Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic changes in localization of chromobox (CBX) family members during the maternal to embryonic transition

The Chromobox domain (Cbx) gene family, consisting of Polycomb and Heterochromatin Protein 1 genes, is involved in transcriptional repression, cell cycle regulation and chromatin remodeling. We report the first study of gene expression and protein localization of the Cbx genes in in vitro produced bovine embryos. All but one gene (Cbx6) were expressed. This was confirmed by immunolocalization for HP1α, β, γ, and Pc2, 3. HP1β was found in the nuclei of embryos from the two‐cell stage onwards, whereas HP1γ showed diffuse cytoplasmic/nuclear localization at the two‐ and eight‐cell stages, and predominantly nuclear localization at the four‐cell stage and the 16‐cell stage onwards. Leptomycin B (LMB), a specific inhibitor of the nuclear export protein CRM‐1 (chromosomal regional maintenance‐1), was found to increase nuclear localization of HP1γ at the eight‐cell stage, and to prevent progression past this stage of embryogenesis. This indicates that HP1γ possesses a CRM‐1‐dependent nuclear export pathway which may represent part of the basis of HP1γ's ability to shuttle between the nucleus and the cytoplasm in dynamic fashion. HP1α was expressed in embryonic nuclei at all stages, but was found to relocalise from euchromatin to heterochromatin during the maternal to embryonic transition (MET). In contrast, Pc2 and Pc3 were evenly distributed between cytoplasm and nucleus until the eight‐ and sixteen‐cell stages or the morula stage, respectively, before relocating preferentially to the cytoplasm. Collectively, the results suggest that dynamic changes of the nuclear‐cytoplasmic and subnuclear distribution of members of the Cbx family may be central to the MET. Mol. Reprod. Dev. 75: 477–488, 2008. © 2007 Wiley‐Liss, Inc.
Interaction potentials for protein folding

We outline a general strategy for determining the effective coarse‐grained interactions between the amino acids of a protein from the experimentally derived native‐state structures. The method is, in principle, free from any adjustable or empirically determined parameters, and it is tested on simple models and compared with other existing approaches. Proteins 30:244–248, 1998. © 1998 Wiley‐Liss, Inc.
Toward estimating user-social event distance: mobility, content, and social relationship

On-site user w.r. t social events are valuable, from whom, government/police could obtain meaningful information which contributes to understand the progress of the event or investigate suspects when the event is associated with crime or terrorist. However, due to the high uncertainty of human mobility patterns, it is hard to identify on-site users while social event happens. In this paper, we propose a F>used fEature Gaussian prOcess Rgression (FEGOR) model, which employs three features from online social networks: mobility influence, content similarity, and social relationship to estimate the distance between user and social event, based on which, we could accomplish the problem of identifying the on-site users. Experiment results on a real-world Twitter dataset demonstrate our method outperforms state-of-the-art methods.
Compositionality in deterministic real-time embedded systems

Many computing applications, especially those in safety critical embedded systems, require highly predictable timing properties. However, time is often not present in the prevailing computing and networking abstractions. In fact, most advances in computer architecture, software, and networking favor average-case performance over timing predictability. This thesis studies several methods for the design of concurrent and/or distributed embedded systems with precise timing guarantees. The focus is on flexible and compositional methods for programming and verification of the timing properties. The presented methods together with related formalisms cover two levels of design: (1) Programming language/model level. We propose the distributed variant of Giotto, a coordination programming language with an explicit temporal semantics—the logical execution time (LET) semantics. The LET of a task is an interval of time that specifies the time instants at which task inputs and outputs become available (task release and termination instants). The LET of a task is always non-zero. This allows us to communicate values across the network without changing the timing information of the task, and without introducing nondeterminism. We show how this methodology supports distributed code generation for distributed real-time systems. The method gives up some performance in favor of composability and predictability. We characterize the tradeoff by comparing the LET semantics with the semantics used in Simulink. (2) Abstract task graph level. We study interface-based design and verification of applications represented with task graphs. We consider task sequence graphs with general event models, and cyclic graphs with periodic event models with jitter and phase. Here an interface of a component exposes time and resource constraints of the component. Together with interfaces we formally define interface composition operations and the refinement relation. For efficient and flexible composability checking two properties are important: incremental design and independent refinement. According to the incremental design property the composition of interfaces can be performed in any order, even if interfaces for some components are not known. The refinement relation is defined such that in a design we can always substitute a refined interface for an abstract one. We show that the framework supports independent refinement, i.e., the refinement relation is preserved under composition operations.
Automatic Gene Prioritization in Support of the Inflammatory Contribution to Alzheimer’s Disease

This research seeks to extend the process of novel therapeutic gene target discovery for the treatment of Alzheimer’s disease (AD). Gene-gene and gene-pathway annotation tools as well as human analysis are used to explore likely connections between potential gene targets and biochemical mechanisms of AD and associated genes. Rule-based annotation systems, such as GeneRanker, can be applied to the continuously growing volume of literature to extract relevant gene lists. The subsequent challenge is to abstract biological significance from associated genes to aid in discovery of novel therapeutic gene targets. Automatic annotation of genes deemed significant by data-driven assays and knowledge-driven analysis is limited. Therefore, human analysis is still crucial to exploring novel gene targets and new disease models. This research illustrates a method of analysis of an extracted gene list which lead to the discovery of KNG1 as a possible therapeutic target, suggests a connection between inflammation and AD pathogenesis.
Identifying the Intellectual Structure of Organizational Psychology Studies: Influential Contribution

With the large number of studies being conducted in the area of organizational psychology, it has become increasing important to be able to effectively identify the most influential and representative collection of research articles. Previous research on citation relationships in organizational psychology literature has focused on investigating the impact of certain authors and/or publications as opposed to the intellectual history of organizational psychology. This manuscript employs bibliometric tools and social network analysis methodology to analyze citation relationships, showing trends and patterns in organizational psychology research and highlighting the most influential authors. Author co-citation analysis is conducted of 43,425 references from 803 articles found in the SSCI and SCI databases during the ten years from 1998 to 2007. In order to examine the possible evolution of research interests in the past 10 years, this study is divided into two separate five-year period are examined. The objective of this study is to provide valuable direction for future researchers to identify key themes and their relationships, thus demonstrating the effectiveness of utilizing bibliometric epistemology while also proposing an objective means of establishing the relative importance of different knowledge nodes in the recent development of the organizational psychology field.
Biometric Touch Sensing: Seamlessly Augmenting Each Touch with Continuous Authentication

Current touch devices separate user authentication from regular interaction, for example by displaying modal login screens before device usage or prompting for in-app passwords, which interrupts the interaction flow. We propose biometric touch sensing, a new approach to representing touch events that enables commodity devices to seamlessly integrate authentication into interaction: From each touch, the touchscreen senses the 2D input coordinates and at the same time obtains biometric features that identify the user. Our approach makes authentication during interaction transparent to the user, yet ensures secure interaction at all times. To implement this on today's devices, our watch prototype Bioamp senses the impedance profile of the user's wrist and modulates a signal onto the user's body through skin using a periodic electric signal. This signal affects the capacitive values touchscreens measure upon touch, allowing devices to identify users on each touch. We integrate our approach into Windows 8 and discuss and demonstrate it in the context of various use cases, including access permissions and protecting private screen contents on personal and shared devices.
Application of Triple Collocation in Ground-Based Validation of Soil Moisture Active/Passive (SMAP) Level 2 Data Products

The validation of the soil moisture retrievals from the recently launched National Aeronautics and Space Administration (NASA) Soil Moisture Active/Passive (SMAP) satellite is important prior to their full public release. Uncertainty in attempts to characterize footprint-scale surface-layer soil moisture using point-scale ground observations has generally limited past validation of remotely sensed soil moisture products to densely instrumented sites covering an area approximating the satellite ground footprint. However, by leveraging independent soil moisture information obtained from land surface modeling and/or alternative remote sensing products, triple collocation (TC) techniques offer a strategy for characterizing upscaling errors in sparser ground measurements and removing the impact of such error on the evaluation of remotely sensed soil moisture products. Here, we propose and validate a TC-based strategy designed to utilize existing sparse soil moisture networks (typically with a single sampling point per satellite footprint) to obtain an unbiased correlation validation metric for satellite surface soil moisture retrieval products. Application of this TC strategy at five SMAP core validation sites suggests that unbiased estimates of correlation between the satellite product and the true footprint average can be obtained—even in cases where ground observations provide only one single reference point within the footprint. An example of preliminary validation results from the application of this TC strategy to the SMAP Level 2 Soil Moisture Passive (beta release version) product is presented.
Lower-Limb Wearable Exoskeleton

There are numerous causes that can affect the functioning of the human locomotor system, leading to the appearance of joint disorders in the lower limb and generating atypical gait patterns. The importance of research and development in assistance technologies to compensate pathological gait have been recognised since the beginning of the twentieth century and numerous challenges still lie ahead to make their clinical application a reality. In this section, GAIT, the lower-limb Wearable exoskeleton is presented, conceived as a compensation and evaluation system of pathological gait, for application in real conditions as a combined assistance and assessment methodology of the problems affecting mobility in individuals with neuromotor disorders. The main technological challenges are discussed with respect to sensing, actuation and control subsystems. Special emphasis is placed on advances in robotic lower-limb orthoses, and biomechanical requirements, structural design considerations and the approaches existing to develop robust real-time controllers for portable solutions with a common aim, human motor control, are analysed.
Vision-Based Web Page Block Segmentation and Informative Block Detection

A web page usually contains various content such as main content block, navigation bars or columns, contacts information at the bottom, advertisements, or just some decoration components. Apart from the main content block, the other parts are all not related to the topic of the web page, we call them noise blocks. Content in noise blocks will seriously harm information extraction, web mining, we searching, etc. Identifying the main content block is a key issue. In this paper, we propose a new low-cost vision based web page segmentation and informative block detection algorithm. Then we apply this algorithm to develop a bids update detection system for a local bids collecting company. Our algorithm mainly utilizes the position information of HTML element, which lowers the cost of applying multiple rules in VIPS. Our proposed row-column splitting indicator helps us provide an easy-to-use partition granularity value which solves the difficulty of choosing an appropriate Degree of Coherence (DoC) value in VIPS algorithm. This row-column splitting indicator also avoids the traditional high cost clustering process in detecting informative block. Through extensive experiments, we conclude that our proposed algorithm has a comparable performance compared to the VIPS and other informative block detection algorithms, but with ease of use granularity value and lower computation cost.
Proteomic Characterization of Tissue Expansion of Rice Scutellum Stimulated by Abscisic Acid

We found that appropriate treatment with a highly potent and long-lasting abscisic acid analog enhanced the tissue expansion of scutellum during early seedling development of rice, accompanied by increases of protein and starch accumulation in the tissue. A comparative display of the protein expression patterns in the abscisic acid analog-treated and non-treated tissues on two dimensional gel electrophoretogram indicated that approximately 30% of the scutellar proteins were induced by abscisic acid. The abscisic acid-induced proteins included sucrose metabolizing, glycolytic, and ATP-producing enzymes. Most of these enzyme proteins also increased during the seedling growth. In addition, the expression of some isoforms of UDP-glucose pyrophosphorylase, 3-phosphoglycerate kinase, and mitochondrial ATP synthase beta chain was stimulated in the scutellum, with suppressed expression of α-amylase. We concluded that abscisic acid directly and indirectly stimulates the expression of numerous proteins, including carbohydrate metabolic enzymes, in scutellar tissues.
RSBN : Regression with Stochastically Bounded Noises

We consider M-estimates in a regression model where the noises are of unknown but stochastically bounded distribution. An asymptotic minimax M-estimate is derived. Simulations demonstrate the robustness of this approach, as well as advantages over commonly used estimates such as the ordinary least square estimate and the Huber’s estimate. The new method is named regression with stochastically bounded noises (RSBN). We provide an iterative numerical solution, which is derived from the proximal point method. The iterative method is elegant, however may not have fast rate of convergence. RSBN can also be solved by applying existing state-of-the-art nonlinear optimization software. We present SNOPT as one example. Insights from RSBN are discussed.
Large marginwavelet-based dictionary for signal classification

This paper addresses the problem of automatic wavelet feature extraction for signal classication. We propose to jointly learn wavelet-based features (including scale and translation of the wavelet as well as its shape) and a decision function by casting the problem as a Multi-Kernel Learning problem. A novel active constraints algorithm is then proposed. Our method has been tested on a toy dataset and compared to classical methods with competitive results.
Proteomic Definitions of Mesenchymal Stem Cells

Mesenchymal stem cells (MSCs) are pluripotent cells isolated from the bone marrow and various other organs. They are able to proliferate and self-renew, as well as to give rise to progeny of at least the osteogenic, chondrogenic, and adipogenic lineages. Despite this functional definition, MSCs can also be defined by their expression of a distinct set of cell surface markers. In the current paper, studies investigating the proteome of human MSCs are reviewed with the aim to identify common protein markers of MSCs. The proteomic analysis of MSCs revealed a distinct set of proteins representing the basic molecular inventory, including proteins for (i) cell surface markers, (ii) the responsiveness to growth factors, (iii) the reuse of developmental signaling cascades in adult stem cells, (iv) the interaction with molecules of the extracellular matrix, (v) the expression of genes regulating transcription and translation, (vi) the control of the cell number, and (vii) the protection against cellular stress.
High Power Diode-Side-Pumped Q-Switched Nd:YAG Solid-State Laser with a Thermoelectric Cooler

A diode-side-pumped, high-energy, high-beam-quality, pulsed solid-state Nd3+:Y3Al5O12 (Nd:YAG) laser with a thermoelectric cooler (TEC) is investigated in this study. The pump laser was a pulsed laser diode array with maximum peak power of 15 kW. A 350 mJ laser pulse was obtained with a wavelength of 1064 nm, a pulse duration of 10 ns, a total electrical-to-optical efficiency of 7.5%, a relative stability of output energy of 5%, and a beam quality of M2 < 4.
P Pilus Assembly Motif Necessary for Activation of the CpxRA Pathway by PapE in Escherichia coli

ABSTRACT P pilus biogenesis occurs via the highly conserved chaperone-usher pathway, and assembly is monitored by the CpxRA two-component signal transduction pathway. Structural pilus subunits consist of an N-terminal extension followed by an incomplete immunoglobulin-like fold that is missing a C-terminal seventh beta strand. In the pilus fiber, the immunoglobulin-like fold of each pilin is completed by the N-terminal extension of its neighbor. Subunits that do not get incorporated into the pilus fiber are driven “OFF-pathway. ” In this study, we found that PapE was the only OFF-pathway nonadhesin P pilus subunit capable of activating Cpx. Manipulation of the PapE structure by removing, relocating within the protein, or swapping its N-terminal extension with that of other subunits altered the protein's self-associative and Cpx-activating properties. The self-association properties of the new subunits were dictated by the specific N-terminal extension provided and were consistent with the order of the subunits in the pilus fiber. However, these aggregation properties did not directly correlate with Cpx induction. Cpx activation instead correlated with the presence or absence of an N-terminal extension in the PapE pilin structure. Removal of the N-terminal extension of PapE was sufficient to abolish Cpx activation. Replacement of an N-terminal extension at either the amino or carboxyl terminus restored Cpx induction. Thus, the data presented in this study argue that PapE has features inherent in its structure or during its folding that act as specific inducers of Cpx signal transduction.
Performance enhancement of local vector pattern with generalized distance local binary pattern for face recognition

In this paper a generalized distance based local binary pattern (GDLBP) is proposed which achieves better recognition accuracy over LBP and significantly increases the recognition accuracy when combined with LVP. The proposed GDLBP is combined with local vector pattern (LVP) to achieve better recognition rates. Proposed GDLBP explores the spatial relationships of the neighboring pixels at different radii and inter radii distances. Proposed descriptors GDLBP and GDLBP-LVP have been analyzed and compared with the existing LBP and LVP over most challenging benchmark facial image databases LFW, and color FERET. Analysis of the descriptors shows that the proposed GDLBP and GDLBP-LVP achieves noticeably better results as compared to LBP and LVP.
Research of Face Recognition Based on Locally Linear Embedding

Image data taken with various capturing devices are usually multidimensional and therefore they are not very suitable for accurate classification normally expecting to operate only on a small set of relevant features. Locally Linear Embedding is an effective nonlinear dimensionality reduction method for exploring the intrinsic characteristics of high dimensional data. In this paper, novel Local linear embedding for face classification is proposed. We modify the LLE algorithm by preserving more geometrical knowledge of the high-dimensional data, then combining with simple classifiers such as the nearest mean classifier. Experimental simulations are shown to yield remarkably good classification results in high dimension face image sequence.
STRATEGI MENINGKATKAN PERSAINGAN BISNIS PERUSAHAAN DENGAN PENERAPAN E-COMMERCE

Saat ini kemajuan ilmu pengetahuan dan teknologi menjadi sebuah perubahan tradisi dari kultur masyarakat sehari-hari, dengan terciptanya sebuah keterbukaan dan transparansi di berbagai bidang, yang terutama di bidang Teknologi Informasi (IT). Informasi yang cepat dan akurat merupakan bentuk informasi yang sangat dibutuhkan oleh masyarakat, termasuk didalamnya dunia bisnis. Berkembangnya penggunaan Internet dan teknologi World Wide Web, menyebabkan munculnya penggunaan internet mengalami perkembangan yang luar biasa di bidang bisnis terutama pada perusahaan skala besar maupun kecil. Sejak berkembangnya teknologi internet tersebut pada tahun 1990-an penggunaannya meluas karena dipandang memberikan manfaat yang sangat besar bagi kelancaran proses-proses bisnis. Penggunaan teknologi internet diharapkan dapat memberikan manfaat yang besar terhadap dunia bisnis yang kompetitif tersebut. Perusahaan yang mampu bersaing dalam kompetisi tersebut adalah perusahaan yang mampu mengimplementasikan teknologi ke dalam perusahaannya. Salah satu jenis implementasi teknologi dalam hal meningkatkan persaingan bisnis dan penjualan produk-produk adalah dengan menggunakan electronic commerce (e-Commerce) untuk memasarkan berbagai macam produk atau jasa, baik dalam bentuk fisik maupun digital. Dalam penggunaan teknologi tersebut, berbagai pihak yang terkait dengan perusahaan seperti investor, konsumen, pemerintah akan ikut berperan. Dengan semakin matangnya teknologi internet dan web, teknologi-teknologi ini meningkatkan kemampuan perusahaan yang canggih dalam hal komunikasi bisnis dan dalam hal kemampuannya berbagi informasi, selain itu berbagi sumber daya lain yang bernilai.