Calculation of the persistence length of a flexible polymer chain with short range self-repulsion

For a self-repelling polymer chain consisting of n segments we calculate the persistence length L(j,n), defined as the projection of the end-to-end vector on the direction of the j`th segment. This quantity shows some pronounced variation along the chain. Using the renormalization group and epsilon-expansion we establish the scaling form and calculate the scaling function to order epsilon^2. Asymptotically the simple result L(j,n) ~ const(j(n-j)/n)^(2nu-1) emerges for dimension d=3. Also outside the excluded volume limit L(j,n) is found to behave very similar to the swelling factor of a chain of length j(n-j)/n. We carry through simulations which are found to be in good accord with our analytical results. For d=2 both our and previous simulations as well as theoretical arguments suggest the existence of logarithmic anomalies.Comment: 28 pages, 8 figures, changed conten

Sec24-Dependent Secretion Drives Cell-Autonomous Expansion of Tracheal Tubes in Drosophila

Epithelial tubes in developing organs, such as mammalian lungs and insect tracheae, need to expand their initially narrow lumina to attain their final, functional dimensions [1]. Despite its critical role for organ function, the cellular mechanism of tube expansion remains unclear. Tracheal tube expansion in Drosophila involves apical secretion and deposition of a luminal matrix [2,3,4,5], but the mechanistic role of secretion and the nature of forces involved in the process were not previously clear. Here we address the roles of cell-intrinsic and extrinsic processes in tracheal tube expansion. We identify mutations in the sec24 gene stenosis, encoding a cargo-binding subunit of the COPII complex [6,7,8]. Via genetic-mosaic analyses, we show that stenosis-dependent secretion drives tube expansion in a cell-autonomous fashion. Strikingly, single cells autonomously adjust both tube diameter and length by implementing a sequence of events including apical membrane growth, cell flattening, and taenidial cuticle formation. Known luminal components are not required for this process. Thus, a cell-intrinsic program, rather than nonautonomous extrinsic cues, controls the dimensions of tracheal tubes. These results indicate a critical role of membrane-associated proteins in the process and imply a mechanism that coordinates autonomous behaviors of individual cells within epithelial structures

A Population of Teraelectronvolt Pulsar Wind Nebulae in the H.E.S.S. Galactic Plane Survey

The most numerous source class that emerged from the H.E.S.S. Galactic Plane Survey are Pulsar Wind Nebulae (PWNe). The 2013 reanalysis of this survey, undertaken after almost 10 years of observations, provides us with the most sensitive and most complete census of gamma-ray PWNe to date. In addition to a uniform analysis of spectral and morphological parameters, for the first time also flux upper limits for energetic young pulsars were extracted from the data. We present a discussion of the correlation between energetic pulsars and TeV objects, and their respective properties. We will put the results in context with the current theoretical understanding of PWNe and evaluate the plausibility of previously non-established PWN candidates.Comment: 4 pages, 5 figures. In Proceedings of the 33rd International Cosmic Ray Conference (ICRC2013), Rio de Janeiro (Brazil

Computational Intelligence in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) are networks of distributed autonomous devices that can sense or monitor physical or environmental conditions cooperatively. WSNs face many challenges, mainly caused by communication failures, storage and computational constraints and limited power supply. Paradigms of computational intelligence (CI) have been successfully used in recent years to address various challenges such as data aggregation and fusion, energy aware routing, task scheduling, security, optimal deployment and localization. CI provides adaptive mechanisms that exhibit intelligent behavior in complex and dynamic environments like WSNs. CI brings about flexibility, autonomous behavior, and robustness against topology changes, communication failures and scenario changes. However, WSN developers are usually not or not completely aware of the potential CI algorithms offer. on the other side, CI researchers are not familiar with all real problems and subtle requirements of WSNs. This mismatch makes collaboration and development difficult. This paper intends to close this gap and foster collaboration by offering a detailed introduction to WSNs and their properties. an extensive survey of CI applications to various problems in WSNs from various research areas and publication venues is presented in the paper. Besides, a discussion on advantages and disadvantages of CI algorithms over traditional WSN solutions is offered. in addition, a general evaluation of CI algorithms is presented, which will serve as a guide for using CI algorithms for WSNs. © 2005 IEEE

Assessing flood risk for a rural detention area

International audienceFlood detention areas serve the primary purpose of controlled water storage during large flood events in order to decrease the flood risk downstream along the river. These areas are often used for agricultural production. While various damage estimation methods exist for urban areas, there are only a few, most often simpler approaches for loss estimation in rural areas. The loss assessment can provide an estimate of the financial provisions required for the farmers' compensation (e.g., in the context of cost-benefit analyses of detention measures). Flood risk is a combination of potential damage and probability of flooding. Losses in agricultural areas exhibit a strong seasonal pattern, and the flooding probability also has a seasonal variation. In the present study, flood risk is assessed for a planned detention area alongside the Elbe River in Germany based on two loss and probability estimation approaches of different time frames, namely a monthly and an annual approach. The results show that the overall potential damage in the proposed detention area amounts to approximately 40 000 ? a?1, with approximately equal losses for each of the main land uses, agriculture and road infrastructure. A sensitivity analysis showed that the probability of flooding (i.e., the frequency of operation of the detention area) has the largest impact on the overall flood risk

The Computational Power of Beeps

In this paper, we study the quantity of computational resources (state machine states and/or probabilistic transition precision) needed to solve specific problems in a single hop network where nodes communicate using only beeps. We begin by focusing on randomized leader election. We prove a lower bound on the states required to solve this problem with a given error bound, probability precision, and (when relevant) network size lower bound. We then show the bound tight with a matching upper bound. Noting that our optimal upper bound is slow, we describe two faster algorithms that trade some state optimality to gain efficiency. We then turn our attention to more general classes of problems by proving that once you have enough states to solve leader election with a given error bound, you have (within constant factors) enough states to simulate correctly, with this same error bound, a logspace TM with a constant number of unary input tapes: allowing you to solve a large and expressive set of problems. These results identify a key simplicity threshold beyond which useful distributed computation is possible in the beeping model.Comment: Extended abstract to appear in the Proceedings of the International Symposium on Distributed Computing (DISC 2015

Rainfall disaggregation for hydrological modeling: is there a need for spatial consistence?

In this study, the influence of disaggregated rainfall products with different degrees of spatial consistence on rainfall–runoff modeling results is analyzed for three mesoscale catchments in Lower Saxony, Germany. For the disaggregation of daily rainfall time series into hourly values, a multiplicative random cascade model is applied. The disaggregation is applied on a station by station basis without consideration of surrounding stations; hence subsequent steps are then required to implement spatial consistence. Spatial consistence is represented here by three bivariate spatial rainfall characteristics that complement each other. A resampling algorithm and a parallelization approach are evaluated against the disaggregated time series without any subsequent steps. With respect to rainfall, clear differences between these three approaches can be identified regarding bivariate spatial rainfall characteristics, areal rainfall intensities and extreme values. The resampled time series lead to the best agreement with the observed ones. Using these different rainfall products as input to hydrological modeling, we hypothesize that derived runoff statistics – with emphasis on seasonal extreme values – are subject to similar differences as well. However, an impact on the extreme values' statistics of the hydrological simulations forced by different rainfall approaches cannot be detected. Several modifications of the study design using rainfall–runoff models with and without parameter calibration or using different rain gauge densities lead to similar results in runoff statistics. Only if the spatially highly resolved rainfall–runoff WaSiM model is applied instead of the semi-distributed HBV-IWW model can slight differences regarding the seasonal peak flows be identified. Hence, the hypothesis formulated before is rejected in this case study. These findings suggest that (i) simple model structures might compensate for deficiencies in spatial representativeness through parameterization and (ii) highly resolved hydrological models benefit from improved spatial modeling of rainfall.</p

Deficits in explicit emotion regulation in bipolar disorder: A systematic review

Background: This study aimed to compile and synthesize studies investigating explicit emotion regulation in patients with bipolar disorder and individuals at risk of developing bipolar disorder. The importance of explicit emotion regulation arises from its potential role as a marker for bipolar disorders in individuals at risk and its potent role in therapy for bipolar disorder patients. Methods: To obtain an exhaustive compilation of studies dealing specifically with explicit emotion regulation in bipolar disorder, we conducted a systematic literature search in four databases. In the 15 studies we included in our review, the emotion-regulation strategies maintenance, distraction, and reappraisal (self-focused and situation-focused) were investigated partly on a purely behavioral level and partly in conjunction with neural measures. The samples used in the identified studies included individuals at increased risk of bipolar disorder, patients with current affective episodes, and patients with euthymic mood state. Results: In summary, the reviewed studies' results indicate impairments in explicit emotion regulation in individuals at risk for bipolar disorder, patients with manic and depressive episodes, and euthymic patients. These deficits manifest in subjective behavioral measures as well as in neural aberrations. Further, our review reveals a discrepancy between behavioral and neural findings regarding explicit emotion regulation in individuals at risk for bipolar disorders and euthymic patients. While these groups often do not differ significantly in behavioral measures from healthy and low-risk individuals, neural differences are mainly found in frontostriatal networks. Conclusion: We conclude that these neural aberrations are a potentially sensitive measure of the probability of occurrence and recurrence of symptoms of bipolar disorders and that strengthening this frontostriatal route is a potentially protective measure for individuals at risk and patients who have bipolar disorders