Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of CTCF as a master regulator of the clustered protocadherin genes

The brain is a large and complex network of neurons. Specific neuronal connectivity is thought to be based on the combinatorial expression of the 52 protocadherins (Pcdh) membrane adhesion proteins, whereby each neuron expresses only a specific subset. Pcdh genes are arranged in tandem, in a cluster of three families: Pcdhα, Pcdhβ and Pcdhγ. The expression of each Pcdh gene is regulated by a promoter that has a regulatory conserved sequence element (CSE), common to all 52 genes. The mechanism and factors controlling individual Pcdh gene expression are currently unknown. Here we show that the promoter of each Pcdh gene contains a gene-specific conserved control region, termed specific sequence element (SSE), located adjacent and upstream to the CSE and activates transcription together with the CSE. We purified the complex that specifically binds the SSE–CSE region and identified the CCTC binding-factor (CTCF) as a key molecule that binds and activates Pcdh promoters. Our findings point to CTCF as a factor essential for Pcdh expression and probably governing neuronal connectivity.
Do Postures of Distal Effectors Affect the Control of Actions of Other Distal Effectors? Evidence for a System of Interactions between Hand and Mouth

The present study aimed at determining whether, in healthy humans, postures assumed by distal effectors affect the control of the successive grasp executed with other distal effectors. In experiments 1 and 2, participants reached different objects with their head and grasped them with their mouth, after assuming different hand postures. The postures could be implicitly associated with interactions with large or small objects. The kinematics of lip shaping during grasp varied congruently with the hand posture, i.e. it was larger or smaller when it could be associated with the grasping of large or small objects, respectively. In experiments 3 and 4, participants reached and grasped different objects with their hand, after assuming the postures of mouth aperture or closure (experiment 3) and the postures of toe extension or flexion (experiment 4). The mouth postures affected the kinematics of finger shaping during grasp, that is larger finger shaping corresponded with opened mouth and smaller finger shaping with closed mouth. In contrast, the foot postures did not influence the hand grasp kinematics. Finally, in experiment 5 participants reached-grasped different objects with their hand while pronouncing opened and closed vowels, as verified by the analysis of their vocal spectra. Open and closed vowels induced larger and smaller finger shaping, respectively. In all experiments postures of the distal effectors induced no effect, or only unspecific effects on the kinematics of the reach proximal/axial component. The data from the present study support the hypothesis that there exists a system involved in establishing interactions between movements and postures of hand and mouth. This system might have been used to transfer a repertoire of hand gestures to mouth articulation postures during language evolution and, in modern humans, it may have evolved a system controlling the interactions existing between speech and gestures.
Malani Igneous Suite of Rocks

Hydrology should become an important part of earth science studies and the efforts of Prof. Eagleson in changing the existing mental image of hydrology should become widely known and appreciated. The cycling of water on a continental scale should be clearly understood and taught in schools and colleges. As recently emphasized in an editorial in Groundwater (July-August 1997, p.S61) 'communication is vital. We need people who can transfer research findings to the field and who can also communicate water-users needs to the researchers. ' The atmosphere of secrecy prevailing in our research organisations and denial of information to user agencies is deplorable and should be given up in favour of free exchange of ideas aimed at improving our understanding of the nature and complexity of our natural resources.
Improved sensitivity in assays for binding of novel beta-lactam antibiotics to penicillin-binding proteins of Escherichia coli

Tigemonam and temocillin, but not aztreonam, bound to penicillin-binding proteins (PBPs) 1a and 3 of Escherichia coli with apparent improved affinity when challenged with benzylpenicillin at lowered temperatures. Half times for deacylation of the tigemonam-PBP complexes were shorter than were those of the corresponding aztreonam-PBP complexes. The implications of the routine testing of PBP affinities are discussed.
Team optimal control of coupled subsystems with mean-field sharing

We investigate team optimal control of stochastic subsystems that are weakly coupled in dynamics (through the mean-field of the system) and are arbitrary coupled in the cost. The controller of each subsystem observes its local state and the mean-field of the state of all subsystems. The system has a non-classical information structure. Exploiting the symmetry of the problem, we identify an information state and use that to obtain a dynamic programming decomposition. This dynamic program determines a globally optimal strategy for all controllers. Our solution approach works for arbitrary number of controllers and generalizes to the setup when the mean-field is observed with noise. The size of the information state is time-invariant; thus, the results generalize to the infinite-horizon control setups as well. In addition, when the mean-field is observed without noise, the size of the corresponding information state increases polynomially (rather than exponentially) with the number of controllers which allows us to solve problems with moderate number of controllers. We illustrate our approach by an example motivated by smart grids that consists of 100 coupled subsystems.
Runoff Responses to Climate and Land Use/Cover Changes under Future Scenarios

Climate and land use/cover (LUC) are the two most significant factors that directly affect the runoff process. However, most research on runoff response has focused mainly on projected climate variation, while future LUC variability has been neglected. Therefore, the objective of this study is to examine the impacts of projected climate and LUC changes on runoff. Future climate scenarios are projected using the Quantile Mapping (QM) method, and future LUC scenarios are predicted with the Cellular Automaton-Markov (CA-Markov) model. Three different scenarios are simulated and compared to evaluate their impacts: Scenario 1 (LUC of 2010 and climate during the 2011–2050 period, abbreviated S1), Scenario 2 (LUC of 2010, 2020, 2030, 2040 and 2050 and climate of the historical wet year, normal year and dry year, abbreviated S2) and Scenario 3 (LUC of 2010, 2020, 2030, 2040 and 2050 and corresponding climate projections of 2011–2020, 2021–2030, 2031–2040 and 2041–2050 period, abbreviated S3). These three scenarios are then input into the Soil and Water Assessment Tool (SWAT) model to assess runoff responses. Beijiang River Basin, located in southern China, is used in this case study. The results obtained from S1, S2 and S3 show that runoff change in this basin is mainly caused by climate change; warmer temperatures and greater precipitation increase runoff. LUC change has little influence on runoff at the whole-basin scale, but changes in runoff components are more notable in the urban area than in the natural region at the sub-watershed level. The impact of LUC change in urbanized region on runoff components differ obviously among the wet, normal and dry years, and surface runoff and groundwater are found to be more sensitive to urbanization. Runoff depth is predicted to increase in this basin under the impacts of both climate and LUC changes in the future. Climate change brings greater increase in water yield and surface runoff, whereas LUC change leads to changes in allocation between surface runoff and groundwater in the urban region.
Monitoring Stream Properties for Continuous Query Processing

We are developing a general-purpose Data Stream Management System for processing continuous queries over multiple continuous data streams. When a new continuous query is registered, our query optimizer creates an initial query plan (possibly merged with existing plans for previously registered queries), and allocates initial resources, such as memory for join or aggregation synopses and for input and inter-operator queues. Dynamically, plans may be altered, resources may be reallocated, and scheduling decisions are made, all based on stream data and arrival characteristics, query plan execution behavior, and resource utilization.
Nonparametric Bayesian Learning of Other Agents? Policies in Interactive POMDPs

We consider an autonomous POMDP agent facing a multiagent environment with unknown opponents, that are modeled as nite state controllers. The agent rst learns the models from (imperfectly) observed behavior, and subsequently exploits them in planning for its own optimal policy by constructing an interactive POMDP. In the learning phase, Bayesian nonparametric methods are used to sample from the posterior distribution over the innite-dimension al space of all possible controllers, resulting in models whose size scales with the complexity of observed behavior. Experimental results show that learning improves the agent’s performance, which increases with the amount of data collected during the learning phase.
Strategies for healthcare professionals to facilitate patient illness understanding

AIMS AND OBJECTIVES To describe how healthcare professionals facilitate patient illness understanding. BACKGROUND Healthcare professionals and patients differ in their illness understanding. If the information provided by healthcare professionals is not adapted to the patient's daily life, it may be unusable for the patient. Previous research has found that healthcare professionals should individualise the information to enable the patient to apply the knowledge to the personal situation and to develop illness understanding. However, little is known of how healthcare professionals can facilitate patient illness understanding. METHOD A qualitative descriptive study based on individual, semi-structured, open-ended and face-to-face interviews was conducted with healthcare professionals (n = 11) concerning how they facilitate patients illness understanding. Three health centres were involved during the period of March to November 2014. The interviews were analysed with qualitative content analysis. RESULTS The result identified a continuous and collaborative process with three strategies used by healthcare professionals to facilitate the patient's illness understanding: (i) assess the patient's illness understanding, (ii) interact with the patient to develop illness understanding and (iii) support the patient's personal development for illness understanding. The steps in the process depend on each other. CONCLUSIONS The results of our analysis indicate that healthcare professionals can use the continuous and collaborative process to enhance the patient's self-care ability and turn his or her knowledge into action for improving illness understanding. RELEVANCE TO CLINICAL PRACTICE The three continuous and collaborative process strategies involving pedagogical approaches can create conditions for healthcare professionals to obtain a holistic view of the patient's life and to be a key resource for person-centred care.
BGrC for Superheated Steam Temperature System Modeling in Power Plant

As a new kind of soft computing method, Rough Set Theory (RST) has been successfully applied in many fields, however, most of its application is focus on the knowledge reduction algorithm that based on the classification. Granular computing (GrC) brings a new thought for problem solving, and it arose much interest since its appearance. This paper introduces GrC method into traditional RST knowledge reduction algorithm by the definition of binary granular matrix. The new algorithm makes the traditional knowledge reduction algorithm become simple matrix operation and it is successfully applied to model for the superheated steam temperature system in the Power Plant. Detailed description is given in this paper.
Affine invariant curve matching using normalization and curvature scale-space

In this paper, an affine invariant curve matching method using curvature scale-space and normalization is proposed. Prior to curve matching, curve normalization with respect to affine transformations is applied, allowing a lossless affine invariant curve representation. The maxima points of the curvature scale-space (CSS) image are then used to represent the normalized curve, while retaining the local properties of the curve. The matching algorithm that follows, matches the maxima sets of CSS images and the resulting matching cost provides a measure of similarity. The methodpsilas performance and robustness is evaluated through a variety of curves and affine transformations, obtaining precise shape similarity and retrieval.
Improving text classification for oral history archives with temporal domain knowledge

This paper describes two new techniques for increasing the accuracy oftopic label assignment to conversational speech from oral history interviews using supervised machine learning in conjunction with automatic speech recognition. The first, time-shifted classification, leverages local sequence information from the order in which the story is told. The second, temporal label weighting, takes the complementary perspective by using the position within an interview to bias label assignment probabilities. These methods, when used in combination, yield between 6% and 15% relative improvements in classification accuracy using a clipped R-precision measure that models the utility of label sets as segment summaries in interactive speech retrieval applications.
MRTP: Mobile Ray Tracing Processor With Reconfigurable Stream Multi-Processors for High Datapath Utilization

This paper presents a mobile ray tracing processor (MRTP) with reconfigurable stream multi-processors (RSMPs) for high datapath utilization. The MRTP includes three RSMPs that operate in multiple instruction multiple data (MIMD) mode asynchronously to exploit instruction-level parallelism. Each RSMP is based on single instruction multiple thread (SIMT) architecture to exploit thread-level parallelism. An RSMP consists of twelve scalar processing elements (SPEs) that run multiple threads in parallel synchronously: twelve scalar threads or four vector threads depending on an operating mode. A low datapath utilization caused by a branch divergence in SIMT architecture is improved by 19.9% on average by reconfiguring twelve SPEs between scalar SIMT and vector SIMT with 0.1% area overheads. Special function instructions occupy only 2% ~ 8% of kernel instructions so that a partial special function unit (PSFU) is implemented instead of a large dedicated SFU. The access conflicts with a look-up table (LUT) caused by concurrent accesses of twelve SPEs are reduced by a table loader (TBLD). The TBLD monitors concurrent requests from twelve SPEs and reduces an access count to LUT by distributing a coefficient to multiple SPEs with only one read-access to LUT. MRTP with area of 4 × 4 mm2 has been fabricated in 0.13 μm CMOS technology. MRTP achieves a peak performance of 673 K rays per second while consuming 156 mW at 100 MHz with VDD = 1.2 V .
DeepFix: A Fully Convolutional Neural Network for Predicting Human Eye Fixations

Understanding and predicting the human visual attention mechanism is an active area of research in the fields of neuroscience and computer vision. In this paper, we propose DeepFix, a fully convolutional neural network, which models the bottom–up mechanism of visual attention via saliency prediction. Unlike classical works, which characterize the saliency map using various hand-crafted features, our model automatically learns features in a hierarchical fashion and predicts the saliency map in an end-to-end manner. DeepFix is designed to capture semantics at multiple scales while taking global context into account, by using network layers with very large receptive fields. Generally, fully convolutional nets are spatially invariant—this prevents them from modeling location-dependent patterns (e.g., centre-bias). Our network handles this by incorporating a novel location-biased convolutional layer. We evaluate our model on multiple challenging saliency data sets and show that it achieves the state-of-the-art results.
Distributed Resource Allocation with Inter-Cell Interference Coordination in OFDMA Uplink

In this paper, we propose a distributed resource allocation mechanism with inter-cell interference (ICI) coordination for practical orthogonal frequency division multiple access (OFDMA) uplink. The designed scheme combines soft frequency reuse (SFR) and interference limited power control of neighboring cells. It avoids severe interference to neighboring cells through adjusting the interference limited power constraints according to the load variations across cells. The computational complexity is greatly lowered by decomposing a multi-cell optimization problem into distributed single-cell sub-problems. The simulation results demonstrate that the proposed scheme not only guarantees the cell-edge UEs' quality of service (QoS) but also improves the overall system performance significantly. Moreover, this scheme can adapt to the load variations in a certain cell or across cells.
Delayless subband echo cancelers using computationally efficient parallel Kalman filters

Conventional delayless subband filters use LMS or NLMS algorithm for coefficient adaptations in subband domain. It is known that. Kalman filter (KF) algorithm shows better convergence than the conventional LMS/NLMS algorithm but with the cost paid in computational complexity. In this work, we show that introducing parallel Kalman filters (PKFs) in the subband domain performance can be made better both in terms of ERLE and computational complexity than that of the LMS/NLMS algorithms.
Enabling indoor exhibition automated guidance and multimedia content delivery on mobile devices

Multimedia content delivery is an important issue in assistive guidance systems for exhibition areas. This paper presents an automatic guidance and multimedia content presentation system utilizing location-based services and their deployment on mobile devices. A prototype installation and experimental usage in a real exhibition environment has provided promising results regarding the system's user acceptance and functionality.
Multisegment Foot Kinematics During Walking in Younger and Older Adults

Background Currently, age-related changes in foot mechanics are poorly understood. A greater understanding of the natural changes in foot motion is needed to improve our understanding of pathological foot conditions. Methods The purpose of this study was to compare multisegment foot kinematic data during gait in younger and older individuals. Eleven (N = 11) adult male participants between the ages of 18 - 30 years (younger group; mean ± SD: 24.6 ± 3.0 years) and eleven (N = 11) adults aged 55 years or older (older group; mean ± SD: 65.0 ± 4.2 years) were recruited for the study. The foot was modeled as a four-segment rigid body model. Three-dimensional kinematic and kinetic gait parameters were recorded using an 8-camera Vicon MCam motion capture system and two Kistler force plates. A MANOVA was used to test for significant differences in mean temporal-spatial data, mean ranges of motion, and mean peak joint angle data between age groups. Results No significant differences (P > 0.05) were found between the two age groups for any of the gait parameters. The results of the present study suggest that individuals aged 65.0 ± 4.2 years have foot mechanics that are comparable to younger walkers. Conclusions As such, any deviations in motion at this age may be indicative of an underlying disease or disorder.
J-Sim: a simulation environment for wireless sensor networks

Wireless sensor networks (WSNs) have gained considerable attention in the past few years. As such, there has been an increasing need for defining and developing simulation frameworks for carrying out high-fidelity WSN simulation. In this paper, the authors presented a modeling and simulation framework for WSNs in J-Sim - an open-source, component-based compositional network simulation environment that is developed entirely in Java. This framework is built upon the autonomous component architecture (ACA) and the extensible internetworking framework (INET) of J-Sim, and provides an object-oriented definition of (i) target, sensor and sink nodes, (ii) sensor and wireless communication channels, and (iii) physical media such as seismic channels, mobility model and power model (both energy-producing and energy-consuming components). Application-specific models can be defined by sub-classing classes in the simulation framework and customizing their behaviors. The use of the proposed WSN simulation framework was demonstrated by implementing several well-known localization, geographic routing, and directed diffusion protocols. In addition, performance comparisons were performed (in terms of execution time incurred, and the memory used) in simulating several typical WSN scenarios in J-Sim and ns-2. The simulation study indicates that the proposed WSN simulation framework in J-Sim is much more scalable than ns-2 (especially in memory usage).
The Complexities of Computer-Supported Collaboration

We introduce the idea of considering computer supported collaborative work as a complex adaptive system (CAS). In other disciplines, such as physics, biology and ecology, the idea of a CAS has proven useful in explaining a wide variety of phenomena. We define a CAS and then describe how CSCW fits that definition. We demonstrate that the concepts in CAS theory can be applied to help understand computer supported collaboration and provide examples of catastrophe and chaos in physics showing how they can be paralleled in CSCW. The implications of the application of CAS theory to CSCW include greater insight into the computer supported collaborative process and inform both evaluation methodology and design of applications.
Wrist rotation for interaction in mobile contexts

In this paper, we investigate wrist rotation as a hands-free method of interaction with a mobile device. To evaluate this technique, a Fitts' Law targeting study is described in four different postures: resting, seated, standing and walking. Results show correlations in movement time and the Index of Difficulty of the task and similarities in the targeting performance for the first three conditions, but show walking and targeting using this method was significantly more difficult.
The origin of embryonic stem cells has sparked ethical controversy over , and prompted legislative responses to , stem cell research

Among the many research fields that have found their way into the focus of public interest, seldom has one become such a hotly debated topic as research on embryonic stem cells. It has set churches and abortion opponents against scientists and patient advocates. Walking a tightrope, Western governments find it hard to draft regulations for this research field that address the concerns of both sides. Here, we will discuss the current state of stem cell research, potential clinical applications and comment on recent public policy decisions to regulate the research and use of embryonic stem cells.