Miracle-dz/UniFAR-FTUs huggingface dataset:
Combinatorial and Cross-Fiber Averaging Transform Muscle Electrical Responses with a Large Stochastic Component into Deterministic Contractions

Pyloric muscles of the stomatogastric neuromuscular system of the lobster Panulirus interruptus produce highly deterministic (range, less than ±6% of mean amplitude) contractions in response to motor nerve stimulation with unchanging spike bursts containing physiological (5–10) spike numbers. Intracellular recordings of extrajunctional potentials (EJPs) evoked in these muscles by motor nerve stimulation revealed a large, apparently stochastic amplitude variation (range, ±36% of mean amplitude). These observations raised the question of how do electrical responses with a large amplitude variation give rise to deterministic muscle output? We show here that this question is likely resolved by (1) combinatorial averaging within individual muscle fibers of the multiple EJPs that occur in motor neuron bursts, and (2) averaging across muscle fibers whose electrical responses are uncorrelated. Synapses with high inherent variability are also present in vertebrate CNSs. Combinatorial averaging in multispike inputs would also reduce variation in postsynaptic response at these synapses. The data reported here provide further support that bursting presynaptic activity could make such synapses functionally deterministic as well.
Deciding Disjunctive Linear Arithmetic with SAT

Disjunctive Linear Arithmetic (DLA) is a major decidable theory that is supported by almost all existing theorem provers. The theory consists of Boolean combinations of predicates of the form $\Sigma_{j=1}^{n}a_j\cdot x_j \le b$, where the coefficients $a_j$, the bound $b$ and the variables $x_1 >. x_n$ are of type Real ($\mathbb{R}$). We show a reduction to propositional logic from disjunctive linear arithmetic based on Fourier-Motzkin elimination. While the complexity of this procedure is not better than competing techniques, it has practical advantages in solving verification problems. It also promotes the option of deciding a combination of theories by reducing them to this logic. Results from experiments show that this method has a strong advantage over existing techniques when there are many disjunctions in the formula.
Enhanced sodium absorption in middle ear epithelial cells cultured at air–liquid interface

Conclusion As we demonstrated previously that transcription of α-ENaC was correlated with oxygen tension in the culture medium, this study suggests that the increase in α-ENaC expression observed under ALI conditions may result from greater oxygenation of ME cells. Objective The physiology of the middle ear (ME) is primarily concerned with keeping the cavities fluid-free, to allow transmission of sound vibrations from the eardrum to the inner ear. ME epithelial cells are thought to play a key role in this process as they actively absorb sodium and water in order to clear any excess fluid present in the cavities. Material and methods As an air–liquid interface (ALI) model has been shown to improve differentiation and enhance sodium absorption in other respiratory epithelia, we established an ALI model for ME cells. Results ME cells cultured under ALI conditions exhibited a fourfold increase in sodium absorption, which was not related to either a metabolic effect or to enhanced morphological differentiation, but instead to an increase in expression of the α-subunit of the epithelial sodium channel (α-ENaC).
Construction of turbo code interleaves from 3-regular Hamiltonian graphs

In this letter, we present a new construction of interleavers for turbo codes from 3-regular Hamiltonian graphs. The interleavers can be generated using a few parameters, which can be selected in such a way that the girth of the interleaver graph (IG) becomes large, inducing a high summary distance. The size of the search space for these parameters is derived. The proposed interleavers themselves work as their de-interleavers.
The role of fluorescence in situ hybridization and polymerase chain reaction in the diagnosis and classification of lymphoproliferative disorders on fine‐needle aspiration

Fine‐needle aspiration (FNA) has been used in the evaluation of lymphadenopathy for a long time and is highly reliable in the identification of metastatic malignancies. However, the role of FNA in the assessment of new lymphoproliferative disorders continues to be a subject of debate. The objective of the current study was to evaluate the role of molecular cytogenetic studies in FNA diagnoses of lymphoproliferative disorders.
Polarimetric SAR remote sensing of earthquake/tsunami disaster

In this study, changes of the L-band PALSAR polarimetric signal scattered from earthquake/tsunami damaged areas has been investigated. Since it is not always possible to get data sets having sufficiently good spatial/temporal resolutions to detect large area of damages precisely, it is of specific interest to use of wave polarization information appropriate to assess disaster-induced changes of scattering phenomena. Experimental results indicate that different polarimetric parameters and similarity measures provide complimentary information on damages. Consequently, it is important to utilize polarimetric features maximizing target changes and minimizing the false-alarm and the missed-alarm rates in developing damage assessment algorithms.
A Comparative Study of the Effectiveness of CPU Consolidation Versus Dynamic Voltage and Frequency Scaling in a Virtualized Multicore Server

Companies operating large datacenters are focusing on how to reduce the electrical energy costs of operating datacenters. A common way of cost reduction is to perform a dynamic voltage and frequency scaling (DVFS), thereby matching the CPU's performance and power level to incoming workloads. Another power saving technique is CPU consolidation, which uses the minimum number of CPUs necessary to meet the service request demands and turns OFF the remaining unused CPUs. DVFS has been already extensively studied and verified its effectiveness. On the other hand, it is necessary to study more about the effectiveness of CPU consolidation. Key questions that must be answered are how effectively the CPU consolidation improves the energy efficiency and how to maximize the improvement. These questions are addressed in this paper. After understanding modern power management techniques and developing an appropriate power model, this paper provides an extensive set of hardware-based experimental results and makes suggestions about how to maximize energy efficiency improvement through CPU consolidation. In addition, this paper also presents new online CPU consolidation algorithms, which reduce the energy-delay product up to 13% compared with the Linux default DVFS algorithm.
Simpler Minimum Enclosing Ball: Fast approximate MEB algorithm for extensive kernel methods

We develop a simple and fast (1 + epsiv)-approximate algorithm for computing the minimum enclosing ball (MEB) of a points set in high dimensional Euclidean space without requirement of any numerical solver. We prove theoretically that the proposed simpler minimum enclosing ball (SMEB) algorithm converges to the optimum within any precision in O(1/epsiv) iterations. Compared to the MEB algorithms adopted in the core vector machines (CVM) and simpler core vector machines (SCVM) recently arisen, it has the competitive performances in both training time and accuracy. Besides, the proposed algorithm does not need any extra requirement of kernels, it can be linked with extensive kernel methods, consequently. We also present the potential application areas for the algorithm theoretically, such as unbalanced SVM and ranking SVM. Experiments demonstrate the validity of the algorithm we proposed.
GUI reverse engineering with machine learning

This paper proposes a new approach to reduce the effort of building formal models representative of the structure and behaviour of Graphical User Interfaces (GUI). The main goal is to automatically extract the GUI model with a dynamic reverse engineering process, consisting in an exploration phase, that extracts information by interacting with the GUI, and in a model generation phase that, making use of machine learning techniques, uses the extracted information of the first step to generate a state-machine model of the GUI, including guard conditions to remove ambiguity in transitions.
Research Issues on Windows Event Log

Due to the rapidly increasing connectivity and dependency over the internet by individuals and corporations to carry out their businesses, security breaches are increasing day by day. Security and privacy are becoming a greater concern for the modern world. The report of loss of critical data, cyber attacks, denial of service attacks, hacking of websites and systems etc. are becoming the headlines in news channels. In this context, log data are very useful as it is used to track the history of an intruder in day to day work and providing evidence for further investigation. Audit log data, which are produced by windows operating systems, are in binary format and are not compatible with the log format of other log sources, which makes the log management very complicated and most challenging. The windows event log stays locally in the host system and the centralization of logging process is not possible due to its distributed design. This paper outlines a brief overview of the various processes involved in the windows event logging environment and stressed to centralize the logging process. This research work implements the Winsyslog server as the central server to centralize the storage of log data and event reporter for translation of windows event log data from binary format to syslog format. The proposed architecture to centralize the storage of log data helps the system administrator in a great way by simplifying the logging process and also enhances the security to log data, which are most important for forensic investigation.
Enhancement of Exopolysaccharide Production of Lactobacillus fermentum TDS030603 by Modifying Culture Conditions

To optimize culture conditions that enhance production of a highly viscous exopolysaccharide of Lactobacillus fermentum TDS030603, a chemically defined medium was examined. The best yield was found to be 199 ± 23 mg/l when 48-hr cultivation was microaerobically performed at 30°C in the chemically defined medium supplemented with 5% glucose and 1% ammonium citrate without pH control. In response to the optimized exopolysaccharide production, the mRNA expression levels of epsB, epsE, and epsG elevated significantly. Our results indicated that the optimal C/N ratio and/or microaerobic condition can alter the expression levels of several exopolysaccharide biosynthesis-related genes promoting the exopolysaccharide production yield.
Preclinically assessed optimal control of postprandial glucose excursions for type 1 patients with diabetes

Type 1 Patients with Diabetes (Type 1 PwDs) have to frequently adjust their insulin dosage to keep their Blood Glucose concentration (BG) within normal bounds. Meal intakes represent the most important disturbance that has to be accounted for. Its effect differs for every individual as well as for every meal. These specificities are automatically taken into account in the approach proposed in this paper. Model parameters are identified for every couple (Patient, Meal) of interest and optimal control is applied to generate individualized meal specific insulin profiles. The method does not require the use of a continuous BG meter, the profiles being infused in an open-loop manner. Results from a preliminary clinical study are presented. The concept is shown to be effective, despite limitations due to the aggressive execution chosen. Improvements are proposed and a possible practical implementation is described.
Combined Gesture-Speech Analysis and Speech Driven Gesture Synthesis

Multimodal speech and speaker modeling and recognition are widely accepted as vital aspects of state of the art human-machine interaction systems. While correlations between speech and lip motion as well as speech and facial expressions are widely studied, relatively little work has been done to investigate the correlations between speech and gesture. Detection and modeling of head, hand and arm gestures of a speaker have been studied extensively and these gestures were shown to carry linguistic information. A typical example is the head gesture while saying "yes/no". In this study, correlation between gestures and speech is investigated. In speech signal analysis, keyword spotting and prosodic accent event detection has been performed. In gesture analysis, hand positions and parameters of global head motion are used as features. The detection of gestures is based on discrete pre-designated symbol sets, which are manually labeled during the training phase. The gesture-speech correlation is modeled by examining the co-occurring speech and gesture patterns. This correlation can be used to fuse gesture and speech modalities for edutainment applications (i.e. video games, 3-D animations) where natural gestures of talking avatars are animated from speech. A speech driven gesture animation example has been implemented for demonstration
Link Peek: A Link Outage Resilient IP Packet Forwarding Mechanism for 6LoWPAN/RPL Based Low-Power and Lossy Networks (LLNs)

Packets traversing through a multi-hop Low-power and Lossy Network (LLN) experience various link outage conditions in transit that can lead to packet loss at an intermediate relay node. Motivated by the problem of providing high Packet Delivery Ratio (PDR) in the LLNs running RPL(Routing Protocol for Low-power and Lossy Networks) routing protocol, we implemented a lightweight add-on functionality to the network layer's packet forwarding mechanism, Link Peek, in which the forwarding node iteratively retransmits the packet to its alternate/next best parent belonging to the same RPL DODAG(Destination Oriented Directed A cyclic Graph) instance whenever IEEE 802.15. 4 MAC layer retransmission count set by our mechanism for the current best parent is exceeded. With this simple reactive and successive retry mechanism, our experimentation has shown significant performance gain in terms of achieving high PDRs, even at higher data rates, over the LLNs under different operating environments. We implemented Link Peek over the Contiki RPL protocol stack. We describe the implementation details and discuss various tunable parameters that affect the network performance. The Cooja simulation and real-world physical test bed experimentation with link outage environment showed PDRs > 99.40% with Link Peek as against the PDRs of 76-90% obtained using the native network stack implementation. Through the experimental results we demonstrate the effectiveness of our approach in supporting higher data rates even in node mobility scenarios.
Linking Microscopic and Macroscopic Models for Evolution: Markov Chain Network Training and Conservation Law Approximations

In this paper, a general framework for the analysis of a connection between the training of artificial neural networks via the dynamics of Markov chains and the approximation of conservation law equations is proposed. This framework allows us to demonstrate an intrinsic link between microscopic and macroscopic models for evolution via the concept of perturbed generalized dynamic systems. The main result is exemplified with a number of illustrative examples where efficient numerical approximations follow directly from network-based computational models, viewed here as Markov chain approximations. Finally, stability and consistency conditions of such computational models are discussed.
Sol–gel synthesis and photoluminescence properties of spherical SiO2@LaPO4:Ce3+/Tb3+ particles with a core–shell structure

LaPO4:Ce3+ and LaPO4:Ce3+, Tb3+ phosphor layers have been deposited successfully on monodispersed and spherical SiO2 particles of different sizes (300, 500, 900 and 1200 nm) through a sol–gel process, resulting in the formation of core–shell structured SiO2@LaPO4:Ce3+/Tb3+ particles. X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), scanning electron microcopy (SEM), transmission electron microscopy (TEM), and general and time-resolved photoluminescence (PL) spectra as well as lifetimes were used to characterize the resulting SiO2@LaPO4:Ce3+/Tb3+ samples. The XRD results demonstrate that the LaPO4:Ce3+, Tb3+ layers begin to crystallize on the SiO2 templates after annealing at 700 °C, and the crystallinity increases on raising the annealing temperature. The obtained core–shell phosphors have perfectly spherical shape with a narrow size distribution, non-agglomeration, and a smooth surface. The doped rare-earth ions show their characteristic emission in the core–shell phosphors, i.e. Ce3+ 5d–4f and Tb3+ 5D4–7FJ (J = 6–3) transitions, respectively. The PL intensity of the Tb3+ increased on increasing the annealing temperature and the SiO2 core particle size. The energy transfer process from Ce3+ to Tb3+ in SiO2@LaPO4:Ce3+, Tb3+ core–shell particles was studied using the time-resolved emission spectra.
Combined evolution strategies for dynamic calibration of video-based measurement systems

Calibration is a crucial step to obtaining 3D measurement using video camera-based stereo systems. All the parameters can be determined except for the pair of principal points, which poses a considerable drawback. Whereas in low-accuracy systems such points can be assumed to lie at the image center without degrading the overall 3D accuracy; in high-accuracy systems their true position must be computed accurately. In this case, all the calibration parameters can still be estimated through epipolar geometry, but it is necessary to minimize a highly nonlinear cost function. It is shown here that by combining two evolutionary optimization strategies this minimization can be carried out, both efficiently and reliably. The resulting strategy, which we call enhanced evolutionary search (EES), allows the full calibration of a stereo system using only a rigid bar. Moreover, EES can be applied to a wide range of applications where the cost function contains complex nonlinear relationships among the optimization variables.
Challenges and solutions in modern analog placement

The analog placement problem is to place devices without overlap and design-rule-correction (DRC) error under position constraints (e.g. symmetry, cluster) such that some cost metric (e.g. area, wirelength) is optimized. However, modern analog design challenges have reshaped the placement problem. A modern analog placer also needs to consider device layout-dependent-effect (LDE) and interconnect parasitic effect. Because of multiple objectives, it is impossible to decide the single best placement. In this paper, we first introduce our placer that can explore multiple placements under position constraints so that a designer can analyze the trade-off among different objectives. Then, we provide some future research directions for the modern analog placement problem.
A Maximum-Entropy Partial Parser for Unrestricted Text

This paper describes a partial parser that assigns syntactic structures to sequences of part-of-speech tags. The program uses the maximum entropy parameter estimation method, which allows a flexible combination of different knowledge sources: the hierarchical structure, parts of speech and phrasal categories. In effect, the parser goes beyond simple bracketing and recognises even fairly complex structures. We give accuracy figures for different applications of the parser.
Intuitive Appliance Identification using Image Matching in Smart Buildings

The number of smart appliances is rapidly increasing to foster the Internet of Things. However, identifying an appliance for interaction in a building is also becoming more confusing. Most work on simplifying contextual appliance identification and selection either requires extra effort from users or infrastructure deployments. In this paper, we present an intuitive system for users to “look up” appliances in a smart building using an image. It constructs an annotated 3D visual model of a building interior using RGB-D cameras and matches a user-provided image on the model to determine the appliances in the image. Our system matched 98% images on a public robot-collected dataset and achieved 100% recall and precision among them. We also deployed the system in our lab with human captured RGB-D videos and images, which have more degrees of freedom and noise than robots. We matched 71% of the images. Of the matched images, 63% of them achieved 80% recall, and 78% achieved 80% precision.
Incentive-based demand response approach for aggregated demand side participation

This paper proposes a novel incentive-based demand response (DR) program that can be utilized by a service provider (SP) to procure capacity resources from its subscribed customers in terms of a load reduction. By providing incentives in advance, the SP can induce customers to participate in the program and voluntarily determine the quantity of load reduction to be sold to the SP. Stackelberg game theory is adopted to capture the interactions between the SP and its customers. The optimal incentives were determined analytically, and each customer's optimal load reduction was also decided accordingly. Simulation results showed that the proposed incentive-based DR approach is effective in determining optimal incentives for an SP to procure the required capacity resources.
The Fate of Hexahydro-1,3,5-Trinitro-1,3,5-Triazine (RDX) and Related Compounds in Anaerobic Denitrifying Continuous Culture Systems Using Simulated Waste Water.

Abstract : This study has demonstrated conclusively that mixtures of compounds present in waste waters resulting from the manufacture of RDX/HMX can be successfully removed in a continuous treatment process provided the system is operated in an anaerobic mode. The present study extends previously reported findings with RDX to HMX and the two acetylated derivatives, AcRDX and AcHMX. Nitrate, in concentrations up to 2400 ppm, is removed by the same continuous system; the lower the E sub h the more efficient the removal. Removal efficiencies were also correlated with TOC(Total Organic Compounds) values, with the eight-membered ring compounds, HMX and AcHMX, being brought up to their highest levels of disappearance by systems having the highest TOC values. This suggests that an anaerobic treatment facility designed to remove these compounds may require the addition of supplemental nutrients to maintain a high efficiency biotransformation. No buildup of transformation products was observed in any of the systems studied. It appeared that if a compound was acted on at all no detectable products remained. From extrapolation of these data it may be expected that treatment of an actual waste stream would be expected to remove all of the RDX and most of the AcRDX, while leaving some percentage of HMX and AcHMX untouched.
Track Routing and Optimization for Yield

In this paper, we propose track routing and optimization for yield (TROY), the first track router for the optimization of yield loss due to random defects. As the probability of failure (POF), which is an integral of the critical area and the defect size distribution, strongly depends on wire ordering, sizing, and spacing, track routing can play a key role in effective wire planning for yield optimization. However, a straightforward formulation of yield-driven track routing can be shown to be integer nonlinear programming, which is a nondeterministic polynomial-time complete problem. TROY overcomes the computational complexity by combining two effective techniques, i.e., the minimum Hamiltonian path (MHP) from graph theory and the second-order cone programming (SOCP) from mathematical optimization. First, TROY performs wire ordering to minimize the critical area for short defects by finding an MHP. Then, TROY carries out optimal wire sizing/spacing through SOCP optimization based on the given wire order. Since the SOCP can be optimally solved in near linear time, TROY efficiently achieves globally optimal wire sizing/spacing for the minimal POF.