Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancer-Trap Flippase Lines for Clonal Analysis in the Drosophila Ovary

The Drosophila melanogaster genetic tool box includes many stocks for generating genetically mosaic tissue in which a clone of cells, related by lineage, contain a common genetic alteration. These tools have made it possible to study the postembryonic function of essential genes and to better understand how individual cells interact within intact tissues. We have screened through 201 enhancer-trap flippase lines to identify lines that produce useful clone patterns in the adult ovary. We found that approximately 70% of the lines produced clones that were present in the adult ovary and that many ovarian cell types were represented among the different clone patterns produced by these lines. We have also identified and further characterized five particularly useful enhancer-trap flippase lines. These lines make it possible to generate clones specifically in germ cells, escort cells, prefollicle cells, or terminal filament cells. In addition, we have found that chickadee is specifically upregulated in the posterior escort cells, follicle stem cells, and prefollicle cells that comprise the follicle stem cell niche region. Collectively, these studies provide several new tools for genetic mosaic analysis in the Drosophila ovary.
Demonstration of Hepatitis C Virus RNA with In Situ Hybridization Employing a Locked Nucleic Acid Probe in Humanized Liver of Infected Chimeric Mice and in Needle-Biopsied Human Liver

Background. In situ hybridization (ISH) with high sensitivity has been requested to demonstrate hepatitis C virus (HCV) RNA in formalin-fixed, paraffin-embedded (FFPE) sections of the liver. Methods. ISH employing a locked-nucleic-acid- (LNA-)modified oligonucleotide probe and biotin-free catalyzed signal amplification system (CSAII) was applied to HCV-RNA detection in the liver tissue. Nested reverse-transcription polymerase chain reaction (RT-PCR) was performed for HCV genotyping using total RNA extracted from FFPE sections. The target tissues included FFPE tissue sections of humanized livers in HCV-infected chimeric mice (HCV genotypes 1a, 1b, and 2a and noninfected) and of needle-biopsied livers from HCV-infected patients. Results. HCV-RNA was demonstrated with the ISH technique in HCV-infected liver tissues from both chimeric mice and 9 (82%) of 11 patients with HCV infection. The HCV signals were sensitive to RNase. Nested RT-PCR confirmed the genotype in 8 (73%) of 11 livers (type 1b: 6 lesions and type 2a: 2 lesions). HCV-RNA was not identified in chronic hepatitis B lesions, fatty liver, autoimmune hepatitis, and hepatocellular carcinoma. Conclusion. ISH using the LNA-modified oligonucleotide probe and CSAII was applicable to detecting HCV-RNA in routinely prepared FFPE liver specimens.
On Returns Differentials

Estimates of U.S. returns differentials have ranged from exorbitant to quite small, in part because of their volatility coupled with the relatively short time series available. We shed light on underlying drivers of returns differentials by presenting a number of decompositions: a by-asset-class decomposition into yields and capital gains, the Gourinchas and Rey (2007a) composition and return effects, and further decompositions of capital gains that focus on exchange rate effects. While each decomposition informs thinking about returns differentials, one constant is evident throughout: to date the existing differential favoring the U.S. has owed primarily to one factor, a differential in direct investment yields. We discuss how our analysis informs the income puzzle (of positive net income flows to the U.S. even as its net international investment position is negative and substantial) and the position puzzle (of a sizeable gap between the reported U.S. net international position and cumulated current account deficits), provide an initial assessment of the literature on the dynamics of returns differentials, and present a framework to guide a forward-looking view of how returns differentials might evolve in the future.
Energy-Efficient Simultaneous Localization and Mapping via Compounded Approximate Computing

We present an energy-efficient implementation of RGB-D simultaneous localization and mapping (SLAM) by applying approximate computing (AC) techniques such as loop perforation (LP) and reduced precision (RP). To reduce processing time and power consumption, LP and RP were applied to the two most computationally challenging portion of the multi-kernel pipeline of SLAM, i.e., SIFT feature detection/extraction and graph-based global pose optimization. We discover that approximation errors on the target kernels can be tolerated due to not only the inherent robustness of the kernel itself but also repairing process of the subsequent functions. Experimental results, assuming the approximated hardware architecture, demonstrate that our approximated SLAM can achieve 48.5% reduction in execution time and up to 71.8% power reduction for the common indoor SLAM scenarios - with negligible changes in quality.
Bit Error Probability and Computational Complexity of Bi-directonal Fano Multiple Symbol Differential Detectors

We present in the paper a suboptimal multiple-symbol differential detector (MSDD) for differential PSK (DPSK) in Rayleigh flat fading channel that uses the Fano Algorithm as its decoding engine. In contrast to a conventional Fano decoder that only searches forward in time for the most promising transmitted pattern, our Fano decoder searches also in the reverse direction, thus providing a mechanism for error detection and correction. The resultant detector, termed a Bi-Fano MSDD, is capable of delivering excellent error performance at moderate implementation complexity over a wide range of signal-to-noise ration (SNR) and fading rates. As an example, for DQPSK modulation and a Doppler frequency of 3 percent the symbol rate, our Bi-Fano MSDD attains almost the same bit-error probability (BEP) performance as the sphere decoder (an efficient implementation of the optimal MSDD) and there is no noticeable irreducible error floor. The most interesting thing is that the computational complexity of the Bi-Fano MSDD is a very stable function of the SNR. In contrast, the sphere decoder has a complexity that grows exponentially as the SNR decreases. In conclusion, the Bi-Fano MSDD incorporates the desirable attributes of the sphere decoder and the DF-DD into one single embodiment. This is consistent with the observation that the Fano decoder is essentially an intelligent DF-DD that uses the accumulated path metric and a running threshold to guide its movement along the decoding tree
Yearly quotas and country-reserved shares in Italian immigration policy

Regular immigration to Italy is based on a quota system setting annual ceilings to legal entries. Reserved shares are granted to single countries or categories of countries. Reserved shares have been increased; they are used as an incentive to obtain the cooperation of countries of origin in stemming irregular migration flows. The total quota of regular immigration has gradually increased too. Still, it does not fully respond to the growing demand of foreign workers on the labour market, and quotas seem to be used as crypto-regularisations rather than as an instrument for regulating legal entries.
Earth and Planetary Science Letters Generation of Tectonic Over-pressure inside Subducting Oceanic Lithosphere Involving Phase-loop of Olivine–wadsleyite Transition

a r t i c l e i n f o a b s t r a c t Keywords: tectonic over-pressure phase transition phase loop olivine–spinel coexistence zone shear heating subducting slab We conducted a two-dimensional numerical model to analyze the generation of tectonic over-pressure, which is a positive deviation from lithostatic pressure, for deep slabs which are anchored at the 660 km phase boundary. The formation of the ductile shear zone under a compressional tectonic setting induces tectonic over-pressure. We first propose that an apparent shear zone originated from an elastic heterogeneity in the phase loop, which is the two-phase (i.e., olivine and wadsleyite) coexistence interval around the 410 km boundary within subducting oceanic lithospheres, can cause tectonic over-pressure with a range from 0.3 to 1.5 GPa. This over-pressure significantly impacts the formation of the olivine–wadsleyite phase transition. The flattening of the olivine–wadsleyite interface by over-pressure is well-resolved. Therefore, we argue that the over-pressure should be applied when analyzing the phase boundary within the subducting lithosphere. Our results provide a new insight on the interplay among the phase transition, shear zone formation and tectonic over-pressure. Pressure at depth in terrestrial planets, which is one of the most important environmental variables controlling geodynamical phenomena such as solid–solid phase transitions and brittle/duc-tile deformation, has been simply interpreted to be the hydrostatic pressure. The pressure distribution inside the Earth is more mono-tonic than that of temperature and deviatoric stress, which can largely vary with short-wavelength perturbations such as mechan-Thus, one might have supposed that the pressure can directly indicate the depth at which high-pressure metamorphism generally occurs. For this reason , the influence of dynamical pressure in geodynamics has been relatively underestimated compared with that of temperature and deviatoric stress. However, the lithostatic pressure assumption is appropriate only for the case of a static or quasi-static lithosphere without shear stress (Mancktelow, 2008). As a result, the depth-estimation based on exhumed high-pressure metamorphic rocks may have an inaccuracy (Schmalholz and Podladchikov, 2014). For more realistic situations where dynamic deformation regimes, including compression, extension, bending and buckling, are taken into account, we should consider tectonic pressure which is an additional pressure generated by the deformation process itself (e.g., Moulas et al., 2013; Schmalholz and Podladchikov, 2013). Henceforth we can deduce that the total pressure is the sum of litho-static and tectonic pressures. The tectonic pressure has positive (i.e., tectonic over-pressure) or negative (i.e., …
SV MACHINES FOR FUNCTION ESTIMATION COVERING QUADRATIC PROGRAMMING WITH LARGE DATA SETS USING FOR INTERIOR POINT

Support Vector Machines (SVM) algorithms combine the simplicity and computational efficiency of linear algorithms, such as the perception algorithm or ridge regression, with the flexibility of nonlinear systems, like neural networks, and rigor of statistical approaches, as regularization methods in multivariate statistics, these algorithms typically reduce the learning step to a convex optimization problem that can always be solved in polynomial time, avoiding the problem of local minima typical of neural networks, decision trees and other nonlinear approaches. The problem of regression is that of finding a function which approximates mapping from an input domain to the real numbers based on a training sample. The basic idea underlying Support Vector (SV) machines for function estimation using interior point algorithm covering both primal and dual optimization extended to SVM regression function with large data sets. Solving by a predictor–corrector method iteratively and the similar data’s are fused together to get maximum accuracy of optimization solution of large data.
Effects of hoarseness on hypernasality ratings

We investigated how hoarseness effects perceived hypernasality ratings in order to make a rating scale for hoarse voices. Thirty stimuli, of which 18 were target stimuli (three each for voices with and without hoarseness at three levels of hypernasality), and of which 12 were foil stimuli. These voices were listened to by four experienced speech pathologists. They were asked to rate hypernasality on 5-point scale. Perceived hypernasality decreased with hoarseness for a severely hypernasal voice, but results varied among the listeners for voices with no and moderate hypernasality.
Anomaly Behavior Analysis of DNS Protocol

DNS protocol is critically important for secure network operations. All networked applications request DNS protocol to translate the network domain names to correct IP addresses. The DNS protocol is prone to attacks like cache poisoning attacks and DNS hijacking attacks that can lead to compromising user’s accounts and stored information. In this paper, we present an anomaly based Intrusion Detection System (IDS) for the DNS protocol (DNS-IDS) that models the normal operations of the DNS protocol and accurately detects any abnormal behavior or exploitation of the protocol. The DNS-IDS system operates in two phases, the training phase and the operational phase. In the training phase, the normal behavior of the DNS protocol is modeled as a finite state machine where we derive the temporal statistics of normal DNS traffic. Then we develop an anomaly metric for the DNS protocol that is a function of the temporal statistics for both the normal and abnormal transitions of the DNS protocol. During the operational phase, the anomaly metric is used to detect DNS attacks (both known and novel attacks). We have evaluated our approach against a wide range of DNS attacks (DNS hijacking, Kaminsky attack, amplification attack, Birthday attack, DNS Rebinding attack). Our results show attack detection rate of 97% with very low false positive alarm rate (0.01397%), and round 3% false negatives.
Prognostic Models: A Methodological Framework and Review of Models for Breast Cancer

Prognostic models are widely used in cancer for investigating patient outcome in relation to multiple patient and disease characteristics. Such a model may allow the (reasonably) reliable classification of patients into two or more groups with different prognoses. It may be of particular interest to identify patients with a good prognosis that adjuvant therapy would not be (cost-)beneficial, or a group with a poor prognosis that more aggressive adjuvant therapy would not be justified (1). We can define a prognostic model as a combination of at least two separate variables to predict patient outcome. In this chapter, I describe a review of published prognostic models that have been developed to predict the outcome of future breast cancer patients. Studies were considered where the specific aim was either to develop a new prognostic model or to attempt to validate an existing model for newly diagnosed patients, and where at least one of the endpoints of death, cancer death, or recurrence of disease was studied. A full account is available elsewhere (2). It is clear that a prognostic model will have no clinical value unless it can be shown to predict outcome with some success; unless the model is shown to be useful it will be quickly forgotten (3). Thus, there is a particular interest in identifying prognostic models for which there has been an evaluation of how successful the models have been when used in a different setting, that is, models which have been validated externally (1, 4, 5).
The Generalized Random Priority Mechanism with Budgets

This paper studies allocation problems with and without monetary transfers, such as combinatorial auctions, school choice, and course allocation. Interdependent values and multidimensional signals are allowed. Despite known negative results, a mechanism exists that is feasible, ex post individually rational, ex post incentive compatible, and asymptotically both efficient and envy-free. This mechanism is a special case of the generalized random priority mechanism (GRP), which always satisfies the first three properties. The asymptotic properties follow as a corollary of the main theorem: GRP approximates virtually any infinite-market mechanism in large finite markets.
On absence of embedded eigenvalues for schrÖdinger operators with perturbed periodic potentials

The problem of absence of eigenvalues imbedded into the continuous spectrum is considered for a Schrödinger operator with a periodic potential perturbed by a sufficiently fast decaying "impurity" potential. Results of this type have previously been known for the one-dimensional case only. Absence of embedded eigenvalues is shown in dimensions two and three if the corresponding Fermi surface is irreducible modulo natural symmetries. It is conjectured that all periodic potentials satisfy this condition. Separable periodic potentials satisfy it, and hence in dimensions two and three Schrödinger operator with a separable periodic potential perturbed by a sufficiently fast decaying "impurity" potential has no embedded eigenvalues
Identification of ABC Transporter Interaction of a Novel Cyanoquinoline Radiotracer and Implications for Tumour Imaging by Positron Emission Tomography

Background The epidermal growth factor receptor (EGFR) is overexpressed in many cancers including lung, ovarian, breast, head and neck and brain. Mutation of this receptor has been shown to play a crucial role in the response of non-small cell lung carcinoma (NSCLC) to EGFR-targeted therapies. It is envisaged that imaging of EGFR using positron emission tomography (PET) could aid in selection of patients for treatment with novel inhibitors. We recognised multi-drug resistant phenotype as a threat to development of successful imaging agents. In this report, we describe discovery of a novel cyanoquinoline radiotracer that lacks ABC transporter activity. Methods Cellular retention of the prototype cyanoquinoline [18F](2E)-N-{4-[(3-chloro-4-fluorophenyl)amino]-3-cyano-7-ethoxyquinolin-6-yl}-4-({[1-(2-fluoroethyl)-1H-1,2,3-triazol-4-yl]methyl}amino)-but-2-enamide ([18F]FED6) and [18F](2E)-N-{4-[(3-chloro-4-fluorophenyl)amino]-3-cyano-7-ethoxyquinolin-6-yl}-4-[({1-[(2R,5S)-3-fluoro-4,5-dihydroxy-6-(hydroxymethyl)oxan-2-yl]-1H-1,2,3-triazol-4-yl}methyl)amino]but-2-enamide ([18F]FED20) were evaluated to establish potential for imaging specificity. The substrate specificity of a number of cyanoquinolines towards ABC transporters was investigated in cell lines proficient or deficient in ABCB1 or ABCG2. Results FED6 demonstrated substrate specificity for both ABCG2 and ABCB1, a property that was not observed for all cyanoquinolines tested, suggesting scope for designing novel probes. ABC transporter activity was confirmed by attenuating the activity of transporters with drug inhibitors or siRNA. We synthesized a more hydrophilic compound [18F]FED20 to overcome ABC transporter activity. FED20 lacked substrate specificity for both ABCB1 and ABCG2, and maintained a strong affinity for EGFR. Furthermore, FED20 showed higher inhibitory affinity for active mutant EGFR versus wild-type or resistant mutant EGFR; this property resulted in higher [18F]FED20 cellular retention in active mutant EGFR expressing NSCLC. Conclusion [18F]FED20 binds EGFR but is devoid of ABC transporter activity, thus, has potential for EGFR imaging.
Secure Community Trust Stores for Peer-to-Peer e-Commerce Applications Using Cloud Services

P2P e-commerce applications have much with lower operational costs and are inherently more scalable than conventional client-server online trading. Community Trust Stores (CTS) provide reliable and secure storage services for peers involved in P2P e-trading by storing trust data for the peers. Freely available cloud services can host the Community Trust Store and provide 24/7 availability to participating trading peers avoiding the need to pay for commercial trusted third party services. However, the community store must provide a certain level of assurance and support suitable security measures in order to support e-trading within the P2P application. It must also support community management of the store including jointly signed trading contract. The Community Trust Stores also stores reputation report and trading outcomes as future reference for others. New membership for P2P e-commerce group must be sponsored by current members.
Multiple source domain adaptation: A bound using p-norm covering numbers

Traditional supervised learning algorithms assume that the training data and the test data are drawn from the same probability distribution. But in many cases, this assumption is too simplified, and too harsh in light of modern applications of machine learning. So domain adaptation problems are proposed when the data distribution in test domain is different from that in training domain. This paper studies the problem of domain adaptation with multiple sources, which has also received considerable attention in many areas such as natural language processing and speech processing. We introduce a novelty weighted Rademacher complexity to restrict the complexity of a hypothesis class in multiple source domain adaptation and give new generalization bounds for multiple source domain adaptation. In addition, we use an analysis of the p-norm covering number to bound our weighted Rademacher complexity which has never been discussed in multiple source domain adaptation learning.
Pengaruh Aliran Kas Dan Perbedaan Antara Laba Akuntansi Dengan Laba Fiskal Terhadap Persistensi Laba

This research is aims to examine and find out empirical of cash flow on earnings persistence and the role of book tax differences in indicating the persistence of earning. Samples used in this research are manufacturing companies listed in Bursa Efek Indonesia in 5 years observation period (2006-2010). Total samples are 53 companies. The data are collected using purposive sampling method. The method of data analysis is multiple regression. The component of cash flow used is the operation cash flow. Earnings persistence is measured using regression coefficient between current earnings and next period earnings. The book tax differences is measured using deferred tax expense. The hypothesis in the alternative form are (1) operating cash flow significantly positive affect the earnings persistence; (2) book tax differences significantly negative affect earnings persistence. The result of this research showed that (1) operating cash flows are significantly positive affect earnings persistence, with score of significant is 0,004 < 0,05 that meaning is H 1 accepted. It showed that companies with high operating cash flow indicating high earnings persistence; (2) And book tax differences significantly negative affect earnings persistence with score of significant is 0,004 < 0,05 that meaning is H 2 accepted. It showed that companies with large (positive or negative) book tax differences have earnings that are less persistent. Keywords: Earnings Persistence, Operating Cash Flow and Book Tax Differences.
Multibehavioral position-force manipulator controller

In the article the whole process of a manipulator controller development is presented. The controller is designed for the execution of various benchmark tasks in the field of service robotics. Initially, a set of system behaviors is presented as the base of the universal controller structure. For that purpose the embodied agent theory and the System Modeling Language are utilized. The execution and switching between the behaviors relies on a particular algorithm. The control system is verified on a two arm robotic system that consists of position-controlled industrial manipulators and a number of extra force/torque sensors and cameras.