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This paper proposes a transformerless/non-isolated, high-gain DC-DC converter required to increase low voltages in renewable energy applications. The converter topology uses only a single-switch wi...

Objectives It remains unknown what degree of risk is conferred by celiac disease (CD)-predisposing human leukocyte antigen (HLA)-DQ genotypes in Saudi Arabia compared with in Western countries. In this study, we aimed to determine the CD risk gradient associated with the HLA-DQ genotypes and to compare HLA-DQ genotypes between symptomatic patients with CD and screening-identified asymptomatic CD patients. Methods We enrolled three groups of subjects, including 46 CD children diagnosed consecutively over the past 10 years, 54 CD children diagnosed during a mass screening of schoolchildren, and 192 healthy controls. All the participants were typed for the HLA-DQA1 and HLA-DQB1 genes by polymerase chain reaction sequence-specific oligonucleotide probes. Results Comparing the patients with CD to controls, we identified 5 groups in the CD risk gradient: (i) very high risk associated with the DQ2.5/DQ8 genotype (odds ratio [OR] 46.93); (ii) high risk (homozygous DQ2.5, DQ2.5/DQ2.2; OR 4.12-5.04); (iii) intermediate risk (heterozygous DQ2.5, DQ8/DQ2.2; OR 1.61 and 1.67); (iv) low risk (DQ8, DQ2.2); and (v) very low risk (DQ2.x, DQX.5, DQX.x). Heterozygous DQ8 was more common in screening-identified group compared to symptomatic patients (13.0% vs 2.2%); however, other genotypes were very similar between the two groups. Conclusion The highest risk of developing CD in our Saudi Arabia population is associated with the DQ2.5/DQ8 genotype.

Due to the upsurge of awareness of the depletion of fossil fuel feedstock and environmental issues, biodiesel has become a more attractive choice. Biodiesel's productivity is deemed a fruitful and significant research field since its relevance obtains from the increased oil prices and environmental benefits. This paper presents a study of Alfa waste cooking oil used to produce biodiesel oil via the transesterification process. The investigation includes various variables such as transesterification time, catalyst ratio, temperature, and biodiesel yield. Two catalysts (NaOH and KOH) have been utilized in this study. The engine test was carried out at constant load with increasing speed to compare different fuels' performance relative to mineral diesel. The produced biodiesel was categorized according to ASTM D6751. The highest conversion and yield of biodiesel in the transesterification method were scrutinized using the KOH catalyst compared to the NaOH catalyst. The maximum conversion and yield of biodiesel are 97.76 and 94.4%, respectively, with optimum operating conditions of 60 oC reaction temperature, 3 hours reaction time, and KOH catalyst at 4% weight. Consequently, the engine test outcomes revealed similar biodiesels trends compared to diesel in terms of engine brake power and brake specific fuel consumption with increasing engine speed.

Energy saving is an important consideration in process design for low cost sustainable production with reduced environmental impacts (carbon footprint). In our earlier laboratory scale pilot plant study of catalytic wet air oxidation (CWAO) of phenol (a typical compound found in wastewater), the energy recovery was not an issue due to small amount of energy usage. However, this cannot be ignored for a large scale reactor operating around 140–160 °C due to high total energy requirement. In this work, energy savings in a large scale CWAO process is explored. The hot and cold streams of the process are paired up using 3 heat exchangers recovering significant amount of energy from the hot streams to be re-used in the process leading to over 40% less external energy consumption. In addition, overall cost (capital and operating) savings of the proposed process is more than 20% compared to that without energy recovery option.

Background/Aim: To determine the frequency of celiac disease (CD)-predisposing human leukocyte antigen (HLA)-DQ genotypes in the Saudi population, where the prevalence of CD is 1.5% as recently reported in a mass screening study. Patients and Methods: In a cross-sectional population-based study, a total of 192 randomly selected healthy school children (97 females, mean age 10.5 ± 2.2 years, all negative for tissue transglutaminase-IgA) were typed for D QA1 and D QB1 genes by polymerase chain reaction sequence–specific oligonucleotide probes. Results: Of the 192 children, 52.7% carried the high-risk CD-associated HLA-DQ molecules: homozygous DQ2.5 ( 2.6%), DQ2.5/DQ2.2 ( 4.7%), heterozygous DQ2.5 ( 28.15%), homozygous DQ8 ( 4.2%), DQ8/DQ2.2 ( 3.6%), and double dose DQ2.2 ( 9.4%). Low-risk CD-associated HLA-DQ molecules (single dose DQ2.2 and heterozygous DQ8) constituted 3.6% and 9.4%, respectively. Among the very low–risk groups, individuals lacking alleles that contribute to DQ2/DQ8 variants (33.5%), 13.5% carried only one of the alleles of the high-risk HLA-DQ2.5 heterodimer called “half-heterodimer” (HLA-DQA1*05 in 12% and HLA-DQB1* 02 in 1.5%), and 20.8% lacked all the susceptible alleles (DQX.x). Gender distribution was not significantly different among the CD-risk groups. Conclusion: We report one of the highest frequencies of CD-predisposing HLA-DQ genotypes among healthy general populations (52.7%) worldwide, which might partly explain the high prevalence of CD in the Saudi community.

Therapeutic hypothermia has become the standard of care for newborns with perinatal asphyxia, for long term neuroprotection. Though, definitive literature on role of therapeutic hypothermia in out of hospital cardiac arrests in pediatric population is limited. Furthermore, little is known about the role of therapeutic hypothermia in cases of sudden unexpected postnatal cardiac arrest and asphyxia. We report a case of a Preterm infant born at 35 weeks, with cardiac arrest soon after birth that was treated successfully with therapeutic hypothermia for 72 hours.

The European standard for access control imposes stringent performance requirements on commercial biometric technologies that few existing recognition systems are able to meet. In this correspondence paper, we present the first mouse dynamics biometric recognition system that fulfills this standard. The proposed system achieves notable performance improvement by developing separate models for separate feature groups involved. The improvements are achieved through the use of a fuzzy classification based on the Learning Algorithm for Multivariate Data Analysis and using a score-level fusion scheme to merge corresponding biometric scores. Evaluation of the proposed framework using mouse data from 48 users achieves a false acceptance rate of 0% and a false rejection rate of 0.36%.

Various techniques have been proposed in different literature to analyze biometric samples collected from individuals. However, not a lot of attention has been paid to the inverse problem, which consists of synthesizing artificial biometric samples that can be used for testing existing biometric systems or protecting them against forgeries. In this paper, we present a framework for mouse dynamics biometrics synthesis. Mouse dynamics biometric is a behavioral biometric technology, which allows user recognition based on the actions received from the mouse input device while interacting with a graphical user interface. The proposed inverse biometric model learns from random raw samples collected from real users and then creates synthetic mouse actions for fake users. The generated mouse actions have unique behavioral properties separate from the real mouse actions. This is shown through various comparisons of behavioral metrics as well as a Kolmogorov–Smirnov test. We also show through a two-fold cross-validation test that by submitting sample synthetic data to an existing mouse biometrics analysis model we achieve comparable performance results as when the model is applied to real mouse data.

The performance analysis of distributed software systems is a challenging task in which the assessment of performance measures is a vital step. Due to its versatility, the concept of software performance engineering (SPE) has been advocated as a promising solution towards realizing that step. This paper illustrates how by using our recently proposed Model-Driven SPE (MDSPE) approach, one can design annotated UML performance models for the performance analysis of distributed software systems, based on the UML profile for Schedulability, Performance and Time. An outline of system performance models and metrics is provided and a case study of a business system is used to validate the stated goal.

Continuous Authentication (CA) systems represent a new class of security systems that are increasingly the focus of much attention in the research literature. CA departs from the traditional (static) authentication scheme by repeating several times the authentication process dynamically throughout the entire login session; the main objectives are to detect session hijacking and ensure session security. As the technology gains in maturity and becomes more diverse, it is essential to develop common and meaningful evaluation metrics that can be used to compare and contrast between existing and future schemes. So far, all the CA systems proposed in the literature were by default evaluated using the same accuracy metrics used for static authentication systems. As an alternative, we discuss in this chapter dynamic accuracy metrics that better capture the continuous nature of CA activity. Furthermore, we introduce and study diverse and more complex forms of the Time-To-Authenticate (TTA) metrics corresponding to the authentication delay. We study and illustrate empirically the proposed metrics and models using a combination of real and synthetic data samples.

Continuous Authentication (CA) systems represent a new generation of security mechanisms that continuously monitor user behavior and use this as basis to re-authenticate periodically throughout a login session. CA has been around for about a decade. As a result a limited amount of research work has been produced to date, and the first commercial products have only recently started reaching the market. We attempt, in this chapter, to provide some general perspectives in order to help achieve some common and better understanding of this emerging field. The chapter introduces basic CA concepts and terminologies, discusses the characteristics of CA data sources, and identifies major areas of application for CA systems.

There are few reported studies on Saudi population for human leukocyte antigens (HLA) genes. We investigated allele lineages (two-digit) and haplotype frequencies of HLA-A, -B, -C, -DRB1, and -DQB1 loci in 499 healthy unrelated individuals, selected from potential bone marrow transplant (BMT) families’ donors at King Fahad Medical City (KFMC), Saudi Arabia (SA). Genotyping was performed by Sequence Specific Oligonucleotide Probe (SSOP) utilizing a Luminex-based method. Allele lineages and haplotype frequencies were evaluated along with principal component analysis (PCA) to compare findings with previously reported data on Arab related populations. A total of 18 allele lineages for HLA-A, 28 for -B, 14 for -C, 13 for -DRB1, and 5 for -DQB1 were detected. High values for linkage disequilibrium indicators were found for B:C ( D’ = 0.86599) and DRB1:DQB1 ( D’ = 0.89468) loci. Additionally, PCA results confirmed previous findings on this population, but also indicated some genetic distances from other Arab related populations. The present study helps in further investigations of this population in anthropological analysis and HLA-associated disease studies.

Case reports of a lithium-ketorolac drug interaction have been published, but no formal investigation of this interaction has been conducted. The objective of the study presented here was to determine significant changes in lithium serum and red blood cell (RBC) concentrations after lithium and ketorolac (oral formulation) coadministration at steady-state conditions. Five healthy men participated in the study and received lithium 900 mg/day (300 mg in the morning and 600 mg at bedtime) for 13 days. Ketorolac 40 mg/day (10 mg four times a day) was added on days 8 through 12. Ten blood samples were obtained on days 7 and 13 to determine area under the concentration-time curve (AUC) lithium serum and RBC concentrations. Serum and RBC lithium concentrations were assayed by atomic absorption spectrophotometry with an intra-assay coefficient of variation (CV) of 1.2% on day 1 (range 0-1.0 microg/mL) and 4.9% (range 0-1.0 microg/mL) on day 2 and an interassay CV of 2.9% (range 0-1.0 microg/mL) on days 1 and 2 of serum analysis and a CV of 5.3% (range 0-0.3 microg/mL) of RBC concentrations. Total serum AUC lithium and RBC AUC values significantly increased by 24% (p < 0.02) and by 27% (p < 0.05) with the ketorolac coadministration, respectively. An increased incidence and severity of lithium-associated side effects were reported during concomitant administration. A clinically significant drug interaction can occur when ketorolac is added to lithium therapy.

Trust in leaders is central to citizen compliance with public policies. One potential determinant of trust is how leaders resolve conflicts between utilitarian and non-utilitarian ethical principles in moral dilemmas. Past research suggests that utilitarian responses to dilemmas can both erode and enhance trust in leaders: sacrificing some people to save many others (‘instrumental harm’) reduces trust, while maximizing the welfare of everyone equally (‘impartial beneficence’) may increase trust. In a multi-site experiment spanning 22 countries on six continents, participants (N = 23,929) completed self-report (N = 17,591) and behavioural (N = 12,638) measures of trust in leaders who endorsed utilitarian or non-utilitarian principles in dilemmas concerning the COVID-19 pandemic. Across both the self-report and behavioural measures, endorsement of instrumental harm decreased trust, while endorsement of impartial beneficence increased trust. These results show how support for different ethical principles can impact trust in leaders, and inform effective public communication during times of global crisis. Protocol Registration Statement: The Stage 1 protocol for this Registered Report was accepted in principle on 13 November 2020. The protocol, as accepted by the journal, can be found at https://doi.org/10.6084/m9.figshare.13247315.v1.