Search Results (1,880)

The construction sector is known for exposing workers to numerous potential hazards, with falls from heights being the leading cause. These fatal fall accidents not only result in human loss but also impose significant financial costs on construction projects. However, current safety planning and management is typically carried out manually using safety documents and 2D models, which are time-consuming and labor-intensive. There is also a lack of visualization for the placement of temporary safety facilities (TSFs) during construction. Meanwhile, Building Information Modeling (BIM) has the potential to be used as a comprehensive workspace planning for TSFs in a scheduling manner. Therefore, this study proposes the development of a construction safety dashboard to inform workers about fall hazards using spatial–temporal data stored in 4D BIM. The proposed approach includes four modules: (1) identification and assessment of risk from identified work activities, (2) development of 4D BIM model, (3) creation of a dashboard to share safety knowledge, and (4) validation of the dashboard through interviews with safety managers and site workers. This approach is tested on a stadium project, particularly focusing on roof work activities, where workers are most prone to fall hazards. The proposed method aims to provide ease for site workers to access safety knowledge, including risk identification (including risk, fatality, location, and time), visualization of TSFs, personal protective equipment, and safety work instructions. This interactive dashboard also enables safety managers to plan safety measures, allocate TSFs efficiently, and make well-informed decisions to effectively mitigate risks. Full article

In this study, we aimed to assess and compare the prevalence of septate uterus using the diagnostic criteria of the ESHRE-ESGE, ASRM 2016, ASRM 2021, and CUME classifications. This prospective observational study included 977 women of reproductive age. Each participant underwent a transvaginal ultrasound, and a 3D volume of the uterus was obtained for further analysis. Offline assessment of the uterine coronal plane was conducted to measure uterine wall thickness, fundal indentation length, and indentation angle. The diagnosis of a septate uterus was determined according to the criteria of the ESHRE-ESGE, ASRM, and CUME classifications. The prevalence of septate uterus was then calculated and compared across these classifications. The ESHRE-ESGE classification identified 132 women (13.5%) with a septate uterus. The 2016 ASRM classification identified nine women (0.9%), with an additional nine women falling into a grey zone. The 2021 ASRM classification identified fourteen women (1.4%), with eleven women in the grey zone. The CUME classification identified 23 women (2.4%). The prevalence of septate uterus was significantly higher when using the ESHRE-ESGE criteria compared to the 2016 ASRM [relative risk (RR): 7.33 (95% CI: 4.52–11.90)], the 2021 ASRM [RR: 5.28 (95% CI: 3.47–8.02)], and the CUME [RR: 5.94 (95% CI: 3.72–8.86)] (p < 0.001). Our findings indicate that the ESHRE-ESGE criteria result in a significantly higher prevalence of septate uterus compared to the ASRM and CUME criteria. The ASRM 2016 criteria may underdiagnose more than half of the cases. Full article

The construction industry has the highest number of fatal accidents compared to other industries. However, manual safety compliance monitoring is complex and difficult for safety engineers, and more automated solutions need to be found. The main research objective was to review the state of the art of real-time monitoring technologies used to assess the risk of falling from height in the construction sector. A systematic review is proposed in order to summarise the technologies used for real-time monitoring in the construction sector, following the PRISMA methodology. Only studies that assessed the risk of falling in real time were selected. From an initial set of 1289 articles, 40 were classified as strictly relevant to addressing the research questions. Various technologies that use artificial intelligence have been designed to monitor workers in real time and to send alerts to workers at any time in the event of a risk situation, thus preventing accidents. This study showed that new technologies are being introduced to predict the risk of a fall in real time, changing the approach from reactive to proactive and allowing this monitoring to improve workplace surveillance and safety. Further research is needed to develop effective systems that are easy for people to use without compromising productivity. Full article

The aim of this study was to improve the diagnostic ability of fall risk classifiers using a Bayesian approach and the Simulated Annealing (SA) algorithm. A total of 47 features from 181 records (40 Center of Pressure (CoP) indices and 7 patient descriptive variables) were analyzed. The wrapper method of feature selection using the SA algorithm was applied to optimize the cost function based on the difference of the mean minus the standard deviation of the Area Under the Curve (AUC) of the fall risk classifiers across multiple dimensions. A stratified 60–20–20% hold-out method was used for train, test, and validation sets, respectively. The results showed that although the highest performance was observed with 31 features (0.815 ± 0.110), lower variability and higher explainability were achieved with only 15 features (0.780 ± 0.055). These findings suggest that the SA algorithm is a valuable tool for feature selection for acceptable fall risk diagnosis. This method offers an alternative or complementary resource in situations where clinical tools are difficult to apply. Full article

Due to poor road design, challenging terrain, and difficult geological conditions, traffic accidents on mountainous two-lane roads are more frequent and severe. This study aims to address the lack of understanding of key factors affecting accident severity with the goal of improving mountainous traffic safety, thereby contributing to sustainable transportation systems. The focus of this study is to compare the interpretability of model performances with three statistical models (Ordered Logit, Partial Proportional Odds Model, and Multinomial Logit) and six machine learning models (Decision Tree, Random Forest, Gradient Boosting, Extra Trees, AdaBoost, and XGBoost) on two-lane mountain roads in Yunnan Province, China. Additionally, we assessed the ability of these models to uncover underlying causal relationships, particularly how accident causes affect severity. Using the SHapley Additive exPlanations (SHAP) method, we interpreted the influence of risk factors in the machine learning models. Our findings indicate that machine learning models, especially XGBoost, outperform statistical models in predicting accident severity. The results highlight that accident patterns are the most significant determinants of severity, followed by road-related factors and the type of colliding vehicles. Environmental factors like weather, however, have minimal impact. Notably, vehicle falling, head-on collisions, and longitudinal slope sections are linked to more severe accidents, while minor accidents are more frequent on horizontal curve sections and areas that combine curves and slopes. These insights can help traffic management agencies develop targeted measures to reduce accident rates and enhance road safety, which is critical for promoting sustainable transportation in mountainous regions. Full article

Heavy metals in road dusts can directly pose significant health risks through ingestion, inhalation, and dermal contact. This study investigated the pollution, distribution, and health effect of heavy metals in street dust from industrial, capital city, and peri-urban areas of Bangladesh. Inductively coupled plasma mass spectrometry (ICP-MS) examined eight hazardous heavy metals such as Zn, Cu, Pb, Ni, Mn, Cr, Cd, and Co. Results revealed that industrial areas showed the highest metal concentrations, following the order Mn > Zn > Cr > Pb > Ni > Co > Cd, with an average level of 444.35, 299.25, 238.31, 54.22, 52.78, 45.66, and 2.73 mg/kg, respectively, for fine particles (≤20 μm). Conversely, multivariate statistical analyses were conducted to assess pollution levels and sources. Anthropogenic activities like traffic emissions, construction, and industrial processing were the main pollution sources. A pollution load index revealed that industrial areas had significantly higher pollution (PLI of 2.45), while the capital city and peri-urban areas experienced moderate pollution (PLI of 1.54 and 1.59). Hazard index values were below the safety level of 1, but health risk evaluations revealed increased non-carcinogenic risks for children, especially from Cr, Ni, Cd, and Pb where Cr poses the highest cancer risk via inhalation, with values reaching 1.13 × 10⁻⁴–5.96 × 10⁻⁴ falling within the threshold level (10⁻⁴ to 10⁻⁶). These results underline the need for continuous environmental monitoring and pollution control in order to lower health hazards. Full article

Performing dual-task (DT) activities is essential for independent living among elderly people. No study has investigated motor performance in various cognitive-motor DT activities, utilizing the Timed Up and Go (TUG) test. This study aimed to compare motor performance between four cognitive-motor DT tests in community-dwelling older adults. The sample consisted of 60 older women. The cognitive tasks performed with the TUG test were (a) mental calculation, (b) memory recall, (c) verbal fluency, and (d) reaction to a stimulus. Lower limb muscle strength was assessed with the 30-Second Chair Stand Test, balance with the Four Square Step Test, and balance confidence with the Activities-specific Balance Confidence Scale. Completion times and DT costs were calculated. Mental calculation (r = 0.63, p < 0.01) and verbal fluency (r = 0.65, p < 0.01) tasks were similarly correlated with the TUG test, and significantly impacted motor performance compared to other DT tests. The reaction to a stimulus test showed a high relationship with the TUG test (r = 0.89, p < 0.01) and had the least impact on motor performance. These findings suggest that the cognitive task type can significantly influence motor performance during DT activities. Adding a cognitive load to the TUG test may improve its ability to identify older adults at risk for falls, aiding in the development of targeted interventions. Further research is required to validate these findings. Full article

The situation/risk of family homelessness presents multiple interrelated issues. It has considerable negative consequences, namely the deterioration of the family members’ health and well-being, and alterations in the family’s dynamics, with parents sometimes being separated from their children. The aim of this research was to understand how parenting takes place in families experiencing, or at risk of, homelessness. The conducted study falls within the qualitative paradigm, using Strauss and Corbin’s version of the Grounded Theory methodology. Three main categories emerged, supported by all the participating families: “Meaning of Parenthood”, “Key Events”, and “Transition Circumstances”. These categories were translated into facilitating/inhibiting factors, within the following dimensions: “Individual”, “Family”, and “Society”. We were able to conclude that, in the population under study, parenting is restricted, being mostly exerted in a remote manner. Furthermore, it takes on different forms, depending on the specific homelessness situation/risk. In families at risk of homelessness, we identified “Remote Parenting with Maintained Parental Authority”, as well as “Restricted Parenting”, when the children still lived with their parents. On the other hand, in families experiencing homelessness, we identified “Remote Parenting with Maintained Parental Authority”, “Unilateral Remote Parenting”, “Interrupted Parenting”, and the “Total Disruption of Parenting”. Full article

Using daily returns of Bitcoin, Litecoin, Ripple and Stellar, we introduce a novel risk measure for quantitative-risk management in the cryptomarket that accounts for the significant co-movements between cryptocurrencies. We find that our model has a lower error margin when forecasting the extent of future losses than traditional risk measures, such as Value-at-Risk and Expected Shortfall. Most notably, we observe this in Litecoin’s results, where Expected Shortfall, on average, overestimates the potential fall in the price of Litecoin by 8.61% and underestimates it by 3.92% more than our model. This research shows that traditional risk measures, while not necessarily inappropriate, are imperfect and incomplete representations of risk when it comes to the cryptomarket. Our model provides a suitable alternative for risk managers, who prioritize lower error margins over failure rates, and highlights the value in exploring how risk measures that incorporate the unique characteristics of cryptocurrencies can be used to supplement and complement traditional risk measures. Full article

Structural Maintenance of Chromosomes (SMC) complexes are an evolutionary conserved protein family. In most eukaryotes, three SMC complexes have been characterized, as follows: cohesin, condensin, and SMC5/6 complexes. These complexes are involved in a plethora of functions, and defects in SMC genes can lead to an increased risk of chromosomal abnormalities, infertility, and cancer. To investigate the evolution of SMC complex genes in mammals, we analyzed their selective patterns in an extended phylogeny. Signals of positive selection were identified for condensin NCAPG, for two SMC5/6 complex genes (SMC5 and NSMCE4A), and for all cohesin genes with almost exclusive meiotic expression (RAD21L1, REC8, SMC1B, and STAG3). For the latter, evolutionary rates correlate with expression during female meiosis, and most positively selected sites fall in intrinsically disordered regions (IDRs). Our results support growing evidence that IDRs are fast evolving, and that they most likely contribute to adaptation through modulation of phase separation. We suggest that the natural selection signals identified in SMC complexes may be the result of different selective pressures: a host-pathogen arms race in the condensin and SMC5/6 complexes, and an intragenomic conflict for meiotic cohesin genes that is similar to that described for centromeres and telomeres. Full article

Fifty-one street dust samples were systematically collected from the urban core of Zhengzhou, China, and analyzed for potentially toxic metals. The concentrations of vanadium (V), manganese (Mn), copper (Cu), zinc (Zn), arsenic (As), lead (Pb), and nickel (Ni) in the samples surpassed the background values of the local soil, indicating a notable potential for contamination. Spatially, the traffic area was the most polluted with a total heavy metal concentration of Cu, Zn, As, Pb, and Ni, while the pollution levels were lower in the culture and education area and commercial area with total concentrations of V and Mn. Seasonal variations were discerned in the concentrations of heavy metals, with V, Cu, Zn, and As exhibiting heightened levels during the fall and winter, while Mn, Ni, and Pb reached peaks in the spring season. Zn exhibited the highest mean geo-accumulation index (I_geo) value at 2.247, followed by Cu at 2.019, Pb at 0.961, As at 0.590, Ni at 0.126, Mn at −0.178, and V at −0.359. The potential ecological risk index (RI) in the traffic-intensive area markedly exceeded other functional areas. Health risk assessments showed that children were more vulnerable to heavy metal exposure than adults, particularly through the ingestion pathway. Correlation analysis, principal component analysis (PCA), and cluster analysis (CA) were applied in conjunction with the spatial–temporal concentration patterns across various functional areas to ascertain the plausible sources of heavy metal pollutants. The results indicated that heavy metals in the urban street dust of Zhengzhou were multifaceted, stemming from natural processes and diverse anthropogenic activities such as coal burning, industrial emissions, traffic, and construction operations. Full article

An increasing number of people are relocating to search for work, leading to substantial implications for both local and global health. Approximately 3.6% of the global population (281 million) migrates annually. Nepal has experienced a notable surge in labour migration in recent years, with a substantial proportion of its residents actively seeking work opportunities abroad. Understanding work-related risks is crucial for informing policies, interventions, and practices that can improve the welfare of this hard-to-reach population. This scoping review aims to systematically identify and analyse occupational health hazards encountered by Nepali migrant workers employed overseas. Medline, Scopus, Directory of Open Access Journals (DOAJ), and the NepJOL databases were systematically searched for primary research papers published in English up to July 2024. Relevant data, including workplace hazards and their impact on health outcomes, were extracted and narratively synthesised by highlighting key themes in the existing literature. A total of 24 articles met the inclusion criteria and were included in this review. Of these, twelve studies were conducted in Nepal, five in Gulf countries, four in Malaysia, two in Hong Kong, and one each in India and Korea. Workplace injuries (motor vehicle injuries, machinery injuries, falls from a height, and falls on a heavy object), poor working environment (including long working hours, work without leave, discrepancy in pay scale, limited access to drinking water and toilet/bathroom facilities), workplace abuse, sexual abuse, and torture were identified as key occupational health hazards faced by the Nepali migrant workers abroad. Multi-level intervention strategies, such as safety training standards, improving working conditions, and eliminating exploitative labour practices, are critical to improving occupational health and safety standards for Nepali migrant workers abroad. This includes creating a supportive working environment where employees can easily and timely access health services as needed. Full article

Background: Our study aimed to investigate the effects of vestibular rehabilitation therapy on functional gait performance in patients with balance disorders. Methods: A total of 40 post-operative patients with balance disorders were included in the study. They were divided into two groups and participated in a vestibular rehabilitation program during their hospital stay. After discharge, the intervention group performed vestibular exercises at home, while the control group did not. Balance was assessed using the Functional Gait Assessment Scale at discharge and three months after surgery. Results: The intervention group included 15 women and 5 men with an average age of 45 years, while the control group included 7 women and 13 men with an average age of 50 years. Three months after surgery, the change in Functional Gait Assessment (FGA) scores exceeded the clinically significant threshold of 5 points in 17 patients in the intervention group and 14 in the control group. There was a statistically significant difference in FGA progression between the groups (p = 0.034). After three months post-surgery, 7 patients in the intervention group experienced falls compared to 12 in the control group. Conclusion: Three months after surgery, we observed a significant improvement in the performance of balance tasks while walking and a lower risk of falls in the intervention group. Full article

The number of migrant workers in Saudi Arabia (SA) has gradually increased, particularly in the construction industry, where migrant workers make up 89% of the workforce. Migrant workers frequently experience exposure to dangerous working conditions and increased risk for occupational injury and hazards due to the work they typically perform. Despite this, there is a lack of comprehensive studies comparing occupational accidents and injuries between migrant and domestic workers. To address this challenge, this study explores the differences between migrant and domestic workers’ injuries and occupational accident rates in SA’s construction industry. Data were analyzed from reported accidents and injuries obtained from the General Organisation for Social Insurance (GOSI) between 2014 and 2019. Chi-square test was used to examine the associations of occupational accidents and injuries among migrant and domestic workers. Migrant workers experienced higher incidences of falls, strikes, collisions, abrasions (wounds caused by scraping), bodily reactions (e.g., chemical reactions), and car accidents compared to domestic workers. Furthermore, migrant workers aged 30–39 and domestic workers aged 20–29 experienced more severe injuries and higher seasonal mortality rates during the six-year period examined (2014–2019). In addition, domestic workers achieved a higher proportion of full recovery across all types of accidents, except for transport and car accidents related to construction. The findings emphasize the need for ongoing safety education, training, and improved safety measures to protect the health and safety of construction workers, especially migrant workers. Full article

Daily walking reflects the quality of life concerning physical status and its association with the risk of falls. Abnormal walking can lead to injuries and increase the likelihood of future falls. It has been found that older adults are more prone to falls than younger persons. However, there is limited research on gait analysis in older adults. Thus, we analyzed gait parameters, involving 10 participants aged between 20 and 30 years old, and 10 participants aged 50 years and older, using the Gait Analysis System (LONGGOOD Meditech Ltd., Taipei, Taiwan), which automatically positions the human body and GaitBEST. GaitBEST is used for analyzing and calculating key timing points and displacement values from the Kinect detector as it captures the location of joint points and adjusts them to the program. After the gait testing, the result is displayed immediately. Each volunteer did not have any surgery that impacted their walking and signed a written informed consent statement before the study. The volunteers walked on a straight flat surface for 4.2 m, repeating the walking test five times at a self-determined comfortable speed. Subsequently, a comparative analysis of the gait parameter outcomes was performed using a parametric test by a t-test. The results showed the balance parameters of both groups significantly differed in the head sway range (p = 0.008), head tilt range (p = 0.018), and pelvis tilt range (p = 0.003). The younger group exhibited better postural control than the other group. The spatiotemporal parameters, stride length, and step length during walking were also significantly different at p = 0.001. This indicated that the older group had shorter lengths compared to the other group, leading to a significant difference in the percentage of falls and functional loss at p = 0.021 and 0.023, respectively. The result of this study assists in examining and assessing the physical condition, preventing falls, optimizing walking efficiency, preventing injuries, and reducing the falling risk. Full article