Miracle-dz/UniFAR-FTUs huggingface dataset:
Assisted Control for Semi-Autonomous Power Infrastructure Inspection Using Aerial Vehicles

This paper presents the design and implementation of an assisted control technology for a small multirotor platform for aerial inspection of fixed energy infrastructure. Sensor placement is supported by a theoretical analysis of expected sensor performance and constrained platform behaviour to speed up implementation. The optical sensors provide relative position information between the platform and the asset, which enables human operator inputs to be autonomously adjusted to ensure safe separation. The assisted control approach is designed to reduced operator workload during close proximity inspection tasks, with collision avoidance and safe separation managed autonomously. The energy infrastructure includes single vertical wooden poles and crossarm with attached overhead wires. Simulated and real experimental results are provided.
A stage–structured predator-prey model with disease in the prey

A non-linear mathematical model for a prey-predator community is proposed and analyzed. In the model, prey gets infected and predator population is structured into two stages of life, immature and mature with a time lag between two stages. Boundedness and non-negativity of the solutions of the system have been proved. Criterion for the stability of the system in the absence of delay is derived and bifurcation is found. The critical value of delay parameter for which stability change may occur is obtained.
Impacts of land use and land cover change on regional climate: a case study in the agro-pastoral transitional zone of China

Assessing the impacts of land use and land cover change (LUCC) on regional climate is essential for understanding land–atmosphere interactions and for designing climate adaptation and mitigation strategies. Using the weather research and forecasting (WRF) model, we examined how different land use and land cover patterns affect regional climate in the agro-pastoral transitional zone of North China, whose environmental and socioeconomic conditions are sensitive to climate change. We parameterized WRF using land use and land cover maps corresponding to 2001 and 2010 conditions, which differ in the representation of four land surface biophysical parameters: vegetation fraction, leaf area index (LAI), albedo, and emissivity. From 2001 to 2010, vegetation fraction and LAI increased in summer, emissivity increased and albedo decreased in winter. Our WRF simulations show that differences in land use and land cover patterns led to widespread reduction in summer temperature with local cooling on the order of 1 °C, and extensive increase in winter temperature with local warming exceeding 0.8 °C. By contrast, simulations using the default landscape representation, provided by WRF itself, show only minor and random changes in temperature. Model evaluation further reveals that our simulations with appropriate land surface properties improve the performance of the WRF model. Our findings demonstrate that LUCC in Northern China has altered the regional climate over the past decade. The magnitude and spatial patterns of temperature changes quantified by our simulations provide useful information for understanding the impacts of LUCC on climate and for developing mitigation and adaptation strategies in arid and semiarid regions.
If you’ve seen one worm, have you seen them all? Spatial, community, and genetic variability of tubificid communities in Montana

Genetic studies are recognized increasingly as important for understanding naturally occurring disease dynamics and are used to predict host genetic diversity and coevolutionary processes and to identify species composition in ecological communities. Tubifex tubifex, the definitive host of the whirling disease parasite Myxobolus cerebralis, comprises 6 known lineages that vary widely in parasite susceptibility. We used 16S ribosomal DNA (16S rDNA) to identify relationships among genetic variability of 3 oligochaete genera (T. tubifex, Rhyacodrilus spp., and Ilyodrilus spp.; Oligochaeta:Tubificidae), oligochaete assemblage composition, and the presence of whirling disease in 9 locations across 4 watersheds in Montana, USA. We assessed genetic variability among 183 tubificid worms from locations classified as positive or negative for whirling disease based on 5 to 8 y of monitoring by the Montana Department of Fish, Wildlife, and Parks. Within genera, we found 2 groups of T. tubifex (lineages I and III), 2 groups of Rhyacodrilus spp. , and 4 groups of Ilyodrilus spp. , possibly suggesting cryptic species. The maximum genetic variability within taxa was relatively high (∼10% sequence divergence) for all 3 genera, but haplotype diversity within groups with >5% sequence divergence was greater for Ilyodrilus spp. (0.719) than for Tubifex spp. (0.246) and Rhyacodrilus spp. (0.143). The variation was nonrandomly distributed over the landscape. Oligochaete genetic composition was more similar among locations in the same watershed than among locations with or without whirling disease. Thus, oligochaete assemblage composition did not appear to be related to the presence of the disease at this watershed spatial scale.
RFM analysis for decision support in e-banking area

The introduction of data mining methods in the banking area due to the nature and sensitivity of bank data can already be considered of great assistance to banks as to prediction, forecasting and decision support. Concerning decision making, it is very important a bank to have the knowledge of (a) customer profitability and customers’ grouping according to this parameter and (b) association rules between products and services it offers in order to more sufficiently support its decisions. Object of this paper is to demonstrate that keeping track of customer groups according to their profitability and discovery of association rules between products and services is of major importance as to its decision support. Key-words: Data Mining, Decision Support, Association Rules, RFM analysis, Clustering
Dietary zinc restriction and repletion affects DNA integrity in healthy men.

BACKGROUND Zinc plays an important role in antioxidant defense and the maintenance of cellular DNA integrity. However, no experimental human studies have been performed to examine the role of zinc status on DNA damage. OBJECTIVE We evaluated the effects of dietary zinc depletion and repletion on DNA strand breaks, oxidative stress, and antioxidant defenses in healthy men. DESIGN Nine healthy men with reported mean daily zinc intakes >11 mg/d were recruited. Subjects completed 3 consecutive dietary periods: baseline (days 1 to 13; 11 mg Zn/d), zinc depletion (days 14 to 55; 0.6 mg Zn/d for 1 wk and 4 mg Zn/d for 5 wk), and zinc repletion (days 56 to 83; 11 mg Zn/d for 4 wk with 20 mg supplemental Zn for first 7 d). Blood samples were collected on days 1, 13, 35, 55, and 83. DNA damage in peripheral blood cells, plasma oxidative stress, and antioxidant defense biomarkers were assessed. RESULTS Dietary zinc depletion (6 wk) was associated with increased DNA strand breaks in peripheral blood cells (day 13 compared with day 55; P < 0.05), changes that were ameliorated by zinc repletion (day 55 compared with day 83; P < 0.05). Plasma zinc concentrations were negatively correlated with DNA strand breaks (r = -0.60, P = 0.006) during the zinc-depletion period. Plasma alpha- and gamma-tocopherol concentrations, plasma total antioxidant capacity, and erythrocyte superoxide dismutase activity did not change significantly, and plasma F(2)-isoprostanes were unaffected by dietary period. CONCLUSIONS Changes in dietary zinc intake affected DNA single-strand breaks. Zinc appears to be a critical factor for maintaining DNA integrity in humans.
VAD-doxil versus VAD-doxil plus thalidomide as initial treatment for multiple myeloma: results of a multicenter randomized trial of the Greek Myeloma Study Group.

BACKGROUND We have previously demonstrated that vincristine, liposomal doxorubicin and dexamethasone (VAD-doxil) is equally effective with VAD-bolus yielding objective response rates of 61% as first-line treatment in multiple myeloma (MM). In a phase II study, the addition of thalidomide to VAD-doxil (TVAD-doxil) proved feasible and increased response rate to 74%. The aim of the present multicenter prospective randomized clinical trial was to compare the efficacy and toxicity of VAD-doxil and TVAD-doxil in previously untreated MM patients. PATIENTS AND METHODS We enrolled 232 newly diagnosed MM patients aged <75 years, 115 randomized to VAD-doxil (arm A) and 117 to TVAD-doxil (arm B). Patients in arm A received vincristine 2 mg i.v. and liposomal doxorubicin 40 mg/m(2) i.v. , on day 1 and dexamethasone 40 mg p.o. daily on days 1-4, 9-12 and 17-20 for the first cycle and on days 1-4 for the next three cycles. Patients in arm B received additionally thalidomide 200 mg p.o. daily, at bedtime. Treatment was administered every 28 days. RESULTS On an intention-to-treat basis, at least partial response was observed, in 62.6% and in 81.2% of patients randomized to arms A and B, respectively (P = 0.003). Progression-free survival (PFS) at 2 years was 44.8% in arm A and 58.9% in arm B (P = 0.013). Overall survival (OS) at 2 years was 64.6% and 77%, in arms A and B, respectively (P = 0.037). Considering overall toxicity, constipation, peripheral neuropathy, dizziness/somnolence, skin rash and edema were significantly higher in arm B compared with arm A (P < 0.01), but grade 3-4 toxicities were low and similar in both arms. CONCLUSIONS The addition of thalidomide to VAD-doxil increases response and PFS rates and probably OS in previously untreated myeloma patients. The superiority of efficacy counterbalances the higher overall toxicity of TVAD-doxil.
Graphical Specification of Dynamic Network Structure

We present a language, MEADOW, for specifying dynamic networks from a structural viewpoint. We demonstrate MEADOW in three examples addressing dynamic reconfiguration in the setting of object-oriented networks, ad hoc networks and mobile code networks. MEADOW is more expressive than any language of this kind (e.g. SDL-2000 agent diagrams, composite structures in UML 2.0) that we are aware of, but maintains, in our opinion, the simplicity and elegance of these languages.
A signaling architecture against dos attacks

Denial of service (DoS) attacks figure highly among the dangers that face the Internet. Many research studies deal with DoS, proposing models and/or architectures to stop this threat. The proposed solutions vary between prevention, detection, filtering and traceback of the attack. The latter (attack traceback) constitutes an important part of the DoS defense. The most complex issue it has to face is related to the fact that attackers often used spoofed or incorrect IP addresses, thus disguising the true origin. In this work, we propose a signaling architecture and a security-oriented signaling protocol named 3SP (Simple Security Signaling Protocol). This solution makes it easier to trace both the DoS and other types of attack back to their sources; it is simple, robust and efficient against IP spoofing, and thus constitutes a novel and efficient approach to deal with the attack traceback problem.
Quality Content Management for E-Learning: General Issues for a Decision Support System

In today’s world, reusable learning object concepts and standards for their treatment represent an advantage for knowledge management systems to whatever kind of business that supports an on-line system. Users are able to manage and reuse content according to their needs without interoperability problems. The possibility of importing learning objects for e-learning aim to increase their information repository but the learning object quality is not guaranteed. This work proposes a system to manage quality learning objects to support teachers to select the best content to structure their course. To achieve this we suggest two subsystems: First, an importation, normalization and evaluation subsystem; and second, a selection, delivery and post evaluation subsystem.
EACHING WITH D ESIRABLE D IFFICULTIES AND S CHEDULED D IVERSITY

We introduce and study minimax curriculum learning (MCL), a new method for adaptively selecting a sequence of training subsets for a succession of stages in machine learning. The subsets are encouraged to be small and diverse early on, and then larger, harder, and allowably more homogeneous in later stages. At each stage, model weights and training sets are chosen by solving a joint continuousdiscrete minimax optimization, whose objective is composed of a continuous loss (reflecting training set hardness) and a discrete submodular promoter of diversity for the chosen subset. MCL repeatedly solves a sequence of such optimizations with a schedule of increasing training set size and decreasing pressure on diversity encouragement. We reduce MCL to the minimization of a surrogate function handled by submodular maximization and continuous gradient methods. We show that MCL achieves better performance and, with a clustering trick, uses fewer labeled samples for both shallow and deep models. Our method involves repeatedly solving constrained submodular maximization of an only slowly varying function on the same ground set. Therefore, we develop a heuristic method that utilizes the previous submodular maximization solution as a warm start for the current submodular maximization process to reduce computation while still yielding a guarantee.
USP18-Based Negative Feedback Control Is Induced by Type I and Type III Interferons and Specifically Inactivates Interferon α Response

Type I interferons (IFN) are cytokines that are rapidly secreted upon microbial infections and regulate all aspects of the immune response. In humans 15 type I IFN subtypes exist, of which IFN α2 and IFN β are used in the clinic for treatment of different pathologies. IFN α2 and IFN β are non redundant in their expression and in their potency to exert specific bioactivities. The more recently identified type III IFNs (3 IFN λ or IL-28/IL-29) bind an unrelated cell-type restricted receptor. Downstream of these two receptor complexes is a shared Jak/Stat pathway. Several mechanisms that contribute to the shut down of the IFN-induced signaling have been described at the molecular level. In particular, it has long been known that type I IFN induces the establishment of a desensitized state. In this work we asked how the IFN-induced desensitization integrates into the network built by the multiple type I IFN subtypes and type III IFNs. We show that priming of cells with either type I IFN or type III IFN interferes with the cell's ability to further respond to all IFN α subtypes. Importantly, primed cells are differentially desensitized in that they retain sensitivity to IFN β. We show that USP18 is necessary and sufficient to induce differential desensitization, by impairing the formation of functional binding sites for IFN α2. Our data highlight a new type of differential between IFNs α and IFN β and underline a cross-talk between type I and type III IFN. This cross-talk could shed light on the reported genetic variation in the IFN λ loci, which has been associated with persistence of hepatitis C virus and patient's response to IFN α2 therapy.
Vitamin D status and biomarkers of inflammation in runners

Background and purpose The extra-skeletal functions of vitamin D - including its role in inflammatory modulation - are now well recognized but have not yet been investigated in an athletic population. Thus, the purpose of this study was to investigate the relationship between vitamin D status and pro- and anti-inflammatory cytokines (as markers of inflammation and immune system function) in endurance athletes. Patients and methods We analyzed fasting blood samples from 19 healthy, endurance-trained male and female runners (following a standardized diet and exercise regimen) for vitamin D status (serum 25-hydroxyvitamin D [25(OH)D)] and specific plasma cytokine concentrations (tumor necrosis factor alpha [TNF-α], interferon-gamma [IFN-γ], interleukin [IL]-4, and IL-10). Serum/plasma concentrations were log-transformed and simple regression analysis was used to determine significant associations between 25(OH)D and cytokine concentrations. Results Forty-two percent of participants had insufficient vitamin D status [25(OH)D< 32 ng/mL], whereas 11% were deficient [25(OH)D < 20 ng/mL]. TNF-α and IL-4 were variable, ranging from 2.9 to 36.4 pg/mL and 0 to 252.1 pg/mL, respectively. Concentrations of IFN-γ and IL-10 were minimal, with means of 6.7 ± 7.0 pg/mL and 4.8 ± 5.1 pg/mL, respectively. Regression analysis revealed a significant inverse association between 25(OH)D and TNF-α concentrations (R2 = 56.5, P < 0.001) but not between 25(OH)D and the remaining cytokines, IFN-γ, IL-4, and IL-10 (P = 0.477, 0.694, and 0.673, respectively). Conclusion These results call further attention to the epidemic of vitamin D insufficiency, even in outdoor athletes, and support a possible link between decreased vitamin D status and one particular marker of inflammation. Future investigations are necessary to determine whether increased inflammation in athletes with reduced vitamin D status could increase risk for inflammation-related injury.
Gene Annotation Easy Viewer (GAEV): Integrating KEGG’s Gene Function Annotations and Associated Molecular Pathways

We developed a Gene Annotation Easy Viewer (GAEV) that integrates the gene annotation data from the KEGG (Kyoto Encyclopedia of Genes and Genomes) Automatic Annotation Server. GAEV generates an easy-to-read table that summarizes the query gene name, the KO (KEGG Orthology) number, name of gene orthologs, functional definition of the ortholog, and the functional pathways that query gene has been mapped to. Via links to KEGG pathway maps, users can directly examine the interaction between gene products involved in the same molecular pathway. We provide a usage example by annotating the newly published freshwater microcrustacean Daphnia pulex genome. This gene-centered view of gene function and pathways will greatly facilitate the genome annotation of non-model species and metagenomics data. GAEV runs on a Windows or Linux system equipped with Python 3 and provides easy accessibility to users with no prior Unix command line experience.
1 Derived Willingness-To-Pay For Water : Effects Of Probabilistic Rationing And Price

A two stage linear programming approach is used to estimate the willingness to pay (WTP) of individual households or groups of households for changes in a combination of probabilistic water supply reliability and retail price of water. By modeling the costs (financial and ‘perceived’) of implementing long and short-term conservation measures and assuming rational (expected value cost minimizing behavior), demand curves for water and expected water use curves can be estimated. Derived demand curves for conservation measures can also be calculated. Next Monte Carlo simulation techniques are used to represent household variability in the model parameters and derive estimates of aggregate WTP for water supply reliability, water demand curves and demand curves for conservation measures. Several examples are provided to illustrate the approach.
Ann-based multiple dimension predictor for ship route prediction

This paper presents a new multiple dimension predictive model based on the diagonal recurrent neural networks (PDRNN) with a combined learning algorithm. This method can be used to predict not only values, but also some points in the multi-dimension space. And also its applications in data mining will be discussed in the paper. Some analysis results show the significant improvement to ship route prediction using the PDRNN model in database of geographic information system (GIS).
GAIN ESTIMATION METHODS FOR POLARIZED RADIO TELESCOPE ARRAYS

In radio telescope arrays, the complex receiver gains and sensor noise powers are initially unknown and have to be calibrated. This can be done by observing a strong astronomical point source. Here we extend the calibration algorithms to the case of dual polarized arrays. The algorithms are based on factor analysis and eigenvalue decompositions. We show that a single observation does not provide a unique solution. With two observations of two point sources with known brightness matrices, the gains can be estimated up to two unknown phases, and with three observations the ambiguity reduces to a single unknown phase.
Sequence-based bot detection in massive multiplayer online games

With the growing popularity of massive multiplayer online games (MMOG), the demand to protect these games and especially the participating players is increasing likewise. In this paper, we discuss a sequence-based solution to protect online games from being exploited by fully automated bots. Our research is based on various commercial and non-commercial bot implementations for the renowned game World of Warcraft. Our evaluation suggests, that a sequence-based detection technique is applicable even for mildly skilled players and effectively protects online games from a negative impact on game economics that causes both, grief to casual gamers and destroys game balance. Our implementation is fit to be deployed on either client- or server side, posing the first player-usable bot detection tool for World of Warcraft.
Two-dimensional crystals-based heterostructures: materials with tailored properties

Graphene is just one example of a large class of two-dimensional crystals. These crystals can either be extracted from layered three-dimensional materials or grown artificially by several different methods. Furthermore, they present physical properties that are unique because of the low dimensionality and their special crystal structure. They have potential for semiconducting behavior, magnetism, superconductivity, and even more complex many-body phenomena. Two-dimensional crystals can also be assembled in three-dimensional heterostructures that do not exist in nature and have tailored properties, opening an entirely new chapter in condensed matter research.
Pomegranate for Prevention and Treatment of Cancer: An Update

Cancer is the second leading cause of death in the United States, and those who survive cancer may experience lasting difficulties, including treatment side effects, as well as physical, cognitive, and psychosocial struggles. Naturally-occurring agents from dietary fruits and vegetables have received considerable attention for the prevention and treatment of cancers. These natural agents are safe and cost efficient in contrast to expensive chemotherapeutic agents, which may induce significant side effects. The pomegranate (Punica granatum L.) fruit has been used for the prevention and treatment of a multitude of diseases and ailments for centuries in ancient cultures. Pomegranate exhibits strong antioxidant activity and is a rich source of anthocyanins, ellagitannins, and hydrolysable tannins. Studies have shown that the pomegranate fruit as well as its juice, extract, and oil exert anti-inflammatory, anti-proliferative, and anti-tumorigenic properties by modulating multiple signaling pathways, which suggest its use as a promising chemopreventive/chemotherapeutic agent. This review summarizes preclinical and clinical studies highlighting the role of pomegranate in prevention and treatment of skin, breast, prostate, lung, and colon cancers.