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Soil Nitrogen Supply Exerts Largest Influence on Leaf Nitrogen in Environments with the Greatest Leaf Nitrogen Demand
No full textAccurately representing the relationships between nitrogen supply and photosynthesis is crucial for reliably predicting carbon–nitrogen cycle coupling in Earth System Models (ESMs). Most ESMs assume positive correlations amongst soil nitrogen supply, leaf nitrogen content, and photosynthetic capacity. However, leaf photosynthetic nitrogen demand may influence the leaf nitrogen response to soil nitrogen supply; thus, responses to nitrogen supply are expected to be the largest in environments where demand is the greatest. Using a nutrient addition experiment replicated across 26 sites spanning four continents, we demonstrated that climate variables were stronger predictors of leaf nitrogen content than soil nutrient supply. Leaf nitrogen increased more strongly with soil nitrogen supply in regions with the highest theoretical leaf nitrogen demand, increasing more in colder and drier environments than warmer and wetter environments. Thus, leaf nitrogen responses to nitrogen supply are primarily influenced by climatic gradients in photosynthetic nitrogen demand, an insight that could improve ESM predictions
Pallidothalamic Circuit-Selective Manipulation Ameliorates Motor Symptoms in A Rat Model of Parkinsonian
No full textDeep brain stimulation (DBS) effectively treats motor symptoms of advanced Parkinson\u27s disease (PD), with the globus pallidus interna (GPi) commonly targeted. However, its therapeutic mechanisms remain unclear. We employed optogenetic stimulation in the entopeduncular nucleus (EP), the rat homologue of GPi, in a unilateral 6-OHDA lesioned female Sprague Dawley rat model of PD. We quantified behavioral effects of optogenetic EP DBS on motor symptoms and conducted single-unit recordings in EP and ventral lateral motor thalamus (VL) to examine changes in neural activity. Behavioral tests showed high-frequency optogenetic EP DBS (75, 100, 130Hz) reduced ipsilateral turning and corrected forelimb stepping, while low-frequency (5 and 20Hz) had no effect. EP and VL neurons exhibited mixed response during stimulation, with both increased and decreased firing. Notably, the average firing rate of all recorded neurons in the EP and VL significantly increased at 130 Hz but not at other frequencies. While beta-band oscillatory activity was reduced in most EP neurons across high frequencies (75, 100, 130 Hz), reductions in beta-band oscillations with the VL occurred only at 130 Hz. These findings suggest that the neural firing rates within EP and VL circuits were differentially modulated by EP DBS, they may not fully explain the frequency-dependent behavioral effect. Instead, high-frequency optogenetic EP DBS at 130Hz may ameliorate parkinsonian motor symptoms by reducing abnormal oscillatory activity in the EP-VL circuits. This study underscores the therapeutic potential of circuit-specific modulation in the pallidothalamic pathway using optogenetic EP DBS to alleviate motor deficits in a PD rat model. The contribution of EP local cells to the therapeutic effects of EP DBS in PD has been unclear. Our study addressed this by employing local cell-specific optogenetic stimulation. Directly stimulating EP local neurons using optogenetics effectively reduced parkinsonian symptoms in the 6-OHDA lesioned rat. These findings highlight the importance of precise circuit manipulation through optogenetic techniques within the pallidothalamic pathway, suggesting a promising approach for ameliorating motor deficits in PD
Reason Profiles for not Returning to Preinjury Activity Level Following Anterior Cruciate Ligament Reconstruction- A Latent Class Analysis With Subgroup Comparison of Patient-Reported Outcome Measures
No full textBACKGROUND: Given the high proportion of athletes who do not return to sports (RTS) after anterior cruciate ligament reconstruction (ACLR), strategies are needed to identify at-risk patients and optimize rehabilitation for successful RTS after ACLR. PURPOSE/HYPOTHESIS: This study used latent class analysis (LCA) to characterize a unique clustering of reasons why athletes do not return to their preinjury activity level after ACLR. We hypothesized that patients with high pain scores and high levels of fear would be less likely to return to their preinjury activity level. STUDY DESIGN: Cohort study Level of evidence, 3. METHODS: All patients at a single institution who underwent primary ACLR between 2005 and 2021 were contacted to complete a survey via REDCap. Patients\u27 ability to RTS and their preinjury activity level, reasons for inability to return to the preinjury activity level, and patient-reported outcome scores were collected from 981 patients. LCA was performed to identify and compare patterns among patients\u27 reasons for not returning to the preinjury activity level. RESULTS: Of the 981 patients included, only 446 (45.5%) were fully able to return to their preinjury activity level. LCA categorized patients into 3 groups based on their reasons for not returning to preinjury activity levels: a high-function group (75.5%), which reported no barriers a multisymptom group (16.1%), which cited pain, lack of strength, and instability and a fear-limited group (8.4%), which reported fear as the sole reason. Among the high-function group, 86.2% reported RTS compared with \u3c36.7% in the other classes. There was no difference in Knee injury and Osteoarthritis Outcome Score (KOOS) subscales-including Pain, Symptoms, or Activities of Daily Living-between the high-function and fear-limited groups, however, the multisymptom group presented with the lowest scores in all KOOS subscales (P \u3c .001). In addition, patient characteristics, the time from the index ACLR to the follow-up, and subsequent revision ACLR were similar between groups, however, the multisymptom profile demonstrated the highest proportion of allograft ACLR (P = .04) and secondary ipsilateral surgery (P \u3c .001). Overall subjective knee grade (1-100) and Marx scores were highest in the high-function group, followed by fear-limited and multisymptom groups (P \u3c .001). CONCLUSION: Patients were differentiated into 3 distinct classes after primary ACLR. Furthermore, those with patient-reported characteristics of pain, lack of strength, instability, or fear were significantly less likely to return to their preinjury activity level or sport
Gribben buried forest site map and tree measurement data
No full textDue to a unique set of circumstances, we were able to excavate an entire spruce (Picea) forest in Michigan\u27s Upper Peninsula, USA, which was buried in the early Holocene (9928 ± 133 uncalibrated 14C years bp). Trees ranged from \u3c 5 cm to \u3e 50 cm in diameter, and dominants were approximately 9 m tall. The stand was multi-aged, with a number of trees over 120 years old. Well-preserved stem cross-sections were recovered, the entire stand was mapped, and field diameter measurements were made on most trees. Data from all stem cross sections are included here, including some that were not used by the authors of Pregitzer et al. (2000; citation below)
Pigment removal from reverse-printed laminated flexible films by solvent-targeted recovery and precipitation
Get PDFThe solvent-targeted recovery and precipitation (STRAP) process separates and recovers the constituent resins in multilayer plastic packaging films by selective polymer dissolution. In this work, the cause of coloring in the STRAP-recycled polyethylene (PE) resins from postindustrial printed films was identified as decomposed diarylide pigments. Two different approaches are needed to completely remove the dissolved colorants during the STRAP process including (i) adding an activated carbon (AC) adsorbent to the solvent after polymer dissolution and (ii) proper mechanical filtration of the polymer-solvent cake to remove as much solvent from the cake as possible. Colorless recycled PE can be produced by a combination of the proposed approaches (choosing the proper solvent, adding an AC adsorbent, and doing proper mechanical filtration) with minimal accumulation of colorants in the recycled STRAP solvents. This study demonstrated that high-quality STRAP low-density PE can be obtained from printed plastic films, enhancing the potential circularity of these packaging materials
Collision Probabilities Between User Equipment Using 5G NR Sidelink Time-Domain-Based Resource Allocation in C-V2X
Get PDFEfficient resource allocation is a critical factor in ensuring reliable and low-latency communication in the fifth-generation New Radio (5G NR) sidelink-based Cellular Vehicle to Everything (C-V2X) networks. One of the critical challenges in adopting C-V2X systems is the potential for packet collisions between User Equipment (UE) when they share resources in the sidelink channel. For reliable and low-latency communication, especially in safety-critical applications, efficient resource allocation is essential. This paper explores collision-related issues that may arise in the 5G NR sidelink and the probability of collisions on resource blocks. To address these challenges, we propose an experimental time-domain resource allocation strategy leveraging dynamic reselection intervals and adaptive reservation mechanisms. Unlike existing approaches, which primarily rely on static or semi-persistent scheduling, our strategy optimizes resource allocation based on real-time variations in generation time, speed and distance between UEs. The proposed approach significantly reduces collision probabilities, enhances communication reliability and ensures efficient resource utilization, even in high-density vehicular networks. Addressing packet collisions in resource allocation becomes crucial for the viability of vehicular communication systems. The goal of this paper is to analyze the dynamics and causes of packet collisions in C-V2X scenarios using 5G NR sidelink technology and to evaluate how our time-domain optimization techniques can enhance system performance in rapidly evolving vehicular communication networks
Generative AI for RF Sensing in IoT Systems
No full textThe development of wireless sensing technologies, using signals such as Wi-Fi, infrared, and RF to gather environmental data, has significantly advanced within Internet of Things (IoT) systems. Among these, Radio Frequency (RF) sensing stands out for its cost-effective and non-intrusive monitoring of human activities and environmental changes. However, traditional RF sensing methods face significant challenges, including noise, interference, incomplete data, and high deployment costs, which limit their effectiveness and scalability. This article investigates the potential of Generative AI (GenAI) to overcome these limitations within the IoT eco-system. We provide a comprehensive review of state-of-the-art GenAI techniques, focusing on their application to RF sensing problems. By generating high-quality synthetic data, enhancing signal quality, and integrating multi-modal data, GenAI offers robust solutions for RF environment reconstruction, localization, and imaging. Additionally, GenAI\u27s ability to generalize enables IoT devices to adapt to new environments and unseen tasks, improving their efficiency and performance. The main contributions of this article include a detailed analysis of the challenges in RF sensing, the presentation of innovative GenAI-based solutions, and the proposal of a unified framework for diverse RF sensing tasks. Through case studies, we demonstrate the effectiveness of integrating GenAI models, leading to advanced, scalable, and intelligent IoT systems
5G NR sidelink time domain based resource allocation in C-V2X
No full textThis study explores the need for efficient resource allocation in fifth generation (5G) New Radio (NR) sidelink communication for cellular vehicle-to-everything (C-V2X) applications. With the advent of 5G networks, C-V2X can enable direct connection between neighboring vehicles and infrastructure without relying on the cellular network. However, direct communication between devices in 5G NR sidelink makes resource allocation more challenging than in a cellular network. Efficient resource allocation is essential to maintain dependable communication, especially in crowded and interference-prone contexts. There are different type of resource allocation methods such as time-domain, frequency-domain, and power-domain resource allocation, which can be used separately or in combination to achieve efficient resource allocation. In this study, the authors discuss time domain based resource allocation method based on packet generation time and packet allocation time. The implications of efficient resource allocation in 5G NR sidelink in C-V2X include increased signal-to-noise ratio, reduced interference, lower latency, and increased network capacity. The proposed approach is demonstrated on a Network Simulator (NS3.34) along with the traffic scenarios generated using Simulated Urban Mobility (SUMO). Our results demonstrate that time allocation is a promising approach to achieve efficient resource allocation, enabling safer and more effective transportation systems for C-V2X applications
A Nonconforming Finite Element Method for the Quad-Curl Hodge-Laplacian Problem in Two Dimensions
No full textIn this paper, we introduce an H1-nonconforming vector-valued finite element whose rot has H1-conformity. This element yields a nonconforming interior-penalty finite element method for the primal formulation of the quad-curl Hodge-Laplacian problem. Contrasting with conforming methods based on the primal formulation, our method effectively avoids spurious solutions on non-convex polygonal domains. We establish rigorous error estimates for the method in both the energy norm and the L2 norm, under graded meshes with various grading parameters. Numerical examples are used to verify our theoretical findings
Calcium phosphate formation and deposition in ischemic neurons
Get PDFIschemic stroke causes acute brain calcium phosphate (CaP) deposition, a process involving primarily the injured neurons. Whereas the adverse impact of CaP deposition on the brain structure and function has been recognized, the underlying mechanisms remain poorly understood. This investigation demonstrated that the neuron-expressed, plasma membrane-associated Ca2+-binding proteins annexin (Anx) A2, AnxA5, AnxA6, and AnxA7 contributed to neuronal CaP deposition in the mouse model of ischemic stroke. These Anxs were released from the degraded plasma membrane of the ischemic neurons and were able to form Anx/CaP complexes, a nanostructure capable of binding to the β actin filaments via Anx–actin interaction to cause neuronal CaP deposition prior to brain infarction. Anx administration to the healthy mouse brain caused brain CaP deposition and infarction. Monomeric β actin was able to block competitively Anx binding to β actin filaments and prevent ischemic stroke- and Anx administration-induced brain CaP deposition and infarction. Administration of siRNAs specific to the four Anx mRNAs alleviated brain CaP deposition and infarction. These observations support the role of Anxs in CaP formation and deposition in ischemic neurons