Negative Input Research Articles

A comprehensive model for the proliferation–quiescence decision in response to endogenous DNA damage in human cells

Human cells that suffer mild DNA damage can enter a reversible state of growth arrest known as quiescence. This decision to temporarily exit the cell cycle is essential to prevent the propagation of mutations, and most cancer cells harbor defects in the underlying control system. Here we present a mechanistic mathematical model to study the proliferation-quiescence decision in nontransformed human cells. We show that two bistable switches, the restriction point (RP) and the G1/S transition, mediate this decision by integrating DNA damage and mitogen signals. In particular, our data suggest that the cyclin-dependent kinase inhibitor p21 (Cip1/Waf1), which is expressed in response to DNA damage, promotes quiescence by blocking positive feedback loops that facilitate G1 progression downstream of serum stimulation. Intriguingly, cells exploit bistability in the RP to convert graded p21 and mitogen signals into an all-or-nothing cell-cycle response. The same mechanism creates a window of opportunity where G1 cells that have passed the RP can revert to quiescence if exposed to DNA damage. We present experimental evidence that cells gradually lose this ability to revert to quiescence as they progress through G1 and that the onset of rapid p21 degradation at the G1/S transition prevents this response altogether, insulating S phase from mild, endogenous DNA damage. Thus, two bistable switches conspire in the early cell cycle to provide both sensitivity and robustness to external stimuli.

Hybrid efficiency measurement and target setting based on identifying defining hyperplanes of the PPS with negative data

The traditional data envelopment analysis (DEA) models can be used for efficiency evaluation of decision making units (DMUs) with nonnegative data. However, in the real world there are DMUs which have negative inputs and/or outputs. Consequently, in the literature of DEA various approaches have been offered in order to deal with negative data. The current research proposes an algorithm concerned with a pure mathematical optimization method to measure hybrid efficiency of DMUs in the presence of negative data, and also a pure mathematical procedure for target setting. In doing so, explicit form equations of strong and weak defining hyperplanes of production possibility set (PPS) based on the multiple criteria decision making methodology are obtained. In characterizing these hyperplanes, a new multiple objective linear programming (MOLP) problem is presented whose feasible region of criterion space is similar to the PPS with variable returns to scale technology on nonnegative and negative data. The MOLP problem is solved using the multicriteria simplex method where its process of solving leads to construct all strong and weak defining hyperplanes. Then, using the strong and weak hyperplanes obtained and also without using any DEA optimization model, a hybrid measure of efficiency and a strong efficient target unit for each inefficient DMU with negative data are obtained. Finally, the results are discussed using two examples, where the first one, in detail, explains the proposed methods and algorithm, and the second one briefly shows the contributions are applicable for the real data.

Passive Damper Network in a Simple DC Distribution Power System

Distributed power system (DPS) distributes power amongst processing units such as power electronics converters with DC system. Due to the increasing usage of power converters in DPS system, the system becomes unstable and the converter tends to draw constant power needed by the load of the system. Constant power load (CPL) characteristic has negative input impedance that could produce instability problems in the DC bus system. Passive damping network which consists of series RC damping circuit was connected in parallel to the DC bus system with the purpose to reduce the instability. The passive damper was designed, simulated with MATLAB/Simulink and verified experimentally with different values of CPL power levels and input voltage changes. The obtained simulation results show that simple DC system with constant power load was successfully stabilized by the installation of the passive damping network. The experimental set up was also conducted to validate of the proposed technique, and the obtained results were in excellent agreement with the theoretical parts of the project.

Mass balance of arsenic fluxes in rivers impacted by gold mining activities in Paracatu (Minas Gerais State, Brazil).

Arsenic (As) is a dangerous and carcinogenic element and drinking water is its main pathway of human exposure. Gold mines are widely recognized as important sources of As pollution. This work proposes the assessment of As distribution along watersheds surrounding "Morro do Ouro" gold mine (Paracatu, southeastern Brazil). A balance approach between filtered As fluxes (As < 0.45μm) and suspended particulate material (AsSPM) in different river segments was applied. Ultrafiltration procedure was used to categorize As into the following classes: particulate > 0.1μm, colloidal < 0.1μm to > 10kDa, dissolved < 10kDa to > 1kDa, and truly dissolved < 1kDa. By applying this approach, arsenic contributions from mining facilities were quantified in order to identify critical fluvial segments and support decision makers in actions of remediation. The mass balance indicated the occurrence of a decreasing gradient from upstream to downstream: (i) of the As concentrations higher than the limit established by Brazilian law (10μgL-1); (ii) of the ratio between specific fluxes (g Askm-2day-1) and those determined using an uncontaminated watershed (a proxy for estimating the anthropic contribution), from 103 to 101; (iii) of the specific fluxes As < 0.45μm and AsSPM from 102 to 100; and (iv) of the negative balance output minus input for each river segment that suggests As accumulation in sediments along the rivers in both urban and rural areas, mainly due to SPM sedimentation and sorption by Fe oxyhydroxides. Ultrafiltration shattering showed concentrations of decreasing As with particle size; the SPM load (> 0.1μm) was almost one order higher to dissolved load (< 1kDa).

High-performance programmable grounded resistor and its applications

ABSTRACTProgrammable resistor and analog computational circuits are essential for many applications such as analog signal processing units, automatic gain control, neural, fuzzy and instrumentation systems. A high-performance programmable grounded resistor (PGR) using complementary metal oxide semiconductor (CMOS) technology is proposed in this paper. A highly linear CMOS resistor with equivalent resistance ranging from 9.4 to 1.5 kΩ is obtained by cancelling the non-linear term present in the current equation of an MOSFET working in the linear region. The proposed resistor operates on both positive as well as negative input voltage. The inherited features of PGR are simplicity, extensive control voltage range, wider bandwidth and low-power dissipation. Additionally, analog computational units such as multiplier, squarer and divider are also discussed as applications of the PGR. All circuits are implemented and simulated using TSMC 0.13 µm CMOS technology in SPICE.

H∞ control of nonlinear systems with positive input with application to antiangiogenic therapy

Abstract There are many systems in practice that can have only positive (nonnegative) input, typical examples for such systems are physiological systems. Moreover, the parameters of these systems are usually not known exactly or may vary over time, thus application of robust controllers represents a reasonable possibility. Most model-based controller design methods are developed for systems that can (or must) have negative and positive inputs as well, thus a dynamical extension is given here to the original system that ensures that the input of the original system is positive but the extended system can have negative input as well. The current paper investigates a robust control design method with positive input for an automatic therapy possibility in the case of antiangiogenic targeted molecular therapy using a recently published tumor growth model based on mice experiments. The extended system is transformed into an integrator series that is further modified using state-feedback to prepare the system for H∞ norm-based controller synthesis. The simulations demonstrate the robustness of the controller and the positivity of the input.

Galectin-1: A Jack-of-All-Trades in the Resolution of Acute and Chronic Inflammation.

Regulatory signals provide negative input to immunological networks promoting resolution of acute and chronic inflammation. Galectin-1 (Gal-1), a member of a family of evolutionarily conserved glycan-binding proteins, displays broad anti-inflammatory and proresolving activities by targeting multiple immune cell types. Within the innate immune compartment, Gal-1 acts as a resolution-associated molecular pattern by counteracting the synthesis of proinflammatory cytokines, inhibiting neutrophil trafficking, targeting eosinophil migration and survival, and suppressing mast cell degranulation. Likewise, this lectin controls T cell and B cell compartments by modulating receptor clustering and signaling, thus serving as a negative-regulatory checkpoint that reprograms cellular activation, differentiation, and survival. In this review, we discuss the central role of Gal-1 in regulatory programs operating during acute inflammation, autoimmune diseases, allergic inflammation, pregnancy, cancer, and infection. Therapeutic strategies aimed at targeting Gal-1-glycan interactions will contribute to overcome cancer immunosuppression and reinforce antimicrobial immunity, whereas stimulation of Gal-1-driven immunoregulatory circuits will help to mitigate exuberant inflammation.

Analysis of Regulated Kinase Signal Network through Feedback Loops in Extra-Cellular Signal

&lt;p&gt;Signal network assumes a vital part in directing the principal cell capacities, for example, cell expansion, survival, separation and motility. Improvement and investigation of scientific model can help us gain a profound comprehension of the unpredictable conduct of ERK flag transduction organizes. This paper exhibits a computational model that offers an incorporated quantitative and dynamic reproduction of ERK flag transduction arranges, actuated by epidermal development figure. The mathematic demonstrate contains the enactment energy of the pathway, a huge number of input circles and association of platform proteins. The model gives knowledge into flag reaction connections between the authoritative of EGF to its receptor at the phone surface and actuation of downstream proteins in the flagging course. The diverse impact of positive and negative input circles of the ERK flag transduction pathway were for the most part examined, showing that criticism circles were the primary affecting variable to the swaying of ERK flag transduction pathway. The forecasts of this wavering of ERK enactment concur well with the writing. It can prompt flag floods of the downstream substrates and instigate relating natural practices.&lt;/p&gt;

Traffic intensity monitoring using multiple object detection with traffic surveillance cameras

Object detection and tracking is a field of research that has many applications in the current generation with increasing number of cameras on the streets and lower cost for Internet of Things(IoT). In this paper, a traffic intensity monitoring system is implemented based on the Macroscopic Urban Traffic model is proposed using computer vision as its source. The input of this program is extracted from a traffic surveillance camera which has another program running a neural network classification which can identify and differentiate the vehicle type is implanted. The neural network toolbox is trained with positive and negative input to increase accuracy. The accuracy of the program is compared to other related works done and the trends of the traffic intensity from a road is also calculated. relevant articles in literature searches, great care should be taken in constructing both. Lastly the limitation and the future work is concluded.

Winnerless competition in clustered balanced networks: inhibitory assemblies do the trick

Balanced networks are a frequently employed basic model for neuronal networks in the mammalian neocortex. Large numbers of excitatory and inhibitory neurons are recurrently connected so that the numerous positive and negative inputs that each neuron receives cancel out on average. Neuronal firing is therefore driven by fluctuations in the input and resembles the irregular and asynchronous activity observed in cortical in vivo data. Recently, the balanced network model has been extended to accommodate clusters of strongly interconnected excitatory neurons in order to explain persistent activity in working memory-related tasks. This clustered topology introduces multistability and winnerless competition between attractors and can capture the high trial-to-trial variability and its reduction during stimulation that has been found experimentally. In this prospect article, we review the mean field description of balanced networks of binary neurons and apply the theory to clustered networks. We show that the stable fixed points of networks with clustered excitatory connectivity tend quickly towards firing rate saturation, which is generally inconsistent with experimental data. To remedy this shortcoming, we then present a novel perspective on networks with locally balanced clusters of both excitatory and inhibitory neuron populations. This approach allows for true multistability and moderate firing rates in activated clusters over a wide range of parameters. Our findings are supported by mean field theory and numerical network simulations. Finally, we discuss possible applications of the concept of joint excitatory and inhibitory clustering in future cortical network modelling studies.

Detection of cost leaders in case of private primary school services

PurposeThe purpose of this paper is to provide an insight into distinguish cost leaders from the architects of diversification (Porter, 1985) using a non-central principal component analysis (PCA)-based approach. The central theme of this paper is based on the assumption that the operational strategy of a competing firm can be understood by observing its resource consumption and technological practice vis-à-vis its rivals present in the market.Design/methodology/approachDepending on the previous surveys, two inputs (spending per student and percentage of non-poor income group) and two outputs (average scores attained by students in science group and in language group six private schools, located within the outskirt of Durgapur) were analyzed.FindingsOut of six schools (A, B, C, D, E and F), A, E and F were found efficient; however, the proposed model identifies that out of them, only E and F remain cost efficient. The efficiency scores, due to cost, are very close to the outputs of other three accepted papers.Research limitations/implicationsThe input and output vectors have to be non-negative. In case of a negative input (output) set, separate treatment must be applied on them before the application of non-central PCA. Any decision-making unit (DMU) producing an output of 0 will prohibit the use of the non-central PCA.Practical implicationsIt can be applied to problems which may or may not be having the information regarding input price for detecting cost-efficient DMUs as in the case of the Banker’s model. Banker’s model remains inconclusive about the fact, whether a DMU is a mere cost leader or it is reigning in both fields. Present model does not have such limitations. Targets to remain cost efficient can be obtained for any competing DMU. Unlike the Banker’s model, the proposed one ascribes unequal weight to the cost of consumption to each resource. This weight vector is determined from the industrial practice. It remains unique in the sense that it relies on few intermediate input variables to measure the performance of a DMU. These variables are dependent on large number of other independent variables, which reflect the extent of its control on the resources to signify the strategic position of it. Moreover, the proposed model offers an ideal frontier of ultimate performers, which provides a very stringent benchmark based on constant return to scale for incorporating those renowned organizations, which operate in various places in West Bengal. However, it also offers lower limits of performance to the strongly efficient performers by using the goal-oriented data envelopment analysis for analyzing the problem on a local basis. The extended model, in addition, is worthy of carrying out SDEA operations.Social implicationsUnder the present scenario, a new model is proposed here to concentrate on the variation present in the market due to specific consumption of resources. All inputs are assumed scarce and desirable for the production of each output (Liu et al., 2010). Thus, a good cost-cutting performance occurs because of an economic use of resources while fulfilling the standards. Unlike Taguchi et al. (1989) and Taguchi (1991), a linear societal loss function, which is solely adhered to the resource consumption, is added here instead of a formal cost function.Originality/valueThe central theme of this paper is as follows: determination of technical efficiency scores for the schools; determination of economic efficiency (with partial information about price); identification of cost leaders and differentiation architects; to prescribe the model of a cost leader so that education can be imparted to a full potential; and to prescribe a non-central PCA and a slack-based optimization model. Superiority in the domain of cost leadership is decided based on the closeness of any DMU from this frontier.

A novel softplus linear unit for deep convolutional neural networks

Current improvements in the performance of deep neural networks are partly due to the proposition of rectified linear units. A ReLU activation function outputs zero for negative component, inducing the death of some neurons and a bias shift of the outputs, which causes oscillations and impedes learning. According to the theory that "zero mean activations improve learning ability", a softplus linear unit (SLU) is proposed as an adaptive activation function that can speed up learning and improve performance in deep convolutional neural networks. Firstly, for the reduction of the bias shift, negative inputs are processed using the softplus function, and a general form of the SLU function is proposed. Secondly, the parameters of the positive component are fixed to control vanishing gradients. Thirdly, the rules for updating the parameters of the negative component are established to meet back- propagation requirements. Finally, we designed deep auto-encoder networks and conducted several experiments with them on the MNIST dataset for unsupervised learning. For supervised learning, we designed deep convolutional neural networks and conducted several experiments with them on the CIFAR-10 dataset. The experiments have shown faster convergence and better performance for image classification of SLU-based networks compared with rectified activation functions.

A Comparative Study on the Effects of Negative Evidence and Enriched Input on Learning of Verb-Noun Collocations.

This study compared the effectiveness of negative evidence and enriched input on learning the verb-noun collocations. There were 52 English as Foreign Language (EFL) learners in this research study and they were randomly assigned to the negative evidence or enriched input groups. While the negative evidence group (n=27) was provided with instruction about what was not acceptable for verb-noun collocation structure, the enriched input group (n=25) was exposed to the target verb-noun collocations many times without any instruction or feedback. In order to determine the effects of the implementation, pre- and post- form recognition tests and pre-and post-production tests were administered to the participants. Wilcoxon signed rank test for paired samples and Mann Whitney U tests were conducted since the data did not meet normality assumptions. The Wilcoxon test results indicated that the negative evidence group achieved significant improvement in both their recognition and production test results. As for the enriched input group, the students presented a considerable improvement in terms of the production test; however, their performance was not very significant on the recognition test results. To compare both groups, Mann Whitney U test was run and it was evident that both the negative evidence and enriched input groups had positive effects on the production of verb-noun collocations. On the other hand, the form recognition test results revealed that the negative evidence group outperformed the enriched input group. Article visualizations:

Numerical simulations of ocean surface waves under hurricane conditions: Assessment of existing model performance

Using the well-observed hurricane case Ivan (2004) as an example, we investigate and intercompare the performance of two wave models under hurricane conditions. One is the WAVEWATCH III model (WW3) and the other is the University of Miami Wave Model (UMWM). Within WW3, four different source term packages (ST2/3/4/6) of wind input, wave breaking dissipation and swell decay are chosen for comparison purposes. Based on the comparisons between model results and measurements from various platforms, we concluded that UMWM shows less accuracy than WW3 in specification of bulk wave parameters. This is possibly because (i) UMWM-estimated drag coefficient does not clearly show a saturation trend when wind speeds are beyond ∼ 35 m s−1 and (ii) the four-wave interaction term of UMWM disagrees evidently with the full solution of the Boltzmann integral in detail. Among the four WW3 source term packages, the older parameterization ST2 is basically the least accurate because of its systematic underestimation of high waves. The remaining three packages (ST3/4/6) are performed well under Ivan. However, we also find that they tend to overestimate energy of waves traveling in the oblique and opposing winds. It is shown that enhancing the strength of negative wind input properly can effectively improve model skills in such situations. Limited by the uncertainty in the wind forcing, we could not determine the most accurate package among ST3/4/6 unambiguously.

Fractionation of sulfur (S) in beech (Fagus sylvatica) forest soils in relation to distance from the stem base as useful tool for modeling S biogeochemistry

The investigation of the fractionation of S compounds in forest soils is a powerful tool for interpreting S dynamics and S biogeochemistry in forest ecosystems. Beech stands on high pH (nutrient-rich) sites on Flysch and on low pH (nutrient-poor) sites on Molasse were selected for testing the influence of stemflow, which represents a high input of water and dissolved elements to the soil, on spatial patterns of sulfur (S) fractions. Soil cores were taken at six distances from a beech stem per site at 55 cm uphill and at 27, 55, 100, 150 and 300 cm downhill from the stem. The cores were divided into the mineral soil horizons 0–3, 3–10, 10–20, 20–30 and 30–50 cm. Soil samples were characterized for pH, Corg, pedogenic Al and Fe oxides and S fractions. Sequential extraction by NH4Cl, NH4H2PO4 and HCl yielded readily available sulfate-S (RAS), adsorbed sulfate-S (AS) and HCl-soluble sulfate-S (HCS). Organic sulfur (OS) was estimated as the difference between total sulfur (ToS) and inorganic sulfur (RAS + AS + HCS). Organic sulfur was further divided into ester sulfate-S (ES, HI-reduction) and carbon bonded sulfur (CS). On Flysch, RAS represented 3–6%, AS 2–12%, HCS 0–8% and OS 81–95% of ToS. On Molasse, RAS amounted 1–6%, AS 1–60%, HCS 0–8% and OS 37–95% of ToS. Spatial S distribution patterns with respect to the distance from the tree stem base could be clearly observed at all investigated sites. The presented data is a contribution to current reports on negative input–output S budgets of forest watersheds, suggesting that mineralization of OS on nutrient rich soils and desorption of historic AS on nutrient-poor soils are the dominant S sources, which have to be considered in future modeling of sulfur.

A 1.6 ps 7 b time to digital converter in 0.18 µm CMOS technology

A fine Time to Digital Converter (TDC) based on time difference amplification is proposed. A current difference based method is introduced to improve the limited input linear range of the conventional×2 Time Amplifier (TA). The modified TA is used in a proposed pipeline TDC to achieve a fine sub-gate delay resolution. A sign detection stage is implemented at the input of the TDC to avoid two separate circuits for conversion of positive and negative inputs, which decreases power consumption by roughly fifty percent. Furthermore, the delay cell circuits are modified to increase the TDC resolution and reduce its susceptibility to mismatch and process variations. The TDC resolution is 1.6ps by post-layout simulation in 180nm CMOS technology. Power consumption of the introduced TDC at 50Msps and 1.2V supply voltage is 280uW.

A Discontinuous Conduction Mode Single-Stage Step-Up Rectifier for Low-Voltage Energy Harvesting Applications

In this paper, a novel ac/dc converter is proposed for low-voltage and low-power ac rectification applications. The proposed converter manages the energy harvested from microscale electromagnetic generators (MEGs). It integrates the conventional boost and buck–boost topologies with a shared inductor, a bidirectional switch, and two split filtering capacitors. The boost and the buck–boost topologies function in the positive and negative half input cycles, respectively. The inductor is energized by being shorted with the input source through the mosfet channel without using the diodes. This enables active rectification of low-amplitude (below 0.7 V) ac voltages. Theoretical analysis, design considerations, and control method are detailed. A 40-mW circuit prototype, which converts a 0.4-V peak, 100-Hz ac voltage source to 3.3-V dc, is designed and tested to verify the proof of concept.

The integration of multiple signaling pathways provides for bidirectional control of CRHR1 gene transcription in rat pituitary cell during hypoxia

Hypoxia upregulates hypothalamic corticotrophin releasing hormone (CRH) and its receptor type-1 (CRHR1) expression and activates the HPA axis and induces hypoxic sickness and behavioral change. The transcriptional mechanism by which hypoxia differently regulates CRHR1 expression remains unclear. Here we report hypoxia time-dependently induced biphasic expression of CRHR1mRNA in rat pituitary during different physiological status. Short exposure of gestational dams to hypoxia reduced CRHR1mRNA in the pituitary of P1-P14 male rat offspring. A short- and prolonged-hypoxia evoked biphasic response of CRHR1mRNA characterized initially by decreases and subsequently by persistent increases, mediated by a rapid negative feedback via CRHR1 signaling and positive transcriptional control via NF-κB, respectively. Further analysis of CRHR1 promoter in cultured primary anterior pituitary and AtT20 cells showed that c-Jun/AP-1 delivered negative while HIF-1α and NF-κB delivered positive control of transcription at CRHR1 promoter. The negative and positive inputs are integrated by hypoxic initiation and duration in CRHR1 transcription.

Impedance Decoupling in DC Distributed Systems to Maintain Stability and Dynamic Performance

DC distributed systems are highly reliable and efficient means of delivering DC power or adopting renewable energy resources. However, DC distributed systems are prone to instability and dynamic performance degradation due to the negative incremental input impedance of DC-DC converts. In this paper, we propose a generic method to eliminate the impact of the negative input impedance on DC systems by shaping the source output impedance such that its bode-plot is restricted in the area that is contained below the product of the source’s duty ratio and its characteristic impedance. The performance deterioration originates whenever the output impedance of the source exceeds, in magnitude, the input impedance of the load converter due to deficiency in stability margins. Hence, confining the impedance in the proposed region helps decouple the interaction between the converters and preserve their own dynamic performances. The proposed method was proven by analytical analysis, time-based simulation, and practical experiments. All of their outcomes were in agreement, proving the effectiveness of the proposed method in preserving the dynamic performance of distributed systems.

State-dependent alterations in inhibitory control and emotional face identification in seasonal affective disorder.

Depressed individuals often exhibit impaired inhibition to negative input and identification of positive stimuli, but it is unclear whether this is a state or trait feature. We here exploited a naturalistic model, namely individuals with seasonal affective disorder (SAD), to study this feature longitudinally. The goal of this study was to examine seasonal changes in inhibitory control and identification of emotional faces in individuals with SAD. Twenty-nine individuals diagnosed with winter-SAD and 30 demographically matched controls with no seasonality symptoms completed an emotional Go/NoGo task, requiring inhibition of prepotent responses to emotional facial expressions and an emotional face identification task twice, in winter and summer. In winter, individuals with SAD showed impaired ability to inhibit responses to angry (p = .0006) and sad faces (p = .011), and decreased identification of happy faces (p = .032) compared with controls. In summer, individuals with SAD and controls performed similarly on these tasks (ps > .24). We provide novel evidence that inhibition of angry and sad faces and identification of happy faces are impaired in SAD in the symptomatic phase, but not in the remitted phase. The affective biases in cognitive processing constitute state-dependent features of SAD. Our data show that reinstatement of a normal affective cognition should be possible and would constitute a major goal in psychiatric treatment to improve the quality of life for these patients. (PsycINFO Database Record