Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting redwood productivity using biophysical data, spatial statistics and site quality indices

Coast redwood (Sequoia sempervirens (D. Don) Endl. ) height growth and basal area growth are sensitive to variations in site quality. Site factors known to be correlated with redwood stand growth and yield include topographic variables such as position on slope, exposure, and the composite variable: topographic relative moisture index. Species composition is also a key driver of redwood stand growth and yield. We studied spatial patterns in species composition in terms of percent hardwood, and spatial patterns in topographic relative moisture index values across 109 ha (270 ac) of coast redwood forest on Jackson Demonstration State Forest in Mendocino County, California. We also examined how redwood height growth (in terms of site index) and basal area productivity varied across the study area. We performed Ordinary Kriging in ArcGIS to interpolate between plots. These continuous raster data sets were used to create contour maps to assess redwood productivity in the study area. These example applications demonstrate a potential framework and method to estimate forest growth, yield, and carbon stocks in natural forests along gradients of productivity.
Dynamic Bandwidth Allocation Criteria Over Satellite Networks

The paper studies the performance of possible bandwidth allocation criteria over satellite network. The methods practically implemented in a simulation framework and evaluated are the "value function" (VALUE), the "Nash bargaining solution" (shortly NBS) and the "Utopia minimum distance" (UMD). All the methods, together with two simple approaches introduced for comparison (fixed allocation (FIX) and a Heuristic method (HEU)), have been tested using TCP/IP traffic and the performance evaluation is carried out by varying the degradation level of the satellite channel in different satellite network conditions.
A model for change propagation based on graph rewriting

This paper presents a model of change propagation during software maintenance and evolution. Change propagation is modeled as a sequence of snapshots, where each snapshot represents one particular moment in the process, with some software dependencies being consistent and others being inconsistent. A snapshot is changed into the next one by a change in one software entity and the dependencies related to it. The formalism for this process is based on graph rewriting. The paper discusses two basic processes of change propagation: change-and-fix, and top-down propagation. It also describes a prototype tool “Ripples 2” which supports both processes, and an example of the use of the tool
Artificial neural networks for diagnosis and prognosis in prostate cancer.

The application of artificial neural networks (ANNs), especially feed-forward neural networks (FFNNs), has become very popular for diagnosis and prognosis in clinical medicine, often accompanied by exaggerated statements of their potential. The excitement stems mainly from the fact that ANNs were developed as attempts to model the decision process of the human brain. Traditionally, logistic regression models and proportional hazard regression models have been used in these applications. In this article, FFNNs are introduced as flexible, nonlinear regression models and necessary precautions for their use are discussed. Furthermore, the results of a literature survey of applications of ANNs in prostate cancer published between 1999 and 2001 are described; most applications suffer from methodologic deficiencies. It is concluded that there is so far no evidence that the application of ANNs provide real progress in the field of diagnosis and prognosis in prostate cancer.
On the Evolution of Yeti, a Drosophila melanogaster Heterochromatin Gene

Constitutive heterochromatin is a ubiquitous and still unveiled component of eukaryotic genomes, within which it comprises large portions. Although constitutive heterochromatin is generally considered to be transcriptionally silent, it contains a significant variety of sequences that are expressed, among which about 300 single-copy coding genes have been identified by genetic and genomic analyses in the last decades. Here, we report the results of the evolutionary analysis of Yeti, an essential gene of Drosophila melanogaster located in the deep pericentromeric region of chromosome 2R. By FISH, we showed that Yeti maintains a heterochromatin location in both D. simulans and D. sechellia species, closely related to D. melanogaster, while in the more distant species e.g., D. pseudoobscura and D. virilis, it is found within euchromatin, in the syntenic chromosome Muller C, that corresponds to the 2R arm of D. melanogaster chromosome 2. Thus, over evolutionary time, Yeti has been resident on the same chromosomal element, but it progressively moved closer to the pericentric regions. Moreover, in silico reconstruction of the Yeti gene structure in 19 Drosophila species and in 5 non-drosophilid dipterans shows a rather stable organization during evolution. Accordingly, by PCR analysis and sequencing, we found that the single intron of Yeti does not undergo major intraspecies or interspecies size changes, unlike the introns of other essential Drosophila heterochromatin genes, such as light and Dbp80. This implicates diverse evolutionary forces in shaping the structural organization of genes found within heterochromatin. Finally, the results of dS - dN tests show that Yeti is under negative selection both in heterochromatin and euchromatin, and indicate that the change in genomic location did not affected significantly the molecular evolution of the gene. Together, the results of this work contribute to our understanding of the evolutionary dynamics of constitutive heterochromatin in the genomes of higher eukaryotes.
Power allocation for three-stage cooperative relaying in wireless networks

In the conventional dual-hop cooperative communications, the relays with imbalanced channels to the source and the destination become the bottleneck of the overall cooperation. In this paper, a Three-Stage Relaying (TSR) scheme is presented to extend the dual-hop cooperation to three stages by dividing relays into two groups. The relay-to-relay cooperation is introduced with which the bottleneck link between the relay and the source (or the destination) can be efficiently broken. We focus on the power allocation based on this framework, with the objective of minimizing the outage probability at the destination under the total power constraint. To address the computational complexity, the problem is decomposed into two subproblems, one deals with the power allocation of the source and the first-hop relays, the other deals with the power allocation of the second-hop relays. We design the algorithms for each subproblems by exploiting the special structure of the problems, and develop a master procedure to handle the power allocation across these subproblems. The performance of the proposed scheme is evaluated through simulation study, which shows that the TSR framework achieves significant improvement on the outage probability compared with the dual-hop protocol, and the power consumption is more balanced across relays.
Locally Compact Contractive Local Groups

We study locally compact contractive local groups, that is, locally compact local groups with a contractive pseudo-automorphism. We prove that if such an object is locally connected, then it is locally isomorphic to a Lie group. We also prove a related structure theorem for locally compact contractive local groups which are not necessarily locally connected. These results are local analogues of theorems for locally compact contractive groups.
Novel missense polymorphism in the regulator of G‐protein signaling 10 gene: analysis of association with schizophrenia

ABSTRACT Dysfunction of neuronal signal transduction via G‐protein has previously been speculated to be involved in the pathophysiology of schizophrenia. Regulator of G‐protein signaling (RGS) is a protein that acts as a GTPase‐activator for Gα protein. A total of 33 Japanese patients with schizophrenia were screened for mutations in the coding region of the RGS10 gene, and a novel missense polymorphism (Val38Met) in the RGS domain was detected. A case‐control study did not reveal a significant association between this polymorphism and schizophrenia. The results do not provide evidence that the RGS10 gene is involved in biological vulnerability to schizophrenia.
X-linked B-lymphocyte defect in CBA/N mice. III. Abnormal development of B-lymphocyte populations defined by their density of surface immunoglobulin

CBA/N mice have an X-linked defect in B-lymphocyte function characterized by a failure to respond to certain thymus-independent antigens. When studied by rapid flow microfluorometry, adult CBA/N splenic B lymphocytes labeled with either fluorescein-conjugated (Fl) anti-Ig or Fl anti-mu had fluorescence profiles which were considerably different from those of B lymphocytes derived from normal mice. By studying progeny of crosses of CBA/N and normal mice, it was shown that the abnormal fluorescence profiles of CBA/N B cells were determined by an X-linked gene. The fluorescence profile of adult CBA/N splenic B lymphocytes labeled with anti-mu were very similar to the patterns of neonatal normal and of neonatal CBA/N splenic B lymphocytes suggesting that the defect of CBA/N mice is due to a failure in the development of a mature B-lymphocyte population. The fluorescence profiles of adult CBA/N splenic B lymphocytes labeled with Fl anti-Ig also had immature characteristics in that the frequency of cells with large amounts of surface immunoglobulin was increased in comparison to that of normal strains and the population of cells with low-to-intermediate density of total surface immunoglobulin, which appear characteristic of normal adult splenic B lymphocytes, was markedly diminished.
Sensor networks for routine indoor air quality monitoring in buildings: Impacts of placement, accuracy, and number of sensors

High-performance buildings will increasingly use sensors to control ventilation and manage indoor air quality, but there is little knowledge regarding placement and accuracy limitations. The authors simulated and assessed two approaches for locating from 1 up to 10 hypothetical sensors for measuring carbon dioxide and the sum of volatile organic compounds in typical offices. The first network approach was intended to best measure spatial variability; the second simply sited each additional sensor in the mechanical system's return duct and averaged readings. Each approach was compared at three levels of sensor accuracy in four different office cases, within a Monte Carlo analysis that varied hundreds of relevant parameters. Results indicated that concentrations in areas served by a common mechanical system, given similar per-area supply flows and at least some air recirculation, were reasonably homogeneous. The standard deviation of concentrations among locations was almost always <20% of the mean concentration, and variability was generally overwhelmed by sensor error when building grade sensors were modeled. One implication was that capturing spatial distribution is likely to be less important than improving sensor accuracy, and without better quality sensors, attempting to do so can actually degrade network accuracy.
Streptococcus pneumoniae Isolates with Reduced Susceptibility to Ciprofloxacin in Spain: Clonal Diversity and Appearance of Ciprofloxacin-Resistant Epidemic Clones

ABSTRACT Analysis of the pulsed-field gel electrophoretic profiles of 82 pneumococcal isolates with reduced susceptibility to ciprofloxacin (RSC) and of 90 co-occurring susceptible isolates indicates a considerable genetic diversity among isolates with RCS and points to a close relation between the two groups. This finding suggests that pneumococci with RCS emerge through independent mutational events.
Investigation on water infiltration and water content changes in a large-scale experimental test dike

The paper presents result of series of experiments made within the DREDGDIKES project, performed on a test dike built from composite soil. The composite is produced by mixing fly ash (by-product of energetics) with dredged material (sand) taken from the mouth of The Vistula river. The test dike, located near Gdansk in Poland, was subjected to hydraulic load in several flooding time scenarios and the unsaturated unsteady flow was measured using moisture sensors. There are experimental results presented via evolution of moisture (degree of saturation) in the dike core is. The experiments are compared and final conclusions are presented.
General massive one-loop off-shell three-point functions

In this work we compute the most general massive one-loop off-shell three-point vertex in D-dimensions, where the masses, external momenta and exponents of propagators are arbitrary. This follows our previous paper in which we have calculated several new hypergeometric series representations for massless and massive (with equal masses) scalar one-loop three-point functions, in the negative dimensional approach.
Interferon gamma selectively inhibits very primitive CD342+CD38- and not more mature CD34+CD38+ human hematopoietic progenitor cells

To assess the effects of interferon gamma (IFN-gamma) on very primitive hematopoietic progenitor cells, CD34(2+)CD38- human bone marrow cells were isolated and cultured in a two-stage culture system, consisting of a primary liquid culture phase followed by a secondary semisolid colony assay. CD34(2+)CD38- cells needed at least the presence of interleukin 3 (IL-3) and kit ligand (KL) together with either IL-1, IL-6, or granulocyte-colony-stimulating factor (G-CSF) in the primary liquid phase in order to proliferate and differentiate into secondary colony- forming cells (CFC). Addition of IFN-gamma to the primary liquid cultures inhibited cell proliferation and generation of secondary CFC in a dose-dependent way. This was a direct effect since it was also seen in primary single cell cultures of CD34(2+)CD38- cells. The proliferation of more mature CD34+CD38+ cells, however, was not inhibited by IFN-gamma, demonstrating for the first time that IFN-gamma is a specific and direct hematopoietic stem cell inhibitor. IFN-gamma, moreover, preserves the viability of CD34(2+)CD38- cells in the absence of other cytokines. IFN-gamma could, therefore, play a role in the protection of the stem cell compartment from exhaustion in situations of hematopoietic stress and may be useful as stem cell protecting agent against chemotherapy for cancer.
What Makes a Better Smeller?

Olfaction is often viewed as difficult, yet the empirical evidence suggests a different picture. A closer look shows people around the world differ in their ability to detect, discriminate, and name odors. This gives rise to the question of what influences our ability to smell. Instead of focusing on olfactory deficiencies, this review presents a positive perspective by focusing on factors that make someone a better smeller. We consider three driving forces in improving olfactory ability: one’s biological makeup, one’s experience, and the environment. For each factor, we consider aspects proposed to improve odor perception and critically examine the evidence; as well as introducing lesser discussed areas. In terms of biology, there are cases of neurodiversity, such as olfactory synesthesia, that serve to enhance olfactory ability. Our lifetime experience, be it typical development or unique training experience, can also modify the trajectory of olfaction. Finally, our odor environment, in terms of ambient odor or culinary traditions, can influence odor perception too. Rather than highlighting the weaknesses of olfaction, we emphasize routes to harnessing our olfactory potential.
Molecular Basis of Evolutionary Events That Shaped the Hardness Locus in Diploid and Polyploid Wheat Species (Triticum and Aegilops)w⃞

The Hardness (Ha) locus controls grain hardness in hexaploid wheat (Triticum aestivum) and its relatives (Triticum and Aegilops species) and represents a classical example of a trait whose variation arose from gene loss after polyploidization. In this study, we investigated the molecular basis of the evolutionary events observed at this locus by comparing corresponding sequences of diploid, tertraploid, and hexaploid wheat species (Triticum and Aegilops). Genomic rearrangements, such as transposable element insertions, genomic deletions, duplications, and inversions, were shown to constitute the major differences when the same genomes (i.e., the A, B, or D genomes) were compared between species of different ploidy levels. The comparative analysis allowed us to determine the extent and sequences of the rearranged regions as well as rearrangement breakpoints and sequence motifs at their boundaries, which suggest rearrangement by illegitimate recombination. Among these genomic rearrangements, the previously reported Pina and Pinb genes loss from the Ha locus of polyploid wheat species was caused by a large genomic deletion that probably occurred independently in the A and B genomes. Moreover, the Ha locus in the D genome of hexaploid wheat (T. aestivum) is 29 kb smaller than in the D genome of its diploid progenitor Ae. tauschii, principally because of transposable element insertions and two large deletions caused by illegitimate recombination. Our data suggest that illegitimate DNA recombination, leading to various genomic rearrangements, constitutes one of the major evolutionary mechanisms in wheat species.
Unsupervised Human Action Categorization with Consensus Information Bottleneck Method

Recent researches have shown consensus clustering can enhance the accuracy of human action categorization models by combining multiple clusterings, which can be obtained from various types of local descriptors, such as HOG, HOF and MBH. However, consensus clustering yields final clustering without access to the underlying feature representations of the human action data, which always makes the final partition limited to the quality of existing basic clusterings. To solve this problem, we present a novel and effective Consensus Information Bottleneck (CIB) method for unsupervised human action categorization. CIB is capable of learning action categories from feature variable and auxiliary clusterings simultaneously. Specifically, by performing Maximization of Mutual Information (MMI), CIB maximally preserves the information between feature variable and existing auxiliary clusterings. Moreover, to solve MMI optimization, a sequential solution is proposed to update data partition. Extensive experiments on five realistic human action data sets show that CIB can consistently and significantly beat other state-of-the-art consensus and multi-view clustering methods.
Modeling and simulation of military tactical logistics distribution

The military tactical logistics planning problem addresses the issue of distributing heterogeneous commodities in a theater of operations using a combination of heterogeneous transportation assets such as logistics trucks and tactical helicopters. The Canadian Forces requires a decision support tool to examine the trade-off between the cost of the support and its effectiveness during sustainment operations. In this study, a mathematical optimization algorithm and a simulation module to build cost efficient and effective military tactical logistics are developed. Details of the optimization algorithm along with several example applications are presented to demonstrate the methodology. The simulation results are focused on the trade-off between cost and lead-time within which demands are required, and on the optimal fleet mix of transportation assets to respond to the different requirements of deployed forces
Living cover crops have immediate impacts on soil microbial community structure and function

Cover cropping is a widely promoted strategy to enhance soil health in agricultural systems. Despite a substantial body of literature demonstrating links between cover crops and soil biology, an important component of soil health, research evaluating how specific cover crop species influence soil microbial communities remains limited. This study examined the effects of eight fall-sown cover crop species grown singly and in multispecies mixtures on microbial community structure and soil biological activity using phospholipid fatty acid (PLFA) profiles and daily respiration rates, respectively. Fourteen cover crop treatments and a no cover crop control were established in August of 2011 and 2012 on adjacent fields in central Pennsylvania following spring oats (Avena sativa L.). Soil communities were sampled from bulk soil collected to a depth of 20 cm (7.9 in) in fall and spring, approximately two and nine months after cover crop planting and prior to cover crop termination. In both fall and spring, cover crops led to an increase in total PLFA concentration relative to the arable weed community present in control plots (increases of 5.37 nmol g−1 and 10.20 nmol g−1, respectively). While there was a positive correlation between aboveground plant biomass (whether from arable weeds or cover crops) and total PLFA concentration, we also found that individual cover crop species favored particular microbial functional groups. Arbuscular mycorrhizal (AM) fungi were more abundant beneath oat and cereal rye (Secale cereale L.) cover crops. Non-AM fungi were positively associated with hairy vetch (Vicia villosa L.). These cover crop-microbial group associations were present not only in monocultures, but also multispecies cover crop mixtures. Arable weed communities were associated with higher proportions of actinomycetes and Gram-positive bacteria. Soil biological activity varied by treatment and was positively correlated with both the size and composition (fungal:bacterial ratio) of the microbial community. This research establishes a clear link between cover crops, microbial communities, and soil health. We have shown that while cover crops generally promote microbial biomass and activity, there are species-specific cover crop effects on soil microbial community composition that ultimately influence soil biological activity. This discovery paves the way for intentional management of the soil microbiome to enhance soil health through cover crop selection.
Anomaly? application change? or workload change? towards automated detection of application performance anomaly and change

Automated tools for understanding application behavior and its changes during the application life-cycle are essential for many performance analysis and debugging tasks. Application performance issues have an immediate impact on customer experience and satisfaction. A sudden slowdown of enterprise-wide application can effect a large population of customers, lead to delayed projects and ultimately can result in company financial loss. We believe that online performance modeling should be a part of routine application monitoring. Early, informative warnings on significant changes in application performance should help service providers to timely identify and prevent performance problems and their negative impact on the service. We propose a novel framework for automated anomaly detection and application change analysis. It is based on integration of two complementary techniques: i) a regression-based transaction model that reflects a resource consumption model of the application, and ii) an application performance signature that provides a compact model of run-time behavior of the application. The proposed integrated framework provides a simple and powerful solution for anomaly detection and analysis of essential performance changes in application behavior. An additional benefit of the proposed approach is its simplicity: it is not intrusive and is based on monitoring data that is typically available in enterprise production environments.