Miracle-dz/UniFAR-FTUs huggingface dataset:
Epigenetic modifications promote the expression of the orphan nuclear receptor NR0B1 in human lung adenocarcinoma cells

The ectopic activation of NR0B1 is involved in the development of some cancers. However, the regulatory mechanisms controlling NR0B1 expression are not well understood. Therefore, the epigenetic modifications promoting NR0B1 activation were examined in this study. NR0B1 protein was detected in cancerous tissues of more than 50% of human lung adenocarcinoma (ADCA) cases and tended to be expressed in low-differentiated cancerous tissues obtained from males. Nevertheless, NR0B1 activation in ADCA has not previously been correlated with DNA demethylation. NR0B1 expression was not detected in 293T cells, although it contains a hypomethylated NR0B1 promoter. Treating 293T cells with a histone deacetylase inhibitor increased acetylated histone H4 binding to the NR0B1 promoter and activated NR0B1 expression. In contrast, treatment with histone methylase inhibitors decreased the methylation of histones H3K9 and H3K27 and slightly induced NR0B1 transcription. Furthermore, the level of acetyl-histone H4 binding to the NR0B1 promoter increased, whereas the occupancy of H3K27me3 was lower in cancerous tissues than in non-cancerous tissues. Similar histone occupancies were confirmed in a comparison of cancerous tissues with strong, moderate and negative NR0B1 expression. In conclusion, this study shows that CpG methylation within the NR0B1 promoter is not involved in the in vivo regulation of NR0B1 expression, whereas the hyperacetylation of histone H4 and the unmethylation of histones H3K9 and H3K27, and their binding to the NR0B1 promoter results in decondensed euchromatin for NR0B1 activation.
Improvements in the Accuracy of Pairwise Genomic Alignment

Pairwise sequence alignment is a fundamental problem in bioinformatics with wide applicability. This thesis presents three new algorithms for this well-studied problem. First, we present a new algorithm, RDA, which aligns sequences in small segments, rather than by individual bases. Then, we present two algorithms for aligning long genomic sequences: CAPE, a pairwise global aligner, and FEAST, a pairwise local aligner. RDA produces interesting alignments that can be substantially different in structure than traditional alignments. It is also better than traditional alignment at the task of homology detection. However, its main negative is a very slow run time. Further, although it produces alignments with different structure, it is not clear if the differences have a practical value in genomic research. Our main success comes from our local aligner, FEAST. We describe two main improvements: a new more descriptive model of evolution, and a new local extension algorithm that considers all possible evolutionary histories rather than only the most likely. Our new model of evolution provides for improved alignment accuracy, and substantially improved parameter training. In particular, we produce a new parameter set for aligning human and mouse sequences that properly describes regions of weak similarity and regions of strong similarity. The second result is our new extension algorithm. Depending on heuristic settings, our new algorithm can provide for more sensitivity than existing extension algorithms, more specificity, or a combination of the two. By comparing to CAPE, our global aligner, we find that the sensitivity increase provided by our local extension algorithm is so substantial that it outperforms CAPE on sequence with 0.9 or more expected substitutions per site. CAPE itself gives improved sensitivity for sequence with 0.7 or more expected substitutions per site, but at a great run time cost. FEAST and our local extension algorithm improves on this too, the run time is only slightly slower than existing local alignment algorithms and asymptotically the same.
Innovation, Knowledge Diffusion, and Selection

This paper constructs a theory of industry growth through innovation and selection-driven creative destruction. Firms’ ideas determine their productivity and stochastically evolve over time. Firms innovate to improve their ideas and endogenously exit if unsuccessful. Entrants adopt the ideas of incumbents. In this model, when better ideas are innovated or adopted, they selectively replace worse ideas. Innovation externalities vary based on firm productivity: ideas generated by more productive firms create 1) longer-lasting positive externalities due to knowledge diffusion and 2) stronger negative externalities due to dynamic displacement of other firms. Therefore, the net external effect of innovation on aggregate productivity is heterogeneous and market equilibrium misallocates investments across firms. The solution to the social planner's problem suggests that optimal innovation policy instruments should depend on firm productivity. Quantitatively, the misallocations are large when the model is calibrated to firm-level data from US manufacturing and retail trade, and imply first-order considerations for the design of innovation policy.
Adaptive MOOCs: A framework for adaptive course based on intended learning outcomes

Increasing attention is being paid to the open learning environments (i.e., Massive Open Online Courses MOOCs) which offer so many courses in different domains by a number of the top universities around the world. Furthermore, users with different background and experience are able to browse and follow different online courses. However, richness of such courses could be also a weakness point. For instance, giving opportunity to different learners to be able to explore a huge number of courses may run the risk of overwhelming them. Furthermore, they may not be able to get the required benefit out of some followed courses as the course level is not suitable for the learners or the courses' contents do not match intended learning outcomes (ILOs). This is considered as a motivation in academic discussions on e-learning domain to support learners with adaptive online MOOCs. This research work is aimed at supporting learners with suitable learning resources in MOOCs by investigating the possibility of providing suitable learning resources and arrange them in a way that match learner's profile. In particular, this work elaborates on the principles used for delivering adaptive courses based on intended learning outcomes and it proposes a conceptual framework to achieve adaptation process. As a future step, a pilot evaluation will be conducted to test and verify the effectiveness of the proposed framework in term of learner's satisfaction and dropout rate.
Continuous-fidelity Bayesian Optimization with Knowledge Gradient

While Bayesian optimization (BO) has achieved great success in optimizing expensive-to-evaluate black-box functions, especially tuning hyperparameters of neural networks, methods such as random search (Li et al., 2016) and multi-fidelity BO (e.g. Klein et al. (2017)) that exploit cheap approximations, e.g. training on a smaller training data or with fewer iterations, can outperform standard BO approaches that use only full-fidelity observations. In this paper, we propose a novel Bayesian optimization algorithm, the continuous-fidelity knowledge gradient (cfKG) method, that can be used when fidelity is controlled by one or more continuous settings such as training data size and the number of training iterations. cfKG characterizes the value of the information gained by sampling a point at a given fidelity, choosing to sample at the point and fidelity with the largest value per unit cost. Furthermore, cfKG can be generalized, following Wu et al. (2017), to settings where derivatives are available in the optimization process, e.g. large-scale kernel learning, and where more than one point can be evaluated simultaneously. Numerical experiments show that cfKG outperforms state-of-art algorithms when optimizing synthetic functions, tuning convolutional neural networks (CNNs) on CIFAR-10 and SVHN, and in large-scale kernel learning.
Adaptation of field pea varieties to organic farming across different environments of Italy

Abstract. This study aimed to support field pea (Pisum sativum L.) breeding strategies for organic systems of southern European environments, by assessing the size of genotype × environment interaction (GEI) due to spatial and temporal factors across climatically contrasting regions and identifying plant characters associated with genotype adaptive responses. Twelve recent varieties were evaluated for grain yield and other traits in six organically managed environments (three sites × two cropping years) of northern, central and southern Italy. GEI for grain yield was large, with the variety × site × year interaction greatly exceeding the variety × site interaction. This finding, and the similar magnitude of the mean genetic correlations for variety yields across pairs of sites (rg = 0.56) and pairs of years (rg = 0.51), indicated the difficulty of exploiting variety × site interaction effects by breeding for specific climatic regions. Pattern analysis highlighted the large inconsistency across years for GEI pattern of the sites from central and southern Italy. GEI also complicated the targeting of varieties, owing to inconsistent top-performing material across years according to additive main effects and multiplicative interaction (AMMI)-modelled yields. Higher genotype mean yield was strictly associated (P < 0.01) with lower weed proportion (hence, greater competitiveness against weeds: r = –0.96), taller plants (r = 0.89) and larger seeds (r = 0.78), with looser associations with lower susceptibility to lodging and ascochyta blight. These traits, which also contributed to preferential adaptation to the moisture-favourable environments of northern Italy, could be selected in breeding widely adapted varieties.
Predicting of Machine Perceptionfor Automated Driving

In the case of highly-automated and fully-automated driving it is necessary for the vehicle itself to recognize the limitations of its machine perception, as well as the functional limitations of processing modules based on this perception to react adequately. While simulator studies of highly-automated driving have shown that realistic transfer times to the driver of between 5 and 10 s can be assumed [1, 2] before the driver can reliably take over the driving task again, with fully-automated driving a human would not provide any backup whatsoever. In the case of functional limitations, the vehicle would have to be able to achieve an intrinsically safe state completely by itself. However, potential transfer times of 5 s and more require extensive autonomy of the vehicle, if only for a limited time, in order to be able to bridge this time period reliably under all circumstances. To be able to achieve this degree of autonomy, the vehicle must perceive its surroundings, interpret them appropriately and be able to derive and execute reliable actions continuously. Technically, this task is carried out by individual processing modules that build on each other. A simplified representation of the relationships is shown in Fig. 20.1. The machine perception of the vehicle’s surroundings is enabled by various sensors, such as cameras or radar sensors, incorporated into the vehicle. Further information about the static driving environment is usually added from very precise digital maps. However, this can only be used when the vehicle knows its exact position. Therefore, the vehicle also requires a self-localization functional module for the map matching. The result of the machine perception is a dynamic vehicle environment model in which the vehicle itself and all other road users are represented by individual dynamic motion models. This
The Addition of Temperature to the TSS-RESTREND Methodology Significantly Improves the Detection of Dryland Degradation

Cold drylands make up 20% of the world's water-limited regions. This paper presents a modification to the Time Series Segmented-RESidual TRENDs (TSS-RESTRENDs) method that allows for the use of temperature as an additional explanatory variable along with precipitation. TSS-RESTREND was performed over Mongolia, both with and without temperature. The addition of temperature reduced the number of pixels that fail the significance tests built into the TSS-RESTREND method from 17% to below 5%. It also improved the statistical confidence in almost all areas. Furthermore, the direction of change is consistent with previous findings that looked at vegetation trends over the same study region. When applied to all of the world's drylands, the inclusion of temperature improved the fit of the vegetation–climate relationship that underpins TSS-RESTREND in 98.8% of areas. The largest improvements to the fit were observed in both the cold drylands of central Asia and North America and the hot drylands of southern Australia. Including temperature also reduced the fraction of global vegetation change that could be attributed to neither climate nor land use from 25.5% to 15.5%.
A How-To guide to: Quantitative high-speed video profiling to discriminate between variants of primary ciliary dyskinesia

This document presents detailed steps to analysing the waveforms of beating cilia, measured in high speed video microscopy. We show that in the case of PCD caused by mutations in DNAH11 and HYDIN the classification by a handful of parameters describing ciliary dynamics allows to distinguish the genotype, as well as (much more easily) distinguishing healthy from PCD samples. This document is intended to complement the brief highlight (1) and presents the details of the datasets used in that letter.
Tumor Endothelial Marker 8 Amplifies Canonical Wnt Signaling in Blood Vessels

Tumor Endothelial Marker 8/Anthrax Toxin Receptor 1 (TEM8/ANTXR1) expression is induced in the vascular compartment of multiple tumors and therefore, is a candidate molecule to target tumor therapies. This cell surface molecule mediates anthrax toxin internalization, however, its physiological function in blood vessels remains largely unknown. We identified the chicken chorioallantoic membrane (CAM) as a model system to study the endogenous function of TEM8 in blood vessels as we found that TEM8 expression was induced transiently between day 10 and 12 of embryonic development, when the vascular tree is undergoing final development and growth. We used the cell-binding component of anthrax toxin, Protective Antigen (PA), to engage endogenous TEM8 receptors and evaluate the effects of PA-TEM8 complexes on vascular development. PA applied at the time of highest TEM8 expression reduced vascular density and disrupted hierarchical branching as revealed by quantitative morphometric analysis of the vascular tree after 48h. PA-dependent reduced branching phenotype was partially mimicked by Wnt3a application and ameliorated by the Wnt antagonist, Dikkopf-1. These results implicate TEM8 expression in endothelial cells in regulating the canonical Wnt signaling pathway at this day of CAM development. Consistent with this model, PA increased beta catenin levels acutely in CAM blood vessels in vivo and in TEM8 transfected primary human endothelial cells in vitro. TEM8 expression in Hek293 cells, which neither express endogenous PA-binding receptors nor Wnt ligands, stabilized beta catenin levels and amplified beta catenin-dependent transcriptional activity induced by Wnt3a. This agonistic function is supported by findings in the CAM, where the increase in TEM8 expression from day 10 to day 12 and PA application correlated with Axin 2 induction, a universal reporter gene for canonical Wnt signaling. We postulate that the developmentally controlled expression of TEM8 modulates endothelial cell response to canonical Wnt signaling to regulate vessel patterning and density.
MEMS Accelerometer Based Gesture Recognition For System Security and Remote User Notificatio

This project is based on the MEMS based accelerometer used for hand gesture recognition for security purposes. This aims to provide a security to any system consisting of confidential data. Thus in this project we will be using MEMS accelerometer which is the central component of this project. This will intake the gesture as an input from the user. The input will then be given to the Matlab program which has the security code in it. This program will be used to map the stored data/templates of the specified user in the system. If the template is matched then the access will be given to the person else not. For the templates to be stored there is a need of use of database MySQL which will store N number of templates in the database. Here if any suspicious or non specified person tries to access the system the person will not be allowed to access the system. Its log will be generated in the database where the details of the person and the event will be stored i.e. gesture of the person, number of times the gesture been made, time for which the person was on the system and so on. Also after 3-5 unsuccessful attempts for login the system will be locked and the intimation of the same will be given to the existing user through the GSM module as a SMS on its mobile phone. Thus the user is able to access the system or is informed by the system at remote places as well. Keywords—Handgesture; MEMS accelerometer; MySQL; Matlab.
A compact low-distortion low-power instrumentation amplifier

A CMOS instrumentation amplifier based on a simple topology that comprises a double-input Gm-stage and a low-distortion class-AB output stage is presented. Sub-threshold design techniques are applied to attain high figures of differential-gain and rejection parameters. Analyses of input-referred noise and CMRR are comprehensively carried out and their dependence on design parameters determined. The prototype was fabricated in a standard n-well CMOS process. For 5V-rail-to-rail supply and bias current of 100nA, stand-by consumption is only 16μW. Low-frequency parameters are ADM=86dB, CMRR=89.3dB, PSRR+=87dB, PSRR-=74dB. For a 6.5pF-damping capacitor, ΦM=73° and GBW=47KHz. The amplifier exhibits a THD of -64.5dB @100Hz for a 1Vpp-output swing. Input-noise spectral density is 5. 2μV/√Hz @1Hz and 1. 9μV/√Hz @10Hz, which gives an equivalent input noise of 37. 6μV, over 1Hz--200Hz bandwidth. This circuit can be employed for low-frequency, low-distortion signal processing, advantageously replacing the conventional 3-opamp approach for instrumentation amplifiers.
Mass Accumulation Efficiency in Helium Shell Flashes for Various White Dwarf Masses

We have calculated the mass accumulation efficiency during helium shell flashes on white dwarfs (WDs) of mass 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, and 1.35 M☉ for the helium accretion rates log He (M☉ yr-1) = -7.4 to -5.8. This efficiency is a crucial factor for binary evolutions of Type Ia supernovae. For less massive WDs (<0.8 M☉) no wind mass loss occurs, and all the accreted mass accumulates on the WD if the Roche lobe size is large enough. The efficiency takes the minimum values in between 1.1 and 1.2 M☉ WD for a given mass accretion rate, as well as increases in both less and more massive WDs. The mass accumulation efficiency is larger than 0.5 for log He ≥ -6.72 in all the WD masses.
Design of FMCW radar transceiver at 24 GHz

Fig. 4 show the performance of circulator. Both the insertion losses S21 and S32 are −3 dB at 24 GHz. The isolation all are lower than −20 dB at 24GHz. The return losses S11 and S33 are lower than −10 dB at 24 GHz. The active balun in cascade with the in-phase combiner as shown in Fig.2 successfully isolate the signal from port 1 to port3. The buffers effectively decrease the insertion loss and increase the isolation. Fig. 5 show the performance of VCO, which has about 4 GHz wide of tuning range, and the phase noise is lower than −100 dBc/Hz at 1 MHz offset over all the operation frequency band. Since the cross-coupled complementary circuit has lower parasitic capacitance and the varactor size is large, the tuning range can be significantly increased and only 2.9 mW is consumed by the VCO.
Performance Evaluation of Joint Routing and Scheduling in Opportunistic Sensor Networks

In present scenario the innovation of mobile phones that are embedded with different types of onboard sensors, has brought on a new interest of using them as the main part of the sensor network, for a wide area of applications (for e.g. monitoring). In such ad-hoc network end to end connectivity cannot be established and the connection comes out to be mainly opportunistic. The connection in Opportunistic Sensor Network (OSN) is many to one i.e. all the nodes have a common destination. The prominent challenge faced in the opportunistic sensor networks includes the Routing /Scheduling and managing the constrained memory. In this paper scheduling is defined by routing combined with proper buffer management policy and since the scheduling in OSN is node based so selection of proper Buffer management is also significant. This paper considers the monitoring application with the help of human carried mobile sensors and hence a performance evaluation of joint Routing/Scheduling and Buffer management using simulator called ONE (Opportunistic Network Environment) Simulator is done. Simulation results indicate superiority of Shortest remaining Life Time (SHLI) scheme for node movement as per human mobility characteristics. This is contrary to community mobility model as shown for PROPHET algorithm, in which Most Forwarded First (MOFO) scheme performs better.
Working Memory Capacity and Visual Attention: Top-Down and Bottom-Up Guidance

Previous studies have indicated that working memory capacity (WMC) is related to visual attention when selection of critical information must be made in the face of distraction. The present study examines whether WMC-related differences in flanker task performance might be decreased by displays that are designed to support bottom-up guidance of attention. Participants were required to respond to a centrally located target while ignoring a peripheral flanker. In one condition, bottom-up support was provided by embedding the target in a row of zeros. In another condition, the zeros were removed, thus emphasizing the role of top-down attention in selecting spatially defined information. It was found that the inclusion of zeros led to the elimination of WMC-related flanker effects. We conclude that bottom-up attentional guidance can attenuate the role of WMC in selective attention.
A hybrid simulated annealing for scheduling in dual-resource cellular manufacturing system considering worker movement

ABSTRACT This paper presents a novel linear mathematical model for integrated cell formation and task scheduling in the cellular manufacturing system (CMS). It is suitable for the dual-resource constrained setting, such as garment process, component assembly, and electronics manufacturing. The model can handle the manufacturing project composing of some tasks with precedence constraints. It provides a method to assign the multi-skilled workers to appropriate machines. The workers are allowed to move among the machines such that the processing time of tasks might be reduced. A hybrid simulated annealing (HSA) is proposed to minimize the makespan of manufacturing project in the CMS. The approach combines the priority rule based heuristic algorithm (PRBHA) and revised forward recursion algorithm (RFRA) with conventional simulated annealing (SA). The result of extensive numerical experiments shows that the proposed HSA outperforms the conventional SA accurately and efficiently.