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Abstract The evidence clearly shows that education greatly impacts people’s well-being. Bangladesh has two main education systems—general and traditional religious schooling. The current study aimed to measure the quality of life of madrasa students and find out the factors influencing it. This was a cross-sectional study on a group of madrasa students in the Mirpur area of Dhaka, Bangladesh. Data were collected using two-stage stratified random sampling between April and May 2022. The final sample size was 373. The health-related quality of life (HRQoL) was calculated using the KIDSCREEN-10 index, and the median split was used to categorize the score into ‘good’ and ‘poor’ categories. A p

Abstract Background Hospitalisation resulting from complications of systemic therapy and radiotherapy places a substantial burden on the patient, society, and healthcare system. To formulate preventive strategies and enhance patient care, it is crucial to understand the connection between complications and the need for subsequent hospitalisation. This review aimed to assess the existing literature on complications related to systemic and radiotherapy treatments for cancer, and their impact on hospitalisation rates. Methods Data was obtained via electronic searches of the PubMed, Scopus, Embase and Google Scholar online databases to select relevant peer-reviewed papers for studies published between January 1, 2000, and August 30, 2023. We searched for a combination of keywords in electronic databases and used a standard form to extract data from each article. The initial specific interest was to categorise the articles based on the aspects explored, especially complications due to systemic and radiotherapy and their impact on hospitalisation. The second interest was to examine the methodological quality of studies to accommodate the inherent heterogeneity. The study protocol was registered with PROSPERO (CRD42023462532). Findings Of 3289 potential articles 25 were selected for inclusion with ~ 34 million patients. Among the selected articles 21 were cohort studies, three were randomised control trials (RCTs) and one study was cross-sectional design. Out of the 25 studies, 6 studies reported ≥ 10 complications, while 7 studies reported complications ranging from 6 to 10. Three studies reported on a single complication, 5 studies reported at least two complications but fewer than six, and 3 studies reported higher numbers of complications (≥ 15) compared with other selected studies. Among the reported complications, neutropenia, cardiac complications, vomiting, fever, and kidney/renal injury were the top-most. The severity of post-therapy complications varied depending on the type of therapy. Studies indicated that patients treated with combination therapy had a higher number of post-therapy complications across the selected studies. Twenty studies (80%) reported the overall rate of hospitalisation among patients. Seven studies revealed a hospitalisation rate of over 50% among cancer patients who had at least one complication. Furthermore, two studies reported a high hospitalisation rate (> 90%) attributed to therapy-repeated complications. Conclusion The burden of post-therapy complications is emerging across treatment modalities. Combination therapy is particularly associated with a higher number of post-therapy complications. Ongoing research and treatment strategies are imperative for mitigating the complications of cancer therapies and treatment procedures. Concurrently, healthcare reforms and enhancement are essential to address the elevated hospitalisation rates resulting from treatment-related complications in cancer patients.

Background: The practice of self-medication (SM) is common worldwide and is an important component of medical self-care. However, improper practice can be dangerous. This study aimed to estimate the prevalence of SM and the factors associated with it among Bangladeshi adults. Methods: A cross-sectional survey was conducted between April and June 2021 among Bangladeshi adults (aged > 19 years) using convenient sampling. A total of 1320 subjects were collected through face-to-face interviews using a standardized questionnaire. Multivariable logistic regression analysis was used to identify factors associated with the practice of SM. Results: Overall, 41% of adults in our survey reported SMP. The most common illnesses that prompted SM were common cold/flu (66.4%), gastric problems (65%), and headache (64.4%). The most frequent reasons for SM were to get better-perceived quality of care (30.6%), perceiving SM without side effects (23.3%), and saving time with effectiveness (14.56%). Potential risk factors included 10 years (AOR = 1.91; 95% CI: 1.04–3.50) and >12 years of schooling (AOR = 5.03; 95% CI: 2.27–11.15), being a businessman (AOR = 4.64; 95% CI: 1.74–12.37), having ≤6 family members (AOR = 2.13; 95% CI: 1.40–3.24), being a member of a social group (AOR = 1.53; 95% CI: 1.10–2.12), a health status check after every six months (AOR = 1.52; 95% CI: 1.08–2.13), and current ill-health (AOR = 1.41; 95% CI: 1.06–1.87). Protective factors identified included ≤30 years of age (AOR = 0.40; 95% CI: 0.17–0.93), and practice of modern (AOR = 0.39; 95% CI: 0.22–0.69) and herbal (AOR = 0.45; 95% CI: 0.21–0.97) treatment modality. Conclusion: More than one-third of the study participants reported practicing SM. Increasing the community’s awareness of the adverse outcomes of SM and not just the average experience might sway individuals away from SM, and implementing strict jurisdiction could be a way to minimize inappropriate SM.

ABSTRACT Background Cancer is a critical public health issue that imposes a considerable economic burden, especially in low‐resource countries. In Bangladesh, there has been a noticeable lack of research focusing on the economic burden associated with cancer. Aims: This study aimed to examine the economic burden of cancer care and the contributing factors. Methods This cross‐sectional study included 623 cancer patients. Data were collected between January and May 2022. The magnitude of the economic burden (no burden to extreme burden) was the outcome variable. A logistic regression model was performed to determine the associated factors of the economic burden of cancer. Results Overall, 34% of cancer survivors experienced extreme economic burden due to treatment costs. Patients with prostate (relative risk ratio, RRR = 23.24; 95% confidence interval, CI: 1.97, 273.70), bone (RRR = 5.85; 95% CI: 1.10, 31.04), and liver cancer (RRR = 4.94; 95% CI: 1.29, 18.9) reported significantly higher extreme economic burden compared to patients with other cancers. The economic burden was significantly higher for patients diagnosed with Stage III (RRR = 38.69; 95% CI: 6.17, 242.72) and Stage IV (RRR = 24.74; 95% CI: 3.22, 190.11) compared to Stage 0. Patients from low‐income households suffered from nine times more extreme burden (RRR = 8.85; 95% CI: 4.05, 19.36) compared with those from high‐income households. Conclusion Our study found a disproportionately high economic burden among patients with cancer, across disease sites, stages, and income quintiles. The burden was significantly higher among patients with prostate, bone, and liver cancer, and those diagnosed with advanced stage. The findings underscore the importance of early cancer detection before metastasis which may lead to more efficient treatment, avoid disease progression, lower disease management costs, and better health outcomes. Patients from low‐income households experience an extreme economic burden due to cancer, highlighting the need for affordable healthcare services, financial support, and healthcare subsidies.

Abstract Background Evaluating the effects of cancer diagnosis and treatment on a patient’s overall well-being is crucial and health-related quality of life (HRQoL) is a reliable metric for assessing this impact. Little is known about HRQoL among cancer survivors across various stages and treatments. The study examined individual and clinical factors influencing HRQoL among cancer survivors. Methods A cross-sectional study was conducted in two specialised cancer care hospitals in Dhaka, Bangladesh. Cancer-diagnosed adults receiving treatment at selected hospitals from January to May 2022 were enrolled. The 5-level EuroQol-5 Dimensions version (EQ-5D-5L) instrument was used to collect HRQoL data. HRQoL scores were derived using UK value sets. The investigation used a multivariable Tobit regression model to determine the association between independent variables and HRQoL scores. Results A total of 607 adult patients were enrolled, with 55% being females and 66% aged 36 to 64 years. Reported health problems in five EQ-5D domains include mobility (11%), self-care (11%), usual daily activities (19%), pain/discomfort (21%), and anxiety/depression (46%). Patients with throat, brain, lung, blood, and liver cancer had lower utility scores. Advanced-stage cancer survivors had lower utility scores (β = -49 units, 95% codfidence interval [CI]: -0.75 to -0.22) compared to early-stage survivors. Physically inactive survivors had lower utility scores by 0.41 units (95% CI: -0.51 to -0.30) compared to their counterparts. Private hospital patients had higher utility scores, whereas patients belonged to poor socioeconomic groups scored worse than wealthier ones. Conclusions This study highlights the impact of clinical and individual characteristics on HRQoL among cancer survivors. These findings advocate for an enhanced Bangladeshi cancer patient care model through timely interventions or programs, early detection or diagnosis, tailored treatments, and the promotion of physical activity to bolster HRQoL outcomes.

Abstract Background Workplace violence (WPV) is an emerging problem for health workers (HWs) and a global concern in health systems. Scientific literatures infer that WPV against HWs is often attributed to workplace injuries and absenteeism, leading to a series of adverse consequences. Therefore, this study aimed to investigate the prevalence of workplace injuries and absenteeism due to WPV among Bangladeshi HWs and its association with factors related to health facilities, work environments, and rotating shift work. Methods This study used participants who had experienced WPV, including medical doctors, nurses, or any form of medical staff. A total of 468 victim HWs were added in the analytical exploration. Participants were generated from our previous cross-sectional study of 1081 Bangladeshi HWs. A logistic regression model was used to find the association between workplace injuries and absenteeism due to WPV among HWs and associated factors. Results The prevalence of workplace injuries and absenteeism due to WPV among HWs were 14.10% (95% CI 11.23–7.57) and 22.44% (95% CI 18.87–26.45), respectively. Injury incidence was higher among males (17.67%) and young HWs (20.83%). Workplace absenteeism was more common among male HWs (25%) and those working in public hospitals (23.46%). The magnitude of injuries and absenteeism varied significantly by hospital departments. Workplace injury was significantly higher among HWs who worked in the emergency (AOR = 21.53, 95% CI 2.55–181.71), intensive care (AOR = 22.94, 95% CI 2.24–234.88), surgery (AOR = 17.22, 95% CI 1.96–151.39), and gynecology & obstetrics departments (AOR = 22.42, 95% CI 2.25–223.07) compared with other departments. The burden of work-related absenteeism was significantly associated with HWs who worked in the emergency (AOR = 4.44, 95% CI 1.56–12.61), surgery (AOR = 4.11, 95% CI 1.42–11.90), and gynecology and obstetrics departments (AOR = 5.08, 95% CI 1.47–17.50). Conclusions This study observed a high prevalence of workplace injuries and absenteeism among HWs due to WPV across hospital departments, including emergency, surgery, intensive care and gynecology & obstetrics units. Policymakers should incorporate suitable strategies into Bangladesh’s national health policy to combat violence in healthcare settings.

Predictably, the upcoming six generation (6G) networks demand ultra-massive interconnectivity comprising densely congested sustainable small-to-tiny networks. The conventional radio access network (RAN) will be redesigned to provide the necessary intelligence in all areas to meet required network flexibility, full coverage, and massive access. In this respect, this paper focuses on intelligent massive RAN (mRAN) architecture and key technologies fulfilling the requirements. Particularly, we investigate potential artificial intelligence algorithms for network and resource management issues in 6G mRAN. Furthermore, we summarize the research issues in edge technologies and physical layer intelligence on 6G network architecture.

Abstract Background The increasing physical violence against doctors in the health sector has become an alarming global problem and a key concern for the health system in Bangladesh. This study aimed to determine the prevalence and associated factors of physical violence against doctors in Bangladeshi tertiary care hospitals. Methods A cross-sectional survey was performed among 406 doctors working in tertiary care hospitals. Data were collected using a self-administered questionnaire and the binary logistic regression model was employed for predicting physical violence against doctors. Results Of the participants, 50 (12.3%) doctors reported being exposed to physical violence in 12 months prior to the survey. According to logistic regression analysis, aged less than 30 years or younger, male and never-married doctors were prone to physical violence. Similarly, doctors from public hospitals and those worked in emergency departments were at higher risk of physical violence. More than 70% of victims reported that patients’ relatives were the main perpetrators. Two-thirds of the victims referred to violence in the hospitals as a grave concern. Conclusions Physical violence against doctors is relatively common in the emergency departments and public hospitals in Bangladesh. This study found that male and younger doctors were at high risk of exposing physical violence. To prevent hospital violence, authorities must develop human resources, bolster patient protocol and offer physician training.

Abstract Unsafe electrical appliances can be hazardous to humans and can cause electrical fires if not monitored, analyzed, and controlled. The purpose of this study is to monitor the system’s condition, including the electrical properties of the appliances, and to diagnose fault conditions without deploying sensors on individual appliances and analyzing individual sensor data. Using historical data and an acceptable range of normal and leakage currents, we proposed a hybrid model based on multiclass support vector machines (MSVM) integrated with a rule-based classifier (RBC) to determine the changes in leakage currents caused by installed devices at a certain moment. For this, we developed a sensor-based monitoring device with long-range communication to store real-time data in a cloud database. In the modeling process, RBC algorithm is used to diagnose the constructed device fault and overcurrent fault where MSVM is applied for detecting leakage current fault. To conduct an operational field test, the developed device was integrated into some houses. The results demonstrate the effectiveness of the proposed system in terms of electrical safety monitoring and detection. All the collected data were stored in a structured database that could be remotely accessed through the Internet.

BackgroundChinese medicine belly button application (CMBBA) has been used to treat childhood diarrhea (CD) in several randomized controlled trials (RCTs), but its effectiveness and combination strategy still need to be clarified. Therefore, we aimed to evaluate the effectiveness, safety, and the optimal combination strategy of CMBBA in treating CD.MethodsUp until January 2023, we searched for studies that met our inclusion criteria in six databases, including PubMed, the Cochrane Library, Chinese SinoMed, CNKI, VIP, and Wanfang. Heterogeneity was quantified using I2 statistics. A methodological evaluation was performed using the Cochrane Risk Bias Tool 2.0. The Confidence in Network Meta-Analysis online software was employed to evaluate evidence grading. A minimally contextualized framework was used to provide a comprehensive conclusion for the network meta-analysis. This study protocol was registered with PROSPERO.ResultsWe analyzed data from 33 RCTs that included 4,490 children with diarrhea. In terms of clinical effectiveness, CMBBA plus montmorillonite powder plus anti-infectives may be the most effective treatment option for children with diarrhea and concurrent infection according to a minimally contextualized framework. Either exclusive use of CMBBA or CMBBA in combination with modern medicine was beneficial in reducing the time to diarrhea disappearance (MD = −1.33 days, 95% CI: −1.59 to −1.08, Z = −10.103, p

Abstract Background Complementary and alternative medicine (CAM) has played a critical role in ensuring universal access to basic health care services around the world. In Bangladesh, conventional medicine is a common approach for health care practices, yet, due to Bangladesh’s high out-of-pocket payment, millions of people utilise CAM-based healthcare services for illnesses. In Bangladesh, there is a scarcity of data on how CAM is perceived and utilised. The goal of this study was to determine the proportion and correlates of the utilisation of CAM among patients visiting a tertiary level hospital, in Bangladesh. Methods A cross-sectional survey involving 1,183 patients who received health care from a hospital in Bangladesh was interviewed for this study. The associated factors on utilising CAM were identified using multivariable logistic regression analysis. Results Thirty-three percent of patients utilised CAM exclusively to treat their illnesses, whereas the rest utilised conventional medicine before CAM. Young adult patients aged 26 to 45 years (AOR = 6.26, 95% CI:3.24–12.07), patients without education (AOR = 2.99, 1.81–4.93), and married patients (AOR = 1.79, 1.08–2.97) were the most likely to be only CAM users. The most common reasons for using CAM were belief in its effectiveness, less adverse effects, affordability and lower costs. Conclusion In Bangladesh, CAM plays a significant role in health care delivery, with high-levels of patient satisfaction and health benefits. Patients who are older and have a higher level of education are more hesitant to use CAM for their illness, yet CAM has the potential to play a significant role in reducing hospitalisation by providing high reliability and low costs.

Background: Depression is a major contributor to overall global disease burden, often beginning in the teenage years and continuing into later life. Previous studies have reported high global rates of depression during these formative years, including in Bangladesh. At the same time, the positive impact that pet ownership can have on depression is steeply being recognized. However, studies examining these effects in Bangladesh are scarce. This study examined the association between household pet ownership and depression among people older than 13 years in Dhaka, Bangladesh. Methods: A cross-sectional study was conducted using online and offline approaches. We employed a snowball sampling technique to identify pet owners aged greater than 13 years residing in Dhaka, Bangladesh. Both web-based survey questionnaires using social media and hard copies were used to collect data from urban-dwelling pet owners. Logistic regression model was used to identify the independent role of pet ownership in depression, adjusting for confounders, including age, sex, marital status, known chronic disabilities, and other variables. Results: A total of 140 pet owners and an equal number of non-pet owners participated in the study. Pet owners were found to be 41% less depressed than non-pet owners (AOR: 0.59; 95% CI: 0.31–1.14). In addition, males (AOR: 3.38; 95% CI: 1.50–7.62) who were either unmarried (AOR: 2.10; 95% CI: 1.05–4.16), smoked tobacco (AOR: 5.27; 95% CI: 1.50–18.53), or had a physical disability (AOR: 5.27; 95% CI: 1.50–18.53) were significantly more likely to be depressed. Conclusion: Regression analysis revealed that in Dhaka, pet owners were associated with lower levels of depression compared to non-pet owners.

In this paper, we present and compare two experimentally feasible photonic crystal fiber (PCF) designs (Type-Iand Type-II) which ensure near-zero flattened dispersion with ultra-high phase and group birefringence at THz frequencies. Both structures are based on a subset of a triangular array of circular air-holes, which define the cladding of the PCF and a central elliptical air-hole which breaks the symmetry of the structure, thus introducing high levels of birefringence. Additionally, we investigate the possibility of further enhancing the birefringence properties of Type-II structure by selectively filling the air-holes with Potassium Chloride (KCl) as strong Epsilon-Near-Zero (ENZ) material. Our investigation reveals that significant enhancement of birefringence can be achieved than its original counterpart with birefringence to be as high as 0.0627 at 6.2 THz and near-zero flat dispersion of -0.54 ± 0.04 ps/THz/cm over the frequency range of 6.2-6.3 THz.

This technical paper presents an optical camera communication system by using data as input collected from a sensor that continuously garners humidity and temperature information from the environment. A small light-emitting diode (LED) and an LED array are used as a transmitter and a low-speed rolling-shutter camera as a receiver. A modulation scheme standardized in IEEE 802.15.7, referred to as variable pulse-width modulation, is used to encode the data bits. The proposed scheme is flicker-free in different frequencies and applicable in both static and mobile scenarios. A neural network is designed for LED detection and improving the bit-error-rate in mobile scenarios. A new method based on the region-wise comparison and an existing method is used to remove the interference and noise generated from the neighboring light sources, respectively. The decoding procedure is performed and analyzed in Python 3.7. A data rate of 1.02 kbps is achieved using the single LED, which is further augmented to 64 kbps by using an 8 × 8 LED dot matrix.

The demand for wireless connectivity has grown exponentially over the last few decades. Fifth-generation (5G) communications, with far more features than fourth-generation communications, will soon be deployed worldwide. A new paradigm of wireless communication, the sixth-generation (6G) system, with the full support of artificial intelligence, is expected to be implemented between 2027 and 2030. Beyond 5G, some fundamental issues that need to be addressed are higher system capacity, higher data rate, lower latency, higher security, and improved quality of service (QoS) compared to the 5G system. This paper presents the vision of future 6G wireless communication and its network architecture. This article describes emerging technologies such as artificial intelligence, terahertz communications, wireless optical technology, free-space optical network, blockchain, three-dimensional networking, quantum communications, unmanned aerial vehicles, cell-free communications, integration of wireless information and energy transfer, integrated sensing and communication, integrated access-backhaul networks, dynamic network slicing, holographic beamforming, backscatter communication, intelligent reflecting surface, proactive caching, and big data analytics that can assist the 6G architecture development in guaranteeing the QoS. Besides, expected applications with 6G communication requirements and possible technologies are presented. We also describe potential challenges and research directions for achieving this goal.

In this paper, an area-time efficient hardware implementation of modular multiplication over five National Institute of Standard and Technology (NIST)-recommended prime fields is proposed for lightweight elliptic curve cryptography (ECC). A modified radix-2 interleaved algorithm is proposed to reduce the time complexity of conventional interleaved modular multiplication. The proposed multiplication algorithm is designed in hardware and separately implemented on Xilinx Virtex-7, Virtex-6, Virtex-5, and Virtex-4 field-programmable gate array (FPGA) platforms. On the Virtex-7 FPGA, the proposed design occupies only 1151, 1409, 1491, 2355, and 2496 look up tables (LUTs) and performs single modular multiplication in 0.93 μs, 1.18 μs, 1.45 μs, 2.80 μs, and 4.69 μs with maximum clock frequencies of 207.1 MHz, 190.7 MHz, 177.3 MHz, 137.6 MHz, and 111.2 MHz over five NIST prime fields of size 192, 224, 256, 384, and 521 bits, respectively. The hardware implementations on the Virtex-6, Virtex-5, and Virtex-4 FPGAs also show that the proposed design is highly efficient in terms of hardware resource utilization and area-delay product compared with other designs for modular multiplication.

In this paper, we consider the current status and technical issues involved in the use of optical camera communication (OCC)/visible light communication (VLC) technologies in vehicular communication systems. Hybrid spatial phase-shift keying was introduced in IEEE 802.15.7-2018 as the standard hybrid modulation scheme for vehicular OCC/VLC systems. We herein propose a functional communication system architecture for vehicular systems based on this hybrid waveform, and we also present state-of-the-art research work on an artificial intelligence (AI)-based vehicular OCC system. Every AI module within the proposed system architecture is discussed in detail. Finally, our experimental procedures and results are analyzed to evaluate the performance of the proposed system over a complex channel model in a vehicular environment. We effectively employed the popular You Only Look Once version 2 object detection algorithm for real-time region-of-interest tracking in city driving (at a vehicular velocity of around 30 km/h and highway night driving (at a vehicular velocity of > 60 km/h) scenarios. Moreover, our novel neural-network-based decoder and AI-based error correction proved effective in improving the data decoding accuracy, resulting in a best-case reduction of 2.2 and 9.0 dB, respectively, in the signal-to-noise ratio needed to achieve the desired bit error rate of 10-4 in a vehicular OCC/VLC system.

In recent times, the electric power management based on customers' demand has drawn significant attention of smart-grid (SG) governors. The SG requires real-time management of dynamic load to maintain the quality of service (i.e., balance between supply and demand) by interfacing with users. In this paper, we propose an approach to respond to the active demand (AD) based on user-defined energy-management policy. An algorithm is also proposed for the smart-controller device (SCD) modeled with the load aggregator and connected to the customers. The total contracted load and the user ADs are determined based on area, load, and phase classification, which specify the individual energy consumption. The proposed scheme is implemented in MATLAB/Simulink using the load-information of the IEEE 30-bus system, and the feasibility is assessed in IEEE 13 and IEEE 34 node test feeder systems. By applying the customer's controlled SCD device both the deficiency and redundancy of generation in terms of grid controllable load have been improved that lead the maximization of generation and distribution services. The voltage regulation and power factor of the particular area have been enhanced by integrating appropriate distributed generation and power factor improvement devices. The results garnered from the performance analysis show that the proposed scheme can optimize power generation based on the user-defined demand.

In this technical paper, we design and implement an optical camera communication system for real-time remote monitoring of patient's heart rate (HR) and oxygen saturation (SpO2) data. The data is collected and transmitted by a patch circuit which comprises a MAX30102 sensor and an RGB LED array. A close circuit television camera is used not only for surveillance but also for receiving the data simultaneously. The LED is modulated using color intensities, and the data can be retrieved regardless of any orientations of the LED array. We propose a neural network (NN) to detect each LED separately, and we implement another NN-based on feature extraction to precisely recognize the colors. The data are also encoded with a unique key, which increases the security of the communication mechanism. System performance of 4.68 kbps with low bit-error-rate (BER) and 1.172 kbps with moderate BER is achieved at 1 and 3 m, respectively.

Background While conventional medicine (CM) is commonly used to treat non-communicable diseases (NCDs), complementary and alternative medicine (CAM) is gaining popularity as a healthcare option in Bangladesh. We aimed to investigate the prevalence and factors associated with using CAM solely and using CAM in conjunction with CM for chronic illness treatment among NCD patients in Bangladesh. Methods A multicenter cross-sectional study was conducted, including 549 adults with a confirmed chronic illness diagnosis from three tertiary care hospitals in Dhaka city. Interviews were used to gather socio-demographic data, while medical records were used to get information on chronic illnesses. A multinomial logistic regression model was used to determine the associated factors of utilizing CAM primarily and CAM use in conjunction with CM to manage the chronic disease. Results Out of 549 NCD patients (282 women [51.4%], mean [standard deviation] age 45.4 [12.8] years), 180 (32.8%) ever used CAM for the treatment of chronic illness. Also, 15.3% of patients exclusively used CAM among the NCD patients, while 17.5% used CAM in conjunction with CM. Homeopathy medicine was the most prevalent type of treatment among CAM users (52.2%). Furthermore, 55.5% of CAM users said they used it due to its less adverse effects, and 41.6% trusted its effectiveness for chronic illness. Elderly patients (≥60 years) preferred CAM in complementary with CM, but they did not rely only on CAM. According to the multinomial regression analysis, unmarried patients, predominantly in the younger age group, adopted CAM significantly for chronic illness treatment (Relative risk ratio, RRR = 0.29, 95% CI = 0.12–0.71, reference = Unmarried). Patients in the high-income group used CAM in conjunction with CM (RRR = 6.26, 95% CI = 1.35–18.90, reference: low-income), whereas patients in the high-income group did not rely on CAM alone (RRR = 0.99, 95% CI = 0.34–2.85). Conclusion Although CM remains the mainstream of health care in Bangladesh, CAM services play an essential role in people’s health care, particularly in treating chronic illnesses. Physicians of Bangladesh should be aware that their patients may be using other services and be prepared to ask and answer questions regarding the risks and benefits of using CAM in addition to regular medical care. Thus, clinicians required to follow best-practice guidelines, which are currently not practiced in Bangladesh, when disseminating information regarding integrative techniques that combine CM and CAM approaches.

Background. Imposter syndrome (IS), associated with self-doubt and fear despite clear accomplishments and competencies, is frequently detected in medical students and has a negative impact on their well-being. This study aimed to predict the students’ IS using the machine learning ensemble approach. Methods. This study was a cross-sectional design among medical students in Bangladesh. Data were collected from February to July 2020 through snowball sampling technique across medical colleges in Bangladesh. In this study, we employed three different machine learning techniques such as neural network, random forest, and ensemble learning to compare the accuracy of prediction of the IS. Results. In total, 500 students completed the questionnaire. We used the YIS scale to determine the presence of IS among medical students. The ensemble model has the highest accuracy of this predictive model, with 96.4%, while the individual accuracy of random forest and neural network is 93.5% and 96.3%, respectively. We used different performance matrices to compare the results of the models. Finally, we compared feature importance scores between neural network and random forest model. The top feature of the neural network model is Y7, and the top feature of the random forest model is Y2, which is second among the top features of the neural network model. Conclusions. Imposter syndrome is an emerging mental illness in Bangladesh and requires the immediate attention of researchers. For instance, in order to reduce the impact of IS, identifying key factors responsible for IS is an important step. Machine learning methods can be employed to identify the potential sources responsible for IS. Similarly, determining how each factor contributes to the IS condition among medical students could be a potential future direction.

One of the major aspects of retrofitting or strengthening of existing concrete structures is to install rebars using chemical adhesives. In a view to lighten the disturbance of existing structures by reducing the number of holes, high strength rebars (80 grade; nominal yield strength of 550 MPa) are more preferable for repairing and strengthening structural components. Here, a total of 108 specimens were prepared to evaluate the performance of post-installed high strength deformed rebar (PIHSDR) in concrete using pull-out tests. Test parameters included concrete compressive strength (fc' ), rebar diameter, embedment length of rebar into concrete and concrete cover to rebar diameter ratio (c/db) to investigate the bond behaviors of PIHSDR at the epoxy-concrete interface. Bond stress-slip relationships for PIHSDR were obtained, investigated, and hence compared with previous research and available codes. It was observed that most of the specimens showed concrete rapture, splitting, or rebar rapture failure and none of them showed pull-out failure which indicates that the epoxy resins are very much effective as bonding chemicals for retrofitting concrete structures in the steel-concrete interface. Besides, regression analyses were performed using the experimental data to obtain a closed-form equation for predicting the bond strength for PIHSDR. The predicted bond strengths were observed close to the actual test data with a high coefficient of determination (R2 = 0.99) and very low root mean square error (0.078).

The application of waste materials in concrete is getting more popular in the concrete industries as it can reduce the associated costs and environmental impacts. The present study investigates the performances of concrete while incorporating polypropylene (PP) plastic, derived from waste plastic products, as a partial replacement of natural stone aggregate (SA) and burnt clay brick aggregate (BA). The main variables include the percentage of PP aggregate (PPA) (0%, 10 %, 20 %, and 30 %), water-cement ratio (0.45 and 0.55), and types of aggregate (SA and BA). Results are presented in terms of workability, hardened density, compressive, tensile strengths, modulus of rupture, modulus of elasticity (MoE), ultrasonic pulse velocity (UPV), and cost analysis. Furthermore, empirical equations are proposed for predicting different properties of concrete; especially, predicting compressive strengths from the UPV values. Results indicated that the slump value increased with increasing the percentage of PPA. Concrete with 10 % PPA exhibited higher compressive strength, modulus of rupture, and splitting tensile strengths, even, higher than that of the control stone aggregate concrete (SAC) and control brick aggregate concrete (BAC). The UPV values varied with aggregate types and PPA content. Both the compressive strength and the UPV values decreased with the increasing percentages of PPA from 10 to 30. Furthermore, SAC exhibited higher compressive strength and UPV values compared to BAC. A good correlation was found between the compressive strength and the UPV values for concrete with PPA. From the cost sensitivity analysis, it was observed that concrete containing 10 % PP content had the highest strength over cost ratio compared to the control and other PPA concrete. Therefore, it is recommended to use up to 10 % PPA either with stone aggregate or brick aggregate for structural concrete. Finally, this study will open new opportunities for producing green concrete by using non-biodegradable waste plastic materials.

Objectives: The main objectives of this study were to examine the prevalence of workplace violence (WPV), its associated factors and explore the experiences of healthcare workers.Methods: A hospital-based cross-sectional study design used a nationally representative sample of 1,081 healthcare workers covering eight administrative divisions of Bangladesh. Logistic regression analysis was employed to estimate the adjusted effect of independent factors on WPV among healthcare workers.Results: Of the participants, 43% (468) experienced some form of WPV. Of those, 84% reported experiencing nonphysical violence, and 16% experienced physical violence in the past year. About 65% of victims claimed no action was taken to investigate the incident, and 44% reported no consequence for perpetrators. Four factors: being married (AOR = 1.63; CI: 1.12–2.39); public sector healthcare worker (AOR = 2.74; CI:1.99–3.76); working in an emergency department (AOR = 2.30; CI:1.03–5.12); and undertaking shift work (AOR = 1.52; CI: 1.10–2.11) were found to be significantly associated with WPV. One-third of the participants were worried about violence in their workplace.Conclusion: WPV is highly prevalent among healthcare workers in Bangladesh. Formal guidelines for reporting and managing WPV are urgently needed at the individual, hospital, and national levels.

The quantization of black hole parameters is a long-standing topic in physics. Adiabatic invariance, periodicity of outgoing waves, quantum tunneling, and quasi-normal modes are the typical tools via which the area and the entropy of a black hole are quantized. In this paper, the quantum spectra of area and entropy of quantum-corrected Schwarzschild black hole are investigated. The deformation in the space–time of Schwarzschild black hole was perused by Kazakov and Solodukhin. Here the deformed Schwarzschild metric is taken into account, and the effect of the space–time modification on the minimal area and entropy increment for the Schwarzschild black hole is scrutinized, utilizing two different procedure: Jiang-Han's method of the adiabatic invariant integral and Zeng et al.'s approach of the periodic property of outgoing waves. The analyses of this paper draw the conclusion that the quantum correction to the space–time does not alter the quantum characteristics of the Schwarzschild black hole.

Considering a quantum correction due to vacuum fluctuation in the Schwarzschild space–time with quintessence, the thermodynamic properties such as mass, temperature, heat capacity–as functions of entropy, are studied. Also the equation of state of the black hole is derived. Furthermore, the results of the quantum-corrected Schwarzschild black hole surrounded by quintessence field are compared with the conventional Schwarzschild black hole with quintessence and the quantum-corrected Schwarzschild black hole without quintessence.

Developing a high-speed elliptic curve cryptographic (ECC) processor that performs fast point multiplication with low hardware utilization is a crucial demand in the fields of cryptography and network security. This paper presents field-programmable gate array (FPGA) implementation of a high-speed, low-area, side-channel attacks (SCAs) resistant ECC processor over a prime field. The processor supports 256-bit point multiplication on recently recommended twisted Edwards curve, namely, Edwards25519, which is used for a high-security digital signature scheme called Edwards curve digital signature algorithm (EdDSA). The paper proposes novel hardware architectures for point addition and point doubling operations on the twisted Edwards curve, where the processor takes only 516 and 1029 clock cycles to perform each point addition and point doubling, respectively. For a 256-bit key, the proposed ECC processor performs single point multiplication in 1.48 ms, running at a maximum clock frequency of 177.7 MHz in a cycle count of 262 650 with a throughput of 173.2 kbps, utilizing only 8873 slices on the Xilinx Virtex-7 FPGA platform, where the points are represented in projective coordinates. The implemented design is time-area-efficient as it offers fast scalar multiplication with low hardware utilization without compromising the security level.

Embedding optical camera communication (OCC) commercially as a favorable complement of radio-frequency technology has led to the desire for an intelligent receiver system that is eligible to communicate with an accurate light-emitting diode (LED) transmitter. To shed light on this issue, a novel scheme for detecting and recognizing data transmitting LEDs has been elucidated in this paper. Since the optically modulated signal is captured wirelessly by a camera that plays the role of the receiver for the OCC technology, the process to detect LED region and retrieval of exact information from the image sensor is required to be intelligent enough to achieve a low bit error rate (BER) and high data rate to ensure reliable optical communication within limited computational abilities of the most used commercial cameras such as those in smartphones, vehicles, and mobile robots. In the proposed scheme, we have designed an intelligent camera receiver system that is capable of separating accurate data transmitting LED regions removing other unwanted LED regions employing a support vector machine (SVM) classifier along with a convolutional neural network (CNN) in the camera receiver. CNN is used to detect every LED region from the image frame and then essential features are extracted to feed into an SVM classifier for further accurate classification. The receiver operating characteristic curve and other key performance parameters of the classifier have been analyzed broadly to evaluate the performance, justify the assistance of the SVM classifier in recognizing the accurate LED region, and decode data with low BER. To investigate communication performances, BER analysis, data rate, and inter-symbol interference have been elaborately demonstrated for the proposed intelligent receiver. In addition, BER against distance and BER against data rate have also been exhibited to validate the effectiveness of our proposed scheme comparing with only CNN and only SVM classifier based receivers individually. Experimental results have ensured the robustness and applicability of the proposed scheme both in the static and mobile scenarios.

With the swift evolution of wireless technologies, the demand for the Internet of Things (IoT) security is rising immensely. Elliptic curve cryptography (ECC) provides an attractive solution to fulfill this demand. In recent years, Edwards curves have gained widespread acceptance in digital signatures and ECC due to their faster group operations and higher resistance against side-channel attacks (SCAs) than that of the Weierstrass form of elliptic curves. In this paper, we propose a high-speed, low-area, simple power analysis (SPA)-resistant field-programmable gate array (FPGA) implementation of ECC processor with unified point addition on a twisted Edwards curve, namely Edwards25519. Efficient hardware architectures for modular multiplication, modular inversion, unified point addition, and elliptic curve point multiplication (ECPM) are proposed. To reduce the computational complexity of ECPM, the ECPM scheme is designed in projective coordinates instead of affine coordinates. The proposed ECC processor performs 256-bit point multiplication over a prime field in 198,715 clock cycles and takes 1.9 ms with a throughput of 134.5 kbps, occupying only 6543 slices on Xilinx Virtex-7 FPGA platform. It supports high-speed public-key generation using fewer hardware resources without compromising the security level, which is a challenging requirement for IoT security.

This study was performed to compare the marginal microleakage of ormocer restorative material with that of giomer in vivo. Forty Class I cavities were prepared in non-carious permanent premolar teeth from 10 patients. Twenty cavities were filled with giomer and the remaining 20 cavities were filled by ormocer restorative materials. After one month, teeth were extracted, immersed in rhodamine dye solution, and then longitudinally bisected to assess the degree of dye penetration by stereoscopy. Furthermore, the gap between the dental material and tooth tissue were observed by the scanning electron microscope. The results showed that no microleakage (score 0) was detected in 15 ormocer and 5 giomer restorations. The remaining restorations were associated with dye penetration which was due to gap formation as seen in stereoscopic and scanning electron microscopic observations. The differences between ormocer and giomer restorative materials in respect to dye penetration were statistically significant. It can be concluded that ormocer restorative material shows less microleakage than that of giomer.

The purpose of the present study was to compare the marginal integrity of resin modified glass ionomer cement with that of resin sealant, in vitro. Forty artificial pit and fissure cavities were prepared in occlusal surface of extracted premolar teeth by using ¼ round carbide bur. Cavities were condensed with artificial organic debris followed by cleaning with prophylaxis pumice brush and paste and then separated into two treatment groups. In Group A, 15 fissure cavities were sealed by resin sealant and in Group B, 15 fissure cavities were sealed by resin modified glass ionomer sealant. These specimens were subjected to thermo-cycling followed by dye penetration test. The remaining 5 cavities from each group were analyzed for debris score by the SEM. The results of the microleakage test showed that the efficacy of preventing microleakage of samples sealed by resin modified glass ionomer sealant was higher than the samples sealed by resin sealant. However, no significant differences were found. It can be concluded that use of resin modified glass ionomer sealant is a good alternative for sealing pits and fissures.

The upcoming fifth- and sixth-generation (5G and 6G, respectively) communication systems are expected to deal with enormous advances compared to the existing fourth-generation communication system. The few important and common issues related to the service quality of 5G and 6G communication systems are high capacity, massive connectivity, low latency, high security, low-energy consumption, high quality of experience, and reliable connectivity. Of course, 6G communication will provide several-fold improved performances compared to the 5G communication regarding these issues. The Internet of Things (IoT) based on the tactile internet will also be an essential part of 5G-and-beyond (5GB) (e.g., 5G and 6G) communication systems. Accordingly, 5GB wireless networks will face numerous challenges in supporting the extensive verities of heterogeneous traffic and in satisfying the mentioned service-quality-related parameters. Optical wireless communication (OWC), along with many other wireless technologies, is a promising candidate for serving the demands of 5GB communication systems. This review paper clearly presents how OWC technologies, such as visible light communication, light fidelity, optical camera communication, and free space optics communication, will be an effective solution for successful deployment of 5G/6G and IoT systems.

Research on electronic healthcare (eHealth) systems has increased dramatically in recent years. eHealth represents a significant example of the application of the Internet of Things (IoT), characterized by its cost effectiveness, increased reliability, and minimal human eff ort in nursing assistance. The remote monitoring of patients through a wearable sensing network has outstanding potential in current healthcare systems. Such a network can continuously monitor the vital health conditions (such as heart rate variability, blood pressure, glucose level, and oxygen saturation) of patients with chronic diseases. Low-power radio-frequency (RF) technologies, especially Bluetooth low energy (BLE), play significant roles in modern healthcare. However, most of the RF spectrum is licensed and regulated, and the effect of RF on human health is of major concern. Moreover, the signal-to-noise-plus-interference ratio in high distance can be decreased to a considerable extent, possibly leading to the increase in bit-error rate. Optical camera communication (OCC), which uses a camera to receive data from a light-emitting diode (LED), can be utilized in eHealth to mitigate the limitations of RF. However, OCC also has several limitations, such as high signal-blockage probability. Therefore, in this study, a hybrid OCC/BLE system is proposed to ensure efficient, remote, and real-time transmission of a patient’s electrocardiogram (ECG) signal to a monitor. First, a patch circuit integrating an LED array and BLE transmitter chip is proposed. The patch collects the ECG data according to the health condition of the patient to minimize power consumption. Second, a network selection algorithm is developed for a new network access request generated in the patch circuit. Third, fuzzy logic is employed to select an appropriate camera for data reception. Fourth, a handover mechanism is suggested to ensure efficient network allocation considering the patient’s mobility. Finally, simulations are conducted to demonstrate the performance and reliability of the proposed system.

Optical camera communication (OCC) is a technology in which a camera image sensor is employed to receive data bits sent from a light source. OCC has attracted a lot of research interest in the area of mobile optical wireless communication due to the popularity of smartphones with embedded cameras. Moreover, OCC offers high-performance characteristics, including an excellent signal-to-interference-plus-noise ratio (SINR), high security, low interference, and high stability with respect to varying communication distances. Despite these advantages, OCC suffers from several limitations, the primary of which is the low data rate. In this paper, we provide a comprehensive analysis of the parameters that influence the OCC performance. These parameters include the camera sampling rate, the exposure time, the focal length, the pixel edge length, the transmitter configurations, and the optical flickering rate. In particular, the focus is on enhancing the data rate, SINR, and communication distance, which are the principal factors determining the quality of service experienced by a user. The paper also provides a short survey of modulation schemes used in OCC on the basis of the achieved data rate, communication distance, and possible application scenarios. A theoretical analysis of user satisfaction using OCC is also rendered. Furthermore, we present the simulation results demonstrating OCC performance with respect to variations in the parameters mentioned above, which include the outage probability analysis for OCC.

An experiment was conducted for a period of 75 days at farmers house to investigate the effect of feeding duckweed (Lemna perpusilla) that replaced conventional protein supplement mustard oil cake (MOC) in the diets for Jinding ducks. The experiment included a total of 84 laying ducks with four treatments and three replicates and seven ducks per replicate. The diets were based on rice by products where soybean meal and mustard oil cake as protein source. The control diet A contained 15% MOC and 5, 10 and 15% MOC was replaced with dry duckweed in diets B, C and D respectively. The birds were raised under extensive system and feeds were supplied two times daily before and after herded. The replacement of MOC by duckweed non-significantly depressed live weight gain (P>0.05), egg weight (P>0.05) and feed conversion efficiency (P>0.05) but significantly increased egg production (P

Objective: Dietary protein restriction induces adaptive changes in food preference, increasing protein consumption over carbohydrates or fat. We investigated whether motivation and reward signaling underpin these preferences. Methods and Results: In an operant task, protein-restricted male mice responded more for liquid protein rewards, but not carbohydrate, fat, or sweet rewards compared to non-restricted mice. When the number of responses required to access protein reward varied, protein-restricted mice exhibited higher operant responses at moderate to high response requirements. The protein restriction-induced increase in operant responding for protein was absent in Fgf21-KO mice and mice with neuron-specific deletion of the FGF21 co-receptor beta-Klotho (KlbCam2ka). Fiber photometry recording of VTA dopamine neurons revealed that oral delivery of maltodextrin triggered a larger dopamine neuron activation than casein in control diet-fed mice, while casein triggered a larger activation in low-protein diet-fed mice. This restriction-induced shift in nutrient-specific VTA dopamine signaling was lost in Fgf21-KO mice. Conclusion: These data suggest that the increased FGF21 during protein restriction acts in the brain to induce a protein-specific appetite by specifically enhancing the reward value of protein-containing foods and the motivation to consume them.