Miracle-dz/UniFAR-FTUs huggingface dataset:
Pharmacodynamics and Subchronic Toxicity in Mice and Monkeys of ISIS 388626, a Second-Generation Antisense Oligonucleotide That Targets Human Sodium Glucose Cotransporter 2

ISIS 388626, a 2′-methoxyethyl (MOE)-modified antisense oligonucleotide (ASO) that targets human sodium glucose cotransporter 2 (SGLT2) mRNA, is in clinical trials for the management of diabetes. SGLT2 plays a pivotal role in renal glucose reabsorption, and inhibition of SGLT2 is anticipated to reduce hyperglycemia in diabetic subjects by increasing urinary glucose elimination. To selectively inhibit SGLT2 in the kidney, ISIS 388626 was designed as a “shortmer” ASO, consisting of only 12 nucleotides with two 2′-MOE-modified nucleotides at the termini. Mice and monkeys received up to 30 mg/kg/week ISIS 388626 via subcutaneous injection for 6 or 13 weeks. Dose-dependent decreases in renal SGLT2 mRNA expression were observed, which correlated with dose-related increases in glucosuria without concomitant hypoglycemia. There were no histologic changes in the kidney attributed to SGLT2 inhibition after 6 or 13 weeks of treatment. The remaining changes observed in these studies were typical of those produced in these species by the administration of oligonucleotides, correlated with high doses of ISIS 388626, and were unrelated to the inhibition of SGLT2 expression. The kidney contained the highest concentration of ISIS 388626, and dose-dependent basophilic granule accumulation in tubular epithelial cells of the kidney, which is evidence of oligonucleotide accumulation in these cells, was the only histologic change identified. No changes in kidney function were observed. These results revealed only readily reversible changes after the administration of ISIS 388626 and support the continued investigation of the safety and efficacy of ISIS 388626 in human trials.
Panoramic Background Model under Free Moving Camera

Segmentation of moving regions in outdoor environment under a moving camera is a fundamental step in many vision systems including automated visual surveillance, human-machine interface, tracking etc. It is also a challenging task due to camera motion, object motion, and outdoor scene challenges i.e. periodic motions of swaying of trees, gradual illumination changes, etc. In this paper, a wide area scene modeling approach for object segmentation under a moving camera is proposed. This approach suffers due to parallax effect, misallignment errors etc and needs their concurrent removal for its success, we explicitly model the dense correspondence between input image and panoramic background model. Foreground segmentation and correspondence estimation are expressed as a unified labeling problem, and are solved efficiently via tree dynamic programming (TDP). Lucas-Kanade method is used to find sparse correspondence between image and model, and robust M-estimator is then applied to find the projective transformation for initialization of TDP's window search. Optimal dense correspondences are achieved and are used to update panoramic background model and as a byproduct, online refined panoramic image is generated which is empty in the beginning and is filled step by step. We test our algorithm with hand-held camera and also with a camera mounted on a moving platform. Experiments proved our algorithm to be robust in performance.
A Reliable Technique for Remaining Useful Life (RUL) Estimation of Rolling Element Bearings using Dynamic Regression Models

Induction motors most often fail due to faults in the rolling element bearings. Sudden failures in a system result in long unscheduled downtimes, which cause huge economic losses. Prediction of imminent failures and estimation of the remaining useful life (RUL) of a bearing is essential for scheduling prior maintenance and avoiding abrupt shutdowns of critical systems. This paper presents a hybrid prognostics technique for rolling element bearings that utilizes dynamic regression models, which are updated recursively, to estimate the evolving trend in a bearing’s health indicator. These models are then used to predict the future value of the bearing health indicator and estimate the RUL of the bearing. The proposed algorithm is tested on the bearing prognostics data from the Center for Intelligent Maintenance Systems (IMS). Experimental results demonstrate excellent prognostic performance and bearing’s RUL estimates within the specified tolerance bounds by effectively determining the time to start prediction (TSP) and dynamically calibrating the models to adopt to the evolving behavior of the bearing health indicator.
A comparison of embedded reconfigurable video-processing architectures

Using field programmable gate arrays (FPGAs) as accelerators for image or video processing operations and algorithms has gained increasing attention over the last few years. One reason for that is FPGAs are able to exploit both temporal and spatial parallelism. In this paper two platforms for FPGA-based real-time image and video processing are presented and compared against each other. With both of these platforms it is possible to update the physical resources during run-time by exploiting the dynamic partial reconfiguration capabilities of Xilinx Virtex FPGAs. The analysis of both platforms with respect to their benefits and draw-backs has led to the concept of an optimal FPGA-based dynamically and partially reconfigurable platform for real-time video and image processing.
Sequence of the murein-lipoprotein and the attachment site of the lipid.

The primary structure of a covalent lipoglycoprotein (murein · lipoprotein) from the cell wall of Escherichia coli is presented. The amino acid sequence consists of 57 residues. The lipid is attached to the N-terminal serine and the murein is bound to the 6-amino group of the C-terminal lysine of the lipoprotein. The repetitive design of the sequence suggests a very conservative evolution in which a structural gene coding for 15 amino acids was duplicated once and then only half of this gene, thus coding for 7 amino acids was fused four times with the first 29 amino acids. Some deletions but only few exchanges of amino acids apparently occurred. This structural membrane lipoprotein aggregates strongly when released from the murein by lysozyme digestion. The molecular weight was therefore determined in 2%, 0.5% and 0.1% dodecylsulfate by polyacrylamide gel electrophoresis and gel chromatography. The molecular weight of 13000 thus found deviated from that of 10000 calculated from the sum of the amino acids, the lipid as known so far and the part of the murein remaining bound to the lipoprotein. This was not due to a different amount of dodecylsulfate binding by the lipoprotein compared with proteins containing no lipid but may be due to a more spherical shape of the small molecule in contrast to the rod-like shape of standard proteins in dodecylsulfate.
Transcriptome-Wide Analysis of Botrytis elliptica Responsive microRNAs and Their Targets in Lilium Regale Wilson by High-Throughput Sequencing and Degradome Analysis

MicroRNAs, as master regulators of gene expression, have been widely identified and play crucial roles in plant-pathogen interactions. A fatal pathogen, Botrytis elliptica, causes the serious folia disease of lily, which reduces production because of the high susceptibility of most cultivated species. However, the miRNAs related to Botrytis infection of lily, and the miRNA-mediated gene regulatory networks providing resistance to B. elliptica in lily remain largely unexplored. To systematically dissect B. elliptica-responsive miRNAs and their target genes, three small RNA libraries were constructed from the leaves of Lilium regale, a promising Chinese wild Lilium species, which had been subjected to mock B. elliptica treatment or B. elliptica infection for 6 and 24 h. By high-throughput sequencing, 71 known miRNAs belonging to 47 conserved families and 24 novel miRNA were identified, of which 18 miRNAs were downreguleted and 13 were upregulated in response to B. elliptica. Moreover, based on the lily mRNA transcriptome, 22 targets for 9 known and 1 novel miRNAs were identified by the degradome sequencing approach. Most target genes for elliptica-responsive miRNAs were involved in metabolic processes, few encoding different transcription factors, including ELONGATION FACTOR 1 ALPHA (EF1a) and TEOSINTE BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTOR 2 (TCP2). Furthermore, the expression patterns of a set of elliptica-responsive miRNAs and their targets were validated by quantitative real-time PCR. This study represents the first transcriptome-based analysis of miRNAs responsive to B. elliptica and their targets in lily. The results reveal the possible regulatory roles of miRNAs and their targets in B. elliptica interaction, which will extend our understanding of the mechanisms of this disease in lily.
Using Modified Partitioning Around Medoids Clustering Technique in Mobile Network Planning

Optimization mobile radio network planning is a very complex task, as many aspects must be taken into account. Deciding upon the optimum placement for the base stations (BS’s) to achieve best services while reducing the cost is a complex task requiring vast computational resource. This paper introduces the spatial clustering to solve the Mobile Networking Planning problem. It addresses antenna placement problem or the cell planning problem, involves locating and configuring infrastructure for mobile networks by modified the original Partitioning Around Medoids PAM algorithm. M-PAM (Modified Partitioning Around Medoids) has been proposed to satisfy the requirements and constraints. Implementation of this algorithm to a real case study is presented. Experimental results and analysis indicate that the M-PAM algorithm is effective in case of heavy load distribution, and leads to minimum number of base stations, which directly affected onto the cost of planning the network. Key-words: clustering techniques, network planning, cell planning and mobile network
Deep Learning-Based Optical Music Recognition for Semantic Representation of Non-overlap and Overlap Music Notes

In the technology era, the process of teaching a computer to interpret musical notation is termed optical music recognition (OMR). It aims to convert musical note sheets presented in an image into a computer-readable format. Recently, the sequence-to-sequence model along with the attention mechanism (which is used in text and handwritten recognition) has been used in music notes recognition. However, due to the gradual disappearance of excessively long sequences of musical sheets, the mentioned OMR models which consist of long short-term memory are facing difficulties in learning the relationships among the musical notations. Consequently, a new framework has been proposed, leveraging the image segmentation technique to break up the procedure into several steps. In addition, an overlap problem in OMR has been addressed in this study. Overlapping can result in misinterpretation of music notations, producing inaccurate findings. Thus, a novel algorithm is being suggested to detect and segment the notations that are extremely close to each other. Our experiments are based on the usage of the Convolutional Neural Network block as a feature extractor from the image of the musical sheet and the sequence-to-sequence model to retrieve the corresponding semantic representation. The proposed approach is evaluated on The Printed Images of Music Staves dataset. The achieved results confirm that our suggested framework successfully solves the problem of long sequence music sheets, obtaining SER 0% for the non-overlap symbols in the best scenario. Furthermore, our approach has shown promising results in addressing the overlapping problem: 23.12 % SER for overlapping symbols.
Microfluidic Technology for the Generation of Cell Spheroids and Their Applications

A three-dimensional (3D) tissue model has significant advantages over the conventional two-dimensional (2D) model. A 3D model mimics the relevant in-vivo physiological conditions, allowing a cell culture to serve as an effective tool for drug discovery, tissue engineering, and the investigation of disease pathology. The present reviews highlight the recent advances and the development of microfluidics based methods for the generation of cell spheroids. The paper emphasizes on the application of microfluidic technology for tissue engineering including the formation of multicellular spheroids (MCS). Further, the paper discusses the recent technical advances in the integration of microfluidic devices for MCS-based high-throughput drug screening. The review compares the various microfluidic techniques and finally provides a perspective for the future opportunities in this research area.
Relay selection with channel allocation for cognitive radio relay channels in CRN

This paper investigates cognitive radio network (CRN) performance through cooperative multiple cognitive radio relays and relay selection with channel allocation scheme. In one approach the overall end-to-end throughput (OEET) improves as the number of cognitive radio relays (CRRs) increases in CRN. In this approach, the OEET increases with the number of CRRs but at the cost of increased transmission power and overheads, so simple and practical approach is proposed for the relay selection from a set of M CRRs then the channel allocation is performed with this selected cognitive radio relay (CRR). This proposed relay selection scheme uses channel conditions of the cooperative links as a metric for selecting the best cognitive radio relay. Simulation results show that the best CRR selected through the proposed approach performs better than the single CRR, in both the cases of with and without channel allocation (CA). Simulation results are compared with channel allocation (CA) scheme presented in [1]. The selected best CRR gives better performance than single CRR when combined with the channel allocation scheme, i.e., first select the best CRR with proposed relay selection approach and then perform channel allocation.
Affinity CNN: Learning Pixel-Centric Pairwise Relations for Figure/Ground Embedding

Spectral embedding provides a framework for solving perceptual organization problems, including image segmentation and figure/ground organization. From an affinity matrix describing pairwise relationships between pixels, it clusters pixels into regions, and, using a complex-valued extension, orders pixels according to layer. We train a convolutional neural network (CNN) to directly predict the pair-wise relationships that define this affinity matrix. Spectral embedding then resolves these predictions into a globally-consistent segmentation and figure/ground organization of the scene. Experiments demonstrate significant benefit to this direct coupling compared to prior works which use explicit intermediate stages, such as edge detection, on the pathway from image to affinities. Our results suggest spectral embedding as a powerful alternative to the conditional random field (CRF)-based globalization schemes typically coupled to deep neural networks.
Institute for Mathematical Physics

In this paper we prove a series of results on the size of distance sets corresponding to sets in the Euclidean space. These distances are generated by bounded convex sets and the results depend explicitly on the geometry of these sets. We also use a diophantine mechanism to convert continuous results into distance set estimates for discrete point sets.
Universal-DB: Towards Representation Independent Graph Analytics

Graph analytics algorithms leverage quantifiable structural properties of the data to predict interesting concepts and relationships. The same information, however, can be represented using many different structures and the structural properties observed over particular representations do not necessarily hold for alternative structures. Because these algorithms tend to be highly effective over some choices of structure, such as that of the databases used to validate them, but not so effective with others, graph analytics has largely remained the province of experts who can find the desired forms for these algorithms. We argue that in order to make graph analytics usable, we should develop systems that are effective over a wide range of choices of structural organizations. We demonstrate Universal-DB an entity similarity and proximity search system that returns the same answers for a query over a wide range of choices to represent the input database.
Volatile-bearing partial melts beneath oceans and continents–Where, how much, and of what compositions?

Besides depth and temperature, CO2 and H2O, are the two most important variables in stabilizing partial melts in the Earth's mantle. However, despite decades of experimental studies on the roles of these two volatile species in affecting mantle melting, ambiguity remains in terms of the stability, composition, and proportion of volatile-bearing partial melts at depths. Furthermore, the difference in the influence of H2O versus CO2 in production of mantle melts is often inadequately discussed. Here I first discuss how as a function of depth and concentration of volatiles, the peridotite + H2O versus peridotite + CO2 near-solidus melting conditions differ - discussing specifically the concepts of saturation of volatile-bearing phases and how the mode of storage of ‘water’ and carbon affects the near solidus melting relations. This analysis shows that for the Earth's mantle beneath oceans and continents, deep, volatile-induced melting is influenced mostly by carbon, with water-bearing carbonated silicate melt being the key agent. A quantitative framework that uses the existing experimental data, allows calculation of the loci, extent of melting, and major element compositions of volatile-bearing partial melts beneath oceans and continents. How the domains of volatile-bearing melt stability are affected when possible oxygen fugacity variation at depths in the mantle is taken into account is also discussed. I show that trace amount hydrous carbonated silicate melt is likely stabilized at two or more distinct depths in the continental lithospheric mantle, at depths ranges similar to where mid-lithospheric discontinuity (MLD) and lithosphere-asthenosphere boundary (LAB) have been estimated from seismology. Whereas beneath oceans, hydrous carbonated silicate melt likely remain continuously stable from the base of the thermal boundary layer to at least 200 km or deeper depending on the prevailing oxygen fugacity at depths. Hotter mantles, such as those beneath oceans, prevent sampling strongly silica-undersaturated, carbonated melts such as kimberlites as shallower basaltic melt generation dominates. Thick thermal boundary layers, such as those in cratonic regions, on the other hand allow production of kimberlitic to carbonatitic melt only. Therefore, the increasing frequency of occurrence of kimberlites starting at the Proterozoic may be causally linked to cooling and growth of sub-continental mantles through time.
Management of Change to Ensure IS Success: A Longitudinal Study

This paper aims to understand the effect of management of change on the success of information system (IS) implementation. Drawing on change management research and self-determination theory, a research model is developed. Data collected from a longitudinal field survey before, during, and after an enterprise-wide IS implementation are analyzed to test the proposed hypotheses. The results indicate that management of change can be used to increase readiness for change and end-user computing satisfaction during and after the implementation. Readiness for change positively impacts satisfaction during an implementation but not after. Contrary to the literature, No significant relationship exists between resistance to change and satisfaction. The paper contributes to IS research and practice by drawing attention to the importance of management of change and readiness for change for IS success.
Secure and Policy-Compliant Source Routing

In today's Internet, inter-domain route control remains elusive; nevertheless, such control could improve the performance, reliability, and utility of the network for end users and ISPs alike. While researchers have proposed a number of source routing techniques to combat this limitation, there has thus far been no way for independent ASes to ensure that such traffic does not circumvent local traffic policies, nor to accurately determine the correct party to charge for forwarding the traffic. We present Platypus, an authenticated source routing system built around the concept of network capabilities, which allow for accountable, fine-grained path selection by cryptographically attesting to policy compliance at each hop along a source route. Capabilities can be composed to construct routes through multiple ASes and can be delegated to third parties. Platypus caters to the needs of both end users and ISPs: users gain the ability to pool their resources and select routes other than the default, while ISPs maintain control over where, when, and whose packets traverse their networks. We describe the design and implementation of an extensive Platypus policy framework that can be used to address several issues in wide-area routing at both the edge and the core, and evaluate its performance and security. Our results show that incremental deployment of Platypus can achieve immediate gains.
Axonal Regeneration from Injured Neurons in the Adult Mammalian Central Nervous System

A failure of axons to grow extensively through damaged central nervous system (CNS) tissues is a common consequence of injury to the brain and spinal cord of adult mammals. By contrast, axons severed in the peripheral nervous system (PNS) can successfully regenerate when they become associated with Schwann cells and other peripheral nerve components. At the turn of this century Cajal expressed his belief that the failure of central fibers to regrow "derives from external conditions, the presence or absence of auxiliary factors that are indispensable to the regenerative process" (Ramon y Cajal, 1928, pp. 1-2, italics added) and after observing with Tello (1911) and others (Leoz & Arcuate, 1914) that peripheral nerve grafts inserted into the brain became temporarily innervated he added, "sprouts, wandering through the scar, can be nourished and oriented by the cells of Schwann that are forming hands of Bungner in the grafted nerves" (Ramon y Cajal, 1928, p. 589, italics added). Since these pioneering studies, other investigators have made use of similar transplantation techniques to assess the influence of the nonneurona! environment on axonal regeneration and to test the capacity of CNS neurons to initiate and sustain fiber growth along a substrate normally only present in peripheral nerves (Clark, 1942; Horvat, 1966; Kao, Chang, & Bloodworth, 1977). The recent advent of anatomical techniques for tracing the origin and termination of nerve fibers has helped establish that under the experimental conditions created by the grafting of nerve segments into the adult rat CNS, a heterogeneous
Non linear position and closed loop stiffness control for a pneumatic actuated haptic interface: the BirthSIM

This paper presents the BirthSIM model, a haptic interface of a childbirth simulator. The aim of this haptic interface is to improve haptic rendering and increase the biofidelity of the movements and forces which occur during the fetal descent. Thus the model of this 2 degrees of freedom pneumatic actuated interface is presented in this article, in order to synthesize a control law based on the backstepping method. The control law obtained allows targeted trajectories of positions and pneumatic stiffness to be tracked but also allows the equivalent stiffness of the end effector in Cartesian coordinates to be adapted in real time. The difference between pneumatic stiffness and closed loop stiffness is explained. Finally, some simulation results are presented to validate the control law behavior.