Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of intracranial aneurysm rupture risk using a point cloud-based deep learning model

Background and Purpose: Precisely assessing the likelihood of an intracranial aneurysm rupturing is critical for guiding clinical decision-making. The objective of this study is to construct and validate a deep learning framework utilizing point clouds to forecast the likelihood of aneurysm rupturing. Methods: The dataset included in this study consisted of a total of 623 aneurysms, with 211 of them classified as ruptured and 412 as unruptured, which were obtained from two separate projects within the AneuX morphology database. The HUG project, which included 124 ruptured aneurysms and 340 unruptured aneurysms, was used to train and internally validate the model. For external validation, another project named @neurIST was used, which included 87 ruptured and 72 unruptured aneurysms. A standardized method was employed to isolate aneurysms and a segment of their parent vessels from the original 3D vessel models. These models were then converted into a point cloud format using open3d package to facilitate training of the deep learning network. The PointNet++ architecture was utilized to process the models and generate risk scores through a softmax layer. Finally, two models, the dome and cut1 model, were established and then subjected to a comprehensive comparison of statistical indices with the LASSO regression model built by the dataset authors. Results: The cut1 model outperformed the dome model in the 5-fold cross-validation, with the mean AUC values of 0.85 and 0.81, respectively. Furthermore, the cut1 model beat the morphology-based LASSO regression model with an AUC of 0.82. However, as the original dataset authors stated, we observed potential generalizability concerns when applying trained models to datasets with different selection biases. Nevertheless, our method outperformed the LASSO regression model in terms of generalizability, with an AUC of 0.71 versus 0.67. Conclusion: The point cloud, as a 3D visualization technique for intracranial aneurysms, can effectively capture the spatial contour and morphological aspects of aneurysms. More structural features between the aneurysm and its parent vessels can be exposed by keeping a portion of the parent vessels, enhancing the model’s performance. The point cloud-based deep learning model exhibited good performance in predicting rupture risk while also facing challenges in generalizability.
THE BURDEN OF ROAD TRAFFIC INJURIES IN ISFAHAN, IRAN IN 2010

Abstract: Background & Aims: Traffic accidents are a major cause of disability and mortality around the world and a major public health problem in developing and developed countries. The aim of this study was to assess the burden of road traffic accidents in Isfahan, Iran. Methods: This cross-sectional study was conducted in Isfahan in 2010. Data were collected from death registration system to calculate years of life lost (YLL) due to traffic accidents. To determine the rate of years lived with disability, hospital records of all people injured in road accidents were used. The methodology of the World Health Organization were used to estimate DALY (Disability adjusted life year), YLD, and YLL. Results: During 2010, the rate of DALY was 23.36 per thousand of which 3.99 per thousand was related to YLL and 19.37 per thousand was related to YLD. DALY rates in males and females were respectively 37.43 per thousand and 8.60 per thousand. Maximum rates of YLL and YDL were in the young age group (15-44). The highest rate of DALY was in summer (6.73 per thousand) and the lowest was in winter (4.29 per thousand). Conclusions: The results of this study showed that accident-related deaths and injuries are mostly in middle-aged men. Since those are the active group of society, traffic accidents can be considered as an economic burden on society. Therefore, appropriate intervention programs and periodic evaluation are required to minimize traffic accidents. Keywords: Keywords: Burden of traffic accident, Death, Disability, DALY, YLL, YLD
Efficient Near-Infrared Spectrum Detection in Nondestructive Wood Testing via Transfer Network Redesign

This study systematically developed a deep transfer network for near-infrared spectrum detection using convolutional neural network modules as key components. Through meticulous evaluation, specific modules and structures suitable for constructing the near-infrared spectrum detection model were identified, ensuring its effectiveness. This study extensively analyzed the basic network components and explored three unsupervised domain adaptation structures, highlighting their applications in the nondestructive testing of wood. Additionally, five transfer networks were strategically redesigned to substantially enhance their performance. The experimental results showed that the Conditional Domain Adversarial Network and Globalized Loss Optimization Transfer network outperformed the Direct Standardization, Piecewise Direct Standardization, and Spectral Space Transformation models. The coefficients of determination for the Conditional Domain Adversarial Network and Globalized Loss Optimization Transfer network are 82.11% and 83.59%, respectively, with root mean square error prediction values of 12.237 and 11.582, respectively. These achievements represent considerable advancements toward the practical implementation of an efficient and reliable near-infrared spectrum detection system using a deep transfer network.
Design and Control of a Soft Knee Exoskeleton for Pediatric Patients at Early Stages of the Walking Learning Process

Pediatric patients can suffer from different motor disorders that limit their neurological and motor development and hinder their independence. If treated at the very early stages of development, those limitations can be palliated or even removed. However, manual interventions are not completely effective due to the restrictions in terms of time, force, or tracking experienced by the physiotherapists. The knee flexo-extension is crucial for walking and often affected by disorders such as spasticity or lack of force in the posterior chain. This article focuses on the development of a knee exosuit to follow angular trajectories mimicking the maximum and minimum peaks present in the knee flexo-extension profiles of healthy individuals during walking. The proposed exosuit is based on shape memory alloy actuators along with four inertial sensors that close the control loop. The whole device is controlled through a two-level controller and has an hybrid rigid–flexible design to overcome the different issues present in the literature. The device was proven to be feasible for this type of application, with replicable and consistent behavior, reducing the price and weight of existing exosuits and enhancing patient comfort.
Knowledge, Awareness, and Practices toward Colorectal Cancer and Its Dietary and Lifestyle-Related Risk Factors among Jordanian University Students: A Cross-Sectional Study

Background Globally, colorectal cancer (CRC) incidence is rising, and it is a leading cause of mortality, with greater death rates pronounced in developing countries, including Jordan. Understanding knowledge and awareness of etiologic factors, unhealthy lifestyles, and dietary patterns is crucial for combating ailments. Hence, this study is aimed at investigating the level of knowledge and awareness of CRC-related risk factors, practices, and possible associations of studied variables among young Jordanians. Methodology. A cross-sectional, observational study was conducted using an online self-reported assessment of anthropometrics, knowledge, awareness, and dietary and lifestyle practices toward CRC and its related risk factors. Results A study of 795 Jordanian university students found that 93.8% were Jordanians, 73.0% were female, aged 18-24, and single. Most participants were from medical and science schools (69.4%). The vast majority (about 84%) were found to have good knowledge and awareness of CRC and its risk factors, but this was not reflected in their dietary practices. There are significant differences in physical activity, smoking, vegetable consumption, and serving sizes of red meat and processed meats between the sexes. Academic study specialties significantly impact knowledge and awareness. Conclusion The study reveals that while young Jordanian university students have good knowledge and awareness about CRC and its risk factors, these levels are not reflected in their dietary behaviors and food choices for CRC prevention, highlighting the need for national programs to improve these practices, particularly in the younger population.
Towards Temporal Mobility Markov Chains

In this paper, we define a type of mobility model that we coin as temporal Mobility Markov Chain (tMMC), which can represent in a compact yet precise way the mobility behaviour of an individual. In short, a tMMC is a timed and probabilistic automaton in which states represent points of interest (POIs) of an individual and transitions between states corresponds to a movement from one POI to another one. The automaton is probabilistic in the sense that a transition between POIs is non deterministic but rather that there is a probability distribution over the transitions that corresponds to the probability of moving from one POI to another (edges are directed).
Recent advances in the treatment and delivery system of diabetic retinopathy

Diabetic retinopathy (DR) is a highly tissue-specific neurovascular complication of type 1 and type 2 diabetes mellitus and is among the leading causes of blindness worldwide. Pathophysiological changes in DR encompass neurodegeneration, inflammation, and oxidative stress. Current treatments for DR, including anti-vascular endothelial growth factor, steroids, laser photocoagulation, and vitrectomy have limitations and adverse reactions, necessitating the exploration of novel treatment strategies. This review aims to summarize the current pathophysiology, therapeutic approaches, and available drug-delivery methods for treating DR, and discuss their respective development potentials. Recent research indicates the efficacy of novel receptor inhibitors and agonists, such as aldose reductase inhibitors, angiotensin-converting enzyme inhibitors, peroxisome proliferator-activated receptor alpha agonists, and novel drugs in delaying DR. Furthermore, with continuous advancements in nanotechnology, a new form of drug delivery has been developed that can address certain limitations of clinical drug therapy, such as low solubility and poor penetration. This review serves as a theoretical foundation for future research on DR treatment. While highlighting promising therapeutic targets, it underscores the need for continuous exploration to enhance our understanding of DR pathogenesis. The limitations of current treatments and the potential for future advancements emphasize the importance of ongoing research in this field.
High upward fluxes of formic acid from a boreal forest canopy

Eddy covariance fluxes of formic acid, HCOOH, were measured over a boreal forest canopy in spring/summer 2014. The HCOOH fluxes were bidirectional but mostly upward during daytime, in contrast to studies elsewhere that reported mostly downward fluxes. Downward flux episodes were explained well by modeled dry deposition rates. The sum of net observed flux and modeled dry deposition yields an upward “gross flux” of HCOOH, which could not be quantitatively explained by literature estimates of direct vegetative/soil emissions nor by efficient chemical production from other volatile organic compounds, suggesting missing or greatly underestimated HCOOH sources in the boreal ecosystem. We implemented a vegetative HCOOH source into the GEOS‐Chem chemical transport model to match our derived gross flux and evaluated the updated model against airborne and spaceborne observations. Model biases in the boundary layer were substantially reduced based on this revised treatment, but biases in the free troposphere remain unexplained.
Investigating the use of snags and downed logs by wild animals in Federal College of Wildlife Management, New-Bussa, Nigeria

This study examined the uses of snags and downed logs in the Federal College of Wildlife Management, New Bussa. The research aimed to identify the kinds of trees that produce snags and deadwood logs in the study region as well as the ways that wild animals utilize these snags and deadwood logs in the study area. The methodology employed involves the use of plot sampling method. Field observation of plant species that have turned into dead trees was carried out. The data obtained were analyzed using descriptive statistics (tables and charts). The results showed that a significant number of plant species were identified as snags and down logs; the finding indicates that Terminelia glaucocens having (12.5%) occurrence and Pterocarpus erinaceus (10.71) was the predominant species in the study area. These dead trees species are used by wild animals in a variety of ways; for instance, 50% of wild animals use the snags and down logs for perching, 17.44% use them as foraging sites, and 4.65% use them as nesting sites. The most common users are squirrels, accounting for 13.95% of the total, followed by francolins birds (11.63%) and hawks (1.16%). Since many wildlife species rely on these trees to survive, it is imperative to protect these tree species inside the college estate to stop the extinction of wild animals. It is not advisable to remove snags.
End-to-End Workflows for Coupled Climate and Hydrological Modeling

: In order to examine the effects of environmental changes on local watersheds, it has become increasingly important to be able to interoperate between diverse models and document and share the resulting data. To this end, we are prototyping an end-to-end workflow that executes multiple, distributed models, loosely couples the model components, and disseminates the model results and metadata using a data portal. This project is made up of three major components and is implemented in multiple phases. The main components include the interface to the models for configuration and execution, the interface to the portal for data dissemination, and the workflow that provides the glue to make it all work together. The models being coupled are a high performance atmospheric model (currently represented by a stubbed-out ESMF Component) and the hydrological model, SWAT (Soil and Water Assessment Tool). Each model is accessed via standard interfaces (OpenMI, ESMF), set up as web services, and in the final product, the resulting data will be published to the ESG (Earth System Grid) or other data portal. Managing the model execution and coupling is initially handled by the OpenMI Configuration Manager, but may eventually be replaced by a more extensive workflow application, such as Kepler. The resulting product is an end-to-end, self-describing and repeatable workflow that demonstrates one-way interactive systems involving climate and other models can be created to address emerging questions about climate impacts.
The Elastic Behavior of Plagioclase Feldspar at High Pressure

Feldspars are one of the archetypical families of framework silicates. They not only comprise around 60% volumetrically of the Earth’s crust, but are among some of the most structurally complicated minerals. Investigation into the structural behavior of various intermediate plagioclases at pressure has been undertaken with the intent of categorizing the elastic behavior with pressure across the solid solution series and establishing a conceptual model to characterize feldspar compression. Complex behavior has been observed in the Equation of State for plagioclase feldspars in excess of 3 GPa, including an anomalous softening of ordered albite in excess of 8.4 GPa (Benusa et al 2005: Am Min 90:1115-1120). This softening was not observed in the EoS for the more intermediate plagioclase compositions containing between 20 and 40 mol% of end-member anorthite. The calculated elastic compliance tensor sums at room pressure show a general stiffening with increasing anorthite component, small elastic changes at the C-1 to I-1 transition, and a dominantly first-order response at the P-1 to I-1 transition near end-member anorthite. The crystal structure of An37 plagioclase was determined by single-crystal X-ray diffraction. The compression mechanisms in An37 are similar to those in albite at lower pressures. The softening in albite at higher pressures is therefore attributed to the structural shearing in albite that is absent in An37 plagioclase up to 9.5 GPa.
Phase-user Relationship Identification Method in Low-voltage Distribution Area Based on FSC-DTW Distance and Clustering Analysis

Aiming at the problem of identifying the topological relationship between the distribution transformer phase sequence and the users in the low-voltage distribution area under the scenario of incomplete data, this paper proposes a method based on fuzzy shape context-dynamic time warping (FSC-DTW) distance and clustering analysis. Firstly, the FSC histogram at each point of each voltage sequence is calculated as the shape descriptor at this point. Secondly, the shape matching cost matrix between each voltage sequence is constructed and used instead of the distance matrix in the classical DTW algorithm to measure the similarity between each voltage sequence. Then, Searching for the alignment path with the minimum cost of regularization. Finally, based on the FCM algorithm, the phase sequence of the distribution transformer and the users are clustered to obtain the phase of the area users. In this paper, the fuzzy membership function is constructed to improve the expression ability of the classical shape context shape descriptor, and the ill-conditioned alignment problem of the classical DTW algorithm is solved by the FSC descriptor. This method can realize the identification of the relationship between the distribution transformer phase sequence and the users in the case of incomplete data or unequal time intervals in the voltage sequence. The simulation results verify the effectiveness and correctness of the proposed method.
Comparison of Late Pliocene and Late Pleistocene Sea-Surface Temperatures in the Equatorial Atlantic Divergence

The record of planktonic foraminifer abundances at Site 662 during the late Pliocene (~ 1.7-2.1 Ma) was examined to determine variations in estimated sea-surface temperature (SST). We compared the results to SST estimates from a late Pleistocene record (~ 1.5-200 ka) from nearby piston core RC24-7. Within the primary orbital band (~20-100 k.y.), the cold-season responses of both equatorial Atlantic records are dominated by the precessional period, and the computed range of variability is quite similar. This is in contrast to the evolution of the dominant climatic response from 41 to 100 k.y. at high northern latitudes between the late Pliocene and the late Pleistocene. The orbital-band SST response in this region of greatest divergence in the equatorial Atlantic has not changed appreciably between the late Pliocene and the late Pleistocene.
A Wideband Polarization Conversion Metasurface with Stable Wide-Angle Performance

A novel polarization conversion metasurface (PCM) is proposed to achieve linearly polarized conversion with good oblique incidence performance. The unit cell of the metasurface is a composite structure consisting of a slotted hexagonal patch and two T-shaped strips. Simulation results show that the polarization conversion ratio (PCR) of the metasurface is higher than 0.9 in the frequency range of 8.46–15.28 GHz (57.45%) for perpendicularly incident TE and TM waves. Furthermore, the device exhibits excellent angular stability. Compared to the case of vertical, when the incident angle is increased to 46°, the bandwidth reduction with PCR > 0.9 is 3.86% for TE incident, and 4.14% for TM incident wave.
Metasurface-Based Wideband Low-RCS Circularly Polarized Antenna

In this paper, a broadband low radar cross-section (RCS) circularly polarized (CP) antenna based on metasurface is proposed. The proposed metasurface unit has the ability of broadband polarization conversion, which is further arranged into a $\boldsymbol{2}\times \boldsymbol{2}$ chessboard metasurface and fed by a sequential rotating feed network to achieve broadband CP radiation and low RCS performance. For the proposed CP antenna, simulation results exhibit that an impedance bandwidth and a 3 dB axial ratio bandwidth of 56.1% (5-8.9 GHz) and 26.7% (6.25-8.18 GHz), respectively, with a peak gain of 9.4 dBi. Additionally, the proposed CP antenna obtains at least 5 dB RCS reduction over a wide frequency range of 6.23-18.6 GHz (99.6%).
Utilizing BERT for Information Retrieval: Survey, Applications, Resources, and Challenges

Recent years have witnessed a substantial increase in the use of deep learning to solve various natural language processing (NLP) problems. Early deep learning models were constrained by their sequential or unidirectional nature, such that they struggled to capture the contextual relationships across text inputs. The introduction of bidirectional encoder representations from transformers (BERT) leads to a robust encoder for the transformer model that can understand the broader context and deliver state-of-the-art performance across various NLP tasks. This has inspired researchers and practitioners to apply BERT to practical problems, such as information retrieval (IR). A survey that focuses on a comprehensive analysis of prevalent approaches that apply pretrained transformer encoders like BERT to IR can thus be useful for academia and the industry. In light of this, we revisit a variety of BERT-based methods in this survey, cover a wide range of techniques of IR, and group them into six high-level categories: (i) handling long documents, (ii) integrating semantic information, (iii) balancing effectiveness and efficiency, (iv) predicting the weights of terms, (v) query expansion, and (vi) document expansion. We also provide links to resources, including datasets and toolkits, for BERT-based IR systems. Additionally, we highlight the advantages of employing encoder-based BERT models in contrast to recent large language models (LLMs) like ChatGPT, which are decoder-based and demand extensive computational resources. Finally, we summarize the comprehensive outcomes of the survey and suggest directions for future research in the area.