Miracle-dz/UniFAR-FTUs huggingface dataset:
Evidence for the Assembly of a Bacterial Tripartite Multidrug Pump with a Stoichiometry of 3:6:3

The multiple transferable resistance (mTR) pump from Neisseria gonorrhoeae MtrCDE multidrug pump is assembled from the inner and outer membrane proteins MtrD and MtrE and the periplasmic membrane fusion protein MtrC. Previously we established that while there is a weak interaction of MtrD and MtrE, MtrC binds with relatively high affinity to both MtrD and MtrE. MtrD conferred antibiotic resistance only when it was expressed with MtrE and MtrC, suggesting that these proteins form a functional tripartite complex in which MtrC bridges MtrD and MtrE. Furthermore, we demonstrated that MtrC interacts with an intraprotomer groove on the surface of MtrE, inducing channel opening. However, a second groove is apparent at the interface of the MtrE subunits, which might also be capable of engaging MtrC. We have now established that MtrC can be cross-linked to cysteines placed in this interprotomer groove and that mutation of residues in the groove impair the ability of the pump to confer antibiotic resistance by locking MtrE in the closed channel conformation. Moreover, MtrE K390C forms an intermolecular disulfide bond with MtrC E149C locking MtrE in the open channel conformation, suggesting that a functional salt bridge forms between these residues during the transition from closed to open channel conformations. MtrC forms dimers that assemble into hexamers, and electron microscopy studies of single particles revealed that these hexamers are arranged into ring-like structures with an internal aperture sufficiently large to accommodate the MtrE trimer. Cross-linking of single cysteine mutants of MtrC to stabilize the dimer interface in the presence of MtrE, trapped an MtrC-MtrE complex with a molecular mass consistent with a stoichiometry of 3:6 (MtrE3MtrC6), suggesting that dimers of MtrC interact with MtrE, presumably by binding to the two grooves. As both MtrE and MtrD are trimeric, our studies suggest that the functional pump is assembled with a stoichiometry of 3:6:3.
Cancer registry and big data exchange

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1 Chemical Identification with Chemical Sensor Arrays

An electronic nose composed of small, inexpensive chemical sensors would have many potential applications in areas such as breath analysis, hazardous gas detection and industrial process monitoring. An electronic nose, in anology to a biological nose, consists of an array of non-specific chemical sensors. With pattern recognition, the system can recognize individual chemicals or scents. Capacitive micromachined ultrasonic transducer (CMUT) chemical sensors are a particularly promising chemical sensor technology. They are micromachined devices, so they can be inexpensively batch fabricated. In addition, they have extraordinary sensitivity; A limit of detection of 50.5 parts-pertrillion (ppt) and sensitivity of 34.5 ppt/Hz to DMMP, a sarin gas simulant have been demonstrated [2]. In this work, I demonstrate the application of machine learning to an array of four CMUT chemical sensors to discriminate between six different chemicals present in low concentrations in nitrogen. Typically, only the equilibrium response of chemical sensors is used in chemical identification. I show that using the response of the sensor over time provides extra information that improves classification performance. I also study the robustness of the system with respect to variations in sensor sensitivity, and test its ability to determine the concentration of the detected chemical once it is identified. The data used in this work has been previously been shown at a conference, with some machine learning tested on it [8], but the feature selection and machine learning work in this paper is new, and shows significant improvement over the previous results.
ParzenWindows Estimation Using Laplace Kernel: A Novel Parametric Analysis with Information Content

Parzen windows estimation is one of the classical non- parametric methods in the field of machine learning and pattern classification, and usually uses Gaussian density function as the kernel. Although the relation between the kernel density estimation (KDE) and low-pass filtering is well known, it is vary difficult to setting the parameters of the other kinds of density functions. This paper proposes a novel method to deal with the parameters of Laplace kernel through measuring the degree of exchanged information among interpolating points. Experimental results showed that the proposed method can improve the performance of Parzen windows significantly.
Platelet-derived growth factor B, but not fibroblast growth factor 2, plasmid DNA improves survival of ischemic myocutaneous flaps.

HYPOTHESIS Tissue flaps are commonly used for surgical reconstruction, especially to cover difficult wounds and in breast reconstruction following mastectomy. Complications due to inadequate flap perfusion are a source of morbidity and, in the lower extremity, can result in amputation. SETTING Laboratory. INTERVENTIONS We evaluated the ability of platelet-derived growth factor (PDGF) B and fibroblast growth factor 2 plasmid DNA, formulated in a type I collagen matrix, to promote tissue survival in a rat transverse rectus abdominis muscle flap model based on the inferior deep epigastric vascular supply. In the absence of any therapeutic agent, only about 24% of flap tissue survives in this model. The DNA/matrix formulations were delivered subcutaneously into the skin paddles 7 days before flap elevation, and tissues were harvested 7 days later. RESULTS Our studies reveal dramatic increases in overall vascularity after treatment with PDGF-B and fibroblast growth factor 2 plasmid DNA; however, only PDGF-B increased flap survival (130% increase at 228 micro g/cm(2) of plasmid DNA vs controls; P<. 01). Transdermal spectral imaging demonstrated an increase in patent vessels supporting blood flow in flaps treated with PDGF-B plasmid DNA vs the fibroblast growth factor 2 transgene. CONCLUSION Matrix-enabled gene therapy may provide an effective nonsurgical approach for promoting flap survival and is well suited for surgical applications in which transient therapeutic transgene expression is desired.
Emotion Analysis in Code-Switching Text With Joint Factor Graph Model

Previous research on emotions analysis has placed much emphasis in monolingual instead of bilingual text. However, emotions on social media platforms are often found in bilingual or code-switching posts. Different from monolingual text, emotions in code-switching text can be expressed in both monolingual and bilingual forms. Moreover, more than one emotion can be expressed within a single post; yet they tend to be related in some ways which offers some implications. It is thus necessary to consider the correlation between different emotions. In this paper, a joint factor graph model is proposed to address this issue. In particular, attribute functions of the factor graph model are utilized to learn both monolingual and bilingual information from each post, factor functions are used to explore the relationship among different emotions, and a belief propagation algorithm is employed to learn and predict the model. Empirical studies demonstrate the importance of emotion analysis in code-switching text and the effectiveness of our proposed joint learning model.
Parameter Estimation of Radar Noise Model for Terrain Referenced Navigation Using a New EM Initialization Method

In this paper, we present an expectation-maximization (EM) initialization method for estimation of unknown parameters in a radar noise model. We deal with radar based terrain referenced navigation (TRN) over vegetated areas, where the radar noise was modeled as a double-mode Gaussian mixture with two unknowns. The known parameters are used for EM initialization along with innovation samples. Through TRN simulation, it is shown that the proposed EM initialization method outperforms random or k-means initialization methods in terms of both the parameter estimation error and the vehicle position error.
A versatile segmentation procedure

In this paper, a new method for the segmentation of natural images is proposed. Original images g(x,y) are first regularized by using a self-adaptive implementation of the Mumford-Shah functional so that the two parameters /spl alpha/ and /spl gamma/ controlling the smoothness and fidelity, automatically adapt to the local scale and contrast of g(x,y). From the regularized image u(x,y) which is piecewise smooth, it is possible to obtain a piecewise constant image s/sub N/(x,y) representing a segmentation of the original image g(x,y). Indeed, s/sub N/(x,y) is the union of N closed regions, having a constant grey level, preserving thin bars and trihedral junctions present in the original image g(x,y). If the number N of closed regions is too high, closed regions can be merged by minimizing a functional which depends on a parameter n. When n is set equal to 1, a coarse segmentation is obtained with a few tens of distinct regions. With larger values of n, finer segmentations are obtained with about a hundred distinct regions. Therefore, by selecting the value of n it is possible to obtain segmentations at different resolutions. The proposed method for image segmentation was evaluated in two cases where a ground truth segmentation is available. The proposed procedure for image segmentation is rather versatile and depends on only one parameter n and seems suitable for higher level processing, such as categorization, recognition, and scene understanding.
Knowledge management model for support of requirement engineering

Requirement engineering (RE) plays an important role in the success or failure of product and is recognized as the most critical factor in the entire software development process. Due to the fact that RE knowledge is highly dependent on human which may result in inconsistencies, terminology conflicts and lack of understanding of requirement knowledge faced in the implementation of information based applications. To address these issues we have proposed the knowledge management model for the support of RE activities. This knowledge model assists the requirement engineers and other stakeholders to share and understand the domain and instance level knowledge which results in strengthening the RE activities through continuous requirement refinement by better knowledge management model.
Ionic Adsorption and Desorption of CNT Nanoropes

A nanorope is comprised of several carbon nanotubes (CNTs) with different chiralities. A molecular dynamic model is built to investigate the ionic adsorption and desorption of the CNT nanoropes. The charge distribution on the nanorope is obtained by using a modified gradient method based on classical electrostatic theory. The electrostatic interactions among charged carbon atoms are calculated by using the Coulomb law. It was found here that the charged nanorope can adsorb heavy metal ions, and the adsorption and desorption can be realized by controlling the strength of applied electric field. The distance between the ions and the nanorope as well as the amount of ions have an effect on the adsorption capacity of the nanorope. The desorption process takes less time than that of adsorption. The study indicates that the CNT nanorope can be used as a core element of devices for sewage treatment.
SPEECH-BASED RETRIEVAL OF VIDEO

This paper discusses issues arising when applying the IBM Audio-Indexing System to retrieval of video. Issues discussed include the relationship between speech transcription accuracy and retrieval performance, query processing schemes and the critical problem of mapping between cues in speech and the relevant video shots. The temporal relationship between the occurrence of cues in speech transcripts and relevant shots is quantified and then simple schemes for performing this mapping are described and evaluated. Experiments demonstrate the promise of more sophisticated schemes involving up-front video ranking and one possible implementation is discussed. Techniques are evaluated using the TREC-2002 Video Track queries and corpus, comprising a total of 68.45 hours of video.
A Network-Based, Genetic-Marker Evaluation for Lewis Lung Carcinoma

Background: Lung cancer is the most common human cancer. There are numerous studies that have sought to discover genetic impact factors associated with it. The study reported on in this article is a systematic search for the genetic networks underlying the Lewis lung carcinoma (LLC) model.Methods: LLC-Gene relation data were extracted from the ResNet 11 Mammalian database, containing 175 LLC candidate genes (nodes). Pathway Enrichment Analysis, Sub-Network Enrichment Analysis, Network Connectivity Analysis, and Network Metrics Analysis were conducted to study network attributes and select the top nodes (genes). LLC-Drug and Drug-Gene relation data examined LLC-Gene relations at the small molecule level.Results: A total of 166 of 175 genes that were enriched in 134 LLC candidate pathways (p < 1e-07), demonstrated strong gene-gene interactions. Metrics analysis revealed 4 genes, IL6, TNF, VEGFA, and HIF1A, as top LLC candidates as measured by replication frequency, network centrality, and functional diversity. Additionally, 169 of 175 LLC candidate genes demonstrated strong interactions with 213 of 253 LLC effective drugs which supports an LLC-gene relationship.Conclusion: The results suggest that LLC genetic causes link to a genetic network composed of a large number of genes. This network, together with literature and enrichment metrics provide a foundation for further biological/genetic studies in the field.
Multiple description coding of 3D dynamic meshes based on temporal subsampling

In this paper, we propose a Multiple Description Coding (MDC) method for reliable transmission of compressed time consistent 3D dynamic meshes. It trades off reconstruction quality for error resilience to provide the best expected reconstruction of 3D mesh sequence at the decoder side. The method is based on partitioning the mesh frames into two sets by temporal subsampling and encoding each set independently by a 3D dynamic mesh coder. The encoded independent bitstreams or so-called descriptions are transmitted independently. The 3D dynamic mesh coder is based on predictive coding with spatial and temporal layered decomposition. In addition, the proposed method allows for different redundancy allocations by including a number of encoded spatial layers of the frames in the other set. The algorithm is evaluated with redundancy-rate-distortion curves and it is shown that, when one of the descriptions is lost, acceptable quality can be achieved with around 50% redundancy.
Multiobjective performance-based designs in fault estimation and isolation for discrete-time systems and its application to wind turbines

ABSTRACT In this work, we develop a performance-based design of model-based observes and statistical-based decision mechanisms for achieving fault estimation and fault isolation in systems affected by unknown inputs and stochastic noises. First, through semidefinite programming, we design the observers considering different estimation performance indices as the covariance of the estimation errors, the fault tracking delays and the degree of decoupling from unknown inputs and from faults in other channels. Second, we perform a co-design of the observers and decision mechanisms for satisfying certain trade-off between different isolation performance indices: the false isolation rates, the isolation times and the minimum size of the isolable faults. Finally, we extend these results to a scheme based on a bank of observers for the case where multiple faults affect the system and isolability conditions are not verified. To show the effectiveness of the results, we apply these design strategies to a well-known benchmark of wind turbines which considers multiple faults and has explicit requirements over isolation times and false isolation rates.
Expression of catalytic mutants of the mtDNA helicase Twinkle and polymerase POLG causes distinct replication stalling phenotypes

The mechanism of mitochondrial DNA replication is a subject of intense debate. One model proposes a strand-asynchronous replication in which both strands of the circular genome are replicated semi-independently while the other model proposes both a bidirectional coupled leading- and lagging-strand synthesis mode and a unidirectional mode in which the lagging-strand is initially laid-down as RNA by an unknown mechanism (RITOLS mode). Both the strand-asynchronous and RITOLS model have in common a delayed synthesis of the DNA-lagging strand. Mitochondrial DNA is replicated by a limited set of proteins including DNA polymerase gamma (POLG) and the helicase Twinkle. Here, we report the effects of expression of various catalytically deficient mutants of POLG1 and Twinkle in human cell culture. Both groups of mutants reduced mitochondrial DNA copy number by severe replication stalling. However, the analysis showed that while induction of POLG1 mutants still displayed delayed lagging-strand synthesis, Twinkle-induced stalling resulted in maturated, essentially fully double-stranded DNA intermediates. In the latter case, limited inhibition of POLG with dideoxycytidine restored the delay between leading- and lagging-strand synthesis. The observed cause-effect relationship suggests that Twinkle-induced stalling increases lagging-strand initiation events and/or maturation mimicking conventional strand-coupled replication.
A software-based redundancy concept for building automation networks

Reliability in automation networks is an important topic. Thus, redundant communication is fundamental in this context. In contrast to other automation domains, building automation networks facilitate Ethernet and IP communication and require reliable and predictable communication that are ideally based on standard network technologies. Since automation components are often based on commonly used operating systems, software-based solutions come into play. However, pure software-based solutions are inefficient and often infeasible due to limited processing resources. Thus, a hybrid redundancy concept is proposed that facilitates standard hardware components in combination with lightweight software modules. This paper presents a new redundancy mechanism for Ethernet networks based on a ring topology. This approach makes use of VLAN-capable Ethernet switches in combination with software modules for controlling the network traffic. Thereby, VLANs are used to provide physical redundancy by preventing from Ethernet loops. The proposed concept can therefore be used on different platforms and provides a transparent and reliable communication channel for automation applications. The concept is theoretically analyzed. Finally, a proof-of-concept shows the feasibility.
Vitamin A equivalency and apparent absorption of β-carotene in ileostomy subjects using a dual-isotope dilution technique

The objective was to quantify the vitamin A equivalency of β-carotene in two diets using a dual-isotope dilution technique and the apparent β-carotene absorption as measured by the oral–faecal balance technique. Seventeen healthy adults with an ileostomy completed the 4-week diet-controlled, cross-over intervention study. Each subject followed both diets for 2 weeks: a diet containing vegetables low in β-carotene content with supplemental β-carotene in salad dressing oil (‘oil diet’; mean β-carotene intake 3·1 mg/d) and a diet containing vegetables and fruits high in β-carotene content (‘mixed diet’; mean β-carotene intake 7·6 mg/d). Daily each subject consumed a mean of 190 μg [13C10]β-carotene and 195 μg [13C10]retinyl palmitate in oil capsules. The vitamin A equivalency of β-carotene was calculated as the dose-corrected ratio of [13C5]retinol to [13C10]retinol in serum. Apparent absorption of β-carotene was determined with oral–faecal balance. Isotopic data quantified a vitamin A equivalency of [13C10]β-carotene in oil of 3·6:1 (95 % CI 2·8, 4·6) regardless of dietary matrices differences. The apparent absorption of (labelled and dietary) β-carotene from the ‘oil diet’ (30 %) was 1·9-fold higher than from the ‘mixed diet’ (16 %). This extrinsic labelling technique can measure precisely the vitamin A equivalency of β-carotene in oil capsules, but it does not represent the effect of different dietary matrices.
Detection of distinctions in car fleets based on measured and simulated data

The main aim of this paper is the analysis of a fleet behavior and comparison of damaged and non-damaged vehicles using different machine learning algorithms to identify the main distinctions in a car fleet. For this purpose OBD (On Board Diagnostics) signals are recorded in three various car types (BMW X3, Peugeot 208, Seat Leon) and several hundred drives. Furthermore, thousands of drives are simulated based on the Discrete Fourier Transformation (DTF) and Monte Carlo simulation (MC) to provide a huge training data for the rule learning algorithms. The simulated data represents the car fleet with given (or assumed) testing conditions. For example it is assumed, that all the cars of the fleet don't exceed the maximum speed of 170 km/hour due to the specs of the product. All made assumptions are variable and can be changed after the analysis process. All signals (simulated and recorded) are analyzed in order to provide information about every single drive (e.g. out of the speed signal: max speed, max acceleration, duration of the drive are determined and stored in a data base).
RANCANG BANGUN SISTEM INFORMASI SHORT MESSAGE SERVICE (SMS) GATEWAY UNTUK INFORMASI KEGIATAN PERSERTA CALON ANGGOTA POLRI

Tujuan dari penulisan penelitian ini adalah untuk membantu pihak Sumber Daya Manusia (SDM) Polda NTB dalam menyampaikan informasi tentang kegiatan calon anggota polri sehingga dapat mempermudah dan lebih efesien dalam menyampaikan informasi kegiatan calon anggota polri kepada masing-masing peserta.Metodologi yang digunakan dalam pembuatan sistem ini adalah metode pengumpulan data berupa, observasi, interview dan studi pustaka. Sedangkan metode analisis yang digunakan adalah analisis SWOT, Untuk metode perancangan menggunakan XP (Extrame Programming), dan Blackbox Testing sebagai metode Testingnya.Dalam pembuatan sistem penulis menggunakan alat bantu yaitu Xampp Server, PHP sebagai bahasa pemrogramannya dan Modem sebagai jambatan antara Gammu dengan Aplikasi. Data yang di proses oleh Sistem Informasi yang Berbasis SMS Gateway ini berupa pesan yang keluar masuk untuk menyampaikan informasi kegiatan pada calon anggota polri dengan sms gateway dan mempermudah dalam penyediaan data calon anggota polri yang nantinya dibutuhkan pimpinan secara lebih cepat dan akurat.
Multicast routing algorithms and protocols: a tutorial

Multicasting is the ability of a communication network to accept a single message from an application and to deliver copies of the message to multiple recipients at different locations. There has been an explosion of research literature on multicast communication. This work presents a tutorial-cum-survey of the various multicast routing algorithms and their relationship with multicast routing protocols for packet-switched-wide-area networks. Our contribution should be of particular benefit to the generic networking audience (and, to a lesser extent, to the expert on this subject).