Miracle-dz/UniFAR-FTUs huggingface dataset:
Respiratory muscle function and free radicals: from cell to COPD

Dysfunction of the respiratory muscles, especially the diaphragm, is known to occur in patients with severe chronic obstructive pulmonary disease (COPD). 1-3 Weakness of the diaphragm is part of a generalised process involving all (respiratory and peripheral) skeletal muscles. Causative factors for respiratory muscle dysfunction in COPD include disturbances in electrolytes,4hypercapnia,5 forward failure,6 and prolonged use of oral corticosteroids.7 In addition, the altered geometry of the thorax in severe emphysema compromises the ventilatory pump function of the diaphragm.8 Malnutrition, which frequently occurs in moderate to severe COPD,9 could also play a part in respiratory muscle dysfunction. Recent studies have indicated that wasting of fat free mass in COPD is associated with peripheral skeletal muscle weakness.10 However, few data are available regarding the effects of malnutrition on respiratory muscle strength. Maximal inspiratory pressure (Pimax) in nutritionally depleted patients with COPD (forced expiratory volume in one second (FEV1) 45.5 (15.1)% predicted) was lower than in non-depleted patients, but this did not reach statistical significance.9 Little is known about the underlying mechanisms of muscle dysfunction and the structural alterations that occur in the diaphragm with COPD. Levine et al 11 have shown that the diaphragm in patients with severe COPD (FEV1 33 (4)% predicted) has a higher proportion of type I (slow) fibres and a lower proportion of type II (fast) fibres than in those without COPD. It has recently been shown that a strong correlation exists between pulmonary functional residual capacity and the proportion of slow myosin heavy chain fibres in the diaphragm.12 This fast to slow fibre transition in the diaphragm can be regarded as an advantageous adaptation since it will attenuate fatiguability of the diaphragm.13 However, eventually most patients with COPD die from respiratory muscle …
A MSE model with learning mechanism and merging module based on FCA

Meta search engine improves the coverage of the search results, but itpsilas hard to ensure the accuracy of the search results. In order to improve search quality we propose a MSE model with learning mechanism and merging module based on FCA. Firstly, learning mechanism can adjust the expertness of member search engine in a certain domain by analyzing userpsilas behavior. Only when the expertness of member search engine reaches a certain value, can the member search engine be employed by meta search engine. Above all, we employ FCA to merge all the search results on the assumption that if a web page is retrieved by more member search engines it is more important. In the concept lattice, the intent of the concept includes member search engines and the extent of the concept includes the web pages retrieved by those member search engines. Because of its hierarchy structure, we can rank concepts by the number of its intents, and then rank the web pages included by the same concept according to their original places in member search engines and the expertness of member search engine which retrieved them.
Groupwise Processing of Relational Queries

In this paper, we define and examine a particular class of queries called group queries. Group queries are natural queries in many decisionsupport applications. The main characteristic of a group query is that it can be executed in a groupby-group fashion. In other words, the underlying relation(s) can be partitioned (based on some set of attributes) into disjoint groups, and each group can be processed separately. We give a syntactic criterion to identify these queries and prove its sufficiency. We also prove the strong result that every group query has an equivalent formulation that satisfies our syntactic criterion. We describe a general evaluation technique for group queries, and demonstrate how an optimizer can determine this plan. We then consider more complex queries whose components are group queries with potentially different partitioning attributes. We give two methods to identify group query components within such a query. We also give some performance results for group queries expressed in standard SQL, comparing a commercial database system with our optimized plan on top of the same commercial system. These results indicate that there are significant potential performance improvements.
On SLA constraints in dynamic bandwidth allocation for long-reach passive optical networks

Long-Reach Passive Optical Network (LRPON) technology seems to be a strong candidate for next generation optical access networks. LRPON aims to combine the advantages of optical metro and access networks before the backbone by offering long feeder distance and high split ratio. On the other hand, long feeder distance causes long propagation delay while together with high split ratio they lead to longer packet delay. In order to decrease packet delay, we have recently proposed a QoS-aware bandwidth allocation scheme which is called as Periodic Gate Optimization with QoS-awareness (PGO-QoS). This scheme is based on multi-threaded MPCP that has been previously proposed in the literature. In this paper, we briefly present PGO-QoS and discuss the impacts of buffer size on its performance under a feeder distance of 100 km. We show that PGO-QoS leads to shorter average delay than multi-threaded MPCP while slightly decreasing the packet loss ratio. As expected, larger buffer size increases the packet delay, especially under heavy loads. However, changing the buffer size does not affect the relative performance of PGO-QoS to the multi-threaded MPCP. Furthermore, we evaluate the effects of pre-specified delay bounds on the performance of PGO-QoS where each ONU runs an estimation to determine whether an incoming packet can reach the OLT within its delay bound.
A Cloud Oriented Approach for People-Provided Services

Web 2.0 started a paradigm shift concerning content generation. Users spend hours browsing and producing contents to share, most of the times, freely. During these activities, their laptops and home PCs are considerably underused. By combining the amount of idle processing capacity with increasingly fast internet accesses, every computer can be considered as a computational “nearby” resource. The question is: what to do with them? This paper explores how these resources can be used to give something back to the user in a secure and private way.
Lightweight Contextual Ranking of City Pictures: Urban Sociology to the Rescue

To increase mobile user engagement, photo sharing sites are trying to identify interesting and memorable pictures. Past proposals for identifying such pictures have relied on either metadata (e.g., likes) or visual features. In practice, techniques based on those two inputs do not always work: metadata is sparse (only few pictures have considerable number of likes), and extracting visual features is computationally expensive. In mobile solutions, geo-referenced content becomes increasingly important. The premise behind this work is that pictures of a neighborhood is linked to the way the neighborhood is perceived by people: whether it is, for instance, distinctive and beautiful or not. Since 1970s, urban theories proposed by Lynch, Milgram and Peterson aimed at systematically capturing the way people perceive neighborhoods. Here we tested whether those theories could be put to use for automatically identifying appealing city pictures. We did so by gathering geo-referenced Flickr pictures in the city of London; selecting six urban qualities associated with those urban theories; computing proxies for those qualities from online social media data; and ranking Flickr pictures based on those proxies. We find that our proposal enjoys three main desirable properties: it is effective, scalable, and aware of contextual changes such as time of day and weather condition. All this suggests new promising research directions for multi-modal learning approaches that automatically identify appealing city pictures.
An Australian perspective on inflation targeting, communication and transparency

When countries began to adopt inflation targets more than a decade ago, their aim was to put in place a credible framework that avoided the drawbacks of previous policy regimes. In New Zealand, Canada and Australia, inflation targets replaced ad hoc regimes that were considered intellectually unsatisfactory and had been associated with periods of poor inflation performance. In the United Kingdom and Sweden, inflation targeting replaced failed exchange rate pegs. In each case, the designers of the new targets sought a balance between constraining the central bank in terms of policy outcomes, and allowing a realistic degree of flexibility in the setting of the policy instrument.
Analysis of machine learning solutions to detect malware in android

The recent use of mobile devices and increase in connectivity technologies(GSM, GPRS, Bluetooth & WiFi enable us to access abundant services. These services and communication channels are exploited by susceptibilities immensely. Hence, for malware writers, mobile devices became ideal target. Applications installed on smartphones request access to the sensitive information which may lead to security vulnerabilities. Different malwares named as Botnet, Backdoor, Rootkits, Virus, Worms, and Trojans can attack android Operating System (OS). Due to these attacks privacy of the users is compromised. This paper surveys the already proposed security solutions by using machine learning approaches especially focused on supervised, semi supervised and unsupervised approaches. We also analyzed the architecture of these approaches and present the taxonomy of Android OS based security solutions. Our aim is to provide the best approach for malware detection in Android OS.
Density-Based Clustering Validation

One of the most challenging aspects of clustering is validation, which is the objective and quantitative assessment of clustering results. A number of different relative validity criteria have been proposed for the validation of globular, clusters. Not all data, however, are composed of globular clusters. Density-based clustering algorithms seek partitions with high density areas of points (clusters, not necessarily globular) separated by low density areas, possibly containing noise objects. In these cases relative validity indices proposed for globular cluster validation may fail. In this paper we propose a relative validation index for density-based, arbitrarily shaped clusters. The index assesses clustering quality based on the relative density connection between pairs of objects. Our index is formulated on the basis of a new kernel density function, which is used to compute the density of objects and to evaluate the within- and between-cluster density connectedness of clustering results. Experiments on synthetic and real world data show the effectiveness of our approach for the evaluation and selection of clustering algo rithms and their respective appropriate parameters.
On Hydrophobicity Correlations in Protein Chains Submitted to Biophysical Journal

We study the statistical properties of hydrophobic/polar model sequences with unique native states on the square lattice. It is shown that this ensemble of sequences differs from random sequences in signiicant ways in terms of both the distribution of hydrophobicity along the chains and total hydrophobicity. Whenever statistically feasible, the analogous calculations are performed for a set of real enzymes, too.
Integrating Genomic and Proteomic Data: The Integr8 Project

Summary Integr8 (http://www.ebi.ac.uk/integr8/) has been developed to provide an integration layer for the exploitation of genomic and proteomic data. High-quality databases from major bioinformatics centres in Europe are included, and some core data and the relationships of biological entities to each other and to entries in other databases are stored. Thus, a framework exists that allows for new kinds of data to be integrated, and an entity-centric view of complete genomes and proteomes is offered. Integr8 is an automatically populated database, providing different entry points to the data, depending on the user’s entity of interest. The Proteome Analysis database for statistical analysis and the Genome Reviews for annotated genome information are the main developments within the Integr8 project. With the BioMart application, an interactive querying tool for performing customisable proteome analysis and data mining is offered. Future developments will especially focus on the Genome Reviews, including mapping not yet annotated protein sequences onto their corresponding genomes, generating new predictions for non-coding RNA genes, and generally extending the scope to lower metazoan organisms.
Impact of Multimorbidity on Disability and Quality of Life in the Spanish Older Population

Background Population aging is closely related to high prevalence of chronic conditions in developed countries. In this context, health care policies aim to increase life span cost-effectively while maintaining quality of life and functional ability. There is still, however, a need for further understanding of how chronic conditions affect these health aspects. The aim of this paper is to assess the individual and combined impact of chronic physical and mental conditions on quality of life and disability in Spain, and secondly to show gender trends. Methods Cross-sectional data were collected from the COURAGE study. A total of 3,625 participants over 50 years old from Spain were included. Crude and adjusted multiple linear regressions were conducted to detect associations between individual chronic conditions and disability, and between chronic conditions and quality of life. Separate models were used to assess the influence of the number of diseases on the same variables. Additional analogous regressions were performed for males and females. Results All chronic conditions except hypertension were statistically associated with poor results in quality of life and disability. Depression, anxiety and stroke were found to have the greatest impact on outcomes. The number of chronic conditions was associated with substantially lower quality of life [β for 4+ diseases: −18.10 (−20.95,−15.25)] and greater disability [β for 4+ diseases: 27.64 (24.99,30.29]. In general, women suffered from higher rates of multimorbidity and poorer results in quality of life and disability. Conclusions Chronic conditions impact greatly on quality of life and disability in the older Spanish population, especially when co-occurring diseases are added. Multimorbidity considerations should be a priority in the development of future health policies focused on quality of life and disability. Further studies would benefit from an expanded selection of diseases. Policies should also deal with gender idiosyncrasy in certain cases.
DoS and port scan attack detection in high speed networks

One of the necessities of high-speed Internet highways is the use of intrusion detection systems (IDSs). To this end, IDS should be able to process a high volume of traffic with limited resources. IDSs have improved significantly in recent years and they showed acceptable outcomes. However, there is no appropriate solution for high-speed networks. This paper proposes a solution for diagnosing denial of service (DoS) and port scan attacks as a layer of defense. The proposed method attains high speed rate using a parallel data structure to filter out DoS and port scan attacks from network traffic before entering the intrusion detection system. Attack filtering is based on statistical anomaly detection. The experimental results from implementing and evaluating the proposed method show acceptable records in both error rate and speed.
Industry 4.0 Intelligence under Attack : From Cognitive Hack to Data Poisoning

Artificial intelligence is an unavoidable asset of Industry 4.0. Artificial actors participate in real-time decision-making and problem solving in various industrial processes, including planning, production, and management. Their efficiency, as well as intelligent and autonomous behavior is highly dependent on the ability to learn from examples, which creates new vulnerabilities exploited by security threats. Today`s disruptive attacks of hackers go beyond system`s infrastructures targeting not only hard-coded software or hardware, but foremost data and trained decision models, in order to approach system`s intelligence and compromise its work. This paper intends to reveal security threats which are new in the industrial context by observing the latest discoveries in the AI domain. Our focus is data poisoning attacks caused by adversarial training samples and subsequent corruption of machine learning process.
Oxidative and reductive metabolism by cytochrome P450 2E1

We are constantly exposed to many potentially toxic chemicals. Most require metabolic activation to species responsible for cell injury. Although cytochrome P450 2E1 is only one of many different forms of cytochrome P450 that catalyze these reactions, it has an important role in human health as a result of being readily induced by acute and chronic alcohol ingestion. The enzyme efficiently catalyzes the low Km metabolism of compounds commonly used as solvents in industry and at home as well as components found in cigarette smoke, many of which are established carcinogens and hepatotoxins. As a result, there is the potential for increased risk to low level exposure to such chemicals while cytochrome P450 2E1 is induced. Many substrates have been identified for cytochrome P450 2E1. Of the 52 substrates for the enzyme identified in this review, the demethylation of N,N‐dimethylnitrosamine and the hydroxylation of p‐nitrophenol and chlorzoxazone are the most effective for monitoring the level of this enzyme. In addition to oxidative reactions, cytochrome P450 2E1 is also an efficient catalyst of reductive reactions. CCl4‐induced hepatotoxicity is one of the best‐documented cases for the participation of cytochrome P450 2E1 in a toxicologically important reductive reaction. The reduction of oxygen to superoxide and peroxide are also important reductive reactions of the enzyme and could be important in lipid peroxidation. However, the role of this reaction in vivo remains controversial. —Koop, D. R. Oxidative and reductive metabolism by cytochrome P450 2E1. FASEB J. 6: 724‐730; 1992.
Design, Fabrication and Control of a Three-Finger Robotic Gripper

In this article a robotic gripper with the ability of cylindrical object grasping is designed and fabricated. With the increasing use of robotic arms in industry, grasping and holding, as a part of industrial processes, are of great importance. Hence, proper design of grippers plays a key role in efficient performance of robotic arms. The main feature of this design is its reliability and efficiency while maintaining simplicity. This robotic gripper is designed for installing on a mobile robot with the task of holding and moving cylindrical object. One of the aspects of an efficient robotic gripper is its ability to satisfy the "Form-gripping" feature which is utilized for the presented design. Kinematic consideration is examined by Catia. Finally, control methods through Matlab and experimental test results are presented in this paper.
Associative Effects: Competition, Social Interactions, Group and Kin Selection

The phenotypes of those individuals with which an focal individual interacts often influences the trait value in the focal individual. Maternal effects is a classic example of this phenomena, as is fitness. If these traits are heritable, then the selection response depends on both the change in the direct effects influencing a target trait and the associative effects contributed by interacting individuals. In such a setting, the breeder's equation no longer holds, as the problem is now a multiple trait one. This chapter examines the theory of response under models with both direct and associative effects, which can lead to a reversed response (a trait selected to increase instead decreases). The evolution of behavioral traits, including the evolution of altruism, is best handled using this approach. Further, kin and group selection follow as special cases of the gerenal model under multilevel selection. This chapter also examines how mixed models can be used estimate model parameters.
Critical dynamics of an interacting magnetic nanoparticle system

Effects of dipole-dipole interactions on the magnetic relaxation have been investigated for three Fe-C nanoparticle samples with volume concentrations of 0.06, 5 and 17 vol%. While both the 5 and 17 vol% samples exhibit collective behaviour due to dipolar interactions, only the 17 vol% sample displays critical behaviour close to its transition temperature. The behaviour of the 5 vol% sample can be attributed to a mixture of collective and single-particle dynamics.
Board governance from life cycle perspectives

There's a general view that with governance of board, poor performance will lead to CEO's turnover, but will this relationship change over the corporate life-cycle, this paper is to investigate the impact of life-cycle on performance-turnover relation. Samples are selected from Shenzhen Stock Exchange listed companies during period 2009-2011, the regression results show that as corporation matures the sensitivity of CEO turnover to poor performance will decrease.
Recent Results on Sizing Router Buffers

Today all Internet routers are built with buffers that hold packets in times of congestion. These buffers can typically store between 250ms to one second worth of data. According to a widely used “rule-of-thumb”, a link needs a buffer of size B = RTT × C, where RTT is the average round-trip time of a flow passing across the link, and C is the data rate of the link. For example, a 10Gb/s router linecard needs approximately 250ms × 10Gb/s = 2.5Gbits of buffers; and the amount of buffering grows linearly with the line-rate. Such large buffers are challenging for router manufacturers, who must use large, slow, off-chip DRAMs. They also lead to high latencies in case of congestion. Recent research suggest that the rule-of-thumb (B = RTT ×C) is now outdated and incorrect for routers serving highly aggregated traffic. According to these new results, a link with n flows requires no more than B = (RTT × C)/ √ n, for long-lived or short-lived TCP flows. These lower buffer requirements have been verified in simulation and laboratory experiments as well as on real networks with live traffic. The consequences on router design are enormous: a 2.5Gb/s link carrying 10,000 flows could reduce its buffers by 99% with negligible difference in throughput, and a 10Gb/s link carrying 50,000 flows requires only 10Mbits of buffering, which can easily be implemented using fast, on-chip SRAM.