Miracle-dz/UniFAR-FTUs huggingface dataset:
Symbolic Anomaly Detection and Assessment Using Growing Neural Gas

Metacognitive architectures provide one solution to the brittleness problem for agents operating in complex, changing environments. The Metacognitive Loop, in which a system notes an anomaly, assesses the problem and guides a solution, is one form of such an architecture. This paper extends prior work on implementing the note phase of this process in symbolic planning domains using the A-distance. This extension uses a growing neural gas algorithm to construct a network which represents various normal and anomalous states. Testing shows that this technique allows for improved detection of anomalies in the note phase as well as categorization of anomalies by severity and type in the assess phase.
Operational Implementation of Sea Ice Concentration Estimates From the AMSR2 Sensor

An operation implementation of a passive microwave sea ice concentration algorithm to support NOAA's operational mission is presented. The NASA team 2 algorithm, previously developed for the NASA advanced microwave scanning radiometer for the Earth observing system (AMSR-E) product suite, is adapted for operational use with the JAXA AMSR2 sensor through several enhancements. First, the algorithm is modified to process individual swaths and provide concentration from the most recent swaths instead of a 24-hour average. A latency (time since observation) field and a 24-hour concentration range (maximum–minimum) are included to provide indications of data timeliness and variability. Concentration from the Bootstrap algorithm is a secondary field to provide complementary sea ice information. A quality flag is implemented to provide information on interpolation, filtering, and other quality control steps. The AMSR2 concentration fields are compared with a different AMSR2 passive microwave product, and then validated via comparison with sea ice concentration from the Suomi visible and infrared imaging radiometer suite. This validation indicates the AMSR2 concentrations have a bias of 3.9% and an RMSE of 11.0% in the Arctic, and a bias of 4.45% and RMSE of 8.8% in the Antarctic. In most cases, the NOAA operational requirements for accuracy are met. However, in low-concentration regimes, such as during melt and near the ice edge, errors are higher because of the limitations of passive microwave sensors and the algorithm retrieval.
Background Selection in Partially Selfing Populations

Self-fertilizing species often present lower levels of neutral polymorphism than their outcrossing relatives. Indeed, selfing automatically increases the rate of coalescence per generation, but also enhances the effects of background selection and genetic hitchhiking by reducing the efficiency of recombination. Approximations for the effect of background selection in partially selfing populations have been derived previously, assuming tight linkage between deleterious alleles and neutral loci. However, loosely linked deleterious mutations may have important effects on neutral diversity in highly selfing populations. In this article, I use a general method based on multilocus population genetics theory to express the effect of a deleterious allele on diversity at a linked neutral locus in terms of moments of genetic associations between loci. Expressions for these genetic moments at equilibrium are then computed for arbitrary rates of selfing and recombination. An extrapolation of the results to the case where deleterious alleles segregate at multiple loci is checked using individual-based simulations. At high selfing rates, the tight linkage approximation underestimates the effect of background selection in genomes with moderate to high map length; however, another simple approximation can be obtained for this situation and provides accurate predictions as long as the deleterious mutation rate is not too high.
Notes on hierarchical ensemble methods for DAG-structured taxonomies

Several real problems ranging from text classification to computational biology are characterized by hierarchical multi-label classification tasks. Most of the methods presented in literature focused on tree-structured taxonomies, but only few on taxonomies structured according to a Directed Acyclic Graph (DAG). In this contribution novel classification ensemble algorithms for DAG-structured taxonomies are introduced. In particular Hierarchical Top-Down (HTD-DAG) and True Path Rule (TPR-DAG) for DAGs are presented and discussed.
Multivariable PID Neural Network based flight control system for small-scale unmanned helicopter

To design the flight control system (FCS) of small-scale unmanned helicopter is still a difficult challenge today. The hardware and software architecture of FCS was designed in this paper. And one novel control approach based on Multivariable PID Neural Network (MPIDNN) was firstly used to design the FCS of small-scale unmanned helicopter on the hardware platform. MPIDNN is suitable for controlling the multi-input multi-output (MIMO), nonlinear, highly coupled, uncertain and dynamic system such as helicopter. Both the training and study algorithm based on target function and MPIDNN forwards algorithm were designed in this control system. The result of simulation indicates that the training algorithm can solve the offline training and study problem of small-scale unmanned helicopter. The forwards algorithm can control the flight of helicopter well and its maximum magnitude of error is about 1%. Simulation shows that the performance of our control approach is perfect.
DLING: A Distributed Mobile Sink Guiding Scheme for Sensor Networks

The energy consumption rates of nodes vary in different positions in sensor networks, leading to the early depletion of the nodes and the disconnection of a network. In this paper, we present a distributed mobile sink guiding scheme (DLING) based on the center of gravity theory in physics. DLING regards the sensor network as an object composed of particles. Sensor nodes act as particles and their residual energy is treated as their "weight". We use the traditional discovering method for the center of gravity to compute the "energy center" of a network. The nodes near the energy center have more residual energy and can afford more traffic load. Then we propose a novel scheme to guide the sink sojourning around the network's center of energy so that the energy consumption of the nodes will be balanced. The simulation results demonstrate that DLING can achieve further improvements on the network lifetime in comparison with previous moving schemes while having low control costs.
The Impact of Cloud Radiative Feedback, Remote ENSO Forcing, and Entrainment on the Persistence of North Pacific Sea Surface Temperature Anomalies

Abstract The influence of cloud radiative feedback, remote ENSO heat flux forcing, and oceanic entrainment on persisting North Pacific sea surface temperature (SST) anomalies is investigated using a stochastically forced ocean mixed layer model. The stochastic heat flux is estimated from an atmospheric general circulation model, the seasonally varying radiative feedback parameter and remote ENSO forcing are obtained from observations, and entrainment is derived from the observed mean seasonal cycle of ocean mixed layer depth. Persistence is examined via SST autocorrelations in the western, central, and subtropical eastern North Pacific and for the leading pattern of variability across the basin. The contribution of clouds, ENSO, and entrainment to SST persistence is evaluated by comparing simulations with and without each term. The SST autocorrelation structure in the model closely resembles nature: the pattern correlation between the two is 0.87–0.9 in the three regions and for the basinwide analyses, an.
Image quality assessment for a selective-processing noise-aided iterative enhancement algorithm

This paper presents a revision of the existing universal image quality index (UIQ) metric in order to gauge the quality of images in a selective-processing iterative enhancement algorithm. The original UIQ is based on factors of loss of correlation, luminance and contrast similarity, and is, therefore, unsuitable in enhancement-related applications. While testing existing state-of-the-art metrics as image quality criterion in an iterative dynamic range compression algorithm, a lack of coherence was observed between the objective scores and that obtained from subjective evaluation study with twenty human subjects. We, therefore, propose to modify the existing UIQ with properties of a tone-mapped image. The proposed variant, named image quality metric for dynamic range compression, IQDRC, maintains the contributing effect of structural correlation and local contrast similarity, but observes an inverse relation with local luminance similarity. The proposed metric was observed to promisingly quantify the image quality and dynamic range compression of such images in close accordance with subjective scores for the target enhancement algorithm. Observations also suggest that IQDRC is indicative of image quality for various other dynamic range compression algorithms.
Delay-Minimal Transmission for Average Power Constrained Multi-Access Communications

We investigate the problem of minimizing the overall transmission delay of packets in a multi-access wireless communication system, where the transmitters have average power constraints. We use a multi-dimensional Markov chain to model the medium access control layer behavior. The state of the Markov chain represents current queue lengths. Our goal is to minimize the average packet delay through controlling the probability of departure at each state, while satisfying the average power constraint for each queue. We consider a general asymmetric system, where the arrival rates to the queues, channel gains and average power constraints of the two users are arbitrary. We formulate the problem as a constrained optimization problem, and then transform it to a linear programming problem. We analyze the linear programming problem, and develop a procedure by which we determine the optimal solution analytically. We show that the optimal policy has a threshold structure: when the sum of the queue lengths is larger than a threshold, both users should transmit a packet during the current slot; when the sum of the queue lengths is smaller than a threshold, only one of the users, the one with the longer queue, should transmit a packet during the current slot. We provide numerical examples for both symmetric and asymmetric settings.
Testing of a treatment planning system with beam data from IAEA TECDOC 1540

Quality assurance of external-beam treatment-planning systems is recommended, and this can be partly achieved with predefined type tests. The beam data and test geometries of IAEA TECDOC 1540 have been used to test the analytical anisotropic algorithm (AAA) and pencil-beam convolution (PBC) algorithm of the Varian Eclipse treatment planning system. Beam models were created in Eclipse for 6 MV, 10 MV and 18 MV from the available beam data. Twelve test geometries were re-created in Eclipse, and the differences between Eclipse dose calculations and dose measurements were recorded. The AAA algorithm generally performed better than the PBC algorithm for the 12 tests, but both algorithms did not meet predefined tolerances for asymmetric wedge fields. An in-house monitor unit check program based on collimator and phantom scatter factors with tissue-phantom ratios was also tested and its calculations were found to agree with measurements to within 3.2% for on-axis points.
Propositional dynamic logic with Belnapian truth values

We introduce BPDL, a combination of propositional dynamic logic PDL with the basic four-valued modal logic BK studied by Odintsov and Wansing (`Modal logics with Belnapian truth values', J. Appl. Non-Class. Log. 20, 279--301 (2010)). We modify the standard arguments based on canonical models and filtration to suit the four-valued context and prove weak completeness and decidability of BPDL.
Alternative Splicing of SLC39A14 in Colorectal Cancer is Regulated by the Wnt Pathway*

Alternative splicing is a crucial step in the generation of protein diversity and its misregulation is observed in many human cancer types. By analyzing 143 colorectal samples using exon arrays, SLC39A14, a divalent cation transporter, was identified as being aberrantly spliced in tumor samples. SLC39A14 contains two mutually exclusive exons 4A and 4B and the exon 4A/4B ratio was significantly altered in adenomas (p = 3.6 × 10−10) and cancers (p = 9.4 × 10−11), independent of microsatellite stability status. The findings were validated in independent exon array data sets and by quantitative real-time reverse-transcription PCR (qRT-PCR). Aberrant Wnt signaling is a hallmark of colorectal tumorigenesis and is characterized by nuclear β-catenin. Experimental inactivation of Wnt signaling in DLD1 and Ls174T cells by knockdown of β-catenin or overexpression of dominant negative TCFs (TCF1 and TCF4) altered the 4A/4B ratio, indicating that SLC39A14 splicing is regulated by the Wnt pathway. An altered 4A/4B ratio was also observed in gastric and lung cancer where Wnt signaling is also known to be aberrantly activated. The splicing factor SRSF1 and its regulator, the kinase SRPK1, were found to be deregulated upon Wnt inactivation in colorectal carcinoma cells. SRPK1 was also found up-regulated in both adenoma samples (p = 1.5 × 10−5) and cancer samples (p = 5 × 10−4). In silico splicing factor binding analysis predicted SRSF1 to bind predominantly to the cancer associated exon 4B, hence, it was hypothesized that SRPK1 activates SRSF1 through phosphorylation, followed by SRSF1 binding to exon 4B and regulation of SLC39A14 splicing. Indeed, siRNA-mediated knockdown of SRPK1 and SRSF1 in DLD1 and SW480 colorectal cancer cells led to a change in the 4A/4B isoform ratio, supporting a role of these factors in the regulation of SLC39A14 splicing. In conclusion, alternative splicing of SLC39A14 was identified in colorectal tumors and found to be regulated by the Wnt pathway, most likely through regulation of SRPK1 and SRSF1.
Measurement of total body water using 2H dilution: impact of different calculations for determining body fat

This study estimated total body water (TBW) in four groups (twelve per group; sedentary and highly trained men and women) at the time of 2H dosing (T0) and after a 3·5 h equilibration period (Teq). Standard TBW calculations were employed at T0 (no correction for disproportionate urinary tracer loss) and Teq (correction for urinary tracer loss only), plus those calculations that corrected for a disproportionate urinary tracer loss and insensible tracer loss respectively. The measurement of body density enabled the four TBW estimates to be compared for the determination of three-compartment % body fat (BF). The very small difference between the standard and corrected T0 TBW data was not significant (P=0·914) and no Group×TBW interaction was identified (P=0·125). These results reflect the closeness of the 2H concentration in the urine produced during the equilibration period and the Teq saliva samples. The associated mean % BF values were essentially identical. Although correcting for insensible 2H losses in addition to urinary losses at Teq produced a statistically significant (P<0·001) lower mean TBW (about 200 g) than the standard calculation, this translated to a small difference in % BF (0·3). The larger difference (about 500 g, P<0·001) between the two (T0, Teq) corrected TBW calculations was also associated with a small body composition difference (0·1 % BF), which was less than the propagated error (0·3 % BF) for the three-compartment body composition model. Corrections to the standard calculations of TBW at T0 and Teq for a protocol employing a brief equilibration period (3·5 h) were therefore of marginal use for improving the accuracy of % BF estimates. The TBW difference over time (T0v. Teq) also had little impact on % BF values.
Efficient Liquid Media for Encystation of Pathogenic Free-Living Amoebae

Pathogenic Naegleria fowleri, Acanthamoeba castellanii, and Acanthamoeba polyphaga, are distributed worldwide. They are causative agents of primary amoebic meningoencephalitis or acanthamoebic keratitis in humans, respectively. Trophozoites encyst in unfavorable environments, such as exhausted food supply and desiccation. Until recently, the method of N. fowleri encystation used solid non-nutrient agar medium supplemented with heat-inactivated Escherichia coli; however, for the amoebic encystment of Acanthamoeba spp. , a defined, slightly modified liquid media is used. In this study, in order to generate pure N. fowleri cysts, a liquid encystment medium (buffer 1) modified from Page’s amoeba saline was applied for encystation of N. fowleri. N. fowleri cysts were well induced after 24 hr with the above defined liquid encystment medium (buffer 1). This was confirmed by observation of a high expression of differential mRNA of nfa1 and actin genes in trophozoites. Thus, this liquid medium can replace the earlier non-nutrient agar medium for obtaining pure N. fowleri cysts. In addition, for cyst formation of Acanthamoeba spp. , buffer 2 (adjusted to pH 9.0) was the more efficient medium. To summarize, these liquid encystment media may be useful for further studies which require axenic and pure amoebic cysts.
On the Capacity of SWIPT Systems with a Nonlinear Energy Harvesting Circuit

In this paper, we study information-theoretic limits for simultaneous wireless information and power transfer (SWIPT) systems employing a practical nonlinear radio frequency (RF) energy harvesting (EH) receiver. In particular, we consider a three-node system with one transmitter that broadcasts a common signal to separated information decoding (ID) and EH receivers. Owing to the nonlinearity of the EH receiver circuit, the efficiency of wireless power transfer depends significantly on the waveform of the transmitted signal. In this paper, we aim to answer the following fundamental question: What is the optimal input distribution of the transmit waveform that maximizes the rate of the ID receiver for a given required harvested power at the EH receiver? In particular, we study the capacity of a SWIPT system impaired by additive white Gaussian noise (AWGN) under average-power (AP) and peak-power (PP) constraints at the transmitter and an EH constraint at the EH receiver. Using Hermite polynomial bases, we prove that the optimal capacityachieving input distribution that maximizes the rate-energy region is unique and discrete with a finite number of mass points. Our numerical results show that the rate-energy region is enlarged for a larger PP constraint and that the rate loss of the considered SWIPT system compared to the AWGN channel without EH receiver is reduced by increasing the AP budget.
DMT of Multi-hop Cooperative Networks - Part II: Half-Duplex Networks with Full-Duplex Performance

We consider single-source single-sink (ss-ss) multi-hop relay networks, with slow-fading links and single-antenna half-duplex relay nodes. In a companion paper, we established some basic results which laid the foundation for the results presented here. In the present paper, we consider two families of networks of half-duplex networks. KPP networks may be viewed as the union of K node-disjoint parallel relaying paths. Generalizations of these networks include KPP(I) networks, which permit interference between paths and KPP(D) networks, which possess a direct link between source and sink. We characterize the DMT of these families of networks completely and show that they can achieve the cut-set bound, thus proving that full-duplex performance can be obtained even in the presence of the half-duplex constraint. We then consider layered networks, and prove that a linear DMT between maximum diversity and maximum multiplexing gain is achievable. All protocols in this paper are explicit and use only amplify-and-forward relaying. We also construct codes that achieve the optimal DMT for all the proposed schemes. Two key implications of the results in the paper are that the half-duplex constraint does not entail any rate loss for a large class of cooperative networks and that AF protocols are often optimal.
Analysis of shape-memory polymer composites with embedded microvascular system for fast thermal response

The microvascular strategy demonstrates unique advantages in shape-memory polymer applications as it can achieve both rapid thermal activation and deactivation during a typical shape-memory cycle. In addition, localized overheating can be avoided in comparison with other heating methods, such as the magnetic and electric heating. In this paper, a finite-element-based computational analysis was performed to study the rapid thermal response of shape-memory polymer composites with an embedded microvascular system. We show that the polymer shape-fixing speed, the shape fixity after a given cooling time, and the shape-recovery rate are significantly enhanced due to the rapid cooling and heating effect of internal microvasculature. The effect of the composite dimensions and microvascular channel arrangement on the activation and deactivation was studied. Typically, reducing the composite thickness and tube spacing increases the shape-recovery speed of the shape-memory polymer composite by effectively reducing the length of the thermal conduction pathways. Strategies for achieving an optimized tube arrangement were also discussed based on the considerations of the system mass and thermal boundary conditions. The results in this paper provide a guideline for further designs and applications of shape-memory polymer composites with embedded microvasculature.
Dyadic attribution model: A mechanism to assess trustworthiness in virtual organizations

Language as a symbolic medium plays an important role in virtual communications. In a primarily linguistic environment such as cyberspace, words are an expressed form of intent and actions. We investigate the functions of words and actions in identifying behavioral anomalies of social actors to safeguard the virtual organization. Social actors are likened to “sensors” as they observe changes in a focal individual's behavior during computer‐mediated communications. Based on social psychology theories and pragmatic views of words and actions in online communications, we theorize a dyadic attribution model that helps make sense of anomalous behavior in creative online experiments. This model is then tested in an experiment. Findings show that observation of the behavioral differences between words and actions, based on either external or internal causality, can offer increased ability to detect the compromised trustworthiness of observed individuals—possibly leading to early detection of insider threat potential. The dyadic attribution model developed in this sociotechnical study can function to detect behavioral anomalies in cyberspace, and protect the operations of a virtual organization.
GRS 1915+105 and the Disc-Jet Coupling in Accreting Black Hole Systems

▪ Abstract GRS 1915+105—the first stellar-scale, highly relativistic jet source identified—is a key system for our understanding of the disc-jet coupling in accreting black hole systems. Comprehending the coupling between inflow and outflow in this source not only is important for X-ray binary systems but has a broader relevance for studies of active galactic nuclei and gamma-ray bursts. In this paper, we present a detailed review of the observational properties of the system, as established in the decade since its discovery. We attempt to place it in context by a detailed comparison with other sources, and construct a simple model for the disc-jet coupling, which may be more widely applicable to accreting black hole systems.