Miracle-dz/UniFAR-FTUs huggingface dataset:
Ecotypes and Ecosystem Function

ecotype in ecosystem function is primarily one of allowing a community of organisms to adjust to its habitat. " The second: "The simultaneous selection of ecotypic variants within different kinds of organisms occupying a given area results in harmonious functions of a particular ecosystem. " The third: "The selection of eco-genetic gradients results in the continuity of an ecosystem-type over geographic diversity. " These three statements, modified here with reference to ecosystems, were made originally with respect to "ecotypes and community function" (McMillan, 1960). Their application here in reference to ecosystem function was facilitated by the use of the same basic concepts: (a) that ecotype, ecotypic differentiation, eco-genetic gradient refer to genetically-based variation that is habitat correlated; (b) that community is applied to the sum total of organisms in a given area; (c) that population is applied to the one or more individuals of a close genetic lineage in a given area; (d) that ecosystem is applied to the sum total of organisms (the community and its included populations) and to their relations with their environmental surroundings in a given area; and (e) that ecosystem-type results from the lumping or sorting of certain ecosystems into a particular kind. To these basic concepts, a time relation is indicated: at a given time. The modified application from the community to the ecosystem has changed the focus from the
Impulse Feature Extraction of Bearing Faults Based on Convolutive Nonnegative Matrix Factorization

The detection of bearing faults is of great significance for the stable operation of rotating machinery. Apart from detection by analysing the vibration response, another powerful strategy is to extract the periodic impulse excitation directly induced by faults, which efficiently eliminates the influence of the transmission path and noise. Typical methods of this strategy include maximum correlated kurtosis deconvolution (MCKD) and multipoint optimal minimum entropy deconvolution (MOMEDA). However, these deconvolution methods based on maximizing a certain measurement index are still insufficient at finding the correct fault period directly because of the interference of noise components. To effectively extract the periodic impulse excitation from the vibration response, a new impulse feature extraction method from the vibration spectrogram based on convex hull convolutive nonnegative matrix factorization (CH-CNMF) is proposed. As the spectrogram intuitively reveals the time and frequency information of the impulse response generated by the fault excitation, according to the decomposition characteristics of CH-CNMF, the time-frequency structure of the impulse response is represented by the basis tensor, while the weight matrix corresponds to the impulse excitation. Meanwhile, autocorrelation is adopted to enhance the periodic impulse excitation. Finally, based on power spectral entropy and first-order correlated kurtosis, the optimal periodic pulse can be selected from the autocorrelation curves of the weight matrix. Both numerical simulation and experimental verifications on bearings indicate that the proposed method can eliminate the influence of random shock excitations and directly attain the periodic impulse for the source of the bearing fault, and that its extraction effectiveness outperforms MOMEDA.
IMMUNOHISTOCHEMICAL EXPRESSION OF S-100 PROTEIN IN REACTIVE AND NEOPLASTIC MYOEPITHELIAL CELLS OF VARIANT SALIVARY PLEOMORPHIC ADENOMAS

Immunohistochemically detectable S-100 protein in 76 salivary pleomorphic adenomas was found in two types of myoepithelium derived neoplastic cells; spindle-shaped anastomosing cells and round cells. Spindle-shaped tumor cells displayed a strong presence of S-100 protein-like immunoreactive substance (LIS), and they were usually located in the outer layer of duct-like structures and showed a continued proliferation into the stroma. Round tumor cells abundantly gave a S-100 protein LIS staining, and they were distributed in the outer layer of duct-like structures. Chondroid cells and chondrocytes in hyalinous and myxomatous tissue were also reactive for S-100 protein LIS. In rare cases, stromal connective tissue fibers exhibited an intense S-100 protein LIS staining. Peripheral nerve fibers and myoepithelial cells in the affected salivary glands were also positive for S-100 protein LIS.
Comparison of Outer and Inner-Rotor toothed doubly salient permanent magnet

This paper presents a results comparison synthesis of an outer and inner rotor doubly salient permanent magnet machine operating at low speed. The outer rotor design has the benefit that coils and cooling can be placed near the shaft, increasing the possible stator bore radius. Consequently, the space required for the coils inside the stator. Electromagnetic design and performances results of the machine is presented and discussed in the following paragraphs.
The Influence of Translocation Strategy and Management Practices on the Genetic Variability of a Reestablished Elk (Cervus elaphus) Population

Reintroduction of terrestrial vertebrates with the goal of ecosystem restoration typically establishes small and isolated populations that may experience reduced genetic variability due to founder effects and genetic drift. Understanding the genetic structure of these populations and maintaining adequate genetic diversity is important for long‐term restoration success. We quantified genetic variability at six microsatellite loci for a reintroduced population of Cervus elaphus (elk) restored to the tallgrass prairie ecosystem of northeastern Kansas. Allelic richness, observed and expected heterozygosity were intermediate to levels reported in other North American elk populations. Current levels of genetic variability in restored North American elk populations were not well explained by founding population size, number of founding populations, or number of years since the last translocation. Simulation results suggest that the retention of genetic variability in isolated populations is strongly influenced by mating system while also being impacted by temporal variability in population size and population growth rate. Our results have implications for understanding how translocation strategies and post‐reintroduction management may influence genetic variability in restored populations.
Blind Source Separation Algorithm for Chaotic Masking Multipath Signals Based on Spectral Peak Search Counter Permutation

Since voice communication is the main method of information transmission, it is important to ensure the safety and efficiency of voice communication. In this paper, a more complex multipath channel model in a wireless environment is considered, and chaotic masking technology is used to ensure the security of voice signal transmission. Based on this, a multipath blind source separation algorithm based on cross-correlation permutation of spectral peak search counters is proposed. First, chaotic masking is performed between multiple voice signals and chaotic signal, and an impulse response filter is used to simulate the multipath transmission process. Next, the short-time Fourier transform is employed to convert the observation signal into a frequency-domain signal. Then, the joint approximate diagonalization of eigen-matrix algorithm is used to perform linear instantaneous blind source separation at each frequency. And to solve the permutation uncertainty problem in the frequency domain method, a cross-correlation permutation algorithm based on a spectral peak search counter is proposed. Finally, the permuted signal is transformed back to the time domain to get the estimated source signal by the inverse short-time Fourier transform. And simulation experiments show that the algorithm greatly reduces the calculation amount of the autocorrelation coefficient in the traditional permutation algorithm. Moreover, the permutation algorithm has stability and accuracy, and provides a solution for the secure transmission and effective separation of voice signals in multipath transmission channels.
Cloud-based Implementation of an Automatic Pixel-based Neighbour Identification System for Cellular Networks

With the ever-increasing demand for mobile bandwidth, the quantity of deployed cells also increases exponentially, creating heterogeneous networks of cells of varying sizes in order to accommodate the spatial domains that they occupy. This creates issues in Handover performance, where it becomes difficult to manage when and to which base station should a mobile user swap to during a connection without significant losses in performance, due to the large quantity of cells in one space. On the other hand, systems like Automatic Neighbour Relations, present in 4G Long Term Evolution configurations, mostly consider Handover statistics to decide the best neighbours, which is insufficient due to potential problems with signal coverage and load balancing which it cannot answer to. In this paper, an implementation of a cloud-based automated pixel-based neighbour identification system for cellular networks using Amazon Web Services is presented, wherein it generates high quality ranked Neighbour Cell Lists by utilizing cell topology and associated signal strengths in a map defined by a Pixel grid, which itself is built from data provided by the network’s Operations Support System. It’s completely technology agnostic and it’s incorporated as a package in the Metric Software as a Service ecosystem, facilitating network planning assessment by measuring the cells’ coverage overlap, and initializing neighbour lists. The proposed method can be used as a starting point for ANR, since it’s capable of building a neighbour cell list in some seconds for a new network deployment, which can be then optimised by ANR mechanisms later with an operating network.
SARRC: Secure Auditing and Re-signing of Revoked Customer Chunks by Cloud Using Regression Method

The demand of deploying information has enormously increased within the last decade. Numerous distributed computing service suppliers have emerged (for eg., Microsoft Azure, Dropbox) in order to satisfy the requirements for information repository and high performance computation. The customers using the cloud repository services can conveniently arrange as a cluster and distribute information among themselves. Information proprietor computes the signatures for every chunk and deploys in the distributed server in order to allow the public verifier to perform public integrity verification on the information stored on the cloud server. In Panda scheme [1], by using the proxy re-signatures, Cloud Service Provider (CSP) verifies and re-signs the revoked customer chunks in favor of the existing customers. The malicious CSP might use the Resign key deliberately to transform the signature of one customer to another. Apart from this, conspiracy amidst the mischievous cloud server and the repudiated customer reveals the private key information of the customers present in the cluster. We propose Secure Auditing and Re-signing of Revoked Customer Chunks by Cloud Using Regression Method. Re-key computed by the information proprietor using regression method is highly secure and the mischievious cloud cannot detect the private information of the customers in the cluster. Our mechanism is collusion resistant, reduces computation cost of re-sign key by information proprietor and in addition CSP securely performs auditing and re-signing of repudiated customer chunks.
A Two-stage Approach for Virtual Resources Adaptive Scheduling in Container Cloud*

In container cloud, when allocating resources for virtual machines(VMs) and containers, it is very important to improve the computing resources utilization. The virtual resources allocating process could be divided into two stages. The first stage is to place the VMs on the physical machines(PMs), and this sub-process will be constrained by PMs’ resources. The second stage is to place the containers on the virtual machines, and this sub-process will be constrained by VMs. We views this process as secondary bin packing problem, and use different packing strategies according the different characteristics of each stage. we proposed the two-stage virtual resources adaptive scheduling algorithm to deal with this problem. The experimental results show that the proposed algorithm can efficiently improve the data center’s computing resources utilization.
Multiattack Intrusion Detection Algorithm for Edge-Assisted Internet of Things

With the continuous development of edge-assisted internet of things (IoT) applications, a large number of computing tasks need to be offloaded into the edge servers. It is critical to secure the security of IoT data transmission to the edge. In this paper, we propose a multi-attack intrusion detection system (IDS) for edge-assisted IoT using the back propagation (BP) Neural Network, and Radial basis function (RBF) neural network. Especially, BP neural network is exploited to find the abnormal and get the importance of features for each attack. Radial basis function (RBF) neural network is used for detecting multi-attack intrusion. The results show high accuracy in proposed multi-attack scenario and elucidate the feasibility and preeminence of our proposed anomaly detection framework.
Analysis of Self-Organizing Maps (SOM) Methods for Cell Clustering with High-Dimensional OAM Collected Data

Mobile network produces a large amount of Operations, Administration and Maintenance (OAM) data. These data include different parameters of the base station and performance information of different cells. The Self-organizing Map (SOM) is an effective neural network for decreasing dimension, visualizing and clustering high dimensional data. It always transforming input vectors into one or two-dimensional grid prototype vectors and reorder them into different groups, which are easier to characterize and visualize the original data. In this work, our objective of this study is to explore and extract several representative cell patterns, at the same time visualizing and clustering cells via the data set analysis by using Self-Organization Maps (SOM) methods and cluster cells into different groups based on various of features in radio access network (RAN) in LTE. We built a SOM model of the network using vectors from all LTE cells. Obtained results show the successful cluster in cells achievable by the SOM.
Non‐conventional signal transduction by type 1 interferons: The NF‐κB pathway

Type I interferons (IFNs) regulate diverse cellular functions by modulating the expression of IFN‐stimulated genes (ISGs) through the activation of the well established signal transduction pathway of the Janus Kinase (JAK) and signal transducers and activators of transcription (STAT) proteins. Although the JAK–STAT signal transduction pathway is critical in mediating IFN's antiviral and antiproliferative activities, other signaling pathways are activated by IFNs and regulate cellular response to IFN. The NF‐κB transcription factor regulates the expression of genes involved in cell survival and immune responses. We have identified a novel IFN mediated signal pathway that leads to NF‐κB activation and demonstrate that a subset of ISGs that play key roles in cellular response to IFN is regulated by NF‐κB. This review focuses on the IFN‐induced NF‐κB activation pathway and the role of NF‐κB in ISG expression, antiviral activity and apoptosis, and the therapeutic application of IFN in cancer and infectious disease. J. Cell. Biochem. 102: 1087–1094, 2007. © 2007 Wiley‐Liss, Inc.
Oligodendrocyte ARNT2 expression is altered in models of MS

Objective We examined expression of aryl hydrocarbon receptor nuclear translocator 2 (ARNT2), a basic-loop-helix transcription factor implicated in neuronal development and axonal health, in oligodendrocyte (OL) cultures and over the course of chronic experimental autoimmune encephalomyelitis (EAE), the murine model of multiple sclerosis (MS). Methods We assessed OL ARNT2 expression in EAE compared with sham-immunized controls and also in OL primary cultures and over the course of dibutyryl cyclic adenosine monophosphate (dbcAMP)-mediated maturation of the immortalized Oli-neu cell line. We also tested the functional role of ARNT2 in influencing OL characteristics using small interfering RNA (siRNA). Results ARNT2 is localized to Olig2+ cells in healthy spinal cord gray and white matter. Despite a significant expansion of Olig2+ cells in the white matter at peak disease, ARNT2 is reduced by almost half in OLs, along with a reduction in the percentage of ARNT2+/Olig2+ cells. Mature OLs in mixed cortical cultures or OLs matured from embryonic progenitors express negligible ARNT2. Similarly, Oli-neu cells express high levels of ARNT2, which are reduced following dbcAMP maturation. siRNA-mediated knockdown of ARNT2 affected OL viability, which led to an enrichment of myelin-producing OLs. Conclusion The analysis of ARNT2 expression in OLs demonstrates that OL ARNT2 expression is altered in EAE and during OL maturation. Findings point to ARNT2 as an important mediator of OL viability and differentiation and warrant further characterization as a target for intervention in demyelinating disorders such as MS.
Antecedents of eCRM success in the hospitality industry

Effective electronic customer relationship management (eCRM) has become a crucial strategy and one of the fastest growing management approaches being adopted across many organizations, including the hospitality industry. However, not all organisations succeed in their eCRM initiatives because of their firm’s inherent factors. This study proposes a framework of eCRM success determinants, using the hotel industry in Thailand as a case study. The four dimensions of eCRM are examined as antecedents of successful eCRM implementation. This research also evaluates the relationships among these eCRM dimensions, successful eCRM implementation and a hotel’s performance. To achieve the intended objectives, this study uses structural equation modelling (SEM) to analysis data; the results show the antecedents of eCRM constructs have a significant impact on eCRM success, which in turn positively influences hotel performance.
Desempenho, digestibilidade e balanço de nitrogênio em cordeiros alimentados com silagem de milho ou cana-de-açúcar e dois níveis de concentrado

Thirty-two non castrated Ile de France lambs fed corn silage or sugar-cane based diets with two roughage:concentrate ratios (60:40 or 40:60) were used. The animals were kept individually confined with control of the supplied food and leftovers, weekly weighted for determination of the daily weight gain and food conversion. Simultaneously, it was carried out digestibility and metabolism trials to determine the nutrient intake and digestibility and nitrogen balance of the experiment diets. The weight gain (294.6 g/day) was higher for the lambs fed corn silage, and regarding to roughage:concentrate 40:60 it was 314.3 g/day. The ratio roughage:concentrate only influenced the consume of digestible fiber in neutral detergent (NDF) and fiber in acid detergent (FAD) in which the highest values, 125.26 and 48.97 g/day obtained with the ratio roughage:concentrate 60:40. The lambs fed corn silage showed a higher intake of all digestible nutrients, except for crude protein (162.00 g/day) and non fibrous carbohydrates (471.42 g/day). The highest digestibility of organic matter (80.34%) and total carbohydrates (80.71%) were obtained with the 40:60 ratio and those of dry matter (78.91%), crude protein (81.30%) and gross energy (78.77%) were obtained for the lambs fed sugar cane. The highest values for ingested, absorbed and retained nitrogen, 32.6, 20.5 and 13.7 g/day, respectively, were observed in diets with 40% of roughage. The type of roughage influences more the nutrient digestibility than its proportion in the diet.
Abundance and distribution of endangered Franciscana dolphins in Argentine waters and conservation implications

This is the first study in Argentine waters on the abundance of the threatened Franciscana dolphin, Pontoporia blainvillei. During 2003–2004 we carried out 17 aerial surveys using line transect sampling methodology. We observed 101 Franciscanas in 71 sightings. In northern areas density was estimated at 0.106 individual/km 2 . Density was lower in southern areas (0.055/km 2 ) and declined with depth beyond 30-m isobaths (0.05/km 2 ). A correction factor for submerged dolphins was applied to density and then extrapolated to the strip between the coastline and the 30-m isobath. Abundance in the northern area was estimated at 8,279 (4,904–13,960) individuals, while in the southern area it was estimated at 5,896 (1,928–17,999) individuals. Considering an annual mortality of about
Artificial Human Balance Control by Calf Muscle Activation Modelling

The natural neuromuscular model has greatly inspired the development of control mechanisms in addressing the uncertainty challenges in robotic systems. Although the underpinning neural reaction of posture control remains unknown, recent studies suggest that muscle activation driven by the nervous system plays a key role in human postural responses to environmental disturbance. Given that the human calf is mainly formed by two muscles, this paper presents an integrated calf control model with the two comprising components representing the activations of the two calf muscles. The contributions of each component towards the artificial control of the calf are determined by their weights, which are carefully designed to simulate the natural biological calf. The proposed calf modelling has also been applied to robotic ankle exoskeleton control. The proposed work was validated and evaluated by both biological and engineering simulation approaches, and the experimental results revealed that the proposed model successfully performed over 92% of the muscle activation naturally made by human participants, and the actions led by the simulated ankle exoskeleton wearers were overall consistent with that by the natural biological response.
Preferential usage of Vα4 and Vβ10 T cell receptor genes by lymphocytic choriomeningitis virus glycoprotein‐specific H‐2Db‐restricted cytotoxic T cells

Correlations between the T cell receptor (TcR) V gene usage and the specificity of T cells have been primarily described for major histocompatibility complex (MHC) class II‐restricted helper T cell responses. In the present study the TcR genes expressed by MHC class I‐restricted murine cytotoxic T cells (CTL) specific for a major epitope of the lymphocytic choriomeningitis virus (LCMV), LCMV‐GP2275–289, were investigated. The TcR primary structure of an LCMV‐GP2275–289 specific H‐2Db‐restricted CTL clone has been determined. It uses a member of the Vα4 family joined to JαAN14. 4 for the α chain and Vβ10 rearranged to Dβ2. 1 and Jβ2. 4 for its β chain. Four other independent LCMV‐GP2275–289 specific H‐2Db‐restricted CTL clones also expressed Vα4 and Vβ10 gene elements. Furthermore, Vα4 and Vβ10 were preferentially expressed by polyclonal CTL of C57BL/6 origin specific for LCMV. These results suggest that both TcR Vα and Vβ regions are important for the recognition of the LCMV‐GP2275‐289 epitope on H‐2Db molecules.