Synthesis, X-ray crystal structure and photophysics of butterfly shape orange and red emanating polynuclear complexes of tris(dibenzoylmethanato)Ln(III) (Ln = Sm/Eu) and exo-bidentate 4,4'-bipyridine.

Reaction of two equivalents of [Ln(dbm)3(H2O)] (Ln = Sm/Eu/Gd) with one equivalent of 4,4'-bipyridine (4,4'-bpy) led to the formation of rare polynuclear complexes of the type [Ln(dbm)3(4,4'-bpy)]n (dbm is the anion of 1,3-diphenyl-1,3-propanedione) instead of symmetrically bridged dinuclear complexes. The structure of the complexes has been established by the single crystal X-ray diffraction (SC-XRD) method and shows that the coordination sphere is composed of a LnO6N2 core (octacoordinated). Shape analysis further revealed that the geometry around Ln(III) is distorted square anti-prismatic with SHAPE value 0.738 and 25.719 for [Sm(dbm)3(4,4'-bpy)]n and [Eu(dbm)3(4,4'-bpy)]n, respectively. Photoluminescence (PL) properties of [Sm(dbm)3(4,4'-bpy)]n and [Eu(dbm)3(4,4'-bpy)]n are discussed in the solid-state and PMMA hybrid film (w/w 6%). By employing theoretical modelling in conjunction with the experimental PL data and crystal structure and an energy transfer (ET) mechanism for the sensitized PL of [Eu(dbm)3(4,4'-bpy)]n is proposed and discussed in detail. Finally, the role of each ligand in sensitized PL of [Eu(dbm)3(4,4'-bpy)]n is calculated and discussed by the chemical partitions of the radiative decay.Graphical abstract.

2D Bi2MoO6/Zn3V2O8 heterojunction photocatalyst for efficient photocatalytic reduction of CO2 to CO and CH4.

Two-dimensional (2D) "face-to-face" heterojunctions promote interfacial charge transfer and separation in composite photocatalysts. Here, we report an efficient 2D/2D step-scheme (S-scheme) photocatalyst composed of Bi2MoO6/Zn3V2O8 (BMO/ZVO), which has been designed and prepared via the self-assembly of BMO and ZVO nanoflakes. The heterojunction with an optimized composition of 30% BMO/ZVO showed extended light absorption capacity and enhanced separation efficiency of photogenerated carriers. Density functional theory (DFT) calculation on work function and charge density revealed the presence of a built-in electric field at the interface region, which should facilitate the separation of photogenerated electron-hole pairs. This work showed that it is essential to select two photocatalysts with interlaced band arrangement and to fine-tune the heterojunction interface for the preparation of S-scheme heterojunctions to achieve high photocatalytic efficiency.

SentiTAM: Sentiments centered integrated framework for mobile learning adaptability in higher education.

Online communities provide facilities to share public opinions and or sentiments on a wide range of subjects, from routine topics to vital issues of critical interest. Nowadays, many higher education institutions (HEIs) recognize the value of students' sentiments and evaluate users' concerns for the successful adaptation of mobile learning applications (MLAs). While digital learning has been extensively studied previously, little has been known about why MLA is underutilized. Therefore, this study extends the literature by proposing the SentiTAM model underlying technology acceptance model (TAM), and students' sentiments on MLA platforms. A self-administered cross-sectional survey of 350 MLA users' data was analyzed through structural equation modeling (SEM) using the AMOS package program. In addition, we have performed sentiment analysis on students' opinions gathered through Google discussion forums and Twitter. The results show that MLA use intention is strongly influenced by sentiments and self-motivation, while perceived usefulness and perceived ease of use directly influence MLA usage. To the best of our knowledge, this study is the first attempt in MLA that investigates several vital factors, including sentiments as a multi-perspective tool and motivational factors with core constructs of TAM. The findings assist developing countries make smart decisions about how to use MLA with emerging technology.

Gender differences in information and communication technology use & skills: a systematic review and meta-analysis.

Even though information and communication technology (ICT) is essential for everyday life and has gained considerable attention in education and other sectors, it also carries individual differences in its use and relevant skills. This systematic review aims to examine the gender differences in ICT use and skills for learning through technology. A comprehensive search of eight journal databases and a specific selection criterion was carried out to exclude articles that match our stated exclusion criteria. We included 42 peer-reviewed empirical publications and conference proceedings published between 2006 and 2020. For a subsample of studies, we performed a small-scale meta-analysis to quantify possible gender differences in ICT use and skills. A random-effects model uncovered a small and positive, yet not significant, effect size in favor of boys (g = 0.17, 95% CI [-0.01, 0.36]). However, this finding needs to be further backed by large-scale meta-analyses, including more study samples and a broader set of ICT use and skills measures. We highlight several concerns that should be addressed and more thoroughly in collaboration with one another to better IT skills and inspire new policies to increase the quality of ICT use. The findings from this review further suggest implications and present existing research challenges and point to future research directions.

Impact of COVID-19 on psychological distress among SME owners in Ghana: Partial least square-structural equation modeling (PLS-SEM) approach.

A critical part of the national economy is small and medium enterprises (SMEs). SME owners are vital contributors to the overall economy. Due to their limited capital and assets, they are more vulnerable. In comparison to their contribution, the value of assessing SME owner's depression, anxiety, and mental stress has been very minimal during the COVID-19 outbreak. Firms were forced to close due to lockdown, and they faced substantial business losses. Thus, this study aims to investigate SME owners' psychological distress due to business losses during this pandemic. The study used psychological parameters: Depression, Anxiety, Stress Scale-21 (DASS-21) to examine SME owners' psychological distress. A total number of 217 owners were surveyed through a judgmental sampling technique using a structured questionnaire. Data were analyzed employing partial least square-based structural equation modeling (PLS-SEM). The findings showed that DASS-21 parameters and fear of business loss affected psychological distress. Besides, fear of business loss increases psychological distress, whereas government support lessens the distress. Theoretically, this study extended the scope of DASS-21 scale and contributed to the literature of psychology. In terms of policy implications, this study provides useful information for government, policymakers, and SME owners about the effects mentioned above.

A multi-method analytical approach to predicting young adults' intention to invest in mHealth during the COVID-19 pandemic.

Mobile-based health (mHealth) systems are proving to be a popular alternative to the traditional visits to healthcare providers. They can also be useful and effective in fighting the spread of infectious diseases, such as the COVID-19 pandemic. Even though young adults are the most prevalent mHealth user group, the relevant literature has overlooked their intention to invest in and use mHealth services. This study aims to investigate the predictors that influence young adults' intention to invest in mHealth (IINmH), particularly during the COVID-19 crisis, by designing a research methodology that incorporates both the health belief model (HBM) and the expectation-confirmation model (ECM). As an expansion of the integrated HBM-ECM model, this study proposes two additional predictors: mobile Internet speed and mobile Internet cost. A multi-method analytical approach, including partial least squares structural equation modelling (PLS-SEM), fuzzy-set qualitative comparative analysis (fsQCA), and machine learning (ML), was utilised together with a sample dataset of 558 respondents. The dataset-about young adults in Bangladesh with an experience of using mHealth-was obtained through a structured questionnaire to examine the complex causal relationships of the integrated model. The findings from PLS-SEM indicate that value-for-money, mobile Internet cost, health motivation, and confirmation of services all have a substantial impact on young adults' IINmH during the COVID-19 pandemic. At the same time, the fsQCA results indicate that a combination of predictors, instead of any individual predictor, had a significant impact on predicting IINmH. Among ML methods, the XGBoost classifier outperformed other classifiers in predicting the IINmH, which was then used to perform sensitivity analysis to determine the relevance of features. We expect this multi-method analytical approach to make a significant contribution to the mHealth domain as well as the broad information systems literature.

DenseNet Convolutional Neural Networks Application for Predicting COVID-19 Using CT Image.

Recently, the destructive impact of Coronavirus 2019, commonly known as COVID-19, has affected public health and human lives. This catastrophic effect disrupted human experience by introducing an exponentially more damaging unpredictable health crisis since the Second World War (Kursumovic et al. in Anaesthesia 75: 989-992, 2020). Strong communicable characteristics of COVID-19 within human communities make the world's crisis a severe pandemic. Due to the unavailable vaccine of COVID-19 to control rather than cure, early and accurate detection of the virus can be a promising technique for tracking and preventing the infection from spreading (e.g., by isolating the patients). This situation indicates improving the auxiliary COVID-19 detection technique. Computed tomography (CT) imaging is a widely used technique for pneumonia because of its expected availability. The artificial intelligence-aided images analysis might be a promising alternative for identifying COVID-19. This paper presents a promising technique of predicting COVID-19 patients from the CT image using convolutional neural networks (CNN). The novel approach is based on the most recent modified CNN architecture (DenseNet-121) to predict COVID-19. The results outperformed 92% accuracy, with a 95% recall showing acceptable performance for the prediction of COVID-19.

Ag0/Au0 nanocluster loaded Bi2O4 photocatalyst for methyl orange dye photodegradation.

Visible-light-sensitive Ag and Au nanocluster loaded Bi2O4 (Ag-Bi2O4 and Au-Bi2O4) semiconductor photocatalysts have been synthesized. The composite materials exhibited increased photocatalytic degradation of the azo-dye pollutant, Methyl Orange (MO). In addition, Au-Bi2O4 (Au-7% wt) showed the highest MO degradation rate (0.05904 min-1) i.e. 7.69 times higher than the pristine Bi2O4 and 1.4 times higher than 1% Ag-Bi2O4. The optical properties of the composites showed that the band gaps of the composite samples 1% Ag-Bi2O4 and 7% Au-Bi2O4 were 1.96 eV and 2.09 eV, respectively. The increase in the degradation rate is attributed to the decrease of the recombination rate of photoinduced e-/h+, caused by the enhanced charge transfer between the metal nanoparticles and Bi2O4 as confirmed in the photocurrent measurements. The photocurrent measurements showed increase in the transients output by 8.25 times and 2.75 times for 1% Ag-Bi2O4 & 3% Au-Bi2O4, respectively as compared to that of the pristine Bi2O4. These features further aided the increase in the photocatalytic efficiency while retaining the original physical properties, thus showing the robustness of Bi2O4 as a photocatalyst.

Impact of "e-Learning crack-up" perception on psychological distress among college students during COVID-19 pandemic: A mediating role of "fear of academic year loss".

While literature reveals the positive perception of e-Learning, this study examined and assessed the impact of e-Learning crack-up perceptions on psychological distress among college students during COVID-19 pandemic. Kessler psychological distress scale (K10) was used to evaluate stress symptoms. This study first conducted an online focus group discussion (OFGD) with the target population to develop the scale of "e-Learning crack-up" and "fear of academic year loss". Afterward, a questionnaire was developed based on OFGD findings. An online survey was conducted amongst college students in Bangladesh using a purposive sampling technique. Results show that "e-Learning crack-up" perception has a significant positive impact on student's psychological distress, and fear of academic year loss is the crucial factor that is responsible for psychological distress during COVID-19 lockdown. This study can provide an understanding of how "e-Learning crack-up" and "Fear of academic year loss" influence college students' mental health. Theoretically, this study extends and validated the scope of Kessler's psychological distress scale with two new contexts. Practically, this study will help the government and policymakers identify the student's mental well-being and take more appropriate action to address these issues.

Methodologies for designing healthcare analytics solutions: A literature analysis.

Healthcare analytics has been a rapidly emerging research domain in recent years. In general, healthcare solution design studies focus on developing analytic solutions that enhance product, process and practice values for clinical and non-clinical decision support. The objective of this study is to explore the scope of healthcare analytics research and in particular its utilisation of design and development methodologies. Using six prominent electronic databases, qualifying articles between 2010 and mid-2018 were sourced and categorised. A total of 52 articles on healthcare analytics solutions were selected for relevant content on public healthcare. The research team scrutinised the articles, using established content analysis protocols. Analysis identified that various methodologies have been used for developing analytics solutions, such as prototyping, traditional software engineering, agile approaches and others, but despite its clear advantages, few show the use of design science. Key topic areas are also identified throughout the content analysis suggesting topical research priorities in the field.

A Methodological Approach for Predicting COVID-19 Epidemic Using EEMD-ANN Hybrid Model.

Predicting the Coronavirus epidemic, popularly known as COVID-19, that has been explored more than 200 countries and already declared as a pandemic by the World Health Organization is an invaluable task. This virus was first identified around December 2019, from central China, but later spread in the rest of the world. To ensure better healthcare service management, an accurate prediction of the uncertain gruesomeness is situational demand. In orders with limited information frameworks, demonstrating and predicting COVID-19 turns into a challenging endeavor. The primary objective of this study is to propose a hybrid model that incorporates ensemble empirical mode decomposition (EEMD) and artificial neural network (ANN) for predicting the COVID-19 epidemic. A real-time COVID-19 time series data has been used on the window periods January 22, 2020, to May 18, 2020. The time-series data first decomposed using EEMD to produce sub-signals and make original data denoised, and ANN architecture has built to train the denoised data. Finally, the result of the proposed model has compared with some traditional statistical analysis. The result of this investigation shows our proposed model outperforms compared with traditional statistical analysis. Thus the model might be promising for COVID-19 epidemic prediction. The government and healthcare provider can take preventive action by understanding the upcoming COVID-19 situation for better healthcare management.

Follow-Up Decision Support Tool for Public Healthcare: A Design Research Perspective.

OBJECTIVES: Mobile health (m-Health) technologies may provide an appropriate follow-up support service for patient groups with post-treatment conditions. While previous studies have introduced m-Health methods for patient care, a smart system that may provide follow-up communication and decision support remains limited to the management of a few specific types of diseases. This paper introduces an m-Health solution in the current climate of increased demand for electronic information exchange. METHODS: Adopting a novel design science research approach, we developed an innovative solution model for post-treatment follow-up decision support interaction for use by patients and physicians and then evaluated it by using convergent interviewing and focus group methods. RESULTS: The cloud-based solution was positively evaluated as supporting physicians and service providers in providing post-treatment follow-up services. Our framework provides a model as an artifact for extending care service systems to inform better follow-up interaction and decision-making. CONCLUSIONS: The study confirmed the perceived value and utility of the proposed Clinical Decision Support artifact indicating that it is promising and has potential to contribute and facilitate appropriate interactions and support for healthcare professionals for future follow-up operationalization. While the prototype was developed and tested in a developing country context, where the availability of doctors is limited for public healthcare, it was anticipated that the prototype would be user-friendly, easy to use, and suitable for post-treatment follow-up through mobility in remote locations.

Hypersensitivity with Inhalational Budesonide: An Under Recognised Entity.

Hypersensitivity reactions are commonly encountered with drugs such as beta lactams, sulphonamides, allopurinol etc., Corticosteroids are frequently employed in the treatment of drug induced allergic reactions. Therefore, it is highly unlikely that a corticosteroid itself may cause such a reaction as an adverse effect. We had encountered a rare case of hypersensitivity reaction with inhalational budesonide in an eight-year-old boy. The patient developed maculopapular rashes over the back, buttocks and legs accompanied with pruritus within four hours of administration of the first dose. The reaction subsided within two days on withdrawal of the drug and treatment with oral fexofenadine. Re-introduction of budesonide by the same route after a month resulted in appearance of similar reaction. Both the parents of the patient were known cases of allergic rhinitis suggesting allergic pre-disposition in the family. Causality analysis using WHO-UMC scale suggested certain association of this allergic reaction with inhaled budesonide.

Development, Validation and Application of RP-HPLC Method: Simultaneous Determination of Antihistamine and Preservatives with Paracetamol in Liquid Formulations and Human Serum.

In this article we describe development and validation of stability indicating, accurate, specific, precise and simple Ion-pairing RP-HPLC method for simultaneous determination of paracetamol and cetirizine HCl along with preservatives i.e. propylparaben, and methylparaben in pharmaceutical dosage forms of oral solution and in serum. Acetonitrile: Buffer: Sulfuric Acid (45:55:0.3 v/v/v) was the mobile phase at flow rate 1.0 mL min(-1) using a Hibar(®) Lichrosorb(®) C18 column and monitored at wavelength of 230nm. The averages of absolute and relative recoveries were found to be 99.3%, 99.5%, 99.8% and 98.7% with correlation coefficient of 0.9977, 0.9998, 0.9984, and 0.9997 for cetirizine HCl, paracetamol, methylparaben and Propylparaben respectively. The limit of quantification and limit of detection were in range of 0.3 to 2.7 ng mL(-1) and 0.1 to 0.8 ng mL(-1) respectively. Under stress conditions of acidic, basic, oxidative, and thermal degradation, maximum degradation was observed in basic and oxidative stress where a significant impact was observed while all drugs were found almost stable in the other conditions. The developed method was validated in accordance with ICH and AOAC guidelines. The proposed method was successfully applied to quantify amount of paracetamol, cetirizine HCl and two most common microbial preservatives in bulk, dosage form and physiological fluid.

Dual Wavelength RP-HPLC Method for Simultaneous Determination of Two Antispasmodic Drugs: An Application in Pharmaceutical and Human Serum.

A reverse phase stability indicating HPLC method for simultaneous determination of two antispasmodic drugs in pharmaceutical parenteral dosage forms (injectable) and in serum has been developed and validated. Mobile phase ingredients consist of Acetonitrile : buffer : sulfuric acid 0.1 M (50 : 50 : 0.3 v/v/v), at flow rate 1.0 mL/min using a Hibar µ Bondapak ODS C18 column monitored at dual wavelength of 266 nm and 205 nm for phloroglucinol and trimethylphloroglucinol, respectively. The drugs were subjected to stress conditions of hydrolysis (oxidation, base, acid, and thermal degradation). Oxidation degraded the molecule drastically while there was not so much significant effect of other stress conditions. The calibration curve was linear with a correlation coefficient of 0.9999 and 0.9992 for PG and TMP, respectively. The drug recoveries fall in the range of 98.56% and 101.24% with 10 pg/mL and 33 pg/mL limit of detection and limit of quantification for both phloroglucinol and trimethylphloroglucinol. The method was validated in accordance with ICH guidelines and was applied successfully to quantify the amount of trimethylphloroglucinol and phloroglucinol in bulk, injectable form and physiological fluid. Forced degradation studies proved the stability indicating abilities of the method.

Hypertensive encephalopathy: a rare presentation of Williams-Beuren Syndrome.

A male child of four years is reported with Williams-Beuren Syndrome (WBS). It was not recognized initially when he presented with odd facies and developmental delay since early infancy. The diagnosis was established later when he developed hypertensive encephalopathy secondary to bilateral renal artery stenosis, a congenital anomaly that must be looked for in such patients. No echographic evidence of congenital heart disease was found. Blood pressure estimation on routine physical examination of every child is emphasized. The diagnosis is mainly clinical as the definitive chromosomal studies are presently not available in Pakistan.

Hepatitis A--frequency in children with non-specific abdominal symptoms.

OBJECTIVE: To study the frequency of subclinical hepatitis 'A' in children having non-specific abdominal symptoms. DESIGN: A descriptive study. PLACE AND DURATION OF STUDY: This study was conducted at Combined Military Hospital (CMH), Peshawar from June to December 2000. SUBJECTS AND METHODS: Three hundred and sixty children of either gender, < 12 years of age, presenting with vague abdominal symptoms and no jaundice were evaluated for hepatitis. Eighty eight (24.4%) children meeting the inclusion criteria of elevated serum alanine aminotransferase (ALT), twice the upper limits of normal (90 IU/L), and normal serum bilirubin were labelled as subclinical hepatitis. RESULTS: A total of 360 children were evaluated for vague abdominal symptoms and 96 (26.7%) of them had hepatitis on laboratory profile. Eight patients developed early jaundice and were excluded from the study. Out of 88 (24.4%) cases of subclinical hepatitis, 82 (93.2%) had hepatitis-A, 03 (3.4%) had hepatitis-B, while no causative agent was found in 03 (3.4%) children. The common presenting symptoms were abdominal pain/discomfort, loss of appetite, nausea, vomiting, malaise, fatigue and fever. Hepatomegaly and splenomegaly was documented in 56% and 43% cases respectively. A history of exposure to a patient with hepatitis was present in 14/88 (15.9%) cases whereas no child was vaccinated against HAV. Serum ALT level declined to normal limits within 4 weeks for 77/88 (87.5%) cases and within 6 weeks for 84/88 (95.4%). All cases recovered spontaneously with out any complication. CONCLUSION: Hepatitis-A was rampant in children presenting with vague abdominal symptoms in our series.

Abdominal epilepsy.

Abdominal epilepsy (AE) is a rather uncommon clinical entity in children that might create diagnostic confusion especially when it lacks the typical manifestations of an epileptic seizure. We report the case of a young boy having apparently unexplained episodes of paroxysmal abdominal symptoms with no other suggestion of an underlying epileptic disorder. The case also explains how the clinical presentation can be misleading unless a high index of suspicion is maintained to reach the ultimate diagnosis.

Correlation of quantitative risk results for high hazard processes.

A quantitative risk analysis was conducted to evaluate the design of the VX neutralization subsystem and related support facilities of the U.S. Army Newport Chemical Agent Disposal Facility. Three major incidents including agent release, personnel injury, and system loss were studied using fault tree analysis methodology. Each incident was assigned a risk assessment code based on the severity level and probability of occurrence of the incident. Safety mitigations or design changes were recommended to bring the "undesired" risk level (typical agent release events) to be "acceptable with controls" or "acceptable."