Calculation Of Volume Research Articles

Strategies for Minimizing Material Waste with the Application of Lean Construction in Building Construction Projects

Waste of construction materials is one of the problems often experienced by several construction service actors in Bali, especially in Gianyar, the utilization of materials is not efficient so that the project experiences cost overruns. The purpose of this study is to identify the dominant indicators causing building construction material waste and formulate strategies to minimize material waste by applying lean construction principles to building construction projects. The research sample was 15 small-scale contracting companies in Gianyar with 2 to 3 respondents in each company, namely directors, site managers and implementers. Data collection using questionnaires. The data processing technique used is factor analysis and focus group discussion. The test results show that there are 10 indicators of the causes of material waste that often occur, namely, the design does not adjust the size of the available materials, lack of knowledge about construction implementation techniques, drawings with volume calculations are not well integrated, construction materials cannot be stored for a long time, excessive mixture of wet materials, distant material storage locations, incorrect use of conventional formwork, lack of periodic checks related to work results, installed material specifications are not appropriate, lack of attention to material specifications on site. The results of the focus group discussion found that the strategies to reduce material waste based on the application of lean construction principles are training for workers involved, scheduling good material procurement, using standard components available on the market by taking into account modules that can be applied, increasing communication with various parties in exchanging information through discussion forums, checking work results and material specifications regularly.

Changes in olfactory bulb volume and olfactory sulcus depth in COVID-19 infection: an autopsy study.

The pathophysiology of COVID-19 remains unclear. Olfactory dysfunction is one of the neurological symptoms of the disease. There is no evidence to evaluate whether there is a morphometric change in the olfactory pathways. This study aimed to examine the effect of COVID-19 on olfactory center sections through morphometric measurements obtained from autopsy cases. Our study was conducted on 63 autopsy cases (COVID-19 [n = 37], control (non-COVID) [n = 26]) between the ages of 18-80 years who came to Tokat Forensic Medicine Institute. The anatomical structures of the olfactory tracts were determined on the brains removed during routine autopsy. The dimensions of the structures belonging to the olfactory center sections were measured with a precision digital caliper, weights were measured with a precision digital scale, and volumes were measured with a 0.01cm³ graduated cylinder. The Archimedes principle method was used for volume calculations. In the autopsy cases examined, it was found that there was a significant decrease in bilateral olfactory bulb (OB) and olfactory tract (OT) volumes in COVID-19 group (p < 0.001). In addition, OB and OT weights were lighter in COVID-19 group on both sides (p < 0.001). The length, width and depth measurements of the examined anatomical structures were found to be shorter in COVID-19 group (p < 0.01). Autopsy findings showed damage in olfactory center sections in COVID-19 group. We believe that knowing the OB and OT morphology in particular will make significant contributions to both clinical approaches and future studies in the pathology of infectious diseases.

High-resolution lake infill time modeling at Jackson Lake, Wyoming (USA)

With growing climatic, anthropogenic, and environmental pressures on lakes and reservoirs globally, accurate quantitative sediment infilling estimates, or lake/reservoir lifespans, are essential to the effective management of these systems. Current methods used to model lake and reservoir infill timescales are limited in scope. This study presents refined data-rich infill models of Jackson Lake, WY (USA). Basin-wide seismic reflection profiles were used to obtain lake volume and total sediment isopach measurements. Radionuclide-dated sediment cores were collected to capture variability in sedimentation patterns, due in part to the lake’s bathymetric complexity. Three infill models were produced, including: (1) a model that uses radionuclide-based sedimentation rates and a 1-D linear infill, (2) a model that uses radionuclide-based sedimentation rates and a 3-D mass-based infill, and (3) a model that relies on sediment volume calculations and assumptions of basin age only. A fill-and-spill approach was utilized to ensure conservation of mass through each time step. All three models exhibited strong agreement on an infilling time of ∼30,000 years from present. Models developed in this study emphasize the need to accurately determine lake volumes and capture basin-wide complexity in sedimentation patterns, both of which are commonly poorly resolved in similar studies. Further development of data-rich lake/reservoir infill models could greatly benefit global lake and reservoir research critical to understanding engineered reservoir lifespans and carbon cycling in these systems. Further, accurate infilling data can assist in the development and application of effective policies for freshwater resource management and conservation, promoting the long-term sustainability of lake/reservoir systems.

Optimization of cycloid wheel shaping based on thermal mixed lubrication and wear characteristics

The cycloid pinwheel mechanism plays a key role in the function of RV reducers, making the lubrication and wear characteristics of the cycloid tooth profile vital areas of research. This study uses the RV-20E reducer as a case study to analyze the time-varying contact force and relative velocity between the cycloid wheel and the pinwheel, factoring in the system's dynamic properties. A transient contact model for thermal mixed lubrication of the cycloid tooth profile was developed, incorporating friction and temperature rise, and was based on a rough surface model of the dynamic bonding interface. This model enabled the calculation of oil film thickness, contact stress, and wear volume at the interface between the cycloid wheel and the pinwheel. Additionally, the study assessed the impact of traditional shaping methods on wear characteristics and derived a fitted cycloid tooth profile for the profile grinding process. These findings provide valuable insights into improving the lifespan of RV reducers.

Normative Values for Thyroid Volume and Tracheal Index in Healthy Turkish Newborns in an Iodine Sufficient Region.

The study aims to determine the normal values of thyroid volume and tracheal index in healthy term newborns born in an iodine-sufficient population. Additionally, we investigated the usability of a handheld device for assessing the tracheal index. Thyroid imaging was performed at 0-2 days and 15-30 days using handheld and portable ultrasound devices. Thyroid volume and tracheal index were calculated using standard formulas. A total of 144 healthy term newborns with a mean birth weight 3230 g were enrolled. The normal thyroid volume for the entire population was 0.66 ± 0.25 ml at 0-2 days, which significantly increased to 1.12 ± 0.33 ml at 15-30 days (p<0.01). There were no significant differences in thyroid volume between genders in either age group (p=0.246 and p=0.879). Thyroid volume correlated with birth weight, length, and head circumference, with the strongest correlation being with birth weight (r=0.404, p<0.001; r=0.252, p=0.002; r=0.223, p=0.007, respectively). The tracheal index at 0-2 days was 1.84±0.30 in girls, 1.82±0.27 in boys, and 1.83±0.29 overall. At 15-30 days, it was 1.99±0.23 in girls, 2.00±0.28 in boys, and 1.99±0.25 overall. Similar to thyroid volume, the tracheal index increased with age (p<0.01), with no significant gender differences in either age group (p=0.593 and p=0.886). Thyroid volume and tracheal index were moderately correlated in both measurements (rho=0.538, p<0.01). Measurements of the trachea, and thyroid lobe widths using portable and handheld ultrasound devices were correlated (r=0.449, p<0.01; r=0.638, p<0.01; r=0.497, p<0.01). There was also a correlation between tracheal index measurements using both devices in both the first and second measurements. This study provides normative data on thyroid volumes and tracheal index in newborns from an iodine-sufficient population. The tracheal index can estimate thyroid size when volume calculation is not feasible and handheld ultrasound devices are effective for this assessment.

Geolocation of Fixed Emission Sources Produced by Artisan Brick Kilns in the Atmospheric Basin of the City of Juliaca, Peru

Objective: The study objective is to investigate the application of georeferencing systems to identify the geospatial location of fixed sources of atmospheric emissions produced by artisanal brickyards in the air basin of Juliaca city-Peru. Theoretical Framework: Previous studies have shown that artisanal brickyards are a significant source of air pollution in developing urban and on the outskirts. Emissions of fine particles, nitrogen oxides and other pollutants from the burning of traditional fuels, such as firewood and coal contribute to the degradation of air quality and can have adverse effects on human health and the environment. The georeferencing application and geospatial analysis techniques in the atmospheric pollution study have allowed a better understanding of the spatial distribution of emission sources and their impact on the environment. These tools are essential to identify and map the artisanal brickyard locations and to evaluate their contribution to air pollution in urban and on the outskirts. Method: The methodology adopted for this research includes data collection and compilation of existing information; georeferencing of brickyards through the use of geographic information systems (GIS); analysis of geospatial data for the identification of spatial patterns; preparation of thematic and spatial distribution maps; and the interpretation of results. Results and Discussion: The study results highlight the importance of locating the fixed sources of emissions produced by artisanal brick factories in the Juliaca air basin. This precise spatial identification provides a solid basis for the formulation of policies and mitigation strategies aimed at reducing air pollution in the region, in addition to representing fundamental data for the use and exploitation of GIS for environmental protection and modelling, among others. Research Implications: The results can be applied or influence practices in the environmental and forestry engineering field, the ICTs application, modelling and simulation, and territorial planning, among others. Originality/Value: This study contributes to the literature using georeferencing techniques for environmental modelling purposes. The relevance and value of this research are evident in obtaining georeferenced points for the estimation of emission factors for the predictive calculation of volumes, flows and dispersion of pollutants in an air basin.

Seepage–Diffusion Mechanism of Gas Kick Considering the Filtration Loss of Oil-Based Muds During Deepwater Drilling

As oil and gas exploration gradually advances into deep waters, the combined effects of various types of gas kick and the accurate calculation of the gas-kick volume have gained increasing attention. This study focused on gas kicks from permeable gas-bearing formations, considering the mass transfer of gas in the filtration region of the drilling fluids and revealed the mechanisms of seepage-driven and diffusion-driven gas kicks. Based on seepage mechanics and diffusion theory, a comprehensive model for calculating gas-kick volume was established, considering the synergistic effect of gas-concentration-diffusion and negative-differential-pressure, as well as mass transfer in both the filtrate zone and the filter-cake zone. The new model showed high calculation accuracy. The sensitivity analysis showed that both the seepage-driven and diffusion-driven gas-kick volumes in the wellbore increased with increasing formation porosity and open-hole length, while the thickness of the filter cake had a strong inhibitory effect on both. Additionally, a “seepage–diffusion ratio” was introduced to reveal the gas-kick evolution pattern under a seepage–diffusion mechanism. Under specific case conditions, when the seepage–diffusion ratio was less than approximately 1%, diffusion-driven gas kick contributed more than seepage-driven gas kick; when the seepage–diffusion ratio exceeded 1%, seepage-driven gas kick contributed more than diffusion-driven gas kick. The research can provide crucial parameters for wellbore multiphase flow calculation and wellbore pressure prediction.

Determination of Species-Specific Differences in Intracranial Volume of Tuj Sheep and Hair Goats Using Stereology and Computed Tomography Methods.

The intracranial cavity contains vitally important organs. The brain, cerebellum, meninges and the vessels that supply these organs are located in the intracranial cavity. Therefore, it is important to learn about the intracranial cavity and to study it. However, there is limited information about the intracranial cavity in the veterinary field. The aim of this study was to determine the differences between the intracranial cavities of different species of animals by using stereology and tomography methods, volume calculations and morphometric measurements. In addition, the compatibility of the methods used with each other was investigated. In the study, six male adult goats and six male adult sheep were used. In this study, the intracranial cavities of sheep and goats were calculated by using Cavalieri's principle and 3D modelling using tomography sections. Morphometric measurements were taken over the intracranial space, and index calculations were made. In 3D models using computed tomography, the intracranial volume was 153.31 ± 24.06 cm3 in goats and 128.07 ± 7.93 cm3 in sheep. In the calculation using Cavalieri's principle, it was determined to be 152.73 ± 22.73 cm3 in goats and 126.15 ± 8.38 cm3 in sheep. As a result of the study, the MWCC (maximum width of the cranial cavity) parameter was found to be statistically significant between species (p < 0.05). The two methods used in Bland-Altman analysis were found to be within the limits of agreement, and the methods can be alternative to each other.

Evaluation of the Effectiveness of Active Vitamin D Use in Experimental Rat Lymphedema Model.

Background and Objectives: Lymphedema is a progressive, chronic condition. Traumatic damage to the lymphatics, removal of lymph nodes, and/or radiation are the major causes of fibrosis and a subsequent pathological cascade. Macrophages play a crucial role in wound healing, with M1 macrophages known for their pro-inflammatory effects and M2 macrophages recognized for their anti-inflammatory effects, including improved angiogenesis, lymph angiogenesis, and tissue healing. This study aims to assess the use of calcitriol to alter the M2/M1 macrophage balance, reduce tissue fibrosis in a lymphedema model, promote new micro-lymphatic vessel formation, and evaluate the benefits of active vitamin D. Material and Methods: Forty-five rats were randomly divided into three groups: control surgery (group A), surgery with preoperative-postoperative calcitriol (group B), and postoperative calcitriol (group C). One week after the surgical ablation a total dose of 20 Gy radiation therapy was administered to the operated groin region. Micro-computed tomography was used for limb volume calculation, fluorescence lymphatic imaging was used to assess the presence of lymphedema, and histopathological analyses were conducted to evaluate the M1/M2 macrophage ratio, fibrosis accumulation, and lymph angiogenesis. Results: The micro-computed tomography evaluation revealed that 75% of the rats of group A exhibited long-lasting lymphedema. In group B, the initial lymphedema ratio was the lowest, affecting only 25% of the rats. After ligating the main vessels, a linear lymphatic microvascular structure was observed in groups B and C. Group B had a significant increase in M2 macrophages and newly formed lymphatic vessels (p < 0.05). However, group A showed a significant elevation of M1 macrophages and collagen accumulation (p < 0.05) in the surgically treated hind limb. Conclusions: Both histological analyses and clinical results reported a relevant influence of calcitriol administration. Among all groups, the most favorable outcomes were seen in group B (prophylaxis group). Hence, calcitriol administration could play a crucial role in enhancing the migration of M2 macrophages to the damaged tissue. Such migration may contribute to lymphedema resolution either by enhancing the organization of superficial lymphatic vessels or resolving fibrosis, or with a combination of both these mechanisms.

A molecular insight into the aggregation of cisplatin in aqueous solutions

Cisplatin (CPT), recognized as a widely used metallodrug, is a prevalent therapeutic agent for the treatment of various cancers. Given the diverse biological conditions in humans, as well as the hydrated environment within cells and the toxicity associated with CPT in cancer treatment, it is imperative to assess and optimize the solvation of CPT under various conditions. In this study, the influence of CPT on the structure of water is explored. In this regard, a systematic molecular dynamics (MD) simulation is employed to investigate the structure and dynamics of CPT in aqueous media, encompassing a range of concentrations from much diluted (0.05 M) to concentrated (5 M). The disruption of water structure by CPT molecules is determined using radial distribution function (RDF), mean-squared displacement (MSD), and combined radial/angular distribution function (CDF). Notably, the CPT aggregates exhibit an impact on the average number of water-water hydrogen bonds. Through calculations of apparent and partial molal volumes of CPT at various concentrations, we observed a sudden and dramatic change in the solution structures up to the critical aggregation concentration of CPT (0.5 molal), a finding corroborated by the calculations of diffusion coefficients. In summary, the self-aggregation of CPT molecules commences at 0.5 molal, leading to increased apparent and partial molal volumes with rising concentration. However, beyond 0.5 molal, the change in volumes becomes less significant, suggesting that while the number of CPT aggregates continues to increase, their size remains relatively constant above this concentration.

A 2D echocardiographic method for accurate right ventricular quantification using deep learning

Abstract Background/Introduction Transthoracic two-dimensional echocardiography (2DE) remains the backbone for non-invasive assessment of the right ventricle (RV) size and function. However, calculation of RV end-diastolic (RVEDV), end-systolic volume (RVESV) and ejection fraction (RVEF) cannot be performed using 2DE due to the complex RV shape (1), whereas currently used, respective 2DE indices lack diagnostic accuracy. Deep learning (DL) may be able to assist in developing new 2DE methods for RV quantification. Purpose To develop a novel DL-based 2DE method for quantitative evaluation of RV size and function without geometric assumptions. Methods 50 adult patients underwent 2DE and CMR within 30 days as part of routine cardiac care between 6/2020 – 9/2021 at a medical center. We excluded patients with prior cardiac surgery of the RV, tricuspid or pulmonic valve repair or replacement, complex congenital heart disease, more than small pericardial effusion, cardiac tamponade, atrial fibrillation at the time of either study, severe RV dysfunction or inadequate imaging quality. End-diastolic and end-systolic areas derived from planimetry of 8 2DE RV views, along with patient age and gender, were to used to train and test a DL algorithm, namely the Feature-Tokenizer and Transformer (Figure 1) in order to predict the corresponding, CMR-derived, RVEDV or RVESV, and subsequently calculate RVEF. We used 5-fold cross-validation for training and evaluation. We assessed the relative importance of each 2DE view using gain metric-powered explainability analysis and subsequently performed a sensitivity analysis to identify optimal combinations of views. Variability analysis was performed for a random subcohort of 10 patients. Results Median age was 51 (interquartile range 32-62) and 42% were women. Mean RVEDV, RVESV and RVEF) by CMR were 163±70ml, 82±42ml and 51±8% respectively. Six patients (12%) had RV dilatation and 9 (18%) had RV dysfunction when using published CMR criteria. Explainability analysis showed that the 3 most important views were parasternal long axis (PLAX) (relative feature importance [RFI] = 0.197), 4-chamber (RFI=0.145) and parasternal short axis at the base (PSAX-base) (RFI=0.112). The 3-view combination of PLAX, 4-chamber and PSAX-base achieved high accuracy when compared to CMR (R2=0.964, absolute percentage error [APE]=8.09±12.07% for RV volumes and APE=9.86±10.68% for RVEF). Good (intraclass correlation coefficient [ICC]&amp;gt;0.75) to excellent (ICC&amp;gt;0.90) intra- and interobserver variability was found for these 3 views. Conclusions We propose an innovative, clinically applicable DL-based 2DE method for quantification of RV size and function that requires manual RV planimetry of 3 views, namely 4-chamber, PLAX and PSAX-base (Figure 2). This method may revolutionize 2DE RV assessment. Further studies with largest number of patients and wider range of RV size and function are needed to validate this method.Deep learning architectureGraphical abstract

Scan-rescan variability of AI-enabled cardiac functional assessment from cine CMR

Abstract Background/Introduction Cine cardiovascular magnetic resonance (CMR) is the gold-standard technique for the assessment of cardiac function and structure. Manual analysis of cine CMR to estimate structural and functional biomarkers is costly and time-consuming, motivating the use of artificial intelligence (AI) for automation. However, the scan-rescan repeatability of AI derived biomarkers remains unknown. Purpose Measure the repeatability of AI-based cine CMR biomarkers in scan-rescan data. Methods 92 scan-rescan short-axis cine CMR were acquired from volunteers on the same day (i.e. 184 in total) and annotated with ground truth (GT) manual segmentations of the left and right ventricle (LV, RV) blood pools, and LV myocardium at end-diastole (ED) and end-systole (ES). AI segmentations and subsequent biomarker estimates were produced using the AI-CMR-QC tool described in [1]. Segmentation performance was assessed with Dice score, pixelwise sensitivity and specificity, and Hausdorff distance. Scan-rescan differences in cardiac biomarkers for each subject were used to assess repeatability. Repeatability of LV ejection fraction (EF) based classification (LVEF&amp;lt;40 = abnormal, 40&amp;gt;LVEF&amp;gt;50 = mildly reduced, LVEF&amp;gt;50 = normal) [2] was also estimated from scan-rescan data. Results The segmentation model obtained high Dice scores (&amp;gt; 88% for LV and RV blood pools, &amp;gt;83% for LV myocardium). The summary of scan-rescan biomarker differences in Fig. 1(a) highlights that biomarker repeatability is generally better in GT segmentations, with lower differences between the two scans. While performance is satisfactory, a more in-depth analysis reveals that in some pairs of scans there are inconsistencies in the segmentations, leading to fluctuations in the calculation of blood pool volumes, which affects the repeatability of the computed biomarkers, as seen in Fig. 2(b). For instance, significant changes in LVEF between pairs of scans can arise from inconsistencies in the segmentation of the LV in basal slices, as shown in Fig. 2(a). This has consequences in the classification of subjects based on LVEF, as shown in Fig. 1(b). Only two subjects belonged to the mildly reduced LVEF class, however, when comparing predicted scan and rescan LVEF, both sensitivity and specificity decrease, suggesting inconsistency in the biomarker estimation. Conclusion(s) While we have demonstrated successful AI cardiac segmentation and biomarker estimation based on conventional performance metrics, additional refinement is necessary to enhance reliability and consistency. Further work is needed to obtain a better delineation of the valve plane, which would help addressing the inconsistencies at the LV basal slice. An automated segmentation and analysis pipeline for cine CMR is vital to support overworked clinicians, however, demonstrably repeatable performance, particularly when looking at therapy response, will have a significant impact on patient care and clinical outcomes.Repeatability of GT and AI biomarkersRepeatability of GT and AI segmentations

Echocardiographic associates of impaired sleep quality in patients with anxiety and depression

Abstract Objective Sleep health, mental health and cardiovascular health are multidimensional constructs that are strongly associated with each other. Anxiety and depression are the most common psychiatric diseases in the community and frequently comorbid in routine clinical practice. This study sought to investigate whether there is an association between sleep quality and echocardiographic parameters in patients with anxiety and/or depression. Methods The clinical and instrumental find­ings of consecutive patients diagnosed with either of anxiety disorders and/or depressive disorders and underwent cardiac examination in our tertiary center on the same day were retrospectively reviewed. The diagnosis was made by a psychiatrist according to the criteria listed in the fifth edition of The Diagnostic and Statistical Manual of Mental Disorders. Afterwards, Hospital Anxiety and Depression Scale (HADS) and Pittsburgh Sleep Quality Index (PSQI) were applied to patients to assess symptom severity and sleep quality, respectively. Subsequent to psychiatric examination, the patients underwent echocardiographic examination that includes two-dimensional conventional echocardiography, tissue doppler imaging (TDI) echocardiography, atrial conduction times, and left atrium (LA) volumes and functions. Results The final study population consisted of 167 patients and divided into two groups according to their PSQI score: PSQI&amp;lt;5 (normal sleep quality) (n=32) and PSQI≥5 (impaired sleep quality) (n=135). Aortic diameter, left ventricular (LV) end-systolic diameter, LV end-diastolic and -systolic volume, LV stroke volume and LV stroke volume index, LV outflow tract velocity–time integral (LVOT-VTI), and LA conduit volume calculations were significantly lower in patients with impaired sleep quality compared to patients with normal sleep quality. The other echocardiographic parameters including LV systolic functions, doppler and TDI echocardiography indices, atrial conduction times, atrial mechanical functions including LA function index (LAFI) were similar among groups. Correlation analysis yielded a negative, weak but statistically significant correlation between LAFI and PSQI score (r=-0.17, p=.030) (Figure 1A). Left intra-AEMD positively and significantly correlated with PSQI score at a weak level (r=0.16, p=.043) (Figure 1B). Aortic diameter, LV stroke volume index, LVOT-VTI and conduit volume were determined as echocardiographic parameters significantly associated with impaired sleep quality in univariate analysis. Among these parameters, only conduit volume remained as significant and independent associate of impaired sleep quality in multivariate logistic regression analysis (Odds ratio:0.91, 95% Confidence interval:0.85-0.98, p=.018) (Table 1). Conclusion There is an independent association between LA conduit volume and impaired sleep quality in patients suffering from anxiety and/or depressive disorders.Figure 1Table 1

Structural insights into the toxicity of type II ribosome inactivating proteins (RIPs): a molecular dynamics study

Ribosome Inactivating Proteins (RIPs) act by irreversibly depurinating the 28S rRNA ricin-sarcin loop (SRL) of the eukaryotic ribosome resulting in protein synthesis inhibition. In general, they consist of two variants: Type I which is single chained (∼30 kDa), and Type II, a more toxic variant which is a Type I N-glycosidase chain covalently linked to a lectin chain. These proteins are believed to play a pivotal role in defence mechanisms. Intriguingly, non-toxic variants of such toxic proteins do exist in nature. To explore their mode of action, in the present study we have selected three toxic (Ricin, Ebulin and HmRIP) as well as two non-toxic (BGSL and SGSL) RIPs and performed molecular docking and molecular dynamic simulations with the SRL loop. This study throws light on the structural stability and plasticity of the toxic and non-toxic RIP complexes. Furthermore, analysis of the active site cavity volume and binding free energy calculations reveal that the SRL, particularly the specific adenine (A4605), is relatively unstable in the case of non-toxic RIPs which is also supported by the free binding energy calculations, and the pocket size analysis indicates the abnormal increase in active site cavity volume of non-toxic RIPs with time. This first-of-its-kind comprehensive study of toxic and non-toxic RIPs gives insights about the mode of action and the dynamic nature of their interaction with the SRL loop. These observations will be helpful in the development of toxoids against RIPs and also in designing novel therapeutic approaches against human diseases.

Comprehensive segmentation of gray matter structures on T1-weighted brain MRI: A Comparative Study of CNN, CNN hybrid-transformer or -Mamba architectures.

Recent advances in deep learning have shown promising results in medical image analysis and segmentation. However, most brain MRI segmentation models are limited by the size of their datasets and/or the number of structures they can identify. This study evaluates the performance of six advanced deep learning models in segmenting 122 brain structures from T1-weighted MRI scans, aiming to identify the most effective model for clinical and research applications. 1,510 T1-weighted MRIs were used to compare six deep-learning models for the segmentation of 122 distinct gray matter structures: nnU-Net, SegResNet, SwinUNETR, UNETR, U-Mamba_BOT and U-Mamba_ Enc. Each model was rigorously tested for accuracy using the Dice Similarity Coefficient (DSC) and the 95th percentile Hausdorff Distance (HD95). Additionally, the volume of each structure was calculated and compared between normal control (NC) and Alzheimer's Disease (AD) patients. U-Mamba_Bot achieved the highest performance with a median DSC of 0.9112 [IQR:0.8957, 0.9250]. nnU-Net achieved a median DSC of 0.9027 [IQR: 0.8847, 0.9205] and had the highest HD95 of 1.392[IQR: 1.174, 2.029]. The value of each HD95 (<3mm) indicates its superior capability in capturing detailed brain structures accurately. Following segmentation, volume calculations were performed, and the resultant volumes of normal controls and AD patients were compared. The volume changes observed in thirteen brain substructures were all consistent with those reported in existing literature, reinforcing the reliability of the segmentation outputs. This study underscores the efficacy of U-Mamba_Bot as a robust tool for detailed brain structure segmentation in T1-weighted MRI scans. The congruence of our volumetric analysis with the literature further validates the potential of advanced deep-learning models to enhance the understanding of neurodegenerative diseases such as AD. Future research should consider larger datasets to validate these findings further and explore the applicability of these models in other neurological conditions. AD = Alzheimer's Disease; ADNI = Alzheimer's Disease Neuroimaging Initiative; DSC = Dice Similarity Coefficient; HD95 = the 95th Percentile Hausdorff Distance; IQR = Interquartile Range; NC = Normal Control; SSMs = State-space Sequence Models.

Molecular interaction studies of Gamma-aminobutyric acid (GABA) in an aqueous medium at various temperatures: A comprehensive analysis using volumetric, thermoacoustic and DFT methods

The interaction of Gamma-aminobutyric acid (GABA) in an aqueous medium at various concentrations (0.101–1.086) mol·kg−1 as a function of temperature is being studied using volumetric, viscosity and acoustic analysis. The calculation of apparent molar volume (VΦ), partial molar volume (V∅o), apparent molar isentropic compression (Kϕ) and partial molar isentropic compression (Kϕ0) of GABA in an aqueous medium has been done by measuring the densities and speed of the sound in the temperature range of 298.15–323.15 K. The thermo-acoustic parameters like adiabatic compressibility (βs), acoustic impedance (Z), intermolecular free length (Lf), relative association (RA), relaxation time (τ), internal pressure (πi), enthalpy (ΔH), Gibbs free energy (ΔG), and change in entropy (ΔS) are also computed. The strength of the hydrogen bond interaction of GABA in an aqueous medium and its dipole moment are calculated using single-point energy calculations. These calculations employ IEFPCM and PCM solvation models using DFT/B3LYP and MP2 methods with the 6-311G++ (d, p) basis set. The outcomes are interpreted in terms of hydrogen bond interactions that exist in the mixture.

Применение новых технологий кислотной обработки пластов для восстановления продуктивности пласта

Oil recovery, measured by the oil recovery factor (ORF), is a key indicator of the efficiency of oil production. In Russia, the ORF decreased to 0.3 while in the United States this indicator increased to 0.4. About 90% of Russian oil is produced by large holdings, the structure of reserves is shifting towards hard-to-recover, which requires the use of new methods to increase oil recovery. Primary and secondary production allows only 20-50% of oil to be extracted, what makes the use of tertiary methods necessary. The development of horizontal wells with multistage hydraulic fracturing contributes to the development of new field sites, but requires careful preparation of wells to minimize risks and cost increases. Cleaning the bottomhole area using acidic formulations is often the only cost-effective way to restore the productivity of a horizontal well. The improved method of acid composition reduction using a guar gel with delayed “crosslinking”, which ensures uniform treatment of all productive zones of the formation is considered in article. The technology allows for continuous multi-stage acid treatment, temporarily blocking highly permeable areas and increasing the coverage of acidic effects on poorly drained areas. The calculation of the diverter volume considers the average efficiency of the liquid after mini-fracturing, adjusting the volume depending on the efficiency of the liquid at each port.

Three-Dimensional Internal Voids and Marginal Adaptation in Deep Margin Elevation Technique: Efficiency of Highly Filled Flowable Composites.

To evaluate interfacial three-dimensional adaptation and internal voids of different flowable materials before and after cyclic fatigue in a simulated deep-margin elevation scenario. Eighty (n &#61; 80) extracted premolars were selected and two Class II cavities were prepared. The mesial one with cervical margin 1 mm above the cementum-enamel junction (CEJ) and the distal one with cervical margin 1 mm below the CEJ. After performing adhesive procedures, specimens were divided into four groups according to the employed materials for 2 mm horizontal deep-margin relocation: nanohybrid composite (Clearfil ES2, Kuraray); conventional viscosity flowable composite (Tetric Flow, Ivoclar); medium viscosity flowable composite (Majesty ES2 Low Flow, Kuraray); high viscosity flowable composite (Majesty ES2 Super Low Flow, Kuraray). All restorations were finalized by oblique layering with nanohybrid composite (Clearfil ES2, Kuraray). To reveal interfacial and internal gap progression, specimens were scanned with a micro-CT (SkyScan 1172), before and after 500,000 cycles of mechanical chewing simulation (50 N, 1 Hz). Data were imported into Mimics software after smoothing and region growing. Only the 2 mm margin relocation volumes were considered. Obtained masks were analyzed for noise removal and volume calculation. At baseline, interfacial gap progression and internal voids, expressed in mm3, were collected and statistically analyzed with two-way ANOVA (α 0.05) for the variables substrate and restorative materials followed by Tukey post-hoc test. An additional two-way ANOVA test, followed by Tukey post-hoc test, was performed to evaluate variation in interfacial gap progression after mechanical aging. At baseline, the ANOVA test showed a significant difference for the variable restorative materials (p &#61; 0.01). More specifically, the Tukey post-hoc test revealed that the highly filled medium viscosity composite performed better than the conventional viscosity composite at baseline for the interfacial gap. The internal voids ANOVA test at baseline reported no significant differences for the variable tested. Analysis of variance for internal gap progression after thermocycling showed no differences for both substrate and restorative material employed. Highly filled medium viscosity composite performed significantly better than the conventional viscosity flowable composite for what concern baseline interfacial gaps. Artificial aging with a chewing simulator and thermocycling did not affect interfacial gap progression on enamel and dentin. The tested restorative materials performed equally after aging.

IRodd (intelligent-road damage detection) for real-time infrastructure preservation in detection, classification, calculation, and visualization

Preserving roads involves regularly evaluating government policy through advanced assessments using vehicles with specialized capabilities and high-resolution scanning technology. However, the cost is often not affordable due to a limited budget. Road surface surveys are highly expected to use low-cost tools and methods capable of being carried out comprehensively. This research aims to create a road damage detection application system by identifying and qualifying precisely the type of damage that occurs using a single CNN to detect objects in real time. Especially for the type of pothole, further analysis is to measure the volume or dimensions of the hole with a LiDAR smartphone. The study area is 38 province’s representative area in Indonesia. This research resulted in the iRodd (intelligent-road damage detection) for detection and classification per type of road damage in real-time object detection. Especially for the type of pothole damage, further analysis is carried out to obtain a damage volume calculation model and 3D visualization. The resulting iRodd model contributes in terms of completion (analyzing the parameters needed to be related to the road damage detection process), accuracy (precision), reliability (the level of reliability has high precision and is still within the limits of cost-effective), correct prediction (four-fifths of all positive objects that should be identified), efficient (object detection models strike a good balance between being able to recognize objects with high precision and being able to capture most objects that would otherwise be detected-high sensitivity), meanwhile, in the calculation of pothole volume, where the precision level is established according to the volume error value, comparing the derived data to the reference data with an average error of 5.35% with an RMSE value of 6.47 mm. The advanced iRodd model with LiDAR smartphone devices can present visualization and precision in efficiently calculating the volume of asphalt damage (potholes).

Crowder Chain Length Variability and Excluded Volume Effect on the Phase Separation Behavior of Mucin.

Phase separation within cellular membranes, a critical process underpinning diverse cellular functions, is significantly influenced by transmembrane proteins. Therefore, elucidating the behavior of a transmembrane protein in its phase-separated state is of utmost importance. Our study explores mucin behavior in the cellular milieu, aiming to determine the role of crowder chain length and excluded volume in phase separation. Confocal microscopy images demonstrate the strong partitioning of mucin into the condensed phase influenced by hydrophobic and electrostatic interactions. Fluorescence recovery after photobleaching analysis revealed increased mobility in the presence of shorter chain length crowders, indicating the dynamic behavior of protein within condensed phases. Excluded volume calculation using the theoretical model emphasizes its importance in mucin phase separation under crowded conditions. Our findings underscore the ability of mucin to phase-separate under crowded conditions, highlighting the crucial role of excluded volume and enhancing our understanding of its involvement in cancer progression.