Miracle-dz/UniFAR-FTUs huggingface dataset:
Interaction of the pneumococcal amidase with lipoteichoic acid and choline.

The choline-containing lipoteichoic acid (LTA, Forssman Antigen) of Streptococcus pneumoniae suppresses the activity of the pneumococcal autolysin, an N-acetyl-muramoyl-L-alanine-amidase (amidase) in aqueous solution [Höltje and Tomasz (1975) Proc. Natl Acad. Sci. USA 72, 1690-1694]. The interaction between LTA and enzyme was used to establish a purification by affinity chromatography on LTA-Sepharose. The amidase could be eluted from the column with choline only. This implies that binding of the enzyme to LTA is mediated via the choline residues of the LTA. Upon binding to the LTA-Sepharose, the amidase converted from the applied E-form (an inactive form of the amidase) to the active C-form, a process which up to now was known to be mediated only by the pneumococcal choline-containing wall teichoic acid. Similar interactions between LTA and amidase seemed to occur in membrane fractions derived from choline-grown cells: the membrane-associated enzyme was present in the C-form and could be detached completely with choline, suggesting that the amidase is bound to the membrane attached LTA rather than being a membrane protein itself. This was supported by the absence of amidase activity in membrane fractions derived from ethanolamine-grown pneumococci, in which choline containing LTA is absent. The LTA-Sepharose-associated amidase was not inhibited, but retained its activity. The enzyme was also not inhibited by lipase-digested LTA. Both are conditions where the LTA is not present in micelles, unlike in aqueous solution. Therefore, mere binding to the LTA is probably not responsible for the inhibitory effect, but inhibition is a manifestation of an inaccessibility of the substrate for the amidase when bound to micellar LTA. When the interactions between choline and amidase were investigated, it was found that high choline concentrations (2%) inhibited the enzyme completely. Even in vivo, 2% choline in the culture medium led to phenotypically amidase-deficient pneumococci. Furthermore, in vitro, low choline concentrations (0.1%) suppressed the wall-mediated conversion. On the other hand, with high choline concentrations (2%) conversion took place in the absence of cell walls. Depending on how the amidase has been converted, the apparent Mr of the resulting C-amidase was different: the cell-wall-converted enzyme was of high Mr, whereas the choline-converted and the LTA-Sepharose-eluted enzyme showed an apparent low molecular mass known for the E-form, when analyzed on sucrose gradients. (ABSTRACT TRUNCATED AT 400 WORDS)
The KEEP ON GOING Protein of Arabidopsis Regulates Intracellular Protein Trafficking and Is Degraded during Fungal Infection[C][W][OA]

The targeting of proteins to specific locations within a cell is a dynamic process that requires sophisticated sorting mechanisms. This work shows that Arabidopsis KEEP ON GOING plays a central role in regulating movement of proteins from the plasma membrane to the central vacuole and in the secretion of defense proteins to the extracellular space. In plants, the trans-Golgi network and early endosomes (TGN/EE) function as the central junction for major endomembrane trafficking events, including endocytosis and secretion. Here, we demonstrate that the KEEP ON GOING (KEG) protein of Arabidopsis thaliana localizes to the TGN/EE and plays an essential role in multiple intracellular trafficking processes. Loss-of-function keg mutants exhibited severe defects in cell expansion, which correlated with defects in vacuole morphology. Confocal microscopy revealed that KEG is required for targeting of plasma membrane proteins to the vacuole. This targeting process appeared to be blocked at the step of multivesicular body (MVB) fusion with the vacuolar membrane as the MVB-associated small GTPase ARA6 was also blocked in vacuolar delivery. In addition, loss of KEG function blocked secretion of apoplastic defense proteins, indicating that KEG plays a role in plant immunity. Significantly, KEG was degraded specifically in cells infected by the fungus Golovinomyces cichoracearum, suggesting that this pathogen may target KEG to manipulate the host secretory system as a virulence strategy. Taking these results together, we conclude that KEG is a key component of TGN/EE that regulates multiple post-Golgi trafficking events in plants, including vacuole biogenesis, targeting of membrane-associated proteins to the vacuole, and secretion of apoplastic proteins.
STORAGE AND RETRIEVAL PROCESSES IN LONG-TERM MEMORY 1

A theory of human memory is described in which a distinction is made between three memory stores: the sensory register, the short-term store, and the long-term store. Primary emphasis is given to the processes by which information is stored in and retrieved from the long-term store, a store which is considered to be a permanent repository for information. Forgetting and related phenomena are attributed to a failure of the retrieval process, in which the search through some memory area becomes less efficient as new information is placed in it. Storage and retrieval in the long-term store are conceived of as parallel processes, one mirroring the other, and each is divided into three stages for conceptual clarity. The memory trace is viewed as an ensemble of information stored in some memory location, the location of storage determined largely by the components of the ensemble itself. The ability of the system to cope with diverse phenomena is demonstrated by a consideration of a number of selected experimental paradigms.
Scalable and bandwidth-efficient multicast for software-defined networks

Software-Defined Networking (SDN) enables flexible network resource allocations for traffic engineering, but at the same time the scalability problem becomes more serious since traffic is more difficult to be aggregated. Those crucial issues in SDN have been studied for unicast but have not been explored for multicast traffic, and addressing those issues for multicast is more challenging since the identities and the number of members in a multicast group can be arbitrary. In this paper, therefore, we propose a new multicast tree for SDN, named Branch-aware Steiner Tree (BST). The BST problem is difficult since it needs to jointly minimize the numbers of the edges and the branch nodes in a tree, and we prove that it is NP-Hard and inapproximable within k, which denotes the number of group members. We further design an approximation algorithm, called Branch Aware Edge Reduction Algorithm (BAERA), to solve the problem. Simulation results demonstrate that the trees obtained by BAERA are more bandwidth-efficient and scalable than the shortest-path trees and traditional Steiner trees. Most importantly, BAERA is computation-efficient to be deployed in SDN since it can generate a tree on massive networks in small time.
The dark side of the alpha rhythm: fMRI evidence for induced alpha modulation during complete darkness

The unique role of the EEG alpha rhythm in different states of cortical activity is still debated. The main theories regarding alpha function posit either sensory processing or attention allocation as the main processes governing its modulation. Closing and opening eyes, a well‐known manipulation of the alpha rhythm, could be regarded as attention allocation from inward to outward focus though during light is also accompanied by visual change. To disentangle the effects of attention allocation and sensory visual input on alpha modulation, 14 healthy subjects were asked to open and close their eyes during conditions of light and of complete darkness while simultaneous recordings of EEG and fMRI were acquired. Thus, during complete darkness the eyes‐open condition is not related to visual input but only to attention allocation, allowing direct examination of its role in alpha modulation. A data‐driven ridge regression classifier was applied to the EEG data in order to ascertain the contribution of the alpha rhythm to eyes‐open/eyes‐closed inference in both lighting conditions. Classifier results revealed significant alpha contribution during both light and dark conditions, suggesting that alpha rhythm modulation is closely linked to the change in the direction of attention regardless of the presence of visual sensory input. Furthermore, fMRI activation maps derived from an alpha modulation time‐course during the complete darkness condition exhibited a right frontal cortical network associated with attention allocation. These findings support the importance of top‐down processes such as attention allocation to alpha rhythm modulation, possibly as a prerequisite to its known bottom‐up processing of sensory input.
Semantic middleware for e‐Science knowledge spaces

The Tupelo semantic content management middleware implements Knowledge Spaces that enable scientists to integrate information into a comprehensive research record as they work with existing tools and domain‐specific applications. Knowledge Spaces combine approaches that have demonstrated success in automating parts of this integration activity, including content management systems for domain‐neutral management of data, workflow technologies for management of computation and analysis, and semantic web technologies for extensible, portable, citable management of descriptive information and other metadata. Tupelo's ‘Context’ facility and its associated semantic operations both allow existing data representations and tools to be plugged in, and also provide a semantic ‘glue’ of important associative relationships that span the research record, such as provenance, social networks, and annotation. Tupelo has enabled the recent work creating e‐Science cyberenvironments to serve distributed, active scientific communities, allowing researchers to develop, coordinate and share datasets, documents, and computational models, while preserving process documentation and other contextual information needed to produce an integrated research record suitable for distribution and archiving. Copyright © 2011 John Wiley & Sons, Ltd.
Ambient Intelligence in Health Care

Ambient Intelligence (AmI) is a new paradigm in information technology, in which people are empowered through a digital environment that is aware of their presence and context, and is sensitive, adaptive, and responsive to their needs, habits, gestures and emotions. The most ambitious expression of AmI is Intelligent Mixed Reality (IMR), an evolution of traditional virtual reality environments. Using IMR, it is possible to integrate computer interfaces into the real environment, so that the user can interact with other individuals and with the environment itself in the most natural and intuitive way. How does the emergence of the AmI paradigm influence the future of health care? Using a scenario-based approach, this paper outlines the possible role of AmI in health care by focusing on both its technological and relational nature. In this sense, clinicians and health care providers that want to exploit AmI potential need a significant attention to technology, ergonomics, project management, human factors and organizational changes in the structure of the relevant health service.
Predictive Visual Tracking of Lines by Industrial Robots

Many tasks for industrial robots can be described by high precision line following at high speed. This can be executed accurately if the lines are sensed by a camera since then not only the desired pose at the current time step is sensable, but also a segment of the desired path can be predicted. We propose polynomials to represent the progression of the elements of the desired pose. This allows us to realize a dynamical sensor control architecture that considers the two main problems: low sampling rate and delays in image processing, and deviations from commanded paths due to the robot dynamics. In contrast to previous publications we now present the complete formulae to control translation and orientation of the robot by tracking (curved) lines that are visible for a single eye-in-hand camera. Experiments using off-the-shelf hardware show that the robot can be precisely controlled at high speed.
Exclusion of Wilms tumour (WT1b) and ovarian cytochrome P450 aromatase (CYP19A1) as candidates for sex determination genes in Nile tilapia (Oreochromis niloticus).

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Folding Kinetics of Riboswitch Transcriptional Terminators and Sequesterers

To function as gene regulatory elements in response to environmental signals, riboswitchesmustadopt specific secondary structures on appropriatetimescales. We employ kinetic Monte Carlo simulation to model the time-dependent folding during transcription of thiamine pyrophosphate (TPP) riboswitch expression platforms. According to our simulations, riboswitch transcriptional terminators, which must adopt a specific hairpin configuration by the time they have been transcribed, fold with higher efficiency than Shine-Dalgarno sequesterers, whose proper structure is required only at the time of ribosomal binding. Our findings suggest both that riboswitch transcriptional terminator sequences have been naturally selected for high folding efficiency, and that sequesterers can maintain their function even in the presence of significant misfolding.
Assessment of the correlation between commonly used radiographic parameters in normal, subluxated and dislocated hips

The correlations between the commonly used radiographic parameters, center–edge angle (CEA), acetabular–head index (AHI), acetabular index angle (AIA), acetabular angle (AA) and ACM angle, in normal, subluxated and dislocated hips were investigated in the radiographs of 364 normal, 23 subluxated and 19 dislocated hips of patients between 5 and 18 years of age. A significant correlation was observed between all the parameters in normal hips. A significant correlation between AIA and the other four parameters, and between CEA–AHI and AA–ACM, was noted in subluxated hips. AIA–AA and AIA–ACM had significant correlations in dislocated hips. It was concluded that measurement of more than one radiographic parameter might be better to exactly evaluate the radiographic hip anatomy in developmental dysplasia of the hip.
Router for Integrated Information Access System

In this paper, we describe the idea and preliminary survey of an Integrated Information Access System (IIAS) that accepts diverse kinds of questions and provides the requested information in the most suitable format for the information need. We designed a set of 18 Information Access Types — categories defined by the form of the output and the semantics of some of the output types. Also, we will report on the implementation of one important component of the system, the Information Access Router (IAR). The IAR is to identify the types of information need which the user requested based on the question in natural language. We evaluated the IAR on about 1500 questions, and the results show that the IAR achieves high accuracy using simple pattern matching methods.
Irradiation-induced degradation of amorphous silicon solar cells in space

Solar cells are the prime power supply for satellites in space. Space is, however, a hostile environment for electronic devices, such as solar cells: in space the devices are subjected to large temperature cycles, atomic oxygen, space dust, meteorites, and high-energy charged-particle irradiation. In this thesis we present the development of a model with which the EOL-performance of hydrogenated amorphous silicon, solar cells can be predicted for a high-radiation space mission. For this development we have performed light-soaking, electron-beam, and proton-beam irradiation experiments on Hydrogenated amorphous silicon, layers and solar cells in order to study the degradation cell performance under these conditions. Furthermore, we present a procedure for the simulation of solar-cell performance degradation and this method has been applied to our measurement results to study some aspects of the degradation in more detail.
Predicting link quality of wireless channel of vehicular users using street and coverage maps

Limited radio resources and increasing user demands make wireless resource allocation a challenging task. As a user moves, his channel quality varies significantly depending on his location. In this paper we show that wireless link quality can be predicted on a large time scale in terms of Path Loss values by using street and coverage maps. The predicted wireless link quality information can be used by the network operators for optimized resource allocation. The feasibility of the proposed approach is demonstrated by extensive simulations advocating this data driven approach for channel prediction.
Empirical evaluation of a practical indoor mobile robot navigation method using hybrid maps

This video presents a practical navigation scheme for indoor mobile robots using hybrid maps. The method makes use of metric maps for local navigation and a topological map for global path planning. Metric maps are generated as occupancy grids by a laser range finder to represent local information about partial areas. The global topological map is used to indicate the connectivity of the ‘places-of-interests’ in the environment and the interconnectivity of the local maps. Visual tags on the ceiling to be detected by the robot provide valuable information and contribute to reliable localization. The navigation scheme based on the hybrid metric-topological maps saves memory space and is also scalable and adaptable since new local maps can be easily added to the global topology, and the method can be deployed with minimum amount of modification if new areas are to be explored. The video demonstrated that the method is implemented successfully on physical robot in a hospital environment, which provides a practical solution for indoor navigation.
When Sensor Meets Tensor: Filling Missing Sensor Values Through a Tensor Approach

In the era of the Internet of Things, enormous number of sensors have been deployed in different locations, generating massive time-series sensory data with geo-tags. However, such sensory readings are easily missing due to various reasons such as the hardware malfunction, connection errors, and data corruption. This paper focuses on this challenge--how to accurately yet efficiently recover the missing values for corrupted time-series sensor data with geo-stamps. In this paper, we formulate the time-series sensor data as a 3-order tensor that naturally preserves sensors' temporal and spatial dependencies. Then we exploit its low-rank and sparse-noise structures by drawing upon recent advances in Robust Principal Component Analysis (RPCA) and tensor completion theory. The main novelty of this paper lies in that, we design a highly efficient optimization method that combines the alternating direction method of multipliers and accelerated proximal gradient to recover the data tensor. Besides testing our method using the synthetic data, we also design a real-world testbed by passive RFID (RadioFrequency IDentification) sensors. The results demonstrate the effectiveness and accuracy of our approach.
Reinforcement Learning for Call Admission Control and Routing in Integrated Service Networks

In integrated service communication networks, an important problem is to exercise call admission control and routing so as to optimally use the network resources. This problem is naturally formulated as a dynamic programming problem, which, however, is too complex to be solved exactly. We use methods of reinforcement learning (RL), together with a decomposition approach, to find call admission control and routing policies. The performance of our policy for a network with approximately 1045 different feature configurations is compared with a commonly used heuristic policy.
Effect of composition of El-lajjun oil shale on its calorific value

A geochemical analysis of El-lajjun oil shale in Jordan was carried out. It was found that El-lajjun oil shale consists of the following groups: organic matter, biogenic calcite and apatite, detrital clay minerals, and quartz. The calorific values of 100 samples of shale were determined. The effect of bore depth, calcium carbonate, organic carbon, and sulfur content on the calorific values were studied. Results were well correlated by the following equation Calorific value = 352,44 ( CaCO 3 ) - 0.066 ( S ) 0.257 ( C org ) 1.141 with correlation coefficient of 0.983 and with an average standard error of 2.63%.
The Oral Tolerance as a Complex Network Phenomenon

The phenomenon of oral tolerance refers to a local and systemic state of tolerance induced in the gut after its exposure to innocuous antigens. Recent findings have shown the interrelationship between cellular and molecular components of oral tolerance, but its representation through a network of interactions has not been investigated. Our work aims at identifying the causal relationship of each element in an oral tolerance network, and also to propose a phenomenological model that’s capable of predicting the stochastic behavior of this network when under manipulation. We compared the changes of a “healthy” network caused by “knock-outs” (KOs) in two approaches: an analytical approach by the Perron Frobenius theory; and a computational approach, which we describe within this work in order to find numerical results for the model. Both approaches have shown the most relevant immunological components for this phenomena, that happens to corroborate the empirical results from animal models. Besides explain in a intelligible fashion how the components interacts in a complex manner, we also managed to describe and quantify the importance of KOs that hasn’t been empirically tested.
20.5 A dual-symmetrical-output switched-capacitor converter with dynamic power cells and minimized cross regulation for application processors in 28nm CMOS

Multicore application processors in smartphones/watches use power-saving techniques such as dynamic voltage and frequency scaling (DVFS) to extend battery cycle, and supply cores with different voltages [1]. High-efficiency fully integrated switched-capacitor (SC) power converters with no external components are promising candidates [2]. Typically, SC converters with different specifications are independently designed (Fig. 20.5.1), leading to a large area overhead, as each converter has to handle its peak output power. Recently, multi-output SC converters are reported to tackle this issue. In [3], an on-demand strategy is used to control two outputs, each with a different loading range, and the outputs are not interchangeable. In [4], the two output voltages are fixed with voltage conversion ratios (VCRs) of 2× and 3× only. In [5], the controller is integrated, but the three output voltages are still from three individual SC converters. Without reallocating the capacitors in the power stages, capacitor utilization is low, as margins have to be reserved to cater for each converter's peak output power. This paper presents a fully integrated dual-output SC converter with dynamic power-cell allocation for application processors. The power cells are shared and can be dynamically allocated according to load demands. A dual-path VCO that works independently of power-cell allocation is proposed to realize a fast and stable regulation loop. The converter can deliver a maximum current of 100mA: one output can be adjusted to deliver 100mA, while the other handles a very light load; or both outputs can be adjusted to deliver 50mA each with over 80% efficiency.