Miracle-dz/UniFAR-FTUs huggingface dataset:
Calving controlled by melt-under-cutting: detailed calving styles revealed through time-lapse observations

Abstract We present a highly detailed study of calving dynamics at Tunabreen, a tidewater glacier in Svalbard. A time-lapse camera was trained on the terminus and programmed to capture images every 3 seconds over a 28-hour period in August 2015, producing a highly detailed record of 34 117 images from which 358 individual calving events were distinguished. Calving activity is characterised by frequent events (12.8 events h−1) that are small relative to the spectrum of calving events observed, demonstrating the prevalence of small-scale calving mechanisms. Five calving styles were observed, with a high proportion of calving events (82%) originating at, or above, the waterline. The tidal cycle plays a key role in the timing of calving events, with 68% occurring on the falling limb of the tide. Calving activity is concentrated where meltwater plumes surface at the glacier front, and a ~ 5 m undercut at the base of the glacier suggests that meltwater plumes encourage melt-under-cutting. We conclude that frontal ablation at Tunabreen may be paced by submarine melt rates, as suggested from similar observations at glaciers in Svalbard and Alaska. Using submarine melt rate to calculate frontal ablation would greatly simplify estimations of tidewater glacier losses in prognostic models.
An automated management tool for unstructured data

The rapidly growing quantity of online data has created a need for automated, content-based categorization and search tools. We describe an open-source, Web-based archive management, which uses latent semantic indexing, coupled with vector clustering techniques, to provide users with a fully searchable and automatically categorized interface to a data collection. The default English document parser included in the project uses part-of-speech tagging and recursive maximal noun phrase extraction to create a more effective term list for LSI than traditional stop list techniques. The archive interface supports multiple user views of the data collection. Advanced search features are implemented through relevance feedback, and do not require users to learn a query syntax.
Molecularly ordered decanethiolate self-assembled monolayers on Au(111) from in situ cleaved decanethioacetate: an NMR and STM study of the efficacy of reagents for thioacetate cleavage.

The cleavage of decanethioacetate (C10SAc) has been studied by (1)H nuclear magnetic resonance (NMR) spectroscopy and scanning tunneling microscopy (STM) imaging of in situ prepared decanethiolate self-assembled monolayers (SAMs) on Au(111). Solutions of C10SAc (46 mM) and previously reported cleavage reagents (typically 58 mM) in CD(3)OD were monitored at 20 degrees C by NMR spectroscopy. Cleavage by ammonium hydroxide, propylamine, or hydrochloric acid was not complete within 48 h; cleavage by potassium carbonate was complete within 24 h and that by potassium hydroxide or 1,8-diazabicyclo[5.4. 0]undec-7-ene (DBU) within 2 h. Similar cleavage rates were observed for phenylthioacetate. The degree of molecular ordering determined by STM imaging increased with increasing extent of in situ cleavage by these same reagents (2.5 mM C10SAc and 2.5 mM reagent in ethanol for 1 h, then 16 h immersion of Au/mica). Less effective cleavage reagents did not cleave the C10SAc sufficiently to decanethiol (C10SH) and gave mostly disordered SAMs. In contrast, KOH or DBU completely cleaved the C10SAc to C10SH and led to well-ordered SAMs composed of (square root(3) x square root(3))R30 degrees domains that are indistinguishable from SAMs grown from C10SH. Monolayer formation from thioacetates in the absence of cleavage agents is likely due to thiol or disulfide impurity in the thioacetates. Eliminating disulfide by using Bu(3)P as a sacrificial reductant also helped to produce good molecular order in the SAM. The methods presented here allow routine growth of molecularly ordered alkanethiolate SAMs from thioacetates using reagents of ordinary purity under ambient, benchtop conditions.
Comparison of rectal swabs and stool cultures in detecting Campylobacter fetus subsp. jejuni

Rectal swabs and stool specimens were compared for the detection of Campylobacter fetus subsp. jejuni in marmosets. Rectal swabs were superior to stool specimens for detection of Campylobacter fetus subsp. jejuni (P = 0.016). Preliminary human data are also presented.
On Cold Pool Collisions in Tropical Boundary Layers

Collisions between cold pools are generally acknowledged to be important processes through which new convective cells are triggered. Yet relatively little has been done to characterize these processes in detail, quantify their impact on the life cycle of cold pools, and include them in convective parameterizations. We use a combination of Eulerian and Lagrangian models to investigate how much cold pools are affected by collisions. Results from simulations in radiative‐convective equilibrium suggest that collisions represent a first‐order process in the dynamics of cold pools, the median time of first collision being under 10 min since cold pool birth. Through a Lagrangian tracking algorithm, it is also shown that cold pools are significantly deformed by collisions and lose the circular shapes they would have if in isolation only a few minutes after birth. Finally, it is suggested that cold pools happen in clusters, and associated spatial and temporal scales are presented.
A Fast Accurate Two-stage Training Algorithm for L1-regularized CRFs with Heuristic Line Search Strategy

Sparse learning framework, which is very popular in the field of nature language processing recently due to the advantages of efficiency and generalizability, can be applied to Conditional Random Fields (CRFs) with L1 regularization method. Stochastic gradient descent (SGD) method has been used in training L1-regularized CRFs, because it often requires much less training time than the batch training algorithm like quasi-Newton method in practice. Nevertheless, SGD method sometimes fails to converge to the optimum, and it can be very sensitive to the learning rate parameter settings. We present a two-stage training algorithm which guarantees the convergence, and use heuristic line search strategy to make the first stage of SGD training process more robust and stable. Experimental evaluations on Chinese word segmentation and name entity recognition tasks demonstrate that our method can produce more accurate and compact model with less training time for L1 regularization.
First spectroscopy of the 1S0 →3P0 transition in Lamb-Dicke confined magnesium atoms

104 magnesium atoms have been trapped in an optical lattice at the predicted magic wavelength of 469 nm. The trap depth of the lattice sites is 16 Er corresponding to a Lamb-Dicke parameter of η = 0.51. The temperature of atoms in the lattice is 10 μK. We performed magnetic field-induced spectroscopy on the strongly spin-forbidden clock transition and observed for the first time a 50 kHz broad carrier signal together with a 80 kHz broad red sideband.
Transmission network expansion planning based on coordinated economy and security

Transmission network expansion planning (TNEP) is a key component of power system planning. Two important aspects to be considered in TNEP are economy and security factors, which are always contradictory and affect the benefits of both investment and power demand side, so the balance between these two factors needs to be focused. In this paper, a TNEP model based on coordinated economy and security is proposed so as to reconcile these two contradictory factors. The objective function of proposed TNEP model is to minimize the annual synthetic cost of transmission system, which contains investment cost, operation cost, maintenance cost and load shedding cost. The annual synthetic cost of transmission system is calculated with multistep load model established by load clustering using improved K-means algorithm. Then, an improved niche genetic algorithm is utilized to solve the TNEP model and an optimal scheme is obtained. Furthermore, the applicability and effectiveness of proposed TNEP model and algorithm are verified by case study on IEEE 24-bus system.
Multilayered metamaterials for Silicon MMIC applications

A multilayered fully integrated left-handed coplanar waveguide metamaterial medium for high resistivity Silicon MMIC applications is presented for the first time. The left-handedness of the structure is validated by full wave simulation and measurement results, showing left-handed bandwidth from 2.8 GHz to 15.26 GHz. The reported multilayered structure consists of six left-handed unit cells and has a size of 1.81 mm2. The super compactness of the structure makes this multilayer technique well suited to RF/microwave MMIC fabrication.
A Proposal for Network Coding with the IEEE 802.15.6 Standard

We examine the Medium Access Control sublayer of the IEEE 802.15. 6 Wireless Body Area Network (WBAN) standard, and propose minor modifications to the standard so that linear random network coding can be included to help improve energy efficiency and throughput of WBANs compatible with the standard. Both generation-based and sliding window approaches are possible, and a group-block acknowledgment scheme can be implemented by modifying block acknowledgment control type frames. Discussions on potential energy and throughput advantages of network coding are provided.
uCache: A Utility-Aware Multilevel SSD Cache Management Policy

SSD is widely adopted as a cache device thanks to its fast data access and large capacity. In order to complement DRAM-based cache, SSD can serve as a second level cache to form a multilevel cache together with DRAM. However, the inherent features of SSD, such as limited lifetime and slow small writes, make it non-trivial to design a multilevel SSD cache management policy. Traditional DRAM-based cache policies mainly target single level cache, while current SSD cache policies mainly focus on increasing SSD lifetime. In this paper, we propose a utility-aware multilevel SSD cache policy uCache. At the DRAM level, uCache employs a filter to figure out suitable data for SSD caching, and meanwhile uses a buffer to aggregate small writes into large writes. As suitable data blocks are filtered out to enter to SSD, at the SSD level, uCache simply uses LRU to manage cached content. The experimental evaluation shows that uCache can effectively reduce unnecessary writes and avoid slow small writes. Compared to LIRS and Sieve Store, uCache achieves higher utility of SSD in a two-level cache.
High data rate ultrasonic communications for wireless intra-body networks

It is well known that electromagnetic radio-frequency (RF) waves that are the basis of most commercial wireless technologies are largely unsuitable to interconnect deeply implanted medical devices. RF waves are in fact absorbed by aqueous biological tissues and prone to malicious jamming attacks or to environmental interference from pervasively deployed RF communication systems; moreover, they pose a potential safety hazard when exposure of tissues is prolonged and at high power. While existing wireless technologies can satisfy the requirements of some specific applications, the root challenge of enabling networked intra-body miniaturized sensors and actuators that communicate through body tissues is largely unaddressed. Considering these limitations, this article proposes a high data rate ultrasonic communication scheme for wireless intra-body networks. The proposed scheme can enable various applications that require high sampling rates such as neural data recording or monitoring of the digestive tract through endoscopic pills. The proposed scheme is based on Orthogonal Frequency-Division Multiplexing (OFDM), which is proven to be robust against frequency-selective channels with relatively long delay spreads like the intra-body ultrasonic channel. The proposed scheme is implemented in a prototype ultrasonic software-radio and demonstrated to achieve data rates up to 28.12 Mbit/s through synthetic phantoms mimicking the ultrasonic propagation characteristics of biological tissues.
Secure and Reliable IPTV Multimedia Transmission Using Forward Error Correction

With the wide deployment of Internet Protocol (IP) infrastructure and rapid development of digital technologies, Internet Protocol Television (IPTV) has emerged as one of the major multimedia access techniques. A general IPTV transmission system employs both encryption and forward error correction (FEC) to provide the authorized subscriber with a high-quality perceptual experience. This two-layer processing, however, complicates the system design in terms of computational cost and management cost. In this paper, we propose a novel FEC scheme to ensure the secure and reliable transmission for IPTV multimedia content and services. The proposed secure FEC utilizes the characteristics of FEC including the FEC-encoded redundancies and the limitation of error correction capacity to protect the multimedia packets against the malicious attacks and data transmission errors/losses. Experimental results demonstrate that the proposed scheme obtains similar performance compared with the joint encryption and FEC scheme.
Voltage Island Aware Floorplanning for Power and Timing Optimization

Power consumption is a crucial concern in nanometer chip design. Researchers have shown that multiple supply voltage (MSV) is an effective method for power consumption reduction. The underlying idea behind MSV is the trade-off between power saving and performance. In this paper, we present an effective voltage assignment technique based on dynamic programming. Given a netlist without reconvergent fanouts, the dynamic programming can guarantee an optimal solution for the voltage assignment. We then generate a level shifter for each net that connects two blocks in different voltage domains, and perform power-network aware floorplanning for the MSV design. Experimental results show that our floorplanner is very effective in optimizing power consumption under timing constraints
Dynamic Analyses of Information Encoding in Neural Ensembles

Neural spike train decoding algorithms and techniques to compute Shan-non mutual information are important methods for analyzing how neural systems represent biological signals. Decoding algorithms are also one of several strategies being used to design controls for brain-machine inter-faces. Developing optimal strategies to desig n decoding algorithms and compute mutual information are therefore important problems in com-putational neuroscience. We present a general recursive filter decoding algorithm based on a point process model of individual neuron spiking activity and a linear stochastic state-space model of the biological signal. We derive from the algorithm new instantaneous estimates of the en-tropy, entropy rate, and the mutual information between the signal and the ensemble spiking activity. We assess the accuracy of the algorithm by computing, along with the decoding error, the true coverage probabil-ity of the approximate 0.95 confidence regions for the individual signal estimates. We illustrate the new algorithm by reanalyzing the position and ensemble neural spiking activity of CA1 hippocampal neurons from two rats foraging in an open circular environment. We compare the per-formance of this algorithm with a linear filter constructed by the widely used reverse correlation method. The median decoding error for Animal 1 (2) during 10 minutes of open foraging was 5.9 (5.5) cm, the median entropy was 6.9 (7.0) bits, the median information was 9.4 (9.4) bits, and the true coverage probability for 0.95 confidence regions was 0.67 (0.75) using 34 (32) neurons. These findings improve significantly on our pre-vious results and suggest an integrated approach to dynamically reading neural codes, measuring their properties, and quantifying the accuracy with which encoded information is extracted.
Mitigating Data Exfiltration in SaaS Clouds

Existing processes and methods for incident handling are geared towards infrastructures and operational models that will be increasingly outdated by cloud computing. Research has shown that to adapt incident handling to cloud computing environments, cloud customers must establish clarity about their requirements on Cloud Service Providers (CSPs) for successful handling of incidents and contract CSPs accordingly. Secondly, CSPs must strive to support these requirements and mirror them in their Service Level Agreements. Intrusion Detection Systems (IDS) have been used widely to detect malicious behaviors in network communication and hosts. Facing new application scenarios in Cloud Computing, the IDS approaches yield several problems since the operator of the IDS should be the user, not the administrator of the Cloud infrastructure. Cloud providers need to enable possibilities to deploy and configure IDS for the user - which poses its own challenges. Current research and commercial solutions primarily focus on protecting against Denial of Service attacks and attacks against the Cloud’s virtual infrastructure. To counter these challenges, we propose a capability that aims to both detect and prevent the potential of data exfiltration by using a novel deception-based methodology. We also introduce a method of increasing the data protection level based on various threat conditions.
An Integrative Neurocircuit Perspective on Psychogenic Nonepileptic Seizures and Functional Movement Disorders

Functional neurological disorder (conversion disorder) is a neurobehavioral condition frequently encountered by neurologists. Psychogenic nonepileptic seizure (PNES) and functional movement disorder (FMD) patients present to epileptologists and movement disorder specialists respectively, yet neurologists lack a neurobiological perspective through which to understand these enigmatic groups. Observational research studies suggest that PNES and FMD may represent variants of similar (or the same) conditions given that both groups exhibit a female predominance, have increased prevalence of mood-anxiety disorders, frequently endorse prior abuse, and share phenotypic characteristics. In this perspective article, neuroimaging studies in PNES and FMD are reviewed, and discussed using studies of emotional dysregulation, dissociation and psychological trauma in the context of motor control. Convergent neuroimaging findings implicate alterations in brain circuits mediating emotional expression, regulation and awareness (anterior cingulate and ventromedial prefrontal cortices, insula, amygdala, vermis), cognitive control and motor inhibition (dorsal anterior cingulate, dorsolateral prefrontal, inferior frontal cortices), self-referential processing and perceptual awareness (posterior parietal cortex, temporoparietal junction), and motor planning and coordination (supplementary motor area, cerebellum). Striatal-thalamic components of prefrontal-parietal networks may also play a role in pathophysiology. Aberrant medial prefrontal and amygdalar neuroplastic changes mediated by chronic stress may facilitate the development of functional neurological symptoms in a subset of patients. Improved biological understanding of PNES and FMD will likely reduce stigma and aid the identification of neuroimaging biomarkers guiding treatment development, selection, and prognosis. Additional research should investigate neurocircuit abnormalities within and across functional neurological disorder subtypes, as well as compare PNES and FMD with mood-anxiety-dissociative disorders.
Anemia and Thrombocytopenia in Acute and Chronic Renal Failure

Background Acute renal failure describes as a syndrome by rapid decline in the ability of the kidney to eliminate waste products, regulate acid–base balance, and manage water homeostasis. When this impairment is prolonged and entered chronic phase, erythropoietin secretion by this organ is decreasing and toxic metabolic accumulates and causes hematological changes include decrease of HCT, MCV and RBC and platelet counts. This study evaluates present of anemia and thrombocytopenia in patients with acute and chronic renal failure. Materials and Methods This study conducted on 132 patients with renal impairment and also 179 healthy individuals as two separated control groups. Initially patients with renal problem were tested and after confirmation of impairment, patients were divided in two groups, acute with less than 3 months and chronic with more than 3 months renal failure, based on duration of the disease. Then complete blood count performed for each patient and finally obtained data were analyzed by SPSS software. Results Comparison between 96 patients with acute and 36 patients with chronic renal failure revealed that severity of anemia (HCT, Hb and MCV) between these two groups were statistically high in comparison with control groups (P > 0.05) but thrombocytopenia in patients with chronic renal failure was statistically different from control and the acute ones (P < 0.001). Conclusion It was recommended that in patients with chronic renal failure, to prevent the risk of bleeding, platelet count should be checked periodically.
The adhesion molecule L1 (CD171) promotes melanoma progression

The adhesion molecule L1 is expressed in primary melanomas and cutaneous metastases in contrast to melanocytic nevi and melanocytes, and is significantly associated with metastatic spread. Recent studies have demonstrated that in carcinomas L1 expression is associated with sustained activation of the extracellular signal‐regulated kinase (ERK) pathway and upregulation of ERK‐dependent, motility‐ and invasion‐associated gene products including αvβ3 integrin. The objective of this study was to further investigate the role of the adhesion molecule L1 in melanoma progression, and to evaluate whether targeting the L1 adhesion molecule would have therapeutic effects against invasive melanoma growth. Using human melanoma cells from different stages of progression in monolayer and organotypic human skin culture mimicking the pathophysiological environment of cutaneous melanoma, we found that (1) L1 expression mostly correlates with melanoma progression and αvβ3 integrin expression, (2) overexpression of L1 in early radial growth phase melanoma cells promotes conversion from radial to vertical growth phase melanoma without upregulation of αvβ3 integrin expression, and (3) suppression of L1 function significantly reduces migration and invasion of melanoma cells, but does not completely block invasive melanoma growth. Altogether, L1 plays a critical role in melanoma invasion and progression and offers therapeutic potential in combination with conventional anticancer agents. © 2006 Wiley‐Liss, Inc.