Miracle-dz/UniFAR-FTUs huggingface dataset:
Metamorphic patterns in orogenic systems and the geological record

Abstract Regional metamorphism occurs in plate boundary zones. Accretionary orogenic systems form at subduction boundaries in the absence of continent collision, whereas collisional orogenic systems form where ocean basins close and subduction steps back and flips (arc collisions), simply steps back and continues with the same polarity (block and terrane collisions) or ultimately ceases (continental collisions). As a result, collisional orogenic systems may be superimposed on accretionary orogenic systems. Metamorphism associated with orogenesis provides a mineral record that may be inverted to yield apparent thermal gradients for different metamorphic belts, which in turn may be used to infer tectonic setting. Potentially, peak mineral assemblages are robust recorders of metamorphic P and T, particularly at high P–T conditions, because prograde dehydration and melting with melt loss produce nominally anhydrous mineral assemblages that are difficult to retrogress or overprint without fluid influx. Currently on Earth, lower thermal gradients are associated with subduction (and early stages of collision) whereas higher thermal gradients are characteristic of back-arcs and orogenic hinterlands. This duality of thermal regimes is the hallmark of asymmetric or one-sided subduction and plate tectonics on modern Earth, and a duality of metamorphic belts will be the characteristic imprint of asymmetric or one-sided subduction in the geological record. Accretionary orogenic systems may exhibit retreating trench–advancing trench cycles, associated with high (>750 °C GPa−1) thermal gradient type of metamorphism, or advancing trench–retreating trench cycles, associated with low (<350 °C GPa−1) to intermediate (350–750 °C GPa−1) thermal gradient types of metamorphism. Whether the subducting boundary advances or retreats determines the mode of evolution. Accretionary orogenic systems may involve accretion of allochthonous and/or para-autochthonous elements to continental margins at subduction boundaries. Paired metamorphic belts, sensu Miyashiro, comprising a low thermal gradient metamorphic belt outboard and a high thermal gradient metamorphic belt inboard, are characteristic and may record orogen-parallel terrane migration and juxtaposition by accretion of contemporary belts of contrasting type. A wider definition of ‘paired’ metamorphism is proposed to incorporate all types of dual metamorphic belts. An additional feature is ridge subduction, which may be reflected in the pattern of high dT/dP metamorphism and associated magmatism. Apparent thermal gradients derived from inversion of age-constrained metamorphic P–T data are used to identify tectonic settings of ancient metamorphism, to evaluate the age distribution of metamorphism in the rock record from the Neoarchaean Era to the Cenozoic Era, and to consider how this relates to the supercontinent cycle and the process of terrane export and accretion. In addition, I speculate about metamorphism and tectonics before the Mesoarchaean Era.
Spatiotemporal multiple persons tracking using Dynamic Vision Sensor

Although motion analysis has been extensively investigated in the literature and a wide variety of tracking algorithms have been proposed, the problem of tracking objects using the Dynamic Vision Sensor requires a slightly different approach. Dynamic Vision Sensors are biologically inspired vision systems that asynchronously generate events upon relative light intensity changes. Unlike conventional vision systems, the output of such sensor is not an image (frame) but an address events stream. Therefore, most of the conventional tracking algorithms are not appropriate for the DVS data processing. In this paper, we introduce algorithm for spatiotemporal tracking that is suitable for Dynamic Vision Sensor. In particular, we address the problem of multiple persons tracking in the occurrence of high occlusions. We investigate the possibility to apply Gaussian Mixture Models for detection, description and tracking objects. Preliminary results prove that our approach can successfully track people even when their trajectories are intersecting.
Transient Responses of Cerebral Blood Flow and Ventilation to Changes in Paco2 in Normal Subjects and Patients With Cerebrovascular Disease

In the present study, the dynamics of the cerebral blood flow (CBF) and ventilatory response to hypercapnia was investigated in a group of patients with cerebrovascular disease and compared to responses measured in a group of normal volunteers. There was a significant correlation between the rapidity of the transient CBF and ventilatory responses and the severity of the cerebrovascular disease. While the steady state CBF response showed no such correlation, the steady state ventilatory response was reduced in patients with severe cerebrovascular disease. Various explanations for the differences in the dynamic responses of CBF and ventilation in patients with mild or severe cerebrovascular disease compared to normal sbjects are considered. Measurement of these circulatory and ventilatory responses may be sensitive means for assessing the changing status of patients with cerebrovascular disease.
Speaker Identification with VoxCeleb DataSet

In this project, we perform a text independent speaker identification experiment with a newly released data set, VoxCeleb (2017)[1], which consists of celebrity interview audio clips downloaded from Youtube. It’s a challenging data set in the sense that there are often multiple vocal sources in the same clip. A MFCC feature vector based Deep Neural Network (DNN) is used as our baseline. It is compared with a support vector machine (SVM) algorithm. We utilzes the k-mean vector quantization technique to optimize our SVM performance, as well as filter out other vocal sources while training the SVM model.
Circulating polymers in &agr;1-antitrypsin deficiency

To the Editor: Most individuals carry two wild-type M alleles of the SERPINA1 gene which encodes α1-antitrypsin. 95% of severe deficiency of α1-antitrypsin is associated with the Z allele (Glu342Lys; denoted PiZZ in the homozygote), and with the retention and polymerisation of α1-antitrypsin within hepatocytes [1]. These polymers are contained within periodic acid–Schiff-positive, diastase-resistant inclusions that are associated with neonatal hepatitis, cirrhosis and hepatocellular carcinoma. The concomitant lack of circulating α1-antitrypsin predisposes the Z α1-antitrypsin homozygote to early-onset emphysema. Polymers of α1-antitrypsin form within the lung as a result of local inflammation and exposure to cigarette smoke [2]. They have also been identified in the skin of an individual with α1-antitrypsin deficiency and panniculitis [3] and in a renal biopsy from an individual with α1-antitrypsin deficiency and vasculitis [4]. It is unknown whether these polymers form locally or are deposited in these tissues from a circulating source, and whether extrahepatic polymers are associated with any disease phenotypes. We have assessed whether polymers of α1-antitrypsin are present within serum, from where they originate, and whether they are associated with clinical features in individuals with PiZZ α1-antitrypsin deficiency. In this investigation we used ELISA with the anti-α1-antitrypsin polymer monoclonal antibody (2C1) [5] to assess the presence of polymers in the plasma of 1) 518 individuals with PiZZ α1-antitrypsin deficiency; 2) an individual with α1-antitrypsin deficiency who underwent liver transplantation; and 3) 293 individuals with a mixture of α1-antitrypsin phenotypes. The specificity of the 2C1 antibody was confirmed by using it to immunoprecipitate polymers from the plasma of individuals with and without a positive signal …
Complex dynamics of semantic memory access in reading

Understanding a word in context relies on a cascade of perceptual and conceptual processes, starting with modality-specific input decoding, and leading to the unification of the word's meaning into a discourse model. One critical cognitive event, turning a sensory stimulus into a meaningful linguistic sign, is the access of a semantic representation from memory. Little is known about the changes that activating a word's meaning brings about in cortical dynamics. We recorded the electroencephalogram (EEG) while participants read sentences that could contain a contextually unexpected word, such as ‘cold’ in ‘In July it is very cold outside’. We reconstructed trajectories in phase space from single-trial EEG time series, and we applied three nonlinear measures of predictability and complexity to each side of the semantic access boundary, estimated as the onset time of the N400 effect evoked by critical words. Relative to controls, unexpected words were associated with larger prediction errors preceding the onset of the N400. Accessing the meaning of such words produced a phase transition to lower entropy states, in which cortical processing becomes more predictable and more regular. Our study sheds new light on the dynamics of information flow through interfaces between sensory and memory systems during language processing.
Using Wearable Sensors for Real-Time Recognition Tasks in Games of Martial Arts - An Initial Experiment

Beside their stunning graphics, modern entertainment systems feature ever-higher levels of immersive user-interaction. Today, this is mostly achieved by virtual (VR) and augmented reality (AK) setups. On top of these, we envision to add ambient intelligence and context awareness to gaming applications in general and games of martial arts in particular. To this end, we conducted an initial experiment with inexpensive body-worn gyroscopes and acceleration sensors for the chum kiu motion sequence in wing tsun (a popular form of kung fu). The resulting data confirm the feasibility of our vision. Fine-tuned adaptations of various thresholding and pattern-matching techniques known from the fields of computational intelligence and signal processing should suffice to automate the analysis and recognition of important wing tsun movements in real time. Moreover, the data also seem to allow for the possibility of automatically distinguishing between certain levels of expertise and quality in executing the movements.
Towards the Development of a Cyber Analysis & Advisement Tool (CAAT) for Mitigating De-Anonymization Attacks

We are seeing a rise in the number of Anonymous Social Networks (ASN) that claim to provide a sense of user anonymity. However, what many users of ASNs do not know that a person can be identified by their writing style. In this paper, we provide an overview of a number of author concealment techniques, their impact on the semantic meaning of an author's original text, and introduce AuthorCAAT, an application for mitigating de-anonymization attacks. Our results show that iterative paraphrasing performs the best in terms of author concealment and performs well with respect to Latent Semantic Analysis.
Qualitative study to explore the health and well-being impacts on adults providing informal support to female domestic violence survivors

Objectives Domestic violence (DV) is hazardous to survivors' health, from injuries sustained and from resultant chronic physical and mental health problems. Support from friends and relatives is significant in the lives of DV survivors; research shows associations between positive support and the health, well-being and safety of survivors. Little is known about how people close to survivors are impacted. The aim of this study was exploratory, with the following research question: what are the health and well-being impacts on adults who provide informal support to female DV survivors? Design A qualitative study using semistructured interviews conducted face to face, by telephone or using Skype. A thematic analysis of the narratives was carried out. Setting Community-based, across the UK. Participants People were eligible to take part if they had had a close relationship (either as friend, colleague or family member) with a woman who had experienced DV, and were aged 16 or over during the time they knew the survivor. Participants were recruited via posters in community venues, social media and radio advertisement. 23 participants were recruited and interviewed; the majority were women, most were white and ages ranged from mid-20s to 80. Results Generated themes included: negative impacts on psychological and emotional well-being of informal supporters, and related physical health impacts. Some psychological impacts were over a limited period; others were chronic and had the potential to be severe and enduring. The impacts described suggested that those providing informal support to survivors may be experiencing secondary traumatic stress as they journey alongside the survivor. Conclusions Friends and relatives of DV survivors experience substantial impact on their own health and well-being. There are no direct services to support this group. These findings have practical and policy implications, so that the needs of informal supporters are legitimised and met.
Oxidative Stress and Platelet Activation in Homozygous Homocystinuria

Background—Severe hyperhomocysteinemia due to cystathionine &bgr;-synthase deficiency (C&bgr;SD) is associated with early atherothrombotic vascular disease. Homocysteine may exert its effects by promoting oxidative damage. In the present study, we investigated whether in vivo formation of 8-iso-prostaglandin (PG) F2&agr;, a platelet-active product of arachidonic acid peroxidation, is enhanced in C&bgr;SD and whether it correlates with in vivo platelet activation, as reflected by thromboxane (TX) metabolite excretion. Methods and Results—Urine and blood samples were obtained from patients with homozygous C&bgr;SD (n=13) and age-matched healthy subjects. Urinary 8-iso-PGF2&agr; excretion was significantly higher in C&bgr;SD patients than in control subjects (640±384 versus 213±43 pg/mg creatinine;P =0.0015) and correlated with plasma homocysteine (&rgr;=0.398, P =0.0076). Similarly, urinary 11-dehydro-TXB2 excretion was enhanced in C&bgr;SD (1166±415 versus 324±72 pg/mg creatinine;P =0.0015) and correlated with urinary 8-iso-PGF2&agr; (&rgr;=0.362, P =0.0153). Vitamin E supplementation (600 mg/d for 2 weeks) was associated with a statistically significant increase in its plasma levels (from 16.6±4.6 to 40.4±8.7 &mgr;mol/L, P =0.0002) and with reductions in 8-iso-PGF2&agr; (from 790±159 to 559±111 pg/mg creatinine, P =0.018) and 11-dehydro-TXB2 (from 1273±383 to 913±336 pg/mg creatinine, P =0.028). A statistically significant inverse correlation was found between urinary 8-iso-PGF2&agr; and plasma vitamin E levels (&rgr;=−0.745, P =0.0135). Conclusions—The results of the present study suggest that enhanced peroxidation of arachidonic acid to form bioactive F2-isoprostanes may represent an important mechanism linking hyperhomocysteinemia and platelet activation in C&bgr;SD patients. Moreover, they provide a rationale for dose-finding studies of vitamin E supplementation in this setting.
Profiling bacterial diversity of B2 Cave, a limestone cave of Baratang, Andaman and Nicobar islands, India

Profiling Bacterial Diversity of B2 Cave, A Limestone Cave of Baratang, Andaman and Nicobar Islands, India ARUN KUMAR DE1,2,*, RAMACHANDRAN MUTHIYAN2, JAI SUNDER1, DEBASIS BHATTACHARYA1, A KUNDU1 and S DAM ROY3 1Animal Science Division, ICAR-Central Island Agricultural Research Institute, Port Blair, Andaman and Nicobar Islands, India 2Bioinformatics Centre, ICAR-Central Island Agricultural Research Institute, Port Blair, Andaman and Nicobar Islands, India 3Division of Fisheries Sciences, ICAR-Central Island Agricultural Research Institute, Port Blair, Andaman and Nicobar Islands, India
Data Stream Clustering: Challenges and Issues

Very large databases are required to store massive amounts of data that are continuously inserted and queried. Analyzing huge data sets and extracting valuable pattern in many applications are interesting for researchers. We can identify two main groups of techniques for huge data bases mining. One group refers to streaming data and applies mining techniques whereas second group attempts to solve this problem directly with efficient algorithms. Recently many researchers have focused on data stream as an efficient strategy against huge data base mining instead of mining on entire data base. The main problem in data stream mining means evolving data is more difficult to detect in this techniques therefore unsupervised methods should be applied. However, clustering techniques can lead us to discover hidden information. In this survey, we try to clarify: first, the different problem definitions related to data stream clustering in general; second, the specific difficulties encountered in this field of research; third, the varying assumptions, heuristics, and intuitions forming the basis of different approaches; and how several prominent solutions tackle different problems.
Minimizing Transmission Loss in Smart Microgrids by Sharing Renewable Energy

Renewable energy (e.g., solar energy) is an attractive option to provide green energy to homes. Unfortunately, the intermittent nature of renewable energy results in a mismatch between when these sources generate energy and when homes demand it. This mismatch reduces the efficiency of using harvested energy by either (i) requiring batteries to store surplus energy, which typically incurs ∼ 20% energy conversion losses, or (ii) using net metering to transmit surplus energy via the electric grid’s AC lines, which severely limits the maximum percentage of renewable penetration possible. In this article, we propose an alternative structure where nearby homes explicitly share energy with each other to balance local energy harvesting and demand in microgrids. We develop a novel energy sharing approach to determine which homes should share energy, and when to minimize system-wide energy transmission losses in the microgrid. We evaluate our approach in simulation using real traces of solar energy harvesting and home consumption data from a deployment in Amherst, MA. We show that our system (i) reduces the energy loss on the AC line by 64% without requiring large batteries, (ii) performance scales up with larger battery capacities, and (iii) is robust to different energy consumption patterns and energy prediction accuracy in the microgrid.
The norepinephrine transporter gene is associated with the retardation symptoms of major depressive disorder in the Han Chinese population

The norepinephrine transporter plays an important role in the pathophysiology and pharmacological treatment of major depressive disorder. Consequently, the norepinephrine transporter gene is an attractive candidate in major depressive disorder research. In the present study, we evaluated the depression symptoms of subjects with major depressive disorder, who were all from the North of China and of Han Chinese origin, using the Hamilton Depression Scale. We examined the relationship between two single nucleotide polymorphisms in the norepinephrine transporter, rs2242446 and rs5569, and the retardation symptoms of major depressive disorder using quantitative trait testing with the UNPHASED program. rs5569 was associated with depressed mood, and the GG genotype may be a risk factor for this; rs2242446 was associated with work and interest, and the TT genotype may be a risk factor for loss of interest. Our findings suggest that rs2242446 and rs5569 in the norepinephrine transporter gene are associated with the retardation symptoms of depression in the Han Chinese population.
Integrated out-of-plane nanoelectrospray thruster arrays for spacecraft propulsion

Nanoelectrosprays, well known for their use in sample injection for the mass spectrometry of large biomolecules, can also be used in other applications such as spacecraft propulsion. The thrust generated by a single electrospray emitter is well below 1 µN, which is several orders of magnitude below the required thrust for planned formation flying missions. This paper presents the process flow and the microfabrication of large 2D arrays of out-of-plane nanoelectrospray capillary emitters with integrated extractor electrodes as well as electrospray results. The capillaries, 70 µm high and with 24 µm inner diameter, are etched from one silicon-on-insulator wafer. The extractor electrodes are from another silicon-on-insulator wafer. Both parts are passively aligned to within 2 µm, centering each capillary under one extractor electrode, thus ensuring highly uniform emitter characteristics over large arrays. Low hydraulic impedance has been a major problem in out-of-plane electrospray designs in the past, which is solved here by adding a post-processing step in which the capillaries are filled with 5 µm silica microspheres fixed in place by silanization. Finally, this paper reports on successful spray tests carried out under vacuum conditions with single and arrays of capillaries spraying the ionic liquid EMI-Tf2 N demonstrating the operation of our nanoelectrospray thrusters in an ionic mode.
GAIS: A Method for Detecting Interleaved Sequential Patterns from Imperfect Data

This paper introduces a novel method, GAIS, for detecting interleaved sequential patterns from databases. A case, where data is of low quality and has errors is considered. Pattern detection from erroneous data, which contains multiple interleaved patterns is an important problem in a field of sensor network applications. We approach the problem by grouping data rows with the help of a model database and comparing groups with the models. In evaluation GAIS clearly outperforms the greedy algorithm. Using GAIS desired sequential patterns can be detected from low quality data.
The Inverse Problems for Some Topological Indices in Combinatorial Chemistry

In the original paper, Goldman et al. (2000) launched the study of the inverse problems in combinatorial chemistry, which is closely related to the design of combinatorial libraries for drug discovery. Following their ideas, we investigate four other topological indices, i.e., the sigma-index, the c-index, the Z-index, and the M(1)-index, with a special emphasis on the sigma-index. Like the Wiener index, these four indices are very popular in combinatorial chemistry and reflect many chemical and physical properties. We give algorithmic and analytical solutions for the inverse problems of the four indices. We also show that the SUBTREEVALUE reconstruction problem for the sigma-index is NP-hard.
Robust building boundary extraction method based on dual-scale feature classification and decision fusion with satellite image

ABSTRACT Building edge or boundary extraction is always one of the most important issues for remote sensing application. In order to accurately extract the edges or boundary of a building, there are usually two problems. Firstly, strong interference edges from backgrounds such as road, trees and others cannot be avoided. Secondly, it is more difficult for the lower contrast building edges to be detected. In order to address these two problems to a certain extent, a Robust Building Boundary Extraction method (DS-RBBE) is proposed in this paper, which is based on dual-scale sparse SVM classification and decision fusion. First, training samples are automatically selected by employing prior knowledge of main direction and linearity information. Next, a sparse SVM classifier is trained using the dual-scale local edge features of the training samples. And then, the trained sparse SVM is employed to classify all extracted edges. Finally, a dual-scale decision fusion strategy is performed for final building boundary extraction. In order to evaluate the performance of proposed method, the experiments are conducted on different types of build regions. The results are shown that the proposed method can efficiently extract the building edges and boundaries.