Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on personalized document retrieval based on user interest model

This thesis studies a user interest model which can correspond with every user by collecting some personal information of users and optimize the retrieval results by search the original query expansion automatically. After putting the inquiry keyword into the search engine, the system will filter and sort the retrieval results according with the relevant of the user's interest model and finally present it to users. The experiments show that using this method can improve the precision ratio and recall ratio and realize the personalized service of the information index for users.
Promoter Methylation Analysis of IDH Genes in Human Gliomas

Mutations in isocitrate dehydrogenase (IDH)-1 or -2 are found in the majority of WHO grade II and III astrocytomas and oligodendrogliomas, and secondary glioblastomas. Almost all described mutations are heterozygous missense mutations affecting a conserved arginine residue in the substrate binding site of IDH1 (R132) or IDH2 (R172). But the exact mechanism of IDH mutations in neoplasia is not understood. It has been proposed that IDH mutations impart a “toxic gain-of-function” to the mutant protein, however a dominant-negative effect of mutant IDH has also been described, implying that IDH may function as a tumor suppressor gene. As most, if not all, tumor suppressor genes are inactivated by epigenetic silencing, in a wide variety of tumors, we asked if IDH1 or IDH2 carry the epigenetic signature of a tumor suppressor by assessing cytosine methylation at their promoters. Methylation was quantified in 68 human brain tumors, including both IDH-mutant and IDH wildtype, by bisulfite pyrosequencing. In all tumors examined, CpG methylation levels were less than 8%. Our data demonstrate that inactivation of IDH function through promoter hypermethylation is not common in human gliomas and other brain tumors. These findings do not support a tumor suppressor role for IDH genes in human gliomas.
Strategy Adaptation by Competing Subpopulations

The breeder genetic algorithm BGA depends on a set of con trol parameters and genetic operators In this paper it is shown that strategy adaptation by competing subpopulations makes the BGA more robust and more e cient Each subpopulation uses a di erent strategy which competes with other subpopulations Numerical results are pre sented for a number of test functions
CEO Narcissism, Risk-Taking, and Resilience: An Empirical Analysis in U.S. Commercial Banks

In this study, we investigate how CEO narcissism, in combination with corporate governance practices, impacts organizational risk-taking and how this in turn affects organizations’ resilience to environmental conditions. We examine these issues in the context of the recent collapse (systemic shock) of the U.S. banking industry in September 2008, using a sample of 92 CEOs from 2006 until 2014. We find that before the shock CEO narcissism positively affected the riskiness of banks’ policies, especially when compensation policies that encourage risk-taking (stock options) are in place. The positive effect of narcissism was dampened, however, when board monitoring was more effective (because of the presence of knowledgeable outsider directors). Furthermore, we find that these preshock features hamper organizations’ resilience to (economic) shocks, as banks led by more narcissistic CEOs before the September 2008 collapse experienced a slower recovery to preshock performance levels afterwards. This effect was partially mediated by banks’ preshock riskiness of policies. We attribute these effects to the associated depletion of the organizations’ internal resources (beyond slack). Post-hoc analyses further underscore this idea, showing that the U.S. government’s capital injections through the Troubled Assets Relief Program (TARP)—resolving the “problem” of resource depletion—moderated these effects.
On Low-High Orders of Directed Graphs: Incremental Algorithms and Applications

A flow graph $G=(V,E,s)$ is a directed graph with a distinguished start vertex $s$. The dominator tree $D$ of $G$ is a tree rooted at $s$, such that a vertex $v$ is an ancestor of a vertex $w$ if and only if all paths from $s$ to $w$ include $v$. The dominator tree is a central tool in program optimization and code generation and has many applications in other diverse areas including constraint programming, circuit testing, biology, and in algorithms for graph connectivity problems. A low-high order of $G$ is a preorder $\delta$ of $D$ that certifies the correctness of $D$ and has further applications in connectivity and path-determination problems. In this paper, we first consider how to maintain efficiently a low-high order of a flow graph incrementally under edge insertions. We present algorithms that run in $O(mn)$ total time for a sequence of $m$ edge insertions in an initially empty flow graph with $n$ vertices.These immediately provide the first incremental certifying algorithms for maintaining the dominator tree in $O(mn)$ total time, and also imply incremental algorithms for other problems. Hence, we provide a substantial improvement over the $O(m^2)$ simple-minded algorithms, which recompute the solution from scratch after each edge insertion. We also show how to apply low-high orders to obtain a linear-time $2$-approximation algorithm for the smallest $2$-vertex-connected spanning subgraph problem (2VCSS). Finally, we present efficient implementations of our new algorithms for the incremental low-high and 2VCSS problems and conduct an extensive experimental study on real-world graphs taken from a variety of application areas. The experimental results show that our algorithms perform very well in practice.
Comparative evaluation of feature normalization techniques for voice password based speaker verification

This paper presents a comparative study of the normalization techniques used at feature level in voice password based speaker verification system. The input sample speech is recorded at different instants of time and environment. Hence, there is a variation in the input sample due to the environmental interference, noise, emotions etc. The input sample is a human voice with unique passwords taken/recorded at three different instants of time or day. This input sample is processed using sampling, pre-emphasis, MFCC feature extraction and DTW. In order to enhance the features we have used three different popular feature normalization techniques namely MVN (Mean and Variance Normalization), CMN (Cepstral Mean Normalization) and PCA(Principal Component Analysis) and analyzed the result of each technique individually. The objective of this paper is to compare the performance and efficiency of these techniques and evaluate which of these gives the best verification rate. According to our findings CMN gives the best results.
Empowerment: Doctor vs Nurses

This paper aims to see the levels of empowerment exist in the private hospital in Dhaka city, considering the case of doctors and nurses. A small sample of 40 respondents from the two private hospitals was chosen randomly. The theories of empowerment are discussed and the results are analyzed in respect to the theories which shows that doctors are more empowered than the nurses.
7-Gb/s monolithic photoreceiver fabricated with 0.25-µm SiGe BiCMOS technology

We demonstrate an 850-nm high-speed photoreceiver with a monolithically integrated silicon avalanche photodetector for optical interconnect applications. The photoreceiver is fabricated with standard 0.25-μm SiGe bipolar complementary metal-oxide-semiconductor technology without any process modification. The photoreceiver achieves 7-Gb/s optical data transmission with the bit-error rate less than 10−10 at −1 dBm incident optical power.
A cepstrum-based harmonics-to-noise ratio in voice signals

A new cepstrum-based technique is developed in order to provide an alternative means of estimating the harmonics-to-noise ratio in voice signals. The geometric mean harmonics-to-noise ratio (GHNR) is defined as the mean of the individual spectral (i.e. at specific frequency locations) harmonics-to-noise ratios in dB. A heuristic development of the method treats the harmonic spectrum (in dB) of voiced speech taken over several cycles of the waveform as a more usual time domain signal, which is Fourier transformed. The sum of the resulting cepstral peaks (rahmonics) gives a direct estimation of the geometric mean harmonics-to-noise ratio (GHNR). The need for, inverse Fourier transform of the masked cepstrum back into the frequency domain, baseline correction and the usual harmonics-to-noise ratio (HNR) calculation is avoided by this approach. The technique is examined using synthetically generated voice signals.
PyFDAP: automated analysis of fluorescence decay after photoconversion (FDAP) experiments

UNLABELLED We developed the graphical user interface PyFDAP for the fitting of linear and non-linear decay functions to data from fluorescence decay after photoconversion (FDAP) experiments. PyFDAP structures and analyses large FDAP datasets and features multiple fitting and plotting options. AVAILABILITY AND IMPLEMENTATION PyFDAP was written in Python and runs on Ubuntu Linux, Mac OS X and Microsoft Windows operating systems. The software, a user guide and a test FDAP dataset are freely available for download from http://people.tuebingen. mpg.de/mueller-lab.
Direct targeting of risk factors significantly increases the detection of liver cirrhosis in primary care: a cross-sectional diagnostic study utilising transient elastography

Objectives To assess the feasibility of a novel diagnostic algorithm targeting patients with risk factors for chronic liver disease in a community setting. Design Prospective cross-sectional study. Setting Two primary care practices (adult patient population 10 479) in Nottingham, UK. Participants Adult patients (aged 18 years or over) fulfilling one or more selected risk factors for developing chronic liver disease: (1) hazardous alcohol use, (2) type 2 diabetes or (3) persistently elevated alanine aminotransferase (ALT) liver function enzyme with negative serology. Interventions A serial biomarker algorithm, using a simple blood-based marker (aspartate aminotransferase:ALT ratio for hazardous alcohol users, BARD score for other risk groups) and subsequently liver stiffness measurement using transient elastography (TE). Main outcome measures Diagnosis of clinically significant liver disease (defined as liver stiffness ≥8 kPa); definitive diagnosis of liver cirrhosis. Results We identified 920 patients with the defined risk factors of whom 504 patients agreed to undergo investigation. A normal blood biomarker was found in 62 patients (12.3%) who required no further investigation. Subsequently, 378 patients agreed to undergo TE, of whom 98 (26.8% of valid scans) had elevated liver stiffness. Importantly, 71/98 (72.4%) patients with elevated liver stiffness had normal liver enzymes and would be missed by traditional investigation algorithms. We identified 11 new patients with definite cirrhosis, representing a 140% increase in the number of diagnosed cases in this population. Conclusions A non-invasive liver investigation algorithm based in a community setting is feasible to implement. Targeting risk factors using a non-invasive biomarker approach identified a substantial number of patients with previously undetected cirrhosis. Trial registration number The diagnostic algorithm utilised for this study can be found on clinicaltrials.gov (NCT02037867), and is part of a continuing longitudinal cohort study.
On-demand multipath routing for mobile ad hoc networks

Mobile ad hoc networks are characterized by multi-hop wireless links, absence of any cellular infrastructure, and frequent host mobility. Design of efficient routing protocols in such networks is a challenging issue. A class of routing protocols called on-demand protocols has recently attracted attention because of their low routing overhead. The on-demand protocols depend on query floods to discover routes whenever a new route is needed. Such floods take up a substantial portion of network bandwidth. We focus on a particular on-demand protocol, called dynamic source routing, and show how intelligent use of multipath techniques can reduce the frequency of query floods. We develop an analytic modeling framework to determine the relative frequency of query floods for various techniques. Results show that while multipath routing is significantly better than single path routing, the performance advantage is small beyond a few paths and for long path lengths. It also shows that providing all intermediate nodes in the primary (shortest) route with alternative paths has a significantly better performance than providing only the source with alternate paths.
Mixing layer height retrievals by multichannel microwave radiometer observations

Abstract. The mixing layer height (MLH) is a key parameter for boundary layer studies, including meteorology, air quality, and climate. MLH estimates are inferred from in situ radiosonde measurements or remote sensing observations from instruments like lidar, wind profiling radar, or sodar. Methods used to estimate MLH from radiosonde profiles are also used with atmospheric temperature and humidity profiles retrieved by microwave radiometers (MWR). This paper proposes an alternative approach to estimate MLH from MWR data, based on direct observations (brightness temperatures, Tb) instead of retrieved profiles. To our knowledge, MLH estimates directly from Tb observations have never been attempted before. The method consists of a multivariate linear regression trained with an a priori set of collocated MWR Tb observations (multifrequency and multi-angle) and MLH estimates from a state-of-the-art lidar system. The proposed method was applied to a 7-month data set collected at a typical midlatitude site. Results show that the method is able to follow both the diurnal cycle and the day-to-day variability as suggested by the lidar measurements, and also it can detect low MLH values that are below the full overlap limit (~200 m) of the lidar system used. Statistics of the comparison between MWR- and reference lidar-based MLH retrievals show mean difference within 10 m, root mean square within 340 m, and correlation coefficient higher than 0.77. Monthly mean analysis for daytime MLH from MWR, lidar, and radiosonde shows consistent seasonal variability, peaking at ~1200–1400 m in June and decreasing down to ~600 m in October. Conversely, nighttime monthly mean MLH from all methods are within 300–500 m without any significant seasonal variability. The proposed method provides results that are more consistent with radiosonde estimates than MLH estimates from MWR-retrieved profiles. MLH monthly mean values agree well within 1 standard deviation with the bulk Richardson number method applied at radiosonde profiles at 11:00 and 23:00 UTC. The method described herewith operates continuously and is expected to work with analogous performances for the entire diurnal cycle, except during considerable precipitation, demonstrating new potential for atmospheric observation by ground-based microwave radiometry.
DC electronic load based on an interleaved chopper converter to determine photovoltaic panel and fuel cell biasing curves

This paper presents the description of a DC electronic load based on an interleaved chopper converter to determine the biasing and dynamics characteristics of either fuel cells (FCs) and photovoltaic panels (PVs). Variable loads are used for experimental data acquisition of I-V power supply characteristics in a way that several operating points can be easily obtained. Laboratory load current tests using ordinary power resistors are not an easy solution due to their size, cost and overall weight. To resolve that it is proposed in this paper that the current through electronically varying loads can give better resolution to the I-V characteristics of FC and PV sources. The interleaved operation of the chopper converter ensures an input high frequency current ripple, reducing so the input LC filters size and converter volume. The converter transfer function is analyzed and controllers are designed to obtain a fast dynamic response and insure good stability in steady state operation. It is presented the converter operating principles, operating states and design. The simulated and results are compared to each other in order to prove the electronic load effectiveness in acquiring the I-V biasing curves of fuel cells and photovoltaic panels.
Mapping Soil Salinity Using Soil Salinity Samples and Variograms: Case Study in the Lower Arkansas Basin

The objective of this study was to develop a methodology to generate high accuracy soil salinity maps with the minimum number of soil salinity samples. Variograms are used in this study to estimate the number of soil salinity samples that need to be collected. A modified residual krig- ing model was used to evaluate the relationship between soil salinity and a number of satellite im- ages. Two datasets, one representing corn fields where Aster, Landsat 7, and Ikonos images were used, and the other representing alfalfa fields where the Landsat 5 and Ikonos images were used. The satellite images were acquired from different sources to check the correlation between meas- ured soil salinity and remote sensing data. Two strategies were applied to the datasets to produce subset samples. For the corn fields dataset, nine subsets of the data ranging from 10% to 90% of the data in 10% increments were produced. For the alfalfa fields dataset, three subsets of the data 75 %, 50%, and 25% of the data were produced. A modified residual kriging model was applied to the reduced datasets for each image. For each combination of satellite image and subset of the data, a variogram was generated and the correlation between soil salinity and the remote sensing data was evaluated. The results show that the variograms can be used to significantly reduce the number of soil salinity samples that need to be collected.
Contribution of outward currents to spike-frequency adaptation in hypoglossal motoneurons of the rat.

Contribution of outward currents to spike-frequency adaptation in hypoglossal motoneurons of the rat. J. Neurophysiol. 78: 2246-2253, 1997. Spike-frequency adaptation has been attributed to the actions of several different membrane currents. In this study, we assess the contributions of two of these currents: the net outward current generated by the electrogenic Na+-K+ pump and the outward current that flows through Ca2+-activated K+ channels. In recordings made from hypoglossal motoneurons in slices of rat brain stem, we found that bath application of a 4-20 microM ouabain solution produced a partial block of Na+-K+ pump activity as evidenced by a marked reduction in the postdischarge hyperpolarization that follows a period of sustained discharge. However, we observed no significant change in either the initial, early, or late phases of spike-frequency adaptation in the presence of ouabain. Adaptation also has been related to increases in the duration and magnitude of the medium-duration afterhyperpolarization (mAHP) mediated by Ca2+-activated K+ channels. When we replaced the 2 mM Ca2+ in the bathing solution with Mn2+, there was a significant decrease in the amplitude of the mAHP after a spike. The decrease in mAHP amplitude resulted in a decrease in the magnitude of the initial phase of spike-frequency adaptation as has been reported previously by others. However, quite unexpectedly we also found that reducing the mAHP resulted in a dramatic increase in the magnitude of both the early and late phases of adaptation. These changes could be reversed by restoring the normal Ca2+ concentration in the bath. Our results with ouabain indicate that the Na+-K+ pump plays little, if any, role in the three phases of adaptation in rat hypoglossal motoneurons. Our results with Ca2+ channel blockade support the hypothesis that initial adaptation is, in part, controlled by conductances underlying the mAHP. However, our failure to eliminate initial adaptation completely by blocking Ca2+ channels suggests that other membrane mechanisms also contribute. Finally, the increase in both the early and late phases of adaptation in the presence of Mn2+ block of Ca2+ channels lends further support to the hypothesis that the initial and later (i.e., early and late) phases of spike-frequency adaptation are mediated by different cellular mechanisms.
Ethical Principles and Economic Analysis

Traditional economics assumes that economic agents are self-interested, whereas arguably individuals are ethically motivated and aware, and hence economic analysis can benefit from an incorporation of ethical motivation, awareness and intention. We argue that ethics can be incorporated into the individual decision-making process by adapting the assumption that individuals are self-interested through an expansion of the notion of self-interest which is consistent with rationality. Ethical motivation therefore has a self-interested foundation, as ethical motivation appears as an extension of self-interest rather than as pure ethical motivation alone. The ethical behaviour which is most appealing is where individuals act ethically due both to an intrinsic valuation of ethics and because it is in their self-interest, rather than because it is in their self-interest alone. This type of ethical behaviour can be represented using a two-stage process, whereby individuals firstly adopt ethical principles because they value ethics in itself, and secondly because it is in their interest to do so. This two-stage process builds on insights provided by, among others, Sen and Etzioni. The first stage of the two-stage process (where the individual makes a commitment to ethical principles due to the intrinsic value of ethics rather than its instrumental value) is the most challenging for economic analysis. Two possible frameworks are suggested based on commitment and learned behaviour and institutional analysis. We find that both frameworks are suggestive but a complete analysis requires inputs from wider socio-political factors.
Robo 4 Counteracts Angiogenesis in Herpetic Stromal Keratitis

The cornea is a complex tissue that must preserve its transparency to maintain optimal vision. However, in some circumstances, damage to the eye can result in neovascularization that impairs vision. This outcome can occur when herpes simplex virus type 1 (HSV-1) causes the immunoinflammatory lesion stromal keratitis (SK). Potentially useful measures to control the severity of SK are to target angiogenesis which with herpetic SK invariably involves VEGF. One such way to control angiogenesis involves the endothelial receptor Robo4 (R4), which upon interaction with another protein activates an antiangiogenic pathway that counteracts VEGF downstream signaling. In this study we show that mice unable to produce R4 because of gene knockout developed significantly higher angiogenesis after HSV-1 ocular infection than did infected wild type (WT) controls. Moreover, providing additional soluble R4 (sR4) protein by subconjunctival administration to R4 KO HSV-1 infected mice substantially rescued the WT phenotype. Finally, administration of sR4 to WT HSV-1 infected mice diminished the extent of corneal angiogenesis compared to WT control animals. Our results indicate that sR4 could represent a useful therapeutic tool to counteract corneal angiogenesis and help control the severity of SK.