Presence Of Target Research Articles

Superstitious Perception: Comparing Perceptual Prediction by Humans and Neural Networks.

Recent developments in convolutional neural networks (CNNs) have introduced new ways to model the complex processes of human vision. To date, the comparison of human vision and CNNs has focused on internal representations (i.e., receptive fields), with behavioral comparisons left largely unexplored. Here, we probe the influence of cognitive strategy on the similarity between CNN output and human behavior. We gave study participants a superstitious perception task (i.e., we asked them to detect an assigned target in white noise) while asking them to engage in either an active or passive attentional strategy. Previous research has shown that an active attentional strategy tends to engage central executive functions, whereas a passive strategy allows perceptual processes to unfold with limited central control. The results showed that the pattern of human responses in the superstitious perception task depended significantly on task strategy. Specifically, detecting targets superstitiously (i.e., false alarms) was correlated with evidence of a target's presence in the passive condition, but not in the active condition.Human data were compared to the performance of a CNN performing the same task, with the decision criterion of the CNN set to match the false alarm rates observed in the two strategy conditions of the human participants. CNN responses resembled those of human participants in the passive condition more closely than those in the active condition. This observation suggests that the CNN does a better job of mimicking human behavior when central executive functions are not engaged than when they are engaged. This, in turn, has important implications for what human participants are doing in the superstitious perception task. Namely, it implies that superstitious perception may have two important ingredients that are somewhat dissociable. First, there is the ability to detect weak signals in noise that correspond to the target image. This appears to be what participants are doing under passive strategy conditions; they allow externally generated signals to dominate their perceptual experience. Second, there is the ability to ignore the noise in favor of basing responses solely on internally generated signals. This seems to correspond more closely to what participants are doing under active strategy conditions, when attention is controlled by representations in memory. This research emphasizes the importance of modeling the full range of human responsiveness in even a simple noisy detection task.

Improved Target Acquisition Rates With Feedback Codes

This paper considers the problem of acquiring an unknown target location (among a finite number of locations) via a sequence of measurements, where each measurement consists of simultaneously probing a group of locations. The resulting observation consists of a sum of an indicator of the target's presence in the probed region, and a zero mean Gaussian noise term whose variance is a function of the measurement vector. An equivalence between the target acquisition problem and channel coding over a binary input additive white Gaussian noise (BAWGN) channel with state and feedback is established. Utilizing this information theoretic perspective, a two-stage adaptive target search strategy based on the sorted Posterior Matching channel coding strategy is proposed. Furthermore, using information theoretic converses, the fundamental limits on the target acquisition rate for adaptive and non-adaptive strategies are characterized. As a corollary to the non-asymptotic upper bound of the expected number of measurements under the proposed two-stage strategy, and to non-asymptotic lower bound of the expected number of measurements for optimal non-adaptive search strategy, a lower bound on the adaptivity gain is obtained. The adaptivity gain is further investigated in different asymptotic regimes of interest.

Artificial Pancreas: from Control-to-Range to Control-to-Target

In the last decade, control algorithms designed for Artificial Pancreas (AP) systems were characterized by significant progresses. In particular, the Control-to-Range Model Predictive Control (MPC) showed its effectiveness and safety in several real life studies. Recent studies on model individualization and the enhanced quality of glucose sensors further improved the efficacy of MPC, thus allowing moving from a Control-to-Range to a Control-to-Target approach. In this study, an integral action in the MPC approach (IMPC) is proposed. This ensures beneficial effects in terms of regulation to the target in presence of disturbances such as delays, pump limitation and model uncertainties. The integral action is even more important when model individualization is performed since, during the identification phase, it allows to focus on the identification of the dynamical part of the model rather than to the static gain. The patient models considered in this contribution have been identified through a constrained optimization approach. A procedure for tuning the IMPC aggressiveness by considering both the glucose control performance and the integral of the error with respect to the target is described. Finally, in silico experiments are presented to assess the effectiveness of the proposed IMPC.

Passive beamforming with coprime arrays

Coprime arrays have been recently proposed as effective sparse configurations suitable for radar beamforming and angle-of-arrival estimation applications. In this study, a new approach for passive beamforming using coprime arrays is presented. In particular, a new detection strategy is proposed, which outperforms the coprime processors presently available in the literature, both in terms of peak sidelobe ratio and integrated sidelobe ratio, without giving rise to ‘ghost’ targets in presence of multiple interferers. The advantage of the proposed detector is demonstrated through the simulation of appropriate array scanned responses and receiver operating characteristic curves.

Adaptive Radar Detectors for Point-Like Gaussian Targets in Gaussian Noise

We address the problem of adaptive radar detection of point-like targets in presence of Gaussian noise with unknown spectral properties, adopting a “second-order approach” to target modeling. In fact, the presence of a useful signal is modeled in terms of a rank-1 modification of the noise covariance matrix, similarly for the possible presence of a fictitious signal under the null hypothesis, aimed at increasing the selectivity of the detector. A set of homogeneous training data is assumed to be available. Results show that the proposed detectors can outperform natural competitors, especially assuming a limited number of training data.

Exploring the Mechanisms Underlying Exercise-Induced Changes in Natural Killer Cell Cytotoxicity

Natural Killer (NK) cells are cytotoxic effectors of the innate immune system that eliminate tumor cells. We have previously shown that NK cell cytotoxicity (NKCA) is enhanced by acute bouts of exercise. However, the mechanisms underlying exercise-induced changes in NKCA are not yet fully understood. Exercise-induced mobilization of highly cytotoxic NK cell subsets has been proposed as one mechanism. Alternatively, exercise increases glucocorticoid and cytokines levels, which have also been shown to alter NKCA. PURPOSE: To examine the role of shifts in proportions of NK cell subsets, cytokines, and hormones on exercise induced changes in NKCA. METHODS: Adults (n=13) cycled 30 min at 115% of their lactate threshold power. Blood was collected pre, post, and 1h post exercise. Effector cells isolated from blood were incubated with K562 or U266 tumor target cells in the presence of autologous serum. NKCA was assessed after 4h by measuring lysed target cells in a flow cytometry based assay. To investigate the effects of factors (hormones and cytokines) released during exercise, pre exercise effectors were incubated with targets in the presence of pre, post, and 1h post exercise serum. The effect of shifts in NK cell subsets was determined by incubating pre, post and 1H post exercise cells with targets in presence of pre exercise serum. We also tested the cytotoxicity of pre, post, and 1h post effectors incubated with serum from the corresponding time point. RESULTS: Autologous pre, post, and 1h post exercise serum did not cause tumor cell lysis in the absence of effectors. The cytotoxicity of pre exercise effector cells was significantly increased against U266 target cells when incubated in 1h post exercise serum (Pre vs. post vs.1H post =0.318±.039 vs. 0.334±.039 vs. 0.438±.039, p<0.05). There was no difference in cytotoxicity of pre, post, 1h post effectors incubated with pre-exercise serum (Pre vs. post vs.1H post =0.321±.046 vs. 0.282±.047 vs. 0.323±.047, p<0.05). CONCLUSION: 1h post exercise serum enhanced resting NK cell cytotoxicity, indicating that factors present in serum after acute exercise can prime effector cell function. Future work will identify levels of glucocorticoids and cytokines present in 1h post exercise serum.

Target-present guessing as a function of target prevalence and accumulated information in visual search.

Target prevalence influences visual search behavior. At low target prevalence, miss rates are high and false alarms are low, while the opposite is true at high prevalence. Several models of search aim to describe search behavior, one of which has been specifically intended to model search at varying prevalence levels. The multiple decision model (Wolfe & Van Wert, Current Biology, 20(2), 121--124, 2010) posits that all searches that end before the observer detects a target result in a target-absent response. However, researchers have found very high false alarms in high-prevalence searches, suggesting that prevalence rates may be used as a source of information to make "educated guesses" after search termination. Here, we further examine the ability for prevalence level and knowledge gained during visual search to influence guessing rates. We manipulate target prevalence and the amount of information that an observer accumulates about a search display prior to making a response to test if these sources of evidence are used to inform target present guess rates. We find that observers use both information about target prevalence rates and information about the proportion of the array inspected prior to making a response allowing them to make an informed and statistically driven guess about the target's presence.

Parameters of supersonic astrophysically-relevant plasma jets collimating via poloidal magnetic field measured by x-ray spectroscopy method

Application of external magnetic field to a laser-generated plasma flows allows to investigate stable, large aspect ratio plasma jets which are relevant to a number of astrophysical cases. In the experiment with 0.6 ns, 40 J laser pulses focused to 700 μm focal spot at solid CF2 target in presence of 20 T poloidal magnetic field the parameters of the plasma jet were studied by means of spatially resolved x-ray spectroscopy. Focusing spectrometer with spatial resolution was used to record the temporally-integrated x-ray emission spectra of the plasma with spatial resolution along the jet propagation. Using the relative intensities of spectral lines emitted by F He-like ions, the electron temperature Te and density Ne profiles of the plasma are obtained. It is shown that Ne decreases monotonically in the case without B-field, but demonstrates an extended density profile up to 10 mm when 20 T magnetic field is applied. Ne values are consistent with that observed via interferometry diagnostics, thus providing the confidence in our x-ray spectroscopy analysis techniques.

Multicenter evaluation of analytical characteristics of the Elecsys® Periostin immunoassay

ObjectiveThe multifunctional cytokine IL-13 is thought to play a central role in Type 2 inflammation in asthma. Serum periostin has been explored as a candidate biomarker for evaluating IL-13 activity in the airway. We describe the technical performance characteristics of a novel, fully automated immunoassay for the determination of periostin in serum. Design and methodsLimit of blank [LoB], limit of detection [LoD] and limit of quantitation [LoQ], linearity, precision and reproducibility across sites and lots were evaluated according to Clinical and Laboratory Standards Institute guidelines. Interferences and sample stability were also investigated. ResultsThe pre-specified values for LoB (2ng/mL), LoD (4ng/mL) and LoQ (10ng/mL) were met. The assay was linear throughout the measuring range (10–160ng/mL) with recoveries within ±10% of target at concentrations >30ng/mL and within ±3ng/mL at concentrations ≤30ng/mL. Recovered periostin concentrations were also within ±10% of target in presence of 43 potentially interfering substances and drugs. Samples were stable across various storage conditions and durations (24h at room temperature, 7days at 4°C, 12weeks at −20°C, and 3 freeze/thaw cycles). Repeatability experiments resulted in CVs across samples and controls ranging from 0.9–1.5%. Intermediate precision was 1.2–1.7% and reproducibility including 3 testing sites and 3 reagent lots was 1.7–3.1%. The final assay correlates to the assay version used in previous clinical trials (Pearson's r=0.998, bias at 50ng/mL=1.2%). ConclusionThe performance evaluation of the Elecsys® Periostin immunoassay including a multicenter precision analysis demonstrated that the assay is suitable for measuring serum periostin at clinically important concentrations around 50ng/mL.

Saliency histogram equalisation and its application to image resizing

This study presents a novel method for content-aware image resizing based on the normalised saliency map of an image termed saliency histogram (SH), which provides the probability of a target's presence in the spatial location domain. Motivated by the idea of spreading the histogram of an image on the grey scale known as image histogram equalisation for contrast enhancement, fast SH equalisation (SHE) has been proposed to distribute the content of an image in the resized image domain similarly. Experimental results show that SHE has a tendency to protect salient foreground objects, and it takes only fractions of a second to resize an 1024 × 768 image.

Differential effects of visual uncertainty and contextual guidance on perceptual decisions: Evidence from eye and mouse tracking in visual search.

Visual search can be seen as a decision-making process that aims to assess whether a target is present or absent from a scene. In this perspective, eye movements collect evidence related to target detection and verification to guide the decision. We investigated whether, in real-world scenes, target detection and verification are differentially recruited in the decision-making process in the presence of prior information (expectations about target location) and perceptual uncertainty (noise). We used a mouse-tracking methodology with which mouse trajectories unveil components of decision-making and eye-tracking measures reflect target detection and verification. Indoor scenes were presented, including a target in usual or unusual locations or no target, and were degraded with additive noise (or no noise). Participants had to respond to the target's presence or absence. Degrading the scene delayed the decision due to increased verification times and reduced mouse velocity. Targets in unusual locations delayed the decision and deviated mouse trajectories toward the target-absent response. Detection times played a major role in these effects. Thus, target detection and verification processes influence decision-making by integrating the available sources of information differently and lead to an accumulation of evidence toward both the presence of a target and its absence.

Enhanced photoresponse of Cu2ZnSn(S, Se)4 based photodetector in visible range

Fast switching response of photodetectors is needed for many applications. Therefore, it is necessary to study the photoconductivity properties of earth abundant and cost effective materials. Till now, there are only two reports based on photoconductivity study of Cu2ZnSnS4(CZTS) based materials. In this study, CZTSSe thin film on soda-lime glass substrate was deposited using one-step reactive sputtering from CZTSe target in presence of H2S followed by annealing. Optical, structural, morphological and elemental compositional analyses were carried out to characterize the CZTSSe thin film. The value of optical band gap estimated using Tauc's plot was 1.45 eV. The presence of very intense peak corresponding to (112) plane in the XRD pattern suggested growth to be oriented. Similar was the case with Raman studies. Photoconductivity study of CZTSSe thin film in visible region (excitation wavelength – 532 nm) is carried out. At a bias voltage of 5 V, response rise time and decay time in visible range for CZTSSe were 330 ms and 0.986 ms, respectively. The values of responsivity, detectivity, sensitivity (Ilight/Idark) and external quantum efficiency were 14.6 mA/W, 3.5 × 109 Jones, 6.9363 and 3.5%, respectively. The shortest reported response decay time by CZTSSe based photodetector is the novelty of this work. This work shows the possibility of utilizing CZTSSe thin film as photodetector for various applications.

Decision support approaches for cyber security investment

When investing in cyber security resources, information security managers have to follow effective decision-making strategies. We refer to this as the cyber security investment challenge.In this paper, we consider three possible decision support methodologies for security managers to tackle this challenge. We consider methods based on game theory, combinatorial optimisation, and a hybrid of the two. Our modelling starts by building a framework where we can investigate the effectiveness of a cyber security control regarding the protection of different assets seen as targets in presence of commodity threats. As game theory captures the interaction between the endogenous organisation's and attackers' decisions, we consider a 2-person control game between the security manager who has to choose among different implementation levels of a cyber security control, and a commodity attacker who chooses among different targets to attack. The pure game theoretical methodology consists of a large game including all controls and all threats. In the hybrid methodology the game solutions of individual control-games along with their direct costs (e.g. financial) are combined with a Knapsack algorithm to derive an optimal investment strategy. The combinatorial optimisation technique consists of a multi-objective multiple choice Knapsack based strategy. To compare these approaches we built a decision support tool and a case study regarding current government guidelines. The endeavour of this work is to highlight the weaknesses and strengths of different investment methodologies for cyber security, the benefit of their interaction, and the impact that indirect costs have on cyber security investment. Going a step further in validating our work, we have shown that our decision support tool provides the same advice with the one advocated by the UK government with regard to the requirements for basic technical protection from cyber attacks in SMEs.

Tribological development of TiCN coatings by adjusting the flowing rate of reactive gases

TiCN coatings were deposited by means of direct current magnetron sputtering of Ti targets in presence of N2 and C2H2 reactive gases. The microstructure, composition, mechanical and tribological properties of the deposited thin films were analyzed by using X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), nanoindentation, ball-on-disc, scratch test, and three dimensional (3D) optical microscopy. The obtained results presents a reproducible processing route for tailoring microstructure, mechanical and tribological behavior of TiCN coatings by controlling flowing rate of the reactive gases.

ABORT-Like Detectors: A Bayesian Approach

In this paper, we deal with the problem of adaptive radar detection of point-like targets in presence of noise with unknown spectral properties. As customary, we assume that a set of data sharing the same properties of the noise in the cell under test is available. To cope with a limited number of training data, a Bayesian framework is adopted at the design stage. In order to come up with detectors with good rejection capabilities, the possible presence of a fictitious signal under the null hypothesis is modeled probabilistically, as opposite to the conventional ABORT-like approach. Several detectors are devised for the problem at hand, with different complexities. The performance assessment, conducted by means of Monte Carlo simulations, reveals that a good trade-off between detection power and selectivity can be achieved, even assuming a limited number of training data.

A Tunable W-ABORT-Like Detector with Improved Detection vs Rejection Capabilities Trade-Off

Adaptive radar detection of point-like targets in presence of disturbance with unknown spectral properties is addressed. By relaxing the assumptions of the W-ABORT, a tunable detector with improved detection vs rejection trade-off is proposed. To this aim, the presence of a fictitious signal under the null hypothesis is modeled probabilistically, so that an additional degree of freedom is introduced in the statistic of the detector. The resulting parametric GLRT shows a range of possible behaviors, from Kelly's detector to the plain W-ABORT. Monte Carlo simulations reveal that an improved compromise can be obtained. Simple closed-form approximations are also given with near-optimal performance, so that the ultimate computational complexity remains comparable to that of the W-ABORT.

ABORT-Like Detection Strategies to Combat Possible Deceptive ECM Signals in a Network of Radars

We address adaptive detection of coherent signals backscattered by possible point-like targets in presence of thermal noise, clutter, noise-like interferers and, possibly, coherent interferers, i.e., deceptive electronic countermeasure (ECM). To this end, we assume a network of radars: for a given cell under test only a subset of the radars receives ECM signals. Training data containing thermal noise, clutter, and noise-like interferers are available. The problem at hand is solved resorting to the generalized likelihood ratio test (GLRT) and to ad hoc solutions: at the design stage we assume that data collected by the radars can be noise only (namely, thermal noise, clutter, and possible noise-like interferers) plus possible coherent interferers or noise plus coherent useful signal. The performance assessment shows that the proposed solutions are effective in presence of ECM systems.

A novel method using blinatumomab for efficient, clinical-grade expansion of polyclonal T cells for adoptive immunotherapy.

Current treatment of chronic lymphocytic leukemia (CLL) patients often results in life-threatening immunosuppression. Furthermore, CLL is still an incurable disease due to the persistence of residual leukemic cells. These patients may therefore benefit from immunotherapy approaches aimed at immunoreconstitution and/or the elimination of residual disease following chemotherapy. For these purposes, we designed a simple GMP-compliant protocol for ex vivo expansion of normal T cells from CLL patients' peripheral blood for adoptive therapy, using bispecific Ab blinatumomab (CD3 × CD19), acting both as T cell stimulator and CLL depletion agent, and human rIL-2. Starting from only 10 ml CLL peripheral blood, a mean 515 × 10(6) CD3(+) T cells were expanded in 3 wk. The resulting blinatumomab-expanded T cells (BET) were polyclonal CD4(+) and CD8(+) and mostly effector and central memory cells. The Th1 subset was slightly prevalent over Th2, whereas Th17 and T regulatory cells were <1%. CMV-specific clones were detected in equivalent proportion before and after expansion. Interestingly, BET cells had normalized expression of the synapse inhibitors CD272 and CD279 compared with starting T cells and were cytotoxic against CD19(+) targets in presence of blinatumomab in vitro. In support of their functional capacity, we observed that BET, in combination with blinatumomab, had significant therapeutic activity in a systemic human diffuse large B lymphoma model in NOD-SCID mice. We propose BET as a therapeutic tool for immunoreconstitution of heavily immunosuppressed CLL patients and, in combination with bispecific Ab, as antitumor immunotherapy.

Identification of Novel Regulatory Small RNAs in Acinetobacter baumannii

Small RNA (sRNA) molecules are non-coding RNAs that have been implicated in regulation of various cellular processes in living systems, allowing them to adapt to changing environmental conditions. Till date, sRNAs have not been reported in Acinetobacter baumannii (A. baumannii), which has emerged as a significant multiple drug resistant nosocomial pathogen. In the present study, a combination of bioinformatic and experimental approach was used for identification of novel sRNAs. A total of 31 putative sRNAs were predicted by a combination of two algorithms, sRNAPredict and QRNA. Initially 10 sRNAs were chosen on the basis of lower E- value and three sRNAs (designated as AbsR11, 25 and 28) showed positive signal on Northern blot. These sRNAs are novel in nature as they do not have homologous sequences in other bacterial species. Expression of the three sRNAs was examined in various phases of bacterial growth. Further, the effect of various stress conditions on sRNA gene expression was determined. A detailed investigation revealed differential expression profile of AbsR25 in presence of varying amounts of ethidium bromide (EtBr), suggesting that its expression is influenced by environmental or internal signals such as stress response. A decrease in expression of AbsR25 and concomitant increase in the expression of bioinformatically predicted targets in presence of high EtBr was reverberated by the decrease in target gene expression when AbsR25 was overexpressed. This hints at the negative regulation of target genes by AbsR25. Interestingly, the putative targets include transporter genes and the degree of variation in expression of one of them (A1S_1331) suggests that AbsR25 is involved in regulation of a transporter. This study provides a perspective for future studies of sRNAs and their possible involvement in regulation of antibiotic resistance in bacteria specifically in cryptic A. baumannii.

Modeling and analysis of exhaustive probabilistic search

AbstractThis article explores a probabilistic formulation for exhaustive search of a bounded area by a single searcher for a single static target. The searcher maintains an aggregate belief of the target's presence or absence in the search area, concluding with a positive or negative search decision on crossing of decision thresholds. The measure of search performance is defined as the expected time until a search decision is made as well as the probability of the search decision being correct. The searcher gathers observations using an imperfect detector, that is, one with false positive and negative errors, and integrates them in an iterative Bayesian manner. Analytic expressions for the Bayesian update recursion of the aggregate belief are given, with theoretical results describing the role of positive and negative detections, as well as sensitivity results for the effect of the detection errors on the aggregate belief evolution. Statistical studies via design of simulation experiments provide insights into the significant search parameters, including imperfect sensor characteristics, initial belief value, search decision threshold values, and the available prior probability information. Regression analysis yields statistical models to provide prescriptive guidance on the search performance as a function of these search parameters.Copyright © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 164–178, 2014