2nd-order ODEs can be found in many applications, e.g., motion of pendulum, vibrating springs, etc. We first convert the 2nd-order nonlinear ODEs to a system of 1st-order ODEs which is easier to deal with. Then, Adams-Bashforth (AB) methods are used to solve the resulting system of 1st-order ODE. AB methods are chosen since they are the explicit schemes and more efficient in terms of shorter computational time. However, the step size is more restrictive since these methods are conditionally stable. We find two test cases (one test problem and one manufactured solution) to be used to validate the AB methods. The exact solution for both test cases are available for the error and convergence analysis later on. The implementation of 1st-, 2nd- and 3rd-order AB methods are done using Octave. The error was computed to retrieve the order of convergence numerically and the CPU time was recorded to analyze their efficiency.
'Causal' direction is of great importance when dealing with complex systems. Often big volumes of data in the form of time series are available and it is important to develop methods that can inform about possible causal connections between the different observables. Here we investigate the ability of the Transfer Entropy measure to identify causal relations embedded in emergent coherent correlations. We do this by firstly applying Transfer Entropy to an amended Ising model. In addition we use a simple Random Transition model to test the reliability of Transfer Entropy as a measure of 'causal' direction in the presence of stochastic fluctuations. In particular we systematically study the effect of the finite size of data sets.
Unmanned Aerial Vehicle (UAV) is one of the latest technologies for high spatial resolution 3D modeling of the Earth. The objectives of this study are to assess low-cost UAV data using image radiometric transformation techniques and investigate its effects on global and local accuracy of the Digital Surface Model (DSM). This research uses UAV Light Detection and Ranging (LIDAR) data from 80 meters and UAV Drone data from 300 and 500 meters flying height. RAW UAV images acquired from 500 meters flying height are radiometrically transformed in Matrix Laboratory (MATLAB). UAV images from 300 meters flying height are processed for the generation of 3D point cloud and DSM in Pix4D Mapper. UAV LIDAR data are used for the acquisition of Ground Control Points (GCP) and accuracy assessment of UAV Image data products. Accuracy of enhanced DSM with DSM generated from 300 meters flight height were analyzed for point cloud number, density and distribution. Root Mean Square Error (RMSE) value of Z is enhanced from ±2.15 meters to 0.11 meters. For local accuracy assessment of DSM, four different types of land covers are statistically compared with UAV LIDAR resulting in compatibility of enhancement technique with UAV LIDAR accuracy.
Clonal selection algorithm and discrete Hopfield neural network are extensively employed for solving higher-order optimization problems ranging from the constraint satisfaction problem to complex pattern recognition. The modified clonal selection algorithm is a comprehensive and less iterative immune-inspired searching algorithm, utilized to search for the correct combination of instances for Very large-scale integrated (VLSI) circuit structure. In this research, the VLSI circuit framework consists of Boolean 3-Satisfiability instances with the different complexities and number of transistors are considered. Hence, a hybrid modified clonal selection algorithm with discrete Hopfield neural network is well developed to optimize the configuration of VLSI circuits with different number of electronic components such as transistors as the instances. Therefore, the performance of the developed hybrid model was assessed experimentally with the standard models, HNNVLSI-3SATES and HNNVLSI-3SATGA in term of circuit accuracy, sensitivity, robustness and runtime to complete the verification process. The results have demonstrated the developed model, HNNVLSI-3SATCSA produced a minimum error (consistently approaching 0), better accuracy (more than 80%) and faster computational time (less than 125 seconds) against changes in the complexity in term of the number of transistors. Furthermore, the developed hybrid model is able to minimize the computational burden and configurational noises for the variant of VLSI circuits.
Fine resolution (hourly rainfall) of rainfall series for various hydrological systems is widely used. However, observed hourly rainfall records may lack in the quality of data and resulting difficulties to apply it. The utilization of Bartlett-Lewis rectangular pulse (BLRP) is proposed to overcome this limitation. The calibration of this model is regarded as a difficult task due to the existence of intensive estimation of parameters. Global optimization algorithms, named as artificial bee colony (ABC) and particle swarm optimization (PSO) were introduced to overcome this limitation. The issues and ability of each optimization in the calibration procedure were addressed. The results showed that the BLRP model with ABC was able to reproduce well for the rainfall characteristics at hourly and daily rainfall aggregation, similar to PSO. However, the fitted BLRP model with PSO was able to reproduce the rainfall extremes better as compared to ABC.
High turnover rate is one of the striking features of the hotel industry and one of the most significant challenges. High turnover rate causes substantial costs for recruitment, selection and training in hotels, on the other hand, it also leads to negative consequences such as the decline of organizational performance and service quality. Thus, it is necessary to search for the root causes of turnover and put forward solutions. This study was designed to examine the impact of psychological capital (PsyCap), organizational commitment (OC), and job satisfaction (JS) on turnover intention among hotel employees. Additionally, it aimed to test the mediating roles of job satisfaction (JS) and organizational commitment (OC). The data were obtained from 228 hotel customer-contact employees with a time lag of two weeks in three waves in Kuala Lumpur based on convenience sampling. A series of structural equation modeling analyses were utilized to investigate hypothesized relationships. The results reveal that there exists a significant and negative impact of PsyCap on employees' turnover intention and this correlation is partially mediated through two job attitudes. That is to say, to retain hotel talents, five-star hotel management should take proper measures to help employees obtain and maintain positive psychological resources such as PsyCap, on the other hand, how to cultivate positive job attitudes and strengthen their sense of identification and belonging for their organizations is supposed to be more focused on.
Psychogenic polydipsia is prevalent among people with schizophrenia. Although its pathophysiology is relatively unknown, it causes life threatening complications due to acute or severe hyponatraemia.. This report illustrates a patient with schizophrenia who had unrecognized psychogenic polydipsia and developed severe complication. It also highlights the clinical salience of its management.
Euler method is a numerical order process for solving problems with the Ordinary Differential Equation (ODE). It is a fast and easy way. While Euler offers a simple procedure for solving ODEs, problems such as complexity, processing time and accuracy have driven others to use more sophisticated methods. Improvements to the Euler method have attracted much attention resulting in numerous modified Euler methods. This paper proposes Cube Polygon, a modified Euler method with improved accuracy and complexity. In order to demonstrate the accuracy and easy implementation of the proposed method, several examples are presented. Cube Polygon’s performance was compared to Polygon’s scheme and evaluated against exact solutions using SCILAB. Results indicate that not only Cube Polygon has produced solutions that are close to identical solutions for small step sizes, but also for higher step sizes, thus generating more accurate results and decrease complexity. Also known in this paper is the general of the RL circuit due to the ODE problem.
Cardiovascular disease (CVD) is a major global cause of premature mortality. While multiple studies propose CVD mortality prediction models based on regression frameworks, incorporating causal understanding through causal inference approaches can enhance accuracy. This paper demonstrates a methodology combining evidence synthesis and expert knowledge to construct a causal model for premature CVD mortality using Directed Acyclic Graphs (DAGs). The process involves three phases: (1) initial DAG development based on the Evidence Synthesis for Constructing Directed Acyclic Graphs (ESC-DAGs) framework, (2) validation and consensus-building with 12 experts using the Fuzzy Delphi method (FDM), and (3) application to data analysis using population-based survey data linked with death records. Expert input refined the initial DAG model, achieving consensus on 45 causal paths. The revised model guided selection of confounding variables for adjustment. For example, to estimate the total effect of diabetes on premature CVD mortality, the suggested adjustment set included age, dietary pattern, genetic/family history, sex hormones, and physical activity. Testing different DAG models showed agreement between expert ratings and data accuracy from regression models. This systematic approach contributes to DAG methodology, offering a transparent process for constructing causal pathways for premature CVD mortality.
We examined preferences for different forms of causal explanations for indeterminate situations. Background: Klein and Hoffman distinguished several forms of causal explanations for indeterminate, complex situations: single-cause explanations, lists of causes, and explanations that interrelate several causes. What governs our preferences for single-cause (simple) versus multiple- cause (complex) explanations?
The purpose of this study was to evaluate the outcomes of isolated medial patellofemoral ligament (MPFL) reconstruction, regardless of the presence of predisposing factors. A total of 21 knees that underwent isolated MPFL reconstruction from March 2014 to August 2017 were included in this retrospective series. Radiographs of the series of the knee at flexion angles of 20, 40, and 60 degrees were acquired. The patellar position was evaluated using the patellar tilt angle, sulcus angle, congruence angle (CA), and Caton-Deschamps and Blackburne-Peel ratios. To evaluate the clinical outcome, the preoperative and postoperative International Knee Documentation Committee (IKDC) and Lysholm knee scoring scales were analyzed. To evaluate the postoperative outcomes based on the predisposing factors, the results were separately analyzed for each group. Regarding radiologic outcomes, 20-degree CA was significantly reduced from 10.37 ± 5.96° preoperatively to -0.94 ± 4.11° postoperatively (p = 0.001). In addition, regardless of the predisposing factors, delta values of pre- and postoperation of 20-degree CA were not significantly different in both groups. The IKDC score improved from 53.71 (range: 18-74) preoperatively to 94.71 (range: 86-100) at the last follow-up (p = 0.004), and the Lysholm score improved from 54.28 (range: 10-81) preoperatively to 94.14 (range: 86-100) at the last follow-up (p = 0.010). Isolated MPFL reconstruction provides a safe and effective treatment for patellofemoral instability, even in the presence of mild predisposing factors, such as trochlear dysplasia, increased patella height, increased TT-TG distance, or valgus alignment. This is a Level 4, case series study.
Novice drivers are at a greatly inflated risk of crashing. This led in the 20th century to numerous attempts to develop training programs that could reduce their crash risk. Yet, none proved effective. Novice drivers were largely considered careless, not clueless. This article is a case study in the United States of how a better understanding of the causes of novice driver crashes led to training countermeasures targeting teen driving behaviors with known associations with crashes. These effects on behaviors were large enough and long-lasting enough to convince insurance companies to develop training programs that they offered around the country to teen drivers. The success of the training programs at reducing the frequency of behaviors linked to crashes also led to several large-scale evaluations of the effect of the training programs on actual crashes. A reduction in crashes was observed. The cumulative effect has now led to state driver licensing agencies considering as a matter of policy both to include items testing the behaviors linked to crashes on licensing exams and to require training on safety critical behaviors. The effort has been ongoing for over a quarter century and is continuing. The case study highlights the critical elements that made it possible to move from a paradigm shift in the understanding of crash causes to the development and evaluation of crash countermeasures, to the implementation of those crash countermeasures, and to subsequent policy changes at the state and federal level. Key among these elements is the development of simple, scalable solutions.
Prurigo pigmentosa is an inflammatory dermatosis characterized by a pruritic, symmetrically distributed erythematous papular or papulo-vesicular eruption on the trunk arranged in a reticulated pattern that resolves with hyperpigmentation. It is typically non-responsive to topical or systemic steroid therapy. The exact etiology is unknown, but it is more commonly described in the Far East countries. Dietary change is one of the predisposing factors. We report on nine young adult patients with prurigo pigmentosa, among whom five were on ketogenic diets prior to the onset of the eruptions. All cases resolved with oral doxycycline with no recurrence. We hope to improve the awareness of this uncommon skin condition among general practitioners and physicians so that disfiguring hyperpigmentation due to delayed diagnosis and treatment can be avoided.
Chikungunya is an infection caused by chikungunya virus which at present has spread to new countries and con- tinents. Chikungunya is associated with self-limiting and non-fatal infection in the past. However, in recent times, increased severity of the disease has been reported resulting in health and economic burden. The threat and bur- den of chikungunya would grow in future in the absence of specific antiviral or vaccine to control or eliminate the infection. This review discusses chikungunya in general including transmission of its etiological agent and clinical manifestations of the disease. Subsequently, management and treatment of chikungunya virus will be reviewed with particular emphasis on natural products or their active compounds with potential anti-chikungunya virus activities.
Introduction: Altered weather patterns and changes in precipitation, temperature and humidity resulting
from climate change could affect the distribution and incidence of cholera. This study is to quantify climateinduced increase in morbidity rates of cholera. Material and Methods: Monthly cholera cases and monthly
temperature, precipitation, and relative humidity data from 2004 to 2014 were obtained from the Malaysian
Ministry of Health and Malaysian Meteorological Department, respectively. Poisson generalized linear models
were developed to quantify the relationship between meteorological parameters and the number of reported
cholera cases. Results: The findings revealed that the total number of cholera cases in Malaysia during the 11
year study period was 3841 cases with 32 deaths. Out of these, 45.1% of the cases were among children below
12 years old and 75% of the cases were from Sabah. Temperature and precipitation gave significant impact on
the cholera cases in Sabah, (p
Neonatal mastitis and abscess are rare and most often unilateral. Neonatal breast massage for physiological breast hypertrophy is suspected to be a predisposing factor in the case reported here: a 14-day-old neonate with bilateral neonatal breast abscess, treated effectively with intravenous cloxacillin and surgical aspiration.
The Gaussian distribution is usually the default causal single-nucleotide polymorphism (SNP) effect size prior in Bayesian population-based fine-mapping association studies, but a recent study showed that the heavier-tailed Laplace prior distribution provided a better fit to breast cancer top hits identified in genome-wide association studies. We investigate the utility of the Laplace prior as an effect size prior in univariate fine-mapping studies. We consider ranking SNPs using Bayes factors and other summaries of the effect size posterior distribution, the effect of prior choice on credible set size based on the posterior probability of causality, and on the noteworthiness of SNPs in univariate analyses. Across a wide range of fine-mapping scenarios the Laplace prior generally leads to larger 90% credible sets than the Gaussian prior. These larger credible sets for the Laplace prior are due to relatively high prior mass around zero which can yield many noncausal SNPs with relatively large Bayes factors. If using conventional credible sets, the Gaussian prior generally yields a better trade off between including the causal SNP with high probability and keeping the set size reasonable. Interestingly when using the less well utilised measure of noteworthiness, the Laplace prior performs well, leading to causal SNPs being declared noteworthy with high probability, whilst generally declaring fewer than 5% of noncausal SNPs as being noteworthy. In contrast, the Gaussian prior leads to the causal SNP being declared noteworthy with very low probability.
Most prosthetic joint infections originate from wound contamination or haematogenous seeding from distant sites of infection. Bacteraemia may follow dental treatment but there is little evidence of it related to prosthetic joint infection. Nevertheless, controversy continues with regards to the effect of dental treatment in patients with prosthetic joints. This article reviews current English literature regarding the use of antibiotic prophylaxis in the dental management of patients with prosthetic joints. Routine antibiotic prophylaxis is not recommended for every patient with prosthetic joints when receiving dental treatments. However, antibiotic prophylaxis may be prescribed for high-risk groups with predisposing factors to infection when undergoing dental treatment with high risk of bacteraemia.
This case report highlights Koro-like symptoms with erectile dysfunction.
Methods: We report a case of a Rohingya refugee who presented with Koro-like symptoms associated with erectile dysfunction and severe religious guilt.
Results: Sexual dysfunction, i.e. erectile dysfunction may be a predisposing factor for a Koro incidence. Religious issues complicated by superstitious beliefs pose a treatment challenge.
Conclusion: Treating patient with sexual dysfunction should involve exploring and addressing patient's conflicts to avoid worsening of symptoms. As this case illustrates, severe anxiety can present with Koro-like symptoms.
Objectives: Chromosomal abnormalities especially aneuploidies are the most common etiology for pregnancy loss. Trisomy 13, trisomy 18 and trisomy 21 are the most common chromosome autosomal aneuploidies with trisomy 21 (Down syndrome) being the most common chromosomal abnormality among liveborn infants. In previous reports, we noted that the recurrence of these aneuploidies in some families may not occur by chance alone.
Methods: Extraction of relevant data from review of medical case notes of a young couple with two offspring with Down syndrome (DS) and Patau syndrome.
Results: A family history of DS is a predisposing factor for both DS and other types of aneuploidy. Certain instances of non-disjunction error are not random.
Conclusion: As the maternal age was not advanced in both pregnancies, there is a possibility that the recurrent aneuploidy in this family may not be accounted by chance alone. The risk of having subsequent affected pregnancy cannot be ignored in this family and prenatal diagnosis is strongly recommended in the subsequent pregnancy.