Miracle-dz/UniFAR-FTUs huggingface dataset:
Cyclic fluid flow through a regionally extensive fracture network within the Kodiak accretionary prism

Two types of periodic textures observed in veins from the Kodiak accretionary prism attest to cyclic fluid flow through a regionally extensive fracture network buried at 8-12 km depth : (1) crack-seal microstructures with bands of mica inclusions and (2) collapse microstructures with jagged bands of residue embedded within euhedral crystals of quartz. The difference in texture reflects the closure of cracks : crack-seal microstructures record the complete chemical sealing of the crack after each fracture event, whereas the collapse features record longer fluid-filled periods followed by more rapid draining of fractures. Collapse features consist of pressure solution selvages trapped within veins and in the wall rock adjacent to euhedral growth terminations ; the high concentrations of immobile elements in these selvages indicate that these fractures closed by collapse and penetration of quartz crystals into wall rock. Analysis of chemical composition on either side of four large euhedral growth veins and whole rock analysis of slates across the Kodiak Formation reveal local depletion of silica adjacent to veins but no evidence for long-distance silica transport within the system. Both crack-seal and collapse textures are observed in a regionally extensive vein system that displays a regular geometry, with thin, closely spaced (0.5-3 cm), near-vertical crack-seal veins that connect vertically and laterally with thicker euhedral growth veins arranged in widely spaced (-500 mm) southeast dipping en echelon sets. The mesoscopic distribution and textural variability of the vein network suggests that the development of the vein system involved early nucleation and growth of vertical hydrofractures. As the fracture density increased, arrays of fractures locally provided zones of weakness and southeast dipping brittle-ductile shear zones nucleated. These en echelon cracks remained open and provided small reservoirs of fluid. Textures show that en echelon fractures remain open but periodically grow by upward and downward propagation. Crack tips are then sealed with locally derived silica, and fluid drains back into en echelon fracture arrays. This local fluid movement is punctuated by less frequent events where the system links up over a greater distance, fractured reservoirs become interconnected, and the fluid within reservoirs is drained upward or laterally. Periodic inflation and deflation of en echelon arrays may reflect periodic slip on crosscutting faults and rupture of the seals that separate reservoirs.
Applied Cultural Analysis and the Compositional Practices of Rendering Ethnography

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EM-ML algorithm for track initialization with features using possibly noninformative data

Initializing and maintaining a track for a low observable (low SNR, low target detection probability and high false alarm rate) target can be very challenging because of the low information content of measurements. In addition, in some scenarios, target-originated measurements might not be present in many consecutive scans because of mispointing, target maneuvers or erroneous preprocessing. That is, one might have a set of noninformative scans that could result in poor track initialization and maintenance. In this paper an algorithm based on the Expectation-Maximization (EM) algorithm combined with Maximum Likelihood (ML) estimation is presented for tracking slowly maneuvering targets in heavy clutter and possibly non-informative scans. The adaptive sliding-window EM-ML approach, which operates in batch mode, tries to reject or weight down non-informative scans using the Q-function in the M-step of the EM algorithm. A track validation technique is used to conﬁrm the validity of the EM-ML estimates. It is shown that target features in the form of, for example, amplitude information, can also be used to improve the estimates. In addition, performance bounds based on the supplemented EM (SEM) technique are also presented. The effectiveness of new algorithm is first demonstrated on a 78-frame Long Wave Infrared (LWIR) data sequence consisting of an F1 Mirage fighter jet in heavy clutter. Previously, this scenario has been used as a benchmark for evaluating the performance of other track initialization algorithms. The new EM-ML estimator conﬁrms the track by frame 20 while the ML-PDA (Maximum Likelihood estimator combined with Probabilistic Data Association) algorithm, the IMM-MHT (Interacting Multiple Model estimator combined with Multiple Hypothesis Tracking) and the IMM-PDA estimator previously required 28, 38 and 39 frames, respectively. The benefits of the new algorithm in terms of accuracy, early detection and computational load are illustrated using simulated scenarios as well.
Organic compound synthesis on the primitive earth.

Since the demonstration by Pasteur that life does not arise spontaneously at the present time, the problem of the origin of life has been one of determining how the first forms of life arose, from which all the present species have evolved. This problem has received considerable attention in recent years, but there is disagreement on many points. We shall discuss the present status of the problem, mainly with respect to the early chemical history of, and the synthesis of organic compounds on, the primitive earth. Many of our modern ideas on the origin of life stem from Oparin (1), who argued that the spontaneous generation of the first living organism might reasonably have taken place if large quantities of organic compounds had been present in the oceans of the primitive earth. Oparin further proposed that the atmosphere was reducing in character and that organic compounds might be synthesized under these conditions. This hypothesis implied that the first organisms were heterotrophic-that is, that they obtained their basic constituents from the environment instead of synthesizing them from carbon dioxide and water. Horowitz (2) discussed this point further and outlined how a simple heterotrophic organism could develop the ability to synthesize various cell constituents and thereby evolve into autotrophic organisms. In spite of the argument by Oparin. numerous attempts were made to synthesize organic compounds under the oxidizing conditions now present on the earth (3). Various sources of energy acting on carbon dioxide and water failed to give reduced carbon compounds except when contaminating reducing agents were present. The one exception to this was the synthesis of formic acid and formaldehyde in very small yield (10-7 H2CO molecules per ion pair) by the use of 40-million-electron-volt helium ions from a 60-inch cyclotron (4). While the simplest organic compounds were indeed synthesized, the yields were so small that this experiment can best be interpreted to mean that it would not have been possible to synthesize organic compounds nonbiologically as long as oxidizing conditions were present on the earth. This experiment is important in that it induced a reexamination of Oparin's hypothesis of the reducing atmosphere (5).
Helping Egyptian women achieve optimal birth spacing intervals through fostering linkages between family planning and maternal / child health services.

Population Councils USAID-funded Frontiers in Reproductive Health (FRONTIERS) program in collaboration with the Egyptian Ministry of Health and Population (MOHP) and the NGO Social Planning Analysis and Administration Consultants; (SPAAC) conducted an operations research study to measure the acceptability and effectiveness of two birth spacing message models. For Model I (health services model) birth spacing messages were communicated through services by health workers to women during prenatal and postpartum periods. Model II (community awareness model) provided this service plus an awareness raising component that targeted men through training community influentials to communicate messages. Both models proved effective in changing womens knowledge and attitudes towards birth spacing and in enhancing use of contraception at 10-11 months postpartum by 48 percent among Model I mothers and 43 percent among Model II mothers compared with 31 percent among control group mothers. Over the postpartum period women in the two intervention groups used contraception more consistently than women in the control group (median duration of protection against pregnancy was 6.8 months for Model I mothers 4.5 months for Model II mothers and 2.9 months for control group mothers). Both intervention models were associated with an increased utilization of services especially family planning services by women who only had one child (36 percent increase in Model I clinics 47 percent increase in Model II clinics and 3.2 percent in control clinics). However a fear of contraceptive side-effects continues to be a major concern among women and men in all groups and is an obstacle in achieving healthy birth intervals. (Excerpts)
Comparing apples with pears. How differences in pesticide residues regulations impact trade

The impact of food safety standards on international trade has already been addressed. Generally, economists try to assess trade losses borne by exporters when importing countries impose stricter regulations. In this paper we assess the impact of the Maximum Residue Levels (MRL) of pesticides on the trade of apples and pears. Rather than focusing on a particular pesticide we take into account the entire list of substances set out by the various regulations with the aim of understanding how the similarity (or dissimilarity) of these can affect trade. Most studies assess the impact of sanitary standard regulations introducing directly in the analysis the MLR put in force in the importing country. We assume that what can be crucial is the difference in the tolerance levels of both the importing and exporting country. Having built a similarity index we then introduce it into a gravity equation to assess the impact of differences in MRL of pesticides on the trade of apples and pears of seven exporting and seven importing countries. Results suggest that harmonizing regulations impacts trade differently depending on the exporter. French Abstract : L’impact sur le commerce international des standards de securite alimentaire a souvent ete etudie. Generalement les economistes essaient d’evaluer les pertes supportees par les exportateurs quand les pays importateurs imposent des reglementations plus strictes. Dans cet article, nous evaluons l’impact des Limites Maximales de Residus (LMR) de pesticides sur le commerce de pommes et de poires. Plutot que de se focaliser sur un pesticide en particulier, nous prenons en consideration la liste complete des substances etablie par les diverses reglementations avec pour but de comprendre comment les similarites (ou differences) entre elles affectent le commerce. La plupart des etudes evaluent l’impact des reglementations sanitaires en introduisant directement dans l’analyse le LMR en vigueur dans le pays importateur. Nous faisons l’hypothese que ce qui importe c’est plutot la difference entre les niveaux de tolerance du pays exportateur et importateur. Apres avoir construit un indice de similarite, nous l’introduisons dans une equation de gravite pour evaluer l’impact sur le commerce de pommes et poires des differences entre niveaux acceptables de residus de pesticides pour sept pays exportateurs et sept pays importateurs. Les resultats suggerent qu’harmoniser les reglementations aurait un impact different selon le pays exportateur.
Algorithm for answer extraction based on pattern learning

The rapid growth of information available on the internet has provoked the development of diverse tool for searching and browsing large document collections. Information retrieval (IR) system act as a vital tool for identifying relevant document for user queries posted to search engine. Some special kind of IR system, such as Google, yahoo and Bing which allow the system to retrieve the relevant information to user question form web. Question Answering System (QAS) play important role for identifying the correct answer to user question by relying on the many IR tools. In this paper, we propose a method for answer extraction based on pattern learning algorithm. Answer extraction component provide precise answer to user question. The proposed QA system uses the pattern learning algorithm which consists of following component such as question transformation, question and answer pattern generation, pattern learning, pattern based answer extraction and answer evaluation. The experiment has been conducted different type question on TREC data sets. Our system used different ranking metrics in the experimental part to find the correct answer to user question. The experimental results were investigated and compare with different type of questions.
Structural mining of molecular biology data

One method for discovering knowledge in structural data is the identification of common substructures, or subgraphs, within the data. Once identified, these substructures can be used to simplify the data by replacing instances of the substructure with a pointer to the newly discovered concept. The discovered substructure concepts allow abstraction over detailed structure in the original data and provide new, relevant attributes for interpreting the data. In this article, we describe the SUBDUE system that discovers interesting substructures in structural data. SUBDUE discovers substructures that compress the original database and represent interesting structural concepts in the data. By compressing previously discovered substructures in the data, multiple passes of SUBDUE produce a hierarchical description of the structural regularities in the data, The capabilities of SUBDUE are used to discover patterns in protein and DNA databases.
e-Shoes: Smart shoes for unobtrusive human activity recognition

Many approaches to human activity recognition such as wearable based or computer vision based are obtrusive in the sense that they prevent the users from performing activities in a natural way, or they might raise privacy invasion concerns. This paper presents e-Shoes — smart shoes for unobtrusive human activity recognition. E-Shoes are shoes instrumented with tiny wireless accelerometers embedded inside the insole of the shoes. The sensors are seamless to the users making the system suitable for recognizing everyday activities. To analyze sensor signals, we propose a convolution neutral networks (CNN) model that automatically learns features from sensing data and makes predictions about performing activities. We verify the effectiveness of the approach with a real dataset that covers seven daily activities. The system achieved 93% accuracy in average, which is very promising, while being energy efficient and easy to use.
Detection and classification of acoustic signals from fixed-wing aircraft

The acoustic emission from a twin propeller aircraft is analyzed in the frequency domain. The time-varying power spectrum estimate of the signal is generated. The approach is to generate frequency spectra for fixed time segments of the signal using the Welch method. A confidence interval is calculated, and if the confidence interval is too wide, the power spectrum estimate is not incorporated into the detection decision. The spectral peaks in the power spectrum estimate are identified by thresholding with a local mean. An algorithm to detect and classify the aircraft based on these spectral peaks is proposed. <<ETX>>
Development of a self-treatment approach for patients with COPD and comorbidities: an ongoing learning process.

BACKGROUND Patient-initiated action plans are an important component of COPD self-management (SM) interventions. When integrated into SM interventions, these action plans have proven to be effective in reducing exacerbation severity, hospitalisations, and costs and in improving health status in patients with COPD without severe comorbidities. Because of overlap in symptoms, a self-treatment (ST) approach that focuses solely on traditional symptoms of COPD is inadequate for patients with COPD and comorbidities. The COPE-III SM intervention combines (I) patient-initiated action plans that are tailored to the individual's co-morbid disease(s), and (II) ongoing nurse support. In this paper we provide information regarding the integration of information from two previous COPD SM studies (COPE I and II) in the development of the current COPE-III ST approach. MATERIALS AND METHODS COPE-III ST materials include daily symptom diaries and action plans that take patient's common comorbidities [chronic heart failure (CHF), anxiety, depression, ischaemic heart disease (IHD), and diabetes] into account. The comorbid diary and action plans components were developed in collaboration with multiple disease-experts. RESULTS Previous SM studies have highlighted some essential topics that need to be considered when developing a SM or ST approach: 'when to initiate ST', 'how to optimize materials and safety', and 'how to achieve behavioural change'. In the COPE-III study, ST is initiated after a significant change in symptoms. This is consistent with the COPE-II approach and was implemented because disease symptoms are often present even when patients are stable. We have tried to ensure patient safety by providing an easily accessible case-manager to patients throughout their involvement in the study. Furthermore, a psychologist has ensured the use of behavioural change techniques throughout the intervention. CONCLUSIONS We should continue to learn from our experiences with SM interventions to further optimize future SM and ST interventions. The use of materials that are suitable for different levels of patient literacy and the training of health care providers are other points of improvement.
Black noise and population persistence

Biological populations are susceptible to random variation in environmental influences such as temperature and moisture. This variability (or noise) can determine population size and, ultimately, cause extinctions. Extinction risk depends on noise colour or the amount of short– and long–term variation. Most environmental noise is reddened: the variation is dominated by long–term fluctuations. Recent modelling has shown that moderately reddened noise affects populations differently from the white noise used in earlier studies. However, some geophysical phenomena, such as temperature and river height, can have deeply reddened ‘brown’ or even ‘black’ spectra. We find that, compared to environments characterized by red noise, very long population persistence times are more likely for black noise. Unlike previous work incorporating a simple autoregressive model of reddened noise, our model suggests that the large variation associated with persistence in a red–noise environment limits our ability to predict the fate of particular populations subject to this noise colour. Thus, we identify the colour of noise experienced by a population (red or black) as a crucial factor in any attempt to manage or conserve that population.
Dynamic-Stochastic Influence Diagrams: Integrating Time-Slices IDs and Discrete Event Systems Modeling

— The Influence Diagrams (IDs) is a kind of Probabilistic Belief Networks for graphic modeling. The usage of IDs can improve the communication among field experts, modelers, and decision makers, by showing the issue frame discussed from a high-level point of view. This paper enhances the Time-Sliced Influence Diagrams (TSIDs, or called Dynamic IDs) based formalism from a Discrete Event Systems Modeling and Simulation (DES M&S) perspective, for Exploring Analysis (EA) modeling. The enhancements enable a modeler to specify times occurred of endogenous events dynamically with stochastic sampling as model running and to describe the in-ter-influences among them with variable nodes in a dynamic situation that the existing TSIDs fails to capture. The new class of model is named Dynamic-Stochastic Influence Diagrams (DSIDs). The paper includes a description of the modeling formalism and the hiberarchy simulators implementing its simulation algorithm, and shows a case study to illustrate its enhancements.
An indoor localization system based on backscatter RFID tag

Indoor localization has been actively researched in recent years due to the increasing demand for location-awareness services. However, to balance localization accuracy and system cost is always a challenge for indoor localization systems. Radio frequency identification (RFID) is a promising technology to achieve both goals, because of its reasonable cost and reliability. In this paper, we propose a novel RFID indoor localization system based on angle of arrival (AoA) and phase of arrival (PoA) methods. This system leverages RFID's two experimental signal diffusion characteristics to estimate AoA. One is that the interrogation zone is constrained in a lobe, and only in this area the tag can be queried. The second is that there exits a stable pattern of received signal strength (RSS) on angle changes. We use the two features to find a general area and to pinpoint the AoA consecutively. This effectively narrows the sampling zone (where signal needs to be sampled), and helps to reduce computational complexity. In addition, we reduce the multipath effect on range estimation by determining the AoA and rotating the reader into the direction of the target. Moreover, we exploit two signals with a slightly different frequency to eliminate the phase ambiguity issue. Our system takes only one reader and achieves mean accuracy of 23 cm. The simplicity and effectiveness of our system make it convenient to be used in practice.
A New Multilevel Framework for Large-Scale Interconnect-Driven Floorplanning

We present in this paper a new interconnect-driven multilevel floorplanner, called interconnect-driven multilevel-floorplanning framework (IMF), to handle large-scale building-module designs. Unlike the traditional multilevel framework that adopts the ldquoLambda-shapedrdquo framework (inaccurately called the ldquoV-cyclerdquo framework in the literature): bottom-up coarsening followed by top-down uncoarsening, the IMF, in contrast, works in the ldquoV-shapedrdquo manner: top-down uncoarsening (partitioning) followed by bottom-up coarsening (merging). The top-down partitioning stage iteratively partitions the floorplan region based on min-cut bipartitioning with exact net-weight modeling to reduce the number of global interconnections and, thus, the total wirelength. Then, the bottom-up merging stage iteratively applies fixed-outline floorplanning using simulated annealing for all regions and merges two neighboring regions recursively. Experimental results show that the IMF obtains the best published fixed-outline floorplanning results with the smallest average wirelength for the Microelectronics Center of North Carolina/Gigascale Systems Research Center benchmarks. In particular, IMF scales very well as the circuit size increases. The V-shaped multilevel framework outperforms the Lambda-shaped one in the optimization of global circuit effects, such as interconnection and crosstalk optimization, since the V-shaped framework considers the global configuration first and then processes down to local ones level by level, and thus, the global effects can be handled at earlier stages. The V-shaped multilevel framework is general and, thus, can be readily applied to other problems.