Miracle-dz/UniFAR-FTUs huggingface dataset:
A Statistical Framework for Automatic Leakage Detection in Smart Water and Gas Grids

In the last few years, due to the technological improvement of advanced metering infrastructures, water and natural gas grids can be regarded as smart-grids, similarly to power ones. However, considering the number of studies related to the application of computational intelligence to distribution grids, the gap between power grids and water/gas grids is notably wide. For this purpose, in this paper, a framework for leakage identification is presented. The framework is composed of three sections aimed at the extraction and the selection of features and at the detection of leakages. A variation of the Sequential Feature Selection (SFS) algorithm is used to select the best performing features within a set, including, also, innovative temporal ones. The leakage identification is based on novelty detection and exploits the characterization of a normality model. Three statistical approaches, The Gaussian Mixture Model (GMM), Hidden Markov Model (HMM) and One-Class Support Vector Machine (OC-SVM), are adopted, under a comparative perspective. Both residential and office building environments are investigated by means of two datasets. One is the Almanac of Minutely Power dataset (AMPds), and it provides water and gas data consumption at 1, 10 and 30 min of time resolution; the other is the Department of International Development (DFID) dataset, and it provides water and gas data consumption at 30 min of time resolution. The achieved performance, computed by means of the Area Under the Curve (AUC), reaches 90 % in the office building case study, thus confirming the suitability of the proposed approach for applications in smart water and gas grids.
Fast Updating Maximal Frequent Itemsets Based on Full Merged Sorted FP-Tree

Because of the low efficiency of Maximal Frequent Itemsets(MFI) updating methods, the MFI's updating methods were analyzed. A new algorithm UAMFI based on Full Merged Sorted FP-Tree (FMSFP-Tree) was proposed. By merging the Sorted FP-Tree and then obtaining the FMSFP-Tree, UAMFI uses the depth-first method to find and update MFI. Finally, the algorithm was tested on the mushroom and T15I4D100K database, and UAMFI's performances were compared with Mafia. The experimental results indicate that UAMFI is an efficient algorithm for updating Maximal Frequent Itemsets.
Near-field source localization in complex indoor environment using uniform circular array

In this paper, we propose a covariance matrix matching technique using a uniform circular array (UCA) to localize a near-field source in indoor multi-path environment. Firstly, we exploit off-line measured covariance matrices for suitable spaced reference points and storing these matrices as a fingerprint; Secondly, a matrix matching algorithm is designed to obtain the position of source. Compared with received signal strength (RSS) fingerprint, covariance matrix can offer more channel information of indoor environment, hence, our proposed algorithm outperforms RSS based algorithm in accuracy of localization. Finally, some simulation results show the efficacy of our proposed technique.
Diversity of Gain Modulation by Noise in Neocortical Neurons: Regulation by the Slow Afterhyperpolarization Conductance

Neuronal firing is known to depend on the variance of synaptic input as well as the mean input current. Several studies suggest that input variance, or “noise,” has a divisive effect, reducing the slope or gain of the firing frequency–current (f–I) relationship. We measured the effects of current noise on f–I relationships in pyramidal neurons and fast-spiking (FS) interneurons in slices of rat sensorimotor cortex. In most pyramidal neurons, noise had a multiplicative effect on the steady-state f–I relationship, increasing gain. In contrast, noise reduced gain in FS interneurons. Gain enhancement in pyramidal neurons increased with stimulus duration and was correlated with the amplitude of the slow afterhyperpolarization (sAHP), a major mechanism of spike-frequency adaptation. The 5-HT2 receptor agonist α-methyl-5-HT reduced the sAHP and eliminated gain increases, whereas augmenting the sAHP conductance by spike-triggered dynamic-current clamp enhanced the gain increase. These results indicate that the effects of noise differ fundamentally between classes of neocortical neurons, depending on specific biophysical properties including the sAHP conductance. Thus, noise from background synaptic input may enhance network excitability by increasing gain in pyramidal neurons with large sAHPs and reducing gain in inhibitory FS interneurons.
Editorial: Designing Social Innovation in Cultural Diversity and with Sensitivity

Most places where we live and work are becoming, if not already, culturally plural due to movement of people, ideas and practices over decades or even centuries. This is signaling a need for greater openness and curiosity on one hand, and a questioning of judgment and hegemony on the other to curb the surge of intolerance of ‘others’ in the context of increasing global social, political and environmental challenges. Design and social innovation has been an active and willing field in addressing such challenges, yet we have also identified how little is known or shared on complex and entangled conditions that shape how different people are coming together to catalyze changes to occur. This has been noted and reflected in discourses in postcolonial HCI that ‘speak at once to the highly local and contingent practices that we see at work in different specific sites of technology design and use, while at the same time recognizing the ways that those localisms are conditioned and embedded within global and historical flows of material, people, capital, knowledge and technology’ (Irani et. al 2010: 1317).
Notch signaling from the endosome requires a conserved dileucine motif

Notch signaling is reliant on γ-secretase–mediated processing, although the subcellular location where it cleaves Notch to initiate signaling remains unresolved. Findings here support a model in which Notch signaling in mammalian systems is initiated from either the plasma membrane or lysosome, but not the early endosome.
Adjustments of Speed and Path when Avoiding Collisions with Another Pedestrian

When walking in open space, collision avoidance with other pedestrians is a process that successfully takes place many times. To pass another pedestrian (an interferer) walking direction, walking speed or both can be adjusted. Currently, the literature is not yet conclusive of how humans adjust these two parameters in the presence of an interferer. This impedes the development of models predicting general obstacle avoidance strategies in humans’ walking behavior. The aim of this study was to investigate the adjustments of path and speed when a pedestrian is crossing a non-reactive human interferer at different angles and speeds, and to compare the results to general model predictions. To do so, we designed an experiment where a pedestrian walked a 12 m distance to reach a goal position. The task was designed in such a way that collision with an interferer would always occur if the pedestrian would not apply a correction of movement path or speed. Results revealed a strong dependence of path and speed adjustments on crossing angle and walking speed, suggesting local planning of the collision avoidance strategy. Crossing at acute angles (i.e. 45° and 90°) seems to require more complex collision avoidance strategies involving both path and speed adjustments than crossing at obtuse angles, where only path adjustments were observed. Overall, the results were incompatible with predictions from existing models of locomotor collision avoidance. The observed initiations of both adjustments suggest a collision avoidance strategy that is temporally controlled. The present study provides a comprehensive picture of human collision avoidance strategies in walking, which can be used to evaluate and adjust existing pedestrian dynamics models, or serve as an empirical basis to develop new models.
Effects of Caffeine on Metabolism and Mitochondria Biogenesis in Rhabdomyosarcoma Cells Compared with 2,4-Dinitrophenol

Purpose This work investigated if treatment with caffeine or 2,4-dinitrophenol (DNP) induce expression of peroxisome proliferator-activated receptor coactivator 1 alpha (PGC-1α) and increase both mitochondrial biosynthesis and metabolism in skeletal muscle. Methods Human rhabdomyosarcoma cells were treated with either ethanol control (0.1% final concentration) caffeine, or DNP at 250 or 500 μM for 16 or 24 hours. PGC-1α RNA levels were determined using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR). PGC-1α protein and mitochondrial content was determined using flow cytometry and immunohistochemistry. Metabolism was determined by quantification of extracellular acidification rate and oxygen consumption rate. Results Treatment with either caffeine or DNP induced PGC-1α RNA and protein as well as mitochondrial content compared with control. Treatment with caffeine and DNP also significantly increased oxidative metabolism and total metabolic rate compared with control. Caffeine similarly increased metabolism and mitochondrial content compared with DNP. Conclusion This work identified that both caffeine and DNP significantly induce PGC-1α, and increase both metabolism and mitochondrial content in skeletal muscle.
Structure and Sequence of the Human Fast Skeletal Troponin T (TNNT3) Gene: Insight Into the Evolution of the Gene and the Origin of the Developmentally Regulated Isoforms

We describe the cloning, sequencing and structure of the human fast skeletal troponin T (TNNT3) gene located on chromosome 11p15.5. The single-copy gene encodes 19 exons and 18 introns. Eleven of these exons, 1–3, 9–15 and 18, are constitutively spliced, whereas exons 4–8 are alternatively spliced. The gene contains an additional subset of developmentally regulated and alternatively spliced exons, including a foetal exon located between exon 8 and 9 and exon 16 or α (adult) and 17 or β (foetal and neonatal). Exon phasing suggests that the majority of the alternatively spliced exons located at the 5′ end of the gene may have evolved as a result of exon shuffling, because they are of the same phase class. In contrast, the 3′ exons encoding an evolutionarily conserved heptad repeat domain, shared by both TnT and troponin I (TnI), may be remnants of an ancient ancestral gene. The sequence of the 5′ flanking region shows that the putative promoter contains motifs including binding sites for MyoD, MEF-2 and several transcription factors which may play a role in transcriptional regulation and tissue-specific expression of TnT. The coding region of TNNT3 exhibits strong similarity to the corresponding rat sequence. However, unlike the rat TnT gene, TNNT3 possesses two repeat regions of CCA and TC. The exclusive presence of these repetitive elements in the human gene indicates divergence in the evolutionary dynamics of mammalian TnT genes. Homologous muscle-specific splicing enhancer motifs are present in the introns upstream and downstream of the foetal exon, and may play a role in the developmental pattern of alternative splicing of the gene. The genomic correlates of TNNT3 are relevant to our understanding of the evolution and regulation of expression of the gene, as well as the structure and function of the protein isoforms. The nucleotide sequence of TNNT3 has been submitted to EMBL/GenBank under Accession No. AF026276.
Penalty Function Approach to Robust Analog Ic Design

Automating the robust IC design process is becoming more and more important due to its complexity and decreasing time to market. In order for the circuit to be robust it must satisfy all design requirements across a range of operating conditions and manufacturing process variations. Part of the design process, which is performed by experienced analog IC designers, is automated. A transformation of the robust design problem into a constrained optimization problem by means of penalty functions is presented. The method is illustrated on a robust differential amplifier design problem. The results show that it is capable of sizing a circuit and reaching comparable or to some extent even superior performance to a humanly designed circuit. The method has great potential in parallel processing although it is efficient enough to be executed on a single computer. Robustno načrtovanje analognih integriranih vezij z uporabo kazenskih funkcij Ključne besede: dimenzioniranje vezij, analogna integrirana vezja, optimizacija, kazenske funkcije, računalniško podprto načrtovanje. Povzetek Avtomatizacija postopka robustnega načrtovanja IV postaja vse bolj pomembna zaradi zahtevnosti samega postopka in čedalje krajšega časa od začetka načrtovanja do pojave vezja na tržišču. Da je vezje robustno, mora zadostiti vsem načrtovalskim zahtevam za dano območje pogojev delovanja in možnih variacij parametrov postopka izdelave. Predstavljen je avtomatiziran postopek načrtovanja, po zgledu postopka, ki ga izvajajo načrtovalci IV. Podana je preslikava iz problema robustnega načrtovanja v omejen optimizacijski problem. Pri tem se poslužujemo kazenskih funkcij za definicijo kriterijske funckcije. Uporaba metode je prikazana na robustnem načrtovanju diferencialnega ojačevalnika. Rezultati kažejo, da je metoda sposobna poiskati nabor parametrov vezja, ki da primerljivo ali pa do neke mere celo boljše vezje kot ga načrtuje človek. Pristop ima velik potencial v vzporednem računanju, a je kljub temu dovolj učinkovit, da lahko pridemo do sprejemljivih rezultatov z uporabo enega samega računalnika.
USING TF-ISF WITH LOCAL CONTEXT TO GENERATE AN OWL DOCUMENT REPRESENTATION FOR SENTENCE RETRIEVAL

In this paper we combine our previous research in the field of Semantic web, especially ontology learning and population with Sentence retrieval. To do this we developed a new approach to sentence retrieval modifying our previous TF-ISF method which uses local context information to take into account only document level information. This is quite a new approach to sentence retrieval, presented for the first time in this paper and also compared to the existing methods that use information from whole document collection. Using this approach and developed methods for sentence retrieval on a document level it is possible to assess the relevance of a sentence by using only the information from the retrieved sentence’s document and to define a document level OWL representation for sentence retrieval that can be automatically populated. In this way the idea of Semantic Web through automatic and semi-automatic extraction of additional information from existing web resources is supported. Additional information is formatted in OWL document containing document sentence relevance for sentence retrieval.
Complex Lattice Reduction Algorithm for Low-Complexity Full-Diversity MIMO Detection

Recently, lattice-reduction-aided detectors have been proposed for multiinput multioutput (MIMO) systems to achieve performance with full diversity like the maximum likelihood receiver. However, these lattice-reduction-aided detectors are based on the traditional Lenstra-Lenstra-Lovasz (LLL) reduction algorithm that was originally introduced for reducing real lattice bases, in spite of the fact that the channel matrices are inherently complex-valued. In this paper, we introduce the complex LLL algorithm for direct application to reducing the basis of a complex lattice which is naturally defined by a complex-valued channel matrix. We derive an upper bound on proximity factors, which not only show the full diversity of complex LLL reduction-aided detectors, but also characterize the performance gap relative to the lattice decoder. Our analysis reveals that the complex LLL algorithm can reduce the complexity by nearly 50% compared to the traditional LLL algorithm, and this is confirmed by simulation. Interestingly, our simulation results suggest that the complex LLL algorithm has practically the same bit-error-rate performance as the traditional LLL algorithm, in spite of its lower complexity.
Improving the E ectiveness of Web Caching

The bandwidth demands on the (World-Wide) Web continue to grow at an exponential rate. It is thus becoming crucial to provide solutions improving the Web latency. In that framework, the most promising low cost solution lies in the use of caches at the level of the clients, network and servers. Caching e ectiveness then relies upon adequate cache management so as to keep in the cache the Web objects that are the most likely to be re-accessed. However, the e ectiveness of a single cache remains poor as it is in general no higher than 40%. One way to further improve caching e ectiveness is thus to make caches cooperate so as to increase the probability of retrieving an object at the caching level. The cache cooperation protocol must then be such that it induces a negligible load for the network and cooperating caches. This paper presents our solutions to improving the e ectiveness of Web caching concerning both cache management and cache cooperation. Regarding cache management, we propose two novel algorithms that exploit the latest results about Web usage, enabling us to undertake replacement decisions that are more accurate than the one taken by existing algorithms. From the standpoint of cooperating caches, we propose a cooperation protocol, which minimizes the associated network bandwidth, processing load, and storage consumption among caches.
“Three Way Approach” to Meeting the Challenges of Migrant Incorporation in the European Union: Reflections from a Turkish Perspective

This paper advocates the idea that the European Union’s “two way process” approach to migration and integration should boldly be replaced by the notion of a “three way” approach for the better incorporation of immigrants in the EU. The first part of the paper outlines the emergence of a “common” immigration and integration policy at the EU level, its main features and in particular the role of the European Commission in shaping this policy. The second part critically examines the place that is attributed to sending countries in efforts to draw up a “common” immigration and integration policy. Particular emphasis is laid on the ways the EU defines and frames the place and function of “sending countries” in its immigration policy. In the last section, the role that sending countries could play in the context of a “three way” approach to integration is explored against the background of the Turkish experience. In this section, the author makes various concrete suggestions in support of a “three way” approach whose aim is to assist Turkish immigrants’ integration into mainstream life within the EU.
My voice, your prosody: sharing a speaker specific prosody model across speakers in unit selection TTS

Data sparsity is a major problem for data driven prosodic models. Being able to share prosodic data across speakers is a potential solution to this problem. This paper explores this potential solution by addressing two questions: 1) Does a larger less sparse model from a different speaker produce more nat-ural speech than a small sparse model built from the original speaker? 2)Does a different speaker’s larger model generate more unit selection errors than a small sparse model built from the original speaker? A unit selection approach is used to produce a lazy learning model of three English RP speaker’s f0 and durational parameters. Speaker 1 (the target speaker) had a much smaller database (approximately one quarter to one ﬁfth the size) of the other two. Speaker 2 was a female speaker with frequent mid phrase rises. Speaker 3 was a male speaker with a similar f0 range to speaker 1 and with a measured prosodic style suitable for news and ﬁnancial text. We apply the models created for speaker 2 (an inappropriate model) and speaker 3 (an appropriate model) to speaker 1 and compare the results. Three passages (of three to four sentences in length) from challenging prosodic genres (news report, poetry and personal email) were synthesised using the target speaker and each of the three models. The synthesised utterances were played to 15 native english subjects and rated using a 5 point MOS scale. In addition, 7 experienced speech engineers rated each word for errors on a three point scale: 1. Acceptable, 2. Poor, 3. Unacceptable. The results suggest that a large model from an appropriate speaker does not sound more natural or produce fewer errors than a smaller model generated from the individual speaker’s own data. In addition it shows that an inappropriate model does produce both less natural and more errors in the speech. High variance in both subject and materials analysis suggest both tests
Application of Lib2.0 Technology in Specialty Reference Room/SRR Website of Institute of Higher Learning

Based on some Significance about the construction of SRR website in the institute of higher learning, this article first of all introduces the Lib2.0 technology, expounding the possibility of applying Lib2.0 technology in the construction of SRR website; Secondly, the article summarizes the present situation of Lib2.0 technology being applied in SRR of the institute of higher learning; And finally, combining Lib2.0 with Web2.0, the article puts forward a couple of viewpoints concerning Lib2.0 technology to be applied in the construction of SRR website.
Context-Sensitive Word Selection For Single-Tap Text Entry

Predictive text input using a single-tap entry method is currently the standard for text entry in the mobile domain. One problem facing this approach is which word to present to the user when more than one word matches an input sequence. The standard single-tap approach selects words using corpus occurrence frequencies, ignoring linguistic context. This can lead to the selection of words that are unrelated to the current input. In this paper we present an implementation of a context-aware predictive text framework that overrides the frequency-based selection model for words related to the current context.
E-TCP: Enhanced TCP for IEEE802.11e Mobile Ad Hoc Networks

TCP, the facto standard used in today's Internet, has been found to perform poorly in Mobile Ad Hoc Networks (MANETs). This is exacerbated by contention with increasing UDP-based high priority multimedia traffic and the class differentiation introduced in current QoS protocols, which results into TCP starvation and increased spurious timeouts. In this paper, we propose a cross-layer TCP enhancement (E-TCP) that makes use of TCP bidirectionality to avoid TCP traffic starvation and spurious retransmissions in presence of high priority traffic. E-TCP is based on prioritizing TCP acknowledgement packets and on adjusting TCP retransmission timer based on the medium contention. Our simulation results reveal considerable improvements in TCP performance in terms of gooput, delay and retransmission efficiency, while the better channel utilization results into even better high priority traffic performance.