How biotic, abiotic, and functional variables drive belowground soil carbon stocks along stress gradient in the Sundarbans Mangrove Forest?

Mangrove forests, some of the most carbon-dense ecosystems on Earth, play an important role in climate change mitigation through storing carbon in the soil. However, increasing anthropogenic pressures and sea level rise are likely to alter mangrove forest structure and functions, including the major source of carbon in mangrove ecosystems - below-ground soil carbon stocks (BSCS). Although estimating soil carbon stocks has been a popular practice in the mangroves, but poorly understood the (I) the linkage between BSCS and key ecosystem drivers (i.e., biotic, abiotic, and functional) and in (II) determining the pathways of how BSCS and multiple forest variables interact along stress gradients. This lack of understanding limits our ability to predict ecosystem carbon dynamics under future changes in climate. Here, we aimed to understand how abiotic factors (such as salinity, canopy gap fraction, nutrients, and soil pH), biotic factors (e.g., structural parameters, canopy packing, and leaf area index, LAI), and forest functional variables (e.g., growth and aboveground biomass stocks, AGB) affect BSCS (i.e., soil organic carbon, SOC, and root carbon, RC) using spatiotemporal data collected from the Sundarbans Mangrove Forest (SMF) in Bangladesh. We observed that BSCS decreased significantly with increasing salinity (e.g., from 70.6 Mg C ha-1 in the low-saline zone to 44.6 Mg C ha-1 in the high-saline zone). In contrast, the availability of several macronutrients (such as nitrogen, phosphorous, and potassium), LAI, species diversity, AGB, and growth showed a significant positive effect on SOC and RC. Stand properties, including tree height, basal area, density, canopy packing, and structural diversity, had a non-significant but positive impact on RC, while tree height and basal area significantly influenced SOC. Pathway analysis showed that salinity affects BSCS variability directly and indirectly by regulating stand structure and restricting nutrients and forest functions, although basal area, nutrients, and LAI directly enhance RC stocks. Our results indicate that an increase in nutrient content, canopy density, species diversity, and leaf area index can enhance BSCS, as they improve forest functions and contribute to a better understanding of the underlying mechanisms.

Effects of hydrocarbon chain on the vesicle size distribution, kinetics of average size, bending modulus, and elastic modulus of lipid membranes.

The effects of the hydrocarbon chain of lipids on the size distribution of giant unilamellar vesicles (GUVs), kinetics of average size, bending modulus, and elastic modulus of membranes have been investigated. 1,2-dioleoyl-sn-glycero-3-phosphocholine (18:1 (Δ9-Cis) PC (DOPC)), 1,2-dipalmitoleoyl-sn-glycero-3-phosphocholine (16:1 (Δ9-Cis) PC), and 1,2-ditridecanoyl-sn-glycerol-3-phosphocholine (13:0 PC (DTPC)) lipids were considered. The number of hydrocarbons in a chain of the corresponding lipid was 18, 16, and 13. GUVs were prepared using the natural swelling method under incubation times of 20, 40, 60, 90, 120, and 180 min. The size distribution of vesicles was fitted using the lognormal distribution. The average sizes of DOPC, 16:1 (Δ9-Cis) PC, and DTPC-GUVs increased with the incubation time until 120 min, and then remained steady at 16.7 ± 0.2, 15.2 ± 0.4 and 12.0 ± 0.3 µm for the corresponding lipids. The average size at equilibrium state increased with the number of hydrocarbons. The incubation time-dependent average size was fitted with an exponential growth equation, and then the kinetic constants of 0.028 ± 0.004, 0.036 ± 0.007, and 0.083 ± 0.009 min-1 for DOPC, 16:1 (Δ9-Cis) PC, and DTPC-GUVs, respectively, were obtained. The equilibrium size distribution was fitted by the theoretical equation, and the bending modulus for DOPC, 16:1 (Δ9-Cis) PC, and DTPC membranes were 19.5 ± 0.2, 18.5 ± 0.1 and 14.3 ± 0.1 kBT, respectively. The bending modulus increased with the number of hydrocarbons. The elastic modulus of these membranes was 261 mN/m with a 4% fluctuation. The correlation between the average size and the square root of the bending modulus was supported by theoretical analysis.

A Dynamic Algorithm for Interference Management in D2D-Enabled Heterogeneous Cellular Networks: Modeling and Analysis.

To supporting a wider and diverse range of applications, device-to-device (D2D) communication is a key enabler in heterogeneous cellular networks (HetCNets). It plays an important role in fulfilling the performance and quality of service (QoS) requirements for 5G networks and beyond. D2D-enabled cellular networks enable user equipment (UE) to communicate directly, without any or with a partial association with base stations (eNBs). Interference management is one of the critical and complex issues in D2D-enabled HetCNets. Despite the wide adoption of D2D communications, there are very few researchers addressing the problems of mode selection (MS), as well as resource allocation for mutual interference in three-tier cellular networks. In this paper, we first identify and analyze three key factors, namely outage probability, signal-to-interference and noise ratio (SINR), and cell density that influence the performance of D2D-enabled HetCNets. We then propose a dynamic algorithm based on a distance-based approach to minimize the interference and to guarantee QoS for both cellular and D2D communication links. Results obtained show that outage probability is improved by 35% and 49% in eNB and SCeNB links, respectively, when compared with traditional neighbor-based methods. The findings reported in this paper provide some insights into interference management in D2D communications that can help network researchers and engineers contribute to further developing next-generation cellular networks.

Correction to: Factors influencing childhood anaemia in Bangladesh: a two level logistic regression analysis.

Following publication of the original article [1], the authors reported that name that appeared in published online version is incorrect.

Factors influencing childhood anaemia in Bangladesh: a two level logistic regression analysis.

BACKGROUND: Anemia is not only a major public health problem among children in developing countries, it is also an important predictor for their future growth and development. The objective of this study was to identify possible factors associated with anemia among pre-school children in Bangladesh after removing a cluster effect of the population, and to determine the prevalence of this condition. METHODS: Data for this study was extracted from the 2011 Bangladesh Demographic and Health Survey (BDHS-2011). In this survey, data was collected using a two-stage stratified cluster sampling approach. The chi-square test and a two-level logistic regression model were used for further analysis. RESULTS: Data from 2231 children aged 6-59 months were included for analysis. The prevalence of child anemia was noted to be 52.10%. Among these anemic children, 48.40% where from urban environment and 53.90% were from rural areas. The prevalence of mild, moderate and severe anemia among children was 57.10, 41.40 and 1.50% respectively. The two-level logistic regression model revealed that the following factors were associated with childhood anemia: children of anemic mothers (p < 0.01), undernourished children (p < 0.05), younger children (age < 2 years) (p < 0.01) and children from poor family (p < 0.05). Lastly, anemia was more common among children living in Barisal and Rangpur divisions compared to those from Dhaka division (p < 0.01), and among non-Muslims than Muslim (p < 0.05). CONCLUSIONS: Our study showed that prevalence of anemia among pre-school children in Bangladesh was very high (52.10%). We noted that young children of anemic mothers, from poor families, and being undernourished were at higher risk of developing anemia. Since most of these risk factors were related to socioeconomic conditions, they were potentially modifiable. Therefore, our findings may be useful for the health authorities to identify children at risk for remedial action and to plan for preventive measures.

Melt Extrusion of High-Dose Co-Amorphous Drug-Drug Combinations : Theme: Formulation and Manufacturing of Solid Dosage Forms Guest Editors: Tony Zhou and Tonglei Li.

PURPOSE: Many future drug products will be based on innovative manufacturing solutions, which will increase the need for a thorough understanding of the interplay between drug material properties and processability. In this study, hot melt extrusion of a drug-drug mixture with minimal amount of polymeric excipient was investigated. METHODS: Using indomethacin-cimetidine as a model drug-drug system, processability of physical mixtures with and without 5% (w/w) of polyethylene oxide (PEO) were studied using Differential Scanning Calorimetry (DSC) and Small Amplitude Oscillatory Shear (SAOS) rheometry. Extrudates containing a co-amorphous glass solution were produced and the solid-state composition of these was studied with DSC. RESULTS: Rheological analysis indicated that the studied systems display viscosities higher than expected for small molecule melts and addition of PEO decreased the viscosity of the melt. Extrudates of indomethacin-cimetidine alone displayed amorphous-amorphous phase separation after 4 weeks of storage, whereas no phase separation was observed during the 16 week storage of the indomethacin-cimetidine extrudates containing 5% (w/w) PEO. CONCLUSIONS: Melt extrusion of co-amorphous extrudates with low amounts of polymer was found to be a feasible manufacturing technique. Addition of 5% (w/w) polymer reduced melt viscosity and prevented phase separation.

MULTILEVEL LINEAR REGRESSION ANALYSIS OF FACTORS INFLUENCING BODY MASS INDEX AMONG BANGLADESHI MARRIED NON-PREGNANT WOMEN.

The aim of this study was to investigate the socioeconomic and demographic factors influencing the body mass index (BMI) of non-pregnant married Bangladeshi women of reproductive age. Secondary (Hierarchy) data from the 2011 Bangladesh Demographic and Health Survey, collected using two-stage stratified cluster sampling, were used. Two-level linear regression analysis was performed to remove the cluster effect of the variables. The mean BMI of married non-pregnant Bangladeshi women was 21.60±3.86 kg/m2, and the prevalence of underweight, overweight and obesity was 22.8%, 14.9% and 3.2%, respectively. After removing the cluster effect, age and age at first marriage were found to be positively (p<0.01) related with BMI. Number of children was negatively related with women's BMI. Lower BMI was especially found among women from rural areas and poor families, with an uneducated husband, with no television at home and who were currently breast-feeding. Age, total children ever born, age at first marriage, type of residence, education level, level of husband's education, wealth index, having a television at home and practising breast-feeding were found to be important predictors for the BMI of married Bangladeshi non-pregnant women of reproductive age. This information could be used to identify sections of the Bangladeshi population that require special attention, and to develop more effective strategies to resolve the problem of malnutrition.

Differentials in the prevalence of anemia among non-pregnant, ever-married women in Bangladesh: multilevel logistic regression analysis of data from the 2011 Bangladesh Demographic and Health Survey.

BACKGROUND: Anemia is one of the most common public health problems globally, and high prevalence has been reported among women of reproductive age, especially in developing countries. This study was conducted to evaluate differentials in the prevalence of anemia among non-pregnant, ever-married women of reproductive age in Bangladesh, and to examine associations with demographic, socioeconomic, and nutritional factors. METHODS: Data for this cross-sectional study were taken from the 2011 Bangladesh Demographic and Health Survey (BDHS). In a sub-sample of one-third of the households, all ever-married women of reproductive age (15 to 49 years) were selected for the biomarker component of the survey, including anemia. The sample size for our study was 5,293. Data were analyzed using multilevel logistic regression analysis. RESULTS: The prevalence of anemia among non-pregnant, ever-married women was 41.3% (urban: 37.2% and rural: 43.5%). Among anemic women, 35.5% had mild anemia, 5.6% had moderate anemia, and 0.2% had severe anemia. Women with no education were more likely to be anemic than those with secondary education (p < 0.01) or higher education (p < 0.01). Undernourished women (BMI < 18.5) were at greater risk of anemia (p < 0.01) compared with normal women, overweight women, and obese women. Anemia was less pronounced among non-pregnant women using contraception (p < 0.05), Muslim women (p < 0.01), and women living in rich households (p < 0.01). CONCLUSIONS: The prevalence of anemia among non-pregnant, ever-married women in Bangladesh is high. Illiteracy, poverty, and undernutrition are contributing factors.

Pivotal relationship between heavy metal, PM2.5 exposures and tuberculosis in Bangladeshi children: protocol paper of a case-control study.

INTRODUCTION: Air pollution is a global issue that poses a significant threat to public health. Children, due to their developing physiology, are particularly susceptible to the inhalation of environmental pollutants. Exposure can trigger immune modulation and organ damage, increasing susceptibility to respiratory diseases. Therefore, we aim to examine the association between heavy metal and particulate matter exposure with tuberculosis in children. METHODS AND ANALYSIS: As a case-control study, we will include children diagnosed with pulmonary tuberculosis (n=60) and matched healthy controls (n=80) recruited from the same communities in Dhaka, Bangladesh. Exposure data for both cases and controls will be collected by a trained field team conducting home visits. They will administer an exposure questionnaire, measure child anthropometry, collect blood and household dust samples and instal 48-hour air quality monitors. The blood samples will be analysed by inductively coupled plasma mass spectrometry for serum heavy metal concentrations (lead, cadmium, arsenic, mercury and chromium), as a representative marker of exposure, and the presence of inflammatory biomarkers. Descriptive and inferential statistics, including independent samples t-tests, analysis of variance and conditional regression analysis, will be used to quantify heavy metal and particulate matter exposure status in tuberculosis cases compared with healthy controls, while accounting for potential confounders. Dust samples and air quality results will be analysed to understand household sources of heavy metal and particulate matter exposure. To test the study hypothesis, there is a positive association between exposure and tuberculosis diseases, we will also measure the accumulated effect of simultaneous exposures using Bayesian statistical modelling. ETHICS AND DISSEMINATION: This study has been approved by International Centre for Diarrhoeal Disease Research, Bangladesh's Institutional Review Board (PR-22030). The study findings will be disseminated at conferences and published in peer-reviewed journals.

Flash flooding considerations aside: Knowledge brokering by the extension and advisory services to adapt a farming system to flash flooding.

The development of agriculture sector and livelihood in Bangladesh are threatened by various climatic stressors, including flash flooding. Therefore, Extension and advisory services (EAS) need to navigate the knowledge landscape effectively to connect various farm actors and help secure the optimum benefits of knowledge and information for making rational decisions. However, little is known how EAS can perform this task to combat various effects of climate change. This study investigates the means of brokering knowledge by the EAS to help the farming sector adapt to flash flooding. The research was conducted in the north-eastern part of Bangladesh with 73 staff of the Department of Agricultural Extension (DAE), the largest public EAS in Bangladesh. The results showed that DAE primarily dealt with crop production-related information. However, EAS did not navigate knowledge and information about flash flooding, such as weather forecasting and crop-saving-embankments updates, among the farming actors. Moreover, they missed the broad utilization of internet-based-communication channels to rapidly navigate information and knowledge about possible flash flooding and its adaptation strategies. This article provides some policy implications to effectively support the adaptation of farming system to flash flooding through EAS.

Application of TOPSIS method for flood susceptibility mapping using Excel and GIS.

This study elaborately manifests a simplified Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) multicriteria decision-making (MCDM) approach that goals to determine the disparity among the distances between the positive and negative ideal solutions. MCDM methods evaluate options based on a variety of criteria by using mathematical and analytical methodologies. This promotes a more transparent and objective decision-making process by removing human biases and subjective judgements. By considering the comparative proximity to the optimal situation, TOPSIS considers the distances between the ideal and the negative-ideal alternatives. This study has concentrated on the normalization process, the appropriate determination of the ideal and the anti-ideal solution, and the metric utilized to compute the euclidean distances from the ideal best and the ideal worst.•This study expresses the simplified TOPSIS methodology as stated by Hwang and Yoon (1981). The categorization and weight assignments of the criteria have been executed from the expert's opinion and based on existing literatures.•Integration of the TOPSIS technique with GIS has been properly performed for the production of a flood susceptibility map of a highly vulnerable region and visual interpretation of the TOPSIS algorithm.•This kind of investigation saved time by sufficiently skilled specialized personnel in this field.

Overcoming barriers to adapt rice farming to recurring flash floods in haor wetlands of Bangladesh.

Climate change resultant hazards have become a major threat to farming, food production systems and agricultural sustainability globally. Like many other countries, Bangladesh is also the prey of climate change extremities. Haor wetlands of this country, a major rice growing area, are subjected to extreme climate tremors where millions of inhabitants lose their boro rice production due to recurring flash flood events. This study examined the barriers to adapt rice farming to recurring flash floods in the haor wetlands of Bangladesh. The ways of overcoming barriers to adapt rice farming to recurring flash floods in the haor wetlands of Bangladesh were also explored during the research work. The research was conducted in the Sunamganj district of Bangladesh and data was collected through a mixed-method approach. A survey was conducted with 115 haor farmers and FGD and key informant interviews were conducted with 32 and 4 respondents respectively. The results showed that the lack of availability of submergence tolerant variety (a rice variety that can survive and continue growing after being completely submerged in water for several days) is the major barrier to farmers' adaptation to flooding events followed by limited market access and lack of access to inputs. A total of 85% of respondents reported encountering moderate to severe barriers to adapt to flash flooding. Besides, some socio-economic traits, including annual family income, extension media exposure, and perception on climate change have been identified to be influencing farmers' adaptation behaviour to adapt their rice farming system to recurring flash flood events. This study elaborated pathways and suggested policy recommendations to adapt to flash flooding and to ensure sustainability in the agricultural system in the haor wetlands of Bangladesh.

General and abdominal obesity and dietary nutrient intake among university students in Bangladesh: A cross-sectional study targeting potential risk factors.

BACKGROUND & AIMS: The overall national increase in the prevalence of overweight and obesity has emerged among university students in Bangladesh. Though, poor dietary habits and lifestyle is quite common among university students, their dietary nutrient intake level, obesity prevalence and potential risk factors has hitherto given little priority. This study aimed to understand the prevalence and factors associated with general and abdominal obesity and level of dietary nutrient intake among university students in Bangladesh. METHODS: Data from 320 unselected tertiary level students (81.6% males, 18.4% females; average age 22.7±3.0, BMI 22.4±3.1 and waist-hip ratio (WHR) 0.88 ± 0.1) was collected randomly, in a single visit, from Islamic University, Kushtia, Bangladesh. Basic demographic and anthropometric information were collected. Twenty-four hour (24H) dietary recall and food frequency questionnaire (FFQ) was used to collect dietary nutrient level retrospectively. Descriptive statistics, chi-square test, t-test, ANOVA, and binomial logistic regression analysis were done. RESULTS: Around 3% and 42% student were reported to be obese and overweight respectively. Whereas abdominal obesity was prevalent among ∼52% and more than 67% of student were reportedly obese/overweight by either BMI or WHR or WHtR category. Energy and carbohydrate (CHO) intake were reported to be significantly higher (P < 0.05) among overweight who born by C-section delivery and were fed formula milk than those were normal weight and born by vaginal-birth and were breastfed. The overweight individual with a history of preterm birth was reported to intake significantly higher (P < 0.05) carbohydrates compared to normal-weight individuals with a history of term birth. While total fat intake was significantly higher (P < 0.05) among overweight individuals with their mother had gestational diabetes than those with normal weight individuals with mother without gestational diabetes. CONCLUSIONS: General and abdominal obesity is common among university students and possibly associated with mode of birth, gestational duration, gestational diabetes, and breastfeeding practice.

Prevalence of antibiotic use for diarrhea among 1.3 million under-five years children: A multicounty retrospective analysis from 2006-2018.

BACKGROUND: This paper aims to estimate the prevalence of antibiotic use for diarrhea among under-five children (u5c) in low- and middle-income countries (LMICs) using data from 112 Demographic Health Surveys (DHS) conducted between 2006 and 2018. The focus is on understanding the extent of antibiotic usage for managing diarrhea, a condition characterized by frequent loose or watery bowel movements that can lead to severe dehydration. METHODS AND FINDINGS: A cross-sectional study design was employed in the DHS. The prevalence of antibiotic use for diarrhea among under-five children was estimated by analyzing DHS data from 2006 to 2018 and using the R statistical programming language. Out of a total of 12,69,944 children under five included in this study, 1,80,067 children had diarrhea and 19,502 children had bloody diarrhea. The overall prevalence of diarrhea estimated at ~14% (prevalence = 0.142; 95% CI = 0.141, 0.142). Among the children with diarrhea, 47,755 child received antibiotic treatment, resulting a prevalence of ~27% (prevalence = 0.27, 95% CI = 0.26, 0.27) globally. Central Asia had the highest prevalence of antibiotic use at ~55% (prevalence = (967/1748) = 0.55, 95% CI = 0.52, 0.59), followed by the Europe region with a prevalence of ~44% (prevalence = (5483/12502) = 0.44, 95% CI = 0.43, 0.45). In the South East and Central Asia region, DHS conducted between 2006 and 2018, showed the highest prevalence of antibiotic use in DHS 2007 (~44%), DHS 2012 (~49%), DHS 2016 (~40%) and DHS 2017 (~65%). The linear trend analysis showed an upward trend for using antibiotic of diarrhea in the South East and Central Asia region. CONCLUSIONS: The Central Asia region had the highest proportion of antibiotic use, with an estimated prevalence of ~55% (95% CI = 0.52, 0.59). The Europe region followed closely with a prevalence of ~44% (95% CI = 0.43, 0.45). The South East Asia region had the lowest prevalence of antibiotic use estimated at ~23% (95% CI = 0.22, 0.24), with a gradual increasing trend.

GIS-based data-driven bivariate statistical models for landslide susceptibility prediction in Upper Tista Basin, India.

Predicting landslides is becoming a crucial global challenge for sustainable development in mountainous areas. This research compares the landslide susceptibility maps (LSMs) prepared from five GIS-based data-driven bivariate statistical models, namely, (a) Frequency Ratio (FR), (b) Index of Entropy (IOE), (c) Statistical Index (SI), (d) Modified Information Value Model (MIV) and (e) Evidential Belief Function (EBF). These five models were tested in the high landslides-prone humid sub-tropical type Upper Tista basin of the Darjeeling-Sikkim Himalaya by integrating the GIS and remote sensing. The landslide inventory map consisting of 477 landslide locations was prepared, and about 70% of all landslide data was utilized for training the model, and 30% was used to validate it after training. A total of fourteen landslide triggering parameters (elevation, slope, aspect, curvature, roughness, stream power index, TWI, distance to stream, distance to road, NDVI, LULC, rainfall, modified fournier index, and lithology) were taken into consideration for preparing the LSMs. The multicollinearity statistics revealed no collinearity problem among the fourteen causative factors used in this study. Based on the FR, MIV, IOE, SI, and EBF approaches, 12.00%, 21.46%, 28.53%, 31.42%, and 14.17% areas, respectively, identified in the high and very high landslide-prone zones. The research also revealed that the IOE model has the highest training accuracy of 95.80%, followed by SI (92.60%), MIV (92.20%), FR (91.50%), and EBF (89.90%) models. Consistent with the actual distribution of landslides, the very high, high, and medium hazardous zones stretch along the Tista River and major roads. The suggested landslide susceptibility models have enough accuracy for usage in landslide mitigation and long-term land use planning in the study area. Decision-makers and local planners may utilise the study's findings. The techniques for determining landslide susceptibility can also be employed in other Himalayan regions to manage and evaluate landslide hazards.

Influence of Sn doping on the optoelectronic properties of ZnO nanoparticles.

Zinc Oxide (ZnO) nanoparticles (NPs) obtained a lot of attention from researchers and industries because of their superior properties as an optoelectronic material. Doping, especially tin (Sn), can further fine-tune their optoelectronic properties. In this manuscript, we have reported the optoelectronic properties of Sn-doped ZnO NPs, which were synthesized by a simple chemical solution method. A wide range of dopant (Sn) concentrations were used in the ratios of 0, 1, 3, 5, 7, and 10 weight percent. The effects of dopant (Sn) concentration on the structural, morphological, elemental composition, and optical properties of ZnO NPs were investigated by using an X-ray diffractometer (XRD), Field Emission Scanning Electron Microscope (FESEM), X-ray photoelectron spectrometer (XPS) and UV-Vis-NIR respectively. XRD analysis revealed the shifting of diffraction patterns towards a higher angle along with decreasing intensity. The calculated crystallite size using the XRD varied from 40.12 nm to 28.15 nm with an increasing doping percentage. Sn doping notably influences the size of ZnO NPs, along with crystal quality, strain, and dislocation density. The X-ray photoelectron spectroscopy (XPS) study showed the presence of zinc (Zn), oxygen (O), and tin (Sn) with their preferred oxidation states in the synthesized NPs. UV-Visible spectroscopy (UV-Vis) showed that the bandgap changed from 3.55 to 3.85 eV with the increasing concentration of Sn. FE-SEM revealed that the structures and surfaces were irregular and not homogeneous. The above findings for ZnO nanostructures show their potential application in optoelectronic devices.

Anthropometry in predicting Semitendinosus and Gracilis graft diameter for arthroscopic ACL reconstruction among the Bengali population.

Semitendinosus and Gracilis autografts are commonly used for anterior cruciate ligament (ACL) reconstruction. However, its main drawback is individual variation in the tendon diameter. This study aimed to evaluate the usefulness of the anthropometric measurements for the prediction of Semitendinosus and Gracilis combined (quadrupled) strands graft diameter in arthroscopic ACL reconstruction among the Bengali population. Sixty consecutive patients who underwent ACL reconstruction between July 2019 to June 2020 were observed in this cross-sectional study. In all cases, the doubled (2 strands) Gracilis and Semitendinosus tendons were combined to get the final quadrupled (combined 4 strands) graft for use. Anthropometries such as body mass index (BMI), body weight, and height were recorded preoperatively and quadrupled combined tendon diameter was measured at the operating theater. The relationship between these parameters was statistically determined using the Pearson correlation coefficient, and scatter diagrams were plotted. Among the study subjects, most (54) were male, and the mean age of all subjects was 24 ±â€…6.92 years. The average graft diameter was 7.20 ±â€…0.76 mm. Correlations between the mean graft diameter with BMI (r = 0.018, and P = .891), body height (r = 0.011 and P = .933), and weight (r = 0.028 and P = .832) were not significant. Scatter diagrams also showed that the variables were not correlated. Anthropometries like BMI, body weight, or body height cannot be used in predicting Semitendinosus and Gracilis tendon graft diameter for arthroscopic ACL reconstruction among the Bengali population.

Synthesis, characterization and thermoluminescence properties of LiCaPO4 phosphor for ionizing radiation dosimetry.

Many minerals and compounds show thermoluminescence (TL) properties but only a few of them can meet the requirements of an ideal dosimeter. Several phosphate materials have been studied for low-dose dosimetryin recent times. Among the various phosphates, ABPO4-type material shows interesting TL properties. In this study, an ABPO4-type (A = Lithium, B=Calcium) phosphor is synthesized using a modified solid-state diffusion method. Temperature is maintained below 800 °C in every step of phosphor preparation to obtain the pure phase of Lithium calcium phosphate (LiCaPO4). The purpose of this work is to synthesize LiCaPO4 using a simple method, examine its structural and luminescence properties in order to gain a deeper understanding of its TL characteristics. The general TL properties, such as TL glow curve, dose linearity, sensitivity, and fading, are investigated. Additionally, this study aims to determine various kinetic parameters through Glow Curve Deconvolution (GCD) method using the Origin Lab software together with the Chen model. XRD analysis confirmed the phase purity of the phosphor with a rhombohedral structure. Lattice parameters, unit cell volume, grain size, dislocated density, and microstrain were also calculated from XRD data. Raman analysis and Fourier Transform Infrared analysis were used to collect information about molecular bonds, vibrations, identity, and structure of the phosphor. To investigate TL properties and associated kinetic parameters, the phosphor was irradiated with 6.0 MV (photon energy) and 6.0 MeV (electron energy) from a linear accelerator for doses ranging from 0.5 Gy to 6.0 Gy. For both photon and electron energy, TL glow curves have two identical peaks near 200 °C and 240 °C.The TL glow curves for 0.5 Gy-6 Gy are deconvoluted, then fitted with the appropriate model and then calculated the kinetic parameters. Kinetic parameters such as geometric factor (µg), order of kinetics, activation energy (E), and frequency factor (s) are obtained from Chen's peak shape method. The dose against the TL intensity curve shows that the response is almost linear in the investigated dose range. For photon and electron energy, the phosphor is found to be the most sensitive at 2.0 Gy and 4.0 Gy, respectively. The phosphor shows a low fading and after 28 days of exposure, it shows a signal loss of better than 3%. The studied TL properties suggest the suitability of LiCaPO4 in radiation dosimetry and associated fields.

Smoker's characteristics, general health and their perception of smoking in the social environment: a study of smokers in Rajshahi City, Bangladesh.

Background: Smoking is one of the bad habits in social environment and is one of the main causes of immature death in Bangladesh. Rajshahi is one of the cleanest, most peaceful cities in Bangladesh, but the inhabitants often feel uncomfortable about smokers who smoke in public places and often on transport. Smoking frequency is very high among males compared to females, and a large number of smokers are building or road construction laborers and people involved in offering different services such as transportation, vending from vans, etc. The practice of smoking in this area is destructive for mental and physical health especially for students compared to other professionals because the city is known as the City of Education. Methods: The study analyzes smokers' characteristics, general health, and their (smokers) perception of smoking in public places. Cross-sectional data were collected randomly from 160 smokers through face-to-face questionnaire survey. The determinants of complexities with regard to social environment and human health were studied using frequency distribution, chi-square test, and binary and multinomial logistic regression analysis using IBM SPSS version 24. Results: Frequency distributions reveal that 93.8% of smokers believe that smoking creates public health hazards, 51.3% of smokers think it causes breathing complexities for non-smokers, 48.8% of smokers feel smoking causes air pollution, 68.8% of smokers think smoking causes gastric problems, 24.4% of smokers had headache problems due to smoking and cigarette fumes, 86.3% of smokers learnt smoking from friends, 48.8% of smokers smoke due to their addiction and 25.6% for depression, and 80.6% usually smoke after having a meal. The chi-square test reveals that class of smokers was significantly associated with frequency of heartbeat rate, starting smoking at specific age level was significantly associated with suffering from diseases, category of smoking articles was significantly associated with suffering from disease, class of smokers was significantly associated with causes for smoking, and starting smoking at specific age level was significantly associated with profession of the smokers at 1% level of significance respectively. A significant odds ratio was found (OR = 6.363, 95% CI 1.918-21.104, p < 0.01) for the profession group of students/labour at 1% level; their outcomes for suffering from diseases such as gastric problem and fever/headache/others were 6.363 times those for the profession group of service/other smokers. Conclusion: Smoking in public places should be restricted because non-smokers cannot breathe freely and it is not healthy for them to inhale smoke indirectly, which has many adverse effects on public health. The study also reveals that the majority of the smokers have gastric problems, abnormal heartbeat rates, frequent headaches, depression and addiction problems, etc., and that they believe that smoking causes significant health hazard on human health and social environment. Therefore, necessary interventions should be taken immediately by policy-makers to prevent smoking in public places. Supplementary Information: The online version contains supplementary material available at 10.1007/s10389-020-01413-w.

Green logistics and environment, economic growth in the context of the Belt and Road Initiative.

Infrastructure development has been a priority area since the Belt and Road Initiative (BRI) was proposed. This paper uses the generalized method of moments (GMM) to analyze the relationship between the green logistics, environment and economic growth based on panel data of countries along the BRI from 2007 to 2018. It is found that fossil fuels are the core of logistics operation activities, and the more fossil fuels are used, the more detrimental to the sustainable development of the environment. "The green logistics is negatively correlated with fossil fuel energy consumption and carbon emissions per capita in countries along the Belt and Road. At the same time, the green logistics can also bring more export opportunities for these countries and increase the national income per capita. The development of the green logistics is of great significance to the countries' environment and sustainable economic development along the Belt and Road.