Miracle-dz/UniFAR-FTUs huggingface dataset:
1 MODELING THE MULTIPLE FACETS OF SPECIATION-WITH-GENE-FLOW TOWARDS IMPROVING DIVERGENCE HISTORY INFERENCE OF A RECENT FISH ADAPTIVE RADIATION

The parallel occurrence of replicated species-pairs in similar environmental contrasts may arise through a variety of evolutionary mechanisms. In particular, whether parallelism reflects a common history of divergence or repeated parallel divergence driven by divergent selection needs to be ascertained. Reconstructing historical gene flow is therefore of fundamental interest to understand how demography and selection jointly shape the genomic landscape of species divergence. Here, we extend the current modeling framework to explore the multiple facets of speciation-with-gene-flow using demo-genetic divergence models that capture both temporal and chromosomal variation in migration rate and effective population size. We implement this approach to investigate the divergence history of a young adaptive radiation involving five sympatric Lake Whitefish limnetic (dwarf) and benthic (normal) species pairs (Coregonus clupeaformis) characterized by variable degrees of ecological divergence and reproductive isolation. Genome-wide SNPs obtained by RADsequencing were used to document the extent of genetic differentiation and of allele sharing among species pairs. Using a composite likelihood approach, we then compared the predictions of 26 divergence models to the unfolded joint allele frequency spectrum of each species-pair. We found strong evidence indicating that a recent (circa 3000-4000 generations) asymmetrical secondary contact between expanding post-glacial populations has accompanied independent Whitefish diversification. Our results suggest that heterogeneous genomic differentiation patterns have emerged through the combined effects of linked selection generating variable rates of lineage sorting across the genome during the allopatric phase, and heterogeneous introgression eroding divergence at different rates across the genome upon secondary contact. This study provides a new retrospective insight into the historical demographic and selective processes that shaped a continuum of divergence associated with ecological speciation. This study also illustrates the efficiency of the newly developed models towards improving the understanding of historical events in the process of adaptive evolution and speciation in any other species complex. CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi. org/10.1101/068932 doi: bioRxiv preprint first posted online Aug. 10, 2016;
International Price Discovery in Stock Markets - A Unique Intensity Based Information Share

This paper proposes a new information share for price discovery based on Russell's (1999) autoregressive conditional intensity model. While previous studies rely on equally spaced high frequency data, we use the information conveyed by trade intensities to determine a market's contribution to price discovery. Thereby, we account for the irregular nature of transaction data. Moreover, in contrast to the commonly applied Hasbrouck (1995) approach, which yields lower and upper bounds for information shares, our model delivers a unique measure. Our empirical application to US-listed Canadian stocks supports previous evidence for the home market leadership in price discovery.
Defect Prediction on Unlabeled Datasets by Using Unsupervised Clustering

Defect prediction on unlabeled datasets is one of the most active research areas in software engineering. Generally, cross-project defect prediction (CPDP) and unsupervised learning defect prediction are utilized to address this problem. The fundamental idea of CPDP is the transfer learning that reuses the prediction model built by labeled source projects. However, because of the difference of data distribution among projects, the prediction performance of CPDP models varies by projects. Usually, unsupervised learning models are not comparable to supervised learning ones in term of prediction performance. Hence, many unsupervised prediction models require manual effort to achieve good prediction performance. Recently, a novel unsupervised learning approach, which is without manual effort and based upon the magnitude of metric value, has been proposed and got good prediction performance on some datasets. With the heuristic of this approach, this paper proposes a new approach for predicting defect proneness on unlabeled datasets-ACL. In our empirical study on 16 open source projects, the ACL models led prediction performance on 9 datasets in term of F-measure, which are comparable to supervised learning models in term of predictive power.
Reed Muller Sensing Matrices and the LASSO

We construct two families of deterministic sensing matrices where the columns are obtained by exponentiating codewords in the quaternary Delsarte-Goethals code $DG(m,r)$. This method of construction results in sensing matrices with low coherence and spectral norm. The first family, which we call Delsarte-Goethals frames, are $2^m$ - dimensional tight frames with redundancy $2^{rm}$. The second family, which we call Delsarte-Goethals sieves, are obtained by subsampling the column vectors in a Delsarte-Goethals frame. Different rows of a Delsarte-Goethals sieve may not be orthogonal, and we present an effective algorithm for identifying all pairs of non-orthogonal rows. The pairs turn out to be duplicate measurements and eliminating them leads to a tight frame. Experimental results suggest that all $DG(m,r)$ sieves with $m\leq 15$ and $r\geq2$ are tight-frames; there are no duplicate rows. For both families of sensing matrices, we measure accuracy of reconstruction (statistical 0-1 loss) and complexity (average reconstruction time) as a function of the sparsity level $k$. Our results show that DG frames and sieves outperform random Gaussian matrices in terms of noiseless and noisy signal recovery using the LASSO.
Strategic beliefs of port authorities

ABSTRACT Over the last decade, insights from the strategic management discipline have increasingly been applied to ports. A review of literature shows that in the analysis of port authority strategy, mainly outside-in approaches are applied. This paper adds to the emerging understanding of the port authority’s strategy by applying a cognitive perspective. Specifically, the strategic cognition of firms’ executives is one of the explanatory variables behind firms’ strategic decisions. Furthermore, cognitions are influenced by the organisational contexts in which port authority executives have worked. As a result, managerial “mental maps’ may vary across industry contexts and over time. This research investigates the strategic cognition of a global set of port authority executives through a survey-based instrument. The results show that, to a large extent, PAs resemble “regular” for-profit companies, but that they possess some specific beliefs that distinguish them from “regular” companies.
Energy- and Spectral-Efficiency Tradeoff for Distributed Antenna Systems with Proportional Fairness

Energy efficiency(EE) has caught more and more attention in future wireless communications due to steadily rising energy costs and environmental concerns. In this paper, we propose an EE scheme with proportional fairness for the downlink multiuser distributed antenna systems (DAS). Our aim is to maximize EE, subject to constraints on overall transmit power of each remote access unit (RAU), bit-error rate (BER), and proportional data rates. We exploit multi-criteria optimization method to systematically investigate the relationship between EE and spectral efficiency (SE). Using the weighted sum method, we first convert the multi-criteria optimization problem, which is extremely complex, into a simpler single objective optimization problem. Then an optimal algorithm is developed to allocate the available power to balance the tradeoff between EE and SE. We also demonstrate the effectiveness of the proposed scheme and illustrate the fundamental tradeoff between energy- and spectral-efficient transmission through computer simulation.
Texture segmentation without human V4

ABSTRACT Texture segmentation, or second-order segmentation, is a rapid perceptual process, allowing object and surface boundaries to be effortlessly detected. It is currently unclear whether this is achieved in early cortical areas or whether it necessitates the region referred to as human V4. The present report presents a single case study of patient MS, whose bilateral occipitotemporal damage includes the putative human V4 area, yet whose early visual cortex is spared. As shown in these experiments, MS can accurately locate a target defined by an orientation contrast to its background, even with considerable orientation noise. Importantly, his performance was significantly reduced when the texture edges were masked by black borders (thus preventing edge-based segmentation), indicating that he retains a functional edge-based texture segmentation process. Additionally, when the sign of the orientation contrast was reversed at a temporal frequency of 12.5 Hz, MS could nonetheless detect the contours defined by the orientation contrast despite being unable to judge whether the surfaces either side of the contrast were the same or not. This reveals that MS’s early visual cortex is sufficient for the intact phase-insensitive component of texture segmentation. Human area V4, therefore, is not necessary for texture segmentation.
Diffuse traumatic brain injury induces prolonged immune dysregulation and potentiates hyperalgesia following a peripheral immune challenge

Background Nociceptive and neuropathic pain occurs as part of the disease process after traumatic brain injury (TBI) in humans. Central and peripheral inflammation, a major secondary injury process initiated by the traumatic brain injury event, has been implicated in the potentiation of peripheral nociceptive pain. We hypothesized that the inflammatory response to diffuse traumatic brain injury potentiates persistent pain through prolonged immune dysregulation. Results To test this, adult, male C57BL/6 mice were subjected to midline fluid percussion brain injury or to sham procedure. One cohort of mice was analyzed for inflammation-related cytokine levels in cortical biopsies and serum along an acute time course. In a second cohort, peripheral inflammation was induced seven days after surgery/injury with an intraplantar injection of carrageenan. This was followed by measurement of mechanical hyperalgesia, glial fibrillary acidic protein and Iba1 immunohistochemical analysis of neuroinflammation in the brain, and flow cytometric analysis of T-cell differentiation in mucosal lymph. Traumatic brain injury increased interleukin-6 and chemokine ligand 1 levels in the cortex and serum that peaked within 1–9 h and then resolved. Intraplantar carrageenan produced mechanical hyperalgesia that was potentiated by traumatic brain injury. Further, mucosal T cells from brain-injured mice showed a distinct deficiency in the ability to differentiate into inflammation-suppressing regulatory T cells (Tregs). Conclusions We conclude that traumatic brain injury increased the inflammatory pain associated with cutaneous inflammation by contributing to systemic immune dysregulation. Regulatory T cells are immune suppressors and failure of T cells to differentiate into regulatory T cells leads to unregulated cytokine production which may contribute to the potentiation of peripheral pain through the excitation of peripheral sensory neurons. In addition, regulatory T cells are identified as a potential target for therapeutic rebalancing of peripheral immune homeostasis to improve functional outcome and decrease the incidence of peripheral inflammatory pain following traumatic brain injury.
Optimal Sum-DoF of the K-user MISO BC with Current and Delayed Feedback

This work identifies the optimal sum degrees-of-freedom (DoF) of the $K$-user MISO Broadcast Channel (BC), in the presence of delayed channel-state information at the transmitter (CSIT) and additional current CSIT of imperfect precision. In a setting where the current channel estimation error scales - in the high SNR regime - as $\text{SNR}^{-\alpha}$ for $\alpha\in[0,1]$, the optimal sum-DoF takes the simple form $(1-\alpha) K/(\sum_{k=1}^K \frac{1}{k})+\alpha K$, and is the result of a novel scheme which deviates from existing efforts as it i) digitally combines interference, ii) uses MAT-type alignment where all symbols are decoded irrespective of order, and iii) utilizes a hierarchical quantizer whose output is distributed across rounds in a way that minimizes unwanted interference. These jointly deliver, for the first time, the elusive simultaneous scaling of both MAT-type delayed-CSI gains as well as ZF-type imperfect-CSI gains.
The Mechanisms of Human Renal Epithelial Cell Modulation of Autologous Dendritic Cell Phenotype and Function

Proximal tubule epithelial cells (PTEC) of the kidney line the proximal tubule downstream of the glomerulus and play a major role in the re-absorption of small molecular weight proteins that may pass through the glomerular filtration process. In the perturbed disease state PTEC also contribute to the inflammatory disease process via both positive and negative mechanisms via the production of inflammatory cytokines which chemo-attract leukocytes and the subsequent down-modulation of these cells to prevent uncontrolled inflammatory responses. It is well established that dendritic cells are responsible for the initiation and direction of adaptive immune responses. Both resident and infiltrating dendritic cells are localised within the tubulointerstitium of the renal cortex, in close apposition to PTEC, in inflammatory disease states. We previously demonstrated that inflammatory PTEC are able to modulate autologous human dendritic cell phenotype and functional responses. Here we extend these findings to characterise the mechanisms of this PTEC immune-modulation using primary human PTEC and autologous monocyte-derived dendritic cells (MoDC) as the model system. We demonstrate that PTEC express three inhibitory molecules: (i) cell surface PD-L1 that induces MoDC expression of PD-L1; (ii) intracellular IDO that maintains the expression of MoDC CD14, drives the expression of CD80, PD-L1 and IL-10 by MoDC and inhibits T cell stimulatory capacity; and (iii) soluble HLA-G (sHLA-G) that inhibits HLA-DR and induces IL-10 expression by MoDC. Collectively the results demonstrate that primary human PTEC are able to modulate autologous DC phenotype and function via multiple complex pathways. Further dissection of these pathways is essential to target therapeutic strategies in the treatment of inflammatory kidney disorders.
Overexpression of the poplar NF-YB7 transcription factor confers drought tolerance and improves water-use efficiency in Arabidopsis

Water deficit is a serious environmental factor limiting the growth and productivity of plants worldwide. Improvement of drought tolerance and efficient water use are significant strategies to overcome this dilemma. In this study, a drought-responsive transcription factor, NUCLEAR FACTOR Y subunit B 7 (PdNF-YB7), induced by osmotic stress (PEG6000) and abscisic acid, was isolated from fast-growing poplar clone NE-19 [Populus nigra × (Populus deltoides × Populus nigra)]. Ectopic overexpression of PdNF-YB7 (oxPdB7) in Arabidopsis enhanced drought tolerance and whole-plant and instantaneous leaf water-use efficiency (WUE, the ratio of biomass produced to water consumed). Overexpressing lines had an increase in germination rate and root length and decrease in water loss and displayed higher photosynthetic rate, instantaneous leaf WUE, and leaf water potential to exhibit enhanced drought tolerance under water scarcity. Additionally, overexpression of PdNF-YB7 in Arabidopsis improved whole-plant WUE by increasing carbon assimilation and reducing transpiration with water abundance. These drought-tolerant, higher WUE transgenic Arabidopsis had earlier seedling establishment and higher biomass than controls under normal and drought conditions. In contrast, Arabidopsis mutant nf-yb3 was more sensitive to drought stress with lower WUE. However, complementation analysis indicated that complementary lines (nf-yb3/PdB7) had almost the same drought response and WUE as wild-type Col-0. Taken together, these results suggest that PdNF-YB7 positively confers drought tolerance and improves WUE in Arabidopsis; thus it could potentially be used in breeding drought-tolerant plants with increased production even under water deficiency.
The Vulnerable Population of Teacher-Researchers; Or, “Why I Can’t Name My Coauthors”

Educational researchers are accustomed to institutional review board (IRB) requirements (e.g., protecting participants) with students often identified as the only “vulnerable population” for IRB purposes. However, as practitioner research has gained more prominence, the vulnerability of teacher-researchers themselves has begun to surface. In this article I tell the stories of teachers who felt ostracized as a result of engaging in research and publication. Drawing on research from Scandinavia and Australia, I present some reasons why teachers might seek to “cut down” colleagues who conduct and publish research. Finally, I present suggestions for university-based researchers and teacher educators who wish to help practitioner researchers prepare for any potential backlash as well as some questions for future research.
A recommendation-based reputation evaluating model using virtual verifying and time decaying for P2P networks

As a recommender in the reputation systems can submit inaccurate recommendations for a variety of reasons, the trustworthiness degree of recommending (TDR) must be critically assessed. In this article, two mechanisms, i.e. the virtual verifying and time decaying, are introduced to help calculating TDR. The former is aimed to solve the accuracy and efficiency problem caused by insufficient evidences of recommending when calculating. The latter focuses on detecting the oscillation of recommender's behaviors, and time-decaying-rate factor and time-decaying-frequency factor are involved to make the recent evidences be more important to the calculating. Experimental results show that our model has better performance and is robust even with large amount of malicious peers.
Paracrine Effect of Mesenchymal Stem Cells Derived from Human Adipose Tissue in Bone Regeneration

Mesenchymal stem cell (MSC) transplantation has proved to be a promising strategy in cell therapy and regenerative medicine. Although their mechanism of action is not completely clear, it has been suggested that their therapeutic activity may be mediated by a paracrine effect. The main goal of this study was to evaluate by radiographic, morphometric and histological analysis the ability of mesenchymal stem cells derived from human adipose tissue (Ad-MSC) and their conditioned medium (CM), to repair surgical bone lesions using an in vivo model (rabbit mandibles). The results demonstrated that both, Ad-MSC and CM, induce bone regeneration in surgically created lesions in rabbit's jaws, suggesting that Ad-MSC improve the process of bone regeneration mainly by releasing paracrine factors. The evidence of the paracrine effect of MSC on bone regeneration has a major impact on regenerative medicine, and the use of their CM can address some issues and difficulties related to cell transplants. In particular, CM can be easily stored and transported, and is easier to handle by medical personnel during clinical procedures.
Bayesian Estimation of Outstanding Claim Reserves

This paper presents a Bayesian approach to forecasting outstanding claims, either the total number of claims or the total amount, that is used for claims reserving. The assumption is made that there is complete information for one or two past years of origin and partial information for some development years of other years of origin. It also assumes payments are made annually and that the development of partial payments follows a stable payoff pattern from one year of origin to another. Two different models are presented: one for the number of claims (intensity) and one for claim amounts (severity). The advantage of using this procedure is that actuaries can derive the complete predictive distribution of the reserve requirements, from which, in turn, it is possible to obtain point estimates as well as probability intervals and other summary measures, such as mean, variance, and quantiles.
Effective Work Unit Knowledge Management (KM): An Exploratory Investigation of the Roles of Network, Task Environment, and KM Strategies

Many organizations have initiated knowledge management practices to improve the effectiveness of knowledge creation, transfer, and utilization. However, few studies have been attempted to address what makes some work units within the organization more effective in their use of knowledge than others. In this study we explore the potential contribution of inter-unit network structure as well as intra-unit task environment to the overall KM effectiveness within an organization. The results indicated that both a unit’s boundary-spanning role and its extensive interaction with other units help promote the overall effectiveness of the unit’s KM activities. In addition, we found that a unit’s KM strategy played a mediating role between intra-unit task characteristics and KM effectiveness.
Present and Potential Future Distribution of Common Vampire Bats in the Americas and the Associated Risk to Cattle

Success of the cattle industry in Latin America is impeded by the common vampire bat, Desmodus rotundus, through decreases in milk production and mass gain and increased risk of secondary infection and rabies. We used ecological niche modeling to predict the current potential distribution of D. rotundus and the future distribution of the species for the years 2030, 2050, and 2080 based on the A2, A1B, and B1 climate scenarios from the Intergovernmental Panel on Climate Change. We then combined the present day potential distribution with cattle density estimates to identify areas where cattle are at higher risk for the negative impacts due to D. rotundus. We evaluated our risk prediction by plotting 17 documented outbreaks of cattle rabies. Our results indicated highly suitable habitat for D. rotundus occurs throughout most of Mexico and Central America as well as portions of Venezuela, Guyana, the Brazilian highlands, western Ecuador, northern Argentina, and east of the Andes in Peru, Bolivia, and Paraguay. With future climate projections suitable habitat for D. rotundus is predicted in these same areas and additional areas in French Guyana, Suriname, Venezuela and Columbia; however D. rotundus are not likely to expand into the U.S. because of inadequate ‘temperature seasonality. ’ Areas with large portions of cattle at risk include Mexico, Central America, Paraguay, and Brazil. Twelve of 17 documented cattle rabies outbreaks were represented in regions predicted at risk. Our present day and future predictions can help authorities focus rabies prevention efforts and inform cattle ranchers which areas are at an increased risk of cattle rabies because it has suitable habitat for D. rotundus.
Learning on the job? Exploring first-year experiences of newly-qualified criminal justice social workers in Scotland

Little is known about the experiences of newly-qualified criminal justice practitioners as they enter the field of community justice for the first time. This article reports on isolated data on newly-qualified criminal justice social workers who participated in a national mixed-method study of readiness to practice in Scotland. Findings suggest that new staff felt well-prepared for practice, but many felt employers failed to provide adequate support and development opportunities. Participants report that disproportionate emphasis is placed on workload management during professional supervision sessions where learning needs and emotions are often underplayed. Professional guidance is often sought from informal sources.