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Abstract The use of antimicrobial drugs in food-producing animals contributes to the selection pressure on pathogenic and commensal bacteria to become resistant. This study aims to evaluate the existence of trade-offs between treatment effectiveness, cost, and the dynamics of resistance in gut commensal bacteria. We developed a within-host ordinary differential equation model to track the dynamics of antimicrobial drug concentrations and bacterial populations in the site of infection (lung) and the gut. The model was parameterized to represent enrofloxacin treatment for bovine respiratory disease (BRD) caused by Pastereulla multocida in cattle. Three approved enrofloxacin dosing regimens were compared for their effects on resistance on P. multocida and commensal E. coli: 12.5 mg/kg and 7.5 mg/kg as a single dose, and 5 mg/kg as three doses. Additionally, we explored non-FDA-approved regimes. Our results indicated that both 12.5 mg/kg and 7.5 mg/kg as a single dose scenario increased the most the treatment costs and prevalence of P. multocida resistance in the lungs, while 5 mg/kg as three doses increased resistance in commensal E. coli bacteria in the gut the most out of the approved scenarios. A proposed non-FDA-approved scenario (7.5 mg/kg, two doses 24 h apart) showed low economic costs, minimal P. multocida, and moderate effects on resistant E. coli. Overall, the scenarios that decrease P. multocida, including resistant P. multocida did not coincide with those that decrease resistant E. coli the most, suggesting a trade-off between both outcomes. The sensitivity analysis suggests that bacterial populations were the most sensitive to drug conversion factors into plasma ( $${\beta}$$ β ), elimination of the drug from the colon ( $$\vartheta$$ ϑ ), fifty percent sensitive bacteria (P. multocida) killing effect ( $${\text{L}}_{\text{s50}}$$ L s50 ), fifty percent of bacteria (E. coli) above ECOFF killing effect ( $${\text{C}}_{\text{r50}}$$ C r50 ), and net drug transfer rate in the lung ( $$\gamma$$ γ ) parameters.

Abstract Background Both dengue and Leptospira infections are endemic to tropical and subtropical regions, with their prevalence increasing in recent decades. Coinfection with these pathogens presents significant diagnostic challenges for clinicians due to overlapping clinical manifestations and laboratory findings. This case report aims to elucidate two clinical scenarios where the coinfection of dengue and leptospirosis complicates the disease course, creating a diagnostic conundrum. Case presentation We present the clinical scenarios of two Bangladeshi males, aged 25 and 35 years, who were admitted to our hospital with acute febrile illness. The first patient exhibited hepatic and renal involvement, while the second presented with symptoms initially suggestive of meningoencephalitis. Both cases were initially managed under the presumption of dengue infection based on positive serology. However, further evaluation revealed coinfection with Leptospira, complicating the disease course. Both patients received appropriate treatment for dengue and antibacterial therapy for leptospirosis, ultimately resulting in their recovery. Conclusion These case scenarios underscore the critical importance for clinicians in regions where dengue and Leptospira are endemic to consider both diseases when evaluating patients presenting with acute febrile illness.

The present world is on the good track to achieve economic growth though it results in huge environmental degradation. Hence, such economic growth poses serious detrimental impacts on human health, and it causes to increase in healthcare spending. Therefore, the present study aims to depict the relationship among carbon dioxide (CO2) emission, healthcare spending and economic growth for the South Asian countries (SAARC member countries) covering the period 1980-2014. The Dynamic Simultaneous-equation Model is fitted with the data set which is estimated by Generalized Method of Moment for investigating the causal relationship among these variables. The empirical results reveal bidirectional causality between carbon dioxide (CO2) emission and economic growth; and between economic growth and health spending. The results of the study also indicate unidirectional causality from carbon dioxide (CO2) and health spending in case of many SAARC member countries.

Abstract This study evaluated the performance of multiple models that used machine learning to anticipate wind speed in the city of Dhaka. The NASA Power website provided the data set for this investigation. The models used for prediction included the decision tree regressor, support vector regressor, random forest, linear regression, neural network and polynomial regression. A hold-out check and k-fold cross-validation were used to assess how well these models performed. With the highest R2 scores and lowest RMSEs on both the validation and test sets, the results demonstrated that the polynomial regression model performed the best. With the lowest R2 scores and largest RMSEs on both sets, the decision tree model scored the poorest. High R2 scores and low RMSEs were achieved by the random forest model, which had comparable performance to the polynomial regression model but required a longer computation time. In addition, the neural network model demonstrated commendable predictive accuracy, yielding an R2 score of 0.67 and a low RMSE of 0.57. However, its application is contingent on the availability of substantial computational resources, given its extensive computation time of 457.93 s. The study concludes by highlighting the efficacy of the Polynomial Regression model as the optimal choice for wind speed prediction in Dhaka, offering a balance between superior performance and efficient computation. This insight provides valuable guidance for practitioners and researchers seeking effective models for similar applications.

Abstract Background In Bangladesh, the most prevalent musculoskeletal condition among office employees is considered as BlackBerry thumb (BBT). Alike official perspectives, our educational system was significantly regulating with the digital interfaces at COVID-19 lockdown, where a greater reliance on Android phones were experienced among the adults. Numerous studies have been conducted in studying the incidences of BBT in young individuals as a result of hazards of Android phone usage (HAPU) in Bangladesh. Objective This research sought to determine the relationship between BBT symptoms and the risks associated with the using Android phones among Bangladeshi university students. Methods A nationwide cross-sectional study was undertaken on a group of university students between the ages of 18 and 25 to determine if BBT symptoms were present based on the Finkelstein test and HAPU, which were also assessed using a well-designed questionnaire. We calculated the crude and adjusted prevalence ratios (aPR) and used a generalized linear model from the Poisson family, using their respective 95% confidence intervals (CI). Results There were 2455 individuals in this research, with a median age of 20 and an interquartile range (IQR) of 19 to 23. Of them, 1185 males (48.27%) and 1270 women (51.75%) made up the study’s participant population. Physical exams showed that 1300 individuals had positive Finkelstein test results (52.95%), whereas 1040 people had occasional risks from using an Android phone and 115 participants had occasional risks from using an iPhone. In our generalized linear model, we observed that participants with occasional and frequent HAPU had higher rates of BBT symptoms than responders without HAPU (aPR = 1.73, 95% CI: 1.47–2.05, and aPR = 1.61, 95% CI: 1.29–2.00), respectively. Conclusion The current study found that Bangladeshi university students experiencing BlackBerry thumb symptoms were more likely to have risks associated with using Android phones.

This paper presented the design and performance analysis of a high-gain balanced antipodal Vivaldi antenna (BAVA) integrated with a parasitic patch and a half-spherical shaped dielectric lens, specifically designed for microwave and millimeter-wave applications. Constructed with a Teflon substrate (εr = 2.1, tanδ = 0.0002) and energized by a 50-Ω microstrip feedline, the innovative design incorporated a parasitic patch and three different types of dielectric lenses: half-circular, conical, and half-spherical shaped. The half-spherical dielectric lens significantly enhanced performance, achieving a gain of 20.54 dB, side lobe level (SLL) of −18.15 dB, and a maximum beam squint of 1.59°. Additionally, it exhibited a 98% radiation efficiency, a front-to-back ratio of 31.75 dB, and a half-power beamwidth (HPBW) of 6.7°. The incorporation of a parasitic patch and a half-spherical shaped dielectric lens enhanced the antenna's performance. Comparative analysis with existing antennas underscored the superiority of the proposed design, positioning it as a promising solution for microwave and millimeter-wave communication systems, radar, and sensing applications.

Enterococcus faecalis are often resistant to different classes of antibiotics, harbor virulence determinants, and produce biofilm. The presence of E. faecalis in raw seafood exhibits serious public health significance. This study aimed to identify antibiotic resistance patterns and virulence factors in biofilm-forming E. faecalis strains extracted from seafood in Bangladesh. A total of 150 samples of raw seafood, comprising 50 shrimps, 25 crabs, and 75 fish, were collected and subjected to culturing, biochemical, and PCR assays to detect E. faecalis. The biofilm-forming abilities of the isolates were determined by Congo Red agar (CRA) plate and Crystal Violet Micro-titer Plate (CVMP) tests. Antibiotic resistance profiles were evaluated using the disk diffusion method. Virulence genes of the isolates were detected by PCR assay. The occurrence of E. faecalis was 29.3 % (44/150), which was higher in crabs and fish (36 %) than in shrimps (16 %). In CRA and CVMP tests, biofilm-forming abilities were observed in 88.64 % of the isolates, whereas 11 (25 %) and 28 (63.6 %) were strong- and intermediate-biofilm formers, respectively. All the isolates contained at least two virulence genes, including pil and ace (97.7 %), sprE (95.5 %), gelE (90.9 %), fsrB (79.6 %), agg (70.5 %), fsrA (68.2 %), and fsrC (61.4 %). All the isolates were phenotypically resistant to penicillin, followed by ampicillin and rifampicin (86.4 %), erythromycin (13.7 %), and tetracycline, vancomycin, norfloxacin, and linezolid (2.3 %). Resistant gene blaTEM was found in 61.4 % of the isolates. Moreover, the study found that E. faecalis strains with strong biofilm-forming capabilities had significantly higher levels of virulence genes and antibiotic resistance (p

Abstract Wireless power transfer (WPT) is a promising technology that has the potential to revolutionize the present methods of power transmission. This paper aims to provide an overview of WPT, including its history, a comparative review of methods, and a review of recent papers about WPT. We discussed different methods of WPT, such as inductive power transmission, capacitive power transmission, optical power transmission, and microwave power transmission. The research briefly discusses the applications, challenges, and opportunities of WPT. The study's findings suggest that WPT can serve as a feasible substitute for traditional wired power transmission. This technology has the potential to offer several advantages, including enhanced convenience, decreased expenses, and heightened safety.

Abstract This study gives a thorough analysis on the wind energy potential in Dhaka, Bangladesh, utilizing data from NASA Power's remote sensing tools and weather data from the Bangladesh Meteorological Department (BMD). The wind speed data collected over a 22 year period at an altitude of 10 m. The results indicate that 3.07 m per second (ms−1) is Dhaka city's typical wind speed, while the maximum wind speeds were recorded in June and July. A Weibull distribution is used to observe the wind data, as well as to calculate the Weibull form parameter of 2.65 and the scale parameter of 3.43 ms−1. Based on these parameters, the most probable wind speed along with the wind speed carrying maximum energy were calculated 2.83 ms−1 and 4.28 ms−1, respectively. The highest density of energy has been found in the month of July with a value of 52.11 W/m2. According to the study, the south is the most prominent wind direction for Dhaka city. Moreover, the study analyzes the relations between energy density and other variables, like wind speed, humidity, dry bulb temperature, etc. Positive correlations between energy density, wind speed, and dry bulb temperature imply that the higher wind speeds and dry bulb temperatures result in greater energies. The study's conclusions offer intuitive information about Dhaka City's potential for wind energy and can support direct future efforts to pursue this green resource in alignment with the Sustainable Development Goals (SDGs) of Bangladesh.

Sodium alginate extracted from Sargassum oligocystum brown seaweed alga is an important blue economy development process of the Bay of Bengal. In the present study, sodium alginate was extracted from the brown seaweed alga collected from the Cox’s Bazar coastal area of the Bay of Bengal. The extracted product was characterized with the Ultraviolet-visible (UV–visible) spectrophotometer, Fluorescence spectrophotometer, Fourier transform-infrared radiation (FT-IR) spectrophotometer, X-ray diffractometer (XRD), and Scanning electron microscope (SEM). The product yield was optimized with different pH levels and the maximum yield was obtained at 32.5 % at pH 10.96. The moisture, and ash content of the extracted product was measured and found at 13.25 % and 4.35 %, respectively. The viscosity of the extracted product was obtained at 60.1 mPs. The UV–visible spectrophotometry showed different absorbance peaks found at 234 nm, 240 nm, 250 nm, and 264 nm which assigned the extracted product of sodium alginate, and the maximum absorption peak lies at 276.7 nm which assigned flavonoids, and their derivatives of alginates. The fluorescence spectrophotometry demonstrated a strong emission peak at 460 nm with higher intensity (200), indicating the presence of sodium alginate. The FTIR showed the characteristic peaks that demonstrated different functional groups of sodium alginate. The XRD pattern demonstrated 0.24 crystalline indexes indicating the semi-crystalline product in nature. SEM showed clear fibrils of sodium alginate morphology indicating the absence of impurity materials.

The main purpose of this paper is to investigate the environmental repercussions of a booming economy, fossil fuel, renewable energy, globalisation, technological innovation, and forest cover in Poland from 1990 to 2018. This study used greenhouse gas (GHG) emissions and load capacity factor as proxies of ecological damage to provide a comprehensive assessment of the surrounding ecosystem in Poland to help implement future policies to reduce emissions and achieve environmental sustainability. Besides, Poland is the only European Union (EU) country lacking a climate neutrality objective and policy instruments to mitigate ecological concerns. The Autoregressive Distributed Lag (ARDL) bounds model and the Dynamic Ordinary Least Squares (DOLS) procedure evaluated yearly data from 1990 to 2018. The empirical outcomes of the DOLS point out that economic growth and fossil fuel energy use enhance GHG emissions despite reducing the load capacity factor in Poland. Instead, renewable power, globalisation, technological innovation, and forest cover might help to reduce GHG emissions and enhance the load capacity factor in Poland. The concluding thoughts from this study suggest the implementation of policies that support raising additional funding for eco-friendly technology studies while promoting renewable energy use and enhancing forest carbon sinks.

ABSTRACTGlaucoma encompasses a spectrum of disorders characterized by the chronic degeneration of retinal ganglion cell (RGC) axons and the progressive loss of RGCs, resulting in visual impairment. In this study, we investigated the effect of autophagy deficiency on two glaucoma hypertensive models, the DBA/2J spontaneous glaucoma model, and the TGFβ2 (transforming growth factor β2) chronic ocular hypertensive model. For this, we used the Atg4b−/− and DBA/2J-Atg4b−/− mice, this latter generated in our laboratory via CRISPR/Cas9 technology, which display impaired autophagy. In contrast to littermate WT controls, mice deficient in Atg4B, did not develop glaucomatous elevation of intraocular pressure (IOP). Moreover, autophagy deficiency protected against RGC death and optic nerve atrophy. Collectively, our data supports a pathogenic role of autophagy in the context of ocular hypertension and glaucoma.Abbreviations: ATG4B: Autophagy-related 4B; BAX: BCL2-associated X protein; BECN1: Beclin 1; BID: BH3 interacting domain death agonist; CASP8: Caspase 8; IOP: Intraocular Pressure; MAP1LC3B: microtubule-associated proteins 1B; ON: Optic Nerve; RGC: Retinal Ganglion Cells; SQSTSM1: Sequestosome 1; TBK1: TANK-binding kinase 1; TGFβ2: Transforming Growth Factor β2; WT: Wild Type.

Summary: Persistent DNA-protein crosslinks formed by human topoisomerase IIIα (TOP3A-DPCs) interfere with DNA metabolism and lead to genome damage and cell death. Recently, we demonstrated that such abortive TOP3A-DPCs are ubiquitylated and proteolyzed by Spartan (SPRTN). Here, we identify transient poly(ADP-ribosylation) (PARylation) in addition to ubiquitylation as a signaling mechanism for TOP3A-DPC repair and provide evidence that poly(ADP-ribose) polymerase 1 (PARP1) drives the repair of TOP3A-DPCs by recruiting flap endonuclease 1 (FEN1) to the TOP3A-DPCs. We find that blocking PARylation attenuates the interaction of FEN1 and TOP3A and that TOP3A-DPCs accumulate in cells with compromised PARP1 activity and in FEN1-deficient cells. We also show that PARP1 suppresses TOP3A-DPC ubiquitylation and that inhibiting the ubiquitin-activating enzyme E1 (UBE1) increases TOP3A-DPCs, consistent with ubiquitylation serving as a signaling mechanism for TOP3A-DPC repair mediated by SPRTN and TDP2. We propose that two concerted pathways repair TOP3A-DPCs: PARylation-driven FEN1 excision and ubiquitylation-driven SPRTN-TDP2 excision.

Using three-dimensional (3D) printing technologies, two of the folded electrically small antennas (FESAs) are simulated, fabricated, and evaluated. A folded spherical helix and a cylindrical helix are chosen as a part of the verification of this fabrication process. FESAs are constructed on the polylactic acid (PLA) material-based 3D printed support and the effect of this extra support on antenna performances are discussed. The similarity index between measured and simulated performance parameters of both spherical helix and cylindrical helix shaped FESAs is high. The fabrication process is faster, dependable and provides the design flexibility of any complex-shaped spiral antenna.

Global warming, induced by human-generated greenhouse gases, especially carbon dioxide (CO2), threatens the planet's ecology, economic development, and long-term viability in unparalleled ways. Vietnam's utilization of energy and CO2 emanations are on the increase as a consequence of the country's increasing economic and improving agricultural practices. Governments seeking to accomplish an equilibrium between combating climate change and sustainable development would benefit from a deeper understanding of Vietnam's climate change vulnerability. A better understanding of the trade-off between pollution and economic growth is crucial if Vietnam is to slow the rate at which its environment is being damaged. So, the current study empirically examined the connections between GDP development, energy consumption, technical advancement, agricultural output, forest region, and carbon dioxide emissions in Vietnam. This study collected annual data from 1990 to 2020 and analyzed it using the Dynamic Ordinary Least Squares method. Based on the projection, Vietnam experiences a direct correlation between energy consumption and CO2 emissions. This implies that an increase in energy consumption and economic growth corresponds to a corresponding emission of carbon dioxide into the atmosphere. Nevertheless, it is essential to acknowledge that this pattern might be alleviated by means of technological innovations, increased agricultural output, and initiatives to broaden forested regions. A negative correlation exists between these variables and CO2 emissions; technological innovations, more sustainable agricultural methods, and forest preservation initiatives may contribute to the gradual reduction of CO2 emissions. Therefore, environmental sustainability could be achieved through reduced emissions if the policies advocated in this article were implemented. Some of these policies include using renewable energy sources, encouraging innovations in technology, encouraging climate-conscious agriculture, and encouraging careful forest management.

South Asia is the most polluted region in the world and is struggling to deal with the effects of growing CO2 emissions and the ecological impact it has left. The region needs to identify the variables that are most effective in reducing pollution in order to achieve long-term sustainable growth. The current study aims to investigate the environmental impacts of the current and projected urbanization rate, the service sector, and the availability of natural resources to test the environmental Kuznets-curve (EKC) theory in six South Asian countries (SAARC). With cross-sectional dependence present, this research examines panel data from 1972 to 2021 using the newly developed Driscoll Kraay Standard Error (DKSE) approach. To check the robustness of DKSE estimation, the study employs a novel Cross Sectional Autoregressive Distributive Lag (CS-ARDL) method. The results of DKSE show that GDP significantly minimizes CO2 emissions in both the short and long run. At the same time, GDP2, urbanization, and the service sector increase CO2 emissions in the South Asian region. The DKSE estimator also shows that industrialization and abundant natural resources have insignificant impacts on CO2 emissions. Inconsistent with the EKC hypothesis, the findings show that higher economic growth leads to increased environmental pollution and CO2 levels. Meanwhile, the CS-ARDL analysis found that GDP and industrialization reduce CO2 emissions, while urbanization, GDP2, and natural resource availability increase CO2 emissions. This research emphasizes the need for establishing appropriate industrialization and urbanization strategies and promoting cleaner energy adoption to reduce CO2 emissions.

The study analysed the impact of tourism, trade, consumption expenditure, electricity usage, and population on carbon dioxide emissions (CO2) in leading tourist destinations. The study uses a panel dataset of 32 countries from different continents between 2001 and 2020 and applies the generalized method of moments (GMM) and Quantile Regression approaches. The results suggest that tourism (arrivals and revenues) can reduce environmental degradation, and that CO2 emissions increase due to factors such as GDP per capita, electricity consumption, and population growth. Trade openness can reduce CO2 emissions, and controlling for final consumption also indicates a decrease in CO2 emissions. The study suggests that sustainable tourism practices, responsible consumption, and larger international integration may play a role in mitigating CO2 emissions. Leading tourist destinations should develop sustainable urban areas to accommodate population growth, and embrace eco-friendly technologies, infrastructure, and consumption patterns to promote sustainable economic growth while reducing CO2 emissions.

This study aims to investigate the long-term relationship between Malaysian tourism, energy consumption, and their association with economic growth, and financial development, using the Autoregressive Distributed Lag (ARDL) method. Utilizing annual data spanning from 1990 to 2020, this research examines how increased international tourist arrivals, economic growth, and financial development contribute to energy consumption in Malaysia. The study's findings reveal that growing tourism escalates energy demands for transportation, accommodation, and leisure activities. Furthermore, economic expansion drives energy usage through business expansion and increased industrial activities. Financial progress facilitates capital accessibility, leading to investments in energy-intensive sectors. In conclusion, to ensure sustainable future energy demand, this study underscores the importance of eco-friendly tourism practices that stimulate economic growth while minimizing emissions. Sustainable economic and financial strategies are also essential.

Sustainable agriculture is an important target of the Sustainable Development Goals (SDGs). Information and communication technologies (ICT) could be an important instrument to assist developing countries in achieving this goal. This study investigates the short- and long-term effects of ICT-related factors (telephone, Internet, mobile phone use) alongside traditional inputs (agricultural land, labor, fertilizer) on sustainable agricultural production in Bangladesh using an autoregressive distributed lag (ARDL) model from 2000 to 2020. In the short term, telephone use and labor involved in agriculture have a positive impact on agricultural production. Conversely, the influence of internet use, mobile phone use, and agricultural land on agricultural production is negative in the short run. In the long run, these relationships have undergone substantial changes. The positive effects of telephone usage and agricultural labor demonstrate a decreasing trend, but the impacts of Internet usage, mobile phone usage, and total agricultural land display a progressively favorable pattern in the long run. Notably, the use of fertilizers has been found to have a positive impact on long-term agricultural production. This study offers valuable insights into the evolving role of ICT in agricultural sustainability, emphasizing the need for context-specific policy interventions that consider both short- and long-term benefits. Doi: 10.28991/HEF-2023-04-04-01 Full Text: PDF

The energy demand in Australia is increasing with the industrialization and rapid economic growth. This study analyzed the relationships among the economic growth, Foreign Direct Investment (FDI), trade openness, urbanization, and energy usage in Australia based on the data from World Development Indicators (WDI) from 1972 to 2021. The results indicated that there is a cointegration among economic growth, FDI, trade openness, urbanization, and energy usage, which was traced through the autoregressive-distributed lag (ARDL). The Zivot-Andrews unit root test reveals that energy usage, economic growth, FDI, urbanization, and trade openness show significant structural breaks in 1993, 1996, 1982, 2008, and 1994, respectively. The ARDL model shows that economic growth has a positive and significant effect on energy usage in the long-run (0.814) and short-run (0.809). Moreover, the results also show that FDI (0.028) and trade openness (0.043) have positive impacts on energy usage in the long-run. However, urbanization shows a negative and significant influence on energy usage in the long-run (−0.965). Then, the research demonstrates a unidirectional causation between energy usage and trade openness, with energy usage significantly causing trade openness. The current study endorses energy consumption policies and investment strategies for a paradigm shifting from a reliance on fossil fuels as the primary energy source to renewable energy sources. These findings have profound implications for sustainable energy usage.

Antimicrobial resistance (AMR), also known as antibiotic resistance, is a global health crisis. Many people die from diseases caused by multi-drug resistant pathogens (MDR). Artificial intelligence (AI) deals with applying theory and developing computer systems to conduct tasks usually requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages to solve problems. AI has been successfully used in various fields, from single-cell study to space science. There is huge potential for using AI in medical science, including fighting against MDR to combat AMR. In this review, we have highlighted some of AI's successful uses and potentiality to combat AMR for the betterment of the human race, including the basic principles of AI, available AI resources, use and scope, advantages and limitations. [ J Adv Biotechnol Exp Ther 2023; 6(3.000): 711-727]