Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Resource Polymorphism in Fish, Driven by Differential Bottom Environments: An Example from an Ancient Lake in Japan

Divergent natural selection rooted in differential resource use can generate and maintain intraspecific eco-morphological divergence (i.e., resource polymorphism), ultimately leading to population splitting and speciation. Differing bottom environments create lake habitats with different benthos communities, which may cause selection in benthivorous fishes. Here, we document the nature of eco-morphological and genetic divergence among local populations of the Japanese gudgeon Sarcocheilichthys (Cyprinidae), which inhabits contrasting habitats in the littoral zones (rocky vs. pebbly habitats) in Lake Biwa, a representative ancient lake in East Asia. Eco-morphological analyses revealed that Sarcocheilichthys variegatus microoculus from rocky and pebbly zones differed in morphology and diet, and that populations from rocky environments had longer heads and deeper bodies, which are expected to be advantageous for capturing cryptic and/or attached prey in structurally complex, rocky habitats. Sarcocheilichthys biwaensis, a rock-dwelling specialist, exhibited similar morphologies to the sympatric congener, S. v. microoculus, except for body/fin coloration. Genetic analyses based on mitochondrial and nuclear microsatellite DNA data revealed no clear genetic differentiation among local populations within/between the gudgeon species. Although the morphogenetic factors that contribute to morphological divergence remain unclear, our results suggest that the gudgeon populations in Lake Biwa show a state of resource polymorphism associated with differences in the bottom environment. This is a novel example of resource polymorphism in fish within an Asian ancient lake, emphasizing the importance and generality of feeding adaptation as an evolutionary mechanism that generates morphological diversification.
Review on the Functional Determinants and Durability of Shape Memory Polymers

Shape memory polymers (SMP) belong to the class of stimuli-responsive materials and have generated significant research interest. Their capability to retain an imposed, temporary shape and to recover the initial, permanent shape upon exposure to an external stimulus depends on the "functional determinants", which in simplistic terms, can be divided into structural/morphological and processing/environmental factors. The primary aim of the first part of this review is to reflect the knowledge about these fundamental relationships. In a next step, recent advances in shape memory polymer composites are summarized. In contrast to earlier reviews, studies on the impairment of shape memory properties through various factors, such as aging, compression and hibernation, lubricants, UV light and thermo-mechanical cycling, are extensively reviewed. Apart from summarizing the state-of-the-art in SMP research, recent progress is commented.
3D Reconstruction of Piecewise Planar Models from Multiple Views Utilizing Coplanar and Region Constraints

An automatic 3D reconstruction method based upon coplanar and region constraints is proposed for synthesizing piecewise 3D planar models of a real-world scene portrayed in a sequence of digital images. Significantly, the reconstruction process requires no prior knowledge about the scene and the camera parameters. The proposed modeling method comprises three steps. Firstly, the corresponding feature points and lines are extracted from a series of images of the world scene. Secondly, the extracted corresponding points and lines are filtered in accordance with region and coplanar constraints and are used to identify the possible half-planes of real-world planes. Finally, a complete 3D planar model is constructed by identifying the correct half-planes in the world scene enlarging these half-planes to their full extent, and then merging all the extended halfplanes which from part of the same world plane. The feasibility of the proposed approach is demonstrated by reconstructing 3D planar models of three real-world scenes containing objects with multiple planar facets.
Membership Dependent Stability Analysis of TS Fuzzy Controlled Systems using Coupling Attenuation

The use of Linear Matrix Inequalities and Common Quadratic Lyapunov Functions is a powerful and commonplace tool for Takagi-Sugeno fuzzy controlled system analysis and synthesis. However, in practice, few practical and performing results are avail- able when the subsystems exhibit different input matrices, because of the strong coupling between the subsystems/subcontrollers. In this paper, this coupling is demonstrated and a method is proposed which allows to synthesize, for a number of subsystems higher than 2, the local gains of a Parallel Distributed Controller. It is shown that the controller gains depend on the values of the input matrices and of the membership functions, and are thus able to relax classical stability conditions by embedding information on the fuzzy premises.
Architectural tradeoffs in the design of MIPS-X

The design of a RISC processor requires a careful analysis of the tradeoffs that can be made between hardware complexity and software. As new generations of processors are built to take advantage of more advanced technologies, new and different tradeoffs must be considered. We examine the design of a second generation VLSI RISC processor, MIPS-X. MIPS-X is the successor to the MIPS project at Stanford University and like MIPS, it is a single-chip 32-bit VLSI processor that uses a simplified instruction set, pipelining and a software code reorganizer. However, in the quest for higher performance, MIPS-X uses a deeper pipeline, a much simpler instruction set and achieves the goal of single cycle execution using a 2-phase, 20 MHz clock. This has necessitated the inclusion of an on-chip instruction cache and careful consideration of the control of the machine. Many tradeoffs were made during the design of MIPS-X and this paper examines several key areas. They are: the organization of the on-chip instruction cache, the coprocessor interface, branches and the resulting branch delay, and exception handling. For each issue we present the most promising alternatives considered for MIPS-X and the approach finally selected. Working parts have been received and this gives us a firm basis upon which to evaluate the success of our design.
A New Electromechanical Coupling Model for Piezoelectric Actuator

Combining the constitutive equation of piezoelectric ceramic with elastic-dynamical equations and coupling theory of FEM, the finite element control equation for piezoelectric actuator is established. Detailed calculation of the electro-mechanical coupling field parameters is made by the SP1 type longitudinal-bending vibrator and results show it can be used for the transparent calculation for piezoelectric intellectual structure and avoid the black box operation in FEM software. The model lays the foundation to develop the special program for piezoelectric actuator and to study the non-linear constitutive equation of piezoelectric ceramic driven by high-power.
Qualification of arm gestures using hidden Markov models

We propose the use of hidden Markov models (HMMs) to qualify arm gestures. A HMM is trained based on the reference or correct gesture. Then, samples of the gesture that we want to score are used to train a second HMM. Both HMMs are compared, and a measure of their similarity is used to qualify the gesture. We used 3 different metrics to compare HMMs: Levinson, Kullback-Leibler and Porikli. For this, a visual system was developed to track a person's arm, which serves as input to the models that qualify the gestures. We applied this method to qualify the arm movements of stroke patients under rehabilitation. We analyzed three therapeutic gestures: flexion, circular and abduction. A HMM is trained to represent the movement of a healthy person for each gesture, which is compared with the HMMs obtained for each patient. The results are compared with the scales that are used in therapy. From the analysis of several experiments, the Porikli metric was the best to qualify the three gestures, in terms of the motricity index.
Fusing bottom-up and top-down pathways in neural networks for visual object recognition

In this paper, an artificial neural network model is built up with two pathways: bottom-up sensory-driven pathway and top-down expectation-driven pathway, which are fused to train the neural network for visual object recognition. During the supervised learning process, the bottom-up pathway generates hypotheses as network outputs. Then target label will be applied to update the bottom-up connections. On the other hand, the hypotheses generated by the bottom-up pathway will produce expectations on the sensory input through the top-down pathway. The expectations will be constrained by the real data from the sensory input which can be used to update the top-down connections accordingly. This two-pathway based neural network can also be applied to semi-supervised learning with both labeled and unlabeled data, where the network is able to generate hypotheses and corresponding expectations. Experiments on visual object recognition suggest that the proposed neural network model is promising to recover the object for the cases with missing data in sensory inputs.
Effect of Lepidium meyenii (Maca) on spermatogenesis in male rats acutely exposed to high altitude (4340 m).

Lepidium meyenii (Maca) is a Peruvian hypocotyl that grows exclusively between 4000 and 4500 m in the central Andes. Maca is traditionally employed in the Andean region for its supposed fertility-enhancing properties. The aim of this study was to test the hypothesis that Maca can prevent high altitude-induced testicular disturbances. Adult male rats were exposed for 21 days to an altitude of 4340 m and treated with vehicle or aqueous extract of Maca (666.6 mg/day). The lengths of the stages of the seminiferous epithelium and epididymal sperm counts were obtained at 0, 7, 14 and 21 days of exposure. The stages of the seminiferous tubules were assessed by transillumination. A dose-response study was also performed at sea level to determine the effect of Maca given to male rats at doses of 0, 6.6, 66.6 and 666.6 mg/day for 7 days on body weight, seminiferous tubule stages and epididymal sperm count. The length of stage VIII and the epididymal sperm count were increased in a dose-dependent manner in Maca-treated rats but treatment reduced the length of stage I. At the highest dose, sperm count increased 1.58 times, the length of stage VIII increased 2.4 times and the length of stage I was reduced 0.48 times compared with the value at dose 0. Exposure to high altitude resulted in a reduction in epididymal sperm count after 7 days and lower values were maintained up to 21 days. Altitude reduced spermiation (stage VIII) to half and the onset of spermatogenesis (stages IX-XI) to a quarter on days 7 and 14 but treatment with Maca (666.6 mg/day) prevented these changes. Data on transillumination and epididymal sperm count in the Maca-treated group exposed to high altitude were similar to those obtained at sea level. Maca increased the sperm count on day 21 of exposure to high altitude to values similar (1095.25 +/- 20.41x10(6) sperm, means +/- S.E. M. ) to those obtained in the Maca-treated group at sea level (1132.30 +/- 172.95x10(6) sperm). Furthermore, in the Maca-treated group exposed for 21 days to high altitude, epididymal sperm count was higher than in the non-treated group at sea level (690.49 +/- 43.67x10(6) sperm). In conclusion, treatment of rats with Maca at high altitude prevented high altitude-induced spermatogenic disruption.
Whole genome alignments using MPI-LAGAN

Advances in sequencing technologies have substantially increased the number of fully sequenced genomes. Alignment algorithms play a crucial rule in analyzing whole genomes, identifying similar and conserved regions between pairs of genomes, leading to annotation of genomes with site-specific properties and functions. In this work we introduce a parallel algorithm for a widely used whole genome alignment method called LAGAN. We use the MPI-based protocol, to develop parallel solutions for two phases of the algorithm which take up a significant portion of the total runtime, and also have a high memory requirement. The serial LAGAN program uses CHAOS [5] to quickly determine initial anchor or seeds, which are extended using a sparse dynamic programming based longest-increasing subsequence method. Our work involves parallelizing the CHAOS and LIS phases of the algorithm using a one-dimensional block cyclic partitioning of the computation. This leads to development of an efficient algorithm that utilizes the processors in a balanced way. We also ensure minimum time spent in communication or transfer of information across processors. We also report experimental evaluation of our parallel implementation using pairs of human contigs of varying lengths. We discuss and illustrate the challenges faced in parallelizing a sparse dynamic programming formulation as in this work, and show equivalent to theoretical speedups for our parallelized phases of the LAGAN algorithm.
Effect of gas tungsten arc welding process variables on dilution and bead geometry of Stellite 6 hardfaced valve seat rings

Abstract Hardfacing is one of the surfacing methods most widely employed in valve manufacturing industries to deposit Stellite 6, a cobalt based alloy, on low carbon steel valve seat rings to enhance specific properties such as wear and corrosion resistance. Gas tungsten arc welding (GTAW) process is used for hardfacing smaller size valves. The quality of the hardfaced deposits depends on the degree of dilution. The control of dilution will result in better metallurgical and mechanical properties of hardfaced deposits. Mathematical models have been developed in this paper to study the effects of GTAW process parameters on dilution and other important hardfacing parameters, namely, penetration, reinforcement and bead width. Models have been tested for their adequacy by regression methods. The direct and interaction effects are presented in graphical form which can be used not only for the prediction of geometry but also for controlling weld bead quality.
Intercellular calcium signaling in a gap junction-coupled cell network establishes asymmetric neuronal fates in C. elegans

The C. elegans left and right AWC olfactory neurons specify asymmetric subtypes, one default AWCOFF and one induced AWCON, through a stochastic, coordinated cell signaling event. Intercellular communication between AWCs and non-AWC neurons via a NSY-5 gap junction network coordinates AWC asymmetry. However, the nature of intercellular signaling across the network and how individual non-AWC cells in the network influence AWC asymmetry is not known. Here, we demonstrate that intercellular calcium signaling through the NSY-5 gap junction neural network coordinates a precise 1AWCON/1AWCOFF decision. We show that NSY-5 gap junctions in C. elegans cells mediate small molecule passage. We expressed vertebrate calcium-buffer proteins in groups of cells in the network to reduce intracellular calcium levels, thereby disrupting intercellular communication. We find that calcium in non-AWC cells of the network promotes the AWCON fate, in contrast to the autonomous role of calcium in AWCs to promote the AWCOFF fate. In addition, calcium in specific non-AWCs promotes AWCON side biases through NSY-5 gap junctions. Our results suggest a novel model in which calcium has dual roles within the NSY-5 network: autonomously promoting AWCOFF and non-autonomously promoting AWCON.
Modeling Intelligent Energy Systems: Co-Simulation Platform for Validating Flexible-Demand EV Charging Management

Energy systems experience a rise in complexity: new technologies, topologies and components, tighter links to other systems like markets and the increased usage of information technology. This leads to challenging questions that can not be answered via traditional methods. The goal of including renewable energy and clean technologies in the grid, however, requires solutions for the resulting complex problems. This paper investigates dynamic demand response for intelligent electric vehicle charging as a use-case for detailed hybrid models that cannot be properly handled by traditional tools alone. Universal modeling languages and specialized domain-specific modeling solutions are brought together via standardized co-simulation interfaces to achieve maximal flexibility and minimal implementation efforts. This combination of previously numerically incompatible modeling paradigms enables a detailed look into the dynamics of hybrid component models while keeping the comfort and the strength of established tools. This coupling of a Modelica-based physical simulation engine, a commercial power system simulation tool and an agent-based discrete event simulator for energy grids results in a novel co-simulation platform. This visionary concept provides the high level of detail, scope, flexibility, scalability and accuracy in simulations needed to analyze and optimize energy systems of the future.
MOD-Derived YBa2Cu3O7-δ Thin Films using a Fast Pyrolysis Process

In the present work, a fast pyrolysis process is developed for YBa2Cu3O7-δ (YBCO) films preparation with trifluroacetates metalorganic deposition technique (TFA-MOD). The decomposition of TFA salts as well as the surface morphology of pyrolyzed films is investigated with respect to the pyrolysis temperature and its heating rate. Two typical surface morphologies for the pyrolyzed films, being smooth or buckled, are revealed subjecting to the heating rate and film thickness, which related to the subsequent YBCO films property. Smooth and wrinkle-free pyrolyzed films are achieved by using this fast pyrolysis process with a heating rate as high as 5°C/min. The final crystallized YBCO films exhibit good performances with the superconducting transition temperature of 91 K and critical current density of 2.0 MA/cm2 at 77 K, suggesting a rapid, promising MOD route available for scale-up preparation of YBCO coated conductors.
Connectionist Models of Reinforcement, Imitation, and Instruction in Learning to Solve Complex Problems

We compared computational models and human performance on learning to solve a high-level, planning-intensive problem. Humans and models were subjected to three learning regimes: reinforcement, imitation, and instruction. We modeled learning by reinforcement (rewards) using SARSA, a softmax selection criterion and a neural network function approximator; learning by imitation using supervised learning in a neural network; and learning by instructions using a knowledge-based neural network. We had previously found that human participants who were told if their answers were correct or not (a reinforcement group) were less accurate than participants who watched demonstrations of successful solutions of the task (an imitation group) and participants who read instructions explaining how to solve the task. Furthermore, we had found that humans who learn by imitation and instructions performed more complex solution steps than those trained by reinforcement. Our models reproduced this pattern of results.
Combined dynamic voltage scaling and adaptive body biasing for lower power microprocessors under dynamic workloads

Dynamic voltage scaling (DVS) reduces the power consumption of processors when peak performance is unnecessary. However, the achievable power saving by DVS alone is becoming limited as leakage power increases. In this paper, we show how the simultaneous use of adaptive body biasing (ABB) and DVS can be used to reduce power in high-performance processors. Analytical models of the leakage current, dynamic power, and frequency as functions of supply voltage and body bias are derived and verified with SPICE simulation. We then show how to determine the correct trade-off between supply voltage and body bias for a given clock frequency and duration of operation. The usefulness of our approach is evaluated on real workloads obtained using real-time monitoring of processor utilization for four applications. The results demonstrate that application of simultaneous DVS and ABB results in an average energy reduction of 48% over DVS alone.
Low-Frequency Noise and Offset Rejection in DC-Coupled Neural Amplifiers: A Review and Digitally-Assisted Design Tutorial

We review integrated circuits for low-frequency noise and offset rejection as a motivation for the presented digitally-assisted neural amplifier design methodology. Conventional AC-coupled neural amplifiers inherently reject input DC offset but have key limitations in area, linearity, DC drift, and spectral accuracy. Their chopper stabilization reduces low-frequency intrinsic noise at the cost of degraded area, input impedance and design complexity. DC-coupled implementations with digital high-pass filtering yield improved area, linearity, drift, and spectral accuracy and are inherently suitable for simple chopper stabilization. As a design example, a 56-channel 0.13 <inline-formula><tex-math notation="LaTeX">$\mu\text{m}$</tex-math></inline-formula> CMOS intracranial EEG interface is presented. DC offset of up to <inline-formula><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula>50 mV is rejected by a digital low-pass filter and a 16-bit delta-sigma DAC feeding back into the folding node of a folded-cascode LNA with CMRR of 65 dB. A bank of seven column-parallel fully differential SAR ADCs with ENOB of 6.6 are shared among 56 channels resulting in 0.018 <inline-formula><tex-math notation="LaTeX">$\text{mm}^{2}$</tex-math></inline-formula> effective channel area. Compensation-free direct input chopping yields integrated input-referred noise of 4.2 <inline-formula><tex-math notation="LaTeX">$\mu V_{\mathrm{rms}}$</tex-math></inline-formula> over the bandwidth of 1 Hz to 1 kHz. The 8.7 <inline-formula><tex-math notation="LaTeX">$\text{mm}^{2}$</tex-math></inline-formula> chip dissipating 1.07 mW has been validated <italic>in vivo</italic> in online intracranial EEG monitoring in freely moving rats.
Flightless, secreted through a late endosome/lysosome pathway, binds LPS and dampens cytokine secretion

Summary Flightless (Flii) is upregulated in response to wounding and has been shown to function in wound closure and scarring. In macrophages intracellular Flii negatively modulates Toll-Like Receptor (TLR) signalling and dampens cytokine production. We now show that Flii is constitutively secreted from macrophages and fibroblasts and is present in human plasma. Secretion from fibroblasts is upregulated in response to scratch wounding and lipopolysaccharide (LPS)-activated macrophages also temporally upregulate their secretion of Flii. Using siRNA, and wild-type and mutant proteins, we show that Flii is secreted by means of a late endosomal/lysosomal pathway that is regulated by Rab7 and Stx11. Flii contains 11 leucine-rich repeat domains in its N-terminus that have nearly 50% similarity to those in the extracellular pathogen binding portion of Toll-like receptor 4 (TLR4). We show secreted Flii can also bind LPS and has the ability to alter macrophage activation. LPS activation of macrophages in Flii-depleted conditioned medium leads to enhanced macrophage activation and increased TNF secretion compared with cells activated in the presence of Flii. These results show secreted Flii binds to LPS and in doing so alters macrophage activation and cytokine secretion, suggesting that like the intracellular pool of Flii, secreted Flii also has the ability to alter inflammation.