Powerful Class Research Articles

Fair vs. fake touristic degrowth

ABSTRACT This contribution aims to advance consideration of the potential and pitfalls entailed in discussions of degrowth within tourism development. Many mass tourist destinations suffer from saturation impacting local working conditions, access to housing and the collective enjoyment of public goods, among the many common drawbacks of so-called ‘overtourism’. Yet proposals to address the negative impacts of mass tourism can become contradictory or even counterproductive. In one manifestation of this dynamic, prominent industry actors increasingly claim to have embraced the agenda of touristic degrowth by focusing on what is euphemistically termed ‘quality tourism’ (fewer tourists who spend more money), which in reality designates elite travel by the most powerful and wealthy social classes. But just as recession is not degrowth, neither can such elitization be considered genuine touristic degrowth, because it does not address the industry’s general eco-social overreach via measures to promote social and environmental justice as degrowth advocates. It could thus instead be labelled ‘fake’ degrowth. By contrast, fair degrowth is defined by a decrease in the flow of energy and materials per capita, in a planned and democratic way, to contribute to equitable redistribution of resource use and access.

Deep phenotyping the cervical spine: automatic characterization of cervical degenerative phenotypes based on T2-weighted MRI.

Radiological degenerative phenotypes provide insight into a patient's overall extent of disease and can be predictive for future pathological developments as well as surgical outcomes and complications. The objective of this study was to develop a reliable method for automatically classifying sagittal MRI image stacks of cervical spinal segments with respect to these degenerative phenotypes. We manually evaluated sagittal image data of the cervical spine of 873 patients (5182 motion segments) with respect to 5 radiological phenotypes. We then used this data set as ground truth for training a range of multi-class multi-label deep learning-based models to classify each motion segment automatically, on which we then performed hyper-parameter optimization. The ground truth evaluations turned out to be relatively balanced for the labels disc displacement posterior, osteophyte anterior superior, osteophyte posterior superior, and osteophyte posterior inferior. Although we could not identify a single model that worked equally well across all the labels, the 3D-convolutional approach turned out to be preferable for classifying all labels. Class imbalance in the training data and label noise made it difficult to achieve high predictive power for underrepresented classes. This shortcoming will be mitigated in the future versions by extending the training data set accordingly. Nevertheless, the classification performance rivals and in some cases surpasses that of human raters, while speeding up the evaluation process to only require a few seconds.

Traditional Rule in the Face of Emerging Elitism in Bafut Noth West Cameroon, 1970-1982

In Bafut, leadership, power and authority resided in the hands of traditional rulers who administered the people according to native law, custom and traditions. The leader was called mfor befeu (translated as fon by colonialist). The fon in his political setting was surrounded by a cream of traditional advisers and institutions such as kwifor and takumbeng, made up of noble men from commoners’ origin and royal family properly rooted in the traditions and customs and needed no other form of training to rule the people. Colonial rule introduced western education with the intention of training young Africans to assist them in administration and governance. Independent African governments inherited the system and spirit. The consequence was the mindset of the educated African tamed against his own customs and traditions. A dichotomy was created in society leading to social class discrimination and power usurpation in local political systems. The educated people hijacked the power machinery from the traditional leaders whom they tagged with stigmatizing words as “illiterate”. This syndrome created what was generally called an “elite class” which regulated power with no recourse to the position of the traditionalists. This paper examines the conflict that ensued in Bafut from 1970 as a result of handing over power to the indigenous westernised and educated elite and imposing them in local affairs and administration. We contend that the involvement of fabricated post-independent elite in leadership positions created conflict given that power tussles between them and the traditional rulers caused societal virtues (as peace) to be trampled upon. We adopted a chronological approach here and from our sources we concluded that elitism in the context of western education acquired is the root of conflict in local politics. Elitism as a concept needs to be carefully tailored to enhance sustainable development and lasting peace in our local communities.

(Invited) Gallium Oxides Devices for Grid-Scale Power Electronics and High Power Switched Mode RF Amplifiers

Within a decade of the first demonstration of a MESFET device, monoclinic β-Ga2O3 (Ga2O3) devices have made incredible progress in breakdown voltages, power device figure of merit and high-speed performance. It has emerged as a promising ultra-widebandgap semiconductor for next generation power, GHz switching and RF applications. In this talk, we will present an overview of our studies on fundamental transport properties, kilovolt class power MOSFETs and aggressively scaled RF devices. The large bandgap of Ga2O3 leads to a high critical field strength. This high field strength in combination with demonstrated room temperature mobility and calculated electron velocity leads to a higher Baliga’s Figure of Merit (BFoM) and Johnston Figure of Merit (JFoM) than current commercially available widebandgap technologies. Additionally, the large bandgap also enables high temperature operation and radiation hardness making it attractive for space applications such as Mars and Venus missions.In the first part, we will discuss the deep insights gained from the first-principles based transport calculations in Ga2O3. We will discuss the limits to low field mobility, saturation velocities and impact ionization coefficients. The impact of the plasmon-phonon coupling on the phonon limited transport will be discussed. We will present the experimental signatures of plasmon-phonon coupling and anti-screening behavior in ionic gated accumulation layers.Next, I will describe our work on the lateral MOSFETs with improved field plate design and beyond-kV breakdown. Temperature dependent analysis and device simulation suggest an extrinsic breakdown mechanism outside the channel. A simple and yet effective SU-8 polymer passivation technology was developed that results in significant improvement in breakdown voltages. The higher field strength of the SU-8 polymer enables a significant increase in breakdown voltage to 8 kVs in lateral MOSFETs. However, these devices show a high Ron, which is due to the depletion caused by RIE of the channel. We will present the use of ultra-high vacuum annealing techniques to improve the on-resistance of the devices still maintaining the multi-kilo-volt rating of the devices.Due to its high JFoM, Ga2O3 is a potential candidate for high power density RF amplifiers. We will also present the performance advancement that can be obtained in RF power performance using Ga2O3 technology. We will present the challenges in the technology and potential solutions. We will present the experimental DC and pulsed measurements on laterally scaled MOSFETs with 100 nm gate length. Severe DC-RF dispersion was observed which is attributed to the RIE damage and surface states on the oxide. Passivation of the devices shows reduced current collapse. Using aggressive gate lengths and gate-source spacing scaling, (AlxGa1-x)2O3/Ga2O3 heterostructure FETs were fabricated that show record high RF performance. The device transconductance was limited by the regrowth interface resistance. Ex-situ silicon nitride passivation was shown to be effective to reduce DC-RF dispersion. Recently, thin channel MOSFETs with deep-sub-micron gate lengths and source/drain regrowth have demonstrated devices with simultaneously low on resistance, high frequency, high voltages.

Techno-economic assessment of wind power generation feasibility in Sabang

Utilization of renewable energy in Aceh is still limited mainly to small-scale electricity through micro-hydro and solar power plants, accounting for less than 1% of the energy composition. Sabang stands out as a region with significant wind energy potential, boasting a speed of 8 m/s and an average power density of 537 W/m2 for the windiest 10% of the region. Therefore, to explore the viability of harnessing wind energy, a pre-feasibility study is needed. This study aimed to assess the techno-economic feasibility of constructing a wind power plant for electricity generation in Sabang by evaluating the region's wind energy. The statistical method of the Weibull Distribution probability density function was employed to evaluate Wind Power Density (WPD), Wind Turbine Capacity Factor, and Energy Output. Additionally, economic feasibility analysis involved calculating Net Present Value (NPV), Benefit Cost Ratio (BCR), Internal Rate of Return (IRR), Discounted Payback Period (DPP), and Levelized Cost of Energy (LCOE). The results showed that Sabang exhibited favorable[UMN1] wind characteristics with a shape parameter (k) of 1.6, average wind speed (Vm) of 7.9 m/s, and scale parameter (c) of 9 m/s. These features classified Sabang as wind power class 6 with a WPD of 735 watts/m2 at a height of 50 m, and the results were categorized as excellent. The study concluded that constructing a wind power plant in Sabang using the Enercon E-70 turbine at a hub height of 100m was technically feasible. The shape parameter (k) was 1.6, the average wind speed (Vm) was 9.3 m/s, scale parameter (c) was 11 m, and the WPD reached 1213 W/m2, leading to a turbine capacity factor of 0.53 and an annual energy production (AEP) of 64,876,560 kW. The economic analysis yielded promising results for wind power projects. The DPP value was estimated at 5.6 years, the BCR at 1.96, the NPV amounted to USD 14,434,994, the IRR reached 17.9%, and the LCOE was assessed at USD 32.50/MWh. Considering all these economic indicators, it was evident that constructing a wind power plant in Sabang was highly feasible and financially viable

A class of power inverted Topp-Leone distribution: Properties, different estimation methods & applications

The power inverted Topp Leone power series (PITLPS) class is a novel three-parameter version of the power inverted Topp Leone (PITL) distribution. The PITLPS class is created by combining a power series distribution with the PITL distribution. This compounding process allows for the creation of flexible classes of distributions with strong physical interpretations in fields such as biology and engineering. The PITLPS class has a number of different hazard rate shapes. This class includes some novel lifetime distributions as well as a new compound class. The formula for the density function, limiting behaviour, moments and incomplete moments, and the Rényi entropy measure are all examined as important distributional features. Furthermore, for one elective model, five distinct estimating approaches are considered. To compare the performance of various estimates, a simulation analysis of the PITL Poisson distribution as a one sub-model is provided. In-depth simulation results have been arranged using partial and overall ranks to find the best estimation technique. Finally, the PITL Poisson model is applied to three real data sets, and the fit is compared to that of some other well-known distributions for explanatory purposes. The proposed model is seen to have certain advantages in interpreting lifetime data when compared to other common models in that it has more shapes and flexibility than many already existing distributions.

Social movements as agents of change: Fighting intersectional food inequalities, building food as webs of life

What does the diversity of social movements and food initiatives tell us about processes of social change? I argue that they offer a productive analytical lens to observe social change because they identify injustices and dynamics of inequalities in the food system and are actively engaged in transforming these. Alternative local food initiatives react to the environmental impacts of globalized food relations; food sovereignty movements highlight class inequalities and power asymmetries in the food system that affect people’s rights to culturally appropriate foodways; food justice movements denounce institutional racism; feminist movements fight persistent gender inequalities from food production to consumption; vegan movements defend animal rights. These are often mapped onto different world regions, with food justice movements more present in the US; food sovereignty movements louder in the Global South; feminist food movements more active in Latin America; and local food movements commonly in the Global North. This article brings together diverse strands of activism and research on social inequalities related to food under the conceptual umbrella of food inequalities. In addition to concept building, it contributes to a sociology of food studies by mapping the geopolitics of knowledge about social change behind the growing mobilization around food issues.

What is the role of the studbook in zoo and aquarium research?

In zoos and aquariums globally, studbooks provide a format by which threatened or important species populations can be carefully managed. These documents can be used to answer complex questions about animal population demographics, animal husbandry, breeding success and mortality. Given the time-intensive nature of studbook collation, only a subset of all animal species held in zoological facilities are managed using these programs. The purpose of this project was to identify how studbooks are being used by researchers, the topics being investigated, and the taxa being covered. To achieve this, data were collected on the types of research paper being produced using studbook information. A literature search, covering several zoo and aquarium journals, was utilized. Data on the types of studbook available were additionally collected for three international zoo organizations. A Poisson regression was run to determine the predictive power of taxonomic class, animal threat status and studbook type on a studbook featuring in published research. Overall, the study identified that taxonomic class and threat status were significant predictors of the number of published studbook papers, with threatened species being more likely to appear in papers. Additionally, population demography was the most common use of studbook data, followed by genetics and reproduction. Not all taxonomic groups were featured in the literature, with mammals featuring much more frequently than would be expected based on the types of studbook available.

Analysis and Design of a Duty-Cycle-Controlled Amplitude Shift Keying Class-E Power Amplifier

This paper presents a method for implementing amplitude modulation in class-E power amplifiers (PA). The output voltage amplitude of a class-E PA is proportional to the input signal duty cycle. The proposed method exploits this feature in order to implement amplitude shift keying (ASK) modulation in the standard class-E power amplifier. The conditions for the optimum operation of a class-E PA while using two different input duty cycles are analyzed. The desired conditions are derived at the same time to reduce differences between optimum circuit elements while using different input duty cycles. The resulting class-E PA satisfies both zero voltage switching (ZVS) and zero derivatives of voltage at switching (ZDVS) conditions by changing only one capacitor. This method neither degrades the efficiency nor needs many changes in circuit components. A step-by-step design procedure based on the proposed method is introduced. The simulations and measurement results verify the accuracy of the proposed method. The fabricated PA is designed to operate at 1MHz frequency with V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DD</sub> = 2V and 50Ω load. The input duty cycle is changed from 25% to 49%, resulting in output amplitudes of 1.2Vpp and 3.68Vpp, and efficiencies of 88% and 94%, respectively.

A Multi-Inverter Multi-Rectifier Wireless Power Transfer System for Charging Stations With Power Loss Optimized Control

Electric vehicles (EVs) with different output power levels can use wireless power transfer (WPT) systems. Different vehicle assemblies (VAs) may be charged by different ground assemblies (GAs) in charging stations. However, the overall efficiency of the WPT system may drop significantly when the power class difference between GA and VA is large. To address this issue this paper proposes a DC-link parallel AC-link series (DPAS) multi-inverter multi-rectifier (MIMR) architecture for high-power WPT systems. Modulation, power transfer capability, and power sharing from the design aspects are investigated. A detailed power loss analysis and an easy-to-implemented power loss optimized control method based on mutual inductance identification are presented in this paper. Finally, experimental results are obtained from a 20-kW LCC-LCC WPT system to validate the analysis and proposed system operation.

Compressible spectral mixture kernels with sparse dependency structures for Gaussian processes

Spectral mixture (SM) kernels comprise a powerful class of generalized kernels for Gaussian processes (GPs) to describe complex patterns. This paper introduces model compression and time- and phase (TP) modulated dependency structures to the original (SM) kernel for improved generalization of GPs. Specifically, by adopting Bienaymé’s identity, we generalize the dependency structure through cross-covariance between the SM components. Then, we propose a novel SM kernel with a dependency structure (SMD) by using cross-convolution between the SM components. Furthermore, we ameliorate the expressiveness of the dependency structure by parameterizing it with time and phase delays. The dependency structure has clear interpretations in terms of spectral density, covariance behavior, and sampling path. To enrich the SMD with effective hyperparameter initialization, compressible SM kernel components, and sparse dependency structures, we introduce a novel structure adaptation (SA) algorithm in the end. A thorough comparative analysis of the SMD on both synthetic and real-life applications corroborates its efficacy.

Ongoing Clinical Trials of Nonviral siRNA Therapeutics.

Short interfering RNAs (siRNA) are a powerful class of genetic medicines whose clinical translation can be hindered by their suboptimal delivery properties in vivo. Here, we provide a clinically focused overview that summarizes ongoing siRNA clinical trials from the perspective of innovations in nonviral delivery strategies. More specifically, our review begins by highlighting the delivery barriers and physiochemical properties of siRNA that make it challenging to deliver it in vivo. We then provide commentary on specific delivery strategies, including sequence modification, siRNA ligand conjugation, and nanoparticle and exosomal packaging, each of which can be used to control the delivery of siRNA therapies in living systems. Last, we provide a summary table of ongoing siRNA clinical trials which also highlights the indication of use, target, and National Clinical Trial (NCT) number associated with each entry. In writing this review, our work aims to highlight the key challenges and strategies for effective nonviral siRNA delivery in vivo, while simultaneously summarizing information on ongoing clinical trials for siRNA therapy in humans.

Surplus Labour in the South at the Current Juncture: A Note

Abstract The ascendancy of neoliberalism from the 1970s has resulted in a massive crisis of reproduction and expansion of labour reserves globally, in particular in the South, contributing significantly to the current global crisis of capitalism. Contemporary neoliberal capitalism has structurally reconfigured the balance of class power everywhere in favour of capital in general, resulting in substantial deterioration in the world of work and workers’ well-being everywhere. This article explores the evolving dynamics of surplus labour in the South at the current juncture through the lens of the Marxian political economy, in the context of some of the most powerful features underlying the ongoing structural transformations in contemporary world capitalism.

Fiscal expropriation in Turkey under the rule of Erdoğan

This work signifies an attempt to elaborate on the concrete workings of fiscal policy in today’s Turkey through the notion of primitive accumulation. The subject matter is a political regime that constitutes itself increasingly through coercion. And to understand the political regime’s constitution in its wholeness, its concrete existence in its relations with the economic life surrounding it, primitive accumulation – the notion that construes coercion as an economic power – is necessary. Furthermore, since the notion of class struggle is inherent to primitive accumulation, the latter notion also elicits to reflect on the formation of the state as it hinges on the class society. The notion of primitive accumulation reveals the class power that the state predicates and the concrete ends that this predicate sights. Political coercion can’t be comprehended separately from the capitalist accumulation, and in the case of Turkey, their unity finds expression most clearly in the practices of fiscal expropriation. Throughout the work, fiscal expropriation is examined through three specific forms it takes: the unity of over-taxation with growing indebtedness of the state, public procurement regime, and public–private partnerships. All of them signify the proletarianisation and further impoverishment of the people just as in the era when Karl Marx has drawn up the notion of primitive accumulation.

Class struggle and the origins of finance capital in Britain, 1870–1920

Marxists often link the emergence of finance capital to developments in the categories of capital, such as flight to money capital, sometimes associated with changes in the organic composition of capital. While not disputing the importance of transformations in capitalist categories, this paper examines the causal role of working-class agency in the emergence of finance capital. The paper addresses finance capital in Britain, giving due consideration to a variety of causal factors cementing its dominance. It then considers the role of labour unrest in developing a working class in itself, gravitating towards and away from political expressions (syndicalism, social democracy) in pursuance of its immediate economic struggles. The overall argument is that the emergence of finance capital in the parasitic form it took in Britain was fundamentally a response to the power of a working class in itself. Parasitism became the default trend to control the working class and prevent any potential movement towards a working class for itself from gaining hegemony.

Meta-Reinforcement-Learning-Based Current Control of Permanent Magnet Synchronous Motor Drives for a Wide Range of Power Classes

Data-driven reinforcement learning-based controller schemes have much potential to aid the design of model-free control algorithms that can be trained without the necessity of plant-specific parameter knowledge. Unfortunately, the corresponding training phase is a time- and possibly money-consuming process which needs to be repeated whenever application to a new plant system is requested. To reduce the total training time for a large set of heterogeneous plant systems, this article proposes a meta-reinforcement learning-based approach that is to be utilized for control of hundreds of different permanent magnet synchronous motor drives ranging from a few watts to hundreds of kilowatts. So-called context variables carry the meta information about the set of considered drive systems. Their estimation using a corresponding artificial neural network as context approximator is a core aspect of this article. The context information allows the reinforcement learning-based control algorithm to automatically adapt itself to individual motor drives without requiring individual plant training. Since the found context variables can also be interpreted as an implicit system identification result they allow to determine irregular plant behavior (e.g., faulty drives) as an added bonus of the proposed meta-reinforcement learning scheme. Empirical results during this proof of concept successfully validate the potential of the proposed approach to drastically reduce the total training time and encourage further research.

Experimental verification of high-performance polymer gears in an electric vehicle powertrain

AbstractGears made of polymers increasingly gain relevance in current research and industrial practice. Due to their advantages such as low density and the possibility of cost-efficient production in large quantities, more and more efforts are made to substitute steel gears with polymer wherever possible. However, the usage of polymer gears in current vehicle systems is still almost exclusively limited to applications with restricted power transmission, like actuators. To extend the field of application to power transmissions as well, in this study a transmission was developed for the usage in a small electric vehicle of the 7Le power class considering the application of polymer gears. Compared to the serial transmission, one of the gear stages was completely substituted with polymer gears. The load-carrying capacity of the newly designed hybrid polymer-steel transmission was investigated for functional verification on a specially developed test rig as well as inside a modified demonstrator vehicle under real-life conditions. Assuming usual operating conditions, the load-carrying capacity of the polymer gears appears suitable for the aimed application on the test rig as well as inside the demonstrator vehicle. Moreover, with increased power and under continuous sustained loading, high performance of the polymer stage as well as a stable temperature behavior can be observed. Under the given circumstances, polymer gears can be used as part of a powertrain in small electric vehicles.

An improved FSK-modulated class-E power and data transmitter for biomedical implants

This paper presents an efficient dual-resonance biomedical inductive link for frequency-shift keying (FSK) modulation. In this link, the combination of PCB coil as the main coil and the solenoid as the compact inductance creates a dual-resonance coil. 3.22 mm of winding diameter in solenoid makes the link suitable for biomedical implants. Using the dual-resonance link, an efficient FSK-modulated power and data transmitter is proposed for biomedical implants to transmit power and data simultaneously with the same carriers and a single inductive link. So, there is no concern about the interference between power and data carriers. Also, the presence of two resonance frequencies at the secondary side of the link significantly improves the efficiency. With a 6 mm air gap and 2.5 Mbps data rate (DR), the measured power delivered to load (PDL) and power transmission efficiency (PTE) are 57.4 mW and 48.4%, respectively. Also, with a 6 mm interface of beef ribs + medical-grade silicone, the measured PDL and PTE are 48.2 mW and 38.8%, respectively. The measured bit error rate (BER) for 2.5 Mbps data rate is less than 10-5.

Towards 5G new radio sidelink communications: A versatile link-level simulator and performance evaluation

Sidelink in cellular networks enables direct exchange of data packets between devices without the need for network infrastructure, resulting in various benefits, including communication in out-of-coverage areas and possible decrease in latency by a considerable extent. Thus, sidelink is a favorable choice for applications like public safety communications and Vehicle-to-Everything (V2X) communications. As 4G Long Term Evolution (LTE) advanced to 5G New Radio (NR) under the Third Generation Partnership Project (3GPP), several new features were introduced to sidelink, such as two-stage Sidelink Control Informations (SCIs), data and control multiplexing, and feedback-based Hybrid Automatic Repeat Request (HARQ) with a configurable maximum number of transmissions. To conduct extensive NR sidelink link-level evaluations, a comprehensive simulation platform is essential. In this paper, we introduce the first publicly accessible 5G NR Link-Level Simulator (LLS) that supports major 5G NR sidelink features and complies with the 3GPP standards. This MATLAB-based simulator allows for flexible control over various Physical Layer (PHY) configurations, facilitating customized simulations on algorithm development and performance evaluations. We discuss the simulator’s structure and the sidelink features implemented in detail and evaluate the 5G NR sidelink performance using the developed simulator. Our simulation results indicate that the Block Error Rate (BLER) curves are insensitive to error-prone 2nd-stage Sidelink Control Information (SCI2) and number of Resource Blocks (RBs) allocated; however, the sidelink communication range is sensitive to the deployment environment. We also highlight the need for a careful choice of numerology, device power class and HARQ configuration to balance performance metrics for a variety of services based on 5G NR sidelink deployment scenarios.

Towards global neural network abstractions with locally-exact reconstruction

Neural networks are a powerful class of non-linear functions. However, their black-box nature makes it difficult to explain their behaviour and certify their safety. Abstraction techniques address this challenge by transforming the neural network into a simpler, over-approximated function. Unfortunately, existing abstraction techniques are slack, which limits their applicability to small local regions of the input domain. In this paper, we propose Global Interval Neural Network Abstractions with Center-Exact Reconstruction (GINNACER). Our novel abstraction technique produces sound over-approximation bounds over the whole input domain while guaranteeing exact reconstructions for any given local input. Our experiments show that GINNACER is several orders of magnitude tighter than state-of-the-art global abstraction techniques, while being competitive with local ones.