Theory and quantum dynamics simulations of exciton-polariton motional narrowing.

The motional narrowing effect has been extensively studied for cavity exciton-polariton systems in recent decades both experimentally and theoretically, which is featured by (1) the subaverage behavior and (2) the asymmetric linewidths for the upper polariton and the lower polariton. However, a minimal theoretical model that is clear and adequate to address all these effects as well as the linewidth scaling relations remains missing. In this work, based on the single mode 1D Holstein-Tavis-Cummings (HTC) model, we studied the motional narrowing effect of the polariton linear absorption spectra via both semi-analytic derivations and numerically exact quantum dynamics simulations using the hierarchical equations of motion approach. The results reveal that under collective light-matter coupling between a cavity mode and N molecules, the polariton linewidth scales as 1/N under the slow limit, while scales as 1/N under the fast limit, due to the polaron decoupling effect. Furthermore, by varying the detunings, the polariton linewidths exhibit significant motional narrowing, covering both characters mentioned above. Our analytic linewidth expressions [Eqs. (34) and (35)] agree well with the numerical exact simulations in all the parameter regimes we explored. These results indicate that the physics of motional narrowing is adequately accounted for by the single-mode 1D HTC model. We envision that both the numerical results and the analytic polariton linewidths expression presented in this work will offer great theoretical value for providing a better understanding of the exciton-polariton motional narrowing based on the HTC model.

Quantum dynamics simulations of the 2D spectroscopy for exciton polaritons.

We develop an accurate and numerically efficient non-adiabatic path-integral approach to simulate the non-linear spectroscopy of exciton-polariton systems. This approach is based on the partial linearized density matrix approach to model the exciton dynamics with explicit propagation of the phonon bath environment, combined with a stochastic Lindblad dynamics approach to model the cavity loss dynamics. Through simulating both linear and polariton two-dimensional electronic spectra, we systematically investigate how light-matter coupling strength and cavity loss rate influence the optical response signal. Our results confirm the polaron decoupling effect, which is the reduced exciton-phonon coupling among polariton states due to the strong light-matter interactions. We further demonstrate that the polariton coherence time can be significantly prolonged compared to the electronic coherence outside the cavity.

LDDNet: A Deep Learning Framework for the Diagnosis of Infectious Lung Diseases.

This paper proposes a new deep learning (DL) framework for the analysis of lung diseases, including COVID-19 and pneumonia, from chest CT scans and X-ray (CXR) images. This framework is termed optimized DenseNet201 for lung diseases (LDDNet). The proposed LDDNet was developed using additional layers of 2D global average pooling, dense and dropout layers, and batch normalization to the base DenseNet201 model. There are 1024 Relu-activated dense layers and 256 dense layers using the sigmoid activation method. The hyper-parameters of the model, including the learning rate, batch size, epochs, and dropout rate, were tuned for the model. Next, three datasets of lung diseases were formed from separate open-access sources. One was a CT scan dataset containing 1043 images. Two X-ray datasets comprising images of COVID-19-affected lungs, pneumonia-affected lungs, and healthy lungs exist, with one being an imbalanced dataset with 5935 images and the other being a balanced dataset with 5002 images. The performance of each model was analyzed using the Adam, Nadam, and SGD optimizers. The best results have been obtained for both the CT scan and CXR datasets using the Nadam optimizer. For the CT scan images, LDDNet showed a COVID-19-positive classification accuracy of 99.36%, a 100% precision recall of 98%, and an F1 score of 99%. For the X-ray dataset of 5935 images, LDDNet provides a 99.55% accuracy, 73% recall, 100% precision, and 85% F1 score using the Nadam optimizer in detecting COVID-19-affected patients. For the balanced X-ray dataset, LDDNet provides a 97.07% classification accuracy. For a given set of parameters, the performance results of LDDNet are better than the existing algorithms of ResNet152V2 and XceptionNet.

Antibacterial effect of kitchen herbs against pathogenic multidrug-resistant E. coli isolates from calf diarrhoea.

Calf diarrhoea remains the biggest challenge both in the small and large farms. Infectious diarrhoea is associated with many pathogens, Escherichia coli being one, but majority are systematically treated with antibiotics. Since antimicrobial resistance (AMR) is a growing menace, the need to find alternative prophylactic solutions using popular kitchen herbs such as Trachyspermum ammi (carom seeds), Curcuma longa (turmeric) and cinnamon (Cinnamomum sp.) extracts is been investigated against virulent form of E. coli isolated from calf diarrhoea. The virulence factors identified in these isolates were ST (32.5%), LT (20%), eaeA (15%), stx1 (2.5%) and stx2 (5%) with the occurrence of the most common serogroups as O18 (15%) followed by O111 (12.5%). Highest resistance was seen with beta lactam + beta lactamase inhibitor (amoxicillin/clavulanic acid) followed by beta lactams (ampicillin, cefuroxime and cefepime). The zone of inhibition due to cinnamon (methanol) and carom seed (ethanol) extracts (500 to 250 µg/mL concentration) on E. coli bacteria was >19 mm, respectively. Turmeric, cinnamon and carom had the potency of inhibiting the pathogenic E. coli which maybe suggestive of its use in calf diets as prophylaxis against diarrhoea.

Differences in the socio-demographic determinants of undernutrition in children aged <5 years in urban and rural areas of Bangladesh measured by the Composite Index of Anthropometric Failure.

OBJECTIVES: This study investigates the prevalence and determinants of undernutrition among children <5 years living in Bangladesh using the Composite Index of Anthropometric Failure (CIAF) and highlights the differences between urban and rural areas. STUDY DESIGN: Data are drawn from three cross-sectional Bangladesh Demographic Health Surveys conducted from 2007 to 2014. METHODS: A Chi-square test was used to assess the prevalence of <5 years child undernutrition. Logistic regression analysis was performed to identify various sociodemographic risk factors. RESULTS: The prevalence of undernutrition based on the CIAF was 52% among children <5 years in Bangladesh. The prevalence of undernutrition in children living in urban areas and rural areas were found to be 45% and 54%, respectively. As per the CIAF, undernutrition was highly prevalent among children in the older age group, children of uneducated and currently working mothers, those of underweight mothers, children of fourth and above in the birth order, children of fathers who were manual labourers, children of households who had no access to television and those in the poorest households whether in urban or rural areas. Children in the older age group, children of uneducated mothers, those with underweight mothers and those from the poorest households provided common key risk factors for undernutrition in both urban and rural areas. Children of fourth and above birth order and not watching television at all were additional risk factors of child undernutrition in rural areas. CONCLUSION: Half of the children in rural areas and two-fifths of them in urban areas are suffering undernutrition in Bangladesh, and several sociodemographic factors heighten the risks. Also, birth order and watching television were identified as the differential risk factors. This study therefore concludes that evidence-based interventions are needed to reduce the burden of undernutrition in children in the country.

Recycling waste thermoplastic for energy efficient construction materials: An experimental investigation.

A large stream of research has studied the performance of waste plastics impregnated concrete, reporting multiple benefits and advocating its use in construction works. But no study has reported the merits of bricks impregnated with waste plastics. The present paper reports the results of experiments done on bricks made up of varying percentages of waste thermoplastics (0 - 10% by weight) and sand (60 - 70% by weight), holding percentages of fly ash and ordinary Portland cement constant at 15% (by weight) each. Three types of waste thermoplastics were used, forming three separate batches of bricks. The plastics were polycarbonates, polystyrenes, and mixed plastics. The bricks were cured under water for 28 days. Some of the batches were baked at temperatures ranging from 90 °C to 110 °C for 2 hours in order to melt the plastics to form voids. The bricks made with the above-stated compositions were found to possess low thermal conductivity and adequately high compressive strength. The compressive strength of these bricks is observed to be more than 17 MPa, which lies within the upper half of the range of strengths specified for bricks in the IS 1077:1992 standard. The waste plastics impregnated bricks display high thermal resistance, a feature that can add economic value to the brick manufacturers, motivating them to establish the necessary logistics for collection and use of all types of waste thermoplastics. The paper also presents a regression model to predict the compressive strength of bricks at varying plastic contents. The study, thus, introduces a new strand of research on sustainable recycling of waste thermoplastics in the context of the circular economy.

Functional assessment of tyrosinase variants identified in individuals with albinism is essential for unequivocal determination of genotype-to-phenotype correlation.

BACKGROUND: Oculocutaneous albinism type 1 (OCA1), caused by pathogenic variations in the tyrosinase gene (TYR), is the most frequent and severe form of hypopigmentary disorder worldwide. While OCA1A manifests as a complete loss of melanin pigment, patients with OCA1B show residual pigmentation of the skin, hair and eyes. Limited experimental evidence suggests retention of TYR in the endoplasmic reticulum (ER) causes OCA1 pathogenesis. However, a comprehensive functional analysis of TYR missense variations and correlation with genotype is lacking. OBJECTIVES: Functional characterization of nonsynonymous tyrosinase variants in patients with OCA1 reported in the Albinism Database, dbSNP and the published literature, and an attempt to correlate them with reported and predicted phenotypes. METHODS: Thirty-four reported missense variants of TYR were subcloned by site-directed mutagenesis, and the dual-enzyme activities of the variant proteins were compared with the wild-type. The degree of ER retention was also checked for each of the variants through endoglycosidase H (Endo H) digestion followed by immunoprecipitation and densitometric analysis. RESULTS: Functional studies revealed one reported OCA1A variation with nearly 100% enzyme activity, 10 OCA1B variants lacking any enzyme activity, eight nonsynonymous single-nucleotide polymorphisms (SNPs) with ~30-70% of enzyme activity, and three SNPs that completely lacked activity altogether. The Endo H assay corroborated these results. CONCLUSIONS: Loss of enzyme activity of TYR variants was completely in agreement with ER retention across all variants examined. The results of the assay clearly established that determination of the biological activity of identified variants in patients with OCA is essential to correlate the identified suspect genotype with the obvious phenotype of the disease.

Morphological characterization and assessment of genetic variability, character association, and divergence in soybean mutants.

Genetic diversity is important for crop improvement. An experiment was conducted during 2011 to study genetic variability, character association, and genetic diversity among 27 soybean mutants and four mother genotypes. Analysis of variance revealed significant differences among the mutants and mothers for nine morphological traits. Eighteen mutants performed superiorly to their mothers in respect to seed yield and some morphological traits including yield attributes. Narrow differences between phenotypic and genotypic coefficients of variation (PCV and GCV) for most of the characters revealed less environmental influence on their expression. High values of heritability and genetic advance with high GCV for branch number, plant height, pod number, and seed weight can be considered as favorable attributes for soybean improvement through phenotypic selection and high expected genetic gain can be achieved. Pod and seed number and maturity period appeared to be the first order traits for higher yield and priority should be given in selection due to their strong associations and high magnitudes of direct effects on yield. Cluster analysis grouped 31 genotypes into five groups at the coefficient value of 235. The mutants/genotypes from cluster I and cluster II could be used for hybridization program with the mutants of clusters IV and V in order to develop high yielding mutant-derived soybean varieties for further improvement.

UDBRNet: A novel uncertainty driven boundary refined network for organ at risk segmentation.

Organ segmentation has become a preliminary task for computer-aided intervention, diagnosis, radiation therapy, and critical robotic surgery. Automatic organ segmentation from medical images is a challenging task due to the inconsistent shape and size of different organs. Besides this, low contrast at the edges of organs due to similar types of tissue confuses the network's ability to segment the contour of organs properly. In this paper, we propose a novel convolution neural network based uncertainty-driven boundary-refined segmentation network (UDBRNet) that segments the organs from CT images. The CT images are segmented first and produce multiple segmentation masks from multi-line segmentation decoder. Uncertain regions are identified from multiple masks and the boundaries of the organs are refined based on uncertainty data. Our method achieves remarkable performance, boasting dice accuracies of 0.80, 0.95, 0.92, and 0.94 for Esophagus, Heart, Trachea, and Aorta respectively on the SegThor dataset, and 0.71, 0.89, 0.85, 0.97, and 0.97 for Esophagus, Spinal Cord, Heart, Left-Lung, and Right-Lung respectively on the LCTSC dataset. These results demonstrate the superiority of our uncertainty-driven boundary refinement technique over state-of-the-art segmentation networks such as UNet, Attention UNet, FC-denseNet, BASNet, UNet++, R2UNet, TransUNet, and DS-TransUNet. UDBRNet presents a promising network for more precise organ segmentation, particularly in challenging, uncertain conditions. The source code of our proposed method will be available at https://github.com/riadhassan/UDBRNet.

Effect of concentration and addition method of glycerol on the quality of cryopreserved mithun (Bos frontalis) spermatozoa.

The effect of concentration and addition method of glycerol on the quality of cryopreserved mithun (Bos frontalis) spermatozoa was investigated. Semen samples were collected from five healthy mithun bulls through rectal massage method and cryopreserved in liquid nitrogen. The samples were diluted in Tris-egg yolk-glycerol extender, equilibrated for 4 h at 4 °C and loaded into 0.50-ml straws. The straws were then frozen in liquid nitrogen vapour for 10 min and finally plunged into liquid nitrogen for storage. The required amount of glycerol was added into the diluted samples either in a single dose (3%, 4%, 5%, 6% or 7%; added at 37 °C immediately before equilibration) or in split doses (5%, 6% or 7%; the total amount was divided into four equal parts, and a part was added at 37 °C immediately before equilibration, and the remaining parts were added subsequently at 1, 2 and 3 h of equilibration at 4 °C). In the single-dose addition method, following freeze-thawing, greater (p < 0.05) motility (%) and proportion of live spermatozoa with intact acrosome (LSIA, %) in 5% glycerol (40.6 ± 1.7 and 43.4 ± 1.8 respectively) and lesser (p < 0.05) total morphological abnormalities (%) in 5% (14.1 ± 0.8) and 6% (13.7 ± 1.0) glycerol were observed compared to the other glycerol concentrations. In the split-dose addition method, following freeze-thawing, greater (p < 0.05) motility (%) and LSIA proportion (%) were found in 5% (50.2 ± 1.9 and 53.3 ± 1.8 respectively) compared to 6% or 7% glycerol, but the total morphological abnormalities were not different among the glycerol concentrations. In addition, in all the glycerol concentrations, better (p < 0.05) post-freeze-thaw motility and LSIA proportions were observed when glycerol was added in split doses compared to a single dose. In conclusion, Tris-egg yolk extender with 5% glycerol added in split doses was found most suitable for cryopreserving mithun sperm.

Study of Body Mass Index, Blood Pressure, Serum Sodium in Newly Diagnosed Hypertensive Patients.

Hypertension 'The sustained elevation of systemic arterial pressure' is a significant risk factor for heart disease, stroke and other cardiovascular diseases and an estimated 970 million people worldwide suffer from the disease resulting in significant morbidity, mortality and financial burden globally. It is the leading modifiable risk factor for morbidity and mortality worldwide. Worldwide an estimated 1.28 billion adults aged 30-79 years have hypertension, the majority (two-thirds) living with low and middle income countries. One of the global targets for non-communicable diseases is to reduce the prevalence of hypertension by 33% between 2010 and 2030.Sodium plays an important role in blood pressure regulation with a reduced sodium intake being associated with a reduction in systolic and diastolic blood pressure. This study was done to evaluate the differences in body mass index (BMI) and serum sodium in hypertensive and normotensive subjects. This analytical type of cross sectional study was carried out in the Department of Physiology, Mymensingh Medical College, Mymensingh between the periods from January 2022 to December 2022. A total number of 140 male subjects, age ranged from (30-59) years were included in this study. Among them, seventy (70) hypertensive subjects were taken as study group (Group II) and seventy (70) age matched normotensive subjects were taken as control group (Group I). The results were calculated and analyzed by using Statistical Package for Social Science (SPSS) version 26.0. Anthropometric measurements like height and weight taken in meter and kilogram respectively. Systolic and diastolic blood pressure was performed by aneroid sphygmomanometer (ALPK2, Japan), laboratory analysis of serum sodium by colorimetric method. In this study we found that body mass index in control group 23.59±1.29 kg/m² and study group 26.81±2.31kg/m²; blood pressure (systolic pressure in control group 113.21±6.76 mm Hg and in study group 149.14±5.03 mm Hg, diastolic pressure in control group 75.57±4.55 mm Hg and in study group 100.21±5.28 mm Hg) and serum sodium in control group 138.84±2.12 & in study group was 147.94±1.41 which were significant in study group in comparison with control group. In study group parameters were significantly increased in comparison to control male group. Therefore, by this study we recommended that routine estimation of these parameters is important for prevention of complication related to hypertension for leading a healthy life.

RVCNet: A hybrid deep neural network framework for the diagnosis of lung diseases.

Early evaluation and diagnosis can significantly reduce the life-threatening nature of lung diseases. Computer-aided diagnostic systems (CADs) can help radiologists make more precise diagnoses and reduce misinterpretations in lung disease diagnosis. Existing literature indicates that more research is needed to correctly classify lung diseases in the presence of multiple classes for different radiographic imaging datasets. As a result, this paper proposes RVCNet, a hybrid deep neural network framework for predicting lung diseases from an X-ray dataset of multiple classes. This framework is developed based on the ideas of three deep learning techniques: ResNet101V2, VGG19, and a basic CNN model. In the feature extraction phase of this new hybrid architecture, hyperparameter fine-tuning is used. Additional layers, such as batch normalization, dropout, and a few dense layers, are applied in the classification phase. The proposed method is applied to a dataset of COVID-19, non-COVID lung infections, viral pneumonia, and normal patients' X-ray images. The experiments take into account 2262 training and 252 testing images. Results show that with the Nadam optimizer, the proposed algorithm has an overall classification accuracy, AUC, precision, recall, and F1-score of 91.27%, 92.31%, 90.48%, 98.30%, and 94.23%, respectively. Finally, these results are compared with some recent deep-learning models. For this four-class dataset, the proposed RVCNet has a classification accuracy of 91.27%, which is better than ResNet101V2, VGG19, VGG19 over CNN, and other stand-alone models. Finally, the application of the GRAD-CAM approach clearly interprets the classification of images by the RVCNet framework.

A novel approach for standardizing clinical laboratory categorical test results using machine learning and string distance similarity.

Standardizing clinical laboratory test results is critical for conducting clinical data science research and analysis. However, standardized data processing tools and guidelines are inadequate. In this paper, a novel approach for standardizing categorical test results based on supervised machine learning and the Jaro-Winkler similarity algorithm is proposed. A supervised machine learning model is used in this approach for scalable categorization of the test results into predefined groups or clusters, while Jaro-Winkler similarity is used to map text terms into standard clinical terms within these corresponding groups. The proposed method is applied to 75062 test results from two private hospitals in Bangladesh. The Support Vector Classification algorithm with a linear kernel has a classification accuracy of 98%, which is better than the Random Forest algorithm when categorizing test results. The experiment results show that Jaro-Winkler similarity achieves a remarkable 99.93% success rate in the test result standardization for the majority of groups with manual validation. The proposed method outperforms previous studies that concentrated on standardizing test results using rule-based classifiers on a smaller number of groups and distance similarities such as Cosine similarity or Levenshtein distance. Furthermore, when applied to the publicly available MIMIC-III dataset, our approach also performs excellently. All these findings show that the proposed standardization technique can be very beneficial for clinical big data research, particularly for national clinical research data hubs in low- and middle-income countries.

Wide variation of heterozygotic genotypes of recent fasciolid hybrids from livestock in Bangladesh assessed by rDNA internal transcribed spacer region sequencing and cloning.

Fascioliasis causes high economic losses in livestock and underlies public health problems in rural areas, mainly of low-income countries. The increasing animal infection rates in Bangladesh were assessed, by focusing on host species, different parts of the country, and rDNA sequences. Fasciolid flukes were collected from buffaloes, cattle, goats and sheep from many localities to assess prevalences and intensities of infection. The nuclear rDNA internal transcribed spacer (ITS) region including ITS-1 and ITS-2 spacers was analyzed by direct sequencing and cloning, given the detection of intermediate phenotypic forms in Bangladesh. The 35.4% prevalence in goats and 55.5% in buffaloes are the highest recorded in these animals in Bangladesh. In cattle (29.3%) and sheep (26.8%) prevalences are also high for these species. These prevalences are very high when compared to lowlands at similar latitudes in neighboring India. The high prevalences and intensities appear in western Bangladesh where cross-border importation of animals from India occur. The combined haplotype CH3A of Fasciola gigantica widely found in all livestock species throughout Bangladesh fits its historical connections with the western Grand Trunk Road and the eastern Tea-Horse Road. The "pure" F. hepatica sequences only in clones from specimens showing heterozygotic positions indicate recent hybridization events with local "pure" F. gigantica, since concerted evolution did not yet have sufficient time to homogenize the rDNA operon. The detection of up to six different sequences coexisting in the cloned specimens evidences crossbreeding between hybrid parents, indicating repeated, superimposed and rapidly evolving hybridization events. The high proportion of hybrids highlights an increasing animal infection trend and human infection risk, and the need for control measures, mainly concerning goats in household farming management. ITS-1 and ITS-2 markers prove to be useful for detecting recent hybrid fasciolids. The introduction of a Fasciola species with imported livestock into a highly prevalent area of the other Fasciola species may lead to a high nucleotide variation in the species-differing positions in the extremely conserved fasciolid spacers. Results suggest that, in ancient times, frequent crossbreeding inside the same Fasciola species gave rise to the very peculiar characteristics of the present-day nuclear genome of both fasciolids.

Comparison of Serum Zinc in Children of Wilson Disease and Non-Wilsonian Volunteers in Bangladesh.

Wilson disease (WD) is an autosomal recessive disorder of copper metabolism with diverse clinical manifestations. Zinc (Zn) has been used for treatment of WD. Recent studies showed low serum zinc level in patients suffering from WD than the normal. This cross-sectional analytical study has been designed to compare the serum zinc level between paediatric patients suffering from WD but yet not started treatment and children who have normal ALT level. This study was carried out at the Department of Pediatric Gastroenterology and Nutrition, BSMMU, Dhaka, Bangladesh from July 2018 to June 2019. Total 51 children were included in this study. Among them 27 were diagnosed case of WD aged between three to eighteen years and 24 children of same ages who were suffering from other than liver disease having normal ALT were included as volunteers. The patients of WD were divided into four groups according to their presentation as acute hepatitis, chronic liver disease (CLD), acute liver failure & neuropsychiatric manifestation. Informed written consent was obtained from all patients and volunteers for participation in this study. Along with other physical findings and laboratory investigations 3 ml of venous blood were collected for estimation of serum zinc level. After estimation of serum zinc level results were analyzed statistically. The difference in serum zinc levels were compared between the groups. Serum zinc level was significantly lower in Wilson disease patients (43.8±19.7µg/dl; range: 13-83) compared to volunteers group (67.8±11.8µg/dl; range: 47-97) p<0.001. Among the diseased group, serum zinc level were significantly lower in 18 CLD (38.4±17.4µg/dl) and in 4 acute liver failure (33.1±3.7µg/dl) compared to 4 acute hepatitis (71.8±4.3µg/dl) (p=0.001) and (p<0.001) respectively. Mean serum zinc level was low in 4 Wilsonian acute liver failure (33.1±3.7µg/dl), which was significant compared to those (23) who presented as Wilson disease non acute liver failure (45.7±20.8µg/dl) (p=0.013). Serum zinc level was significantly lower in Wilson disease children compared to the volunteers. Zinc level was also found significantly low in Wilson disease presented as CLD and acute liver failure in comparison to Wilson disease presented as acute hepatitis.

Seed yield of mungbean (Vigna radiata (L.) Wilczek) in relation to growth and developmental aspects.

Growth parameters such as leaf area (LA), total dry mass (TDM) production, crop growth rate (CGR), relative growth rate (RGR), and net assimilation rate (NAR) were compared in six varieties of mungbean under subtropical condition (24°8' N 90°0' E) to identify limiting growth characters for the efficient application of physiology breeding for higher yields. Results revealed that a relatively smaller portion of TDM was produced before flower initiation and the bulk of it after anthesis. The maximum CGR was observed during pod filling stage in all the varieties due to maximum leaf area (LA) development at this stage. Two plant characters such as LA and CGR contributed to the higher TDM production. Results indicated that high yielding mungbean varieties should possess larger LA, higher TDM production ability, superior CGR at all growth stages, and high relative growth rate and net assimilation rate at vegetative stage which would result in superior yield components.

Comparison of three fluid regimens for preloading in elective caesarean section under spinal anaesthesia.

The most common problem associated with subarachnoid block (SAB) for caesarean section remains the rapid onset of profound hypotension. This study was designed to compare the incidence of hypotension after preloading with Ringer's Lactate, Hydroxyethylstarch and combination prior to SAB in caesarean section. Ninety non-labouring ASA grade 1 and 2, aged 20-35 years, weight and height was 45-60kg and 153-165cm respectively divided randomly into three groups. Group-RL received Ringer's Lactate 20ml/kg as preloading fluid. Group-H received Hydroxyethylstarch-6% 8ml/kg and Group-RLH received preloading fluid with combination of Ringer's Lactate 10ml/kg and Hydroxyethylstarch-6% 4ml/kg. Blood pressure (Systolic, Diastolic & Mean arterial pressure) was measured every 5 minute for 20 minute and every 10 minutes thereafter. Hypotension was less in Group-RLH (6.7%) whereas in Group-H and Group-RL hypotension was 20% and 47.7% respectively. Systolic blood pressure decreased significantly in all three groups. But the decreasing was less in Group-RLH than other two groups. Less IV fluid was required in Group-RLH (403ml) and Group-H (577ml) in comparison to Group-RL (1032ml) to prevent and treat peroperative hypotension. No ephedrine was needed in Group-RLH. Variation in Pulse rate was not significant in Group-RLH (p=0.061). But in other two groups it was highly significant (Group RL p≤0.001 and Group H p=0.004). There was no significant difference in neonatal outcome between three groups. Preloading with low volume colloid (4ml/kg) plus crystalloid (10ml/kg) is superior to crystalloid or colloid alone.

Stability of the age distribution of measles cases over time during outbreaks in Bangladesh, 2004-2006.

Despite recommendations from WHO to conduct measles outbreak response vaccination campaigns based on the age distribution of cases at the beginning of an outbreak, few data exist to specifically examine whether the age distribution of cases remains constant over time in a measles outbreak. This analysis explores this question with use of measles outbreak surveillance data from Bangladesh from the period 2004-2006. Pearson χ(2) tests were conducted of age distributions over 2 periods during 41 large laboratory-confirmed measles outbreaks. Statistically significant changes in age distribution over time were observed in 24% of the outbreaks. No single pattern was detected in the shifts in age distribution; however, an increase in the proportion of cases occurring among infants <9 months of age was evident in 6 outbreaks. These findings suggest a need to consider the possibility of a shift in the age distribution over time when planning an outbreak response vaccination campaign.

Comparative nutrient utilization, growth, and rumen enzyme profile of mithun (Bos frontalis) and Tho-tho cattle (Bos indicus) fed on tree-leaves-based ration.

A study was conducted to compare the nutrient utilization, growth, and rumen enzyme profile of mithun (Bos frontalis) and Tho-tho cattle (Bos indicus) reared in the same feeding and managemental conditions. For the purpose, male mithun (n = 8) and male Tho-tho cattle (n = 8) of 1.5 years age, selected from the farm of National Research Centre on Mithun, Nagaland, India, were fed on mixed-tree-leaves-based ration as per the requirement of NRC (2001) for cattle for 12 months. Average daily gain (ADG), average dry matter intake (DMI), and feed conversion ratio (FCR) for all animals were recorded. A metabolic trial was conducted at 6 months of the experiment to assess the digestibility coefficient of different nutrients and nutritive value of ration. At 12 months of the experiment, rumen liquor was collected from all animals and analyzed for rumen enzyme profiles, viz., carboxymethylcellulase, xylanase, α-amylase, ß-glucosidase, α-glucosidase, urease, and protease. It was found that ADG (507.8 g vs 392.8 g), DM intake (6.59 vs 5.85 kg/day) and DMI/W(0.75) (98.75 g vs 91.00 g/day), crude protein intake (780 vs 700 g/day), and total digestible nutrient intake (3.65 vs 3.32 kg/day) were higher (p < 0.05) in mithun than cattle. The nitrogen balance was higher and FCR was better (p < 0.05) in mithun compared with cattle. The digestibility coefficient of different nutrients was similar (p > 0.05) between the species. The microbial enzyme profiles of mithun and cattle were not different (p > 0.05). The better growth performance of mithun than cattle as found in the present study clearly indicates that the mithun has higher genetic potential for growth than Tho-tho cattle of north-eastern hilly region of India.

CO-IRv2: Optimized InceptionResNetV2 for COVID-19 detection from chest CT images.

This paper focuses on the application of deep learning (DL) in the diagnosis of coronavirus disease (COVID-19). The novelty of this work is in the introduction of optimized InceptionResNetV2 for COVID-19 (CO-IRv2) method. A part of the CO-IRv2 scheme is derived from the concepts of InceptionNet and ResNet with hyperparameter tuning, while the remaining part is a new architecture consisting of a global average pooling layer, batch normalization, dense layers, and dropout layers. The proposed CO-IRv2 is applied to a new dataset of 2481 computed tomography (CT) images formed by collecting two independent datasets. Data resizing and normalization are performed, and the evaluation is run up to 25 epochs. Various performance metrics, including precision, recall, accuracy, F1-score, area under the receiver operating characteristics (AUC) curve are used as performance metrics. The effectiveness of three optimizers known as Adam, Nadam and RMSProp are evaluated in classifying suspected COVID-19 patients and normal people. Results show that for CO-IRv2 and for CT images, the obtained accuracies of Adam, Nadam and RMSProp optimizers are 94.97%, 96.18% and 96.18%, respectively. Furthermore, it is shown here that for the case of CT images, CO-IRv2 with Nadam optimizer has better performance than existing DL algorithms in the diagnosis of COVID-19 patients. Finally, CO-IRv2 is applied to an X-ray dataset of 1662 images resulting in a classification accuracy of 99.40%.