Miracle-dz/UniFAR-FTUs huggingface dataset:
Feature Selection and Intrusion Detection in Cloud Environment Based on Machine Learning Algorithms

Characteristics and way of behavior of attacks and infiltrators on computer networks are usually very difficult and need an expert. In addition; the advancement of computer networks, the number of attacks and infiltrations is also increasing. In fact, the knowledge coming from expert will lose its value over time and must be updated and made available to the system and this makes the need for expert person always felt. In machine learning techniques, knowledge is extracted from the data itself which has diminished the role of the expert. Various methods used to detect intrusions, such as statistical models, safe system approach, neural networks, etc., all weaken the fact that it uses all the features of an information packet rotating in the network for intrusion detection. Also, the huge volume of information and the unthinkable state space is also an important issue in the detection of intrusion. Therefore, the need for automatic identification of new and suspicious patterns in attempt for intrusion with the use of more efficient methods (Lower cost and higher performance) is needed more than before. The purpose of this study is to provide a new method based on intrusion detection systems and its various architectures aimed at increasing the accuracy of intrusion detection in cloud computing.
Relationship between Injury and Spirituality in Pilgrims on the Camino de Santiago

The purpose of this research was to determine whether there is a relationship between spirituality and the likelihood of injury and the impact of that injury on pilgrims walking along the Camino de Santiago; an ancient, 791 km pilgrimage route along the north of Spain from the French Pyrenees to Santiago de Compostela in Galicia, Spain.
Adjuvant Chemotherapy Guided by a 21‐Gene Expression Assay in Breast Cancer

BACKGROUND The recurrence score based on the 21‐gene breast cancer assay predicts chemotherapy benefit if it is high and a low risk of recurrence in the absence of chemotherapy if it is low; however, there is uncertainty about the benefit of chemotherapy for most patients, who have a midrange score. METHODS We performed a prospective trial involving 10,273 women with hormone‐receptor–positive, human epidermal growth factor receptor 2 (HER2)–negative, axillary node–negative breast cancer. Of the 9719 eligible patients with follow‐up information, 6711 (69%) had a midrange recurrence score of 11 to 25 and were randomly assigned to receive either chemoendocrine therapy or endocrine therapy alone. The trial was designed to show noninferiority of endocrine therapy alone for invasive disease–free survival (defined as freedom from invasive disease recurrence, second primary cancer, or death). RESULTS Endocrine therapy was noninferior to chemoendocrine therapy in the analysis of invasive disease–free survival (hazard ratio for invasive disease recurrence, second primary cancer, or death [endocrine vs. chemoendocrine therapy], 1.08; 95% confidence interval, 0.94 to 1.24; P=0.26). At 9 years, the two treatment groups had similar rates of invasive disease–free survival (83.3% in the endocrine‐therapy group and 84.3% in the chemoendocrine‐therapy group), freedom from disease recurrence at a distant site (94.5% and 95.0%) or at a distant or local–regional site (92.2% and 92.9%), and overall survival (93.9% and 93.8%). The chemotherapy benefit for invasive disease–free survival varied with the combination of recurrence score and age (P=0.004), with some benefit of chemotherapy found in women 50 years of age or younger with a recurrence score of 16 to 25. CONCLUSIONS Adjuvant endocrine therapy and chemoendocrine therapy had similar efficacy in women with hormone‐receptor–positive, HER2‐negative, axillary node–negative breast cancer who had a midrange 21‐gene recurrence score, although some benefit of chemotherapy was found in some women 50 years of age or younger. (Funded by the National Cancer Institute and others; TAILORx ClinicalTrials.gov number, NCT00310180.)
Crowdsourced Software Design Platforms: Critical Assessment

There is a great interest towards the use of crowdsourcing into software development activities including: Requirements engineering, implementation, testing, evaluation and the focus of this research, design. Software design is one of the least explored activities within the concept of crowdsourcing. Therefore, this research provides a comprehensive coverage on the current state-of-the-art in the use of crowdsourcing in software design. It analyzes the current existing major crowdsourced software design platforms and discusses their workflows. The analysis results in identifying a set of limitations in the current platforms and improvements are proposed to overcome those limitations. Both findings of this research including (limitations and improvements) are validated by creating and distributing a questionnaire to software practitioners to justify the need to overcome those limitations through the proposed improvements.
The real tau‐conjecture is true on average

Koiran's real τ‐conjecture claims that the number of real zeros of a structured polynomial given as a sum of m products of k real sparse polynomials, each with at most t monomials, is bounded by a polynomial in mkt. This conjecture has a major consequence in complexity theory since it would lead to superpolynomial lower bounds for the arithmetic circuit size of the permanent. We confirm the conjecture in a probabilistic sense by proving that if the coefficients involved in the description of f are independent standard Gaussian random variables, then the expected number of real zeros of f is 𝒪(mk2t) .
Magnetic Detection Structure for Lab-on-Chip Applications Based on the Frequency Mixing Technique

A magnetic frequency mixing technique with a set of miniaturized planar coils was investigated for use with a completely integrated Lab-on-Chip (LoC) pathogen sensing system. The system allows the detection and quantification of superparamagnetic beads. Additionally, in terms of magnetic nanoparticle characterization ability, the system can be used for immunoassays using the beads as markers. Analytical calculations and simulations for both excitation and pick-up coils are presented; the goal was to investigate the miniaturization of simple and cost-effective planar spiral coils. Following these calculations, a Printed Circuit Board (PCB) prototype was designed, manufactured, and tested for limit of detection, linear response, and validation of theoretical concepts. Using the magnetic frequency mixing technique, a limit of detection of 15 µg/mL of 20 nm core-sized nanoparticles was achieved without any shielding.
Energy-Efficient Timely Truck Transportation for Geographically-Dispersed Tasks

We consider a common truck operation scenario, where a long-haul heavy-duty truck drives across a national highway system to fulfill multiple geographically-dispersed tasks in a specific order. The objective is to minimize the total fuel consumption subject to the pickup and delivery time window constraints of individual tasks, by jointly optimizing task execution times, path planning, and speed planning. The need to coordinate execution times for multiple tasks differentiates our study from existing ones on single task. We first prove that our problem is NP-hard. Moreover, it is uniquely challenging to solve our problem, as we further show that optimizing task execution times is a non-convex puzzle. We then exploit the problem structure to develop (i) a Fully-Polynomial-Time Approximation Scheme (FPTAS), and (ii) a fast and efficient heuristic algorithm, called SPEED (Sub-gradient-based Price-driven Energy-Efficient Delivery). We characterize sufficient conditions under which SPEED generates an optimal solution, and derive an optimality gap for SPEED when the conditions are not satisfied. We evaluate the practical performances of our solutions using real-world traces over the US national highway. We observe that our solutions can save up to 22% fuel as compared to the fastest-/shortest- path baselines, and up to 10% fuel than a conceivable alternative generalized from the state-of-the-art single-task algorithm. The fuel saving is robust to the number of tasks to be fulfilled. Simulations also show that our algorithms always obtain close-to-optimal solutions and meet time window constraints for all feasible problem instances. In comparison, the conceivable alternative fails to meet time window constraints for up to 45% of the instances.
Slow luminescence kinetics of semi-synthetic aequorin: expression, purification and structure determination of cf3-aequorin

cf3-Aequorin is one of the semi-synthetic aequorins that was produced by replacing 2-peroxycoelenterazine (CTZ-OOH) in native aequorin with a 2-peroxycoelenterazine analog, and it was prepared using the C2-modified trifluoromethyl analog of coelenterazine (cf3-CTZ) and the histidine-tagged apoaequorin expressed in Escherichia coli cells. The purified cf3-aequorin showed a slow luminescence pattern with half-decay time of maximum intensities of luminescence of 5.0 s. This is much longer than that of 0.9 s for native aequorin, and its luminescence capacity was estimated to be 72.8% of that of native aequorin. The crystal structure of cf3-aequorin was determined at 2.15 Å resolution. The light source of 2-peroxytrifluoromethylcoelenterazine (cf3-CTZ-OOH) was stabilized by the hydrogen-bonding interactions at the C2-peroxy moiety and the p-hydroxy moiety at the C6-phenyl group. In native aequorin, three water molecules contribute to stabilizing CTZ-OOH through hydrogen bonds. However, cf3-aequorin only contained one water molecule, and the trifluoromethyl moiety at the C2-benzyl group of cf3-CTZ-OOH interacted with the protein by van der Waals interactions. The slow luminescence kinetics of cf3-aequorin could be explained by slow conformational changes due to the bulkiness of the trifluoromethyl group, which might hinder the smooth cleavage of hydrogen bonds at the C2-peroxy moiety after the binding of Ca2+ to cf3-aequorin.
miR-155 and miR-122 Expression of Spermatozoa in Obese Subjects

Obesity is characterized by mild chronic inflammation that is linked with impaired iron homeostasis. Studies in human and murine show that there is a transgenerational epigenetic inheritance via the gametes in obesity; however, there is little information on changes in the expression of microRNAs related to inflammation and iron homeostasis in spermatozoa from obese subjects. The present study investigated the expression of microRNAs related to inflammation (miR-21 y miR-155) and iron nutrition (miR-122 and miR-200b) in plasma, peripheral blood mononuclear cells (PBMC) and spermatozoa from normozoospermic controls (Cn; n = 17; BMI: 24.6 ± 2.0) and obese (Ob; n = 17; BMI: 32.6 ± 4.4) men. To determine the inflammation levels, we measured IL-6, TNF-α, and monocyte chemoattractant protein-1 (MCP1) by Magnetic Luminex® Assay. mRNA expression of IL6, TNF-α, and hepcidin (HAMP) in PBMC were evaluated by RT-qPCR. The analysis of microRNAs was performed using the Taqman® assays. The iron content in PBMC, seminal plasma, and spermatozoa was determined by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). High serum IL6, TNF-α, and MCP1 levels were observed in Ob group (p < 0.05). Gene expression analysis showed an increased abundance relative of TNF-α (p = 0.018), HAMP (p = 0.03), and IL6 (p = 0.02) in PBMC from obese subjects. Also, we observed high levels of serum ferritin (p = 0.03), iron content in seminal plasma (p = 0.04), and spermatozoa (p = 0.002), but lower serum Fe (p = 0.007) in obese subjects. In the Ob group, a high expression of miR-155 (p = 0.02) and miR-21 (p = 0.03) was observed in PBMC and miR-122 (p = 0.03) in plasma. In sperm, both miR-155 (p = 0.004) and miR-122 (p = 0.028) were high in the Ob group. Our results showed that obese subjects have increased expressions of miR-155 and miR-122, two microRNAs that were previously related with inflammation and iron metabolism, respectively, at both the systemic and sperm levels.
Optimal Algorithms for Min-Closed, Max-Closed and Arc Consistency over Connected Row Convex Constraints

A key research interest in the area of Constraint Satisfaction Problems (CSP) is to identify tractable classes of constraints and develop efficient algorithms for solving them. In this paper, we propose an optimal algorithm for solving r-ary min-closed and max-closed constraints. Assuming r = O(1), our algorithm has an optimal running time of O(ct) where c and t are the number of constraints and the maximum size of any constraint, respectively. This significantly improves the existing pairwise consistency based algorithm that takes O(c2t2) time. Moreover, for (binary) connected row convex (CRC) constraints, we design an optimal algorithm for arc consistency that runs in O(cd) time where d is the largest size of any domain. This again improves upon the existing O(cd2) algorithms. This, in turn, leads to a faster algorithm for solving CRC constraints. We also show how our solutions can be applied to determine problems in large distributed IT systems. The experimental evaluation shows that the proposed algorithms are several orders of magnitudes faster than the state-of-the-art algorithms.
De Novo Transcriptome Assembly and Characterization of Lithospermum officinale to Discover Putative Genes Involved in Specialized Metabolites Biosynthesis

Abstract Lithospermum officinale is a valuable source of bioactive metabolites with medicinal and industrial values. However, little is known about genes involved in the biosynthesis of these metabolites, primarily due to the lack of genome or transcriptome resources. This study presents the first effort to establish and characterize de novo transcriptome assembly resource for L. officinale and expression analysis for three of its tissues, namely leaf, stem, and root. Using over 4Gbps of RNA-sequencing datasets, we obtained de novo transcriptome assembly of L. officinale, consisting of 77,047 unigenes with assembly N50 value as 1524 bps. Based on transcriptome annotation and functional classification, 52,766 unigenes were assigned with putative genes functions, gene ontology terms, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. KEGG pathway and gene ontology enrichment analysis using highly expressed unigenes across three tissues and targeted metabolome analysis showed active secondary metabolic processes enriched specifically in the root of L. officinale. Using co-expression analysis, we also identified 20 and 48 unigenes representing different enzymes of lithospermic/chlorogenic acid and shikonin biosynthesis pathways, respectively. We further identified 15 candidate unigenes annotated as cytochrome P450 with the highest expression in the root of L. officinale as novel genes with a role in key biochemical reactions toward shikonin biosynthesis. Thus, through this study, we not only generated a high-quality genomic resource for L. officinale but also propose candidate genes to be involved in shikonin biosynthesis pathways for further functional characterization.
Structure of histone-based chromatin in Archaea

Origin of DNA compaction As a repeating unit in eukaryotic chromatin, a nucleosome wraps DNA in superhelical turns around a histone octamer. Mattiroli et al. present the crystal structure of an archaeal histone-DNA complex in which the histone-mediated DNA geometry is exactly the same as that in the nucleosome. Comparing features of archaeal and eukaryotic chromatin structures offers important insights into the evolution of eukaryotic nucleosomes. Science, this issue p. 609 Archaeal histone homodimers form a complex with DNA that is similar to the eukaryotic nucleosome. Small basic proteins present in most Archaea share a common ancestor with the eukaryotic core histones. We report the crystal structure of an archaeal histone-DNA complex. DNA wraps around an extended polymer, formed by archaeal histone homodimers, in a quasi-continuous superhelix with the same geometry as DNA in the eukaryotic nucleosome. Substitutions of a conserved glycine at the interface of adjacent protein layers destabilize archaeal chromatin, reduce growth rate, and impair transcription regulation, confirming the biological importance of the polymeric structure. Our data establish that the histone-based mechanism of DNA compaction predates the nucleosome, illuminating the origin of the nucleosome.
Hedging under square loss

The framework of minimum-variance hedging rests on a highly restrictive foundation. The objective of variance minimization is only justifiable when variance coincides with expected squared forecast error. Nevertheless, the classical framework is routinely applied when the condition fails, giving rise to inaccurate risk assessments and suboptimal hedging decisions. This study proposes a new, improved framework of hedging which relaxes the above condition at no tangible cost. It derives a new objective function, an optimal hedge ratio, and a measure of hedging effectiveness under square loss. Their superior performance is demonstrated from a theoretical standpoint and by applying them to hedging the price risk of oil and natural gas. Simple yet general, the new framework is well suited to replace the classical one and facilitates adequate risk measurement and improved hedging decisions. It also provides fundamental insight into dealing with uncertainty under square loss and beyond.
Phytoplankton iron limitation in the Humboldt Current and Peru Upwelling

We investigated phytoplankton Fe limitation using shipboard incubation experiments in the highߚnutrient South American eastern boundary current regime. Low ambient Fe concentrations (~0.1 nM) in water collected from the Humboldt and Peru Currents were supplemented with a range of added Fe levels up to 2.5 nM. Phytoplankton chlorophyll a, photosystem II photosynthetic efficiency, and nitrate and phosphate drawdown increased in proportion to the amount of Fe added. The Humboldt Current algal community after Fe additions included colonial and flagellated Phaeocystis globosa and large pennate diatoms, whereas the Peru Upwelling assemblage was dominated by coccolithophorids and small pennate diatoms. Apparent halfߚsaturation constants for growth of the two communities were 0.17 nM Fe (Humboldt Current) and 0.26 nM Fe (Peru Upwelling). Net molar dissolved Si(OH)4 : NO3- drawdown ratios were low in both experiments (~0.2ߝ0.7), but net particulate silica to nitrogen production ratios were higher. Fe limitation decreased net NO3-:PO43- utilization ratios in the Humboldt Current incubation to well below Redfield values. Phytoplankton community sinking rates were decreased by Fe additions in the Peru Upwelling, suggesting potential Fe effects on carbon export. Our results confirm that primary producers in the Peru Upwelling/Humboldt Current system can be limited by Fe, but the biological and biogeochemical consequences of Fe limitation differ from Feߚlimited California coastal upwelling waters that have been previously studied.
Efficient Traffic-Sign Recognition with Scale-aware CNN

The paper presents a Traffic Sign Recognition (TSR) system, which can fast and accurately recognize traffic signs of different sizes in images. The system consists of two well-designed Convolutional Neural Networks (CNNs), one for region proposals of traffic signs and one for classification of each region. In the proposal CNN, a Fully Convolutional Network (FCN) with a dual multi-scale architecture is proposed to achieve scale invariant detection. In training the proposal network, a modified "Online Hard Example Mining" (OHEM) scheme is adopted to suppress false positives. The classification network fuses multi-scale features as representation and adopts an "Inception" module for efficiency. We evaluate the proposed TSR system and its components with extensive experiments. Our method obtains $99.88\%$ precision and $96.61\%$ recall on the Swedish Traffic Signs Dataset (STSD), higher than state-of-the-art methods. Besides, our system is faster and more lightweight than state-of-the-art deep learning networks for traffic sign recognition.
DFINITY Technology Overview Series, Consensus System

The DFINITY blockchain computer provides a secure, performant and flexible consensus mechanism. At its core, DFINITY contains a decentralized randomness beacon which acts as a verifiable random function (VRF) that produces a stream of outputs over time. The novel technique behind the beacon relies on the existence of a unique-deterministic, non-interactive, DKG-friendly threshold signatures scheme. The only known examples of such a scheme are pairing-based and derived from BLS. The DFINITY blockchain is layered on top of the DFINITY beacon and uses the beacon as its source of randomness for leader selection and leader ranking. A "weight" is attributed to a chain based on the ranks of the leaders who propose the blocks in the chain, and that weight is used to select between competing chains. The DFINITY blockchain is layered on top of the DFINITY beacon and uses the beacon as its source of randomness for leader selection and leader ranking blockchain is further hardened by a notarization process which dramatically improves the time to finality and eliminates the nothing-at-stake and selfish mining attacks. DFINITY consensus algorithm is made to scale through continuous quorum selections driven by the random beacon. In practice, DFINITY achieves block times of a few seconds and transaction finality after only two confirmations. The system gracefully handles temporary losses of network synchrony including network splits, while it is provably secure under synchrony.
Functional variation in the gut microbiome of wild Drosophila populations

Most of the evidence that the gut microbiome of animals is functionally variable, with consequences for the health and fitness of the animal host, is based on laboratory studies, often using inbred animals under tightly controlled conditions. It is largely unknown whether these microbiome effects would be evident in outbred animal populations under natural conditions. In this study, we quantified the functional traits of the gut microbiota (metagenome) and host (gut transcriptome) and the taxonomic composition of the gut microorganisms (16S rRNA gene sequence) in natural populations of three mycophagous Drosophila species. Variation in microbiome function and composition was driven principally by the period of sample collection, while host function varied mostly with Drosophila species, indicating that variation in microbiome traits is determined largely by environmental factors, and not host taxonomy. Despite this, significant correlations between microbiome and host functional traits were obtained. In particular, microbiome functions dominated by metabolism were positively associated with host functions relating to gut epithelial turnover. Much of the functional variation in the microbiome could be attributed to variation in abundance of Bacteroidetes, rather than the two other abundant groups, the γ‐Proteobacteria or Lactobacillales. We conclude that functional variation in the interactions between animals and their gut microbiome can be detectable in natural populations, and, in mycophagous Drosophila, this variation relates primarily to metabolism and homeostasis of the gut epithelium.
A Survey on Software-Defined Wide Area Networks

Better cost effectiveness of Software-Defined Network(SDN) is motivating enterprises to adopt it in Wide Area Network(WAN). The idea is then called Software-Defined Wide Area Network(SD-WAN). In this paper, first we review the architecture of SDN, which provide theoretical support for SD-WAN. Then we analyze three typical SD-WAN realizations, which are Google’s B4, Microsoft’s SWAN and Software-Defined Internet eXchange Point respectively. Finally, we make a conclusion and discuss future works. Index Terms —SD-WAN, B4, SWAN, SDX, survey