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The lack of process-based classification procedures may lead to unrealistic hyetograph design due to complex oscillation of rainfall depths when assimilated at high temporal resolutions. Four consecutive years of sub-hourly rainfall data were assimilated in three study areas (Guaraira, GEB, Sao Joao do Cariri, CEB, and Aiuaba, AEB) under distinct climates (very hot semi-arid and tropical wet). This study aimed to define rainfall events (for Minimum Inter-event Time, MIT, and Minimum Rainfall Depth, MRD, equal to 30 min and 1.016 mm, respectively), classify their hyetograph types (rectangular, R, unimodal with left-skewed, UL, right-skewed, UR, and centred peaks, UC, bimodal, B, and shapeless, SL), and compare their key rainfall properties (frequency, duration, depth, rate and peak). A rain pulse aggregation process allowed for reshaping SL-events for six different time spans varying from 2 to 30 min. The results revealed that the coastal area held predominantly R-events (64% events and 49% rainfall depth), in western semi-arid prevailed UL-events (57% events and 63% rainfall depth), whereas in eastern semi-arid mostly were R-events (61% events and 30% rainfall depth) similar to coastal area. It is concluded that each cloud formation type had important effects on hyetograph properties, differentiating them even within the same climate.
Social transitions are characterized by an increased heterogeneity in Western societies. Following the life course perspective, individual agency becomes central in shaping one’s life course. This article examines social transitions of adolescents using individual resource theory to explain differences of the timing of five transitions in partnership and family formation: the first sexual experience, the first intimate relationship, the first cohabitation, the first marriage, and the birth of the first child. Since little is so far known about how individual characteristics interact and influence the social transition to adulthood, we focus on the varying impacts of personal, social and socio-economic resources across the social life course. We use longitudinal data from the German LifE-Study, which focuses on the birth cohort of individuals born between 1965 and 1967. Using event history analysis, we find that the timing of the first sexual experience and first partnership transitions are mainly influenced by personal and social ressources, whereas socio-economic resources offer better explanations for the timing of entering marriage and parenthood. Most striking are the different explanatory models for women and men.
Poly[(rac-lactide)-co-glycolide] (PLGA) is used in medicine to provide mechanical support for healing tissue or as matrix for controlled drug release. The properties of this copolymer depend on the evolution of the molecular weight of the material during degradation. which is determined by the kinetics of the cleavage of hydrolysable bonds. The generally accepted description of the degradation of PLGA is a random fragmentation that is autocatalyzed by the accumulation of acidic fragments inside the bulk material. Since mechanistic studies with lactide oligomers have concluded a chain-end scission mechanism and monolayer degradation experiments with polylactide found no accelerated degradation at lower pH, we hypothesize that the impact of acidic fragments on the molecular degradation kinetics of PLGA is overestimated By means of the Langmuir monolayer degradation technique. the molecular degradation kinetics of PLGA at different pH could be determined. Protons did not catalyze the degradation of PLGA. The molecular mechanism at neutral pH and low pH is a combination of random and chainend-cut events, while the degradation under strongly alkaline conditions is determined by rapid chainend cuts. We suggest that the degradation of bulk PLGA is not catalyzed by the acidic degradation products. Instead. increased concentration of small fragments leads to accelerated mass loss via fast chain-end cut events. In the future, we aim to substantiate the proposed molecular degradation mechanism of PLGA with interfacial rheology.
Enzymes have recently attracted increasing attention in material research based on their capacity to catalyze the conversion of polymer-bound moieties for synthesizing polymer networks, particularly bulk hydrogels. hi this study. the surface immobilization of a relevant enzyme. mushroom tyrosinase, should be explored using glass as model surface. In a first step. the glass support was functionalized with silanes to introduce either amine or carboxyl groups, as confirmed e.g. by X-ray photoelectron spectroscopy. By applying glutaraldehyde and EDC/NHS chemistry, respectively, surfaces have been activated for subsequent successful coupling of tyrosinase. Via protein hydrolysis and amino acid characterization by HPLC, the quantity of bound tyrosinase was shown to correspond to a full surface coverage. Based on the visualized enzymatic conversion of a test substrate at the glass support. the functionalized surfaces may be explored for surface-associated material synthesis in the future.
Humanoid robots, prosthetic limbs and exoskeletons require soft actuators to perform their primary function, which is controlled movement. In this wont we explored whether crosslinked poly[ethylene-co-(vinyl acetate)] (cPEVA) fibers, with different vinyl acetate (VA) content can serve as torsional fiber actuators. exhibiting temperature controlled reversible rotational changes. Broad melting transitions ranging from 50 to 90 degrees C for cPEVA18-165 or from 40 to 80 degrees C for cPEVA28-165 fibers in combination with complete crystallization at temperatures around 10 degrees C make them suitable actuating materials with adjustable actuation temperature ranges between 10 and 70 degrees C during repetitive cooling and heating. The obtained fibers exhibited a circular cross section with diameters around 0.4 +/- 0.1 mm, while a length of 4 cm was employed for the investigation of reversible rotational actuation after programming by twist insertion using 30 complete rotations at a temperature above melting transition. Repetitive heating and cooling between 10 to 60 degrees C or 70 degrees C of one-end-tethered programmed fibers revealed reversible rotations and torsional force. During cooling 3 +/- 1 complete rotations (Delta theta(r) = + 1080 +/- 360 degrees) in twisting direction were observed, while 4 +/- 1 turns in the opposite direction (Delta theta(r) = - 1440 +/- 1360 degrees) were found during heating. Such torsional fiber actuators, which are capable of approximately one rotation per cm fiber length, can serve as miniaturized rotary motors to provide rotational actuation in futuristic humanoid robots.
The variation of the molecular architecture of multiblock copolymers has enabled the introduction of functional behaviour and the control of key mechanical properties. In the current study, we explore the synergistic relationship of two structural components in a shape-memory material formed of a multiblock copolymer with crystallizable poly(epsilon-caprolactone) and crystallizable polyfoligo(3S-iso-butylmorpholine-2,5-dione) segments (PCL-PIBMD). The thermal and structural properties of PCL-PIBMD films were compared with PCI.-PU and PMMD-PU investigated by means of DSC, SAXS and WARS measurements. The shape-memory properties were quantified by cyclic, thermomechanical tensile tests, where deformation strains up to 900% were applied for programming PCL-PIBMD films at 50 degrees C. Toluene vapor treatment experiments demonstrated that the temporary shape was fixed mainly by glassy PIBMD domains at strains lower than 600% with the PCL contribution to fixation increasing to 42 +/- 2% at programming strains of 900% This study into the shape-memory mechanism of PCL-PIBMD provides insight into the structure function relation in multiblock copolymers with both crystallizable and glassy switching segments.
In rural/remote areas, resource constrained smart micro-grid (RCSMG) architectures can provide a cost-effective power supply alternative in cases when connectivity to the national power grid is impeded by factors such as load shedding. RCSMG architectures can be designed to handle communications over a distributed lossy network in order to minimise operation costs. However, due to the unreliable nature of lossy networks communication data can be distorted by noise additions that alter the veracity of the data. In this chapter, we consider cases in which an adversary who is internal to the RCSMG, deliberately distorts communicated data to gain an unfair advantage over the RCSMG’s users. The adversary’s goal is to mask malicious data manipulations as distortions due to additive noise due to communication channel unreliability. Distinguishing malicious data distortions from benign distortions is important in ensuring trustworthiness of the RCSMG. Perturbation data anonymisation algorithms can be used to alter transmitted data to ensure that adversarial manipulation of the data reveals no information that the adversary can take advantage of. However, because existing data perturbation anonymisation algorithms operate by using additive noise to anonymise data, using these algorithms in the RCSMG context is challenging. This is due to the fact that distinguishing benign noise additions from malicious noise additions is a difficult problem. In this chapter, we present a brief survey of cases of privacy violations due to inferences drawn from observed power consumption patterns in RCSMGs centred on inference, and propose a method of mitigating these risks. The lesson here is that while RCSMGs give users more control over power management and distribution, good anonymisation is essential to protecting personal information on RCSMGs.
In this chapter, we provide a framework to specify how cheating attacks can be conducted successfully on power marketing schemes in resource constrained smart micro-grids. This is an important problem because such cheating attacks can destabilise and in the worst case result in a breakdown of the micro-grid. We consider three aspects, in relation to modelling cheating attacks on power auctioning schemes. First, we aim to specify exactly how in spite of the resource constrained character of the micro-grid, cheating can be conducted successfully. Second, we consider how mitigations can be modelled to prevent cheating, and third, we discuss methods of maintaining grid stability and reliability even in the presence of cheating attacks. We use an Automated-Cheating-Attack (ACA) conception to build a taxonomy of cheating attacks based on the idea of adversarial acquisition of surplus energy. Adversarial acquisitions of surplus energy allow malicious users to pay less for access to more power than the quota allowed for the price paid. The impact on honest users, is the lack of an adequate supply of energy to meet power demand requests. We conclude with a discussion of the performance overhead of provoking, detecting, and mitigating such attacks efficiently.
Resource constrained smart micro-grid architectures describe a class of smart micro-grid architectures that handle communications operations over a lossy network and depend on a distributed collection of power generation and storage units. Disadvantaged communities with no or intermittent access to national power networks can benefit from such a micro-grid model by using low cost communication devices to coordinate the power generation, consumption, and storage. Furthermore, this solution is both cost-effective and environmentally-friendly. One model for such micro-grids, is for users to agree to coordinate a power sharing scheme in which individual generator owners sell excess unused power to users wanting access to power. Since the micro-grid relies on distributed renewable energy generation sources which are variable and only partly predictable, coordinating micro-grid operations with distributed algorithms is necessity for grid stability. Grid stability is crucial in retaining user trust in the dependability of the micro-grid, and user participation in the power sharing scheme, because user withdrawals can cause the grid to breakdown which is undesirable. In this chapter, we present a distributed architecture for fair power distribution and billing on microgrids. The architecture is designed to operate efficiently over a lossy communication network, which is an advantage for disadvantaged communities. We build on the architecture to discuss grid coordination notably how tasks such as metering, power resource allocation, forecasting, and scheduling can be handled. All four tasks are managed by a feedback control loop that monitors the performance and behaviour of the micro-grid, and based on historical data makes decisions to ensure the smooth operation of the grid. Finally, since lossy networks are undependable, differentiating system failures from adversarial manipulations is an important consideration for grid stability. We therefore provide a characterisation of potential adversarial models and discuss possible mitigation measures.
Power Systems
(2018)
Studies indicate that reliable access to power is an important enabler for economic growth. To this end, modern energy management systems have seen a shift from reliance on time-consuming manual procedures, to highly automated management, with current energy provisioning systems being run as cyber-physical systems. Operating energy grids as a cyber-physical system offers the advantage of increased reliability and dependability, but also raises issues of security and privacy. In this chapter, we provide an overview of the contents of this book showing the interrelation between the topics of the chapters in terms of smart energy provisioning. We begin by discussing the concept of smart-grids in general, proceeding to narrow our focus to smart micro-grids in particular. Lossy networks also provide an interesting framework for enabling the implementation of smart micro-grids in remote/rural areas, where deploying standard smart grids is economically and structurally infeasible. To this end, we consider an architectural design for a smart micro-grid suited to low-processing capable devices. We model malicious behaviour, and propose mitigation measures based properties to distinguish normal from malicious behaviour.
We consider a distributed learning approach in supervised learning for a large class of spectral regularization methods in an reproducing kernel Hilbert space (RKHS) framework. The data set of size n is partitioned into m = O (n(alpha)), alpha < 1/2, disjoint subsamples. On each subsample, some spectral regularization method (belonging to a large class, including in particular Kernel Ridge Regression, L-2-boosting and spectral cut-off) is applied. The regression function f is then estimated via simple averaging, leading to a substantial reduction in computation time. We show that minimax optimal rates of convergence are preserved if m grows sufficiently slowly (corresponding to an upper bound for alpha) as n -> infinity, depending on the smoothness assumptions on f and the intrinsic dimensionality. In spirit, the analysis relies on a classical bias/stochastic error analysis.
BACKGROUND: The formation of a functionally-confluent endothelial cell (EC) monolayer affords proliferation of EC, which only happens in case of appropriate migratory activity. AIM OF THE STUDY: The migratory pathway of human umbilical endothelial cells (HUVEC) was investigated on different polymeric substrates. MATERIAL AND METHODS: Surface characterization of the polymers was performed by contact angle measurements and atomic force microscopy under wet conditions. 30,000 HUVEC per well were seeded on polytetrafluoroethylene (PTFE) (theta(adv) = 119 degrees +/- 2 degrees), on low-attachment plate LAP (theta(adv) = 28 degrees +/- 2 degrees) and on polystyrene based tissue culture plates (TCP, theta(adv) = 22 degrees +/- 1 degrees). HUVEC tracks (trajectories) were recorded by time lapse microscopy and the euclidean distance (straight line between starting and end point), the total distance and the velocities of HUVEC not leaving the vision field were determined. RESULTS: On PTFE, 42 HUVEC were in the vision field directly after seeding. The mean length of single migration steps (SML) was 6.1 +/- 5.2 mu m, the mean velocity (MV) 0.40 +/- 0.3 mu m.min(-1) and the complete length of the trajectory (LT) was 710 +/- 440 mu m. On TCP 82 HUVEC were in the vision field subsequent to seeding. The LT was 840 +/- 550 mu m, the SML 6.1 +/- 5.2 mu m and the MV 0.44 +/- 0.3 mu m.min(-1). The trajectories on LAP differed significantly in respect to SML (2.4 +/- 3.9 mu m, p <0.05), the MV (0.16 +/- 0.3 mu m.min(-1), p <0.05) and the LT (410 +/- 300 mu m, p <0.05), compared to PTFE and TCP. Solely on TCP a nearly confluent EC monolayer developed after three days. While on TCP diffuse signals of vinculin were found over the whole basal cell surface organizing the binding of the cells by focal adhesions, on PTFE vinculin was merely arranged at the cell rims, and on the hydrophilic material (LAP) no focal adhesions were found. CONCLUSION: The study revealed that the wettability of polymers affected not only the initial adherence but also the migration of EC, which is of importance for the proliferation and ultimately the endothelialization of polymer-based biomaterials.
In this chapter, an overview of systematic eradication of basic science foci in European universities in the last two decades is given. This happens under the slogan of optimisation of the university education to the needs and demands of the society. It is pointed out that reliance on “market demands” brings with it long-term deficiencies in the maintenance of basic and advanced knowledge construction in societies necessary for long-term future technological advances. University policies that claim improvement of higher education towards more immediate efficiency may end up with the opposite effect of affecting its quality and long term expected positive impact on society.
Since the 1980s, central governments have decentralized forestry to local governments in many countries of the Global South. More recently, REDD+ has started to impact forest policy-making in these countries by providing incentives to ensure a national-level approach to reducing emissions from deforestation and forest degradation. Höhne et al. analyze to what extent central governments have rebuilt capacity at the national level, imposed regulations from above, and interfered in forest management by local governments for advancing REDD+. Using the examples of Brazil and Indonesia, the chapter illustrates that while REDD+ has not initiated a large-scale recentralization in the forestry sector, it has supported the reinforcement and pooling of REDD+ related competences at the central government level.
Uniformly valid confidence intervals post model selection in regression can be constructed based on Post-Selection Inference (PoSI) constants. PoSI constants are minimal for orthogonal design matrices, and can be upper bounded in function of the sparsity of the set of models under consideration, for generic design matrices. In order to improve on these generic sparse upper bounds, we consider design matrices satisfying a Restricted Isometry Property (RIP) condition. We provide a new upper bound on the PoSI constant in this setting. This upper bound is an explicit function of the RIP constant of the design matrix, thereby giving an interpolation between the orthogonal setting and the generic sparse setting. We show that this upper bound is asymptotically optimal in many settings by constructing a matching lower bound.
We consider composite-composite testing problems for the expectation in the Gaussian sequence model where the null hypothesis corresponds to a closed convex subset C of R-d. We adopt a minimax point of view and our primary objective is to describe the smallest Euclidean distance between the null and alternative hypotheses such that there is a test with small total error probability. In particular, we focus on the dependence of this distance on the dimension d and variance 1/n giving rise to the minimax separation rate. In this paper we discuss lower and upper bounds on this rate for different smooth and non-smooth choices for C.
We consider truncated SVD (or spectral cut-off, projection) estimators for a prototypical statistical inverse problem in dimension D. Since calculating the singular value decomposition (SVD) only for the largest singular values is much less costly than the full SVD, our aim is to select a data-driven truncation level (m) over cap is an element of {1, . . . , D} only based on the knowledge of the first (m) over cap singular values and vectors. We analyse in detail whether sequential early stopping rules of this type can preserve statistical optimality. Information-constrained lower bounds and matching upper bounds for a residual based stopping rule are provided, which give a clear picture in which situation optimal sequential adaptation is feasible. Finally, a hybrid two-step approach is proposed which allows for classical oracle inequalities while considerably reducing numerical complexity.