A document by Shahid Nawaz Khan. Click on the document to view its contents.

YOLO, which has an extremely fast architecture with a detection pipeline consisting of a single neural network, is among the popular deep learning models of recent times. Since YOLO is a real-time object detector, its accuracy and detection speed are very important. When the model is evaluated from this perspective, activation functions help improve the performance of the model. In this study, performance improvements were made by using alternative activation functions instead of the default SiLU activation function of the YOLOv8 model. Appropriate activation functions were selected to increase the performance of the YOLOv8s model. ReLU, LeakyReLU, ELU, Sigmoid and HardTanh functions were used in the improved models. Experimental results were obtained using the BCCD and Urine datasets with the improved YOLOv8s models. The results were evaluated with recall, precision and mean Average Precision (mAP) metrics and the effect of the change of the activation function on the original YOLOv8s model was observed. When the experimental results and evaluation metrics were examined, better results were obtained compared to the original YOLOv8s model.

Suffering from speckle noise is one of the main obstacles to detect accurate change in synthetic aperture radar (SAR) images, gives rise to synthetic aperture radar image quality degradation. To address this issue, existing deep learning methods typically emphasize spatial information. Inspired by the nonlinear signal processing characteristics, this letter introduces the dendrite neuron model for SAR image change detection task. With a locally nonlinear dendrite structure, dendrite neuron model can adaptively construct the nonlinear effects that these synaptic inputs in the dendrite structure, which is beneficial for describing the contribution of these neighbouring synaptic inputs to the task. Meanwhile, multichannel input signals converge into the cell body by these branches of the dendrite layer, from which different intensities of stimulation on the neuron cell body were aggregated. The parameters involved in this model were searched for the optimal combination using a differential evolution algorithm. Though Simple in structure, visual and quantitative results obtained on three real SAR image data sets have demonstrated the effectiveness and robustness of the dendrite neuron model.

not-yet-known not-yet-known not-yet-known unknown Ecosystem size and spatial resource flows are key factors driving species diversity and ecosystem function. However, the question of whether and how these drivers interact has been largely overlooked. Here, we investigated how ecosystem size asymmetry affects species diversity and function of two-patch meta-ecosystems connected through flows of non-living resources. We conducted a microcosm experiment, mimicking resource flows between ecosystems of different sizes yet otherwise identical properties or between ecosystems of the same size. Meta-ecosystems with asymmetric ecosystem sizes displayed higher α- diversity but lower β-diversity and ecosystem function (total biomass) than their unconnected counterparts. At the same time, such an effect was not found for meta-ecosystems of identical patch sizes. Our work demonstrates how the size of ecosystems, interconnected via resource flows, can modulate cross-ecosystem dynamics, having implications for species diversity and function across scales.

7085 aluminum alloy with T74 was exposed to heat at 80℃-240℃ for 5 h, and the microstructure, the fatigue properties after thermal exposure were analyzed and the relationship between them was built. The results show that the grain size of 7085-T74 aluminum alloy did not change significantly at the studied thermal exposure temperature. Within 120℃, the microstructure including precipitates and mechanical properties have no significant change. Above 120℃, with the increase of thermal exposure temperature, the average radius of[1](#fn-0002) precipitates increased significantly from 3.9 nm to 12.3 nm. The tensile strength and fatigue strength decreased conspicuously from 560MPa and 235MPa to 382MPa and 139MPa respectively. The fatigue life decreased from 10,000,000 cycles to 21,505 cycles under the load of 200 MPa when the thermal exposure temperature increased from room temperature to 240℃. In the range from room temperature to 240℃, the conditional fatigue strengths of the alloy under the fatigue life of 10 6 cycles decreased from 242 MPa to 158 MPa. Furthermore, it is found that the fatigue strength is proportional to the -1/2 power of the precipitate size. In addition, the mechanism on the fatigue properties change after thermal exposure was discussed based on the microstructure variation.

not-yet-known not-yet-known not-yet-known unknown The current lack of diversity in neuroimaging datasets limits the potential generalisability of research findings. This situation is also likely to have a downstream impact on our ability to translate fundamental research into effective interventions and treatments for the global population. We propose that electroencephalography (EEG) is viable for delivering truly inclusive and global neuroscience. Over the past two decades, advances in portability, affordability, and computational sophistication have created a tool that can readily reach underrepresented communities and scale across low-resource contexts—advantages that surpass those of other neuroimaging modalities. However, skepticism persists within the neuroscience community regarding the feasibility of realizing EEG’s full potential for studying the brain on a global scale shortly. We highlight several challenges impeding progress, including the need to amalgamate large-scale, harmonized datasets to provide the statistical power and robust computational frameworks necessary for examining subtle differences between populations; the advancement of EEG technology to ensure high-quality data acquisition from all individuals—irrespective of hair type—and operable by non-specialists; and the importance of engaging directly with communities to co-create culturally sensitive and ethically appropriate research methodologies. By tackling these technical and social challenges and building on initiatives dedicated to inclusivity and collaboration, we can harness EEG’s potential to deliver neuroscience genuinely representative of the global population.

The system focuses on automation of conventional training and placement management system. This system can be used as an application for the Training & Placement Officers in the college to manage the student information with regard to placement and providing assistance using the assistance portal where students can post their query to the TPO and coordinators. Providing Student login helping them to update their personal and educational information in a form which will be added to the database and upload a resume and providing them with preparation materials for placements. An additional feature of the portal is a Company Tab which will be providing assistance to the companies to shortlist the students as per their eligibility criteria. It reduces the manual work and consumes less paperwork to reduce the time. Front end of the system is developed with the help of CSS, Bootstrap, and HTML. Backend of this system will be managed with the help of PHP, Android and XML. Database management of this system will be done with the help of MYSQL database. Online Training and Placement system automates activities of Training and placement cell and place the best coordination between student. It provide student community to use collective intelligence to increase selection ratio and eases out process of creation of management information automatically. Online Training and Placement focuses on automation of placement cell. Authorizing the CV, communicating about the various job openings to the student community, managing the corporate relationship for inviting them for the placements as well other activities, monitoring the progress of the selection process and communicating with different users.

This project is a clinic management system that will be used to solve the current problems that facing by the local clinic in Malaysia. Clinic Management System is a web-based platform system. The main objectives of this project is to improve the business process of the clinic in Malaysia by using the information technology and also

The recent proliferation of portable computers, the advent of personal digital assistants (PDAs) and continuing advances in computer networking all point to a future in which mobility of both users and computing system elements will be standard. However, these developments also invalidate many of the assumptions made by current system software, which has been built for stationary systems and users. An important component of system software that needs to looked at afresh is the file system. A user should be able to access the files he or she needs regardless of location. Although existing research efforts do provide some support for this, there are significant deficiencies that need to be remedied. We propose two related designs to address these problems. The first exploits the unique property of a PDA that it can accompany its owner at all times by using it to carry files of most immediate need to him or her. The second makes use of the recently proposed idea of a computing persona.

What has been the impact of the epidemic, a negative life event shared globally, on human emotions and values during these five years? As a cultural product, are pop song lyrics, which are thought to reflect emotions valued by many members of society, responsive to the impact of shared negative life events on society? To address this question, sentiment analysis and thematic modeling of annual Chinese and foreign lyric texts over a five-year period from 2019-2023 revealed inflection points in the pattern of emotional content embedded in the lyrics over time correlated with national policies regarding control.

Wearable UV sensors are increasingly valuable for monitoring solar exposure and preventing harmful effects of UV-B radiation, such as DNA damage, skin cancer, and immune suppression. However, many current sensors require electronic components to detect UV-B radiation specifically. In this study, we developed a simple, cost-effective UV sensor using silver-ion-loaded short-chain glucan microbeads (Ag@SMB) to selectively monitor UV-B levels in sunlight. The sensor’s UV-induced colorimetric response is triggered by the reduction of Ag nanoparticles on the microbead surface, resulting in a visible color change that corresponds to accumulated UV exposure. This change can be quantified by converting the color shift into greyscale (ΔG) values. When integrated into a paper membrane, the Ag@SMB sensor maintained its UV-dose-dependent response, with ΔG values strongly correlating with UV doses measured electrically, allowing real-time measurement of UV doses ranging from as low as 28 J/m 2 to as high as 3650 J/m 2. We further developed a wearable UV sensor, such as a bracelet, by embedding Ag@SMB in an alginate film, enabling real-time monitoring of UV doses within the Minimal Erythemal Dose range for all skin types. Additionally, the Ag@SMB sensor exhibits antimicrobial properties and low cytotoxicity, making it a safe and practical tool for daily use.

The integration of antimicrobial peptides (AMPs) into microstructured delivery systems enhances the controlled release and stability of bioactives like Resveratrol. This study examines third-generation microparticles based on alginate and pectin with aggregated AMPs for dual antioxidant and antimicrobial effects. The AMP self-assembled into nanoparticles before forming microparticles via spray drying, improving structural stability. In silico modeling and in vitro release studies under simulated gastrointestinal conditions showed that AMP-containing microparticles provided a slower, sustained Resveratrol release compared to peptide-free systems. The Weibull model best described the release, indicating a multi-phase behavior driven by diffusion and erosion. In gastric conditions, AMP-incorporated matrices improved structural integrity, reducing release, while in intestinal conditions, partial erosion enabled controlled release. In vivo infection studies using Galleria mellonella demonstrated significant reductions in inflammation and bacterial load 48 h post-infection. These results suggest that alginate-pectin microparticles with aggregated AMPs enhance antioxidant release and maintain antimicrobial activity, making them promising for gastrointestinal applications. Further optimization will focus on maximizing localized therapeutic efficacy.

Background: Atrial fibrillation (AF) and dementia are increasingly prevalent in aging U.S. populations. Their association raises public health concerns, emphasizing the need to understand mortality trends in older adults. This study examines AF and dementia-related mortality trends from 2000 to 2020. Methods: Using the CDC WONDER Multiple Cause of Death database, we analyzed death certificates for individuals aged 65 and older, reporting age-adjusted mortality rates (AAMRs) per 100,000 persons. Trends were assessed through annual percent change (APC) analysis via Joinpoint regression, with stratifications by sex, race/ethnicity, urbanization, and Census regions. Results: A total of 400,103 AF and dementia-related deaths were recorded between 2000 and 2020. The AAMR increased markedly from 25.4 in 2000 to 70.4 in 2020. The overall AAMR showed a steady increase from 2000 to 2018 (APC: +4.4%; 95% CI: 3.7–4.8), with a sharper rise from 2018 to 2020 (APC: +9.5%; 95% CI: 4.5–12.2; p < 0.001). Mortality rates were comparable between men (AAMR: 72.7) and women (AAMR: 71.6). NH White individuals exhibited the highest AAMR (47.0), followed by NH Black (26.6), Hispanic (23.1), and NH Asian/Pacific Islander (18.0) populations. Nonmetropolitan areas had higher AAMRs (48.1) compared to metropolitan areas (43.5). Regionally, the Western U.S. recorded the highest AAMR at 48.2, while state-level disparities showed a nearly threefold difference between the top 90th and bottom 10th percentiles. Conclusion: Rising AF and dementia-related mortality rates among older adults highlight a need for targeted screening and intervention, particularly for high-risk demographics and underserved regions.

Exploring S-ICD Extraction rates and frequency in modern PracticeMoied M. Al Sakan MD, Marwan M. Refaat, MDDivision of Cardiology, Department of Internal Medicine, American University of Beirut Medical Center, Beirut, LebanonRunning Title: S-ICD ExtractionWords: 620 (excluding the title page and references)Keywords: subcutaneous, Implantable cardioverter-defibrillator, cardiac arrhythmias, cardiology, cardiovascular diseases, extractionFunding: NoneDisclosures: NoneCorresponding Author:Marwan M. Refaat, MD, FACC, FAHA, FHRS, FASE, FESC, FACP, FRCPTenured Professor of MedicineTenured Professor of Biochemistry and Molecular GeneticsMember, Division of Cardiology/ Section of Cardiac ElectrophysiologyDirector, Cardiovascular Fellowship ProgramAmerican University of Beirut Faculty of Medicine and Medical CenterPO Box 11-0236, Riad El-Solh 1107 2020- Beirut, LebanonUS Address: 3 Dag Hammarskjold Plaza, 8th Floor, New York, NY 10017, USAOffice: +961-1-350000/+961-1-374374 Extension 5353 or Extension 5366 (Direct)The subcutaneous implantable cardioverter defibrillator (S-ICD) represents a significant advancement in the management of patients at risk for lethal arrhythmias and sudden cardiac death, particularly those not expected to have a need for pacing. This technology offers a compelling alternative to traditional transvenous ICDs (TV-ICDs), especially in young patients with a long-life expectancy, normal heart, and no need for pacing or cardiac resynchronization therapy, at increased risk of infections and with limited vascular access.[1] This study by Arati Gangadharan et al in the Journal of Cardiovascular Electrophysiology sheds light on an important aspect of S-ICD management, which is the extraction rates and indications for S-ICD extraction.[2]In this retrospective analysis of 372 patients undergoing S-ICD implantation between 2010 and 2022, the authors reported an extraction rate of 5.9% over a median follow-up period of 4.4 years. This figure falls within a spectrum of previously reported extraction rates, highlighting a notable variability across studies. What was notable is the importance of smoking and obesity as independent associations with increased S-ICD extraction. This study focused primarily on key indications of S-ICD extraction such as the need for bradycardia pacing, inappropriate shocks due to oversensing, infection and cardiac transplantation. Additional non-infectious indications have been reported such as lead rupture (2.42%), sensing issues (4.35%) and patient discomfort (2.42%). [1] When comparing the indications for lead extraction between this study and the indications noted in the systematic review on S-ICD lead extraction by Riccardo Vio et al, spanning the same period (articles collected until 2022), we can note similarities between the two studies (inappropriate shocks, infection, and the need for cardiac resynchronization therapy) but also other indications included defibrillation threshold testing failure (2.42%), lead malposition (1.93%), and premature battery depletion (0.48%). [1] Cardiac implantable electronic devices has been shown to be of benefit in patients with severe cardiomyopathy. [3,4] Also, when looking at the indications for S-ICD implantation- one of the most common indications for S-ICD implantation was primary prevention in patients with heart failure with reduced ejection fraction, Univariate analysis demonstrated that a history of lower left ventricular ejection fraction (P=<0.001), was associated with S-ICD extraction. (2,5) Notably, this study shed some light on the independent associations with a history of smoking and elevated body mass index (BMI) which serve as important factors that clinicians should consider during the pre-implantation assessment. These findings corroborate existing sparse literature suggesting that obesity and smoking may complicate device function and patient outcomes (2,5-7).The observational design from a single center limit the generalizability of these results to other populations. Future studies incorporating larger, multicenter cohorts also considering the socioeconomic status could provide more definitive insights.[2]In conclusion, while the S-ICD is generally preferred over TV-ICD in appropriately selected patients, the findings from this study highlight the necessity for meticulous pre-implantation assessments and the recognition of specific risk factors that may influence the risk of device extraction. As electrophysiology advances, combining the subcutaneous ICD (S-ICD) with a leadless pacemaker could shift the S-ICD toward becoming the preferred device choice, particularly for patients who would benefit from both defibrillation and pacing functions.[8] Furthermore, as suggested by the authors, the development of S-ICD technology and evolving guidelines over the last ten years may have affected the clinical decision-making process regarding device extraction and implantation as well as the rates of complications.[9]In summary, the results of this study emphasize the need for thorough pre-implantation evaluations and the identification of particular risk factors that may affect the risk of device extraction, even if the S-ICD is typically preferred over the TV-ICD in some patients.[2] The growing use of S-ICDs in a variety of patient populations necessitates continuous assessment of their safety and efficacy, especially when new technologies and indications are developed.

not-yet-known not-yet-known not-yet-known unknown Cancer immunotherapy represents a transformative strategy in modern oncology, utilizing the body’s immune system to recognize and eliminate malignant cells with precision. Unlike traditional therapies, which often directly target the tumor, immunotherapy enhances the immune system’s inherent ability to differentiate between healthy and cancerous cells, leading to more targeted and potentially longer-lasting therapeutic effects. The advent of immune checkpoint inhibitors (ICIs), particularly those targeting the PD-1/PD-L1 and CTLA-4 pathways, has marked a significant breakthrough in this field, yielding substantial clinical success in various cancer types. However, the therapeutic landscape is still challenged by issues such as the development of resistance mechanisms, heterogeneity in patient responses, and the limited efficacy of current ICIs across all tumor types. Given these challenges, there is a critical need to identify and validate new immune targets that can synergize with existing therapies or function independently to overcome resistance and improve patient outcomes. This review provides a comprehensive overview of the latest research efforts focused on uncovering novel immune targets. By expanding the repertoire of immune targets, these discoveries aim to enhance the effectiveness of cancer immunotherapy, offering hope for more personalized and resilient treatment options. The integration of these novel targets into clinical practice could not only extend the benefits of immunotherapy to a broader spectrum of cancers but also mitigate some of the current limitations, paving the way for more durable and effective therapeutic strategies in the fight against cancer.

The proliferation of malicious encryption-based cyberattacks has posed significant challenges to existing detection systems, which often struggle to keep pace with rapidly evolving threat landscapes. Introducing a computational framework that combines algorithmic entropy with neural correlation analysis addresses critical gaps in detection capabilities by enabling the identification of complex and previously untraceable malicious patterns. The proposed approach achieves high accuracy and efficiency through a synergy of entropy-based evaluations and advanced neural modeling, offering an automated and scalable solution to contemporary challenges. Comprehensive experiments demonstrate the framework's superior detection rates and minimal false positives across diverse datasets, highlighting its adaptability to varying operational environments and its potential to redefine cybersecurity methodologies. These results establish a robust foundation for integrating advanced computational paradigms into real-time threat detection systems, significantly enhancing their resilience against dynamic and sophisticated ransomware tactics.

Implementation of cross-enterprise business processes is complex. The globalization of businesses has resulted in a greater demand for business platforms that provide information security and privacy. In these processes, technological advancements are extensively leveraging automation and simplification. However, most enterprise systems are still centralized and work in silos. The advent of Distributed Ledger Technologies (DLT) and Smart Contracts is addressing some security and privacy challenges. However, these systems do not provide a perfect balance between end-to-end and cross-enterprise visibility and security. A further challenge is that the consensus/agreement provided by these systems cannot accommodate wider application requirements. The business platforms currently provide agreement at the level of individual messages without considering the context of the business workflow. This paper defines the Design-Centric Consensus (DCC) and information flow security inspired by the literature on information flow models and security protocols. It also identifies the need for multiple levels of consensus based on the application requirements. An architectural framework is also proposed that provides application-specific consensus while maintaining DCC and visibility

This study investigates the effects of different reference level (RL) criteria on dredging volume requirements for the Paraguay River, where recent declines in water levels, especially during dry seasons, pose challenges for safe navigation. Given that the Brazilian Navy’s traditional RL criteria rely on 20-year historical data, this may no longer reflect the river’s current hydrological conditions. To address this, were analyzed three RL scenarios: the standard 20-year RL, a critical-year RL from 2021 (an extreme drought year), and a recent 5-year RL based on the 94th percentile, which provides an adaptive approach to more recent conditions. Using a two-dimensional hydrodynamic model integrated with Geographic Information Systems (GIS), dredging volumes were calculated for each scenario. Results indicate that dredging requirements under the recent 5-year RL scenario are nearly three times higher than those estimated using the 20-year RL, reflecting the impact of declining water levels over the past decade. These findings suggest that adaptive RL criteria based on shorter, more recent time frames could improve river management, optimize dredging operations, reduce costs, and enhance navigational safety in response to increasing hydrological variability.

L’evoluzione dei calcolatori rappresenta una delle trasformazioni più significative della storia dell’umanità. Dal semplice calcolo matematico fino alle moderne applicazioni di intelligenza artificiale, la storia dei calcolatori è una narrazione di innovazione, creatività e cambiamento. Gli Antichi Strumenti di Calcolo Il primo strumento di calcolo conosciuto è l’abaco, utilizzato già intorno al 2000 a.C. in Mesopotamia. L’abaco consiste in una serie di palline mobili su aste o corde, utilizzato per eseguire semplici operazioni aritmetiche come addizione e sottrazione. Sebbene primitivo, rappresentava un grande passo avanti, poiché permetteva a commercianti e contabili di eseguire calcoli in modo più efficiente.Nel 1642, il filosofo e matematico francese Blaise Pascal inventò la Pascalina, una macchina meccanica che poteva eseguire addizioni e sottrazioni. Era costituita da ingranaggi e ruote dentate che ruotavano per mostrare il risultato del calcolo. Questa macchina è spesso considerata il primo calcolatore meccanico della storia, anche se aveva capacità molto limitate.Nel XVIII secolo, un altro matematico, perfezionò il concetto con la sua calcolatrice a ruota di Leibniz, capace di eseguire anche moltiplicazioni e divisioni. Leibniz introdusse anche il sistema binario, base per la matematica dei calcolatori moderni.

The redbelly tilapia (Coptodon zillii) is one of the most dangerous invasive alien fishes in the world. In order to better understand the feeding patterns of invasive populations in different habitats and seasons, and to reveal the driving force of differences in dietary composition among populations, we used DNA metabarcoding technology to analyze the dietary composition of 23 specimens from five different water bodies (two rivers and three reservoirs) in southern China, and 60 specimens from Shuikou Reservoir in four seasons (spring, summer, fall, and winter). The results showed that samples from five different water bodies and four seasons in Shuikou Reservoir were annotated to a total of 22 and 37 phyla of food categories, respectively. Generalist trophic strategies were dominant in C. zillii populations. There was significant spatial heterogeneity in the diet composition, with higher levels of trophic diversity in riverine populations. Water temperature, dissolved oxygen, and conductivity were important environmental factors driving changes in prey taxa of populations in different habitats. Dietary composition of populations in Shuikou Reservoir showed significant seasonal heterogeneity, with summer being the season with the highest level of trophic diversity. Total nitrogen, turbidity degree, pH and permanganate index were the important environmental factors driving the prey taxa changes of populations in different seasons of Shuikou Reservoir. Our results indicated that C. zillii are omnivorous, they have a wide range of recipes in both rivers and reservoirs in southern China, and show high trophic plasticity in different habitats and at different seasons of the year.

Background: Modulator therapy restores CFTR function and has led to health benefits for persons with CF (PwCF) including lower rates of pulmonary exacerbations. It is unknown if modulators affect lung function trajectories after inpatient treatment of pulmonary exacerbations (PEx). Methods: We conducted a retrospective review of hospital encounters for PEx for subjects 6-25 years old admitted to a large tertiary care center from 2014-2021 in order to capture hospitalizations of individual PwCF before and after starting modulators. Descriptive analyses were used to characterize the population and lung function findings. Logistic regression analyses were conducted to assess the association between modulators and FEV1pp outcomes. Results: The study sample included 575 encounters representing 149 unique PwCF. Hospital encounters of PwCF taking modulator were associated with higher mean FEV1pp at baseline, midway, discharge, and follow-up assessments. Mean FEV1pp increased during inpatient treatment of APE with loss of lung function at follow-up regardless of modulator use. At follow-up, hospitalizations of PwCF taking modulators were associated with significantly higher probability of sustained improvement in FEV1pp from discharge (average treatment effect (ATE) 0.118, p<0.05). Conclusions: Hospitalizations for PwCF taking modulators were associated with higher lung function at all assessments. Inpatient treatment for PEx was associated with lung function recovery at discharge followed by loss of function at follow-up that was partially ameliorated by taking modulators.

not-yet-known not-yet-known not-yet-known unknown The distribution of biodiversity along elevational gradients, and the drivers of these patterns, are research hotspots in community ecology; nonetheless, these aspects remain insufficiently understood. To address this, we established 24 plots along an elevational gradient from 300–1400 m on Daming Mountain, Guangxi, China, and examined the patterns and drivers of species and phylogenetic diversity along this gradient, via polynomial regression, correlation analysis, and redundancy analyses. With increasing elevation, species and phylogenetic diversity showed a hump-shaped trend, and the phylogenetic structure shifted from clustering to dispersion (or reduced clustering). Elevation was the primary environmental driver of variation in species diversity, soil available phosphorus and soil pH were the primary factors influencing both species and phylogenetic diversity, and nitrate nitrogen content was the most significant factor affecting species diversity. These findings, which reveal the patterns of diversity of woody plant communities along an elevational gradient on Daming Mountain, will contribute to the development of biodiversity conservation strategies for the region

not-yet-known not-yet-known not-yet-known unknown The Arctic experiences rapid climate change, but our ability to predict how this will influence plant communities is hampered by a lack of data on the extent to which different species are associated with particular environmental conditions, how these conditions are interlinked, and how they will change in coming years. Increasing temperatures may negatively affect plants associated with cold areas due to increased competition with warm-adapted species, but less so if local temperature variability is larger than the expected increase. Here we studied the potential drivers of change in vegetation composition and species richness along coast to inland and altitudinal gradients by the Nuuk fjord in western Greenland using Hierarchical Modelling of Species Communities (HMSC) and linear mixed models. Community composition was more strongly associated with random variability at intermediate spatial scales (among plot groups 500 m apart) than with large-scale variability in summer temperature, altitude or soil moisture, and the variation in community composition along the fjord was small. Species richness was related to plant cover, altitude and slope steepness, which explained 42% of the variation, but not to temperature. Jointly, this suggests that the direct effect of climate change will be weak, and that many species are associated with topographically defined microhabitats. However, both species richness and the occurrence of several species with inferior competitive capabilities peaked at intermediate cover, indicating that increasing dominance of competitive warm-adapted species can result in decreasing diversity under warmer climatic conditions.

Understanding the dispersal dynamics of an invasive species is important for predicting ecosystem impacts and potential rate of spread. Individuals at the invasion front often have specific behaviors, morphologies, and diets. However, how these three factors change in concert has received little attention. To address this question, we examined the behavior, morphology, and diet of invasive rusty crayfish (Faxonius rusticus, Girard 1852) in northeastern Oregon, USA. Sites included the point of introduction, the invasion front, and one site located mid-way between the other two. We sampled adult males at the three locations, conducted laboratory behavioral assays, characterized diets using DNA metabarcoding, and measured relative claw size. We predicted that crayfish at the invasion front would show a suite of correlated behaviors identified as being part of a bold behavioral syndrome (e.g., high aggression and exploration). In addition, we predicted that diets of individuals at the invasion front would include more preferred prey and a greater diversity of prey items. We found that two behaviors predicted to be positively correlated, exploration and aggression, were negatively correlated. Relative claw size was negatively related to exploration and positively related to aggression and potentially de-coupled the predicted positive correlation between the two behaviors. The negative correlation with exploration likely stems from the energetic costs of moving with large claws. Rusty crayfish at the invasion front had small claws, low levels of aggression, but high exploration rates. We did not find a correlation between diet composition and behavior or morphology at the individual level. However, at the location level diets of crayfish at the invasion front were characterized by animal taxa, while diets at the established location were characterized by plant taxa. Our results highlight the importance of the interplay between behavior and morphology and how morphology can drive unexpected patterns in behavioral syndromes.