Miracle-dz/UniFAR-FTUs huggingface dataset:
The Neurospora Transcription Factor ADV-1 Transduces Light Signals and Temporal Information to Control Rhythmic Expression of Genes Involved in Cell Fusion

Light and the circadian clock have a profound effect on the biology of organisms through the regulation of large sets of genes. Toward understanding how light and the circadian clock regulate gene expression, we used genome-wide approaches to identify the direct and indirect targets of the light-responsive and clock-controlled transcription factor ADV-1 in Neurospora crassa. A large proportion of ADV-1 targets were found to be light- and/or clock-controlled, and enriched for genes involved in development, metabolism, cell growth, and cell fusion. We show that ADV-1 is necessary for transducing light and/or temporal information to its immediate downstream targets, including controlling rhythms in genes critical to somatic cell fusion. However, while ADV-1 targets are altered in predictable ways in Δadv-1 cells in response to light, this is not always the case for rhythmic target gene expression. These data suggest that a complex regulatory network downstream of ADV-1 functions to generate distinct temporal dynamics of target gene expression relative to the central clock mechanism.
Singular (Lipschitz) homology and homology of integral currents

We compare the homology groups $H_n ^{IC}(X)$ of the chain complex of integral currents with compact support of a metric space $X$ with the singular Lipschitz homology $H^L_n (X)$ and with ordinary singular homology. If $X$ satisfies certain cone inequalities all these homology theories coincide. On the other hand, for the Hawaiian Earring the homology of integral currents differs from the singular Lipschitz homology and it differs also from the classical singular homology $H_n(X)$.
Teaching Three-and-A-Half-Year-Olds to Revise Their Beliefs Given Ambiguous Evidence

Previous research suggests that three-year-olds fail to learn from statistical data when their prior beliefs conflict with evidence. Are children’s beliefs entrenched in their folk theories, or can preschoolers rationally update their beliefs? Motivated by a Bayesian account, we conducted a training study to investigate this question. Children (45 months) who failed to endorse a statistically more probable (but a priori unlikely) cause following ambiguous evidence were assigned to a Statistical Reasoning training, one of two Prior Belief trainings (Base Rates, Mechanisms), or a Control condition. Relative to the Control, children in the trainings were more likely to endorse the a priori unlikely variable on a free-explanation task. Critically, children in the Statistical Reasoning condition passed this task, even though their only information about the belief-violating variable came from ambiguous evidence. This suggests that statistical reasoning training improves preschoolers’ ability to learn even from data inconsistent with their prior beliefs.
Efficient algorithm for extreme maximal biclique mining in cognitive frequency decision making

The cognitive radio is growing an important interest in wireless communication study. A cognitive radio ad hoc network may take a master-slave tree-based structure in some special applications. For a master node with limited communication capability, slave nodes usually use the same frequency to access a subnet managed by the master. Each slave node can acquire many frequencies for communication by a local spectrum sensing process. However, there may be no common set of frequencies available for every slave node. In this case, we should delete some slave nodes and keep other nodes staying in the subnet as many as possible. By mapping the node set and frequency set to be both parts of a bipartite graph respectively, the problem can be turned into a special case of searching for maximal bicliques. Based on a well-known LCM (Linear time Closed itemset Miner) algorithm which enumerates frequent item sets (maximal bicliques), and using a new technique in terms of dynamic thresholds, we have solved this problem in real time to meet requirements of most cases from our application. And we also improved the LCM algorithm by pruning more rows and columns of vertices in a bipartite graph and by mining more heuristic information about what vertices make others unclosed to achieve much better performance.
Developing an optimal match within online communities: an exploration of CMC support communities and traditional support

This study investigates the complementary nature of face-to-face and computer-mediated social support and the development of a context through which hyperpersonal communication can develop within online communities. Optimal matching theory is used as a framework for explaining how hyperpersonal communication develops within online cancer support communities. We compared online participants' perceptions of illness support from the list with the support they received from a nonmediated relationship. Respondents participated more within the online community only when they perceived that the depth and support that they received from the online community was high, and when the depth and support they received from the specific person in their life was low.
Price Deception, Market Power and Consumer Policy

This paper presents a model in which a firm attempts to gain market power by pricing above the competitive market price and simply trying to persuade ill-informed consumers not to search for other lower priced firms. Fictitious price comparisons, or false sale signs could be used in this way to deceptively and profitably deter consumer search. A simplified model shows how this mechanism could exist when combined with moderately enforced consumer regulatory policy.
Dynamic Clustering and Neuro-Fuzzy Identification for the Analysis of Fusion Plasma Signals

Measurements in long pulse devices like ITER require the use of intelligent techniques to detect interesting events and anomalous behaviors within a continuous data flow. This detection will trigger the execution of some experimental procedures such as: increasing sampling rates, starting data sampling in additional channels or notifying the event to other diagnostics. In a first approach, an interesting event can be any non-average behavior in the expected temporal evolution of the waveforms. Therefore, a model of the signals is needed. In this work, a model that represents each type of plasma signal is obtained by means of fuzzy inference systems (FIS) which are generated by applying adaptive neuro-fuzzy techniques. The purpose of this neuro-fuzzy modeling is to identify patterns of these groups of data to produce a concise representation of a signal. Previously the signals have been preprocessed and a new dynamic clustering strategy based on a partitioning method has been applied to obtain the clusters. Off-line analyses have been applied to bolometric signals of the fusion device TJ-II Stellator with encouraging results.
Haplotype Inference by Pure Parsimony via Genetic Algorithm

Haplotypes are specially important in the study of complex diseases since they contain more information about gene alleles than genotype data. However, getting haplotype data via experiments methods is techniquely difficult and expensive. Thus, haplotype inference through computational methods is practical and attractive. There are several models for inferrings haplotype from population genotypes, of which we are interested in the pure parsimony model. This problem has been proved to be an NP-hard problem, so the goal of this paper is to design a heuristic method to obtain good solutions within acceptable time. A heuristic method based on genetic algorithm is presented for haplotype inference under pure parsimony criterion. The algorithm was tested on a variety of biological data and simulated data. In comparison with the exact algorithm HAPAR (based on a branch and bound algorithm), experiment results show that the method can obtain optimal solutions in almost all cases and runs much faster than HAPAR when the number of genotypes or SNP sites is large. It is suited for haplotype inference in relative large haplotype blocks because the algorithm is fast and its running time is not exponentially increased with input size.
Lehmer's Question, Knots and Surface Dynamics

Abstract Lehmer's question is equivalent to one about generalized growth rates of Lefschetz numbers of iterated pseudo-Anosov surface homeomorphisms. One need consider only homeomorphisms that arise as monodromies of fibered knots in lens spaces L(n, 1), n > 0. Lehmer's question for Perron polynomials is equivalent to one about generalized growth rates of words under free group endomorphisms.
RNA interference-mediated knockdown of translationally controlled tumor protein induces apoptosis, and inhibits growth and invasion in glioma cells

Translationally controlled tumor protein (TCTP) is a highly conserved, growth-associated and small molecule protein, which is highly expressed in various types of tumor cell. TCTP can promote the growth and suppress apoptosis of tumor cels. However, few studies have reported the effects of TCTP in gliomas. In the present study, a glioma cell line was established, which was stably transfected with TCTP short hairpin ribonucleic acid (shRNA), to investigate the impact of downregulated expression of TCTP on the proliferation, apoptosis and invasion of glioma cells. Western blot and reverse transcription-quantitative polymerase chain reaction analyses demonstrated that TCTP shRNA effectively reduced the expression of TCTP in the U251 glioma cell line. MTT and colony formation assays revealed that downregulated expression of TCTP significantly inhibited glioma cell proliferation. Cell cycle analysis using flow cytometry revealed that the cells in the pRNA-H1.1-TCTP group were arrested in the G0/G1 phase of the cell cycle. Western blot analysis detected downregulated expression levels of cyclins, including Cyclin D1, Cyclin E and Cyclin B. Annexin V-fluorescein isothiocyanate/propidium iodide and Hoechst staining demonstrated that the apoptotic rate of the cells in the pRNA-H1.1-TCTP group was significantly higher than that of the cells in the pRNA-H1.1-control group, with upregulated expression levels of B-cell-associated X protein and cleaved-caspase-3 and downregulated expression of B-cell lmyphoma-2 in the apoptotic process. Wound healing and Transwell assays revealed that downregulated expression of TCTP significantly inhibited the migration and invasiveness of the glioma cells; and the expression levels and activities of matrix metalloproteinase (MMP)-2 and MMP-9 were also significantly affected. In conclusion, the present study demonstrated that downregulated expression of TCTP significantly inhibited proliferation and invasion, and induced apoptosis in the glioma cells. These results suggested that TCTP may be important in glioma development and metastasis. Therefore, TCTP is expected to become an effective target for glioma gene therapy.
N T ] 3 0 N ov 2 00 6 Further Remarks on Multiple p-adic qL-Function of Two Variables ∗

Abstract : The object of this paper is to give several properties and applications of the multiple p-adic q-L-function of two variables L (r) p,q (s, z, χ). The explicit formulas relating higher order qBernoulli polynomials, which involve sums of products of higher order q-zeta function and higher order Dirichlet q-L-function are given. The value of higher order Dirichlet p-adic q-L-function for positive integers is also calculated. Furthermore, the Kummer-type congruences for multiple generalized q-Bernoulli polynomials are derived by making use of the difference theorem of higher order Dirichlet p-adic q-L-function.
Advances in Magnetically Separable Photocatalysts: Smart, Recyclable Materials for Water Pollution Mitigation

Organic and inorganic compounds utilised at different stages of various industrial processes are lost into effluent water and eventually find their way into fresh water sources where they cause devastating effects on the ecosystem due to their stability, toxicity, and non-biodegradable nature. Semiconductor photocatalysis has been highlighted as a promising technology for the treatment of water laden with organic, inorganic, and microbial pollutants. However, these semiconductor photocatalysts are applied in powdered form, which makes separation and recycling after treatment extremely difficult. This not only leads to loss of the photocatalyst but also to secondary pollution by the photocatalyst particles. The introduction of various magnetic nanoparticles such as magnetite, maghemite, ferrites, etc. into the photocatalyst matrix has recently become an area of intense research because it allows for the easy separation of the photocatalyst from the treated water using an external magnetic field. Herein, we discuss the recent developments in terms of synthesis and photocatalytic properties of magnetically separable nanocomposites towards water treatment. The influence of the magnetic nanoparticles in the optical properties, charge transfer mechanism, and overall photocatalytic activity is deliberated based on selected results. We conclude the review by providing summary remarks on the successes of magnetic photocatalysts and present some of the future challenges regarding the exploitation of these materials in water treatment.
Advanced Exposure‐Time Calculations: Undersampling, Dithering, Cosmic Rays, Astrometry, and Ellipticities

The familiar tools of Fourier analysis and Fisher matrices are applied to derive the uncertainties on photometric, astrometric, and weak‐lensing measurements of stars and galaxies in real astronomical images. Many effects or functions that are ignored in basic exposure‐time calculators can be included in this framework: pixels of size comparable to the stellar image, undersampled and dithered exposures, cosmic‐ray hits, intrapixel sensitivity variations, and positional and ellipticity errors, as well as photometric errors. I present a formalism and a C++ implementation of these methods. As examples of their use, I answer some commonly arising questions about imaging strategies: What amount of dithering is ideal? What pixel size optimizes the productivity of a camera? Which is more efficient—space‐based or ground‐based observing?
Inter-cloud Networking Gateway Architecture

This paper presents a Cloud Networking Gateway (CNG) Manager, to enable networking of distributed cloud resources by authorized customers and to provide network control and configuration capabilities. The CNG Manager interconnects virtual machines, acquired from distributed heterogeneous resources and multiple providers, using generic gateways according to user connectivity requests. The CNG Manager is integrated with a "Cloud Broker" architecture for evaluation in the multiple providers context. The proposed framework extends and supports the current state of the art in cloud and software defined networks technologies with compatible connectivity control and management capabilities.
ProKinO: A Unified Resource for Mining the Cancer Kinome

Protein kinases represent a large and diverse family of evolutionarily related proteins that are abnormally regulated in human cancers. Although genome sequencing studies have revealed thousands of variants in protein kinases, translating “big” genomic data into biological knowledge remains a challenge. Here, we describe an ontological framework for integrating and conceptualizing diverse forms of information related to kinase activation and regulatory mechanisms in a machine readable, human understandable form. We demonstrate the utility of this framework in analyzing the cancer kinome, and in generating testable hypotheses for experimental studies. Through the iterative process of aggregate ontology querying, hypothesis generation and experimental validation, we identify a novel mutational hotspot in the αC‐β4 loop of the kinase domain and demonstrate the functional impact of the identified variants in epidermal growth factor receptor (EGFR) constitutive activity and inhibitor sensitivity. We provide a unified resource for the kinase and cancer community, ProKinO, housed at http://vulcan.cs. uga.edu/prokino.
Active Fault Tolerant Control of a quadrotor UAV based on gainscheduled PID control

In this paper, an Active Fault-Tolerant Control (AFTC) technique is developed and applied to an unmanned quadrotor helicopter UAV (Unmanned Aerial Vehicle, known also as Qball-X4) with 6 degrees of freedom based on a Gain-Scheduled Proportional-Integral Derivative (GS-PID) control technique. For implementing such an AFTC system, a Fault-Detection and Diagnosis (FDD) block is essential and implemented to detect and identify the actuator fault. The FDD block is implemented based on the OptiTrack visual feedback for providing information needed by GS-PID to switch from one set of pre-tuned controller gains for normal (pre-fault) condition to another set of controller gains tuned for faulty (post-fault) conditions in the presence of an actuator fault in the Qball-X4 UAV. Finally, experimental testing results are presented to demonstrate the effectiveness of the proposed active fault-tolerant control strategy based on the GS-PID control technique.
Comparative Analysis of the Volatile Components of Agrimonia eupatoria from Leaves and Roots by Gas Chromatography-Mass Spectrometry and Multivariate Curve Resolution

Gas chromatography-mass spectrometry and multivariate curve resolution were applied to the differential analysis of the volatile components in Agrimonia eupatoria specimens from different plant parts. After extracted with water distillation method, the volatile components in Agrimonia eupatoria from leaves and roots were detected by GC-MS. Then the qualitative and quantitative analysis of the volatile components in the main root of Agrimonia eupatoria was completed with the help of subwindow factor analysis resolving two-dimensional original data into mass spectra and chromatograms. 68 of 87 separated constituents in the total ion chromatogram of the volatile components were identified and quantified, accounting for about 87.03% of the total content. Then, the common peaks in leaf were extracted with orthogonal projection resolution method. Among the components determined, there were 52 components coexisting in the studied samples although the relative content of each component showed difference to some extent. The results showed a fair consistency in their GC-MS fingerprint. It was the first time to apply orthogonal projection method to compare different plant parts of Agrimonia eupatoria, and it reduced the burden of qualitative analysis as well as the subjectivity. The obtained results proved the combined approach powerful for the analysis of complex Agrimonia eupatoria samples. The developed method can be used to further study and quality control of Agrimonia eupatoria.
Photo-Quality Evaluation based on Computational Aesthetics: Review of Feature Extraction Techniques

Researchers try to model the aesthetic quality of photographs into low and high- level features, drawing inspiration from art theory, psychology and marketing. We attempt to describe every feature extraction measure employed in the above process. The contribution of this literature review is the taxonomy of each feature by its implementation complexity, considering real-world applications and integration in mobile apps and digital cameras. Also, we discuss the machine learning results along with some unexplored research areas as future work.
Establishment of an Inflamed Animal Model of Diabetic Nephropathy

Aims Inflammatory stress plays a crucial role in the progression of diabetic nephropathy (DN). This study aimed to establish a novel inflamed animal model of DN and to evaluate its significance in DN. Methods Nondiabetic db/m mice and diabetic db/db mice were randomly divided into four groups: db/m, db/m+casein, db/db, and db/db+casein for eight weeks. Casein was subcutaneously injected to induce chronic inflammation. Body weight and albumin to creatinine ratio (ACR) in the urine were measured every week. The plasma levels of serum amyloid protein A (SAA) and tumour necrotic factor-α (TNF-α) were determined with the enzyme-linked immunosorbent assay. The morphological changes to the renal pathology and ultra-microstructures were checked by pathological staining and electron microscopy. Immunofluorescent staining and Western blotting were used to determine the protein expression of podocyte-specific molecules and inflammatory cytokines in kidneys. Results ACR, plasma levels of SAA and TNF-α, protein expression of inflammatory cytokines, mesangial expansion, collagen accumulation, and foot process effacement in kidneys of casein-injected db/db mice were significantly increased compared with the db/db mice. Casein injection markedly decreased the protein expression of Wilms' tumor-1 and nephrin in kidneys of db/db mice, which are specific podocyte biomarkers, suggesting that chronic inflammation accelerates podocyte injuries in db/db mice. Interestingly, no obvious urinary protein, inflammatory cytokine expression, or histological changes in the kidneys of casein-injected db/m mice were found compared with the db/m mice. Conclusion An inflamed animal model of DN was successfully established and may provide a useful tool for investigating the pathogenesis of DN under inflammatory stress.
Temperature coefficients of material properties for electrodeposited MEMS

This paper presents the use of micromachined differential capacitive strain sensors to investigate mechanical properties of electroplated Ni deposited under two different conditions on Si and glass substrates. The thermal expansion coefficient (/spl alpha/), Young's modulus, and residual strain were studied as a function of temperature. The measured a was 8-16 ppm/K over 23-150/spl deg/C; the residual strain changed from neutral to -880 microstrain over 23-100/spl deg/C in one case and +68.5 microstrain to -420 microstrain over 23-130/spl deg/C in another case; and the Young's modulus ranged from 115-135 GPa at room temperature. The sensitivity of the device to structural non-idealities was evaluated by numerical modeling.
Millimeter-Wave Transition From Waveguide to Two Microstrip Lines Using Rectangular Patch Element

A millimeter-wave transition from a waveguide to two microstrip lines and the design methodology are proposed. A rectangular patch element in a short-terminated waveguide is analyzed by the cavity model of a patch antenna and the dyadic Green's function of the waveguide. The analysis points out that the rectangular patch element has an optimum width for wideband, which only has the function of the broad wall width of the waveguide. The transition also works as a divider. A numerical investigation of a transition having two microstrip lines validates the analytical model in terms of wideband, and indicates that the distance between the two microstrip lines has an optimum length for suppressing higher order modes. A prototype transition exhibits an insertion loss of 0.5 dB from 76 to 77 GHz, and a bandwidth of 6.9% (5.29 GHz) for the reflection coefficient below -15 dB for the waveguide port
Pinpointed control of muscles by using power-assisting device

The aim of this paper is to arbitrarily modify the load force of any selected muscle by using an exoskeleton, thus enabling "pinpointed" motion support, rehabilitation, and training. An advanced dynamic model, called a musculoskeletal-exoskeletal integrated human model, is developed. The driving-forces of the pneumatic actuators are designated by a muscle force control algorithm using the integrated model. A prototype power-assisting system is developed using pneumatic rubber actuators. The feasibility of the muscle force control is analyzed from a view point of nonlinear programming. The validity of the method is confirmed by measuring surface electromyographic signals of related muscles.