Miracle-dz/UniFAR-FTUs huggingface dataset:
Joint Resource Allocation and Power Control Based on Vehicle's Motion Characteristics in NOMA-Based V2V Systems

Due to the high spectrum utilization of Nonorthogonal Multiple Access (NOMA), it becomes one of the potential candidate technologies for future wireless communication systems. Meanwhile, in New Radio, Vehicle to Everything (V2X) has been proposed as a promising issue in the 3rd Generation Partnership Project (3GPP). This paper studies the resource allocation mechanism with power control strategy which makes full use of vehicles’ moving characteristics in the NOMA-based Vehicle to Vehicle (V2V) communication system. Firstly, vehicles are grouped according to their moving characteristics by spectral clustering. Then, vehicles which are in the same group are allocated the same wireless resource with NOMA strategy. Two grouping methods have been designed for freeway and urban scenarios separately. After that, the transmission power of vehicles is adjusted based on the result of power control strategy utilizing Q-learning. The simulation results show that the performance of the V2V system in terms of Packet Received Ratio (PRR) can be evidently improved by the proposed joint NOMA resource allocation and power control mechanism compared to typical energy sensing-based resource allocation method.
Making AI Machines Work for Humans in FoW

The Future of Work (FoW) is witnessing an evolution where AI systems (broadly machines or businesses) are used to the benefit of humans. Work here refers to all forms of paid and unpaid labor in both physical and virtual workplaces and that is enabled by AI systems. This covers crowdsourcing platforms such as Amazon Mechanical Turk, online labor marketplaces such as TaskRabbit and Qapa, but also regular jobs in physical workplaces. Bringing humans back to the frontier of FoW will increase their trust in AI systems and shift their perception to use them as a source of self-improvement, ensure better work performance, and positively shape social and economic outcomes of a society and a nation. To enable that, physical and virtual workplaces will need to capture human traits, behavior, evolving needs, and provide jobs to all. Attitudes, values, opinions regarding the processes and policies will need to be assessed and considered in the design of FoW ecosystems.
Improving the Restore Performance via Physical-Locality Middleware for Backup Systems

Data deduplication as an important middleware plays an essential role in current backup systems due to the high space efficiency, which however suffers from low restore performance, since the chunks are heavily fragmented. Existing systems leverage caching and rewriting schemes to reduce the number of container reads to restore the original data. However, when storing a large number of versions, the caching schemes become inefficient since each cached container consists of a few required chunks due to the exacerbated fragmentation, while the rewriting schemes consume more space to store the duplicate chunks. In this paper, we explore and exploit the behaviors of the fragmented chunks in the backup systems. Based on the observations, we propose the open-sourced HiDeStore1, a High-performance Deduplication and reStore backup system without decreasing the deduplication ratio. The main insight is to enhance the physical locality for the new backup versions during the deduplication process. Thus, the chunks are stored closely and the number of container reads significantly decreases to restore the original data. Compared with state-of-the-art deduplication and restore schemes, HiDeStore reduces the index lookup overhead by 38% and improves the restore performance by up to 1.6x, without decreasing the deduplication ratio.
Can You Trust Your Number Sense: Distinct Processing of Numbers and Quantities in Elementary School Children

Theories of number development have traditionally argued that the acquisition and discrimination of symbolic numbers (i.e., number words and digits) are grounded in and are continuously supported by the Approximate Number System (ANS)—an evolutionarily ancient system for number. In the current study, we challenge this claim by investigating whether the ANS continues to support the symbolic number processing throughout development. To this end, we tested 87 first(Age M = 6.54 years, SD = 0.58), third(Age M = 8.55 years, SD = 0.60) and fifth-graders (Age M = 10.63 years, SD = 0.67) on four audio-visual comparison tasks (1) Number words–Digits, (2) Tones–Dots, (3) Number words–Dots, (4) Tones–Digits, while varying the Number Range (Small and Large), and the Numerical Ratio (Easy, Medium, and Hard). Results showed that larger and faster developmental growth in the performance was observed in the Number Words–Digits task, while the tasks containing at least one non-symbolic quantity showed smaller and slower developmental change. In addition, the Ratio effect (i.e., the signature of ANS being addressed) was present in the Tones–Dots, Tones–Digits, and Number Words–Dots tasks, but was absent in the Number Words–Digits task. These findings suggest that it is unlikely that the ANS continuously underlines the acquisition and the discrimination of the symbolic numbers. Rather, our results indicate that non-symbolic quantities and symbolic numbers follow qualitatively distinct developmental paths, and argue that the latter ones are processed in a semantic network which starts to emerge from an early age.
BoLT: Barrier-optimized LSM-Tree

Key-value stores such as LevelDB and RocksDB are widely used in various systems due to their high write performance. However, the background compaction operations inherent to the key-value stores are often to blame for write amplification and write stall. In particular, the SSTable size in the existing key-value stores introduces, upon compactions, a tradeoff between the fsync() call frequency and the amount of amplified writes. Small SSTables require a larger number of fsync()/fdatasync() than large SSTables to maintain file consistency. On the contrary, large SSTables result in large overlaps and frequent rewrites of SSTables. In this paper, to reduce file consistency overhead without increasing key ranges of SSTables, we present a variant of LSM-tree, namely, BoLT (Barrier-optimized LSM-Tree), that minimizes the number of calls to fsync()/fdatasync() barriers while taking advantage of fine-grained SSTables. BoLT consists of four key elements: (i) compaction file, (ii) logical SSTables, (iii) group compaction, and (iv) settled compaction. We implement BoLT in LevelDB and HyperLevelDB and compare the performances against LevelDB, HyperLevelDB, RocksDB, and the state-of-the-art PebblesDB. Our experimental study shows that BoLT achieves significantly higher write throughputs than LevelDB and HyperLevelDB.
An Agent based model for the transmission and control of the COVID-19 in Dijon (extended abstract)

The coronavirus disease (COVID-19) is a global threat with a profound impact on health and economy in the world. Realistic mathematical models are needed in order to evaluate the effects produced by the containment policies such as total or partial closure of facilities (universities, companies, shops). This goal can be reached using compartmental models with various degrees of sophistication [1,2]. Classical mean-field models assume an homogeneous population where all the individuals are identical. Metapopulation models go one step further by introducing a spatial dimension. The entire population is split into a finite number of sub-populations with their own local epidemic model and individuals commuting patterns. More recent models integrate individuals spatial and social structure as well as the awareness evolution of the population during the epidemic [3–5]. While these models allow to understand the macroscopic behavior of an epidemic in a large population, they are not well suited to analyze the transmission dynamics in small populations with complex behavior. On the contrary, agent-based modeling allows to observe the emergence of global behavioral patterns through a set of simple rules describing the interaction among individuals with distinct characteristics [6]. In this work, an agent-based model to evaluate the spatiotemporal transmission process of the COVID-19 in Dijon is presented. Simulated agents make decisions depending on spatial patterns and infection conditions. Each agent is characterized by an individual profile defining its main social characteristics and health conditions. The proposed framework allows to perform simulations on the progress of the COVID-19 virus. It relies on collected data required for simulating the epidemic spreading (before containment, after containment, containment measure, etc.), and the geospatial data associated with its semantics and reliable information. Based on the SEIR epidemiological model, it allows to carry out simulations according to different types of scenarios, such as a more or less virulent virus, more or less strict confinement rules, and the number of Intensive care units available. Initially, the study is restricted to Dijon city center in order to reduce the size of the geospatial data and the number of agents for simulations.
Evaluation on the Effects of Visual Intervention on Emotion and Fatigue While Driving Using Brainwave Indicator

In this modern era, driving has become one of the most common habit that humans do. However, this phenomenon can lead to a big problem. The more people drive, the higher the chance of a traffic accident can occur. This study investigated the effects of visual intervention on emotion and fatigue in car driving simulation using brainwave indicator or changes in electroencephalography (EEG). Frontal Alpha Asymmetry (FAA) method were used to determine the effects on emotion while Ratio method were used to determine the effects on fatigue level. Twenty males were recruited to perform a 40 minutes car driving simulation while frontal channel of EEG was recorded. This was a within subject experiment where each participant was given both no intervention and visual intervention treatment. For the FAA method, the no intervention had a tendency to fluctuate. Therefore, inducing both positive and negative emotions. Meanwhile, the visual intervention remains on the positive side throughout the driving session indicating that the visual intervention induced a more positive emotion. The results for the repeated measure test also indicate that there is a significant difference between interventions. For the Ratio, the fatigue level was decreased for the first 30 minutes on visual intervention. Meanwhile, the fatigue level did not decrease at all for no intervention. Significant differences were found on the first 30 minutes while for the last 10 minutes there were no significant differences. These findings can be utilized as baseline for a more comprehensive research regarding traffic safety.
secureTF: A Secure TensorFlow Framework

Data-driven intelligent applications in modern online services have become ubiquitous. These applications are usually hosted in the untrusted cloud computing infrastructure. This poses significant security risks since these applications rely on applying machine learning algorithms on large datasets which may contain private and sensitive information. To tackle this challenge, we designed secureTF, a distributed secure machine learning framework based on Tensorflow for the untrusted cloud infrastructure. secureTF is a generic platform to support unmodified TensorFlow applications, while providing end-to-end security for the input data, ML model, and application code. secureTF is built from ground-up based on the security properties provided by Trusted Execution Environments (TEEs). However, it extends the trust of a volatile memory region (or secure enclave) provided by the single node TEE to secure a distributed infrastructure required for supporting unmodified stateful machine learning applications running in the cloud. The paper reports on our experiences about the system design choices and the system deployment in production use-cases. We conclude with the lessons learned based on the limitations of our commercially available platform, and discuss open research problems for the future work.
TEEMon: A continuous performance monitoring framework for TEEs

Trusted Execution Environments (TEEs), such as Intel Software Guard eXtensions (SGX), are considered as a promising approach to resolve security challenges in clouds. TEEs protect the confidentiality and integrity of application code and data even against privileged attackers with root and physical access by providing an isolated secure memory area, i.e., enclaves. The security guarantees are provided by the CPU, thus even if system software is compromised, the attacker can never access the enclave's content. While this approach ensures strong security guarantees for applications, it also introduces a considerable runtime overhead in part by the limited availability of protected memory (enclave page cache). Currently, only a limited number of performance measurement tools for TEE-based applications exist and none offer performance monitoring and analysis during runtime. This paper presents TEEMon, the first continuous performance monitoring and analysis tool for TEE-based applications. TEEMon provides not only fine-grained performance metrics during runtime, but also assists the analysis of identifying causes of performance bottlenecks, e.g., excessive system calls. Our approach smoothly integrates with existing open-source tools (e.g., Prometheus or Grafana) towards a holistic monitoring solution, particularly optimized for systems deployed through Docker containers or Kubernetes and offers several dedicated metrics and visualizations. Our evaluation shows that TEEMon's overhead ranges from 5% to 17%.
Determining Progression in Ectatic Corneal Disease

Abstract Before the advent of modern tomographic imaging and corneal cross-linking (CXL), diagnosis and treatment of ectatic disease were limited to disease severity where changes on the anterior corneal surface lead to visual complaints. Rigid contact lenses and/or penetrating keratoplasty addressed late stage disease, as identifying early or subclinical disease was not possible, or its need appreciated. The emergence of CXL as a viable treatment to alter the natural progression of keratoconus heightened the need for improved diagnostics. Several methods have been described in the literature to evaluate and document progression in keratoconus, but there has been no consistent definition of ectasia progression. Newer imaging techniques (ie, tomography) allowed the detection of earlier ectatic disease, before visual loss and subjective complaints. The Belin ABCD classification/staging system was introduced on a Scheimpflug imaging system [Pentacam, (Oculus GmbH, Wetzlar, Germany)] to address previous shortcomings. The ABCD system utilizes 4 parameters: Anterior (“A”) and posterior (“B” for Back) radius of curvature taken from a 3.0 mm optical zone centered on the thinnest point, “C” is minimal Corneal thickness, and “D” best spectacle Distance visual acuity. The first 3 parameters (A, B, C) are machine-generated objective measurements that can be used to determine progressive change. The staging system is not limited to a specific commercial entity and can be incorporated in any tomographic imaging system. The ABCD Progression Display graphically displays each parameter and shows when statistical change above measurement noise is reached. This should allow the clinician the ability to diagnose progressive disease at a much earlier stage than was previously possible, with the confidence that earlier intervention could prevent visual loss.
HEAT SHOCK INDUCED MORPHO-PHYSIOLOGICAL RESPONSE IN INDICA RICE (ORYZA SATIVA L.) AT EARLY SEEDLING STAGE

Heat stress is a serious threat for rice production in various localities around the world. Present research was conducted to explore the mechanism of heat tolerance in rice at early seedling stage. Forty six rice genotypes including 39 mutants (M5generation) of super basmati and 7 varieties were subjected to heat stress (45±2°C) for 12 h followed by three days recovery under normal temperature (28±2°C). The relative heat tolerance of genotypes was assessed on the basis of various morphological (fresh and dry leaf weight, fresh and dry weight of seedlings) and physiological (relative water contents (RWC), cell membrane thermo-stability (CMTS), photosynthetic pigments and malondialdehyde (MDA)) parameters. Significant variation was observed among the tested rice genotypes for morpho-physiological response. Based on relatively higher CMTS, RWC and photosynthetic pigments along with higher fresh and dry weights of leaves and seedlings, and less MDA content, fifteen genotypes including 11 mutants and four varieties were identified as heat tolerant. HTT-1 was identified as moderately heat sensitive mutant. In conclusion, tested morpho-physiological markers were useful to screen rice germplasm for heat tolerance at early growth stage. In addition, Kashmir basmati and HTT-114 can be used as heat tolerant check and HTT-1 can be used as heat sensitive check in screening experiments at early growth stage.
Action of anesthetics on membranes and protein adsorption on solid surfaces studied by molecular dynamics simulations

In this thesis, the mechanisms underlying anesthesia and the adsorption of proteins on solid surfaces have been studied using the method of molecular dynamics simulations. It is generally assumed that biological membranes are the site of anesthetic action. However, there is no consensus whether anesthetics act directly by binding to membrane proteins, thereby inhibiting their function, or indirectly by modulating the physical properties of the lipid part of the membrane. In the simulations presented here, distinct changes of lipid bilayer properties in response to the presence of alkanols, a group of anesthetics, have been observed. An anesthetic-induced shift of the equilibrium between different membrane protein conformations, modeled by simple geometric shapes, has been found. In simulations with the ion channel gramicidin A embedded in a lipid bilayer, alkanols distributed inhomogeneously in the bilayer, with almost no alkanol molecules residing in close vicinity to the gramicidin. These results provide evidence for an indirect mode of anesthetic action. Spontaneous protein adsorption on solid-liquid interfaces is the first step in the formation of biofilms. Here, a coarse-grained molecular dynamics scheme has been applied to study this complex process at high resolution, but still reaching the necessary time and length scales. Changes in protein structure and dynamics after adsorption and preferred orientations of proteins on the surface were observed. In dieser Arbeit wurde die Wirkungsweise von Anasthetika und die Adsorption von Proteinen an Festkorperoberflachen mittels Molekuldynamik-Simulationen untersucht. Es wird allgemein angenommen, dass Anasthetika auf biologische Membranen wirken. Umstritten ist jedoch, ob Anasthetika direkt an Membranproteine binden und damit deren Funktion hemmen, oder ob sie indirekt wirken, indem sie die physikalischen Eigenschaften der Lipiddoppelschicht der Membran verandern. Solche indirekten Effekte wurden in den hier vorgestellten Simulationen bei Anwesenheit von Alkanolen, einer Gruppe von Anasthetika, beobachtet. Gleichzeitig wurde eine durch Anasthetika verursachte Verschiebung des Gleichgewichts zwischen unterschiedlichen, vereinfacht dargestellten Proteinkonformationen gefunden. Simulationen eines in einer Lipiddoppelschicht eingebetteten Ionenkanals zeigten eine sehr geringe Konzentration von Alkanolen in unmittelbarer Nahe des Kanals. Diese Ergebnisse deuten auf eine indirekte Wirkungsweise von Anasthetika hin. Spontane Adsorption von Proteinen an fest-flussig Grenzflachen ist der erste Schritt bei der Bildung von Biofilmen. Um diesen Prozess der Proteinadsorption mit hoher Auflosung auf ausreichend langen Zeit- und Langenskalen zu untersuchen, wurde ein "coarse-grained" Molekuldynamik-Schema verwendet. Es wurden Veranderungen in der Proteinstruktur und -dynamik und bevorzugte Ausrichtungen der Proteine auf der Oberflache beobachtet.
Elastic Constants of Aluminum

The adiabatic elastic constants of aluminum have been measured with an ultrasonic pulse technique at liquid‐heluim, liquid‐nitrogen, and room temperatures. The values of the elastic constants at 4°K are c11=11.63, c12=6.48, and c44=3.09 in units of 1010 N/m2. The Debye characteristic temperature calculated from these figures is θ=425°K in good agreement with the value obtained from speciffic heat data.The shear elastic constants ½(c11−c12) and c44 are discussed with reference to the theory given by Leigh.
Theory-based Behavioral Predictors of Self-reported Use of Face Coverings in Public Settings during the COVID-19 Pandemic in the United States

Abstract Background Investigating antecedents of behaviors, such as wearing face coverings, is critical for developing strategies to prevent SARS-CoV-2 transmission. Purpose The purpose of this study was to determine associations between theory-based behavioral predictors of intention to wear a face covering and actual wearing of a face covering in public. Methods Data from a cross-sectional panel survey of U.S. adults conducted in May and June 2020 (N = 1,004) were used to test a theory-based behavioral path model. We (a) examined predictors of intention to wear a face covering, (b) reported use of cloth face coverings, and (c) reported use of other face masks (e.g., a surgical mask or N95 respirator) in public. Results We found that being female, perceived importance of others wanting the respondent to wear a face covering, confidence to wear a face covering, and perceived importance of personal face covering use was positively associated with intention to wear a face covering in public. Intention to wear a face covering was positively associated with self-reported wearing of a cloth face covering if other people were observed wearing cloth face coverings in public at least “rarely” (aOR = 1.43), with stronger associations if they reported “sometimes” (aOR = 1.83), “often” (aOR = 2.32), or “always” (aOR = 2.96). For other types of face masks, a positive association between intention and behavior was only present when observing others wearing face masks “often” (aOR = 1.25) or “always” (aOR = 1.48). Conclusions Intention to wear face coverings and observing other people wearing them are important behavioral predictors of adherence to the CDC recommendation to wear face coverings in public.