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We present the Eindhoven Wildflower Dataset (EWD) as well as a PyTorch object detection model that is able to classify and count wildflowers. EWD, collected over two entire flowering seasons and expert annotated, contains 2,002 top-view images of flowering plants captured ‘in the wild’ in five different landscape types (roadsides, urban green spaces, cropland, weed-rich grassland, marshland). It holds a total of 65,571 annotations for 160 species belonging to 31 different families of flowering plants and serves as a reference dataset for automating wildflower monitoring and object detection in general. To ensure consistent annotations, we define species-specific floral count units and provide extensive annotation guidelines. With a 0.82 mAP (@IoU > 0.50) score the presented baseline model, trained on a balanced subset of EWD, is to the best of our knowledge superior in its class. Our approach empowers automated quantification of wildflower richness and abundance, which helps understanding and assessing natural capital, and encourages the development of standards for AI-based wildflower monitoring. The annotated EWD dataset and the code to train and run the baseline model are publicly available.

Background Large language models (LLMs) show increasing potential for their use in healthcare for administrative support and clinical decision making. However, reports on their performance in critical care medicine is lacking. Methods This study evaluated five LLMs (GPT-4o, GPT-4o-mini, GPT-3.5-turbo, Mistral Large 2407 and Llama 3.1 70B) on 1181 multiple choice questions (MCQs) from the gotheextramile.com database, a comprehensive database of critical care questions at European Diploma in Intensive Care examination level. Their performance was compared to random guessing and 350 human physicians on a 77-MCQ practice test. Metrics included accuracy, consistency, and domain-specific performance. Costs, as a proxy for energy consumption, were also analyzed. Results GPT-4o achieved the highest accuracy at 93.3%, followed by Llama 3.1 70B (87.5%), Mistral Large 2407 (87.9%), GPT-4o-mini (83.0%), and GPT-3.5-turbo (72.7%). Random guessing yielded 41.5% ( p  < 0.001). On the practice test, all models surpassed human physicians, scoring 89.0%, 80.9%, 84.4%, 80.3%, and 66.5%, respectively, compared to 42.7% for random guessing ( p  < 0.001) and 61.9% for the human physicians. However, in contrast to the other evaluated LLMs ( p  < 0.001), GPT-3.5-turbo’s performance did not significantly outperform physicians ( p  = 0.196). Despite high overall consistency, all models gave consistently incorrect answers. The most expensive model was GPT-4o, costing over 25 times more than the least expensive model, GPT-4o-mini. Conclusions LLMs exhibit exceptional accuracy and consistency, with four outperforming human physicians on a European-level practice exam. GPT-4o led in performance but raised concerns about energy consumption. Despite their potential in critical care, all models produced consistently incorrect answers, highlighting the need for more thorough and ongoing evaluations to guide responsible implementation in clinical settings.

Obese patients are more likely to develop periprosthetic joint infection (PJI) after primary total joint arthroplasty. This study compared the clinical and microbiological characteristics of non-obese, obese and severely obese patients with early PJI, in order to ultimately optimize antibiotic prophylaxis and other prevention measures for this specific patient category. We retrospectively evaluated patients with early PJI of the hip and knee treated with debridement, antibiotics and implant retention (DAIR) between 2006 and 2016 in three Dutch hospitals. Only patients with primary arthroplasties indicated for osteoarthritis were included. Early PJI was defined as an infection that developed within 90 days after index surgery. Obesity was defined as a BMI ≥30kg/m2 and severe obesity as a BMI ≥35kg/m2. A total of 237 patients were analyzed, including 64 obese patients (27.0%) and 62 severely obese patients (26.2%). Compared with non-obese patients, obese patients had higher rates of polymicrobial infections (60.3% vs 33.3%, p<0.001) with more often involvement of Enterococcus species (27.0% vs 11.7%, p = 0.003). Moreover, severely obese patients had more Gram-negative infections, especially with Proteus species (12.9% vs 2.3%, p = 0.001). These results were only found in periprosthetic hip infections, comprising Gram-negative PJIs in 34.2% of severely obese patients compared with 24.7% in obese patients and 12.7% in non-obese patients (p = 0.018). Our results demonstrate that obese patients with early periprosthetic hip infections have higher rates of polymicrobial infections with enterococci and Gram-negative rods, which stresses the importance of improving preventive strategies in this specific patient category, by adjusting antibiotic prophylaxis regimens, improving disinfection strategies and optimizing postoperative wound care.

Many Indonesian, and in particular Javan, birds are suspected to have declined dramatically as a result of unsustainable trapping for the cagebird trade, but quantitative evidence of the scale of declines is lacking for the great majority of species. We conducted field surveys of the heavily traded Javan White-eye Zosterops flavus at 19 key sites in 2018–2019 matching the methods and personnel used in baseline surveys done around 10 years earlier. Overall numbers counted were 84% lower in the later survey, and while more white-eyes were recorded at three sites in 2018–2019, there was a significant decline in numbers across all sites. The three sites with highest numbers in 2006–2019 (502 birds counted) had 22 individuals counted in 2018–2019, but there was no overall trend for ‘declines’ to be greater at sites that held more birds originally. Declines in white-eyes were much steeper than those of several lesser-traded bird species at the sites, suggesting that trapping has been a more important driver of declines than habitat changes such as conversion of mangrove to shrimp ponds. Small numbers of white-eyes were recorded at several previously unvisited sites, but we suggest that the species, on Java at least, has shown declines in the region of 80% over the last 10 years. Although since 2018 Javan White-eye is legally protected, we urge that this protection is extended to all white-eye species, because of their similarity.

Designating protected areas remains a core strategy in biodiversity conservation. Despite high endemism, montane forests across the island of Java are under-represented in Indonesia's protected area network. Here, we document the montane biodiversity of Gunung Slamet, an isolated volcano in Central Java, and provide evidence to support its increased protection. During September–December 2018, we surveyed multiple sites for birds, primates, terrestrial mammals, reptiles, amphibians and vegetation. Survey methods included transects, camera traps and targeted searches at six sites, at altitudes of 970–2,512 m. We used species distribution models for birds and mammals of conservation concern to identify priority areas for protection. We recorded 99 bird species (13 globally threatened), 15 mammals (five globally threatened) and 17 reptiles and amphibians (two endemic). Our species distribution models showed considerable cross-taxon congruence between important areas on Slamet's upper slopes, generally above 1,800 m. Particularly important were records of the endemic subspecies of the Endangered Javan laughingthrush Garrulax rufifrons slamatensis, not recorded in the wild since 1925, the Endangered Javan gibbon Hylobates moloch and Javan surili Presbytis comata, and the Vulnerable Javan lutung Trachypithecus auratus and Javan leopard Panthera pardus melas. Recent forest loss has been modest, at least 280 km2 of continuous forest remain above 800 m, and our surveys show that forest habitats are in good condition. However, the mountain is widely used by trappers and hunters. Given its importance for biodiversity conservation, we discuss different options for improving the protection status of Gunung Slamet, including designation as a National Park or Essential Ecosystem.

The recent availability of sex pheromone lures for the navel orangeworm, Amyelois transitella (Walker) (Lepidoptera: Pyralidae), improves options for monitoring this key pest in conventionally managed almonds. These lures are, however, minimally effective in the presence of mating disruption. Experiments were conducted to determine if phenyl propionate (PPO), an attractant for the navel orangeworm, acts in an additive or synergistic manner when presented together with the pheromone. In the absence of mating disruption, traps baited with PPO captured significantly fewer adults than traps baited with a sex pheromone lure. There was no difference in the number of adults captured in traps with both attractants when mating disruption was not used. In the presence of mating disruption, pheromone traps were completely suppressed, yet traps with both pheromone and PPO captured significantly more adults than traps baited with only PPO. Traps with only PPO captured equal numbers of both sexes, whereas traps with both attractants had significantly more males. These findings demonstrate that PPO is likely to be useful for monitoring navel orangeworm in fields treated with mating disruption.

BackgroundLaparoscopic surgery potentially increases the physical burden to operating theater personnel and can cause physical discomfort. This study aims to evaluate if a robotic camera holder (AutoLap™ system) can improve ergonomics for the surgeon and the camera assistant during laparoscopic procedures.MethodsA total of thirty cases were included and randomized (15 AutoLap™, 15 control). Five types of surgery were included: right hemicolectomy, fundoplication, sigmoid resection, rectopexy, and low anterior resection. The posture of the surgeon and assistant was photographed during predefined steps of the procedure. MATLAB was used to calculate angles relevant for the RULA score. The RULA score is a validated method to evaluate body posture, force and repetition of the upper extremities. Two investigators assessed the RULA score independently. Three subjective questionnaires (SMEQ, NASA TLX, and LED) were used to assess mental and physical discomfort.ResultsNo differences in patient characteristics were observed. Sixteen fundoplications, seven right hemicolectomies, five sigmoid resections, one rectopexy, and one low anterior resection were included. The mean RULA score of the surgeon was comparable in both groups, 2.58 (AutoLap™) versus 2.72 (control). The mean RULA score of the assistant was significantly different in both groups, with 2.55 (AutoLap™) versus 3.70 (control) (p = 0.001). The inter-observer variability (ICC) was excellent with 0.93 (surgeon) and 0.97 (assistant). The questionnaires showed a significant difference in physical discomfort for the assistant. The LED and SMEQ score were significantly lower in the robotic group. The NASA TLX demonstrated a significant reduction in scores in all domains when using robotics with the exception of the mental domain.ConclusionUse of the AutoLap™ system shows improvement in ergonomics and posture of the first assistant, and ergonomics of the surgeon are not affected. Furthermore, the subjective work load is significantly reduced by using a robotic camera holder.Trial registration numberNCT0339960, https://clinicaltrials.gov/ct2/show/study/NCT03339960?term=autolap&rank=5.

Non-volatile 'flash' memories are key components of integrated circuits because they retain their data when power is interrupted. Despite their great commercial success, the semiconductor industry is searching for alternative non-volatile memories with improved performance and better opportunities for scaling down the size of memory cells. Here we demonstrate the feasibility of a new semiconductor memory concept. The individual memory cell is based on a narrow line of phase-change material. By sending low-power current pulses through the line, the phase-change material can be programmed reversibly between two distinguishable resistive states on a timescale of nanoseconds. Reducing the dimensions of the phase-change line to the nanometre scale improves the performance in terms of speed and power consumption. These advantages are achieved by the use of a doped-SbTe phase-change material. The simplicity of the concept promises that integration into a logic complementary metal oxide semiconductor (CMOS) process flow might be possible with only a few additional lithographic steps.

Aims/hypothesis There is a lack of e-health systems that integrate the complex variety of aspects relevant for diabetes self-management. We developed and field-tested an e-health system (POWER2DM) that integrates medical, psychological and behavioural aspects and connected wearables to support patients and healthcare professionals in shared decision making and diabetes self-management. Methods Participants with type 1 or type 2 diabetes (aged >18 years) from hospital outpatient diabetes clinics in the Netherlands and Spain were randomised using randomisation software to POWER2DM or usual care for 37 weeks. This RCT assessed the change in HbA 1c between the POWER2DM and usual care groups at the end of the study (37 weeks) as a primary outcome measure. Participants and clinicians were not blinded to the intervention. Changes in quality of life (QoL) (WHO-5 Well-Being Index [WHO-5]), diabetes self-management (Diabetes Self-Management Questionnaire – Revised [DSMQ-R]), glycaemic profiles from continuous glucose monitoring devices, awareness of hypoglycaemia (Clarke hypoglycaemia unawareness instrument), incidence of hypoglycaemic episodes and technology acceptance were secondary outcome measures. Additionally, sub-analyses were performed for participants with type 1 and type 2 diabetes separately. Results A total of 226 participants participated in the trial (108 with type 1 diabetes; 118 with type 2 diabetes). In the POWER2DM group ( n =111), HbA 1c decreased from 60.6±14.7 mmol/mol (7.7±1.3%) to 56.7±12.1 mmol/mol (7.3±1.1%) (means ± SD, p <0.001), compared with no change in the usual care group ( n =115) (baseline: 61.7±13.7 mmol/mol, 7.8±1.3%; end of study: 61.0±12.4 mmol/mol, 7.7±1.1%; p =0.19) (between-group difference 0.24%, p =0.008). In the sub-analyses in the POWER2DM group, HbA 1c in participants with type 2 diabetes decreased from 62.3±17.3 mmol/mol (7.9±1.6%) to 54.3±11.1 mmol/mol (7.1±1.0%) ( p <0.001) compared with no change in HbA 1c in participants with type 1 diabetes (baseline: 58.8±11.2 mmol/mol [7.5±1.0%]; end of study: 59.2±12.7 mmol/mol [7.6±1.2%]; p =0.84). There was an increase in the time during which interstitial glucose levels were between 3.0 and 3.9 mmol/l in the POWER2DM group, but no increase in clinically relevant hypoglycaemia (interstitial glucose level below 3.0 mmol/l). QoL improved in participants with type 1 diabetes in the POWER2DM group compared with the usual care group (baseline: 15.7±3.8; end of study: 16.3±3.5; p =0.047 for between-group difference). Diabetes self-management improved in both participants with type 1 diabetes (from 7.3±1.2 to 7.7±1.2; p =0.002) and those with type 2 diabetes (from 6.5±1.3 to 6.7±1.3; p =0.003) within the POWER2DM group. The POWER2DM integrated e-health support was well accepted in daily life and no important adverse (or unexpected) effects or side effects were observed. Conclusions/interpretation POWER2DM improves HbA 1c levels compared with usual care in those with type 2 diabetes, improves QoL in those with type 1 diabetes, improves diabetes self-management in those with type 1 and type 2 diabetes, and is well accepted in daily life. Trial registration ClinicalTrials.gov NCT03588104. Funding This study was funded by the European Union’s Horizon 2020 Research and Innovation Programme (grant agreement number 689444). Graphical Abstract

The focus of our study is to identify physical properties of different impact-resistant/toughened structural adhesives and identify/develop an elastic-viscoelastic-plastic model as a function of loading rate by using Ludwik-type equations to be able to predict adhesive behavior at higher loading rates and to make cars more crashworthy. For this purpose, we first characterized eight different commercial toughened epoxy structural adhesives to provide detailed information about their constituents using X-ray diffraction (XRD), differential thermal analysis (DTA), thermogravimetric analysis (TGA), scanning electron microscope (SEM) and energy dispersive x-ray spectrometer (EDS). Most (but not all) of the model adhesives contained organic tougheners in the form of carboxyl terminated butadiene acrylonitrile (CTBN) copolymer, as well as polyurethane adducts. The main crystalline inorganic phases were found as calcite (CaCO3), wollastonite (CaSiO3) or calcium silicate (CaSiO3), talc (Mg3Si4O10 (OH)2), zeolite which is an alumina silicate based mineral and has many different elements in its composition (M2/nO·Al2O3·xSiO2·yH2O, M can be Mg, Na, Ca, K, Li). The total amount of inorganic fillers was found to be different in each adhesive. Material behavior of the model adhesives were determined via tensile tests and Single Lap Joint (SLJ) tests in shear. Split Hopkinson pressure bar (SHPB) was also used to measure the strain and stress values at higher strain rates in the order of 102 s−1, which is generally encountered in impact related loading situations. Toughness values in the range ~0.5 to ~1.35 MJ/m3 were observed with the model adhesives tested in tensile mode within the ~3 × 10−3 to 0.18 m/m/s strain rate range. The softening behavior of the elastic moduli at higher strain rates observed during tensile testing was also observed with SHPB testing. It is remarkable that, overall, the modulus magnitudes seem to be similar between the tensile test and SHPB specimens within this softening range of the initial bilinear elastic behavior observed. When the results from bulk (tensile) and bonded (shear) specimens were compared, it was clearly seen that the toughness responses of the adhesives to (tensile/shear) strain rates in the bulk and bonded forms, respectively, were different, with the bonded shear toughness values in the ~25 to ~120 MJ/m3 range within ~1.25 to ~25 mm/mm/s shear strain range. The model adhesive which included just inorganic fillers had the lowest tensile toughness at the lowest tensile strain rate, but the highest slope in its tensile toughness regression line, exhibited the second highest bonded shear toughness. When tested at the extension rates of 25 mm/min and 100 mm/min in bonded lap shear, the same adhesive exhibited limited interfacial failure areas, however the dominant failure mode was cohesive failure. When the extension rate increased further, transition to interfacial (adhesive) failure was observed revealing that interfacial failures do not necessarily diminish adhesive bond toughness. Our observations point to the fact that cohesive deformation/failure processes indicating interfacial separations, inter-particle interactions as well as polymer matrix deformation in high deformation loading scenario as in bonded shear loadings may provide the highest toughness. Apparently, a large inorganic filler weight fraction is not necessary to obtain high shear toughness in bonded form since the highest bonded shear toughness was obtained with the adhesive which had the least amount of inorganic fillers among the model adhesives with 14.72 wt %.