Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of spatial connectivity on host resistance in a highly fragmented natural pathosystem

Both theory and experimental evolution studies predict migration to influence the outcome of antagonistic coevolution between hosts and their parasites, with higher migration rates leading to increased diversity and evolutionary potential. Migration rates are expected to vary in spatially structured natural pathosystems, yet how spatial structure generates variation in coevolutionary trajectories across populations occupying the same landscape has not been tested. Here, we studied the effect of spatial connectivity on host evolutionary potential in a natural pathosystem characterized by a stable Plantago lanceolata host network and a highly dynamic Podosphaera plantaginis parasite metapopulation. We designed a large inoculation experiment to test resistance of five isolated and five well‐connected host populations against sympatric and allopatric pathogen strains, over 4 years. Contrary to our expectations, we did not find consistently higher resistance against sympatric pathogen strains in the well‐connected populations. Instead, host local adaptation varied considerably among populations and through time with greater fluctuations observed in the well‐connected populations. Jointly, our results suggest that in populations where pathogens have successfully established, they have the upper hand in the coevolutionary arms race, but hosts may be better able to respond to pathogen‐imposed selection in the well‐connected than in the isolated populations. Hence, the ongoing and extensive fragmentation of natural habitats may increase vulnerability to diseases.
Personalized Preclinical Trials in BRAF Inhibitor–Resistant Patient-Derived Xenograft Models Identify Second-Line Combination Therapies

Purpose: To test second-line personalized medicine combination therapies, based on genomic and proteomic data, in patient-derived xenograft (PDX) models. Experimental Design: We established 12 PDXs from BRAF inhibitor–progressed melanoma patients. Following expansion, PDXs were analyzed using targeted sequencing and reverse-phase protein arrays. By using multi-arm preclinical trial designs, we identified efficacious precision medicine approaches. Results: We identified alterations previously described as drivers of resistance: NRAS mutations in 3 PDXs, MAP2K1 (MEK1) mutations in 2, BRAF amplification in 4, and aberrant PTEN in 7. At the protein level, re-activation of phospho-MAPK predominated, with parallel activation of PI3K in a subset. Second-line efficacy of the pan-PI3K inhibitor BKM120 with either BRAF (encorafenib)/MEK (binimetinib) inhibitor combination or the ERK inhibitor VX-11e was confirmed in vivo. Amplification of MET was observed in 3 PDX models, a higher frequency than expected and a possible novel mechanism of resistance. Importantly, MET amplification alone did not predict sensitivity to the MET inhibitor capmatinib. In contrast, capmatinib as single agent resulted in significant but transient tumor regression in a PDX with resistance to BRAF/MEK combination therapy and high pMET. The triple combination capmatinib/encorafenib/binimetinib resulted in complete and sustained tumor regression in all animals. Conclusions: Genomic and proteomic data integration identifies dual-core pathway inhibition as well as MET as combinatorial targets. These studies provide evidence for biomarker development to appropriately select personalized therapies of patients and avoid treatment failures. Clin Cancer Res; 22(7); 1592–602. ©2015 AACR. See related commentary by Hartsough and Aplin, p. 1550
Human-Assisted Signature Recognition Based on Comparative Attributes

This work analyzes the performance of comparative attributes labeled by humans for handwritten semi-automatic signature recognition. Despite the large deployment of automatic sys-tems, humans have still an important role in many tasks relat-ed to handwritten signature recording and verification. How humans can help to improve these processes is a primary aim of different research lines. Comparative attributes try to ex-ploit the abilities of humans to extract discriminant infor-mation of the signatures. Instead of absolute attributes (e.g. is this stroke vertical? ), the comparative attributes offer richer responses (e.g. how vertical is this stroke? ). In this work we present a new semi-automatic signature labeling interface in-spired by Forensic Document Examiners (FDE). Fifteen com-parative attributes have been labeled by 21 laymen, where each one carries out the labeling of 28 signatures from 130 users of the publicly available corpus BiosecurID database. Through the manual labeling, a new Bio-HSL (Biometric-Handwritten Signatures Labelling) database is generated, which contains 4,968,600 signature attributes. The results show that compara-tive attributes outperform absolute attributes for semi-automatic signature recognition with Equal Error Rates ranging from 5.5% for random comparisons to 21.2% for simulated forgeries.
Uncertainty quantification in modelling equiaxed alloy solidification

Abstract Numerical simulations can provide insight into physical phenomena during alloy solidification processes that cannot be observed experimentally. These model predictions depend on the material, process and numerical parameters which contain inherit uncertainties due to their origin in experimental measurements or model assumptions. As a step towards understanding the effect of uncertain inputs on solidification process modelling, uncertainty quantification and sensitivity analysis are performed on a transient model of transport phenomena during the solidification of grain refined Al-4.5 wt. % Cu in a rectangular cavity. The effect of microstructural model parameters, thermal boundary conditions and material property input uncertainties are examined for their effect on macrosegregation levels and solidification time. Predictions of the macrosegregation level are most sensitive to the dendrite arm spacing of the rigid mushy zone.
Tunnel technique versus coronally advanced flap with acellular dermal matrix graft in the treatment of multiple gingival recessions.

AIM The aim of this randomized controlled clinical study was to evaluate the outcomes of acellular dermal matrix (ADM) graft in combination with tunnel technique (TUN) on root coverage, aesthetics, and patient satisfaction and to compare with coronally advanced flap (CAF)+ADM in the treatment of multiple gingival recessions. MATERIAL AND METHODS A total of 20 patients with 58 Miller Class I multiple recessions ≥3 mm were included and divided into TUN+ADM and CAF+ADM groups. At baseline and 12 months, probing depth (PD), clinical attachment level (CAL), recession height (RH) and width (RW), keratinized tissue height (KT), gingival thickness, and complete and mean root coverage (CRC, MRC) were evaluated. Patient satisfaction and root coverage aesthetic scores (RES) were also assessed. RESULTS Mean root coverage was 75.72% in TUN+ADM and 93.81% in CAF+ADM. Intragroup comparisons revealed significant differences at 12 months for all parameters in both groups (p < 0.05). Intergroup differences were found to be statistically significant for RH and RW reduction, KT increase, CAL gain, MRC, CRC, and RES in favour of CAF+ADM group (p < 0.05). CONCLUSION Both techniques were effective in root coverage of multiple recessions; however, better clinical results were achieved with CAF and ADM combination.
A Fine-Grained API Link Prediction Approach Supporting Mashup Recommendation

Service (API) discovery and recommendation is key to the wide spread of service oriented architecture and service oriented software engineering. Service recommendation typically relies on service linkage prediction calculated by the semantic distances (or similarities) among services based on their collection of inherent attributes. Given a specific context (mashup goal), however, different attributes may contribute differently to a service linkage. In this paper, instead of training a model for all attributes as a whole, a novel approach is presented to simultaneously train separate models for individual attributes. Meanwhile, a latent attribute modeling method is developed to reveal context-aware attribute distribution. Experiments over real-world datasets have demonstrated that this fine-grained method yields higher link prediction accuracy.
Cure of human diabetic neuropathy by HPLC validated bark extract of Onosma echioides L. root

Abstract HPLC validated hexane bark extract of Onosma echioides L. root (OE) was evaluated for cure of human diabetic neuropathy in human neuroblastoma cell line. HPLC analysis was performed. Human neuroblastoma cells were grouped into control, normal glucose, high glucose (HG) and HG plus different concentrations of OE extract (10, 25 and 50 μg/mL). MTT, DCFH-DA staining and nuclear condensation assays were performed on neuroblastoma cells to evaluate antiproliferative activity, ROS activity level and apoptotic effect of OE. HPLC analysis revealed the existence of maximum yield of shikonin in n-hexane extract of OE. Exposure with different concentrations of OE effectively decreased ROS level and apoptosis of cells and as a result improved the viability of cells in a dose dependent manner in response to HG-induced oxidative stress. Thus, OE possesses the property to cure human diabetic neuropathy and further can be clinically tested for its use in diabetic neuropathy.
Progressive neurodegeneration following spinal cord injury

Objective To quantify atrophy, demyelination, and iron accumulation over 2 years following acute spinal cord injury and to identify MRI predictors of clinical outcomes and determine their suitability as surrogate markers of therapeutic intervention. Methods We assessed 156 quantitative MRI datasets from 15 patients with spinal cord injury and 18 controls at baseline and 2, 6, 12, and 24 months after injury. Clinical recovery (including neuropathic pain) was assessed at each time point. Between-group differences in linear and nonlinear trajectories of volume, myelin, and iron change were estimated. Structural changes by 6 months were used to predict clinical outcomes at 2 years. Results The majority of patients showed clinical improvement with recovery stabilizing at 2 years. Cord atrophy decelerated, while cortical white and gray matter atrophy progressed over 2 years. Myelin content in the spinal cord and cortex decreased progressively over time, while cerebellar loss decreases decelerated. As atrophy progressed in the thalamus, sustained iron accumulation was evident. Smaller cord and cranial corticospinal tract atrophy, and myelin changes within the sensorimotor cortices, by 6 months predicted recovery in lower extremity motor score at 2 years. Whereas greater cord atrophy and microstructural changes in the cerebellum, anterior cingulate cortex, and secondary sensory cortex by 6 months predicted worse sensory impairment and greater neuropathic pain intensity at 2 years. Conclusion These results draw attention to trauma-induced neuroplastic processes and highlight the intimate relationships among neurodegenerative processes in the cord and brain. These measurable changes are sufficiently large, systematic, and predictive to render them viable outcome measures for clinical trials.
Episodic Tags Enhance Striatal Valuation Signals during Temporal Discounting in pathological Gamblers

Abstract Similar to many addiction disorders, pathological gambling is associated with an increased preference for immediate rewards (steep temporal discounting). In healthy participants, episodic future thinking has been shown to reduce impulsivity during intertemporal choice. Here, we examine for the first time a modulation of temporal discounting via episodic future thinking in a group of pathological gamblers. We investigated a sample of 24 pathological gamblers and 24 matched healthy controls with functional magnetic resonance imaging (fMRI). Participants made intertemporal choices in two experimental conditions. In the control condition, delayed monetary rewards were offered with the respective amount and delay. In the episodic condition, rewards were additionally associated with participant-specific personal future events. We replicated previous findings of increased temporal discounting in pathological gambling. On a trend level, episodic future thinking attenuated discounting across all participants. We found that pathological gamblers could successfully recruit a prospection related network during decision-making in the presence of episodic information. The episodic condition modulated the functional connection between ventromedial prefrontal cortex (vmPFC) and ventral striatum, a mechanism that might support the increase in striatal value coding observed in the episodic condition in gamblers. However, in controls, but not in gamblers, valuation signal changes in the hippocampus were associated with less impulsive behavior. We provide first evidence that by episodic cues during intertemporal decision-making striatal valuation signals can be enhanced in pathological gamblers. Further research is needed to explore interventions that reliably reduce impulsive choice behavior in pathological gambling.
“Anything that makes life’s journey better.” Exploring the use of digital technology by people living with motor neurone disease

Abstract Our aim was to explore the attitudes of those living with motor neuron disease towards digital technology. Postal and online questionnaires surveyed 83 people with MND (pwMND) and 54 friends and family members (fMND). Five pwMND and five fMND underwent semi-structured interviews. 82% of pwMND and 87% of fMND use technology every day with iPads and laptops being the devices most commonly used. pwMND used technology to help them continue to participate in everyday activities such as socialising, entertainment and accessing the internet. The internet provided peer support and information about MND but information could be distressing or unreliable. Participants preferred information from professionals and official organisations. Participants were generally supportive of using of technology to access medical care. Barriers to technology, such as lack of digital literacy skills and upper limb dysfunction, and potential solutions were identified. More challenging barriers included language and cognitive difficulties, and the fear of becoming dependent on technology. Addressing the barriers identified in this research could help pwMND access technology. However, as healthcare delivery becomes more reliant on digital technology, care should be taken to ensure that those who are unable or unwilling to use technology continue to have their needs met in alternative ways.
First Experiments with a Flexible Infrastructure for Normative Reasoning

A flexible infrastructure for normative reasoning is outlined. A small-scale demonstrator version of the envisioned system has been implemented in the proof assistant Isabelle/HOL by utilising the first authors universal logical reasoning approach based on shallow semantical embeddings in meta-logic HOL. The need for such a flexible reasoning infrastructure is motivated and illustrated with a contrary-to-duty example scenario selected from the General Data Protection Regulation.
Developer Turnover in Global, Industrial Open Source Projects: Insights from Applying Survival Analysis

Large open source software projects often have a globally distributed development team. Studies have shown developer turnover has a significant impact on the project success. Frequent developer turnover may lead to loss of productivity due to lacking relevant knowledge and spending extra time learning how projects work. Thus, lots of attention has been paid to which factors are related to developer retention, however, few of them focus on the impact of activities of individual developers. In this paper, we study five open source projects from different organizations and examine whether developer turnover is affected by when they start contributing and what types of contributions they are making. Our study reveals that developers have higher chances to survive in software projects when they 1) start contributing to the project earlier, 2) mainly modify instead of creating files, 3) mainly code instead of dealing with documentations. Our results also shed lights on the potential approaches to improving developer retention.
Users are not Influenced by High Impact and Core Journals while Searching

Much attention has been paid recently in analyzing the interaction between the user and the search system. Interactive information retrieval researchers have become more interested in studying the user behavior in academic search engines in order to improve ranking and to better understand the user expectations. In our previous work, we analyzed the user behavior towards Marcia Bates’ search stratagems such as ’footnote chasing’, ’citation search’, ’keyword search’ and ’author search’. In this paper, we propose to examine in more detail the user behavior towards journal paper search known as the ’journal run’ stratagem. We study the frequency and the stage of ’journal run’ use in a social sciences academic search engine log. We found that the journal run is mostly used at the end of retrieval sessions and has an approximate usefulness of 55% measured by the presence of positive user actions in the log. Moreover, we include typical journal metrics in our case study and test whether there is an influence of the journals’ impact factor (IF) and coreness of a journal on the overall session conduct. We found that the metric IF and coreness of a journal do not have a measurable impact on the journals utilization of social sciences users.
Exposure of Honey Bee (Apis mellifera L.) Colonies to Pesticides in Pollen, A Statewide Assessment in Maine

Abstract In 2015, we conducted a statewide assessment of honey bee exposure to pesticides with assistance of volunteer beekeepers. Pollen trapping was conducted at 32 sites in the spring, summer, and early fall. Apiary locations ranged from unmanaged natural landscapes to managed agricultural or urban landscapes. Pollen samples at each site were aggregated over the collection dates and chemical residue analysis was conducted on each pollen sample for 190 pesticides and metabolites using HPLC/MS. Twenty-five different residues were detected for an average of 2.9 detections per site. Detections were dominated by fungicides, but risk, calculated as: ppb residue concentration/ LD50, was mostly due to insecticides. Beekeeper perceived land-use in the vicinity of each apiary was associated with significant differences in the number of detections and residue concentrations, agricultural landscapes greater than nonagricultural. However, there was no significant difference in oral or contact risk quotients due to land-use type. The landscape composition surrounding apiaries, derived with GIS, determined pesticide exposure for honey bees when total detections, log pesticide residue concentration, and log contact risk quotients were used as measures. Partial least squares explained 43.9% of the variance in pesticide exposure due to landscape composition. The best predictors describing pesticide exposure were: area (ha) of blueberry, coniferous forest, and urban/developed land cover types. Maine is the most forested state in the United States (as determined by % land area forested, 93%) and a negative exponential decay was observed between land area in conifer forest and the number of pesticide detections per apiary.
Swept-Wing Ice Accretion Characterization and Aerodynamics

NASA, FAA, ONERA, the University of Illinois and Boeing have embarked on a significant, collaborative research effort to address the technical challenges associated with icing on large-scale, three-dimensional swept wings. The overall goal is to improve the fidelity of experimental and computational simulation methods for swept-wing ice accretion formation and resulting aerodynamic effect. A seven-phase research effort has been designed that incorporates ice-accretion and aerodynamic experiments and computational simulations. As the baseline, full-scale, swept-wing-reference geometry, this research will utilize the 65 percent scale Common Research Model configuration. Ice-accretion testing will be conducted in the NASA Icing Research Tunnel for three hybrid swept-wing models representing the 20, 64 and 83 percent semispan stations of the baseline-reference wing. Threedimensional measurement techniques are being developed and validated to document the experimental ice-accretion geometries. Artificial ice shapes of varying geometric fidelity will be developed for aerodynamic testing over a large Reynolds number range in the ONERA F1 pressurized wind tunnel and in a smaller-scale atmospheric wind tunnel. Concurrent research will be conducted to explore and further develop the use of computational simulation tools for ice accretion and aerodynamics on swept wings. The combined results of this research effort will result in an improved understanding of the ice formation and aerodynamic effects on swept wings. The purpose of this paper is to describe this research effort in more detail and report on the current results and status to date.
Novel Pulsed-Latch Replacement in Non-Volatile Flip-Flop Core

In this paper, we propose efficient scalable nonvolatile flip-flops (NV-FF) with single-stage pulsed latch which is explored as the flip-flop core in hybrid CMOS/MTJ (magnetic tunnel junction) integration. Typical full-custom FF cores are implemented with a 28nm ultra-thin body and buried oxide (UTBB) fully depleted silicon-on-insulator (FD-SOI) technology. The performance analysis takes into account sensing delay, dynamic power, leakage power and process variations. Results show that the transmission gate pulsed latch (TGPL) based NVFF exhibits enhanced performance compared to conventional master-slave structure, with improved variability, 15.7% fast timing metric, 76% dynamic, 79% leakage power reduction and 30% layout area reduction in multi-bit NV-FF hybrid circuit integration. The pulsed latch FF core can enhance NVFF scalability with increased energy-delay and layout efficiency, as well as reduced active and leakage energy.
Investigation of Replication Factor for Performance Enhancement in the Hadoop Distributed File System

The massive growth in the volume of data and the demand for big data utilisation has led to an increasing prevalence of Hadoop Distributed File System (HDFS) solutions. However, the performance of Hadoop and indeed HDFS has some limitations and remains an open problem in the research community. The ultimate goal of our research is to develop an adaptive replication system; this paper presents the first phase of the work - an investigation into the replication factor used in HDFS to determine whether increasing the replication factor for in-demand data can improve the performance of the system. We constructed a physical Hadoop cluster for our experimental environment, using TestDFSIO and both the real world and the synthetic data sets, NOAA and TPC-H, with Hive to validate our proposal. Results show that increasing the replication factor of the »hot» data increases the availability and locality of the data, and thus, decreases the job execution time.