Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of the SnapChat mobile social networking application for breast cancer awareness among Saudi students in the Dammam Region of the Kingdom of Saudi Arabia

Purpose The main aim of this study was to investigate the feasibility and the effectiveness of the SnapChat social networking mobile application in increasing the awareness of breast cancer among the Saudi female students in the Dammam region of Saudi Arabia. Patients and methods An intervention study was carried out with 200 participants divided among 2 groups: a control group and an intervention group. The control group did not receive any awareness materials, and the intervention group received awareness about breast cancer through SnapChat using videos, texts, and pictures. A questionnaire-based survey was conducted at the beginning and at the end of the study to assess the change in the awareness among the participants. Results A significant improvement in the breast cancer awareness was found in the intervention group with P=0.001. The mean knowledge was found to be increased from 8.7±2.8 to 14.8±3.01 (mean ± SD). Conclusion The SnapChat mobile social networking application can be effectively used in creating breast cancer awareness among the Saudi population.
Software Metrics for Policy-Driven Software Development Life Cycle Automation

Automation of SDLC requires continuous verification of compliance of the software product under construction to a set of expectations about its quality. We define a policy as an expectation about some aspects of software quality that is expressed as a collection of non-functional requirements (NFRs), compliance to which can be potentially measured. The results of such measurements can be used to verify whether the product meets the expectation set about it. In this paper, we discuss existing NFR taxonomies and propose mapping of software metrics to twelve NFRs. We then propose a model for reliability prediction using publicly available quality metrics for several open source projects.
Applying Automated Test Case Generation in Industry: A Retrospective

Automated test case generation promises to reduce the high effort of manually developing and maintaining test cases, to improve the effectiveness of testing, and to speed-up testing cycles. Research on generating test cases has advanced over the past decades and today a wide range of techniques and tools are available, including studies showing their successful evaluation in real-world scenarios. We conducted a multi-firm research project on automated software testing that involved the application of automated test case generation approaches in industry projects. This paper provides a retrospective on the related activities. It reports on our observations and insights from applying automated test case generation in practice, identifies pitfalls and gaps in current research, and summarizes lessons learned from transferring software testing research results to industry.
Interpreting Video Recommendation Mechanisms by Mining View Count Traces

All large-scale online video systems, for example, Netflix and Youku, make a significant investment on video recommendations that can dramatically affect video information diffusion processes among users. However, there is a lack of efficient methodology to interpret how various recommendation mechanisms affect information diffusion processes resulting in the difficulty to evaluate video recommendation efficiency. In this paper, we propose to quantify and explain video recommendation mechanisms by using epidemic models to mine video view count traces. It is well known that an epidemic model is an efficient approach to model information diffusion processes; while view count traces can be viewed as the results of video information diffusion driven by video recommendations. Thus, we propose a framework based on extended epidemic models to quantify and interpret two recommendation mechanisms, that is, direct and word-of-mouth (WOM) recommendations, by fitting video view count traces collected from Tencent Video, a large-scale online video system in China. Our approach is a novel methodology to evaluate video recommendation mechanisms, and a new perspective to interpret how recommendation mechanisms drive view count evolution.
Benchmarking of Stability and Robustness Against Grid Impedance Variation for LCL -Filtered Grid-Interfacing Inverters

This paper comprehensively analyzes the stability of a grid-interfacing inverter with the LCL -filter in the discrete domain, where the LCL-filter, along with the controller, is modeled in a polar coordinate. System open-loop and closed-loop poles are analytically studied and expressed in the z -domain. Through the poles movement and distribution analysis, the relationship between system stability and the ratio of resonance frequency over sampling frequency is mathematically revealed and calculated as well as the system control gain limit. Moreover, this paper demonstrates that a grid-voltage feedforward regulator would significantly alter the inverter stability in a weak power system. By means of Jury stability criterion, the stability status under different filter resonance frequency is given. The selection of resonance frequency and filter parameters makes a considerable difference on system behavior. Finally, to improve the robustness against grid inductance variation, a conservative design recommendation of filter parameters and control gain is given. Through the tests on a laboratory-scale prototype, the theoretical analysis is validated by experimental results.
Distributed Power System Virtual Inertia Implemented by Grid-Connected Power Converters

Renewable energy sources (RESs), e.g., wind and solar photovoltaics, have been increasingly used to meet worldwide growing energy demands and reduce greenhouse gas emissions. However, RESs are normally coupled to the power grid through fast-response power converters without any inertia, leading to decreased power system inertia. As a result, the grid frequency may easily go beyond the acceptable range under severe frequency events, resulting in undesirable load-shedding, cascading failures, or even large-scale blackouts. To address the ever-decreasing inertia issue, this paper proposes the concept of distributed power system virtual inertia, which can be implemented by grid-connected power converters. Without modifications of system hardware, power system inertia can be emulated by the energy stored in the dc-link capacitors of grid-connected power converters. By regulating the dc-link voltages in proportional to the grid frequency, the dc-link capacitors are aggregated into an extremely large equivalent capacitor serving as an energy buffer for frequency support. Furthermore, the limitation of virtual inertia, together with its design parameters, is identified. Finally, the feasibility of the proposed concept is validated through simulation and experimental results, which indicate that 12.5% and 50% improvements of the frequency nadir and rate of change of frequency can be achieved.
Nearly Constant Switching Space Vector Based Hysteresis Controller for VSI Fed IM Drive

A constant switching frequency hysteresis controller based on current error space vector (CESV) for two-level voltage source inverter fed induction motor (IM) drive is proposed in this paper. Here the stator voltages along the α- and β-axes are estimated using current error information and steady-state model of IM. Estimated stator voltages, switching dwell times, and instantaneous voltage error vectors are used in the online hysteresis boundary computations. The steady-state CESV boundaries and the phase voltage normalized harmonic spectrum of the proposed hysteresis controller at different speeds resembles that of a constant switching frequency voltage-controlled bus clamping pulse-width modulation-based drive. The proposed controller exhibits adjacent voltage vector switching, fast dynamic response under transient conditions, and has a simple controller implementation. The superior performance of the proposed controller is simulated using MATLAB/Simulink platform and experimentally verified on a three-phase 2.2 kW IM drive.
Design of Rectangular Patch Antenna Array Using Different Feeding Technique

In wireless communication system, Patch antenna applicable for the development of low cost, minimal weight and low profile antennas that are capable of maintaining high performance. This paper presents a comparison between rectangular patch antenna arrays using two different feeding techniques: microstrip line feeding and coaxial probe feeding at 2.4 GHz operating frequency. A 2× 2 linear array is designed for both line feeding and coaxial probe feeding. Finally, we analyzed the 2× 3 linear antenna array to increase directivity, gain, efficiency and better radiation patterns. The substrate used is FR4 with dielectric constant of 4.3 and thickness about 1.6mm. The antenna array is designed and simulated by CST microwave studio.
Unbalanced Magnetic Pull Compensation With Active Magnetic Bearings in a 2 MW High-Speed Induction Machine by FEM

High-power high-speed induction machines (IMs) are gaining ground in various industrial applications, especially in replacing traditional motors and gearboxes driving compressors or high-pressure pumps, etc. However, the high-speed technology presents extra challenges for the mechanical structure of the machine including bearing systems. Therefore, it is often reasonable to use active magnetic bearings (AMBs) instead of traditional bearings as they provide much smaller friction and allow a not perfectly centered orbit of the rotor without affecting the lifetime of the bearings. Using AMBs in a machine, the nonuniformity of the rotor leads to an inevitable rotor eccentricity; the level of which depends on the control tolerance and dynamic characteristics of the AMB and the maximum force generated by the AMB. This rotor eccentricity results in an unbalanced magnetic pull (UMP) of the rotor, which has to be compensated by the AMB. This paper analyzes the UMPs of a 2 MW, 12 000 r/min IM in the static eccentricity, dynamic eccentricity, and mixed eccentricity conditions. The AMB system was designed and optimized with the consideration of gravity and UMP effects. Furthermore, the required current compensation for the forces in the horizontal and vertical directions was studied during the operation and verified by the finite-element method.
Unsupervised Deep Hashing with Similarity-Adaptive and Discrete Optimization

Recent vision and learning studies show that learning compact hash codes can facilitate massive data processing with significantly reduced storage and computation. Particularly, learning deep hash functions has greatly improved the retrieval performance, typically under the semantic supervision. In contrast, current unsupervised deep hashing algorithms can hardly achieve satisfactory performance due to either the relaxed optimization or absence of similarity-sensitive objective. In this work, we propose a simple yet effective unsupervised hashing framework, named Similarity-Adaptive Deep Hashing (SADH), which alternatingly proceeds over three training modules: deep hash model training, similarity graph updating and binary code optimization. The key difference from the widely-used two-step hashing method is that the output representations of the learned deep model help update the similarity graph matrix, which is then used to improve the subsequent code optimization. In addition, for producing high-quality binary codes, we devise an effective discrete optimization algorithm which can directly handle the binary constraints with a general hashing loss. Extensive experiments validate the efficacy of SADH, which consistently outperforms the state-of-the-arts by large gaps.
Concentrated Conditioned Media from Adipose Tissue Derived Mesenchymal Stem Cells Mitigates Visual Deficits and Retinal Inflammation Following Mild Traumatic Brain Injury

Blast concussions are a common injury sustained in military combat today. Inflammation due to microglial polarization can drive the development of visual defects following blast injuries. In this study, we assessed whether anti-inflammatory factors released by the mesenchymal stem cells derived from adipose tissue (adipose stem cells, ASC) can limit retinal tissue damage and improve visual function in a mouse model of visual deficits following mild traumatic brain injury. We show that intravitreal injection of 1 μL of ASC concentrated conditioned medium from cells pre-stimulated with inflammatory cytokines (ASC-CCM) mitigates loss of visual acuity and contrast sensitivity four weeks post blast injury. Moreover, blast mice showed increased retinal expression of genes associated with microglial activation and inflammation by molecular analyses, retinal glial fibrillary acidic protein (GFAP) immunoreactivity, and increased loss of ganglion cells. Interestingly, blast mice that received ASC-CCM improved in all parameters above. In vitro, ASC-CCM not only suppressed microglial activation but also protected against Tumor necrosis alpha (TNFα) induced endothelial permeability as measured by transendothelial electrical resistance. Biochemical and molecular analyses demonstrate TSG-6 is highly expressed in ASC-CCM from cells pre-stimulated with TNFα and IFNγ but not from unstimulated cells. Our findings suggest that ASC-CCM mitigates visual deficits of the blast injury through their anti-inflammatory properties on activated pro-inflammatory microglia and endothelial cells. A regenerative therapy for immediate delivery at the time of injury may provide a practical and cost-effective solution against the traumatic effects of blast injuries to the retina.
Domain-specific Accelerators for Ideal Lattice-based Public Key Protocols

Post Quantum Lattice-Based Cryptography (LBC) schemes are increasingly gaining attention in traditional and emerging security problems, such as encryption, digital signature, key exchange, homomorphic encryption etc, to address security needs of both short and long-lived devices — due to their foundational properties and ease of implementation. However, LBC schemes induce higher computational demand compared to classic schemes (e.g., DSA, ECDSA) for equivalent security guarantees, making domain-specific acceleration a viable option for improving security and favor early adoption of LBC schemes by the semiconductor industry. In this paper, we present a workflow to explore the design space of domain-specific accelerators for LBC schemes, to target a diverse set of host devices, from resource-constrained IoT devices to high-performance computing platforms. We present the first results of design space exploration on workloads executing NewHope and BLISSB-I schemes accelerated by our domain-specific accelerators, with respect to a baseline without acceleration. We show that achieved performance with acceleration makes the execution of NewHope and BLISSB-I comparable to classic key exchange and digital signature schemes while retaining some form of general purpose programmability. In addition to 44% and 67% improvement in energy-delay product (EDP), we enhance performance (cycles) of the sign and verify steps in BLISSB-I schemes by 24% and 47%, respectively. Performance (EDP) improvement of server and client side of the NewHope key exchange is improved by 37% and 33% (52% and 48%), demonstrating the practicality of the approach to favor early adoption.
Power-Aware Virtual Network Function Placement and Routing Using an Abstraction Technique

The Network Function Virtualization (NFV) is very promising for efficient provisioning of network services and is attracting a lot of attention. NFV can be implemented in commercial off-the-shelf servers or Physical Machines (PMs), and many network services can be offered as a sequence of Virtual Network Functions (VNFs), known as VNF chains. Furthermore, many existing network devices (e.g., switches) and collocated PMs are underutilized or over-provisioned, resulting in low power-efficiency. In order to achieve more energy efficient systems, this work aims at designing the placement of VNFs such that the total power consumption in network nodes and PMs is minimized, while meeting the delay and capacity requirements of the foreseen demands. Based on existing switch and PM power models, we formulate an Integer Linear Programming (ILP) model to find the optimal solution. We also propose a heuristic based on the concept of Blocking Islands (BI), and a baseline heuristic based on the Betweenness Centrality (BC) property of the graph. Both heuristics and the ILP solutions have been compared in terms of total power consumption, delay, demands acceptance rate, and computation time. Our simulation results suggest that BI-based heuristic is superior compared with the BC-based heuristic, and very close to the optimal solution obtained from the ILP in terms of total power consumption and demands acceptance rate. Compared to the ILP, the proposed BI-based heuristic is significantly faster and results in 22% lower end-to-end delay, with a penalty of consuming 6% more power in average.
The Effects of the Honey-Roasting Process on the Pharmacokinetics of the Six Active Compounds of Licorice

A convenient UPLC-MS/MS method was established to determine the contents of six bioactive compounds, namely, liquiritin apioside, liquiritin, isoliquiritin, liquiritigenin, isoliquiritigenin, and glycyrrhetinic acid, in rat plasma and their pharmacokinetics. By comparing the pharmacokinetic parameters of these compounds in rats by orally administering raw and honey-roasting licorice, the Cmax of isoliquiritin showed a significant decrease, while the AUC0-24h showed no significant differences. The Cmax and AUC0-24h of isoliquiritigenin were increased by 49.3% and 42.7% over those of the raw licorice group, respectively. These results indicate that the absorption of isoliquiritin in rats was reduced while the absorption of isoliquiritigenin was promoted in the honey-roasting process. These results may provide one explanation as to why licorice is more able to relieve cough, while honey-roasting licorice is better at invigorating qi and restoring pulse. Furthermore, the Cmax of glycyrrhetinic acid was increased, suggesting that it may enhance the tonic effect of licorice. Additionally, the amount of honey added in the honey-roasting process influenced the pharmacokinetic parameters of the six compounds whose absorption decreased when the 50% honey-roasting licorice water decoction was administered. These results provide an experimental basis for studying the influence of licorice processing on bioactive compound pharmacokinetics.
Perceptual Dominance in Brief Presentations of Mixed Images: Human Perception vs. Deep Neural Networks

Visual perception involves continuously choosing the most prominent inputs while suppressing others. Neuroscientists induce visual competitions in various ways to study why and how the brain makes choices of what to perceive. Recently deep neural networks (DNNs) have been used as models of the ventral stream of the visual system, due to similarities in both accuracy and hierarchy of feature representation. In this study we created non-dynamic visual competitions for humans by briefly presenting mixtures of two images. We then tested feed-forward DNNs with similar mixtures and examined their behavior. We found that both humans and DNNs tend to perceive only one image when presented with a mixture of two. We revealed image parameters which predict this perceptual dominance and compared their predictability for the two visual systems. Our findings can be used to both improve DNNs as models, as well as potentially improve their performance by imitating biological behaviors.
Homology Modeling Informs Ligand Discovery for the Glutamine Transporter ASCT2

The Alanine-Serine-Cysteine transporter (SLC1A5, ASCT2), is a neutral amino acid exchanger involved in the intracellular homeostasis of amino acids in peripheral tissues. Given its role in supplying glutamine to rapidly proliferating cancer cells in several tumor types such as triple-negative breast cancer and melanoma, ASCT2 has been identified as a key drug target. Here we use a range of computational methods, including homology modeling and ligand docking, in combination with cell-based assays, to develop hypotheses for structure-function relationships in ASCT2. We perform a phylogenetic analysis of the SLC1 family and its prokaryotic homologs to develop a useful multiple sequence alignment for this protein family. We then generate homology models of ASCT2 in two different conformations, based on the human EAAT1 structures. Using ligand enrichment calculations, the ASCT2 models are then compared to crystal structures of various homologs for their utility in discovering ASCT2 inhibitors. We use virtual screening, cellular uptake and electrophysiology experiments to identify a non-amino acid ASCT2 inhibitor that is predicted to interact with the ASCT2 substrate binding site. Our results provide insights into the structural basis of substrate specificity in the SLC1 family, as well as a framework for the design of future selective and potent ASCT2 inhibitors as cancer therapeutics.
New Biological Insights Into How Deforestation in Amazonia Affects Soil Microbial Communities Using Metagenomics and Metagenome-Assembled Genomes

Deforestation in the Brazilian Amazon occurs at an alarming rate, which has broad effects on global greenhouse gas emissions, carbon storage, and biogeochemical cycles. In this study, soil metagenomes and metagenome-assembled genomes (MAGs) were analyzed for alterations to microbial community composition, functional groups, and putative physiology as it related to land-use change and tropical soil. A total of 28 MAGs were assembled encompassing 10 phyla, including both dominant and rare biosphere lineages. Amazon Acidobacteria subdivision 3, Melainabacteria, Microgenomates, and Parcubacteria were found exclusively in pasture soil samples, while Candidatus Rokubacteria was predominant in the adjacent rainforest soil. These shifts in relative abundance between land-use types were supported by the different putative physiologies and life strategies employed by the taxa. This research provides unique biological insights into candidate phyla in tropical soil and how deforestation may impact the carbon cycle and affect climate change.
Synthesis, Characterization, Cytotoxicity, and Antibacterial Properties of trans‐γ‐Halo‐δ‐lactones

Abstract A new four‐step pathway for the synthesis of γ‐halo‐δ‐lactones is described from simple, commercially available substrates: aryl bromides and 3‐methyl crotonaldehyde. The halogenolactonization reaction of β,δ‐substituted, γ,δ‐unsaturated carboxylic acid 4 a–c is regio‐ and stereoselective and gives only the trans‐isomers of lactones 5 a–c, 6 a–c, and 7 a–c. The structures of all synthesized compounds were confirmed by using spectroscopic methods. For bromolactone, containing a naphthyl moiety in the structure, crystallographic analysis was also performed. The lactones were tested for their cytotoxic activity against L929 cell lines (mouse fibroblasts) and antibacterial activity against Escherichia coli strains ATCC 8739 and Staphylococcus aureus ATCC 65389. Compounds 5 a, 5 c, 7 a, and 7 b statistically significantly inhibited the metabolic activity of mouse fibroblasts L929. Compounds 5 b and 6 a were not cytotoxic towards L929 cells, but showed moderate bactericidal properties.
Temporal Bone Imaging Features in Osteogenesis Imperfecta

We present the case of a 33-year old woman with osteogenesis imperfecta (OI) with progressive hearing loss and persisting vertigo. On CT-scan, symmetric extensive lucency in the pericochlear bony otic capsule and promontorium was demonstrated. The MRI-scan demonstrated symmetric areas of increased signal intensity on the T2-images with moderate contrast enhancement in the same regions. These findings correlate histologically by undermineralized thickened bone, the hallmark of OI. Hearing loss is an important clinical feature in patients with OI. The value of temporal bone imaging lies in additional confirmation of the diagnosis, determining the extent disease and excluding concomitant pathology.