In this review paper, we discuss the use of BERT, one of the most well-liked deep learning-based language models. The model's operation mechanism, key areas of applicability to text analytics tasks, comparisons with related models for each activity, and a description of certain proprietary models are all covered in this work. The data from several dozen original scientific studies that have been published in the last few years and have garnered the greatest interest from the scientific community were systematized in order to prepare this review. All researchers and students who wish to learn about the most recent developments in the field of natural language text analysis may find this survey helpful. Bidirectional Encoder Representations from Transformers, or BERT for short, is the subject of a thorough investigation that we present. The area of natural language processing holds significant importance in the creation of intelligent systems. To do a variety of activities, one must comprehend the sentence's correct meaning in order to produce the desired result. Computers have a hard time understanding languages because of how context constantly changes. The main challenge in natural language processing tasks is getting computers to understand text context, and BERT is seen as a revolution in this regard. It picks up the language and its meaning in a manner that is quite similar to how the human brain processes meaning from sentences. Its capacity to identify a word from both the left and right contexts of a sentence makes it special. A new era in the perception and comprehension of natural languages has been ushered in with the development of BERT, which could help computers understand natural languages more fully. This study aims to provide readers with a deeper knowledge of the BERT language model and how it is applied to different NLP tasks.

In the realm of artificial intelligence, knowledge graphs have become a fascinating area of research. Relationships between entities are depicted through a structural framework in knowledge graphs. In this paper, we propose to build a domain-specific medicine dictionary (DSMD) based on the principles of knowledge graphs. Our dictionary is composed of structured triples, where each entity is defined as a concept, and these concepts are interconnected through relationships. This comprehensive dictionary boasts more than 348,000 triples, encompassing over 20,000 medicine brands and 1,500 generic medicines. It offers a groundbreaking approach to storing and accessing medical data. Our dictionary facilitates various functionalities, including medicine brand information extraction, brand-specific queries, as well as queries involving two words or question answering. We anticipate that our dictionary will serve a broad spectrum of users, catering to both human users, such as diverse range of healthcare professionals as well as AI applications.

Lily–belong to the genus Lilium is one of the top cut flowers worldwide. Production and propagation of bulblets in vitro is an important approach for high-volume production, but not proved satisfactory. Hence, the aim of this study was to describe and compare the performances of morphological characteristics of the lily bulb in vivo produced by in vitro and conventional culture method and compare the production timelines in vitro vs conventional culture method. In results, it seems clear that in vitro re-culture of lily bulblet was able to be sustained and maintained its growth and so, ontogenic development after their performance in soil. Our results demonstrate that in the conventional pathway, the course of bulblet growth to bulb and ontogenic development took 3–4 growing seasons to reach the adult flowering phase. On the other hand, along with the re-culture in vitro, the course of bulb growth and ontogenic development took 1–2 growing seasons to reach the adult flowering phase because of the increasing initial bulb size and advancement of ontogenic development. Other than bulblet production through bulb scale explant, this study represents the first report on the method of in vitro bulb production of lily through re-culture by in vitro pathway with a comparison of the timelines and ontogenic development obtained from in vitro versus conventional pathway.

Transferring in vitro-cultured Eustoma seedlings to an ex vitro condition (acclimation) is a big challenge that may expose the seedlings to biotic and abiotic stresses, and affect the internal and external structure of the plants. In addition, in vitro-cultured seedlings of Eustoma are difficult to handle and phenotype and physiological traits such as survival and rosette rate may have altered in the acclimation stage. Therefore, the present study aims to examine the effects of blue, red, and white LED light on the growth and development ex vitro of in vitro-cultured seedlings of Eustoma. The results showed that blue LEDs resulted in greater plant height, internode length, and leaf number, increased upper and lower fresh biomass, and higher chlorophyll content compared with treatment by the other LED lights. Higher stomatal density on the abaxial leaf surface was also observed in the blue LED-treated plants, which also showed a higher survival rate and lower rosette rate. In contrast, the white LED-treated plants had the highest leaf width and internode diameter. Acclimation of the Eustoma plants ex vitro suggests that a combination of blue and white LEDs may be advantageous for better growth and development for large-scale production in a controlled environment.

Farmers’ conventional tillage (CT) and residue removal practices in rice-maize systems in South Asia’s Eastern Gangetic Plain (EGP) are input-intensive, costly and soil degradative. We conducted a rice-maize-mungbean (R-M-MB) system experiment with six tillage and three residue management treatments in Bangladesh representing the EGP. Maize yields were significantly (p≤0.05) higher under permanent (PB) or fresh (FB) beds and strip tillage (ST) than CT but no differences in mungbean yields. Rice yields under PB, FB and CT were similar, but significantly higher than under zero or minimum tillage and ST. Yields of all crops increased significantly (p≤0.05) with residue retention compared to no retention. Total system productivity was highest under PB followed by FB and ST. Compared with CT, gross margins in PB, FB and ST increased by 18, 13 and 11%, and soil organic matter (SOM) and total N contents across tillage treatments increased by 11-16% and 12-24%, respectively. After three years, SOM and total N and available P and S contents increased significantly (p≤0.05) by residue retention. Results demonstrate the potential of PB, FB and ST with residue retention, for improving the productivity, profitability and soil health under R-M-MB systems in Bangladesh and similar soils in the EGP.

Increased nutrient withdrawal by rapidly expanding intensive cropping systems, in combination with imbalanced fertilization, is leading to potassium (K) depletion from agricultural soils in Asia. There is an urgent need to better understand the soil K-supplying capacity and K-use efficiency of crops to address this issue. Maize is increasingly being grown in rice-based systems in South Asia, particularly in Bangladesh and North East India. The high nutrient extraction, especially K, however, causes concerns for the sustainability of maize production systems in the region. The present study was designed to estimate, through a plant-based method, the magnitude, and variation in K-supplying capacity of a range of soils from the maize-growing areas and the K-use efficiency of maize in Bangladesh. Eighteen diverse soils were collected from several upazillas (or sub-districts) under 11 agro-ecological zones to examine their K-supplying capacity from the soil reserves and from K fertilization (@ 100 mg K kg-1 soil) for successive seven maize crops grown up to V10-V12 in pots inside a net house. A validation field experiment was conducted with five levels of K (0, 40, 80, 120 and 160 kg ha-1) and two fertilizer recommendations based on “Nutrient Expert for Maize-NEM” and “Maize Crop Manager-MCM” decision support tools (DSSs) in 12 farmers’ fields in Rangpur, Rajshahi and Comilla districts in Bangladesh. Grain yield and yield attributes of maize responded significantly (P < 0.001) to K fertilizer, with grain yield increase from 18 to 79% over control in all locations. Total K uptake by plants not receiving K fertilizer, considered as potential K-supplying capacity of the soil in the pot experiment, followed the order: Modhukhali >Mithapukur >Rangpur Sadar >Dinajpur Sadar >Jhinaidah Sadar >Gangachara >Binerpota >Tarash >Gopalpur >Daudkandi >Paba >Modhupur >Nawabganj Sadar >Shibganj >Birganj >Godagari >Barura >Durgapur. Likewise in the validation field experiment, the K-supplying capacity of soils was 83.5, 60.5 and 57.2 kg ha-1 in Rangpur, Rajshahi, and Comilla, respectively. Further, the order of K-supplying capacity for three sites was similar to the results from pot study confirming the applicability of results to other soils and maize-growing areas in Bangladesh and similar soils and areas across South Asia. Based on the results from pot and field experiments, we conclude that the site-specific K management using the fertilizer DSSs can be the better and more efficient K management strategy for maize.

The COVID-19 outbreak has focused attention on the use of social distancing as the primary defence against community infection, yet forcing social animals to maintain that physical distance has presented significant challenges for health authorities and law enforcement. Anecdotal media reports suggest widespread dissatisfaction with social distancing as a policy, yet there is little prior work aimed at measuring community acceptance of social distancing. In this paper, we propose a new approach to measuring attitudes towards social distancing by using social media and sentiment analysis. Over a 4 month period, we found 82.5% of tweets were in favour of social distancing. The results indicate a widespread acceptance of social distancing in the community. We conclude by examining options for estimating the optimal (minimal) social distance required at scale, and the implications for securing widespread community support and acceptance of public health messaging.

The present study investigates the relationship between the transmission of COVID-19 infections and climate indicators in Dhaka City, Bangladesh, using coronavirus infections data available from the Institute of Epidemiology, Disease Control and Research (IEDCR), Bangladesh. The Spearman-ranked correlation test was carried out to study the association of seven climate indicators, including humidity, air quality, minimum temperature, precipitation, maximum temperature, mean temperature and wind speed with the COVID-19 outbreak in Dhaka City, Bangladesh. The study found that, among the seven indicators, only three indicators (air quality, minimum temperature and average temperature) have a significant relationship with new COVID-19 cases. The results of this paper will give health regulators and policymakers valuable information to lessen the COVID-19 infection in Dhaka and other countries around the world.

The application of electrode-based microfluidic devices in biological entity often imposes a problem due to joule heating. The strong applied potentials or micro channels having narrow cross sections generate undesirable temperature inside the microfluidic channels leading to strong thermal distribution inside the micro channel. When intrinsic distribution of temperature, if not fix with threshold value, causes device damage or cell loss. In this work, we investigate the effects of temperature generated due to joules heating effects and we attempt to address the design constraints for minimizing the joule heating effects in the microfluidic device for developing effective microfluidic device. The device reliability was analyzed under different parametric constraints for various types of substrate materials (PDMS, PMMA, Polyimide and glass). We also attempt to investigate the effects of cell reliability due to strong temperature gradients generated through different applied potentials on different cell types. Furthermore, the response of the device performance due to different electrode configuration and different conductivity of the medium was also studied. Our investigation will eventually provide guidelines for microfluidic researchers to fabricate efficient electrode based microfluidic device which will ultimately help to choose a critical channel dimensions, threshold potentials, and conductivity of solutions in order to avoid device damage and cell loss.

Apoptosis, also known as the programmed death of cells, is responsible for maintaining the homeostasis of tissues and this function is carried out by caspases. The process of apoptosis is carried out via two distinct pathways: the extrinsic pathway, which is governed by death receptors, and the intrinsic pathway, also known as the mitochondrial pathway. The BCL-2 protein family encoded by the BCL-2 gene, located at the 18q21.33 chromosomal location, is in charge of regulating the intrinsic pathway, which is responsible for inducing cell death via the permeabilization of the mitochondrial membrane and the release of apoptosis - inducing components. The BCL-2 homology (BH1, BH2, BH3, BH4) domains of this family proteins are crucial for their functioning and their common BH domains allow interactions between members of the same family and can also serve as indications of pro- or anti-apoptotic activity. A direct correlation may be shown between the overexpression of BCL-2 and the postponement of cell death. It has been determined that a change in the expression of BCL-2 is the root cause of a variety of malignancies, including lung, breast, melanoma, and chronic lymphocytic leukemia, Multiple Sclerosis, Diabetes. In this review, we discuss the therapeutic potential of regulating BCL-2 family connections and their relevance to health and disease.

Staphylococcus aureus is a major food-borne pathogen. The ability of S. aureus to produce biofilm is a significant virulence factor triggering its persistence in hostile environments. In this study, we screened a total of 420 different food samples and human hand swabs to detect S. aureus and to determine their biofilm formation ability. Samples analyzed were meat, milk, egg, fish, fast foods, and hand swabs. S. aureus were detected by culturing, staining, biochemical, and PCR. Biofilm formation ability was determined by Congo Red Agar (CRA) plate and Crystal Violet Microtiter Plate (CVMP) tests. The icaA, icaB, icaC, icaD, and bap genes involved in the synthesis of bio-film-forming intracellular adhesion compounds were detected by PCR. About 23.81% (100/420; 95% CI: 14.17-29.98%) samples harbored S. aureus as revealed by detection of the nuc gene. CRA plate revealed 20% of S. aureus isolates as strong biofilm producers, while 69% and 11% as in-termediate and non-biofilm producers, respectively. By the CVMP staining method, 20%, 77%, and 3% of the isolates were found strong, intermediate, and non-biofilm producers. Furthermore, 21% of S. aureus isolates carried at least one biofilm-forming gene, where icaA, icaB, icaC, icaD, and bap genes were detected in 15%, 20%, 7%, 20%, and 10% of the S. aureus isolates, respectively. Bivariate analysis showed high significant correlations (p<0.001) between any of the two adhesion genes of S. aureus isolates. To the best of our knowledge, this is the first study in Bangladesh describing the detection of biofilm-forming S. aureus from foods and hand swabs with molecular-based evidence. Our findings suggest that food samples should be deemed a potential reservoir of biofilm-forming S. aureus that indicates a potential public health significance.