Search results for: aortic dissection detection risk score

Authors: Obulesh Avuku, Satwik Sunnam, Sri Charan Mohan Janthuka, Keerthi Yalamaddi

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In the United States alone, there are over 1.5 million spine fractures per year, resulting in about 17,730 spinal cord injuries. The cervical spine is where fractures in the spine most frequently occur. The prevalence of spinal fractures in the elderly has increased, and in this population, fractures may be harder to see on imaging because of coexisting degenerative illness and osteoporosis. Nowadays, computed tomography (CT) is almost completely used instead of radiography for the imaging diagnosis of adult spine fractures (x-rays). To stop neurologic degeneration and paralysis following trauma, it is vital to trace any vertebral fractures at the earliest. Many approaches have been proposed for the classification of the cervical spine [2d models]. We are here in this paper trying to break the bounds and use the vision transformers, a State-Of-The-Art- Model in image classification, by making minimal changes possible to the architecture of ViT and making it 3D-enabled architecture and this is evaluated using a weighted multi-label logarithmic loss. We have taken this problem statement from a previously held Kaggle competition, i.e., RSNA 2022 Cervical Spine Fracture Detection.

Keywords: cervical spine, spinal fractures, osteoporosis, computed tomography, 2d-models, ViT, multi-label logarithmic loss, Kaggle, public score, private score

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Authors: Ae Ra Han, Taek Hoo Lee, Sun Zoo Kim, Hwa Young Lee

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Introduction: Ovarian endometrioma is one of the important causes of poor ovarian reserve and up to half of them have recurred. However, the treatment for recurrence prevention has limited efficiency and repeated surgical management makes worsen the ovarian reserve. To find better management for recurrence prevention, we investigated risk factors and biomarkers for the recurrence of ovarian endometrioma. Methods: The medical records of women with the history of surgical dissection for ovarian endometrioma were collected. After exclusion of the cases with concurrent hysterectomy, been menopaused during follow-up, incomplete medical record, and loss of follow-up, a total of 134 women were enrolled. Immunohistochemical staining for progesterone receptor isoform B (PR-B) and nuclear factor kappa B (NFκB) was done with the fixed tissue blocks of their endometriomas which were collected at the time of surgery. Results: Severity of dysmenorrhea and co-existence of adenomyosis had significant correlation with recurrence of endometrioma. Increased PR-B (P = .041) and decreased NFκB (P = .036) immunoreactivity were found in recurrent group. Serum CA-125 level at the time of recurrence was higher than the highest level of CA-125 during follow-up in unrecurred group (55.6 vs. 21.3 U/mL, P = .014). Conclusion: We found that the severity of dysmenorrhea and coexistence of adenomyosis are risk factors for recurrence of ovarian endometrioma, and serial follow-up of CA-125 is effective to detect and prevent the recurrence. However, to determine the possibility of immunoreactivity of PR-B and NFκB as biomarkers for ovarian endometrioma, further studies of various races and large numbers with prospective design are needed.

Keywords: endometriosis, recurrence, biomarker, risk factor

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Authors: Tomohiro Uchida, Noriaki Satake, Toshimichi Nakaho, Akira Inoue, Hidemitsu Saito

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In this study, we assessed the bereavement risk of family caregivers of patients with cancer. In the palliative care unit of Tohoku University Hospital, we conducted a family psychoeducation session to support the family caregivers of patients with cancer. A total of 50 participants (8 males and 42 females; mean age = 62.98 years, SD = 11.10) were assessed after the session for bereavement risk using the Japanese version of the Bereavement Risk Assessment Tool (BRAT-J). According to the BRAT-J scores, eight participants were considered to be having no known risk (Level 1), seventeen had minimal risk (Level 2), twenty had a low risk (Level 3), four had a moderate risk (Level 4), and one had a high risk (Level 5). Of these participants, seven participants had completed the follow-up postal survey that assessed their psychological distress (the Kessler Psychological Distress Scale: K6) to compare the bereavement risk. According to the K6 scores, three-fourth of the individuals, who were considered to be at Level 3 on the BRAT-J, scored higher than the cutoff point (>10) for the detection of depressive disorder. On the other hand, one-third of the individuals, who were considered to be at Level 2 on the BRAT-J, scored higher than the cutoff point. Therefore, it appears that the BRAT-J can predict the likelihood of difficulties or complications in bereaved family caregivers. This research was approved by the Ethics Committee of Tohoku University Graduate School of Medicine and Tohoku University Hospital.

Keywords: palliative care, family caregivers, bereavement risk, BRAT, post-loss psychological distress

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Authors: Novee Lor C. Leyso, Maylin C. Palatino

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Under-five malnutrition continues to persist in the Philippines, particularly in the island Province of Marinduque, with prevalence of some forms of malnutrition even worsening in recent years. Local spatial cluster detection provides a spatial perspective in understanding this phenomenon as key in analyzing patterns of geographic variation, identification of community-appropriate programs and interventions, and focused targeting on high-risk areas. Using data from a province-wide household-based census conducted in 2014–2016, this study aimed to determine and evaluate spatial clusters of under-five malnutrition, across the province and within each municipality at the individual level using household location. Malnutrition was defined as weight-for-age z-score that fall outside the 2 standard deviations from the median of the WHO reference population. The Kulldorff’s elliptical spatial scan statistic in binomial model was used to locate clusters with high-risk of malnutrition, while adjusting for age and membership to government conditional cash transfer program as proxy for socio-economic status. One large significant cluster of under-five malnutrition was found southwest of the province, in which living in these areas at least doubles the risk of malnutrition. Additionally, at least one significant cluster were identified within each municipality—mostly located along the coastal areas. All these indicate apparent geographical variations across and within municipalities in the province. There were also similarities and disparities in the patterns of risk of malnutrition in each cluster across municipalities, and even within municipality, suggesting underlying causes at work that warrants further investigation. Therefore, community-appropriate programs and interventions should be identified and should be focused on high-risk areas to maximize limited government resources. Further studies are also recommended to determine factors affecting variations in childhood malnutrition considering the evidence of spatial clustering found in this study.

Keywords: Binomial model, Kulldorff’s elliptical spatial scan statistic, Philippines, under-five malnutrition

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Authors: Qisheng Hu, Jianglei Han, Yue Yang, My Hoa Ha

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When a company is considering purchasing software for commercial use, contract risk assessment is critical to identify risks to mitigate the potential adverse business impact, e.g., security, financial and regulatory risks. Contract risk assessment requires reviewers with specialized knowledge and time to evaluate the legal documents manually. Specifically, validating contracts for a software vendor requires the following steps: manual screening, interpreting legal documents, and extracting risk-prone segments. To automate the process, we proposed a framework to assist legal contract document risk identification, leveraging pre-trained deep learning models and natural language processing techniques. Given a set of pre-defined risk evaluation problems, our framework utilizes the pre-trained transformer-based models for question-answering to identify risk-prone sections in a contract. Furthermore, the question-answering model encodes the concatenated question-contract text and predicts the start and end position for clause extraction. Due to the limited labelled dataset for training, we leveraged transfer learning by fine-tuning the models with the CUAD dataset to enhance the model. On a dataset comprising 287 contract documents and 2000 labelled samples, our best model achieved an F1 score of 0.687.

Keywords: contract risk assessment, NLP, transfer learning, question answering

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Authors: H. Benmoussa, A. A. El Kalam, A. Ait Ouahman

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The design and implementation of intrusion detection systems (IDS) remain an important area of research in the security of information systems. Despite the importance and reputation of the current intrusion detection systems, their efficiency and effectiveness remain limited as they should include active defense approach to allow anticipating and predicting intrusions before their occurrence. Consequently, they must be readapted. For this purpose we suggest a new generation of distributed intrusion detection system based on preventive detection approach and using intelligent and mobile agents. Our architecture benefits from mobile agent features and addresses some of the issues with centralized and hierarchical models. Also, it presents advantages in terms of increasing scalability and flexibility.

Keywords: Intrusion Detection System (IDS), preventive detection, mobile agents, distributed architecture

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Authors: Linda P. M. Pluymen, Mariska M. G. Leeflang, I. Stegeman, Henock G. Yebyo, Anne E. M. Brabers, Patrick M. Bossuyt, E. Dekker, Anke J. Woudstra, Mirjam P. Fransen

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Weighing the benefits and harms of colorectal cancer screening can be difficult for individuals. An existing online decision aid was expanded with a benefit-harm analysis to help people make an informed decision about participating in colorectal cancer screening. In a randomized controlled trial, we investigated whether those in the intervention group who used the decision aid with benefit-harm analysis were more certain about their decision than those in the control group who used the decision aid without benefit-harm analysis. Participants were 623 (39% of those invited) men and women aged 45 until 75 years old. Analyses were performed in those 386 participants (62%) who reported to have completed the entire decision aid. No statistically significant differences were observed between intervention and control group in decisional conflict score (mean difference 2.4, 95% CI -0.9, 5.6), clarity of values (mean difference 1.0, 95% CI -4.4, 6.6), deliberation score (mean difference 0.5, 95% CI -0.6, 1.7), anxiety score (mean difference 0.0, 95% CI -0.3, 0.3) and risk perception score (mean difference 0.1, -0.1, 0.3). Adding a benefit-harm analysis to an online decision aid did not improve informed decision making about participating in colorectal cancer screening.

Keywords: benefit-harm analysis, decision aid, informed decision making, personalized decision making

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Authors: Chirag Raval, Jimmy Toussaint, Tieuvi Nguyen, Hadi Fadaifard, George Wolberg, Steven Quarfordt, Kung-ming Jan, David S. Rumschitzki

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Numerous studies examine aquaporins’ role in osmotic water transport in various systems but virtually none focus on aquaporins’ role in hydrostatically-driven water transport involving mammalian cells save for our laboratory’s recent study of aortic endothelial cells. Here we investigate aquaporin-1 expression and function in the aortic endothelium in two high-renin rat models of hypertension, the spontaneously hypertensive genomically altered Wystar-Kyoto rat variant and Sprague-Dawley rats made hypertensive by two kidney, one clip Goldblatt surgery. We measured aquaporin-1 expression in aortic endothelial cells from whole rat aortas by quantitative immunohistochemistry, and function by measuring the pressure driven hydraulic conductivities of excised rat aortas with both intact and denuded endothelia on the same vessel. We use them to calculate the effective intimal hydraulic conductivity, which is a combination of endothelial and subendothelial components. We observed well-correlated enhancements in aquaporin-1 expression and function in both hypertensive rat models as well as in aortas from normotensive rats whose expression was upregulated by 2h forskolin treatment. Upregulated aquaporin-1 expression and function may be a response to hypertension that critically determines conduit artery vessel wall viability and long-term susceptibility to atherosclerosis. Numerous studies examine aquaporins’ role in osmotic water transport in various systems but virtually none focus on aquaporins’ role in hydrostatically-driven water transport involving mammalian cells save for our laboratory’s recent study of aortic endothelial cells. Here we investigate aquaporin-1 expression and function in the aortic endothelium in two high-renin rat models of hypertension, the spontaneously hypertensive genomically altered Wystar-Kyoto rat variant and Sprague-Dawley rats made hypertensive by two kidney, one clip Goldblatt surgery. We measured aquaporin-1 expression in aortic endothelial cells from whole rat aortas by quantitative immunohistochemistry, and function by measuring the pressure driven hydraulic conductivities of excised rat aortas with both intact and denuded endothelia on the same vessel. We use them to calculate the effective intimal hydraulic conductivity, which is a combination of endothelial and subendothelial components. We observed well-correlated enhancements in aquaporin-1 expression and function in both hypertensive rat models as well as in aortas from normotensive rats whose expression was upregulated by 2h forskolin treatment. Upregulated aquaporin-1 expression and function may be a response to hypertension that critically determines conduit artery vessel wall viability and long-term susceptibility to atherosclerosis.

Keywords: acute hypertension, aquaporin-1, hydraulic conductivity, hydrostatic pressure, aortic endothelial cells, transcellular flow

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Authors: Oktavian Prasetia Wardana, Martono Tri Utomo, Risa Etika, Kartika Darma Handayani, Dina Angelika, Wurry Ayuningtyas

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Background: Critically ill neonates are newborn babies with high-risk factors that potentially cause disability and/or death. Scoring systems for determining the severity of the disease have been widely developed as well as some designs for use in neonates. The SNAPPE-II method, which has been used as a mortality predictor scoring system in several referral centers, was found to be slow in assessing the outcome of critically ill neonates in the Neonatal Intensive Care Unit (NICU). Objective: To analyze the predictive value of MSNS on the outcome of critically ill neonates at the time of arrival up to 24 hours after being admitted to the NICU. Methods: A longitudinal observational analytic study based on medical record data was conducted from January to August 2022. Each sample was recorded from medical record data, including data on gestational age, mode of delivery, APGAR score at birth, resuscitation measures at birth, duration of resuscitation, post-resuscitation ventilation, physical examination at birth (including vital signs and any congenital abnormalities), the results of routine laboratory examinations, as well as the neonatal outcomes. Results: This study involved 105 critically ill neonates who were admitted to the NICU. The outcome of critically ill neonates was 50 (47.6%) neonates died, and 55 (52.4%) neonates lived. There were more males than females (61% vs. 39%). The mean gestational age of the subjects in this study was 33.8 ± 4.28 weeks, with the mean birth weight of the subjects being 1820.31 ± 33.18 g. The mean MSNS score of neonates with a deadly outcome was lower than that of the lived outcome. ROC curve with a cut point MSNS score <10.5 obtained an AUC of 93.5% (95% CI: 88.3-98.6) with a sensitivity value of 84% (95% CI: 80.5-94.9), specificity 80 % (CI 95%: 88.3-98.6), Positive Predictive Value (PPV) 79.2%, Negative Predictive Value (NPV) 84.6%, Risk Ratio (RR) 5.14 with Hosmer & Lemeshow test results p>0.05. Conclusion: The MSNS score has a good predictive value and good calibration of the outcomes of critically ill neonates admitted to the NICU.

Keywords: critically ill neonate, outcome, MSNS, NICU, predictive value

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Authors: Omair Ghori, Anton Stadler, Stefan Wilk, Wolfgang Effelsberg

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Fire-related incidents account for extensive loss of life and material damage. Quick and reliable detection of occurring fires has high real world implications. Whereas a major research focus lies on the detection of outdoor fires, indoor camera-based fire detection is still an open issue. Cameras in combination with computer vision helps to detect flames and smoke more quickly than conventional fire detectors. In this work, we present a computer vision-based smoke detection algorithm based on contrast changes and a multi-step classification. This work accelerates computer vision-based fire detection considerably in comparison with classical indoor-fire detection.

Keywords: contrast analysis, early fire detection, video smoke detection, video surveillance

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Authors: Jongsung Kim, Daegun Han, Myungjin Lee, Soojun Kim, Hung Soo Kim

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Recently, the frequency and magnitude of natural disasters are gradually increasing due to climate change. Especially in Korea, large-scale damage caused by heavy rainfall frequently occurs due to rapid urbanization. Therefore, this study proposed a Heavy rain Damage Risk Index (HDRI) using PSR (Pressure – State - Response) structure for heavy rain risk assessment. We constructed pressure index, state index, and response index for the risk assessment of each local government in Gyeonggi-do province, and the evaluation indices were determined by principal component analysis. The indices were standardized using the Z-score method then HDRIs were obtained for 31 local governments in the province. The HDRI is categorized into three classes, say, the safest class is 1st class. As the results, the local governments of the 1st class were 15, 2nd class 7, and 3rd class 9. From the study, we were able to identify the risk class due to the heavy rainfall for each local government. It will be useful to develop the heavy rainfall prediction function by risk class, and this was performed in this issue. Also, this risk class could be used for the decision making for efficient disaster management. Acknowledgements: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2017R1A2B3005695).

Keywords: natural disaster, heavy rain risk assessment, HDRI, PSR

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Authors: M. Okeke, A. Blyth

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Industrial Control Systems (ICS) such as Supervisory Control And Data Acquisition (SCADA) can be seen in many different critical infrastructures, from nuclear management to utility, medical equipment, power, waste and engine management on ships and planes. The role SCADA plays in critical infrastructure has resulted in a call to secure them. Many lives depend on it for daily activities and the attack vectors are becoming more sophisticated. Hence, the security of ICS is vital as malfunction of it might result in huge risk. This paper describes how the application of Prey Predator (PP) approach in flocks of birds could enhance the detection of malicious activities on ICS. The PP approach explains how these animals in groups or flocks detect predators by following some simple rules. They are not necessarily very intelligent animals but their approach in solving complex issues such as detection through corporation, coordination and communication worth emulating. This paper will emulate flocking behavior seen in birds in detecting predators. The PP approach will adopt six nearest bird approach in detecting any predator. Their local and global bests are based on the individual detection as well as group detection. The PP algorithm was designed following MapReduce methodology that follows a Split Detection Convergence (SDC) approach.

Keywords: artificial life, industrial control system (ICS), IDS, prey predator (PP), SCADA, SDC

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Authors: Abdullah Almilaibary, Jeremy Jolley, Mark Hayter

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Background: Despite recent progress in enhancing the accessibility of HIV-related health services worldwide, opportunities to diagnose patients are often missed due to genuine barriers at different levels. The aim of the study is to explore the factors that affect the utilization of HIV testing services by young people aged 17-25 in Saudi Arabia. Methods: A non-experimental descriptive cross-sectional design was used to predict factors that influenced HIV testing among Umm- Al Qura University students aged 17-25 years. A newly developed self-completed online questionnaire was used and the study sample was drawn using a convenience sampling technique. The questionnaire consisted of 52 items divided into three scales: 12 items for HIV/AIDS-related knowledge, 3 items for risk perception, and 37 items for attitudes toward HIV testing. Five experts in the field of HIV/AIDS validated the contents of the questionnaire and agreed that the items included were related to the construct being measured. The reliability of the questionnaire was also assessed using a test/re-test strategy with 27 participants recruited from the population under study. The reliability assessment revealed that the questionnaire was consistent as Cronbach’s Alpha was 0.80 for HIV/ADS knowledge, 0.88 for risk perception and 0.78 for attitudes towards HIV testing. The data were collected between 14th of July and 14th of October 2014. Results: 394 participants completed the questionnaires: 116 (29.4%) male and 278 (70%) female. 50.5% of the participants were aged 20 to 22 years, 34.8% were 17-19 years and 14.7% were aged between 23-25 years; about 93% of the participants were single. Only 20 (6%) participants had previously been tested for HIV. The main reasons for not being tested for HIV were: exposure to HIV was considered unlikely (48%), HIV test was not offered (36%) and unawareness of HIV testing centres (16%). On HIV/AIDS-related knowledge, the male participants scored higher than the females as the mean score for males was (M = 6.4, SD = 2.4) while for females it was (M 5.7, SD 2.5). In terms of risk perception, female participants appeared to have lower levels of risk perception than male participants, with the mean score for males being (M 11.7, SD 2.5) and (M 10.5, SD 2.4) for females. The female participants showed slightly more positive attitudes towards HIV testing than male participants: the mean score for males was (M = 108.14, SD = 17.9) and was (M = 111.32, SD = 17.3) for females. Conclusions: The data reveal that misconceptions about HIV/AIDS in Saudi Arabia are still a challenge. Although the attitudes towards HIV testing were reasonably positive, the utilization of the HIV test was low. Thus, tailoring HIV/AIDS preventive strategies in Saudi Arabia should focus on the needs of young people and other high risk groups in the country.

Keywords: attitude toward hiv testing, hiv testing, hiv/aids related knowledge, risk perception

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Authors: S. Cowley, M. Lawrance, D. Bick, R. McCord

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Technology that automates manual handling (musculoskeletal disorder or MSD) risk assessments is increasingly available to ergonomists, engineers, generalist health and safety practitioners alike. The risk assessment process is generally based on the use of wearable motion sensors that capture information about worker movements for real-time or for posthoc analysis. Traditionally, MSD risk assessment is undertaken with the assistance of a checklist such as that from the SafeWork Australia code of practice, the expert assessor observing the task and ideally engaging with the worker in a discussion about the detail. Automation enables the non-expert to complete assessments and does not always require the assessor to be there. This clearly has cost and time benefits for the practitioner but is it an improvement on the assessment by the human. Human risk assessments draw on the knowledge and expertise of the assessor but, like all risk assessments, are highly subjective. The complexity of the checklists and models used in the process can be off-putting and sometimes will lead to the assessment becoming the focus and the end rather than a means to an end; the focus on risk control is lost. Automated risk assessment handles the complexity of the assessment for the assessor and delivers a simple risk score that enables decision-making regarding risk control. Being machine-based, they are objective and will deliver the same each time they assess an identical task. However, the WHS professional needs to know that this emergent technology asks the right questions and delivers the right answers. Whether it improves the risk assessment process and results or simply distances the professional from the task and the worker. They need clarity as to whether automation of manual task risk analysis and reporting leads to risk control or to a focus on the worker. Critically, they need evidence as to whether automation in this area of hazard management leads to better risk control or just a bigger collection of assessments. Practitioner experienced determinants of this automated manual task risk analysis and reporting being a benefit or distraction will address an understanding of emergent risk assessment technology, its use and things to consider when making decisions about adopting and applying these technologies.

Keywords: automated, manual-handling, risk-assessment, machine-based

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Authors: Devineni Vijay Bhaskar, Yendluri Raja

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We recommend a model for traffic sign detection stranded on Convolutional Neural Networks (CNN). We first renovate the unique image into the gray scale image through with support vector machines, then use convolutional neural networks with fixed and learnable layers for revealing and understanding. The permanent layer can reduction the amount of attention areas to notice and crop the limits very close to the boundaries of traffic signs. The learnable coverings can rise the accuracy of detection significantly. Besides, we use bootstrap procedures to progress the accuracy and avoid overfitting problem. In the German Traffic Sign Detection Benchmark, we obtained modest results, with an area under the precision-recall curve (AUC) of 99.49% in the group “Risk”, and an AUC of 96.62% in the group “Obligatory”.

Keywords: convolutional neural network, support vector machine, detection, traffic signs, bootstrap procedures, precision-recall curve

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Authors: Naridchaya Aberdour, Joanna Kao, Anne Miller, Timothy Shore, Richard Maher, Zhixin Liu

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Background: COVID-19 has and continues to be a strain on healthcare globally, with the number of patients requiring hospitalization exceeding the level of medical support available in many countries. As chest x-rays are the primary respiratory radiological investigation, the Radiological Assessment of Lung Edema (RALE) score was used to quantify the extent of pulmonary infection on baseline imaging. Assessment of RALE score's reproducibility and associations with clinical outcome parameters were then evaluated to determine implications for patient management and prognosis. Methods: A retrospective study was performed with the inclusion of patients testing positive for COVID-19 on nasopharyngeal swab within a single Local Health District in Sydney, Australia and baseline x-ray imaging acquired between January to June 2020. Two independent Radiologists viewed the studies and calculated the RALE scores. Clinical outcome parameters were collected and statistical analysis was performed to assess RALE score reproducibility and possible associations with clinical outcomes. Results: A total of 78 patients met inclusion criteria with the age range of 4 to 91 years old. RALE score concordance between the two independent Radiologists was excellent (interclass correlation coefficient = 0.93, 95% CI = 0.88-0.95, p<0.005). Binomial logistics regression identified a positive correlation with hospital admission (1.87 OR, 95% CI= 1.3-2.6, p<0.005), oxygen requirement (1.48 OR, 95% CI= 1.2-1.8, p<0.005) and invasive ventilation (1.2 OR, 95% CI= 1.0-1.3, p<0.005) for each 1-point increase in RALE score. For each one year increased in age, there was a negative correlation with recovery (0.05 OR, 95% CI= 0.92-1.0, p<0.01). RALE scores above three were positively associated with hospitalization (Youden Index 0.61, sensitivity 0.73, specificity 0.89) and above six were positively associated with ICU admission (Youden Index 0.67, sensitivity 0.91, specificity 0.78). Conclusion: The RALE score can be used as a surrogate to quantify the extent of COVID-19 infection and has an excellent inter-observer agreement. The RALE score could be used to prognosticate and identify patients at high risk of deterioration. Threshold values may also be applied to predict the likelihood of hospital and ICU admission.

Keywords: chest radiography, coronavirus, COVID-19, RALE score

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Authors: Rashid Mahmood

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The network as a service (NaaS) usage has been well-known from the last few years in the many applications, like mission critical applications. In the NaaS, prevention method is not adequate as the security concerned, so the detection method should be added to the security issues in NaaS. The authentication and encryption are considered the first solution of the NaaS problem whereas now these are not sufficient as NaaS use is increasing. In this paper, we are going to present the concept of intrusion detection and then survey some of major intrusion detection techniques in NaaS and aim to compare in some important fields.

Keywords: IDS, cloud, naas, detection

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Authors: L. Sun, O. Bloom, K. Anderson

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The medial and lateral sural artery perforator flaps (MSAP and LSAP, respectively) are two recently described flaps that are less commonly used in lower limb trauma reconstructive surgeries compared to flaps such as the anterolateral thigh (ALT) flap or the gastrocnemius flap. The LSAP flap has several theoretical benefits over the MSAP, including the ability to be sensate and being more easily manoeuvred into position as a local flap for coverage of lateral knee or leg defects. It is less commonly used in part due to a lack of documented studies of the anatomical reliability of the perforator, and an unquantified average length of the pedicle used for microsurgical anastomosis (if used as a free flap) or flap rotation (if used as a pedicled flap). It has been shown to have significantly lower donor site morbidity compared to other flaps such as the ALT, due to the decreased need for intramuscular dissection and resulting in less muscle loss at the donor site. 11 cadaveric lower limbs were dissected, with a mean of 1.6 perforators per leg, with an average pedicle length of 45mm to the sural artery and 70mm to the popliteal artery. While the majority of perforating arteries lay close to the midline (average of 19mm lateral to the midline), there were patients whose artery was significantly lateral and would have been likely injured by the initial incision during an operation. Adding to the literature base of documented LSAP dissections provides a greater understanding of the anatomical basis of these perforator flaps, and the authors hope this will establish them as a more commonly used and discussed option when managing complicated lower limb trauma requiring soft tissue reconstruction.

Keywords: cadaveric, dissection, lateral, perforator flap, sural artery, surface anatomy

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Authors: Zhang Shuqi, Liu Dan

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For the problems in intelligent network anomaly traffic detection models, such as low detection accuracy caused by the lack of training samples, poor effect with small sample attack detection, a classification model enhancement method, F-ACGAN(Flow Auxiliary Classifier Generative Adversarial Network) which introduces generative adversarial network and adversarial training, is proposed to solve these problems. Generating adversarial data with category labels could enhance the training effect and improve classification accuracy and model robustness. FACGAN consists of three steps: feature preprocess, which includes data type conversion, dimensionality reduction and normalization, etc.; A generative adversarial network model with feature learning ability is designed, and the sample generation effect of the model is improved through adversarial iterations between generator and discriminator. The adversarial disturbance factor of the gradient direction of the classification model is added to improve the diversity and antagonism of generated data and to promote the model to learn from adversarial classification features. The experiment of constructing a classification model with the UNSW-NB15 dataset shows that with the enhancement of FACGAN on the basic model, the classification accuracy has improved by 8.09%, and the score of F1 has improved by 6.94%.

Keywords: data imbalance, GAN, ACGAN, anomaly detection, adversarial training, data augmentation

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Authors: Sophie Mills, Constantinos Aristotelous, Leila L. Touil, Richard C. W. James

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Objectives: Historical studies of the anatomy of the spinal accessory nerve (SAN) have reported conflicting results regarding its relationship with the internal jugular vein (IJV). A literature review was undertaken to establish the prevalence of anatomical variations of the SAN encountered during routine neck dissection surgery in order to increase awareness and reduce morbidity associated with iatrogenic SAN injury. Materials and Methods: The largest systematic review to date was performed using PRISMA-ScR guidelines, which yielded nine articles following the application of inclusion and exclusion criteria. A case report is also included, which demonstrates the rare anatomical relationship of the SAN traversing a fenestrated IJV, seen for the first time in the senior author’s career. Results: The mean number of dissections per study was 119, of which 55.6% (n=5) studies were performed on cadaver subjects, and 44.4% (n=4) were surgical dissections. Incidences of the SAN lateral to the IJV and medial to the IJV ranged from 38.9%-95.7% and 2.8%-57.4%, respectively. Over half of the studies reported incidences of the SAN traversing the IJV in 0.9%-2.8% of dissections. One study reported an isolated variant of the SAN dividing around the IJV with a prevalence of 0.5%. Conclusion: At the level of the posterior belly of the digastric muscle, the surgeon can anticipate the identification of the SAN lateral to the IJV in approximately three-quarters of cases, whilst around one-quarter are estimated to be medial. A mean of 1.6% of SANs traverses a fenestration of the vein. It is essential for surgeons to be aware of these anatomical variations and their prevalence to prevent injury to vital structures during surgery.

Keywords: anatomical variant, internal jugular vein, neck dissection, spinal accessory nerve

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Authors: K. Sekulová, M. Šimon

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The article demonstrates on a case study how it is possible to identify MSD risk. It is based on a dissertation risk identification model of occupational diseases formation in relation to the work activity that determines what risk can endanger workers who are exposed to the specific risk factors. It is evaluated based on statistical calculations. These risk factors are main cause of upper-extremities musculoskeletal disorders.

Keywords: case study, upper-extremity musculoskeletal disorders, ergonomics, risk identification

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Authors: Ogbuagu Josephat Okechukwu, Okeke Abuchi Princewill, Arinze Rosemary Uche, Tabugbo Ifeyinwa Blessing, Ogbuagu Adaora Stellamaris

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Phthalates or Phthalate esters (PAEs), categorized as an endocrine disruptor and persistent organic pollutants, are known for their environmental contamination and toxicological effects. In this study, the concentration of selected phthalates was determined across the sampling site to investigate their occurrence and the ecological and health risk assessment they pose to the environment. Water and sediment samples were collected following standard procedures. Solid phase and ultrasonic methods were used to extract seven different PAEs, which were analyzed by Gas Chromatography with Mass Detector (GCMS). The analytical average recovery was found to be within the range of s83.4% ± 2.3%. The results showed that PAEs were detected in six out of seven samples with a high percentage of detection rate in water. Di-n-butyl phthalate (DPB) and diisobutyl phthalates (DiBP) showed greater detection rate compared to other PAEs monomers. The concentration of PEs was found to be higher in the sediment samples compared to the water samples due to the fact that sediments serve as a sink for most persistent organic pollutants. The concentrations of PAEs in water samples and sediments ranged from 0.03 ± 0.01 to 0.29 ± 0.002 ppm and 3.99 ± 0.43 to 6.04 ± 1.25 ppm, respectively. Ecological risk assessment using the risk quotient method (RQ) reveals that the estimated environmental risk caused by phthalates lies within the moderate level as RQ ranges from 0.1 to 1.0, whereas the health risk assessment caused by phthalates on estimating the average daily dose reveals that the ingestion of phthalates was found to be high which can cause serious carcinogenic occurrence in the human system with time due to excess accumulation.

Keywords: phthaletes, assessment, marine pollution, endocrine

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Authors: Yousef Farhaoui

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An IDS is a tool which is used to improve the level of security. We present in this paper different architectures of IDS. We will also discuss measures that define the effectiveness of IDS and the very recent works of standardization and homogenization of IDS. At the end, we propose a new model of IDS called BiIDS (IDS Based on the two principles of detection) for securing web servers and applications by the Intrusion Detection System (IDS).

Keywords: intrusion detection, architectures, characteristic, tools, security, web server

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Authors: Mahalakshmi Vivekanandan S.

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As per the recent changes happening in the global policies, climate-related changes and the impact it causes across every sector are viewed as green swan events – in essence, climate-related changes can often happen and lead to risk and a lot of uncertainty, but needs to be mitigated instead of considering them as black swan events. This brings about a question on how this risk can be computed so that the financial institutions can plan to mitigate it. Climate-related changes impact all risk types – credit risk, market risk, operational risk, liquidity risk, reputational risk and other risk types. And the models required to compute this has to consider the different industrial needs of the counterparty, as well as the factors that are contributing to this – be it in the form of different risk drivers, or the different transmission channels or the different approaches and the granular form of data availability. This brings out the suggestion that the climate-related changes, though it affects Pillar I risks, will be a Pillar II risk. This has to be modeled specifically based on the financial institution’s actual exposure to different industries instead of generalizing the risk charge. And this will have to be considered as the additional capital to be met by the financial institution in addition to their Pillar I risks, as well as the existing Pillar II risks. In this paper, the author presents a risk assessment framework to model and assess climate change risks - for both credit and market risks. This framework helps in assessing the different scenarios and how the different transition risks affect the risk associated with the different parties. This research paper delves into the topic of the increase in the concentration of greenhouse gases that in turn cause global warming. It then considers the various scenarios of having the different risk drivers impacting the Credit and market risk of an institution by understanding the transmission channels and also considering the transition risk. The paper then focuses on the industry that’s fast seeing a disruption: the automobile industry. The paper uses the framework to show how the climate changes and the change to the relevant policies have impacted the entire financial institution. Appropriate statistical models for forecasting, anomaly detection and scenario modeling are built to demonstrate how the framework can be used by the relevant agencies to understand their financial risks. The paper also focuses on the climate risk calculation for the Pillar II Capital calculations and how it will make sense for the bank to maintain this in addition to their regular Pillar I and Pillar II capital.

Keywords: capital calculation, climate risk, credit risk, pillar ii risk, scenario modeling

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Authors: Forough Ataollahi, Sumit Pramanik, Belinda Pingguan-Murphy, Wan Abu Bakar Bin Wan Abas, Noor Azuan Bin Abu Osman

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Endothelium proliferation is an important process in cardiovascular homeostasis and can be regulated by extracellular environment, as cells can actively sense mechanical environment. In this study, we evaluated endothelial cell proliferation on PDMS/alumina (Al2O3) composites and pure PDMS. The substrates were prepared from pure PDMS and its composites with 5% and 10% Al2O3 at curing temperature 50˚C for 4 h and then characterized by mechanical, structural and morphological analyses. Higher stiffness was found in the composites compared to the pure PDMS substrate. Cell proliferation of the cultured bovine aortic endothelial cells on substrate materials were evaluated via Resazurin assay and 1, 1’-Dioctadecyl-1, 3, 3, 3’, 3’-Tetramethylindocarbocyanine Perchlorate-Acetylated LDL (Dil-Ac-LDL) cell staining, respectively. The results revealed that stiffer substrates promote more endothelial cells proliferation to the less stiff substrates. Therefore, this study firmly hypothesizes that the stiffness elevates endothelial cells proliferation.

Keywords: stiffness, proliferation, bovine aortic endothelial cells, extra cellular matrix, vascular

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Authors: Maryam Nabati, Mahmood Moosazadeh, Ehsan Soroosh, Hanieh Shiraj, Mahnaneh Gholami, Ali Ghaemian

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Background: Reported effects of obesity on the extent of angiographic coronary artery disease(CAD) have beeninconsistent. The present study aimed to investigate the relationships between the indices of obesity and otheranthropometric markers with the extent of CAD. Methods: This study was conducted on 1008 consecutive patients who underwent coronary angiography. Bodymass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) wereseparately calculated for each patient. Extent, severity, and complexity of CAD were determined by the Gensini andSYNTAX scores. Results: According to the results, there was a significant inverse correlation between the SYNTAX score with BMI(r = − 0.110; P < 0.001), WC (r = − 0.074; P = 0.018), and WHtR (r = − 0.089; P = 0.005). Furthermore, a significant inversecorrelation was observed between the Gensini score with BMI (r = − 0.090; P = 0.004) and WHtR (r = − 0.065; P =0.041). However, the results of multivariate linear regression analysis did not show any association between theSYNTAX and Gensini scores with the indices of obesity and overweight. On the other hand, the patients with anunhealthy WC had a higher prevalence of diabetes mellitus (DM) (P = 0.004) and hypertension (HTN) (P < 0.001) compared to the patients with healthy values. Coexistence of HTN and DM was more prevalent in subjects with anunhealthy WC and WHR compared to that in those with healthy values (P = 0.002 and P = 0.032, respectively). Conclusion: It seems that the anthropometric indices of obesity are not the predictors of the angiographic severityof CAD. However, they are associated with an increased risk of cardiovascular risk factors and higher risk profile.

Keywords: body mass index, BMI, coronary artery disease, waist circumference

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Authors: Azita Ramezani, Atousa Ramezani

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In the ever-escalating landscape of windows malware the necessity for pioneering defense strategies turns into undeniable this study introduces an avant-garde approach fusing the capabilities of clustering random forests and support vector machines SVM to combat the intricate web of cyber threats our fusion model triumphs with a staggering accuracy of 98.67 and an equally formidable f1 score of 98.68 a testament to its effectiveness in the realm of windows malware defense by deciphering the intricate patterns within malicious code our model not only raises the bar for detection precision but also redefines the paradigm of cybersecurity preparedness this breakthrough underscores the potential embedded in the fusion of diverse analytical methodologies and signals a paradigm shift in fortifying against the relentless evolution of windows malicious threats as we traverse through the dynamic cybersecurity terrain this research serves as a beacon illuminating the path toward a resilient future where innovative fusion models stand at the forefront of cyber threat defense.

Keywords: fusion models, cyber threat defense, windows malware, clustering, random forests, support vector machines (SVM), accuracy, f1-score, cybersecurity, malicious code detection

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Authors: Ali Kazemi

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The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

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Authors: Rami S. Alasmari, Abdullah Al Zahrani, Hattan A. Hassani, Hattan A. Hassani, Nawwaf A. Almalky, Abdullah F. Bokhari, Alwalied A. Hafez

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Diabetes mellitus type 2 (DMT2) is a major chronic condition that is considered common among elderly people, with multiple potential complications that could contribute to falls. However, this concept is not well understood, thus, the aim of this study is to determine whether diabetes is an independent risk factor for falls in elderly. In this observational cross-sectional study, 309 diabetic patients aged 60 or more who visited the primary healthcare centers of the Ministry of National Guard Health Affairs in Jeddah were chosen via convenience sampling method. To collect the data, Semi-structured Fall Risk Assessment questionnaire and Fall Efficacy Score scale were used. The mean age of the participants was estimated to be 68.5 (SD:7.4) years. Among the participants, 48.2% experienced falling before, and 63.1% of them suffered falls in the past 12-months. The results showed that gait problems were independently associated with a higher likelihood of fall among the elderly patients (OR = 1.98, 95%CI, 1.08 to 3.62, p = 0.026. This paper suggests that diabetes mellitus is an independent fall risk factor among elderly. Therefore, identifying such patients as being at higher risk and prompt referral to a specialist falls clinic is recommended.

Keywords: diabetes, fall, elderly, risk factors

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Authors: Yuchao Yao

Abstract:

As two of the main characteristics of Chinese demographic trends, increasing divorce rates and decreasing fertility rates both shaped the population structure in the recent decade. Figuring out to what extent can be having a child make a difference in the divorce rate of a couple will not only draw a picture of Chinese families but also bring about a new perspective to evaluate the Chinese child-breeding policies. Based on China Family Panel Studies (CFPS) Data 2010-2018, this paper provides a systematic evaluation of how children influence a couple’s marital stability through a series of empirical models. Using survival analysis and propensity score matching (PSM) model, this paper finds that the number and age of children that a couple has mattered in consolidating marital relationship, and these effects vary little over time; during the last decade, newly having children can in fact decrease the possibility of divorce for Chinese couples; the such decreasing effect is largely due to the birth of a second child. As this is an inclusive attempt to study and compare not only the effects but also the causality of children on divorce risk in the last decade, the results of this research will do a good summary of the status quo of divorce in China. Furthermore, this paper provides implications for further reforming the current marriage and child-breeding policies.

Keywords: divorce risk, fertility, China, survival analysis, propensity score matching

Procedia PDF Downloads 55