High Results Research Articles

Seasonality and Generalist Plant Resource Use Drive Bee Community (Hymenoptera, Apidae) composition in herbaceous restinga and dune environments

Few bee inventories have investigated the interaction between bees and plants in the restinga in Santa Catarina State, a highly anthropized coastal environment, due to its value. In this context, in the southern coastal region of the State, the bee community and their foraging resources were ecologically analyzed, aiming to obtain data that support their conservation. For sampling, bees were collected over one year in herbaceous restinga and Laguna (SC) dunes, using entomological nets, trap dishes, and aromatic baits. The bees and plants were prepared, identified, and quantified. Ecological indices were calculated. Eighteen species of bees and sixteen species of associated plants were found. The collector’s curve stabilized, and richness estimators indicated a possible richness of 21.57 to 26.25 species. The five subfamilies of bees occurring in Brazil were found, with Halictinae having the highest richness and Apinae having the greatest abundance. Andreninae showed only one species (Callonychium luteimaculatum), as abundant as Apis mellifera. The plants most visited in terms of bee diversity are typical of the restinga and are highly attractive to bees. The periods with the highest results were spring and summer. The variation in temperature and the increase in plant richness increased bee abundance and richness, highlighting the region’s seasonality. The bee community showed a conservative generalist condition, which is favorable for species living in inhospitable conditions, providing moderate robustness. Due to the lack or absence of nesting resources, the studied bee community appears to originate from nearby adjacent areas.

Hen’s egg white allergy in adults leading to strong impairment of quality of life

In adulthood, hen’s egg white allergy (EWA) is a rare condition and rising in prevalence. Typically, EWA begins in early childhood and resolves at school age. Persistence into adulthood or newly onset of the allergy has been reported, but scientific data is scarce. Symptoms reach from typical gastrointestinal problems to severe systemic reactions. EWA and the fear of allergic reactions lead to drastic restrictions in diet as in social life of the affected individuals. This study aims to assess health related quality of life (HRQoL) in adults with EWA using the validated questionnaire “Food Allergy Quality of Life Questionnaire - adult form (FAQoLQ-AF)” and Food Allergy Independent Measure (FAIM). Between July 2023 and October 2023, 16 adults with hen’s egg white allergy were identified and questioned using the FAQoLQ-AF to evaluate HRQoL. Patients’ characteristics were obtained including age at allergy onset and the most severe allergic symptom. The results were summarized using descriptive statistical analysis. HRQoL was impaired in 16/16 allergic individuals with an overall mean score of 4.64/7 (SD 1.3). Self-assessed emotional impact of the EWA was more problematic than food allergy related health. Food Allergy Independence Measure (FAIM) mean score was 4.64 (SD 1.0) with highest result in product avoidance. The most frequent occurring symptoms were oral allergy syndrome and stomach pain in 7 (44%) patients each. This study shows impaired HRQoL in a small cohort of adults with hen’s egg white allergy using the FAQoLQ and FAIM questionnaire with special emphasis on emotional impact. We identified an urgent need for correct food labelling and research into safe treatment options to improve HRQoL.

Automatic segmentation, classification, and prediction of pelvic bone tumors using deep learning techniques

AbstractMRI and CT images are widely utilized for detecting tumors in internal organs. However, accurately distinguishing tumors using these images only, poses a challenge. This demands human expertise to effectively mark tumors in a given MRI or CT image, which is time-consuming. In this study, MONAI Label and MONAI Dynamic U-Net (DynU-Net) were used to segment tumors in any given 3D CT image of the pelvic bone, aiming to assist radiologists further. This method helps to run the model without needing a GPU which is better than traditional approaches. In addition, a convolutional neural network (CNN) was used to classify the tumors as benign or malignant and to predict three grades of tumors (low, medium, and high). The use of CNN in classification and prediction gives higher results than other studies. A dataset of 178 3D CT picture images was employed to feed the networks with the help of Adam optimizer and Categorical cross-entropy. We employ a set of 3D CT scans because of their greater contrast and spatial resolution which is better used for pelvic bone tumors. The Dice similarity coefficient (DSC) and Hausdorff distance (HD) have been used to perform calculations in segmentation. The results show a DSC of 0.7660280 and an HD of 16.75480. A range of performance metrics, such as sensitivity, specification, and F1-score for classification and prediction methods, are used to evaluate the accuracy of the proposed system. The system has accuracy (99.4%) for classification and (97.8%) for prediction. These findings indicate that MONAI Label is effective for automatic segmentation of tumors in a given CT scan; with high accuracy. Moreover, CNN is useful for classification and prediction systems with high accuracy. However, achieving better results is possible with an abundance of training samples.

Exploration of Polysaccharides and Oligosaccharides from Jali (Coix Lacryma-jobi) and Its Potential as Prebiotic

Jali (Coix lacryma-jobi) is a cereal plant widely used as a functional food because it contains carbohydrate compounds, such as polysaccharides and oligosaccharides with a positive impact on the digestive system. This study was divided into two stages, namely extraction Jali and prebiotic analysis. The extraction method used was hot water extraction and alkali extraction according to their solubility in solvents. The prebiotic activity of oligosaccharide and polysaccharide extracts from jali was evaluated using in-vitro analysis. Therefore, this study aimed to explore polysaccharides and oligosaccharides in jali and their potential to act as prebiotic. The results showed that the extraction process affected the types of oligosaccharides, namely Fructooligosaccharides (FOS), as well as polysaccharides, including α-glucan and arabinoxylan. In this study, FOS and α-glucan were obtained by heating at 80 °C for 60 minutes, while arabinoxylan was extracted by heating at 80 °C for 120 minutes. The results of crude extracts of FOS and arabinoxylan were tested for HPLC analysis, while α-glucan was explored using FTIR. The jali seeds exhibited a remarkable FOS content of 40.78%, while their arabinoxylan composition included 22.4% arabinose and 4.8% xylose. In addition, the FTIR analysis revealed the presence of (14) (16) -α-D-glucan bond in jali seeds. The results showed that the extraction from the polysaccharide group, namely α-Glucan and Arabinoxylan, as well as from the oligosaccharides (FOS) had potential as prebiotic for the growth of Bifidobacterium longum and Lactobacillus casei. However, the highest results were based on OD and SCFA from the FOS extract. The addition of FOS affected the growth of Bifidobacterium longum more significantly (OD 0,871) compared to Lactobacillus casei (OD 0,725). Bifidobacterium longum exhibited SCFA levels of 243,827 mmol/L, while Lactobacillus casei showed levels of 140,942 mmol/L.

Comparison of Different Linseed Genotypes Meal in Terms of Feed Value Properties

This study was conducted to determine the nutritional content and nutritive values of some varieties of linseed meal. For this purpose, neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), crude ash (CA), and crude protein (CP) analyses were performed on meals obtained from 13 different linseed varieties (Clli 1423, Larkana, Milas, NewTurk, Dillman, Sari-85, Clli 1351, Clli 1370, Clli 1400, Clli 1412, Karakız, Beyaz Gelin, Noreum) in order to determine some nutritional content. Based on some data obtained from these analyses, nutritive values such as dry matter digestibility (DMD), dry matter intake (DMI), relative feed value (RFV), metabolizable energy (ME), and net energy for lactation (NEL) were calculated. In terms of nutritional content, the NDF, ADF, ADL, and CP contents of linseed meals were found to be significant, while the CA content was not found to be significant. The NDF, ADF, ADL, and CP contents of the meal varied within the ranges of %58.40-96.37, %18.62-35.64, %8.55-20.45, and %34.84-41.21, respectively. In terms of nutritive value characteristics, the DMD, ME, and NEL properties of linseed meal were found to be significant, while the DMI and RFV features were deemed insignificant. The DMD, ME, and NEL values of the meal varied within the ranges of %61.14-74.39, 9.35-11.91 MJ/kg, and 1.37-1.81 Mcal/kg, respectively. In conclusion, it was determined that among the linseed varieties, the highest results in terms of both nutritional content and nutritive value were provided by the NewTurk variety, while the worst results were generally observed in the Beyaz Gelin variety. However, it was concluded that the meals from all evaluated linseed varieties could be utilized in the intensive feed industry.

Sleep apnea test prediction based on Electronic Health Records

The identification of Obstructive Sleep Apnea (OSA) is done by a Polysomnography test which is often done in later ages. Being able to notify potential insured members at earlier ages is desirable. For that, we develop predictive models that rely on Electronic Health Records (EHR) and predict whether a person will go through a sleep apnea test after the age of 50. A major challenge is the variability in EHR records in various insured members over the years, which this study investigates as well in the context of controls matching, and prediction. Since there are many temporal variables, the RankLi method was introduced for temporal variable selection. This approach employs the t-test to calculate a divergence score for each temporal variable between the target classes. We also investigate here the need to consider the number of EHR records, as part of control matching, and whether modeling separately for subgroups according to the number of EHR records is more effective. For each prediction task, we trained 4 different classifiers including 1-CNN, LSTM, Random Forest, and Logistic Regression, on data until the age of 40 or 50, and on several numbers of temporal variables. Using the number of EHR records for control matching was found crucial, and using learning models for subsets of the population according to the number of EHR records they have was found more effective. The deep learning models, particularly the 1-CNN, achieved the highest balanced accuracy and AUC scores in both male and female groups. In the male group, the highest results were also observed at age 50 with 100 temporal variables, resulting in a balanced accuracy of 90% and an AUC of 93%.

Bacterial endophyte Pseudomonas mosselii PR5 improves growth, nutrient accumulation, and yield of rice (Oryza sativa L.) through various application methods

BackgroundPseudomonas spp. have drawn considerable attention due to their rhizospheric abundance and exceptional plant growth-promoting attributes. However, more research is needed on the optimal application methods of Pseudomonas mosselii for rice growth, nutrient accumulation, and yield improvement. This research explored the application of the endophytic bacterium P. mosselii PR5 on rice cultivar BRRI dhan29 with four treatments: control, seedling priming, root drenching, and bacterial cell-free culture (CFC) foliar application.ResultsPR5 led to better rice growth, improved nutrient acquisition, and higher yields compared to the control, regardless of the application method used. The highest results in fresh weight of root (146.93 g/pot), shoot (758.98 g/pot), and flag leaf (7.88 g/pot), dry weight of root (42.16 g/pot), shoot (97.32 g/pot), and flag leaf (2.69 g/pot), and grains/panicle (224.67), were obtained from seedling priming treatment, whereas root drenching resulted in maximum plant height (105.67 cm), root length (49.0 cm), tillers/pot (23.7), and panicles/pot (17.67). In all three application methods, rice grain yield per pot was higher in PR5 inoculated treatments, compared to the control. The amount of P, Mg and Zn in the shoot and N, P, Ca, Mg and Si content in the flag leaf was significantly increased along with effective suppression of naturally occurring blast disease in bacterial CFC foliar application, validated by multivariate analysis.ConclusionOur results indicated that rice seedlings priming with PR5 improved rice growth, yield and nutrient uptake, whereas CFC foliar application significantly increased the concentration of most nutrients in the rice plant and suppressed the naturally occurring rice blast disease. This research highlights the significant potential of P. mosselii PR5 in enhancing rice growth, yield, and nutrient uptake, particularly through seedling priming and CFC foliar application methods.

Selected Actinomycetes as Potential Biostimulant of Eggplant (Solanum melongena L) in Mali

Aims: This study aims to formulate at least one efficient biostimulant based on actinomycetes that promotes good eggplant growth in Mali. Study Design: The experimental design was a completely randomized block design with three replications and four treatments randomly distributed. The treatments were three Actinomycete strains (Act, S1 and St1) and a non inoculated control and the mode of application (inoculation or spraying) of these treatments were considered as blocking factor. Place and Duration of Study: The trials were conducted in Bamako, in the Greenhouse of the LaboREM-Biotech situated on the colline of Badalabougou. Methodology: Eggplant seeds inoculated or not with Actinomyces sp. Ts1, Actinomyces sp. S1 and Actinomyces sp. Act; were randomly sown in plastic pots filled with approximately 2.50 kg of air-dried soil. The first block sown with coated seeds and the second with non-inoculated seeds and seedlings from them pulverized. Leaf length, leaf area, leaf diameter, leaf area, leaf fresh weight, leaf dry weight, root fresh weight, root dry weight, plant height and root length were determined. Results: Eggplant seed inoculated with all the tested Actinomycetes strains had significantly enhanced leaf length, leaf diameter, leaf area, leaves fresh weight. The highest results were obtained with the strain Act, followed by strain St1. Sprayed treatment improved eggplant leaf length, leaf diameter, leaf area, leaves fresh weight, leaves dry weight, root fresh weight, root dry weight; compared to the coated treatment Conclusion: Field application of actinomyctes may reduce production cost, by increasing eggplant growth and fruit yield while reducing production cost. The present work showed that Act and Ts1 using spray method were best suited for eggplant. Actinomyces sp. Act produced the highest leaf length, leaf diameter, leaf area, leaves fresh weight. Therefore, Actinomyces sp. Act is suggested as bioinoculant for eggplant.

Effect of probiotics 'Bio-health' and foliar fertilization with zinc sulfate on growth and yield of okra (Abelmoschus esculentus (L.) Moench)

The experiment was conducted in a private field in Jaflawiya, Al-Mishkhab District, Najaf Governorate, for the spring season 2021, to study the effect of soil application with probiotics Bio health and foliar fertilization with aqueous zinc sulfate on some vegetative growth characteristics and yield of okra Husainawia variety. The experiment was a factorial experiment according to Randomized Complete Block Design (R.C.B.D.) with 2 factors and 3 replicates. The first factor was ground application with probiotics Bio health at 3 levels (0, 2500, 5000 g ha-1) and the second factor is the foliar spraying of zinc in (ZnSO4.7H20) using 3 concentrations (0, 75 and 150 mg L-1). Both factors were applied 3 times during the growing season. The first application was in the stage of 4 true leaves and zinc was sprayed a week later. The second and third were 30 and 60 days after the first addition respectively. Analysis of variance (ANOVA) was performed and the averages were compared using the least significant difference test. Least Significant Difference Test (L.S.D.) at 0.05 probability level. The highest results were recorded in the treatment of adding the Bio health at a level of 5000 g ha-1, which led to the highest rates of vegetative growth indicators, quantitative and qualitative yield and chemical indicators, including plant height, leaf area, knot ratio, number of pods, total yield, nitrogen and phosphorous ratio in pods, zinc content in pods and protein % in pods. In general, the ground application of Bio health at 5000 g ha-1 with zinc 150 mg L-1 significantly outperformed most of the single and interaction treatments. It gave the highest significant increase in vegetative growth indicators, yield, chemical and qualitative indicators.

Multi-modal classification of breast cancer lesions in Digital Mammography and contrast enhanced spectral mammography images

Breast cancer ranks as the second most prevalent cancer in women, recognized as one of the most dangerous types of cancer, and is on the rise globally. Regular screenings are essential for early-stage treatment. Digital mammography (DM) is the most recognized and widely used technique for breast cancer screening. Contrast-Enhanced Spectral Mammography (CESM or CM) is used in conjunction with DM to detect and identify hidden abnormalities, particularly in dense breast tissue where DM alone might not be as effective. In this work, we explore the effectiveness of each modality (CM, DM, or both) in detecting breast cancer lesions using deep learning methods. We introduce an architecture for detecting and classifying breast cancer lesions in DM and CM images in Craniocaudal (CC) and Mediolateral Oblique (MLO) views. The proposed architecture (JointNet) consists of a convolution module for extracting local features, a transformer module for extracting long-range features, and a feature fusion layer to fuse the local features, global features, and global features weighted based on the local ones. This significantly enhances the accuracy of classifying DM and CM images into normal or abnormal categories and lesion classification into benign or malignant. Using our architecture as a backbone, three lesion classification pipelines are introduced that utilize attention mechanisms focused on lesion shape, texture, and overall breast texture, examining the critical features for effective lesion classification. The results demonstrate that our proposed methods outperform their components in classifying images as normal or abnormal and mitigate the limitations of independently using the transformer module or the convolution module. An ensemble model is also introduced to explore the effect of each modality and each view to increase our baseline architecture's accuracy. The results demonstrate superior performance compared with other similar works. The best performance on DM images was achieved with the semi-automatic AOL Lesion Classification Pipeline, yielding an accuracy of 98.85 %, AUROC of 0.9965, F1-score of 98.85 %, precision of 98.85 %, and specificity of 98.85 %. For CM images, the highest results were obtained using the automatic AOL Lesion Classification Pipeline, with an accuracy of 97.47 %, AUROC of 0.9771, F1-score of 97.34 %, precision of 94.45 %, and specificity of 97.23 %. The semi-automatic ensemble AOL Classification Pipeline provided the best overall performance when using both DM and CM images, with an accuracy of 94.74 %, F1-score of 97.67 %, specificity of 93.75 %, and sensitivity of 95.45 %. Furthermore, we explore the comparative effectiveness of CM and DM images in deep learning models, indicating that while CM images offer clearer insights to the human eye, our model trained on DM images yields better results using Attention on Lesion (AOL) techniques. The research also suggests a multimodal approach using both DM and CM images and ensemble learning could provide more robust classification outcomes.

T. MARTEMIANOVA’S PROPAEDEUTIC COURSE “PRO-PHYSICS”: EXPERIMENTAL EVALUATION OF EFFECTIVENESS

The purpose of this work was to evaluate the effectiveness of the propaedeutic course “PRO-physics” by T. Martemianova. The methods of this research are: analysis of sources on the issues of propaedeutics of physics, empirical methods (analysis of data arrays from electronic systems of educational process management, lists of winners and prize-winners of olympiads, statistics of admission to universities, survey methods), statistical methods of results processing. The study proposes a methodology for assessing the effectiveness of propaedeutic courses. The study revealed that students who took the “PRO-physics” propaedeutic course programme subsequently have higher results in physics olympiads at all levels, more often enter universities from the top 20 of the RAEX rating, better cope with intermediate and final control activities in physics within the framework of school education. The results of the questionnaire survey of teachers and students have shown high efficiency of the propaedeutic course under consideration.

A-220 Method Intercomparison Study between Atellica Solution® and CI® Analyzers for HDL and LDL Methods

Abstract Background After validating a new Siemens equipment, the Atellica CI®, it is essential to ensure result interchangeability in our laboratory accredited by ISO 15189:2012. Objectives verify if the results of the HDL and LDL methods measured by Atellica Solution® and CI® analyzers are interchangeable and could be used interchangeably on both instruments Methods 40 patient samples were selected for each assay, with results distributed across the entire measurement range and analyzed by both instruments. Result evaluation was conducted using the statistical program Method Validator v.19. To determine the degree of agreement between the instruments, a Bland-Altman mean difference analysis and a Passing-Bablok regression were performed. Statistics are expressed with their 95% confidence intervals (CI). Results HDL: After analyzing the Bland-Altman differences, a systematic error was found as the mean difference between the results obtained by Atellica Solution® and CI® was 0.686, with higher results in CI 1900®. Regarding the Passing Bablok analysis, constant systematic differences were observed as the confidence interval of the intercept does not include the zero value, and statistically significant proportional differences based on the slope whose 95% CI does not include the value 1.LDL: After analyzing the Bland-Altman differences, a systematic error was found as the mean difference between the results obtained by Atellica and CI® was -3.16, with higher results in Atellica Solution®. Regarding the Passing Bablok analysis, there were no systematic differences of constant type as the confidence interval of the intercept includes the zero value, but there were proportional differences based on the slope whose 95% CI does not include the value 1. Conclusions After evaluating the results, it is concluded that Atellica Solution® and CI® analyzers are interchangeable for HDL and LDL assays despite the presence of a systematic error, as the observed difference is not clinically significant.

A-219 Method Intercomparison Study between Atellica Solution® and CI® Analyzers for Total Cholesterol and Triglycerides

Abstract Background Method intercomparison is an essential requirement that every Laboratory must perform when considering a method or instrument change for a specific analyte. Objective verify if the results of two analytical techniques (Total Cholesterol and Triglycerides) measured by Atellica Solution® and CI® analyzers (Siemens Healthineers) are interchangeable. Methods 40 patient samples were selected for each assay, with results distributed across the entire measurement range and analyzed by both instruments. Estatistical program Method Validator was used. To determine the degree of agreement between both instruments, Bland-Altman difference analysis and Passing-Bablok regression were performed. Statistics are expressed with their 95% confidence intervals. Results Total Cholesterol: After analyzing Bland-Altman differences, a systematic error was found as the mean difference between the results obtained by Atellica Solution® and CI 1900® was 13.8 with a 95% CI that does not include the null value. Regarding Passing Bablok analysis, a constant systematic difference was observed as the confidence interval of the intercept does not include the zero value, and also a proportional difference based on the 95% CI of the slope that does not include the value 1.• Triglycerides: After analyzing the Bland-Altman differences, a systematic error was found as the mean difference between the results obtained by Atellica Solution® and CI 1900® was -15.6, with higher results in Atellica Solution®. Regarding the Passing Bablok analysis, constant systematic differences were observed as the confidence interval of the intercept does not include the zero value, and also proportional differences based on the slope, whose 95% CI does not include the value 1 Conclusions It´s concluded that Atellica Solution® and CI® analyzers are not interchangeable for Total Cholesterol and Triglycerides assays due to the presence of a constant systematic error. To use them on both instruments, it would be advisable to modify the reference values for both methods.

Long-term outcomes and trends in elbow arthroplasty with Coonrad-Morrey prosthesis: a retrospective study in large group of patients.

Total Elbow Arthroplasty (TEA) was first developed to treat severe rheumatoid arthritis, but its uses have grown to encompass end-stage osteoarthritis, post-traumatic arthritis, and distal humeral fractures. This study analyzes indications changes, long-term survival, complications, and post-operative functional results of the Coonrad-Morrey prostheses, enhancing the existing literature on this technique and substantial case history. We included 122 arthroplasties in 117 patients, 28 males and 89 females (mean age of 67 years) treated in our hospital between 2002 and 2016. Minimum follow-up was four years. We collect functional parameters of 48 patients (51 elbows), due to death of patients due to old age and loss at follow-up. Survival rate at five years was 90%, 85% at 10 years and 83% at 15 years. The overall medium Mayo elbow score was 79.7 ± 18.3 with the highest result in osteoarthritis patients (p < 0.005); QuickDASH score was 33.1 ± 25.5 with the worse result in rheumatoid group. Average post-operative arc of motion (ROM) was 95°±27°. There were complications in 46 out of 122 cases (37.7%) and revision surgeries were performed in 12 of them (9.8%): seven aseptic loosening, four late septic loosening, one bushing wear. In 27 instances (22.1%) was reported ulnar nerve involvement. Coonrad-Morrey prosthesis has shown satisfactory clinical results in the treatment of a wide range of pathologies. The long-term implant survivorship was satisfactory, yet the occurrence of failures and complications cannot be overlooked, above all the ulnar nerve paresthesia. There was a good recovery in quality of life, pain-free with limited residual limb disability.

Impact of Vermicompost and Different Plant Activators on Yield and Some Quality Parameters in Pumpkin (Cucurbita pepo L.)

In addition to being used as a snack, pumpkin seeds are an industrial product. It also has the potential to be used in the food, pharmaceutical, and cosmetic industries. Seed yield and quality are traits of economic importance. This study aims to determine the effect of vermicompost and different plant activators on the yield and some parameters of the pumpkin's quality. For this purpose, three plant activators [(ISR-2000 (I), Symbion-Vam (S), and Green-Miracle (G)] together with vermicompost (V) have been used. The experiment was conducted in the field of the Cukurova University Pozantı Agricultural Research and Application Center, Turkey. A total of 8 applications were made. Conventional fertilizer (CF) application was determined as the control group. The results showed that the applications increased the snack pumpkin's fruit, seed yield, and quality. The highest fruit and seed yield was obtained from CF (37.2 t ha-1, 101.42 g-1m2) application, followed by V+I (27.1 t ha -1, 80.09 g-1m2) application. Additionally, CF applications resulted in the highest fruit width (14.82 cm), length (23.31 cm), seed width (10.21 mm), and length (20.66 mm) of internal weight (74.33 %) measurements. Regarding mineral element and phenolic content, higher results were obtained when vermicompost and plant activators were combined. According to the study results, different doses of vermicompost may be recommended as an alternative to conventional fertilizer application in future studies.

Solubility Enhancement of BCS Class II Antibiotic (Azithromycin) by Solid Dispersion Technique by Using Skimmed Milk

Azithromycin has a low water solubility; Hence, dissolution represents a rate-limiting process. The goal of the present investigation is to improve azithromycin dissolution and solubility rate. The purpose of this study was to create, characterize, and test the dissolving characteristics of an Azithromycin solid dispersion with skimmed milk. Formulated tablet of optimized batch compared with marketed formulation and study its drug release and make a formulation that gives the highest rate of solubility. This experiment was conducted utilizing the solid dispersion method. The rationale for solid dispersion is that it produces better results than other methods while costing less. Skimmed milk is used as a carrier to increase the solubility of azithromycin. Azithromycin purity is certified using assessment tests such as HPLC assay, UV spectroscopy, FTIR, and DSC. Azithromycin solid dispersion (Azithromycin in skimmed milk) SD2 consistently performs well in all physiochemical tests as compared to all batches. The designed tablet F2 batch releases the drug more effectively than the marketed one. Azithromycin’s solubility was successfully enhanced by utilizing the solid dispersion method with skimmed milk. Batch SD 2 gives the highest results in all parameters like solubility. Preformulation study, mainly in tablet formulation, also it gives the highest solubility.

HỌC BIỂU DIỄN CÂU SỬ DỤNG MÔ HÌNH LSTM TRONG BÀI TOÁN TÌM KIẾM CÂU HỎI

Learning sentence representation with the full semantics of a document is a challenge in natural language processing problems because if the semantic representation vector of the sentence is suitable, it will increase the performance of finding similar question problems. In this paper, we propose implementing a series of LSTM models with different ways of extracting sentence representations and applying them to question retrieval to exploit the hidden semantics of sentences. These methods give sentence representation from hidden layers of the LSTM model. The results show that the technique using a combination of both Max Pooling and Mean Pooling gives the highest results on the 2017 SemEval dataset for the problem of finding similarity questions. Keywords: LSTM; Deep Learning; NLP; QA; learning sentence representation; CQA.

Implementation of MOORA and MOORSA Methods in Supporting Computer Lecturer Selection Decisions

The selection of computer science lecturers is an important process for educational institutions, requiring a balanced assessment of various criteria to find the most suitable candidates. This paper examines the implementation of Multi-Objective Optimization based on Ratio Analysis (MOORA) and its variant, namely Multi-Objective Optimization based on Ratio Analysis with a Subjective Attitude (MOORSA), as a tool to support decision making. in this case. This selection process is often complex, requiring consideration of various criteria, such as academic qualifications, teaching experience, research capabilities, and others. This research was conducted to support the decision-making process. by developing a Decision Support System (DSS) using the Multi-Objective Optimization on The Basic of Ratio Analysis (MOORA) and MOORSA methods. Many methods are used, such as SAW, AHP, Topsis and others. based on the calculation of the MOORA method, the highest result has been achieved by A1 worth 0.651819 and similarly, in the MOOSRA method the highest alternative result is A1 worth 0.592177.

Informative genetic markers of predisposition to the formation of high-level intelligence

This study is devoted to investigating the association of intelligence with a person’s genotype. Comparative psychological and molecular genetic testing was carried out on a representative sample of Belarusian population representatives numbering 746 people. Intelligence quotient (IQ) was determined using D. Wechsler’s test. It was established that the distribution of general intelligence values among the Belarusian population representatives was shifted towards higher results. The persons were divided into low and high IQ groups using the quartile method. The association of intelligence level with genotype was determined using a panel of genetic markers consisting of 18 gene polymorphic variants of neurogenesis, synaptic plasticity and neurotransmitter systems. Molecular genetic testing was carried out using real-time PCR. To automate a search for informative gene combinations associated with cognitive abilities, we used a special computer program that we had previously developed, taking into account the gene interaction effects. 15 most informative combinations of polymorphic gene variants associated with a high intelligence level were identified. These gene variants can be used to assess a genetic predisposition to the formation of high-level intelligence, which will allow assessing the abilities of candidates for extreme activities.

A Comparison of Two Fluorescent Stains for the Evaluation of Bioceramic Sealer Penetration into the Tubular Dentine Using Confocal Microscopy

This study aimed to compare the percentage of bioceramic sealer penetration and maximum penetration sealer depending on the fluorescent staining method when evaluated with confocal laser scanning microscopy (CLSM). In total, 42 single-rooted premolars were instrumented. Two groups of 20 teeth each were filled using the single cone technique. TotalFill BC Sealer® mixed with Rhodamine B was used for the first group and TotalFill BC Sealer® mixed with Fluo-3 for the second group. Two teeth made up the control group. All teeth were sectioned at 3 and 6 mm from the apex and were analyzed with CLSM. The canal perimeter where the tubular penetration happened and the maximum penetration of each sample were calculated. There were no significant differences between the two groups in either the apical or medial sections. In terms of maximum penetration, Rhodamine B had greater tubular penetration in the apical sections, and it had similar results to Fluo-3 in the medial sections. TotalFill BC Sealer® has a higher tubular penetration in the medial slices than in the apical slices regardless of the fluorescent stain used. Rhodamine B has higher results than Fluo-3 in terms of the percentage of sealer penetration and maximum penetration.