In Bangladesh, a number of screening tests for asymptomatic bacteriuria in pregnancy are in practice. The objective of this study was to assess the validity and cost-effectiveness of these screening tests. A total of 600 apparently healthy pregnant mothers were included in this study. The validity of the screening tests was calculated against the urine culture as 'gold standard'. Incremental cost-effective ratio between the screening test methods and the least costly method (microscopic urine analysis) was calculated. Bacterial count/oil-immersion field in Gram-stained smear of urine was the most sensitive (91.7%) and specific (97.2%). Incremental cost per additional positive cases of bacterial count, leukocyte esterase and combination of leukocyte esterase and nitrite were US$3, US$25 and US$23, respectively. Gram staining may be the alternative approach to traditional routine urinalysis for the screening of asymptomatic bacteriuria during pregnancy in clinical practice in Bangladesh, as well as other developing countries.
In this paper, a novel coronavirus infection system with a fuzzy fractional differential equation defined in Caputo's sense is developed. By using the fuzzy Laplace method coupled with Adomian decomposition transform, numerical results are obtained for better understanding of the dynamical structures of the physical behavior of COVID-19. Such behavior on the general properties of RNA in COVID-19 is also investigated for the governing model. The results demonstrate the efficiency of the proposed approach to address the uncertainty condition in the pandemic situation.
Cloud computing is new technology that has considerably changed human life at different aspect over the last decade. Especially after the COVID-19 pandemic, almost all life activity shifted into cloud base. Cloud computing is a utility where different hardware and software resources are accessed on pay per user ground base. Most of these resources are available in virtualized form and virtual machine (VM) is one of the main elements of visualization.VM used in data center for distribution of resource and application according to benefactor demand. Cloud data center faces different issue in respect of performance and efficiency for improvement of these issues different approaches are used. Virtual machine play important role for improvement of data center performance therefore different approach are used for improvement of virtual machine efficiency (i-e) load balancing of resource and task. For the improvement of this section different parameter of VM improve like makespan, quality of service, energy, data accuracy and network utilization. Improvement of different parameter in VM directly improve the performance of cloud computing. Therefore, we conducting this review paper that we can discuss about various improvements that took place in VM from 2015 to 20,201. This review paper also contain information about various parameter of cloud computing and final section of paper present the role of machine learning algorithm in VM as well load balancing approach along with the future direction of VM in cloud data center.
It has been suggested that a birthweight limit of 2.5 kg should not be regarded as valid for all populations as the cut-off point of low-weight births because of demographic, genetic and environmental differences. Countries often choose alternative cut-off values for low birthweight for clinical purposes. Bangladesh also needs to choose a convenient cut-off value for low birthweight. A total of 770 live singleton full-term normal newborns were included in this study by stratified sampling; birthweight was measured using the Detecto-type baby weight machine. Newborns were followed up to the end of their first week of life. For data collection a pretested structured questionnaire and an Apgar Score estimating checklist were used. Chi-square test was applied to assess the association of different birthweight strata and neonatal health outcomes. Multiple logistic regression analyses were carried out to identify the independent effects of different levels of birthweight on early neonatal health. The neonates having birthweight < or = 2 kg had a significantly higher risk of early neonatal mortality and morbidity than the higher level birthweight group. Birth asphyxia was the commonest cause of early neonatal mortality and morbidity. Borderline birthweight (>2 to <2.5 kg) neonates experienced the same mortality and morbidity rates as the normal birthweight neonates during their early neonatal life. Birthweight < or = 2 kg may be one of the criteria for admission to a neonatal intensive care unit whereas more than 2 kg may not require admission unless otherwise necessary.
The present study aims to identify the impact of corporate social responsibility on patients' intention to revisit the healthcare industry. Furthermore, mediating the role of patient satisfaction and patient loyalty along with serial mediation through corporate social responsibility = > patient satisfaction = > patient loyalty = > intention to revisit was also tested. The present study is quantitative in nature, while the data for the study was collected using purposive sampling from 321 patients working in eight hospitals in Rawalpindi and Islamabad, Pakistan. For the data analysis, statistical package for the social sciences (SPSS) and structural equation modeling through the partial least square approach (smart-PLS v 3.3.9) were employed. The study results show that corporate social responsibility forms a significantly positive relationship with patient satisfaction, patient loyalty, and patient intention to revisit. Study findings confirmed the mediating role of patient satisfaction and patient loyalty. Furthermore, serial mediation through patient satisfaction and patient loyalty was also confirmed. In the current competitive environment, understanding the direct and indirect effects of CSR activities on patient satisfaction, patient loyalty, and intentions to revisit is of the utmost importance for hospitals. These activities provide hospitals with the opportunity to take certain actions to improve patient satisfaction, and these actions increase their loyalty, which in turn encourages their intention to revisit.
The objective of this paper is to investigate the impact of sustainability reporting (SR) quality on the corporate financial performance (CFP) of initial public offering (IPO) in Malaysia. This research applies the OLS and WLS regressions through content analysis of annual reports. The data was collected from Datastream, where 131 IPOs listed companies on Bursa Malaysia between 2007 and 2017. The findings indicate a positive and negative association between SR and its components with CFP. It is found that there is a negative and significant association between the SR characteristics of employees and products with CFP. However, it was discovered that the societal and environmental components have a significantly positive association with CFP. This finding shows that SR practices might be seen as an attempt to enhance IPO performance. The findings can facilitate financial institutions and regulatory agencies in driving responsibility on the part of companies regarding SR issues. The firms should involve SR practices in their SR decisions. Thus, this study emphasises the significance of combining social and organisational activities.
Globally, the rising concentration of anthropogenic greenhouse gases emission in the atmosphere is extremely detrimental to the environment. The high concentration among all greenhouse gases is carbon dioxide emission. Therefore, this study explores the linkages between energy consumption, trade openness, globalization, urbanization, and carbon dioxide emission for Malaysia over the spans from 1978 to 2018. ARDL bound testing model was employed to investigate involvement in the elevation of carbon dioxide emissions in the economy. The study illustrates that a 1% growth in energy consumption, trade openness, and urbanization will deteriorate the environment by 0.18%, 0.03%, and 2.51% respectively. Further, variance decomposition analysis predicts that all the determinants in the study have significantly caused carbon dioxide emission in Malaysia. The paper presents scientific support for further studies and argues for the use of innovation shocks as a policy instrument for a prosperous future by formulating more successful environmental policies.
Pathophysiological changes in diabetes like hyperglycemia, oxidative stress, insulin resistance and compensatory hyperinsulinemia predispose cells to malignant transformation and damage DNA repair mechanism. This study was designed to explore the potential synergistic toxic effects of anti-diabetic drug (Metformin), and an analgesic drug (Celecoxib) at cellular level. MTT assay run on Vero cell line revealed that the combinations of Metformin and Celecoxib augment the anti-proliferative effects, whereas Single cell gel electrophoresis spotlighted that Metformin produce non-significant DNA damage with the threshold concentration of 400μg/ml in peripheral blood mononuclear cells (lymphocytes and monocytes), while Celecoxib produced significant (P<0.05) DNA damage (class III comets) above the concentration of 75μg/ml, however the DNA damage or DNA tail protrusions by combinations of both drugs were less than what was observed with Celecoxib alone. Metformin or Celecoxib did not appear mutagenic against any mutant strains (TA 100 and TA 98) but their combination exhibited slight mutagenicity at much higher concentration. The results obtained at concentrations higher than the therapeutic level of drugs and reflect that Metformin in combination with Celecoxib synergistically inhibits the cell proliferation in a concentration dependent pattern. Since, this increase in cytotoxicity did not confer an increase in DNA damage; this combination could be adopted to inhibit the growth of malignant cell without producing any genotoxic or mutagenic effects at cellular level.
Electrocardiogram (ECG) signals play a vital role in diagnosing and monitoring patients suffering from various cardiovascular diseases (CVDs). This research aims to develop a robust algorithm that can accurately classify the electrocardiogram signal even in the presence of environmental noise. A one-dimensional convolutional neural network (CNN) with two convolutional layers, two down-sampling layers, and a fully connected layer is proposed in this work. The same 1D data was transformed into two-dimensional (2D) images to improve the model's classification accuracy. Then, we applied the 2D CNN model consisting of input and output layers, three 2D-convolutional layers, three down-sampling layers, and a fully connected layer. The classification accuracy of 97.38% and 99.02% is achieved with the proposed 1D and 2D model when tested on the publicly available Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database. Both proposed 1D and 2D CNN models outperformed the corresponding state-of-the-art classification algorithms for the same data, which validates the proposed models' effectiveness.
Lung cancer (LC) is one of the leading causes of cancer-related death. As one of the key features of tumor microenvironment, hypoxia conditions are associated with poor prognosis in LC patients. Upregulation of hypoxic-induced factor-1α (HIF-1α) leads to the activation of various factors that contribute to the increased drug resistance, proliferation, and migration of tumor cells. Apurinic/apyrimidinic endonuclease-1 (APEX1) is a multi-functional protein that regulates several transcription factors, including HIF-1α, that contribute to tumor growth, oxidative stress responses, and DNA damage. In this study, we explored the mechanisms underlying cell responses to hypoxia and modulation of APEX1, which regulate HIF-1α and downstream pathways. We found that hypoxia-induced APEX1/HIF-1α pathways regulate several key cellular functions, including reactive oxygen species (ROS) production, carbonic anhydrase 9 (CA9)-mediated intracellular pH, migration, and angiogenesis. Cephalomannine (CPM), a natural compound, exerted inhibitory effects in hypoxic LC cells via the inhibition of APEX1/HIF-1α interaction in vitro and in vivo. CPM can significantly inhibit cell viability, ROS production, intracellular pH, and migration in hypoxic LC cells as well as angiogenesis of HUVECs under hypoxia through the inhibition of APEX1/HIF-1α interaction. Taken together, CPM could be considered as a promising compound for LC treatment.
The aim of this study is to provide a holistic review of the fight against COVID-19 in developing countries, particularly Malaysia. Specifically, the study aims to determine how facilities management delivery in public hospitals can be improved to ensure readiness in handling COVID-19 cases. We conducted a review of the literature and reliable media updates on COVID-19 and services management. A critical synthesis of COVID-19 information was conducted to scrutinise the technical aspects and highlight how facilities management can be improved to ensure hospital readiness in managing COVID-19 cases. The data and information used in the present study were collected up to the time of writing this paper, which leaves a room for further studies. Nonetheless, this study's recommendations are useful for understanding the present and future pandemics. This study is a first attempt to summarise the data on facilities management in relation to the COVID-19 pandemic in the Malaysian context. The study's findings are suitable for the developing countries in managing healthcare management practices in the fight against COVID-19. This study aims to highlight current issues in order to provide a more objective assessment of facilities management to ensure hospital readiness in handling COVID-19 cases.
This study examined the effect of air pollution on the initial return of IPOs in Pakistan. Cross-sectional data were used to examine 102 listed IPOs on Pakistan Stock Exchange between 1996 and 2019. Ordinary least squares and quantile least squares were employed to examine the influence of air pollution on IPO initial returns. Lastly, stepwise regression was utilised for additional analysis. According to the findings, in the presence of high air pollution, IPO initial returns also increase due to higher uncertainty. The findings demonstrate that air pollution intensifies a company's information environment and financial uncertainty. Therefore, addressing environmental challenges is critical for both public health and capital formation. This study's findings will increase companies' awareness of the economic effect of air pollution, particularly in a country where air pollution is strictly regulated. This study provides businesses with an economic reason to reduce their pollution levels, and it can also help regulators pass environmental laws that are aimed at addressing this issue.
The low-temperature sintering of (Bi0.5Na0.5)TiO3-based ceramics can be achieved by sintering aid CuO. Piezoelectric ceramics (1 - x)[0.90(Bi0.5Na0.5)TiO3 - 0.10SrTiO3] - xCuO (BNT-ST-Cu) with x = 0, 0.01, 0.02, 0.03, and 0.04 were prepared through the mixed oxide route. A tetragonal structure was indexed for the undoped sample. Its structure was found to be changed to a pseudocubic when Cu was added. For undoped Cu samples, the sintering temperature (T s) for sufficient densification was 1160 °C. However, T s was reduced to 1090-1120 °C for Cu-added specimens. Field emission scanning electron microscopy (FE-SEM) showed a uniform and dense grain morphology for all samples. The maximum dielectric constant temperature (T m) was decreased with the doping concentration of Cu and applied frequency. The strain was increased with Cu concentration and had the maximum value of 500 pm/V for the sample x = 0.02 with symmetric and slim strain loops.
The Internet of vehicles (IoVs) is an innovative paradigm which ensures a safe journey by communicating with other vehicles. It involves a basic safety message (BSM) that contains sensitive information in a plain text that can be subverted by an adversary. To reduce such attacks, a pool of pseudonyms is allotted which are changed regularly in different zones or contexts. In base schemes, the BSM is sent to neighbors just by considering their speed. However, this parameter is not enough because network topology is very dynamic and vehicles can change their route at any time. This problem increases pseudonym consumption which ultimately increases communication overhead, increases traceability and has high BSM loss. This paper presents an efficient pseudonym consumption protocol (EPCP) which considers the vehicles in the same direction, and similar estimated location. The BSM is shared only to these relevant vehicles. The performance of the purposed scheme in contrast to base schemes is validated via extensive simulations. The results prove that the proposed EPCP technique outperformed compared to its counterparts in terms of pseudonym consumption, BSM loss rate and achieved traceability.
Programmable Object Interfaces are increasingly intriguing researchers because of their broader applications, especially in the medical field. In a Wireless Body Area Network (WBAN), for example, patients' health can be monitored using clinical nano sensors. Exchanging such sensitive data requires a high level of security and protection against attacks. To that end, the literature is rich with security schemes that include the advanced encryption standard, secure hashing algorithm, and digital signatures that aim to secure the data exchange. However, such schemes elevate the time complexity, rendering the data transmission slower. Cognitive radio technology with a medical body area network system involves communication links between WBAN gateways, server and nano sensors, which renders the entire system vulnerable to security attacks. In this paper, a novel DNA-based encryption technique is proposed to secure medical data sharing between sensing devices and central repositories. It has less computational time throughout authentication, encryption, and decryption. Our analysis of experimental attack scenarios shows that our technique is better than its counterparts.
The Internet of Things (IoT) is a network of intelligent devices especially in healthcare-based systems. Internet of Medical Things (IoMT) uses wearable sensors to collect data and transmit to central repositories. The security and privacy of healthcare data is a challenging task. The aim of the study is to provide a secure data sharing mechanism. The existing studies provide secure data sharing schemes but still have limitations in terms of hiding the patient identify in the messages exchanged to upload the data on central repositories. This paper presents a Secure Aggregated Data Collection and Transmission (SADCT) that provides anonymity for the identities of patient's mobile device and the intermediate fog nodes. Our system involves an authenticated server for node registration and authentication by saving security credentials. The proposed scheme presents the novel data aggregation algorithm at the mobile device, and the data extraction algorithm at the fog node. The work is validated through extensive simulations in NS along with a security analysis. Results prove the supremacy of SADCT in terms of energy consumption, storage, communication, and computational costs.
A contaminated aquatic environment may end up in the food chain and pose risks to tourist health in a tourist destination. To assess the health risk for tourists that visit St. Martine Island, which is a popular domestic and foreign tourist destination in Bangladesh, a study is undertaken to analyse the level of heavy metal contamination from chromium (Cr), manganese (Mn), copper (Cu), zinc (Zn), arsenic (As), cadmium (Cd), lead (Pb), mercury (Hg) and iron (Fe) in six of the most consumed fish (L. fasciatus, R. kanagurta, H. nigrescens, P. cuneatus, P. annularis and S. rubrum) and five crustacean species, which consist of a shrimp (P. sculptilis), a lobster (P. versicolor) and three crabs (P. sanguinolentus, T. crenata and M. victor) captured. The samples were analysed for trace metals using atomic absorption spectrometer, and the concentrations of the metals were interpreted using the United State Environmental Protection Agency (USEPA) health risk model. The muscle and carapace/exoskeleton of shrimp, lobster and crabs were analysed and contained various concentrations of Pb, Hg, As, Cr, Cd, Fe, Cu, Zn and Mn. The hierarchy of the heavy metal in marine fish is Fe > Cd > Zn > Pb > Cu > Cr > Mn > Hg. The concentrations of Pb in the species R. kanagurta, H. nigresceus and S. rubrum were above the food safety guideline by Australia, New Zealand and other legislations in most marine fish and crustaceans. Crabs showed higher mean heavy metal concentrations than shrimp and lobster. Acceptable carcinogen ranges were observed in three fish species (R. kanagurata, H. nigresceus and S. rubrum) and one crustacean species (P. sculptilis) samples.
Aim: Indole is an important component of many drug molecules, and its conjugation with thiosemicarbazone moiety would be advantageous in finding lead compounds for the development of diabetic complications. Methodology: We have designed, synthesized and evaluated a series of 17 indole-thiosemicarbazones (3a-q) as aldose reductase (ALR2) and aldehyde reductase (ALR1) inhibitors. Results: After in vitro evaluation, all indole-thiosemicarbazones showed significant inhibition against both enzyme ALR1 and ALR2 with IC50 in range of 0.42-20.7 and 1.02-19.1 μM, respectively. The docking study was also carried out to consider the putative binding of molecules with the target enzymes. Conclusion: Compound 3f was found to be most active and selective for ALR2. The indole-thiosemicarbazones series described here has selective hits for diabetes-mellitus-associated complications.
Cellulose is the most abundant polysaccharide on earth. It has a large number of desirable properties. Its low toxicity makes it more useful for a variety of applications. Nowadays, its composites are used in most engineering fields. Composite consists of a polymer matrix and use as a reinforcing material. By reducing the cost of traditional fibers, it has an increasing demand for environment-friendly purposes. The use of these types of composites is inherent in moisture absorption with hindered natural fibers. This determines the reduction of polymer composite material. By appropriate chemical surface treatment of cellulose composite materials, the effect could be diminished. The most modern and advanced techniques and methods for the preparation of cellulose and polymer composites are discussed here. Cellulosic composites show a reinforcing effect on the polymer matrix as pointed out by mechanical characterization. Researchers tried their hard work to study different ways of converting various agricultural by-products into useful eco-friendly polymer composites for sustainable production. Cellulose plays building blocks, that are critical for polymer products and their engineering applications. The most common method used to prepare composites is in-situ polymerization. This help to increase the yields of cellulosic composites with a significant enhancement in thermal stability and mechanical properties. Recently, cellulose composites used as enhancing the incorporation of inorganic materials in multi-functional properties. Furthermore, we have summarized in this review the potential applications of cellulose composites in different fields like packaging, aerogels, hydrogels, and fibers.
The antipyretic potential of viscosine, a natural product isolated from the medicinal plant Dodonaea viscosa, was investigated using yeast-induced pyrexia rat model, and its structure-activity relationship was investigated through molecular docking analyses with the target enzymes cyclooxygenase-1 (COX-1), cyclooxygenase-2 (COX-2), and microsomal prostaglandin E synthase-1 (mPGES-1). The in vivo antipyretic experiments showed a progressive dose-dependent reduction in body temperatures of the hyperthermic test animals when injected with viscosine. Comparison of docking analyses with target enzymes showed strongest bonding interactions (binding energy -17.34 kcal/mol) of viscosine with the active-site pocket of mPGES-1. These findings suggest that viscosine shows antipyretic properties by reducing the concentration of prostaglandin E2 in brain through its mPGES-1 inhibitory action and make it a potential lead compound for developing effective and safer antipyretic drugs for treating fever and related pathological conditions.