Miracle-dz/UniFAR-FTUs huggingface dataset:
Direct integrals of strongly irreducible operators

Strongly irreducible operators can be considered as building blocks for bounded linear operators on complex separable Hilbert spaces. Many bounded linear operators can be written as direct sums of at most countably many strongly irreducible operators. In this paper, we show that a bounded linear operator A is similar to a direct integral of strongly irreducible operators if its commutant contains a bounded maximal abelian set of idempotents. We find that bounded linear operators which are similar to direct integrals of strongly irreducible operators form a dense subset of L(H) in the operator norm.
Transcriptional Responses of Stress-Related Genes in Pale Chub (Zacco platypus) Inhabiting Different Aquatic Environments: Application for Biomonitoring Aquatic Ecosystems

Pale chub (Zacco platypus) is a dominant species in urban rivers and reservoirs, and it is used as an indicator to monitor the effects of environmental contaminants. Gene responses at the molecular level can reflect the health of fish challenged with environmental stressors. The objective of this study was to identify correlations between water quality factors and the expression of stress-related genes in Z. platypus from different lake environments (Singal and Juam Lakes). To do so, transcriptional responses of genes involving cellular homeostasis (heat-shock protein 70, HSP70; heat-shock protein 90, HSP90), metal detoxification (metallothionein, MT), and antioxidation (superoxide dismutase, SOD; catalase, CAT) were analyzed in the gill and liver tissues of Z. platypus. HSP70, HSP90, and MT genes were overall upregulated in Z. platypus from Singal Lake, which suffered from poorer water quality than Juam Lake. In addition, gene responses were significantly higher in Singal Lake outflow. Upregulation of HSP70, HSP90, and MT was significantly higher in Z. platypus gills than in the liver tissue. In addition, integrated biomarker response and heatmap analysis determined correlations between expression of biomarker genes or water quality factors and sampling sites of both lakes. These results suggest that stress-related genes used as multiple biomarkers may reflect spatial characteristics and water quality of different lake environments, and they can be used for biomonitoring and ecological risk assessment.
Identification of Coumarins and Antimicrobial Potential of Ethanolic Extracts of Dipteryx odorata and Dipteryx punctata

Dipteryx odorata and Dipteryx punctata are species native to the Amazonian, traded by extractivists to obtain coumarin. We aimed to analyze the presence of coumarin in the ethanolic extracts of leaves, branches and fruits of D. odorata and D. punctata and to evaluate the antimicrobial activity of these extracts against phytopathogenic fungi and bacteria of clinical interest. Chemical analyses were performed by thin layer chromatography (TLC) and by gas chromatography coupled to mass spectrometry (GC-MS). For the antifungal assays, the fungi used were Cercospora longissima, Colletotrichum gloeosporioides, two isolates of Fusarium spp. and Sclerotium rolfsii, and the antibacterial assay was performed using the minimum inhibitory concentration (MIC) test with Burkholderia cepacia, Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus bacteria. In D. odorata seed extracts and in D. punctata husks, endocarps, and seeds, we identified 1,2-benzopyrone. D. odorata endocarp extracts and D. punctata seeds provided the greatest decrease in mycelial growth of the evaluated phytopathogens, showing promise as an alternative control. The husk and endocarp extracts of both species had a weak effect on E. coli. This research is the first to compare the different parts of species of the genus Dipteryx and to evaluate the use of husks and endocarps of D. punctata fruits to obtain coumarin. Chemical analyses used to quantify the compounds existing in the extracts, and tests with phytopathogens in vitro and in vivo are currently being carried out.
Optimal Control Theory: Applications to Management Science and Economics

Preface to First Edition. - Preface to Second Edition. - What is Optimal Control Theory? - The Maximum Principle: Continuous Time. - The Maximum Principle: Mixed Inequality Constraints. - The Maximum Principle: General Inequality Constraints. - Applications to Finance. - Applications to Production and Inventory. - Applications to Marketing. - The Maximum Principle: Discrete Time. - Maintenance and Replacement. - Applications to Natural Resources. - Economic Applications. - Differential Games, Distributed Systems, and Impulse Control. - Stochastic Optimal Control. - Solutions of Linear Differential Equations. - Calculus of Variations and Optimal Control Theory. - An Alternative Derivation of the Maximum Principle. - Special Topics in Optimal Control. - Answers to Selected Exercises. - Bibliography. - Index. - List of Figures. - List of Tables.
Complex norm localization: from price competitiveness to local production in East African Community pharmaceutical policy

This article offers a critical contribution to debates around access to medicines and the global politics of pharmaceutical production in Africa. Specifically, we seek to account for a normative shift within these debates whereby the promotion of local pharmaceutical production in Africa has once again come to be viewed as a central modality for achieving access to health across the continent. While the onset of this normative shift has been highlighted by the global Covid-19 pandemic, in this article we argue that its antecedents can be traced to a more incremental process of global and regional normative change that has been in motion since the late 1990s. To illustrate this, we narrow our empirical focus onto the East African Community (EAC) and the regional initiatives its members have pursued to promote local pharmaceutical production capacities since 2012. We draw and build upon the literature on norm localization to emphasize how the emergence and distinctiveness of this policy reflected the complex way in which policy actors within the EAC sought to localize and combine separate (and somewhat competing) changing global norms around access to health and industrial policy. The article also points to the tensions and unintended consequences which emerged from this complex process of norm localization and the challenges of implementing this strategy within the institutional landscape of the EAC.
Valorization of Biomasses from Energy Crops for the Discovery of Novel Thermophilic Glycoside Hydrolases through Metagenomic Analysis

The increasing interest for environmentally friendly technologies is driving the transition from fossil-based economy to bioeconomy. A key enabler for circular bioeconomy is to valorize renewable biomasses as feedstock to extract high value-added chemicals. Within this transition the discovery and the use of robust biocatalysts to replace toxic chemical catalysts play a significant role as technology drivers. To meet both the demands, we performed microbial enrichments on two energy crops, used as low-cost feed for extremophilic consortia. A culture-dependent approach coupled to metagenomic analysis led to the discovery of more than 300 glycoside hydrolases and to characterize a new α-glucosidase from an unknown hyperthermophilic archaeon. Aglu1 demonstrated to be the most active archaeal GH31 on 4Np-α-Glc and it showed unexpected specificity vs. kojibiose, revealing to be a promising candidate for biotechnological applications such as the liquefaction/saccharification of starch.
Meghalayan environmental evolution of the Thapsus coast (Tunisia) as inferred from sedimentological and micropaleontological proxies

Abstract. Thapsus was one of the Roman Empire's largest harbors and is situated next to an easily defended promontory on Tunisia's coast in northern Africa. It was provided with a huge stone and cement breakwater mole that extended almost 1 km into the sea. We examined sedimentological and micropaleontological proxies from 14C-dated core material and shifts in microfauna and macrofauna community structure to infer patterns of sediment dynamics and the chronology of events that shaped the coastal evolution in the Dzira Lagoon at Thapsus over the past 4000 years. The sedimentological and faunal record of environmental changes reflect a sequence of events that display a transition from an open to a semi-closed lagoon environment. At around 4070 cal yr BP and again between 2079 and 1280 cal yr BP, the data reveal two transgressive events and a deposition of sandy sediments in a largely open marine lagoon environment. The transgressive sands overlay marine carbonate sandstones that are upper Pleistocene in age. A gradual closure of the lagoon from 1280 cal yr BP until today is indicated by decreasing species richness values, lower abundances of typical marine taxa, and increasing percent abundances of fine-grained sediments. The environmental transition from an open to a closed lagoon setting was also favored by the construction of an extensive harbor breakwater mole, changes in longshore current drift patterns, and the formation of an extensive sand spit.
Recrystallized and epitaxially thickened poly-silicon layers on graphite substrates [solar cell manufacture]

Polycrystalline silicon films suitable for solar cell manufacturing have been realized by recrystallizing and epitaxially thickening thin silicon layers deposited on graphite substrates. The recrystallization is carried out in an electron beam zone melting process. Either vapor phase epitaxy or liquid phase epitaxy have been applied to enlarge the recrystallized seed layer to a thickness of 30-40 /spl mu/m. This paper characterizes the seed layer and especially the epitaxial layer with regard to their structural properties. Surface morphology and crystalline quality have been analyzed for different process parameters. TEM investigations show how epitaxy is influenced by silicon carbide formed at the surface of the seed layer.
Deep Learning-based Lung Cancer Classification of CT Images using Augmented Convolutional Neural Networks

Lung cancer is worldwide the second death cancer, both in prevalence and lethality, both for women and men. The applicability of machine learning and pattern classification in lung cancer detection and classification is proposed. Pattern classification algorithms can classify the input data into different classes underlying the characteristic features in the input. Early identification of lung cancer using pattern recognition can save lives by analyzing the significant number of Computed Tomography images. Convolutional Neural Networks recently achieved remarkable results in various applications including Lung cancer detection in Deep Learning. The deployment of augmentation to improve the accuracy of a Convolutional Neural Network has been proposed. Data augmentation is utilized to find suitable training samples from existing training sets by employing various transformations such as scaling, rotation, and contrast modification. The LIDC-IDRI database is utilized to assess the networks. The proposed work showed an overall accuracy of 95%. Precision, recall, and F1 score for benign test data are 0.93, 0.96, and 0.95, respectively, and 0.96, 0.93, and 0.95 for malignant test data. The proposed system has impressive results when compared to other state-of-the-art approaches.
Systematic Identification, Fragmentation Pattern, And Metabolic Pathways of Hyperoside in Rat Plasma, Urine, And Feces by UPLC-Q-Exactive Orbitrap MS

Hyperoside is a natural flavonol glycoside, which has antioxidation, antitumor, and anticancer activities together with other healthy effects like improving cardiovascular function, protecting the liver, and regulating the immune system. It is a popular compound used in the traditional Chinese medicine and different studies on hyperoside are present in the literature. However, studies on the metabolism of hyperoside in vivo were not comprehensive. In this study, UPLC-Q-Exactive Orbitrap MS technology was used to establish a rapid and comprehensive analysis strategy to explore the metabolites and metabolic process of hyperoside in rats. The metabolites of hyperoside were systematically identified in rat plasma, urine, and feces. According to the hyperoside standard substance and relevant works of literature, a total of 33 metabolites were identified, including 16 in plasma, 31 in urine, and 14 in feces. Among them, the metabolites quercetin and dihydroquercetin were unambiguously confirmed by comparison with standard substances. In addition, 13 metabolites had not been reported in hyperoside metabolism-related articles at present. The metabolic reactions of hyperoside in vivo were further explored, including phase I metabolism (hydroxylation, dehydroxylation, glycoside hydrolysis, hydrogenation, and hydration) and phase II metabolism (methylation, acetylation, sulfation, and glucuronide conjugation). The fragment ions of hyperoside and its metabolites were usually produced by glucoside bond hydrolysis, the neutral loss of (CO + OH), COH, CO, O, and Retro-Diels Alder (RDA) cleavage. In conclusion, this study comprehensively characterized the metabolism of hyperoside in rats, providing a basis for exploring its various biological activities.
Online Coordinated NFV Resource Allocation via Novel Machine Learning Techniques

Thanks to Network Function Virtualization (NFV), Internet Service Providers (ISPs) can improve network resource utilization with significantly reduced capital and operational expenditures. To dig deeper into the potential of NFV, an important challenge is the resource allocation problem in NFV (NFV-RA), which can be divided into three stages: VNFs chain composition, VNF forwarding graph embedding, and VNFs scheduling. The key to the NFV-RA problem is to design an effective and coordinated resource allocation algorithm for the three stages. Besides, the NFV-RA problem has been proved to be NP-Hard, and thus most existing approaches focus on heuristic and meta-heuristic algorithms. In this paper, we propose an NFV online coordinated resource allocation framework (OCRA) that completes the three stages simultaneously in a coordinated manner by combining parallel Multi-Agent Deep Reinforcement Learning with novel neural networks and RL training techniques. The extensive experimental results show that compared with the state-of-the-art solutions, OCRA is highly-efficient in terms of time, with up to 50% and 10.8% improvement on resource overhead and acceptance ratio, respectively.
Mobile-Bearing Total Ankle Replacement In Vivo Kinematic Assessment: A Prospective Study Protocol

Total ankle prosthesis as a surgical solution in the case of end-stage osteoarthritis has seen a considerable increase in the last two decades. This study protocol arises from the need to understand the in vivo kinematics of mobile-bearing, flat tibial component total ankle replacement, evaluating the real range of motion and the reciprocal relationships between the components during normal motor tasks through the use of model-based radio-stereometric analysis (MB-RSA). In addition, pre- and post-operative evaluation of walking kinematics with inertial motion sensors, proprioception through a dedicated workstation, and clinical outcomes are discussed. We expect that based on our study protocol researchers will be able to improve future prosthetic designs and validate the setup of MB-RSA, as well as to understand “how an ankle prosthesis moves” once implanted in the patient.
Assessment of tap water quality in mobile homes in the Eastern Coachella Valley, California

Very few studies have been undertaken on water quality from mobile homes, with most information coming from press and policy reports suggesting that people living in mobile homes in the US have poor water quality. Our goal was to evaluate resident exposure to microbes at the point of use of tap water sourced from the Oasis Mobile Homes Park (OMHP), using physico-chemical parameters, concentrations of target cultivatable microbes, and quantitative polymerase chain reaction (qPCR) analyses. In this study, we sampled 15 mobile homes (MHs) and found arsenic concentrations to be 4–8 times above the acceptable EPA standard of 10 ppm. Our qPCR demonstrated high concentrations of gene targets for Salmonella spp. , L. monocytogenes, P. aeruginosa, C. jejuni, E. faecalis, and E. coli in one or more of our sampled mobile homes. Except for MH4, which had the highest concentration of L. monocytogenes and E. faecalis, all MHs had different predominant microorganisms. Based on the physico-chemical parameters and our microbiological analysis, we conclude that drinking water from MH taps in the OMHP is unsafe for consumption.
Morphological variations between native and Vietnam-originated striped snakeheads (Channa striata) in Bangladesh

The freshwater striped snakehead, Channa striata, known as “shol” in Bangladesh was introduced from Vietnam for commercial aquaculture that lacks morphological background. Therefore, the present study sought to differentiate various C. striata populations morphologically using one hundred eighty-six samples, consisting of nine native and two Vietnam-originated populations in Bangladesh. Seventeen morphometric and six meristic characters were studied, and the analysis highlighted that native and Vietnamese snakeheads were significantly different considering all morphological traits examined except eye diameter. The discrimination analysis illustrated that pelvic fin length (PVFL), pectoral fin length (PCFL), mouth gape (MG), and body width (BW) were the central characters caused to differentiate between native and Vietnamese populations. However, morphological findings compared with the previous findings reveal that Vietnam-originated snakeheads in Bangladesh do not correspond to wild morphotypes in Vietnam and that need to maintain carefully to avoid possible new morphotypes through genetic introgression and different culture condition practiced in Bangladesh.
Delay and QoS Aware Low Complex Optimal Service Provisioning for Edge Computing

Edge computing can be used as a distributed counterpart of the cloud computing, and task offloading with much shorter delays can be achieved. In general, edge servers are resource-limited, but the services are becoming further diversified to meet the ever-increasing user demand. When an edge server cannot process the received service request of a particular service type for not locally having the corresponding service execution image, the request needs to be forwarded to another on which the particular image is installed. In this article, an optimal scheduling method that forwards such requests is proposed by using the variant multiple-knapsack framework. Then, to find the optimal solution, we propose to reformulate it as an integer linear program. As the problem size increases, however, the problem easily becomes intractable, so we propose a distributed solution by using both Lagrangian relaxation and decomposition theory. To evaluate the effectiveness of the proposed approaches, we carry out simulations with different network layouts and with different request arrival scenarios. The evaluation results show that the centralized Lagrange dual solution can yield near-optimal solutions. In addition, the decomposed distributed solution can significantly reduce the computational and operational complexity at the expense of the total reward.
A Note on Inverse Document Frequency Weighting Scheme

Based on the Shannon information theory, a measure for term value is introduced. This study is an attempt to provide a theoretical justification for the inverse document frequency (IDF) weighting scheme. The argument presented in this paper is somewhat different from those suggested earlier. It is shown that IDF weights can be derived from the proposed approach by assuming that each index term has an even distribution within a subset of documents. A critical comment on the signal-noise ratio (S/N) weighting method is also included.
Group-covariant extreme and quasiextreme channels

Constructing all extreme instances of the set of completely positive trace-preserving (CPTP) maps, i.e., quantum channels, is a challenging valuable open problem in quantum information theory. Here we introduce a systematic approach that enables us to construct exactly those extreme channels that are covariant with respect to a finite discrete group or a compact connected Lie group. Innovative labeling of quantum channels by group representations enables us to identify the subset of group-covariant channels whose elements are group-covariant generalized-extreme channels. Furthermore, we exploit essentials of group representation theory to introduce equivalence classes for the labels and also partition the set of group-covariant channels. As a result we show that it is enough to construct one representative of each partition. We construct Kraus operators for group-covariant generalized-extreme channels by solving systems of linear and quadratic equations for all candidates satisfying the necessary condition for being group-covariant generalized-extreme channels. Deciding whether these constructed instances are extreme or quasi-extreme is accomplished by solving system of linear equations. We formalize the problem of constructing and classifying group-covariant generalized extreme channels, thereby yielding an algorithmic approach to solving, which we express as pseudocode. To illustrate the application and value of our method, we solve for explicit examples of group-covariant extreme channels. With unbounded computational resources to execute our algorithm, our method always delivers a description of an extreme channel for any finite-dimensional Hilbert-space and furthermore guarantees a description of a group-covariant extreme channel for any dimension and for any finite-discrete or compact connected Lie group if such an extreme channel exists.
Experimental Implementation of Hybrid Concentration-Controlled Direct-Proportional Length-Based DNA Computing for Numerical Optimization of the Shortest Path Problem

DNA computing often makes use of hybridization, whether for vastly generating the initial candidate answers or amplification via polymerase chain reaction (PCR). The main idea behind DNA computing approaches for solving weighted graph problems is that if the degree of hybridization can be controlled, then it is able to generate more double-stranded DNAs (dsDNAs), which represents the solu- tion to the problem during initial pool generation. Previously, concentration and melting temperature of DNA have been exploited for controlling DNA hybridization during an in vitro computation. In this pa- per, we present an improved direct-proportional length-based DNA computing (DPLB-DNAC), which combines two characteristics: length and concentration for encoding and at the same time, effectively control the degree of hybridization of DNA. The encoding by length is realized whereby the cost of each path is encoded by the length of the DNA strands in a proportional way. On the other hand, the control of concentration is done by varying the amount of input DNA strands, based on the input graph. The proposed approach shows improvements in terms of materials usage and scalability. The experimental results demonstrate the feasibility of the proposed approach for solving weighted graph problems, such as the shortest path problem.