Miracle-dz/UniFAR-FTUs huggingface dataset:
Resolving IRAS 09111–1007 at 350 µm: a different path to ULIRG formation?

We have resolved the ultraluminous infrared galaxy (ULIRG) IRAS 09111−1007 with the new 350-μm-optimized Second Generation Submillimeter High Angular Resolution Camera (SHARC II), and present the first submillimetre fluxes and images for the system. IRAS 09111−1007 comprises two interacting luminous infrared galaxies (LIRGs) with a projected nuclear separation of 39 h−171 kpc. The western galaxy is roughly four times more luminous in the submillimetre than its eastern counterpart. It is an extremely bright LIRG with an active galactic nucleus (AGN). The classification of the eastern source is uncertain: it could be a Seyfert 2 galaxy or a LINER. We highlight IRAS 09111−1007 as a system that necessitates further study: a double AGN ULIRG whose molecular gas content differs from that of other widely separated pairs, and whose ULIRG phase might not be explained by current multiple-merger and/or final-stage ULIRG scenarios.
SLuRp: a tool to help large complex systematic literature reviews deliver valid and rigorous results

Background: Systematic literature reviews are increasingly used in software engineering. Most systematic literature reviews require several hundred papers to be examined and assessed. This is not a trivial task and can be time consuming and error-prone. Aim: We present SLuRp - our open source web enabled database that supports the management of systematic literature reviews. Method: We describe the functionality of SLuRp and explain how it supports all phases in a systematic literature review. Results: We show how we used SLuRp in our SLR. We discuss how SLuRp enabled us to generate complex results in which we had confidence. Conclusions: SLuRp supports all phases of an SLR and enables reliable results to be generated. If we are to have confidence in the outcomes of SLRs it is essential that such automated systems are used.
Reservoir Simulation with the Finite Element Method Using Biot Poroelastic Approach

We are developing a finite element program for oil and gas reservoir simulation based on Biot’s poroelastic theory, where a simultaneous solution is sought for both the pore pressure and strain in the solid phase. Several 2-D and 3-D cases are presented, which are compared with analytical solutions for verification of this approach. We have also applied this method to simulate surface subsidence due to gas and oil production in a subsurface reservoir. The development of this code is still in its initial stage, but the approach shows promise.
Radiation pattern measurements of mobile phones next to different head phantoms

An investigation of the radiation from 5 different phones next to two head phantoms proposed for radiation measurements has been carried out and the radiation has been evaluated through the total radiated power, the total receiver sensitivity and the mean effective gain. The investigation is based on measurements of the far field patterns measured in an anechoic room using a system tester to avoid any disturbance of the radiation patterns. The results shows that the losses due to the phantom heads are twice as high in dB values, at 900 MHz compared to 1800 MHz. Even though the two head phantoms are rather different in shape it is concluded that the influence by the phantom on the radiation is the essentially same.
Analysis of voice source characteristics using a constrained polynomial model

This paper presents an analysis method of voice source characteristics from speech by simultaneously employing models of the vocal tract and voice source signal. The vocal tract is represented as a linear ﬁlter based on the conventional all-pole assumption. On the other hand, the voice source signal is represented by linearly overlapping multiple number of base signals obtained from a generalization of the Rosenberg model. The resulting voice source model is a polynomial function of time and has lesser degrees-of-freedom than the polynomial order. By virtue of the linearity of both models, the optimal values of their parameters can be jointly determined when the instants of the glottal opening and closing are given for each pitch period. We also present a temporal search method of these glottal events us-ing the dynamic programming technique. Finally, experimental results are presented to reveal the applicability of the proposed method for several phonation conditions.
Water-filling capacity analysis in large MIMO systems

In this paper, we study a water-filling power allocation scheme in large M × N MIMO systems over flat Rayleigh fading channels. It is shown that when M = N with sufficiently large M, the channel capacity of the water-filling scheme almost converges to a constant regardless of channel randomness. Moreover, it is proved that for the water-filling scheme, the required channel information at the transmitter in large MIMO systems can be greatly reduced without capacity loss. When M ≫ N or M ≪ N, it is shown that allocating equal power on each eigenchannel is almost as optimal as water-filling power allocation scheme in channel capacity.
Myomaker, Regulated by MYOD, MYOG and miR-140-3p, Promotes Chicken Myoblast Fusion

The fusion of myoblasts is an important step during skeletal muscle differentiation. A recent study in mice found that a transmembrane protein called Myomaker, which is specifically expressed in muscle, is critical for myoblast fusion. However, the cellular mechanism of its roles and the regulatory mechanism of its expression remain unclear. Chicken not only plays an important role in meat production but is also an ideal model organism for muscle development research. Here, we report that Myomaker is also essential for chicken myoblast fusion. Forced expression of Myomaker in chicken primary myoblasts promotes myoblast fusion, whereas knockdown of Myomaker by siRNA inhibits myoblast fusion. MYOD and MYOG, which belong to the family of myogenic regulatory factors, can bind to a conserved E-box located proximal to the Myomaker transcription start site and induce Myomaker transcription. Additionally, miR-140-3p can inhibit Myomaker expression and myoblast fusion, at least in part, by binding to the 3ʹ UTR of Myomaker in vitro. These findings confirm the essential roles of Myomaker in avian myoblast fusion and show that MYOD, MYOG and miR-140-3p can regulate Myomaker expression.
The Fate of Membrane-bound Ribosomes Following the Termination of Protein Synthesis*

Contemporary models for protein translocation in the mammalian endoplasmic reticulum (ER) identify the termination of protein synthesis as the signal for ribosome release from the ER membrane. We have utilized morphometric and biochemical methods to assess directly the fate of membrane-bound ribosomes following the termination of protein synthesis. In these studies, tissue culture cells were treated with cycloheximide to inhibit elongation, with pactamycin to inhibit initiation, or with puromycin to induce premature chain termination, and ribosome-membrane interactions were subsequently analyzed. It was found that following the termination of protein synthesis, the majority of ribosomal particles remained membrane-associated. Analysis of the subunit structure of the membrane-bound ribosomal particles remaining after termination was conducted by negative stain electron microscopy and sucrose gradient sedimentation. By both methods of analysis, the termination of protein synthesis on membrane-bound ribosomes was accompanied by the release of small ribosomal subunits from the ER membrane; the majority of the large subunits remained membrane-bound. On the basis of these results, we propose that large ribosomal subunit release from the ER membrane is regulated independently of protein translocation.
Sparse K-Means with $\ell_{\infty}/\ell_0$ Penalty for High-Dimensional Data Clustering

Sparse clustering, which aims to find a proper partition of an extremely high-dimensional data set with redundant noise features, has been attracted more and more interests in recent years. The existing studies commonly solve the problem in a framework of maximizing the weighted feature contributions subject to a $\ell_2/\ell_1$ penalty. Nevertheless, this framework has two serious drawbacks: One is that the solution of the framework unavoidably involves a considerable portion of redundant noise features in many situations, and the other is that the framework neither offers intuitive explanations on why this framework can select relevant features nor leads to any theoretical guarantee for feature selection consistency. In this article, we attempt to overcome those drawbacks through developing a new sparse clustering framework which uses a $\ell_{\infty}/\ell_0$ penalty. First, we introduce new concepts on optimal partitions and noise features for the high-dimensional data clustering problems, based on which the previously known framework can be intuitively explained in principle. Then, we apply the suggested $\ell_{\infty}/\ell_0$ framework to formulate a new sparse k-means model with the $\ell_{\infty}/\ell_0$ penalty ($\ell_0$-k-means for short). We propose an efficient iterative algorithm for solving the $\ell_0$-k-means. To deeply understand the behavior of $\ell_0$-k-means, we prove that the solution yielded by the $\ell_0$-k-means algorithm has feature selection consistency whenever the data matrix is generated from a high-dimensional Gaussian mixture model. Finally, we provide experiments with both synthetic data and the Allen Developing Mouse Brain Atlas data to support that the proposed $\ell_0$-k-means exhibits better noise feature detection capacity over the previously known sparse k-means with the $\ell_2/\ell_1$ penalty ($\ell_1$-k-means for short).
Photothermal excitation for improved cantilever drive performance in tapping mode atomic force microscopy

Photothermal excitation is an alternative cantilever drive mechanism for tapping mode atomic force microscopy. It uses a power-modulated laser focused on the cantilever to directly drive its oscillation, producing cantilever tunes that match the thermal response almost perfectly. This enables quantitatively accurate AFM imaging and viscoelastic nanomechanical mapping in all environments. In addition, the clean cantilever tunes are stable with time, even in liquids, and therefore result in exceptional imaging stability. Lastly, the ease of use of photothermal excitation and compatibility with small high-frequency cantilevers allows high-speed imaging in both air and liquid environments. We explain the advantages of photothermal excitation in these contexts, and contrast its benefits to problems associated with the well-established piezoacoustic
HierTrack: an energy-efficient cluster-based target tracking system forwireless sensor networks

Target tracking is a typical and important application of wireless sensor networks (WSNs). Existing target tracking protocols focus mainly on energy efficiency, and little effort has been put into network management and real-time data routing, which are also very important issues for target tracking. In this paper, we propose a scalable cluster-based target tracking framework, namely the hierarchical prediction strategy (HPS), for energy-efficient and real-time target tracking in large-scale WSNs. HPS organizes sensor nodes into clusters by using suitable clustering protocols which are beneficial for network management and data routing. As a target moves in the network, cluster heads predict the target trajectory using Kalman filter and selectively activate the next round of sensors in advance to keep on tracking the target. The estimated locations of the target are routed to the base station via the backbone composed of the cluster heads. A soft handoff algorithm is proposed in HPS to guarantee smooth tracking of the target when the target moves from one cluster to another. Under the framework of HPS, we design and implement an energy-efficient target tracking system, HierTrack, which consists of 36 sensor motes, a sink node, and a base station. Both simulation and experimental results show the efficiency of our system.
Regulation of transcription by eukaryotic-like serine-threonine kinases and phosphatases in Gram-positive bacterial pathogens

Bacterial eukaryotic-like serine threonine kinases (eSTKs) and serine threonine phosphatases (eSTPs) have emerged as important signaling elements that are indispensable for pathogenesis. Differing considerably from their histidine kinase counterparts, few eSTK genes are encoded within the average bacterial genome, and their targets are pleiotropic in nature instead of exclusive. The growing list of important eSTK/P substrates includes proteins involved in translation, cell division, peptidoglycan synthesis, antibiotic tolerance, resistance to innate immunity and control of virulence factors. Recently it has come to light that eSTK/Ps also directly modulate transcriptional machinery in many microbial pathogens. This novel form of regulation is now emerging as an additional means by which bacteria can alter their transcriptomes in response to host-specific environmental stimuli. Here we focus on the ability of eSTKs and eSTPs in Gram-positive bacterial pathogens to directly modulate transcription, the known mechanistic outcomes of these modifications, and their roles as an added layer of complexity in controlling targeted RNA synthesis to enhance virulence potential.
Identification of nuclear pre-replication centers poised for DNA synthesis in Xenopus egg extracts: immunolocalization study of replication protein A

We demonstrate by immunofluorescence that a 70-kD protein (P70) purified from Xenopus egg extracts is associated with subnuclear foci (about 200) which we propose to be an assembly of DNA pre-replication centers (preRCs). A cDNA encoding this protein reveals that P70 is the Xenopus homologue of replication protein A (RPA also called RF-A). RPA is know to be a cellular, three-subunit single-stranded DNA binding protein, which assists T-antigen in the assembly of the pre-priming complex in the SV40 replication system. The punctated preRCs exist transiently; they form post-mitotically during the period of nuclear membrane breakdown and disappear during ongoing DNA replication. P70 is homogeneously associated with chromatin at the later stages of the S- phase and is displaced from chromatin post replication, so that P70 cannot be detected on mitotic chromosomes. Double-immunofluorescence studies using biotin-dUTP demonstrate that initiation of DNA synthesis is confined to preRCs, resulting in the punctated replication pattern observed previously by others. PreRCs form efficiently on decondensed chromatin in membrane-free egg extracts if ATP and divalent cations are present. Our results suggest that preRCs are composed of an assembly of a large number of pre-initiation replication complexes poised for initiation at discreet subnuclear regions prior to nuclear reconstruction and initiation of DNA synthesis.
XDB - A Novel Database Architecture for Data Analytics as a Service

Parallel shared-nothing database systems are major platforms for efficiently analyzing large amounts of structured data. However, in order to offer SQL-like services for data analytics in the cloud, providers such as Amazon and Google do not use these systems as a basis. A major reason for this trend is that existing parallel shared-nothing database systems are expensive and that they do not fulfill many of the requirements such as elasticity and fault-tolerance needed for providing a service for data analytics in the cloud. In this paper, we present an overview of an elastic and fault-tolerant database system called XDB, which supports complex analytics. XDB builds on the following novel concepts: (1) a partitioning scheme that supports elasticity with regard to data and queries, (2) a cost-based fault-tolerance scheme that allows to recover from mid-query faults, and (3) adaptive parallelization techniques to better support complex analytical queries. XDB is implemented using a middleware approach on top of multiple nodes each hosting an instance of a single node database system (MySQL in our prototype). Initial experiments show that our novel concepts effectively support elasticity, fault-tolerance and complex analytics when compared to the traditional behavior of existing databases.
Some theoretical aspects of watermarking detection

This paper considers watermarking detection, also known as zero-bit watermarking. A watermark, carrying no hidden message, is inserted in content. The watermark detector checks for the presence of this particular weak signal in content. The paper aims at looking to this problem from a classical detection theory point of view, but with side information enabled at the embedding side. This means that the watermarking signal is a function of the host content. Our study is twofold. The first issue is to design the best embedding function for a given detection function (a Neyman-Pearson detector structure is assumed). The second issue is to find the best detection function for a given embedding function. This yields two conditions, which are mixed into one 'fundamental' differential equation. Solutions to this equation are optimal in these two senses. Interestingly, there are other solutions than the regular quantization index modulation scheme. The JANIS scheme, for instance, invented in a heuristic manner several years ago, is justified as it is one of these solutions.
Evaluating Classifiers in Detecting 419 Scams in Bilingual Cybercriminal Communities

Incidents of organized cybercrime are rising because of criminals are reaping high financial rewards while incurring low costs to commit crime. As the digital landscape broadens to accommodate more internet-enabled devices and technologies like social media, more cybercriminals who are not native English speakers are invading cyberspace to cash in on quick exploits. In this paper we evaluate the performance of three machine learning classifiers in detecting 419 scams in a bilingual Nigerian cybercriminal community. We use three popular classifiers in text processing namely: Na\"ive Bayes, k-nearest neighbors (IBK) and Support Vector Machines (SVM). The preliminary results on a real world dataset reveal the SVM significantly outperforms Na\"ive Bayes and IBK at 95% confidence level.
Aging effects on resting state networks after an emotional memory task

Aging is one of the primary health concerns in nowadays world, being memory decline an important worry that affects daily functioning of healthy adults. This work presents a study of this kind of decline in normal aging, by processing and analysing electroencephalographs (EEGs) of 72 healthy subjects, categorized as either young or older adults. These biosignals are first pre-processed using a customized pre-processing pipeline using the EEGLAB tool in Matlab. Once the signals have been pre-processed, two different analyses are carried out: a frequency analysis, obtaining the powers for each band of the EEG signals, and a time-frequency analysis. The data obtained from these studies is analysed using R, obtaining some important results and conclusions.
Natural Variation of ebony Gene Controlling Thoracic Pigmentation in Drosophila melanogaster

We identified the causal genetic variation for the difference in the thoracic trident pigmentation intensity between two wild-derived strains of Drosophila melanogaster. It was found to be the difference in expression level of ebony, which codes for an enzyme in the melanin-synthesis pathway and has pleiotropic effects on vision and behavior.
Automated Identification of Drug-Drug Interactions in Pediatric Congestive Heart Failure Patients

Congestive Heart Failure, or CHF, is a serious medical condition that can result in fluid buildup in the body as a result of a weak heart. When the heart can't pump enough blood to efficiently deliver nutrients and oxygen to the body, kidney function may be impaired, resulting in fluid retention. CHF patients require a broad drug regimen to maintain the delicate system balance, particularly between their heart and kidneys. These drugs include ACE inhibitors and Beta Blockers to control blood pressure, anticoagulants to prevent blood clots, and diuretics to reduce fluid overload. Many of these drugs may interact, and potential effects of these interactions must be weighed against their benefits. For this project, we consider a set of 44 drugs identified as specifically relevant for treating CHF by pediatric cardiologists at Lucile Packard Children's Hospital. This list was generated as part of our current work at the LPCH Heart Center. The goal of this project is to identify and evaluate potentially harmful drug-drug interactions (DDIs) within pediatric patients with Congestive Heart Failure. This identification will be done autonomously, so that it may continuously update by evaluating newly published literature.
Towards An Adaptive Mail Classifier

Abstract. We introduce a technique based on data mining algorithms for classifyingincoming messages, as a basis for an overall architecture for maintenance and mana-gement of e-mail messages. We exploit clustering techniques for grouping structuredand unstructured information extracted from e-mail messages in an unsupervised way,and exploit the resulting algorithm in the process of folder creation (and maintenance)and e-mail redirection. Some initial experimental results show the effectiveness of thetechnique, both from an efﬁciency and a quality-of-results viewpoint. 1 IntroductionThe process of analyzing and organizing e-mail messages is a challenging application of Weband Text mining techniques. In recent years, the increasing popularity of the Web as a meanfor sharing information has generated a huge trafﬁc of e-mail messages in various forms.The problem of detecting unsolicited (spam) e-mails, analyzing newsletter and mailing-listmessages, and rapidly detecting important messages (and separating them from unimportantones), has become readily actual. The activity of organizing e-mails keeps users busy for arelevant amount of their time, and it may also cost money in dial-up connections or bandwidthconsumption.Many tools have been developed, with the aim of helping users to organize their mailbox.For example, the Microsoft Outlook mail reader offers the user the possibility of deﬁningﬁlters , i.e., rules that allow the identiﬁcation of the content of an e-mail message, and, conse-quently, to classify and organize the e-mail in the context of the mailbox. Such tools, however,are mainly human-centered, in the sense that the user is required to manually describe rulesand keyword lists that can be used to recognize the relevant features of messages. Such anapproach has the following disadvantages:• it is inadequate to a large volume of e-mails, which may contain too many distinct andpossibly overlapping concepts. As a consequence, the process of manually detecting themain contents of mail messages occurring in a mailbox can be time-consuming. • it does not accomodate to requirement changes, that usually occurs when users need toperiodically re-organize their mailbox. The contents of e-mail messages may change with