Miracle-dz/UniFAR-FTUs huggingface dataset:
A Vision Based Optical Measurement Technique With Augmented Reality Concepts

In this paper, we present the implementation of an application of augmented reality which makes it possible to measure objects in a scene captured using cameras. The implementation is based on a standard planar (Pattern) introduced into the scene. Initially, the detection and the follow-up of the pattern make it possible to use the last to calibrate the camera and to extract its parameters. This allows the passage between the different references (scene, camera, and image) and gives us the possibility of measuring existing objects in the acquired scene. Finally, some tests are presented to prove the validity and to evaluate our method.
LSDA: Lightweight Secure Data Aggregation Scheme in Healthcare using IoT

The Internet of Things (IoT) is one of the most promising technologies for the near future. Healthcare and well-being will receive great benefits with the evolution of this technology. For example, the communicating objects can be body sensors, which enable a continuous real-time monitoring of vital information patients. However, due to the direct involvement to patient health information, the privacy and integrity of medical data have become a matter of much concern to the healthcare applications. In this paper, we propose the Lightweight Secure Data Aggregation (LSDA) Scheme, which is a novel secure data aggregation scheme for Healthcare using IoT. This new scheme is characterized by employing the homomorphic encryption. Also, each aggregator needs to verify all packets received from its member nodes, which can filter bogus packets in-network and thus the nodes can save energy on transmission phase. The security analysis and experimental results show that our proposed scheme guarantees patients privacy, messages authenticity, and integrity with lightweight efficiency in terms of communication overheads.
Feature Selection based Arabic Text Classification using Different Machine Learning Algorithms: Comparative Study

Feature selection is a method of data pre-processing widely used when mining large data, such as textual classification. Several studies have been conducted to compare the different methods of feature selection applied to corpora in English. Unfortunately, a small number of works concern the Arabic language. This article aims to present a comparative study of different feature selection techniques including: Chi2, the ANOVA method and mutual information, applied on a corpus in Arabic language, while also diversifying the machine learning algorithms (Naive Bayes, SVM and KNN). This experimental study has shown in general that reducing dimensionality with feature selection techniques has slightly affected the performance of textual classification, reducing the size of the corpus by up to 1%.
Succinct range filters

We present the Succinct Range Filter (SuRF), a fast and compact data structure for approximate membership tests. Unlike traditional Bloom filters, SuRF supports both single-key lookups and common range queries, such as range counts. SuRF is based on a new data structure called the Fast Succinct Trie (FST) that matches the performance of state-of-the-art order-preserving indexes, while consuming only 10 bits per trie node---a space close to the minimum required by information theory. Our experiments show that SuRF speeds up range queries in a widely used database storage engine by up to 5×.
An AI-enabled future for Qatar and the region

APRIL 2021 | VOL. 64 | NO. 4 | COMMUNICATIONS OF THE ACM 59 P H O T O B Y H A S A N Z A I D I /S H U T T E R S T O C K . C O M South Asia and the Middle East and North Africa (MENA) region. As the finite horizon of a natural resource-based economy comes closer, countries like Qatar have no option but to embrace AI to transition into a knowledgebased economy while protecting and perhaps enhancing their current standard of living. In October 2019, and in the strategy makes Qatarspecific recommendations in order for the country to realize its national vision to transition into a knowledgebased economy by 2030. Here, we briefly outline and contextualize the pillars and report on progress since the strategy was announced. Race for talent. Some 95% of the workforce in Qatar consists of non-Qatari expatriates. A large bulk of the workforce consists of blue-collar workers employed in the construction and service sector. As the infrastructure work related to the FIFA 2022 World Cup comes to an end, Qatar must create pathways to attract talent that has experience working in AI and digital ecosystems. For example, fast-track visas for AI engineers can help build a critical mass of AI collaboration with Qatar Computing Research Institute (QCRI), the government of Qatar released a National Strategy for AI. The aim of the strategy is to provide decision-makers and the wider public in Qatar with a nuanced and realistic view of AI technology and at the same time serve as a “call for action” toward a future where AI will become the defining technology of the 21 century and beyond.
A Siamese convolutional neural network with high–low level feature fusion for change detection in remotely sensed images

ABSTRACT Automatic change detection is an important and difficult task in the field of remote sensing. In this study, a deep Siamese convolutional network based on the fusion of high- and low-level features is proposed for change detection in remote sensing images. Given that low-level features correspond to low-order ones (e.g., texture) that are sensitive to change and that high-level features can accurately reflect image category information (e.g., semantic information), we fuse these features to enhance the abstractness and robustness of the extracted features in the change detection framework. The whole system is end-to-end and does not require any pre- or post-processing. Experimental results on three datasets show that our method is superior to other advanced methods by adding a high- and low-level fusion framework.
Exploring the Structural Fractality of Urban Road Networks by Different Representations

Organisms and other living things grow as fractals, helping to maximize space-filling ability and transmit flow efficiently. In recent years, many studies on fractals have been carried out, mostly at a geometric level, although little work has been done on fractal properties at a structural level. In fact, the capacity of geographical objects, especially road networks, is dependent not only on the geometric distribution described by a geometric fractal dimension but also on the level of structural complexity as described by a structural fractal dimension. Past studies on a structural fractal dimension are limited to a single scale and a single representation. Because different representations could lead to different results in fractal analysis, this study aims to examine the structural fractality of urban road networks by different representations. The road networks of the 100 most populous cities in the United States were examined by three commonly used topological representations. The following results were established: Despite differences in representation, structural fractality always exists; structural fractal dimensions in stroke-based representation are obviously larger than those in segment-based representation; and scale has no obvious effects on structural fractality. These results could deepen our understanding of how urban road networks evolve.
20 years of Nordic hospitality research: a review and future research agenda

ABSTRACT Communicating hospitality and tourism research has been at the core of the journal aim since the early start in 2001. The aim of the current paper is to provide an overview of the first 20 years of hospitality research in Scandinavian Journal of Hospitality and Tourism, to draw some lines to international hospitality research, and to propose a future research agenda. The review provides a brief account of the main themes addressed in Nordic hospitality research including (1) hospitality as a concept and practice, (2) business strategy, (3) hospitality operations, (4) service encounters as performative work, (5) human resource management, and (6) labour market perspectives. Potential research avenues are outlined.
Improving the denoising of WNNM-based imagery: three different strategies

ABSTRACT Weighted nuclear norm minimization (WNNM) has produced remarkable denoising results; however, it still has some limitations, including only being able to measure the similarity of noisy patches by Euclidean distance, fixing the feedback proportion of method noise for all noise levels, and establishing an inflexible number of iterations for each image. In this paper, three strategies are used to improve the abovementioned shortcomings. The first strategy is to calculate the correlation coefficient using Grey theory, and it is combined with Euclidean distance as the final similarity measure value. The second strategy is to adaptively add the feedback coefficient of the method noise according to various noise levels. The last strategy is to apply a stopping criterion based on residual noise to the iteration process. Experimental results show our method provides better results compared to various state-of-the-art algorithms.
The categorical relational process mechanism in enactment learning: effects of divided attention and categorical cues

ABSTRACT The aim of this study was to examine the effects of divided attention and the notification of categorical cues on the categorical relational processing of an enactment paradigm. In this study, we conducted a 3 (encoding condition: verbal tasks vs. experimenter-performed tasks vs. subject-performed tasks) × 2 (attention state: full attention vs. divided attention) × 2 (cue notification condition: with notification vs. without notification) mixed design to explore these questions. Our data analysis showed that the categorical relational processing of subject-performed tasks was not significantly disrupted by divided attention regardless of whether categorical cues were provided. Additionally, categorical cues did not help effectively resist the reduction effects of divided attention in experimenter-performed tasks and verbal tasks. These findings suggest that subject-performed tasks mainly relied on automatic categorical relational encoding processes, minimally disrupted by divided attention.
Generating a highly detailed DSM from a single high-resolution satellite image and an SRTM elevation model

ABSTRACT In this paper, a different approach based on convolutional neural networks (CNNs) is proposed to generate digital surface model (DSM) from a single high-resolution satellite image. In this regard, an approach based on a deep convolutional neural network was designed. The proposed CNN has an encoder-decoder structure to extract multi-scale features in the encoding part and estimate the height values by up-sampling the extracted abstract features. Then, a filtering approach based on morphological operators is proposed to extract the non-ground pixels from each estimated height image. The final digital surface mode Shuttle Radar Topography Mission (SRTM) is obtained by integrating the SRTM elevation model and extracted non-ground objects. Evaluating the estimated height images indicated 0.219, 0.865, and 2.912 m on average log10 error, relative error, and root mean square error (RMSE), respectively. In addition, investigating the final integrated DSM indicated 4.625 m on average for RMSE, demonstrating a promising performance of the proposed approach.
Chemically Modified Soy Protein Films

Glycerin-plasticized soy protein films were produced by casting heated alkaline (pH 8.5) protein solutions. Acetic anhydride, succinic anhydride, calcium cations, and formaldehyde were added to the film-forming solutions and their effects on film water solubility (WS), tensile strength (TS), puncture strength (PS), water vapor permeability (WVP), and oxygen permeability (OP) were determined. Acylation with acetic and succinic anhydrides increased film WS without affecting other film properties. Treatment with calcium cations increased TS and PS by 96 and 43%, respectively, but did not change film barrier properties. Formaldehyde resulted in larger than two-fold increases in TS and PS, while reducing WS and WVP. As a trade-off, formaldehyde treated films were more permeable to oxygen.
Testing quantum theory with thought experiments

Quantum mechanics is one of our most successful physical theories; its predictions agree with experimental observations to an extremely high accuracy. However, the bare formalism of quantum theory does not provide straightforward answers to seemingly simple questions: for example, how should one model systems that include agents who are themselves using quantum theory? These foundational questions may be investigated with a theorist's tool – the thought experiment. Its purpose is to turn debates about the interpretation of quantum theory into actual physics questions. In this article, we give a state-of-the-art overview on quantum thought experiments involving observers, from the basic Wigner's friend to the recent Frauchiger-Renner setup, clarifying their interpretational significance and responding to objections and criticism on the way.
Investigation in the Characteristics of the Personal Ventilation Using Computational Fluid Dynamics

Detailed information of transient exhaled air dispersion and recirculation in the breathing zone can be obtained using computational fluid dynamics (CFD) to generate detailed numerical models and obtain the necessary information. In this study, interaction of free convection flow around human body with respiration flow of breathing and vertical personalized flow from personalized ventilation (PV) system was simulated using a commercial CFD package. Impact of breathing process on personal exposure effectiveness εp was evaluated for different operating and environmental conditions. Re-inhaled exposure index εRI for exhaled CO2 was used to assess the amount of exhaled air re-inhaled due to the interaction between personalized and exhaled airflows. Another objective of this study was to consider the risk of airborne infection transmission, caused by undesirable transport and dispersion of exhaled pathogens to surrounding air when infected individual uses PV. Results show that calculation of personal exposure effectiveness would be sufficiently accurate to give proper information about the protection of occupant with a PV system also without the breathing simulation included. The operating mode of a PV proved as the main factor for dispersion of exhaled air and its transport to the background room air, resulting in an increased risk of airborne infection transmission.
On the Embryonic Development of the Nasal Turbinals and Their Homology in Bats

Multiple corrugated cartilaginous structures are formed within the mammalian nasal capsule, eventually developing into turbinals. Due to its complex and derived morphology, the homologies of the bat nasal turbinals have been highly disputed and uncertain. Tracing prenatal development has been proven to provide a means to resolve homological problems. To elucidate bat turbinate homology, we conducted the most comprehensive study to date on prenatal development of the nasal capsule. Using diffusible iodine-based contrast-enhanced computed tomography (diceCT), we studied in detail the 3D prenatal development of various bat species and non-bat laurasiatherians. We found that the structure previously identified as “maxilloturbinal” is not the true maxilloturbinal and is only part of the ethmoturbinal I pars anterior. Our results also allowed us to trace the evolutionary history of the nasal turbinals in bats. The turbinate structures are overall comparable between laurasiatherians and pteropodids, suggesting that pteropodids retain the ancestral laurasiatherian condition. The absence of the ethmoturbinal I pars posterior in yangochiropterans and rhinolophoids has possibly occurred independently by convergent evolution.
Case Report: Compromised Airway Following Anesthesia and Its Correlation With the Use of ACE Inhibitors—An Unexpected Clinical Event and Review of Literature

Angiotensin-converting enzyme inhibitors associated angioedema involving the upper aerodigestive tract is indisputably a hazardous airway condition which is clinically poorly recognized and frequently underestimated. We describe and present case of a 70-year old man on ramipril who developed massive tongue swelling post-operatively after unremarkable laryngeal mask anaesthesia which was fortuitously managed conservatively. High index of suspicion, timely recognition and knowledge of pathophysiology and the clinical course should guide airway and further supportive management in these patients.
pH-Responsive Amphiphilic Carboxylate Polymers: Design and Potential for Endosomal Escape

The intracellular delivery of emerging biomacromolecular therapeutics, such as genes, peptides, and proteins, remains a great challenge. Unlike small hydrophobic drugs, these biotherapeutics are impermeable to the cell membrane, thus relying on the endocytic pathways for cell entry. After endocytosis, they are entrapped in the endosomes and finally degraded in lysosomes. To overcome these barriers, many carriers have been developed to facilitate the endosomal escape of these biomacromolecules. This mini-review focuses on the development of anionic pH-responsive amphiphilic carboxylate polymers for endosomal escape applications, including the design and synthesis of these polymers, the mechanistic insights of their endosomal escape capability, the challenges in the field, and future opportunities.
Emergence of High Level Carbapenem and Extensively Drug Resistant Escherichia coli ST746 Producing NDM-5 in Influent of Wastewater Treatment Plant, Seoul, South Korea

High level carbapenem and extensively drug resistant (XDR) Escherichia coli strain N7, which produces a variant of New Delhi metallo-β-lactamase (NDM-5), was isolated from the influent of the Jungnang wastewater treatment plant located on Han River, Seoul, South Korea. Phenotypic and genotypic resistances to carbapenem were tested using agar and broth dilution methods, and polymerase chain reaction. Whole-genome sequencing was performed to characterize the genetic structure of strain N7. E. coli strain N7, which harbors the blaNDM–5 gene, showed high level of carbapenem resistance at concentrations of doripenem (512 mg/L) and meropenem (256 mg/L), and XDR to 15 antibiotics. Based on the genomic sequence analysis, two plasmids, a hybrid IncHI2/N-type and an IncX3 type, were present. The former contains a cluster (blaNDM–5-bleMBL-trpF-dsbD) bracketed by multi-insertional sequences, IS3000, ISAba125, IS5, and IS26. The latter carries the following resistance genes: blaCTX–14, aac(3)-IV, aadA1, aadA2, aph(3′)-Ia, aph(4)-Ia, sul1, sul2, sul3, dfrA12, fosA3, oqxA, oqxB, mph(A), and floR, and cmlA1. The chromosome, contig3, and contig5 also carry blaCTX–64 and mdf(A), tet(A), and erm(B), tet(M) and aadA22, respectively. Strain N7 also harbors virulence factors such as fimH, flu, ecpABCDE, sfmA, hlyE, and gadA. This study demonstrates the emergence of high level carbapenem resistant XDR E. coli strain N7 containing blaNDM–5 in aquatic environment, Seoul, South Korea. Due to the presence of mobile genetic elements, this strain could horizontally transfer resistance genes, including blaNDM–5 to environmental bacteria. Thus, it is necessary to conduct continuous surveillance for carbapenem resistance in various aquatic environments.
International Consensus Based Review and Recommendations for Minimum Reporting Standards in Research on Transcutaneous Vagus Nerve Stimulation (Version 2020)

Given its non-invasive nature, there is increasing interest in the use of transcutaneous vagus nerve stimulation (tVNS) across basic, translational and clinical research. Contemporaneously, tVNS can be achieved by stimulating either the auricular branch or the cervical bundle of the vagus nerve, referred to as transcutaneous auricular vagus nerve stimulation(VNS) and transcutaneous cervical VNS, respectively. In order to advance the field in a systematic manner, studies using these technologies need to adequately report sufficient methodological detail to enable comparison of results between studies, replication of studies, as well as enhancing study participant safety. We systematically reviewed the existing tVNS literature to evaluate current reporting practices. Based on this review, and consensus among participating authors, we propose a set of minimal reporting items to guide future tVNS studies. The suggested items address specific technical aspects of the device and stimulation parameters. We also cover general recommendations including inclusion and exclusion criteria for participants, outcome parameters and the detailed reporting of side effects. Furthermore, we review strategies used to identify the optimal stimulation parameters for a given research setting and summarize ongoing developments in animal research with potential implications for the application of tVNS in humans. Finally, we discuss the potential of tVNS in future research as well as the associated challenges across several disciplines in research and clinical practice.
Gluten-Free Foods Cooked in Shared Fryers With Wheat: A Pilot Study Assessing Gluten Cross Contact

Introduction: Consumers with celiac disease are discouraged from eating fried foods cooked in shared fryers with wheat-containing foods at restaurants based on presumed gluten exposure. The purpose of the present study is to assess gluten levels of fries free of gluten-containing ingredients cooked in shared fryers with wheat. Methods: 20 orders of fries were purchased from 10 different restaurants. Restaurants confirmed that fries and oil were free of gluten-containing ingredients. All restaurants confirmed that their fryers were used to cook wheat-containing foods. Fries were sent to Bia Diagnostics and tested in 1-gram duplicates using the R7001 sandwich R5 ELISA and the R7021 competitive R5 ELISA. A microwave control also was run. Results: The sandwich ELISA found gluten in 9/20 fry orders (7 to > 80 ppm). The competitive ELISA found gluten in 3/20 fry orders (14 to > 270 ppm). In the microwave control (60-ppm gluten mixture of wheat flour and canola oil), the unheated mixture tested at a mean level of 64 ppm gluten using the sandwich ELISA and 137 ppm gluten using the competitive ELISA. The mixture heated to 190°C tested at a mean level of 55 ppm gluten using the sandwich ELISA and < 10 ppm and 16 ppm gluten using the competitive ELISA. Discussion: Based on test results, 25% of fry orders would not be considered gluten-free. Summary: Gluten cross contact may occur when gluten-free foods are cooked in shared fryers with wheat. ELISAs may underperform when analyzing for gluten that has been heated.