Conservative Networks Research Articles

Lagrangian dual framework for conservative neural network solutions of kinetic equations

<p style='text-indent:20px;'>In this paper, we propose a novel conservative formulation for solving kinetic equations via neural networks. More precisely, we formulate the learning problem as a constrained optimization problem with constraints that represent the physical conservation laws. The constraints are relaxed toward the residual loss function by the Lagrangian duality. By imposing physical conservation properties of the solution as constraints of the learning problem, we demonstrate far more accurate approximations of the solutions in terms of errors and the conservation laws, for the kinetic Fokker-Planck equation and the homogeneous Boltzmann equation.</p>

Identifying key interactions between process variables of different material categories using mutual information-based network inference method

This paper analyzes production data from injection molding processes to identify key interactions between the process variables from different material categories using the network inference method called “bagging conservative causal core network” (BC3net). This approach is an ensemble method with mutual information that is measured between process variables to select pairs that show significant shared information. We construct networks for different time intervals and aggregate them by calculating the proportion of significant pairs of process variables (weighted edges) for each production process over time. The weighted edges of the aggregated network for each product are used in a machine learning model to optimize the network interval size (interval split) and feature selection, where edge weights are the input features and material categories are the output classification labels. The time intervals are optimized based on the classification accuracy of the machine learning model. Our analysis shows that the aggregated edge features of inferred networks can classify different material categories and identify critical features that represent interdependence in the associated process variables. We further used the “one vs. other” labels for the machine learning models to identify material-specific interactions for each material category. Additionally, we constructed an aggregated network over all samples in which the process variable interactions were steady over time. The resulting network showed modular characteristics where process variables of similar categories were grouped in the same community.

Illiberal thought collectives and policy networks in Hungary and Poland

ABSTRACT Focusing on the emergence of ideas and the knowledge networks involved in producing a counter-narrative to the liberal and neoliberal ideational consensus of the 1990s and 2000s, this contribution traces the intellectual trajectory of the illiberal turn in Poland and Hungary. We make use of the ideational scholarship differentiating between public philosophies, problem definitions and policy solutions to discuss how illiberal state transformation and heterodox socio-economic policies became the new paradigm that the two ruling parties PiS and Fidesz have promoted during the last decade. We suggest that the viability of PiS and Fidesz’s policies was largely conditioned by the increasing influence of conservative networks in the public sphere which prepared the grounds for these reforms. The contribution discusses the main intellectual actors, structures, and ideas paving the way and legitimizing illiberalism in the two countries.

Impact of Surgical and Transcatheter Aortic Valve Replacement in Low-Gradient Aortic Stenosis: A Meta-Analysis.

The aim of this study was to assess the impact of aortic valve replacement (AVR) on survival in patients with each subclass of low-gradient (LG) aortic stenosis (AS) and to compare outcomes following surgical AVR (SAVR) and transcatheter AVR (TAVR). LG severe AS encompasses a wide variety of pathophysiology, including classical low-flow, LG (LF-LG), paradoxical LF-LG, and normal-flow, LG (NF-LG) AS, and uncertainty exists regarding the impact of AVR on each subclass of LG AS. PubMed and Embase were queried through October 2020 to identify studies comparing survival with different management strategies (SAVR, TAVR, and conservative) in patients with LG AS. Pairwise meta-analysis comparing AVR versus conservative management and network meta-analysis comparing SAVR versus TAVR versus conservative management were performed. Thirty-two studies with a total of 6,515 patients and a median follow-up time of 24.2months (interquartile range: 36.5months) were included. AVR was associated with a significant decrease in all-cause mortality in classical LF-LG (hazard ratio [HR]: 0.42; 95% confidence interval [CI]: 0.36 to 0.48), paradoxical LF-LG (HR: 0.41; 95%CI: 0.29 to 0.57), and NF-LG (HR: 0.41; 95%CI: 0.27 to 0.62) AS compared with conservative management. SAVR and TAVR were each associated with a decrease in all-cause mortality in classical LF-LG (HR: 0.46 [95%CI: 0.38 to 0.55] and 0.49 [95%CI: 0.37 to 0.64], respectively), paradoxical LF-LG (HR: 0.42 [95%CI: 0.28 to 0.65] and 0.42 [95%CI: 0.25 to 0.72], respectively), and NF-LG (HR: 0.40 [95%CI: 0.21 to 0.77] and 0.46 [95%CI: 0.26 to 0.84], respectively) AS compared with conservative management. No significant difference was observed between SAVR and TAVR. In all subclasses of LG AS, AVR was associated with a significant decrease in all-cause mortality regardless of surgical or transcatheter approach.

Orthodox Conservatism and the Refugee Crisis in Bulgaria and Moldova

In 2015, the Bulgarian Orthodox Church issued an unusual statement declaring that the arrival of refugees represented a “true invasion” in the region. One year later, during debates on Moldova’s presidential elections, the Orthodox Church endorsed the fake news that 30,000 Syrians were about to arrive in the country. Drawing on interviews in Chişinău and Sofia, the article argues that the European refugee crisis has led to an internationally-linked Orthodox conservatism characterized by five components: defending a mythical past; fostering close relations with state authorities; anti-Westernism; building conservative networks at local, national, and geopolitical levels; and presenting Orthodox churches as alternative governance structures. These components shape religion–state relations in predominantly Orthodox countries in the region and have had a direct impact on the ways in which religious and state bodies have responded to populism and geopolitics.

Political Ideology and Corporate Innovation: Evidence from the Expansion of a Local TV Network

We investigate how political ideology affects corporate innovation by using the expansion of Sinclair Broadcasting, the largest conservative media network in the U.S., as a plausible shock to the local ideology. We find that innovation quantity (patent counts) and quality (citation counts per patent, originality, generality, the number of impactful patents, and the economic value of innovation) fall significantly upon the Sinclair entry to a local TV market. The effect is driven by the departure of innovative talent, and the decline in innovativenesss among the inventors who remain in the firms. These findings are important especially with the increasing political divide in the U.S., and the heightened polarization in the media environment.

Impact of Trump's Promotion of Unproven COVID-19 Treatments and Subsequent Internet Trends: Observational Study.

BackgroundIndividuals with large followings can influence public opinions and behaviors, especially during a pandemic. In the early days of the pandemic, US president Donald J Trump has endorsed the use of unproven therapies. Subsequently, a death attributed to the wrongful ingestion of a chloroquine-containing compound occurred.ObjectiveWe investigated Donald J Trump’s speeches and Twitter posts, as well as Google searches and Amazon purchases, and television airtime for mentions of hydroxychloroquine, chloroquine, azithromycin, and remdesivir.MethodsTwitter sourcing was catalogued with Factba.se, and analytics data, both past and present, were analyzed with Tweet Binder to assess average analytics data on key metrics. Donald J Trump’s time spent discussing unverified treatments on the United States’ 5 largest TV stations was catalogued with the Global Database of Events, Language, and Tone, and his speech transcripts were obtained from White House briefings. Google searches and shopping trends were analyzed with Google Trends. Amazon purchases were assessed using Helium 10 software.ResultsFrom March 1 to April 30, 2020, Donald J Trump made 11 tweets about unproven therapies and mentioned these therapies 65 times in White House briefings, especially touting hydroxychloroquine and chloroquine. These tweets had an impression reach of 300% above Donald J Trump’s average. Following these tweets, at least 2% of airtime on conservative networks for treatment modalities like azithromycin and continuous mentions of such treatments were observed on stations like Fox News. Google searches and purchases increased following his first press conference on March 19, 2020, and increased again following his tweets on March 21, 2020. The same is true for medications on Amazon, with purchases for medicine substitutes, such as hydroxychloroquine, increasing by 200%.ConclusionsIndividuals in positions of power can sway public purchasing, resulting in undesired effects when the individuals’ claims are unverified. Public health officials must work to dissuade the use of unproven treatments for COVID-19.

Anti-abortion activism in the Czech Republic and Slovakia: ‘nationalizing’ the strategies

ABSTRACT The article focuses on the changing strategies of anti-abortion activists in the Czech Republic and Slovakia. Firstly, it explores the interlinkage with the global conservative network and describes the shared strategies. Secondly, it focuses on the role of religion and church in the Czech Republic and Slovakia with an emphasis on abortion attitudes in both countries. Thirdly, by pointing out the expected public role of religion in each country, the text examines the specific nature of anti-abortion activism in the political, public, and service spheres of the Czech Republic and Slovakia. Drawing upon comparative design, the article argues that, despite the mutual history of the two countries, the anti-abortion movements are driven to choose different strategies with which to promote their cause that reflects the ‘national’ cultural and religious ethos of the country. Whereas in the secularized Czech Republic, activists follow a model of downplaying religious background, the decentralized Slovak movements oscillate between appealing to traditional Catholic morality and engaging in more secularized strategies similar to those adopted by the Czech movements.

Conservative TV and Corporate Social Responsibility

We study the impact of exposure to conservative media on firms’ CSR activities using the quasi-natural expansion of Sinclair Broadcast Group: the largest conservative broadcasting network in the U.S. local TV markets. In a difference-in-differences setting, we find that firms significantly reduce CSR activities after exposure to Sinclair TV in all three dimensions: environmental, social, and governance. Consistent with ideology as a driver of our results, the effect is stronger when there is more propensity for the audience to accept Sinclair messaging: for example, for firms belonging to the gun, tobacco, and gambling industries, when Sinclair acquires more Fox-affiliated TV stations, and for those headquartered in Republican-leaning counties. Cross-sectional evidence also suggests stronger effects associated with lower institutional ownership, past prosecution history, or younger CEOs. Related, we find no impact of Sinclair exposure on firms’ accounting performance measured by ROA, but a negative impact on their Tobin’s Q and stock returns.

Robust design for a multi-echelon regional construction and demolition waste reverse logistics network based on decision Maker’s conservative attitude

Improving the robustness of a reverse logistics network for construction and demolition waste (C&DW) can increase the ability of the network to mitigate supply uncertainty. However, a very conservative network may entail a higher price for its increased robustness. Thus, to maximize the robustness decision utility, decision-makers need to make a trade-off between relative robustness against uncertain situations and the price of such robustness. In this paper, we argue that facility capacity acquisition can improve the robustness of the network. We use a robust optimization method to establish the decision-making model for this problem, and propose a way to prove the model’s effectiveness in providing a lower bound of network robustness. Then the study takes on a real case in the Chongming district of Shanghai, China, and conducts a Monte Carlo simulation to investigate the trade-off performance. The results show that based on the decision-maker’s conservative attitude toward uncertain situations, the proposed model can adjust the robustness of the reverse logistics network. They also show that accepting a lower degree of robustness will result in substantial savings, due to the high “price” of robustness. This study provides a decision tool to help design a robust reverse logistics network under uncertain situations.

Enhancement of CoAP based congestion control in IoT network - a novel approach

IoT technologies are an inclusive kind of application and provide insolent environments. IoT devices accomplish actuating and recognize tasks through unique addresses. Resources of the WSN control the memory utilization of the network, network bandwidth, and network power consumption. The traffic strategy of the WSN IoT network is different from the conservative network. CoAP is the best data protocol in handling consistency and congestion control in the IoT environment. It is very important in cluster communication in multicast with server and numerous clients. This work emphasizes CoAP due to its squat overhead to reduce consumption in memory utilization and reduced the overall network power consumption. The proposed work presents a new approach to predict congestion control with the best feasible technique. An advanced congestion control mechanism uses various margins implemented using CoAP to analyze. Network congestion information is transpiring via massive, constrained communication devices. The proposed work implementation results are shows that it is better to compare to the real terms like transmission of packets, reduction in the latency, and increase in the transmission response time and reduction in power consumption.

Conservative physics-informed neural networks on discrete domains for conservation laws: Applications to forward and inverse problems

We propose a conservative physics-informed neural network (cPINN) on discrete domains for nonlinear conservation laws. Here, the term discrete domain represents the discrete sub-domains obtained after division of the computational domain, where PINN is applied and the conservation property of cPINN is obtained by enforcing the flux continuity in the strong form along the sub-domain interfaces. In case of hyperbolic conservation laws, the convective flux contributes at the interfaces, whereas in case of viscous conservation laws, both convective and diffusive fluxes contribute. Apart from the flux continuity condition, an average solution (given by two different neural networks) is also enforced at the common interface between two sub-domains. One can also employ a deep neural network in the domain, where the solution may have complex structure, whereas a shallow neural network can be used in the sub-domains with relatively simple and smooth solutions. Another advantage of the proposed method is the additional freedom it gives in terms of the choice of optimization algorithm and the various training parameters like residual points, activation function, width and depth of the network etc. Various forms of errors involved in cPINN such as optimization, generalization and approximation errors and their sources are discussed briefly. In cPINN, locally adaptive activation functions are used, hence training the model faster compared to its fixed counterparts. Both, forward and inverse problems are solved using the proposed method. Various test cases ranging from scalar nonlinear conservation laws like Burgers, Korteweg–de Vries (KdV) equations to systems of conservation laws, like compressible Euler equations are solved. The lid-driven cavity test case governed by incompressible Navier–Stokes equation is also solved and the results are compared against a benchmark solution. The proposed method enjoys the property of domain decomposition with separate neural networks in each sub-domain, and it efficiently lends itself to parallelized computation, where each sub-domain can be assigned to a different computational node.

Who passes restrictive labour policy? A view from the States

AbstractWhat leads states to adopt more restrictive labour policies? The conventional wisdom is that unified Republican states, with help from conservative political networks, are more likely to adopt restrictions on labour unions. We argue that party control of government matters but is constrained by voter preferences and the power of organised labour. We create new estimates of state-level public support for unions by income thirds using dynamic multilevel regression and poststratification. Using this measure, we predict the adoption of restrictive labour policies, such as right-to-work and minimum wage preemption laws. We find that Republican governments are less likely to adopt restrictive policies when unions are strong and when union support among middle- and low-income earners is high. Interestingly, these results run contrary to much of the literature on the unequal representation of the wealthy in public policy.

The Diffusion of Christian Mysticism: From the Medieval Rhineland to Contemporary China

The Diffusion of Christian Mysticism: From the Medieval Rhineland to Contemporary China Glen G. Scorgie (bio) It was 1938, between the two great World Wars. China was in upheaval, and the Middle Kingdom’s first experiment with Western-style democracy was in tatters. The Communists under Chairman Mao would not be able to consolidate their hold on the nation for another decade. But meanwhile, Japan was encroaching, and local gangs and militias roamed the country. Regional conflicts ebbed and flowed. Against this volatile backdrop, a new, growing, fiercely independent and theologically conservative network of Protestant churches known as the Little Flock decided to prepare and publish the first-ever Chinese translation of the autobiography of the seventeenth century French mystic Madame Guyon. The title of this abridged translation was Sweet Smelling Myrrh.1 Observing this is rather like wandering through some farmer’s pasture and discovering an asteroid. How on earth did this get here? By what sequence of events, what chain of relationships and baton relays did Madame Guyon and her Quietist mysticism show up in China, and to such a surprisingly warm welcome from earnest Chinese Protestants? Not so long ago Jonah Berger published for a wide readership a book entitled Contagious: Why Things Catch On.2 A lot of people found it quite fascinating. For a time, it enjoyed the spotlight as a New York Times bestseller. And in a more scholarly format, Everett M. Rogers has pioneered the sociological study of the diffusion of innovations.3 How do things catch on? Scholars of Christian spirituality should begin searching for answers to this question, which is so critical to the future of Christian spirituality itself. We need more studies of how various spiritual themes, practices, and experiences have traveled through time, diffused across geographic regions, and taken root in new settings. Such studies will also surely confirm that elements of Christian spirituality inevitably morph as they adapt to new traditions and contexts, and embrace local wisdom. As a small contribution to this recommended genre of inquiry, this essay explores (admittedly, from a very high-altitude vantage point) the journey of Christian mysticism from the medieval Rhineland to parts of modern-day China via rather unexpected carriers—populist Protestant preachers, Holiness [End Page 1] evangelists, and missionaries shaped by the Keswick Movement. It is a narrative that would have been difficult to predict, and one in which, incidentally, thin little books play pivotal roles. THE NATURE OF CHRISTIAN MYSTICISM In order to trace any historical pathway of Christian mysticism, we must first penetrate “the cloud of unknowing” that too often surrounds the term itself. If at all possible, we should try to put the mystification of mysticism behind us. Built into the very word mysticism is an acknowledgment of the ultimately ineffable nature of this experience. But the mystery in the experience does not justify murkiness in its definition. I think it is best (and in our circles, probably safest) to align with Bernard McGinn’s generously inclusive depiction of mysticism as direct and immediate apprehension of the divine presence.4 The consciousness of which he speaks goes beyond, or moves deeper than, the more familiar and more objective experiences of sensing, knowing and loving.5 Karl Rahner has helpfully tagged at least a couple of important additional features of the mystical experience when he described it as “a genuine experience of God emerging from the very heart of our existence.”6 In the language of the biblical Psalmist, deep calleth unto deep. The function of mystical theology is to provide seekers with an interpretive orientation to such a quest, and to guide them into proven pathways toward its realization. Typically, the term mystic is reserved for those who are “all in” in their yearning for, and their relentless pursuit of, such experience of the divine. Nevertheless, it must also be acknowledged that there is at least a mystical dimension to the experiences of most Christians, and it is difficult to imagine how a religious commitment can be sustained in the long haul without it. A strain of the mystical has been present in the Christian tradition from the very beginning.7 Its earliest phase was catalyzed...

The Integrative Complexity of Media Reports of Natural Disasters: A Preliminary Analysis

Integrative complexity is a measure of the intellectual style used by individuals or groups in processing information, problem-solving, and decision making. Research generally shows that integratively complex thinkers are better able to reach mutually advantageous solutions to complex problems, although they may also be less likely to act when necessary. A substantial portion of the published research on integrative complexity comes from political scientists who have focused on examining linguistic distinctions across the liberal-conservative political spectrum. In this research, we assessed integrative complexity in a sample of news stories concerning natural disasters (hurricanes, wildfires and floods) from three television news networks that span the liberal-conservative spectrum. The results showed that the news coverage of the network considered to be more liberal in its reporting scored significantly higher in integrative complexity than the news coverage of the more conservative network. These findings align with previous research that has used integrative complexity as a dependent measure. We discuss the practical implications of these findings as they relate to the quality of decisions made by relevant officials that typically precedes and follows large-scale natural disasters.

When State Policy Makes National Politics: The Case of "Obamacare" Marketplace Implementation.

State governments have been powerful sites of Republican resistance to the implementation of the Affordable Care Act (ACA), the Democratic Party's signature 2010 law. By influencing how citizens experience the ACA, state-level implementation can affect the national-level political implications of the law. I examine three largely unstudied areas of marketplace implementation: navigator laws, transitional plan termination, and rating area configurations. For each policy area, I use linear probability models to investigate the determinants of state lawmakers bolstering or eroding marketplaces. In each case, Democrat-controlled states were more likely to bolster marketplaces than Republican-controlled states were, with decisions more polarized in those policy areas-navigator laws and transitional plan termination-and with greater potential for national-level feedback. For navigator laws, where Republican state lawmakers were most cross-pressured by national party interests and local interests, marketplace eroding policy was highly associated with strength of conservative networks. Crafters of federal legislation cannot expect state lawmakers to universally implement federal law to maximize the direct benefits to their constituents. Rather, we should expect state lawmakers to, in many instances, implement federal law in ways that benefit their parties.

Energy Storage and POPI Networks in Power Processing Systems

In this paper, the modeling of storage elements and a unified theory liberated of the I–V characteristics of a specific technology is developed. First, the definition of an ideal storage element with limited energy capacity is presented, then the semiideal storage properties are discussed. The addition of power conservative two-port network denoted POPI (Pout = Pin) is added in order to define a flexible storage element in terms of characteristics. The paper demonstrates the theory by examples of storage elements integrated in power electronics systems. The ideas and methodology presented in this work can be applied to power electronics applications as well as power systems, smart grids, and microgrids, where storage is an important factor.

Modern-Day Crusaders in Europe. Tradition, Family and Property

Three recent events affecting human rights in sexuality and reproduction (a proposed ban on abortion in Poland, blocking support for She Decides in Croatia and halting a civil union law in Estonia) were spearheaded by organizations which appear to be the national antennae of the transnational, socially conservative network called Tradition, Family and Property (TFP). TFP refers to a set of interrelated conservative, Catholic-inspired organizations which share a common world view inspired by the TFP founder, Plinio Corrêa de Oliveira. Originating in Brazil in 1960 and eventually spreading throughout the world, TFP has long been an insurrection movement within Catholicism, with a distinct way of working by fusing social conservatism with economic hyper-liberalism and a legacy of complicity with far-right movements. Having withered away from Latin America, TFP is now an active European network with positions against sexual and reproductive rights (SRR ) among its priorities. TFP’s influence on SRR takes three main routes: social mobilization; norm entrepreneur and entering decision-making spaces. TFP has found new horizons in Eastern Europe and ambitions to influence the European Union and the United Nations. The reactionary narrative of TFP espousing religious orthodoxy and sanctifying economic inequality could become attractive to some by offering religious legitimization for illiberalism and authoritarianism.

Cross-Layer Optimization & VGALA Structure for 5G Grid

Heterogeneous cloud radio access network (HCRAN) promises higher energy efficiency (EE) than the conservative cellular networks by centralizing the baseband signal processing into the baseband unit (BBU) pool hosted by cloud computing platforms. In existing energy-efficient networking mechanisms designed for conservative cellular networks cannot fully leverage the parameters like latency, load balancing, power consumption and the network energy consumption. In this work ,Cross-layer based VGALA optimization structure is proposed which endeavours a balance between network utilities. The average traffic delivery latency, green energy utilization are techniques used to optimize the packet dropping policy, power allocation policy and bandwidth allocation policy to minimize the transmit power under the QoS constraint. The optimal solution is obtained, depends upon both channel and queue state information. The final result show that recommended framework empowers an adaptable trade off among the on grid power consumption and the normal traffic latency. And finally saves a significant amount of on-grid power and the optimal solution obtained depends on both channel and queue state information. It also shows that setting the three packet loss probabilities as equal causes marginal power loss caused in H-CRAN design.

Probabilistic Power Flow Analysis of Bulk Power System for Practical Grid Planning Application

The sizes of PV power plants have grown in such a way that their effects on the power system can no longer be neglected. In order to address these issues, grid operators are forced to expand grid connection points, and a power flow analysis considering uncertain renewable generation is required. Thus, a modified probabilistic power flow (PPF) analysis for practical grid planning is suggested in this paper. The regularity and randomness of PV power are modeled by a Monte Carlo-based probabilistic model combining both k-means clustering and the kernel density estimation method. The certain cluster group is selected so as to reflect the severe PV generation scenario, and the chi-square test to represent the $n$ th conservative network planning was suggested. In order to provide the power flow result more effectively, a mapping function of graphic representation based on a significant grid code violation is provided in an automatic PPF tool written by Python scripts. Following this procedure yields a reasonable network design for various renewable energy penetration levels.