Ideal Case Research Articles

From punishment to help? Continuity and change in the Norwegian decriminalization reform proposal.

In 2018 the Norwegian government appointed a committee to prepare the implementation of a drug decriminalization reform. The overall goal of the committee was to propose a model where responsibility for society's response to the use and possession of illegal drugs for personal use would be transferred from the justice sector to the health service, under the catchphrase 'from punishment to help'. While the proposal ultimately did not get the necessary backing in parliament, the proposed reform still constitutes a very comprehensive and recent proposal for reforming national drug policy and it provides an ideal case for studying contemporary discourses on 'drug decriminalization'. The analysis of this reform proposal is guided by the post-structuralist "What's the Problem Represented to be" (WPR) approach, which is used for investigating the problem representation(s) in the proposal, as well as the rationalities, practices and deep-seated assumptions underpinning these. In doing this, the paper explores how the strategy represents both changes and continuities in discourses around illicit drugs and the people who use them. Based on the WPR approach, two problem representations in the proposal are identified: the 'problem of illicit drug use' and the 'problem of criminalization'. However, the 'problem of illicit drug use' is argued to be the authoritative representation, that takes precedence over the other. In that regard, the paper points to how the proposed shift from the justice sector to the health sector would only be partial, given that the role of the police and drug law enforcement would be retained in the reform. Furthermore, the paper points to how illicit drug use continued to be fundamentally pathologized in the proposed reform. The paper concludes with a discussion about the overall ambition of shifting from a crime-centered to a health-centered approach to people who use drugs and some reflections on the potential of an additional rights-based approach is provided.

The art of plucking the goose: Chinese urban residents' tax consciousness

AbstractPublic finance lies at the heart of politics. It shapes citizens' political attitudes and behaviors. While the expenditure side has been studied very extensively, the income side has been neglected, especially in authoritarian regimes. Taking China as an ideal case, we use a nation‐wide random sample of urban residents to study how citizens under strong authoritarian states perceive their tax burdens. We find that Chinese citizens have low tax consciousness, defined as the perception of fairness both in comparison to people they know and to the amount of public goods they receive. Citizens' income, the amount of public goods they receive, and media consumption have important effects on their tax perception. We argue that there are three mechanisms used by China's “half‐tax state” to reduce their citizens' tax perception: (1) reduce the salience of people's tax burden, conditional on their income level, (2) generate fiscal illusion effects while providing public services in return for taxes paid, and (3) use propaganda to shape the ideology of tax compliance.

Self-supervised machine learning pushes the sensitivity limit in label-free detection of single proteins below 10 kDa

Interferometric scattering (iSCAT) microscopy is a label-free optical method capable of detecting single proteins, localizing their binding positions with nanometer precision, and measuring their mass. In the ideal case, iSCAT is limited by shot noise such that collection of more photons should extend its detection sensitivity to biomolecules of arbitrarily low mass. However, a number of technical noise sources combined with speckle-like background fluctuations have restricted the detection limit in iSCAT. Here, we show that an unsupervised machine learning isolation forest algorithm for anomaly detection pushes the mass sensitivity limit by a factor of 4 to below 10 kDa. We implement this scheme both with a user-defined feature matrix and a self-supervised FastDVDNet and validate our results with correlative fluorescence images recorded in total internal reflection mode. Our work opens the door to optical investigations of small traces of biomolecules and disease markers such as α-synuclein, chemokines and cytokines.

Executive functions are modulated by the context of dual language use: diglossic, bilingual and monolingual older adults

AbstractStudies investigating the role of dual language use in modulating executive functions have reported mixed results, with some studies reporting benefits in older adults. These studies typically focus on bilingual settings, while the role of dual language use in diglossic settings is rarely investigated. In diglossia, the two language varieties are separated by context, making it an ideal test case for the effects on cognition of Single Language Contexts, as defined by the Adaptive Control Hypothesis (Green & Abutalebi, 2013). We compare the performances of three groups of older adults, Arab diglossics (n = 28), bilinguals (n = 29), and monolinguals (n = 41), on the Flanker and Stroop tasks, measuring inhibition abilities, and the Color-shape task, measuring switching abilities. We report a diglossic benefit in inhibition as measured by the Flanker task only, and no benefits for the bilingual group. These findings are discussed with reference to conversational contexts in dual language use.

Critical Participatory Action Research as Leadership Praxis: Sociopolitical Crises as Ordinary Moments for Expansive Educational Leadership

Philadelphia offers an ideal case study for understanding how community and education leaders negotiate the contemporary sociopolitical context and various crises to advance educational equity and justice. This paper focuses on our critical participation action research and organizing within an education coalition to offer an example of community-engaged research that strives for education equity and justice through leadership development. Our goal is to expand conceptualizations of educational leadership to include diverse stakeholders connected to school communities as experts. Toward that end, we examine and amplify the expertise of informal education leaders (e.g., families and communities) involved in struggles for education justice with attention to their response to the twin crises of COVID-19 and uprisings against anti-Black racism and police violence. Our work centers those directly impacted by systems and structures of oppression as experts on relationship building and community engagement. Findings offer insights and strategies to educational leaders for fostering family and community engagement and collaboration in times of crises and conflict.

Incompressible limit for a fluid mixture

In this paper we discuss the incompressible limit for multicomponent fluids in the isothermal ideal case. Both a direct limit-passage in the equation of state and the low Mach-number limit in rescaled PDEs are investigated. Using the relative energy inequality, we obtain convergence results for the densities and the velocity-field under the condition that the incompressible model possesses a sufficiently smooth solution, which is granted at least for a short time. Moreover, in comparison to single-component flows, uniform estimates and the convergence of the pressure are needed in the multicomponent case because the incompressible velocity field is not divergence-free. We show that certain constellations of the mobility tensor allow to control gradients of the entropic variables and yield the convergence of the pressure in L1.

Phase sensitivity of an SU(1,1) interferometer in photon-loss via photon operations.

We study the phase sensitivity of an SU(1,1) interferometer with photon loss by using three different photon operations schemes, i.e., performing photon-addition operation on the input port of the SU(1,1) interferometer (Scheme A), the interior of SU(1,1) interferometer (Scheme B), and both of them (Scheme C). We compare the performance of the three schemes in phase estimation by performing the same times of photon-addition operation to the mode b. The results show that Scheme B improves the phase sensitivity best in ideal case, and Scheme C performs well against internal loss, especially in the case of strong loss. All the three schemes can beat the standard quantum limit in the presence of photon loss, but Scheme B and Scheme C can break through the standard quantum limit in a larger loss range.

Development and Evaluation of a Cellular Vehicle-to-Everything Enabled Energy-Efficient Dynamic Routing Application.

Cellular vehicle-to-everything (C-V2X) is a communication technology that supports various safety, mobility, and environmental applications, given its higher reliability properties compared to other communication technologies. The performance of these C-V2X-enabled intelligent transportation system (ITS) applications is affected by the performance of the C-V2X communication technology (mainly packet loss). Similarly, the performance of the C-V2X communication is dependent on the vehicular traffic density which is affected by the traffic mobility patterns and vehicle routing strategies. Consequently, it is critical to develop a tool that can simulate, analyze, and evaluate the mutual interactions of the transportation and communication systems at the application level to quantify the benefits of C-V2X-enabled ITS applications realistically. In this paper, we demonstrate the benefits gained when using C-V2X Vehicle-to-Infrastructure (V2I) communication technology in an energy-efficient dynamic routing application. Specifically, we develop a Connected Energy-Efficient Dynamic Routing (C-EEDR) application using C-V2X as a communication medium in an integrated vehicular traffic and communication simulator (INTEGRATION). The results demonstrate that the C-EEDR application achieves fuel savings of up to 16.6% and 14.7% in the IDEAL and C-V2X communication cases, respectively, for a peak hour demand on the downtown Los Angeles network considering a 50% level of market penetration of connected vehicles. The results demonstrate that the fuel savings increase with increasing levels of market penetration at lower traffic demand levels (25% and 50% the peak demand). At higher traffic demand levels (75% and 100%), the fuel savings increase with increasing levels of market penetration with maximum benefits at a 50% market penetration rate. Although the communication system is affected by the high density of vehicles at the high traffic demand levels (75% and 100% the peak demand), the C-EEDR application manages to perform reliably, producing system-wide fuel consumption savings.The C-EEDR application achieves fuel savings of 15.2% and 11.7% for the IDEAL communication and 14% and 9% for the C-V2X communication at the 75% and 100% market penetration rates, respectively. Finally, the paper demonstrates that the C-V2X communication constraints only affect the performance of the C-EEDR application at the full demand level when the market penetration of the connected vehicles exceeds 25%. This degradation, however, is minimal (less than a 2.5% reduction in fuel savings).

Exploring the scaling limitations of the variational quantum eigensolver with the bond dissociation of hydride diatomic molecules

AbstractMaterials simulations involving strongly correlated electrons pose fundamental challenges to state‐of‐the‐art electronic structure methods but are hypothesized to be the ideal use case for quantum computing algorithms. To date, no quantum computer has simulated a molecule of a size and complexity relevant to real‐world applications, despite the fact that the variational quantum eigensolver (VQE) algorithm can predict chemically accurate total energies. Nevertheless, because of the many applications of moderately sized, strongly correlated systems, such as molecular catalysts, the successful use of the VQE stands as an important waypoint in the advancement toward useful chemical modeling on near‐term quantum processors. In this paper, we take a significant step in this direction. We lay out the steps, write, and run parallel code for an (emulated) quantum computer to compute the bond dissociation curves of the TiH, LiH, NaH, and KH diatomic hydride molecules using the VQE. TiH was chosen as a relatively simple chemical system that incorporates d orbitals and strong electron correlation. Because current VQE implementations on existing quantum hardware are limited by qubit error rates, the number of qubits available, and the allowable gate depth, recent studies using it have focused on chemical systems involving s and p block elements. Through VQE + UCCSD calculations of TiH, we evaluate the near‐term feasibility of modeling a molecule with d‐orbitals on real quantum hardware. We demonstrate that the inclusion of d‐orbitals and the use of the UCCSD ansatz, which are both necessary to capture the correct TiH physics, dramatically increase the cost of this problem. We estimate the approximate error rates necessary to model TiH on current quantum computing hardware using VQE + UCCSD and show them to likely be prohibitive until significant improvements in hardware and error correction algorithms are available.

Deep learning-based circular disk type radar target detection in complex environment

Target identification is one of the most popular radar uses in real life. Target identification is a classifier that analyzes whether a signal contains an echo from a target (target-present) or is merely noise (target-absent). Deep learning techniques are a popular topic in classification, and they have evinced to be effective in a range of applications. In this paper, a 64 layers Circular Disk type RADAR Target Detection (CDRTD) model is proposed based on Transfer Learning using the SqueezeNet architecture of Convolutional Neural Network (CNN) that functions directly with processed radar target return eco signal and minimize the requirement of conventional laborious radar signal processing. Further, the proposed 64 layers SqueezeNet-based CNN CDRTD model was then implemented to identify circular disk type targets in complex environment. Finally, the target return eco data was tested to identify the circular disk type radar target in complex environments. We further analyzed target detection probability, false alarm rate, precision, recall, F1 in a complex environment and compared it with the ideal case. We found that our proposed CDRTD model can classify 83.3% of the test samples correctly with an overall accuracy of 94.59% in a noisy and cluttered environment whereas 100% of the test samples are classified correctly with an overall accuracy of 100% in an ideal environment.

Experimental Study and Modeling of Solid-liquid Equilibrium for Binary and Ternary Pharmaceutical and Food Systems

Background: The experimental measurement of the solubility of a solute in a given solvent is a difficult task; hence, there is a need for reliable thermodynamic models for its prediction. However, these models require either molecular or group interaction parameters, which are not always available. Objective: The objective of the present study is to measure experimentally the solubility of different solutes in solvents selected from pharmaceutical or food fields on the basis that not all the required model interaction parameters are available to use the obtained experimental data for their determination. Methods: The experimental study of solid-liquid equilibrium for chosen binary and ternary systems at different temperatures was carried out using differential scanning calorimetry to determine the essential thermophysical properties like melting temperature and enthalpy. The modeling of these phase equilibrium data was performed using thermodynamic models like Random Two Liquids (NRTL) and Universal Functional Activity Coefficient (UNIFAC). The required NRTL interaction parameters were determined by minimizing a well-defined objective function using the simplex method. Results: The solubilities of the solutes in the different considered solvents at different temperatures obtained experimentally provided the required NRTL molecular interaction parameters. Solute solubilities were obtained using NRTL, UNIFAC, and ideal models. The comparisons showed an excellent agreement between the experimental values and the NRTL results, contrary to UNIFAC and ideal case models. Conclusion: This study shows the importance of thermodynamic modeling to predict solubility data that may be difficult, time-consuming, and costly to obtain experimentally.

Analytical study of the transport problem in the city of Constantine (North-East of Algeria)

The problem of urban transport is considered to be one of the major concerns facing cities today; this situation is due to several factors, notably the lack of harmony and compatibility between spatial expansion, population growth and the development of road infrastructure in these cities, which are growing at a rate that exceeds that of the road network. The effects are multiple, congestion and traffic jams, pollution, economic and social impacts. Constantine, the third metropolis of Algeria and capital of the eastern region of the country, represents an ideal case to study the subject; given its physical and human geographical specificities, as well as the different interventions in terms of land use planning during the post-independence period. What we are going to approach through the present paper

Theoretical analysis of electrostatic energy harvester configured as Bennet's doubler based on Q‐V cycles

SummaryWe present a theoretical analysis of a MEMS electrostatic energy harvester configured as Bennet's doubler. The steady‐state operation of the circuit can be approximated by a rectangular Q‐V cycle in the ideal case or by a trapezoid diagram when the electrical losses are taken into account. A similarity between the voltage doubler and charge‐pump circuit is highlighted. The analytical solution of the saturation voltage is derived, providing a more insightful comprehension of the system performance and the influence of its parameters. The results obtained from studying the Q‐V diagram coincide with those of circuit simulations for both cases when using (i) a mathematically idealized diode or (ii) a realistic diode model that includes the electrical losses. A configuration employing a simple switch connected in series with one of the three diodes that can further increase the saturation voltage is investigated, providing an efficient alternative for boosting the output voltage of an electrostatic energy harvester.

The effect of collisions on the multi-fluid plasma Richtmyer–Meshkov instability

The Richtmyer–Meshkov instability (RMI) results from the impulsive acceleration of a density interface where the RMI itself or the acceleration is perturbed. The RMI is ubiquitous in shock environments and may arise due to an interface of fluid species, isotopes, temperature, or more. The plasma RMI can be significantly influenced by electromagnetic effects and can be modeled more accurately by a multi-fluid plasma (MFP) model rather than conventional magnetohydrodynamics, though with increased computational expense. MFP modeling of the plasma RMI has revealed many phenomena but has only been completed within the ideal regime. Modeling the effects of elastic collisions is vital for understanding the behavior of the instability in a dense plasma. The Braginskii transport coefficients provide theoretically based relations modeling thermal equilibration, inter-species drag, viscous momentum- and energy-transfers, and thermal conductivity. Our numerical simulations of the MFP RMI with these relations show that the key changes from the ideal case are (1) reduction of relative motion between the ion and electron fluids (consequently affecting the self-generated electromagnetic fields), (2) introduction of anisotropy in momentum and energy via transport coefficients, and (3) damping of high frequency electromagnetic waves and plasma waves. Under the conditions studied, the net effect is a reduction in the MFP RMI amplitude width and the growth rate to levels approaching the neutral fluid instability, as well as a reduction in large scale perturbations along the ion fluid density interface, a positive for inertial confinement fusion efforts. There are, however, two important caveats: small-scale density interface perturbations remain, and the conditions simulated are a few relevant points in a large parameter space that requires further investigation.

Abiotic Methane Reservoirs in the Western Tianshan HP–UHP Metamorphic Belt, China

AbstractNatural gas, consisting primarily of methane (CH4), has become a major source of clean energy in modern society in many parts of the globe. Recent experimental observations and discoveries of deep‐sourced abiotic CH4 in cold subduction zones indicate the important ability of cold subducted slabs to generate natural gas reservoirs. However, most CH4 flux and reservoirs remain unknown and their potential is overlooked in global carbon flux estimations. Massive abiotic CH4‐rich fluid inclusions (FIs) in garnet and omphacite from ultrahigh‐pressure (UHP) eclogites have been found in the Western Tianshan (WT) UHP metamorphic belt, which provides one ideal case for quantification of abiotic CH4 stored in the cold subducted crust. By two methods, we assess the abiotic CH4 content stored in the Chinese WT HP–UHP metamorphic belt. Our calculations show that at least 113 Mt CH4 is stored in the WT eclogites. We also discuss the implications for CH4 reservoirs in subduction zones worldwide and speculate that the cold subduction zones may represent one of the largest, yet overlooked, sources of abiotic CH4 on Earth, which should not be ignored in the global natural resource and carbon flux estimations.

A Random Fourier Feature Based Receiver Detection for Enhanced BER Performance in Nonlinear PD-NOMA

Non-orthogonal multiple access (NOMA) has been proposed as a potential enabler for massive connectivity. Among the different NOMA schemes, power-domain (PD-NOMA) is particularly appealing as it improves user fairness while enhancing spectral efficiency. However, the practical implementation of NOMA faces several challenges, including radio frequency impairments, such as power-amplifier (PA) nonlinearity, which can limit its performance. In this paper, we study the impact of PA nonlinearity on the detection performance of PD-NOMA, and propose a random Fourier feature (RFF) based solution to mitigate the effects of such imperfections. Computer simulations carried out assuming different PA nonlinearity types demonstrate that the proposed RFF based algorithm considerably improves the BER performance and achieves results that are close to the ideal case. Lastly, the analytical proof of our proposed algorithms performance is provided to support our simulation results.

Efficient light transfer in coupled nonlinear triple waveguides using shortcuts to adiabaticity

We use the method of shortcuts to adiabaticity to design the variable couplings in a three-waveguide directional coupler which may contain nonlinear elements, in order to accomplish efficient light transfer between the outer waveguides for shorter device lengths, despite the presence of nonlinearity. The shortcut couplings are obtained for the ideal case where all the waveguides are linear, for which a perfect transfer is guaranteed in theory, but are tested for various combinations of linear and nonlinear waveguides in the device. We show with numerical simulations that, in most configurations, high levels of transfer efficiency can be maintained even for large values of the input power, and for shorter lengths than those of conventional adiabatic devices. We also find that efficiency is improved for shortcut couplings with less spatial extent, since in this case the nonlinearity acts during a shorter range. The present work is expected to find application in research fields like optoelectronic computing and ultrafast light switching, where the fast and controlled light transmission inside a set of waveguides is a crucial task. Additionally, the reduction in the device size may be exploited for incorporating them in integrated optical systems, where a high density of waveguides is required.

Negative Valley Polarization of the Intralayer Exciton via One-Step Growth of H-Type Heterobilayer WS2/MoS2

Vertical type II van der Waals heterobilayers of transition metal dichalcogenides (TMDs) have attracted wide attention due to their distinctive features mostly arising from the emergence of intriguing electronic structures that include moiré-related phenomena. Owing to strong spin-orbit coupling under a noncentrosymmetric environment, TMD heterobilayers host nonequivalent +K and -K valleys of contrasting Berry curvatures, which can be optically controlled by the helicity of optical excitation. The corresponding valley selection rules are well established by not only intralayer excitons but also interlayer excitons. Quite intriguingly, here, we experimentally demonstrate that unusual valley switching can be achieved using the lowest-lying intralayer excitons in H-type heterobilayer WS2/MoS2 prepared by one-step growth. This TMD combination provides an ideal case for interlayer coupling with an almost perfect lattice match, thereby also in the momentum space between +K and -K valleys in the H-type heterostructure. The underlying valley-switching mechanism can be understood by bright-to-dark conversion of initially created electrons in the valley of WS2, followed by interlayer charge transfer to the opposite valley in MoS2. Our suggested model is also confirmed by the absence of valley switching when the lowest-lying excitons in MoS2 are directly generated in the heterobilayer. In contrast to the H-type case, we show that no valley switching is observed from R-type heterobilayers prepared by the same method, where interlayer charge transfer does not occur between the opposite valleys. We compare the case with the series of valley polarization data from other heterobilayer combinations obtained under different excitation energies and temperatures. Our valley switching mechanism can be utilized for valley manipulation by controlling the excitation photon energy together with the photon helicity in valleytronic devices derived from H-type TMD heterobilayers.

Digital platforms to close the information asymmetry GAPS

Market intermediaries coordinate the actions of buyers and sellers. Digital platforms, including the case Platform as a Service (PaaS), take the roles of market intermediaries with some novel ones. In a multi-intermediary world, consumers and suppliers continue to incur search costs due to reacting to multiple intermediaries. Consumers and suppliers discount future net gains due to monetization of search time costs. Consumers have different levels of willingness to pay, suppliers have different opportunity costs, and intermediary firms have different transaction costs. These firms set both bid prices and ask prices. Consumers look for firms that offer a lower purchase price, and suppliers look for firms that offer a higher sale price. Due to such heterogeneity and search costs, the market equilibrium is a distribution of sale prices and a distribution of purchase prices. This equilibrium depends on the discount rate of consumers and suppliers, for whom a higher discount rate stands for a decrease in activity (the number of active consumers and suppliers), while a higher discount rate means an increase in the activity of intermediary firms (the number of active firms): a higher discount rate increases the costs of time-consuming search for consumers and suppliers. Intermediary firms then raise their purchase prices and lower their sale prices because consumers and suppliers are willing to pay a premium to avoid further search, thus increasing the returns to intermediation for firms and stimulating growth in the number of intermediary firms active at the market equilibrium. Thus, the discount rate determines the search costs. When this rate falls to zero, the search costs are eliminated and the relationships between the size of the bid-ask spread and transaction costs are revealed. Then the Walras equilibrium will be the limiting case of the intermediated market when transaction costs fall, and the supply and demand model can be considered an ideal case compatible with the market under consideration at the presence of search costs and price-setting firms. The cloud technologies are saving the general search costs. The two basic cases of providers for such technologies are monopoly and competition.

Development and Validation of Accumulation Term (Distributed and/or Point Source) in a Finite Element Hydrodynamic Model

During tropical storms, precipitation and associated rainfall-runoff can lead to significant flooding, in both the upland and coastal areas. Flooding in coastal areas is compounded by the storm surge. Several hurricanes in recent history have exhibited the destructive force of compound flooding due to precipitation, rainfall-runoff, storm surge and waves. In previous work, various coupled modeling systems have been developed to model total water levels (defined as tides, waves, surge, and rainfall-runoff) for tropical storms. The existing coupled system utilizes a hydrologic model in the upland areas of the domain to capture the precipitation and rainfall-runoff associated with the storms; however, in the coastal areas the precipitation and rainfall-runoff is not captured. Herein a source/sink term is incorporated within the hydrodynamic model itself to capture precipitation and rainfall-runoff over the already inundated coastal areas. The new algorithm is verified for several idealized test cases, and then it is applied to Hurricane Irene. Validation indicates that the new methodology is comparable to the existing river flux forcing under most conditions and allows for the addition of streamflows due to overland runoff, as well as the actual precipitation itself.