Miracle-dz/UniFAR-FTUs huggingface dataset:
Ada-copy: An Adaptive Memory Copy Strategy for Virtual Machine Live Migration

In the cloud computing architecture, virtual machine (VM) live migration is a fundamental research topic which has drawn extensive attention from communities of industry and academy. It is critical to transfer the VM memory pages that contain essential state information to resume the VM on another host during virtual machine (VM) live migration. There are many memory copy methods, such as pre-copy and post-copy. However, these methods have two limitations: application generality and performance imbalance. In this paper, we propose Ada-copy (adaptive copy), an adaptive memory copy strategy for VM live migration. The basic idea of Ada-copy is that the memory copy method of a VM should be determined by its workload characteristics. Specifically, based on the variation of current dirty page rate of memory, Ada-copy can adaptively select the most appropriate migration method to copy memory pages, thus addressing the two limitations of existing memory copy methods. To evaluate the effectiveness of our proposed strategy, we experiment with the Ada-copy on a variety of migration tasks with different dirty page rate and diverse memory usage workloads. Evaluation results show, compared with traditional methods, Ada-copy can significantly reduce the total migration time by 26%, the VM downtime by 42% and the amount of pages transferred by 35% in average.
CrowdRev: A platform for Crowd-based Screening of Literature Reviews

In this paper and demo we present a crowd and crowd+AI based system, called CrowdRev, supporting the screening phase of literature reviews and achieving the same quality as author classification at a fraction of the cost, and near-instantly. CrowdRev makes it easy for authors to leverage the crowd, and ensures that no money is wasted even in the face of difficult papers or criteria: if the system detects that the task is too hard for the crowd, it just gives up trying (for that paper, or for that criteria, or altogether), without wasting money and never compromising on quality.
Culture and Differentiation of Monocyte Derived Macrophages Using Human Serum: An Optimized Method

Background: Monocyte derived macrophages (MDMs) are appropriate in vitro models to study the function of macrophages in immune related diseases. Not only most of the methods in literature for efficient MDM culture and differentiation are expensive but also they require specific equipment. However, there are some reports indicating that monocyte enrichment is possible through attachment. Purification and differentiation of macrophages occurs in media containing human serum or platelet depleted plasma without extra supplementations. Different variables such as incubation time and serum concentration affect this simple MDM preparation method. Objectives: Here we represent an optimized simple method for MDM preparation from peripheral blood mononuclear cells (PBMC). Materials and Methods: To introduce an optimized method we accomplished the present descriptive study. After PBMC isolation and monocyte enrichment in complete RPMI 1640 growth media, macrophages were cultured and differentiated using human serum. Efficient phagocytosis was evaluated using heat-inactivated Escherichia coli followed by SYBR staining. Geimsa staining of macrophages was accomplished to visualize the typical morphology under light microscopy. Results: The derived macrophages have the typical morphology of differentiated macrophages and are able to phagocyte the heat inactivated SYBR stained E. coli. Conclusions: This optimized method is a simple and cost effective method to prepare MDM with typical morphology representations able to phagocytosis efficiently.
Eon Mode: Bringing the Vertica Columnar Database to the Cloud

The Vertica Analytic Database is a powerful tool for high performance, large scale SQL analytics. Historically, Vertica has managed direct-attached disk for performance and reliability, at a cost of product complexity and scalability. Eon mode is a new architecture for Vertica that places the data on a reliable shared storage, matching the original architecture's performance on existing workloads and supporting new workloads. While the design reuses Vertica's optimizer and execution engine, the metadata, storage, and fault tolerance mechanisms are re-architected to enable and take advantage of shared storage. A sharding mechanism distributes load over the nodes while retaining the capability of running node-local table joins. Running on Amazon EC2 compute and S3 storage, Eon mode demonstrates good performance, superior scalability, and robust operational behavior. With these improvements, Vertica delivers on the promise of cloud economics, consuming only the compute and storage resources needed, while supporting efficient elasticity.
Focal sweep imaging with multi-focal diffractive optics

Depth-dependent defocus results in a limited depth-of-field in consumer-level cameras. Computational imaging provides alternative solutions to resolve all-in-focus images with the assistance of designed optics and algorithms. In this work, we extend the concept of focal sweep from refractive optics to diffractive optics, where we fuse multiple focal powers onto one single element. In contrast to state-of-the-art sweep models, ours can generate better-conditioned point spread function (PSF) distributions along the expected depth range with drastically shortened (40%) sweep distance. Further by encoding axially asymmetric PSFs subject to color channels, and then sharing sharp information across channels, we preserve details as well as color fidelity. We prototype two diffractive imaging systems that work in the monochromatic and RGB color domain. Experimental results indicate that the depth-of-field can be significantly extended with fewer artifacts remaining after the deconvolution.
Post-Traumatic Growth in Children and Adolescents

Introduction: Children and adolescents often suffer from adverse or even traumatic events. While clinicians and researchers so far have focused predominantly on their negative consequences more recently it has been postulated that traumatic events may exert positive effects in some individuals. In this context the concept of post-traumatic growth (PTG) has been investigated increasingly in adults. However, so far data in children and adolescents is rare. Method: We performed a narrative review of the current literature regarding PTG especially in children and adolescents as well as the pertinent literature on the PTG framework in general. Results: Data indicates that PTG in youth is quite similar to that observed among adults and can be assessed reliably in childhood and adolescents. However, mechanisms underlying the origination of PTG are still not sufficiently understood and further factors influencing its development have to be identified. Furthermore, there seems to be an overlap between PTG and concepts of resilience. Conclusion: PTG should be considered in the aftermath of trauma and may be useful in therapeutic contexts. There is a considerable dearth of objective measures of PTG causing an intensive debate whether PTG is a real positive identity change or rather a kind of safety mechanism that may be interpreted as a subconscious strategy. Neurobiological data may help to further investigate the “real” character of PTG in the future.
Antibacterial Activity of Silver Nanoparticles: Structural Effects

The increase of antibiotic resistance in bacteria has become a major concern for successful diagnosis and treatment of infectious diseases. Over the past few decades, significant progress has been achieved on the development of nanotechnology‐based medicines for combating multidrug resistance in microorganisms. Among this, silver nanoparticles (AgNPs) hold great promise in addressing this challenge due to their broad‐spectrum and robust antimicrobial properties. This review illustrates the antibacterial mechanisms of silver nanoparticles and further elucidates how different structural factors including surface chemistry, size, and shape, impact their antibacterial activities, which are expected to promote the future development of more potent silver nanoparticle‐based antibacterial agents.
High parasite diversity accelerates host adaptation and diversification

Between bacteria and phages, increasing phage diversity accelerates arms races with the host and leads to increased bacterial divergence. Multiple parasites speed host evolution Virtually all organisms are parasitized by multiple species, but our current understanding of host-parasite interactions is based on pairwise species interactions. Betts et al. address this by using the bacterium Pseudomonas aeruginosa and five different phage virus parasites. Increasing parasite diversity accelerated the rate of host evolution, driving both faster genomic evolution within populations and greater divergence between populations. Thus, different parasite loads prompt different evolutionary dynamics and profoundly shape host evolution by different mechanisms. Science, this issue p. 907 Host-parasite species pairs are known to coevolve, but how multiple parasites coevolve with their host is unclear. By using experimental coevolution of a host bacterium and its viral parasites, we revealed that diverse parasite communities accelerated host evolution and altered coevolutionary dynamics to enhance host resistance and decrease parasite infectivity. Increases in parasite diversity drove shifts in the mode of selection from fluctuating (Red Queen) dynamics to predominately directional (arms race) dynamics. Arms race dynamics were characterized by selective sweeps of generalist resistance mutations in the genes for the host bacterium’s cell surface lipopolysaccharide (a bacteriophage receptor), which caused faster molecular evolution within host populations and greater genetic divergence among populations. These results indicate that exposure to multiple parasites influences the rate and type of host-parasite coevolution.
ECI-Cache

In recent years, high interest in using Virtual Machines (VMs) in data centers and Cloud computing has significantly increased the demand for high-performance data storage systems. A straightforward approach to provide a high performance storage system is using Solid-State Drives (SSDs). Inclusion of SSDs in storage systems, however, imposes significantly higher cost compared to Hard Disk Drives (HDDs). Recent studies suggest using SSDs as a caching layer for HDD-based storage subsystems in virtualization platforms. Such studies neglect to address the endurance and cost of SSDs, which can significantly affect the efficiency of I/O caching. Moreover, previous studies only configure the cache size to provide the required performance level for each VM, while neglecting other important parameters such as cache write policy and request type, which can adversely affect both performance-per-cost and endurance. In this paper, we present a new high-Endurance and Cost-efficient I/O Caching (ECI-Cache) scheme for virtualized platforms, which can significantly improve both the performance-per-cost and endurance of storage subsystems as opposed to previously proposed I/O caching schemes. Unlike traditional I/O caching schemes which allocate cache size only based on reuse distance of accesses, we propose a new metric, Useful Reuse Distance (URD), which considers the request type in reuse distance calculation, resulting in improved performance-per-cost and endurance for the SSD cache. Via online characterization of workloads and using URD, ECI-Cache partitions the SSD cache across VMs and is able to dynamically adjust the cache size and write policy for each VM. To evaluate the proposed scheme, we have implemented ECI-Cache in an open source hypervisor, QEMU (version 2.8.0), on a server running the CentOS 7 operating system (kernel version 3.10.0-327). Experimental results show that our proposed scheme improves the performance, performance-per-cost, and endurance of the SSD cache by 17%, 30% and 65%, respectively, compared to the state-of-the-art dynamic cache partitioning scheme.
Pediatric reference intervals for general clinical chemistry components – merging of studies from Denmark and Sweden

Abstract Background: Reference intervals are crucial tools aiding clinicians when making medical decisions. However, for children such values often are lacking or incomplete. The present study combines data from separate pediatric reference interval studies of Denmark and Sweden in order to increase sample size and to include also pre-school children who were lacking in the Danish study. Methods: Results from two separate studies including 1988 healthy children and adolescents aged 6 months to 18 years of age were merged and recalculated. Eighteen general clinical chemistry components were measured on Abbott and Roche platforms. To facilitate commutability, the NFKK Reference Serum X was used. Results: Age- and gender-specific pediatric reference intervals were defined by calculating 2.5 and 97.5 percentiles. Conclusion: The data generated are primarily applicable to a Nordic population, but could be used by any laboratory if validated for the local patient population.
Genotypic Characterization of Rickettsia bellii Reveals Distinct Lineages in the United States and South America

The bacterium Rickettsia bellii belongs to a basal group of rickettsiae that diverged prior to the pathogenic spotted fever group and typhus group Rickettsia species. Despite a diverse representation of R. bellii across more than 25 species of hard and soft ticks in the American continent, phylogeographical relationships among strains of this basal group-Rickettsia species are unknown; the work described here explores these relationships. DNA was extracted from 30 R. bellii tick isolates: 15 from the United States, 14 from Brazil, and 1 from Argentina. A total of 2,269 aligned nucleotide sites of 3 protein coding genes (gltA, atpA, and coxA) and 2 intergenic regions (rpmE-tRNAfmet and RC1027-xthA2) were concatenated and subjected to phylogenetic analysis by Bayesian methods. Results showed a separation of almost all isolates between North and South Americas, suggesting that they have radiated within their respective continents. Phylogenetic positions of the 30 isolates could be a result of not only their geographical origin but also the tick hosts they have coevolved with. Whether R. bellii originated with ticks in North or South America remains obscure, as our analyses did not show evidence for greater genetic divergence of R. bellii in either continent.
Imperfect Monitoring of Job Search: Structural Estimation and Policy Design

We build and estimate a nonstationary structural job search model that incorporates the main stylized features of a typical job search monitoring scheme in unemployment insurance (UI) and acknowledges that search effort and requirements are measured imperfectly. On the basis of Belgian data, monitoring is found to affect search behavior only weakly because assessments were scheduled late and infrequently, the monitoring technology was not sufficiently precise, and lenient Belgian UI results in caseloads that are less responsive to incentives than elsewhere. Simulations show how changing the aforementioned design features can enhance effectiveness and that precise monitoring is key in this.
The Arabidopsis AtUNC-93 Acts as a Positive Regulator of Abiotic Stress Tolerance and Plant Growth via Modulation of ABA Signaling and K+ Homeostasis

Potassium (K+) is one of the essential macronutrients required for plant growth and development, and the maintenance of cellular K+ homeostasis is important for plants to adapt to abiotic stresses and growth. However, the mechanism involved has not been understood clearly. In this study, we demonstrated that AtUNC-93 plays a crucial role in this process under the control of abscisic acid (ABA). AtUNC-93 was localized to the plasma membrane and mainly expressed in the vascular tissues in Arabidopsis thaliana. The atunc-93 mutants showed typical K+-deficient symptoms under low-K+ conditions. The K+ contents of atunc-93 mutants were significantly reduced in shoots but not in roots under either low-K+ or normal conditions compared with wild type plants, whereas the AtUNC-93-overexpressing lines still maintained relatively higher K+ contents in shoots under low-K+ conditions, suggesting that AtUNC-93 positively regulates K+ translocation from roots to shoots. The atunc-93 plants exhibited dwarf phenotypes due to reduced cell expansion, while AtUNC-93-overexpressing plants had larger bodies because of increased cell expansion. After abiotic stress and ABA treatments, the atunc-93 mutants was more sensitive to salt, drought, osmotic, heat stress and ABA than wild type plants, while the AtUNC-93-overexpressing lines showed enhanced tolerance to these stresses and insensitive phenotype to ABA. Furthermore, alterations in the AtUNC-93 expression changed expression of many ABA-responsive and stress-related genes. Our findings reveal that AtUNC-93 functions as a positive regulator of abiotic stress tolerance and plant growth by maintaining K+ homeostasis through ABA signaling pathway in Arabidopsis.
CuisineNet: Food Attributes Classification using Multi-scale Convolution Network

Diversity of food and its attributes represents the culinary habits of peoples from different countries. Thus, this paper addresses the problem of identifying food culture of people around the world and its flavor by classifying two main food attributes, cuisine and flavor. A deep learning model based on multi-scale convotuional networks is proposed for extracting more accurate features from input images. The aggregation of multi-scale convolution layers with different kernel size is also used for weighting the features results from different scales. In addition, a joint loss function based on Negative Log Likelihood (NLL) is used to fit the model probability to multi labeled classes for multi-modal classification task. Furthermore, this work provides a new dataset for food attributes, so-called Yummly48K, extracted from the popular food website, Yummly. Our model is assessed on the constructed Yummly48K dataset. The experimental results show that our proposed method yields 65% and 62% average F1 score on validation and test set which outperforming the state-of-the-art models.
Guest Editors’ Introduction

Cybersecurity underpins the lives of ordinary people—their safety, work, health, and entertainment. Yet despite its importance, cybersecurity is often approached in a reactive manner—taking corrective actions to “patch” vulnerabilities after they are detected or exploited. In the absence of fundamental improvements in formal processes and methods, the same or similar problems can recur. In contrast, a scientific vision for security and privacy should be proactive. The focus of this TOIT special section is to provide a forum to discuss and advance security and privacy by means of Artificial Intelligence (AI) approaches. Approaches that are intelligent and self-adaptive are crucial to deal with the complexities of effectively protecting sensitive assets in all security-critical domains. This is where research from the AI community can make a difference in security and privacy. Specifically, AI can help address a long-standing problem, namely, that security and privacy are attempted to be inserted as an afterthought, which is rarely adequate. We identify the following key areas in AI, and review advancements in such areas that would help solve fundamental hard problems regarding security (CyBOK 2017) and privacy (Such 2017). Normative models: Secure and privacy-aware governance of sociotechnical systems can only be achieved by bridging the divide between technical solutions to security and privacy such as access control systems and the human and social factors associated with the users of such systems. Development of unified computational models for the social and the technical tiers of sociotechnical systems as well as their verification are therefore of utmost importance. Previous work (Barth et al. 2006; Chopra et al. 2014; Criado and Such 2016; Kafalı et al. 2016a; Singh 2013) has shown that a formalization of norms captures sociotechnical system concepts by regulating user interactions. Norms serve as a computational method for establishing user accountability by capturing a precise
On 5G Radio Access Network Slicing: Radio Interface Protocol Features and Configuration

Network slicing is a fundamental capability for future Fifth Generation (5G) networks to facilitate the cost-effective deployment and operation of multiple logical networks over a common physical network infrastructure in a way that each logical network (i.e. network slice) can be customized and dimensioned to best serve the needs of specific applications (e.g. mobile broadband, smart city, connected car, public safety, fixed wireless access) and users (e.g. general public, enterprise customers, virtual operators, content providers). The practical realization of such capability still raises numerous technical challenges, both in the Core and RAN parts of the 5G system. Through a comprehensive analysis of the impact that the realization of RAN slicing has on the different layers of the radio interface protocol architecture, this article proposes a framework for the support and specification of RAN slices based on the definition of a set of configuration descriptors that characterize the features, policies and resources to be put in place across the radio protocol layers of a next-generation RAN node.
New directors, customers, and fans: the transformation of English football in the 1990s.

In the 1990s, English professional football has undergone rapid and marked changes with the restructuring of the Football League, the signing of new and lucrative television contracts, the construction of all-seater stadiums, and the growing involvement of progressive entrepreneurial capitalists—the new directors—in the game. This article examines one element of those transformations; the political use which the new directors have made of the concept of the customer. The article argues that the use of this term has been important to the transformation of the relation between the fan and the clubs, facilitating and legitimating the profit-making projects of the new directors. Drawing on the tradition of dialectical critical theory derived from Mannheim and Adorno, the article submits this notion of the customer critique to demonstrate its deliberate partiality and its intensely political nature.
Effects of perturbation relative phase on transverse mode instability gain

We have shown that the relative phase between the fundamental fiber mode and the transverse perturbation affects significantly the local transverse modal instability (TMI) gain. The gain variation is more pronounced as the core diameter increases. This finding can be used in conjunction with other proposed approaches to develop efficient strategies for mitigating TMI in high power fiber amplifiers and lasers. It also provides some physical insight on the physical origin of the observed large differences in the TMI threshold dependence on core diameter for narrow and broad linewidth operation.
Controlling Guessing Bias in the Dichotomous Rasch Model Applied to a Large-Scale, Vertically Scaled Testing Program

Recent research has shown how the statistical bias in Rasch model difficulty estimates induced by guessing in multiple-choice items can be eliminated. Using vertical scaling of a high-profile national reading test, it is shown that the dominant effect of removing such bias is a nonlinear change in the unit of scale across the continuum. The consequence is that the proficiencies of the more proficient students are increased relative to those of the less proficient. Not controlling the guessing bias underestimates the progress of students across 7 years of schooling with important educational implications.