Miracle-dz/UniFAR-FTUs huggingface dataset:
XNP/dATRX interacts with DREF in the chromatin to regulate gene expression

The ATRX gene encodes a chromatin remodeling protein that has two important domains, a helicase/ATPase domain and a domain composed of two zinc fingers called the ADD domain. The ADD domain binds to histone tails and has been proposed to mediate their binding to chromatin. The putative ATRX homolog in Drosophila (XNP/dATRX) has a conserved helicase/ATPase domain but lacks the ADD domain. In this study, we propose that XNP/dATRX interacts with other proteins with chromatin-binding domains to recognize specific regions of chromatin to regulate gene expression. We report a novel functional interaction between XNP/dATRX and the cell proliferation factor DREF in the expression of pannier (pnr). DREF binds to DNA-replication elements (DRE) at the pnr promoter to modulate pnr expression. XNP/dATRX interacts with DREF, and the contact between the two factors occurs at the DRE sites, resulting in transcriptional repression of pnr. The occupancy of XNP/dATRX at the DRE, depends on DNA binding of DREF at this site. Interestingly, XNP/dATRX regulates some, but not all of the genes modulated by DREF, suggesting a promoter-specific role of XNP/dATRX in gene regulation. This work establishes that XNP/dATRX directly contacts the transcriptional activator DREF in the chromatin to regulate gene expression.
Integration Characteristics next Generation Class … … Self-organizing Maps Self-organizing Maps Decision Trees Decision Trees Support Vector Machines Support Vector Machines Back Propagation Networks Back Propagation Networks Integration Framework Integration Framework Figure 1. Establishing an Inte

Building on existing hybrid classifi ers still poses important challenges, mostly related to the selection, interoperability and scalability of different classifi ers. As the classifi ers themselves are approaching their limits, the next natural challenge is to establish frameworks that integrate multiple classifi ers into a single unifi ed approach (Figure 1). There are several characteristics that such frameworks should exhibit: z Multi-method support. Frameworks should be open enough to support classifi ers from various AI methods, for example different neural networks (e.g. self-organizing maps, backpropagation and support vector machines), decision trees, and genetic algorithms among others. z Complexity on-demand. Simple classifi cation tasks may not require complex algorithms or multi-dimensional inputs. A successful framework should be able to match algorithms to problem complexity. By doing so, such systems typically exhibit better generalization in results because they do not suffer from overfi tting. z Transparency. The ability to backtrack errors to the original source (i.e. classifi er) is critical to assess each classifi er's performance. Framework architecture should be simple enough to allow identifi cation of problematic classifi ers. z Classifi er independency. Within the framework, each classifi er should work independently of another. This is important to move towards " plug-in " classifi ers where one may be replaced without causing a ripple effect requiring replacement of others. z Scalability. Framework architecture should allow adjustments as problem requirements change, and/or additional groundtruth data become available. Introduction Remote sensing as a field of study has reached its adulthood; computer-assisted classifi ers have been in development for more than two decades. The complexity of remote sensing classifi cation has led to a variety of methods, some of them based on artifi cial intelligence (AI), and provides motivation for this special issue. AI techniques range from simple out-of-the-box implementations to algorithms tailored to the specifi cs of remote sensing classifi cation. Recently, we have also observed a significant increase in parallel processing capabilities. Computer workstations with multiple processors are becoming the mainstream in research laboratories. Physical limitations in processor design indicate that future computational power improvements will result from parallel processing rather than single processor advances. Parallel computing presents a unique opportunity and challenge for image classifi ers. The question arises: how can we harvest this new power to improve classifi cation results? One solution is to implement hybrid clas-sifi ers, i.e. methods that merge multiple approaches together. In the fi eld …
Transactional Memory: Architectural Support For Lock-free Data Structures

A shared data structure is lock-free if its operations do not require mutual exclusion. If one process is interrupted in the middle of an operation, other processes will not be prevented from operating on that object. In highly concurrent systems, lock-free data structures avoid common problems associated with conventional locking techniques, including priority inversion, convoying, and difficulty of avoiding deadlock. This paper introduces transactional memory, a new multiprocessor architecture intended to make lock-free synchronization as efficient (and easy to use) as conventional techniques based on mutual exclusion. Transactional memory allows programmers to define customized read-modify-write operations that apply to multiple, independently-chosen words of memory. It is implemented by straightforward extensions to any multiprocessor cache-coherence protocol. Simulation results show that transactional memory matches or outperforms the best known locking techniques for simple benchmarks, even in the absence of priority inversion, convoying, and deadlock.
Least significant bit image steganography using particle swarm optimization and optical pixel adjustment

Data hiding is a method of concealing secret data into a cover media and preventing a spectator from being aware of the existence of the hidden message. According to the problems of steganography, the main effort is to provide a better imperceptibility of stego-image that can be done by decreasing distortion of image. One of the popular techniques in data hiding is steganography in which the simple method for image hiding is the Least Significant Bit (LSB) substitution method. Wu et al. proposed two image hiding techniques to improve the quality of the stego-image [1]. The first one is to find the best block matching matrix and the other one is to find the optimal substitution matrices. The proposed method utilizes particle Swarm optimization (PSO) for finding the best pixel locations, and then the secret image is transformed to a new secret image. Optimal Pixel Adjustment (OPA) method is applied to further increase the quality of image. Results are then compared with those obtained by Simple LSB, Wang’s et al. method, Wu’s et al. method. The experimental results confirmed that PSNR of the proposed method is higher than mentioned methods which mean the imperceptibility of the image improves. Also the results illustrate that the proposed approach is robust against chi-square attack.
Biogenesis of Insulin‐Responsive GLUT4 Vesicles is Independent of Brefeldin A‐Sensitive Trafficking

Insulin stimulates translocation of GLUT4 from an intracellular compartment to the plasma membrane in adipocytes. As a significant amount of GLUT4 is localised to the TGN, independently of the biosynthetic pathway, one possibility is that trafficking via the TGN is important in either intracellular sequestration or insulin‐dependent movement to the cell surface. In this study we have used immuno‐electron microscopy to show that GLUT4 is localised to AP‐1 vesicles in the TGN region in 3T3‐L1 adipocytes. To dissect the role of this trafficking pathway we used brefeldin A (BFA) to disrupt AP‐1 association with membranes. Despite a reorganisation of GLUT4 compartments following BFA treatment, the intracellular sequestration of GLUT4, and its insulin‐dependent movement to the cell surface, was unaffected. BFA increased the half time of reversal of insulin‐stimulated glucose transport from 17 to 30 min but did not prevent complete reversal. Furthermore, following reversal re‐stimulation of glucose transport activity by insulin was not compromised. We conclude that under basal conditions GLUT4 cycles between the TGN and endosomes via the AP‐1 pathway. However, neither this pathway, nor any other BFA‐sensitive pathway, appears to play a major role in insulin‐dependent recruitment of GLUT4 to the cell surface.
Long-Term Prospective, Randomized, Controlled Study Using Repetitive Education at Six-Month Intervals and Monitoring for Adherence in Heart Failure Outpatients: The REMADHE Trial

Background—The effectiveness of heart failure disease management programs in patients under cardiologists' care over long-term follow-up is not established. Methods and Results—We investigated the effects of a disease management program with repetitive education and telephone monitoring on primary (combined death or unplanned first hospitalization and quality-of-life changes) and secondary end points (hospitalization, death, and adherence). The REMADHE [Repetitive Education and Monitoring for ADherence for Heart Failure] trial is a long-term randomized, prospective, parallel trial designed to compare intervention with control. One hundred seventeen patients were randomized to usual care, and 233 to additional intervention. The mean follow-up was 2.47±1.75 years, with 54% adherence to the program. In the intervention group, the primary end point composite of death or unplanned hospitalization was reduced (hazard ratio, 0.64; confidence interval, 0.43 to 0.88; P=0.008), driven by reduction in hospitalization. The quality-of-life questionnaire score improved only in the intervention group (P<0.003). Mortality was similar in both groups. Number of hospitalizations (1.3±1.7 versus 0.8±1.3, P<0.0001), total hospital days during the follow-up (19.9±51 versus 11.1±24 days, P<0.0001), and the need for emergency visits (4.5±10.6 versus 1.6±2.4, P<0.0001) were lower in the intervention group. Beneficial effects were homogeneous for sex, race, diabetes and no diabetes, age, functional class, and etiology. Conclusions—For a longer follow-up period than in previous studies, this heart failure disease management program model of patients under the supervision of a cardiologist is associated with a reduction in unplanned hospitalization, a reduction of total hospital days, and a reduced need for emergency care, as well as improved quality of life, despite modest program adherence over time.
Energy-transferring approach to power allocation with energy harvesting constraints

This paper studies the problem of optimal power allocation towards maximizing the throughput of point-to-point wireless communication systems with energy harvesting. A novel energy-transferring approach is proposed to analyze the throughput maximization problem with causality constraints, in which we study the transfer energy rather than the water level widely used in the existing literature. The proposed approach simplifies the power allocation as a linear function with respect to only two transfer energy variables, i.e., the energy transferred from the previous epoch and the energy transferred to the next epoch. Moreover, we prove that all the positive transfer energy variables can be determined by solving a set of linear equations with a special coefficient matrix derived from the KKT conditions for the dual problem. Based on the energy-transferring approach, we propose an iterative algorithm to obtain the optimal solution with a much lower complexity compared to those existing algorithms based on the directional water-filling structure results. Numerical studies verify the analytical results as well as the effectiveness of the proposed algorithm.
Web API Fragility: How Robust is Your Mobile Application?

Web APIs provide a systematic and extensible approach for application-to-application interaction. A large number of mobile applications makes use of Web APIs to integrate services into apps. Each Web API's evolution pace is determined by their respective developer and mobile application developers are forced to accompany the API providers in their software evolution tasks. In this paper we investigate whether and how mobile application developers deal with the added distress of Web APIs evolving. In particular, we studied how robust 43 high profile mobile applications are when dealing with mutated Web API responses. Additionally, we interviewed three mobile application developers to better understand their choices and trade-offs regarding Web API integration.
The Performance Evaluation of Qos in Wireless Personal Area Network (WPAN) on Impact of Bluetooth Worms

The Bluetooth technology is the convergence of Mobile Co mmun ication and Co mputing Applications. The set of Mobile Devices "Laptops, Notebook Co mputers,PDA's,Mobile Smart Phones etc" connected by Bluetooth protocol forms a Bluetooth Network or Bluetooth Piconet or WPAN.Even through the devices have numerous benefits its open nature increases the threats and risks being posed on them. The wired network faces challenging problems because of internet worms , similiarly the Bluetooth Network or WPAN faces serious problems because of Bluetooth Worms. This paper gives a comparative study of WPAN performance on impact of Bluetooth Worms in Bluetooth Piconet (symmetric) and Bluetooth Piconet(asymmetric) and derives the result how the degree of homogeneity increases the infection rate.
Determining magnetic susceptibility in loess‐paleosol sections by near‐infrared reflectance spectroscopy

Loess deposits are widespread, covering about 10 percent of the Earth's land surface. Magnetic susceptibility (MS), an important parameter in loess deposits, is a function of the concentration of magnetic minerals, which exhibit diagnostic features in their visible and near‐infrared (NIR) spectra. Therefore, MS should correlate with spectral reflectance. To determine if a relationship exists between MS and reflectance spectra we analyzed NIR spectra and MS of over 550 samples from seven loess‐paleosol sequences on Loess Plateau of Central China. NIR reflectance data were first converted into eight spectral bands and then a step‐wise multiple linear regression was applied to a calibration dataset to establish a model to predict MS values. Test datasets indicate our model is very successful, all produced an r2 > 0.9. By applying this new method for estimating MS to hyperspectral remote sensing data we anticipate mapping soil quality and MS on the Loess Plateau.
Crowd Guilds: Worker-led Reputation and Feedback on Crowdsourcing Platforms

Crowd workers are distributed and decentralized. While decentralization is designed to utilize independent judgment to promote high-quality results, it paradoxically undercuts behaviors and institutions that are critical to high-quality work. Reputation is one central example: crowdsourcing systems depend on reputation scores from decentralized workers and requesters, but these scores are notoriously inflated and uninformative. In this paper, we draw inspiration from historical worker guilds (e.g., in the silk trade) to design and implement crowd guilds: centralized groups of crowd workers who collectively certify each other's quality through double-blind peer assessment. A two-week field experiment compared crowd guilds to a traditional decentralized crowd work model. Crowd guilds produced reputation signals more strongly correlated with ground-truth worker quality than signals available on current crowd working platforms, and more accurate than in the traditional model.
AIDS Education and Training Centers fact sheet. U.S. Department of Health and Human Services Health Resources and Services Administration.

The MIECHV TACC is funded under contract #HHSH250201100023C, US Department of Health and Human Services, Health Resources and Services Administration. The State Maternal, Infant, and Early Childhood Home Visiting Program is administered by HRSA, in collaboration with the Administration for Children and Families. Maternal, Infant, and Early Childhood Home Visiting (MIECHV) Program Technical Assistance Coordinating Center’s Webinar “Impacting Infant Mortality through Home Visiting” October 23, 2012 3:00pm Eastern, 2:00pm Central, 1:00pm Mountain, 12:00pm Pacific Presentation by: Michael Fraser, PhD CAE Chief Executive Officer, Association of Maternal & Child Health Programs
Extrinsic summarization evaluation: A decision audit task

In this work we describe a large-scale extrinsic evaluation of automatic speech summarization technologies for meeting speech. The particular task is a decision audit, wherein a user must satisfy a complex information need, navigating several meetings in order to gain an understanding of how and why a given decision was made. We compare the usefulness of extractive and abstractive technologies in satisfying this information need, and assess the impact of automatic speech recognition (ASR) errors on user performance. We employ several evaluation methods for participant performance, including post-questionnaire data, human subjective and objective judgments, and a detailed analysis of participant browsing behavior. We find that while ASR errors affect user satisfaction on an information retrieval task, users can adapt their browsing behavior to complete the task satisfactorily. Results also indicate that users consider extractive summaries to be intuitive and useful tools for browsing multimodal meeting data. We discuss areas in which automatic summarization techniques can be improved in comparison with gold-standard meeting abstracts.
Pituitary adenylate cyclase-activating peptide induces neurite outgrowth in cultured monkey trigeminal ganglion cells: Involvement of receptor PAC1

Purpose Our previous studies in the rabbit trigeminal nerve (TgN) showed that pituitary adenylate cyclase-activating peptide (PACAP) accelerated the extension of neuronal processes and recovery of corneal sensitivity. The purposes of the present study were 1) develop a procedure to culture trigeminal nerve (TgN) cells from monkeys, 2) test whether PACAP induces sprouting and elongation of axons in our culture system, 3) investigate the signaling mechanisms producing axon elongation induced by PACAP, and 4) test the action of PACAP on tear protein secretion by monkey lacrimal acinar cells. Methods Primary cultures of TgN cells were established from rhesus monkeys. Cellular distribution of the PACAP receptor, PAC1, was determined with immunostaining. Axonal length in cultured TgN ganglion cells was evaluated with staining by antibody for neurofilament. mRNA expression was determined with quantitative real-time polymerase chain reaction (qPCR). Secretion of tear protein from cultured acinar cells was measured with immunoblotting. Results Our results showed that dissociated, cultured TgN cells contained neuronal ganglion and Schwann cells, and the PAC1 receptor was expressed in both cell types. PACAP-27 significantly induced neurite outgrowth, which was inhibited by PACAP 6–27. Inhibitors for adenylate cyclase and phospholipase C also inhibited neurite outgrowth. Follistatin was upregulated by PACAP-27 during the culture period. PACAP enhanced secretion of tear proteins. Conclusions Our data suggested PAC1 activation is involved in TgN neurite outgrowth.
Ergodicity of Adaptive Monte Carlo

Ergodicity results for adaptive Monte Carlo algorithms usually assume time-stability of transition kernels. On the other hand, a large class of time-inhomogeneous Markov Chains is ergodic. This suggests existence of adaptive MC algorithms which fail to satisfy the time-stability condition but are still ergodic. We present a modification of Atchadé-Rosenthal ergodicity Theorems (3.1 and 3.2 in [1]) that does not assume time-stability of transition kernels. We use a weaker path-stability condition instead, that results from time-stability condition by the triangle inequality.
Coordinate-free numerics: all your variation points for free?

Whenever we develop software we know it will evolve over time, and it will need to be adapted to changing requirements. A variation point is where a program has been designed for change, or where it easily can be accommodated to change. Here we discuss variation points in numerical solvers for Partial Differential Equations (PDEs). Our experience is that an abstraction oriented approach based on coordinate-free numerics naturally provides most, if not all, variation points needed.
Combining multiple FDG-PET radiotherapy target segmentation methods to reduce the effect of variable performance of individual segmentation methods.

PURPOSE Many approaches have been proposed to segment high uptake objects in 18F-fluoro-deoxy-glucose positron emission tomography images but none provides consistent performance across the large variety of imaging situations. This study investigates the use of two methods of combining individual segmentation methods to reduce the impact of inconsistent performance of the individual methods: simple majority voting and probabilistic estimation. METHODS The National Electrical Manufacturers Association image quality phantom containing five glass spheres with diameters 13-37 mm and two irregularly shaped volumes (16 and 32 cc) formed by deforming high-density polyethylene bottles in a hot water bath were filled with 18-fluoro-deoxyglucose and iodine contrast agent. Repeated 5-min positron emission tomography (PET) images were acquired at 4:1 and 8:1 object-to-background contrasts for spherical objects and 4.5:1 and 9:1 for irregular objects. Five individual methods were used to segment each object: 40% thresholding, adaptive thresholding, k-means clustering, seeded region-growing, and a gradient based method. Volumes were combined using a majority vote (MJV) or Simultaneous Truth And Performance Level Estimate (STAPLE) method. Accuracy of segmentations relative to CT ground truth volumes were assessed using the Dice similarity coefficient (DSC) and the symmetric mean absolute surface distances (SMASDs). RESULTS MJV had median DSC values of 0.886 and 0.875; and SMASD of 0.52 and 0.71 mm for spheres and irregular shapes, respectively. STAPLE provided similar results with median DSC of 0.886 and 0.871; and median SMASD of 0.50 and 0.72 mm for spheres and irregular shapes, respectively. STAPLE had significantly higher DSC and lower SMASD values than MJV for spheres (DSC, p < 0.0001; SMASD, p = 0.0101) but MJV had significantly higher DSC and lower SMASD values compared to STAPLE for irregular shapes (DSC, p < 0.0001; SMASD, p = 0.0027). DSC was not significantly different between 128 × 128 and 256 × 256 grid sizes for either method (MJV, p = 0.0519; STAPLE, p = 0.5672) but was for SMASD values (MJV, p < 0.0001; STAPLE, p = 0.0164). The best individual method varied depending on object characteristics. However, both MJV and STAPLE provided essentially equivalent accuracy to using the best independent method in every situation, with mean differences in DSC of 0.01-0.03, and 0.05-0.12 mm for SMASD. CONCLUSIONS Combining segmentations offers a robust approach to object segmentation in PET. Both MJV and STAPLE improved accuracy and were robust against the widely varying performance of individual segmentation methods. Differences between MJV and STAPLE are such that either offers good performance when combining volumes. Neither method requires a training dataset but MJV is simpler to interpret, easy to implement and fast.