Search Results (10)

Hepatobiliary surgery is a technically complex subspecialty within general surgery, which requires a comprehensive understanding of complex liver and liver tumour anatomy. The current body of literature highlights the use of three-dimensional-printed liver models (3DPLMs) reconstructed from medical imaging datasets may improve clinician comprehension of patient-specific liver anatomy thus creating a useful tool for hepatobiliary surgical planning and clinician training. The purpose of this systematic review was to examine the clinical utility and feasibility of 3DPLMs in hepatobiliary surgical planning and clinical education and investigate whether these applications influence patient outcomes. Studies were retrieved from three electronic databases (ProQuest, PubMed and Scopus) according to predetermined eligibility criteria. In total, 25 eligible articles were identified, including 18 original research articles and seven case reports. An inductive content analysis approach suitable for heterogeneous bodies of literature was used to synthesise key concepts in this review. There are significant case report and descriptive evidence to support the use of 3DPLMs in clinical education, preoperative planning and intraoperative guidance of patient liver and tumour anatomy to improve hepatobiliary surgical decision making. The studies presented display a large variance in cost and times necessary for the production of 3DPLMs, as studies did not include the software, equipment and full expense of materials used. Additionally, studies concentrated on different aspects of the 3DPLMs production process making them not comparable. This review demonstrates the potential value of 3DPLMs in clinical education, preoperative planning and intraoperative guidance in hepatobiliary anatomy and surgery. Future studies, in particular, randomised controlled trials and experimental research are required to investigate the relationship between 3DPLMs and clinical education and surgical planning outcomes. Full article

The Philippines, located along the Pacific Ring of Fire, is highly susceptible to significant seismic activity arising from the active convergence of major tectonic plates. These seismic events often induce ground shaking intense enough to trigger soil liquefaction, particularly in geologically sensitive regions such as Davao del Sur. This study presents a nonlinear static and dynamic analysis of a mat foundation for a proposed midrise building located within the liquefaction-prone zone of Padada, Davao del Sur. Geotechnical data were obtained through rotary drilling and Standard Penetration Tests (SPTs), which provided the basis for developing the numerical model. Liquefaction assessment was conducted using the PLAXIS Liquefaction Model (UBC3D-PLM), confirming that the site adjacent to the Padada–Mainit River exhibits a high liquefaction potential. Subsequently, finite element analyses were performed in PLAXIS 3D using ground motion records from the 2013 Bohol Earthquake, scaled to 1.0 g, and modeled under the Hardening Soil Model with Small-Strain Stiffness (HSsmall). Results showed excess pore pressure ratios approaching 1, and vertical displacements of the mat foundation exceed 100 mm. These results suggest severe degradation in soil strength, as well as reduced friction angles and mobilized pressure. Full article

This study assessed and compared the postmortem concentrations of 6-monoacetylmorphine [6-MAM] and 6-acetylcodeine [6-AC], morphine, and codeine in various tissues and fluids from 52 postmortem cases related to heroin use. Samples were received at the Poison Control and Forensic Chemistry Center in Jeddah, Saudi Arabia, and analyzed using liquid chromatography–mass spectrometry. Descriptive and inferential statistics, including median, range, variability, and outliers, were used for analysis. The results showed significant variability in heroin and metabolite concentrations across different fluids and tissues. Tissue specimens were analyzed in 38 cases (73%), with 50% of cases exhibiting putrefaction. Blood and tissue samples were available in 39 cases, highlighting the need for alternative specimens in challenging cases. Notably, heroin metabolites were detected in unique matrices, such as nasal swabs, bladder tissues, lung tissues, and small intestine tissues, underscoring the potential of these samples in forensic investigations, especially when traditional bodily fluids are unavailable or compromised. These findings suggest that environmental factors, timing of substance use, and postmortem changes influence substance distribution, emphasizing the need to consider the location of death when interpreting toxicological results for accurate forensic analysis. This study provides valuable insights into the distribution, correlation, and significance of heroin and its metabolites in postmortem samples, aiding the confirmation of heroin overdose. These findings contribute to the limited data on postmortem cases in the Middle East and North Africa, particularly Saudi Arabia, supporting efforts to curb drug abuse in this region. This knowledge can inform public health strategies and forensic practices, ultimately aiding efforts to address and mitigate drug abuse. Full article

In this article, a numerical calibration procedure for undrained cyclic triaxial tests is presented to evaluate the liquefaction potential in sand and silt samples from mining tailings in northern Chile. The numerical modeling of an axisymmetric specimen involved two stages: isotropic consolidation using the Hardening Soil Small (HSS) model and a cycling phase employing the UBC3D-PLM model to simulate the onset of liquefaction using the criterion that the excess pore pressure ratio $R_u$ should exceed 0.8. The results demonstrate that the UBC3D-PLM modeling calibrated with experimental data from cyclic triaxial tests effectively represents the excess pore pressure in both sandy and silty soils from mining tailings. The accuracy of the modeling decreases when a single set of parameters is applied to the same soil at different cyclic stress ratios (CSR), highlighting the need for specific calibrations for each loading. Full article

The prediction of vacant parking spaces (VPSs) can reduce the time drivers spend searching for parking, thus alleviating traffic congestion. However, previous studies have mostly focused on modeling the temporal features of VPSs using historical data, neglecting the complex and extensive spatial characteristics of different parking lots within the transportation network. This is mainly due to the lack of direct physical connections between parking lots, making it challenging to quantify the spatio-temporal features among them. To address this issue, we propose a dynamic spatio-temporal adaptive graph convolutional recursive network (DSTAGCRN) for VPS prediction. Specifically, DSTAGCRN divides VPS data into seasonal and periodic trend components and combines daily and weekly information with node embeddings using the dynamic parameter-learning module (DPLM) to generate dynamic graphs. Then, by integrating gated recurrent units (GRUs) with the parameter-learning graph convolutional recursive module (PLGCRM) of DPLM, we infer the spatio-temporal dependencies for each time step. Furthermore, we introduce a multihead attention mechanism to effectively capture and fuse the spatio-temporal dependencies and dynamic changes in the VPS data, thereby enhancing the prediction performance. Finally, we evaluate the proposed DSTAGCRN on three real parking datasets. Extensive experiments and analyses demonstrate that the DSTAGCRN model proposed in this study not only improves the prediction accuracy but can also better extract the dynamic spatio-temporal characteristics of available parking space data in multiple parking lots. Full article

Subway systems are a crucial component of urban public transportation, especially in terms of safety during seismic events. Soil liquefaction triggered by earthquakes is one of the key factors that can lead to underground structural damage. This study investigates the impact of deep soil liquefaction on the response of subway station structures during seismic activity, aiming to provide evidence and suggestions for earthquake-resistant measures in underground constructions. The advanced finite element software PLAXIS was utilized for dynamic numerical simulations. Non-linear dynamic analysis methods were employed to construct models of subway stations and the surrounding soil layers, including soil–structure interactions. The UBC3D-PLM liquefaction constitutive model was applied to describe the liquefaction behavior of soil layers, while the HS constitutive model was used to depict the dynamic characteristics of non-liquefied soil layers. The study examined the influence of deep soil liquefaction on the dynamic response of subway station structures under different seismic waves. The findings indicate that deep soil liquefaction significantly increases the vertical displacement and acceleration responses of subway stations compared to non-liquefied conditions. The liquefaction behavior of deep soil layers leads to increased horizontal effective stress on both sides of the structure, thereby increasing the horizontal deformation of the structure and posing a potential threat to the safety and functionality of subway stations. This research employed detailed numerical simulation methods, incorporating the non-linear characteristics of deep soil layer liquefaction, providing an analytical framework based on regulatory standards for evaluating the impact of deep soil liquefaction on the seismic responses of subway stations. Compared to traditional studies, this paper significantly enhances simulation precision and practical applicability. Results from this research indicate that deep soil layer liquefaction poses a non-negligible risk to the structural safety of subway stations during earthquakes. Therefore, the issue of deep soil liquefaction should receive increased attention in engineering design and construction, with effective prevention and mitigation measures being implemented. Full article

Successful liver cancer resection requires a comprehensive pre- and intraoperative understanding of the spatial relationships between a patient’s cancer and intrahepatic anatomy. The recent literature has highlighted that patient-specific 3D-printed liver models (3DPLMs) reconstructed from medical imaging data may enhance the comprehension of patients’ liver anatomy and thereby provide a useful preoperative planning and intraoperative guidance tool for liver cancer resection (LCR). The purpose of this systematic review was to critically examine the utility and feasibility of 3DPLMs for LCR surgical planning and intraoperative guidance and explore whether these applications improve patient outcomes. Articles were retrieved from four electronic databases (Scopus, Embase, PubMed, and Curtin University Database) according to predetermined eligibility criteria. In total, 22 eligible articles were identified, including 11 original research articles and 11 case reports. Key concepts were synthesised using an inductive content analysis approach suitable for this heterogeneous body of literature. There is significant descriptive and case-report evidence that 3DPLMs strengthen pre- and intraoperative comprehension of patient liver and liver tumour anatomy and can enhance pre- and intraoperative surgical decision making for LCR. The analysis of these studies presents large variances in the times and costs necessary to produce 3DPLMs, as studies did not provide the full expenses of materials, software, and equipment. Production times were focused on different aspects of the 3D printing process and were not comparable. The review nonetheless demonstrates the potential value of 3DPLMs as preoperative planning and intraoperative guidance tools for LCR. Future studies should detail these economic data points to ensure 3DPLMs’ viability. Further experimental research and randomised controlled trials are also necessary to examine the relationship between 3DPLMs and patient’s intra- and postoperative outcomes. Full article

In this study, the presence of 11-nor-Δ⁹-carboxy tetrahydrocannabinol (THC-COOH) in postmortem fluid obtained from the chest cavity (FCC) of postmortem cases collected from drug-related fatalities or criminal-related deaths in Jeddah, Saudi Arabia, was investigated to evaluate its suitability for use as a complementary specimen to blood and biological specimens in cases where no bodily fluids are available or suitable for analysis. The relationships between THC-COOH concentrations in the FCC samples and age, body mass index (BMI), polydrug intoxication, manner, and cause of death were investigated. Methods: Fifteen postmortem cases of FCC were analyzed using fully validated liquid chromatography-positive-electrospray ionization tandem mass spectrometry (LC-MS/MS). Results: FCC samples were collected from 15 postmortem cases; only THC-COOH tested positive, with a median concentration of 480 ng/mL (range = 80–3010 ng/mL). THC-COOH in FCC were higher than THC-COOH in all tested specimens with exception to bile, the median ratio FCC/blood with sodium fluoride, FCC/urine, FCC/gastric content, FCC/bile, FCC/liver, FCC/kidney, FCC/brain, FCC/stomach wall, FCC/lung, and FCC/intestine tissue were 48, 2, 0.2, 6, 4, 6, 102, 11, 5 and 10-fold, respectively. Conclusion: This is the first postmortem report of THC-COOH in the FCC using cannabinoid-related analysis. The FCC samples were liquid, easy to manipulate, and extracted using the same procedure as the blood samples. The source of THC-COOH detected in FCC could be derived from the surrounding organs due to postmortem redistribution or contamination due to postmortem changes after death. THC-COOH, which is stored in adipose tissues, could be a major source of THC-COOH found in the FCC. Full article

The rise of digitalization, sensory devices, cloud computing and internet of things (IoT) technologies enables the design of novel digital product lifecycle management (DPLM) applications for use cases such as manufacturing and delivery of digital products. The verification of the accomplishment/violations of agreements defined in digital contracts is a key task in digital business transactions. However, this verification represents a challenge when validating both the integrity of digital product content and the transactions performed during multiple stages of the DPLM. This paper presents a traceability method for DPLM based on the integration of online and offline verification mechanisms based on blockchain and fingerprinting, respectively. A blockchain lifecycle registration model is used for organizations to register the exchange of digital products in the cloud with partners and/or consumers throughout the DPLM stages as well as to verify the accomplishment of agreements at each DPLM stage. The fingerprinting scheme is used for offline verification of digital product integrity and to register the DPLM logs within digital products, which is useful in either dispute or violation of agreements scenarios. We built a DPLM service prototype based on this method, which was implemented as a cloud computing service. A case study based on the DPLM of audios was conducted to evaluate this prototype. The experimental evaluation revealed the ability of this method to be applied to DPLM in real scenarios in an efficient manner. Full article

In this study, we present a procedure to optimize a set of finite impulse response filter (FIR) coefficients for digital pulse-amplitude measurement. Such an optimized filter is designed using an adapted digital penalized least mean square (DPLMS) method. The effectiveness of the procedure is demonstrated using a dataset from a case study on high-resolution X-ray spectroscopy based on single-photon detection and energy measurements. The energy resolutions of the K${}_{\alpha }$ and K${}_{\beta }$ lines of the Manganese energy spectrum have been improved by approximately $20\%$, compared to the reference values obtained by fitting individual photon pulses with the corresponding mathematical model. Full article