bluuebunny/crossref_metadata_2025 huggingface dataset:
Approach to the specificity and selectivity between D2 and D3 receptors by mutagenesis and binding experiments part I: Expression and characterization of D2 and D3 receptor mutants
Authors: Legros Céline , Rojas Anne , Dupré Clémence , Brasseur Chantal , Riest‐Fery Isabelle , Muller Olivier , Ortuno Jean‐Claude , Nosjean Olivier , Guenin Sophie‐Pénélope , Ferry Gilles , Boutin Jean A.
Published: September 2022

D3/D2 sub‐specificity is a complex problem to solve. Indeed, in the absence of easy structural biology of the G‐protein coupled receptors, and despite key progresses in this area, the systematic knowledge of the ligand/receptor relationship is difficult to obtain. Due to these structural biology limitations concerning membrane proteins, we favored the use of directed mutagenesis to document a rational towards the discovery of markedly specific D3 ligands over D2 ligands together with basic binding experiments. Using our methodology of stable expression of receptors in HEK cells, we constructed the gene encoding for 24 mutants and 4 chimeras of either D2 or D3 receptors and expressed them stably. Those cell lines, expressing a single copy of one receptor mutant each, were stably constructed, selected, amplified and the membranes from them were prepared. Binding data at those receptors were obtained using standard binding conditions for D2 and D3 dopamine receptors. We generated 26 new molecules derived from D2 or D3 ligands. Using 8 reference compounds and those 26 molecules, we characterized their binding at those mutants and chimeras, exemplifying an approach to better understand the difference at the molecular level of the D2 and D3 receptors. Although all the individual results are presented and could be used for minute analyses, the present report does not discuss the differences between D2 and D3 data. It simply shows the feasibility of the approach and its potential.
A study of McVittie Spacetime in Stationary and Dynamical Regime
Authors: Bhattacharyya Indranath , Ray Saibal , Khlopov Maxim , Nag Riju , Nag Samudra Sundar
Published: September 2022

One of the solutions of the Einstein equations, called McVittie solution, signifying a black hole embedded by the dynamic spacetime is studied. In the stationary spacetime the Mcvittie metric becomes the Schwarzschild‐de Sitter metric (SdS). The geodesic of a freely falling test particle towards the black hole is examined in the SdS spacetime. It is found that unlike the Schwarzschild case the potential of such particle becomes maximum at a point where it eventually stops for a while and then resumes its motion towards the center of the black hole. It is shown that an observer or system of particles is spaghettified near the black hole singularity in the SdS spacetime. The dynamics of the universe in the framework of McVittie metric, being a generalized time dependent SdS solution, is represented in terms of that point, called stationary or turning point. The motion of the stationary point is studied in various regimes of the expanding universe and the possible outcomes are discussed in brief.
Opioids and antidepressants: When is the mantra wrong?
Authors: Price Lawrence H.
Published: September 2022

It's become a bit of a mantra that psychotropic drugs and opioids shouldn't be co‐prescribed. That shouldn't be surprising. As every reader of the Update surely knows, we are in the midst of an opioid overdose epidemic, with deaths involving any opioid, whether prescription or illicit, increasing by more than seven‐fold from 1999 to 2020. That's more than 564,000 deaths. For perspective: 68,630 Americans died from opioid‐involved overdoses in 2020; deaths from motor vehicle crashes that year were 38,680. Small wonder that physicians, as well as the lay public, have looked for any possible means to limit the carnage.
On the use of the likelihood ratio test methodology in pharmacovigilance
Authors: Chakraborty Saptarshi , Liu Anran , Ball Robert , Markatou Marianthi
Published: September 2022

The safety of medical products due to adverse events (AE) from drugs, therapeutic biologics, and medical devices is a major public health concern worldwide. Likelihood ratio test (LRT) approaches to pharmacovigilance constitute a class of rigorous statistical tools that permit objective identification of AEs of a specific drug and/or a class of drugs cataloged in spontaneous reporting system databases. However, the existing LRT approaches encounter certain theoretical and computational challenges when an underlying Poisson model assumption is violated, including in cases of zero‐inflated data. We briefly review existing LRT approaches and propose a novel class of (pseudo‐) LRT methods to address these challenges. Our approach uses an alternative parametrization to formulate a unified framework with a common test statistic that can handle both Poisson and zero‐inflated Poisson (ZIP) models. The proposed framework is computationally efficient, and it reveals deeper insights into the comparative behaviors of the Poisson and the ZIP models for handling AE data. Our extensive simulation studies document notably superior performances of the proposed methods over existing approaches particularly under zero‐inflation, both in terms of statistical (eg, much better control of the nominal level and false discovery rate with substantially enhanced power) and computational (100‐500‐fold gains in average running times) performance metrics. An application of our method on thestatindrug class from the FDA FAERS database reveals interesting insights on potential AEs. An R package,pvLRT, implementing our methods has been released in the public domain.
The potential adverse effects of acrylamide on the oxidative stress response, fatty acids profile, and histopathological aspect of the Mediterranean Holothuria forskali respiratory tree
Authors: Trabelsi Wafa , Fouzai Chaima , Telahigue Khaoula , Chetoui Imene , Nechi Salwa , Chelbi Emna , Zrelli Sonia , Soudani Nejla
Published: September 2022

Acrylamide (ACR), organic compound, has been widely used owing to its broad spectrum of chemical and industrial applications. This study aims at evaluating the response of the antioxidant defense system, fatty acid composition and histopathological aspect in the respiratory trees of Holothuria forskali against ACR exposure under laboratory conditions. Holothuries were exposed to 5, 10, and 20 mg L−1 ACR concentrations for 5 days. A significant increase in n‐6 polyunsaturated fatty acids levels especially the arachidonic acid (ARA, C20:4n‐6) and its precursor linoleic acid (LA, C18:2n‐6) in ACR‐treated organisms. Regarding the n‐3 levels, eicosapentaenoic acid (EPA, C20:5n‐3) levels were increased in treated groups despite an acute decrease in docosahexaenoic acid (DHA, C22:6n‐3) levels was observed. Our results showed a significant increase in hydrogen peroxide, malondialdehyde, protein carbonyl, and metallothionein levels along with an alteration of the antioxidants status in all treated sea cucumbers. The exposure to ACR prompted the inhibition of Acetylcholinesterase activity in a concentration‐dependent manner. The histopathological aspect was marked especially with the infiltration of coelomic cells which confirms our biochemical findings. Our study provided novel insights to create a link between redox status and fatty acid composition disruptions to better understand ACR‐triggered toxicity.
Comparison of blood leptin and vitamin E and blood and adipose fatty acid compositions in wild and captive populations of critically endangered Vancouver Island marmots (Marmota vancouverensis)
Authors: Aymen Jessica , Delnatte Pauline , Beaufrère Hugues , Chalil Dan , Steckel Klaudia. E. , Gourlie Sarra , Stark Ken D. , McAdie Malcolm
Published: September 2022

Vancouver Island marmots (Marmota vancouverensis) (VIMs) are a critically endangered species of fat‐storing hibernators, endemic to Vancouver Island, British Columbia, Canada. In addition to in‐situ conservation efforts, a captive breeding program has been ongoing since 1997. The captive diet is mostly pellet‐based and rich in n−6 polyunsaturated fatty acids (PUFAs). In captivity, overall length of hibernation is shortened, and marmots have higher adipose tissue reserves compared to their wild‐born counterparts, which may be a risk factor for cardiovascular disease, the leading cause of mortality in captive marmots. To investigate differences in lipid metabolism between wild and captive populations of VIMs, blood vitamin E, fatty acid (FA) profiles and leptin, and white adipose tissue (WAT) FA profiles were compared during the active season (May to September 2019). Gas chromatography, high‐performance liquid chromatography, and multiplex kits were used to obtain FA profiles, α‐tocopherol, and leptin values, respectively. In both plasma and WAT, the concentration of the sum of all FA in the total lipids was significantly increased in captive VIMs. The n−6/n−3 ratio, saturated FAs, and n−6 PUFAS were higher in captive marmots, whereas n−3 PUFAs and the HUFA score were higher in wild marmots. Serum concentrations of α‐tocopherol were greater by an average of 45% in captive marmots, whereas leptin concentrations did not differ. Results from this study may be applied to improve the diet and implement weight management to possibly enhance the quality of hibernation and decrease the risk of cardiovascular and metabolic diseases of captive VIMs.
Data Collection and Analysis in Learning Technology and CCI Research
Authors: Giannakos Michail
Published: September 2022

Conducting experimental studies in learning technology and CCI research entails an iterative process of observation, rationalization, and validation. Although data collection and data analysis procedures may vary widely in complexity, their selection is based on the research objectives, RQs or hypotheses. So the researchers need to carefully select them and make sure that the research design decisions of data collection and analysis, are adequate for the goals of the study. This chapter provides information on the various data collections and analyses that are usually employed in learning technology and CCI research. This chapter is intended to serve as a guide for CCI and learning technology researchers, and help them deciding what data they need to collect and how they should analyze them to address the goals of their study.
Inflection-point inflation and dark matter redux
Authors: Ghoshal Anish , Lambiase Gaetano , Pal Supratik , Paul Arnab , Porey Shiladitya
Published: September 2022

Abstract

We investigate for viable models of inflation that can successfully produce dark matter (DM) from inflaton decay process, satisfying all the constraints from Cosmic Microwave Background (CMB) and from some other observations. In particular, we analyze near-inflection-point small field inflationary scenario with non-thermal production of fermionic DM from the decaying inflaton field during the reheating era. To this end, we propose two different models of inflation with polynomial potential. The potential of Model I contains terms proportional to linear, quadratic, and quartic in inflaton; whereas in Model II, the potential contains only even power of inflaton and the highest term is sextic in inflaton. For both the models, we find out possible constraints on the model parameters which lead to proper inflationary parameters from CMB data with a very small tensor-to-scalar ratio, as expected from a small-field model. With the allowed parameter space from CMB, we then search for satisfactory relic abundance for DM, that can be produced from inflaton via reheating, to match with the present-day cold dark matter (CDM) relic density for the parameter spaces of the DM χ mass and Yukawa couplings in the range 10−9 ≳ yχ ≳ 10−15 and 103GeV ≲ mχ ≲ 109GeV. The DM relic is associated with the inflection-points in each model via maximum temperature reached in the early universe during its production. Finally, we find out allowed parameter space coming out of combined constraints from stability analysis for both SM Higgs and DM decays from inflaton as well as from BBN and Lyman-α bounds.
Smart cities: reviewing the debate about their ethical implications
Authors: Ziosi Marta , Hewitt Benjamin , Juneja Prathm , Taddeo Mariarosaria , Floridi Luciano
Published: September 2022

This paper considers a host of definitions and labels attached to the concept of smart cities to identify four dimensions that ground a review of ethical concerns emerging from the current debate. These are: (1) network infrastructure, with the corresponding concerns of control, surveillance, and data privacy and ownership; (2) post-political governance, embodied in the tensions between public and private decision-making and cities as post-political entities; (3) social inclusion, expressed in the aspects of citizen participation and inclusion, and inequality and discrimination; and (4) sustainability, with a specific focus on the environment as an element to protect but also as a strategic element for the future. Given the persisting disagreements around the definition of a smart city, the article identifies in these four dimensions a more stable reference framework within which ethical concerns can be clustered and discussed. Identifying these dimensions makes possible a review of the ethical implications of smart cities that is transversal to their different types and resilient towards the unsettled debate over their definition.
Reduplicated medial parapatellar plica: a case of a medial plica anatomical variation recalcitrant to conservative treatment
Authors: Marín Fermín Theodorakys , Macchiarola Luca , Tsakotos George , Terzidis Ioannis , Totlis Trifon
Published: September 2022

Purpose

The current study aims to report the radiologic and clinical appearance of a rare anatomical variation of the knee medial synovial plica along with its response to conservative and surgical treatment.

Case presentation

This report portrays a 29-year-old male patient with anteromedial gradual onset right knee pain, aggravated when descending stairs or prolonged sitting. Physical examination revealed medial parapatellar local tenderness, a palpable click in this area when the knee was extended, and hamstring tightness. Magnetic resonance imaging showed a duplicated medial plica, characterized by a high-intensity signal of the infrapatellar fat pad medial portion, after which a presumptive diagnosis of medial plica syndrome was proposed. After conservative treatment failure, the patient underwent standard knee arthroscopy that revealed a superior low profile and an inferior high profile medial plica, and hypertrophy of the medial portion of the infrapatellar fat pad. Both plicae and fat pad were resected with a mechanical shaver until no contact between the femoral trochlea and the fat pad was observed during full range of motion. At 4 weeks postoperatively, symptoms completely resolved, and the patient was allowed to return to full activity with no recurrences at 1 year follow-up.

Conclusions

The current study presented a rare anatomical variation of the knee medial synovial plica that was symptomatic and recalcitrant to conservative treatment. This case report may be useful for radiologists and orthopaedic surgeons to differentiate this special plica type and consider its response to conservative and surgical treatment during patient management.
Zwei Jahre Pilotphase Gemeindenotfallsanitäter in der Region Oldenburg (Niedersachsen)
Authors: Sommer Anja , Rehbock Cassandra , Seeger Insa , Klausen Andrea , Günther Ulf , Schröder Hanna , Neuerer Maresa , Beckers Stefan K. , Krafft Thomas
Published: September 2022

Hintergrund

Steigende Einsatzzahlen im Rettungsdienst, demografischer Wandel sowie Veränderungen bei der Morbidität und in den Strukturen der Akutversorgung erfordern eine Weiterentwicklung der Versorgungsoptionen an den Sektorengrenzen zwischen ambulanter und stationärer Versorgung. Zur Erprobung von Gemeindenotfallsanitätern (G-NFS) als eine unterstützende Ressource des Rettungsdienstes wird in der Region Oldenburg seit 2019 ein Modellprojekt mit wissenschaftlicher Begleitung durchgeführt.

Methodik

Im Rahmen einer Mixed-Methods-Studie wurden Fokusgruppeninterviews mit den vier regionalen G‑NFS-Gruppen (Stadt Oldenburg und die Kreise Vechta, Cloppenburg und Ammerland) durchgeführt. Die Interviews (Teilnahme ca. 56,7 % aller G‑NFS) wurden jeweils durch eine kurze anonyme Online-Umfrage (Teilnahme ca. 53,3 % aller G‑NFS) mit denselben Teilnehmern ergänzt. Interviews und Online-Befragung zielten auf die persönlichen Einsatzerfahrungen vor und während der Coronapandemie ab. Die Interviewergebnisse wurden anhand thematischen Codierens analysiert und ausgewertet.

Ergebnisse

An den Interviews und der anschließenden Umfrage nahmen 17 bzw. 16 G-NFS teil. Aus Sicht der G‑NFS ergänzt die Ressource das bisherige Reaktionsspektrum des Rettungsdienstes in Form von Rettungswagen (RTW) oder Krankentransportwagen (KTW) um eine sinnvolle und fachgerechte Komponente, die insbesondere zur erforderlichen Entlastung der Einsatzmittel der Notfallversorgung beiträgt. Die notwendige sektorenübergreifende Zusammenarbeit mit anderen Diensten verläuft in Abhängigkeit von den jeweiligen lokalen Gegebenheiten unterschiedlich, aber insgesamt zielgerichtet und effizient; Gleiches gilt für die Zusammenarbeit mit den zuständigen Rettungsleitstellen. G‑NFS wurden in den Hochphasen der Pandemie in die Triagierung von COVID-Verdachtsfällen einbezogen und haben zur dringend gebotenen Entlastung des Rettungssystems in der Region beigetragen.

Diskussion

Das G‑NFS-Konzept hat sich aus Sicht der Mitarbeiter in der bisherigen Projektlaufzeit bewährt. Die vorliegenden Erfahrungen bieten eine gute Grundlage für die konzeptionelle Weiterentwicklung des G‑NFS.
FreesoundVR: soundscape composition in virtual reality using online sound repositories
Authors: Turchet Luca , Carraro Marco , Tomasetti Matteo
Published: September 2022

The intersection between sound and music computing and Virtual Reality (VR) has grown significantly over the past decades, amounting to an established area of research today. However, still scarce research has been conducted on the development of specific tools for sound design and composition. In this paper, we investigate a new way of exploring online sound repositories to retrieve sounds to be used in soundscape composition, which leverages the VR medium. Specifically, we created a VR system that allows users to search, download, and explore Freesound content in an immersive manner, as well as to use it for soundscape composition practices via a virtual digital audio workstation (DAW). The tags associated to a sound in the repository were converted into virtual objects and environments, which the user could navigate while listening to the sound. We conducted a user study with 16 composers where the developed system was compared against a conventional counterpart comprising the Freesound web version and the Audacity DAW. Overall, quantitative and qualitative results did not indicate a clear and generalized preference for a system over the other. The usability of the two systems along with their offered creativity support, cognitive workload and emotional impact were deemed to be at a comparable level. Nevertheless, the full potential of VR in creating novel compositional experiences also clearly emerged. Our study shows that VR is an effective medium to support users’ creativity during the process of exploring and selecting sounds from an online repository as well as for composing a soundscape.
Integrating Gender-Based Violence Screening and Support into the Research Clinic Setting: Experiences from an HIV Prevention Open-Label Extension Trial in Sub-Saharan Africa
Authors: Garcia Morgan , Roberts Sarah T. , Mayo Ashley J. , Scheckter Rachel , Mansoor Leila E. , Palanee-Phillips Thesla , Reddy Krishnaveni , Naidoo Yuthika , Akello Carolyne Agwau , Gaffoor Zakir , Siva Samantha , Rushwaya Chenai , Hlahla Kudzai , Jambaya Jane , Makoni Rujeko , Kachale Evans , Ndovie Margret , Zuma Jabulisile , Montgomery Elizabeth T. ,   the MTN-025/HOPE study team
Published: September 2022

HIV and gender-based violence (GBV) are syndemic in sub-Saharan Africa and provision of support for participants who disclose GBV constitutes part of comprehensive care. Consequently, a process was undertaken to develop, implement, and evaluate standard operating procedures (SOPs) in MTN-025/HOPE, a study of the dapivirine vaginal ring for HIV prevention. The SOP was developed using needs assessment surveys in addition to World Health Organization (WHO) guidelines and other literature. Sites tailored and implemented the SOP through HOPE implementation. At study end, staff reported increased training 32/35 (91.43%); improved confidence (18/26; 69.23%); and improved vicarious trauma prevention onsite (17/28; 60.71%). Leadership reported increased staff competence in GBV response. Obstacles included limited referral organizations and time for follow-up, continued training needs, and cultural norms. Development and implementation of an SOP is a feasible strategy to build a GBV response to improve health systems and support sustained effective use of HIV prevention products.
A data-driven system for cooperative-bus route planning based on generative adversarial network and metric learning
Authors: Wang Jiguang , Zhang Yilun , Xing Xinjie , Zhan Yuanzhu , Chan Wai Kin Victor , Tiwari Sunil
Published: September 2022

Faced with dynamic and increasingly diversified public transport requirements, bus operators are urged to propose operational innovations to sustain their competitiveness. In particular, ordinary bus operations are heavily constrained by well-established route options, and it is challenging to accommodate dynamic passenger flows effectively and with a good level of resource utilization performance. Inspired by the philosophy of sharing economy, many of the available transport resources on the road, such as minibuses and private vehicles, can offer opportunities for improvement if they can be effectively incorporated and exploited. In this regard, this paper proposes a metric learning-based prediction algorithm which can effectively capture the demand pattern and designs a route planning optimizer to help bus operators effectively deploy fixed routing and cooperative buses with traffic dynamics. Through extensive numerical studies, the performance of our proposed metric learning-based Generative Adversarial Network (GAN) prediction model outperforms existing ways. The effectiveness and robustness of the prediction-supported routing planner are well demonstrated for a real-time case. Further, managerial insights with regard to travel time, bus fleet size, and customer service levels are revealed by various sensitivity analysis.
Sensitivity to uncertainty and scalarization in robust multiobjective optimization: an overview with application to mean-variance portfolio optimization
Authors: Rocca Matteo
Published: September 2022

Robust optimization is proving to be a fruitful tool to study problems with uncertain data. In this paper we deal with the minmax aproach to robust multiobjective optimization. We survey the main features of this problem with particular reference to results concerning linear scalarization and sensitivity of optimal values with respect to changes in the uncertainty set. Furthermore we prove results concerning sensitivity of optimal solutions with respect to changes in the uncertainty set. Finally we apply the presented results to mean-variance portfolio optimization.
Evaluation of Neurofeedback Learning in Patients with ADHD: A Systematic Review
Authors: Kuznetsova Elizaveta , Veilahti Antti Veikko Petteri , Akhundzadeh Ruhoollah , Radev Stefan , Konicar Lilian , Cowley Benjamin Ultan
Published: September 2022

NFB has a clear potential as a recognised treatment option for ADHD, but suffers from a lack of clarity about its efficacy, still unresolved after multiple controlled trials. Comparing learners and non-learners based on the evolution of patient-level indicators during the trial serves as a ‘natural’ control, and can help elucidate the mechanisms of NFB. We present a systematic review motivated by the need to establish the state of the art of patient learning during NFB treatment in current clinical literature. One particularly striking question we would like to answer here is whether existing NFB papers study learning variability, since only individual performance differences can give us information about mechanisms of learning. The results show that very few clinical trial reports have dealt with the heterogeneity of NFB learning, nor analysed whether NFB efficacy is dependent on NFB learning, even though NFB is believed to be a treatment based on learning to perform. In this systematic review we examine not only what has been reported, but also provide a critical analysis of possible flaws or gaps in existing studies, and discuss why no generalized conclusions about NFB efficacy have yet been made. Future research should focus on finding reliable ways of identifying the performers and studying participants’ individual learning trajectories as it might enhance prognosis and the allocation of clinical resources.
A review of molecular diagnoses of bacterial fish diseases
Authors: Abdelsalam Mohamed , Elgendy Mamdouh Y. , Elfadadny Medhat R. , Ali Sameh Samir , Sherif Ahmed H. , Abolghait Said Kamal
Published: September 2022

Egypt is the world’s ninth-largest fish producer with a total production of 1.5 billion tons per year, and farmed fishes comprise almost 79.6% of the total production. Massive mortalities in market-sized farmed fish (freshwater and marine species) were documented all over fish farms in Egypt leading to serious economic losses. The poor biosecurity practices and awareness among smallholder fish farmers accompanied with a long period of temperature fluctuation may predispose farmed fish to be simultaneously coinfected with multiple pathogens. Moribund fishes usually exhibited various septicemic clinical signs and post-mortem lesions indicating that one or more septicemic bacterial pathogens were involved in these outbreak reports. Therefore, rapid and accurate identification of pathogens in the asymptomatic fish population is important for preventing the occurrence of infectious diseases and protecting consumers from seafood-borne illnesses. Molecular techniques provide sensitive, quick, and accurate data for identifying specific pathogens without the need for time-consuming traditional techniques. In addition, the development of cost-effective molecular techniques facilitates their wide implementation in routine clinical diagnostic approaches. Molecular diagnostic methods are useful for simultaneously identifying multiple bacterial pathogens that were challenging to recognize by commercial biochemical techniques. Genetic testing procedures could determine the genetic diversity between closely related strains at the subspecies level. Consequently, these techniques are required for the development of detecting methods for specific strains and for epidemiological investigations in bacterial diseases. This review documented a variety of molecular techniques, including amplification of nucleic acids, polymerase chain reaction (PCR), nested PCR, real-time PCR, multiplex PCR, loop-mediated isothermal amplification (LAMP), DNA microarrays, and nucleotide sequencing assays, that are commonly used to identify fish pathogens.
Extended in vitro storage of eggs and milt increases maternal but not paternal variation in embryo viability of landlocked Atlantic salmon (Salmo salar m. sebago)
Authors: Janhunen Matti , Turkka Juha-Pekka , Kekäläinen Jukka
Published: September 2022

Appropriate fertilization practices play a crucial role in the maintenance of genetic diversity within captive fish broodstocks. We assessed the influence of in vitro storage of gametes (0-, 7- and 14-days post-stripping) at 1 °C on ovarian fluid pH, sperm motility, and embryo viability in the critically endangered Finnish landlocked salmon (Salmo salar m. sebago) population. A repeated full-factorial design used in both sperm-ovarian fluid activation analyses and fertilizations allowed us to separate the effects of female, male and their interaction on gamete quality and embryo survival across storage times. The ovarian fluid pH decreased most significantly during the first week of storage and showed considerable variation among females. The decrease of sperm motility varied across males, females and male–female (sperm-ovarian fluid) combinations. The mean proportion of viable embryos was initially 96.4%, but dropped to 45.5% after 7 days, and to 13.1% after 14 days of gamete storage. Embryo viability responses to gamete storage time predominantly increased among- and within-female variation but also showed major differences between female × male combinations (non-additive genetic effects). Interestingly, embryo viability showed virtually complete re-ranking (change of order) among full-sib families between the first two fertilization times (rs =  − 0.03) but consistency between the first and last times (rs = 0.59). Overall, our results indicate that even when the primary aim is to maximize the genetic diversity of endangered fish populations, it may be advisable to prioritize minimal egg storage time rather than maximizing the number of parental combinations in fertilizations.
ASAP: adaptive transmission scheme for online processing of event-based algorithms
Authors: Tapia R. , Martínez-de Dios J. R. , Gómez Eguíluz A. , Ollero A.
Published: September 2022

Online event-based perception techniques on board robots navigating in complex, unstructured, and dynamic environments can suffer unpredictable changes in the incoming event rates and their processing times, which can cause computational overflow or loss of responsiveness. This paper presents ASAP: a novel event handling framework that dynamically adapts the transmission of events to the processing algorithm, keeping the system responsiveness and preventing overflows. ASAP is composed of two adaptive mechanisms. The first one prevents event processing overflows by discarding an adaptive percentage of the incoming events. The second mechanism dynamically adapts the size of the event packages to reduce the delay between event generation and processing. ASAP has guaranteed convergence and is flexible to the processing algorithm. It has been validated on board a quadrotor and an ornithopter robot in challenging conditions.

Graphic Abstract
Farmer adoption and intensity of use of extreme weather adaptation and mitigation strategies: evidence from a sample of Missouri farmers
Authors: Skevas Theodoros , Massey Ray , Grashuis Jasper
Published: September 2022

Climate change and its associated weather extremes pose a threat to agriculture. To slow down climate change and reduce its associated risks, governments around the world are currently developing policies to encourage farmers to engage in adaptation and mitigation efforts. The aim of this study is to assess the adoption and intensity of use of extreme weather adaptation and mitigation strategies among a sample of Missouri farmers and to identify the factors that influence adaptation and mitigation behavior. Of particular interest is the influence of the 2019 Missouri River flooding on adaptation and mitigation efforts. An econometric hurdle model that separates the decision on whether to adopt adaptation/mitigation strategies from the decision on how many strategies to employ was used to achieve the study’s purpose. Improving field drainage or soil water retention capacity for potential flooding was found to be by far the most used adaptation. The most used mitigations were increasing use of minimum tillage, managing fertilizer, and planting cover crops. Types of crops grown, farm income, and opinions on extreme weather events were the most important determinants of both adaptation and mitigation decision. Direct experience with the 2019 Missouri River floods is found to only influence adaptation decision. Adaptation and mitigation intensity were found to be strongly influenced by opinions on government support for adaptation and CRP involvement, respectively. Directions for policy and outreach that can promote adaptation and mitigation efforts among farmers are discussed.
Coastline matching via a graph-based approach
Authors: Panagiotakis Costas , Markaki Smaragda , Kokinou Eleni , Papadakis Harris
Published: September 2022

This paper studies the problem of unsupervised detection of geometrically similar fragments (segments) in curves, in the context of boundary matching. The goal is to determine all pairs of sub-curves that are geometrically similar, under local scale invariance. In particular, we aim to locate the existence of a similar section (independent of length and/or orientation) in the second curve, to a section of the first curve, as indicated by the user. The proposed approach is based on a suitable distance matrix of the two given curves. Additionally, a suitable objective function is proposed to capture the trade-off between the similarity of the common sub-sequences and their lengths. The goal of the algorithm is to minimize this objective function via an efficient graph-based approach that capitalizes on Dynamic Time Warping to compare the two subcurves. We apply the proposed technique in the context of geometric matching of coastline pairs. This application is crucial for investigating the forcing factors related to the coastline evolution. The proposed method was successfully applied to global coastline data, yielding a bipartite graph with analytical point-to-point correspondences.
Consumption Corridors and the Case of Meat
Authors: Kanerva M.
Published: September 2022

Consumer policy must address the unsustainability of consumption which now threatens consumer safety in the form of the climate and ecological crises. Arguably, only strong sustainable consumption governance methods can bring about changes at the scale and speed required. This article discusses one emerging policy tool within strong governance, namely consumption corridors which could bring about absolute reductions in the negative impacts of consumption in a just manner and using deliberative democracy. Consumption corridors are applied in the context of the current meat system, a common driver for the twin crises, and an issue central to achieving the sustainable development, biodiversity, and Paris climate goals. The recently developed planetary health diet offers a useful plan for the transformation of global food systems, and could be combined with sustainable consumption corridors for meat. Systems thinking identifies change in societal paradigms as most effective. To support such change, this article suggests two metaphors as discourse tools, whereby individual and societal transformation in meat consumption occurs as a journey along a continuum of different meatways. The article also suggests specific actions for bringing about meat consumption corridors, and argues that this context could also serve as a bridge for increased societal acceptance of recomposed consumption.
Decision tree boosted varying coefficient models
Authors: Zhou Yichen , Hooker Giles
Published: September 2022

Varying coefficient models are a flexible extension of generic parametric models whose coefficients are functions of a set of effect-modifying covariates instead of fitted constants. They are capable of achieving higher model complexity while preserving the structure of the underlying parametric models, hence generating interpretable predictions. In this paper we study the use of gradient boosted decision trees as those coefficient-deciding functions in varying coefficient models with linearly structured outputs. In contrast to the traditional choices of splines or kernel smoothers, boosted trees are more flexible since they require no structural assumptions in the effect modifier space. We introduce our proposed method from the perspective of a localized version of gradient descent, prove its theoretical consistency under mild assumptions commonly adapted by decision tree research, and empirically demonstrate that the proposed tree boosted varying coefficient models achieve high performance qualified by their training speed, prediction accuracy and intelligibility as compared to several benchmark algorithms.
Biomechanical and histomorphometric evaluation of skin integration on titanium and PEEK implants with different surface treatments
Authors: Kjellin Per , Danielsson Karin , Håkansson Joakim , Agrenius Karin , Andersson Therese , Stenlund Patrik
Published: September 2022

Percutaneous implants are frequently affected by bacterial growth at the skin-implant interface. Integration between implant and surrounding skin is important to prevent bacteria from spreading to the underlying tissue. The standard method to evaluate skin-implant integration is by histomorphometry on samples which have been placed in tissue grown in vivo or ex vivo. In this study, a biomechanical method was developed and evaluated. The integration of implants into porcine skin was studied in an ex vivo model, where pig skin samples were cultivated in a nutrient solution. Cylindrical shaped implants, consisting of polyether ether ketone (PEEK) and titanium (Ti) with different surface treatments, were implanted in the skin tissue and the skin was grown in nutrient solution for 2 weeks. The implants were then extracted from the implantation site and the mechanical force during extraction was measured as a quantitative assessment of skin-implant integration. Implants from each group were also processed for histomorphometry and the degree of epidermal downgrowth (ED) and tissue to implant contact (TIC) was measured. A higher mean pullout force was observed for the PEEK implants compared to the Ti implants. Applying nanosized hydroxyapatite (HA) on Ti and PEEK increased the pullout force compared to uncoated controls, 24% for machined and 70% for blasted Ti, and 51% for machined PEEK. Treatment of Ti and PEEK with nanosized zirconium phosphate (ZrP) did not increase the pullout force. The histomorphometry analysis showed correlation between ED and pullout force, where the pullout force was inversely proportional to ED. For TIC, no significant differences were observed between the groups of same material (i.e. Ti, Ti+HA, Ti+ZrP, and PEEK, PEEK + HA, PEEK + ZrP), but it was significantly higher for PEEK compared to Ti. Scanning electron microscopy analysis was done on samples before and after the pullout tests, showing that the ZrP coating was unaffected by the 2 week ex vivo implantation and pullout procedure, no dissolution or detachment of the coating was observed. For the HA coating, a loss of coating was seen on approximately 5% of the total surface area of the implant.
Imperialism and nationalism
Authors: Rojek Paweł
Published: September 2022

Is Russia a neoimperial or postimperial state? In this paper, I compare two interpretations proposed by political commentators Marcel Van Herpen and Dmitri Trenin. Van Herpen holds that the Russian empire is literally being rebuilt, whereas Trenin believes that Russia is just ceasing to be an empire. I argue that, contrary to popular belief, the current war against Ukraine cannot be interpreted as an attempt to restore the Russian empire. This is because being an empire requires a universalistic ideology that can be accepted by other nations. Meanwhile, the ideological foundation of the current war is an obviously nationalistic conception of the “Russian world.” Polish historians Andrzej Nowak and Włodzimierz Marciniak brilliantly argued that it was Russian nationalism that had previously led to the collapse of both Imperial Russia and the Soviet Union. Under this interpretation the current war in Ukraine can be seen not as the rebirth but rather as the dramatic end of Russian imperialism.
Adaptive random neighbourhood informed Markov chain Monte Carlo for high-dimensional Bayesian variable selection
Authors: Liang Xitong , Livingstone Samuel , Griffin Jim
Published: September 2022

We introduce a framework for efficient Markov chain Monte Carlo algorithms targeting discrete-valued high-dimensional distributions, such as posterior distributions in Bayesian variable selection problems. We show that many recently introduced algorithms, such as the locally informed sampler of Zanella (J Am Stat Assoc 115(530):852–865, 2020), the locally informed with thresholded proposal of Zhou et al. (Dimension-free mixing for high-dimensional Bayesian variable selection, 2021) and the adaptively scaled individual adaptation sampler of Griffin et al. (Biometrika 108(1):53–69, 2021), can be viewed as particular cases within the framework. We then describe a novel algorithm, theadaptive random neighbourhood informedsampler, which combines ideas from these existing approaches. We show using several examples of both real and simulated data-sets that a computationally efficient point-wise implementation (PARNI) provides more reliable inferences on a range of variable selection problems, particularly in the very largepsetting.
Approximate Laplace importance sampling for the estimation of expected Shannon information gain in high-dimensional Bayesian design for nonlinear models
Authors: Englezou Yiolanda , Waite Timothy W. , Woods David C.
Published: September 2022

One of the major challenges in Bayesian optimal design is to approximate the expected utility function in an accurate and computationally efficient manner. We focus on Shannon information gain, one of the most widely used utilities when the experimental goal is parameter inference. We compare the performance of various methods for approximating expected Shannon information gain in common nonlinear models from the statistics literature, with a particular emphasis on Laplace importance sampling (LIS) and approximate Laplace importance sampling (ALIS), a new method that aims to reduce the computational cost of LIS. Specifically, in order to centre the importance distributions LIS requires computation of the posterior mode for each of a large number of simulated possibilities for the response vector. ALIS substantially reduces the amount of numerical optimization that is required, in some cases eliminating all optimization, by centering the importance distributions on the data-generating parameter values wherever possible. Both methods are thoroughly compared with existing approximations including Double Loop Monte Carlo, nested importance sampling, and Laplace approximation. It is found that LIS and ALIS both give an efficient trade-off between mean squared error and computational cost for utility estimation, and ALIS can be up to 70% cheaper than LIS. Usually ALIS gives an approximation that is cheaper but less accurate than LIS, while still being efficient, giving a useful addition to the suite of efficient methods. However, we observed one case where ALIS is both cheaper and more accurate. In addition, for the first time we show that LIS and ALIS yield superior designs to existing methods in problems with large numbers of model parameters when combined with the approximate co-ordinate exchange algorithm for design optimization.
Quantum median filter for total variation image denoising
Authors: De Santis Simone , Lazzaro Damiana , Mengoni Riccardo , Morigi Serena
Published: September 2022

In this new computing paradigm, named quantum computing, researchers from all over the world are taking their first steps in designing quantum circuits for image processing, through a difficult process of knowledge transfer. This effort is named quantum image processing, an emerging research field pushed by powerful parallel computing capabilities of quantum computers. This work goes in this direction and proposes the challenging development of a powerful method of image denoising, such as the total variation (TV) model, in a quantum environment. The proposed quantum TV is described and its sub-components are analysed. Despite the natural limitations of the current capabilities of quantum devices, the experimental results show a competitive denoising performance compared to the classical variational TV counterpart.
Automatic Cerebral Hemisphere Segmentation in Rat MRI with Ischemic Lesions via Attention-based Convolutional Neural Networks
Authors: Valverde Juan Miguel , Shatillo Artem , De Feo Riccardo , Tohka Jussi
Published: September 2022

We present MedicDeepLabv3+, a convolutional neural network that is the first completely automatic method to segment cerebral hemispheres in magnetic resonance (MR) volumes of rats with ischemic lesions. MedicDeepLabv3+ improves the state-of-the-art DeepLabv3+ with an advanced decoder, incorporating spatial attention layers and additional skip connections that, as we show in our experiments, lead to more precise segmentations. MedicDeepLabv3+ requires no MR image preprocessing, such as bias-field correction or registration to a template, produces segmentations in less than a second, and its GPU memory requirements can be adjusted based on the available resources. We optimized MedicDeepLabv3+ and six other state-of-the-art convolutional neural networks (DeepLabv3+, UNet, HighRes3DNet, V-Net, VoxResNet, Demon) on a heterogeneous training set comprised by MR volumes from 11 cohorts acquired at different lesion stages. Then, we evaluated the trained models and two approaches specifically designed for rodent MRI skull stripping (RATS and RBET) on a large dataset of 655 MR rat brain volumes. In our experiments, MedicDeepLabv3+ outperformed the other methods, yielding an average Dice coefficient of 0.952 and 0.944 in the brain and contralateral hemisphere regions. Additionally, we show that despite limiting the GPU memory and the training data, our MedicDeepLabv3+ also provided satisfactory segmentations. In conclusion, our method, publicly available at https://github.com/jmlipman/MedicDeepLabv3Plus, yielded excellent results in multiple scenarios, demonstrating its capability to reduce human workload in rat neuroimaging studies.
Vitamin D deficiency leads to the abnormal activation of the complement system
Authors: Li Huan , Xie Xiaomin , Bai Guirong , Qiang Dan , Zhang Li , Liu Huili , He Yanting , Tang Yanpan , Li Ling
Published: September 2022

Vitamin D deficiency can damage the human immune system, and the complement system is a key component of the immune system. This study aimed to elucidate the mechanism by which vitamin D affects the immune system by analyzing the changes in the protein expression of the complement system under different vitamin D levels. We selected 40 participants and divided them into three groups according to their serum levels of 25-hydroxyvitamin D (25(OH)VD): group A, 25(OH)VD ≥ 40 ng/mL; group B, 30 ng/mL ≤ 25(OH)VD < 40 ng/mL; and group C, 25(OH)VD < 30 ng/mL. Serum samples were subjected to biochemical analysis, followed by proteomic analysis using high-throughput untargeted proteomic techniques. Vitamin D deficiency increased the levels of fasting blood sugar, fasting serum insulin, and homeostasis model assessment (HOMA) of insulin resistance and decreased the secretion of HOMA of β-cell function, which led to insulin resistance and glucose metabolism disorder. Moreover, vitamin D deficiency resulted in the abnormal expression of 56 differential proteins, among which the expression levels of complement factor B, complement component C9, inducible co-stimulator ligand, and peptidase inhibitor 16 significantly changed with the decrease in vitamin D content. Functional enrichment analysis of these differential proteins showed that they were mainly concentrated in functions and pathways related to insulin secretion and inflammation. In conclusion, vitamin D deficiency not only contributes to insulin resistance and glucose metabolism disorder but also causes abnormal protein expression, resulting in the abnormal activation of the complement system. This study provides a novel theoretical basis for further studies on the relationship between vitamin D and the immune system.