Immunohistochemical study of CD74 biomarker in normal and malignant breast tissues.

OBJECTIVE: Aim: To detect the role of CD74 expression in breast carcinoma as a predictive marker for identifying the biological behavior of malignancy in Iraqi women.. PATIENTS AND METHODS: Materials and Methods: The study used technique of immunohistochemistry for detection CD74 protein role in breast cancer, and its expression in breast cancer tissue samples. Samples were collected in Al-Najaf city in Iraq, from Al-Forat Al-Awsat Oncology Center. The study was achieved at the Laboratories of the Faculty of Science in the University of Kufa. Fifty samples of breast cancer tissue, and twenty controls benign tissue were included in the study. The study has investigated relationship between expression of biomarker with grade, age of patient and tumor size. RESULTS: Results: The study showed that the cytoplasmic expression of CD74 with more clear and intensive staining in the cytoplasm, and reported that CD74 positivity rate was 52%. A significant association between CD74 expression and grade and size of tumor, so CD74 can be considered as a biomarker for prediction of breast cancer in women. No association was found between CD74 expression and each of patients' age and node metastasis. CONCLUSION: Conclusions: The study represents an important step in our region because there are a few studies about this topic; more efforts are required to approve the function of this biomarker.

Risk assessment of driver performance in the oil and gas transportation industry: Analyzing the relationship between driver vigilance, attention, reaction time, and safe driving practices.

The increasing use of road traffic for land transportation has resulted in numerous road accidents and casualties, including those involving oil and gas tanker vehicles. Despite this, little empirical research has been conducted on the factors influencing tanker drivers' performance. This study aims to address this knowledge gap, particularly in the energy transportation industry, by examining the driving performance factors that affect tanker drivers and incorporating risk assessment measures. The model variables were identified from the literature and used to develop a survey questionnaire for the study. A total of 307 surveys were collected from Malaysian oil and gas tanker drivers, and the driving performance factors were contextually adjusted using the Exploratory Factor Analysis (EFA) approach. The driving performance model was developed using partial least squares structural equation modeling (PLS-SEM). The EFA results categorized driving performance into two constructs: 1) drivers' reaction time with ß = 0.320 and 2) attention and vigilance with ß value = 0.749. The proposed model provided full insight into how drivers' reaction time, attention, and vigilance impact drivers' performance in this sector, which can help identify potential risks and prevent accidents. The findings are significant in understanding the factors that affect oil and gas drivers' performance and can aid in enhancing oil and gas transportation management by including effective risk assessment measures to prevent fatal crashes.

Assessment of Hydroxyproline Content in Rabbit Achilles Tendon Treated with Platelet Rich Fibrin (PRF).

Tendon is similar to rope and consists of strong, flexible, dense connective tissue. Tendon disorder healing is challenging as it is an avascular tissue. The repaired tissue appears scar-like, and its biomechanical properties never ultimately return to their pre-injury state. This study aimed to evaluate the effects of platelet-rich fibrin (PRF) on the hydroxyproline content of the Achilles tendon after injury. For this purpose, 24 adult rabbits weighing 1.5-2 kg were used in this study. The animals were divided into three groups of eight, including the advanced-PRF (A-PRF) group in which the tendon defect was treated with xenogeneic A-PRF, the leukocyte-PRF (L-PRF) group in which xenogeneic L-PRF was used for tendon defect treatment, and a control group which was treated with normal saline. Hydroxyproline concentration was measured 1 and 2 months after the operation. Clinically, lameness was improved in the A-PRF group, compared to the L-PRF and control groups at the end of the third week after the surgery. Hydroxyproline level was significantly increased in the A-PRF group (50.33±1.44), compared to the L-PRF (44.70±1.12) and control (35.97±1.05) groups 2 months after the surgery (P<0.05). Moreover, the L-PRF group showed an increase in hydroxyproline content, compared to the control at the same period. The results of the current study demonstrated that A-PRF could enhance the hydroxyproline content of rabbit Achilles tendon after injury. Xenogenic PRF can be used as an alternative biomaterial to accelerate and regenerate tendon tissue.

Integrated FRET Polymers Spatially Reveal Micro- to Nanostructure and Irregularities in Electrospun Microfibers.

A spatial view of macroscopic polymer material properties, in terms of nanostructure and irregularities, can help to better understand engineering processes such as when materials may fail. However, bridging the gap between the molecular-scale arrangement of polymer chains and the spatially resolved macroscopic properties of a material poses numerous difficulties. Herein, an integrated messenger material that can report on the material micro- to nanostructure and its processes is introduced. It is based on polymer chains labeled with fluorescent dyes that feature Förster resonance energy transfer (FRET) dependent on chain conformation and concentration within a host polymer material. These FRET materials are integrated within electrospun polystyrene microfibers, and the FRET is analyzed by confocal laser scanning microscopy (CLSM). Importantly, the use of CLSM allows a spatial view of material nanostructure and irregularities within the microfibers, where changes in FRET are significant when differences in fiber geometries and regularities exist. Furthermore, changes in FRET observed in damaged regions of the fibers indicate changes in polymer conformation and/or concentration as the material changes during compression. The system promises high utility for applications where nano-to-macro communication is needed for a better understanding of material processes.

A Systematic Review of Mobile Phone Data in Crime Applications: A Coherent Taxonomy Based on Data Types and Analysis Perspectives, Challenges, and Future Research Directions.

Digital technologies have recently become more advanced, allowing for the development of social networking sites and applications. Despite these advancements, phone calls and text messages still make up the largest proportion of mobile data usage. It is possible to study human communication behaviors and mobility patterns using the useful information that mobile phone data provide. Specifically, the digital traces left by the large number of mobile devices provide important information that facilitates a deeper understanding of human behavior and mobility configurations for researchers in various fields, such as criminology, urban sensing, transportation planning, and healthcare. Mobile phone data record significant spatiotemporal (i.e., geospatial and time-related data) and communication (i.e., call) information. These can be used to achieve different research objectives and form the basis of various practical applications, including human mobility models based on spatiotemporal interactions, real-time identification of criminal activities, inference of friendship interactions, and density distribution estimation. The present research primarily reviews studies that have employed mobile phone data to investigate, assess, and predict human communication and mobility patterns in the context of crime prevention. These investigations have sought, for example, to detect suspicious activities, identify criminal networks, and predict crime, as well as understand human communication and mobility patterns in urban sensing applications. To achieve this, a systematic literature review was conducted on crime research studies that were published between 2014 and 2022 and listed in eight electronic databases. In this review, we evaluated the most advanced methods and techniques used in recent criminology applications based on mobile phone data and the benefits of using this information to predict crime and detect suspected criminals. The results of this literature review contribute to improving the existing understanding of where and how populations live and socialize and how to classify individuals based on their mobility patterns. The results show extraordinary growth in studies that utilized mobile phone data to study human mobility and movement patterns compared to studies that used the data to infer communication behaviors. This observation can be attributed to privacy concerns related to acquiring call detail records (CDRs). Additionally, most of the studies used census and survey data for data validation. The results show that social network analysis tools and techniques have been widely employed to detect criminal networks and urban communities. In addition, correlation analysis has been used to investigate spatial-temporal patterns of crime, and ambient population measures have a significant impact on crime rates.

Subacute infective endocarditis presenting with an isolated splenic infarction.

Background: Subacute endocarditis usually presents over a period of weeks or months. Symptoms usually include low grade fever, and generalized symptoms of malaise, anorexia, weight loss. Here we present a case of subacute endocarditis presenting solely as acute left hypochondrial pain, which was found to be splenic infarct. Typical symptoms of subacute endocarditis were absent in our patient. Case report: A 48-year-old Yemeni gentleman presented to the emergency department with acute and severe left hypochondrial abdominal pain for a few hours. Blood investigations revealed normal blood count differential, renal, liver function, and electrolyte levels. CT abdomen with contrast showed large focal wedge-shaped splenic lesion representing splenic infarct. Initial workup was negative for an underlying etiology. TEE showed a spherical mobile mass attached to the aortic valve with moderate to severe aortic regurgitation. Subsequently, 3 sets of blood cultures were sent and revealed growth of streptococcus viridians in all bottles. The patient received IV antibiotics as a treatment of endocarditis. Conclusion: This case highlights how subacute endocarditis presented as splenic infarction, with the absence of the typical infectious symptoms. In case of splenic infarction with unclear source or etiology, it is reasonable to investigate thoroughly for infective endocarditis preferably with TEE.

Potential Regulation of miRNA-29 and miRNA-9 by Estrogens in Neurodegenerative Disorders: An Insightful Perspective.

Finding a link between a hormone and microRNAs (miRNAs) is of great importance since it enables the adjustment of genetic composition or cellular functions without needing gene-level interventions. The dicer-mediated cleavage of precursor miRNAs is an interface link between miRNA and its regulators; any disruption in this process can affect neurogenesis. Besides, the hormonal regulation of miRNAs can occur at the molecular and cellular levels, both directly, through binding to the promoter elements of miRNAs, and indirectly, via regulation of the signaling effects of the post-transcriptional processing proteins. Estrogenic hormones have many roles in regulating miRNAs in the brain. This review discusses miRNAs, their detailed biogenesis, activities, and both the general and estrogen-dependent regulations. Additionally, we highlight the relationship between miR-29, miR-9, and estrogens in the nervous system. Such a relationship could be a possible etiological route for developing various neurodegenerative disorders.

Changes in Semen Analysis over Time: A Temporal Trend Analysis of 20 Years of Subfertile Non-Azoospermic Men.

PURPOSE: To examine trends of population-level semen quality over a 20-year period. MATERIALS AND METHODS: We performed a retrospective review of data from the andrology lab of a high volume tertiary hospital. All men with semen samples between 2000 and 2019 were included and men with azoospermia were excluded. Semen parameters were reported using the World Health Organization (WHO) 4th edition. The primary outcome of interest was changes in semen parameters over time. Generalized least squares (GLS) with restricted cubic splines were used to estimate average-monthly measurements, adjusting for age and abstinence period. Contrasts of the estimated averages based on GLS between the first and last months of collection were calculated. RESULTS: A total of 8,990 semen samples from subfertile non-azoospermic men were included in our study. Semen volume decreased over time and estimate average at the beginning and end were statistically different (p<0.001). Similarly sperm morphology decreased over time, with a statistically significant difference between estimated averages from start to finish (p<0.001). Semen pH appeared to be increasing over time, but this difference was not significant over time (p=0.060). Sperm concentration and count displayed an increase around 2003 to 2005, but otherwise remained fairly constant over time (p=0.100 and p=0.054, respectively). Sperm motility appeared to decrease over time (p<0.001). CONCLUSIONS: In a large sample of patients presenting to a single institution for fertility assessment, some aspects of semen quality declined across more than two decades. An understanding of the etiologies and driving forces of changing semen parameters over time is warranted.

Optimized protocol for quantification of extracellular nicotinamide adenine dinucleotide: evaluating clinical parameters and pre-analytical factors for translational research.

Nicotinamide adenine dinucleotide (NAD+), a coenzyme for more than 500 enzymes, plays a central role in energy production, metabolism, cellular signaling, and DNA repair. Until recently, NAD+ was primarily considered to be an intracellular molecule (iNAD+), however, its extracellular species (eNAD+) has recently been discovered and has since been associated with a multitude of pathological conditions. Therefore, accurate quantification of eNAD+ in bodily fluids such as plasma is paramount to answer important research questions. In order to create a clinically meaningful and reliable quantitation method, we analyzed the relationship of cell lysis, routine clinical laboratory parameters, blood collection techniques, and pre-analytical processing steps with measured plasma eNAD+ concentrations. Initially, NAD+ levels were assessed both intracellularly and extracellularly. Intriguingly, the concentration of eNAD+ in plasma was found to be approximately 500 times lower than iNAD+ in peripheral blood mononuclear cells (0.253 ± 0.02 µM vs. 131.8 ± 27.4 µM, p = 0.007, respectively). This stark contrast suggests that cellular damage or cell lysis could potentially affect the levels of eNAD+ in plasma. However, systemic lactate dehydrogenase in patient plasma, a marker of cell damage, did not significantly correlate with eNAD+ (n = 33; r = -0.397; p = 0.102). Furthermore, eNAD+ was negatively correlated with increasing c-reactive protein (CRP, n = 33; r = -0.451; p = 0.020), while eNAD+ was positively correlated with increasing hemoglobin (n = 33; r = 0.482; p = 0.005). Next, variations in blood drawing, sample handling and pre-analytical processes were examined. Sample storage durations at 4°C (0-120 min), temperature (0° to 25°C), cannula sizes for blood collection and tourniquet times (0 - 120 s) had no statistically significant effect on eNAD+ (p > 0.05). On the other hand, prolonged centrifugation (> 5 min) and a faster braking mode of the centrifuge rotor (< 4 min) resulted in a significant decrease in eNAD+ levels (p < 0.05). Taken together, CRP and hemoglobin appeared to be mildly correlated with eNAD+ levels whereas cell damage was not correlated significantly to eNAD+ levels. The blood drawing trial did not show any influence on eNAD+, in contrast, the preanalytical steps need to be standardized for accurate eNAD+ measurement. This work paves the way towards robust eNAD+ measurements, for use in future clinical and translational research, and provides an optimized hands-on protocol for reliable eNAD+ quantification in plasma.

Association of Psychosocial Stress With Risk of Acute Stroke.

Importance: Psychosocial stress is considered a modifiable risk factor for stroke. Given the prevalence of chronic and acute exposure to stress, it represents a potentially attractive target for population-health interventions. Objectives: To determine the association of psychosocial stress with the risk of acute stroke and explore factors that might modify the association of stress with risk of acute stroke in a large international population. Design, Setting, and Participants: INTERSTROKE is an international retrospective case-control study of risk factors for first acute stroke in 32 countries in Asia, North and South America, Europe, Australia, the Middle East, and Africa. A total of 13 462 patients with stroke and 13 488 matched controls were recruited between January 11, 2007, and August 8, 2015. The present analyses were performed from June 1 to 30, 2021, and included 13 350 cases and 13 462 controls with available data on psychosocial stress. Exposures: Psychosocial stress and occurrence of stressful life events within the preceding year were measured using a standardized questionnaire of self-reported stress at home and work. Main Outcomes and Measures: The association of stress with acute stroke and its subtypes was examined using multivariable conditional logistic regression and factors that might modify the association, particularly self-reported locus of control. Results: Among 26 812 participants included in the analysis, the mean (SD) age of cases was 62.2 (13.6) years; that of controls, 61.3 (13.3) years; 7960 cases (59.6%) and 8017 controls (59.6%) were men. Several periods of stress and permanent stress were reported for 2745 cases (20.5%) and 1933 controls (14.4%), with marked regional variation in prevalence, with the lowest in China (201 of 3981 [5.0%] among controls and 364 of 3980 [9.1%] among cases) and highest in South East Asia (233 of 855 [26.1%] among controls and 241 of 782 [30.8%] among cases). Increased stress at home (odds ratio [OR], 1.95 [95% CI, 1.77-2.15]) and at work (OR, 2.70 [95% CI, 2.25-3.23]) and recent stressful life events (OR, 1.31 [95% CI, 1.19-1.43]) were associated with an increased risk of acute stroke on multivariable analyses (vs no self-reported stress). Higher locus of control at home was associated with a reduced odds of all stroke (OR, 0.73 [95% CI, 0.68-0.79]), and higher locus of control both at work and at home were associated with a lower odds of acute stroke and significantly diminished the association with stress at work (OR, 2.20 [95% CI, 1.88-2.58]; P = .008 for interaction) and home (OR, 1.69 [95% CI, 1.44-1.98]; P < .001 for interaction) for acute stroke. Conclusions and Relevance: Psychosocial stress is a common risk factor for acute stroke. The findings of this case-control study suggest that higher locus of control is associated with lower risk of stroke and may be an important effect modifier of the risk associated with psychosocial stress.

COVID-19 Vaccine as a Potential Triggering Factor for Anti-Glomerular Basement Membrane (GBM) Disease: A Case Report and Literature Review.

Coronavirus 2019 (COVID-19) is considered one of the most significant medical pandemics of this century, with high morbidity and mortality associated with the pandemic. The virus was recognized initially as a cause of pneumonia, but subsequent studies showed significant association with gastrointestinal, neurological, and autoimmune diseases. By 2020, several vaccines became available for use, significantly reducing the infection rate. A good safety profile supported most of the studies related to vaccines. However, this area is still under study, and some reports linked the COVID-19 vaccine to the development of thrombocytopenia, thrombosis, Guillain-Barre syndrome, autoimmune diseases, and myocarditis. These side effects need to be reported to VAERS (Vaccine Adverse Event Reporting System). The exact etiology of anti-glomerular basement (Anti-GBM) disease remains unknown, but the disease is thought to be triggered by environmental factors in genetically predisposed individuals. It is considered one of the serious diseases that could lead to permanent kidney impairment if not treated early and adequately. That's why a great effort is being made by health care practitioners to figure out and avoid the risk and triggering factors. Few previously published papers linked the COVID-19 vaccine and the development of anti-GBM disease, which raised concerns about digging more into this area. Herein, we are reporting a case of a patient who developed rapidly progressive glomerulonephritis (RPGN) due to anti-glomerular basement membrane (GBM) antibody disease two days after receiving the second dose of the COVID-19 vaccine.

Charge-Compensated N-Doped π-Conjugated Polymers: Toward both Thermodynamic Stability of N-Doped States in Water and High Electron Conductivity.

The understanding and applications of electron-conducting π-conjugated polymers with naphtalene diimide (NDI) blocks show remarkable progress in recent years. Such polymers demonstrate a facilitated n-doping due to the strong electron deficiency of the main polymer chain and the presence of the positively charged side groups stabilizing a negative charge of the n-doped backbone. Here, the n-type conducting NDI polymer with enhanced stability of its n-doped states for prospective "in-water" applications is developed. A combined experimental-theoretical approach is used to identify critical features and parameters that control the doping and electron transport process. The facilitated polymer reduction ability and the thermodynamic stability in water are confirmed by electrochemical measurements and doping studies. This material also demonstrates a high conductivity of 10-2  S cm-1  under ambient conditions and 10-1  S cm-1  in vacuum. The modeling explains the stabilizing effects  for various dopants. The simulations show a significant doping-induced "collapse" of the positively charged side chains on the core bearing a partial negative charge. This explains a decrease in the lamellar spacing observed in experiments. This study fundamentally enables a novel pathway for achieving both thermodynamic stability of the n-doped states in water and the high electron conductivity of polymers.

Investigating the Effect of COVID-19 on Driver Behavior and Road Safety: A Naturalistic Driving Study in Malaysia.

The spread of the novel coronavirus COVID-19 resulted in unprecedented worldwide countermeasures such as lockdowns and suspensions of all retail, recreational, and religious activities for the majority of 2020. Nonetheless, no adequate scientific data have been provided thus far about the impact of COVID-19 on driving behavior and road safety, especially in Malaysia. This study examined the effect of COVID-19 on driving behavior using naturalistic driving data. This was accomplished by comparing the driving behaviors of the same drivers in three periods: before COVID-19 lockdown, during COVID-19 lockdown, and after COVID-19 lockdown. Thirty people were previously recruited in 2019 to drive an instrumental vehicle on a 25 km route while recording their driving data such as speed, acceleration, deceleration, distance to vehicle ahead, and steering. The data acquisition system incorporated various sensors such as an OBDII reader, a lidar, two ultrasonic sensors, an IMU, and a GPS. The same individuals were contacted again in 2020 to drive the same vehicle on the same route in order to capture their driving behavior during the COVID-19 lockdown. Participants were approached once again in 2022 to repeat the procedure in order to capture their driving behavior after the COVID-19 lockdown. Such valuable and trustworthy data enable the assessment of changes in driving behavior throughout the three time periods. Results showed that drivers committed more violations during the COVID-19 lockdown, with young drivers in particular being most affected by the traffic restrictions, driving significantly faster and performing more aggressive steering behaviors during the COVID-19 lockdown than any other time. Furthermore, the locations where the most speeding offenses were committed are highlighted in order to provide lawmakers with guidance on how to improve traffic safety in those areas, in addition to various recommendations on how to manage traffic during future lockdowns.

A Rare Case of Undifferentiated Pleomorphic Cardiac Sarcoma with Inflammatory Pattern.

Cardiac undifferentiated pleomorphic sarcoma (UPS) associated with fever and inflammatory response is an extremely rare condition. Herein, we report a rare case of cardiac UPS with unusual clinical presentation and inflammatory response. A 67-year-old male complaining of progressive dyspnea and intermittent fever of unknown cause was referred to our hospital for surgical resection of a left atrial mass. Laboratory analysis showed leukocytosis (26 × 103/µL) and high C-reactive protein (CRP) levels (155.4 mg/L). Hemoculture tests and urine analysis were negative for infection. A contrast chest computed tomography revealed a mass measuring 5.5 × 4.5 cm, occupying the left atrium cavity. The patient underwent surgical excision of the mass, however, surgical margin of the resected tumor could not be evaluated, due to the multifragmented nature of the resection specimen. Postoperative CRP and leukocyte levels normalized, highlighting the relationship between the tumor and the inflammatory status. Early diagnosis is crucial for a proper management and favorable outcome, enabling patients to undergo chemotherapy and achieve complete surgical resection.

Chaos in Cancer Tumor Growth Model with Commensurate and Incommensurate Fractional-Order Derivatives.

Analyzing the dynamics of tumor-immune systems can play an important role in the fight against cancer, since it can foster the development of more effective medical treatments. This paper was aimed at making a contribution to the study of tumor-immune dynamics by presenting a new model of cancer growth based on fractional-order differential equations. By investigating the system dynamics, the manuscript highlights the chaotic behaviors of the proposed cancer model for both the commensurate and the incommensurate cases. Bifurcation diagrams, the Lyapunov exponents, and phase plots confirm the effectiveness of the conceived approach. Finally, some considerations regarding the biological meaning of the obtained results are reported through the manuscript.

Organophosphate Insecticides Resistance in Field Populations of House Flies, Musca domestica L.: Levels of Resistance and Acetylcholinesterase Activity.

The house fly, Musca domestica L., is an important medical and veterinary pest associated with humans and livestock. Management of house flies has relied extensively on chemical control. In this study, we report on the resistance of house fly field-collected populations to diazinon and fenitrothion OP insecticides in Riyadh, Saudi Arabia. The diazinon and fenitrothion median lethal dose (LD50) values against adult female M. domestica field-collected populations were significantly higher than those of the laboratory (LAB) strain. Different levels of resistance were detected in all field-collected populations toward the two OP insecticides. The resistance ratios for diazinon ranged from 62.47 to 309.78, while there were 53.08 to 261.24 for fenitrothion in the eight field-collected populations. The specific activity of acetylcholinesterase (AChE) in all field populations was significantly (p < 0.05) higher than that in the LAB strain. In vitro diazinon and fenitrothion median inhibitory concentration (IC50) values of LAB strain AChE activity were significantly (p < 0.05) lower than those for field-collected populations. This study found high levels of resistance in the house fly field-collected populations to diazinon and fenitrothion. Replacing these two insecticides and any other OPs with novel ones that have different modes of action is an urgent need in the insect-vector control programs in Riyadh, Saudi Arabia. An altered AChE enzyme of M. domestica field populations might be partially responsible for the developed resistance. Monitoring of insecticide resistance development in M. domestica populations and a better understanding of its mechanisms are needed to design operative management strategies for controlling the house flies.

Driver Behavior Profiling and Recognition Using Deep-Learning Methods: In Accordance with Traffic Regulations and Experts Guidelines.

The process of collecting driving data and using a computational model to generate a safety score for the driver is known as driver behavior profiling. Existing driver profiles attempt to categorize drivers as either safe or aggressive, which some experts say is not practical. This is due to the "safe/aggressive" categorization being a state that describes a driver's conduct at a specific point in time rather than a continuous state or a human trait. Furthermore, due to the disparity in traffic laws and regulations between countries, what is considered aggressive behavior in one place may differ from what is considered aggressive behavior in another. As a result, adopting existing profiles is not ideal. The authors provide a unique approach to driver behavior profiling based on timeframe data segmentation. The profiling procedure consists of two main parts: row labeling and segment labeling. Row labeling assigns a safety score to each second of driving data based on criteria developed with the help of Malaysian traffic safety experts. Then, rows are accumulated to form timeframe segments. In segment labeling, generated timeframe segments are assigned a safety score using a set of criteria. The score assigned to the generated timeframe segment reflects the driver's behavior during that time period. Following that, the study adopts three deep-learning-based algorithms, namely, Deep Neural Network (DNN), Recurrent Neural Network (RNN), and Convolutional Neural Network (CNN), to classify recorded driving data according to the established profiling procedure, and selects the most suitable one for a proposed recognition system. Various techniques were used to prevent the classification algorithms from overfitting. Using gathered naturalistic data, the validity of the modulated algorithms was assessed on various timeframe segments ranging from 1 to 10 s. Results showed that the CNN, which achieved an accuracy of 96.1%, outperformed the other two classification algorithms and was therefore recommended for the recognition system. In addition, recommendations were outlined on how the recognition system would assist in improving traffic safety.

Investigating the Effect of Social and Cultural Factors on Drivers in Malaysia: A Naturalistic Driving Study.

Road accidents are increasing every year in Malaysia, and it is always challenging to collect reliable pre-crash data in the transportation community. Existing studies relied on simulators, police crash reports, questionnaires, and surveys to study Malaysia's drivers' behavior. Researchers previously criticized such methods for being biased and unreliable. To fill in the literature gap, this study presents the first naturalistic driving study in Malaysia. Thirty drivers were recruited to drive an instrumented vehicle for 750 km while collecting continuous driving data. The data acquisition system consists of various sensors such as OBDII, lidar, ultrasonic sensors, IMU, and GPS. Irrelevant data were filtered, and experts helped identify safety criteria regarding multiple driving metrics such as maximum acceptable speed limits, safe accelerations, safe decelerations, acceptable distances to vehicles ahead, and safe steering behavior. These thresholds were used to investigate the influence of social and cultural factors on driving in Malaysia. The findings show statistically significant differences between drivers based on gender, age, and cultural background. There are also significant differences in the results for those who drove on weekends rather than weekdays. The study presents several recommendations to various public and governmental sectors to help prevent future accidents and improve traffic safety.

A systematic review on sensor-based driver behaviour studies: coherent taxonomy, motivations, challenges, recommendations, substantial analysis and future directions.

In the plan and development of Intelligent Transportation Systems (ITS), understanding drivers behaviour is considered highly valuable. Reckless driving, incompetent preventive measures, and the reliance on slow and incompetent assistance systems are attributed to the increasing rates of traffic accidents. This survey aims to review and scrutinize the literature related to sensor-based driver behaviour domain and to answer questions that are not covered so far by existing reviews. It covers the factors that are required in improving the understanding of various appropriate characteristics of this domain and outlines the common incentives, open confrontations, and imminent commendations from former researchers. Systematic scanning of the literature, from January 2014 to December 2020, mainly from four main databases, namely, IEEEXplore, ScienceDirect, Scopus and Web of Science to locate highly credible peer-reviewed articles. Amongst the 5,962 articles found, a total of 83 articles are selected based on the author's predefined inclusion and exclusion criteria. Then, a taxonomy of existing literature is presented to recognize the various aspects of this relevant research area. Common issues, motivations, and recommendations of previous studies are identified and discussed. Moreover, substantial analysis is performed to identify gaps and weaknesses in current literature and guide future researchers into planning their experiments appropriately. Finally, future directions are provided for researchers interested in driver profiling and recognition. This survey is expected to aid in emphasizing existing research prospects and create further research directions in the near future.

Optimal timing for repeat semen analysis during male infertility evaluation.

OBJECTIVE: To assess whether the 4-week time period between semen analyses during the workup of male infertility is optimal and whether two samples are needed. DESIGN: Retrospective study. SETTING: Tertiary hospital. PATIENTS: Men whose semen samples were obtained within 90 days of each other, without known fertility intervention, treatment, and/or azoospermia. INTERVENTIONS: Semen analysis. MAIN OUTCOME MEASURES: Correlation between semen parameters and agreement among consecutive semen analyses. RESULTS: A total of 2,150 semen samples from 1,075 men were included in the analysis. The optimal correlation for volume occurred at weeks 2, 8, and 12 (r = 0.803, r = 0.802, and r = 0.821, respectively). For concentration, the correlation was maximized at weeks 1, 4, and 5 (r = 0.950, r = 0.841, and r = 0.795, respectively). Total sperm count correlated at weeks 1, 2, and 4 (r = 0.929, r = 0.727, and r = 0.808, respectively). Motility was maximally correlated at weeks 1, 10, and 13 (r = 0.711, r = 0.760, and r = 0.708, respectively). Morphology was optimally correlated at weeks 1, 2, and 9 (r = 0.935, r = 0.815, and r = 0.839, respectively). Semen volume was correlated in 55% of men, sperm concentration in 64% of men, sperm motility in 52% of men and sperm morphology 64% of men. CONCLUSIONS: Our data suggest that four weeks may not be the optimal time for repeat semen analysis and that one sample is insufficient to assess any abnormalities in the result of semen analysis. The optimal time between repeat semen analyses should be individualized depending on the results of the initial analysis and additional factors, suggesting the need for future large-scale studies to investigate this trend.