Miracle-dz/UniFAR-FTUs huggingface dataset:
The contribution of rectangularization to the secular increase of life expectancy: an empirical study.

BACKGROUND In low-mortality countries, life expectancy is increasing steadily. This increase can be disentangled into two separate components: the delayed incidence of death (i.e. the rectangularization of the survival curve) and the shift of maximal age at death to the right (i.e. the extension of longevity). METHODS We studied the secular increase of life expectancy at age 50 in nine European countries between 1922 and 2006. The respective contributions of rectangularization and longevity to increasing life expectancy are quantified with a specific tool. RESULTS For men, an acceleration of rectangularization was observed in the 1980s in all nine countries, whereas a deceleration occurred among women in six countries in the 1960s. These diverging trends are likely to reflect the gender-specific trends in smoking. As for longevity, the extension was steady from 1922 in both genders in almost all countries. The gain of years due to longevity extension exceeded the gain due to rectangularization. This predominance over rectangularization was still observed during the most recent decades. CONCLUSIONS Disentangling life expectancy into components offers new insights into the underlying mechanisms and possible determinants. Rectangularization mainly reflects the secular changes of the known determinants of early mortality, including smoking. Explaining the increase of maximal age at death is a more complex challenge. It might be related to slow and lifelong changes in the socio-economic environment and lifestyles as well as population composition. The still increasing longevity does not suggest that we are approaching any upper limit of human longevity.
Signal transduction pathways for activation of extracellular signal‐regulated kinase by arachidonic acid in rat neutrophils

Phosphorylation of extracellular signal‐regulated kinase (ERK) inresponse to arachidonic acid (AA) was rapid and transient, peaking at 1min and disappearing after 3 min, and it was accompanied by an increasein ERK activity in rat neutrophils. We examined the upstream regulationof AA‐stimulated ERK activation using one of the following signalingpathway inhibitors to pretreat rat cells: the ERK kinase inhibitorU0126 or PD98059, the Gi/o inhibitor pertussis toxin (PTX),the tyrosine kinase inhibitor genistein, the phosphatidylinositol3‐kinase (PI3K) inhibitor wortmannin or LY294002, the Ca2+chelator 1,2‐bis(O‐aminophenoxy)ethane‐N,N,N′,N′‐tetraacetic acid, or the phospholipase C(PLC) inhibitor U73122. All of these inhibitors attenuated AA‐inducedERK activation. Activation of ERK was also effectively attenuated bythe cyclooxygenase and lipoxygenase inhibitor BW755C and by theleukotriene biosynthesis inhibitor MK886, but the cyclooxygenaseinhibitor indomethacin did not attenuate ERK activation. After exposingcells to three distinct protein kinase C (PKC) inhibitors, we foundthat Gö6976 significantly attenuated ERK phosphorylation butpotentiated ERK activity. Neither Gö6983 nor GF109203Xaffected AA‐induced responses. These data suggest that the lipoxygenasemetabolite(s) produced mediates AA‐stimulated ERK activation and thatthis effect is upstream regulated by PT‐sensitive G protein,nonreceptor tyrosine kinase, PI3K, and PLC/Ca2+ signalingpathways in rat neutrophils.
Social Network Visualization: Can We Go Beyond the Graph?

Visualizations have played an important role in generating new insights in social network analysis. We suggest that such visualizations can be of interest not only to analysts and researchers but also to the people whose data is being analyzed. In this paper we briefly talk about two visualizations of email that we developed to give people a better sense of their email archives and social networks. One visualization shows a traditional network graph with email contacts as nodes. The second visualization depicts the temporal rhythms of interactions in dyadic relationships between ego and individual contacts. While observing and interviewing users of these systems, it became clear that, when used in tandem, these visualizations complemented and clarified each other’s depiction of a person’s social network. Based on our experience with these two systems, we propose that visualizations of social networks that are aimed at end users ought to go beyond the graph paradigm. We posit that basic cartographic principles – such as adaptive zooming and multiple viewing modes – provide system designers with useful visual solutions to the depiction
Speech enhancement based on hidden Markov model with discrete cosine transform coefficients using Laplace and Gaussian distributions

This paper presents a novel HMM-based speech enhancement framework based on Laplace and Gaussian distributions in DCT domain. We propose analytical procedures for training clean speech and noise models with the aim of Baum's auxiliary function and present two MMSE estimators based on Gaussian-Gaussian (for clean speech and noise respectively) and Laplace-Gaussian combinations in the HMM framework. The performance evaluation is done using SNR and PESQ measures and the results of the proposed techniques are compared with AR-HMM approach. Higher SNR improvement is achieved for the proposed method in the Gaussian-Gaussian case in comparison with AR-HMM and Laplace-Gaussian techniques for both nonstationary and stationary noises. A similar result is obtained in term of PESQ in the presence of nonstationary noise types.
Machine learning based blog classification personal vs. official facet

Since the blog service brings a wealth of information resources, blog search and classification are showing their great research value. This paper focuses on the blog classification on the personal vs. official facet. Our system adopts a two-stage strategy; in training model, lexicons are built automatically; in classification model, scoring and ranking are carried out orderly. Our experimental results reveal that feature selection, Mutual Information weighting are good for lexicons with significant results. However, sentiment words can only slightly improve the results.
A Method for Estimating Mean First-passage Time in Genetic Algorithms

This paper presents a simple method for estimating the mean time at which the best solution, or optimum allele, appears for the first time in the search process of genetic algorithms. A set of equations modified from Eigen’s evolution equation is used for calculating the mean first-passage time. The essential point of the method is that the optimum allele is considered as an absorbing state. It is shown that the theory can generally reproduce numerical experiments on three types of fitness landscapes.
Structures containing Atg9A and the ULK1 complex independently target depolarized mitochondria at initial stages of Parkin-mediated mitophagy

Mitochondria can be degraded by autophagy in a process termed mitophagy. The Parkinson-disease-associated ubiquitin ligase Parkin can trigger mitophagy of depolarized mitochondria. However, it remains to be determined how the autophagy machinery is involved in this specific type of autophagy. It has been speculated that adaptor proteins such as p62 might mediate the interaction between the autophagosomal LC3 family of proteins and ubiquitylated proteins on mitochondria. Here, we describe our systematic analysis of the recruitment of Atg proteins in Parkin-dependent mitophagy. Structures containing upstream Atg proteins, including ULK1, Atg14, DFCP1, WIPI-1 and Atg16L1, can associate with depolarized mitochondria even in the absence of membrane-bound LC3. Atg9A structures are also recruited to these damaged mitochondria as well as to the autophagosome formation site during starvation-induced canonical autophagy. In the initial steps of Parkin-mediated mitophagy, the structures containing the ULK1 complex and Atg9A are independently recruited to depolarized mitochondria and both are required for further recruitment of downstream Atg proteins except LC3. Autophagosomal LC3 is important for efficient incorporation of damaged mitochondria into the autophagosome at a later stage. These findings suggest a process whereby the isolation membrane is generated de novo on damaged mitochondria as opposed to one where a preformed isolation membrane recognizes mitochondria.
Building Semi-Elastic Virtual Clusters for Cost-Effective HPC Cloud Resource Provisioning

Recent studies have found cloud environments increasingly appealing for executing HPC applications, including tightly coupled parallel simulations. At the same time, while public clouds offer elastic, on-demand resource provisioning and pay-as-you-go pricing, individual users setting up their on-demand virtual clusters may not be able to take full advantage of common cost-saving opportunities, such as reserved instances. In this paper, we propose a Semi-Elastic Cluster (SEC) computing model for organizations to reserve and dynamically resize a virtual cloud-based cluster. We present a set of integrated batch scheduling plus resource scaling strategies uniquely enabled by SEC, as well as an online reserved instance provisioning algorithm based on job history. Our trace-driven simulation results show that such a model has a 61.0 percent cost saving than individual users acquiring and managing cloud resources without causing longer average job wait time. Moreover, to exploit the advantages of different public clouds, we also extend SEC to a multi-cloud environment, where SEC can get a lower cost than on any single cloud. We design and implement a prototype system of the SEC model and evaluate it in terms of management overhead and average job wait time. Experimental results show that the management overhead is negligible with respect to the job wait time.
Dynamic Graphs For The Dynamic Reconfiguration Of Groups Of Computers

In the last years, the computers have in- creased their capacity of calculus and networks, for the interconnection of these machines, have improved until obtaining the actuals high rates of data transfer- ing. The programs that nowadays try to take advan- tage of these new technologies cannot be written using the traditional techniques of programming, since most of the algorithms were designed for being executed in an only processor, in a nonconcurrent form instead of being executed concurrently in a set of processors working and communicating through a network. This paper aims to present the ongoing development of a new system for the reconfiguration of groupings of computers, taking into account these new technolo- gies.
All DPLLs based on fuzzy PI control algorithm

An all DPLL (All-Digital Phase Locked Loop) based on fuzzy PI control algorithm is proposed in this paper. On analyzing system performance of a second-order PI control based PLL (Phase Locked Loop), the relationship between noise bandwidth with PI control parameters is derived, and fuzzy controller of the system is designed. Under the Matlab/Simulink® environment, system-level PLL is directly modeled by using DSP Builder®, and then is represented by using VHDL. Software simulation confirms the correctness of the design. The PLL can automatically adjust noise bandwidth according its working state, and it is characteristic of its fast lock speed, small phase jitter, outstanding anti-interference performance and prone to integration and so on.
Robust bandwidth extension of noise-corrupted narrowband speech

We present a new bandwidth extension algorithm for converting narrowband telephone speech into wideband speech using a transformation in the mel cepstral domain. Unlike previous approaches, the proposed method is designed specifically for bandwidth extension of narrowband speech that has been corrupted by environmental noise. We show that by exploiting previous research in mel cepstrum feature enhancement, we can create a unified probabilistic framework under which the feature denoising and bandwidth extension processes are tightly integrated using a single shared statistical model. By doing so, we are able to both denoise the observed narrowband speech and robustly extend its bandwidth in a jointly optimal manner. A series of experiments on clean and noise-corrupted narrowband speech is performed to validate our approach.
Why are identity disorders interesting for philosophers

"Identity disorders" constitute a large class of psychiatric disturbances that, due to deviant forms ofself-modeling, result in dramatic changes in the patients' phenomenal experience of their own personal identity. The phenomenal experience of selfhood and transtemporal identity can vary along an extremely large number of dimensions: There are simple losses of content (for example, complete losses of proprioception, resulting in a "bodiless" state of self-consciousness, see Cole 1995, Gallagher and Cole 1995, Sacks 1998). There are also various typologies of phenomenal disintegration as in schizophrenia, in depersonalization disorders and in Dissociative Identity Disorder (DID), sometimes accompanied by multiplications of the phenomenal self within one and the same physical system. It is important to not only analyze these state-classes in terms of functional deficits or phenomenology alone, but as self-representational content as well. For instance, in the second type of cases just mentioned, we confront major redistributions of the phenomenal property of "mineness" in representational space, of what is sometimes also called the "sense of ownership". Finally, there are at least four different delusions of misidentification (DM1; namely Capgras syndrome, FrA©goli syndrome, intermetamorphosis, reverse intermetamorphosis and reduplicative paramnesia). Being a philosopher, I will discuss two particular types of identity disorder in this contribution - disorders, which are of direct philosophical relevance: A specific form of DM, and the Cotard delusion. Why should philosophers do this? And why should psychiatrists care?
Functional link PSO neural network based classification of EEG mental task signals

Classification of EEG mental task signals is a technique in the design of Brain machine interface [BMI]. A BMI can provide a digital channel for communication in the absence of the biological channels and are used to rehabilitate patients with neurodegenerative diseases, a condition in which all motor movements are impaired including speech leaving the patients totally locked-in. BMI are designed using the electrical activity of the brain detected by scalp EEG electrodes. In this paper five different mental tasks from two subjects were studied, combinations of two tasks are used in the classification process. A novel functional link neural network trained by a PSO algorithm is proposed for classification of the EEG signals. Principal component analysis features are used in the training and testing of the neural network. The average classification accuracies were observed to vary from 80.25% to 93% for the 10 different task combinations for each of the subjects. The proposed network has an average training time of 0.16 sec. The results obtained validate the performance of the proposed algorithm for mental task classification.
Exploring communication in international workplaces in Ho Chi Minh City: a grounded theory study

This study explores in depth, with a sample of foreign managers and local Vietnamese employees, their experiences of communication at work. The purpose is to examine what they perceived to be issues or concerns when communicating with each other at work. This study also develops a theory based on the findings to better explain the situation under investigation. This study selected a sample of 19 foreign managers and 19 local employees from seven Anglo-based companies operating in the service sector such as accounting, banking and advertising, in Ho Chi Minh City (HCMC), Vietnam. The primary data collection method was the semi-structured individual interviews. Complementing the individual interviews were focus group discussions with managers and employees who did not take part in the individual interviews. The interview data was collected and analysed using the qualitative grounded theory method. The collected data was coded and subsequently organised according to themes or categories. The categories generated corresponded with the categories of extant literature reviewed, namely culture, communication and leadership. The managers and employees were generally concerned with the different aspects of work roles, work communication, communication orientation and language use at work. The managers focused on work independence and involvement, proactive communication including feedback and language proficiency. The employees focused on close and supportive relationships, respectful and empathetic communication particularly listening, and language clarity. By integrating the categories, a model was developed depicting misunderstandings occurring in the international workplaces. The model describes how the different and oftentimes opposing concerns and expectations of work roles, work communication, communication orientation and language held by managers and employees can often contribute to misunderstandings at work. Exacerbating the situation further are the different cultural background and training of the managers and employees. Cultural beliefs and education serve to polarise rather than moderate expectations of behaviours, making for a more volatile situation. The findings of this study revealed that the misunderstandings can negatively affect employee morale and work performance. Consequently it concludes with several recommendations for practice for the managers and their employees.
Responsibility of regulatory gene expression and repressed protein synthesis for triacylglycerol accumulation on sulfur-starvation in Chlamydomonas reinhardtii

Triacylglycerol (TG) synthesis is induced for energy and carbon storage in algal cells under nitrogen(N)-starved conditions, and helps prevent reactive oxygen species (ROS) production through fatty acid synthesis that consumes excessive reducing power. Here, the regulatory mechanism for the TG content in sulfur(S)-starved cells of Chlamydomonas reinhardtii was examined, in comparison to that in N- or phosphorus(P)-starved cells. S- and N- starved cells exhibited markedly increased TG contents with up-regulation of mRNA levels of diacylglycerol acyltransferase (DGAT) genes. S-Starvation also induced expression of the genes for phosphatidate synthesis. In contrast, P-starved cells exhibited little alteration of the TG content with almost no induction of these genes. The results implied deficient nutrient-specific regulation of the TG content. An arg9 disruptant defective in arginine synthesis, even without nutritional deficiencies, exhibited an increased TG content upon removal of supplemented arginine, which repressed protein synthesis. Repression of protein synthesis thus seemed crucial for TG accumulation in S- or N- starved cells. Meanwhile, the results of inhibitor experiments involving cells inferred that TG accumulation during S-starvation is supported by photosynthesis and de novo fatty acid synthesis. During S-starvation, sac1 and snrk2.2 disruptants, which are defective in the response to the ambient S-status, accumulated TG at lower and higher levels, respectively, than the wild type. The sac1 and snrk2.2 disruptants showed no or much greater up-regulation of DGAT genes, respectively. In conclusion, TG synthesis would be activated in S-starved cells, through the diversion of metabolic carbon-flow from protein to TG synthesis, and simultaneously through up-regulation of the expression of a particular set of genes for TG synthesis at proper levels through the actions of SAC1 and SNRK2.2.
Mapping a database into an ontology : an interactive relational learning approach

A crucial aspect when building a system which integrates data from multiple sources is to define mappings between schemas of the different sources. Using rewriting techniques, such mappings allow the integration system to translate queries posed over one schema into queries in the other schema. Building by hand such mappings is known to be non-evident and labor-intensive. In this paper, we propose an approach combining relational learning and user interaction to build mappings between a database and an ontology. The proposed approach allows to build mappings which can be complex queries over the source database. Furthermore, guarantees on the correctness of the mappings can be given.
Tectonics, topography, and mammalian diversity

Terrestrial vertebrates show striking changes in species richness across topographic gradients. For mammals, nearly twice as many species per unit area occur in topographically complex regions as in adjacent lowlands. The geological context of this pervasive biogeographic pattern suggests that tectonic processes have a first-order impact on regional diversity. I evaluate ecological, evolutionary, and historical influences of tectonics and topography on the regional diversity of terrestrial mammals, focusing on the hypothesis that diversification rates are higher in active versus passive tectonic settings. Ten predictions follow from this hypothesis. 1) The timing of peaks in speciation should be congruent with the timescale for tectonic episodes. 2) The rates of speciation and genetic differentiation of populations should be greater for species inhabiting topographically complex regions than spatially continuous landscapes. 3) If topographic complexity per se promotes diversification, then a cluster of young divergences should occur for montane species compared to lowland relatives. 4) Endemism in tectonically active regions should reflect origination within the region rather than range reduction from larger areas. 5) Extinction rates should differ for lineages in tectonically active regions compared to adjacent lowlands. 6) The relationship between local and regional species richness should differ between topographic settings because of higher beta diversity in topographically complex regions. 7) Species originating in topographically complex regions should colonize adjacent lowlands more often than the reverse pattern. 8) North-south mountain ranges should have higher regional species richness than east-west mountain ranges. 9) Areas with multiple mountain ranges should have higher regional species richness than comparable areas with single mountain ranges. 10) Global climate changes should affect diversification in tectonically active regions. Research addressing these topics places elevational diversity gradients into a geohistorical context and integrates data from modern biotas and the fossil record.
On the Relevance of Social Information to Opportunistic Forwarding

In opportunistic ad-hoc networks, multi-hop data transfer over contemporaneous paths is unlikely since the devices are often disconnected from each other. However, data can still be stored and forwarded over time in an opportunistic hop-by-hop manner. Previous work has considered how the availability of various types of information such as social relationships can be used to guide forwarding algorithm to make better decisions and bring messages closer to the destination. This implicitly assumes that opportunistic contacts relate with the social property of node. However, the impact of such correlation between social and contact properties on social forwarding performances remains largely unexplored. In this paper we argue that the relevance of such social information (social inputs) is as important as designing a new social forwarding algorithms. We examine multiple datasets to determine the impact of correlation, if any, between social information of individuals and their mobility patterns on the forwarding performances. We propose methods which process the social inputs to improve the relevance of such social information to forwarding. We show that our processing methods could improve the success rate performances of many social forwarding algorithms by more than 30%.