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Abstract Background Out-of-pocket healthcare expenditure (OOPHE) without adequate social protection often translates to inequitable financial burden and utilization of services. Recent publications highlighted Cambodia’s progress towards Universal Health Coverage (UHC) with reduced incidence of catastrophic health expenditure (CHE) and improvements in its distribution. However, departing from standard CHE measurement methods suggests a different storyline on trends and inequality in the country. Objective This study revisits the distribution and impact of OOPHE and its financial burden from 2009–19, employing alternative socio-economic and economic shock metrics. It also identifies determinants of the financial burden and evaluates inequality-contributing and -mitigating factors from 2014–19, including coping mechanisms, free healthcare, and OOPHE financing sources. Methods Data from the Cambodian Socio-Economic Surveys of 2009, 2014, and 2019 were utilized. An alternative measure to CHE is proposed: Excessive financial burden (EFB). A household was considered under EFB when its OOPHE surpassed 10% or 25% of total consumption, excluding healthcare costs. A polychoric wealth index was used to rank households and measure EFB inequality using the Erreygers Concentration Index. Inequality shifts from 2014–19 were decomposed using the Recentered Influence Function regression followed by the Oaxaca-Blinder method. Determinants of financial burden levels were assessed through zero-inflated ordered logit regression. Results Between 2009–19, EFB incidence increased from 10.95% to 17.92% at the 10% threshold, and from 4.41% to 7.29% at the 25% threshold. EFB was systematically concentrated among the poorest households, with inequality sharply rising over time, and nearly a quarter of the poorest households facing EFB at the 10% threshold. The main determinants of financial burden were geographic location, household size, age and education of household head, social health protection coverage, disease prevalence, hospitalization, and coping strategies. Urbanization, biased disease burdens, and preventive care were key in explaining the evolution of inequality. Conclusion More efforts are needed to expand social protection, but monitoring those through standard measures such as CHE has masked inequality and the burden of the poor. The financial burden across the population has risen and become more unequal over the past decade despite expansion and improvements in social health protection schemes. Health Equity funds have, to some extent, mitigated inequality over time. However, their slow expansion and the reduced reliance on coping strategies to finance OOPHE could not outbalance inequality.

Citizen science has become a proven method across a range of scientific disciplines, able to collect new and complementary data which enhances and adds context to existing scientific methods. By upscaling to a transnational level, citizen science could collect, analyse and exploit a vast amount of data across Europe and beyond, achieving a higher impact through creating a multinational community of citizen scientists. However, many citizen science initiatives start at a small-scale, facing technical and practical challenges when attempting to upscale to a wider level, with current EU mechanisms not providing the support or resources required to assist their effort. The CROPS project (crops-cs.eu) will evolve the EU Research & Innovation system so that it can support the transition of citizen science from small-scale to a Europe-wide level, changing it towards a modern, open-science approach. CROPS consists of four activities: (i) appraisal of existing citizen science, their activities and their suitability for upscaling; (ii) creation of protocols and guidance for the upscaling of citizen science, replicating and building on best practice that exists; (iii) providing guidance regarding practical considerations such as open data sharing, sustainability, RRI and diverse funding opportunities; and (iv) development of transnational citizen science communities, including establishing societal coalitions and prospective citizen science champions to raise awareness of the potential of citizen science when addressing Horizon Europe EU Mission goals.

Over the last decades, an expansion of the underground network has been taking place to cope with the increasing amount of moving people and freight. As a consequence, it is of vital importance to guarantee the full functionality of the tunnel network by means of preventive maintenance and the monitoring of the tunnel lining state over time. A new method has been developed for the real-time prediction of the utilization level in tunnel segmental linings based on input monitoring data. The new concept is founded on a framework, which encompasses an offline and an online stage. In the former, the generation of feedforward neural networks is accomplished by employing synthetically produced data. Finite element simulations of the lining structure are conducted to analyze the structural response under multiple loading conditions. The scenarios are generated by assuming ranges of variation of the model input parameters to account for the uncertainty due to the not fully determined in situ conditions. Input and target quantities are identified to better assess the structural utilization of the lining. The latter phase consists in the application of the methodological framework on input monitored data, which allows for a real-time prediction of the physical quantities deployed for the estimation of the lining utilization. The approach is validated on a full-scale test of segmental lining, where the predicted quantities are compared with the actual measurements. Finally, it is investigated the influence of artificial noise added to the training data on the overall prediction performances and the benefits along with the limits of the concept are set out.

Abstract Fisheries worldwide face uncertain futures as climate change manifests in environmental effects of hitherto unseen strengths. Developing climate-ready management strategies traditionally requires a good mechanistic understanding of stock response to climate change in order to build projection models for testing different exploitation levels. Unfortunately, model-based projections of fish stocks are severely limited by large uncertainties in the recruitment process, as the required stock-recruitment relationship is usually not well represented by data. An alternative is to shift focus to improving the decision-making process, as postulated by the decision-making under deep uncertainty (DMDU) framework. Robust Decision Making (RDM), a key DMDU concept, aims at identifying management decisions that are robust to a vast range of uncertain scenarios. Here we employ RDM to investigate the capability of North Sea cod to support a sustainable and economically viable fishery under future climate change. We projected the stock under 40,000 combinations of exploitation levels, emission scenarios and stock-recruitment parameterizations and found that model uncertainties and exploitation have similar importance for model outcomes. Our study revealed that no management strategy exists that is fully robust to the uncertainty in relation to model parameterization and future climate change. We instead propose a risk assessment that accounts for the trade-offs between stock conservation and profitability under deep uncertainty.

Abstract Marine fisheries are increasingly impacted by climate change, affecting species distribution and productivity, and necessitating urgent adaptation efforts. Climate vulnerability assessments (CVA), integrating expert knowledge, are vital for identifying species that could thrive or suffer under changing environmental conditions. This study presents a first CVA for the Western Baltic Sea's fish community, a crucial fishing area for Denmark and Germany. Characterized by a unique mix of marine, brackish, and freshwater species, this coastal ecosystem faces significant changes due to the combined effects of overfishing, eutrophication and climate change. Our CVA involved a qualitative expert scoring of 22 fish species, assessing their sensitivity and exposure to climate change. Our study revealed a dichotomy in climate change vulnerability within the fish community of the Western Baltic Sea because traditional fishing targets cod and herring as well as other species with complex life histories are considered to face increased risks, whereas invasive or better adaptable species might thrive under changing conditions. Our findings hence demonstrate the complex interplay between life-history traits and climate change vulnerability in marine fish communities. Eventually, our study provides critical knowledge for the urgent development of tailored adaptation efforts addressing existing but especially future effects of climate change on fish and fisheries in the Western Baltic Sea, to navigate this endangered fisheries systems into a sustainable future.

Curcumin is a biopharmaceutical classification system (BCS) class IV substance with many potential therapeutic effects. However, like many other BCS IV active pharmaceutical ingredients, complex formulations are needed to guarantee a sufficiently high bioavailability. A not-so-well-known delivery system is a suspoemulsion (SE). SEs are emulsions with a crystalline API in continuous or dispersed phases. This study aimed to produce curcumin-loaded o/w suspoemulsions with the particle in the oil phase for, e.g., encapsulation or triggered release effects. The particles need to be smaller than the emulsion droplet size to attain high encapsulation efficiencies (EE) in the oil phase. Sonofragmentation and bead milling were tested for their ability to produce these nanocrystals in different dispersion media. It was discovered that production in miglyol was the best fit for the needed application of the crystals in SEs. Around 85% (by volume) of the particles produced with bead milling were smaller than the droplet size of about 5 µm. In contrast, only 23% of the sonofragmentated particles were below the diameter of those droplets. This oily suspension was then used to successfully produce hydrogel-based o/w suspoemulsions. In the second part of this study, we investigated different methods for determining encapsulation efficiency, but none of the methods accurately and satisfactorily resolved the encapsulation efficiency. Finally, the suspoemulsions could not be macroscopically distinguished from one another and were physically stable. In summary, we showed that stable hydrogel-based curcumin-loaded o/w suspoemulsions could be produced. [ABSTRACT FROM AUTHOR]

The continuous monitoring of structural integrity is crucial, as imperceptible damage may appear at any point throughout a structure's lifespan. Several Structural Health Monitoring (SHM) technologies have been developed so far to detect and assess defects in structures. Deep Learning is a common tool for processing data obtained with SHM systems. Although many artificial intelligence-based SHM technologies exist already for damage detection, only a few are focused on damage localization. Existing localization approaches are limited through them being applied on defined simple structures and requiring a large amount of data, which is usually unavailable in practical applications. In this work, measured data from guided ultrasonic wave propagation is used to determine the location of damage in a composite stiffened structure representative of fuselage segments. A novel artificial intelligencebased approach for damage localization is presented and tested with a feed-forward as well as a convolutional neural network. Both architectures show that localization is possible. The accuracy is then analyzed with the probability of localization method and compared to existing non-artificial intelligence-based approaches. These results make it possible to define the minimum damage that can be correctly localized.

This work introduces the “pyJSON Schema Loader and JSON Editor”, a client-side desktop application for offline and local environments capable of creating, editing and tracking metadata-containing JSON documents. The newly developed tool aims to support the generation and re-use of structured metadata, required for the implementation of research data management and the FAIR data principles in research workflows. pyJSON is written in Python, a modern and flexible programming language. The interface consists of a table-like view tailored to present JSON documents, enriched with information from the corresponding JSON schema. It shall assist in creating and maintaining documents containing metadata by simplifying the process of generation and editing based on a given schema. It is used to document data sets, data collections and devices in a local file structure, intending to support the transition from paper-based documentation to more modern research data management workflows, while sustaining a uniform and standardised structure, without the need to bind users to an often complex and resource demanding database system.

Abstract Gas sensors based on micro‐electromechanical systems (MEMS) offer advantages such as a broad spectrum of potentially sensitive materials and analytes, easy miniaturization and integration, high sensitivity, and low costs. This paper introduces a novel MEMS sensor platform utilizing a suspended gate field effect transistor (SGFET) transducer. In this approach, the flexible gate membrane of the SGFET is coated with a sensitive material exhibiting responsive swelling behavior. For the proof of concept, kraft lignin hydrogel is chosen as a biorenewable material for humidity sensing. A precision dispensing technique is used to deposit kraft lignin hydrogel on the SGFETs. The sensor measurements yield reversible shifts in the sensor's output current of up to 9% in response to 5000 ppm water vapor. The results successfully demonstrate the feasibility of this new sensing platform.

IntroductionThe ABLE Exoskeleton has been tested to be safe and feasible for persons with spinal cord injury (SCI) to complete basic skills in clinical settings but has not been tested for use in home and community environments. A user-centered design process was employed to test the feasibility of the current ABLE Exoskeleton (designed for clinical use) for persons with SCI to perform the basic and advanced skills required for home and community environments, to gain crucial feedback for the development of a novel personal-use exoskeleton.MethodsIn this prospective pretest-posttest quasi-experimental study across two SCI centers (Germany, Spain), in-and outpatients with SCI were included into a 22-session training and assessment protocol, utilizing the ABLE Exoskeleton. Feasibility and usability measures [level of assistance (LoA) for basic and advanced skills, donning/doffing-time and LoA] were recorded together with safety outcomes, and participant and therapist satisfaction with the device.Results10 participants (44.4 ± 24 years), with SCI from C5 to T11, (American Spinal Injury Association Impairment Scale A–D) completed the study. In 209 sessions, six device-related adverse events (pain and skin lesions) were reported. Average total time for don and doff was 10:23 ± 3:30 min. Eight participants were able to complete don and doff with minimal assistance or less. Independence to carry out all skills in the device increased significantly for all participants (p

Abstract Background The prevalence of sacroiliac joint pain (SIJP) is estimated to be 10–30% in patients with chronic low back pain. Numerous conservative and surgical treatment modalities for SIJP have been described with limited evidence regarding long-term pain relief. Spinal cord stimulation (SCS) is a well-established technique to treat patients with chronic low back pain. However, the effect on patients with SIJP is not consistent. Therefore, peripheral nerve stimulation (PNS) for chronic SIJP was implemented in experimental trials. Clinical data on PNS for SIJP is still lacking. The authors present a case series and a protocol for a prospective, multicenter study to determine the effect of PNS in patients with chronic intractable SIJP. Method A multicenter, prospective randomized controlled trial was designed. Patients with chronic intractable SIJP will be recruited and randomized in a 4:3 ratio to either the peripheral nerve stimulation group or to the best medical treatment group. A total of 90 patients are planned to be enrolled (52 in the PNS group and 38 in the BMT group). Patients in the intervention group receive a percutaneous implantation of a unilateral or bilateral lead which is externalized for a trial phase for 3–14 days. After trial phase only patients with at least 50% reduction of pain receive an impulse generator for permanent stimulation. Regular visits for participants are planned on day 0, after 3 months (± 30 days), 6 months (± 30 days), and 12 months (± 60 days). The primary outcome measurements is the difference in Numeric Pain Rating Scale (NRS) between baseline and after 6 months. Secondary outcomes is improvement of pain associated disability (ODI) and improvement of health-related quality of life after 6 and 12 months. Discussion We have described the protocol for a prospective, multicenter, randomized trial evaluating the influence of PNS on patients with chronic sacroiliac joint syndrome. We believe that PNS on patients with chronic sacroiliac joint syndrome will show promising results regarding pain relief and quality of life in comparison to BMT after 12 months. The design of this trial promises high evidence in comparison to the data to date. Trial registration ClinicalTrials.gov, NCT05357300. Registered on April 26, 2022.

Background: Vagus nerve stimulation (VNS) at low frequencies (≤30 Hz) has been an established treatment for drug-resistant epilepsy (DRE) for over 25 years. Objective: To examine the initial safety and efficacy performance of an investigational, high-frequency (≥250 Hz) VNS paradigm herein called “Microburst VNS” (μVNS). μVNS consists of short, high-frequency bursts of electrical pulses believed to preferentially modulate certain brain regions. Methods: Thirty-three (33) participants were enrolled into an exploratory feasibility study, 21 with focal-onset seizures and 12 with generalized-onset seizures. Participants were titrated to a personalized target dose of μVNS using an investigational fMRI protocol. Participants were then followed for up to 12 months, with visits every 3 months, and monitored for side-effects at all time points. This study was registered as NCT03446664 on February 27th, 2018. Results: The device was well-tolerated. Reported adverse events were consistent with typical low frequency VNS outcomes and tended to diminish in severity over time, including dysphonia, cough, dyspnea, and implant site pain. After 12 months of μVNS, the mean seizure frequency reduction for all seizures was 61.3% (median reduction: 70.4%; 90% CI of median: 48.9%–83.3%). The 12-month responder rate (≥50% reduction) was 63.3% (90% CI: 46.7%–77.9%) and the super-responder rate (≥80% reduction) was 40% (90% CI: 25.0%–56.6%). Participants with focal-onset seizures appeared to benefit similarly to participants with generalized-onset seizures (mean reduction in seizures at 12 months: 62.6% focal [n = 19], versus 59.0% generalized [n = 11]). Conclusion: Overall, μVNS appears to be safe and potentially a promising therapeutic alternative to traditional VNS. It merits further investigation in randomized controlled trials which will help determine the impact of investigational variables and which patients are most suitable for this novel therapy.

Abstract Background Coronary heart diseases (CHDs) have experienced the largest increase worldwide as a cause of death, accounting for 16% of all deaths. In Saxony-Anhalt, a federal state in Germany, both CHD morbidity and acute myocardial infarction mortality rates are particularly high. Several risk factors associated with CHDs have been studied in Saxony-Anhalt, but sex differences in service use and medication have not been investigated. This study therefore aimed to investigate sex differences in the quality and quantity of cardiological care provided to adults with CHD. Methods This study used health claims data from 2018 to 2020 to analyse the utilisation of healthcare services and adherence to medication-related guideline recommendations in primary and specialist care. The sample included 133,661 individuals with CHD from a major statutory health insurance company (Germany). Results Almost all CHD patients (> 99%) received continuous primary care. Continuous cardiologist utilisation was lower for females than for males, with 15.0% and 22.2%, respectively, and sporadic utilisation showed greater differences, with 33.5% of females and 43.4% of males seeking sporadic cardiologist consultations. Additionally, 43.1% of the identified CHD patients participated in disease management programmes (DMPs). The study also examined the impact of DMP participation and cardiologist care on medication uptake and revealed that sex differences in medication uptake, except for statin use, were mitigated by these factors. Statins were prescribed to 42.9% of the CHD patients eligible for statin prescription in accordance with the QiSA indicator for statin prescription eligibility. However, there were significant sex differences in statin utilisation. Female CHD patients were less likely to use statins (35.2%) than male CHD patients were (50.1%). The difference in statin utilisation persisted after adjustment for DMP participation and cardiologist consultation. Conclusions This study highlights sex differences in the utilisation of cardiological healthcare services for patients with CHD in the Saxony-Anhalt cohort. These findings underscore the continuing need for interventions to reduce sex inequalities in accessing healthcare and providing health care for patients with CHD. Factors at the health care system, patient, and physician levels should be further investigated to eventually improve statin prescription in people with CHD, especially women.

Abstract Importance Contact tracing is the process of identifying people who have recently been in contact with someone diagnosed with an infectious disease. During an outbreak, data collected from contact tracing can inform interventions to reduce the spread of infectious diseases. Understanding factors associated with completion rates of contact tracing surveys can help design improved interview protocols for ongoing and future programs. Objective To identify factors associated with completion rates of COVID-19 contact tracing surveys in New York City (NYC) and evaluate the utility of a predictive model to improve completion rates, we analyze laboratory-confirmed and probable COVID-19 cases and their self-reported contacts in NYC from October 1st 2020 to May 10th 2021. Methods We analyzed 742,807 case investigation calls made during the study period. Using a log-binomial regression model, we examined the impact of age, time of day of phone call, and zip code-level demographic and socioeconomic factors on interview completion rates. We further developed a random forest model to predict the best phone call time and performed a counterfactual analysis to evaluate the change of completion rates if the predicative model were used. Results The percentage of contact tracing surveys that were completed was 79.4%, with substantial variations across ZIP code areas. Using a log-binomial regression model, we found that the age of index case (an individual who has tested positive through PCR or antigen testing and is thus subjected to a case investigation) had a significant effect on the completion of case investigation – compared with young adults (the reference group,24 years old 65 years old) were lower by 12.1% (95%CI: 11.1% – 13.3%), and the completion rate for youth group (age

With the fact that the main operational parameters of the construction process in mechanized tunneling are currently selected based on monitoring data and engineering experience without exploiting the advantages of computer methods, the focus of this work is to develop a simulation-based real-time assistant system to support the selection of operational parameters. The choice of an appropriate set of these parameters (i.e., the face support pressure, the grouting pressure, and the advance speed) during the operation of tunnel boring machines (TBM) is determined by evaluating different tunneling-induced soil-structure interactions such as the surface settlement, the associated risks on existing structures and the tunnel lining behavior. To evaluate soil-structure behavior, an advanced process-oriented numerical simulation model based on the finite cell method is utilized. To enable the real-time prediction capability of the simulation model for a practical application during the advancement of TBMs, surrogate models based on the Proper Orthogonal Decomposition and Radial Basis Functions (POD-RBF) are adopted. The proposed approach is demonstrated through several synthetic numerical examples inspired by the data of real tunnel projects. The developed methods are integrated into a user-friendly application called SMART to serve as a support platform for tunnel engineers at construction sites. Corresponding to each user adjustment of the input parameters, i.e., each TBM driving scenario, approximately two million outputs of soil-structure interactions are quickly predicted and visualized in seconds, which can provide the site engineers with a rough estimation of the impacts of the chosen scenario on structural responses of the tunnel and above ground structures.

Abstract Background Transglutaminase 2 (TGase 2) is a multifunctional protein and has a prominent role in various (patho)physiological processes. In particular, its transamidase activity, which is rather latent under physiological conditions, gains importance in malignant cells. Thus, there is a great need of theranostic probes for targeting tumor-associated TGase 2, and targeted covalent inhibitors appear to be particularly attractive as vector molecules. Such an inhibitor, equipped with a radionuclide suitable for noninvasive imaging, would be supportive for answering the general question on the possibility for functional characterization of tumor-associated TGase 2. For this purpose, the recently developed 18F-labeled N ε-acryloyllysine piperazide [ 18 F]7b, which is a potent and selective irreversible inhibitor of TGase 2, was subject to a detailed radiopharmacological characterization herein. Results An alternative radiosynthesis of [ 18 F]7b is presented, which demands less than 300 µg of the respective trimethylammonio precursor per synthesis and provides [ 18 F]7b in good radiochemical yields (17 ± 7%) and high (radio)chemical purities (≥ 99%). Ex vivo biodistribution studies in healthy mice at 5 and 60 min p.i. revealed no permanent enrichment of 18F-activity in tissues with the exception of the bone tissue. In vivo pretreatment with ketoconazole and in vitro murine liver microsome studies complemented by mass spectrometric analysis demonstrated that bone uptake originates from metabolically released [18F]fluoride. Further metabolic transformations of [ 18 F]7b include mono-hydroxylation and glucuronidation. Based on blood sampling data and liver microsome experiments, pharmacokinetic parameters such as plasma and intrinsic clearance were derived, which substantiated the apparently rapid distribution of [ 18 F]7b in and elimination from the organisms. A TGase 2-mediated uptake of [ 18 F]7b in different tumor cell lines could not be proven. Moreover, evaluation of [ 18 F]7b in melanoma tumor xenograft models based on A375-hS100A4 (TGase 2 +) and MeWo (TGase 2 −) cells by ex vivo biodistribution and PET imaging studies were not indicative for a specific targeting. Conclusion [ 18 F]7b is a valuable radiometric tool to study TGase 2 in vitro under various conditions. However, its suitability for targeting tumor-associated TGase 2 is strongly limited due its unfavorable pharmacokinetic properties as demonstrated in rodents. Consequently, from a radiochemical perspective [ 18 F]7b requires appropriate structural modifications to overcome these limitations.

This paper deals with double-pulse laser-induced breakdown spectroscopy (LIBS) underwater, which is a promising analytical method for elemental analysis in the deep sea up to a water depth of 6000 m. A double-pulse laser with a wavelength of 1064 nm is used, which provides a pulse energy of up to 266 mJ for each laser pulse (in single pulse mode), a pulse width of 5–7 ns and a pulse delay in the range of 0.5 to 20 µs. In the double-pulse LIBS method, the first laser pulse creates a cavity on the material surface, and then the second laser pulse forms the plasma in this cavity. It is expected that the plasma is affected by the cavity’s size and lifetime. For this reason, the influence of focus position, pulse energy and pulse delay on the cavity and plasma formation at shallow water depth has been investigated.