Miracle-dz/UniFAR-FTUs huggingface dataset:
The Petrological and Geochemical Evolution of Ediacaran Rare‐Metal Bearing A‐type Granites from the Jabal Aja Complex, Northern Arabian Shield, Saudi Arabia

New fieldwork, mineralogical and geochemical data and interpretations are presented for the rare‐metal bearing A‐type granites of the Aja intrusive complex (AIC) in the northern segment of the Arabian Shield. This complex is characterized by discontinuous ring‐shaped outcrops cut by later faulting. The A‐type rocks of the AIC are late Neoproterozoic post‐collisional granites, including alkali feldspar granite, alkaline granite and peralkaline granite. They represent the outer zones of the AIC, surrounding a core of older rocks including monzogranite, syenogranite and granophyre granite. The sharp contacts between A‐type granites of the outer zone and the different granitic rocks of the inner zone suggest that the AIC was emplaced as different phases over a time interval, following complete crystallization of earlier batches. The A‐type granites represent the late intrusive phases of the AIC, which were emplaced during tectonic extension, as shown by the emplacement of dykes synchronous with the granite emplacement and the presence of cataclastic features. The A‐type granites consist of K‐feldspars, quartz, albite, amphiboles and sodic pyroxene with a wide variety of accessory minerals, including Fe‐Ti oxides, zircon, allanite, fluorite, monazite, titanite, apatite, columbite, xenotime and epidote. They are highly evolved (71.3–75.8 wt% SiO2) and display the typical geochemical characteristics of post‐collisional, within‐plate granites. They are rare‐metal granites enriched in total alkalis, Nb, Zr, Y, Ga, Ta, REE with low CaO, MgO, Ba, and Sr. Eu‐negative anomalies (Eu/Eu* = 0.17–0.37) of the A‐type granites reflect extreme magmatic fractionation and perhaps the effects of late fluid‐rock interactions. The chemical characteristics indicate that the A‐type granites of the AIC represent products of extreme fractional crystallization involving alkali feldspar, quartz and, to a lesser extent, ferromagnesian minerals. The parent magma was derived from the partial melting of a juvenile crustal protolith with a mantle contribution. Accumulation of residual volatile‐rich melt and exsolved fluids in the late stage of the magma evolution produced pegmatite and quartz veins that cut the peripheries of the AIC. Post‐magmatic alteration related to the final stages of the evolution of the A‐type granitic magma, indicated by alterations of sodic amphibole and sodic pyroxene, hematitization and partial albitization.
Face Feature Recognition System Considering Central Moments 1

Shape Features is used in pattern recognition because of their discrimination power and robustness. These features can also be normalized by Central moment. In this work, Faces Features Recognition System considering central moment (FFRS) is including three steps, first step, some image processing techniques worked together for shape features extraction step, step two, extract features of shape ( face image) using central moment, third step is recognition of face features by comparing between an input test face features from the input image and an face features which stored in the features database. Keyword: Recognition, detection, face feature, moment, image preprocessing, feature database, and central moment.
A perspective of batching methods in a simulation environment of multiple replications in parallel

Discrete event simulation is frequently time-consuming either because modern dynamic systems, such as telecommunication networks, are becoming increasingly complex and/or a great number of observations is required to yield reasonably accurate results. An interesting approach to reduce the time duration of simulation is that of concurrently running multiple replications in parallel (MRIP) on a number of processors connected via networking and averaging the results adequately. We present the results of our research on the suitability of batch-means-based procedures in such distributed stochastic simulation.
Racial and ethnic service use disparities among homeless adults with severe mental illnesses receiving ACT.

OBJECTIVE Case management-based interventions aimed at improving quality of care have the potential to narrow racial and ethnic disparities among people with chronic illnesses. The aim of this study was to assess the equity effects of assertive community treatment (ACT), an evidence-based case management intervention, among homeless adults with severe mental illness. METHODS This study used baseline, three-, and 12-month data for 6,829 black, Latino, and white adults who received ACT services through the ACCESS study (Access to Community Care and Effective Services and Support). Zero-inflated Poisson random regression models were used to estimate the adjusted probability of use of outpatient psychiatric services and, among service users, the intensity of use. Odds ratios and rate ratios (RRs) were computed to assess disparities at baseline and over time. RESULTS No disparities were found in probability of use at baseline or over time. Compared with white users, baseline intensity of use was lower for black users (RR=.89; 95% confidence interval [CI]=.83-.96) and Latino users (RR=.65; CI=.52-.81]). Intensity did not change over time for whites, but it did for black and Latino users. Intensity increased for blacks between baseline and three months (RR=1.11, CI=1.06-1.17]) and baseline and 12 months (RR=1.17, CI=1.11-1.22]). Intensity of use dropped for Latinos between baseline and three months (RR=.83, CI=.70-.98). CONCLUSIONS Receipt of ACT was associated with a reduction in service use disparities for blacks but not for Latinos. Findings suggest that ACT's equity effects differ depending on race-ethnicity.
Techniques for the retrieval of aerosol properties over land and ocean using multiangle imaging

Aerosols are believed to play a direct role in the radiation budget of Earth, but their net radiative effect is not well established, particularly on regional scales. Whether aerosols heat or cool a given location depends on their composition and column amount and on the surface albedo, information that is not routinely available, especially over land. Obtaining global information on aerosol and surface radiative characteristics, over both ocean and land, is a task of the Multi-angle Imaging SpectroRadiometer (MISR), an instrument to be launched in 1998 on the Earth Observing System EOS-AM1 platform. Three algorithms are described that will be implemented to retrieve aerosol properties globally using MISR data. Because of the large volume of data to be processed on a daily basis, these algorithms rely on lookup tables of atmospheric radiative parameters and predetermined aerosol mixture models to expedite the radiative transfer (RT) calculations. Over oceans, the "dark water" algorithm is used, taking full advantage of the nature of the MISR data. Over land, a choice of algorithms is made, depending on the surface types within a scene-dark water bodies, heavily vegetated areas, or high-contrast terrain. The retrieval algorithms are tested on simulated MISR data, computed using realistic aerosol and surface reflectance models. The results indicate that aerosol optical depth can be retrieved with an accuracy of 0.05 or 10%, whichever is greater, and some information can be obtained about the aerosol chemical and physical properties.
Power Load Forecasting Based on Neural Network and Time Series

In the analysis of predicting power load forecasting based on least squares neural network, the instability of the time series could lead to decrease of prediction accuracy. On the other hand,neural network and chaos theories parameters must be carefully predetermined in establishing an efficient model. In order to solve the problems mentioned above, in this paper, the neural network and chaos theory was established. It can be seen that possessed chaotic features, providing a basis for performing short-term forecast of power load with the help of neural network theory. Chaotic Time Series method is used to find the optimal time lag. Then the time series is decomposed by wavelet transform to eliminate the instability. Chaotic Time Series method is adopted to determine the parameters of neural network. Additionally, the proposed model was tested on the prediction of share price of one listed company in China. Especially, In order to validate the rationality of chosen dimension, the other dimensions were selected to compare with the calculated dimension. And to prove the effectiveness of the model, neural network algorithm was used to compare with the result of chaos theory. Experimental results showed that the proposed model performed the best predictive accuracy and generalization, implying that integrating the wavelet transform with neural network model can serve as a promising alternative for power load forecasting.
Lipopolysaccharide elicits expression of immune‐related genes in the silkworm, Bombyx mori

Lipopolysaccharide (LPS), a major cell wall component of Gram‐negative bacteria, was found to be unable to activate immune‐related genes in Drosophila melanogaster. In contrast, highly purified LPS elicited immune‐related gene expression in the fat body of Bombyx mori. However, the level of activation by highly purified LPS was lower than crude LPS and peptidoglycan. Furthermore, synthetic lipid A also activated these genes, suggesting that B. mori possesses unknown signal pathways to activate immune‐related genes by LPS. Up‐regulation of antimicrobial peptide genes by highly purified LPS was not confirmed in the immune‐responsive cell line, NIAS‐Bm‐aff3, suggesting that some factors necessary for signal transduction activated by LPS are deficient in this cell line.
Linkage of compound objects for supporting maintenance of large-scale web sites

Departments of organizations such as companies and universities tend to publish various information on their own Web sites. For example, descriptions of the members of a certain laboratory at a university may appear on the laboratory's Web site, the department's Web site, and so on. However, inconsistencies may occur between descriptions on these sites if their update timings and management policies are different. It is not easy to find such inconsistencies on large-scale Web sites, and the maintenance costs of doing so are huge. Record linkage techniques, which determine if two entities represented as relational records are approximately the same, have been developed as ways of identifying whether two entities are approximately the same. The current methods focus on simple objects, that are represented by individual records. But objects often consist of numerous simple objects; namely, they are often compound objects. For example, a research team object may contain several researcher objects. In this case, the research team object is a compound object, and the individual researcher objects are simple objects. The current record-level linkage methods can't detect such compound objects correctly when a record of one compound object doesn't match the record of the other. We propose novel methods of linking compound objects for supporting maintenance of large-scale Web sites. We first extract the relational records of Web objects by exploiting the structure of the Web pages they are on and the linguistic features of their descriptions. To find linkable compound objects that are constituted of simple objects, after the record-level linkage, we look at the compound objects' features, i.e., records continuity, common attribute values, and co-occurrences. Experimental results show that our method can detect compound objects that can't be detected by making only record-level linkages.
Evidence-based review of subjective pediatric sleep measures.

OBJECTIVE This manuscript provides an evidence-based psychometric review of parent and child-report pediatric sleep measures using criteria developed by the American Psychological Association (APA) Division 54 Evidence-Based Assessment (EBA) Task Force. METHODS Twenty-one measures were reviewed: four measures of daytime sleepiness, four measures of sleep habits/hygiene, two measures assessing sleep-related attitudes/cognitions, five measures of sleep initiation/maintenance, and six multidimensional sleep measures. RESULTS Six of the 21 measures met "well-established" evidence-based assessment criteria. An additional eight measures were rated as "approaching well-established" and seven were rated as "promising. " CONCLUSIONS Overall, the multidimensional sleep measures received the highest ratings. Strengths and weaknesses of the measures are described. Recommendations for future pediatric sleep assessment are presented including further validation of measures, use of multiple informants, and stability of sleep measures over time.
Assessing the Exoproteome of Marine Bacteria, Lesson from a RTX-Toxin Abundantly Secreted by Phaeobacter Strain DSM 17395

Bacteria from the Roseobacter clade are abundant in surface marine ecosystems as over 10% of bacterial cells in the open ocean and 20% in coastal waters belong to this group. In order to document how these marine bacteria interact with their environment, we analyzed the exoproteome of Phaeobacter strain DSM 17395. We grew the strain in marine medium, collected the exoproteome and catalogued its content with high-throughput nanoLC-MS/MS shotgun proteomics. The major component represented 60% of the total protein content but was refractory to either classical proteomic identification or proteogenomics. We de novo sequenced this abundant protein with high-resolution tandem mass spectra which turned out being the 53 kDa RTX-toxin ZP_02147451. It comprised a peptidase M10 serralysin domain. We explained its recalcitrance to trypsin proteolysis and proteomic identification by its unusual low number of basic residues. We found this is a conserved trait in RTX-toxins from Roseobacter strains which probably explains their persistence in the harsh conditions around bacteria. Comprehensive analysis of exoproteomes from environmental bacteria should take into account this proteolytic recalcitrance.
Design of frequency generator and amplifier level converter using 300nm CMOS technology for electro capacitive cancer therapy (ECCT) standard operation mode system

Electro capacitive cancer therapy (ECCT) system are constructed by six sub-systems, in this paper presented design and simulation for two sub-system in ECCT namely frequency generator and amplifier level converter. Design of two sub-system become first study for ECCT system can be applying to the IC technology. Design process begins with understand ECCT standard operation mode signal specification like input signal voltage, output signal voltage, form and frequency. Then using ring oscillator, negative clamper biased, two stage operational amplifier (op amp) circuits that estimated can produce those signal specification and layout them based on BSIM 3.1 MOSFET model using 300nm CMOS technology. Simulation result show that the system layout can produce 19Vpp, 100 kHz and asymmetric output signal from 5 volt DC input signal.
An E cient Solution to Tra c Characterization ofVBR Video in Quality-of-Service Networks

A network that ooers deterministic, i.e., worst-case, quality-of-service (QoS) guarantees to variable-bit-rate (VBR) video must provide a resource reservation mechanism that allocates bandwidth, buuer space, and other resources for each video connection. Such a resource reservation scheme must be carefully designed, otherwise network resources are wasted. A key issue for the design of a resource reservation scheme is the selection of a traac characterization that speciies the traac arrivals on a video connection. The traac characterization should accurately describe the actual arrivals so that a large number of connections can be supported, but it must also map directly into eecient traac policing mechanisms that monitor arrivals on each connection. In this study, we present a fast and accurate traac characterization method for stored VBR video in networks with a deterministic service. Our characterization approach approximates the so-called empirical envelope of a video sequence. We use this approximation to obtain a traac characterization that can be eeciently policed by a small number of leaky buckets. We present a case study where we apply our characterization method to networks that employ a dynamic resource reservation scheme with renegotiation. We use traces from a set of 25-30 minute MPEG sequences to evaluate our method against other characterization schemes from the literature.
The Interactive Effects of Recovery Mode and Duration on Subsequent Repeated Sprint Performance

Abstract Brown, J and Glaister, M. The interactive effects of recovery mode and duration on subsequent repeated sprint performance. J Strength Cond Res 28(3): 651–660, 2014—The aim of this study was to examine the interactive effects of recovery mode and duration on subsequent repeated short sprint (RSS) performance. Ten male recreational athletes (age, 27.9 ± 5.0 years; height, 1.80 ± 0.07 m; mass, 81.6 ± 13.5 kg) performed 4 randomized trials consisting of a 30-second cycle sprint, followed by a specified recovery period (45 or 180 seconds), and a subsequent set of RSS (7 × 5 seconds, 20-second passive rest periods). Recovery mode was either active (AR; 70% of the power output at lactate threshold) or passive (PR). Mean heart rate and V[Combining Dot Above]O2 were significantly higher (p ⩽ 0.05) in AR than in PR over both recovery durations. Although the difference in V[Combining Dot Above]O2 reached significance after 10–15 seconds, a significant (p ⩽ 0.05) difference in heart rate was observed only after 26 seconds (45-second trials) − 75 seconds (180-second trials). Blood lactate was significantly (p ⩽ 0.05) lower in AR than in PR only after 135 seconds (mean difference, 2.16 mmol·L−1; 95% likely range, 0.77–3.55 mmol·L−1). Mean peak power output in the RSS test was significantly (p ⩽ 0.05) higher following PR45 than AR45 (12.0 ± 1.4 vs. 11.4 ± 1.4 W·kg−1) and following AR180 than PR180 (12.7 ± 1.2 vs. 12.0 ± 1.2 W·kg−1). In conclusion, when rest periods are short, a PR strategy appears to optimize subsequent RSS performance. However, as the recovery duration increases subsequent RSS performance appears to benefit from an AR strategy.
The small pyramidal neuron of the rat cerebral cortex. The perikaryon, dendrites and spines.

The small pyramidal neurons of layers II and III of the rat parietal cortex have been examined with both Golgi staining and electron microscopy. The cell body contains a large nucleus and only a thin rim of cytoplasm in which the Nissl substance is not well developed. A cap of Nissl substance occurs at the base of the apical dendrite, however, and a number of cisternae of the Golgi apparatus occur in this same location. A centriole is often found here too, so that this region of the neuron represents the cell center. Little Nissl substance occurs in the dendrites, which mainly contain well-ordered arrays of microtubules. Projecting from the stem of the apical dendrite and from the secondary dendrites are spines. Basically, the spines are of three types. The most common ones have long, thin stalks and small end bulbs. The least common ones are mushroom-shaped and have thick stalks ending in large bulbs. The other spines are short and stubby, and have no well-defined stalk. The distribution of these three types of spines has been determined. Although they are rare, spines may also project from the cell body, which has very few synapses on its surface.
Optimizing E-tailer Profits and Customer Savings: Pricing Multistage Customized Online Bundles

Online retailing provides an opportunity for new pricing options that are not feasible in traditional retail settings. This paper proposes an interactive, dynamic pricing strategy from the perspective of customized bundling to derive savings for customers while maximizing profits for electronic retailers (“e-tailers”). Given product costs, posted prices, shipping fees, and customers' reservation prices, we propose a nonlinear mixed-integer programming model to increase e-tailers' profits by sequentially pricing customized bundles. The model is flexible in terms of the number and variety of products customers may choose to incorporate during the various stages of their online shopping. Our computational study suggests that the proposed model not only attracts more customers to purchase the discounted bundle but also noticeably increases profits for e-tailers. This online dynamic bundle pricing model is robust under various bundle sizes and scenarios. It improves e-tailer profit and customer savings the most when facing divergent views about product values, lower budgets, and higher cost ratios.
A rejection technique for sampling from T-concave distributions

A rejection algorithm that uses a new method for constructing simple hat functions for a unimodal, bounded density <italic>f</italic> is introduced called “transformed density rejection. ” It is based on the idea of transforming <italic>f</italic> with a suitable transformation <italic>T</italic> such that <italic>T(f(x))</italic> is concave. <italic>f</italic> is then called <italic>T</italic>-concave, and tangents of <italic>T(f(x))</italic> in the mode and in a point on the left and right side are used to construct a hat function with a table-mountain shape. It is possible to give conditions for the optimal choice of these points of contact. With <italic>T</italic>= -1/xxx, the method can be used to construct a universal algorithm that is applicable to a large class of unimodal distributions, including the normal, beta, gamma, and <italic>t</italic>-distribution.
SHRiNK: Enabling scaleable performance prediction and efficient simulation of networks

— As the Internet grows, it is becoming increasingly dif ﬁ cult to collect performance measurements of a network or a web-server farm, to monitor its state, and to perform simulations ef ﬁ ciently. Besides, the heterogeneity of the Internet makes it time-consuming and dif ﬁ cult to devise traf ﬁ c models and analytic tools which would allow us to work with summary statistics. We explore a method to side-step these problems by combining sampling, modeling and simulation. Our hypothesis is this: if we take a sample of the input traf ﬁ c, and feed it into a suitably scaled version of the system, we can extrapolate from the performance of the scaled system to that of the original. Our main ﬁ ndings are: When we scale an IP network which is shared by short-and long-lived TCP-like and UDP ﬂ ows; and which is controlled by a variety of active queue management schemes, then performance measures such as queueing delay and drop probability are left virtually unchanged. We show this in theory and in simulations. This makes it possible to capture the performance of large networks quite faithfully using smaller scale replicas.
A Study on the Influence of Speed on Road Roughness Sensing: The SmartRoadSense Case †

SmartRoadSense is a crowdsensing project aimed at monitoring the conditions of the road surface. Using the sensors of a smartphone, SmartRoadSense monitors the vertical accelerations inside a vehicle traveling the road and extracts a roughness index conveying information about the road conditions. The roughness index and the smartphone GPS data are periodically sent to a central server where they are processed, associated with the specific road, and aggregated with data measured by other smartphones. This paper studies how the smartphone vertical accelerations and the roughness index are related to the vehicle speed. It is shown that the dependence can be locally approximated with a gamma (power) law. Extensive experimental results using data extracted from SmartRoadSense database confirm the gamma law relationship between the roughness index and the vehicle speed. The gamma law is then used for improving the SmartRoadSense data aggregation accounting for the effect of vehicle speed.