Search results for: open building information modeling

Authors: Zeina Bourhane, Anders Lanzen, Christine Cagnon, Olfa Ben Said, Cristiana Cravo-Laureau, Robert Duran

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The anthropogenic pressure in coastal areas increases dramatically with the exploitation of environmental resources. Biomonitoring coastal areas are crucial to determine the impact of pollutants on bacterial communities in soils and sediments since they provide important ecosystem services. However, relevant biomonitoring tools allowing fast determination of the ecological status are yet to be defined. Microbial ecology approaches provide useful information for developing such microbial monitoring tools reporting on the effect of environmental stressors. Chemical and microbial molecular approaches were combined in order to determine microbial bioindicators for assessing the ecological status of soil and river ecosystems around the Ichkeul Lake (Tunisia), an area highly impacted by human activities. Samples were collected along soil/river/lake continuums in three stations around the Ichkeul Lake influenced by different human activities at two seasons (summer and winter). Contaminant pressure indexes (PI), including PAHs (Polycyclic aromatic hydrocarbons), alkanes, and OCPs (Organochlorine pesticides) contents, showed significant differences in the contamination level between the stations with seasonal variation. Bacterial communities were characterized by 16S ribosomal RNAs (rRNA) gene metabarcoding. Although microgAMBI indexes, determined from the sequencing data, were in accordance with contaminant contents, they were not sufficient to fully explain the PI. Therefore, further microbial indicators are still to be defined. The comparison of bacterial communities revealed the specific microbial assemblage for soil, river, and lake sediments, which were significantly correlated with contaminant contents and PI. Such observation offers the possibility to define a relevant set of bioindicators for reporting the effects of human activities on the microbial community structure. Such bioindicators might constitute useful monitoring tools for the management of microbial communities in coastal areas.

Keywords: bacterial communities, biomonitoring, contamination, human impacts, microbial bioindicators

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Authors: Thapa M., J.P. Dutta, K.R. Pandey, R.R. Kattel

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Nepal is extremely vulnerable to the impact of climate change. To mitigate the climate change effects on agricultural production and productivity a range of adaptive strategies needs to be considered. The study was conducted to assess organic paddy production as a coping strategy to the adverse impact of climate change in Phulbari, VDC of Chitwan district. Altogether, 120 respondents (60 adopters of organic farming and 60 from non adopter) were selected using snowball technique of sampling. Pre- tested interview schedule, direct observation, focus group discussion, key informant interview as well as secondary data were used to collect the required information. Factors determining the adoption of organic farming were found to be age, year of schooling, training, frequency of extension contact, perception about climate change, economically active members and poor. A unit increase in these factors except poor would increase the probability of adoption by 4.1%, 7.5%, 7.8%, 43.1%, 41.8% and 7% respectively. However, for poor, it would decrease the probability of adoption of organic farming by 5.1%. Average organic matter content in the adopters' field was higher (2.7%) than the non-adopters' field (2.5%). The regression result showed that type of farmer, price and area under rice cultivation had positive and significant relationship with income; however dependency ratio had negative relationship. As the year of adoption of organic farming increases, the production of rice decline in the first two years then after goes on increasing but the cost of production goes on decreasing with the year of adoption. The respondents adapted to the changing climate through diversification of crops, use of resistance varieties and following good cropping pattern. Gradually growing consumers' awareness about health, preference towards quality food products are the strong points behind organic farming, whereas lacks of bio-fertilizers, lack of effective extension services, no price differentiation between organic and inorganic products were the weak points. There is need for more training and education to change the attitude of farmers and enhance their confidence about the role of organic farming to cope with climate change impact.

Keywords: Organic farming, climate change, sustainable development

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Authors: Shehu Isyaku

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The general objective of the study was to investigate ‘the relationship between the external business environment and the sustainability of micro, small and medium enterprises (MSMEs) in Jigawa state’, Nigeria. Specifically, the study was to examine the relationship between 1) the economic environment, 2) the social environment, 3) the technological environment, and 4) the political environment and the sustainability of MSMEs in Jigawa state, Nigeria. The study was drawn on Resource-Based View (RBV) Theory and Knowledge-Based View (KBV). The study employed a descriptive cross-sectional survey design. A researcher-made questionnaire was used to collect data from the 350 managers/owners who were selected using stratified, purposive and simple random sampling techniques. Data analysis was done using means and standard deviations, factor analysis, Correlation Coefficient, and Pearson Linear Regression analysis. The findings of the study revealed that the sustainability potentials of the managers/owners were rated as high potential (economic, environmental, and social sustainability using 5 5-point Likert scale. Mean ratings of effectiveness of the external business environment were; as highly effective. The results from the Pearson Linear Regression Analysis rejected the hypothesized non-significant effect of the external business environment on the sustainability of MSMEs. Specifically, there is a positive significant relationship between 1) economic environment and sustainability; 2) social environment and sustainability; 3) technological environment and sustainability and political environment and sustainability. The researcher concluded that MSME managers/owners have a high potential for economic, social and environmental sustainability and that all the constructs of the external business environment (economic environment, social environment, technological environment and political environment) have a positive significant relationship with the sustainability of MSMEs. Finally, the researcher recommended that 1) MSME managers/owners need to develop marketing strategies and intelligence systems to accumulate information about the competitors and customers' demands, 2) managers/owners should utilize the customers’ cultural and religious beliefs as an opportunity that should be utilized while formulating business strategies.

Keywords: business environment, sustainability, small and medium enterprises, external business environment

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Authors: Ahmed Sami Hammami, Mohamed Jellazi

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Background: The aim of the study is to evaluate the magnitude of different psychological outcomes among Tunisian health care professionals (HCP) during the COVID-19 pandemic and to identify the associated factors. Methods: HCP completed a cross-sectional questionnaire from April 4th to April, 28th 2020. The survey collected demographic information, factors that may interfere with the psychological outcomes, behavior changes and mental health measurements. The latter was assessed through 3 scales; the 7-item questions Insomnia Severity Index, the 2-item Patient Health Questionnaire and the 2-item Generalized Anxiety Disorder. Multivariable logistic regression was conducted to identify factors associated with psychological outcomes. Results: A total of 503 HCP successfully completed the survey; among those, n=493 consented to enroll in the study, 411 [83.4%] were physicians, 323 [64.2%] were women and 271 [55%] had a second-line working position. A significant proportion of HCP had anxiety 35.7%, depression 35.1% and insomnia 23.7%. Females, those with psychiatric history and those using public transport exhibited the highest proportions for overall symptoms compared to other groups e.g., depression among females vs. males: 44,9% vs. 18,2%, P=0.00. Those with a previous medical history and nurses, had more anxiety and insomnia compared to other groups e.g. anxiety among nurses vs. interns/residents vs. attending 45,1% vs 36,1% vs 27,5%; p=0.04. Multivariable logistic regression showed that female gender was a risk factor for all psychological outcomes e.g. female sex increased the odds of anxiety by 2.86; 95% confidence interval [CI], 1, 78-4, 60; P=0.00, whereas having a psychiatric history was a risk factor for both anxiety and insomnia. (e.g. for insomnia OR=2,86; 95% [CI], 1,78-4,60; P=0.00), Having protective equipment was associated with lower risk for depression (OR=0,41; 95% CI, 0,27-0,62; P=0.00) and anxiety. Physical activity was also protective against depression and anxiety (OR=0,41, 95% CI, 0,25-0,67, P=0.00). Conclusion: Psychological symptoms are usually undervalued among HCP, though the COVID-19 pandemic played a major role in exacerbating this burden. Prompt psychological support should be endorsed and simple measures such as physical activity and ensuring the necessary protection are paramount to improve mental health outcomes and the quality of care provided to patients.

Keywords: COVID-19 pandemic, health care professionals, mental health, protective factors, psychological symptoms, risk factors

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Authors: Tammeen Siraj, Wenxing Zhou, Terry Huang, Mohammad Al-Amin

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The high resolution inline inspection (ILI) tool is used extensively in the pipeline industry to identify, locate, and measure metal-loss corrosion anomalies on buried oil and gas steel pipelines. Corrosion anomalies may occur singly (i.e. individual anomalies) or as clusters (i.e. a colony of corrosion anomalies). Although the ILI technology has advanced immensely, there are measurement errors associated with the sizes of corrosion anomalies reported by ILI tools due limitations of the tools and associated sizing algorithms, and detection threshold of the tools (i.e. the minimum detectable feature dimension). Quantifying the measurement error in the ILI data is crucial for corrosion management and developing maintenance strategies that satisfy the safety and economic constraints. Studies on the measurement error associated with the length of the corrosion anomalies (in the longitudinal direction of the pipeline) has been scarcely reported in the literature and will be investigated in the present study. Limitations in the ILI tool and clustering process can sometimes cause clustering error, which is defined as the error introduced during the clustering process by including or excluding a single or group of anomalies in or from a cluster. Clustering error has been found to be one of the biggest contributory factors for relatively high uncertainties associated with ILI reported anomaly length. As such, this study focuses on developing a consistent and comprehensive framework to quantify the measurement errors in the ILI-reported anomaly length by comparing the ILI data and corresponding field measurements for individual and clustered corrosion anomalies. The analysis carried out in this study is based on the ILI and field measurement data for a set of anomalies collected from two segments of a buried natural gas pipeline currently in service in Alberta, Canada. Data analyses showed that the measurement error associated with the ILI-reported length of the anomalies without clustering error, denoted as Type I anomalies is markedly less than that for anomalies with clustering error, denoted as Type II anomalies. A methodology employing data mining techniques is further proposed to classify the Type I and Type II anomalies based on the ILI-reported corrosion anomaly information.

Keywords: clustered corrosion anomaly, corrosion anomaly assessment, corrosion anomaly length, individual corrosion anomaly, metal-loss corrosion, oil and gas steel pipeline

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Authors: Florence Awde

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In 2023, it was expected 350 parents in Arizona would have a child receive a cancer diagnosis (Welcome Arizona Cancer Foundation For Children, n.d.). The news of a child’s diagnosis with cancer can be overwhelming and confusing, especially for those lucky enough to lack a personal tie to the disease that takes approximately 1800 children’s lives each year in the United States (Deegan et al., n.d.). A parent’s beliefs, attitudes, and understandings surrounding cancer are vital for medical staff to provide adequate and culturally competent care for each patient, especially across cultural and ethnic lines in regions housing multicultural populations. Arizona's cultural/linguistic mosaic houses many White and Latino populations and English and Spanish speakers. Variations in insurance coverage, from those insured through public insurance programs (e.g., Medicaid) or private insurance plans (e.g., employee-sponsored insurance) versus those uninsured, also factor into health-seeking attitudes and behaviors. To further understand parental attitudes, understandings, and beliefs towards childhood cancer, 22 parents (11 of Latino ethnicity, 11 of White ethnicity) were interviewed on these facets of childhood cancer, despite 21 of the 22 never having a child receive a cancer diagnosis. The exploration of these perceptions across ethnic lines revealed a higher report of fear-orientated beliefs amongst Latino parents--hypothesized to be rooted in the starkly contrasting lack of belief in the possibility of recovering for children with cancer, compared to their white counterparts who displayed more optimism in the recovery process. Further, this study’s results lay the foundation for future scholarship to explore avenues of information dispersal to Latino parents that correct misconceptions of health outcomes and enable earlier intervention to be possible, ultimately correlating to better health and treatment outcomes by increasing parental health literacy rates for childhood cancer in the Phoenix Metropolitan.

Keywords: Childhood Cancer, Parental Beliefs, Parental Attitudes, Parental Understandings, Phoenix Metropolitan, Culturally Competent Care, Health Disparities, Health Inequities

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Authors: Umamaheswari Shanmugam, Silvia Ronchi

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Software, artificial intelligence, and machine learning can improve healthcare through innovative and advanced technologies that can use the large amount and variety of data generated during healthcare services every day; one of the significant advantages of these new technologies is the ability to get experience and knowledge from real-world use and to improve their performance continuously. Healthcare systems and institutions can significantly benefit because the use of advanced technologies improves the efficiency and efficacy of healthcare. Software-defined as a medical device, is stand-alone software that is intended to be used for patients for one or more of these specific medical intended uses: - diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of a disease, any other health conditions, replacing or modifying any part of a physiological or pathological process–manage the received information from in vitro specimens derived from the human samples (body) and without principal main action of its principal intended use by pharmacological, immunological or metabolic definition. Software qualified as medical devices must comply with the general safety and performance requirements applicable to medical devices. These requirements are necessary to ensure high performance and quality and protect patients' safety. The evolution and the continuous improvement of software used in healthcare must consider the increase in regulatory requirements, which are becoming more complex in each market. The gap between these advanced technologies and the new regulations is the biggest challenge for medical device manufacturers. Regulatory requirements can be considered a market barrier, as they can delay or obstacle the device's approval. Still, they are necessary to ensure performance, quality, and safety. At the same time, they can be a business opportunity if the manufacturer can define the appropriate regulatory strategy in advance. The abstract will provide an overview of the current regulatory framework, the evolution of the international requirements, and the standards applicable to medical device software in the potential market all over the world.

Keywords: artificial intelligence, machine learning, SaMD, regulatory, clinical evaluation, classification, international requirements, MDR, 510k, PMA, IMDRF, cyber security, health care systems

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Authors: Seulki Lee, Seoung Bum Kim

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Statistical process control (SPC) is a practical and effective method for quality control. The most important and widely used technique in SPC is a control chart. The main goal of a control chart is to detect any assignable changes that affect the quality output. Most conventional control charts, such as Hotelling’s T2 charts, are commonly based on the assumption that the quality characteristics follow a multivariate normal distribution. However, in modern complicated manufacturing systems, appropriate control chart techniques that can efficiently handle the nonnormal processes are required. To overcome the shortcomings of conventional control charts for nonnormal processes, several methods have been proposed to combine statistical learning algorithms and multivariate control charts. Statistical learning-based control charts, such as support vector data description (SVDD)-based charts, k-nearest neighbors-based charts, have proven their improved performance in nonnormal situations compared to that of the T2 chart. Beside the nonnormal property, time-varying operations are also quite common in real manufacturing fields because of various factors such as product and set-point changes, seasonal variations, catalyst degradation, and sensor drifting. However, traditional control charts cannot accommodate future condition changes of the process because they are formulated based on the data information recorded in the early stage of the process. In the present paper, we propose a SVDD algorithm-based control chart, which is capable of adaptively monitoring time-varying and nonnormal processes. We reformulated the SVDD algorithm into a time-adaptive SVDD algorithm by adding a weighting factor that reflects time-varying situations. Moreover, we defined the updating region for the efficient model-updating structure of the control chart. The proposed control chart simultaneously allows efficient model updates and timely detection of out-of-control signals. The effectiveness and applicability of the proposed chart were demonstrated through experiments with the simulated data and the real data from the metal frame process in mobile device manufacturing.

Keywords: multivariate control chart, nonparametric method, support vector data description, time-varying process

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Authors: Oluwasina Folajinmi, Kate Ssamulla, Penninah Lutung, Daniel Reijer

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Background: Despite of well-verified benefits of anti-retroviral therapy (ART) in prolonging life expectancy being lost to follow-up (LTFU) presents a challenge to the success of ART programs in resource limited countries like Nigeria. In several studies of ART programs in developing countries, researchers have reported that there has been a high rate of LTFU among patients receiving care and treatment at ART treatment centers. This study seeks to determine the cause of LTFU among HIV clients. Method: A descriptive cross sectional study focused on a population of 9,280 persons living with HIV/AIDS who were enrolled in nine treatment centers in Nigeria (both pre-ART and ART patients were included). Out of the total population, 1752 (18.9%) were found to be LTFU. Of this group we randomly selected 1200 clients (68.5%) their d patients’ information was generated through a database. Data on demographics and CD4 counts, causes of LTFU were analyzed and summarized. Results: Out of 1200 LTFU clients selected, 462 (38.5%) were on ART; 341 clients (73.8%) had CD4 level < 500cell/µL and 738 (61.5%) on pre-ART had CD4 level >500/µL. In our records we found telephone number for 675 (56.1%) of these clients. 675 (56.1%) were owners of a phone. The majority of the client’s 731 (60.9%) were living at not more than 25km away from the ART center. A majority were females (926 or 77.2%) while 274 (22.8%) were male. 675 (56.1%) clients were reported traced via telephone and home address. 326 (27.2%) of clients phone numbers were not reachable; 173 (14.4%) of telephone numbers were incomplete. 71 (5.9%) had relocated due to communal crises and expert client trackers reported that some patient could not afford transportation to ART centers. Conclusion: This study shows that, low health education levels, poverty, relocations and lack of reliable phone contact were major predictors of LTFU. Periodic updates of home addresses, telephone contacts including at least two next of kin, phone text messages and home visits may improve follow up. Early and consistent tracking of missed appointments is crucial. Creation of more ART decentralized centres are needed to avoid long distances.

Keywords: anti-retroviral therapy, HIV/AIDS, predictors, lost to follow up

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Authors: David Mafullul, Jiang Lei, Edward Goacher, Jibin Francis

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PURPOSE: Timely decompressive surgery for cauda equina syndrome (CES) is dependent on efficient referral pathways for patients presenting at local primary or secondary centres to tertiary spinal centres in the United Kingdom (UK). Identifying modifiable points of delay within this process is important as minimising time between presentation and surgery may improve patient outcomes. This study aims to analyse whether adequacy of referral impacts on time to surgery in CES. MATERIALS AND METHODS: Data from all cases of confirmed CES referred to a single tertiary UK hospital between August 2017 to December 2019, via a suspected CES e-referral pathway, were obtained retrospectively. Referral adequacy was defined by the inclusion of sufficient information to determine the presence or absence of several NICE ‘red flags’. Correlation between referral adequacy and delay from referral-to-surgery was then analysed. RESULTS: In total, 118 confirmed CES cases were included. Adequate documentation for saddle anaesthesia was associated with reduced delays of more than 48 hours from referral-to-surgery [X2(1, N=116)=7.12, p=.024], an effect partly attributable to these referrals being accepted sooner [U=16.5; n1=27, n2=4, p=.029, r=.39]. Other red flags had poor association with delay. Referral adequacy was better for somatic red flags [bilateral sciatica (97.5%); severe or progressive bilateral neurological deficit of the legs (95.8%); saddle anaesthesia (91.5%)] compared to autonomic red flags [loss of anal tone (80.5%); urinary retention (79.7%); faecal incontinence or lost sensation of rectal fullness (57.6%)]. Although referral adequacy for urinary retention was 79.7%, only 47.5% of referrals documented a post-void residual numerical value. CONCLUSIONS: Adequate documentation of saddle anaesthesia in e-referrals is associated with reduced delay-to-surgery for confirmed CES, partly attributable to these referrals being accepted sooner. Other red flags had poor association with delay to surgery. Referral adequacy for autonomic red flags, including documentation for post-void residuals, has significant room for improvement.

Keywords: cauda equina, cauda equina syndrome, neurosurgery, spinal surgery, decompression, delay, referral, referral adequacy

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Authors: Adepeju Simon-Oke, Olatunji Odeyemi, Mobolanle Oniya

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Urinary tract infection has become the most common bacterial infections in humans, both at the community and hospital settings; it has been reported in all age groups and in both sexes. This study was carried out in order to determine and evaluate the prevalence, current drug susceptibility pattern of the isolated organisms and identify the associated risk factors of UTIs among the pregnant women in Akure, Ondo State, Nigeria. A cross-sectional study was conducted on the urine of pregnant women, and socio-demographic information of the women was collected. A total of 300 clean midstream urine samples were collected, and a general urine microscopic examination and culture were carried out, the Microbact identification system was used to identify gram-negative bacteria. Out of the 300 urine samples cultured, 183(61.0%) yielded significant growth of urinary pathogens while 117(39.0%) yielded either insignificant growth or no growth of any urinary pathogen. Prevalence of UTI was significantly associated with the type of toilet used, symptoms of UTI, and previous history of urinary tract infection (p<0.05). Escherichia coli 58(31.7%) was the dominant pathogen isolated, and the least isolated uropathogens were Citrobacter freudii and Providencia retgerri 2(1.1%) respectively. Gram-negative bacteria showed 77.6%, 67.9%, and 61.2% susceptibility to ciprofloxacin, augmentin, and chloramphenicol, respectively. Resistance against septrin, chloramphenicol, sparfloxacin, amoxicillin, augmentin, gentamycin, pefloxacin, trivid, and streptomycin was observed in the range of 23.1 to 70.1%. Gram-positive uropathogens isolated showed high resistance to amoxicillin (68.4%) and high susceptibility to the remaining nine antibiotics in the range 65.8% to 89.5%. This study justifies that pregnant women are at high risk of UTI. Therefore screening of pregnant women during antenatal clinics should be considered very important to avoid complications. Health education with regular antenatal and personal hygiene is recommended as precautionary measures to UTI.

Keywords: pregnant women, prevalence, risk factor, UTIs

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Authors: Thomas Ruppert, Shana Jones, J. Scott Pippin

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State and federal government agencies within the United States have recently invested substantial resources into studies of future flood risk conditions associated with climate change and sea-level rise. A review of numerous case studies has uncovered several key themes that speak to an overall incoherence within current flood risk assessment procedures in the U.S. context. First, there are substantial local differences in the quality of available information about basic infrastructure, particularly with regard to local stormwater features and essential facilities that are fundamental components of effective flood hazard planning and mitigation. Second, there can be substantial mismatch between regulatory Flood Insurance Rate Maps (FIRMs) as produced by the National Flood Insurance Program (NFIP) and other 'current condition' flood assessment approaches. This is of particular concern in areas where FIRMs already seem to underestimate extant flood risk, which can only be expected to become a greater concern if future FIRMs do not appropriately account for changing climate conditions. Moreover, while there are incentives within the NFIP’s Community Rating System (CRS) to develop enhanced assessments that include future flood risk projections from climate change, the incentive structures seem to have counterintuitive implications that would tend to promote moral hazard. In particular, a technical finding of higher future risk seems to make it easier for a community to qualify for flood insurance savings, with much of these prospective savings applied to individual properties that have the most physical risk of flooding. However, there is at least some case study evidence to indicate that recognition of these issues is prompting broader discussion about the need to move beyond FIRMs as a standalone local flood planning standard. The paper concludes with approaches for developing climate adaptation and flood resilience strategies in the U.S. that move away from the social welfare model being applied through NFIP and toward more of an informed risk approach that transfers much of the investment responsibility over to individual private property owners.

Keywords: climate change adaptation, flood risk, moral hazard, sea-level rise

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Authors: Monica Gonzalez Machorro

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Dementia is hard to diagnose because of the lack of early physical symptoms. Early dementia recognition is key to improving the living condition of patients. Speech technology is considered a valuable biomarker for this challenge. Recent works have utilized conventional acoustic features and machine learning methods to detect dementia in speech. BERT-like classifiers have reported the most promising performance. One constraint, nonetheless, is that these studies are either based on human transcripts or on transcripts produced by automatic speech recognition (ASR) systems. This research contribution is to explore a method that does not require transcriptions to detect early Alzheimer’s disease (AD) and mild cognitive impairment (MCI). This is achieved by fine-tuning a pre-trained ASR model for the downstream early AD and MCI tasks. To do so, a subset of the thoroughly studied Pitt Corpus is customized. The subset is balanced for class, age, and gender. Data processing also involves cropping the samples into 10-second segments. For comparison purposes, a baseline model is defined by training and testing a Random Forest with 20 extracted acoustic features using the librosa library implemented in Python. These are: zero-crossing rate, MFCCs, spectral bandwidth, spectral centroid, root mean square, and short-time Fourier transform. The baseline model achieved a 58% accuracy. To fine-tune HuBERT as a classifier, an average pooling strategy is employed to merge the 3D representations from audio into 2D representations, and a linear layer is added. The pre-trained model used is ‘hubert-large-ls960-ft’. Empirically, the number of epochs selected is 5, and the batch size defined is 1. Experiments show that our proposed method reaches a 69% balanced accuracy. This suggests that the linguistic and speech information encoded in the self-supervised ASR-based model is able to learn acoustic cues of AD and MCI.

Keywords: automatic speech recognition, early Alzheimer’s recognition, mild cognitive impairment, speech impairment

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Authors: Nusrat Praween, Krishna Thej Pammi Guru, Palash Kumar Basu

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Designing non-invasive biosensors for cancer diagnosis is essential for developing an affordable and specific tool to measure cancer-related exosome biomarkers. Exosomes, released by healthy as well as cancer cells, contain valuable information about the biomarkers of various diseases, including cancer. Despite the availability of various isolation techniques, ultracentrifugation is the standard technique that is being employed. Post isolation, exosomes are traditionally exposed to detergents for extracting their proteins, which can often lead to protein degradation. Further to this, it is very essential to develop a sensing platform for the quantification of clinically relevant proteins in a wider range to ensure practicality. In this study, exosomes were immobilized on the Au Screen Printed Electrode (SPE) using EDC/NHS chemistry to facilitate binding. After immobilizing the exosomes on the screen-printed electrode (SPE), we investigated the impact of the electric field by applying various voltages to induce exosome lysis and release their contents. The lysed solution was used for sensing TSG101, a crucial biomarker associated with various cancers, using both faradaic and non-faradaic electrochemical impedance spectroscopy (EIS) methods. The results of non-faradaic and faradaic EIS were comparable and showed good consistency, indicating that non-faradaic sensing can be a reliable alternative. Hence, the non-faradaic sensing technique was used for label-free quantification of the TSG101 biomarker. The results were validated using ELISA. Our electrochemical immunosensor demonstrated a consistent response of TSG101 from 125 pg/mL to 8000 pg/mL, with a detection limit of 0.125 pg/mL at room temperature. Additionally, since non-faradic sensing is label-free, the ease of usage and cost of the final sensor developed can be reduced. The proposed immunosensor is capable of detecting the TSG101 protein at low levels in healthy serum with good sensitivity and specificity, making it a promising platform for biomarker detection.

Keywords: biosensor, exosomes isolation on SPE, electric field lysis of exosome, EIS sensing of TSG101

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Authors: A. Durgadevi, S. Pushpavanam

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For the past several decades, CO2 levels have been dramatically increasing in the atmosphere due to the man-made emissions such as fossil fuel-fired power plants. With the increase in CO2 emissions, CO2 concentration in the atmosphere has increased resulting in global warming. This shows the need to study different ways to capture the emitted CO2 directly from the exhausts of power plants or atmosphere. There are several ways to remove CO2, such as absorption into a liquid solvent, adsorption into a solid, cryogenic separation, permeation through membranes and photochemical conversion. In most industries, the absorption of CO2 in chemical solvents (in absorption towers) is used for CO2 capture. In these towers, the mass transfer along with chemical reactions take place between the gas and liquid phase. This helps in the separation of CO2 from other gases. It is important to understand these processes in detail. These flow patterns are difficult to maintain in large scale industrial absorbers. So to get accurate information controlled gas-liquid absorption experiments are carried out in milli-channels in this work under controlled atmosphere. The absorption experiments of CO2 in varying concentrations of sodium hydroxide solution are carried out in T-junction glass milli-channels with a circular cross section (inner diameter of 2mm). The gas and liquid flow rates are controlled by a mass flow controller (MFC) and a Harvard syringe pump respectively. The slug flow in the channel is recorded using a camera and the videos are analysed. The gas slug of pure CO2 is found to decrease in size along the length of the channel due to absorption of gas in the liquid. This is also captured with the model developed and the mass transfer characteristics are studied. The pressure drop across the channel is determined by sum of the pressure drops from the gas slugs and the liquid plugs. A dimensionless correlation for the mass transfer coefficient is developed in terms of Sherwood number and compared with the existing correlations in the literature. They are found to be in close agreement with each other. In this case, due to the presence of chemical reaction, the enhancement of mass transfer is obtained. This is quantified with the help of an enhancement factor.

Keywords: absorption, enhancement factor, mass transfer coefficient, Sherwood number

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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Authors: N. G. I. Aroshana, S. Edirisooriya

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Construction of highway is the most emerging development tendency in Sri Lanka. With these development activities, there are a lot of environmental and social issues started. Landscape fragmentation is one of the main issues that highly effect to the environment by the construction of expressways. Sri Lankan expressway system getting effort to treat fragmented landscape by using highway crossing structures. This paper designates, a highway post construction landscape study on the effectiveness of the landscape connectivity structures to restore connectivity. Geographic Information Systems (GIS), least cost path tool has been used in the selected two plots; 25km alone the expressway to identify animal crossing paths. Animal accident data use as measure for determining the most contributed plot for landscape connectivity. Number of patches, Mean patch size, Class area use as a parameter to determine the most effective land use class to reestablish the landscape connectivity. The findings of the research express scrub, grass and marsh were the most positively affected land use typologies for increase the landscape connectivity. It represents the growth increased by 8% within the 12 years of time. From the least cost analysis within the plot one, 28.5% of total animal crossing structures are within the high resistance land use classes. Southern expressway used reinforced compressed earth technologies for construction. It has been controlled the growth of the climax community. According to all findings, it could assume that involvement of the landscape crossing structures contributes to re-establish connectivity, but it is not enough to restore the majority of disturbance performed by the expressway. Connectivity measures used within the study can use as a tool for re-evaluate future involvement of highway crossing structures. Proper placement of the highway crossing structures leads to increase the rate of connectivity. The study recommends that monitoring the all stages (preconstruction, construction and post construction) of the project and preliminary design, and the involvement of the research applied connectivity assessment strategies helps to overcome the complication regarding the re-establishment of landscape connectivity using the highway crossing structures that facilitate the growth of flora and fauna.

Keywords: landscape fragmentation, least cost path, land use analysis, landscape connectivity structures

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Authors: Zuhal Mohammed, Khalid Siddig, Harald Grethe

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Vocational training (VT) has been identified as a potential engine for achieving economic and social development, particularly in developing countries, while during the last two decades it is deemed as an essential determinant of human capital accumulation. Furthermore, it has a crucial role in reducing inequality, wage gaps and unemployment and in promoting skill decomposition. Government plays an important role in the human capital formulation by providing finance for education. In some countries, a large portion of the public educational investment is devoted to academic education (primary, secondary and tertiary). This is reflected in disproportionately increasing investment in various education sectors other than vocational education and VT. Nevertheless, the finance of VT system is not likely to increase or even remain at its existing level. This paper conducts an in-depth analysis to quantify the impacts of various options for expanding the public expenditure on education as well as vocational training in the Sudan. The study uses a recursive dynamic CGE modelling framework that accommodates VT and allows depicting the impact of various policies targeting the vocational training system with special focus on the agricultural sector. This allows for depicting the potential effects of various resource allocation policies not only among education versus non-education sectors, but also between the various types of education and training. Moreover, the study assesses the role of VT system in the economy through its influence on workers’ skill improvement and their movement across sectors. The results show that an increase in the public educational investment will lead to decrease the supply of low and high educated workers as results of increasing the school participation of the students in the short run. While in the medium to long run, this measure guides to increase the productivity of the labour and thus the growth rate of the gross domestic product (GDP). Therefore, the findings of the study provide Sudanese policymakers with needed information to help to adopt measures to reduce unemployment, enhance workers’ skill and ultimately improve livelihoods.

Keywords: vocational training, recursive dynamic CGE, skill level, labour market, economic growth, Sudan

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Authors: Ali Ahmadi, Maryam Abbasi, Mohammad Mehdi Parsaei

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Background: Stress in the workplace today is one of the most important public health concerns and a serious threat to the health of the workforce worldwide. Occupational stress can cause occupational events and reduce quality of life. As a result, it has a very undesirable impact on the performance of organizations, companies, and their human resources. This study aimed to evaluate the relationship between job stress dimensions and occupational accidents in industrial factories in Southwest Iran. Materials and Methods: This cross-sectional study was conducted among 200 workers in the summer of 2023 in the Southwest of Iran. To select participants, we used a convenience sampling method. The research tools in this study were the Health and Safety Executive (HSE) stress questionnaire with 35 questions and 7 dimensions and demographic information. A high score on this questionnaire indicates that there is low job stress and pressure. All workers completed the informed consent form. Univariate analysis was performed using chi-square and T-test. Multiple regression analysis was used to estimate the odds ratios (OR) and 95% confidence interval (CI) for the association of stress-related factors with job accidents in participants. Stata 14.0 software was used for analysis. Results: The mean age of the participants was 39.81(6.36) years. The prevalence of job accidents was 28.0% (95%CI: 21.0, 34.0). Based on the results of the multiple logistic regression with the adjustment of the effect of the confounding variables, one increase in the score of the demand dimension had a protective impact on the risk of job accidents(aOR=0.91,95%CI:0.85-0.95). Additionally, an increase in one of the scores of the managerial support (aOR=0.89, 95% CI: 0.83-0.95) and peer support (aOR=0.76, 95%CI: 0.67-87) dimensions was associated with a lower number of job accidents. Among dimensions, an increase in the score of relationship (aOR=0.89, 95%CI: 0.80-0.98) and change (aOR=0.86, 95%CI: 0.74-0.96) reduced the odds of the accident's occurrence among the workers by 11% and 16%, respectively. However, there was no significant association between role and control dimensions and the job accident (p>0.05). Conclusions: The results show that the prevalence of job accidents was alarmingly high. Our results suggested that an increase in scores of dimensions HSE questioners is significantly associated with a decrease the accident occurrence in the workplace. Therefore, planning to address stressful factors in the workplace seems necessary to prevent occupational accidents.

Keywords: HSE, Iran, job stress occupational accident, safety, occupational health

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Authors: Fatemeh Dehghan Khangahi, Hakan Gunes

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Transforming a public necessity into a commercial commodity becomes more and more evident as time goes on, and it is one of the issues of water shortage. Development projects of countries, consume the water and waterbeds in various forms, ignoring the concepts such as sustainability and the negative effects they place on the environment, pollute and change the ways of waterways. Throughout these processes, the water basins and all the vital environments sometimes can suffer damage to the irreparable level. In this context, the issue of Lake Urmia that is located in the North West of Iran left alone by drought, has been researched. The lake, which is on the list of UNESCO's biosphere reserves, is now exposed to the danger of desiccation. If the desiccation is fully realized, more than 5.000.000 people that they are living around the lake, will have to migrate as a result of negative living conditions. As a matter of fact, along with the recent years of increasing drought level, regional migrations have begun. In addition to migration issues, it is also necessary to specify the negative effects on human and all-round’s life that depend on the formation of salt storms, mixing of salt into the air and soil, which threaten human health seriously because the lake is salty. The main aim of this work is to raise national and international awareness of this problem, which is an environment and a human tragedy at the same time. This research has two basic questions: 1) In the case of Lake Urmia, what are environmental problems and how they have emerged and what is the role of governments? 2) What is the social consequence of this problem in relation to the first question? In response, after the literature search, having a comparative view of the situation of the Aral Sea and the Great Salt Lake (Utah, USA), which involved the two major international examples. The first, one is related to the terms of population and migration, the second is about biological properties. Then, data and status information that provided after 3 years area research has been evaluated. Towards the end, with the support of qualitative and quantitative methods, the study of social mobilization in the region has been carried out. An example of it is using the public space of TRAXTOR matches like a protests area.

Keywords: environment problems, water, social mobilization, Lake Urmia, migration

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Authors: M. Y. Abubakar, Ipinjolu J. K., Yuzine B. Esa, Magawata I., Hassan W. A., Turaki A. A.

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Catfish (Heterobranchus spp.) is a major freshwater fish that are widely distributed in Nigeria waters and are gaining rapid aquaculture expansion. However, indiscriminate artificial crossbreeding of the species with others poses a threat to their biodiversity. There is a paucity of information about the genetic variability, hence this insight on the genetic variability is badly needed, not only for the species conservation but for aquaculture expansion. In this study, we tested the level of Genetic diversity, population differentiation and phylogenetic relationship analysis on 35 individuals of two populations of Heterobranchus bidorsalis and 29 individuals of three populations of Heterobranchus longifilis using the mitochondrial cytochrome c oxidase subunit I (mtDNA COI) gene sequence. Nucleotide sequences of 650 bp fragment of the COI gene of the two species were compared. In the whole 4 and 5 haplotypes were distinguished in the populations of H. bidorsalis & H. longifilis with accession numbers (MG334168 - MG334171 & MG334172 to MG334176) respectively. Haplotypes diversity indices revealed a range of 0.59 ± 0.08 to 0.57 ± 0.09 in H. bidorsalis and 0.000 to 0.001051 ± 0.000945 in H. longifilis population, respectively. Analysis of molecular variance (AMOVA) revealed no significant variation among H. bidorsalis population of the Niger & Benue Rivers, detected significant genetic variation was between the Rivers of Niger, Kaduna and Benue population of H. longifilis. Two main clades were recovered, showing a clear separation between H. bidorsalis and H. longifilis in the phylogenetic tree. The mtDNA COI genes studied revealed high gene flow between populations with no distinct genetic differentiation between the populations as measured by the fixation index (FST) statistic. However, a proportion of population-specific haplotypes was observed in the two species studied, suggesting a substantial degree of genetic distinctiveness for each of the population investigated. These findings present the description of the species character and accessions of the fish’s genetic resources, through gene sequence submitted in Genetic database. The data will help to protect their valuable wild resource and contribute to their recovery and selective breeding in Nigeria.

Keywords: AMOVA, genetic diversity, Heterobranchus spp., mtDNA COI, phylogenetic tree

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Authors: Rofida Gamal, Mostafa Mohammed, Mariam Adel, Marwa Gamal, Marwa kamal, Ayat Saber, Maha Mamdouh, Amira Emad, Mai Ramadan

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Lynch Syndrome is an inherited genetic condition associated with an increased risk of colorectal and other cancers. Detecting Lynch Syndrome in individuals is crucial for early intervention and preventive measures. This study proposes a computational pipeline for Lynch Syndrome detection by integrating alignment, variant calling, and annotation. The pipeline leverages popular tools such as FastQC, Trimmomatic, BWA, bcftools, and ANNOVAR to process the input FASTQ file, perform quality trimming, align reads to the reference genome, call variants, and annotate them. It is believed that the computational pipeline was applied to a dataset of Lynch Syndrome cases, and its performance was evaluated. It is believed that the quality check step ensured the integrity of the sequencing data, while the trimming process is thought to have removed low-quality bases and adaptors. In the alignment step, it is believed that the reads were accurately mapped to the reference genome, and the subsequent variant calling step is believed to have identified potential genetic variants. The annotation step is believed to have provided functional insights into the detected variants, including their effects on known Lynch Syndrome-associated genes. The results obtained from the pipeline revealed Lynch Syndrome-related positions in the genome, providing valuable information for further investigation and clinical decision-making. The pipeline's effectiveness was demonstrated through its ability to streamline the analysis workflow and identify potential genetic markers associated with Lynch Syndrome. It is believed that the computational pipeline presents a comprehensive and efficient approach to Lynch Syndrome detection, contributing to early diagnosis and intervention. The modularity and flexibility of the pipeline are believed to enable customization and adaptation to various datasets and research settings. Further optimization and validation are believed to be necessary to enhance performance and applicability across diverse populations.

Keywords: Lynch Syndrome, computational pipeline, alignment, variant calling, annotation, genetic markers

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Authors: H. Tavakoli, S. S. Mohtasebi, R. Alimardani, R. Gebbers

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Nitrogen (N) is one of the most important agricultural inputs affecting crop growth, yield and quality in rain-fed cereal production. N demand of crops varies spatially across fields due to spatial differences in soil conditions. In addition, the response of a crop to the fertilizer applications is heavily reliant on plant available water. Matching N supply to water availability is thus essential to achieve an optimal crop response. The objective of this study was to determine effect of drought stress on estimation of nitrogen status of winter wheat by some vegetation indices. During the 2012 growing season, a field experiment was conducted at the Bundessortenamt (German Plant Variety Office) Marquardt experimental station which is located in the village of Marquardt about 5 km northwest of Potsdam, Germany (52°27' N, 12°57' E). The experiment was designed as a randomized split block design with two replications. Treatments consisted of four N fertilization rates (0, 60, 120 and 240 kg N ha-1, in total) and two water regimes (irrigated (Irr) and non-irrigated (NIrr)) in total of 16 plots with dimension of 4.5 × 9.0 m. The indices were calculated using readings of a spectroradiometer made of tec5 components. The main parts were two “Zeiss MMS1 nir enh” diode-array sensors with a nominal rage of 300 to 1150 nm with less than 10 nm resolutions and an effective range of 400 to 1000 nm. The following vegetation indices were calculated: NDVI, GNDVI, SR, MSR, NDRE, RDVI, REIP, SAVI, OSAVI, MSAVI, and PRI. All the experiments were conducted during the growing season in different plant growth stages including: stem elongation (BBCH=32-41), booting stage (BBCH=43), inflorescence emergence, heading (BBCH=56-58), flowering (BBCH=65-69), and development of fruit (BBCH=71). According to the results obtained, among the indices, NDRE and REIP were less affected by drought stress and can provide reliable wheat nitrogen status information, regardless of water status of the plant. They also showed strong relations with nitrogen status of winter wheat.

Keywords: nitrogen status, drought stress, vegetation indices, precision agriculture

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Authors: Cláudia Alcoforado, Anabela Ribeiro

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This paper is part of an ongoing PhD thesis. It seeks to develop a model to identify the spatial failures of the public transportation supply. In the construction of the model, it also seeks to detect the social needs arising from the disadvantage in transport. The case study is carried out for the Brazilian city of Recife. Currently, Recife has a population density of 7,039.64 inhabitants per km². Unfortunately, only 46.9% of urban households on public roads have adequate urbanization. Allied to this reality, the trend of the occupation of the poorest population is that of the peripheries, a fact that has been consolidated in Brazil and Latin America, thus burdening the families' income, since the greater the distances covered for the basic activities and consequently also the transport costs. In this way, there have been great impacts caused by the supply of public transportation to locations with low demand or lack of urban infrastructure. The model under construction uses methods such as Currie’s Gap Assessment associated with the London’s Public Transport Access Level, and the Public Transport Accessibility Index developed by Saghapour. It is intended to present the stage of the thesis with the spatial/need gaps of the neighborhoods of Recife already detected. The benefits of the geographic information system are used in this paper. It should be noted that gaps are determined from the transport supply indices. In this case, considering the presence of walking catchment areas. Still in relation to the detection of gaps, the relevant demand index is also determined. This, in turn, is calculated through indicators that reflect social needs. With the use of the smaller Brazilian geographical unit, the census sector, the model with the inclusion of population density in the study areas should present more consolidated results. Based on the results achieved, an analysis of transportation disadvantage will be carried out as a factor of social exclusion in the study area. It is anticipated that the results obtained up to the present moment, already indicate a strong trend of public transportation in areas of higher income classes, leading to the understanding that the most disadvantaged population migrates to those neighborhoods in search of employment.

Keywords: gap assessment, public transport supply, social exclusion, spatial gaps

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Authors: Antonio Lopez-Villegas, Rafael Bautista-Mesa, Emilio Robles-Musso, Daniel Catalan-Matamoros, Cesar Leal-Costa

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Objectives: The purpose of this trial was to evaluate the burden borne by and the costs to informal caregivers of users with telemonitoring of pacemakers. Methods: This is a controlled, non-randomised clinical trial, with data collected from informal caregivers, five years after implantation of pacemakers. The Spanish version of the Survey on Disabilities, Personal Autonomy, and Dependency Situations was used to get information on clinical and social characteristics, levels of professionalism, duration and types of care, difficulties in providing care, health status, economic and job aspects, impact on the family or leisure due to informal caregiving for patients with pacemakers. Results: After five years of follow-up, 55 users with pacemakers finished the study. Of which, 50 were helped by a caregiver, 18 were included in the telemonitoring group (TM) and 32 in the conventional follow-up group (HM). Overall, females represented 96.0% of the informal caregivers (88.89% in TM and 100.0% in HM group). The mean ages were 63.17 ± 15.92 and 63.13 ± 14.56 years, respectively (p = 0.83) in the groups. The majority (88.0%) of the caregivers declared that they had to provide their services between 6 and 7 days per week (83.33% in TM group versus 90.63% in HM group), without significant differences between both groups. The costs related to care provided by the informal caregivers were 47.04% higher in the conventional follow-up group than in the TM group. Conclusions: The results of this trial confirm that there were no significant differences between the informal caregivers regarding to baseline characteristics, workload and time worked in both groups of follow-up. The costs incurred by the informal caregivers providing care for users with pacemakers included in telemonitoring group are significantly lower than those in the conventional follow-up group. Trial registration: ClinicalTrials.gov NCT02234245. Funding: The PONIENTE study, has been funded by the General Secretariat for Research, Development and Innovation, Regional Government of Andalusia (Spain), project reference number PI/0256/2017, under the research call 'Development and Innovation Projects in the Field of Biomedicine and Health Sciences', 2017.

Keywords: costs, disease burden, informal caregiving, pacemaker follow-up, remote monitoring, telemedicine

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Authors: Chin-Hsiang Lo, Wey Chia, Shih-Tien Hsu

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Introduction: Since 2016, the annual number of passengers on commercial flights at Taoyuan International Airport (TIA) has been ~40 million. Due to the outbreak and spread of COVID-19, the number of international flights sharply diminished in recent years. However, TIA is located at an East-Asian flight transportation junction; thus, many commercial and cargo flights continue service. When severe medical events happen on a commercial airliner, the decision to divert or not is based on consideration of both medical and operational issues. This study discusses the events related to the diversion of airplanes or reentry after taxiing for medical emergencies at Taoyuan International Airport. Background: We analyzed emergency medical records from the medical clinic of TIA from January 1, 2017, to December 31, 2022, for patients who needed emergency medical services but were unable to reach the airport clinic by themselves. We also collected data for patients treated after diversion from other airports or reentry after taxiing due to medical emergencies. Information such as when and where the event occurred, chief signs and symptoms, the tentative diagnosis (using the ICD-9-CM), management, and the sociodemographic features of the passengers were extracted from the medical records. Summary of Cases: TIA handled approximately 152 million passengers and 1,093,762 flights during the study period; a total of 2,804 emergencies occurred during this time period. Thirty-three medical emergencies warranted diversion (21 cases) or reentry (12 cases); 13 cases were diverted from Asia-Pacific flights and five from Asia-North America flights. The age of the passengers with diversion emergencies ranged from 2–85 years (mean, 46±20-years-old). Twenty-seven patients were transported to an emergency department, and four patients died. For all cases of diversion or reentry, the most common diagnoses were neurogenic problems (42.4%), Out-of-hospital cardiac arrest (OHCA) (15.2%), and cardiovascular problems (12.1%). Discussion: Most aircraft diversions were related to syncope, seizure, and OHCA. The decision to divert depends on medical and operational considerations. Emergency conditions are often serious; thus, improvement of the effectiveness of cooperation between airlines and medical teams remains a challenge.

Keywords: diversion, syncope, seizure, OHCA

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Authors: Ashenafi Ayele, Shewit Haftu, Tesfalem Araya

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Background: “Post-psychotic depression”, “post schizophrenic depression”, and “secondary depression” have been used to describe the occurrence of depressive symptoms during the chronic phase of schizophrenia. Post-psychotic depression is the most common cause of death due to suicide in schizophrenia patients. Overall lifetime risk for patients with schizophrenia is 50% for suicide attempts and 9-13% lifetime risk for completed suicide and also it is associated with poor prognosis and poor quality of life. Objective: To assess determinant of post psychotic depression in schizophrenia patients ACSH and Mekelle General Hospital, Tigray Ethiopia 2019. Methods: An institutional based unmatched case control study was conducted among 69 cases and 138 controls with the ratio of case to control 1 ratio 2. The sample is calculated using epi-info 3.1 to assess the determinant factors of post-psychotic depression in schizophrenia patients. The cases were schizophrenia patients who have been diagnosed at least for more than one-year stable for two months, and the controls are any patients who are diagnosed as schizophrenia patients. Study subjects were selected using a consecutive sampling technique. The Calgary depression scale for schizophrenia self-administered questionnaire was used. Before the interview, it was assessed the client’s capacity to give intended information using a scale called the University of California, San Diego Brief Assessment of Capacity to Consent (UBACC). Bivariant and multiple Logistic regression analysis was performed to determine between the independent and dependent variables. The significant independent predictor was declared at 95% confidence interval and P-value of less than 0.05. Result: Females were affected by post psychotic depression with the (AOR=2.01, 95%CI: 1.003- 4.012, P= 0.49).Patients who have mild form of positive symptom of schizophrenia affected by post psychotic depression with (AOR =4.05, 95%CI: 1.888- 8.7.8, P=0001).Patients who have minimal form of negative symptom of schizophrenia are affected by post psychotic depression with (AOR =4.23, 95%CI: 1.081-17.092, P=.038). Conclusion: In this study, sex (female) and presence of positive and negative symptoms of schizophrenia were significantly associated. It is recommended that the post psychotic depression should be assessed in every schizophrenia patient to decrease the severity of illness, and to improve patient’s quality of life.

Keywords: determinants, post-psychotic depression, Mekelle city

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Authors: Ferran Paulí Pla, Pere Palacín Farré, Albert Fornells Herrera, Pol Toldrà Fernández

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Poor image acquisition is limiting the promising growth of industrial vision in food control. In recent years, the food industry has witnessed a significant increase in the implementation of automation in quality control through artificial vision, a trend that continues to grow. During the packaging process, some defects may appear, compromising the proper sealing of the products and diminishing their shelf life, sanitary conditions and overall properties. While failure to detect a defective product leads to major losses, food producers also aim to minimize over-rejection to avoid unnecessary waste. Thus, accuracy in the evaluation of the products is crucial, and, given the large production volumes, even small improvements have a significant impact. Recently, efforts have been focused on maximizing the performance of classification neural networks; nevertheless, their performance is limited by the quality of the input data. Monochrome linear backlight systems are most commonly used for online inspections of food packaging thermo-sealing zones. These simple acquisition systems fit the high cadence of the production lines imposed by the market demand. Nevertheless, they provide a limited amount of data, which negatively impacts classification algorithm training. A desired situation would be one where data quality is maximized in terms of obtaining the key information to detect defects while maintaining a fast working pace. This work presents a backlight hyperspectral imaging system designed and implemented replicating an industrial environment to better understand the relationship between visual data quality and spectral illumination range for a variety of packed food products. Furthermore, results led to the identification of advantageous spectral bands that significantly enhance image quality, providing clearer detection of defects.

Keywords: artificial vision, food packaging, hyperspectral imaging, image acquisition, quality control

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Authors: Layal Mansour

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The aim of this paper is to identify whether oil price volatility or geopolitical risks can predict future financial stress periods or economic recessions in Kuwait. We construct the first Financial Stress Index for Kuwait (FSIK) that includes informative vulnerable indicators of the main financial sectors: the banking sector, the equities market, and the foreign exchange market. The study covers the period from 2000 to 2020, so it includes the two recent most devastating world economic crises with oil price fluctuation: the Covid-19 pandemic crisis and Ukraine-Russia War. All data are taken by the central bank of Kuwait, the World Bank, IMF, DataStream, and from Federal Reserve System St Louis. The variables are computed as the percentage growth rate, then standardized and aggregated into one index using the variance equal weights method, the most frequently used in the literature. The graphical FSIK analysis provides detailed information (by dates) to policymakers on how internal financial stability depends on internal policy and events such as government elections or resignation. It also shows how monetary authorities or internal policymakers’ decisions to relieve personal loans or increase/decrease the public budget trigger internal financial instability. The empirical analysis under vector autoregression (VAR) models shows the dynamic causal relationship between the oil price fluctuation and the Kuwaiti economy, which relies heavily on the oil price. Similarly, using vector autoregression (VAR) models to assess the impact of the global geopolitical risks on Kuwaiti financial stability, results reveal whether Kuwait is confronted with or sheltered from geopolitical risks. The Financial Stress Index serves as a guide for macroprudential regulators in order to understand the weakness of the overall Kuwaiti financial market and economy regardless of the Kuwaiti dinar strength and exchange rate stability. It helps policymakers predict future stress periods and, thus, address alternative cushions to confront future possible financial threats.

Keywords: Kuwait, financial stress index, causality test, VAR, oil price, geopolitical risks

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Authors: Md Mizanur Rahman, Lotanna Micah Nneji, Adeola C. Adeniyi, Edem Archibong Eniang, Abiodun B. Onadeko, Felista Kasyoka Kilunda, Babatunde E. Adedeji, Ifeanyi C. Nneji, Adiaha A. A. Ugwumba, Jie-Qiong Jin, Min-Sheng Peng, Caroline Olory, Nsikan Eninekit, Jing Che

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Nigeria contains a number of forest habitats that believed to host highly rich amphibian diversity. However, a dearth of herpetological studies has restricted information on the amphibian diversity in Nigeria. To cover the gap of knowledge, this study focused field surveys on relatively less studied forests–Afi Forest Reserve and Ikpan forest ecosystem. The goal of this study is to make a checklist and to investigate the habitat preferences of amphibians in these two forests. The study areas were surveyed between August 2018 and July 2019 following visual and acoustic methods. Individuals were identified using the morphological and molecular (16S ribosomal RNA) approach. Literature searches were conducted to document additional species that were not encountered during the current field surveys. Using the observational records and arrays of diversity indices, the patterns of species richness and abundance across habitat types were evaluated. Voucher specimens and tissue samples were deposited in the museums of the Department of Zoology, University of Ibadan Nigeria, and the remainder at the Kunming Institute of Zoology (KIZ), Chinese Academy of Sciences, Kunming, China. The result of this study revealed the presence of 30 and 31 amphibian species from the Afi Forest Reserve and the Ikpan Forest Ecosystem, respectively. There were two unidentified species from AFR and one from IFE. In total, 324 individuals of amphibian species were observed from the two study areas. Forest and swamps showed high species diversity and richness than the agricultural field and savannah. Savannah and agricultural fields had the highest similarity in the species composition. Given the increased human disturbances and consequent threats to these forests, this study offers recommendations for the initiation of conservation plans immediately.

Keywords: biodiversity, conservation, cryptic species, ecology, integrated taxonomy, species inventory

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