Miracle-dz/UniFAR-FTUs huggingface dataset:
Risk Factors for Psychosocial Disorders in Children with Congenital Adrenal Hyperplasia during the COVID-19 Pandemic

Background: Congenital adrenal hyperplasia (CAH) is a chronic disease that requires lifelong medical therapy; thus, it has become a psychosocial stressor associated with mental, emotional, and behavioral disorders in children and adolescents. The COVID-19 pandemic is also an additional stressor in addition to chronic physical illness, biological factors, cognitive factors, environment, age, parental education, parents’ occupations, and family income. Thus, in this study, we aim to analyze the risk factors for psychosocial disorders among children with CAH. Methods: This research was a cross-sectional study conducted from January to April 2021 at the Pediatric Endocrinology Outpatient Clinic in Dr. Soetomo General Hospital in Surabaya. Data were collected through interviews, questionnaires, and medical records and then analyzed via univariate and bivariate analyses using chi-square test (Fisher’s exact test). Result: In total, 30 children were enrolled in this study, among which 8 (26.7%) had emotional disorders, 5 (16.7%) had behavioral disorders, and most (83.3%) did not have hyperactivity/attention disorders. It was found that 8 children (26.7%) had problems with peer relationships, whereas most (83.3%) did not experience prosocial disorders. Family income (p-value = 0.032, CI = 95%) and hyperactivity (p-value = 0.019, CI = 95%) were found to be significantly correlated to conduct problems. Conclusions: Family income, behavioral disorders, and hyperactivity/attention disorders were identified as risk factors for psychosocial disorders in children with CAH during the COVID-19 pandemic.
Circuit-model analysis for spintronic devices with chiral molecules as spin injectors

Recent research discovered that charge-transfer processes in chiral molecules can be spin-selective, and the effect was named chiral-induced spin selectivity (CISS). Follow-up work studied hybrid spintronic devices with conventional electronic materials and chiral (bio)molecules. However, a theoretical foundation for the CISS effect is still in development, and the spintronic signals were not evaluated quantitatively. We present a circuit-model approach that can provide quantitative evaluations. Our analysis assumes the scheme of a recent experiment that used photosystem I (PSI) as spin injectors, for which we find that the experimentally observed signals are, under any reasonable assumptions on relevant PSI timescales, too high to be fully due to the CISS effect. We also show that the CISS effect can in principle be detected using the same type of solid-state device, and by replacing silver with graphene, the signals due to spin generation can be enlarged four orders of magnitude. Our approach thus provides a generic framework for analyzing these types of experiments and advancing the understanding of the CISS effect.
Detecting Irony in Arabic Microblogs using Deep Convolutional Neural Networks

—A considerable amount of research has been de- veloped lately to analyze social media with the intention of understanding and exploiting the available information. Recently, irony has took a significant role in human communication as it has been increasingly used in many social media platforms. In Natural Language Processing (NLP), irony recognition is an important yet difficult problem to solve. It is considered to be a complex linguistic phenomenon in which people means the opposite of what they literally say. Due to its significance, it becomes essential to analyze and detect irony in subjective texts to improve the analysis tools to classify people opinion automatically. This paper explores how deep learning methods can be employed to the detection of irony in Arabic language with the help of Word2vec term representations that converts words to vectors. We applied two different deep learning models; Convolutional Neural Network (CNN) and Bidirectional Long Short-Term Memory (BiLSTM). We tested our frameworks with a manually annotated datasets that was collected using Tweet Scraper. The best result was achieved by the CNN model with an F1 score of 0.87.
Does board composition matter? An evidence from Saudi Arabia

The study investigates the impact of board of directors’ composition on the financial performance of the Saudi listed firms, using models that aim to represent the effect of different board of directors’ composition. This paper is focused on dependent, independent and control variables that aim to test further areas that was limited to some previous researchers. It was assumed that there is a negative relationship between the board size and firm performance, as well as female board directors and firm recruiting. However, it was found that both variables have no relationship with firm performance. It was predicted that there is a positive relationship between chair independence and firm performance, as well as a negative relationship in regard to chair independence. Thus, it was established that there is a positive relationship between the non-executive directors and firm performance.
Fully Metallic Glide-Symmetric Leaky-Wave Antenna at Kₐ-Band With Lens-Augmented Scanning

A fully metallic leaky-wave antenna (LWA) with enhanced scanning rate is presented. The leaky waveguide is implemented in groove gap waveguide technology and is periodically loaded to produce backward radiation. Furthermore, glide-symmetric pins are placed inside the leaky waveguide to increase the dispersion. A parallel-plate waveguide metasurface prism lens is used to disperse the backward radiation and increase the scanning rate of the LWA. The designed antenna can steer the radiation from −26° to 26° from 27 to 35 GHz, and an average total efficiency of 74% is achieved. A prototype of the designed antenna is manufactured, and measurements corroborate the simulated results. The proposed concept is applicable to other frequency-scanning antennas and can be used to increase the scanning rate in radar and imaging systems.
Iron Oxide Nanoparticles and Nano-Composites: An Efficient Tool for Cancer Theranostics

In recent years, functional Iron oxides nanoparticles and nano-composites have gained a special traction in the field of nano-biomedicine, owing to their multifunctional capabilities that includes the inherent magnetic resonance imaging, magnetic bioseparation, cargo delivery and magnetic hyperthermia behavior. Interestingly, there are various forms of iron oxides available, with each form having their own specific characteristics. The different polymorphic forms of iron oxides are obtained through various synthetic routes and are usually surface modified to prevent their oxidation. The chapter shall encompass the synthesis and surface modification of Iron oxides nanoparticles, physicochemical properties, and theranostic application of the magnetic iron oxide nanoparticles in cancer. Also, the future directions of Iron oxide nanoparticles and nano-composites towards the achievement of clinically realizable nanoformulation for cancer theranostic applications were highlighted.
Improving the thermal performance of ‘hard-to-treat’ historic buildings in Edinburgh’s new town.

This paper documents an innovative partnership project between Historic Scotland, the Scottish Energy Centre at Edinburgh Napier University and Castle Rock Edinvar Housing Association in which five Category B Listed, traditional pre-1919, solid wall ‘hard-to-treat’ residential tenement properties located within Edinburgh’s historic UNESCO World Heritage site each received energy efficient upgrades to walls and windows. A variety of measures were tested, achieving significant reductions in fabric heat loss without impacting upon the character and appearance of the buildings. The project is significant in that the energy-efficient upgrades all met with strict conservation requirements on alterations to Listed Buildings and have the potential to be replicated in similar properties throughout Scotland. The project won the award for best refurbishment project at the Carbon Trust’s Low Carbon Building Awards in 2012. All of the properties featured in this study are occupied by tenants within the social-rented sector who prior to the study had indicated some thermal discomfort due to poor window conditions and high heat loss through walls causing increase fuel consumption. The occupants all remained in their homes during the refurbishment activities.
The Electrodynamics of the Induction Motor

In this work, we apply Maxwell's equations on the induction motor. A direct solution being unfeasible, we propose an iterative method. We test the method for the steady state behaviour of 2-pole motor with known stator current and we then use it to derive a dynamic motor model. We flrst examine the case where the magnetic coupling between the stator and rotor is weak. This case leads intuitively to the general case. Induction motors are the backbone of modern industry because of their high performance and low maintenance requirements. The standard procedure for analysing the steady state performance of these motors is the equivalent circuit method (1), in which the motor is modelled as a circuit where voltages are applied causing currents to ∞ow. The dynamic model of the motor also follows from circuital considerations | the assumptions and approximations made vary slightly from model to model resulting in minor difierences among the many models (2{4) existing in literature. In this work we propose an alternative model starting from Maxwell's equations for the motor. 2. MOTOR MODEL AND INFINITE-ORDER PERTURBATION TECHNIQUE We flrst consider a three-phase 2-pole motor. Taking advantage of the fact that the height of a cylindrical motor is typically much greater than the radius, we use a two-dimensional model assuming the flelds and currents to be invariant along the axial direction. We deflne the height of the motor as h, the radii of the cage rotor and the stator as r and R, the conductivities as ae and ae 0 and the depth of the conductor bars as b and b 0 . We treat the rotor and stator as continuous conducting cylinders since the narrow gaps between adjacent bars and wires merely serve to eliminate currents in undesirable directions. The thicknesses b and b 0 being much less than the radii r and R we work in terms of the surface currents ∞owing through the rotor and stator. Accordingly the flnal schematic of our model is as in Fig. 1. The applied stator surface current for the nth phase (n = 1; 2; 3) is
Performance and quality assurance of medical image using hybrid thresholding wavelet transform with Wiener filter

ABSTRACT Medical images like X-ray, computed tomography, ultrasound, and magnetic resonance imaging (MRI) are produced using different techniques; during this process, noise is added that decreases the image quality and image analysis. Image denoising is an important task in image processing; use of wavelet transform improves the quality of an image and reduces noise level. We propose in this research, a denoising approach basing on discrete wavelet transform (DWT) using Hybrid Thresholding (bayesShrink) with Wiener filter technique for enhancing the quality image. This technique improved a better balance between smoothness and accuracy than the traditional wavelet DWT and are less redundant than stationary wavelet transform (SWT). In addition, the Structural Similarity Index Measure (SSIM) and Peak Signal-to-Noise Ratio (PSNR) were used to analyse the denoised images quality.
A decade of experience in prescribing hydroxychloroquine and azithromycin: A retrospective analysis of medication queries in a Saudi drug and poison information center

Purpose: To analyze drug information queries related to treatment with hydroxychloroquine (HCQ), chloroquine (CQ), and azithromycin submitted to a local drug and poison information center in Riyadh, Saudi Arabia. Methods: This retrospective study explored HCQ-, CQ-, and azithromycin-related inquiries submitted to the Drug and Poison Information Center at the Security Forces Hospital Program, Riyadh, Saudi Arabia. These inquiries were analyzed quantitatively and qualitatively. The quantitative analysis included the frequency of each request per year, the profession of the requesters, and the source material classification. A thematic analysis was also performed to categorize requests from healthcare professionals. Results: The Drug and Poison Information Center received 10,685 usable inquiries between 2005 and 2018. There were 160 CQ-, HCQ-, and azithromycin-related queries. Most requests were made by pharmacists (61.25 %). The main sources used to answer the queries were tertiary (92.31 %) and primary (7.69 %) sources. In the dataset, three major topics were identified: administration and dosing, safety, and pregnancy and lactation, each associated with a query subset. Conclusion: These results emphasize the importance of continued education on antimicrobial agents in general, and HCQ, CQ, and azithromycin in particular. The three items have been identified as focus areas that policymakers can us to ensure the quality of future medication prescriptions.
Reconfigurable Transmitarray Antennas

Transmitarrays have been shown to be viable architectures for achieving high-directivity reconfigurable apertures. The existing work on reconfigurable transmitarrays is sparse, with only a few experimental demonstrations of reconfigurable implementations. Furthermore, of the designs that have been presented, different approaches have been proposed, but the advantages and drawbacks of these approaches have not been compared. Therefore, in this thesis we present a systematic study of the different approaches to designing reconfigurable transmitarrays, and present designs following these approaches with experimental validation. First, we investigate the distributed-scatterer approach, which is modeled with layers of identical scattering surfaces. We characterize the beamforming capabilities and then present a Method of Moments technique for analyzing and optimizing designs that follow this approach. Then, we present experimental results for a unit cell with varactor-loaded dipoles following this approach. From these results, we demonstrate that the structure thickness following this approach is problematic for beamforming applications. Taking the coupled-resonator approach, we next present a slot-coupled patch design that is significantly thinner and easier to fabricate than designs that follow the first approach. Implementing this design in a fully reconfigurable transmitarray, we demonstrate two-dimensional beamforming. An advantage of this design is that it can also operate as a reflectarray. Next, following the guided-wave approach, we present a transmitarray design that uses a bridged-T phase shifter and proximity-coupled differentially-fed stacked patches. Not only does this design not require vias, it is has a large fractional bandwidth of 10 percent, which is unprecedented in reconfigurable transmitarrays. Implementing this design in a full transmitarray, we experimentally demonstrate reconfigurable two-dimensional beamsteering, as well as shaped-beam synthesis. The main contributions of this thesis are two-fold. First, we thoroughly and systematically compare the transmitarray approaches, which has not been previously done in literature. Secondly, we experimentally demonstrate a reconfigurable array design that achieves better bandwidth, scan angle range, and beam-shaping capability, than existing designs, with reduced fabrication complexity and physical profile. %%%%PhD
On SFBC Schemes for Enabling Virtual Array Concept in Monostatic ISAC Scenarios

The integrated sensing and communication (ISAC) paradigm is being proposed for 6G as a new feature of the physical layer (PHY), for tackling dual-functional applications, i.e., demanding radio-sensing and communication functions, such as the Internet of Things (IoT) and autonomous driving systems. This work considers the integration of sensing and communications functionalities in a unique platform. To achieve this goal, the use of orthogonal space frequency block codes (SFBC) is proposed. SFBC code orthogonality enables both the separation of communications data streams at a user terminal and the estimation of target parameters. The SFBC enhances the communications link diversity without requiring channel state information knowledge at the transmitter and enable the virtual antenna array concept for enhancing the direction-finding resolution. The use of different SFBCs provides a tradeoff between achieved diversity and sensing resolution. For example, an Alamouti code, applicable for the case with two transmitting antennas, duplicates sensing resolution and achieves a diversity order of two while the use of a Tarokh code, applicable for a scenario with four transmitting antennas, provides a fourfold better resolution and diversity order of four. However, the code rate achieved with the Tarokh code is half of the one achieved with the Alamouti code. Furthermore, the unambiguous range is reduced since the bandwidth is divided to multiplex the different antenna signals. For its simplicity, good performance and reduced integration requirements, the method is promising for future ISAC systems.
Autonomous Robotic Detection of Anti-Personnel Landmines using Ground-Penetrating Radar and On-Contact Antennas

Ground-penetrating radar is a mature technology which has promise as a solution for humanitarian demining. The technology is fast, inexpensive, and capable of detecting both metallic and non-metallic landmine casings. However, the rough air-ground interface below which anti-personnel mines are buried, reduces the efficacy of air-coupled GPR by increasing clutter and masking target responses. Recent literature focuses on optimizing signal processing techniques to remove the effects of the surface and reliably extract the target reflection. Conversely, this work proposes the use of ground-contact antennas, which greatly improve signal penetration and are less affected by ground clutter, thereby simplifying data analysis. Achieving contact between the surface and the antennas is done by integrating the antennas onto the feet of the Walking Tri-Sphere, a non-articulated walking robotic platform designed by Square One Systems Design (Jackson, WY, USA). Rather than imaging the subsurface, localization of potential targets is achieved using a robust geometric analysis, minimizing the required number of GPR scans. Overall, by using fewer scans and simpler data processing techniques, this method is capable of increasing the surveying speed of traditional GPR methods. The proposed detection system is evaluated experimentally using the P400 ultra-wideband impulse radar from Time Domain (Huntsville, AL, USA), and computationally using a 3D finite-difference time-domain model. Compact spiral antennas which operate from 3-6GHz were designed considering the application and desired coupling into the ground. The polarization and directivity of the antennas minimizes the direct signal, simplifying the identification of target reflections. Subsurface scans which satisfy both an amplitude and correlation threshold are then analyzed with a localization algorithm, which utilizes time-difference of arrivals to geometrically determine the target location. A minimum of four unique bistatic GPR scans are necessary to evaluate for the target’s position, and an increased number of GPR scans improves the accuracy and reliability of the results. Using the proposed localization method, metallic cylindrical targets are successfully located experimentally. Consideration of non-metallic targets is also addressed experimentally and more extensively computationally. Overall, the proposed method provides a viable solution for autonomous pre-screening of an area for humanitarian demining.
Slice-Guided Components Detection and Spatial Semantics Acquisition of Indoor Point Clouds

Extracting indoor scene components (i.e., the meaningful parts of indoor objects) and obtaining their spatial relationships (e.g., adjacent, in the left of, etc.) is crucial for scene reconstruction and understanding. At present, the detection of indoor scene components with complex shapes is still challenging. To fix the problem, a simple yet powerful slice-guided algorithm is proposed. The key insight is that slices of indoor scene components always have similar profiles no matter if the components are simple-shaped or complex-shaped. Specifically, we sliced the indoor scene model into many layers and transformed each slice into a set of two-dimensional (2D) profiles by resampling. After that, we clustered 2D profiles from neighbor slices into different components on the base of spatial proximity and similarity. To acquire the spatial relationships between indoor scene components, an ontology was constructed to model the commonsense knowledge about the semantics of indoor scene components and their spatial relationships. Then the spatial semantics of the relationships between indoor scene components were inferred and a semantic graph of spatial relationship (SGSR) was yielded to represent them. The experimental results demonstrate that our method can effectively detect complex-shaped indoor scene components. The spatial relationships between indoor components can be exactly acquired as well.
Bioengineered conduits for directing digitized molecular-based information

Title of Dissertation: BIOENGINEERED CONDUITS FOR DIRECTING DIGITIZED MOLECULAR-BASED INFORMATION Jessica L. Terrell, Doctor of Philosophy, 2015 Directed By: Professor William E. Bentley Fischell Department of Bioengineering Molecular recognition is a prevalent quality in natural biological environments: moleculessmall as well as macroenable dynamic response by instilling functionality and communicating information about the system. The accession and interpretation of this rich molecular information leads to context about the system. Moreover, molecular complexity, both in terms of chemical structure and diversity, permits information to be represented with high capacity. Thus, an opportunity exists to assign molecules as chemical portrayals of natural, non-natural, and even non-biological data. Further, their associated upstream, downstream, and regulatory pathways could be commandeered for the purpose of data processing and transmission. This thesis emphasizes molecules that serve as units of information, the processing of which elucidates context. The project first strategizes biocompatible assembly processes that integrate biological componentry in organized configurations for molecular transfer (e.g. from a cell to a receptor). Next, we have explored the use of DNA for its potential to store data in richer, digital forms. Binary data is embedded within a gene for storage inside a cell carrier and is selectively conveyed. Successively, a catalytic relay is developed to transduce similar data from sequencebased DNA storage to a delineated chemical cue that programs cellular phenotype. Finally, these cell populations are used as mobile information processing units that independently seek and collectively categorize the information, which is fed back as ‘binned’ output. Every development demonstrates a transduction process of molecular data that involves input acquisition, refinement, and output interpretation. Overall, by equipping biomimetic networks with molecular-driven performance, their interactions serve as conduits of information flow. BIOENGINEERED CONDUITS FOR DIRECTING DIGITIZED MOLECULAR-BASED INFORMATION