bluuebunny/crossref_metadata_2025 huggingface dataset:
Urbanization and population contraction
Authors: Muroishi Madoka , Yakita Akira
Published: July 2022

Urbanization is treated in the literature as a process that occurs along with economic development. We consider an overlapping generations model with two regions, designated as ‘urban’ and ‘rural’. Concentration of population to urban areas involves population inflows from rural areas, thereby exacerbating urban congestion. Inverse agglomeration economies in rural areas exert negative effects on rural income, consequently increasing the attractiveness of urban areas. Because of lower urban fertility rates, urbanization involves population decreases. Therefore, population dynamics might be explained as simultaneous urbanization and population contraction. However, depopulation mitigates congestion, which increases the fertility rate and the worker’s lifetime utility level. Eventually, it can lead to a stationary population size.
Combining N-mixture models with ecological niche modeling supplies a low-cost and fast procedure for estimating population size in remote areas
Authors: Sacchi Roberto , Coladonato Alan Jioele , Scali Stefano , Mangiacotti Marco , Zuffi Marco Alberto Luca
Published: July 2022

Monitoring population changes and trends is a central task in conservation. However, obtaining detailed information for wide and low accessible areas, such as remote islands, is challenging, and cannot be achieved with conventional approaches, such as capture–mark–recapture protocols (CMR). In this paper, we show that combining N-mixture models with ecological niche modeling allows assessing reliable estimates of population size over large target areas on short time intervals. We used it to estimate the population size of a subspecies of the Italian wall lizards (Podarcis siculus calabresiae) endemic to the Island of Montecristo (10.39 km2 in surface). During a single week, we first generated a niche model of the species based on satellite images sampled few days before sampling. Then, we estimated lizard abundance through Bayesian N-mixture models on repeated counts (n = 3) along transects (n = 6), settled in different areas of habitat suitability defined on the basis of the niche model. Finally, we estimated in approximately 20.000 the total number of lizards living in the Island by extrapolating the values computed on transects to the areas of the islands with the same suitability estimated by the niche model. The procedure can be easily repeated allowing monitoring the status of conservation of the species in the island of Montecristo. More in general, this procedure has the potential to be applied to monitor any other species of conservation interest in remote areas whenever detailed satellite images are available.

Graphical Abstract
Invite everyone to the table, but not to every course
Authors: Oschinsky Frederike Marie , Klein Hans Christian , Niehaves Bjoern
Published: July 2022

Innovative collaboration strategies are a promising tool for fostering the governance of smart cities while acknowledging citizen centricity. During implementation, however, determining the number and background of the involved actors is challenging. The Design-Thinking (DT) approach appears suitable for addressing this issue as it offers a concrete and adaptable course of action. The present contribution involves a study on implementing DT principles in a German health resort and identifies three critical components: (1) team, (2) process, and (3) workspace. Our use case is an adaptable project- and workshop plan that encourages the implementation of DT collaboration in smart cities when designing digital services. Our results provide initial guidelines on how to involve diverse actors, when to integrate trained DT coaches, and how to design collaborative innovation in a digital way. The practice-oriented insights gained in the study can be applied, adapted, and discussed in other smart cities and citizen-centered projects.
Visual analysis of blow molding machine multivariate time series data
Authors: Musleh Maath , Chatzimparmpas Angelos , Jusufi Ilir
Published: July 2022

The recent development in the data analytics field provides a boost in production for modern industries. Small-sized factories intend to take full advantage of the data collected by sensors used in their machinery. The ultimate goal is to minimize cost and maximize quality, resulting in an increase in profit. In collaboration with domain experts, we implemented a data visualization tool to enable decision-makers in a plastic factory to improve their production process. The tool is an interactive dashboard with multiple coordinated views supporting the exploration from both local and global perspectives. In summary, we investigate three different aspects: methods for preprocessing multivariate time series data, clustering approaches for the already refined data, and visualization techniques that aid domain experts in gaining insights into the different stages of the production process. Here we present our ongoing results grounded in a human-centered development process. We adopt a formative evaluation approach to continuously upgrade our dashboard design that eventually meets partners’ requirements and follows the best practices within the field. We also conducted a case study with a domain expert to validate the potential application of the tool in the real-life context. Finally, we assessed the usability and usefulness of the tool with a two-layer summative evaluation that showed encouraging results.

Graphical Abstract
Onsite/offsite social commerce adoption for SMEs using fuzzy linguistic decision making in complex framework
Authors: Hussain Walayat , Merigo Jose M.
Published: July 2022

There has been a growing social commerce adoption trend among SMEs for few years. However, it is often a challenging strategic task for SMEs to choose the right type of social commerce. SMEs usually have a limited budget, technical skills and resources and want to maximise productivity with those limited resources. There is much literature that discusses the social commerce adoption strategy for SMEs. However, there is no work to enable SMEs to choose social commerce—onsite/offsite or hybrid strategy. Moreover, very few studies allow the decision-makers to handle uncertain, complex nonlinear relationships of social commerce adoption factors. The paper proposes a fuzzy linguistic multi-criteria group decision-making in a complex framework for onsite, offsite social commerce adoption to address the problem. The proposed approach uses a novel hybrid approach by combining FAHP, FOWA and selection criteria of the technological–organisation–environment (TOE) framework. Unlike previous methods, the proposed approach uses the decision maker's attitudinal characteristics and recommends intelligently using the OWA operator. The approach further demonstrates the decision behaviour of the decision-makers with Fuzzy Minimum (FMin), Fuzzy Maximum (FMax), Laplace criteria, Hurwicz criteria, FWA, FOWA and FPOWA. The framework enables the SMEs to choose the right type of social commerce considering TOE factors that help them build a stronger relationship with current and potential customers. The approach's applicability is demonstrated using a case study of three SMEs seeking to adopt a social commerce type. The analysis results indicate the proposed approach's effectiveness in handling uncertain, complex nonlinear decisions in social commerce adoption.
Clozapine-Induced Chemogenetic Neuromodulation Rescues Post-Stroke Deficits After Chronic Capsular Infarct
Authors: Cho Jongwook , Ryu Seungjun , Lee Sunwoo , Kim Junsoo , Park Ji-Young , Kwon Hyuk-Sang , Kim Hyoung-Ihl
Published: July 2022

Long-term disabilities induced by stroke impose a heavy burden on patients, families, caregivers, and public health systems. Extensive studies have demonstrated the therapeutic value of neuromodulation in enhancing post-stroke recovery. Among them, chemogenetic neuromodulation activated by clozapine-N-oxide (CNO) has been proposed as the potential tool of neuromodulation. However, recent evidence showed that CNO does not cross the blood − brain barrier and may in fact have low binding affinity for chemogenetic tool. Thus, clozapine (CLZ) has been suggested for use in chemogenetic neuromodulation, in place of CNO, because it readily crosses the blood–brain barrier. Previously we reported that low doses of CLZ (0.1 mg/kg) successfully induced neural responses without off-target effects. Here, we show that low-dose clozapine (0.1 mg/kg) can induce prolonged chemogenetic activation while avoiding permeability issues and minimizing off-target effects. In addition, clozapine-induced excitatory chemogenetic neuromodulation (CLZ-ChemoNM) of sensory-parietal cortex with hsyn-hM3Dq-YFP-enhanced motor recovery in a chronic capsular infarct model of stroke in rats, improving post-stroke behavioral scores to 56% of pre-infarct levels. Longitudinal 2-deoxy-2-[18F]-fluoro-D-glucose microPET (FDG-microPET) scans showed that a reduction in diaschisis volume and activation of corticostriatal circuits were both correlated with post-stroke recovery. We also found c-Fos increases in bilateral cortices and BDNF increases in the cortices and striatum after CLZ-ChemoNM, indicating an increase in neural plasticity. These findings suggest the translational feasibility of CLZ-ChemoNM for augmenting recovery in chronic stroke.
A Neural-Symbolic Approach for Explanation Generation Based on Sub-concept Detection: An Application of Metric Learning for Low-Time-Budget Labeling
Authors: Rabold Johannes
Published: July 2022

Deep learning methods, although effective in their assigned tasks, are mostly black-boxes with respect to their inner workings. For image classification with CNNs, there exists a variety of visual explanation methods that highlight parts of input images that were relevant for the classification result. But in many domains visual highlighting may not be expressive enough when the classification relies on complex relations within visual concepts. This paper presents an approach to enrich visual explanations with verbal local explanations, emphasizing important relational information. The proposed SymMetric algorithm combines metric learning and inductive logic programming (ILP). Labels given by a human for a small subset of important image parts are first generalized to a neighborhood of similar images using a learned distance metric. The information about labels and their spatial relations is then used to build background knowledge for ILP and ultimately to learn a first-order theory that locally explains the black-box with respect to the given image. The approach is evaluated with the Dogs vs. Cats data set demonstrating the generalization ability of metric learning and with Picasso Faces to illustrate recognition of spatial meaningful constellations of sub-concepts and creation of an expressive explanation.
The Ergogenic Effects of Acute Carbohydrate Feeding on Resistance Exercise Performance: A Systematic Review and Meta-analysis
Authors: King Andrew , Helms Eric , Zinn Caryn , Jukic Ivan
Published: July 2022

Background

Carbohydrate (CHO) ingestion has an ergogenic effect on endurance training performance. Less is known about the effect of acute CHO ingestion on resistance training (RT) performance and equivocal results are reported in the literature.

Objective

The current systematic review and meta-analysis sought to determine if and to what degree CHO ingestion influences RT performance.

Methods

PubMed, MEDLINE, SportDiscus, Scopus, and CINAHL databases were searched for peer-reviewed articles written in English that used a cross-over design to assess the acute effect of CHO ingestion on RT performance outcomes (e.g., muscle strength, power, and endurance) in healthy human participants compared to a placebo or water-only conditions. The Cochrane Collaboration’s risk of bias tool and GRADE approaches were used to assess risk of bias and certainty of evidence, respectively. Random effects meta-analyses were performed for total training session volume and post-exercise blood lactate and glucose. Sub-group meta-analysis and meta-regression were performed for categorical (session and fast durations) and continuous (total number of maximal effort sets, load used, and CHO dose) covariates, respectively.

Results

Twenty-one studies met the inclusion criteria (n = 226 participants). Pooled results revealed a significant benefit of CHO ingestion in comparison to a placebo or control for total session training volume (standardised mean difference [SMD] = 0.61). Sub-group analysis revealed a significant benefit of CHO ingestion during sessions longer than 45 min (SMD = 1.02) and after a fast duration of 8 h or longer (SMD = 0.39). Pooled results revealed elevated post-exercise blood lactate (SMD = 0.58) and blood glucose (SMD = 2.36) with CHO ingestion. Meta-regression indicated that the number of maximal effort sets, but not CHO dose or load used, moderates the effect of CHO ingestion on RT performance (beta co-efficient [b] = 0.11). Carbohydrate dose does not moderate post-exercise lactate accumulation nor do maximal effort sets completed, load used, and CHO dose moderate the effect of CHO ingestion on post-exercise blood glucose.

Conclusions

Carbohydrate ingestion has an ergogenic effect on RT performance by enhancing volume performance, which is more likely to occur when sessions exceed 45 min and where the fast duration is ≥ 8 h. Further, the effect is moderated by the number of maximal effort sets completed, but not the load used or CHO dose. Post-exercise blood lactate is elevated following CHO ingestion but may come at the expense of an extended time-course of recovery due to the additional training volume performed. Post-exercise blood glucose is elevated when CHO is ingested during RT, but it is presently unclear if it has an impact on RT performance.

Protocol Registration

The original protocol was prospectively registered on the Open Science Framework (Project identifier: https://doi.org/10.17605/OSF.IO/HJFBW).
Electron transfer dominated triboelectrification at the hydrophobic/slippery substrate—water interfaces
Authors: Chen Yi , Li Xiaojuan , Xu Chenggong , Wang Daoai , Huang Jinxia , Guo Zhiguang , Liu Weimin
Published: July 2022

Triboelectric nanogenerator (TENG) based on triboelectrification has attracted wide attention due to its effective utilization of green energy sources such as marine energy. However, researches about liquid-liquid triboelectrification are still scanty as solid—liquid triboelectrification has been widely studied. Herein, this work focuses on the hydrophobic/slippery substrate—water interfacial triboelectrification based on the solid friction materials of polytetrafluoroethylene (PTFE) nanoparticles. The hydrophobic/slippery substrate—water interfacial triboelectrification are studied by assembling PTFE coated Al sheets and perfluoropolyether (PFPE) infused PTFE coated Al sheets (formed the slippery lubricant-infused surfaces (SLIPSs)) as the friction electrode, and water as liquid friction materials, respectively. The results show that the hydrophobic TENG output performances improved as the PTFE nanoparticles cumulating, and the SLIPSs TENG output performances increased with the thinner PFPE thickness. Both the triboelectrification behavior of hydrophobic/SLIPSs TENG assembled in this work are dominated by the electron transfer. Thanks to the introduction of SLIPSs, the SLIPSs TENG exhibits superior stability and durability than the hydrophobic TENG. The investigation of hydrophobic/slippery substrate—water interfacial triboelectrification contributes to optimize the TENG performances, and expands the application in harsh environments including low temperature and high humidity on the ocean.
Quantifying safety risks of deep neural networks
Authors: Xu Peipei , Ruan Wenjie , Huang Xiaowei
Published: July 2022

Safety concerns on the deep neural networks (DNNs) have been raised when they are applied to critical sectors. In this paper, we define safety risks by requesting the alignment of network’s decision with human perception. To enable a general methodology for quantifying safety risks, we define a generic safety property and instantiate it to express various safety risks. For the quantification of risks, we take the maximum radius of safe norm balls, in which no safety risk exists. The computation of the maximum safe radius is reduced to the computation of their respective Lipschitz metrics—the quantities to be computed. In addition to the known adversarial example, reachability example, and invariant example, in this paper, we identify a new class of risk—uncertainty example—on which humans can tell easily, but the network is unsure. We develop an algorithm, inspired by derivative-free optimization techniques and accelerated by tensor-based parallelization on GPUs, to support an efficient computation of the metrics. We perform evaluations on several benchmark neural networks, including ACSC-Xu, MNIST, CIFAR-10, and ImageNet networks. The experiments show that our method can achieve competitive performance on safety quantification in terms of the tightness and the efficiency of computation. Importantly, as a generic approach, our method can work with a broad class of safety risks and without restrictions on the structure of neural networks.
A coin selection strategy based on the greedy and genetic algorithm
Authors: Wei Xuelin , Wu Chang , Yu Haoran , Liu Siyan , Yuan Yihong
Published: July 2022

Coin selection method refers to the process undergone when selecting a set of unspent transaction outputs (UTXOs) from a cryptocurrency wallet or account to use as inputs in each transaction. The most applied coin selection method that UTXO-based cryptocurrencies currently employ is an algorithm that decides on a certain set of UTXOs that matches the target amount and limits the transaction fee. However this approach trades off favourable maintenance overhead of the entire network for low transaction fees, as many low-value UTXOs known as “dust” is produced. Over time, this will impact the scalability and management of the cryptocurrency network as the global set of UTXOs become larger. Therefore, there is an urgency to find a higher-performing coin selection method suitable for UTXO-based cryptocurrencies. This paper proposes a method based on the greedy and genetic algorithm for effectively choosing sets of UTXOs in Bitcoin. The main objective of this coin selection strategy is to get as close as possible to the target while also maintaining and possibly reducing the number of UTXO inputs.
Deep learning based brain tumor segmentation: a survey
Authors: Liu Zhihua , Tong Lei , Chen Long , Jiang Zheheng , Zhou Feixiang , Zhang Qianni , Zhang Xiangrong , Jin Yaochu , Zhou Huiyu
Published: July 2022

Brain tumor segmentation is one of the most challenging problems in medical image analysis. The goal of brain tumor segmentation is to generate accurate delineation of brain tumor regions. In recent years, deep learning methods have shown promising performance in solving various computer vision problems, such as image classification, object detection and semantic segmentation. A number of deep learning based methods have been applied to brain tumor segmentation and achieved promising results. Considering the remarkable breakthroughs made by state-of-the-art technologies, we provide this survey with a comprehensive study of recently developed deep learning based brain tumor segmentation techniques. More than 150 scientific papers are selected and discussed in this survey, extensively covering technical aspects such as network architecture design, segmentation under imbalanced conditions, and multi-modality processes. We also provide insightful discussions for future development directions.
A simple method to form a forest of carbon nanotube bundles during growth stage
Authors: Alzahrani Ahmed Obaid M. , Alayash Meshari , Alghamdi Salem
Published: July 2022

This study reports a novel, cost-effective and reproducible method of densifying carbon nanotubes into bundles during growth stage. This is achieved by utilizing Fe3O4 catalyst nanoparticles and microwave plasma-enhanced chemical vapor deposition. The grown CNTs were characterized using TEM, SEM and Raman spectrometer. The achieved site density of bundles is 5 × 109 m–2, with an inter-bundle distance of 14 μm and bundle height of 17 μm. A qualitative investigation was carried out, and a possible densification mechanism was proposed.

Article Highlights

A cost-effective method to form bundles of carbon nanotubes.

Densification of carbon nanotubes occurs during growth stage.

The resultant structures are desirable for electron field emission applications.
Analyzing the EU Migration Crisis as Reflected on Twitter
Authors: Mukherjee Sagnik , Hauthal Eva , Burghardt Dirk
Published: July 2022

The proliferation of social media has resulted in its extensive use as a valuable source of information for researchers. This paper aims to use Twitter data to analyze and visualize tweets about the migration crisis in the European Union from 2016 to 2021. The paper uses a methodology to structure data for better understanding of complex social media data. The methods and metrics include the facet model of location based social media, the HyperLogLog data structure and novel uses of the metric typicality. The authors have also developed a web based interactive application closely following the methodology used to organize the dataset. Additionally the work also includes maps using spatial typicality which could be utilized for studying spatial phenomenon. The case study selected also provides unique insights and sets a template for working with multi-lingual geo-social media data. The authors believe that these methods and metrics could be reproduced for other case studies and aid in understanding and communication geo-social media data.
Modelling the Impact of Individual Preferences on Traffic Policies
Authors: Nguyen Johannes , Powers Simon T. , Urquhart Neil , Farrenkopf Thomas , Guckert Michael
Published: July 2022

Urban traffic is a system always prone to overload, often approaching breakdown during rush hour times. Well-adjusted modifications of traffic policies, with appropriate interventions, promise potential improvements by inducing change in both individual as well as global system behaviour. However, truly effective measures are hard to identify, and testing in vivo is at least expensive and often hardly feasible. Computer-based simulations have successfully been applied for studying effects of policies, and multi-agent systems are accepted tools for that purpose as they provide means to model individual behaviour. These simulations have primarily studied effects of policies by measuring performance indicators on social benefit, while effects on individuals are hardly considered. However, successful implementation of policies hinges on whether they are accepted by the common public. Thus, effects on individuals cannot be neglected. Evaluating effects on individuals requires a more detailed modelling that is able to capture individual preferences as determining factors of agent decisions. In this paper, we present a simulation framework that focuses on modelling of individuals and thus allows evaluation of effects of policies on both the individual as well as global system behaviour. We use semantic technology (OWL ontologies and SWRL rules) to model preferences and knowledge of agents in our simulation. Using AGADE Traffic simulator, we demonstrate modelling and simulation for a mobility scenario and discuss observed results.
Spatial social network research: a bibliometric analysis
Authors: Wu Ling , Peng Qiong , Lemke Michael , Hu Tao , Gong Xi
Published: July 2022

A restless and dynamic intellectual landscape has taken hold in the field of spatial social network studies, given the increasingly attention towards fine-scale human dynamics in this urbanizing and mobile world. The measuring parameters of such dramatic growth of the literature include scientific outputs, domain categories, major journals, countries, institutions, and frequently used keywords. The research in the field has been characterized by fast development of relevant scholarly articles and growing collaboration among and across institutions. The Journal of Economic Geography, Annals of the Association of American Geographers, and Urban Studies ranked first, second, and third, respectively, according to average citations. The United States, United Kingdom, and China were the countries that yielded the most published studies in the field. The number of international collaborative studies published in non-native English-speaking countries (such as France, Italy, and the Netherlands) were higher than native English-speaking countries. Wuhan University, the University of Oxford, and Harvard University were the universities that published the most in the field. “Twitter”, “big data”, “networks”, “spatial analysis”, and “social capital” have been the major keywords over the past 20 years. At the same time, the keywords such as “social media”, “Twitter”, “big data”, “geography”, “China”, “human mobility”, “machine learning”, “GIS”, “location-based social networks”, “clustering”, “data mining”, and “location-based services” have attracted increasing attention in that same time frame, indicating the future research trends.
Platelet Rich Plasma (PRP) Growth Factor Concentration Varies in Men with Erectile Dysfunction
Authors: Khodamoradi Kajal , Dullea Alexandra , Golan Roei , Molina Manuel , Arora Himanshu , Masterson Thomas A. , Ramasamy Ranjith
Published: July 2022

Background

Platelet Rich Plasma (PRP) is a novel therapy rich in growth factors and cytokines used to target the underlying causes of erectile dysfunction (ED). It is not known, however, if the composition of growth factors in PRP varies between men.

Aim

To evaluate PRP growth factor variability among men with ED.

Methods

Whole blood was collected from 8 participants with at least a 6-month history of ED. Seven men with Peyronie’s disease and 1 healthy male (without sexual dysfunction) were used as the control group. PRP was extracted from whole blood using the Arthrex Angel system. A Human Growth Factor Antibody Array for 41 proteins was performed using 3 participants and the healthy control. Using all 16 samples, quantitative detection of factors from the array that were decreased by 1.5-fold were validated with western blot.

Outcomes

From the growth factor array, 2 growth factors—granulocyte-macrophage colony stimulating factor and transforming growth factor-β were identified as having a 1.5-fold decrease between the participants and the control. Vascular endothelial growth factor (VEGF) was selected because androgens can upregulate VEGF production. Other than a weak negative correlation between VEGF expression and age, we found no correlation between growth factor expression for granulocyte-macrophage colony stimulating factor or transforming growth factor-β and age, body mass index, or comorbidities.

Clinical Translation

PRP growth factor concentration appears to vary among men with ED. PRP treatment for ED may need to be personalized for patients, depending on individual growth factor concentration.

Strengths and Limitations

This study demonstrates the variability in PRP growth factors among men with ED. This is an important finding in the investigation of PRP as a restorative treatment option for men with ED. Our study, however, was limited by a small sample size.

Conclusion

PRP growth factors vary among men with ED.
The Use of Intravenous Lidocaine as an Analgesic Modality in the Austere Environment: Two Cases
Authors: Dryden Bryce , Kerr Win B. , Higgins Sophie , Tou Kevin , Dhanjal Sandeep T.
Published: July 2022

Providing effective analgesia for trauma in austere settings is particularly difficult and often complicated by equipment and medication limitations and harsh environmental conditions. Common modalities that are employed in conventional clinical practices may not be available or pragmatic in austere environments. Furthermore, side effects such as sedation, altered mentation, or hypoxemia require additional resources and attention. We report 2 cases that demonstrate the use of intravenous lidocaine for the management of acute pain, secondary to trauma, in an austere environment. In the first, the administration of intravenous lidocaine reduced pain, secondary to a tibia fracture, thereby facilitating splinting. In the second, a patient, who had sustained rib fractures, was also treated with intravenous lidocaine. In this case, the analgesic effects of the medication resulted in reduction in pain and improvement in pulmonary function. Of note, the narrow therapeutic window of this modality was made evident as both patients transiently experienced tinnitus following the initial lidocaine bolus. This report describes 2 cases in which intravenous lidocaine was used to manage acute pain, in an austere environment, while avoiding many of the detrimental effects that accompany alternative analgesics.
Mesopotamian Civilization and the Origins of the New Testament
Authors: Baker Robin
Published: July 2022

In this ground-breaking study, Robin Baker investigates the contribution ancient Mesopotamian theology made to the origins of Christianity. Drawing on a formidable range of primary sources, Baker's conclusions challenge the widely held opinion that the theological imprint of Babylonia and Assyria on the New Testament is minimal, and what Mesopotamian legacy it contains was mediated by the Hebrew Bible and ancient Jewish sources. After evaluating and substantially supplementing previous research on this mediation, Baker demonstrates significant direct Mesopotamian influence on the New Testament presentation of Jesus and particularly the character of his kingship. He also identifies likely channels of transmission. Baker documents substantial differences among New Testament authors in borrowing Mesopotamian conceptions to formulate their Christology. This monograph is an essential resource for specialists and students of the New Testament as well as for scholars interested in religious transmission in the ancient Near East and the afterlife of Mesopotamian culture.
The Housing Crisis in Superstar Cities: Labour Markets, Price Inflation, and Financialization
Authors: Findeisen Francesco
Published: July 2022

This article advances explanations of the housing crisis in modern political economies. It argues that the rise of agglomeration economies is driving the massive increase in housing prices in superstar cities. These concentrate high-paying jobs and life chances in central metropolitan areas, pulling in a highly skilled workforce who are willing and able to pay ‘whatever it takes’ for access to these opportunities. As a result, the value of homeownership in strategic urban locations has surged. Investors have thus found it rational to capitalize on longer-term price inflation and invest. Based on a comparison between New York City, London, Paris, and Berlin, this article demonstrates that housing prices in superstar cities move in lockstep with the reconfiguration of urban labour markets. Investors follow this trend in their decisions to invest in housing, which further compounds affordability pressures. The article concludes that access to homeownership in strategic urban locations increasingly mediates inequality and class formation in modern political economies.
Tisagenlecleucel for relapsed/refractory acute lymphoblastic leukemia in the Irish healthcare setting: cost-effectiveness and value of information analysis
Authors: Carey Niamh , Leahy Joy , Trela-Larsen Lea , McCullagh Laura , Barry Michael
Published: July 2022

Objectives

This study evaluates the cost-effectiveness of tisagenlecleucel (a CAR T-cell therapy), versus blinatumomab, for the treatment of pediatric and young adult patients with relapsed/refractory acute lymphoblastic leukemia (R/R ALL) in the Irish healthcare setting. The value of conducting further research, to investigate the value of uncertainty associated with the decision problem, is assessed by means of expected value of perfect information (EVPI) and partial EVPI (EVPPI) analyses.

Methods

A three-state partitioned survival model was developed. A short-term decision tree partitioned patients in the tisagenlecleucel arm according to infusion status. Survival was extrapolated to 60 months; general population mortality with a standardized mortality ratio was then applied. Estimated EVPI and EVPPI were scaled up to population according to the incidence of the decision.

Results

At list prices, the incremental cost-effectiveness ratio was EUR 73,086 per quality-adjusted life year (QALY) (incremental costs EUR 156,928; incremental QALYs 2.15). The probability of cost-effectiveness, at the willingness-to-pay threshold of EUR 45,000 per QALY, was 16 percent. At this threshold, population EVPI was EUR 314,455; population EVPPI was below EUR 100,000 for each parameter category.

Conclusions

Tisagenlecleucel is not cost effective, versus blinatumomab, for the treatment of pediatric and young adult patients with R/R ALL in Ireland (at list prices). Further research to decrease decision (parameter) uncertainty, at the defined willingness-to-pay threshold, may not be of value. However, there is a high degree of uncertainty underpinning the analysis, which may not be captured by EVPI analysis.
Fluctuation response patterns of network dynamics – An introduction
Authors: ZHANG XIAOZHU , TIMME MARC
Published: July 2022

Networked dynamical systems, i.e., systems of dynamical units coupled via nontrivial interaction topologies, constitute models of broad classes of complex systems, ranging from gene regulatory and metabolic circuits in our cells to pandemics spreading across continents. Most of such systems are driven by irregular and distributed fluctuating input signals from the environment. Yet how networked dynamical systems collectively respond to such fluctuations depends on the location and type of driving signal, the interaction topology and several other factors and remains largely unknown to date. As a key example, modern electric power grids are undergoing a rapid and systematic transformation towards more sustainable systems, signified by high penetrations of renewable energy sources. These in turn introduce significant fluctuations in power input and thereby pose immediate challenges to the stable operation of power grid systems. How power grid systems dynamically respond to fluctuating power feed-in as well as other temporal changes is critical for ensuring a reliable operation of power grids yet not well understood. In this work, we systematically introduce a linear response theory (LRT) for fluctuation-driven networked dynamical systems. The derivations presented not only provide approximate analytical descriptions of the dynamical responses of networks, but more importantly, also allow to extract key qualitative features about spatio-temporally distributed response patterns. Specifically, we provide a general formulation of a LRT for perturbed networked dynamical systems, explicate how dynamic network response patterns arise from the solution of the linearised response dynamics, and emphasise the role of LRT in predicting and comprehending power grid responses on different temporal and spatial scales and to various types of disturbances. Understanding such patterns from a general, mathematical perspective enables to estimate network responses quickly and intuitively, and to develop guiding principles for, e.g., power grid operation, control and design.
Psilocybin in neuropsychiatry: a review of its pharmacology, safety, and efficacy
Authors: Dodd Seetal , Norman Trevor R. , Eyre Harris A. , Stahl Stephen M. , Phillips Arnie , Carvalho André F. , Berk Michael
Published: July 2022

Psilocybin is a tryptamine alkaloid found in some mushrooms, especially those of the genus Psilocybe. Psilocybin has four metabolites including the pharmacologically active primary metabolite psilocin, which readily enters the systemic circulation. The psychoactive effects of psilocin are believed to arise due to the partial agonist effects at the 5HT2A receptor. Psilocin also binds to various other receptor subtypes although the actions of psilocin at other receptors are not fully explored. Psilocybin administered at doses sufficient to cause hallucinogenic experiences has been trialed for addictive disorders, anxiety and depression. This review investigates studies of psilocybin and psilocin and assesses the potential for use of psilocybin and a treatment agent in neuropsychiatry. The potential for harm is also assessed, which may limit the use of psilocybin as a pharmacotherapy. Careful evaluation of the number needed to harm vs the number needed to treat will ultimately justify the potential clinical use of psilocybin. This field needs a responsible pathway forward.
Vertical Transport of Sensible Heat and Meteoric Na by the Complete Temporal Spectrum of Gravity Waves in the MLT Above McMurdo (77.84°S, 166.67°E), Antarctica
Authors: Chu Xinzhao , Gardner Chester S. , Li Xianxin , Lin Cissi Ying‐Tsen
Published: July 2022

We report the first lidar observations of vertical fluxes of sensible heat and meteoric Na from 78 to 110 km in late May 2020 at McMurdo, Antarctica. The measurements include contributions from the complete temporal spectrum of gravity waves and demonstrate that wave‐induced vertical transport associated with atmospheric mixing by non‐breaking gravity waves, Stokes drift imparted by the wave spectrum, and perturbed chemistry of reactive species, can make significant contributions to constituent and heat transport in the mesosphere and lower thermosphere (MLT). The measured sensible heat and Na fluxes exhibit downward peaks at 84 km (−3.0 Kms−1 and −5.5 × 104 cm−2s−1) that are ∼4 km lower than the flux peak altitudes observed at midlatitudes. This is likely caused by the strong downwelling over McMurdo in late May. The Na flux magnitude is double the maximum at midlatitudes, which we believe is related to strong persistent gravity waves in the MLT at McMurdo. To achieve good agreement between the measured Na flux and theory, it was necessary to infer that a large fraction of gravity wave energy was propagating downward, especially between 80 and 95 km where the Na flux and wave dissipation were largest. These downward propagating waves are likely secondary waves generated in‐situ by the dissipation of primary waves that originate from lower altitudes. The sensible heat flux transitions from downward below 90 km to upward from 97 to 106 km. The observations are explained with the fully compressible solutions for polarization relations of primary and secondary gravity waves with λ

z
 > 10 km.
Magnetic Fabric Signature Within a Thrust Imbricate; an Analog Modeling Approach
Authors: Schöfisch T. , Koyi H. , Almqvist B.
Published: July 2022

In this study, we report results from three analog models with a similar initial setup and different amounts of bulk shortening, to simulate the development of a thrust imbricate in fold‐and‐thrust belts at different stages. Samples are taken at the back‐ and forethrusts, in the complex forekink zones, and at random distances to thrusts for analysis using anisotropy of magnetic susceptibility as strain indicator. This analysis shows that three distinct types of magnetic fabric can be identified throughout the models: (a) a compactional oblate fabric that changes as a function of distance toward a localized deformation zone (e.g., thrust or kinkzone), (b) a thrust‐induced fabric with magnetic foliation parallel to the thrust surface depicting its geometry, and (c) a complex forekink zone fabric with broad girdle distributions of principal axes and magnetic lineation perpendicular to the shortening direction. The latter indicates an interplay between folding and thrusting of the shortened sand layers. Additionally, a decrease in the degree of anisotropy with appearance of a quantitatively more prolate fabric can be observed toward the thrusts and kinkzones. Moreover, a thrust‐induced fabric is inherited by the variation of strain, depicted by changes in magnetic fabrics. In conclusion, our analysis of model results shows that strain changes as a function of distance toward localized deformation zones with characteristic magnetic fabrics that develop as deformation continues.
Distribution of Rare Earth Elements and Yttrium in Sediments From the Clarion‐Clipperton Fracture Zone, Northeastern Pacific Ocean
Authors: Kim Mun Gi , Hyeong Kiseong , Yoo Chan Min
Published: July 2022

Deep‐sea sediments enriched in rare earth elements and yttrium (REY) are attracting scientific and exploration attention as a new REY resource. In the Clarion‐Clipperton Fracture Zone (CCFZ) of the northeastern Pacific, sedimentary units with high REY contents (average REY content >700 ppm) occur sporadically at only a few decimeters beneath the sediment surface covered with polymetallic nodules. Here we report the results of bulk chemical and sequential extraction analyses of sediment cores containing these units, collected from the southeastern part of the CCFZ. Correlations between element contents and shale‐normalized REY patterns suggest that the REY are associated primarily with calcium phosphates. Sequential extraction to determine the contribution from different sedimentary components confirms that calcium phosphates contain >70% of trivalent REY in REY‐enriched units. Despite the study location being favorable for nodule formation and subject to distal hydrothermal plume fallout, only subordinate amounts of REY are hosted by Mn‐ and Fe‐(oxyhydr)oxides. Hydrothermal Fe‐(oxyhydr)oxides may have played a more important role in accumulating REY, as evidence suggest that large amounts of Fe‐(oxyhydr)oxides have been transformed into Fe‐rich smectite during early diagenesis of REY‐enriched units.
The Relative Contribution of Climatic, Demographic Factors, Disease Control Measures and Spatiotemporal Heterogeneity to Variation of Global COVID‐19 Transmission
Authors: Cao Yihan , Whittington Jason D. , Kausrud Kyrre , Li Ruiyun , Stenseth Nils Chr.
Published: July 2022

Despite a substantial number of COVID‐19 related research papers published, it remains unclear as to which factors are associated with the observed variation in global transmission and what are their relative levels of importance. This study applies a rigorous statistical framework to provide robust estimations of the factor effects for a global and integrated perspective on this issue. We developed a mixed effect model exploring the relative importance of potential factors driving COVID‐19 transmission while incorporating spatial and temporal heterogeneity of spread. We use an integrated data set for 87 countries across six continents for model specification and fitting. The best model accounts for 70.4% of the variance in the data analyzed: 10 fixed effect factors explain 20.5% of the variance, random temporal and spatial effects account for 50% of the variance. The fixed effect factors are classified into climatic, demographic and disease control groups. The explained variance in global transmission by the three groups are 0.6%, 1.1%, and 4.4% respectively. The high proportion of variance accounted for by random effects indicated striking differences in temporal transmission trajectories and effects of population mobility among the countries. In particular, the country‐specific mobility‐transmission relationship turns out to be the most important factor in explaining the observed global variation of transmission in the early phase of COVID‐19 pandemic.
Coupled Lithospheric Deformation in the Qinling Orogen, Central China: Insights From Seismic Reflection and Surface‐Wave Tomography
Authors: Zhang Yueqiao , Dong Shuwen , Wang Haiyan , Feng Mei , Thybo H. , Li Jianhua , Gao Rui , Shi Wei
Published: July 2022

We combine a ∼485 km‐long seismic reflection profile and a S‐wave speed transect from surface‐wave tomography, to reveal the lithospheric deformation mode of the intracontinental Qinling orogeny, central China. We observe a thick lithosphere keel in the convergence zone between the Yangtze Block and the North China Craton (NCC) and a shallow‐crustal (8–15 km depth) décollement that extends into the lower crust of the Qinling Orogen. Combining with surface structural geology and magmatism, we interpret these seismic findings as kinematically linked features formed by renewed intracontinental convergence between the NCC and the Yangtze Block in the late Mesozoic. We highlight that the ∼40 km lithospheric thickening in the convergence zone was likely balanced by > 130 km thin‐skinned crustal shortening along a crustal‐scale strain‐transfer décollement, and was responsible for the occurrence of late Mesozoic magmatism (∼160–100 Ma) at the southern edge of the NCC.
Dominant Processes for Dependence of Boreal Summer Intraseasonal Oscillation on El Niño Phases
Authors: Lee Doo Young , Lee June‐Yi , Yang Young‐Min , Hsu Pang‐Chi , Kim Ji‐Eun
Published: July 2022

Boreal summer intraseasonal oscillation (BSISO) strongly interacts with background mean fields and tends to be stronger and longer in its northward propagation during La Niña than El Niño summers. However, BSISO dependence on El Niño‐Southern Oscillation phase has not been well understood. Here, we show that BSISO‐related convections are stronger and more organized with northward propagation on 30–60‐day timescales during El Niño developing (E‐DV) than decaying (E‐DC) summers over the western Pacific. The easterly vertical shear, responsible for the next vorticity generation north of the BSISO convection, in the E‐DV (E‐DC) remarkably increases (decreases) due to the enhanced (weakened) upper‐level easterly anomaly. The air‐sea interaction in E‐DV gets stronger due to the larger meridional gradient of sea surface temperature, amplifying northward propagation than in E‐DC.
Synaptic plasticity and mental health: methods, challenges and opportunities
Authors: Appelbaum Lawrence G. , Shenasa Mohammad Ali , Stolz Louise , Daskalakis Zafiris
Published: July 2022

Activity-dependent synaptic plasticity is a ubiquitous property of the nervous system that allows neurons to communicate and change their connections as a function of past experiences. Through reweighting of synaptic strengths, the nervous system can remodel itself, giving rise to durable memories that create the biological basis for mental function. In healthy individuals, synaptic plasticity undergoes characteristic developmental and aging trajectories. Dysfunctional plasticity, in turn, underlies a wide spectrum of neuropsychiatric disorders including depression, schizophrenia, addiction, and posttraumatic stress disorder. From a mechanistic standpoint, synaptic plasticity spans the gamut of spatial and temporal scales, from microseconds to the lifespan, from microns to the entire nervous system. With the numbers and strengths of synapses changing on such wide scales, there is an important need to develop measurement techniques with complimentary sensitivities and a growing number of approaches are now being harnessed for this purpose. Through hemodynamic measures, structural and tracer imaging, and noninvasive neuromodulation, it is possible to image structural and functional changes that underlie synaptic plasticity and associated behavioral learning. Here we review the mechanisms of neural plasticity and the historical and future trends in techniques that allow imaging of synaptic changes that accompany psychiatric disorders, highlighting emerging therapeutics and the challenges and opportunities accompanying this burgeoning area of study.