Miracle-dz/UniFAR-FTUs huggingface dataset:
Ecophysiology of mesophotic reef‐building corals in Hawai‘i is influenced by symbiont–host associations, photoacclimatization, trophic plasticity, and adaptation

Mesophotic reef corals remain largely unexplored in terms of the genetic adaptations and physiological mechanisms to acquire, allocate, and use energy for survival and reproduction. In the Hawaiian Archipelago, the Leptoseris species complex form the most spatially extensive mesophotic coral ecosystem known and provide habitat for a unique community. To study how the ecophysiology of Leptoseris species relates to symbiont–host specialization and understand the mechanisms responsible for coral energy acquisition in extreme low light environments, we examined Symbiodinium (endosymbiotic dinoflagellate) photobiological characteristics and the lipids and isotopic signatures from Symbiodinium and coral hosts over a depth‐dependent light gradient (55–7 μmol photons m−2 s−1, 60–132 m). Clear performance differences demonstrate different photoadaptation and photoacclimatization across this genus. Our results also show that flexibility in photoacclimatization depends primarily on Symbiodinium type. Colonies harboring Symbiodinium sp. COI‐2 showed significant increases in photosynthetic pigment content with increasing depth, whereas colonies harboring Symbiodinium spp. COI‐1 and COI‐3 showed variability in pigment composition, yield measurements for photosystem II, as well as size and density of Symbiodinium cells. Despite remarkable differences in photosynthetic adaptive strategies, there were no significant differences among lipids of Leptoseris species with depth. Finally, isotopic signatures of both host and Symbiodinium changed with depth, indicating that coral colonies acquired energy from different sources depending on depth. This study highlights the complexity in physiological adaptations within this symbiosis and the different strategies used by closely related mesophotic species to diversify energy acquisition and to successfully establish and compete in extreme light‐limited environments.
Crystallization of Ca + ions in a linear rf octupole ion trap

A laser-cooling experiment with ${\mathrm{Ca}}^{+}$ ions trapped in a linear rf octupole ion trap is presented. The phase transition of the laser-cooled ${\mathrm{Ca}}^{+}$ ions from the cloud to the crystal state is observed by an abrupt dip of the laser-induced fluorescence spectrum and indicates that mK temperatures are obtained. We have also performed molecular dynamics simulations under various conditions to confirm this property by deducing axially symmetric structures of Coulomb crystals and by evaluating the translational temperatures of the laser-cooled ions. The simulation results show that for small numbers of ions novel ring-shaped crystals are produced. As the number of ions is increased, cylindrical layers in the ring crystal are sequentially formed. For more than 100 ions, also hexagonal and spiral structures emerge in parts of the large-size ion crystal, which has a length on the order of millimeters for the present geometrical arrangement and voltages. An advantage of the linear rf octupole trap is its large almost-field-free region in the middle of the trap, where the micromotion amplitude is small for trapped ions. These results demonstrate that such a multipole trap has attractive features for quantum computing and ultracold ion-atom collision studies.
Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: the yeast proteome.

Highly complex protein mixtures can be directly analyzed after proteolysis by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). In this paper, we have utilized the combination of strong cation exchange (SCX) and reversed-phase (RP) chromatography to achieve two-dimensional separation prior to MS/MS. One milligram of whole yeast protein was proteolyzed and separated by SCX chromatography (2.1 mm i.d.) with fraction collection every minute during an 80-min elution. Eighty fractions were reduced in volume and then re-injected via an autosampler in an automated fashion using a vented-column (100 microm i.d.) approach for RP-LC-MS/MS analysis. More than 162,000 MS/MS spectra were collected with 26,815 matched to yeast peptides (7,537 unique peptides). A total of 1,504 yeast proteins were unambiguously identified in this single analysis. We present a comparison of this experiment with a previously published yeast proteome analysis by Yates and colleagues (Washburn, M. P.; Wolters, D.; Yates, J. R., III. Nat. Biotechnol. 2001, 19, 242-7). In addition, we report an in-depth analysis of the false-positive rates associated with peptide identification using the Sequest algorithm and a reversed yeast protein database. New criteria are proposed to decrease false-positives to less than 1% and to greatly reduce the need for manual interpretation while permitting more proteins to be identified.
Super-Resolution using Motion and Defocus Cues

Reconstruction-based super-resolution algorithms use either sub-pixel shifts or relative blur among low-resolution observations as a cue to obtain a high-resolution image. In this paper, we propose a super-resolution algorithm that exploits the information available in the low-resolution observations due to both sub-pixel shifts and relative blur to yield a better quality image. Performance analysis is carried out based on the Cramer-Rao lower bound. Several experimental results on synthetic and real images are given for validation.
Case study: visualizing sets of evolutionary trees

We describe a visualization tool which allows a biologist to explore a large set of hypothetical evolutionary trees. Interacting with such a dataset allows the biologist to identify distinct hypotheses about how different species or organisms evolved, which would not have been clear from traditional analyses. Our system integrates a point-set visualization of the distribution of hypothetical trees with detail views of an individual tree, or of a consensus tree summarizing a subset of trees. Efficient algorithms were required for the key tasks of computing distances between trees, finding consensus trees, and laying out the point-set visualization.
A Bag-of-Pages Approach to Unordered Multi-page Document Classification

We consider the problem of classifying documents containing multiple unordered pages. For this purpose, we propose a novel bag-of-pages document representation. To represent a document, one assigns every page to a prototype in a codebook of pages. This leads to a histogram representation which can then be fed to any discriminative classifier. We also consider several refinements over this initial approach. We show on two challenging datasets that the proposed approach significantly outperforms a baseline system.
A Simple Technique for High-Throughput Screening of Drugs That Modulate Normal and Psoriasis-Like Differentiation in Cultured Human Keratinocytes

Established treatments for psoriasis act ei-ther on hyperproliferation, inflammation, aberrant epidermal differentiation or a combination of these aspects of the disease. Potential new drugs for treatment of psoriasis or other disorders with abnormalities in epidermal differentiation can be identified by high-throughput screening of large compound libraries using surrogate markers for the disease. Here we describe a screening model to detect pharmacologically active drugs in two keratinocyte-based, 96-well culture models that use expression of cytokeratin 10 (CK10) and skin-derived antileucoprotease (SKALP)/elafin as markers for normal and psoriatic differentiation, respectively, and allow multiple parameters to be determined from a single well. In this model we tested a number of compounds in a pharmacological range from 10–7 to 10–5 M, including known antipsoriatic drugs, and experimental drugs that are potentially useful in the treatment of psoriasis. All-trans-retinoic acid, dithranol and the p38 mitogen-activated protein (MAP) kinase inhibitor SB220025 displayed a strong inhibitory effect on SKALP expression while cyclosporin A, dexamethasone, the vitamin D3 derivative calcipotriol and the p38 MAP kinase inhibitor SB203580 showed only moderate inhibition. Methotrexate and dimethylfumarate did not affect the expression of SKALP. With respect to CK10 expression, all-trans-retinoic acid, calcipotriol, SB203580 and SB220025 exhibited strong inhibition while dithranol showed only moderate suppression of this normal differentiation marker. Expression levels of CK10 were not significantly affected by dexamethasone, methotrexate, cyclosporin A or dimethylfumarate. This model system parallels most, but not all, findings on the in vitro effect of known antipsoriatic drugs on keratinocytes. In addition, the model identifies p38 MAP kinase inhibitors as potent suppressors of differentiation-associated gene expression. Although further delineation and validation of this model is required, we conclude that the system is amenable to down-scaling and application as a high-throughput screen for differentiation-modifying compounds.
Channel reliability metrics for flat Rayleigh fading channels without channel state information

In this work, iterative decoding of block turbo codes (BTCs) over flat Rayleigh fading channels is considered. The signal is modulated using binary phase shift keying (BPSK) and coherently detected. An exact channel reliability metric that should be passed to the iterative decoder to achieve optimum performance, when no channel state information (CSI) is available at the receiver, is developed. A low complexity cubic approximation to the exact metric, which has no performance loss, is presented. The numerical results obtained using (10, 9)/sup 2/ single parity check (SPC) BTC, show that the conventional approach, which uses a linear approximation to the channel reliability metric, results in a 27 dB penalty at BER of 10/sup -5/ compared to the case where perfect CSI is available. On the other hand, the use of the proposed reliability metric outperforms the existing metric and results in only a 1.1 dB performance loss at BER of 10/sup -5/ compared to the use of the metric when the CSI is perfectly known.
Learning to recognize patterns without a teacher

An important problem in pattern recognition or signal detection is the recognition of a pattern that is completely characterized statistically except for a finite set of unknown parameters. If a machine is required to solve such a problem on a number of occasions, it is possible to take advantage of this repetition. One can design a machine that will extract more and more of the pertinent information about these unknown parameters as it recognizes the patterns and readjusts itself to be more selective to them; the machine improves in performance as it gains experience on the problem. This paper presents a model suitable for many such problems and evolves a solution in the form of a machine that "learns" to solve the problem without external aid. Such machines are said to "learn without a teacher. " The Bayes solution to the model problem requires the computation of the a posteriori probability density of the unknown parameters. A recursive equation for this density is derived. This equation describes the structure of a relatively simple system of finite size that may be realized in a delay-feedback form. The application of the model and the synthesis of a learning system are illustrated by the derivation of a receiver for the detection of signals of unknown amplitude in white Gaussian noise.
Diffusion of Innovation Assessment of Adoption of the Dry Port Concept

Dry ports, when implemented effectively, reduce seaport congestion, improve seaport throughput and, due to the movement of containers from road to rail, reduce harmful emissions. This study investigates the implementation of dry ports at five U.S. seaports, which is then analysed considering the diffusion of innovation attributes. Data for the study was collected through face-to-face interviews at US East Coast seaports of Miami, Everglades, Jacksonville, Savannah and Charleston. To ensure validity, the triangulation of data sources was performed; i.e. a number of secondary sources were used, such as reports, internal and external documents, as well as site visits to the facilities. Three components have been recognized as key to the successful dry port concept: on/near-dock rail, reliable inland rail connection and a functional inland intermodal facility. These three components have a diverse group of stakeholders, many of whom are unknown to one another; however, when coordinated, they create the innovation of the dry port concept. If the attributes of successful innovations are understood, with respect to their influence specifically on dry ports, then they can be managed to contribute to the successful implementation of dry ports. The novelty of the research lies in its approach of using the diffusion of innovation attributes that have been historically proven to impact the adoption rates of innovations to provide insight into the adoption of the dry port concept.
A Topic-driven Summarization using K-mean Clustering and Tf-Isf Sentence Ranking

Enormous online information is available due to the World Wide Web. This needed efficient and accurate summarization systems to extract significant information. Text summarization system automatically generates a summary of a given document and helps people to make effective decisions in less time. In this paper two methods have been proposed for query-focused multi-document summarization that uses k-mean clustering, term-frequency and inversesentence-frequency method for sentence weighting to rank the sentences of the documents with respect to a given query. The proposed method finds the proximity of documents and query, and later uses this proximity to rank sentences of each document. It is assumed that the document which is nearer to a query might contain more meaning full sentences with respect to the information need expressed by user’s query further if a sentence contains rare query term than it is more informative than the sentences that contains frequent query term. Both methods first gives weights to documents according to their proximity and use these document weights to rank each of their sentences with tf-idf ranking function. A relative study for proposed methods has been done and experimental results shows that both methods are comparable because of a slight difference in performance. DUC 2007 test dataset and ROUGH-1.5. 5 summarization evaluation package is used for evaluation purpose.
Cholesterol-mediated regulation of angiogenesis: An emerging paradigm

Angiogenesis, the fundamental process that generates new blood vessels from parental vessels, is essential for embryogenesis and pathogenesis. A variety of underlying molecular and cellular mechanisms control angiogenesis. In this review, we focus on a unique mechanism of action – cholesterol-regulated angiogenesis. We will discuss lipoproteins, including low-density lipoprotein and high-density lipoprotein, cholesterol-rich lipid rafts/caveolae, apoA-I-binding protein (AIBP, also known as NAXE)-regulated cholesterol efflux, the effect of the hydroxycholesterol-activated nuclear receptor liver X receptor α/β on the proangiogenic vascular endothelial growth factor receptor 2 and antiangiogenic Notch signaling, and cholesterol-modified sonic hedgehog signaling. These pathways can be exploited, either alone or in conjunction with the currently available regimen for angiogenesis treatment, to control neovascularization in dyslipidemia. A treatment protocol for angiogenesis that takes into consideration cholesterol management might constitute an important component in precision and personalized medicine.
Dynamic queries and brushing on choropleth maps

Users who must combine demographic, economic or other data in a geographic context are often hampered by the integration of tabular and map representations. Static, paper-based solutions limit the amount of data that can be placed on a single map or table. By providing an effective user interface, we believe that researchers, journalists, teachers, and students can explore complex data sets more rapidly and effectively. This paper presents Dynamaps, a generalized map-based information visualization tool for dynamic queries and brushing on choropleth maps. Users can use color coding to show a variable on each geographic region, and then filter out areas that do not meet the desired criteria. In addition, a scatterplot view and a details-on-demand window support overviews and specific fact-finding.
The mesh is a network of microtubule connectors that stabilizes individual kinetochore fibers of the mitotic spindle

Kinetochore fibers (K-fibers) of the mitotic spindle are force-generating units that power chromosome movement during mitosis. K-fibers are composed of many microtubules that are held together throughout their length. Here, we show, using 3D electron microscopy, that K-fiber microtubules (MTs) are connected by a network of MT connectors. We term this network ‘the mesh’. The K-fiber mesh is made of linked multipolar connectors. Each connector has up to four struts, so that a single connector can link up to four MTs. Molecular manipulation of the mesh by overexpression of TACC3 causes disorganization of the K-fiber MTs. Optimal stabilization of K-fibers by the mesh is required for normal progression through mitosis. We propose that the mesh stabilizes K-fibers by pulling MTs together and thereby maintaining the integrity of the fiber. Our work thus identifies the K-fiber meshwork of linked multipolar connectors as a key integrator and determinant of K-fiber structure and function. DOI: http://dx.doi. org/10.7554/eLife.07635. 001
Constructing the Energy Landscape for Genetic Switching System Driven by Intrinsic Noise

Genetic switching driven by noise is a fundamental cellular process in genetic regulatory networks. Quantitatively characterizing this switching and its fluctuation properties is a key problem in computational biology. With an autoregulatory dimer model as a specific example, we design a general methodology to quantitatively understand the metastability of gene regulatory system perturbed by intrinsic noise. Based on the large deviation theory, we develop new analytical techniques to describe and calculate the optimal transition paths between the on and off states. We also construct the global quasi-potential energy landscape for the dimer model. From the obtained quasi-potential, we can extract quantitative results such as the stationary distributions of mRNA, protein and dimer, the noise strength of the expression state, and the mean switching time starting from either stable state. In the final stage, we apply this procedure to a transcriptional cascades model. Our results suggest that the quasi-potential energy landscape and the proposed methodology are general to understand the metastability in other biological systems with intrinsic noise.
A Comparative Study on the Association of Labour process with Oxidative stress in Normal and Preeclamptic mothers

Oxidative stress plays an important role in the pathophysiology of preeclampsia. An increase in lipid peroxidation and decrease in antioxidant activity in preeclamptic women with hypertension have been reported. The present contribution aimed to understand the effect of labour on the levels of free radicals in normotesive pregnant mothers (control group) and hypertensive preeclamptic mothers. Serum MDA (Malondialdehyde) is used as a marker of oxidative stress mediated changes in the study subjects and the levels of enzymatic antioxidants viz SOD, GRx, GPx in the arterial blood (before delivery) and in cord blood are estimated. The results indicate that in hypertensive preeclamptic mothers, there is a significant (p<0.001) increase in the levels of serum MDA and a significant (p<0.001) decrease in the levels of antioxidant enzymes in cord blood when compared to control groups. This is attributed to the oxidative stress during labour pain. Hence it is inferred that antioxidant supplementation during pregnancy could prevent oxidative stress mediated changes to cell and biomolecules during the gestational period.
ISS-N1 makes the First FDA-approved Drug for Spinal Muscular Atrophy

Abstract Spinal muscular atrophy (SMA) is one of the leading genetic diseases of children and infants. SMA is caused by deletions or mutations of Survival Motor Neuron 1 (SMN1) gene. SMN2, a nearly identical copy of SMN1, cannot compensate for the loss of SMN1 due to predominant skipping of exon 7. While various regulatory elements that modulate SMN2 exon 7 splicing have been proposed, intronic splicing silencer N1 (ISS-N1) has emerged as the most promising target thus far for antisense oligonucleotide-mediated splicing correction in SMA. Upon procuring exclusive license from the University of Massachussets Medical School in 2010, Ionis Pharmaceuticals (formerly ISIS Pharamaceuticals) began clinical development of Spinraza™ (synonyms: Nusinersen, IONIS-SMNRX, ISIS-SMNRX), an antisense drug based on ISS-N1 target. Spinraza™ showed very promising results at all steps of the clinical development and was approved by US Food and Drug Administration (FDA) on December 23, 2016. Spinraza™ is the first FDA-approved treatment for SMA and the first antisense drug to restore expression of a fully functional protein via splicing correction. The success of Spinraza™ underscores the potential of intronic sequences as promising therapeutic targets and sets the stage for further improvement of antisense drugs based on advanced oligonucleotide chemistries and delivery protocols.
Mixed Reality TVs: Applying Motion Parallax for Enhanced Viewing and Control Experiences on Consumer TVs

Smart TVs have been popularized in the last years, presenting continued innovation regarding different topics such as connectivity, platform support, and options for interaction. Examples of LG and Samsung present interaction options such as voice and gesture control, showing these emerging technologies that were previously tackled mainly on research investigations, as market alternative solutions for the already established remote control. In this paper, we address the interactivity with Smart TVs by using body gestures combined with the visualization modification through the Motion Parallax effect. We show that by tracking the user viewpoint and hand tips, plus applying the Parallax effect, it is possible to fully calibrate the virtual environment demonstrated by the TV with the real world. Once the calibration is performed, the TV becomes a Mixed Reality display, showing its content coupled with the real world, and allowing the user to perceive this coupling through the depth cue provided by the distortions of the Parallax effect. This calibration enables the use of a set of interaction techniques such as enabling the user to visually pinpoint and touch the virtual items of a TV menu. Moreover, we show that by modeling the interaction with the TV content as a 3D virtual world interaction, it is possible to use new metaphors based on physical interactions such as collisions, lights and shadows and magnetic attractions.
Consensus over Weighted Directed Graphs: A Robustness Perspective

The present paper investigates the robustness of the consensus protocol over weighted directed graphs using the Nyquist criterion. The limit to which a single weight can vary, while consensus among the agents can be achieved, is explicitly derived. It is shown that even with a negative weight on one of the edges, consensus may be achieved. The result obtained in this paper is applied to a directed acyclic graph and to the directed cycle graph. Graph theoretic interpretations of the limits are provided for the two cases. Simulations support the theoretical results.