the baseline run is made stronger by considering the contribution of the query, index, and retrieval model. Although the existing studies well-explored the role of query formulation and document representation, only a few considered the contribution of the retrieval models. Also, they experimented with a few retrieval models. This article fills this gap in the literature. It identifies the best retrieval model in the SBS context by experimenting with twenty-five retrieval models using the Terrier IR platform on the Amazon/LibraryThing dataset holding topic sets, relevance judgments, and a book corpus of 2.8 million records. The findings suggest that these retrieval models behave differently with changes in query and document representation. DirichletLM and InL2 are the best-performing retrieval models for a majority of the retrieval runs. The previous best-performing SBS studies would have produced better results if they had tested multiple retrieval models in selecting baseline runs. The findings confirm that the retrieval model plays a vital role in developing stronger baseline runs. [ABSTRACT FROM AUTHOR]

The exponential outbreak of news articles makes it troublesome for the readers to find, select and read the most relevant ones and alleviate the resulting information and cognitive overload problems. In recent years, various deep learning (DL) models were developed to recommend personalized quality news articles and support readers. Yet, no survey paper highlights the strengths, weaknesses, and trends of news recommendation models employing DL methods. This survey fills this gap in the literature by identifying the current state of DL-based news recommendation methods. Specifically, it covers (1) the classification of DL-based news recommendation models, (2) their performance comparison, and (3) the essential issues faced by these models. It discusses the most commonly used datasets, evaluation methods, and implications for researchers working in this area. [ABSTRACT FROM AUTHOR]

The intensified quest for efficient materials drives us to study the alkali (Na)-based niobate (NaNbO3) and tantalate (NaTaO3) perovskites while exploiting the first-principles approach based on density functional theory, coded within WIEN2K. While using the Birch Murnaghan fit, we find these materials to be stable structurally. Similarly, the ab-initio molecular dynamics simulations (AIMD) at room temperature reveals that the compounds exhibit no structural distortion and are stable at room temperature. By using the recommended modified Becke–Johnson potential, we determine the electronic characteristics of the present materials providing insight into their nature: they are revealed to be indirect semiconductors with the calculated bandgaps of 2.5 and 3.8 eV for NaNbO3 and NaTaO3, respectively. We also determine the total and partial density of states for both materials and the results obtained for the bandgap energies of these materials are consistent with those determined by the band structure. We find that both compounds exhibit transparency to the striking photon at low energy and demonstrate absorption and optical conduction in the UV region. The elastic study shows that these compounds are mechanically stable, whereas NaNbO3 exhibits stronger ability to withstand compressive as well as shear stresses and resists change in shape while NaTaO3 demonstrates weaker ability to resist change in volume. We also find that none of the compound is perfectly isotropic and NaNbO3 and NaTaO3 are ductile and brittle in nature, respectively. By studying the optical properties of these materials, we infer that they are promising candidates for applications in optoelectronic devices. We believe that this report will invoke the experimental studies for further investigation. [ABSTRACT FROM AUTHOR]

Gas, which is trapped in either solid or liquid pockets, results in foam formation. Foam formation is common in many industries, i.e., in detergents, food and beverage, cosmetics, and fire-fighting. Foam formation in excess causes biotechnology fermentation instabilities, including material loss and the danger of contaminating the fermentation and the environment. Many foam-controlling measures have been reported, including thermal, enzymatic, mechanical, ultrasound pretreatments, steam explosion, reducing digester mixing, and surface sludge spray. Using antifoaming agents for foam control in fermentation is the most common method, sometimes supported by mechanical foam breakers. However, antifoam can be costly and can complicate product purification. Indeed, effective foam control can significantly impact the economics of the whole process. This mini-review summarizes some unconventional foam destruction techniques, including their various challenges. [ABSTRACT FROM AUTHOR]

Fabricated multifunctional sensors have the following structure: the flexible transparent conductive sheet as the first electrode, the orange dye as sensitive material and the CNT film as second electrode deposited on the flexible rubber substrate by rubbing-in technology. The samples (ITO/OD/CNT/Rubber) were investigated under the effects of displacement, pressure, temperature, relative humidity and infrared irradiation (IR). It was observed that under the effect of 25-µm displacement, the resistance and the impedances at 100 Hz, 1 kHz and 10 kHz decreased by 1.62, 1.34, 1.26 and 1.23 times, accordingly. Under the effect of pressure up to 47 gf/cm2, the resistance and impedances at 100 Hz, 1 kHz and 10 kHz decreased, respectively, by 1.35, 1.34, 1.32 and 1.29 times. The illumination of the samples by infrared irradiations of intensity up to 4830 W/m2 brings to decrease the resistance and impedances up to 5 and 2 times, accordingly. By investigating temperature dependences of the impedances, it was found that the temperature coefficients of the impedances for frequencies of 100 Hz, 1 kHz and 10 kHz were equal to 0.037, 0.036 and 0.035 °C−1, respectively. The change in impedance/resistance with variation in the displacement, pressure, temperature and infrared irradiation may be explained by percolation theory. Investigation of humidity effect on the impedances of sensor showed that the decreased impedances (on increasing humidity) can be estimated by the humidity coefficients of impedance, which were equal to 0.020, 0.0190 and 0.014 RH−1 for the frequencies of 100 Hz, 1 kHz and 10 kHz. The investigation of frequency response showed that the samples are high-pass filter with cutoff frequency of 100 Hz. The fabricated devices may be implemented for various industrial and environmental applications. [ABSTRACT FROM AUTHOR]

Dear Editor, The emergence and development of the COVID-19 pandemic is having a toll on the mental health of the general population, and healthcare workers around the world, often manifested in depression, fear, stress, trauma, and anxiety (Ahorsu et al. [1]; Mamun and Ullah [10]; Lee et al, [9]). We searched PubMed using the keywords "COVID-19" or "SARS-CoV-2" or "Coronavirus disease" and "Fear Scale" or "FCV-19S" or "Fear of COVID-19 Scale" till 30 August 2020. The Fear of COVID-19 Scale (FCV-19S) is a 7-item scale that assesses the severity of COVID-19-related fear (Ahorsu et al. [1]). [Extracted from the article]

The manufacturing industry consumes a considerable amount of energy every year, which poses a major challenge to resource consumption and environment problem. To overcome these difficulties, it is necessary to understand the machine tools' power characteristics. The current research aims to investigate the energy consumption of the machine tool and to establish a cutting power model for ball-end milling process. First, a cutting power theoretical model for a ball-end milling cutter was established based on the infinitesimal cutting force. Secondly, a series of experiments were conducted to reveal and validate the mathematical function of spindle power and feed power. Finally, slotting milling experiments were conducted, and a cutting power empirical model was proposed by analyzing the correlation between cutting forces and cutting power. The results showed that the spindle power, feed power, and cutting power could be exactly predicted by the proposed method. Furthermore, the Z-axis's feed power characteristic was revealed that the gravity made the Z-axis's motor transform to the generator when Z-axis moved in the downward direction. For cutting power model, the theoretical model and empirical model had the same predictive accuracy, while the empirical model had a simpler form and could be easier applied. The proposed power investigation method provided technical support for the research of the machine tools' energy consumption characteristics. [ABSTRACT FROM AUTHOR]

The massive number of research articles on the Web makes it troublesome for researchers to identify related works that could meet their preferences and interests. Consequently, various network representation learning-based models have been proposed to produce citation recommendations. Nevertheless, these models do not exploit semantic relations and contextual information between the objects of bibliographic papers' networks, which can result in inadequate citation recommendations. Moreover, existing citation recommendation methods face problems such as lack of personalization, cold-start, and network sparsity. To mitigate such problems and produce individualized citation recommendations, we propose a heterogeneous network embedding model that jointly learns node representations by exploiting semantics corresponding to the author, time, context, field of study, citations, and topics. Compared to baseline models, the results produced by the proposed model over the DBLP datasets prove 10% and 12% improvement on mean average precision (MAP) and normalized discounted cumulative gain (nDCG@10) metrics, respectively. Also, the effectiveness of our model is analyzed on the cold-start papers and network sparsity problems, where it gains 12% and 9% better MAP and recall@10 scores, respectively. [ABSTRACT FROM AUTHOR]

China has witnessed significant growth in trade through vide range trade liberalization strategies and urbanization has also been entered in advanced stage. Based on these dynamics, how much energy consumption of both renewable and none renewable account for energy consumption in whole system is a point of higher attention for the researchers. To understand this salient emerging debatable concern, we investigate the impact of trade openness and urbanization effect on renewable and non-renewable energy consumption in China for the period 1990–2018. We apply the quantile regression technique for the analysis; our results show that trade significantly increases the non-renewable energy consumption in all quintiles while partially increasing renewable energy consumption. This shows that trade activities in production and export commodities heavily rely on non-renewable energy inputs instead of renewable energy inputs. Urbanization affects non-renewable energy consumption only in three quintiles, while its effect is insignificant in most of the quintiles. Similarly, urbanization does not affect renewable energy consumption as in almost all quantiles the coefficients are statistically insignificant. This implies that urbanization is one of the determinants of energy consumption in China. The empirical findings of this study suggest some policy recommendations; first, the government needs to implement certain regulations while expanding trade to minimize the negative effect of non-renewable energy consumption; besides government should provide incentives to industrial units and traders for using renewable energy which may help to attain long term sustainable development goals. The government should also put certain limitations on population moving from rural to urban destinations. [ABSTRACT FROM AUTHOR]

The United States of America (USA) has a culturally and ethnically diverse population. Various gender and racial minorities in the healthcare system are not represented adequately when compared to their ratios in the general population. This study reviewed the gender and racial distribution and its temporal trends among fellows in Consultation-Liaison Psychiatry (CLP) within the USA. A retrospective analysis was performed to evaluate the gender and race of fellows in CLP fellowship programs in the USA from 2007 to 2019. Data was retrieved from publicly available Accreditation Council for Graduate Medical Education (ACGME) Resource Books. According to ACGME data, races were categorized as White (non-Hispanic), Asian/Pacific Islander, Hispanic, Black (non-Hispanic), Native American/Alaskan, Others, and Unknown. Gender was self-reported as male, female, and not reported. Among fellows in CLP, the White (Non-Hispanic) race remained the most represented and increased by 7.3% from 2011 to 2019, with an 18.6% increase in relative change. In contrast, the Asian/Pacific Islander, African American/Black (Non-Hispanic), and others decreased by 6.2%, 4.0%, and 4.6%, respectively. Gender distribution trends showed an increase in male representation with a relative increase of 14.7% and an absolute increase of 5.5%. Similar trends were seen in female representation with a relative and absolute increase of 5.2% and 2.8%, respectively. However, women remained the most represented throughout the period. Considering the ongoing globalization & rapidly evolving US demographics, it is crucial to analyze the gender and racial disparities within psychiatry. Racial concordance and a diversified culturally competent physician workforce is imperative for the effective delivery of mental health services. [ABSTRACT FROM AUTHOR]

Objective: The United States (USA) is a culturally and ethnically diverse country with an estimated 5.6 to 8 million elderly population living with psychiatric and substance use disorders and a dwindling geriatric psychiatry workforce. In this study, we explored the gender and racial trends in USA geriatrics psychiatry fellowship programs from 2007–20, and forecasted the 2030 geriatric psychiatry workforce to identify the gaps and provide recommendations. Method: This retrospective analysis of the Accreditation Council for Graduate Medical Education (ACGME) data included trainees in geriatric psychiatry fellowship programs in the USA from 2007–20. Races were classified as White (Non-Hispanic), Asian/Pacific Islander, Hispanic, Black (Non-Hispanic), Native American/Alaskan, Others, and Unknown. Gender was categorized as Male, Female, and Not Reported. Results: Amongst the geriatric psychiatry fellowship trainees, there was an overall decrease in the representation of all races from 2011–20. There was a relative decrease of 16%, 8.6% and 2.3% for White (Non-Hispanic), Asian/Pacific Islander, and Black (Non-Hispanics) respectively whereas the Hispanic and Native American/Alaskan trainees remained unchanged. Women relatively increased 28.4% from 2007–20 while men relatively decreased 27.1%. Our projections suggest that without changes in the current health professional recruitment trends and the shortage of geriatric psychiatrists will persist with a shortfall of 1,080 (9.7%) by 2030. Conclusion: There are critical gaps in racial and gender representation in geriatric psychiatry fellowship programs in the USA. An inclusive workforce is required to address diverse communities and bridge gaps in physician workforce gender and racial disparities. [ABSTRACT FROM AUTHOR]

The United States (US) has a culturally diverse population. However, the percentage of underrepresented minorities (URMs) and women in healthcare does not fully reflect their current and future demographics. Our objective was to explore and forecast the gender and racial trends in the US addiction psychiatry fellowship programs. A retrospective analysis was performed using data from Accreditation Council for Graduate Medical Education (ACGME) Resource Books which encompassed US addiction psychiatry fellows from 2007 to 2020. Simple linear and multiple regression were used to predict the 2030 addiction psychiatry workforce. White (Non-Hispanic) and Asian/Pacific Islander had a relative change of -2.8% and -26.1% from 2011 to 2020, respectively. Black (non-Hispanic) had a relative change of + 5.2%. Hispanic and Native American/Alaskan had no relative change during this time. From 2007 to 2020, women's representation relatively decreased by 10.9%. Statistically, these dynamic trends of the addiction psychiatry workforce will continue to exist in 2030. Women and URM addiction psychiatrists play an effective role in addressing substance use disorders (SUD). Unfortunately, the current gender and racial disparities in addiction psychiatry will exist in the future. Understanding the continued gender and racial bias in addiction psychiatry fellowships and devising appropriate recommendations can help mitigate the existing disparities. [ABSTRACT FROM AUTHOR]

Coronavirus disease (COVID-19) is a novel pandemic disease and was first identified in Wuhan, China, at the end of 2019. It has affected the whole world in a short period of time and declared as a sixth global health emergency as it disturbed routine of human being and all life activities. This study presents a review focusing on ongoing pandemic as a disaster that provided a way of opportunity for change towards potentially positive and negative impacts on the environment. The observed positive aspect for environment in the context of short time impacts are improvement in air quality due to reduction in greenhouse gas emission, noise, nitrogen dioxide, and particulate matter < = 2.5 μm experienced in countries including India, Pakistan, China, USA, Italy, France, Spain, and other European countries. The observed negative impacts include organic waste generation and its mismanagement due to lockdown, non-functioning of waste recycling plants, municipal activities, and medical waste of materials used for personnel care protection. The study is explored through image data available from European Space Agency and National Aeronautical Space Agency to assess positive and negative impacts on environment. With available environmental observations, this review aims to assess impacts of current pandemic on environment focusing on some major Asian, European countries and USA. The present approach enabled determining changes with positive and negative effects on the environment. The observed assessments provide spatiotemporal based support for theoretical perspective that pandemic disasters can provide a way of opportunity for positive change in environment with slight negative environmental change. [ABSTRACT FROM AUTHOR]

In this paper, a novel scheme for radio resource allocation is proposed for downlink transmission in a clustered cellular network that employs orthogonal frequency division multiple access. The proposed resource allocation scheme is based on maximizing the cluster throughput, with emphasis on improving individual performance, especially those at the cell edges. The users within the cell are segregated into edge users, having strong coupling with the neighboring cells, and the center users close to the cell sites. In order to improve the data rate for the edge users, cell clustering with the joint transmission, forming virtual MIMO systems is introduced. The throughput for the center users is improved through classical opportunistic channel scheduling with interference avoidance. The frequency resources are pre-assigned to edge and center users, and the optimization problem for throughput maximization is applied separately to each so as to improve the fairness between them without affecting the overall spectrum efficiency. The simulations have been performed under various frequency reuse patterns and resource distributions within the cell–sectors to assess the performance of the proposed solution. Results indicate that clustering ensures tremendous gains in throughput per resource and spectral efficiency of edge users, while it significantly reduces scheduling complexity of the system. [ABSTRACT FROM AUTHOR]

This project purposes to develop chitosan and sodium alginate–based hydrogel membranes loaded with curcumin through microwave-based physical cross-linking technique and its evaluation for wound healing potential. For the purpose, curcumin-loaded chitosan and sodium alginate membranes were developed using microwave at fixed frequency of 2450 MHz, power 350 W for 60 s, and tested for their physicochemical attributes like swelling, erosion, surface morphology, drug content, and in vitro drug release. The membranes were also subjected to tensile strength and vibrational and thermal analysis followed by testing in vivo on animals. The results indicated that microwave treatment significantly enhanced the swelling ability, reduced the erosion, and ensured smooth surface texture with optimal drug content. The drug was released in a slow fashion releasing total of 41 ± 4.2% within 24-h period with a higher tensile strength of 16.4 ± 5.3 Mpa. The vibrational analysis results revealed significant fluidization of hydrophilic domains and defluidization of hydrophobic domains which translated into a significant rise in the melting temperature and corresponding enthalpy which were found to be 285.2 ± 3.2 °C and 4.89 ± 1.4 J/g. The in vivo testing revealed higher percent re-epithelialization (75 ± 2.3%) within 14 days of the treatment application in comparison to only gauze and other treatments applied, with higher extent of collagen deposition having well-defined epidermis and stratum corneum formation. The microwave-treated chitosan-sodium alginate hydrogel membranes loaded with curcumin may prove to be another alternative to treat skin injuries. [ABSTRACT FROM AUTHOR]

The World Health Organization (WHO) defines mental health as the state of wellbeing in which an individual realizes their capabilities to combat with normal life stressors and work competencies in contributing to the belonged community, which is underpinned by six psychological elements comprising (i) self-acceptance, (ii) meaning in life, (iii) autonomy, (iv) healthy relationships with others, (v) environmental mastery, and (vi) personal growth (Mukhtar [18]). Aggregated COVID-19 suicide incidences in India: Fear of COVID-19 infection is the prominent causative factor. These mental health and emotional issues are now among the foremost public health concerns throughout the world because of the novel coronavirus 2019 (COVID-19) pandemic, due to fear of infection or fear of death from the virus. First COVID-19 suicide case in Bangladesh due to fear of COVID-19 and xenophobia: possible suicide prevention strategies. [Extracted from the article]

Understanding the prevailing changes in temperature and relative humidity (RH) is of crucial importance for climate risk reduction and management. Despite their importance, trends and temperature variability associated with other climate variables over the Southeast Asian nation of Myanmar are not fully understood. This study investigates the annual and seasonal variations in air temperature and RH, as well as dew point temperature and their relationships, based on 47 meteorological stations located around Myanmar from 2001 to 2019. The results indicate that an increasing trend in air temperature was observed in the central, western, deltaic and southern regions of Myanmar. In contrast, air temperatures trended downward in the eastern (southern Shan state), northern (Hkakabo Razi Mountain) and western (Chin state) parts of the country. RH exhibited a significant increase in the northern region and a decrease in the central dry zone. A lower RH always accompanied high temperatures. Dew points increased in the deltaic and southern parts of Myanmar, as opposed to in the eastern (south Shan state) and western (Chin state) parts of the country. Moreover, in comparison to the daily RH variability, the observed daily temperature variability had a relatively stronger influence on Myanmar’s climate, whereas dew points typically remained stationary for a day. The associated linkage between the RH and the dew point temperature was significantly linear, with a correlation coefficient (R2) of 0.65. The annual (seasonal) correlation of air temperature and dew point was highly correlated in the winter, where R2 was measured at 0.71 (0.75). During the rainy season, however, the annual (seasonal) R2 was measured at only 0.30 (0.04). However, the air temperature and RH showed a weak positive correlation of 0.20 (0.26) in summer (winter) and a weak positive correlation in the rainy season (0.01). This study’s findings are important for enhancing seasonal forecasts of extreme heat and can aid policy-makers in formulating better climate change adaptation plans. [ABSTRACT FROM AUTHOR]

The financial system development has got considerable attention due to its association with the environment of the country. To address the apprehension of the researchers about the effect of the determinants of the financial system on the environmental quality of high-income developed countries, we analyze the data of twenty developed countries with sound and strong financial systems for the period 2001 to 2018. We consider both banking development and stock market development as the main key determinants of the financial system. We employ numerous modern-day penal data estimation techniques, namely Dynamic Penal GMM in both linear and non-linear form, Common Correlated Effect Mean Group (CCEMG), and Dynamic Fixed Effect for capturing the issues of heterogeneity, endogeneity, and cross-sectional dependence. Our results show that banking development substantiates the environmental quality in high-income developed countries. The positive gesture of the banking development on environmental quality could be the reason for the established environmentally friendly policies in the developed part of the world. Hence, we conclude that banking development in high-income developed countries significantly reduces the emissions of dangerous gases, which resultantly enhances the environmental quality. The study reveals an insignificant and tenuous impact of the market development on the environmental quality that might be due to the adoption of cleaner technologies by firms in the developed world that are environmentally friendly. The results of our long-term estimations also predict the significant effect of banking development and an insignificant effect of the market development on environmental quality. In addition, our results also demonstrate an inverted U-shaped relationship of the determinants of the financial system and environmental quality. More institutional and legal initiatives must be made for a more robust banking and stock market development framework by the policy makers with a view to substantiating the quality of the environment to a more sustainable level in the developed world. [ABSTRACT FROM AUTHOR]

The machining-induced material's microstructure evolution, which can be determined from the thermo-mechanical loading history, dramatically influences the end products' service performances. The present research investigates the microstructural and mechanical property changes of the machined surface layer of Ti-6Al-4V alloy by utilizing some advanced characterization techniques. First, high-speed milling experiments of Ti-6Al-4V alloy under various cutting parameters were carried out. The effect of machining parameters on cutting forces and workpiece temperature was investigated. Secondly, based on the cutting forces and workpiece temperature, the machined surface layer's microstructural and phase composition changes were observed using optical and scanning electron microscopy and X-ray diffraction analysis, respectively. The experimental results indicate that the machined surface and sub-surface exhibit a transformed layer (white layer) and a localized plastic deformation, respectively. The intensity of the transformed layer increases with both the cutting speed and feed rate. In contrast, the plastic deformation shows a slight variation among cutting speeds but increases gradually with the feed rates. The phase transformation analysis reveals that the conversion of β-Ti into α-Ti is not time dependent and can coincide. Finally, the nano-indentation technique was employed to measure the hardness from the machined surface down to the bulk region. The improved machined surface hardness is mainly attributed to grain refinement, deformation twinning, and the material phase proportions. The current research can provide a better understanding of the machined surface integrity in high-speed milling of Ti-6Al-4V alloy. [ABSTRACT FROM AUTHOR]

Banking industries are blamed to be among the major factors that affect global climate change both directly and indirectly. The green banking concept has emerged in the last decade to trigger the adverse impact the banks put on a healthy environment. However, research regarding the adoption of green banking practices in developing economies, especially in Pakistan, is scarce. While environment friendly businesses are promoted by the government including in the banking industry. Green banking practices not only adopted by the business operations but also to practice it at policy-making level. It also encourages green project financing to ascertain environmental efficiency. Based on SRI theory, this study investigates the relationship between green banking practices and their direct and indirect impact on environmental performance. Structural equation modelling approach has been adopted to test the relationships of variables of the study. The impact of the green practices has been recognized much greater and influential in promoting green environment regarding policy-making and investments in green projects. Results reveal that there is a significant influence of policy, daily operations, and investments on the adoption of green banking practices. Interested parties can adopt the study proposed framework to access and identify the factors which can promote justified level of green banking practices in the country. Moreover, this study may help in providing rich updated literature in green banking to speed up future research in the same area. [ABSTRACT FROM AUTHOR]

The present research aims to inspect the bidirectional association among healthcare expenditures, carbon dioxide (CO2) emissions, and human development index (HDI). For this purpose, we employ a balanced panel data set of 33 OECD countries for the period 2006–2016. A newly developed econometric approach known as panel vector autoregression based on the generalized method of moments estimations is employed to test this relationship. The key empirical findings reveal that (1) all of the three main variables namely healthcare expenditures, CO2 emissions, and HDI exhibit a causal relationship, (2) there exists bidirectional causality between healthcare expenditures and CO2 emissions which suggests that CO2 emissions significantly escalate the healthcare expenditures in OECD countries. Likewise, healthcare investments also increase emissions due to higher use of energy, (3) positive bidirectional causation between healthcare expenditures and HDI entails that investments in health infrastructure lead to improvement in the overall quality of living in these countries. Moreover, a higher HDI reinforces the governments to increase their healthcare spending, and (4) there is a unidirectional negative causality between CO2 emissions and HDI which implies that carbon emissions significantly deteriorate human health and wellness in these countries. Based on these empirical outcomes, the policy prescriptions are discussed for the relevant authorities to curtail emission and enhance the quality of living of the masses. [ABSTRACT FROM AUTHOR]

Recommendation systems assist web users with personalized suggestions based on past preferences for products, or items including documents, books, movies, and research papers. The plethora and variety of research papers on the Web and digital libraries make it challenging for researchers to find relevant publications to their scholarly interests. To cope with this inevitable challenge, various models and algorithms have been proposed to assist researchers with personalized citation recommendations. Nevertheless, so far, no research study has exploited the validity and suitability of evaluations conducted for these models to find the most promising among them. This study investigates and examines the existing citation recommendation algorithms based on the following criteria: evaluation methods adopted, comparative baselines employed, the complexity of the proposed algorithm, reproducibility of the experimental results, and consistency and universality of the evaluation methods. Besides this, our study presents a generic architecture and process of a typical citation recommendation system and provides a brief overview of information filtering methods used in the existing models. The findings of the study have implications for researchers and practitioners working on research paper recommendation and related areas. [ABSTRACT FROM AUTHOR]