Search

Traumatic brain injury (TBI) is a significant global health issue characterized by disrupted brain function due to external mechanical force. The Glasgow Coma Scale (GCS) remains the standard tool for assessing TBI severity. However, it faces limitations in certain clinical scenarios, such as patients under sedation. The neutrophil-lymphocyte ratio (NLR) in cerebrospinal fluid (CSF) is being explored as a potential objective marker for evaluating the severity of traumatic brain injury (TBI). This study analyzes the relationship between the NLR in CSF and GCS scores in patients with TBI. An observational analytic study employed a prospective design involving 15 TBI patients treated at Dr. Soetomo General Hospital. GCS scores and NLR values from both blood and CSF were measured on the day of admission (D0) and two days later (D2). The mean blood NLR was 11.28 ± 7.52, while the means of CSF NLR D0 and D2 were 0.349 ± 0.446 and 0.469 ± 0.985. The mean scores of GCS D0 and D2 were 7.87 ± 3.70 and 8.80 ± 4.11. A statistically significant negative correlation was observed between the CSF NLR D0 and the GCS D0 scores (p < 0.05, r = -0.706), indicating that higher NLR values in CSF are associated with lower GCS scores, and thus, greater TBI severity. There were no significant correlations observed between blood NLR on day 0 (D0) and GCS scores on day 0 (D0), nor between CSF NLR on day 2 (D2) and GCS scores on day 2 (D2). The NLR in CSF at the time of hospital admission can serve as an objective marker for assessing the TBI severity. This marker could be useful in clinical settings where GCS assessment is challenging. [ABSTRACT FROM AUTHOR]

Nanoencapsulation of essential oils exhibited promising applications in food industries, especially in controlling spoilage due to food-borne microbes. In this study, the enhanced antimicrobial efficacy of nanoencapsulated Cuminum cyminum essential oil (Ne-CEO) against food-borne molds, and aflatoxin B1 contamination was observed in a dose-dependent manner. The GC-MS results represent 14 different volatile organic compounds of (CEO) (94.49%), where cuminaldehyde was found to be the major one. The interaction of the Cuminum cyminum essential oil (CEO) and chitosan nanoparticles (CSNPs) was confirmed with the Scanning Electron Microscopy (SEM) and Fourier Transform Infrared Spectroscopy (FTIR) analysis. The Ne-CEO exhibited superior antimicrobial effects compared to non-encapsulated CEO and inhibited the growth of selected mold species (0.3–0.5 µL/mL) and aflatoxin B1 (AFB1) secretion at 0.4 µL/mL. The probable toxicity mechanism results show membrane impairment and cellular homeostasis linked with decreased ergosterol content, increased cation leakage, impairment in antioxidant defenses, carbon metabolism, and transcriptional genes (Ver-1 and Nor-1) functioning of AFB1 biosynthesis. Furthermore, during the six months in-situ trial, Ne-CEO (0.4 µL/mL) remarkably protected the biodeterioration of A. hypogaea seed samples against A. flavus growth and AFB1 contamination, thus enhancing its practical application as a plant-based food preservative to enhance the shelf-life of food commodities. [ABSTRACT FROM AUTHOR]

Volatility in supply and demand caused by global disruptions such as wars or pandemics requires adaptable and changeable production systems. Since assembly accounts for significant production time and costs, the demand for changeable, line-less assembly systems is advancing. Controlling mobile robots in line-less assembly depends on understanding task executability. We propose the implementation of performance maps to evaluate the executability of assembly tasks within robot workspaces. Firstly, established performance metrics and typical assembly tasks are categorized to identify which metrics evaluate the executability of which type of tasks. The assembly tasks are grouped according to the type of movement (continuous or discrete), the required execution precision (high or low), and the amount of poses for execution (reachable or dexterous). The metrics are categorized according to their range (local or global), their physics (kinematic or dynamic), task reference (intrinsic or extrinsic), and scale (absolute or relative). Metrics are then matched to task types. This matching provides a systematic way to identify metrics to assess the executability of a task. Secondly, the performance map is presented. The performance map is a discretized representation of the distribution of chosen performance metrics for a specific robot. The current implementation is restricted to calculating the manipulability, dexterity, and condition number. Based on the input of a robot model and a task type, the metrics are calculated in distributed poses for a given resolution in the robot's workspace to form the performance map. The performance map is applied to exemplary tasks and robots. Previous approaches to workspace evaluation fail to consider the suitability of performance metrics to evaluate specific tasks, as different metrics are more or less relevant for different tasks. Consequently, the paper contributes by introducing performance maps and providing quantific metrics for comparing base placements of mobile robots according to the executability of specific assembly tasks. [ABSTRACT FROM AUTHOR]

This study examines Chinese consumers' perceptions and responses to disruptive innovations within the New Energy Vehicles (NEVs) market, utilizing a questionnaire survey to explore awareness, perceived value of technological advancements, and the impact of these perceptions on adoption decisions. The survey, encompassing a diverse demographic of 154 respondents, highlights a female majority with a significant representation from the "25-34" age group, indicating a young, educated demographic with a considerable interest in NEVs. Analysis reveals a moderate familiarity with NEVs, a high valuation of technological progress, and a clear recognition of charging infrastructure availability as critical factors influencing adoption. Primary barriers identified include the high initial cost and limited charging infrastructure, with the data suggesting a strong potential for NEVs market growth if these concerns are addressed. Additionally, the survey uncovers optimistic future expectations among consumers, closely tied to government policies, technological advancements, and evolving market trends. This research contributes to understanding consumer attitudes in the rapidly changing NEVs landscape, offering insights for stakeholders to foster adoption and align strategies with consumer preferences and needs, underscoring the necessity for focused educational and marketing efforts to mitigate existing barriers and leverage consumer interest in technology. [ABSTRACT FROM AUTHOR]

This paper aims to verify the impact of capital structure on business model innovation and firm performance and the mediating effect of business model innovation. We use the data of the Chinese growth enterprises market (GME) listed high-tech firms from 2016 to 2022 as a dynamic panel data model with the system–generalized method of moments (sys-GMM), adopting return on asset and earning per share as firm performance. Our results show that capital structure has a lag effect on firm performance. The total debt ratio in the last period has a significant non-linear impact on the performance and business model innovation level of nowadays, presenting a U-shaped relationship. The first-order lag short-term debt ratio positively improves firm performance. Business model innovation significantly promotes better firm performance, and business model innovation does exist in the mediating effect between enterprise capital structure and its performance. These results remain robust to different sample sizes or proxy variables. This paper proposes some suggestions for firm operations and government policies based on the findings. [ABSTRACT FROM AUTHOR]

This article is focused on the experimental study of flexural properties in different multi-layer carbon fiber-reinforced polymer (CFRP) composites and correlations with the results of finite element method (FEM) simulations of mechanical properties. The comparison of the results shows the possibility of reducing the number of experimental specimens for testing. The experimental study of flexural properties for four types of carbon fiber-reinforced polymer matrix composites with twill weaves (2 × 2) was carried out. As input materials, pre-impregnated carbon laminate GG 204 T and GG 630 T (prepreg) and two types of carbon fiber fabrics (GG 285 T and GG 300 T (fabric)) were used. Multi-layer samples were manufactured from two types of prepregs and two types of fabrics, which were hand-impregnated during sample preparation. The layers were stacked using same orientation. All specimens for flexural test were cut with the longer side in the weft direction. Pre-impregnated carbon laminates were further impregnated with resin DT 121H. Carbon fabrics were hand-impregnated with epoxy matrix LG 120 and hardener HG 700. To fulfill the aim of this research, finite element method (FEM)-based simulations of mechanical properties were performed. The FEM simulations and analysis were conducted in Hexagon's MSC Marc Mentat 2022.3 and Digimat 2022.4 software. This paper presents the results of actual experimental bending tests and the results of simulations of bending tests for different composite materials (mentioned previously). We created material models for simulations based on two methods—MF (Mean Field) and FE (Finite Element), and the comparative results show better agreement with the MF model. The composites (GG 285 T and GG 300 T) showed better flexural results than composites made from pre-impregnated carbon laminates (GG 204 T and GG 630 T). The difference in results for the hand-impregnated laminates was about 15% higher than for prepregs, but this is still within an acceptable tolerance as per the reported literature. The highest percentage difference of 14.25% between the simulation and the real experiment was found for the software tool Digimat FE 2022.4—GG 630 T composite. The lowest difference of 0.5% was found for the software tool Digimat MF 2022.4—GG 204 T composite. By comparing the results of the software tools with the results of the experimental measurements, it was found that the Digimat MF 2022.4 tool is closer to the results of the experimental measurements than the Digimat FE 2022.4 tool. [ABSTRACT FROM AUTHOR]

Dentistry frequently makes use of intraoral scanning technologies to digitally acquire the three‐dimensional (3D) geometry of teeth. In recent times, dental clinics over the globe utilize used computer aided diagnosis (CAD) models to make treatment plans, for example, orthodontics. Orthodontic CAD system acts as a vital part of the advanced dentistry field. A 3D dental model, computed by patient impression, as input and aids dentist in the extraction, moving, deletion, and rearranging of teeth to simulate treatment output. Tooth segmentation and labelling is the basic and foremost element of the CAD model which needs to be addressed. Automated segmentation and classification of 3D dental images using advanced machine learning and deep learning (DL) models become essential. This article introduces a new 3D dental image segmentation and classification using DL with tunicate swarm algorithm (3DDISC‐DLTSA) model. The major intention of the 3DDISC‐DLTSA system is to segment the tooth model and identify seven distinct tooth types. To accomplish this, the presented 3DDISC‐DLTSA model performs image pre‐processing in two stages namely image filtering and U‐Net segmentation. In addition, the 3DDISC‐DLTSA model derives DenseNet‐169 model for feature extraction purposes. For the recognition and classification of tooth type, the TSA based hyperparameter tuning process is carried out which helps to accomplish maximum classification performance. A wide range of experimental analyses is performed and the outcomes are inspected under many aspects. On dataset‐1, 3DDISC‐DLTSA model accuracy rose by 96.67%. On dataset‐3, 3DDISC‐DLTSA model accuracy rose by 97.48% and algorithm accuracy by 97.35%. The 3DDISC‐DLTSA model outperformed more modern models, according to the comparative investigation. [ABSTRACT FROM AUTHOR]

Background: Traumatic brain injury (TBI) stands as one of the foremost reasons for mortality and incapacitation in young adults on a global scale, accounting for nearly half of all injury-related deaths. The severity of TBI can be assessed using various biomarkers, with the SI00B protein being one of them. While many studies have explored the correlation between serum protein levels and various aspects such as neuroimaging findings, clinical scores, and neuropsychological evaluations, there is a notable lack of research examining the correlation with cerebrospinal fluid (CSF) levels. Methods: The research design of this study was prospective and observational, employing analytic methods for analysis. Fifteen TBI patients who met the inclusion and exclusion criteria and were fitted with ICP monitors comprised the study sample. GCS data used is post-resuscitation GCS. Data on SIOOB protein levels were taken from the examination of CSF samples taken when the ICP monitor was installed. Rotterdam CT score variables was taken from the last CT scan performed before the patient was fitted with an ICP monitor. The statistical analysis was conducted utilizing the SPSS version 26 software. Results: Demographic characteristics for this study tended to be more male (73.3%), with ages ranging from 18 to 65 years, and a mean age of 34.60 ± 16.22 years. The majority of injury mechanisms were traffic accidents (80%), and the most common lesion type was ICH. The mean CSF S 100B value of the 15 samples was 2753.689 pg/ml. The results of the relationship test between S 100B CSF and GCS using the Spearman test obtained a p-value of less than 0.05, indicating a meaningful correlation between S 100B CSF and GCS, with a correlation coefficient or r value of -0.684. The results of the SIOOB CSF relationship test with Rotterdam CT Score obtained a p-value <0.05, with a correlation coefficient or r value of 0.827. Conclusion: Increased levels of S100B in cerebrospinal fluid are associated with decreased GCS and increased Rotterdam CT score in traumatic brain injury patients. [ABSTRACT FROM AUTHOR]

Background: Propofol TIVA has been shown to be more effective than sevoflurane in craniotomy surgery. Propofol TIVA offers the benefit of giving better brain relaxation during surgery while also being less expensive than sevoflurane. Nonetheless, it is important to highlight that propofol has side effects that should be considered. Large doses and prolonged anesthesia may result in increased triglycerides (lipids) as well as Propofol Infusion Syndrome (PRIS). As part of their investigation into the detrimental effects of propofol, researchers discovered the necessity for controls to avoid confusing the effects of the surgery itself. Therefore, sevoflurane was chosen as the control group to comprehend and analyze the effects of propofol more accurately. Methods: A prospective observational study analysis was conducted on elective craniotomy patients at RSUD Dr. Soetomo from November to December 2023. 52 subjects were divided into two groups, namely the TIVA Propofol and Sevoflurane Inhalation groups. Each group will be examined for preoperative triglyceride levels and postoperative triglyceride levels while already in the ICU. Results: Postoperative triglyceride levels in the Propofol TIVA group were significantly higher. In the comparison test between the two anesthesia methods on triglyceride levels, there was a significant effect in the Propofol TIVA group. In the test of the relationship between the duration of anesthesia in both groups, there was no significant relationship. In the test of the relationship between the total dose of propofol and triglyceride levels, it was found that the greater the dose of propofol used, the higher the increase in triglyceride levels. In the test of the relationship between the total amount of sevoflurane and triglyceride levels, it was found that the greater the dose of sevoflurane used, the greater the decrease in triglyceride levels, which was statistically not significant. Conclusion: TIVA Propofol increases triglyceride levels compared to sevoflurane inhalation in patients undergoing elective craniotomies. [ABSTRACT FROM AUTHOR]