Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantum phases of hard-core dipolar bosons in coupled one-dimensional optical lattices

Hard-core dipolar bosons trapped in a parallel stack of N 2 one-dimensional optical lattices (tubes) can develop several phases made of composites of particles from different tubes: superfluids, supercounterfluids, and insulators as well as mixtures of those. Bosonization analysis shows that these phases are thresholdless with respect to the dipolar interaction, with the key “control knob” being filling factors in each tube, provided the intertube tunneling is suppressed. The effective ab initio quantum Monte Carlo algorithm capturing these phases is introduced and some results are presented.
Big Data Meets Digital Cultural Heritage

Information and Communication Technologies have radically changed the modern Cultural Heritage scenery: Simple traditional Information Systems supporting the management of cultural artifacts have left the place to complex systems that expose rich information extracted from heterogeneous data sources—like Sensor Networks, Social Networks, Digital Libraries, Multimedia Collections, Web Data Service, and so on—by means of sophisticated applications that enhance the users’ experience. In this article, we describe SCRABS, a Smart Context-awaRe Browsing assistant for cultural EnvironmentS. SCRABS has been developed during the Cultural Heritage Information Systems national project and promoted by DATABENC, the Cultural Heritage Technological District of the Campania Region, in Italy. SCRABS has been designed on top of a Big Data technological stack as the result of a multidisciplinary project carried out by a heterogeneous team of computer scientists, archeologists, architects, and experts in humanities. We describe the main ideas that support the system, showing its use in some real application scenarios located in the Paestum Archeologica Sites.
Randomized feature selection using Scopira

Feature selection is a useful preprocessing strategy when dealing with the classification and interpretation of high-dimensional biomedical data coupled with small sample sizes. A classification technique, exploiting parallelization efficiencies, is presented where sets of linear discriminant functions are designed using randomly selected feature subsets with varying cardinality. This technique, tested with biomedical data acquired from several sources, had fewer classification errors than a conventional linear discriminant analysis strategy. The algorithm development framework used to implement the technique is also discussed.
Bandwidth extension of narrowband speech using cepstral analysis

This paper describes a vector quantization based algorithm that extends the bandwidth of narrowband speech into wideband speech. Cepstral analysis is used to represent the spectral envelope information and the wideband excitation is generated using fullwave rectification with spectral whitening. Objective and subjective tests conducted show great improvement in speech quality over the original narrowband speech. The algorithm can be implemented as a postprocessor without the need for any side information.
1-string B2-VPG representation of planar graphs

In this paper, we prove that every planar graph has a 1-string $B_2$-VPG representation---a string representation using paths in a rectangular grid that contain at most two bends. Furthermore, two paths representing vertices $u,v$ intersect precisely once whenever there is an edge between $u$ and $v$.
PENGARUH SOCIAL MEDIA MARKETING TERHADAP EKUITAS MEREK

Tujuan penelitian ini adalah untuk menentukan seberapa besar pengaruh social media marketing program “Kulineria” di Instagram terhadap ekuitas merek Tehbotol Sosro berdasarkan teori ekologi media. Penelitian ini menggunakan metode kuantitatif dengan jenis asosiatif kausal, di mana penelitian meneliti pengaruh dari variabel bebas terhadap variabel terikat. Sampel penelitian diambil dengan teknik purposive sampling. Analisis data yang dilakukan menunjukkan hasil dari kuesioner yang disebar valid, reliabel, dan lolos uji asumsi klasik. Sehingga simpulan dari penelitian ini, terdapat hubungan yang kuat dan positif pada uji korelasi dengan nilai sebesar 0.664. Koefisien determinasi yang diperoleh menunjukkan bahwa terdapat pengaruh social media marketing program “Kulineria” di Instagram terhadap ekuitas merek Tehbotol Sosro sebesar 44% dengan persamaan regresi Y = 22.65 + 0.549 X. Pengaruh tersebut dapat dijelaskan oleh asumsi kedua dari teori ekologi media yang menyatakan bahwa media memperbaiki persepsi dan mengelola pengalaman. Penelitian ini juga membuktikan asumsi pertama dan ketiga dari teori ekologi media berdasarkan gambaran umum responden. Saran dari penelitian ini adalah perusahaan perlu merancang social media marketing yang dapat meningkatkan engagement antara konsumen dengan perusahaan sehingga dapat memberikan dampak yang lebih signifikan terhadap ekuitas merek.
Robust growth of avirulent phase II Coxiella burnetii in bone marrow-derived murine macrophages

Published data show that murine bone marrow-derived macrophages (BMDM) restrict growth of avirulent phase II, but not virulent phase I, Coxiella burnetii. Growth restriction of phase II bacteria is thought to result from potentiated recognition of pathogen-associated molecular patterns, which leads to production of inhibitory effector molecules. Past studies have used conditioned medium from L-929 murine fibroblasts as a source of macrophage-colony stimulating factor (M-CSF) to promote differentiation of bone marrow-derived myeloid precursors into macrophages. However, uncharacterized components of conditioned medium, such as variable amounts of type I interferons, can affect macrophage activation status and their permissiveness for infection. In the current study, we show that the C. burnetii Nine Mile phase II (NMII) strain grows robustly in primary macrophages from C57BL/6J mice when bone marrow cells are differentiated with recombinant murine M-CSF (rmM-CSF). Bacteria were readily internalized by BMDM, and replicated within degradative, LAMP1-positive vacuoles to achieve roughly 3 logs of growth over 6 days. Uninfected BMDM did not appreciably express CD38 or Egr2, markers of classically (M1) and alternatively (M2) activated macrophages, respectively, nor did infection change the lack of polarization. In accordance with an M0 phenotype, infected BMDM produced moderate amounts of TNF and nitric oxide. Similar NMII growth results were obtained using C57BL/6J myeloid progenitors immortalized with an estrogen-regulated Hoxb8 (ER-Hoxb8) oncogene. To demonstrate the utility of the ER-Hoxb8 system, myeloid progenitors from natural resistance-associated macrophage protein 1 (Nramp1) C57BL/6J knock-in mice were transduced with ER-Hoxb8, and macrophages were derived from immortalized progenitors using rmM-CSF and infected with NMII. No difference in growth was observed when compared to macrophages from wild type mice, indicating depletion of metal ions by the Nramp1 transporter does not negatively impact NMII growth. Results with NMII were recapitulated in primary macrophages where C57BL/6J Nramp1+ BMDM efficiently killed Salmonella enterica serovar Typhimurium. M-CSF differentiated murine macrophages from bone marrow and conditional ER-Hoxb8 myeloid progenitors will be useful ex vivo models for studying Coxiella-macrophage interactions.
Quantization Noise Cancellation of Fractional-N Frequency Synthesizers Using Pre-distortion Technique

This work proposes a novel pre-distortion technique for the quantization noise cancellation of frac- tional-N frequency synthesizers. The proposed technique utilizes the coordinate rotation digital computer (CORDIC) algorithm to pre-distort the baseband signal of a wireless system with the quantization noise. The pre-distorted signal then modulates the noisy output signal of the fractional-N frequency synthesizer. The transmitter (Tx) modulation quality is thereby improved. In the receiver (Rx) mode, the phase noise of the Rx carrier signal can also be improved by modulation with a pre-distorted sinusoidal signal rather than a baseband signal. Experimental results demonstrate that the novel pre-distortion technique effectively improves the modulation quality of a Tx by an error vector magni- tude (EVM) of about 10 % under a 13 Mbps QPSK modu- lation. The carrier in-band and out-band phase noise of the fractional-N frequency synthesizer is improved by ap- proximately 6 dB and 10 dB, respectively.
Two-step reduction approach based on the scattering-symmetric Lanczos algorithm for TLM-ROM

The non-symmetric properties of the TLM-matrix require the application of general Krylov subspace methods for the purposes of model order reduction (MOR). Application of the Arnoldi algorithm is computational expensive. Furthermore, the classical non-symmetric Lanczos algorithm requires the transpose TLM-matrix in order to form a biorthogonal basis for Krylov subspaces; hence, its algorithmic simplicity is also penalized and its computational complexity is increased. In this paper we propose a novel scattering-symmetric (S-symmetric) Lanczos algorithm, which is faster and consumes less memory in comparison to the conventional non-symmetric Lanczos algorithm, since the S-symmetric Lanczos algorithm generates the biorthogonal basis utilizing a single sequence like the symmetric Lanczos procedure. Along with the details of the proposed S-symmetric Lanczos algorithm, estimates are provided for its computational cost in comparison to the standard TLM time evolution scheme, the general Arnoldi process and the non-symmetric Lanczos process. However, the reduced TLM operator can still be large. Instead of the conventional eigenvalue decomposition (EVD) the second reduction of the TLM system can be applied in order to extract only eigenvalues corresponding to a needed frequency band. The two-step reduction algorithm allows us to decrease the computational effort in TLM-MOR.
An siRNA-based method for efficient silencing of gene expression in mature brown adipocytes

ABSTRACT Brown adipose tissue is a promising therapeutic target for opposing obesity, glucose intolerance and insulin resistance. The ability to modulate gene expression in mature brown adipocytes is important to understand brown adipocyte function and delineate novel regulatory mechanisms of non-shivering thermogenesis. The aim of this study was to optimize a lipofection-based small interfering RNA (siRNA) transfection protocol for efficient silencing of gene expression in mature brown adipocytes. We determined that a critical parameter was to deliver the siRNA to mature adipocytes by reverse transfection, i.e. transfection of non-adherent cells. Using this protocol, we effectively knocked down both high- and low-abundance transcripts in a model of mature brown adipocytes (WT-1) as well as in primary mature mouse brown adipocytes. A functional consequence of the knockdown was confirmed by an attenuated increase in uncoupled respiration (thermogenesis) in response to β-adrenergic stimulation of mature WT-1 brown adipocytes transfected with uncoupling protein 1 siRNA. Efficient gene silencing was also obtained in various mouse and human white adipocyte models (3T3-L1, primary mouse white adipocytes, hMADS) with the ability to undergo “browning. ” In summary, we report an easy and versatile reverse siRNA transfection protocol to achieve specific silencing of gene expression in various models of mature brown and browning-competent white adipocytes, including primary cells.
ASPicDB: A database resource for alternative splicing analysis

MOTIVATION Alternative splicing has recently emerged as a key mechanism responsible for the expansion of transcriptome and proteome complexity in human and other organisms. Although several online resources devoted to alternative splicing analysis are available they may suffer from limitations related both to the computational methodologies adopted and to the extent of the annotations they provide that prevent the full exploitation of the available data. Furthermore, current resources provide limited query and download facilities. RESULTS ASPicDB is a database designed to provide access to reliable annotations of the alternative splicing pattern of human genes and to the functional annotation of predicted splicing isoforms. Splice-site detection and full-length transcript modeling have been carried out by a genome-wide application of the ASPic algorithm, based on the multiple alignments of gene-related transcripts (typically a Unigene cluster) to the genomic sequence, a strategy that greatly improves prediction accuracy compared to methods based on independent and progressive alignments. Enhanced query and download facilities for annotations and sequences allow users to select and extract specific sets of data related to genes, transcripts and introns fulfilling a combination of user-defined criteria. Several tabular and graphical views of the results are presented, providing a comprehensive assessment of the functional implication of alternative splicing in the gene set under investigation. ASPicDB, which is regularly updated on a monthly basis, also includes information on tissue-specific splicing patterns of normal and cancer cells, based on available EST sequences and their library source annotation. AVAILABILITY www.caspur. it/ASPicDB
Designing an Internet-based directory service for e-markets

The application of Internet technologies to online transactions has lead to the amazing growth of Internet-based electronic markets (e-markets). This paper describes an Internet-based directory service for e-markets that aims to facilitate online buyers by making the process of finding an e-market easier and less time-consuming. This service, termed e-Market Metadata (eMaM) directory service, is based on a metadata repository of e-markets' descriptions. These descriptions store a number of e-market characteristics according to the 'Dublin Core for E-Markets' (DC-EM) metadata model which has been developed for this purpose. In particular, this paper introduces metadata models and describes the DC-EM metadata model. Then, it presents the specification and implementation of the eMaM service using the Unified Modelling Language (UML). Finally, a pilot usage of the implemented eMaM service that examines 120 B2B, B2C, and C2C e-markets for various business sectors is discussed.
Comparison of different motor-generator sets for long term storage flywheels

Flywheels feature relatively low size, long lifetime and robustness and are, therefore, very attractive as energy storage devices. In case of long term energy storage, low idle losses are essential to keep the stored energy in the system. The motor generator set for mechanical energy storage systems are most likely permanent magnet, synchronous and switched reluctance machines. In this article, the different motor topologies, suitable for long term energy storage, are analyzed regarding the trade-off between efficiency and material utilization, including permanent magnet synchronous and synchronous reluctance machines. The used evolutionary optimization procedure considers iron losses as well as material saturation effects for certain points of operation. Finally, an overall comparison shows the performance of the different drive topologies.
Research Statement Nicolas Schiper

Cloud-based applications are everywhere around us. They range from performance sensitive services such as web search, e-commerce, and social networking to mission-critical applications such as air-traffic control and the power grid. These applications tend to be complex, involve a large number of computers, and must face all sorts of failures ranging from power outages and software bugs to malicious attackers. My research interests are centered around making these applications reliable, trustworthy, and scalable. Designing protocols that meet all these requirements is not only a science but also an art and it is a very exciting topic. As such, I design, build, and evaluate protocols to make these services fault-tolerant and scalable, and I use formal methods to provide bug-free code for critical components. As fault-tolerant storage systems have become pervasive in today’s data centers, I have also started investigating the issue of energy-efficient cloud storage. In this line of research, I strive to maximize the performance obtained per Watt by adapting the replication protocol to the workload. My approach to research consists in identifying a problem, precisely stating what properties the solution should guarantee, and exploring the space of solutions. I carry out this exploration both at a theoretical level to distinguish what can be done from what cannot, and at a practical level by building the complete system for it to be extensively evaluated. As a theoretical model cannot fully encompass the complexity of a real system, the initial formal model and algorithms may have to be adapted. This can take the form of refining the fault-model, e.g., in a single tenant cloud hardware and software failures may be more common than malicious attacks; or it may mean trading off some performance for the sake of simplicity. Empirical evaluations often reveal protocol behaviors not foreseen in the design process and are thus essential. To date, I have successfully applied this approach to several projects, various of which I will describe below.
Association of Moving Objects Across Visual Sensor Networks

We present a novel inter-camera trajectory association algorithm for partially overlapping visual sensor networks. The approach consists of three steps, namely Extraction, Representation and Association. Firstly, we extract trajectory segments in each camera view independently. These local trajectory segments are then projected on a common-plane. Next, we learn dynamic motion models of the projected trajectory segments using Modified Consistent Akaike’s Information Criterion (MCAIC). These models help in removing noisy observations from a segment and hence perform smoothing efficiently. Then, each smoothed trajectory is represented by its curvature. Finally, we use normalized cross correlation, as a proximity measure, to establish correspondence among trajectories that are observed in multiple views. We evaluated the performance of the proposed approach on a simulated and real scenarios with simultaneous moving objects observed by multiple cameras and compared it with state-of-the-art algorithms. Convincing results are observed in favor of the proposed approach.
Observations on Multi-Band Asynchrony in Distant Speech Recordings

Whenever the speech signal is captured by a microphone distant from the user, the acoustic response of the room introduces significant distortions. To remove these distortions from the signal, solutions exist that greatly improve the ASR performance (what was said? ), such as dereverberation or beamforming. It may seem natural to apply those signal-level methods in the context of speaker clustering (who spoke when? ) with distant microphones, for example when annotating a meeting recording for enhanced browsing experience. Unfortunately, on a corpus of real meeting recordings, it appeared that neither dereverberation nor beamforming gave any improvement on the speaker clustering task. The present technical report constitutes a first attempt to explain this failure, through a cross-correlation analysis between close-talking and distant microphone signals. The various frequency bands of the speech spectrum appear to become desynchronized when the speaker is 1 or 2 meters away from the microphone. Further directions of research are suggested to model this desynchronization.
Limitations of Empirical Testing Technique Knowledge

Engineering disciplines are characterised by the use of mature knowledge by means of which they can achieve predictable results. Unfortunately, the type of knowledge used in software engineering can be considered to be of a relatively low maturity, and developers are guided by intuition, fashion or market-speak rather than by facts or undisputed statements proper to an engineering discipline. Testing techniques determine different criteria for selecting the test cases that will be used as input to the system under examination, which means that an effective and efficient selection of test cases conditions the success of the tests. The knowledge for selecting testing techniques should come from studies that empirically justify the benefits and application conditions of the different techniques. This paper analyses the maturity level of the knowledge about testing techniques by examining existing empirical studies about these techniques. For this purpose, we classify testing technique knowledge according to four categories.
Mapping transit‐based access: integrating GIS, routes and schedules

Accessibility is a concept that is not entirely easy to define. Gould (1969) once stated that it is a ‘slippery notion … one of those common terms that everyone uses until faced with the problem of defining and measuring it’. Considerable research over the last 40 years has been devoted to defining and measuring accessibility, ranging from access to jobs within an hour's travel time to the ease at which given places can be reached. This article is concerned with the measurement of access provided by transit. It includes a review of past work on measuring accessibility in general and with respect to transit services in particular. From this overview of the literature, it can be seen that current methods fall short in measuring transit service access in several meaningful aspects. Based on this review and critique, we propose new refinements that can be used to help overcome some of these shortcomings. As a part of this, we define an extended GIS data structure to handle temporal elements of transit service. To demonstrate the value of these new measures, examples are presented with respect to mapping accessibility of transit services in Santa Barbara, California. Finally, we show how these measures can be used to develop a framework for supporting transit service analysis and planning.
Time-fractional nonlinear gas transport equation in tight porous media: An application in unconventional gas reservoirs

The prospects of meeting the future's high energy demands lie in the exploration of unconventional hydrocarbon reservoirs, of which the shale gas and the tight gas are two important resources. The deep understanding of such reservoirs is crucial to the economical recovery of such energy resources. With the advancement in the technological sides, such as, hydraulic fracturing and horizontal drilling, new mathematical models are needed that can precisely capture the complexity of the physical phenomena and can describe the flow of gas through the natural and induced fractures. The performance and future behavior of such reservoirs can be enhanced through careful modeling. We develop a new mathematical model based on time fractional derivative combined with the consideration of various flow regimes and a nonlinear treatment of reservoir parameters. The model describes the transport of gas in tight porous media (such as shale formations). The derivation of the model is done by using the mass balance equation and momentum conservation equation (basically modified time-fractional form of Darcy's law) which incorporates the properties of tight porous media and accounts on the previous behavior. We find the pressure equation by considering that the rock properties, such as, permeability, viscosity, porosity, are pressure dependent. The pressure equation can be used to study the pressure distribution in the reservoir.