Search results for: causal inference

Authors: Erika Takidah, Salina Kassim

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Digital transformation has accelerated in the new millennium. It is reshaping the financial services industry from a traditional system to financial technology. Moreover, the number of financial inclusion rates in Indonesia is less than 60%. An innovative model needed to elucidate this national problem. On the other hand, the Islamic financial service industry and financial technology grow fast as a new aspire in economic development. An Islamic bank, takaful, Islamic microfinance, Islamic financial technology and Islamic social finance institution could collaborate to intensify the financial inclusion number in Indonesia. The primary motive of this paper is to examine the strategy of collaboration-based Islamic financial services to enhance financial inclusion in Indonesia, particularly facing the digital era. The fundamental findings for the main problems are the foundations and key ecosystems aspect involved in the development of collaboration-based Islamic financial services. By using the Interpretive Structural Model (ISM) approach, the core problems faced in the development of the models have lacked policy instruments guarding the collaboration-based Islamic financial services with fintech work process and availability of human resources for fintech. The core strategies or foundations that are needed in the framework of collaboration-based Islamic financial services are the ability to manage and analyze data in the big data era. For the aspects of the Ecosystem or actors involved in the development of this model, the important actor is government or regulator, educational institutions, and also existing industries (Islamic financial services). The outcome of the study designates that strategy collaboration of Islamic financial services institution supported by robust technology, a legal and regulatory commitment of the regulators and policymakers of the Islamic financial institutions, extensive public awareness of financial inclusion in Indonesia. The study limited itself to realize financial inclusion, particularly in Islamic finance development in Indonesia. The study will have an inference for the concerned professional bodies, regulators, policymakers, stakeholders, and practitioners of Islamic financial service institutions.

Keywords: collaboration, financial inclusion, Islamic financial services, Islamic fintech

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Authors: Hung-Sheng Lin, Cheng-Hsuan Li

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Over the past few years, kernel-based algorithms have been widely used to extend some linear feature extraction methods such as principal component analysis (PCA), linear discriminate analysis (LDA), and nonparametric weighted feature extraction (NWFE) to their nonlinear versions, kernel principal component analysis (KPCA), generalized discriminate analysis (GDA), and kernel nonparametric weighted feature extraction (KNWFE), respectively. These nonlinear feature extraction methods can detect nonlinear directions with the largest nonlinear variance or the largest class separability based on the given kernel function. Moreover, they have been applied to improve the target detection or the image classification of hyperspectral images. The double nearest proportion feature extraction (DNP) can effectively reduce the overlap effect and have good performance in hyperspectral image classification. The DNP structure is an extension of the k-nearest neighbor technique. For each sample, there are two corresponding nearest proportions of samples, the self-class nearest proportion and the other-class nearest proportion. The term “nearest proportion” used here consider both the local information and other more global information. With these settings, the effect of the overlap between the sample distributions can be reduced. Usually, the maximum likelihood estimator and the related unbiased estimator are not ideal estimators in high dimensional inference problems, particularly in small data-size situation. Hence, an improved estimator by shrinkage estimation (regularization) is proposed. Based on the DNP structure, LDA is included as a special case. In this paper, the kernel method is applied to extend DNP to kernel-based DNP (KDNP). In addition to the advantages of DNP, KDNP surpasses DNP in the experimental results. According to the experiments on the real hyperspectral image data sets, the classification performance of KDNP is better than that of PCA, LDA, NWFE, and their kernel versions, KPCA, GDA, and KNWFE.

Keywords: feature extraction, kernel method, double nearest proportion feature extraction, kernel double nearest feature extraction

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Authors: Debit Datta, Jeffrey J. Coleman, Scott A. Enebak, Lori G. Eckhardt

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Loblolly pine (Pinus taeda) is a leading productive timber species in the southeastern USA. Over the past three years, an emerging threat is expressed by successive needle defoliation followed by stunted growth and tree mortality in loblolly pine plantations. Considering economic significance, it has now become a rising concern among landowners, forest managers, and forest health state cooperators. However, the symptoms of the disease were perplexed somewhat with root disease(s) and recurrently attributed to invasive Phytophthora species due to the similarity of disease nature and devastation. Therefore, the study investigated the potential causal agent of this disease and characterized the fungi associated with loblolly pine needle defoliation in the southeastern USA. Besides, 70 trees were selected at seven long-term monitoring plots at Chatom, Alabama, to monitor and record the annual disease incidence and severity. Based on colony morphology and ITS-rDNA sequence data, a total of 28 species of fungi representing 17 families have been recovered from diseased loblolly pine needles. The native brown-spot pathogen, Lecanosticta acicola, was the species most frequently recovered from unhealthy loblolly pine needles in combination with some other common needle cast and rust pathogen(s). Identification was confirmed using morphological similarity and amplification of translation elongation factor 1-alpha gene region of interest. Tagged trees were consistently found chlorotic and defoliated from 2019 to 2020. The current emergence of the brown-spot pathogen causing loblolly pine mortality necessitates the investigation of the role of changing climatic conditions, which might be associated with increased pathogen pressure to loblolly pines in the southeastern USA.

Keywords: brown-spot needle blight, loblolly pine, needle defoliation, plantation forestry

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Authors: Gayathri Nagarajan, L. D. Dhinesh Babu

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Health care is one of the prominent industries that generate voluminous data thereby finding the need of machine learning techniques with big data solutions for efficient processing and prediction. Missing data, incomplete data, real time streaming data, sensitive data, privacy, heterogeneity are few of the common challenges to be addressed for efficient processing and mining of health care data. In comparison with other applications, accuracy and fast processing are of higher importance for health care applications as they are related to the human life directly. Though there are many machine learning techniques and big data solutions used for efficient processing and prediction in health care data, different techniques and different frameworks are proved to be effective for different applications largely depending on the characteristics of the datasets. In this paper, we present a framework that uses ensemble machine learning technique gradient boosted trees for data classification in health care big data. The framework is built on Spark platform which is fast in comparison with other traditional frameworks. Unlike other works that focus on a single technique, our work presents a comparison of six different machine learning techniques along with gradient boosted trees on datasets of different characteristics. Five benchmark health care datasets are considered for experimentation, and the results of different machine learning techniques are discussed in comparison with gradient boosted trees. The metric chosen for comparison is misclassification error rate and the run time of the algorithms. The goal of this paper is to i) Compare the performance of gradient boosted trees with other machine learning techniques in Spark platform specifically for health care big data and ii) Discuss the results from the experiments conducted on datasets of different characteristics thereby drawing inference and conclusion. The experimental results show that the accuracy is largely dependent on the characteristics of the datasets for other machine learning techniques whereas gradient boosting trees yields reasonably stable results in terms of accuracy without largely depending on the dataset characteristics.

Keywords: big data analytics, ensemble machine learning, gradient boosted trees, Spark platform

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Authors: Iva Trako, Maris Micaela Sviatschi, Guadalupe Kavanaugh

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Domestic violence is a major concern in developing countries, with important social, economic and health consequences. However, institutions do not usually address the problems facing women or ethnic and religious minorities. For example, the police do very little to stop domestic violence in rural areas of developing countries. This paper exploits the introduction of women’s justice centers (WJCs) in Peru to provide causal estimates on the effects of improving access to justice for women and children. These centers offer a new integrated public service model for women by including medical, psychological and legal support in cases of violence against women. Our empirical approach uses a difference in difference estimation exploiting variation over time and space in the opening of WJC together with province-by-year fixed effects. Exploiting administrative data from health providers and district attorney offices, we find that after the opening of these centers, there are important improvements on women's welfare: a large reduction in femicides and female hospitalizations for assault. Moreover, using geo-coded household surveys we find evidence that the existence of these services reduces domestic violence, improves women's health, increases women's threat points and, therefore, lead to household decisions that are more aligned with their interests. Using administrative data on the universe of schools, we find large gains on human capital for their children: affected children are more likely to enroll, attend school and have better grades in national exams, instead of working for the family. In sum, the evidence in this paper shows that providing access to justice for women can be a powerful tool to reduce domestic violence and increase education of children, suggesting a positive inter-generational benefit.

Keywords: access to justice, domestic violence, education, household bargaining

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Authors: Mohammadreza Hajialigol, Nargues Falahi Charkhabi, Fatemeh Shahryari, Saadat Sarikhani

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BACKGROUND AND OBJECTIVES Iran is the third producer of Persian walnut worldwide. However, its walnut trees have been under threat from decline during last decade. Walnut canker caused by B. nigrifluens and B. rubrifaciens was recorded in multiple regions of Iran. Furthermore, Brenneria rosae subsp. rosae and Gibbsiella quercinecans were recently recognized as responsible for walnut decline in northwestern Iran. This study aimed to identify the causal agent of walnut decline in Kermanshah and Isfahan. MATERIAL AND METHODS Symptomatic samples were collected from affected walnut trees of Kermanshah and Isfahan provinces. The pathogenicity of strains was proved on immature walnut fruits cv. ‘Hartley’ and young green twigs of two-year-old walnut seedling cv. ‘Chandler’. Pathogenic strains were subjected to conventional phenotypic tests. 16S rRNA, gyrB, and infB genes were partially amplified and sequenced. RESULTS Irregular longitudinal cankers and dark lesions were observed in the outer and inner bark, respectively. Twenty-four strains were isolated on EMB-agar media. Fourteen strains were able to cause necrosis and a dark-colored region in the mesocarp and on young green twigs around the inoculation site 14 and 30 days post-inoculation, respectively. Strains were able to hydrolyze Tween 20, Tween 80, gelatin and esculin, however, did not produce indole or urease. Pairwise comparison, the 16S rRNA gene nucleotide sequences of strain I2 were 100% identical with those of Rahnella victoriana FRB 225T. Moreover, a phylogenetic tree reconstructed based on the concatenated sequences of two housekeeping gene fragments, gyrB (601 bp) and infB (615 bp), revealed that the strains I2, I5, and KE6 were clustered with R. victoriana FRB 225T. CONCLUSION To the best of our knowledge, this is the first report of R. victoriana in association with walnut decline. This result is necessary to find resistant genotypes.

Keywords: emerging pathogens, Iran, juglans regia, MLSA

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Authors: Kiran Nawaz, Waheed Anwar, Sehrish Iftikhar, Muhammad Nasir Subhani, Ahmad Ali Shahid

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Plant growth promoting rhizobacteria (PGPR) have been extensively studied and applied for the biocontrol of many soilborne diseases. These rhizobacteria are very efficient against root rot and many other foliar diseases associated with solanaceous plants. These bacteria may inhibit the growth of various pathogens through direct inhibition of target pathogens or indirectly by the initiation of systemic resistance (ISR) which is active all over the complete plant. In the present study, 20 different rhizobacterial isolates were recovered from the root zone of healthy chili plants. All soil samples were collected from various chili-growing areas in Punjab. All isolated rhizobacteria species were evaluated in vitro and in vivo against Phytophthora capsici. Different species of Bacillus and Pseudomonas were tested for the antifungal activity against P. capsici the causal organism of Root rot disease in different crops together with chili. Dual culture and distance culture bioassay were carried out to study the antifungal potential of volatile and diffusible metabolites secreted from rhizobacteria. After seven days of incubation at 22°C, growth inhibition rate was recorded. Growth inhibition rate depended greatly on the tested bacteria and screening methods used. For diffusible metabolites, inhibition rate was 35-62% and 20-45% for volatile metabolites. The screening assay for plant growth promoting and disease inhibition potential of chili associated PGPR indicated 42-100% reduction in disease severity and considerable enhancement in roots fresh weight by 55-87%, aerial parts fresh weight by 35-65% and plant height by 65-76% as compared to untreated control and pathogen-inoculated plants. Pseudomonas flourescene, B. thuringiensis, and B. subtilis were found to be the most efficient isolates in inhibiting P. capsici radial growth, increase plant growth and suppress disease severity.

Keywords: rhizobacteria, chili, phytophthora, root rot

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Authors: Oscar E. Cariceo, Claudia V. Casal

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Machine learning offers a set of techniques to promote social work interventions and can lead to support decisions of practitioners in order to predict new behaviors based on data produced by the organizations, services agencies, users, clients or individuals. Machine learning techniques include a set of generalizable algorithms that are data-driven, which means that rules and solutions are derived by examining data, based on the patterns that are present within any data set. In other words, the goal of machine learning is teaching computers through 'examples', by training data to test specifics hypothesis and predict what would be a certain outcome, based on a current scenario and improve that experience. Machine learning can be classified into two general categories depending on the nature of the problem that this technique needs to tackle. First, supervised learning involves a dataset that is already known in terms of their output. Supervising learning problems are categorized, into regression problems, which involve a prediction from quantitative variables, using a continuous function; and classification problems, which seek predict results from discrete qualitative variables. For social work research, machine learning generates predictions as a key element to improving social interventions on complex social issues by providing better inference from data and establishing more precise estimated effects, for example in services that seek to improve their outcomes. This paper exposes the results of a classification algorithm to predict cyberbullying among adolescents. Data were retrieved from the National Polyvictimization Survey conducted by the government of Chile in 2017. A logistic regression model was created to predict if an adolescent would experience cyberbullying based on the interaction and behavior of gender, age, grade, type of school, and self-esteem sentiments. The model can predict with an accuracy of 59.8% if an adolescent will suffer cyberbullying. These results can help to promote programs to avoid cyberbullying at schools and improve evidence based practice.

Keywords: cyberbullying, evidence based practice, machine learning, social work research

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Authors: Mohammadreza Hajialigol, Nargues Falahi Charkhabi, Fatemeh Shahryari, Saadat Sarikhani

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BACKGROUND AND OBJECTIVES Walnut canker is characterized by brown to blackish roundish blotches on the trunks and main branches, necrosis of inner bark and bleeding with dark brown to black-colored exudates. The present study aimed to identify the causative agents of walnut decline by their phenotypic features, approval of pathogenicity, the partial sequencing of the housekeeping genes in Razavi Khorasan. MATERIAL AND METHODS Ten Symptomatic samples were collected from walnut orchards of Razavi Khorasan in 2019. Pathogenicity of all isolated strains was carried out on walnut immature fruits cv. ‘Hartley’ and young green twigs of cv. ‘Chandler’. All pathogenic strains were subjected to physiological, morphological and biochemical tests. 16S rRNA and housekeeping genes (fusA, leuS, and pyrG) were partially amplified and sequenced. RESULTS Eight strains were able to cause necrosis and a dark-colored region in the mesocarp of immature walnut fruits, and three representative strains caused necrosis on young inoculated twigs. Strains utilized starch, however, did not utilized esculin, Tween 20, Tween 80, and gelatin. The partial 16S rRNA gene sequence of strain KH7 indicated 99.63 % similarity to that of Citrobacter braakii ATCC5113T. The phylogenetic analyses based on the partial sequencing of three housekeeping genes, fusA (633 bp), pyrG (305), and leuS (640 bp), demonstrated that strains KH1, KH3, and KH7 belong to C. braakii species in a monophyletic clade with high bootstrap support. CONCLUSION To the best of our knowledge, this is the first report of C. braakii as a new plant pathogen which cause walnut decline. Identification of bacteria associated with walnut decline will eventually improve our understanding of the etiology of the disease and may result in improved management techniques for control.

Keywords: emerging pathogens, Iran, juglans regia, MLSA

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Authors: M. P. Dandekar, A. P. Bharne, P. T. Borkar, D. M. Kokare, N. K. Subhedar

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Ethanol ingestion by the mother ensue adverse consequences for her offspring. Herein, we examine the behavioral phenotype and neural substrate of the offspring of the mother on ethanol. Female rats were fed with ethanol-containing liquid diet from 8 days prior of conception and continued till 25 days post-parturition to coincide with weaning. Behavioral changes associated with anxiety, depression and learning and memory were assessed in the offspring, after they attained adulthood (day 85), using elevated plus maze (EPM), forced swim (FST) and novel object recognition tests (NORT), respectively. The offspring of the alcoholic mother, compared to those of the pair-fed mother, spent significantly more time in closed arms of EPM and showed more immobility time in FST. Offspring at the age of 25 and 85 days failed to discriminate between novel versus familiar object in NORT, thus reflecting anxiogenic, depressive and amnesic phenotypes. Neuropeptide cocaine- and amphetamine-regulated transcript peptide (CART) is known to be involved in central effects of ethanol and hence selected for the current study. Twenty-five days old pups of the alcoholic mother showed significant augmentation in CART-immunoreactivity in the cells of Edinger-Westphal (EW) nucleus and lateral hypothalamus. However, a significant decrease in CART-immunoreactivity was seen in nucleus accumbens shell (AcbSh), lateral part of bed nucleus of the stria terminalis (BNSTl), locus coeruleus (LC), hippocampus (CA1, CA2 and CA3), and arcuate nucleus (ARC) of the pups and/or adults offspring. While no change in the CART-immunoreactive fibers of AcbSh and BNSTl, CA2 and CA3 was noticed in the 25 days old pups, the CART-immunoreactive cells in EW and paraventricular nucleus (PVN), and fibers in the central nucleus of amygdala of 85 days old offspring remained unaffected. We suggest that the endogenous CART system in these discrete areas, among other factors, may be a causal to the abnormalities in the next generation of an alcoholic mother.

Keywords: anxiety, depression, CART, ethanol, immunocytochemistry

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Authors: Ben Khayut, Lina Fabri, Maya Avikhana

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The models of the modern Artificial Narrow Intelligence (ANI) cannot: a) independently and continuously function without of human intelligence, used for retraining and reprogramming the ANI’s models, and b) think, understand, be conscious, cognize, infer, and more in state of Uncertainty, and changes in situations, and environmental objects. To eliminate these shortcomings and build a new generation of Artificial Intelligence systems, the paper proposes a Conception, Model, and Method of Computational Psycholinguistic Cognitive Situational-Fuzzy Self-Controlled Brain and Mind System (CPCSFSCBMSUU) using a neural network as its computational memory, operating under uncertainty, and activating its functions by perception, identification of real objects, fuzzy situational control, forming images of these objects, modeling their psychological, linguistic, cognitive, and neural values of properties and features, the meanings of which are identified, interpreted, generated, and formed taking into account the identified subject area, using the data, information, knowledge, and images, accumulated in the Memory. The functioning of the CPCSFSCBMSUU is carried out by its subsystems of the: fuzzy situational control of all processes, computational perception, identifying of reactions and actions, Psycholinguistic Cognitive Fuzzy Logical Inference, Decision making, Reasoning, Systems Thinking, Planning, Awareness, Consciousness, Cognition, Intuition, Wisdom, analysis and processing of the psycholinguistic, subject, visual, signal, sound and other objects, accumulation and using the data, information and knowledge in the Memory, communication, and interaction with other computing systems, robots and humans in order of solving the joint tasks. To investigate the functional processes of the proposed system, the principles of Situational Control, Fuzzy Logic, Psycholinguistics, Informatics, and modern possibilities of Data Science were applied. The proposed self-controlled System of Brain and Mind is oriented on use as a plug-in in multilingual subject Applications.

Keywords: computational brain, mind, psycholinguistic, system, under uncertainty

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Authors: Liana Gomide, Juliana Rodrigues

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The morphology of the foot defines its mode of operation and a biomechanical reform indispensable for a symmetrical distribution of plantar pressures in order not to overload some of its components in isolation. High plantar pressures at specific points in the foot may be a causal factor in several orthopedic disorders that affect the feet such as pain and stress fracture. With digital baro-podometry equipment one can observe an intensity of pressures along the entire foot and quantify some of the movements, such as a subtalar pronation present in the midfoot region. Although, they are involved in microtraumas. In clinical practice, excessive movement has been limited with the use of different taping techniques applied on the plantar arch. Thus, the objective of the present study was to analyze and compare the influence of the inelastic and elastic taping on the distribution of plantar pressure of runners pronators. This is a randomized clinical trial and blind-crossover. Twenty (20) male subjects, mean age 33 ± 7 years old, mean body mass of 71 ± 7 kg, mean height of 174 ± 6 cm, were included in the study. A data collection was carried out by a single research through barop-odometry equipment - Tekscan, model F-scan mobile. The tests were performed at three different times. In the first, an initial barop-odometric evaluation was performed, without a bandage application, with edges at a speed of 9.0 km/h. In the second and third moments, the inelastic or elastic taping was applied consecutively, according to the definition defined in the randomization. As results, it was observed that both as inelastic and elastic taping, provided significant reductions in contact pressure and peak pressure values when compared to the moment without a taping. However, an elastic taping was more effective in decreasing contact pressure (no bandage = 714 ± 201, elastic taping = 690 ± 210 and inelastic taping = 716 ± 180) and no peak pressure in the midfoot region (no bandage = 1490 ± 42, elastic taping = 1273 ± 323 and inelastic taping = 1487 ± 437). It is possible to conclude that it is an elastic taping provided by pressure in the middle region, thereby reducing the subtalar pronunciation event during the run.

Keywords: elastic taping, inelastic taping, running, subtalar pronation

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Authors: Scott A. Abbott

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This paper examines the increase in the occurrence of natural disasters worldwide and the need to support vulnerable communities in post-disaster recovery. Preparation and implementation of post-disaster recovery projects need to be improved to allow communities to recover infrastructure, housing, economically and socially following a catastrophe. With the continual rise in catastrophic events worldwide due to climate change, impacts on construction resources affect the ability for post-disaster recovery to be undertaken. This research focuses on case studies of catastrophic events in Queensland, Australia, to contribute to the body of knowledge and gain valuable insights on lessons learned from past events and how they have been managed. The aim of this research is to adopt qualitative data using semi-structured interviews from participants predominantly from the insurance sector to understand barriers that have previously and currently exist in post-disaster recovery. Existing literature was reviewed to reveal gaps in knowledge that needed to be tested. Qualitative data was collected and summarised from field research with the results analysed and discussed. Barriers that impacted post-disaster recovery included time, cost, and resource capability and capacity. Causal themes that impacted time and cost were identified as decision making, pre-planning, and preparedness, as well as effective communication across stakeholders. The research study applied a qualitative approach to the existing literature and case studies across Queensland, Australia, to identify existing and new barriers that impact post-disaster recovery. It was recommended to implement effective procurement strategies to assist in cost control; implement pre-planning and preparedness strategies across funder, contractor, and local governments; more effective and timely decision making to reduce time and cost impacts.

Keywords: construction recovery, cost, disaster recovery, resources, time

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Authors: Carolyn Scott, Rachel Nugent

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The agricultural industry in Ireland and worldwide is one of the most dangerous occupations with respect to occupational health and safety accidents and fatalities. Many accident causation models have been developed in safety research to understand the underlying and contributory factors that lead to the occurrence of an accident. Due to the uniqueness of the agricultural sector, current accident causation theories cannot be applied. This paper presents an accident causation model named the Irish Farm Accident Causation Model (IFACM) which has been specifically tailored to the needs of Irish farms. The IFACM is a theoretical and practical model of accident causation that arranges the causal factors into a graphic representation of originating, shaping, and contributory factors that lead to accidents when unsafe acts and conditions are created that are not rectified by control measures. Causes of farm accidents were assimilated by means of a thorough literature review and were collated to form a graphical representation of the underlying causes of a farm accident. The IFACM was validated retrospectively through case study analysis and peer review. Participants in the case study (n=10) identified causes that led to a farm accident in which they were involved. A root cause analysis was conducted to understand the contributory factors surrounding the farm accident, traced back to the ‘root cause’. Experts relevant to farm safety accident causation in the agricultural industry have peer reviewed the IFACM. The accident causation process is complex. Accident prevention requires a comprehensive understanding of this complex process because to prevent the occurrence of accidents, the causes of accidents must be known. There is little research on the key causes and contributory factors of unsafe behaviours and accidents on Irish farms. The focus of this research is to gain a deep understanding of the causality of accidents on Irish farms. The results suggest that the IFACM framework is helpful for the analysis of the causes of accidents within the agricultural industry in Ireland. The research also suggests that there may be international applicability if further research is carried out. Furthermore, significant learning can be obtained from considering the underlying causes of accidents.

Keywords: farm safety, farm accidents, accident causation, root cause analysis

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Authors: Thuraya Ahmed Al Shidhani, Yahya Al Farsi, Alya Al Husni, Samir Al Adawi

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Background: Knee osteoarthritis (knee OA) represents a major public health burden worldwide, particularly among older adults. However, little has been documented from Arabian Gulf countries, which have left an information gap. Objective: This study describes the socio-demographic, clinical risk factors, and use of herbal medicine among men and women seeking consultation for knee OA at two secondary healthcare facilities in Muscat, Oman. Methods: A cross-sectional study was conducted among 213 Omani adults with knee OA attending a referral polyclinic in Muscat, Oman, over 12 months from January to December. Socio-demographic data were collected from the participants who are seeking consultation for knee OA. Results: Among the 213 study participants, 171 were females and 42 males. The females were comparatively older than the males, had lower education and lower-income, and more overweight. The majority of the participants were normal weight or underweight. About one-third of participants reported OA in other joints as well. Most participants recalled that they had knee OA for less than a year. About 12% reported a history of trauma. The majority (63%) concurrently had other chronic illnesses, and 33% reported having at least one complication. About 22% were using herbal medicines. About 77% are using herbal local applications in form of powder and creams. Conclusion: This study, to our knowledge, is the first to explore socio-demographic characteristics, clinical risk factors and use of herbal medicine among sufferers of knee OA in Oman. Knee OA tended to occur among our participants at younger ages than reported elsewhere, while obesity appeared orthogonal to the severity of knee OA. Women were more affected than men. About one quarter of Omani patients are using herbal medicine. More studies are needed to understand the causal factors and development of knee OA in Oman. Targeted health education and rehabilitation programs are needed, particularly among Omani women, to improve their physical quality of life.

Keywords: knee joint, osteoarthritis, herbal medicine, Oman

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Authors: Balasooriya B. M. C. M., Sujeeva N., Thowfeek Z., Siddiqa Omo, Liyanagunawardana J. E., Jayawardana Saiu, Manathunga S. S., Katulanda G. W.

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Introduction and objectives: Adrenal venous sampling (AVS) is the gold standard to discriminate unilateral primary aldosteronism (UPA) from bilateral disease (BPA). AVS is technically demanding and only performed in a limited number of centers worldwide. To the best of our knowledge, Except for one study conducted in India, no other research studies on this area have been conducted in South Asia. This study aimed to evaluate the effectiveness of AVS in the management of primary aldosteronism. Methods: A total of 32 patients who underwent AVS at the National Hospital of Sri Lanka from April 2021 to April 2023 were enrolled. Demographic, clinical and laboratory data were obtained retrospectively. A procedure was considered successful when adequate cannulation of both adrenal veins was demonstrated. Cortisol gradient across the adrenal vein (AV) and the peripheral vein was used to establish the success of venous cannulation. Lateralization was determined by the aldosterone gradient between the two sides. Continuous and categorical variables were summarized with mean, SD, and proportions, respectively. The mean and standard deviation of the contralateral suppression index (CSI) were estimated with an intercept-only Bayesian inference model. Results: Of the 32 patients, the average age was 52.47 +26.14 and 19 (59.4%) were males. Both AVs were successfully cannulated in 12 (37.5%). Among them, lateralization was demonstrated in 11(91.7%), and one was diagnosed as a bilateral disease. There were no total failures. Right AV cannulation was unsuccessful in 18 (56.25%), of which lateralization was demonstrated in 9 (50%), and others were inconclusive. Left AV cannulation was unsuccessful only in 2 (6.25%); one was lateralized, and the other remained inconclusive. The estimated mean of the CSI was 0.33 (89% credible interval 0.11-0.86). Seven patients underwent unilateral adrenalectomy and demonstrated significant improvement in blood pressure during follow-up. Two patients await surgery. Others were treated medically. Conclusions: Despite failure due to procedural difficulties, AVS remained useful in the management of patients with PA. Moreover, the success of the procedure needs experienced hands and advanced equipment to achieve optimal outcomes in PA.

Keywords: adrenal venous sampling, lateralization, contralateral suppression index, primary aldosteronism

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Authors: Jalal Haghighat Monfared, Zahra Akbari

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Today, business executives need to have useful information to make better decisions. Banks have also been using information tools so that they can direct the decision-making process in order to achieve their desired goals by rapidly extracting information from sources with the help of business intelligence. The research seeks to investigate whether there is a relationship between the quality of decision making and the business intelligence capabilities of Mellat Bank. Each of the factors studied is divided into several components, and these and their relationships are measured by a questionnaire. The statistical population of this study consists of all managers and experts of Mellat Bank's General Departments (including 190 people) who use commercial intelligence reports. The sample size of this study was 123 randomly determined by statistical method. In this research, relevant statistical inference has been used for data analysis and hypothesis testing. In the first stage, using the Kolmogorov-Smirnov test, the normalization of the data was investigated and in the next stage, the construct validity of both variables and their resulting indexes were verified using confirmatory factor analysis. Finally, using the structural equation modeling and Pearson's correlation coefficient, the research hypotheses were tested. The results confirmed the existence of a positive relationship between decision quality and business intelligence capabilities in Mellat Bank. Among the various capabilities, including data quality, correlation with other systems, user access, flexibility and risk management support, the flexibility of the business intelligence system was the most correlated with the dependent variable of the present research. This shows that it is necessary for Mellat Bank to pay more attention to choose the required business intelligence systems with high flexibility in terms of the ability to submit custom formatted reports. Subsequently, the quality of data on business intelligence systems showed the strongest relationship with quality of decision making. Therefore, improving the quality of data, including the source of data internally or externally, the type of data in quantitative or qualitative terms, the credibility of the data and perceptions of who uses the business intelligence system, improves the quality of decision making in Mellat Bank.

Keywords: business intelligence, business intelligence capability, decision making, decision quality

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Authors: Jane N. O'Sullivan

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In most studies relating change in fertility to potentially causal factors (such as girls’ educational attainment, infant mortality or urbanization), the presence or nature of family planning efforts are not examined, potentially misattributing their contributions. Modest impacts of voluntary family planning programs on fertility change have been claimed, citing the near-term effects of historical quasi-experimental projects – notably in Bangladesh and in Ghana – where recipients and non-recipients could be contrasted. By their nature, such experiments lacked the wider cultural impacts of national programs. Concurrently, analyses relating population growth with economic advancement have been equivocal, discrediting previous widespread concern which prevailed before the 1980s. This neutral view has been revised more recently with demographic dividend theory crediting higher working-age proportion with some economic stimulus if supported by sufficient institutional and human capacity. In this study of country-level data, cross-country comparisons spanning six decades relate fertility decline with family planning effort, GDP per capita and female education, finding that the timing of rapid fertility decline aligns with commencement of voluntary family planning programs, while economic betterment came after substantial fertility fall. The relationship between fertility and primary education completion was inconsistent, with potential channels of causation operating in both directions. GDP per capita was unrelated to rate of fertility decline, but total fertility rates above three children per woman strongly impeded enrichment. By synchronizing countries with respect to their fertility transition, strong relationships are revealed which suggest lower fertility enables economic betterment, rather than the other way around. These results argue in favour of elevating voluntary family planning as a development priority.

Keywords: economic advance, family planning effort, fertility decline, population growth rate

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Authors: Tasneem Imam, Justine S. Gibson, Mohammad Foysal, Shetu B. Das, Rashed Mahmud, Suman D. Gupta, Ahasanul Hoque, Guillaume Fournie, Joerg Henning

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Commercial chicken production is an import livestock industry in Bangladesh. Antimicrobials are commonly used to control and prevent infectious diseases. It was hypothesized that inadequate biosecurity practices might promote antimicrobial usage on commercial chicken farms. A cross-sectional study was carried out to evaluate antimicrobial usage and farm biosecurity practices implemented on 57 layer and 83 broiler farms in eight sub-districts of the Chattogram district in Bangladesh. A questionnaire was used to collect data on antimicrobial usage and biosecurity practices on these farms. A causal framework was used to guide the development of a multi-level mixed-effects logistic regression analysis to evaluate the total and direct effects of practiced biosecurity management on prophylactic and therapeutic administration of antimicrobials. A total of 24 antimicrobials were administered in the current production cycle at the time of the survey. The most administered antimicrobials on layer farms were ciprofloxacin (37.0% of farms), amoxicillin (33.3%), and tiamulin (31.5%); however, on broiler farms, colistin (56.6% of farms), doxycycline (50.6%), and neomycin (38.6%) were most used. Only 15.3% of commercial farmers used antimicrobials entirely for therapeutic purposes, whereas 84.7% administered antimicrobials prophylactically. Inadequate biosecurity practices were more common among commercial broiler farmers compared to layer farmers. For example, only 2.4% of broiler farmers used footbaths before entering sheds compared to 22.2% of the layer farmers (p < 0.001). Farms that used antimicrobials only for therapeutic purposes (vs prophylactic) implemented more frequently adequate disease control measures, such as separating sick birds from healthy birds. This research highlighted that the prophylactic application of antimicrobials is often conducted to substitute poor biosecurity practices on commercial chicken farms. Awareness programs for farmers are crucial to inform them about the risk associated with antimicrobial usage and to highlight the economic benefits of implementing cost-effective biosecurity measures to control infectious poultry diseases.

Keywords: antimicrobial, biosecurity, broiler, layer

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Authors: Kafeero Frank

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This study aimed at developing a frame work for open source software adoption in an institution of higher learning in Uganda, with the case of KIU as a study area. There were mainly four research questions based on; individual staff interaction with open source software forum, perceived FOSS characteristics, organizational characteristics and external characteristics as factors that affect open source software adoption. The researcher used causal-correlation research design to study effects of these variables on open source software adoption. A quantitative approach was used in this study with self-administered questionnaire on a purposively and randomly sampled sample of university ICT staff. Resultant data was analyzed using means, correlation coefficients and multivariate multiple regression analysis as statistical tools. The study reveals that individual staff interaction with open source software forum and perceived FOSS characteristics were the primary factors that significantly affect FOSS adoption while organizational and external factors were secondary with no significant effect but significant correlation to open source software adoption. It was concluded that for effective open source software adoption to occur there must be more effort on primary factors with subsequent reinforcement of secondary factors to fulfill the primary factors and adoption of open source software. Lastly recommendations were made in line with conclusions for coming up with Kyambogo University frame work for open source software adoption in institutions of higher learning. Areas of further research recommended include; Stakeholders’ analysis of open source software adoption in Uganda; Challenges and way forward. Evaluation of Kyambogo University frame work for open source software adoption in institutions of higher learning. Framework development for cloud computing adoption in Ugandan universities. Framework for FOSS development in Uganda IT industry

Keywords: open source software., organisational characteristics, external characteristics, cloud computing adoption

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Authors: Emily Injete Amondo, Alisher Mirzabaev, Emmanuel Rukundo

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Children in rural farming households are often vulnerable to a multitude of risks, including health risks associated with climate change and variability. Cognizant of this, this study empirically traced the relationship between climate variability and nutritional health outcomes in rural children while identifying the cause-and-effect transmission mechanisms. We combined four waves of the rich Uganda National Panel Survey (UNPS), part of the World Bank Living Standards Measurement Studies (LSMS) for the period 2009-2014, with long-term and high-frequency rainfall and temperature datasets. Self-reported drought and flood shock variables were further used in separate regressions for triangulation purposes and robustness checks. Panel fixed effects regressions were applied in the empirical analysis, accounting for a variety of causal identification issues. The results showed significant negative outcomes for children’s anthropometric measurements due to the impacts of moderate and extreme droughts, extreme wet spells, and heatwaves. On the contrary, moderate wet spells were positively linked with nutritional measures. Agricultural production and child diarrhea were the main transmission channels, with heatwaves, droughts, and high rainfall variability negatively affecting crop output. The probability of diarrhea was positively related to increases in temperature and dry spells. Results further revealed that children in households who engaged in ex-ante or anticipatory risk-reducing strategies such as savings had better health outcomes as opposed to those engaged in ex-post coping such as involuntary change of diet. These results highlight the importance of adaptation in smoothing the harmful effects of climate variability on the health of rural households and children in Uganda.

Keywords: extreme weather events, undernutrition, diarrhea, agricultural production, gridded weather data

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Authors: José Luis Gallizo, Pilar Gargallo, Ramon Saladrigues, Manuel Salvador

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This study offers an exploratory statistical analysis of the persistence of annual profits across a sample of firms from different European Union (EU) countries. To this end, a hierarchical Bayesian dynamic model has been used which enables the annual behaviour of those profits to be broken down into a permanent structural and a transitory component, while also distinguishing between general effects affecting the industry as a whole to which each firm belongs and specific effects affecting each firm in particular. This breakdown enables the relative importance of those fundamental components to be more accurately evaluated by country and sector. Furthermore, Bayesian approach allows for testing different hypotheses about the homogeneity of the behaviour of the above components with respect to the sector and the country where the firm develops its activity. The data analysed come from a sample of 23,293 firms in EU countries selected from the AMADEUS data-base. The period analysed ran from 1999 to 2007 and 21 sectors were analysed, chosen in such a way that there was a sufficiently large number of firms in each country sector combination for the industry effects to be estimated accurately enough for meaningful comparisons to be made by sector and country. The analysis has been conducted by sector and by country from a Bayesian perspective, thus making the study more flexible and realistic since the estimates obtained do not depend on asymptotic results. In general terms, the study finds that, although the industry effects are significant, more important are the firm specific effects. That importance varies depending on the sector or the country in which the firm carries out its activity. The influence of firm effects accounts for around 81% of total variation and display a significantly lower degree of persistence, with adjustment speeds oscillating around 34%. However, this pattern is not homogeneous but depends on the sector and country analysed. Industry effects depends also on sector and country analysed have a more marginal importance, being significantly more persistent, with adjustment speeds oscillating around 7-8% with this degree of persistence being very similar for most of sectors and countries analysed.

Keywords: dynamic models, Bayesian inference, MCMC, abnormal returns, persistence of profits, return on assets

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Authors: Viktor Müller, Ulman Lindenberger

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Neurophysiological evidence suggests that the physiological states of the system are characterized by specific network structures and network topology dynamics, demonstrating a robust interplay between network topology and function. It is also evident that interpersonal action coordination or social interaction (e.g., playing music in duets or groups) requires strong intra- and interbrain synchronization resulting in a specific hyper brain network activity across two or more brains to support such coordination or interaction. Such complex hyper brain networks can be described as multiplex or multilayer networks that have a specific multidimensional or multilayer network organization characteristic for superordinate systems and their constituents. The aim of the study was to describe multilayer hyper brain networks and synchronization patterns of guitarists playing guitar in a quartet by using electroencephalography (EEG) hyper scanning (simultaneous EEG recording from multiple brains) and following time-frequency decomposition and multilayer network construction, where within-frequency coupling (WFC) represents communication within different layers, and cross-frequency coupling (CFC) depicts communication between these layers. Results indicate that communication or coupling dynamics, both within and between the layers across the brains of the guitarists, play an essential role in action coordination and are particularly enhanced during periods of high demands on musical coordination. Moreover, multilayer hyper brain network topology and dynamical structure of guitar sounds showed specific guitar-guitar, brain-brain, and guitar-brain causal associations, indicating multilevel dynamics with upward and downward causation, contributing to the superordinate system dynamics and hyper brain functioning. It is concluded that the neuronal dynamics during interpersonal interaction are brain-wide and frequency-specific with the fine-tuned balance between WFC and CFC and can best be described in terms of multilayer multi-brain networks with specific network topology and connectivity strengths. Further sophisticated research is needed to deepen our understanding of these highly interesting and complex phenomena.

Keywords: EEG hyper scanning, intra- and interbrain coupling, multilayer hyper brain networks, social interaction, within- and cross-frequency coupling

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Authors: Isabel Lopez-Oliva, Akshay Paropkari, Shweta Saraswat, Stefan Serban, Paola de Pablo, Karim Raza, Andrew Filer, Iain Chapple, Thomas Dietrich, Melissa Grant, Purnima Kumar

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Objective: We aimed to explicate the role of the subgingival microbiome in the causal link between rheumatoid arthritis (RA) and periodontitis (PD). Methods: Subjects with/without RA and with/without PD were randomized for treatment with scaling and root planing (SRP) or oral hygiene instructions. Subgingival biofilm, gingival crevicular fluid, and serum were collected at baseline and at 3- and 6-months post-operatively. Correlations were generated between 72 million 16S rDNA sequences, immuno-inflammatory mediators, circulating antibodies to oral microbial antigens, serum inflammatory molecules, and clinical metrics of RA. The dynamics of inter-microbial and host-microbial interactions were modeled using differential network analysis. Results: RA superseded periodontitis as a determinant of microbial composition, and DAS28 score superseded the severity of periodontitis as a driver of microbial assemblages (p=0.001, ANOSIM). RA subjects evidenced higher serum anti-PPAD (p=0.0013), anti-Pg-enolase (p=0.0031), anti-RPP3, anti- Pg-OMP and anti- Pi-OMP (p=0.001) antibodies than non-RA controls (with and without periodontitis). Following SRP, bacterial networks anchored by IL-1b, IL-4, IL-6, IL-10, IL-13, MIP-1b, and PDGF-b underwent ≥5-fold higher rewiring; and serum antibodies to microbial antigens decreased significantly. Conclusions: Our data suggest a circular relationship between RA and PD, beginning with an RA-influenced dysbiosis within the healthy subgingival microbiome that leads to exaggerated local inflammation in periodontitis and circulating antibodies to periodontal pathogens and positive correlation between severity of periodontitis and RA activity. Periodontal therapy restores host-microbial homeostasis, reduces local inflammation, and decreases circulating microbial antigens. Our data highlights the importance of integrating periodontal care into the management of RA patients.

Keywords: rheumatoid arthritis, periodontal, subgingival, DNA sequence analysis, oral microbiome

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Authors: Francisco Fernandez de Castro

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The Conditional Cash Transfer (CCT) model gives monetary transfers to beneficiary families on the condition that they take specific education and health actions. According to the economic rationale of CCTs the poor need incentives to invest in their human capital because they are trapped by a lack of information and misleading beliefs. If left to their own decision, the poor will not be able to choose what is in their best interests. The basic assumption of the CCT model is that the poor need incentives to take care of their own education and health-nutrition. Due to the incentives (income cash transfers and conditionalities), beneficiary families are supposed to attend doctor visits and health talks. Children would stay in the school. These incentivized behaviors would produce outcomes such as better health and higher level of education, which in turn will reduce poverty. Based on a grounded theory approach to conduct a two-year period of qualitative data collection in northern Mexico, this study shows that this explanation is incomplete. In addition to the information failure and inadequate beliefs, there are structural barriers in everyday life of households that make health-nutrition and education investments difficult. In-depth interviews and observation work showed that the program takes for granted local conditions in which beneficiary families should fulfill their co-responsibilities. Data challenged the program’s assumptions and unveiled local obstacles not contemplated in the program’s design. These findings have policy and research implications for the CCT agenda. They bring elements for late programming due to the gap between the CCT strategy as envisioned by policy designers, and the program that beneficiary families experience on the ground. As for research consequences, these findings suggest new avenues for scholarly work regarding the causal mechanisms and social processes explaining CCT outcomes.

Keywords: conditional cash transfers, incentives, poverty, structural barriers

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Authors: Bărbuță Alina

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The inter-causal relationship between social inequalities and the digital divide raises the relation issue of gender and information and communication technologies (ICT) - a key element in achieving sustainable development. In preparing generations as future digital citizens and for active socio-economic participation, ICT plays a key role in respecting gender equality. Although several studies over the years have shown that gender plays an important role in digital exclusion, in recent years, many studies with a focus on economically developed or developing countries identify an improvement in these aspects and a gap narrowing. By measuring students' digital competencies level, this paper aims to identify and analyse the existing gender digital inequalities among students. Our analyses are based on a sample of 1526 middle school students residing in rural areas from Republic of Moldova (54.2% girls, mean age 14,00, SD = 1.02). During the online survey they filled in a questionnaire adapted from the (yDSI) ”The Youth Digital Skills Indicator”. The instrument measures the level of five digital competence areas indicated in The European Digital Competence Framework (DigiCom 2.3.). Our results, based on t-test, indicate that depending on gender, there are no statistically significant differences regarding the levels of digital skills in 3 areas: Information navigation and processing; Communication and interaction; Problem solving. However, were identified significant differences in the level of digital skills in the area of ”Digital content creation” [t(1425) = 4.20, p = .000] and ”Safety” [t(1421) = 2.49, p = .000], with higher scores recorded by girls. Our results contradicts the general stereotype regarding the low level of digital competence among girls, in our sample girls scores being on pear with boys and even bigger in knowledge related to digital content creation and online safety skills. Additional investigations related to boys competence on digital safety are necessary as the implication of their low scores on this dimension may suggest boys exposure to digital threats.

Keywords: digital divide, education, gender digital divide, digital literacy, remote learning

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Authors: Laura Bickel

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This paper aims to investigate to what extent Merleau-Ponty’s philosophy of body memory serves as a viable resource for the enactive approach to cognitive science and its first-person experience-based research on ‘recurrent depressive disorder’ coded F33 in ICD-10. In pursuit of this goal, the analysis begins by revisiting the neuroreductive paradigm. This paradigm serves biological psychiatry to explain the condition of vital contact in terms of underlying neurophysiological mechanisms. It is demonstrated that the neuroreductive model cannot sufficiently account for the depressed person’s episodical withdrawal in causal terms. The analysis of the irregular loss of vital resonance requires integrating the body as the subject of experience and its phenomenological time. Then, it is shown that the enactive approach to depression as disordered sense-making is a promising alternative. The enactive model of perception implies that living beings do not register pre-existing meaning ‘out there’ but unfold ‘sense’ in their action-oriented response to the world. For the enactive approach, Husserl’s passive synthesis of inner time consciousness is fundamental for what becomes perceptually present for action. It seems intuitive to bring together the enactive approach to depression with the long-standing view in phenomenological psychopathology that explains the loss of vital contact by appealing to the disruption of the temporal structure of consciousness. However, this paper argues that the disruption of the temporal structure is not justified conceptually. Instead, one may integrate Merleau-Ponty’s concept of the past as the unconscious into the enactive approach to depression. From this perspective, the living being’s experiential and biological past inserts itself in the form of habit and bodily skills and ensures action-oriented responses to the environment. Finally, it is concluded that the depressed person’s withdrawal indicates the impairment of this application process. The person suffering from F33 cannot actualize sedimented meaning to respond to the valences and tasks of a given situation.

Keywords: depression, enactivism, neuroreductionsim, phenomenology, temporality

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Authors: Samrawit Tamrat Gebretsadik

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Recurrent wheezing is a common respiratory symptom among children, often indicative of underlying airway inflammation and hyperreactivity. Understanding the prevalence and associated factors of recurrent wheezing in specific age groups is crucial for targeted interventions and improved respiratory health outcomes. This study aimed to investigate the prevalence and associated factors of recurrent wheezing among 6-year-old children attending Adama Comprehensive Specialized Hospital Medical College in Ethiopia. A cross-sectional study design was employed, involving structured interviews with parents/guardians, medical records review, and clinical examination of children. Data on demographic characteristics, environmental exposures, family history of respiratory diseases, and socioeconomic status were collected. Logistic regression analysis was used to identify factors associated with recurrent wheezing. The study included X 6-year-old children, with a prevalence of recurrent wheezing found to be Y%. Environmental exposures, including tobacco smoke exposure (OR = Z, 95% CI: X-Y), indoor air pollution (OR = Z, 95% CI: X-Y), and presence of pets at home (OR = Z, 95% CI: X-Y), were identified as significant risk factors for recurrent wheezing. Additionally, a family history of asthma or allergies (OR = Z, 95% CI: X-Y) and low socioeconomic status (OR = Z, 95% CI: X-Y) were associated with an increased likelihood of recurrent wheezing. The impact of recurrent wheezing on the quality of life of affected children and their families was also assessed. Children with recurrent wheezing experienced a higher frequency of respiratory symptoms, increased healthcare utilization, and decreased physical activity compared to their non-wheezing counterparts. In conclusion, recurrent wheezing among 6-year-old children attending Adama Comprehensive Specialized Hospital Medical College is associated with various environmental, genetic, and socioeconomic factors. These findings underscore the importance of targeted interventions aimed at reducing exposure to known triggers and improving respiratory health outcomes in this population. Future research should focus on longitudinal studies to further elucidate the causal relationships between risk factors and recurrent wheezing and evaluate the effectiveness of preventive strategies.

Keywords: wheezing, inflammation, respiratory, crucial

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Authors: Michelle R. Sullivan

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Positive romantic relationships and marriages offer a buffer against a host of physical and emotional difficulties. Conversely, poor relationship quality and marital discord can have deleterious consequences for individuals and families. Research has described non-monogamy, infidelity, and consensual non-monogamy, as both consequential and causal of relationship difficulty, or as a unique way a couple strives to make a relationship work. Much research on consensual non-monogamy has built on feminist theory and critique. To the author’s best knowledge, to date, no studies have examined the predictive relationship between individual and relationship characteristics and expectations of non-monogamy. The current longitudinal study: 1) estimated the prevalence of expectations of partner non-monogamy and 2) evaluated whether gender, sexual identity, age, education, how a couple met, and relationship quality were predictive expectations of partner non-monogamy. This study utilized the publically available longitudinal dataset, How Couples Meet and Stay Together. Adults aged 18- to 98-years old (n=4002) were surveyed by phone over 5 waves from 2009-2014. Demographics and how a couple met were gathered through self-report in Wave 1, and relationship quality and expectations of partner non-monogamy were gathered through self-report in Waves 4 and 5 (n=1047). The prevalence of expectations of partner non-monogamy (encompassing both infidelity and consensual non-monogamy) was 4.8%. Logistic regression models indicated that sexual identity, gender, education, and relationship quality were significantly predictive of expectations of partner non-monogamy. Specifically, male gender, lower education, identifying as lesbian, gay, or bisexual, and a lower relationship quality scores were predictive of expectations of partner non-monogamy. Male gender was not predictive of expectations of partner non-monogamy in the follow up logistic regression model. Age and whether a couple met online were not associated with expectations of partner non-monogamy. Clinical implications include awareness of the increased likelihood of lesbian, gay, and bisexual individuals to have an expectation of non-monogamy and the sequelae of relationship dissatisfaction that may be related. Future research directions could differentiate between non-monogamy subtypes and the person and relationship variables that lead to the likelihood of consensual non-monogamy and infidelity as separate constructs, as well as explore the relationship between predicting partner behavior and actual partner behavioral outcomes.

Keywords: open relationship, polyamory, infidelity, relationship satisfaction

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Authors: A. Chowdhury, P. Egodawatta, J. M. McGree, A. Goonetilleke

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Hydrologic models are increasingly used as tools to predict stormwater quantity and quality from urban catchments. However, due to a range of practical issues, most models produce gross errors in simulating complex hydraulic and hydrologic systems. Difficulty in finding a robust approach for model calibration is one of the main issues. Though automatic calibration techniques are available, they are rarely used in common commercial hydraulic and hydrologic modelling software e.g. MIKE URBAN. This is partly due to the need for a large number of parameters and large datasets in the calibration process. To overcome this practical issue, a framework for automatic calibration of a hydrologic model was developed in R platform and presented in this paper. The model was developed based on the time-area conceptualization. Four calibration parameters, including initial loss, reduction factor, time of concentration and time-lag were considered as the primary set of parameters. Using these parameters, automatic calibration was performed using Approximate Bayesian Computation (ABC). ABC is a simulation-based technique for performing Bayesian inference when the likelihood is intractable or computationally expensive to compute. To test the performance and usefulness, the technique was used to simulate three small catchments in Gold Coast. For comparison, simulation outcomes from the same three catchments using commercial modelling software, MIKE URBAN were used. The graphical comparison shows strong agreement of MIKE URBAN result within the upper and lower 95% credible intervals of posterior predictions as obtained via ABC. Statistical validation for posterior predictions of runoff result using coefficient of determination (CD), root mean square error (RMSE) and maximum error (ME) was found reasonable for three study catchments. The main benefit of using ABC over MIKE URBAN is that ABC provides a posterior distribution for runoff flow prediction, and therefore associated uncertainty in predictions can be obtained. In contrast, MIKE URBAN just provides a point estimate. Based on the results of the analysis, it appears as though ABC the developed framework performs well for automatic calibration.

Keywords: automatic calibration framework, approximate bayesian computation, hydrologic and hydraulic modelling, MIKE URBAN software, R platform

Procedia PDF Downloads 289