Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving QoE of Deep Neural Network Inference on Edge Devices: A Bandit Approach

Edge devices, including, in particular, mobile devices, have been emerging as an increasingly more important platform for deep neural network (DNN) inference. Typically, multiple lightweight DNN models generated using different architectures and/or compression schemes can fit into a device, thus selecting an optimal one is crucial in order to maximize the users’ Quality of Experience (QoE) for edge inference. The existing approaches to device-aware DNN optimization are usually time consuming and not scalable in view of extremely diverse edge devices. More importantly, they focus on optimizing standard performance metrics (e.g., accuracy and latency), which may not translate into improvement of the users’ actual subjective QoE. In this article, we propose a novel automated and user-centric DNN selection engine, called <inline-formula> <tex-math notation="LaTeX">$\mathsf {Aquaman}$ </tex-math></inline-formula>, which keeps users into a closed loop and leverages their QoE feedback to guide DNN selection decisions. The core of <inline-formula> <tex-math notation="LaTeX">$\mathsf {Aquaman}$ </tex-math></inline-formula> is a neural network-based QoE predictor, which is continuously updated online. Additionally, we use neural bandit learning to balance exploitation and exploration, with a provably efficient QoE performance. Finally, we evaluate <inline-formula> <tex-math notation="LaTeX">$\mathsf {Aquaman}$ </tex-math></inline-formula> on a 15-user experimental study as well as synthetic simulations, demonstrating the effectiveness of <inline-formula> <tex-math notation="LaTeX">$\mathsf {Aquaman}$ </tex-math></inline-formula>.
Bit commitment as an introduction to quantum cryptography

This paper analyzes some of the drawbacks of Bennett & Brassard’s quantum key distribution protocol when used in an educational setting introducing components of quantum cryptography. We propose to utilize a quantum bit commitment protocol instead in order to avoid the outlined difficulties. Additionally, we present implementations of the latter protocol in two different programming paradigms which may either be used as a practical demonstration tool for holding a quantum bit ballot, or as a means to foster an in-depth understanding of the cryptographic protocol amongst pupils with a background in computer science.
Pretransplant Systemic Lipidomic Profiles in Allogeneic Stem Cell Transplant Recipients

Simple Summary Stem cell transplantation is used in the treatment of aggressive hematological malignancies and consists of initial high-dose and potentially lethal chemotherapy, followed by rescue with the transplantation of hematopoietic stem cells. Transplantation with stem cells from a healthy donor (i.e., allogeneic stem cells) has the strongest anti-cancer effect, but also the highest risk of severe toxicity. Furthermore, the clinical status at the time of transplantation (inflammation, fluid overload) is associated with posttransplant mortality, and immune-mediated acute graft-versus-host disease (GVHD) is a potential lethal complication. Finally, lipid metabolism regulates the proliferation and survival of both malignant hematological cells and immunocompetent cells that cause GVHD. Our study shows that the pretransplant lipid profiles differ between allotransplant recipients and can be used for the subclassification of patients and possibly to identify patients with an increased risk of death due to disease relapse or treatment toxicity. The therapeutic targeting of lipid metabolism should therefore be further explored in these transplant recipients. Abstract Allogeneic stem cell transplantation is used in the treatment of high-risk hematological malignancies. However, this treatment is associated with severe treatment-related morbidity and mortality. The metabolic status of the recipient may be associated with the risk of development of transplant-associated complications such as graft-versus-host disease (GVHD). To better understand the impact of the lipidomic profile of transplant recipients on posttransplant complications, we evaluated the lipid signatures of patients with hematological disease using non-targeted lipidomics. In the present study, we studied pretransplant serum samples derived from 92 consecutive patients with acute myeloid leukemia (AML) or high-risk myelodysplastic syndrome (MDS). A total of 960 lipid biochemicals were identified, and the pretransplant lipidomic profiles differed significantly when comparing patients with and without the risk factors: (i) pretransplant inflammation, (ii) early fluid overload, and (iii) patients with and without later steroid-requiring acute GVHD. All three factors, but especially patients with pretransplant inflammation, were associated with decreased levels of several lipid metabolites. Based on the overall concentrations of various lipid subclasses, we identified a patient subset characterized by low lipid levels, increased frequency of MDS patients, signs of inflammation, decreased body mass index, and an increased risk of early non-relapse mortality. Metabolic targeting has been proposed as a possible therapeutic strategy in allotransplant recipients, and our present results suggest that the clinical consequences of therapeutic intervention (e.g., nutritional support) will also differ between patients and depend on the metabolic context.
Anisotropy of arrival directions of ultrahigh energy cosmic rays

Anisotropy of Arrival Directions of Ultrahigh Energy Cosmic Rays Chad Barrett Finley This thesis investigates the origins of ultrahigh energy cosmic rays by searching for evidence of small-scale anisotropy in their arrival directions from space. We begin with a short review of what is known about cosmic rays and specifically about the propagation of charged particles through galactic and extragalactic space. We next describe the experimental techniques of detecting these particles by measuring the extensive air showers they produce in the atmosphere, with special focus on the High Resolution Fly’s Eye (HiRes) experiment. In stereo operation the HiRes detector observes cosmic ray arrival directions with unprecedented angular resolution, on the order of 0.5 at all energies above 10 eV, opening a new window in particle astronomy. Before analyzing the data produced by this experiment, we examine previously claimed evidence for clustering of cosmic rays seen by the Akeno Giant Air Shower Array (AGASA) experiment, and identify potential biases in the analysis which call the evidence into question. An unbiased method is then developed to search for the same kind of clustering signal and is applied to the HiRes data. We next develop an unbinned maximum likelihood ratio test for point-source searches, a technique that is optimal for data combined from experiments with different angular resolution, and we apply this to the combined set of HiRes and AGASA data. Finally, we investigate a series of recent claims that ultrahigh energy cosmic rays, including those observed by HiRes, are correlated with the positions of bright BL Lacertae objects (a class of active galaxies), and propose tests of these claims that require independent data. We conclude that at present no statistically significant evidence exists for small-scale anisotropy.
Environmental Taxation and Food Security in Sub-Saharan Africa

The study examined the impact of environmental taxation on food security in sub-Saharan Africa. Panel data was obtained and ordinary least square regression was employed to analyze the data for the study. The findings of the study depicted environmental taxation having a negative effect with food security in sub-Saharan Africa. The recommendation which emanated from the findings is that proper carbon accounting and carbon pricing should be implemeted to ensure that firms are taxed properly as well as tax justice should be promoted. This research throws light on the contribution of accountants as well as the accounting discipline to sustainable development issues such as climate change and food security.
ShareOn: Shared Resource Dynamic Container Migration Framework for Real-Time Support in Mobile Edge Clouds

Mobile Edge Cloud (MEC) technology is envisioned to play a key role in next generation mobile networks by supporting low-latency applications using geographically distributed local cloud clusters. However, MEC faces challenges of resource assignment and load balancing to support user mobility and latency-sensitive applications. Virtualized resource reallocation techniques including dynamic service migration are evolving to achieve load balance, fault tolerance and system maintenance objectives for resource constrained edge nodes. In this work, a compute and network-aware lightweight resource sharing framework with dynamic container migration, ShareOn, is proposed. The migration framework is validated using a set of heterogeneous edge cloud nodes distributed in San Francisco city, serving mobile taxicab users across that region. The end-to-end system is implemented using a container hypervisor called LXD (Linux Container Hypervisor) executing a real-time application to detect license number plates in automobiles. The system is evaluated based on key metrics associated with application quality-of-service (QoS) and network efficiency such as the average system response time and the migration cost for different combinations of load, compute resources, inter-edge cloud bandwidth, network and user latency. A detailed migration cost analysis enables evaluation of migration strategies to improve ShareOn’s performance in comparison to alternative migration techniques, achieving a gain of 15–22% in system response time for highly loaded edge cloud nodes.
Terahertz Metamaterial Sensor for Sensitive Detection of Citrate Salt Solutions

Citrate salts (CSs), as one type of organic salts, have been widely used in the food and pharmaceutical industries. Accurate and quantitative detection of CSs in food and medicine is very important for health and safety. In this study, an asymmetric double-opening ring metamaterial sensor is designed, fabricated, and used to detect citrate salts combined with THz spectroscopy. Factors that influence the sensitivity of the metamaterial sensor including the opening positions and the arrangement of the metal opening ring unit, the refraction index and the thickness of the analyte deposited on the metamaterial sensor were analyzed and discussed from electromagnetic simulations and THz spectroscopy measurements. Based on the high sensitivity of the metamaterial sensor to the refractive index of the analyte, six different citrate salt solutions with low concentrations were well identified. Therefore, THz spectroscopy combined with a metamaterials sensor can provide a new, rapid, and accurate detection of citrate salts.
Task-Based Network Reconfiguration in Distributed UAV Swarms: A Bilateral Matching Approach

In this paper, we study the problem of network reconfiguration when unmanned aerial vehicle (UAV) swarms suffer damage. Multiple UAVs are divided into several groups to perform various tasks. Each master UAV is connected to the ground control station and provides network services for small UAVs that perform various tasks, ensuring that the information of small UAVs can be transmitted back in a timely manner. When master UAVs are destroyed due to factors such as jamming or attacks, the associated small UAVs must select new master UAVs for network service and cooperate with other small UAVs to execute tasks. Based on the heterogeneity and relevance of tasks, we model and analyze the task relationship among different UAVs. Since both master UAVs and small UAVs have respective optimization objectives in the network reconfiguration process, we construct a many-to-one bilateral matching market to model the interaction between master UAVs and small UAVs. To realize an efficient solution for UAV network reconfiguration in complex environments, we propose a distributed matching algorithm and prove that the algorithm can converge to two-sided stable matching. Simulation results indicate that the proposed algorithm can significantly improve the task completion degree of the network compared with three other algorithms.
A Multi-path Nonoverlapping Routing Algorithm for Deterministic Networking

Deterministic Networking (DetNet) is a new network architecture proposed by IETF DetNet working group for industrial Internet of Things and other application scenarios. Its communication service with high reliability and low delay needs multi-path nonoverlapping routing algorithm. Because it is different from existing routing algorithms on the Internet, it is an important subject to study routing algorithms that meet requirements of DetNet. Based on routing characteristics of DetNet, we studied a multi-routing algorithm - Bhandari algorithm. Aiming at the problem that the algorithm cannot calculate nonoverlapping routes in some cases, we improve the algorithm, then we also make the improved algorithm more efficient by introducing Tarjan algorithm. The improved algorithm is verified and tested in the simulation environment and results show the effectiveness of the improved algorithm.
Effects of the COVID-19 Pandemic on Patients with Schizophrenia Spectrum Disorders

Objective: To evaluate the mental health of patients with schizophrenia spectrum disorders with the prolongation of the pandemic. Materials and Methods: This descriptive cross-sectional study was conducted between August-October 2020. Fifty-two patients with schizophrenia spectrum disorders who were hospitalized prior to the onset of the pandemic between March 2019-March 2020 at the inpatient clinic were reassessed during the pandemic. The Positive and Negative Syndrome Scale (PANSS), the Clinical Global Impression-Severity (CGI-S) Scale, Hamilton Depression Rating Scale (HAM-D), Hamilton Anxiety Rating Scale (HAM-A) and Fear of COVID-19 Scale were used to evaluate psychopathology during the pandemic. The PANSS and the CGI severity scores at discharge from the inpatient clinic for each patient were obtained from the medical records review for comparison along with sociodemographic variables.Results: A total of 34 patients, 33 with schizophrenia (97.1%) and 1 with schizoaffective disorder (2.9%) were included. There was no significant difference between the pre- and during the pandemic assessments in the PANSS total and the CGI severity scores. The PANSS total, the CGI, HAM-D, HAM-A and the Fear of COVID-19 scale scores, medical comorbidity and utilization of psychiatric health care services were significantly higher in patients who reported subjectively increased psychiatric symptoms during the pandemic. There was no significant difference in the change of PANSS total and CGI scores between the two groups. Fear of COVID-19 Scale and HAM-A scores were correlated positively. Conclusion: During pandemic increase in psychiatric symptoms may be related not only to psychosis but also depression, anxiety. According to the results of patients who reported subjectively increased psychiatric symptoms during the pandemic, while the psychotic symptoms did not worsen during the pandemic, patients with higher anxiety or depression scores reported an increase in their symptoms and were more likely to seek help.
Describing the Myths and Misconceptions Regarding COVID-19 Vaccines Among the Population of the Kingdom of Saudi Arabia

Objectives This study aims to describe the common myths and misconceptions in addition to the perception and attitudes toward coronavirus disease 2019 (COVID-19) vaccines in the Saudi Arabian community. Methods This is a cross-sectional study that included adults (18 years and older) residing in the Kingdom of Saudi Arabia. Participants were asked to complete an online survey that evaluated their perception and attitudes toward the available COVID-19 vaccines in Saudi Arabia. Statistical comparison between two groups and more was done using chi-square, independent t-test, and one-way ANOVA. Results A total of 471 responses were analyzed with a majority (83.2%) believing that vaccinations are important. The vaccine preferred among the Saudi Arabian population was Pfizer (65.4%). More than half of our respondents (54.8%) strongly agreed that COVID-19 vaccines can reduce the severity of the COVID-19 infection. Respondents in the healthcare sector were significantly more likely to have a more positive view on vaccines compared to those in non-healthcare sectors (p < 0.001). Conclusion The Saudi Arabian population has shown substantial awareness about COVID-19 vaccines; however, public health officials need to further increase awareness measures on COVID-19 vaccines to limit myths and misconceptions, especially among certain populations that are more prone to it.
Individual and Joint Effect of Alpha-Tocopherol and Hydroxytyrosol Acetate on the Oxidation of Sunflower Oil Submitted to Oxidative Conditions: A Study by Proton Nuclear Magnetic Resonance

This study tackles the individual and joint effect of alpha-tocopherol and hydroxytyrosol acetate on the oxidation of sunflower oil submitted to accelerated storage conditions at intermediate temperature, in order to deepen the understanding of antioxidant–prooxidant behaviour. This was accomplished by 1H Nuclear Magnetic Resonance. For this purpose, the evolution of the degradation of both the main components of the oil and the aforementioned added compounds was monitored by this technique throughout the storage time. Furthermore, the formation of a very large number of oxylipins and the evolution of their concentration up to a very advanced stage of oil oxidation, as well as the occurrence of lipolysis, were also simultaneously studied. The results obtained show very clearly and thoroughly that in the oxidation process of the oil enriched in binary mixtures, interactions occur between alpha-tocopherol and hydroxytyrosol acetate that notably reduce the antioxidant effect of the latter compound with the corresponding negative consequences that this entails. The methodology used here has proved to be very efficient to evaluate the antioxidant power of mixtures of compounds.
NADPH Oxidases in Pain Processing

Inflammation or injury to the somatosensory nervous system may result in chronic pain conditions, which affect millions of people and often cause major health problems. Emerging lines of evidence indicate that reactive oxygen species (ROS), such as superoxide anion or hydrogen peroxide, are produced in the nociceptive system during chronic inflammatory and neuropathic pain and act as specific signaling molecules in pain processing. Among potential ROS sources in the somatosensory system are NADPH oxidases, a group of electron-transporting transmembrane enzymes whose sole function seems to be the generation of ROS. Interestingly, the expression and relevant function of the Nox family members Nox1, Nox2, and Nox4 in various cells of the nociceptive system have been demonstrated. Studies using knockout mice or specific knockdown of these isoforms indicate that Nox1, Nox2, and Nox4 specifically contribute to distinct signaling pathways in chronic inflammatory and/or neuropathic pain states. As selective Nox inhibitors are currently being developed and investigated in various physiological and pathophysiological settings, targeting Nox1, Nox2, and/or Nox4 could be a novel strategy for the treatment of chronic pain. Here, we summarize the distinct roles of Nox1, Nox2, and Nox4 in inflammatory and neuropathic processing and discuss the effectiveness of currently available Nox inhibitors in the treatment of chronic pain conditions.
Effects of Pasteurella multocida on Histopathology, miRNA and mRNA Expression Dynamics in Lung of Goats

Simple Summary Pasteurella multocida (Pm) infection can cause pasteurellosis in goats. Currently, the mechanisms of Pm infection in goats are limited. In this study, the effects of Pm infection to goats were characterized from the aspects of histopathology, miRNA and mRNA expression dynamics in lung of goats infected for 1, 2, 5 and 7 days and the clinical symptoms of animals. We further revealed the potential role of differentially expressed RNAs, which are commonly involved in and regulate the host immune reaction to the Pm infection. The differentially expressed genes were mapped to marker genes of the immune cells in the lung, which further confirmed the cells detected by the histopathological method. Abstract Pasteurella multocida (Pm) infection causes severe respiratory disease in goats. We investigated the effects of the Pm infection intratracheally on the histopathology, miRNA and mRNA expression dynamics in the lung of goats infected for 1, 2, 5 and 7 days. Pm infection caused fever, which significantly (p < 0.05) increased the body temperature of the goats from day 1 to 5. Haemotoxylin–eosin staining of the infected lung tissue showed characteristics of suppurative pneumonia with inflammatory cells infiltration and the lung structure destruction. During the Pm infection of the goats, compared with the control group, there were 3080, 3508, 2716 and 2675 differentially expressed genes and 42, 69, 91 and 108 significantly expressed miRNAs (|log2Fold Change| > 1, p < 0.05) in the Pm_d1, Pm_d2, Pm_d5 and Pm_d7 groups, respectively. Five miRNAs and nine immune-related genes were selected for confirmation by reverse transcription–polymerase chain reaction. The results indicated that the expression patterns of the miRNAs and genes were consistent with those determined by next-generation sequencing. The differentially expressed genes were enriched in cytokine–cytokine receptor interaction, cell adhesion molecules, complement and coagulation cascades, tight junction and phagosome Kyoto Encyclopedia of Genes and Genomes pathways and cytokine production, leukocyte migration, myeloid leukocyte migration, cell periphery, plasma membrane, extracellular region part, extracellular region and other Gene Ontology terms. The differentially expressed genes were mapped to marker genes in human and mouse lung cells. The results showed the presence of some marker genes of the immune cells. Compared with the CK group, five miRNAs and 892 common genes were differentially expressed in the Pm_d1, Pm_d2, Pm_d5 and Pm_d7 groups. The target relationships between the common 5 miRNAs and 892 differentially expressed genes were explored and the miRNAs involved in the host immune reaction may act through the target genes. Our study characterized goats’ reaction in the lung from histopathological and molecular changes upon Pm infection, which will provide valuable information for understanding the responses in goats during Pm infection.
A CMOS AFE With 37-nArms Input-Referred Noise and Marked 96-dB Timing DR for Pulsed LiDAR

This paper presents an analog front-end (AFE) circuit with marked timing point for pulsed time-of-flight LiDAR that employs either sampling- or event-based timing approach. The proposed AFE adopts a dual-mode structure for its pre-amplifier which can be configured as a charge-sensitive amplifier (CSA) or a gated active load-assisted TIA (GALA-TIA), depending on the intensity of input current. As a result, both the sensitivity and dynamic range (DR) of the AFE have been effectively improved. In addition, the zero-crossing point of the output signal has been marked as the timing point with a built-in pulse shaper, which allows the back-end circuits of LiDAR receiver discriminate the timing conveniently and accurately. The measured input-referred RMS noise current of the proposed AFE is 37 nA. With dual-mode control, a linear output DR of 80 dB and a wide timing DR of 96 dB with walk error no more than ±160 ps have been achieved. For single-shot measurement application, only CSA mode was enabled and the pulse widths of saturated output signals have been measured to compensate the walk errors, which realized a timing DR of 78 dB with accuracy of ±150 ps. The averaged power consumption is 66 mW and the total silicon area is $0.79\times 0.42\,\,mm^{2}$ in 0.18- $\mu \text{m}$ CMOS process.