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Context: Rheumatoid arthritis is a chronic inflammatory disease that causes synovitis. Vitamin D deficiency is common in rheumatoid arthritis. Objective: This systematic review and meta-analysis investigated whether vitamin D supplementation affects the inflammatory and clinical outcomes in patients with rheumatoid arthritis on the basis of randomized clinical trials. Data Sources: A literature search was performed in the Cochrane Central Register of Controlled Trials (CENTRAL), PubMed, MEDLINE, Embase, and Google Scholar for articles published until May 2022. Data Extraction: The studies were selected according to PRISMA guidelines, and the risk of bias was assessed for randomized controlled trials. Data Analysis: A random effects model was used to conduct a meta-analysis, and heterogeneity was assessed using the I2 statistic. Of 464 records, 11 studies were included from 3049 patients. Conclusion: Vitamin D supplementation did not significantly reduce C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), disease activity score in 28 joints (DAS28), or the health assessment questionnaire score; however, the response to supplementation was highly heterogeneous. The pooled analysis showed that vitamin D significantly reduced the pain–visual analogue scale (VAS) weighted mean difference (WMD¼ –1.30, 95% confidence interval [CI] [–2.34, 27], P = .01), DAS28–CRP (WMD = –.58, 95% CI [–.86, –.31], P < .0001), and DAS28–ESR (WMD = –.58, 95% CI [–.86, –.31], P = .0001). Subgroup analysis for vitamin D doses (>100 mg per day versus <100 mg per day) showed that the higher doses had a more significant effect on CRP than the lower doses (P < .05). Conclusions: There was no significant difference between the effect of 2 vitamin D doses on ESR and DAS28. To minimize the high heterogeneity among studies in this meta-analysis, other confounding factors such as baseline vitamin D, age, dietary

Laser weeding may contribute to less dependency on herbicides and soil tillage. Several research and commercial projects are underway to develop robots equipped with lasers to control weeds. Artificial intelligence can be used to locate and identify weed plants, and mirrors can be used to direct a laser beam towards the target to kill it with heat. Unlike chemical and mechanical weed control, laser weeding only exposes a tiny part of the field for treatment. Laser weeding leaves behind only ashes from the burned plants and does not disturb the soil. Therefore, it is an eco-friendly method to control weed seedlings. However, perennial weeds regrow from the belowground parts after the laser destroys the aerial shoots. Depletion of the belowground parts for resources might be possible if the laser continuously kills new shoots, but it may require many laser treatments. We studied how laser could be used to destroy the widespread and aggressive perennial weed Elymus repens after the rhizomes were cut into fragments. Plants were killed with even small dosages of laser energy and stopped regrowing. Generally, the highest efficacy was achieved when the plants from small rhizomes were treated at the 3-leaf stage.

There exists a generalization of the concept named "completely bounded", which we denote "Jordan bounded". Grothendieck's non commutative inequality shows that a bounded bilinear form on a pair of C*-algebras is always Jordan bounded.

Determining the properties of molecules and materials is one of the premier applications of quantum computing. A major question in the field is how to use imperfect near-term quantum computers to solve problems of practical value. Inspired by the recently developed variants of the quantum counterpart of the equation-of-motion (qEOM) approach and the orbital-optimized variational quantum eigensolver (oo-VQE), we present a quantum algorithm (oo-VQE-qEOM) for the calculation of molecular properties by computing expectation values on a quantum computer. We perform noise-free quantum simulations of BeH2 in the series of STO-3G/6-31G/6-31G* basis sets, H4 and H2O in 6-31G using an active space of four electrons and four spatial orbitals (8 qubits) to evaluate excitation energies, electronic absorption, and for twisted H4, circular dichroism spectra. We demonstrate that the proposed algorithm can reproduce the results of conventional classical CASSCF calculations for these molecular systems.

We explore Davidson methods for obtaining excitation energies and other linear response properties within quantum self-consistent linear response (q-sc-LR) theory. Davidson-type methods allow for obtaining only a few selected excitation energies without explicitly constructing the electronic Hessian since they only require the ability to perform Hessian-vector multiplications. We apply the Davidson method to calculate the excitation energies of hydrogen chains (up to H10) and analyze aspects of statistical noise for computing excitation energies on quantum simulators. Additionally, we apply Davidson methods for computing linear response properties such as static polarizabilities for H2, LiH, H2O, OH−, and NH3, and show that unitary coupled cluster outperforms classical projected coupled cluster for molecular systems with strong correlation. Finally, we formulate the Davidson method for damped (complex) linear response, with application to the nitrogen K-edge X-ray absorption of ammonia, and the C6 coefficients of H2, LiH, H2O, OH−, and NH3.

The project began in 2013 with a dual purpose: to promote more apple trees in the Danish landscape and to develop robust apple cultivars for organic growers. We collected 10.000 open-pollinated apple-seeds from 52 robust and tasty old Danish apple cultivars from our National apple gene-bank. Then we invited volunteers to sow the seeds in their private farms/gardens. More than 100 volunteered to the project in 2013. In 2019, we followed up on the trees. Approximately 50 volunteers had succeeded to grow about 2000 apple-seedlings. Since 2019, we are evaluating the robustness of the trees, disease tolerance (Apple scab (Venturia inaequalis), Apple mildew (Podosphaera leuchotricha), Apple canker (Neonectria ditissima) and Elsinoe fruit and leaf spot (Elsinoe piri)) and the quality of the fruits, as soon as the trees are fruiting. In 2020-23 we have selected for further investigations: 74 dessert apples, 17 ornamental apples, 6 cider apples, 1 columnar apple and 1 rootstock. In total 99 interesting new apples. The preliminary results of our screening of robustness and fruit quality are described.

Linear response (LR) theory is a powerful tool in classic quantum chemistry crucial to understanding photo-induced processes in chemistry and biology. However, performing simulations for large systems and in the case of strong electron correlation remains challenging. Quantum computers are poised to facilitate the simulation of such systems, and recently, a quantum linear response formulation (qLR) was introduced. To apply qLR to near-term quantum computers beyond a minimal basis set, we here introduce a resource-efficient qLR theory using a truncated active-space version of the multi-configurational self-consistent field LR ansatz. Therein, we investigate eight different near-term qLR formalisms that utilize novel operator transformations that allow the qLR equations to be performed on near-term hardware. Simulating excited state potential energy curves and absorption spectra for various test cases, we identify two promising candidates dubbed ``proj LRSD'' and ``all-proj LRSD''.

We formulate and implement the Variational Quantum Eigensolver Self Consistent Field (VQE-SCF) algorithm in combination with polarizable embedding (PE), thereby extending PE to the regime of quantum computing. We test the resulting algorithm, PE-VQE-SCF, on quantum simulators and demonstrate that the computational stress on the quantum device is only slightly increased in terms of gate counts compared to regular VQE-SCF. On the other hand, no increase in shot noise was observed. We illustrate how PE-VQE-SCF may lead to the modeling of real chemical systems using a simulation of the reaction barrier of the Diels-Alder reaction between furan and ethene as an example.

Tectonic plate motions are a prime constraint on lithosphere dynamics and on the torques acting upon plates. Researchers typically test hypotheses on the controlling torques via forward computer models, which allow accepting or rejecting hypotheses on the basis of the fit of model–output plate velocities to kinematic reconstructions. Such models typically require a significant amount of input information (e.g., tectonic boundaries, structure of the lithosphere, lateral variations of rheology, among others) to appropriately model the tectonic system, and obtain sufficiently–realistic realizations of plate motions. Alternatively, the inverse problem approach takes the difference between the plate torque–balance at two distinct moments in time. This results in an equation in which (a) torques that have not varied through time are canceled out and (b) torques that instead have varied through time are linked to the resulting plate–motion change through a term that accounts for the plate shape and the rheology of the underlying asthenosphere. This approach sacrifices the capability to describe the different individual forces/torques acting upon a plate. Instead, it focuses on determining torque temporal variations, which significantly reduces the amount of input knowledge required. In this technical note we introduce MYRIAM, an open–source software that implements such an inverse approach. MYRIAM takes plate–motion temporal changes, and outputs an estimate of the torque variation required upon a plate to generate the input kinematic change. MYRIAM is released as an open–source repository hosted at GitHub, complete with source code and executable files for Windows and Unix–based operating systems.

Docent, fil. dr. Inga Hedberg (Fig. 1) died in Uppsala on the 13th of January 2024, at the age of 96 years. Together with her husband, Olov Hedberg, she has been a central and tireless figure in a range of important international projects on African botany, probably with the Flora of Ethiopia and Eritrea (1980-2009) as the most remarkable.

Finetuning is a useful method for adapting Transformer-based text encoders to new tasks but can be computationally expensive for structured prediction tasks that require tuning at the token level. Furthermore, finetuning is inherently inefficient in updating all base model parameters, which prevents parameter sharing across tasks. To address these issues, we propose a method for efficient task adaptation of frozen Transformer encoders based on the local contribution of their intermediate layers to token representations. Our adapter uses a novel attention mechanism to aggregate intermediate layers and tailor the resulting representations to a target task. Experiments on several structured prediction tasks demonstrate that our method outperforms previous approaches, retaining over 99% of the finetuning performance at a fraction of the training cost. Our proposed method offers an efficient solution for adapting frozen Transformer encoders to new tasks, improving performance and enabling parameter sharing across different tasks.

The world needs equitable and democratic dialogue. As a global society, we face numerous so-called “wicked problems” related to the unsustainable use of the Earth’s resources. The notion of wicked problems, developed by Horst Rittel and Melvin Webber in 1973, describes problems that are ill-defined and rely on value judgments for resolution – and are never truly solved. Today, such problems include climate disruption, the biodiversity crisis, and most recently, the COVID-19 pandemic. The process of tackling these problems is exacerbated by the widespread atmosphere of science scepticism and denialism along with delay tactics and misinformation. From a science communication perspective, the situation can seem overwhelming. Often, it is difficult to see how constructive space can be created for the discussions that are necessary to address the challenges we face.In this paper, I will consider the role science centres, science and technology museums, natural history museums, and other public science communication institutions can play in creating inclusive spaces to address these challenges. As I discuss in the paper, science museums have the resources, the expertise, and the social presence to counteract mis- and disinformation and to engage a diversity of stakeholders in co-creating responses to the problems we face.

BACKGROUND: Multiple and simultaneous attacks by pathogens and insect pests frequently occur in nature. Plants respond to biotic stresses by activating distinct defense mechanisms, but little is known about how plants cope with multiple stresses. The focus of this study was the combined interaction of fungal infection caused by Leptosphaeria maculans (synonym Plenodomus lingam) and arthropod infestation by the diamondback moth (Plutella xylostella) in oilseed rape (Brassica napus). We hypothesized that infection by the fungal pathogen L. maculans could alter oilseed rape palatability to P. xylostella-chewing caterpillars. Feeding preference tests were complemented with analyses of defense gene transcription, and levels of glucosinolates (GLSs) and volatile organic compounds (VOCs) in L. maculans-inoculated and non-inoculated (control) leaves to determine possible causes of larval choice. RESULTS: Caterpillars preferred true leaves to cotyledons, hence true leaves were used for further experiments. True leaves inoculated with L. maculans were more palatable to caterpillars over control leaves during the early stage of infection at 3 days post inoculation (dpi), but this preference disappeared in the later stages of infection at 7 dpi. In parallel, genes involved in the salicylic acid and ethylene pathways were up-regulated in L. maculans-inoculated leaves at 3 and 7 dpi; L. maculans increased the level of total aliphatic GLSs, specifically glucobrassicanapin, and decreased the level of glucoiberin at 3 dpi and altered the content of specific VOCs. A group of 55 VOCs with the highest variability between treatments was identified. CONCLUSION: We suggest that the P. xylostella preference for L. maculans-inoculated leaves in the early stage of disease development could be caused by the underlying mechanisms leading to changes in metabolic composition. Further research should pinpoint the compounds responsible for driving larval preference and evaluate whether the be

Pomelo fruit is naturally rich in health-promoting components. However, few studies have quantified phytic acid (PA), which is both an antioxidant compound and an antinutrient that limits mineral bioavailability. In this study, we analyzed the temporospatial changes in fruit PA, total phenolic, total flavonoid, estimated mineral bioavailabilities, and their response to fertilization strategies. Compared to pulp, pomelo peel contained higher PA, total phenolic, total flavonoid and most minerals concentrations (except for P) but lower estimated mineral bioavailabilities (Mg, Zn and Fe). The concentrations of PA, total flavonoid, and minerals (P, Ca, Mg, Zn) and Fe estimated bioavailability in pulp gradually decreased with ripening. Total phenolic concentrations and the estimated bioavailabilities of Ca, Mg and Zn in pulp decreased in the early fruit expansion stage but subsequently increased markedly until maturity. Reduced chemical fertilization while supplementing Mg simultaneously increased estimated mineral bioavailabilities in pulp through reduced PA as an antinutrient, and increased bioactives concentrations in peel through increased PA as an antioxidant together with total phenolic and total flavonoid. Overall, our results indicate that reducing NPK while supplementing Mg fertilization in pomelo orchards with acidic and Mg-deficient soil is the most beneficial approach for achieving biofortification of the edible pulp parts and integrated fruit quality enhancement.

Walking-based locomotion techniques in virtual reality (VR) can use redirection to enable walking in a virtual environment larger than the physical one. This results in a mismatch between the perceived virtual and physical movement, which is known to cause VR sickness. However, it is unclear if different types of walking techniques (e.g., resetting, reorientation, or self-overlapping spaces) affect VR sickness differently. To address this, we conducted a systematic review and meta-analysis of 96 papers published in 2016–2022 that measure VR sickness in walking-based locomotion. We find different VR sickness effects between types of redirection and between normal walking and redirection. However, we also identified several problems with the use and reporting of VR sickness measures. We discuss the challenges in understanding VR sickness differences between walking techniques and present guidelines for measuring VR sickness in locomotion studies.

The “doorway effect” predicts that crossing an environmental boundary affects memory negatively. In virtual reality (VR), we can design the crossing and the appearance of such boundaries in non-realistic ways. However, it is unclear whether locomotion techniques like teleportation, which avoid crossing the boundary altogether, still induce the effect. Furthermore, it is unclear how different appearances of a doorway act as a boundary and thus induce the effect. To address these questions, we conducted two lab studies. First, we conceptually replicated prior doorway effect studies in VR using natural walking and teleportation. Second, we investigated the effect of five doorway visualizations, ranging from doors to portals. The results show no difference in object recognition performance due to the presence of a doorway, locomotion technique, or doorway visualization. We discuss the implications of these findings on the role of boundaries in event-based memory and the design of boundary interactions in VR.

In this study, the performance of the doubles-corrected higher random-phase approximation (HRPA(D)) has been investigated in calculations of NMR spin-spin coupling constants (SSCCs) for 58 molecules with the experimental values used as the reference values. HRPA(D) is an approximation to the second-order polarization propagator approximation (SOPPA), and is therefore computationally less expensive than SOPPA. HRPA(D) performs comparable and sometimes even better than SOPPA, and therefore when calculating SSCCs it should be considered as an alternative to SOPPA. Furthermore, it was investigated whether a CCSD(T) or MP2 geometry optimization was optimal for a SOPPA and a HRPA(D) SSCCs calculation for 8 smaller molecules. CCSD(T) is the optimal geometry optimization for the SOPPA calculation, and MP2 was optimal for the HRPA(D) SSCC calculations.

The Anthropocene signifies the start of a no-analogue trajectory of the Earth system that is fundamentally different from the Holocene. This new trajectory is characterized by rising risks of triggering irreversible and unmanageable shifts in Earth system functioning. We urgently need a new global approach to safeguard critical Earth system regulating functions more effectively and comprehensively. The global commons framework is the closest example of an existing approach with the aim of governing biophysical systems on Earth upon which the world collectively depends. Derived during stable Holocene conditions, the global commons framework must now evolve in the light of new Anthropocene dynamics. This requires a fundamental shift from a focus only on governing shared resources beyond national jurisdiction, to one that secures critical functions of the Earth system irrespective of national boundaries. We propose a new framework—the planetary commons—which differs from the global commons framework by including not only globally shared geographic regions but also critical biophysical systems that regulate the resilience and state, and therefore livability, on Earth. The new planetary commons should articulate and create comprehensive stewardship obligations through Earth system governance aimed at restoring and strengthening planetary resilience and justice.

In recent years, large-scale tree mortality events linked to global change have occurred around the world. Current forest monitoring methods are crucial for identifying mortality hotspots, but systematic assessments of isolated or scattered dead trees over large areas are needed to reduce uncertainty on the actual extent of tree mortality. Here, we mapped individual dead trees in California using sub-meter resolution aerial photographs from 2020 and deep learning-based dead tree detection. We identified 91.4 million dead trees over 27.8 million hectares of vegetated areas (16.7-24.7% underestimation bias when compared to field data). Among these, a total of 19.5 million dead trees appeared isolated, and 60% of all dead trees occurred in small groups ( ≤ 3 dead trees within a 30 × 30 m grid), which is largely undetected by other state-level monitoring methods. The widespread mortality of individual trees impacts the carbon budget and sequestration capacity of California forests and can be considered a threat to forest health and a fuel source for future wildfires.

There is a longstanding assumption that if people perceive a risk as high, they will act to reduce it. In fact, research has shown a lack of consistently strong causal relations between risk perception (RP) and mitigative behavior—the so-called “risk perception paradox.” Despite a recent increase in research on RP, individuals’ risk tolerance (RT; or demand for risk reduction) only rarely appears as a consideration for explaining behavioral response to natural hazards. To address this research gap, we first systematically review relevant literature and find that RT has been directly assessed or operationalized using perceived thresholds related to costs and benefits of risk reduction measures, risk consequences, hazard characteristics, behavioral responses, or affective reactions. It is either considered a component or a result of RP. We then use survey data of individuals’ RP, RT, and behavioral intention to assess relations among these variables. Comparing across three European study sites, “behavioral intention” is assessed as the public’s willingness to actively support the implementation of nature- based solutions to reduce disaster risk. A series of tests using regression models shows RT significantly explains variance in behavioral intention and significantly contributes additional explanatory power beyond RP in all three sites. In two sites, RT is also a significant partial mediator of the relation between RP and behavior. Taken together, our findings demand further conceptual and empirical research on individuals’ RT and its systematic consideration as a determinant for (in)action in response to natural hazards.

Introduction: Male elite cyclists (average VO2-max: 71 ml/min/kg, n=18) completed seven weeks of high-intensity interval training (HIT) (3x/week; 4-min and 30-s intervals) during the competitive part of the season. The influence of a maintained or lowered total training volume combined with HIT was evaluated in a two-group design. Weekly moderate-intensity training was lowered by ~33% (~5 hours) (LOW, n=8) or maintained at normal volume (NOR, n=10). Endurance performance and fatigue resistance was evaluated via 400 kcal time-trials (~20 min) commenced either with or without prior completion of a 120-min preload (including repeated 20-s sprints to simulate physiologic demands during road races). Results: Time-trial performance without preload was improved after the intervention (p=0.006) with a 3% increase in LOW (p=0.04) and a 2% increase in NOR (p=0.07). Preloaded time-trial was not significantly improved (p=0.19). In the preload, average power during repeated sprinting increased by 6% in LOW (p<0.01) and fatigue resistance in sprinting (start vs end of preload) was improved (p<0.05) in both groups. Blood lactate during the preload was lowered (p<0.001) solely in NOR. Measures of oxidative enzyme activity remained unchanged, whereas the glycolytic enzyme PFK increased by 22% for LOW (p=0.02).Conclusion: The present study demonstrates that elite cyclists can benefit from intensified training during the competitive season both with maintained and lowered training volume at moderate intensity. In addition to benchmarking effects of such training in ecological elite settings, the results also indicate how some performance and physiological parameters may interact with training volume.

Adaptation to heat stress and hypoxia are relevant for athletes participating in Tour de France or similar cycling races taking place during the summertime in landscapes with varying altitude. Both to minimize detrimental performance effects associated with arterial desaturation occurring at moderate altitudes in elite athletes, respectively reduce the risk of hyperthermia on hot days, but also as a pre-competition acclimatization strategy to boost blood volume in already highly adapted athletes. The hematological adaptations require weeks of exposure to manifest, but are attractive as an augmented hemoglobin mass may improve arterial oxygen delivery and hence benefit prolonged performances. Altitude training camps have in this context a long history in exercise physiology and are still common practice in elite cycling. However, heat acclimation training provides an attractive alternative for some athletes either as a stand-alone approach or in combination with altitude. The present paper provides an update and practical perspectives on the potential to utilize hypoxia and heat exposure to optimize hematological adaptations. Furthermore, we will consider temporal aspects both in terms of onset and decay of the adaptations relevant for improved thermoregulatory capacity and respiratory adaptations to abate arterial desaturation during altitude exposure. From focus on involved physiological mechanisms, time-course and responsiveness in elite athletes, we will provide guidance based on our experience from practical implementation in cyclists preparing for prolonged stage races such as the Tour de France.

Blood doping is prohibited for athletes but has been a well-described practice within endurance sports throughout the years. With improved direct and indirect detection methods, the practice has allegedly moved towards micro-dosing, i.e., reducing the blood doping regime amplitude. This narrative review evaluates whether blood doping, specifically recombinant human erythropoietin (rhEpo) treatment and blood transfusions are performance-enhancing, the responsible mechanism as well as detection possibilities with a special emphasis on micro-dosing. In general, studies evaluating micro-doses of blood doping are limited. However, in randomized, double-blinded, placebo-controlled trials, three studies find that infusing as little as 130 ml red blood cells or injecting 9 IU × kg bw-1 rhEpo three times per week for four weeks improve endurance performance ~4-6 %. The responsible mechanism for a performance-enhancing effect following rhEpo or blood transfusions appear to be increased O2 -carrying capacity, which is accompanied by an increased muscular oxygen extraction and likely increased blood flow to the working muscles, enabling the ability to sustain a higher exercise intensity for a given period. Blood doping in micro-doses challenges indirect detection by the Athlete Biological Passport, albeit it can identify ~20-60% of the individuals depending on the sample timing. However, novel biomarkers are emerging, and some may provide additive value for detection of micro blood doping such as the immature reticulocytes or the iron regulatory hormones hepcidin and erythroferrone. Future studies should attempt to validate these biomarkers for implementation in real-world anti-doping efforts and continue the biomarker discovery.

Purpose: There is an increasing interest in the use of non-nutritive sweeteners to replace added sugar in food and beverage products for reasons of improving consumer health. Much work has been done to understand safety of sweeteners, but very little on sustainability. To address that gap, this study presents the results of a life cycle assessment (LCA) of production of rebaudioside A 60%, 95% pure (RA60) steviol glycoside mix from Stevia rebaudiana leaf grown in Europe.Methods: An attributional cradle-to-factory-gate life cycle assessment was conducted on growing of stevia leaves and extraction of steviol glycosides in Europe. Primary data were used from a case study supply chain. Results are reported in impact categories from the ReCiPe 2016 (H) method, with focus given to global warming potential, freshwater eutrophication, water consumption, and land use. Impacts are expressed both in terms of production mass and sweetness equivalence, a common metric for understanding high intensity sweetener potency. Sweetness equivalence of RA60 is typically 200 to 300 times that of sugar. Comparison of environmental impact is made to sugar (sucrose) produced from both cane and beets. The research is part of the EU project SWEET (sweeteners and sweetness enhancers: impact on health, obesity, safety, and sustainability).Results and discussion: Global warming potential for production of RA60 was found to be 20.25 kgCO2-eq/kgRA60 on a mass basis and 0.081 kgCO2-eq/kgSE on a sweetness equivalence basis. Field production of stevia leaves was found to be the main source of impact for most impact categories, and for all four focus categories. Extraction of the RA60 was the main source of impact for the others. Leaf processing and seedling propagation were minor contributors to life cycle impact. Removal of international transport from the supply chain reduced global warming potential by 18.8%. C

Palynology is widely used in both academic and industrial research for correlation and interpretation of subsurface geology on both local and regional scales. While most data gathering tools for the subsurface have undergone major technological developments during the last decades, palynological research has, apart from the use of more advanced microscopes, remained virtually unchanged and can be quite time consuming when large data sets are required. With increasing demand for faster, more high resolution and more detailed palynological analyses from the continuously developing technological industry as well as the academic science community, palynology is at risk of being left behind. The answer could lie in adopting strategies of digitalisation and Artificial Intelligence (AI) originally developed for medical research. The technology of scanning microscope slides into a digital high-resolution image has already been developed, and AI software specifically developed for palynology can be utilised to examine the digital images and detect, identify and quantify the fossil content. In this project we have designed and developed an AI software for clustering and classification of microfossils based on deep-learning based algorithms for detection of palynomorphs and algorithms based on autoencoders for extracting features predictive of different fossil types. The AI is trained to recognize and identify fossils from different angles, preservation levels and fragmentation stages, as well as partially obscured or folded specimens. The AI can then analyse specimens for morphological parameters such as texture, shape and/or RGB/HSV values and use these parameters to categorize the specimen into clusters. The clustering has many applications, e.g., identifying morphological variations within taxa and recognizing variations in colour and preservation related to reworking or caving during the drilling process. The project also explores the advantages and disa

Integrating research and teaching in a meaningful manner is a challenge. With the growing number of students in universities and the rapid advances and innovations across many fields and technologies, the one-on-one mentor relationship seems utopia. However, increasing demands for inquiry-competent problem-solvers and the expanding integrative nature of science require a rethinking of teaching styles. Using the intrinsically disordered proteins (IDPs) as an instrument for research-integrating teaching, we have developed a teaching platform, which provides research opportunities for both students and researchers. The unpredictable and dynamic, but technically manageable character of IDPs offers an opportunity for open- ended processes of inquiry that are key to both learning and research. Organizing a course around a dynamic scientific field allowed the students to take active part in exploring and developing knowledge about scientific problems of interest to academia and industries. These experiences of exploring IDPs offer concrete ideas on how to organize courses in ways that integrate research and teaching.