Miracle-dz/UniFAR-FTUs huggingface dataset:
A Random Walk Through Large Data: Caveats Regarding the Potential for False Inference.

The field of transplantation has been fortunate to have several large, well-managed data sets to track patient outcomes after organ transplantation. Although much important information has been obtained from these data sets, there are important caveats and potential limitations that must be acknowledged. This short commentary will cover issues pertaining to the process of analyzing or “mining” these large data sets. Data mining (ie, the utilization of sophisticated mathematical and statistical techniques to find patterns and associations within very large data collections) is a sound and useful discovery technique that, like any analytic endeavor, must be put into context. However, one must keep in mind that the inferences garnered from these analyses are exploratory by nature. The Organ Procurement and Transplantation Network's Scientific Registry of Transplant Recipients (SRTR), a data set that has been built and improved over time by groups in both Ann Arbor, MI, and now Minneapolis, MN, and has served as a seminal resource for aggregating the clinical outcomes for transplant patients in the United States. The data sets have been strengthened over the past 2 decades through linkages to external data sources. Linkage to the Centers for Medicare andMedicaid Services ensure that any graft failure is caught as soon as the patient returns to dialysis (before this linkage, nonreporting was a major issue). Linkage to Social Security Administration files allows for accurate assessment of death (again, before this linkage, failure to report death was a major issue). In addition, the SRTR has continually, added variables and fine-tuned the imputation of missing data to increase the accuracy and completeness of the data set. This data set has led to frequent scientific inquiry and analysis, a major strength of this data set.Many other important data sets are also available and, while the particular details of each data set is outside of the scope of this article, the statistical concepts and principles will apply to any large regional, national, or multinational data set.
Application of log-cumulants to the detection of spatiotemporal discontinuities in multitemporal SAR images

Multitemporal satellite synthetic aperture radar (SAR) images are a useful source of information for geophysicists to monitor changing regions. In this paper, a new approach is proposed to extract from multitemporal SAR images two kinds of information: temporal changes (flooded areas, coastline erosion, etc.) and stable spatial features (roads, rivers, etc.). The novelty of the proposed approach is to detect simultaneously these two kinds of discontinuities. In a first step, the contrast and the heterogeneity information is extracted by a "multitemporal" application of the ratio of local means and by new three-dimensional texture parameters based on the log-cumulants. In a second step, the resulting attributes that measure the time variability or the presence of spatial features are merged. An interactive fuzzy fusion approach is proposed to provide end-users with a simple and easily understandable tool for tuning the change-detection results. The performances of the proposed attributes and fusion technique are presented on a set of seven multitemporal SAR images acquired by the European Remote Sensing (ERS-1) satellite.
Identifying differences of travel time budgets between the elderly and the nonelderly groups using PSL structural equation models: A case study for Seoul metropolitan area

ABSTRACT To date, aging is one of the most important issues in our society because of its significant socioeconomic impacts. Corresponding concerns about the transportation needs of the elderly have led to a focus on the mobility and quality of life of the elderly and motivated various studies of senior mobility. As the fastest aging country in the world, Korea will need to provide insightful information for an aging society. The purpose of this study is to investigate the difference in travel behavior between the elderly and the nonelderly groups by focusing on travel time budget (TTB), using the 2006 household travel diary survey data from the Seoul metropolitan area. We develop partial least square (PLS) structural equation models to identify major variables that affect the TTB of each of the two groups and then compare the differences between the models. Model results indicate that the significant explanatory variables differ between the two age groups, and the degree to which the variables affect the TTB differs by personal and household characteristics.
Subhashinie coli Isolates among Extraintestinal and Commensal E . Escherichia coli Strain O 1 Genomic Islands Prevalence of Avian-Pathogenic

Escherichia coli strains that cause disease outside the intestine are known as extraintestinal pathogenic E. coli (ExPEC) and include pathogens of humans and animals. Previously, the genome of avian-pathogenic E. coli (APEC) O1:K1:H7 strain O1, from ST95, was sequenced and compared to those of several other E. coli strains, identifying 43 genomic islands. Here, the genomic islands of APEC O1 were compared to those of other sequenced E. coli strains, and the distribution of 81 genes belonging to 12 APEC O1 genomic islands among 828 human and avian ExPEC and commensal E. coli isolates was determined. Multiple islands were highly prevalent among isolates belonging to the O1 and O18 serogroups within phylogenetic group B2, which are implicated in human neonatal meningitis. Because of the extensive genomic similarities between APEC O1 and other human ExPEC strains belonging to the ST95 phylogenetic lineage, its ability to cause disease in a rat model of sepsis and meningitis was assessed. Unlike other ST95 lineage strains, APEC O1 was unable to cause bacteremia or meningitis in the neonatal rat model and was significantly less virulent than uropathogenic E. coli (UPEC) CFT073 in a mouse sepsis model, despite carrying multiple neonatal meningitis E. coli (NMEC) virulence factors and belonging to the ST95 phylogenetic lineage. These results suggest that host adaptation or genome modifications have occurred either in APEC O1 or in highly virulent ExPEC isolates, resulting in differences in pathogenicity. Overall, the genomic islands examined provide targets for further discrimination of the different ExPEC subpathotypes, serogroups, phylogenetic types, and sequence types. Disciplines Bacteriology | Genomics | Veterinary Microbiology and Immunobiology | Veterinary Preventive Medicine, Epidemiology, and Public Health Comments This article is from Journal of Bacteriology 194, no. 11 ( June 2012): 2846–2853, doi:10.1128/JB.06375-11. Authors Timothy J. Johnson, Yvonne Wannemuehler, Subhashinie Kariyawasam, James R. Johnson, Catherine M. Logue, and Lisa K. Nolan This article is available at Iowa State University Digital Repository: http://lib.dr.iastate.edu/vmpm_pubs/26 Published Ahead of Print 30 March 2012. 2012, 194(11):2846. DOI: 10.1128/JB.06375-11. J. Bacteriol. Lisa K. Nolan Kariyawasam, James R. Johnson, Catherine M. Logue and Timothy J. Johnson, Yvonne Wannemuehler, Subhashinie coli Isolates among Extraintestinal and Commensal E. Escherichia coli Strain O1 Genomic Islands Prevalence of Avian-Pathogenic http://jb.asm. org/content/194/11/2846 Updated information and services can be found at:
Numerical calculation of line-to-line short circuit fault for single-cage induction motor

A line-to-line short circuit fault of a stator is one of come faults in the real working process of single cage induction motors. Therefore, studying the electromagnetic field and electromagnetic force after faults is of great importance. In this paper, the transient mathematical theory model of the line-to-line faults of squirrel cage induction motors was presented, and the two dimensional field circuit coupling electromagnetic force calculation model was proposed based on finite element method and stress tensor method. Finite element software was used to analyze the rotor electromagnetic field distribution after short circuit faults of motors. The three dimensional dynamic diagram of magnetic flux density in the normal and tangential directions of motor rotor was evaluated by field calculator. Harmonic analysis was performed for key moments within one period after a fault, in order to obtain the harmonic amplitude contents of each key moment and to find the main harmonic frequency and key moments affecting the electromagnetic force. Calculation results indicated that the rotor changes after faults under electromagnetic force of air gap and the electromagnetic forces in normal and tangential directions were respectively 1.2 and 1.8 times those of rated operation.
Biotic and abiotic factors affecting the δ13C of soil respired CO 2 in a Mediterranean oak woodland

The flux (R s) and carbon isotopic composition (δ13C Rs ) of soil respired CO 2 was measured every 2 h over the course of three diel cycles in a Mediterranean oak woodland, together with measurements of the δ13C composition of leaf, root and soil organic matter (δ13C SOM) and metabolites. Simulations of R s and δ13C Rs were also made using a numerical model parameterised with the SOM data and assuming short-term production rates were driven mainly by temperature. Average values of δ13C Rs over the study period were within the range of root metabolite and average δ13C SOM values, but enriched in 13C relative to the bulk δ13C of leaf, litter, and roots and the upper soil organic layers. There was good agreement between model output and observed CO 2 fluxes and the underlying features of δ13C Rs . Observed diel variations of 0.5 ‰ in δ13C Rs were predicted by the model in response to temperature-related shifts in production rates along a ∼3 ‰ gradient observed in the profile of δ13C SOM. However, observed δ13C Rs varied by over 2 ‰, indicating that both dynamics in soil respiratory metabolism and physical processes can influence short-term variability of δ13C Rs .
Dynamic Asset Allocation in the Presence of Housing and Incomplete Markets

This paper studies in continuous time and in an incomplete market setting the optimal housing, consumption, labor and portfolio choice of an agent in the presence of stochastic house prices and wages. Thus, the house prices and wage rates cannot be spanned by the financial market. In particular, the paper investigates the optimal strategies under two different preference specifications with respect to housing. The paper provides new closed-form solutions in the special case in which the market is complete. In addition, the paper also studies the optimal housing, consumption, labor, portfolio and welfare implications of frictions in the housing market. Particularly, the optimal strategies and welfare loss are analyzed if the house is a non-traded asset. This paper suggests that the consumption, labor, speculative investment and hedging of human capital is similar across preference specification and frictions in the market for housing when the economy is complete. The consumption and labor strategies are, however, dependent on frictions in the market for housing in the case where the economy is incomplete. The welfare loss from these frictions is small in magnitude but will influence the optimal consumption, labor and portfolio choice.
The Asymmetric Response of Gasoline Prices to International Crude Oil Price Changes Considering Inventories

: This study analyzed the impact of crude oil inventory while gasoline price adjusts to international crude oil price(WTI) fluctuations. We mainly focused on asymmetric relationship between crude oil and petroleum product prices and added oil inventory as an variable, using the error correction model which is based on Borenstein et al.(1997). This paper selected the sample period from January 1988 to December 2012, analyzed the asymmetry of each intervals and the influence of crude oil inventory to the degree of asymmetry changes, both full period and five years period respectively. The results showed that when considering crude oil inventory, existence and degrees of time ․ amount asymmetry varies.
Optical properties of high aspect ratio plasma etched silicon nanowires: fabrication-induced variability dramatically reduces reflectance

In this work we investigate both experimentally and theoretically the optical properties of aligned, perpendicular to the substrate, high aspect ratio (AR), plasma etched Si nanowires (SiNWs) with controlled variability. We focus on the role of imperfections in fabrication, which manifest themselves as dimensional variability of SiNW, lattice defects or positional randomization. SiNW arrays are fabricated by e-beam lithography (perfectly ordered array) or colloidal particle self-assembly (quasi-ordered array) followed by cryogenic Si plasma etching, which offers fast etch rate (up to 3 μm min−1) combined with clean, smooth, and controllable sidewall profile, but induces some dimensional variability on the diameters of the SiNWs. Sub-200 nm diameter SiNWs having AR as high as 37:1 are demonstrated. The total reflectance of SiNWs is below 2% in a wide range of the optical spectrum. We experimentally demonstrate improved light absorption when moving from a perfectly ordered (after e-beam lithography) to a defective and quasi-ordered (after colloidal self-assembly) SiNW array. In addition our measured reflectivity (for both ordered and quasi-ordered SiNWs) is much lower compared to the one predicted theoretically for a perfect SiNWs array, using full-electrodynamic calculations with the layer-multiple-scattering method. To explain such low reflectivity, we model the influence of disorder using the average T-matrix approximation and show that even small dimensional variability (10–20%) leads to dramatic reduction of the reflectance (matching the experimental results) and increased light trapping inside the SiNW justifying their possible application in photovoltaic devices.
Energy efficient Wireless Sensor Networks using FAF and dual cluster head technique for weed detection

The main challenge of Wireless Sensor Networks is to transfer the data with less cost and energy. Another requirement of efficient WSN is to have a maximum lifetime of sensor nodes. This lifetime of sensor nodes gets reduced due to usage of large amounts of energy and fading. To overcome this barrier, many techniques such as, LEACH, PEGASIS etc., are invented over the decades. Existing system used single cluster head to transfer the data from nodes to base station. This paper proposes the concept of dual cluster head which follows sleep and awake modes to share the work load. AODV routing protocol is used in this technique. Here the next hop is selected based on forward aware factor (FAF). This system improved the energy efficiency and reduced the delay. Experimental results are compared with LEACH and PEGASIS. It has been proved that this system outstripped the other traditional systems. This technique can be used for weed detection among cereal crops.
Turbo detection and decoding for single-carrier block transmission systems

We study the low complexity turbo detector for cyclic prefix based single-carrier block transmission (CP-SCBT) systems with multiple receive antennas. It has the following characteristics: firstly, it can be implemented by FFT/IFFT with low complexity; secondly, along with SISO decoder, turbo detection can be applied. Simulation results show that the iterative receiver provides much better performance than the conventional CP-SCBT system. It also outperforms its coded OFDM counterpart. The most attractive advantage is that it can be implemented by FFT/IFFT without significantly increasing the complexity of the system.
Quantum Dots: Next Generation of Smart Nano-Systems.

BACKGROUND The amalgamation of biological sciences with nano stuff has significantly expedited the progress of biological strategies, greatly promoting practical applications in biomedical fields. OBJECTIVE With distinct optical attributes (e.g., robust photostability, restricted emission spectra, tunable broad excitation, and high quantum output), fluorescent quantum dots (QDs) have been feasibly functionalized with manageable interfaces and considerably utilized as a new class of optical probe in biological investigations. METHODS In this review article, we structured the current advancements in the preparation methods and attributes of QDs. Furthermore, we extend an overview of the outstanding potential of QDs for biomedical research and radical approaches to drug delivery. CONCLUSION Notably, the applications of QDs as smart next-generation nanosystems for neuroscience and pharmacokinetic studies have been explained. Moreover, recent interests in the potential toxicity of QDs are also apprised, ranging from cell investigations to animal studies.
Climate, history and neutrality as drivers of mammal beta diversity in Europe: insights from multiscale deconstruction.

1. Environmental sorting, historical factors and neutral dynamics may all drive beta diversity (change in species composition across space), but their relative importance remains unresolved. In the case of European mammals, key potential drivers of large-scale beta diversity include current climate, neutral dynamics and two historical factors: Pleistocene glaciations and peninsular dynamics (immigration from extra-regional eastern faunal source areas and inter-linked relictual survival and evolutionary differentiation in isolated areas). 2. We assessed the relative importance of these drivers using a novel analytical framework to deconstruct beta diversity of non-volant mammals in Europe (138 species) into its turnover (change in species composition because of species replacements) and nestedness components (change in species composition because of species richness differences) at continental and regional (250,000 km(2) ) scales. 3. We found continental-scale mammal beta diversity to be mainly caused by spatial turnover (99·9%), with only a small contribution (0·1%) from nestedness. 4. Current climate emerged as an important driver of beta diversity, given the strong continental-scale turnover, particularly in north-south direction, i.e., in line with the latitudinal climate gradient, and, more directly, the strong correlation of climate with spatial turnover at both continental and regional scales. 5. However, there was also evidence for the importance of non-climatic drivers. Notably, the compositional variation purely accounted for by space was greater than that purely accounted for by environment for both the turnover and the nestedness component of beta diversity. Furthermore, the strong longitudinal turnover within Southern Europe is in accordance with the region's long-term climatic stability having allowed multiple refugia and local evolutionary diversification. As expected from peninsular dynamics, there was increasing dissimilarity with geographic distance in an east-west direction because of nestedness, but only in Central and Northern Europe. 6. In conclusion, European mammal beta diversity mainly reflects spatial turnover and only to a limited extent nestedness and is driven by current climate in combination with historical - and perhaps, neutral - dynamics. These findings suggest that a key challenge for climate-change predictive studies will be taking the influence of non-climatic factors into account.
Three Essays on Earnings Dynamics

This thesis consists of three essays that use modern econometric methods to empirically study earnings dynamics in the United States using samples drawn from the Panel Study of Income Dynamics (PSID). In Chapter 2, I study a non-linear parametric model that allows an agent’s future earning to depend on the earning quantile he occupies in the current period. Such dynamics reflect a different set of opportunities opened up to an agent once he changes position in the earning distribution. Chapter 3 extends the model presented in Chapter 2 to take into account the accumulation of agents’ past experiences by allowing an agent’s earning process to depend on both his current quantile position and the average of his previous quantiles. The current quantile position represents an agent’s current opportunity or luck whereas the average of his previous quantiles assumes the role of his past experiences. I estimate the models using a method of indirect inference called simulated minimum distance. I find that the underlying process differs across the earning distribution. In particular, individuals in the bottom quantile have a unit root process whereas individuals in upper quantiles have a stationary process with the top quantile workers having the lowest autoregressive coefficients. Chapter 3 shows that a model specification with a higher weight assigned to luck, i the current quantile position, has better predictions for the earning mobility presented from the data. This result implies that luck certainly plays a role in the earning process. In Chapter 4, I study the earning mobility of US households using nonparametric quantile regressions. I estimate future earning quantiles for individuals from every initial earning level. I find that earning mobility tends to improve in more recent years or over a longer time span. Moreover, the substantial non-linearity found in upper earning distribution suggests that relatively higher earners face more earning uncertainty than others. In addition, the slopes of quantiles as a function of initial earnings are flatter in the long run. Therefore, more than half of high earners experience an earning decline whereas the majority of low earners experience an earning increase in the long run.
THE IMPACT OF TRANSFORMATIONAL LEADERSHIP AND CONTINGENT REWARD LEADERSHIP STYLES ON INNOVATIVE BEHAVIOUR: MEDIATING ROLE OF LEADER-MEMBER EXCHANGE QUALITY

Innovation is utmost factor of organizational success during the period of unbelievable global competition. Innovation is generally triggered by leader’s strategic behaviors and leadership styles are decisive in organizations’ vision and mission nowadays. Employee’s innovation perception and also innovative behavior have an important role at the execution process of innovation. From this aspect, determination of factors which effect innovative behavior is an important research area. The paper focus on the determination of leader-member exchange quality’s (LMX) mediator role at the effects of transformational and contingent reward leadership’s style, at private and public sector, to employee’s innovative behaviors
A comparison of neural network methods for unsupervised representation learning on the zero resource speech challenge

The success of supervised deep neural networks (DNNs) in speech recognition cannot be transferred to zero-resource languages where the requisite transcriptions are unavailable. We investigate unsupervised neural network based methods for learning frame-level representations. Good frame representations eliminate differences in accent, gender, channel characteristics, and other factors to model subword units for withinand acrossspeaker phonetic discrimination. We enhance the correspondence autoencoder (cAE) and show that it can transform Mel Frequency Cepstral Coefficients (MFCCs) into more effective frame representations given a set of matched word pairs from an unsupervised term discovery (UTD) system. The cAE combines the feature extraction power of autoencoders with the weak supervision signal from UTD pairs to better approximate the extrinsic task’s objective during training. We use the Zero Resource Speech Challenge’s minimal triphone pair ABX discrimination task to evaluate our methods. Optimizing a cAE architecture on English and applying it to a zero-resource language, Xitsonga, we obtain a relative error rate reduction of 35% compared to the original MFCCs. We also show that Xitsonga frame representations extracted from the bottleneck layer of a supervised DNN trained on English can be further enhanced by the cAE, yielding a relative error rate reduction of 39%.