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The stage of pregnancy is crucial for women of reproductive age and their families. However, in low- and middle-income countries like Bangladesh, antenatal and postnatal care are not widely practiced due to various socio-economic factors, such as low education levels, income, age, pregnancy knowledge, and limited healthcare facilities. The objective of this study was to examine the factors associated with antenatal care in two locations in Bangladesh based on the data collected from the Bangladesh Demographic and Health Survey (BDHS) 2017–2018. We explored different variables as explanatory variables related to ANC service. The results showed that most of the respondents were from rural areas, with 77.02% receiving antenatal care at home. Women with secondary education were more likely to receive care at home than those without education. The Chi-square test indicated a positive correlation between antenatal care at home with several variables, whereas, in the case of Upazila health complexes, only three variables showed a positive association. Logistic regression analysis further showed some specific variables such as geographical division, religion, iron intake during pregnancy, and reporting pregnancy complications had a significant impact on ANC at home. In contrast, covariates such as residence, division, and wealth index were significant for antenatal care at Upazila health complexes. The division was a significant covariate in both cases. Interestingly, we observed that mothers who had been informed about the signs of pregnancy complications were 92% more likely to receive antenatal care at home than those who had not experienced pregnancy complications. Conversely, the results revealed that mothers who were unaware of pregnancy complications were 32% more likely to receive antenatal care at home than those who had been informed about complications. This suggests that when women are educated about pregnancy complications, they are more likely to receive more antenatal care. However, Bangladesh's situation is quite different due to a lack of proper education and knowledge of antenatal care services.

Introduction COVID-19 has caused severe disruption to clinical services in Bangladesh but the extent of this, and the impact on healthcare professionals is unclear. We aimed to assess the perceived levels of anxiety, depression and burnout among doctors and nurses during COVID-19 pandemic.Methods We undertook an online survey using RedCap, directed at doctors and nurses across four institutions in Bangladesh (The Sheikh Russel Gastro Liver Institute & Hospital (SRNGIH), Dhaka Medical College Hospital (DMCH), Mugda Medical College Hospital (MMCH) and M Abdur Rahim Medical College (MARMC) Hospital). We collected information on demographics, awareness of well-being services, COVID-19-related workload, as well as anxiety, depression and burnout using two validated questionnaires: the Hospital Anxiety and Depression Scale (HADS) and the Maslach Burnout Inventory (MBI).Results Of the 3000 participants approached, we received responses from 2705 (90.2%). There was a statistically significant difference in anxiety, depression and burnout scores across institutions (p

The Bangla Language ranks seventh in the list of most spoken languages with 265 native and non-native speakers around the world and the second Indo-Aryan language after Hindi. However, the growth of research for tasks such as sentiment analysis (SA) in Bangla is relatively low compared to SA in the English language. It is because there are not enough high-quality publically available datasets for training language models for text classification tasks in Bangla. In this paper, we propose a Bangla annotated dataset for sentiment analysis on the ongoing Ukraine–Russia war. The dataset was developed by collecting Bangla comments from various videos of three prominent YouTube TV news channels of Bangladesh covering their report on the ongoing conflict. A total of 10,861 Bangla comments were collected and labeled with three polarity sentiments, namely Neutral, Pro-Ukraine (Positive), and Pro-Russia (Negative). A benchmark classifier was developed by experimenting with several transformer-based language models all pre-trained on unlabeled Bangla corpus. The models were fine-tuned using our procured dataset. Hyperparameter optimization was performed on all 5 transformer language models which include: BanglaBERT, XLM-RoBERTa-base, XLM-RoBERTa-large, Distil-mBERT and mBERT. Each model was evaluated and analyzed using several evaluation metrics which include: F1 score, accuracy, and AIC (Akaike Information Criterion). The best-performing model achieved the highest accuracy of 86% with 0.82 F1 score. Based on accuracy, F1 score and AIC, BanglaBERT outperforms baseline and all the other transformer-based classifiers.

Mitogen-activated protein kinase (MEK) inhibitors and oncolytic virotherapy are identified as promising cancer therapies that can enhance the efficacy of other cancer treatments. A few studies demonstrate that cancer cells proliferate when exposed to virotherapy with MEK inhibitors in an integer order model or without them in a fractional order model. None of them are intended to investigate tumor cell growth under the combined treatment strategy of chemo-virotherapy with a MEK inhibitor in a fractional order model. In this paper, a mathematical model based on fractional order ordinary differential equations (ODEs) is developed for the mutual interactions among tumor cells, as well as a therapeutic combination of chemotherapy, oncolytic viruses and the functional consequence of MEK inhibitor, to investigate how virotherapy could enhance chemotherapy under the action of MEK inhibitor. The numerical results show that virus burst size and MEK inhibitors have a noticeable impact on regulating the trend of tumor cell proliferation. While virotherapy responses to tumor cell proliferation are undoubtedly quicker than chemotherapeutic treatment responses, MEK intensity clearly affects the success of the treatment regimen. The results of this study can contribute to the development of a therapeutic strategy that combines MEK inhibitor functional monitoring with tumor cell growth control.

In March 2020, the COVID-19 pandemic rapidly spread across Bangladesh, affecting various sectors, including aquaculture. However, there is a lack of evidence regarding the effects on aquaculture production and profitability in the country. The present study addresses this gap and investigates the impact of the COVID-19 pandemic using a convenience questionnaire survey utilising face-to-face and telephonic interviews with 499 fish farmers from five prominent fish-culture regions (Satkhira, Khulna, Madaripur, Bhola, and Mymensingh) in Bangladesh from April to August 2020. The results show aquaculture production losses averaging 29.1 % during the pandemic compared to the pre-pandemic period. Before the COVID-19 pandemic outbreak, the farmers reported a profit of USD3813 per hectare, which turned into a loss of USD2565.4 per hectare during the pandemic period. The standard multiple linear regression analysis indicated that large farms experienced a more significant impact on aquaculture production loss and economic loss during the pandemic period compared to small farms [β = 0.15, P = 0.029]. The causes for the production loss were identified by rank based quotient (RBQ), indicating that increased fish transportation costs and prices of seed and feed dominated during the lockdown. The lockdown and movement restrictions also reduced selling prices because of fewer buyers. The government provided financial support to the fish farmers, but only onethird (36 %) of the respondents received financial aid. The study suggests implementing medium and long-term measures, such as strengthening communication networks, digital marketing strategies and developing strategic planning initiatives to improve disaster management and resilience to mitigate the effects of the pandemic.

This paper focuses on the production systems that may produce a proportion of recyclable defective products. The developed model is called an Economic Recycle Quantity (ERQ) model with the assumption of a full recovery of defective items. The defective parts are collected during the production-off time and can be used during the next production cycle of the same category. The demand rate of the non-defective items is a two-level piecewise factor—one during the production-run time and another during the production-off time. The developed model aims to optimize the total inventory cost, the order quantity, and the amount of recyclable defective items that represent the ERQ. The mathematical formulations of the model are deduced theoretically. The model was solved analytically, and the optimal results are illustrated. Sensitivity analysis is carried out to investigate the effect of varying system parameters and validate the proposed model. Results of the sensitivity analysis show that the consideration of defective part recycling reduces the total inventory cost where the raw material is reduced. The cost reduction is about 1%; of course, the environmental impact is more appreciated. Furthermore, the managerial implications are described, and the future perspectives are discussed.

Directional force sensing is an intrinsic feature of tactile sensing. As technologies of exploratory robots evolve, with special emphasis on the emergence of soft robotics, it is crucial to equip robotic end-effectors with effective means of characterizing trends in force detection and grasping phenomena, while these trends are largely derived from networks of tactile sensors working together, individual sensors must be built to meet an intended function and maintain functionality with respect to environmental operating conditions. The harshness of underwater exploration imposes a unique set of circumstances onto the design of tactile sensors. When exposed to underwater conditions a tactile sensor must be able to withstand the effects of increased pressure paired with water intrusion while maintaining computational and mechanical integrity. Robotic systems designed for the underwater environment often become expensive and cumbersome. This paper presents the design, fabrication, and performance of a low-cost, soft-material sensor capable of multi-directional force detection. The fundamental design consists of four piezo-resistive flex elements offset at 90∘ increments and encased inside of a hemispherical silicone membrane filled with a non-compressive and non-conductive fluid. The sensor is simulated numerically to characterize soft-material deformation and is experimentally interrogated with indentation equipment to investigate sensor-data patterns when subject to different contact forces. Furthermore, the sensor is subject to a cyclic loading test to analyze the effects of hysteresis in the silicone and is submerged underwater for a 7-day period to investigate any effect of water intrusion at a shallow depth. The outcome of this paper is the proposed design of a waterproofed, soft-material tactile sensor capable of directional force detection and contact force localization. The overall goal is to widen the scope of tactile sensor concepts outfitted for the underwater environment.

Temperature uncertainty models for land and sea surfaces can be developed based on statistical methods. In this paper, we developed a novel time-series temperature uncertainty model, which is the autoregressive moving average (ARMA) (1,1) model. The model was developed for an observed annual mean temperature anomaly X(t), which is a combination of a true (latent) global anomaly Y(t) for a year (t) and normal variable w(t). The uncertainty is taken as the variance of w(t), which was divided into land surface temperature (LST) uncertainty, sea surface temperature (SST) uncertainty, and the corresponding source of uncertainty. The ARMA model was analyzed and compared with autoregressive (AR) and autoregressive integrated moving average (ARIMA) for the data obtained from the NASA Goddard Institute for Space Studies Surface Temperature (GISTEMP) Analysis. The statistical analysis of the autocorrelation function (ACF), partial autocorrelation function (PACF), normal quantile–quantile (normal Q-Q) plot, density of the residuals, and variance of normal variable w(t) shows that ARMA (1,1) fits better than AR (1) and ARIMA (1, d, 1) for d = 1, 2.

Conventional solid-state reaction method has been cautiously employed to prepare the Ba0.75Sr0.25Ti1−xMnxO3 ceramic where Sr was firmly doped at the Ba site and Mn was doped with different densities at the Ti site. Since the performance of materials varies with frequency, electric field, and temperature, we have elucidated the various features of the synthesized samples for the sake of scientific benefit in the fields of microelectronics, telecommunications, and spintronics. Structural and morphological features of the ready samples were examined by X-ray diffraction and scanning electron microscopy (SEM). The crystal's tetragonal behavior was verified by XRD analysis, and with the increment of Mn content, the volume of the unit cell is little changed. It is clear from the SEM images that the grain size of the prepared samples increases with Mn doping. The dielectric properties of Ba0.75Sr0.25Ti1−xMnxO3 were measured by dielectric constant and AC conductivity in a wide range of frequency from 1 kHz to 10 MHz. This result also explores that the dielectric constant rises with the concentration of Mn, most significantly for the 20% Mn substitution with Ti. We also found from the experimental result that the dielectric constant is high in the frequency range of 1–10 kHz. The magnetic permeability of the prepared sample increased with 10% and 20% of Mn replacement. Ferromagnetic features with a weak coercive field and the increased ferromagnetic order with rising Mn concentrations of the prepared samples were confirmed by VSM data analysis. The developed multiferroic materials can be employed in future spintronic devices like spin transistors, sensors, spin diodes, and memory devices. [ABSTRACT FROM AUTHOR]

In this research, curium oxide (CmO2) is studied as fuel for VVER-1200 reactor to get an attention to its energy value and possibilities. For this purpose, CmO2 is used in fuel rods or integrated burnable absorber (IBA) rods with and without UO2 and then compared with the conventional fuel assembly of VVER-1200 reactor. It is burned to 60 GWd/t by using SRAC-2006 code and JENDL-4.0 data library. From these studies, it is found that CmO2 is competent like UO2 as a fuel due to higher fission cross-section of 243Cm and 245Cm isotopes and neutron capture cross-section of 244Cm and 246Cm isotopes. As a result, when some or all of the UO2 of fuel rods or IBA rods are replaced by CmO2, we get a similar k-inf like the reference even with lower enrichment UO2 fuels. These studies show that the use of CmO2 as IBA rods is more effective than the fuel rods considering the initially loaded amount, power peaking factor (PPF), fuel temperature and void coefficient, and the quality of spent fuel. From a detailed study, 3% CmO2 with inert material ZrO2 in IBA rods are recommended for the VVER-1200 reactor assembly from the once through concept.