The main objective of this paper is to analyze the stability of existing cracks in two-dimensional materials, we applied the principles of fracture mechanics to calculate the stress intensity factor KI using the integral J .
The stress intensity factor is a common parameter in fracture mechanics, this parameter helps to predict whether a specific crack causes the structure to fail. When this calculated value becomes equal to the material's critical fracture toughness, KIc (a property of the material), catastrophic failure usually occurs.
The determination of the stress intensity factor directly starting from the local state in crack tip is problematic, because the stresses are singular there. For this reason, more indirect energy-based methods are attractive. In this work, KI is calculated using the J-integral and the energy release rate. In addition, the crack growth rate and the number of cycles required to propagate the crack over a certain distance are calculated

This research centered on the investigation of effective strategies for enhancing the mechanical behavior and mobility of industrial devices with mobile elements subjected to three-point torsion loads. Several steps were taken to accomplish the objective of creating effective engineering solutions. One of the beams underwent a sensitivity analysis to determine the effect of each variable in the mass and displacement parameter space. It has been shown that parameterizing the ANSYS input file is effective for finding out how sensitive is the system to the design variables studied. In the future, additional research could be conducted in an effort to generalize the methodology to various models and/or situations.

Sustainability is crucial for technological development of a country, as it is closely intertwined with daily life and functioning of public and private institutions. It is not only a demand for national sovereignty, but it also has immense potential for reducing greenhouse gas emissions and solid waste, as highlighted in conventions such as The Intergovernmental Panel on Climate Change (IPCC) and UN Sustainable Development Goals (SDGs). This work aims to develop a methodology for generating energy from the treatment of chemical waste, using a fuzzy algorithm and converting it into a web platform. Therefore, 5 methodological steps were used for the web platform development, following the methodological aspects. i. Definition of the best web-interface methodology to explore the best technological development path. ii. Construction of an interface prototype using Figma. iii. Coding-implementation of step ii. iv-Tests. v-Coding. Through this web structure using an easy-to-use fuzzy model for practical energy sustainability for small and medium-sized companies, it is expected to improve industrial energy consumption through the reuse of discarded chemical materials. Hence, this project can help society, mainly the manufacturing sector of small and medium industries, the government sector to reach the goals of sustainable development, and the environment by reducing some pollutants with toxic characteristics and high solubility.

One of the key characteristics of pharmaceutical substances is their solubility in pharmaceutically significant mediums. This characteristic reflects the quality of the medication and the rate at which the pharmaceutical substance is released from its dosage form. Decrease in efficiency and difficulty in medical application of pharmaceutical substances is often associated with their low solubility in aqueous solutions. It's worth noting that around 40% of medicinal products are practically insoluble, given that 85% are intended for oral administration, which is the simplest and most convenient form. The encapsulation of medicinal substances can address this issue. In the modern pharmaceutical industry, molecular containers such as cyclodextrinsare used for this purpose. Inclusion of the target component occurs in a "host-guest" manner and is dictated by weak intermolecular interactions, the nature of which is not yet fully understood. It has been proven that encapsulation contributes to stability during storage, improved taste qualities, enhanced pharmacological activity and bioavailability, reduced side effects, and most importantly, increased solubility of these substances. Our study presents the synthesis of an inclusion complex of nimesulide into the cavity of β-, γ-cyclodextrin. The results of the experiment were confirmed using TLC, HPLC, UV- and IR-spectroscopy, as well as X-ray structural analysis. The theoretical substantiation of the stability of the β-cyclodextrin/nimesulide complex was carried out by one of the most innovative methods, the molecular dynamics method, using the NAMD software at a simulation step of 2 femtoseconds and a duration of 10 nanosecondsThe modified CHARMM36 force field was used as the MD force field. The ability to enhance the solubility of medicinal substances and maintain their stability is a promising direction in the field of pharmaceutical chemistry.

This study evaluated the index and physico-chemical characteristics of lateritic soil classified as A-2-6 (1) in the American Association of State Highway and Transportation Officials (AASHTO) system and SC in the Unified Soil Classification System (USCS) treated with stepped Bacillus sphaericus (Bs) suspension density (i.e., 0, 1.5 x 10⁸, 6.0 x 10⁸, 1.2 x 10⁹, 1.8 x 10⁹, 2.4 x 10⁹ cells/ml) for varying cementation reagent (C_r) concentration (i.e., 0.25, 0.5, 0.75 and 1.0 M)using 25 Bs:75 C_r, 50 Bs:50 C_r, 75 Bs:25 C_r mix ratios, respectively. Results obtained show that the optimum calcium carbonate content was 9.0 %, 8.7 %, and 6.5 % for bacteria-cementation mix ratios stated above, respectively, for Bs (1.2 x 10⁹ cells/ml) and C_r (0.5 M) with urease activity of 80.8 ms/cm and optimum pH of 8.99. Bio-treatment of soil with 25% bacteria (1.2 x 10⁹ cells/ml) and 75% C_r (0.5 M) mix ratio reduced the liquid limit (LL) of the natural soil from 36.5 to 34.2 %, and the plasticity index (PI) from 16.4 to 11.6 %. Microanalysis of specimens showed that the treated soil appears more uniform and aggregated. The findings of the study show that lateritic soil bio-treated with 25 Bs (1.2 x 10⁹ cells/ml) : 75 C_r (0.5 M) mix ratio can improve the index and physico-chemical properties of lateritic soil.

Abstract: Aiming at the problems of target initialization and target tracking failure in images, a visual SLAM algorithm for point-line-plane feature fusion is proposed to improve the accuracy and robustness of automatic localization and map creation in mobile robots. Firstly, a suitable algorithm is selected to extract point features, line features, and planar features, respectively; secondly, a structural constraint model for feature fusion is constructed to build a point, line, and plane fusion visual odometry and a loopback detection module; finally, a structural constraint model is constructed for fusing point, line, and planar features, fusing the data information between frames, realizing the estimation of the camera poses, constructing a global consistency map, and realizing the back-end nonlinear optimization. Compare with the ORB SLAM and LSD SLAM methods, and verify the accuracy and effectiveness of the proposed method in this paper through the TUM dataset. The experimental results show that the plp SLAM method proposed in this paper reduces the average value of the root mean square error of the absolute trajectory by about 0.6 and 20, respectively, compared with the ORB SLAM and LSD SLAM methods, and is able to realize the motion trajectory in an unknown environment, which sufficiently verifies that the plp SLAM method proposed in this paper is feasible and effective.

Amyloidosis is systemic diseases, leading into disfunction of many organs.

There are several clinical and morphological forms of amyloidosis based on the organ-specific nature of the amyloid fibrils deposition, which are found in the heart, brain, kidneys, spleen, liver, pancreas and thyroid glands, bone marrow, intestines. The nature of organ damage correlates with the types of amyloid fibrils. Thus, damage to the tissues of the heart and kidneys are the most significant factors affecting mortality.

The complexity of drug molecules discovery against amyloidosis is connected with the fact the more than 30 proteins are involved in the fibril formation.

The crucial approach for the discovery of drug molecules against cardiac amyloidosis needs the predictive models. The restriction of most developed models connects with their reproducibility and cost. Therefore, in silico approach may be quite effective procedure to minimize time and difficulties during drug discovery process.

In this paper we collected main knowledge which highlights scope and limitations considered during in silico approach development. For this the publications including patents covered past 20 years have been analyzed.

This research was funded by the Russian Science Foundation, project number 21-74-20093. Link to information about the project: https://rscf.ru/en/project/21-74-20093/

Background : Needle phobia is one of the most common fear inducing, painful and uncomfortable procedure in pediatric dentistry. Managing procedural distress can provide both short- and long-term benefits by increasing compliance and reducing avoidance behavior in dental care. Therefore, an expanded focus on fear-reducing interventions is advised for needle operations in addition to pain management.

Aim : Evaluation and comparison of efficacy of extraoral vibratory stimulus with and without coolant in alleviating pain and anxiety among children receiving inferior alveolar nerve block.

Methodology : A randomized clinical study was conducted in 66 children of age 7-13 years, and were divided into two groups receiving inferior alveolar nerve block along with extraoral vibratory stimulus (group 1) and extraoral vibratory stimulus with a coolant (group 2). Pulse rate, pain and anxiety were assessed using pulse oximeter, Wong-Baker faces pain scale, FLACC scale and modified child dental anxiety scale-faces (MCDAS-F).

Results : Lower pain sensation and anxiety was recorded in the group using combined external coolant and vibratory stimulus. Kruskal-Wallis test showed statistically significant difference in the pre and post treatment score of group 2 for MCDAS anxiety scale (p value = 0.003) and WBFPS pain scale (p value = <0.001)

Conclusion : Vibratory device with coolant can be an effective alternative in reducing pain and anxiety in children receiving inferior alveolar nerve block and can be a promising tool in pediatric dentistry.

Determining the mode choice for movement in developing cities like Dhaka is beset with multifaceted challenges and intricacies, rendering it an arduous undertaking. Numerous factors contribute to the complexity, thereby impeding the selection of an optimal transportation mode. Bangladesh University of Engineering & Technology (BUET) attracts students from various regions and cultures in Dhaka city. Both on-campus and off-campus students select their preferable mode while traveling to their university based on different factors which affect their choice. Mode performance for off-campus students is significant because of time management, academic success, convenience, flexibility, safety, security, financial considerations, and most importantly as they reside in different locations from the campus of the university. Examining users' perceptions of the choice of preferred modes of transportation in Dhaka city is the primary objective of this study. Transportation performance of buses, rickshaws, private vehicles, and institutional buses were considered as the four main modes. Structural equation modeling (SEM) was implemented to create four distinct empirical models to investigate the correlations between key factors that impact mode choice. Models were calibrated using data gathered from 1664 respondents who were formally surveyed to learn about their expectations, experiences, and opinions regarding their usual means of off-campus transportation. There were 20 attributes of travel experience consisting of safety, comfort, travel cost, travel time, waiting time, convenience, reliability, availability, environment- friendliness, travel distance, driver behavior, driving skill, vehicle quality, overtaking tendency, vehicle speed, obeying traffic law, accident probability, weather effect, punctuality of arrival and departure. Moreover, socio-demographic user data on age, gender, method of payment to make trip to institution, travel distance, and time to reach the institution were also amalgamated. Factor analysis and path analysis were conducted using two different statistical software SPSS and STATA 13.
Policy implications have been analyzed in the context of a developing country as Bangladesh from the perceived ratings on mode choice so that by providing reliable, efficient, and student-friendly transportation options; educational institutions, planners, and transportation authorities can support the success and overall well-being of off-campus students.

The “curse of dimensionality” phenomenon in machine learning tasks results in poor generalization when dealing with high-dimensional hyperspectral images (HSIs).To solve this issue, Band selection is a frequently used dimension reduction technique for hyperspectral images that identifies and selects a subset of the most crucial bands from the original ones to remove redundancy and noisy bands while maintaining optimal generalization ability.Band selection methods can be categorized as supervised or unsupervised techniques based on whether labels are used.Unsupervised approaches have the potential for extensive applications since they do not require labeled data, which can be difficult to obtain.Several techniques have been proposed for unsupervised band selection, including Autoencoders (AE), which aim to represent datasets from the original data space to a reduced and more informative feature space. In this study, we propose an innovative framework for unsupervised band selection and feature extraction that trains a sub-neural network to identify the most important and informative bands.The classification performance of the selected band combination on the Indian Pines, Pavia University, and Salinas hyperspectral datasets have been verified using machine learning techniques. Our proposed method not justenhances the classification resultsof HSIs, butalso reduce the computational time when compared to other state-of-the-art band selection approaches.