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This study addresses the challenges inherent in the maintenance and inspection of wind turbines through the application of deep learning methodologies for fault detection on Wind Turbine Blades (WTBs). Specifically, this research focuses on defect detection on the blades of small-scale WTBs due to the unavailability of commercial wind turbines. This research compared popular object localization architectures, YOLO and Mask R-CNN, to identify the most effective model to detect common WTB defects, including cracks, holes, and erosion. YOLOv9 C emerged as the most effective model, with the highest scores of mAP50 and mAP50-95 of 0.849 and 0.539, respectively. Modifications to Mask R-CNN, specifically integrating a ResNet18-FPN network, reduced computational complexity by 32 layers and achieved a mAP50 of 0.8415. The findings highlight the potential of deep learning and computer vision in improving WTB fault analysis and inspection.

This paper introduces a drone-based surrogate project aimed at serving as a preliminary educational platform for undergraduate students in the Electrical and Computer Engineering (ECE) fields. Utilizing small Unmanned Aerial Vehicles (sUAVs), this project serves as a surrogate for the inspection of wind turbines using scaled-down pedestal fans to replace actual turbines. This approach significantly reduces the costs, risks, and logistical complexities, enabling feasible and safe on-campus experiments. Through this project, students engage in hands-on applications of Python programming, computer vision, and machine learning algorithms to detect and classify simulated defects in pedestal fan blade (PFB) images. The primary educational objectives are to equip students with foundational skills in autonomous systems and data analysis, critical for their progression to larger scale projects involving professional drones and actual wind turbines in wind farm settings. This surrogate setup not only provides practical experience in a controlled learning environment, but also prepares students for real-world challenges in renewable energy technologies, emphasizing the transition from theoretical knowledge to practical skills.

The implementation of cover crops in crop rotation is a suggested soil health practice. As cover crops are not harvested and sold, they do not directly provide monetary gain to producers. Therefore, it is imperative that planting cover crops does not negatively affect the subsequent cash crop. However, there is no overall consensus in the literature regarding the effects of cover crops on cash crop yield. To better understand the effects of cover crops on soybean growth and yield in Oklahoma soybean systems, trials were conducted in Bixby, OK, in 2019 and Perkins, OK, in 2019, 2020, and 2021. The objectives of these trials were to (1) determine how different cover crop mixes affect soybean growth parameters and (2) determine if cover crops significantly influence soybean seed yield. Treatments within the trials included six cover crops and a fallow treatment. Soybeans were planted after the termination of the cover crops. Yield and growth parameter data were collected after harvest. No significant differences or consistent trends were detected in the yield among treatments. While cover crops had a significant impact on the number of three- and four-bean pods, no other differences in the growth parameters existed, and they never translated into significant yield differences. Based on our data, cover crops would not benefit the overall cash crop production in the continuous cover crop soybean system in Oklahoma. However, the fact that cover crops did not consistently or significantly reduce soybean yield allows growers to explore other benefits, such as weed management or soil health improvement.

Fractal evolution is apparently effective in selectively preserving environmentally resilient traits for more than 80 million years in Streptotrichaceae (Bryophyta). An analysis simulated maximum destruction of ancestral traits in that large lineage. The constraints enforced were the preservation of newest ancestral traits, and all immediate descendant species obtained different new traits. Maximum character state changes in ancestral traits were 16 percent of all possible traits in any one sub-lineage, or 73 percent total of the entire lineage. Results showed, however, that only four ancestral traits were permanently eliminated in any one lineage or sub-lineage. A lineage maintains maximum biodiversity of temporally and regionally survival-effective traits at minimum expense to resilience across a geologic time of 88 million years for the group studied. Similar processes generating an extant punctuated equilibrium as bursts of about four descendants per genus and one genus per 1–2 epochs are possible in other living groups given similar emergent processes. The mechanism is considered complexity-related, the lineage being a self-organized emergent phenomenon strongly maintained in the ecosphere by natural selection on fractal genera.

Recent advances in deep sequencing technologies have revealed that, while less than 2% of the human genome is transcribed into mRNA for protein synthesis, over 80% of the genome is transcribed, leading to the production of large amounts of noncoding RNAs (ncRNAs). It has been shown that ncRNAs, especially long non-coding RNAs (lncRNAs), may play crucial regulatory roles in gene expression. As one of the first isolated and reported lncRNAs, H19 has gained much attention due to its essential roles in regulating many physiological and/or pathological processes including embryogenesis, development, tumorigenesis, osteogenesis, and metabolism. Mechanistically, H19 mediates diverse regulatory functions by serving as competing endogenous RNAs (CeRNAs), Igf2/H19 imprinted tandem gene, modular scaffold, cooperating with H19 antisense, and acting directly with other mRNAs or lncRNAs. Here, we summarized the current understanding of H19 in embryogenesis and development, cancer development and progression, mesenchymal stem cell lineage-specific differentiation, and metabolic diseases. We discussed the potential regulatory mechanisms underlying H19's functions in those processes although more in-depth studies are warranted to delineate the exact molecular, cellular, epigenetic, and genomic regulatory mechanisms underlying the physiological and pathological roles of H19. Ultimately, these lines of investigation may lead to the development of novel therapeutics for human diseases by exploiting H19 functions.

Pigments produced by anoxygenic phototrophic bacteria are valuable proxies of past anoxia in lacustrine and marine environments. Pigment measurement typically requires time-consuming and costly chemical extractions and chromatographic analyses, which limits the temporal resolution of paleoenvironmental reconstructions based on sedimentary pigments. Here, we evaluate the potential of in situ hyperspectral imaging (HSI) core scanning as a rapid, non-destructive method to document high-resolution changes in oxygenic and anoxygenic phototrophic communities at meromictic Lake Cadagno, Switzerland. Three distinct groups of pigments can be detected with the HSI method in the sediments of Lake Cadagno; each pigment group represents a different phototrophic community. Oxygenic phototrophs are indicated by total chloropigments (TChl; chlorophyll a, b, and derivatives). Two types of anoxygenic phototrophs were distinguished – purple sulfur bacteria (PSB), represented by bacteriochlorophyll a, and green sulfur bacteria (GSB), represented by bacteriochlorophyll c, d, and e. HSI pigment indices were validated by pigment measurements performed on extracted samples using spectrophotometer and high-performance liquid chromatography (HPLC). Bacteriochlorophylls were present throughout the past 10 kyr, confirming geochemical evidence of nearly continuous stratification and sulfidic conditions at Lake Cadagno. Major shifts in the anoxygenic phototropic communities are recorded at decadal to millennial scales. GSB and PSB communities coexisted from 10.2–8.8 kyr BP. Dominance of PSB over GSB from 8.8–3.4 kyr BP indicates strongly stratified conditions in the lake and strong light radiation at the chemocline. From 3.4–1.3 kyr BP, PSB were mostly absent, and GSB became dominant, implying lower light intensity at the chemocline due to a combination of factors including deforestation in the lake surroundings, increased flood frequency, cooler climatic conditions, and changes in groundwater solute concentrations. The high-resolution HSI data show that frequent flood events and mass movements disturbed the chemocline and the anoxygenic bacterial communities and that the PSB were particularly sensitive and slow to recover following these disturbance events. This study demonstrates for the first time that HSI can detect GSB-related pigments, making the method uniquely valuable as a rapid tool to study samples containing pigments of both oxygenic and anoxygenic phototrophs.

Frost damage is one of the major concerns for crop growers as it can impact the growth of the plants and hence, yields. Early detection of frost can help farmers mitigating its impact. In the past, frost detection was a manual or visual process. Image-based techniques are increasingly being used to understand frost development in plants and automatic assessment of damage resulting from frost. This research presents a comprehensive survey of the state-of the-art methods applied to detect and analyse frost stress in plants. We identify three broad computational learning approaches i.e., statistical, traditional machine learning and deep learning, applied to images to detect and analyse frost in plants. We propose a novel taxonomy to classify the existing studies based on several attributes. This taxonomy has been developed to classify the major characteristics of a significant body of published research. In this survey, we profile 80 relevant papers based on the proposed taxonomy. We thoroughly analyse and discuss the techniques used in the various approaches, i.e., data acquisition, data preparation, feature extraction, computational learning, and evaluation. We summarise the current challenges and discuss the opportunities for future research and development in this area including in-field advanced artificial intelligence systems for real-time frost monitoring.

Background Domiciliary spirometry (DS) is a novel tool that is widely employed in the assessment of respiratory disease. We assessed real-world feasibility, effectiveness and value of a physiologist-led home spirometry programme in patients with treatment-refractory severe asthma. Methods Patients were referred and provided with a hand-held DS device. Patients completed baseline measurements in a physiologist-led virtual clinic and were instructed to provide further values during any periods of respiratory symptoms. Outcome measures included prevalence of new obstructed events, DS adherence and uptake of this approach. Results 112 patients were enrolled from November 2020 to January 2023. 102 individuals, mean±sd age 44±13 years (86% female) with median (IQR) forced expiratory volume in 1 s % predicted 88% (77–97%), successfully recorded baseline spirometry values. During follow-up (24 months), 11 (11%) were identified with new obstructive spirometry and were subsequently able to be commenced on biologic therapy. Patient engagement was poor with median (IQR) of 4 (2–6) attempts of contact made before baseline values were recorded, and 2 (1–3) attempts required to record technically acceptable values. Continued DS use was suboptimal; 34% failed to use their device after baseline and only 10% continued at the end of the study period. The cost of DS measurements was greater than a single hospital-based visit but enables multiple event capture. Conclusion Overall, DS measurement uptake was poor, with a minority of patients continuing to use the device at the end of the study period. However, for those that engage, DS provides an alternative approach to traditional hospital-based spirometry measurements that can alter clinical management.

ABSTRACTFrancisella tularensis is one of the several biothreat agents for which a licensed vaccine is needed. To ensure vaccine protection is achieved across a range of virulent F. tularensis strains, we assembled and characterized a panel of F. tularensis isolates to be utilized as challenge strains. A promising tularemia vaccine candidate is rLVS ΔcapB/iglABC (rLVS), in which the vector is the LVS strain with a deletion in the capB gene and which additionally expresses a fusion protein comprising immunodominant epitopes of proteins IglA, IglB, and IglC. Fischer rats were immunized subcutaneously 1–3 times at 3-week intervals with rLVS at various doses. The rats were exposed to a high dose of aerosolized Type A strain Schu S4 (FRAN244), a Type B strain (FRAN255), or a tick derived Type A strain (FRAN254) and monitored for survival. All rLVS vaccination regimens including a single dose of 107 CFU rLVS provided 100% protection against both Type A strains. Against the Type B strain, two doses of 107 CFU rLVS provided 100% protection, and a single dose of 107 CFU provided 87.5% protection. In contrast, all unvaccinated rats succumbed to aerosol challenge with all of the F. tularensis strains. A robust Th1-biased antibody response was induced in all vaccinated rats against all F. tularensis strains. These results demonstrate that rLVS ΔcapB/iglABC provides potent protection against inhalational challenge with either Type A or Type B F. tularensis strains and should be considered for further analysis as a future tularemia vaccine.

Background and aim: Herbarium specimens were reviewed as part of broader project that deals with the diversity of bryophytes from the Chaco province (Argentina). One of the samples matched the description of Timmiella acaulon, a species poorly known. The aim of this work is to record T. acaulon as new to Chaco Province and to describe morphologically and illustrate in detail this remarkable species. M&M: Herbarium samples were analyzed with standard techniques for bryophytes. Examination with scanning electron microscope was made using samples mounted directly on double-sided tape and coated in gold-palladium. Results: Timmiella acaulon is newly registered for Chaco province. A complete and detailed morphological description, and illustrations are here presented. Conclusions: Due to the rediscovery of the species more than 100 years after its original description, the distribution range of T. acaulon is extended to northeastern Argentina, and details of morphological characters of systematic value are provided.

Brain-computer interfaces (BCI) can provide real-time and continuous assessments of mental workload in different scenarios, which can subsequently be used to optimize human-computer interaction. However, assessment of mental workload is complicated by the task-dependent nature of the underlying neural signals. Thus, classifiers trained on data from one task do not generalize well to other tasks. Previous attempts at classifying mental workload across different cognitive tasks have therefore only been partially successful. Here we introduce a novel algorithm to extract frontal theta oscillations from electroencephalographic (EEG) recordings of brain activity and show that it can be used to detect mental workload across different cognitive tasks. We use a published data set that investigated subject dependent task transfer, based on Filter Bank Common Spatial Patterns. After testing, our approach enables a binary classification of mental workload with performances of 92.00 and 92.35%, respectively for either low or high workload vs. an initial no workload condition, with significantly better results than those of the previous approach. It, nevertheless, does not perform beyond chance level when comparing high vs. low workload conditions. Also, when an independent component analysis was done first with the data (and before any additional preprocessing procedure), even though we achieved more stable classification results above chance level across all tasks, it did not perform better than the previous approach. These mixed results illustrate that while the proposed algorithm cannot replace previous general-purpose classification methods, it may outperform state-of-the-art algorithms in specific (workload) comparisons.

BackgroundStaging, especially clinical lymph node staging in esophageal adenocarcinoma has only moderate sensitivity and specificity. Therefore, we evaluated combined molecular markers to predict prognosis.Patients and methods890 tumor tissue samples were obtained from patients who underwent surgery for esophageal adenocarcinoma with curative intent. These were stained by tissue micro array for 48 markers which are associated with tumorigenesis and correlated with clinical data (TNM-staging, overall survival) by multivariate Cox regression.ResultsTwo markers (preserved Y chromosome and high grade of (CD3+) T-cell infiltration) were found to be significantly and independently associated with better overall survival. We formed a score (called CY score) from the two markers. The more markers are positive and thus the higher the score (ranging from 0 to 2), the better the overall survival, independently of UICC. Moreover, we developed a combination score of the UICC and CY score based on cluster analysis. Patients with a UICC stage of III with the presence of both traits (CY=2) can be assigned to a better prognosis group (group II), whereas patients with a UICC stage of I without both traits (CY=0) must be assigned to a worse prognosis group (group II). Therefore, patients in stage I with adverse molecular signature might benefit of multimodal therapy.ConclusionIn summary, the CY score adds prognostic information to the UICC stage based on tumor biology in esophageal adenocarcinoma and warrants further evaluations in independent clinical cohorts.

First Nations people in remote Australia hold important historical and local knowledge on how to respond effectively to environmental changes and extreme environmental conditions. However, there has been comparatively little attention paid to the use of First Nations people's environmental knowledge to devise environmental health responses or the effects of various environmental factors on remote residents’ health and well-being. The report explores environmental health injustice among First Nations people living in remote Australia caused by inadequate engagement of remote community members and remote health professionals in environmental health decision-making, a lack of continuous environmental monitoring in remote locations and reliance on health outcome data sets that do not reflect the actual environmental health effects on remote residents. Such environmental health injustice affects people's right to have information on the constituents of the environment they interact with daily and contributes to the lost opportunity to capitalize on local cultural knowledge to create successful environmental health responses for remote residents of Australia.

Objective: This study aims to investigate the impact of slow embryo development on the subsequent live birth rate and birthweight outcomes following a fresh day 5 transfer. Study design: This retrospective multicenter cohort study included 1,213 consecutive patients undergoing autologous oocyte in vitro fertilization (IVF) treatment at four associated private clinics during 2016–2019. Only fresh single day 5 transfers were included for analysis. Results: No implantation was achieved by embryos that failed to reach the early blastocyst stage on day 5 ([Formula: see text]). After adjusting for potential confounding factors, multivariate logistic regression (expressed as adjusted odds ratio or aOR and [Formula: see text] confidence interval) showed a significantly reduced live birth rate in early blastocysts ([Formula: see text]) in reference to those at the expanding (aOR = 0.584, [Formula: see text], [Formula: see text], [Formula: see text]), expanded (aOR = 0.322, [Formula: see text], [Formula: see text], [Formula: see text]), or hatching/hatched stages (aOR = 0.255, [Formula: see text], [Formula: see text], [Formula: see text]). However, early blastocysts led to similar birthweights ([Formula: see text], [Formula: see text]) in comparison to those at the expanding ([Formula: see text], [Formula: see text], [Formula: see text]), expanded ([Formula: see text], [Formula: see text], [Formula: see text]), or hatching/hatched stages ([Formula: see text], [Formula: see text], [Formula: see text]). This was further confirmed by linear regression analysis using either birthweight or [Formula: see text] score (gestation-adjusted birthweight). Conclusion: Slow day 5 development is associated with reduced live birth rate when transferred fresh, however, subsequent birthweight is not impacted once pregnancy is initiated.

Abstract In this paper, we investigate the impact of coronary artery dynamics on the wall shear stress (WSS) vector field topology by comparing fluid–structure interaction (FSI) and computational fluid dynamics (CFD) techniques. As one of the most common causes of death globally, coronary artery disease (CAD) is a significant economic burden; however, novel approaches are still needed to improve our ability to predict its progression. FSI can include the unique dynamical factors present in the coronary vasculature. To investigate the impact of these dynamical factors, we study an idealized artery model with sequential stenosis. The transient simulations made use of the hyperelastic artery and lipid constitutive equations, non‐Newtonian blood viscosity, and the characteristic out‐of‐phase pressure and velocity distribution of the left anterior descending coronary artery. We compare changes to established metrics of time‐averaged WSS (TAWSS) and the oscillatory shear index (OSI) to changes in the emerging WSS divergence, calculated here in a modified version to handle the deforming mesh of FSI simulations. Results suggest that the motion of the artery can impact downstream patterns in both divergence and OSI. WSS magnitude is also decreased by up to 57% due to motion in some regions. WSS divergence patterns varied most significantly between simulations over the systolic period, the time of the largest displacements. This investigation highlights that coronary dynamics could impact markers of potential CAD progression and warrants further detailed investigations in more diverse geometries and patient cases.

In this work, authors provide a proof-of-concept study showing that deubiquitinating enzyme inactivation in MERS-CoV leads to attenuation in mice, and protection against a lethal challenge.

The Association of Pathology Chairs, an organization of American and Canadian academic pathology departments, has a record percent of women department chairs in its ranks (31%), although still not representative of the percent of women pathology faculty (43%). These women chairs were surveyed to determine what had impeded and what had facilitated their academic advancement before becoming chairs. The 2 most frequently identified impediments to their career advancement were heavy clinical loads and the lack of time, training, and/or funding to pursue research. Related to the second impediment, only one respondent became chair of a department which was in a top 25 National Institutes of Health-sponsored research medical school. Eighty-nine percent of respondents said that they had experienced gender bias during their careers in pathology, and 31% identified gender bias as an important impediment to advancement. The top facilitator of career advancement before becoming chairs was a supportive family. Strikingly, 98% of respondents have a spouse or partner, 75% have children, and 38% had children younger than 18 when becoming chairs. Additional top facilitators were opportunities to attend national meetings and opportunities to participate in leadership. Previous leadership experiences included directing a clinical service, a residency training program, and/or a medical student education program. These results suggest important ways to increase the success of women in academic pathology and increasing the percent of women department chairs, including supporting a family life and providing time, encouragement and resources for research, attending national meetings, and taking on departmental leadership positions.

Computer-aided diagnosis systems (CADx) can improve colorectal polyp (CRP) optical diagnosis. For integration into clinical practice, better understanding of artificial intelligence (AI) by endoscopists is needed. We aimed to develop an explainable AI CADx capable of automatically generating textual descriptions of CRPs. For training and testing of this CADx, textual descriptions of CRP size and features according to the Blue Light Imaging (BLI) Adenoma Serrated International Classification (BASIC) were used, describing CRP surface, pit pattern, and vessels. CADx was tested using BLI images of 55 CRPs. Reference descriptions with agreement by at least five out of six expert endoscopists were used as gold standard. CADx performance was analyzed by calculating agreement between the CADx generated descriptions and reference descriptions. CADx development for automatic textual description of CRP features succeeded. Gwet’s AC1 values comparing the reference and generated descriptions per CRP feature were: size 0.496, surface-mucus 0.930, surface-regularity 0.926, surface-depression 0.940, pits-features 0.921, pits-type 0.957, pits-distribution 0.167, and vessels 0.778. CADx performance differed per CRP feature and was particularly high for surface descriptors while size and pits-distribution description need improvement. Explainable AI can help comprehend reasoning behind CADx diagnoses and therefore facilitate integration into clinical practice and increase trust in AI.

This article was motivated by the need to academically frame and share the response of the North-West University (NWU) to the perceived increase of academic dishonesty during COVID-19. Within the ambit of the online (hybrid) teaching and learning approach that became dominant during the COVID-19 pandemic, the NWU established a Community of Practice for Academic Integrity (CoPAI) to enhance Academic Integrity (AI) in a holistic manner. By critically discussing the NWU's response through their CoPAI, the lessons learned, and strategies developed in the process, the NWU can hopefully assist other Higher Education institutes to progressively enhance AI in the future. This is important, because many contextual shifts in teaching and learning approaches, pedagogy, assessment, and the application of technology, that were enforced in an online mode of delivery during the pandemic, will prevail in future. In writing this article, we focused on contextualising the NWU CoPAI within current literature on community of practice (CoP) and Academic integrity (AI) and emphasising the unique strategy and holistic nature of this CoPAI. The establishment of the CoPAI is discussed within the appreciative inquiry as methodological framework. This methodology is commonly used by CoPs, but it is particularly relevant to the CoPAI since CoPAI sought answers to all the AI questions that presented itself due to disruptions in the higher education landscape. The appreciative inquiry method allowed for the opportunity to find some answers in a holistic manner. Some of these answers or insights gained through the activities of CoPAI is further discussed in the latter part of the article. In conclusion, some of the outcomes and shortcomings of CoPAI at the NWU are highlighted. The main finding of this article concluded that the establishment of a CoPAI can enhance AI at HE institutions in a holistic manner. The applicability, relevance, and success of this CoPAI was realised through its holistic approach which included the valorisation of institutional aspects, the engagement and empowerment of lecturers, and the engagement and empowerment of students. This novel and unique approach to promote AI in HE could fill the existing knowledge gap in the South African context, where the establishment of a CoPAI, the application of appreciative inquiry as methodology, and the inclusion of a holistic approach are still absent. It might however also be an example for other HE institutions to follow globally.

The histone deacetylase inhibitor (HDACi) valproic acid (VPA) has neuroprotective and anti-inflammatory effects in experimental traumatic brain injury (TBI), which have been partially attributed to the epigenetic disinhibition of the transcription repressor RE1-Silencing Transcription Factor/Neuron-Restrictive Silencer Factor (REST/NRSF). Additionally, VPA changes post-traumatic brain injury (TBI) brain metabolism to create a neuroprotective environment. To address the interconnection of neuroprotection, metabolism, inflammation and REST/NRSF after TBI, we subjected C57BL/6N mice to experimental TBI and intraperitoneal VPA administration or vehicle solution at 15 min, 1, 2, and 3 days post-injury (dpi). At 7 dpi, TBI-induced an up-regulation of REST/NRSF gene expression and HDACi function of VPA on histone H3 acetylation were confirmed. Neurological deficits, brain lesion size, blood–brain barrier permeability, or astrogliosis were not affected, and REST/NRSF target genes were only marginally influenced by VPA. However, VPA attenuated structural damage in the hippocampus, microgliosis and expression of the pro-inflammatory marker genes. Analyses of plasma lipidomic and polar metabolomic patterns revealed that VPA treatment increased lysophosphatidylcholines (LPCs), which were inversely associated with interleukin 1 beta (Il1b) and tumor necrosis factor (Tnf) gene expression in the brain. The results show that VPA has mild neuroprotective and anti-inflammatory effects likely originating from favorable systemic metabolic changes resulting in increased plasma LPCs that are known to be actively taken up by the brain and function as carriers for neuroprotective polyunsaturated fatty acids.

Background and Aims: It is well-documented that fertility rates decline with maternal age, however there is limited information on the success rates for women between 40 to 50 years old using their own eggs. Many ART providers set differing maternal age limits for accessing treatment, with minimal clinical evidence to support these limits being set. The aim of this study was to identify clinical and live birth rates for women aged 40 to 46 at egg pick-up (EPU), who used autologous oocytes and ET (with or without pre-implantation genetic testing (PGT)). Method: A retrospective cohort study was performed on 7,521 autologous EPU cycles undertaken between 2015 and 2020 for women between 40 and 46 years old at clinics in Victoria, Australia. Maternal age was determined by age at the time of EPU. Clinical pregnancy rate (CPR) and live birth rate (LBR) outcomes were calculated following the transfer of a single fresh or frozen blastocyst stage embryo. Outcomes were also determined for PGT-tested compared with non-PGT-tested frozen embryo transfer (FET) cycles based on maternal age at time of embryo creation and analysed at each age by Fisher’s exact test. Results: CPR and LBR declined with increasing maternal age for both fresh and frozen single blastocyst ETs (Tables 1 and 2), with no live births for women who had eggs collected at 46 years old. Equally, outcomes were lower for fresh compared with frozen ET cycles (P

Abstract Sowing flower strips along field edges is a widely adopted method for conserving pollinating insects in agricultural landscapes. To maximize the effect of flower strips given limited resources, we need spatially explicit tools that can prioritize their placement, and for identifying plant species to include in seed mixtures. We sampled bees and plant species as well as their interactions in a semi‐controlled field experiment with roadside/field edge pairs with/without a sown flower strip at 31 sites in Norway and used a regional spatial model of solitary bee species richness to test if the effect of flower strips on bee species richness was predictable from the modelled solitary bee species richness. We found that sites with flower strips were more bee species rich compared to sites without flower strips and that this effect was greatest in areas that the regional solitary bee species richness model had identified to be particularly important for bees. Spatial models revealed that even within small landscapes there were pronounced differences between field edges in the predicted effect of sowing flower strips. Of the plant species that attracted the most bee species, the majority mainly attracted bumblebees and only few species also attracted solitary bees. Considering both the taxonomic diversity of bees and the species richness of bees attracted by plants we suggest that seed mixes containing Hieracium spp. such as Hieracium umbellatum, Pilosella officinarum, Taraxacum spp., Trifolium repens, Lotus corniculatus, Stellaria graminea and Achillea millefolium would provide resources for diverse bee communities in our region. Spatial prediction models of bee diversity can be used to identify locations where flower strips are likely to have the largest effect and can thereby provide managers with an important tool for prioritizing how funding for agri‐environmental schemes such as flower strips should be allocated. Such flower strips should contain plant species that are attractive to both solitary and bumblebees, and do not need to be particularly plant species rich as long as the selected plants complement each other.

Summary: Background: The Bruton's tyrosine kinase inhibitor ibrutinib and the proteasome inhibitor bortezomib have single-agent activity, non-overlapping toxicities, and regulatory approval in mantle cell lymphoma (MCL). In vitro, their combination provides synergistic cytotoxicity. In this investigator-initiated phase 1/2 trial, we established the recommended phase 2 dose of ibrutinib in combination with bortezomib, and assessed its efficacy in patients with relapsed or refractory MCL. Methods: In this phase 1/2 study open in 15 sites in Switzerland, Germany and Italy, patients with relapsed or refractory MCL after ≤2 lines of chemotherapy and both ibrutinib-naïve and bortezomib-naïve received six cycles of ibrutinibb and bortezomib, followed by ibrutinib maintenance. For the phase 1 study, a standard 3 + 3 dose escalation design was used to determine the recommended phase 2 dose of ibrutinib in combination with bortezomib. The primary endpoint in phase 1 was the dose limiting toxicities in cycle 1. The phase 2 study was an open-label, single-arm trial with a Simon's two-stage min–max design, with a primary endpoint of overall response rate (ORR) assessed by CT/MRI. This study was registered with ClinicalTrials.gov, NCT02356458. Findings: Between August 2015 and September 2016, nine patients were treated in the phase 1 study, and 49 patients were treated between November 2016 and March 2020 in the phase 2 of the trial. The ORR was 81.8% (90% CI 71.1, 89.8%, CR(u) 21.8%) which increased with continued ibrutinib (median 10.6 months) to 87.3%, (CR(u) 41.8%). 75.6% of patients had at least one high-risk feature (Ki-67 > 30%, blastoid or pleomorphic variant, p53 overexpression, TP53 mutations and/or deletions). In these patients, ibrutinib and bortezomib were also effective with an ORR of 74%, increasing to 82% during maintenance. With a median follow-up of 25.4 months, the median duration of response was 22.7, and the median PFS was 18.6 months. PFS reached 30.8 and 32.9 months for patients with a CR or Cru, respectively. Interpretation: The combination of ibrutinib and bortezomib shows durable efficacy in patients with relapsed or refractory MCL, also in the presence of high-risk features. Funding: SAKK (Hubacher Fund), Swiss State Secretariat for Education, Research and Innovation, Swiss Cancer Research Foundation, and Janssen.

In recent years, there has been growing concern about the decline in human green space use and nature-based recreation in Western countries. While some evidence suggests that the COVID-19 pandemic led to increased recreational mobility in urban green spaces, it is unclear whether the pandemic led to nationwide changes in green space use in both densely and less densely populated neighborhoods, as well as whether social inequalities in green space use were reinforced or attenuated by the pandemic. To address these questions, we used daily nationwide aggregated mobility data from more than 2 million cell phone subscribers in 14,331 geographical grids across Norway to examine potential changes in mobility in green spaces as measured by the normalized difference vegetation index (NDVI) during the pandemic. Additionally, we controlled for weather conditions, holiday periods, and neighborhood sociodemographic characteristics. The results from linear mixed model analyses showed a 9.4% increase in recreational visits in the greenest spaces during the pandemic. Notably, this increase was most prominent in neighborhoods of low socioeconomic status (SES) and was observed in both high- and low-population density neighborhoods, although the increase was somewhat stronger in neighborhoods with low population density. Our study findings suggest that the COVID-19 pandemic has played a role in increasing nationwide green space use in Norway and potentially narrowing the gap of green inequalities, thus highlighting the importance of preserving and promoting green spaces as a public health resource, particularly in disadvantaged neighborhoods.

Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity, biodiversity, and the provision of ecosystem services. The use of digital technologies can support this by designing and managing resource-efficient and context-specific agricultural systems. We present the Digital Agricultural Knowledge and Information System (DAKIS) to demonstrate an approach that employs digital technologies to enable decision-making towards diversified and sustainable agriculture. To develop the DAKIS, we specified, together with stakeholders, requirements for a knowledge-based decision-support tool and reviewed the literature to identify limitations in the current generation of tools. The results of the review point towards recurring challenges regarding the consideration of ecosystem services and biodiversity, the capacity to foster communication and cooperation between farmers and other actors, and the ability to link multiple spatiotemporal scales and sustainability levels. To overcome these challenges, the DAKIS provides a digital platform to support farmers' decision-making on land use and management via an integrative spatiotemporally explicit approach that analyses a wide range of data from various sources. The approach integrates remote and in situ sensors, artificial intelligence, modelling, stakeholder-stated demand for biodiversity and ecosystem services, and participatory sustainability impact assessment to address the diverse drivers affecting agricultural land use and management design, including natural and agronomic factors, economic and policy considerations, and socio-cultural preferences and settings. Ultimately, the DAKIS embeds the consideration of ecosystem services, biodiversity, and sustainability into farmers' decision-making and enables learning and progress towards site-adapted small-scale multifunctional and diversified agriculture while simultaneously supporting farmers' objectives and societal demands.