Averaged Research Articles

Engineering region flexibility of cellobiohydrolase Ⅰ for efficient hydrolysis of cellulose based on molecular dynamics simulation

Cellobiohydrolase, a workhorse enzyme for cellulose degradation, has the potential for application in biofuels, biochemicals, biomaterials, etc. However, highly efficient cellobiohydrolase is desirable to improve the economic feasibility of industrial applications. In this work, two variants TrCel7AT97A and TrCel7AK166A were designed to increase the flexibility of the entrance of the catalytic tunnel. We performed the molecular dynamics simulations using NAMD for 100 ns at 300 K in the NPT (isothermal–isobaric) ensemble and then we found that the region flexibility at the catalytic tunnel entrances of TrCel7AT97A and TrCel7AK166A was improved, compared to that of TrCel7A, based on the calculation of the average root mean square fluctuation. The specific activities of TrCel7AT97A and TrCel7AK166A were increased by 37 % and 68 %, respectively, compared with that of TrCel7A at 45 °C for 12 h. An effective approach named revive amino acid flexibility for enzyme activity based on amino acid flexibility was proposed for protein engineering of cellobiohydrolase TrCel7A.

Assessment of the sheet steel surface roughness to justify the target values of its parameters

Sheet steel roughness estimation is considered as determination of influence of surface roughness on quality characteristics and production process efficiency. A comprehensive quantitative assessment of the impact of the steel base surface roughness on the quality and quantity of the highest grade of Electrolytic Tinplate was performed. An increase in the Arithmetical mean deviation of the assessed profile (Ra), oriented perpendicular to the rolling direction, increases the tin consumption, worsens the corrosion resistance and stampability of the Electrolytic Tinplate. However, at the same timethe quantity of the highest grade products is increases. Quantitative assessment of the combined effect of the steel base surface roughness, the velocity of strip and the tinning current indicates that the effect of the roughnessis more significant for the stampability and corrosion resistance of the Electrolytic Tinplate. The mass of the coating is been defined largely bythe tinning current strength. The minimum deviation the actual mass of the coating from the nominal, satisfactory corrosion resistance of the Electrolytic Tinplate and a consistently quantity of the highest grade products are observed if the steel base surface roughness issatisfies the restrictions: 0.35 ≤ Ra ≤ 0.63 μm for a class III coating and 0.35 ≤ Ra ≤ 0.55 μm for a class II coatingper GOST 13345–85, nominal mass of which is corresponds to E8,4 and E5,6 coatings per GOST R 52204–2004.

Multi-spectral image transformer descriptor classification combined with molecular tools for early detection of tomato grey mould

Accurate early detection of plant diseases is a critical milestone in the development of self-navigating robots for precision agriculture and still remains one of the most significant challenges. Plant pathogens, like Botrytis cinerea causing grey mould disease, pose significant threats to agriculture and food safety. This study focuses on the early detection of B. cinerea in tomato crops using Artificial Intelligence. Specifically, the Deep Learning (DL) YOLOv8 architecture was employed to apply single class segmentation on plant captures to extract the tomato leaves locational information. Each plant capture includes five images from hyperspectral wavelengths (at 460, 540, 640, 775 and 875 nm) and one RGB images. The leaf segmentation achieved 81.7 % Mean Average Precision (mAP) at Intersection over Union (IoU) threshold 0.5 (mAP50). Then the for each leaf segment, and array of descriptors is extracted through various Transformer models. Finally, the descriptors are classified through a KNN or an LSTM solution and the results of all the descriptors for each leaf from each of the Transformer models, for each of the six images of the capture, are ensembled to yield the class of each leaf. The best ensemble results were produced by only accumulating results from some of the Transformer and specifically the MaxViT-L, the ViT-B (P:16 × 16 – C), the VOLO (D:5) and the XCIT-L (L:24 – P:16 × 16), by only using the results provided by the images at the hyperspectral wavelengths at 540, 640 nm and the RGB image, and by applying the LSTM solution. The process achieved a 79.41 % classification accuracy and 71.12 % F1-Score for all classes. Additionally, early, rapid and accurate detection of grey mould at the early stages of the infection or at latent infections when symptoms are not visible was assessed by comparative qPCR-based methods (qRT-PCR) for fungal biomass estimation in plant tissues and the rest of this study's methodology. The findings of this study represent a significant advancement in crop disease detection and management, and highlight the potential for integrating these methods into on-site digital systems (robots, mobile apps, etc.) under real-world settings. The results, demonstrate the effectiveness of combining segmentation and transformer-based classification models for early and accurate detection of grey mould disease.

Mathematical Model of Drilling Mud Movement along a Shale Shaker Screen

Introduction. When drilling oil or gas wells, rock from the bottomhole is brought to the surface by drilling mud, which is cleaned of sludge by shale shakers at the first stage. Shale shakers are equipped with such a screen and create such trajectories of vibration of the frame in order to solve a dual problem: on the one hand, to provide the cleaning of the drilling mud coming from the well mouth, and on the other hand — to maintain the proper degree of cleaning. To correctly select the nomenclature of screens, it is necessary to reliably determine the throughput capacity of a shale shaker in the real-time setting. This will allow you to pre-order the required number of screens with the required cell size. Previously, studies were conducted by sieving a mixture of calibrated granules on a standard shaker or by straining mineral oil through a fixed screen. However, this does not fully correspond to the actual conditions of drilling mud screening. The objective of this article was to simulate the throughput of a drilling shale shaker under real conditions by calculating the movement of drilling mud along a vibrating screen using its previously obtained specific throughput capacity.Materials and Methods. When creating a mathematical model of the full throughput capacity of a shale shaker, a previously known mathematical model of fluid flow in an open channel and a finite-dimensional approximation in the form of a sequence of sections of concentrated containers connected by hydraulic conductivities (by analogy with the approximation of long electrical lines and extended gas pipelines by the finite element method) were used. The fluid flow rate over the screen was determined according to Chézy law. In this case, the cross-sectional area of the flow above the screen for a specific section was specified as the arithmetic mean between the initial and final values of the drilling mud height in the corresponding section.Results. A chain calculation scheme for sieving drilling mud was compiled. Based on the material balance, mathematical models were developed for determining the throughput and height of drilling mud above the screen: for the first section of the screen and the first nodal point of the screen; for subsequent screen sections and subsequent screen nodal points; for the last section of the screen and the last nodal point of the screen.A mathematical model of the drilling mud movement along the shale shaker screen has been obtained, which, due to the finite-dimensional representation of this flow along n sections of the screen length, is a system of n integral equations describing concentrated tanks, and n – 1 algebraic equations describing the flow of drilling mud between tanks.Discussion and Conclusion. The movement of drilling mud along the length of the shale shaker screen corresponds to the movement of a steady uneven flow in an open channel. However, in the first case, the volume flow along the length is variable (decreasing to zero), and in the second case, it is constant along the length. Therefore, the use of only one differential equation for steady uneven flow in an open channel is not sufficient in this case. The resulting mathematical model of the drilling mud movement along the shale shaker screen is a mathematical basis for the development of a modeling program to determine the throughput of the shale shaker for real operating conditions, i.e., for a specific drilling mud, a given screen or a given drive system of the shale shaker.

Corneal densitometry measurements comparison between anterior segment OCT and scheimpflug imaging

PurposeTo evaluate and compare the repeatability of corneal densitometry (CD) measurements obtained using both an anterior-segment optical coherence tomography (AS-OCT) device and a Scheimpflug camera system, while also assessing the level of agreement. The study also sought to investigate the correlation of CD with age, gender, and central corneal thickness (CCT) in normal eyes.MethodsCD measurements were obtained using the Casia 2 and the Pentacam AXL Wave. Data were collected on Total Corneal Densitometry and 4 concentric corneal annular areas, these are referred to as zone 1, denoting the central area, through to zone 4, designating the outermost peripheral region. Repeatability was assessed using intra-session test–retest variability, coefficient of variation (CoV), and intraclass correlation coefficient (ICC). The agreement was evaluated using Bland–Altman plots. Correlation analysis was performed between CD, age, gender, and CCT.ResultsThe study included 96 healthy volunteers. The Casia 2 demonstrated high repeatability with ICC values exceeding 0.9 in all the corneal zones and lower CoV values compared to the Pentacam AXL Wave (ranging from 1.07% to 2.25% for Casia 2 and from 1.91% to 6.89% for Pentacam).95% LoA were within ± 2 standard deviation from the average mean except from zone 1 (± 2.42).However, the measurements showed a consistent bias among all the corneal zones. CD values were positively correlated with age, except for zone 1 with the Pentacam (p = 0.083).ConclusionsThe findings suggest that the Casia 2 can be a reliable tool for assessing corneal transparency in healthy individuals, however its measurements are not interchangeable with those provided by the Pentacam. The AS-OCT device may be more sensitive in detecting subtle age-related changes in CD within the central zone.

Development of microsatellite markers and evaluation of the genetic diversity of the edible sea anemone Paracondylactissinensis (Cnidaria, Anthozoa) in China.

Paracondylactissinensis Carlgren, 1934 is a sea anemone with economic value in China. The wild population of P.sinensis has been shrinking due to overfishing and environmental pollution, which have caused price instability. In winter, the price of P.sinensis can reach 25 USD per kilogram. Up to now, there are no genetic markers developed for P.sinensis, preventing a further exploration of their population genetic diversity. In this study, the full-length transcriptome of P.sinensis was sequenced and microsatellite DNA markers (simple sequence repeats [SSRs]) were developed from those transcripts. A total of 52 primer pairs, which can amplify specific polymorphic bands in PCR experiments, were designed for the SSR markers. Genetic diversity and population genetics were analysed for P.sinensis populations collected from the coasts of Taizhou and Rizhao using six microsatellite DNA loci. While inbreeding was detected in both populations (Fis > 0), the overall number of alleles (Na = 11.3) and bottleneck analysis suggested that the genetic diversity of P.sinensis has not been greatly impacted. Clustering analyses using STRUCTURE, principal coordinate analysis and unweighted pair group method with arithmetic mean tree revealed that the Taizhou population diverged from the Rizhao population; however, the genetic differentiation between the populations was moderate. Human-mediated commercial activities may be the principal reasons for the gene flow between the populations. Our study provides the first evaluation of the genetic resources of wild P.sinensis populations in China, which can serve as a useful reference for future comparative studies on population genetics and may guide policy-makers in initiating strategies for germplasm conservation and artificial breeding.

Night time Surveillance in Communication Using YOLOv3

Nighttime surveillance presents significant challenges due to low visibility, varying lighting conditions, and interference from artificial light sources. Hence, this study proposed an effective object detection framework using the YOLOv3 model to enhance real-time monitoring in night surveillance applications, specifically within communication and security systems. YOLOv3's architecture, with its multi-scale detection and use of predefined anchor boxes, enables robust detection of objects under low-light environments and amidst light interference from vehicles and streetlights. The proposed system is tested on a night surveillance dataset, where it demonstrates high precision and speed in identifying objects, making it suitable for real-time applications. With Mean Average Precision (mAP) 87.9%, YOLOv3 effectively balances detection accuracy with inference time, ensuring minimal latency in live surveillance feeds. The results indicate that YOLOv3 outperforms traditional models such as Faster RCNN, particularly in detecting small objects under poor illumination. This approach offers a reliable solution for enhancing communication and security systems in nighttime surveillance scenarios.

Research on the Cable-to-Terminal Connection Recognition Based on the YOLOv8-Pose Estimation Model

Substations, as critical nodes for power transmission and distribution, play a pivotal role in ensuring the stability and security of the entire power grid. With the ever-increasing demand for electricity and the growing complexity of grid structures, traditional manual inspection methods for substations can no longer meet the requirements for efficient and safe operation and maintenance. The advent of automated inspection systems has brought revolutionary changes to the power industry. These systems utilize advanced sensor technology, image processing techniques, and artificial intelligence algorithms to achieve real-time monitoring and fault diagnosis of substation equipment. Among these, the recognition of cable-to-terminal connection relationships is a key task for automated inspection systems, and its accuracy directly impacts the system’s diagnostic capabilities and fault prevention levels. However, traditional methods face numerous limitations when dealing with complex power environments, such as inadequate recognition performance under conditions of significant perspective angles and geometric distortions. This paper proposes a cable-to-terminal connection relationship recognition method based on the YOLOv8-pose model. The YOLOv8-pose model combines object detection and pose estimation techniques, significantly improving detection accuracy and real-time performance in environments with small targets and dense occlusions through optimized feature extraction algorithms and enhanced receptive fields. The model achieves an average inference time of 74 milliseconds on the test set, with an accuracy of 92.8%, a recall rate of 91.5%, and an average precision mean of 90.2%. Experimental results demonstrate that the YOLOv8-pose model performs excellently under different angles and complex backgrounds, accurately identifying the connection relationships between terminals and cables, providing reliable technical support for automated substation inspection systems. This research offers an innovative solution for automated substation inspection systems, with significant application prospects.

The Development of Using Lao Language for Communication of Teacher in Phonethong District, Luangprabang Province Academic year 2020 - 2021

The purposes of research are: 1) to develop the teaching of Lao language for communication for teachers at Phonthong secondary School, Phonethong District, Luang Prabang Province, 2). to examine the results of theteaching of Lao language for communication for teachers, and 3). to investigate the teachers’ satisfaction with the learning activities in teaching Lao language for communication for teachers at Phonthong secondary School, Phonethong District, Luang Prabang Province. This study model was the measurement of before and after the pilot activities which employed the one – Group Pretest – Posttest Design for data collection. The target group consisted of 23 Lao language teachers at Phonthong Secondary School, Phonthong District, Luangprabang Province for the academic year 2021. The instruments used for the study comprised of 1) lesson plans on the subject of Lao language for communication for teachers. 2) pre – post tests of training achievement, 3) a questionnaire for eliciting the teachers’ opinions concerning their satisfaction towards the learning activities on the Lao language teaching for communication for teachers, and 4) the assessment form of ability to speak the Lao language for trainees and the collected data was analyzed by means of calculating arithmetic mean, standard deviation and percentage. The result vealed that: 1. The learning activities using teaching the Lao language for communication for teachers as was statistically significant at 0.00 difference with the, mean (after learning) of 12.83 and S.D. of 2.33 (12.83, SD=2.33) which is higher than the mean ( before learning ) of 15.91 and S.D. of 1.96 (15.91, SD=1.96) which is in accordance with the established assumptions. 2. The participants showed the “highest” level of satisfaction towards the learning activities using the teaching of the Lao language for communication for (4.51, SD=0.61). However, when considering each aspect, it could be seen that the participants show the highest “highest” level of satisfaction towards the measurement and evaluation (4.56, SD= 0.60), followed by the environment aspect (4.55, SD= 0.53), teaching and learning activities, application, lesson content and teaching methods (4.50, SD= 0.54), (4.49, SD= 0.61), (4.46, SD= 0.61), (4.43, SD= 0.56) respectively, and they were also concistant with the established assumptions.

أبرز المشكلات الشائعة في مكونات القراءة لدى الطلبة ذوي صعوبات التعلم

The current study aimed to identify the most common problems in the reading components among students with learning disabilities from the perspective of Arabic language course's teachers in government primary schools that contain learning disabilities programs in the education departments in Makkah Al-Mukarramah region, and to study the differences in knowledge levels according to the study variables. The final study sample consisted of (224) male and female teachers. To achieve the objectives of the current study, a descriptive survey approach was used, where a questionnaire was prepared as a tool for collecting data. The questionnaire consisted of (36) statements distributed over five dimensions. The results of the current study showed that the most common problems in the reading components among students with learning disabilities came at a level of (medium) agreement in general, with a general arithmetic mean of (3.155), while at the level of the sub-dimensions of the questionnaire, they all came at a level of (medium) agreement. The results also showed statistically significant differences in the total score averages of the questionnaire according to the gender variable in favor of male teachers, the number of years of experience variable in favor of male teachers who have experience from (1-5 years), and the workplace variable in favor of the education departments in the governorates of Makkah Al-Mukarramah and Taif, while the results showed no statistically significant differences in the total score averages of the scale according to the academic qualification variable. Based on the results reached, the researcher recommended several research recommendations and proposals, the most important of which is that the curriculum should include methods that motivate students to return to linguistic dictionaries and glossaries to search for the meanings of new vocabulary, and conduct additional studies aimed at discovering more scientific facts about the phenomenon of reading problems.

Research on a 3D Point Cloud Map Learning Algorithm Based on Point Normal Constraints.

Laser point clouds are commonly affected by Gaussian and Laplace noise, resulting in decreased accuracy in subsequent surface reconstruction and visualization processes. However, existing point cloud denoising algorithms often overlook the local consistency and density of the point cloud normal vector. A feature map learning algorithm which integrates point normal constraints, Dirichlet energy, and coupled orthogonality bias terms is proposed. Specifically, the Dirichlet energy is employed to penalize the difference between neighboring normal vectors and combined with a coupled orthogonality bias term to enhance the orthogonality between the normal vectors and the subsurface, thereby enhancing the accuracy and robustness of the learned denoising of the feature maps. Additionally, to mitigate the effect of mixing noise, a point cloud density function is introduced to rapidly capture local feature correlations. In experimental findings on the anchor public dataset, the proposed method reduces the average mean square error (MSE) by 0.005 and 0.054 compared to the MRPCA and NLD algorithms, respectively. Moreover, it improves the average signal-to-noise ratio (SNR) by 0.13 DB and 2.14 DB compared to MRPCA and AWLOP, respectively. The proposed algorithm enhances computational efficiency by 27% compared to the RSLDM method. It not only removes mixed noise but also preserves the local geometric features of the point cloud, further improving computational efficiency.

Study on Factors Affecting Performance in the Construction Business of Contractors in the Pakse Municipality, Champasack Province, Lao PDR Case study: Building construction business

The purpose of this research is to examine the key factors that affect the construction business of the construction companies in the Pakse Municipality, Champasack Province of the Lao People's Democratic Republic, which include the business model and operations of the construction company, as well as the analyze of various factors that affect the success of the business. Additionally, the research investigates the causes and methods for preventing or resolving such issues, considering the project's two critical aspects. The data were obtained from 53 construction company utilizing questionnaires. The data was further statistically examined to determine the factors' relative relevance and test the hypothesis. Research results showed 12 major problems: 1) project owner does not pay the agreed-upon construction costs; 2) lack of pre-employment financial assessment; 3) lack of personnel planning; 4) lack of motivation to work; 5) inflation and country's economic insolvency; 6) registered capital and performance of the company; 7) overproduction and overpricing; 8) lack of mechanical planning; 9) lack of planning and control of material use; 10) competitors who are companies from other provinces or abroad; 11) shortage of subcontractors and skilled labor; 12) encouragement-promotion and knowledge of modern construction techniques from the government. Altogether, the two fundamental factors indicated that the most significant issue is within the project, specifically the finances and building budget, with an average mean score of 4.18, which is 100%. As for personnel and staff, the average mean score of 4.14 covers 100%. In terms of sourcing, the average mean score of 3.85, accounting for 83.33%; for tools and construction machinery, the average mean score of 3.78, representing 83.33%. Considering building materials, the average mean score of 3.74, forming 71.42%, and in terms of environment and regulations, the average mean score of 3.74, equivalent to 60 percent of the problems with an average mean score greater than 3.5. The hypothesis testing showed that the value is less than the value. In summary, factors that affect the operation of construction contractor businesses do not depend on whether the contractor is profitable or at a loss/equity, or the importance of the factors does not depend on performance.

Effect of Ultraviolet-C Light Exposure Time on the Dimensional Stability of Addition Silicone Dental Impressions: An In Vitro Study.

To compare the effect of different ultraviolet-C (UV-C) light exposure times on the dimensional stability of addition silicone dental impressions. The dimensional stability of the addition silicone dental impressions was assessed by measuring specific dimensions on dental casts that were recovered from an upper acrylic resin model of dental implants. The impressions were reproduced using a customized tray adapted in a three-point simplex dental articulator permitting only opening and closing movements. Addition silicone dental impressions were divided into five groups (N = 12) according to the UV-C light exposure time. Group A was untreated; group B received 10 minutes; group C, 20 minutes; group D, 30 minutes; and group E, 40 minutes. All the impressions were poured with type IV dental stone and the internal edges of the upper silicone retainers of impression copings were used as five reference points (E, D, C, B, and A) to determine six linear measurements between ED, CB, EA, AD, EB, and CD points using a traveling microscope of 0.001 mm accuracy. One-way analysis of variance (ANOVA) was used for the statistical analysis (p < 0.05). Expansion and contraction were noted among ED, CB, EA, and EB measurements, whereas only expansion was noted among AD and CD measurements. The ANOVA analysis showed there was no significant difference in the arithmetic means for the measurements between and within group A and the other groups (p > 0.05). The UV-C light exposure time of 10, 20, 30, and 40 minutes did not have any negative effect on the dimensional stability of the addition silicone dental impressions evaluated. In the daily routine dental practice, dental impressions need to be washed and disinfected immediately after making to prevent cross-infections. The UV-C light has been proposed as a promising method for disinfection, but only a few studies have been published about its effect on the dimensional stability of dental silicones. How to cite this article: Bravo-Cueto AG, Tinedo-López PL, Malpartida-Carrillo V. Effect of Ultraviolet-C Light Exposure Time on the Dimensional Stability of Addition Silicone Dental Impressions: An In Vitro Study. J Contemp Dent Pract 2024;25(6):507-513.

Peak width of skeletonized mean diffusivity as a neuroimaging biomarker in first-episode schizophrenia.

Peak width of skeletonized mean diffusivity (PSMD), a fully automated diffusion tensor imaging (DTI) biomarker of white matter (WM) microstructure damage, has been shown to be associated with cognition in various WM pathologies. However, its application in schizophrenic disease remains unexplored. This study aims to investigate PSMD along with other DTI markers in first-episode schizophrenia patients compared to healthy controls (HCs), and explore the correlations between these metrics and clinical characteristics. A total of 56 first-episode drug-naive schizophrenia patients and 64 HCs were recruited for this study. Participants underwent structural imaging and DTI, followed by comprehensive clinical assessments, including the Positive and Negative Syndrome Scale (PANSS) for patients and cognitive function tests for all participants. We calculated PSMD, peak width of skeletonized fractional anisotropy (PSFA), axial diffusivity (PSAD), radial diffusivity (PSRD) values, skeletonized average mean diffusivity (MD), average fractional anisotropy (FA), average axial diffusivity (AD), and average radial diffusivity (RD) values as well as structural network global topological parameters, and examined between-group differences in these WM metrics. Furthermore, we investigated associations between abnormal metrics and clinical characteristics. Compared to HCs, patients exhibited significantly increased PSMD values (t = 2.467, p = 0.015), decreased global efficiency (Z = -2.188, p = 0.029), and increased normalized characteristic path length (lambda) (t = 2.270, p = 0.025). No significant differences were observed between the groups in the remaining metrics, including PSFA, PSAD, PSRD, average MD, FA, AD, RD, local efficiency, normalized cluster coefficient, small-worldness, assortativity, modularity, or hierarchy (p > 0.05). After adjusting for relevant variables, both PSMD and lambda values exhibited a significant negative correlation with reasoning and problem-solving scores (PSMD: r = -0.409, p = 0.038; lambda: r = -0.520, p = 0.006). No statistically significant correlations were observed between each PANSS score and the aforementioned metrics in the patient group (p > 0.05). Multivariate linear regression analysis revealed that increased PSMD (β = -0.426, t = -2.260, p = 0.034) and increased lambda (β = -0.490, t = -2.994, p = 0.007) were independently associated with decreased reasoning and problem-solving scores respectively ( = 0.295, F = 2.951, p = 0.029). But these significant correlations did not withstand FDR correction (p_FDR > 0.05). PSMD can be considered as a valuable neuroimaging biomarker that complements conventional diffusion measurements for investigating abnormalities in WM microstructural integrity and cognitive functions in schizophrenia.

A reexamination of the relationship between β to α crystal transition and the surface crater formation in biaxially oriented polypropylene film

The formation mechanism of the crater-like surface of biaxially oriented polypropylene (BOPP) film remains controversial. To clarify this issue, in this work, three isotactic polypropylene (iPP) samples with different tacticities are selected to prepare BOPP films. It is shown that the relative β crystal content (kβ) in the cast sheet increases with tacticity. The β crystal transforms to the α crystal when stretched at 145 °C along the machine direction. For all the samples, rough surfaces are obtained even if the kβ value of the cast sheet is very low (kβ < 0.1). The arithmetic mean roughness (Ra) of the BOPP films increases with the increase of the kβ in the cast sheet. While higher kβ in the iPP cast sheet contributes to a higher Ra value, the β crystallites hinder the enlargement of roughening rings, and cause surface defects (cavitation), which are detrimental to applications. Our results indicate that the β crystal in the cast sheet is not essential for the crater formation and a higher β crystal content is not always beneficial for BOPP capacitor films.

Evaluation of refractive surgery with posterior chamber intraocular lenses in patients with high myopia treated in an Ophthalmologic Center of the city of Rosario, years 2019-2022

Introduction: Myopia is an ametropia that is highly prevalent and causes loss of visual acuity, characterized by having diopters greater than -5.00. The implantation of a posterior chamber intraocular lens represents a treatment option for those patients who cannot undergo the Excimer Laser technique.Objective: To describe the results achieved with the placement of posterior chamber intraocular lenses in patients with high myopia treated in an ophthalmologic center in the city of Rosario between the years of 2019-2022.Materials and Methods: Quantitative, descriptive, observational, retrospective, retrospective, cross-sectional, non-probabilistic study by convenience. Conducted at Centro Oftalmología Global, a private center specialized in ocular pathologies, located at Bv. Oroño 1003 in the city of Rosario - Santa Fe. Data were collected by review of medical records. The data obtained were entered into a Microsoft Excel database. The data were tabulated for presentation and analysis. Summary measures of central tendency (arithmetic mean, median and mode) and dispersion (standard deviation) and descriptive statistical techniques (frequency distributions, averages and percentages) were used.Results: A total of 38 medical records were studied, of which n=23 (60.5%) were female and n=15 (39.5%) were male. The mean age was 31.2 (SD ±2.84 years; min. 24 and max. 35). The age group with the highest frequency was 30 and 35 with 25 patients (65.8%). Of the total, n=21 (55.3%) were patients with high myopia and n=17 (45.7%) with high myopia and astigmatism. Of n=38, 44.7% presented preoperative visual acuity less than 1/10 and 26.3% of 1/10. Refractometry showed results between -3.00 to -20.00 diopters of sphere and -1.00 to -6.00 diopters of cylinder.Conclusion: It was possible to assess that 86.8% of the patients who underwent refractive surgery were able to achieve an optimal visual quality (10/10) after LCI placement, and of the total number of patients (n=38) studied, only 5 (13.2%) presented complications in the postoperative period

The Effectiveness of Test for Speed and Strength Development for 12-14 Years Boys Judo Athletes: A Case Study of Binh Duong Province, Vietnam

Judo is an individual combat sport that requires high psychological, technical, tactical and physical factors, in which strength and speed play an important role. The aim of the study was selecting some tests for speed and strength development for 12-14 years boys Judo athletes, evaluating the effectiveness of these tests to develop speed strength for them. The study group consisted of 20 boys 12-14 years old Judo athletes in Binh Duong Province, Vietnam. The test for speed and strength development (collecting by previous research) was used in the study, including 5 tests: (1) Test 30m high start run (s); (2) Test long jump in place (cm); (3) Test prone push-up 15s (times); (4) Test Seoinage kick 20s (times); (5) Test knocking down Ippon Seoinage 30s (times). Test results based on the score tables were subjected to statistical calculations. An arithmetic mean, and Cv index were calculated for independent samples. The boys 12-14 years old Judo athletes who train 5 tests for speed and strength development exceed on the level statistically significant than the boys who practice current test. Comparing the results after the experiment between the two groups shows that the test system introduced by the study is superior to the current test system in terms of development rate (in each survey indicator, as well as in terms of average development rate).

Implementasi Data Mining Prediksi Penjualan Produk Semen Menggunakan Metode Linear Regression (Studi Kasus PT. Toyo Mortar Indonesia)

The cement industry in Indonesia plays a vital role in infrastructure development and the construction sector. PT. Toyo Mortar Indonesia, established in 2015 in the Tangerang industrial area, focuses on the production of instant mortar cement. However, the national cement industry faces the challenge of declining sales due to the pandemic, which has affected people's purchasing power and slowed down property and infrastructure projects. To achieve future growth potential, the right strategy is needed in sales planning. This study implements data mining using the linear regression method with the RapidMiner application to predict cement product sales. The data used includes historical sales data and product information from PT. Toyo Mortar Indonesia. In the tests conducted, the data was processed using 12 variables, of which 10 variables influenced the prediction results: TM-168, TM-178, TM-188, TM-189, TM-198, UM-100, UM-101, UM BIRU, raw materials, and other sales. The test results show that the Linear Regression method can predict cement product sales with an average Root Mean Square Error (RMSE) value of 493,125.701 with a standard deviation of 126,330.525. The average Absolute Error is 303,270.965 with a standard deviation of 46,207.586, and the average relative error is 1.89% with a standard deviation of 0.36%, indicating very good prediction accuracy. This can help the company in making decisions related to sales planning using the available sales data.

The state of charge predication of lithium-ion battery energy storage system using contrastive learning

The state of charge (SOC) is a critical state quantity that must be determined in real-time for a battery energy storage system (BESS). It is a prerequisite for the operation of a BESS. However, obtaining the precise value of SOC is challenging due to it being a hidden state quantity. Existing neural network models commonly employ an end-to-end prediction paradigm for SOC estimation, which fails to fully exploit the rich information present in the time-series battery data. Unlike most studies available in the literature, we propose a novel SOC prediction method named CLDMM. This method is the first to apply contrastive learning techniques from the image field to the SOC prediction of lithium batteries. The method utilizes data augmentation, a multi-scale encoder, and multi-layer perceptrons to learn latent representations and mix these with raw data proportionally for downstream predictive tasks. The performance of the proposed method is evaluated using the Panasonic NCR18650PF dataset, and ablation study were conducted. Experimental results show that CLDMM outperforms baseline methods, achieving an average mean absolute error (MAE) of 0.64% and an average maximum error (MAX) of 2.66%.

Rapid distance estimation of odor sources by electronic nose with multi-sensor fusion based on spiking neural network

The inference of odor source locations holds great potential value in chemical leak detection, explosive searches and flammable substance detection. Sensor response and derivative changes are common indicators used to estimate source distance. However, most studies often rely on single-feature methods using a single sensor. In this study, a novel distance indicator based on a spiking neural network (SNN) that integrates multiple sensors is proposed. SNN was introduced for effective multi-sensor data fusion, which can provide accurate and rapid source distance estimation. The indicator's accuracy and quick detection capabilities were tested using a publicly available wind tunnel dataset and compared with single-sensor indicators. Additionally, an olfactory robot platform was constructed to test the method's real-time performance. Results demonstrate that this method effectively utilizes sensor arrays to estimate source distance, with an average root mean square error (RMSE) of less than 0.1 m across different wind speeds, outperforming single-sensor-based indicators. Additionally, the model exhibits good distance estimation performance within a relatively short detection time, with an average RMSE of 0.118 m. Practical testing on a mobile robot platform confirms the applicability of this distance indicator for real-time distance monitoring. In conclusion, the proposed distance indicator enables effective distance estimation for odor sources, providing a promising method for odor source localization and olfactory navigation.