Miracle-dz/UniFAR-FTUs huggingface dataset:
Systemic Transplantation of Human Adipose Tissue-Derived Mesenchymal Stem Cells for the Regeneration of Irradiation-Induced Salivary Gland Damage

Objectives Cell-based therapy has been reported to repair or restore damaged salivary gland (SG) tissue after irradiation. This study was aimed at determining whether systemic administration of human adipose-derived mesenchymal stem cells (hAdMSCs) can ameliorate radiation-induced SG damage. Methods hAdMSCs (1×106) were administered through a tail vein of C3H mice immediately after local irradiation, and then this infusion was repeated once a week for 3 consecutive weeks. At 12 weeks after irradiation, functional evaluations were conducted by measuring salivary flow rates (SFRs) and salivation lag times, and histopathologic and immunofluorescence histochemistry studies were performed to assay microstructural changes, apoptosis, and proliferation indices. The engraftment and in vivo differentiation of infused hAdMSCs were also investigated, and the transdifferentiation of hAdMSCs into amylase-producing SG epithelial cells (SGCs) was observed in vitro using a co-culture system. Results The systemic administration of hAdMSCs exhibited improved SFRs at 12 weeks after irradiation. hAdMSC-transplanted SGs showed fewer damaged and atrophied acinar cells and higher mucin and amylase production levels than untreated irradiated SGs. Immunofluorescence TUNEL assays revealed fewer apoptotic cells in the hAdMSC group than in the untreated group. Infused hAdMSCs were detected in transplanted SGs at 4 weeks after irradiation and some cells were found to have differentiated into SGCs. In vitro, a low number of co-cultured hAdMSCs (13%–18%) were observed to transdifferentiate into SGCs. Conclusion The findings of this study indicate that hAdMSCs have the potential to protect against irradiation-induced cell loss and to transdifferentiate into SGCs, and suggest that hAdMSC administration should be viewed as a candidate therapy for the treatment of radiation-induced SG damage.
A novel out-of-band signaling mechanism for enhanced real-time support in tactical ad hoc wireless networks

Ad hoc wireless networks have been an increasingly important area of research in the recent past. One issue of great interest in this area is the provision of real-time support. While existing military applications use reservation-based approaches to provide real-time bandwidth guarantees, these schemes are adversely affected by node mobility. We propose an enhanced real-time support scheme that uses a novel out-of-band signaling mechanism to predict future mobility patterns and take corrective action when needed. We also propose an architecture to support differentiated service classes. This helps mobility affected nodes to take proactive measures so as to offer better real-time services to bandwidth critical applications. Through extensive simulations, we show that the use of the out-of-band signaling leads to better real-time support overall, and better response to the more critical classes as needed. We also provide a theoretical analysis for estimating the probability of disruption of a real-time call.
Knowledge-Based Support-Vector Regression for Reinforcement Learning

Reinforcement learning (RL) methods have difficulty scaling to large, complex problems. One approach that has proven effective for scaling RL is to make use of advice provided by a human. We extend a recent advice-giving technique, called Knowledge-Based Kernel Regression (KBKR), to RL and evaluate our approach on the KeepAway subtask of the RoboCup soccer simulator. We present empirical results that show our approach can make effective use of advice. Our work not only demonstrates the potential of advice-giving techniques such as KBKR for RL, but also offers insight into some of the design decisions involved in employing support-vector regression in RL.
A Strategy-Based Interpretation of Stroop

Most accounts of the Stroop effect (Stroop, 1935) emphasize its negative aspect, namely, that in particular situations, processing of an irrelevant stimulus dimension interferes with participants' performance of the instructed task. In contrast, this paper emphasizes the fact that, even with that interference, participants actually can (and usually do) exert enough control to perform the instructed task. An Adaptive Control of Thought-Rational (ACT-R) model of the Stroop task interprets this as a kind of learned strategic control. Specifically, the concept of utility is applied to the two processes that compete in the Stroop task, and a utility-learning mechanism serves to update the corresponding utility values according to experience and hence influence the competition. This model both accounts for various extant Stroop results and makes novel predictions about when people can reduce their susceptibility to Stroop interference. These predictions are tested in three experiments that involve a double-response variant of the Stroop task.
Calculating landscape surface area from digital elevation models

Abstract There are many reasons to want to know the true surface area of the landscape, especially in landscape analysis and studies of wildlife habitat. Surface area provides a better estimate of the land area available to an animal than planimetric area, and the ratio of this surface area to planimetric area provides a useful measure of topographic roughness of the landscape. This paper describes a straightforward method of calculating surface-area grids directly from digital elevation models (DEMs), by generating 8 3-dimensional triangles connecting each cell centerpoint with the centerpoints of the 8 surrounding cells, then calculating and summing the area of the portions of each triangle that lay within the cell boundary. This method tended to be slightly less accurate than using Triangulated Irregular Networks (TINs) to generate surface-area statistics, especially when trying to analyze areas enclosed by vector-based polygons (i.e., management units or study areas) when there were few cells within the polygon. Accuracy and precision increased rapidly with increasing cell counts, however, and the calculated surface-area value was consistently close to the TIN-based area value at cell counts above 250. Raster-based analyses offer several advantages that are difficult or impossible to achieve with TINs, including neighborhood analysis, faster processing speed, and more consistent output. Useful derivative products such as surface-ratio grids are simple to calculate from surface-area grids. Finally, raster-formatted digital elevation data are widely and often freely available, whereas TINs must generally be generated by the user.
A ten-year survey of software architecture

A software architecture can be described as the “blueprint” of a system at the highest level of abstraction, describing components and their important interconnections. In this paper, we retrospectively examine advances and achievements in software architecture during the last ten years, including software architecture description languages, design, analysis and evaluation, evolution and service-oriented architecture. Finally, we discuss the promising research directions on software architecture.
Probabilistic Inference in Queueing Networks

Although queueing models have long been used to model the performance of computer systems, they are out of favor with practitioners, because they have a reputation for requiring unrealistic distributional assumptions. In fact, these distributional assumptions are used mainly to facilitate analytic approximations such as asymptotics and large-deviations bounds. In this paper, we analyze queueing networks from the probabilistic modeling perspective, applying inference methods from graphical models that afford significantly more modeling flexibility. In particular, we present a Gibbs sampler and stochastic EM algorithm for networks of M/M/1 FIFO queues. As an application of this technique, we localize performance problems in distributed systems from incomplete system trace data. On both synthetic networks and an actual distributed Web application, the model accurately recovers the system's service time using 1% of the available trace data.
Received Signal Strength Estimation in Wireless Local Area Network (WLAN) Environment

This paper is focused on indoor propagation prediction in wireless local area network. In this paper, measurements of received signal strength were carried out within fifteen meters of the three access points with a step size of one meter at a test bed environment in the Faculty of Engineering Building; Block A, Nnamdi Azikiwe University Awka, Anambra State, Nigeria. The Netstumbler software installed in a laptop (DELL. Model: Inspiron E1505) with an inbuilt wireless interface card was used in recording the received signal strength from each of the access points. Results obtained showed that the received signal strength decreases as the distance of the receiver increases from the transmitting point and the developed mathematical signal model can be used as a valuable tool for accurate prediction of the received signal strength in the testbed environment.
The Lateral Occipital Complex shows no net response to object familiarity

In 1995, Malach et al. discovered an area whose fMRI BOLD response was greater when viewing intact, familiar objects than when viewing their scrambled versions (resembling texture). Since then hundreds of studies have explored this late visual region termed the Lateral Occipital Complex (LOC), which is now known to be critical for shape perception (James, Culham, Humphrey, Milner, & Goodale, 2003). Malach et al. (1995) discounted a role of familiarity by showing that “abstract” Henry Moore sculptures, unfamiliar to the subjects, also activated this region. This characterization of LOC as a region that responds to shape independently of familiarity has been accepted but never tested with control of the same low-level features. We assessed LOC's response to objects that had identical parts in two different arrangements, one familiar and the other novel. Malach was correct: There is no net effect of familiarity in LOC. However, a multivoxel correlation analysis showed that LOC does distinguish familiar from novel objects.
Q value-based Dynamic Programming with SARSA Learning for real time route guidance in large scale road networks

In this paper, a distributed dynamic traffic management model has been proposed to guide the vehicles, in order to minimize the computation time, make full use of real time traffic information and consequently improve the efficiency of the traffic system. For making the model work, we proposed a new dynamic route determination method, in which Q value-based Dynamic Programming and Sarsa Learning are combined to calculate the approximate optimal traveling time from each section to the destinations in the road networks. The proposed traffic management model is applied to the large scale microscopic simulator SOUND/4U based on the real world road network of Kurosaki, Kitakyushu in Japan. The simulation results show that the proposed method could reduce the traffic congestion and improve the efficiency of the traffic system effectively compared with the conventional method in the real world road network.
FPGA/ASIC based Cryptographic Object Store System

avoid re-encryption in cryptographic storage system when revoking users, Field Programmable Gate Array (FPGA) and Application Specific Integrated Circuit (ASIC) hardware module have been introduced to a cryptographic object store system, let private key never leave the hardware module and symmetric key only exist in hardware module in plaintext. Anyone doesn 7 know private or symmetric key, so when revoking users, it just needs to modify access control list (A CL) to delete the privileges of the users. To facilitate file sharing and key management, group is adopted. In our system, almost all computationally expensive cryptographic operations are through FPGA/ASIC hardware module. Once creator revokes some users, objects don't need re- encryption. How to use ACL and FPGA/ASIC hardware module to authenticate and authorize are described. And the procedure of object store and the distribution of meta-data are detailed. Finally, a cryptographic object store prototype system is implemented with tested and effective performance.
miRNA-Mediated Functional Changes through Co-Regulating Function Related Genes

Background microRNAs play important roles in various biological processes involving fairly complex mechanism. Analysis of genome-wide miRNA microarray demonstrate that a single miRNA can regulate hundreds of genes, but the regulative extent on most individual genes is surprisingly mild so that it is difficult to understand how a miRNA provokes detectable functional changes with such mild regulation. Results To explore the internal mechanism of miRNA-mediated regulation, we re-analyzed the data collected from genome-wide miRNA microarray with bioinformatics assay, and found that the transfection of miR-181b and miR-34a in Hela and HCT-116 tumor cells regulated large numbers of genes, among which, the genes related to cell growth and cell death demonstrated high Enrichment scores, suggesting that these miRNAs may be important in cell growth and cell death. MiR-181b induced changes in protein expression of most genes that were seemingly related to enhancing cell growth and decreasing cell death, while miR-34a mediated contrary changes of gene expression. Cell growth assays further confirmed this finding. In further study on miR-20b-mediated osteogenesis in hMSCs, miR-20b was found to enhance osteogenesis by activating BMPs/Runx2 signaling pathway in several stages by co-repressing of PPARγ, Bambi and Crim1. Conclusions With its multi-target characteristics, miR-181b, miR-34a and miR-20b provoked detectable functional changes by co-regulating functionally-related gene groups or several genes in the same signaling pathway, and thus mild regulation from individual miRNA targeting genes could have contributed to an additive effect. This might also be one of the modes of miRNA-mediated gene regulation.
A phrase-based model to discover hidden factors and hidden topics in recommender systems

The majority of existing recommender systems focus on modeling the ratings; however, these systems ignore a large number of reviews. Existing rating based recommender systems are hard to discover the hidden dimensions in human feedback that can identify user preferences. In this study, we combine collaborative filtering with latent review topics to generate a new model called phraseHFT. We apply reviews to the phrase-level document, and use the phrase-based topic model to discover the review topics that are embedded in the review text. The interpretable topics which are learned and presented as phrases can help us understand characteristics of users or items. The conducted experiment shows that our approach outperforms the state-of-the-art techniques in perplexity and topic visualization due to the strong topic learning functionality.
Efficient irradiance normal mapping

Irradiance normal mapping is a method to combine two popular techniques, light mapping and normal mapping, and is used in games such as Half-Life 2 or Halo 3. This combination allows using low-resolution light caching on surfaces with only a few coefficients which are evaluated by normal maps to render spatial high-frequency changes in the lighting. Though there are dedicated bases for this purpose such as the Half-Life 2 basis, higher order basis functions such as quadratic Spherical Harmonics are needed for an accurate representation. However, a full spherical basis is not needed since the irradiance is stored on the surface of a scene. In order to represent the irradiance signals efficiently, we propose a novel polynomial, hemispherically orthonormal basis function set that is specifically designed to carry a directional irradiance signal on the hemisphere and which makes optimal use of the number of coefficients. To compare our results with previous work, we analyze the relations and attributes of previously proposed basis systems and show that 6 coefficients are sufficient to accurately represent an irradiance signal on the hemisphere. To create the necessary irradiance signals, we use Spherical Harmonics as an intermediate basis due to their fast filtering capabilities.
Validating Discovered Cis-Acting Regulatory Genetic Variants: Application of an Allele Specific Expression Approach to HapMap Populations

Background Localising regulatory variants that control gene expression is a challenge for genome research. Several studies have recently identified non-coding polymorphisms associated with inter-individual differences in gene expression. These approaches rely on the identification of signals of association against a background of variation due to other genetic and environmental factors. A complementary approach is to use an Allele-Specific Expression (ASE) assay, which is more robust to the effects of environmental variation and trans-acting genetic factors. Methodology/Principal Findings Here we apply an ASE method which utilises heterozygosity within an individual to compare expression of the two alleles of a gene in a single cell. We used individuals from three HapMap population groups and analysed the allelic expression of genes with cis-regulatory regions previously identified using total gene expression studies. We were able to replicate the results in five of the six genes tested, and refined the cis- associated regions to a small number of variants. We also showed that by using multi-populations it is possible to refine the associated cis-effect DNA regions. Conclusions/Significance We discuss the efficacy and drawbacks of both total gene expression and ASE approaches in the discovery of cis-acting variants. We show that the ASE approach has significant advantages as it is a cleaner representation of cis-acting effects. We also discuss the implication of using different populations to map cis-acting regions and the importance of finding regulatory variants which contribute to human phenotypic variation.
The Pomeron as a Finite Sum of Gluon Ladder

A model for the Pomeron at t=0 is suggested. It is based on the idea of a finite sum of ladder diagrams in QCD. Accordingly, the number of s-channel gluon rungs and correspondingly the powers of logarithms in the forward scattering amplitude depends on the phase space (energy) available, i.e. as energy increases, progressively new prongs with additional gluon rungs in the s-channel open. Explicit expressions for the total cross section involving two and three rungs or, alternatively, three and four prongs (with $\ln^2(s)$ and $\ln^3(s)$ as highest terms) is fitted to the proton-proton and proton-antiproton total cross section data in the accelerator region.
Performance evaluation of half-bridge cascaded multilevel converters operated with multicarrier sinusoidal PWM techniques

High-power high-voltage power electronics systems with fully-controlled semiconductors can benefit from the development of modular solutions based on voltage-sourced building blocks. This paper offers a performance comparison of various multicarrier sinusoidal pulse width modulation (PWM) techniques for the control of the modular multilevel converter (MMC) based on the half-bridge capacitor cell. It is found that the PWM method can significantly affect the ripple of the capacitor free DC-bus, hence the selection of the carrier frequency and the multi-carrier PWM method is an important design question for the MMC topology. Simulation results for a three-phase rectifier-inverter system generated with the PSCAD/EMTDC software package are provided to support the theoretical considerations.
A novel grade-lymph node ratio model predicts the prognosis of the advanced gastric cancer patients after neoadjuvant radiotherapy

Although local advanced gastric cancer (AGC) could benefit from neoadjuvant radiotherapy (NRT), there are few studies evaluating patients survival after NRT. In current study, we aimed to investigate the value of prognostic factors in AGC patients after NRT and to evaluate whether post-therapy pathological characteristics were predictive factors in these patients. We retrospectively analyzed AGC patients who underwent NRT from Surveillance, Epidemiology, and End Results (SEER) Database. The patients clinical and post-therapy pathological characteristics were analyzed. The best cutoff points for continuous variables were identified by X-tile. The discrimination of risk factors were compared by receiver operating characteristic (ROC) curve. As a result, 1,429 AGC patients were included into this study. In the multivariate analysis, the lymph nodes status and histology grade were significant risk factors for DSS (disease special survival). Then, we propose a novel Grade-lymph node Ratio (G-R) staging system for the AGC patients survival prognosis. Clearly, the new G-R staging system has a more-accurate 3-year and 5-year DSS prediction than the AJCC staging system (p = 0.001, 0.007, respectively). In conclusions, the current large, general population-based study demonstrated that the G-R staging system resulting in more-accurate DSS prediction. It could be regarded as a reliable classification for AGC patients after NRT in future.
Tagging gene and protein names in biomedical text

MOTIVATION The MEDLINE database of biomedical abstracts contains scientific knowledge about thousands of interacting genes and proteins. Automated text processing can aid in the comprehension and synthesis of this valuable information. The fundamental task of identifying gene and protein names is a necessary first step towards making full use of the information encoded in biomedical text. This remains a challenging task due to the irregularities and ambiguities in gene and protein nomenclature. We propose to approach the detection of gene and protein names in scientific abstracts as part-of-speech tagging, the most basic form of linguistic corpus annotation. RESULTS We present a method for tagging gene and protein names in biomedical text using a combination of statistical and knowledge-based strategies. This method incorporates automatically generated rules from a transformation-based part-of-speech tagger, and manually generated rules from morphological clues, low frequency trigrams, indicator terms, suffixes and part-of-speech information. Results of an experiment on a test corpus of 56K MEDLINE documents demonstrate that our method to extract gene and protein names can be applied to large sets of MEDLINE abstracts, without the need for special conditions or human experts to predetermine relevant subsets. AVAILABILITY The programs are available on request from the authors.