Miracle-dz/UniFAR-FTUs huggingface dataset:
Event-Driven Control With Deadline Optimization for Linear Systems With Stochastic Delays

This work presents a novel control strategy for systems with actuation delays with known stochastic distribution, which improves upon previously proposed deadline-driven and event-driven strategies. In the event-driven strategy, the control input is immediately updated after the delay, whereas in the deadline-driven strategy, the actuation is updated in a periodic fashion, where the sampling period sets a deadline; if the delay is larger than this deadline, the actuation is not updated. Our method switches between these two strategies and guarantees better performance, in a linear–quadratic–Gaussian sense, than either method considered separately. An extension of the novel method with a deadline-optimization scheme is shown to improve the performance even further. Simulation results illustrate the effectiveness of the proposed methods.
Regional and seasonal feeding by bowhead whales Balaena mysticetus as indicated by stable isotope ratios

The feeding habitats of the Bering-Chukchi-Beaufort stock of bowhead whales Balaena mysticetus during summer and fall migration are generally known, but the relative amounts of food they consume in various parts of the seasonal range are poorly understood. We used natural geographic gradients in stable isotope ratios of carbon and nitrogen within zooplankton (bowhead prey) to measure the relative importance of the eastern Beaufort Sea versus Bering and Chukchi Seas (combined) as feeding habitat for bowheads. The δ 13 C content of their prey differs by 3.9%o, on a weighted average basis, between the 2 regions. δ 13 C in bowhead muscle changed by only 0.5‰ while bowheads were in the Beaufort Sea, indicating that only ca. 10% of the muscle carbon in the average whale turns over during summer feeding, with 95 % confidence intervals (CI) of 0 to 23 %. Considering subadult whales only, estimated turnover averaged 14 % with 95 % CI of 4 to 23 %. For adults, the estimated turnover was 5 % (95 % CI = 0 to 30 %). Overall δ 13 C values in muscle are not significantly different in adult and subadult bowheads, suggesting no major age-related shift in the relative importance of different feeding habitats, and very closely matching Bering-Chukchi-derived food. δ 15 N values for muscles were near 1‰ higher in whales taken in the 1980s, consistent with the observed long-term declining trends in environmental δ 15 N values as indicated by chronological sampling of baleen plates. In contrast to muscle data, δ 13 C values in baleen, each representing feeding during a shorter time increment, do show seasonal and age-related differences. Subadult whales apparently feed more in the eastern Beaufort Sea than do adults, but nonetheless acquire insufficient food there to significantly alter their bulk carbon isotope ratios.
Efficacy of Plant Compounds for Reducing Foodborne Pathogens on Fresh Produce

v Chapter 1: Introduction 1 Chapter 2: Review of Literature 5 Current trends in fresh produce production and consumption 6 Foodborne illness burden in the United States 7 Contamination of fresh produce 8 Escherichia coli O157:H7 9 Listeria monocytogenes 9 Salmonella spp. 10 Outbreaks linked to fresh produce (Table 1). 11 Methods for reducing pathogens on fresh produce 14 Chlorine 14 Toxicity of chlorine compounds 15 Peroxyacetic acid 16 Hydrogen peroxide 16 Ozone 17 Natural alternatives 17 Antimicrobial mechanisms of plant molecules 18 Chapter 3: Inactivation of Salmonella spp. on tomatoes by plant molecules 36 Chapter 4: Effect of trans-cinnamaldehyde and carvacrol on Escherichia coli O157:H7 and Listeria monocytogenes on iceberg lettuce 61 Chapter 5: Conclusion 91
Teaching Reform of Course Group Regarding Theory and Design of Mechanisms Based on MATLAB Technology

Considering that the course group regarding theory and design of mechanisms is characterized by strong engineering application background and the students generally feel very boring and tedious during the learning process, some teaching reforms for the theory and design of mechanisms are carried out to improve the teaching effectiveness in this paper. Taking the engineering cases as the teaching objectives, we combine the course contents with the engineering background. Moreover, in order to help the students understand the knowledge difficulty and improve the design capacity of the mechanisms and machines, the matlab technology is introduced into the theoretical teaching to provide assisted analysis. At the same time, the matlab is also introduced into the practical teaching to provide theoretical guidance. The teaching effect shows that matlab—based teaching reform under the engineering application can deepen the understandings of course contents for students, improve the interest in learning, strengthen the design capacity and develop the innovation ability.
Impact of a parasitic plant on the structure and dynamics of salt marsh vegetation

We investigated the effect of a native parasitic plant, Cuscuta salina, on the structure and dynamics of the plant community in a California salt marsh. Cuscuta was common in the middle marsh zones. The abundance of Cuscuta was positively correlated with the abundance of Limonium californicum at two sampling scales (0.25- and -40-m2 quadrats). Sampling at the scale of individual plants indicated that the dominant plant in the marsh, Salicornia virginica, was preferred by Cuscuta as a host over Arthrocnemum subterminale, Limonium californicum, and Frankenia salina. This result was confirmed with host-choice experiments in the field. Based on spatial correlations and host-choice experiments, we hypothesized that Cuscuta indirectly facilitated Limonium and Frankenia, increasing plant diversity and initiating vegetation cycles. This hypothesis was supported by sampling patches with different his- tories of Cuscuta infection. Patches with recent heavy Cuscuta infection had reduced Sal- icornia biomass and increased Limonium and Frankenia biomass relative to controls. This effect was most pronounced at higher elevations and in larger, older patches. The hypothesis was also supported by sampling permanent quadrats repeatedly over time. The probability that Cuscuta would invade a quadrat increased with increasing cover of Salicornia. Quadrats containing Cuscuta increased in Limonium and Frankenia cover between censuses relative to quadrats lacking Cuscuta. Our results indicate that parasitic plants can have strong effects on the structure and dynamics of natural vegetation assemblages. However, these effects are mediated by phys- ical and biological gradients across the landscape.
A FUZZY SEGMENTATION-BASED APPROACH TO EXTRACTION OF COASTLINES FROM IKONOS IMAGERY

This paper presents a new approach to effective and accurate extraction of coastlines from commercial high-resolution satellite imagery. The approach is based on a fuzzy segmentation algorithm, which models segmentation of a colour image as a fuzzy c-partition and uses colour histogram analysis and a genetic algorithm to determine the number of clusters and optimal fuzzy c-partition, respectively. After segmenting the satellite image into homogenous regions based on colour similarity, the segmented regions are classified into water and land semiautomatically. Then, morphological operations are applied to filter noise in the classified images. The coastline is finally extracted from the filtered images by a delineation algorithm. The developed approach is tested by using 1 m resolution IKONOS pan-sharpened imagery. The effectiveness of the algorithm is demonstrated by the experimental results and accuracy evaluation.
GEOMETRIC CONTEXT AND ORIENTATION MAP COMBINATION FOR INDOOR CORRIDOR MODELING USING A SINGLE IMAGE

Since people spend most of their time indoors, their indoor activities and related issues in health, security and energy consumption have to be understood. Hence, gathering and representing spatial information of indoor spaces in form of 3D models become very important. Considering the available data gathering techniques with respect to the sensors cost and data processing time, single images proved to be one of the reliable sources. Many of the current single image based indoor space modeling methods are defining the scene as a single box primitive. This domain-specific knowledge is usually not applicable in various cases where multiple corridors are joined at one scene. Here, we addressed this issue by hypothesizing-verifying multiple box primitives which represents the indoor corridor layout. Middle-level perceptual organization is the foundation of the proposed method, which relies on finding corridor layout boundaries using both detected line segments and virtual rays created by orthogonal vanishing points. Due to the presence of objects, shadows and occlusions, a comprehensive interpretation of the edge relations is often concealed. This necessitates the utilization of virtual rays to create a physically valid layout hypothesis. Many of the former methods used Orientation Map or Geometric Context to evaluate their proposed layout hypotheses. Orientation map is a map that reveals the local belief of region orientations computed from line segments, and in a segmented image geometric context uses color, texture, edge, and vanishing point cues to estimate the likelihood of each possible label for all super-pixels. Here, the created layout hypotheses are evaluated by an objective function which considers the fusion of orientation map and geometric context with respect to the horizontal viewing angle at each image pixel. Finally, the best indoor corridor layout hypothesis which gets the highest score from the scoring function will be selected and converted to a 3D model. It should be noted that this method is fully automatic and no human intervention is needed to obtain an approximate 3D reconstruction.
Providing in-between meals during dialysis treatment contributes to an adequate protein and energy intake in hemodialysis patients : a non-randomized intervention study

Mathews Journal of Nutrition & Dietetics Providing In-Between Meals During Dialysis Treatment Contributes to an Adequate Protein And Energy Intake in Hemodialysis Patients: A Non-Randomized Intervention Study Geertrude I Struijk-Wielinga1, Marieke Romijn2, Floor Neelemaat1, Piet M ter Wee2, Peter JM Weijs1,3 1Department of Nutrition and Dietetics, Internal Medicine, VU University Medical Center, Amsterdam, Netherlands. 2Department of Nephrology, VU University Medical Center, Amsterdam, Netherlands. 3School of Sports and Nutrition, Amsterdam University of Applied Sciences, Amsterdam, Netherlands. Corresponding Author: Geertrude I. Struijk-Wielinga, RD, Department of Dietetic and Nutrition, Internal Medicine, VU University Medical Center, De Boelelaan 1117, 1081HV Amsterdam, Netherlands, Tel: 0031 20 4441997; Email: g.struijk@vumc.nl
Australian Catholic Schools Today: School Identity and Leadership Formation.

This article focuses on the challenge of faith leadership in Catholic schools. In particular, it reviews Australian research that has aimed to understand how principals conceptualize and enact their role as faith leaders. Consistent with American research, Australian research found that principals saw themselves as playing a leadership role in the evangelizing mission of the church by strengthening Catholic school identity and culture. At the same time, they were mindful of their limits with respect to their faith leadership capabilities. Moreover, the principals worried that the next generation of school leaders might lack the knowledge, skills, and attitudes to engage faith leadership in a changing social and cultural context. Consequently, they recommended faith leadership formation for teachers as well as principals, their deputies, and assistants. By situating these findings within the theoretical framework of symbolic interactionism, this article argues that, together, the current interest in Australia in Catholic school identity and leadership formation represents a positive development. However, there are also inherent dangers to the imposition of a generic Catholic school identity and a “one size fits all” approach to the leadership role. This article concludes by suggesting a way forward with the promotion of a new model for leadership formation that seeks to avoid these dangers.
Assessing the ability of airborne LiDAR to map river bathymetry

Airborne bathymetric LiDAR was collected for 220 river kilometres in the Yakima and Trinity River Basins in the USA. Concomitant with the aerial data collection, ground surveys of the river bed were performed in both basins. We assess the quality of the bathymetric LiDAR survey from the perspective of its application toward creating accurate, precise and complete streambed topography for numerical modelling and geomorphological assessment. Measurement error is evaluated with respect to ground surveys for magnitude and spatial variation. Analysis of variance statistics indicate that residuals from two independent ground surveys in similar locations do not come from the same population and that mean errors at different study locations also come from different populations. Systematic error indicates a consistent bias in the data and random error falls within values of expected precision. Published in 2007 by John Wiley & Sons, Ltd.
Chapter 7 BASAL GANGLIONIC LEARNING APPLIED TO CONTROL OF AN UNDERACTUATED SYSTEM

This chapter presents a learning algorithm inspired by the neural computation in the basal ganglia and cerebellum. The learning algorithm can be described as a switching-based reinforce algorithm. The performance of the learning algorithm is evaluated by an application to an underactuated system, the Cart-Pole system. Two separate controls, swing-up and balancing controls, are required to successfully achieve the task goal. Adaptive tuning of the control gain is performed by the learning algorithm. The control signal processing and rewardbased learning rule can be interpreted in terms of basal ganglionic neural computations: The parallel operation of the two separate controls mimics the parallel signal processing of the direct and indirect pathways in the basal ganglia. The reward-based update rule may correspond to the long-term potentiation and long-term depression of synaptic plasticity in the striatum inducted by dopamine release. Switching between the two controls can be explained with a plausible neural operation in the cerebellum: Cerebellar neural circuit with inhibition can be interpreted as competitive signal processing, which attains a switching mechanism.
Deep Attentive Structured Language Model based on LSTM

Language model (LM) plays an essential role in natural language processing tasks. Given the context, the language model can predict the next word. However, when the history becomes longer, the single hidden vector may be not big enough to store the entire information. In this paper, we propose a deep attentive structured language model (DAS LM), which extends the Long Short-Term Memory (LSTM) neural network with the attention mechanism. With the alternative input of part of speech (POS) tags, the language model is capable of extracting relations between a word and its context. Our model is evaluated on Penn Treebank, Chinese short message and Swb-Fisher corpora. The experiments in language modeling show that our model achieves significant improvements compared to the conventional LSTM language model.
Cuttlefish: Hierarchical SDN Controllers with Adaptive Offload

Offloading computation to local controllers (closer to switches) has been a popular approach to designing scalable SDN controllers. We observe that, in addition to the offload of local switch-specific state, a subset of global state can also be offloaded to, and accessed at local controllers with suitable synchronization. We present the design and implementation of Cuttlefish, an SDN controller framework that adaptively offloads a portion of the application state (and computation) to local controllers. Cuttlefish uses developer-specified input to identify control messages that can be correctly processed at local controllers, and makes offloading decisions based on the cost of synchronizing the offloaded state across controllers. SDN applications use the Cuttlefish API to access the offloaded state, and Cuttlefish transparently manages the state synchronization, and redirection of control messages to the appropriate (central or local) controller. We have implemented Cuttlefish using the Floodlight SDN controller. Our evaluation shows that Cuttlefish applications achieve ~2X higher control plane throughput and ~50% lower control plane latency as compared to the traditional SDN design.
Robust Path-based Image Segmentation Using Superpixel Denoising

Clustering is the important task of partitioning data into groups with similar characteristics, with one category being spectral clustering where data points are represented as vertices of a graph connected by weighted edges signifying similarity based on distance. The longest leg path distance (LLPD) has shown promise when used in spectral clustering, but is sensitive to noisy data, therefore requiring a data denoising procedure to achieve good performance. Previous denoising techniques have involved identifying and removing noisy data points, however this is not a desirable pre-clustering step for data sets with a specific structure like images. The process of partitioning an image into regions of similar features known as image segmentation can be represented as a clustering problem by defining the vector of intensity and spatial information at each pixel as data point. We therefore propose the method of pre-cluster denoising to formulate a robust LLPD clustering framework. By creating a fine clustering of approximately equal-sized groups and averaging each, a reduced number of data points can be defined that represent the relevant information of the original data set by locally averaging out noise influence. We can then construct a smaller graph representation of the data based on the LLPD between the reduced data points, and identify the spectral embedding coordinates for each reduced point. An out-of-sample extension procedure is then used to compute spectral embedding coordinates at each of the original data points, after which a simple (k-means) clustering is performed to compute the final cluster labels. In the context of image segmentation, computing superpixels provides a nice structure for performing this type of pre-clustering. We show how the above LLPD framework can be carried out in the context of image segmentation, and show that a simple computationally efficient spatial interpolation procedure can be used instead to extend the embedding in a way that yields better segmentation performance with respect to ground truth on a publicly available data set. Similar experiments are also performed using the standard Euclidean distance in place of the LLPD to show the proficiency of the LLPD for image segmentation.
Adversarial Machine Learning Against Digital Watermarking

Machine learning and digital watermarking are independent research areas. Their methods, however, are vulnerable to similar attacks if operated in an adversarial environment. Recent research has thus started to bring both fields together by introducing a unified view for black-box attacks and defenses between learning and watermarking methods. In this paper, we extend this work and examine a novel black-box attack against digital watermarking based on concepts from adversarial learning. With a set of marked images, we let a neural network approximate the watermark detection and use this network to remove the watermark. The attack does not require knowledge of the watermarking scheme.
Impact of intermittent hypoxia on in vitro cultured embryonic rats' cortical neuronal activities and apoptosis

This study aimed to evaluate the impact of Intermittent Hypoxia (IH) on neuronal activity and apoptosis in embryonic rat cortical neurons in vitro. The cultured cortical neurons were randomly divided into four experimental groups: IH group, Intermittent Normal Oxygen group (INO), Persistent Hypoxia group (PH), and Controls (CON). The IH group was further divided into five subgroups according to the degree and time points of hypoxia. Using the MTT cell proliferation assay and 4? , 6-diamidino-2- phenylindole staining to evaluate neuronal cell proliferation and apoptosis, we observed significant differences between the different IH subgroups and the PH group (P 0.05). Under the same hypoxia degree and accumulative time, intermittent oxygen supply exhibited a higher impact on neuronal activities and apoptosis than sustained oxygen supply. Thus, IH could cause significant changes of neuronal activities and apoptosis.
Bridging the Gap between Formal Argumentation and Actual Human Reasoning

s of Invited Talks Structured Argumentation Frameworks and Reasoning with Maximal Consistency Oct. 4 17:30 Ofer Arieli The Academic College of Tel-Aviv A common view in maintaining the consistency of a given set of assertions is that the main information of the set is carried by its consistent subsets and that such subsets should be as large as possible in order not to lose data. Reasoning with maximal consistent subsets of premises has gained a considerable interest since its introduction by Rescher and Manor [5]. A number of applications of this approach and its extensions have been considered for different AI-related areas, such as knowledgebase integration systems, consistency operators for belief revision, computational linguistics, and many others. In this talk we consider several variations of this kind of reasoning, for each one we introduce two complementary computational methods that are based on structured (logical) argumentation theory: 1. a declarative method, based on Dung’s semantics [3] for the underlying (structured) argumentation framework, and 2. a computational (proof-theoretical) method, based on generalized Gentzenstyle sequent calculi [4], applied to the relevant framework. The first approach is a common method to interpret argumentation frameworks by means of extensions, that is: sets of arguments that can be collectively accepted by the reasoners. The second approach is based on what we call dynamic derivations, which are intended for explicating actual reasoning in an argumentation framework. Unlike “standard” proof methods, the idea here is that an argument can be challenged (and possibly withdrawn) by a counter-argument, and so a certain sequent may be considered as not derived at a certain stage of the proof, even if it were considered derived in an earlier stage of the proof. The outcome of the presentation is thus an indication of the strong link, in different settings, between reasoning with consistent sets and argumentative reasoning. A by-product of this are soundness and completeness results of dynamic proof systems with respect to several of Dung’s semantics. This is a joint work with AnneMarie Borg, Jesse Heyninck and Christian Straßer. It is mainly based on the results reported in [1] and [2].