Miracle-dz/UniFAR-FTUs huggingface dataset:
A preliminary study of the 29 June tornadic storm during STEPS

Preliminary results from observations of a severe thunderstorm near Bird City, Kansas on 29 June 2000 during the Severe Thunderstorm Electrification and Precipitation Study (STEPS) are presented. Storm characteristics included large hail, frequent positive cloud-to-ground lightning, and an F1 tornado. The tornado was present for the period 2328-2344 UTC. Analysis of single radar measurements of reflectivity and radial velocity showed that the storm formed ahead of an advancing surface boundary and turned right near the time that it became tornadic and electrically active. A noteworthy tornadic vortex signature and mesocyclone were observed, even though a well-defined hook echo (often interpreted as an indicator of tornadic potential) was missing. Triple-Doppler wind synthesis was employed for five storm-volume scans for the period 2305-2343 UTC. Three-dimensional wind fields indicated that this storm had a sequence of small, but intense, updrafts that followed a larger-scale, quasi-steady path that entered the storm on the southwest flank, ascended through the storm turning anticyclonically, and exited into the anvil on the northeast flank. This quasi-steady airflow with embedded updrafts (a distinctly multicellular behavior) of some so-called supercells has been documented in the literature and is discussed herein. At times, the storm exhibited weak echo regions coincident with updrafts, and there is evidence that a rear-flank downdraft was present. When compared to previous classification criteria, this storm resembled a “classic” supercell for only a short period, but rather it exhibited characteristics across several regimes throughout its lifetime. This work was done under the auspices of the Significant Opportunities in Atmospheric Research and Science program of the University Corporation for Atmospheric Research, with funding from the National Science Foundation, the U.S. Department of Energy, the National Oceanic and Atmospheric Administration, the Cooperative Institute for Research in Environmental Sciences, and the National Aeronautic and Space Administration. SOARS is a registered trademark of the University Corporation for Atmospheric Research. SOARS 2001, Sarah Tessendorf 1
LEARNING BAYESIAN BELIEF NETWORKS: AN APPROACH BASED ON THE MDL PRINCIPLE

A new approach for learning Bayesian belief networks from raw data is presented. The approach is based on Rissanen's minimal description length (MDL) principle, which is particularly well suited for this task. Our approach does not require any prior assumptions about the distribution being learned. In particular, our method can learn unrestricted multiply‐connected belief networks. Furthermore, unlike other approaches our method allows us to trade off accuracy and complexity in the learned model. This is important since if the learned model is very complex (highly connected) it can be conceptually and computationally intractable. In such a case it would be preferable to use a simpler model even if it is less accurate. The MDL principle offers a reasoned method for making this trade‐off. We also show that our method generalizes previous approaches based on Kullback cross‐entropy. Experiments have been conducted to demonstrate the feasibility of the approach.
Chromatin and genomic determinants of alternative splicing

Alternative splicing significantly contributes to proteomic diversity and mis-regulation of splicing can cause diseases in human. Although both genomic and chromatin features have been shown to associate with splicing, the mechanisms by which various chromatin marks influence splicing is not clear for the most part. Moreover, it is not known whether the influence of specific genomic features on splicing is potentially modulated by the chromatin context. Here we report a deep neural network (DNN) model for predicting exon inclusion based on comprehensive genomic and chromatin features. Our analysis in three cell lines shows that, while both genomic and chromatin features can predict splicing to varying degrees, genomic features are the primary drivers of splicing, and the predictive power of chromatin features can largely be explained by their correlation with genomic features; chromatin features do not yield substantial independent contribution to splicing predictability. However, our model identified specific interactions between chromatin and genomic features suggesting that the effect of genomic elements may be modulated by chromatin context.
The QoSbox: A PC-Router for Quantitative Service Differentiation in IP Networks

We describe the design and implementation in UNIX-based PCs of the QoSbox, a configurable IP router that provides per-hop service guarantees on loss, delays and throughput to classes of traffic. There is no restriction on the number of classes or the specific service guarantees each class obtains. The novel aspects of the QoSbox are that (1) the QoSbox does not rely on any external component (e.g., no traffic shaping and no admission control) to enforce the desired service guarantees, but instead, (2) dynamically adapts packet forwarding and dropping decisions as a function of the instantaneous traffic arrivals; also, (3) the QoSbox can enforce both absolute bounds and proportional service guarantees on queueing delays, loss rates, and throughput at the same time. We evaluate the QoSbox in a testbed of PC-routers over a FastEthernet network, and show that the QoSbox is a possible solution allowing for incremental deployment to the problem of providing service differentiation in a scalable manner.
Indian Statistical Institute Kolkata at PR-SOCO 2016: A Simple Linear Regression Based Approach

We participated in the PR-SOCO task hosted in FIRE 2016 and tried some basic approaches which we look to improve in the future. We defined some simple features from the source code which, in our opinion, were indicative of the manner in which the code was written and which might give some clues about the personality of the programmer. We built a multiple linear regression model from the training data and applied this model on the test data. The results show that our method produces good prediction performances for Neuroticism, Extroversion and Openness.
A Geoweb-Based Tagging System for Borderlands Data Acquisition

Borderlands modeling and understanding depend on both spatial and non-spatial data, which were difficult to obtain in the past. This has limited the progress of borderland-related research. In recent years, data collection technologies have developed greatly, especially geospatial Web 2.0 technologies including blogs, publish/subscribe, mashups, and GeoRSS, which provide opportunities for data acquisition in borderland areas. This paper introduces the design and development of a Geoweb-based tagging system that enables users to tag and edit geographical information. We first establish the GeoBlog model, which consists of a set of geospatial components, posts, indicators, and comments, as the foundation of the tagging system. GeoBlog is implemented such that blogs are mashed up with OpenStreetMap. Moreover, we present an improvement to existing publish/subscribe systems with support for spatio-temporal events and subscriptions, called Spatial Publish/Subscribe, as well as the event agency network for routing messages from the publishers to the subscribers. A prototype system based on this approach is implemented in experiments. The results of this study provide an approach for asynchronous interaction and message-ordered transfer in the tagging system.
Image transmission over the polya channel via channel-optimized quantization

We introduce two progressive methods for image transmission over binary channels with additive bursty noise modeled by the finite-memory Polya (contagion) channel. The methods, which are based on channel-optimized scalar quantization (COSQ) of the wavelet transform coefficients, exploit channel memory to offer superior performance over a number of more complex systems designed for the fully interleaved channel.
Experimental Atrial Septal Defect Closure With a New, Transcatheter, Self‐Centering Device

BackgroundDespite two decades of research, a transcatheter atrial septal defect closure device is not available for clinical use. We have designed a new superelastic Nitinol-Dacron, double-disk, selfcentering, atrial septal defect closure device and studied its efflicacy in a canine model of atrial septal defects. Methods and ResultsAtrial septal defects were created surgically in 20 adult dogs using either a 7.5-mm or 10-mm punch. Percutaneous transcatheter closures were attempted using a new device. The device sizes used were 20 mm in 6 dogs, 22 mm in 9, and 25 mm in 5 (22.1±1.9 mm, mean±SD). The stretched atrial septal defect diameter was 10.5±13 mm, and the device to stretched atrial septal defect diameter ratio was 2.1±03. Closures were successful in 19 studies and unsuccessful in 1. Angiography showed a left-to-right shunt in all 20 dogs before closure. Immediately after closure (n= 19), there were no shunts in 17 and trivial shunts in 2. Six dogs were followed for a period of 4.7±3.0 months (range, 2 to 8 months). The trivial shunt present in 1 animal immediately after closure had closed by the time of the repeat study. Spontaneous embolization of the device was not seen during follow-up. A solitary wire fracture was found 8 months after closure in 1 device. Light microscopy at 8 weeks in 3 dogs showed the devices to be covered by smooth endocardium, enmeshed in mature collagen tissue, with a minimal mononuclear cell infiltration. Retrievability was assessed by deliberately embolizing 4 devices in 2 dogs into the right atrium (n=l) and pulmonary artery (n=3). All devices were successfully retrieved with a snare.Concusions. This feasibility study demonstrates that this new self-centering atrial septal defect closure device has a number of design features that permit effective and safe closures in a canine model. These results support the investigation of this device in human clinical trials.
GSearcher: Agile Attribute Querying for Biological Networks

Summary: GSearcher provides a highly interactive user experience in navigating attribute data associated with large and complex biological networks. The user may either perform a quick search using keywords, phrases or regular expressions, or build a complex query with a group of filters for efficient and flexible exploration of large datasets. Availability: http://brainarray.mbni. med.umich.edu/gsearcher/ Contact: sugang@umich.edu
Dependency Treebank of Urdu and its Evaluation

In this paper we describe a currently underway treebanking effort for Urdu-a South Asian language. The treebank is built from a newspaper corpus and uses a Karaka based grammatical framework inspired by Paninian grammatical theory. Thus far 3366 sentences (0.1M words) have been annotated with the linguistic information at morpho-syntactic (morphological, part-of-speech and chunk information) and syntactico-semantic (dependency) levels. This work also aims to evaluate the correctness or reliability of this manual annotated dependency treebank. Evaluation is done by measuring the inter-annotator agreement on a manually annotated data set of 196 sentences (5600 words) annotated by two annotators. We present the qualitative analysis of the agreement statistics and identify the possible reasons for the disagreement between the annotators. We also show the syntactic annotation of some constructions specific to Urdu like Ezafe and discuss the problem of word segmentation (tokenization).
Body weight supported treadmill training at very low treatment frequency for a young adult with incomplete cervical spinal cord injury.

INTRODUCTION Body weight supported treadmill training (BWSTT) using high treatment frequency has been shown to improve gait after spinal cord injury (SCI). This case report describes the use of BWSTT at a very low treatment frequency. SUBJECT The subject was a 19 y.o. female with an incomplete C6 SCI, one year post-injury, with multiple gait deficits. INTERVENTION BWSTT was combined with conventional rehabilitation. Mean treatment frequency was 1.16 days/wk over 28.5 wks. A BWSTT progression algorithm based on observational gait analysis guided progressive changes in support levels, treadmill speed, and session length. OUTCOMES During the first 3 sessions, the subject tolerated an average of 15.7 minutes of BWSTT with 26% BWS at 0.8 m/s, improving to an average of 28 minutes of BWSTT with 10% BWS at 1.6 m/s in the last 3 sessions. Following 28.5 wks of very low frequency BWSTT, the subject displayed improved kinematics, walking speed, endurance, and distance during overground gait. CONCLUSION Very low frequency BWSTT combined with conventional treatment improved quality and endurance of walking for a person with incomplete cervical SCI. Further work is needed to evaluate the long-term outcome of very low frequency BWSTT and the interaction of BWSTT with other interventions.
A Non-convex One-Pass Framework for Generalized Factorization Machine and Rank-One Matrix Sensing

We develop an efficient alternating framework for learning a generalized version of Factorization Machine (gFM) on steaming data with provable guarantees. When the instances are sampled from $d$ dimensional random Gaussian vectors and the target second order coefficient matrix in gFM is of rank $k$, our algorithm converges linearly, achieves $O(\epsilon)$ recovery error after retrieving $O(k^{3}d\log(1/\epsilon))$ training instances, consumes $O(kd)$ memory in one-pass of dataset and only requires matrix-vector product operations in each iteration. The key ingredient of our framework is a construction of an estimation sequence endowed with a so-called Conditionally Independent RIP condition (CI-RIP). As special cases of gFM, our framework can be applied to symmetric or asymmetric rank-one matrix sensing problems, such as inductive matrix completion and phase retrieval.
Development of a Quantitative Assay for Mycobacterial Endogenous Arabinase and Ensuing Studies of Arabinase Levels and Arabinan Metabolism in Mycobacterium smegmatis

ABSTRACT Treatment of either Mycobacterium tuberculosis or M. smegmatis with ethambutol results both in inhibition of arabinan synthesis and in copious loss of previously formed arabinan from the cell wall. The loss of arabinan has been shown to be due to the action of an endogenous arabinase. To better understand this phenomenon, a quantitative assay for endogenous arabinase was developed. Using the assay it was determined that various subcellular fractions of M. smegmatis showed significant amounts of endogenous arabinase activity. Surprisingly, treatment with ethambutol yielded only minor changes in the amounts of endogenous arabinase activities. Endogenous arabinase was present in the cell wall, and consistently, incubation of the M. smegmatis cell wall in only buffer resulted in the release of arabinan, mimicking the effect of ethambutol on whole cells. To determine if cell wall arabinan is rapidly turned over, the arabinan was labeled in the early log phase of culture by feeding [14C]glucose, followed by a “chase” with nonradioactive glucose. Most of the labeled arabinan remained in the cell wall after the culture was grown to late log phase. Thus, there is active arabinase in the cell wall, but arabinan is not rapidly removed unless ethambutol is present. Purification of the endogenous arabinase, using the assay described, is ongoing to help further discern its biological function.
Spectral Compressed Sensing via Structured Matrix Completion

The paper studies the problem of recovering a spectrally sparse object from a small number of time domain samples. Specifically, the object of interest with ambient dimension $n$ is assumed to be a mixture of $r$ complex multi-dimensional sinusoids, while the underlying frequencies can assume any value in the unit disk. Conventional compressed sensing paradigms suffer from the {\em basis mismatch} issue when imposing a discrete dictionary on the Fourier representation. To address this problem, we develop a novel nonparametric algorithm, called enhanced matrix completion (EMaC), based on structured matrix completion. The algorithm starts by arranging the data into a low-rank enhanced form with multi-fold Hankel structure, then attempts recovery via nuclear norm minimization. Under mild incoherence conditions, EMaC allows perfect recovery as soon as the number of samples exceeds the order of $\mathcal{O}(r\log^{2} n)$. We also show that, in many instances, accurate completion of a low-rank multi-fold Hankel matrix is possible when the number of observed entries is proportional to the information theoretical limits (except for a logarithmic gap). The robustness of EMaC against bounded noise and its applicability to super resolution are further demonstrated by numerical experiments.
A thermally-aware performance analysis of vertically integrated (3-D) processor-memory hierarchy

Three-dimensional (3D) integrated circuits have emerged as promising candidates to overcome the interconnect bottlenecks of nanometer scale designs. While they offer several other advantages, it is expected that the benefits from this technology can potentially be off-set by thermal considerations which impact chip performance and reliability. The work presented in this paper is the first attempt to study the performance benefits of 3D technology under the influence of such thermal constraints. Using a processor-cache-memory system and carefully chosen applications encompassing different memory behaviors, the performance of 3D architecture is compared with a conventional planar (2D) design. It is found that the substantial increase in memory bus frequency and bus width contribute to a significant reduction in execution time with a 3D design. It is also found that increasing the clock frequency translates into larger gains in system performance with 3D designs than for planar 2D designs in memory intensive applications. The thermal profile of the vertically stacked chip is generated taking into account the highly temperature sensitive leakage power dissipation. The maximum allowed operating frequency imposed by temperature constraint is shown to be lower for 3D than for 2D designs. In spite of these constraints, it is shown that the 3D system registers large performance improvement for memory intensive applications
Evaluation of pairwise calibration techniques for range cameras and their ability to detect a misalignment

Many applications require the use of multiple cameras to cover a large volume. In this paper, we evaluate several pairwise calibration techniques dedicated to multiple range cameras. We compare the precision of a self-calibration technique based on the movement in front of the cameras to object based calibration. While the self-calibration technique is less precise than its counterparts, it yields a first estimation of the transformation between the cameras and permits to detect when the cameras become mis-aligned. Therefore, this technique is useful in a practical situations.
An ontology-based mining approach for user search intent discovery

Discovering proper search intents is a vital process to return desired results. It is constantly a hot research topic regarding information retrieval in recent years. Existing methods are mainly limited by utilizing context-based mining, query expansion, and user profiling techniques, which are still suffering from the issue of ambiguity in search queries. In this paper, we introduce a novel ontology-based approach in terms of a world knowledge base in order to construct personalized ontologies for identifying adequate concept levels for matching user search intents. An iterative mining algorithm is designed for evaluating potential intents level by level until meeting the best result. The propose-to-attempt approach is evaluated in a large volume RCV1 data set, and experimental results indicate a distinct improvement on top precision after compared with baseline models.
Inhibitor binding in a class 2 dihydroorotate dehydrogenase causes variations in the membrane‐associated N‐terminal domain

The flavin enzyme dihydroorotate dehydrogenase (DHOD; EC 1.3.99.11) catalyzes the oxidation of dihydroorotate to orotate, the fourth step in the de novo pyrimidine biosynthesis of UMP. The enzyme is a promising target for drug design in different biological and clinical applications for cancer and arthritis. The first crystal structure of the class 2 dihydroorotate dehydrogenase from rat has been determined in complex with its two inhibitors brequinar and atovaquone. These inhibitors have shown promising results as anti‐proliferative, immunosuppressive, and antiparasitic agents. A unique feature of the class 2 DHODs is their N‐terminal extension, which folds into a separate domain comprising two α‐helices. This domain serves as the binding site for the two inhibitors and the respiratory quinones acting as the second substrate for the class 2 DHODs. The orientation of the first N‐terminal helix is very different in the two complexes of rat DHOD (DHODR). Binding of atovaquone causes a 12 Å movement of the first residue in the first α‐helix. Based on the information from the two structures of DHODR, a model for binding of the quinone and the residues important for the interactions could be defined. His 56 and Arg 136, which are fully conserved in all class 2 DHODs, seem to play a key role in the interaction with the electron acceptor. The differences between the membrane‐bound rat DHOD and membrane‐associated class 2 DHODs exemplified by the Escherichia coli DHOD has been investigated by GRID computations of the hydrophobic probes predicted to interact with the membrane.
Visual Methods

Traditional guest feedback methods such as surveys or mystery shopping are not ideal for collecting information about customers' reactions to a hotel's physical design. Because design is a visual medium, survey questions may not capture the whole of a guest's reaction to the design. By the same token, the reaction of mystery shoppers to design is not necessarily representative of all guests. Instead, a photography-based approach allows guests to show managers and researchers what they consider to be the hotel's design highlights and failures. A pilot study indicated that guests took notice of design elements that signified that the hotel was being considerate of their needs, as well as providing a functional, high-quality environment.
Effects of Plastic Mulch on Soil Heat Flux and Energy Balance in a Cotton Field in Northwest China

Surface energy balance (SEB) is a basic principle for all of the atmospheric circulation models, and surface soil heat flux (G0) is an important component of energy balance. Plastic mulch is widely used in arid regions and alters land surface processes. In this study, hourly/daily G0 and SEB over a mulched cotton field were analyzed in Northwest China. The net radiation beneath the mulch was simulated using transmitted down short-wave and down long-wave radiation through the mulch and up short-wave and up long-wave radiation from the soil beneath mulch. The results show that: (1) on the hourly time scale, G0 in mulched soil is much smaller than that in non-mulched soil, day and night. This implies that mulch prevents energy going into the soil during the daytime and reduces soil heat loss at night. On the daily time scale, G0 is similar in mulched and non-mulched soil. (2) During the seedling emergence period when the cotton is small, the energy balance closure over mulched soil (0.79) is slightly smaller than that over non-mulched soil (0.81). (3) Comparing to soil temperature in non-mulched soil, there’s a time offset on soil temperature in mulched soil at the same depth, which will bring a hysteresis on G0 and SEB.