bluuebunny/crossref_metadata_2025 huggingface dataset:
Faster, Better, Stronger
Authors: Hallonsten Olof
Published: June 2023

Insightful sociological analyses of current society have identified acceleration as its defining feature. A competitiveness ideal, and a constant aspiration to exceed the promise of a better future with the help of technological progress, have led to a broad exploitation of vague but powerful expectations The result is often mere window-dressing, but progress has also become an identity marker for a class of politicians and business leaders who look for roles for themselves to play in the fulfillment of promises, both “moving fast and breaking things” and launching huge and very costly strategic innovation programs. The chapter analyzes these features of contemporary public and economic life and question the validity of the underlying assumptions.
Bulk reconstruction of AdSd+1 metrics and developing kinematic space
Authors: Sugiura Kakeru , Takeda Daichi
Published: June 2023

Abstract

The metrics of the global, Poincaré, and Rindler AdSd+1 are explicitly reconstructed with given lightcone cuts. We first compute the metric up to a conformal factor with the lightcone cuts method introduced by Engelhardt and Horowitz. While a general prescription to determine the conformal factor is not known, we recover the factor by identifying the causal information surfaces from the lightcone cuts and finding that they are minimal. In addition, we propose a new type of kinematic space as the space of minimal surfaces in AdSd+1, where a metric is introduced as a generalization of the case of d = 2. This metric defines the set of bulk points, which is equivalent to that of lightcone cuts. Some other properties are also studied towards establishing a reconstruction procedure for general bulk metrics.
Einmal geimpft, immer geimpft? Routinedatenanalyse zur wiederholten Influenzaimpfung von ≥ 60-Jährigen
Authors: Storch Josephine , Meissner Franziska , Böde Monique , Kwetkat Anja , Pletz Mathias W. , Freytag Antje
Published: June 2023

Hintergrund

Die Ständige Impfkommission empfiehlt eine jährliche Influenzaimpfung als Standardimpfung für ≥ 60-Jährige und als altersunabhängige Indikationsimpfung. Empirische Daten zur wiederholten Impfung liegen für Deutschland nicht vor. Ziel der Studie war es daher, Häufigkeit und Einflussfaktoren der wiederholten Impfung zu untersuchen.

Methoden

Wir führten eine längsschnittliche retrospektive Beobachtungsstudie mit Routinedaten von ≥ 60‑jährigen Versicherten der Thüringer AOK Plus im Zeitraum 2012–2018 durch. Die Anzahl der Saisons mit Impfung wurde beschrieben und der Zusammenhang mit verschiedenen Versichertenmerkmalen in einem Regressionsmodell analysiert.

Ergebnisse

Es wurden 103.163 Versicherte mit mindestens einer Impfung in der Saison 2014/2015 eingeschlossen, von denen 75,3 % in ≥ 6 von 7 Saisons geimpft wurden. Häufigere Impfungen zeigten sich bei Pflegeheimbewohner:innen (Rate Ratio (RR) 1,27), Personen mit erhöhter gesundheitlicher Gefährdung infolge einer Grunderkrankung (RR 1,21) und höheren Altersgruppen (vs. 60- bis 69-Jährige: RR 1,17–1,25). Mit jedem zusätzlichen Jahr der Teilnahme an einem Disease-Management-Programm stieg die Anzahl der Impfungen (RR 1,03). Weniger häufig geimpft waren Frauen (RR 0,91), Versicherte mit Pflegestufe 1 (vs. keiner Pflegestufe: RR 0,90) und Versicherte mit einer Komorbidität (vs. keiner Komorbidität: RR 0,97).

Diskussion

Ein Großteil der einmal gegen Influenza geimpften ≥ 60-Jährigen lässt sich auch wiederholt impfen. Entsprechend den Empfehlungen sind vor allem Pflegeheimbewohner:innen und Personen mit erhöhter gesundheitlicher Gefährdung wiederholt geimpft. Hausärzt:innen kommt eine zentrale Rolle zu: Nichtakute Patientenkontakte sollten für Impfangebote genutzt werden, insbesondere bei Frauen und in der Häuslichkeit lebenden Pflegebedürftigen.
Clonal diploid and autopolyploid breeding strategies to harness heterosis: insights from stochastic simulation
Authors: Labroo Marlee R. , Endelman Jeffrey B. , Gemenet Dorcus C. , Werner Christian R. , Gaynor Robert Chris , Covarrubias-Pazaran Giovanny E.
Published: June 2023

Key message

Reciprocal recurrent selection sometimes increases genetic gain per unit cost in clonal diploids with heterosis due to dominance, but it typically does not benefit autopolyploids.

Breeding can change the dominance as well as additive genetic value of populations, thus utilizing heterosis. A common hybrid breeding strategy is reciprocal recurrent selection (RRS), in which parents of hybrids are typically recycled within pools based on general combining ability. However, the relative performances of RRS and other breeding strategies have not been thoroughly compared. RRS can have relatively increased costs and longer cycle lengths, but these are sometimes outweighed by its ability to harness heterosis due to dominance. Here, we used stochastic simulation to compare genetic gain per unit cost of RRS, terminal crossing, recurrent selection on breeding value, and recurrent selection on cross performance considering different amounts of population heterosis due to dominance, relative cycle lengths, time horizons, estimation methods, selection intensities, and ploidy levels. In diploids with phenotypic selection at high intensity, whether RRS was the optimal breeding strategy depended on the initial population heterosis. However, in diploids with rapid-cycling genomic selection at high intensity, RRS was the optimal breeding strategy after 50 years over almost all amounts of initial population heterosis under the study assumptions. Diploid RRS required more population heterosis to outperform other strategies as its relative cycle length increased and as selection intensity and time horizon decreased. The optimal strategy depended on selection intensity, a proxy for inbreeding rate. Use of diploid fully inbred parents vs. outbred parents with RRS typically did not affect genetic gain. In autopolyploids, RRS typically did not outperform one-pool strategies regardless of the initial population heterosis.
Suicidal thoughts, suicide attempt and non-suicidal self-harm amongst lesbian, gay and bisexual adults compared with heterosexual adults: analysis of data from two nationally representative English household surveys
Authors: Kidd Garrett , Marston Louise , Nazareth Irwin , Osborn David , Pitman Alexandra
Published: June 2023

Purpose

We aimed to compare differences in suicidality and self-harm between specific lesbian, gay and bisexual (LGB) groups, and investigate whether minority stress factors might contribute to any associations, addressing methodological limitations of previous research.

Methods

We analysed data combined from two population-based representative household surveys of English adults (N = 10,443) sampled in 2007 and 2014. Using multivariable logistic regression models adjusted for age, gender, educational attainment, area-level deprivation, and common mental disorder, we tested the association between sexuality and three suicide-related outcomes: past-year suicidal thoughts, past-year suicide attempt, and lifetime non-suicidal self-harm (NSSH). We added bullying and discrimination (separately) to final models to explore whether these variables might mediate the associations. We tested for interactions with gender and survey year.

Results

Lesbian/gay people were more likely to report past-year suicidal thoughts [adjusted odds ratio (AOR) = 2.20; 95% CI 1.08–4.50] than heterosexuals. No minority group had an increased probability of suicide attempt. Bisexual (AOR = 3.02; 95% CI = 1.78–5.11) and lesbian/gay (AOR = 3.19; 95% CI = 1.73–5.88) individuals were more likely to report lifetime NSSH than heterosexuals. There was some evidence to support a contribution of bullying in the association between lesbian/gay identity and past-year suicidal thoughts, and of each minority stress variable in the associations with NSSH. There was no interaction with gender or survey year.

Conclusion

Specific LGB groups are at elevated risk of suicidal thoughts and NSSH, with a possible contribution of lifetime bullying and homophobic discrimination. These disparities show no temporal shift despite apparent increasing societal tolerance towards sexual minorities.
When to use matching and weighting or regression in instrumental variable estimation? Evidence from college proximity and returns to college
Authors: Tübbicke Stefan
Published: June 2023

Standard two-stage least squares (2SLS) regression remains dominant in instrumental variables estimation of causal effects even though the literature has shown that 2SLS may be inconsistent when effects are heterogenous and the instrument is only valid when conditioning on covariates. To show that this is not merely a hypothetical threat, this paper re-estimates the returns to college using college proximity as an instrument based on the data from Card (Aspects of labour market behavior: essays in honour of John Vanderkamp, University of Toronto Press, Toronto, 1995). The results show that 2SLS yields systematically larger estimates of the returns to college than more flexible estimators based on the instrument propensity score. In the full sample, differences amount to about 50 to 100%. This is due to the implicit conditional-variance weighting performed by 2SLS. Moreover, in line with the theoretical prediction by Sloczynski (When should we (not) interpret linear IV estimands as LATE? IZA discussion papers 14349, Institute of Labor Economics (IZA), 2021), findings suggest that the impact of the conditional-variance weighting is larger when instrument groups are not roughly the same size. Thus, it is advised to use 2SLS with caution and use estimators based on the instrument propensity score instead when groups are of different size and covariates are predictive of the instrument.
Biomarkers in 5q-associated spinal muscular atrophy—a narrative review
Authors: Lapp H. S. , Freigang M. , Hagenacker T. , Weiler M. , Wurster C. D. , Günther René
Published: June 2023

5q-associated spinal muscular atrophy (SMA) is a rare genetic disease caused by mutations in theSMN1gene, resulting in a loss of functional SMN protein and consecutive degeneration of motor neurons in the ventral horn. The disease is clinically characterized by proximal paralysis and secondary skeletal muscle atrophy. New disease-modifying drugs drivingSMNgene expression have been developed in the past decade and have revolutionized SMA treatment. The rise of treatment options led to a concomitant need of biomarkers for therapeutic guidance and an improved disease monitoring. Intensive efforts have been undertaken to develop suitable markers, and numerous candidate biomarkers for diagnostic, prognostic, and predictive values have been identified. The most promising markers include appliance-based measures such as electrophysiological and imaging-based indices as well as molecular markers including SMN-related proteins and markers of neurodegeneration and skeletal muscle integrity. However, none of the proposed biomarkers have been validated for the clinical routine yet. In this narrative review, we discuss the most promising candidate biomarkers for SMA and expand the discussion by addressing the largely unfolded potential of muscle integrity markers, especially in the context of upcoming muscle-targeting therapies. While the discussed candidate biomarkers hold potential as either diagnostic (e.g., SMN-related biomarkers), prognostic (e.g., markers of neurodegeneration, imaging-based markers), predictive (e.g., electrophysiological markers) or response markers (e.g., muscle integrity markers), no single measure seems to be suitable to cover all biomarker categories. Hence, a combination of different biomarkers and clinical assessments appears to be the most expedient solution at the time.
Soil microbiomes in lawns reveal land-use legacy impacts on urban landscapes
Authors: Thompson Grant L. , Bray Natalie , Groffman Peter M. , Kao-Kniffin Jenny
Published: June 2023

Land-use change is highly dynamic globally and there is great uncertainty about the effects of land-use legacies on contemporary environmental performance. We used a chronosequence of urban grasslands (lawns) that were converted from agricultural and forested lands from 10 to over 130 years prior to determine if land-use legacy influences components of soil biodiversity and composition over time. We used historical aerial imagery to identify sites in Baltimore County, MD (USA) with agricultural versus forest land-use history. Soil samples were taken from these sites as well as from existing well-studied agricultural and forest sites used as historical references by the National Science Foundation Long-Term Ecological Research Baltimore Ecosystem Study program. We found that the microbiomes in lawns of agricultural origin were similar to those in agricultural reference sites, which suggests that the ecological parameters on lawns and reference agricultural systems are similar in how they influence soil microbial community dynamics. In contrast, lawns that were previously forest showed distinct shifts in soil bacterial composition upon recent conversion but reverted back in composition similar to forest soils as the lawns aged over decades. Soil fungal communities shifted after forested land was converted to lawns, but unlike bacterial communities, did not revert in composition over time. Our results show that components of bacterial biodiversity and composition are resistant to change in previously forested lawns despite urbanization processes. Therefore land-use legacy, depending on the prior use, is an important factor to consider when examining urban ecological homogenization.
Effect of active warming on perioperative cardiovascular outcomes: a systematic review and meta-analysis of randomized controlled trials
Authors: Feng Yunying , Zhang Yuelun , Sun Boyuan , He Yumiao , Pei Lijian , Huang Yuguang
Published: June 2023

Purpose

The objective of this study was to provide an updated review on the active warming effects on major adverse cardiac events, 30-day all-cause mortality, and myocardial injury after noncardiac surgery.

Method

We systematically searched MEDLINE, EMBASE, CINAHL, Cochrane CENTRAL, Web of Science, and Chinese BioMedical Literature Database. We included randomized controlled trials of adult population undergoing noncardiac surgeries that concentrate on the comparison of active warming methods and passive thermal management. Cochrane Collaboration’s tool was applied for risk-of-bias assessment. We used trial sequential analysis to evaluate the possibility of false positive or negative results.

Results

A total of 13,316 unique records were identified, of which only 19 with reported perioperative cardiovascular outcomes were included in the systematic review and nine of them were included in final meta-analysis. No statistically significant difference between active warming methods and routine care was found in major adverse cardiac events (RR 0.56, 95% confidence interval (CI) 0.14–2.21,I2 = 71%, number of events 59 vs. 70), 30-day all-cause mortality (RR 0.81, 95% CI 0.43–1.54,I2 = 0%, number of events 17 vs. 21), and myocardial injury after noncardiac surgery (RR 0.61, 95% CI 0.17–2.22,I2 = 79%, number of events 236 vs. 234). Trial sequential analysis suggests that current trials did not reach the minimum information size regarding the major cardiovascular events.

Conclusions

Compared to routine perioperative care, we found that active warming methods are not necessary for cardiovascular prevention in patients undergoing noncardiac surgery.
SINNHAFT – die Merkhilfe für die standardisierte Übergabe in der zentralen Notaufnahme
Authors: Gräff I. , Ehlers P. , Schacher S.
Published: June 2023

In der Regel existiert nur eine Möglichkeit für die Übergabe in der Medizin und somit für die Übertragung relevanter Behandlungs- und Patienteninformationen. Der Übergabe an der Nahtstelle zur zentralen Notaufnahme muss somit eine außerordentliche Bedeutung beigemessen werden. Auch aus juristischer Sicht, im Sinne der Übertragung der Verantwortlichkeit, schließt die Übergabe einerseits die präklinische Versorgung ab und gewährleistet andererseits die Weitergabe wichtiger Informationen, um eine bestmögliche klinische Versorgung zu gewährleisten. Aufbauend auf dem Konsensuspapier aus dem Jahr 2020, mit insgesamt 15 Empfehlungen zum strukturierten Übergabeprozess in der zentralen Notaufnahme (ZNA), wurde ein Delphi-Verfahren mit 52 Teilnehmern eingeleitet, welches sich an den Regularien der Arbeitsgemeinschaft der Wissenschaftlichen Medizinischen Fachgesellschaften e. V. (AWMF) orientiert. Im März 2023 konnten die Ergebnisse der zwei Abstimmungsrunden publiziert werden und bieten somit eine evidenzbasierte Grundlage zur Definition der festen Inhalte einer Merkhilfe. Unter Berücksichtigung aller Ergebnisse des Delphi-Verfahrens lässt sich eine Merkhilfe mit dem Akronym „SINNHAFT“ ableiten. Somit ist SINNHAFT 1.0 eine konkrete Merkhilfe, welche erstmalig in einem aufwendigen wissenschaftlichen Prozess Übergabeinhalte, unter Integration von CRM(Crew Ressource Management)-Aspekten, definiert und die Basis für eine Standardisierung der Übergabe an der Nahtstelle Rettungsdienst zur ZNA in Deutschland darstellt.
Anaemia is associated with higher disease activity in axial spondyloarthritis but is not an independent predictor of spinal radiographic progression: data from the Swiss Clinical Quality Management Registry
Authors: Micheroli Raphael , Kissling Seraphina , Bürki Kristina , Möller Burkhard , Finckh Axel , Nissen Michael J. , Exer Pascale , Bräm René , Kyburz Diego , Rubbert-Roth Andrea , Andor Michael , Baraliakos Xenofon , de Hooge Manouk , Distler Oliver , Scherer Almut , Ciurea Adrian
Published: June 2023

Objective

As anaemia represents a biomarker for increased radiographic damage in rheumatoid arthritis, we aimed to investigate whether it independently predicts spinal radiographic progression in axial spondyloarthritis (axSpA).

Methods

AxSpA patients with available haemoglobin levels from the prospective Swiss Clinical Quality Management Registry were included for comparison of patients with and without anaemia. Spinal radiographic progression was assessed according to the modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS) in patients with ankylosing spondylitis (AS) if ≥ 2 sets of spinal radiographs were available every 2 years. The relationship between anaemia and progression (defined as an increase ≥ 2 mSASSS units in 2 years) was analysed with generalized estimating equation models after adjustment for the Ankylosing Spondylitis Disease Activity Score (ASDAS) and potential confounding, as well as after multiple imputations of missing values.

Results

A total of 212/2522 axSpA patients presented with anaemia (9%). Anaemic patients had higher clinical disease activity, higher acute phase reactants and more severe impairments in physical function, mobility and quality of life. In the subgroup of patients with AS (N = 433), a comparable mSASSS progression was found in anaemic and non-anaemic patients (OR 0.69, 95% CI 0.25 to 1.96, p = 0.49). Age, male sex, baseline radiographic damage and ASDAS were associated with enhanced progression. The results were confirmed in complete case analyses and with progression defined as the formation of ≥ 1 syndesmophyte in 2 years.

Conclusion

Although anaemia was associated with higher disease activity in axSpA, it did not additionally contribute to the prediction of spinal radiographic progression.

Key Points• Anaemia is associated with higher disease activity and more severely impaired physical function, mobility and quality of life in axSpA.• Anaemia does not provide an additional value to ASDAS for prediction of spinal radiographic progression.
Deep Ensembles Are Robust to Occasional Catastrophic Failures of Individual DNNs for Organs Segmentations in CT Images
Authors: Petrov Yury , Malik Bilal , Fredrickson Jill , Jemaa Skander , Carano Richard A. D.
Published: June 2023

Deep neural networks (DNNs) have recently showed remarkable performance in various computer vision tasks, including classification and segmentation of medical images. Deep ensembles (an aggregated prediction of multiple DNNs) were shown to improve a DNN’s performance in various classification tasks. Here we explore how deep ensembles perform in the image segmentation task, in particular, organ segmentations in CT (Computed Tomography) images. Ensembles of V-Nets were trained to segment multiple organs using several in-house and publicly available clinical studies. The ensembles segmentations were tested on images from a different set of studies, and the effects of ensemble size as well as other ensemble parameters were explored for various organs. Compared to single models, Deep Ensembles significantly improved the average segmentation accuracy, especially for those organs where the accuracy was lower. More importantly, Deep Ensembles strongly reduced occasional “catastrophic” segmentation failures characteristic of single models and variability of the segmentation accuracy from image to image. To quantify this we defined the “high risk images”: images for which at least one model produced an outlier metric (performed in the lower 5% percentile). These images comprised about 12% of the test images across all organs. Ensembles performed without outliers for 68%–100% of the “high risk images” depending on the performance metric used.
An evolution of low-field strength MRI
Authors: Hennig Juergen
Published: June 2023

The paper describes the evolution of low-field MRI from the very early pioneering days in the late 70 s until today. It is not meant to give a comprehensive historical account of the development of MRI, but rather to highlight the different research environments then and now. In the early 90 s, when low-field systems below 1.5 T essentially vanished, there were just no reasonable means available to make up for the factor of roughly three in signal-to-noise-ratio (SNR) between 0.5 and 1.5 T. This has drastically changed. Improvements in hardware—closed Helium-free magnets, RF receiver systems and especially much faster gradients, much more flexible sampling schemes including parallel imaging and compressed sensing and especially the use of AI at all stages of the imaging process have made low-field MRI a clinically viable supplement to conventional MRI. Ultralow-field MRI with magnets around 0.05 T are also back and constitute a bold and courageous endeavor to bring MRI to communities, which have neither the means nor the infrastructure to sustain a current standard of care MRI.
The Buddy intervention: designing an additional support system for the last year of life. Qualitative insights from triangulated interviews and focus group discussions
Authors: Kasdorf Alina , Voltz Raymond , Strupp Julia
Published: June 2023

Aim

Health and social care structures available for the last year of life care are still not always adequately used. Palliative care, for instance, is still provided late in the disease course, contradicting early integration. We therefore aim to define elements of a possible complementary support concept based on specific experience to help facilitate death at home.

Subject/methods

Qualitative triangulation of data was conducted from countrywide individual interviews (patients and relatives, n = 45) and focus group discussions (health and social care professionals, n = 22), in Germany. Data were transcribed verbatim and analyzed within a framework analysis. Using Bradshaw’s sociological construct of needs, qualitative data sequences were converted into needs and sorted by the theory of social support.

Results

Informants described having needs in emotional, informational, appraisal, and instrumental dimensions. Unmet needs for information were frequently reported, affecting all other need dimensions. To address these concerns, informants expressed a need for someone proactively providing emotional, appraisal, and instrumental support, such as organizing respite support, giving feedback on care provision, and validating caring relatives.

Conclusion

We assume an impact of insufficient information about care options on instrumental, emotional, and appraisal needs and help-seeking actions, increasing the risk of inpatient death. Proactive support is required to address patients’ and families’ needs, connecting the existing care structures. A “buddy” for the last phase of life serving as a low-threshold contact person with real-time knowledge to support patients and families could be one model to support and guide patients and their families and enable dying at home, if possible.
Design Elements of Conflict: A Design Study of a Gamified Smartphone Application for Employee Onboarding
Authors: Palmquist Adam
Published: June 2023

Gamification, the use of game-like elements in non-game contexts, has gained popularity in the field of human resources. However, little research has been conducted on the use of gamification in the employee onboarding process, specifically in terms of socializing and assimilating new employees into an organization. This study aimed to explore the design, development, and implementation of a gamified smartphone application for employee onboarding in a manufacturing company. Ethnographic data was collected over the course of 60 weeks through participation at various field sites and analyzed using thematical analysis with a human-centered design focus, examining the meaning attributed to the gamified application by different stakeholders within the organization. The results showed that different stakeholder groups attributed different and sometimes conflicting meanings to various design elements. The key finding was the identification of four bipolar design dimensions that both supported and hindered the design among stakeholders. These findings have both academic and practical implications for the design of future gamified employee onboarding tools in large enterprises.
How Azide Ion/Hydrazoic Acid Passes Through Biological Membranes: An Experimental and Computational Study
Authors: Hartl Simona Lojevec , Žakelj Simon , Dolenc Marija Sollner , Smrkolj Vladimir , Mavri Janez
Published: June 2023

Hydrazoic acid (HN3) and its deprotonated form azide ion (N3−) (AHA) are toxic because they inhibit the cytochrome c oxidase complex IV (CoX IV) embedded in the inner mitochondrial membrane that forms part of the enzyme complexes involved in cellular respiration. Critical to its toxicity is the inhibition of CoX IV in the central nervous system and cardiovascular system. Hydrazoic acid is an ionizable species and its affinity for membranes, and the associated permeabilities, depend on the pH values of aqueous media on both sides of the membranes. In this article, we address the permeability of AHA through the biological membrane. In order to understand the affinity of the membrane for the neutral and ionized form of azide, we measured the octanol/water partition coefficients at pH values of 2.0 and 8.0, which are 2.01 and 0.00034, respectively. Using a Parallel Artificial Membrane Permeability Assay (PAMPA) experiment, we measured the effective permeability through the membrane, which is logPe − 4.97 and − 5.26 for pH values of 7.4 and pH 8.0, respectively. Experimental permeability was used to validate theoretical permeability, which was estimated by numerically solving a Smoluchowski equation for AHA diffusion through the membrane. We demonstrated that the rate of permeation through the cell membrane of 8.46·104 s−1 is much higher than the rate of the chemical step of CoX IV inhibition by azide of 200 s−1. The results of this study show that transport through the membrane does not represent the rate-limiting step and therefore does not control the rate of CoX IV inhibition in the mitochondria. However, the observed dynamics of azide poisoning is controlled by circulatory transport that takes place on a time scale of minutes.
Measuring Agreement Using Guessing Models and Knowledge Coefficients
Authors: Moss Jonas
Published: June 2023

Several measures of agreement, such as the Perreault–Leigh coefficient, the <mml:math xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mnf="http://cambridge.org/core/manifest" xmlns:cup="http://contentservices.cambridge.org" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:m="http://cambridge.org/core/metadata" xmlns:core="http://cambridge.org/core" xmlns:c="http://cambridge.org/core/content">AC1\documentclass[12pt]{minimal}
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A YOLOv5-based network for the detection of a diffuse reflectance spectroscopy probe to aid surgical guidance in gastrointestinal cancer surgery
Authors: Gkouzionis Ioannis , Zhong Yican , Nazarian Scarlet , Darzi Ara , Patel Nisha , Peters Christopher J. , Elson Daniel S.
Published: June 2023

Purpose

A positive circumferential resection margin (CRM) for oesophageal and gastric carcinoma is associated with local recurrence and poorer long-term survival. Diffuse reflectance spectroscopy (DRS) is a non-invasive technology able to distinguish tissue type based on spectral data. The aim of this study was to develop a deep learning-based method for DRS probe detection and tracking to aid classification of tumour and non-tumour gastrointestinal (GI) tissue in real time.

Methods

Data collected from both ex vivo human tissue specimen and sold tissue phantoms were used for the training and retrospective validation of the developed neural network framework. Specifically, a neural network based on the You Only Look Once (YOLO) v5 network was developed to accurately detect and track the tip of the DRS probe on video data acquired during an ex vivo clinical study.

Results

Different metrics were used to analyse the performance of the proposed probe detection and tracking framework, such as precision, recall, mAP 0.5, and Euclidean distance. Overall, the developed framework achieved a 93% precision at 23 FPS for probe detection, while the average Euclidean distance error was 4.90 pixels.

Conclusion

The use of a deep learning approach for markerless DRS probe detection and tracking system could pave the way for real-time classification of GI tissue to aid margin assessment in cancer resection surgery and has potential to be applied in routine surgical practice.
VIS+AI: integrating visualization with artificial intelligence for efficient data analysis
Authors: Wang Xumeng , Wu Ziliang , Huang Wenqi , Wei Yating , Huang Zhaosong , Xu Mingliang , Chen Wei
Published: June 2023

Visualization and artificial intelligence (AI) are well-applied approaches to data analysis. On one hand, visualization can facilitate humans in data understanding through intuitive visual representation and interactive exploration. On the other hand, AI is able to learn from data and implement bulky tasks for humans. In complex data analysis scenarios, like epidemic traceability and city planning, humans need to understand large-scale data and make decisions, which requires complementing the strengths of both visualization and AI. Existing studies have introduced AI-assisted visualization as AI4VIS and visualization-assisted AI as VIS4AI. However, how can AI and visualization complement each other and be integrated into data analysis processes are still missing. In this paper, we define three integration levels of visualization and AI. The highest integration level is described as the framework of VIS+AI, which allows AI to learn human intelligence from interactions and communicate with humans through visual interfaces. We also summarize future directions of VIS+AI to inspire related studies.
Perceived altruism in cause-related marketing
Authors: Lopes Julia Maringoni , Bairrada Cristela Maia , Coelho Arnaldo Fernandes de Matos
Published: June 2023

The purpose of this paper is to analyze how corporate image may mediate the effects of cause-related marketing on consumer behavior, aiming to expand existing literature in the field of corporate social responsibility. Altruism was used as a moderator of the proposed relationships. The conceptual model presents 7 hypotheses, and the testing is based on a sample of 463 valid respondents from Brazil and Portugal. Data was collected through an online survey and statistically analyzed using the structural equations modeling. The Ekos line of the Brazilian brand Natura is used as an object of study in this research. Brand-cause fit, consumer-cause identification and trust in cause-related marketing (CRM) campaign showed evidence of a positive relationship with corporate image. Corporate image showed a positive relationship with purchase intention, life satisfaction and brand attitude. However, results show how different levels of altruism may affect consumer perceptions. The study has several limitations, in particular due to the use of a convenience sample. This research finds evidence of relevant impacts of brand-cause fit, consumer-cause identification and trust in CRM campaign in the construction of a credible corporate image, which in turn influences greatly purchase intention, consumer satisfaction and overall attitude towards brand, giving precious clues to how to redirect marketing campaigns. The research offers a model that depicts the chain of effects between a CRM campaign and customer decision, introducing the possible impacts on life satisfaction and the moderation of consumer altruistic values.
Adipocyte-derived extracellular vesicles: bridging the communications between obesity and tumor microenvironment
Authors: Zhou Chuan , Huang Yu-Qian , Da Ming-Xu , Jin Wei-Lin , Zhou Feng-Hai
Published: June 2023

By the year 2035 more than 4 billion people might be affected by obesity and being overweight. Adipocyte-derived Extracellular Vesicles (ADEVs/ADEV-singular) are essential for communication between the tumor microenvironment (TME) and obesity, emerging as a prominent mechanism of tumor progression. Adipose tissue (AT) becomes hypertrophic and hyperplastic in an obese state resulting in insulin resistance in the body. This modifies the energy supply to tumor cells and simultaneously stimulates the production of pro-inflammatory adipokines. In addition, obese AT has a dysregulated cargo content of discharged ADEVs, leading to elevated amounts of pro-inflammatory proteins, fatty acids, and carcinogenic microRNAs. ADEVs are strongly associated with hallmarks of cancer (proliferation and resistance to cell death, angiogenesis, invasion, metastasis, immunological response) and may be useful as biomarkers and antitumor therapy strategy. Given the present developments in obesity and cancer-related research, we conclude by outlining significant challenges and significant advances that must be addressed expeditiously to promote ADEVs research and clinical applications.
Seroprevalence of arthropod-borne bacterial infections in homeless individuals in Hamburg in 2020
Authors: Heinrich Fabian , Rauch Jessica , Bertram Franziska , Kempf Volkhard A. J. , Besier Silke , Kuta Piotr , Renné Thomas , Ondruschka Benjamin , Püschel Klaus , Tappe Dennis
Published: June 2023

Purpose

The number of homeless people in Germany is steadily increasing. Due to their often precarious living conditions, this specific population may be increasingly exposed to ectoparasites that can transmit various pathogens. To assess the prevalence and thus the risk of such infections, we analyzed the seropositivity of rickettsiosis, Q fever, tularemia and bartonellosis in homeless individuals.

Methods

A total of 147 homeless adults from nine shelters in Hamburg, Germany, were included. The individuals underwent questionnaire-based interviewing, physical examination, and venous blood was drawn between May and June 2020. Blood samples were analyzed for antibodies against rickettsiae (Rickettsia typhi and R. conorii), Coxiella burnetii, Francisella tularensis and bartonellae.

Results and conclusion

A very low seroprevalence of R. typhi and F. tularensis infection was found (0–1%), while antibodies against R. conorii and C. burnetii were more common (7% each), followed by a relatively high seroprevalence of 14% for bartonellosis. Q fever seroprevalence was associated with the country of origin, whereas bartonellosis seroprevalence was associated with the duration of homelessness. Preventive measures targeting ectoparasites, especially body lice, should be put in place continuously.
Artificial Intelligence Algorithms for Collaborative Book Recommender Systems
Authors: Tegetmeier Clemens , Johannssen Arne , Chukhrova Nataliya
Published: June 2023

Book recommender systems provide personalized recommendations of books to users based on their previous searches or purchases. As online trading of books has become increasingly important in recent years, artificial intelligence (AI) algorithms are needed to recommend suitable books to users and encourage them to make purchasing decisions in the short and the long run. In this paper, we consider AI algorithms for so called collaborative book recommender systems, especially the matrix factorization algorithm using the stochastic gradient descent method and the book-based k-nearest-neighbor algorithm. We perform a comprehensive case study based on the Book-Crossing benchmark data set, and implement various variants of both AI algorithms to predict unknown book ratings and to recommend books to individual users based on the highest predicted ratings. This study aims to evaluate the quality of the implemented methods in recommending books by using selected evaluation metrics for AI algorithms.
WRANet: wavelet integrated residual attention U-Net network for medical image segmentation
Authors: Zhao Yawu , Wang Shudong , Zhang Yulin , Qiao Sibo , Zhang Mufei
Published: June 2023

Medical image segmentation is crucial for the diagnosis and analysis of disease. Deep convolutional neural network methods have achieved great success in medical image segmentation. However, they are highly susceptible to noise interference during the propagation of the network, where weak noise can dramatically alter the network output. As the network deepens, it can face problems such as gradient explosion and vanishing. To improve the robustness and segmentation performance of the network, we propose a wavelet residual attention network (WRANet) for medical image segmentation. We replace the standard downsampling modules (e.g., maximum pooling and average pooling) in CNNs with discrete wavelet transform, decompose the features into low- and high-frequency components, and remove the high-frequency components to eliminate noise. At the same time, the problem of feature loss can be effectively addressed by introducing an attention mechanism. The combined experimental results show that our method can effectively perform aneurysm segmentation, achieving a Dice score of 78.99%, an IoU score of 68.96%, a precision of 85.21%, and a sensitivity score of 80.98%. In polyp segmentation, a Dice score of 88.89%, an IoU score of 81.74%, a precision rate of 91.32%, and a sensitivity score of 91.07% were achieved. Furthermore, our comparison with state-of-the-art techniques demonstrates the competitiveness of the WRANet network.
A framework for drivers fostering social-ecological restoration within forest landscape based on people’s participation. A systematic literature review
Authors: Maniraho Leonidas , Frietsch Marina , Sieber Stefan , Löhr Katharina
Published: June 2023

Degradation exacerbates food and water insecurity, economic hardship, biodiversity loss, and the devastating effects of climate change. Given that ecosystem restoration is a global challenge, the United Nations declared 2021 to 2030 as the Decade of Ecosystem Restoration.

Many ecological restoration projects overlook social perspectives, resulting in unsuccessful restoration outcomes within Forest Landscape Restoration (FLR). Against this background, we review social-ecological restoration frameworks and summarize seven key balanced drivers that could help enhance the adoption of ecosystem restoration in a dynamic social context. The drivers relate to including the most affected communities, privileging local knowledge and practices, empowering local representatives and opinion leaders, ensuring social and environmental justice and equity, targeting deep leverage points, aligning restoration practices with local needs and aspirations, and connecting neighboring communities.

We argue that ecosystem restoration will be most effective if approached from a social-ecological perspective. In developing countries, establishing social groups that share savings and credit structures within neighboring households can be a sustainable approach. With increasing global initiatives, taking a social-ecological perspective on ecosystem restoration as a social-ecological restoration approach offers new opportunities for both research and practice. Social-ecological restoration is a key strategy that can support the achievement of sustainable development goals (SDGs) and deliver net positive gains environmentally, socially, and economically. Further studies should focus on two new cross-cutting aspects: the ecological and social effects of restoration at small to large scales and social ecological restoration and peace building within a restorative landscape.
Sensor system for development of perception systems for ATO
Authors: Tagiew Rustam , Leinhos Dirk , von der Haar Henrik , Klotz Christian , Sprute Dennis , Ziehn Jens , Schmelter Andreas , Witte Stefan , Klasek Pavel
Published: June 2023

Developing AI systems for automatic train operation (ATO) requires developers to have a deep understanding of the human tasks they are trying to replace. This paper fills this gap and translates the regulatory requirements from the context of German railways for the AI developer community. As a result, tasks such as train’s path monitoring for collision prediction, signal detection, door operation, etc. are identified. Based on this analysis, a functionally justified sensor setup with detailed configuration requirements is presented. This setup was also evaluated by a survey within the railway industry. The evaluated sensors include RGB/IR cameras, LIDARs, radars and ultrasonic sensors. Calculations and estimates for the evaluated sensors are presented graphically and included in this paper. However, the ultimate sensor setup is still a subject of research. The results of this paper also address the lack of training and test datasets for railway AI systems. It is proposed to acquire research datasets that will allow the training of domain adaptation algorithms to transform other datasets, thus increasing the number of available datasets. The sensor setup is also recommended for such research datasets.
Pearls of Algorithm Engineering
Authors: Ferragina Paolo
Published: June 2023

There are many textbooks on algorithms focusing on big-O notation and basic design principles. This book offers a unique approach to taking the design and analyses to the level of predictable practical efficiency, discussing core and classic algorithmic problems that arise in the development of big data applications, and presenting elegant solutions of increasing sophistication and efficiency. Solutions are analyzed within the classic RAM model, and the more practically significant external-memory model that allows one to perform I/O-complexity evaluations. Chapters cover various data types, including integers, strings, trees, and graphs, algorithmic tools such as sampling, sorting, data compression, and searching in dictionaries and texts, and lastly, recent developments regarding compressed data structures. Algorithmic solutions are accompanied by detailed pseudocode and many running examples, thus enriching the toolboxes of students, researchers, and professionals interested in effective and efficient processing of big data.
Africa's Fourth Industrial Revolution
Authors: Signé Landry
Published: June 2023

With the rise of new technologies and disruptive innovations reshaping the global economy, the Fourth Industrial Revolution has been characterized as a fusion between the physical, digital, and biological worlds. From the increasing adoption of mobile devices to the entrepreneurial use of 3D printing, artiﬁcial intelligence, and robotics, trends across Africa speak to the continent's potential for growth and sustainable development in the Fourth Industrial Revolution. In this innovative and timely study, Landry Signé examines the meaning, drivers, and implications of the Fourth Industrial Revolution for Africa. Drawing upon comparative, continent-wide analysis, Signé powerfully challenges our understandings of Africa's transformation and sheds light on the potential of the Fourth Industrial Revolution to change and shape the Global South. By deﬁning and investigating the Fourth Industrial Revolution, Signé develops a valuable framework for further study and suggests strategies that Africans and their global partners can use to capitalize upon this rapidly evolving technological landscape.
Meaning, Identity, and Interaction
Authors: Burnett Heather
Published: June 2023

Exciting parallel developments have been made in sociolinguistics and formal semantics, yet these two subfields have had very little contact in the past. This pioneering book bridges this gap, bringing together research and methodologies from both areas of study into a new framework for studying the relation between language, ideologies and the social world. It demonstrates how tools from semantics can be used to formalize theories from sociolinguistics, linguistic anthropology and gender studies, and also shows how tools from epistemic game theory can be used to bring those theories in closer line with empirical studies of sociolinguistic variation and identity construction through language. Engaging and accessible, it highlights how a cross-pollination of ideas in sociolinguistics and semantics can open up a completely new empirical domain of research. It is essential reading for sociolinguists interested in meaning, and semanticists and philosophers interested in language in its social context.
Orchestral Masterpieces under the Microscope
Authors: Del Mar Jonathan
Published: June 2023

A must-have for any conductor, conducting student and orchestral librarian.
Kenya's and Zambia's Relations with China 1949-2019
Authors: Sun Jodie Yuzhou
Published: June 2023

Examines the history of post-colonial Kenya's and Zambia's relations with the People's Republic of China from ideological, political, economic and social perspectives.
Cyber insurance-linked securities
Authors: Braun Alexander , Eling Martin , Jaenicke Christoph
Published: June 2023

We investigate the feasibility of cyber risk transfer through insurance-linked securities (ILS). On the investor side, we elicit the preferred characteristics of cyber ILS and the corresponding return expectations. We then estimate the cost of equity of insurers and compare it to the Rate on Line expected by investors to match demand and supply in the cyber ILS market. Our results show that cyber ILS will work for both cedents and investors if the cyber risk is sufficiently well understood. Thus, challenges related to cyber risk modeling need to be overcome before a meaningful cyber ILS market may emerge.