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We measured carbon dioxide and methane flux exchange with the atmosphere at the deepest site of Falling Creek Reservoir (Vinton, Virginia, USA) every 30 minutes from 04 April 2020 to 31 December 2024. Falling Creek Reservoir is a drinking water supply reservoir owned and managed by the Western Virginia Water Authority (WVWA) as a primary drinking water source. The dataset consists of micrometeorological and flux data collected using an eddy covariance system (LiCor Biosciences, Lincoln, Nebraska, USA) and analyzed with associated Eddy Pro software (Eddy Pro Version 7.0.6), including carbon dioxide, methane, and water vapor. All analysis scripts are included for data processing and quality assurance/quality control following best practices. 

Trained and optimized for typical and fluent speech, speech AI works poorly for people with speech diversities, often interrupting them and misinterpreting their speech. The increasing deployment of speech AI in automated phone menus, AI-conducted job interviews, and everyday devices poses tangible risks to people with speech diversities. To mitigate these risks, this workshop aims to build a multidisciplinary coalition and set the research agenda for fair and accessible speech AI. Bringing together a broad group of academics and practitioners with diverse perspectives, including HCI, AI, and other relevant fields such as disability studies, speech language pathology, and law, this workshop will establish a shared understanding of the technical challenges for fair and accessible speech AI, as well as its ramifications in design, user experience, policy, and society. In addition, the workshop will invite and highlight first-person accounts from people with speech diversities, facilitating direct dialogues and collaboration between speech AI developers and the impacted communities. The key outcomes of this workshop include a summary paper that synthesizes our learnings and outlines the roadmap for improving speech AI for people with speech diversities, as well as a community of scholars, practitioners, activists, and policy makers interested in driving progress in this domain. 

Abstract Pollen function is critical for successful plant reproduction and crop productivity and it is important to develop accessible methods to quantitatively analyze pollen performance to enhance reproductive resilience. Here we introduce TubeTracker as a method to quantify key parameters of pollen performance such as, time to pollen grain germination, pollen tube tip velocity and pollen tube survival. TubeTracker integrates manual and automatic image processing routines and the graphical user interface allows the user to interact with the software to make manual corrections of automated steps. TubeTracker does not depend on training data sets required to implement machine learning approaches and thus can be immediately implemented using readily available imaging systems. Furthermore, TubeTracker is an excellent tool to produce the pollen performance data sets necessary to take advantage of emerging AI-based methods to fully automate analysis. We tested TubeTracker and found it to be accurate in measuring pollen tube germination and pollen tube tip elongation across multiple cultivars of tomato. Abstract FigureGraphical AbstractGraphical user interface of TubeTracker showing all supported functionalities. 

We measured eddy covariance data and fluxes (carbon dioxide, methane) collected at the deepest site of Falling Creek Reservoir (Vinton, Virginia, USA) every 30 minutes from 04 April 2020 to 31 December 2023. Falling Creek Reservoir is a drinking water supply reservoir owned and managed by the Western Virginia Water Authority (WVWA) as a primary drinking water source. The dataset consists of micrometeorological and flux data collected using an eddy covariance system (LiCor Biosciences, Lincoln, Nebraska, USA) and analyzed with associated Eddy Pro software (Eddy Pro Version 7.0.6), including carbon dioxide and methane fluxes. All analysis scripts are included for data processing and quality assurance/quality control following best practices. 

Rising temperature extremes during critical reproductive periods threaten the yield of major grain and fruit crops. Flowering plant reproduction depends on the ability of pollen grains to generate a pollen tube, which elongates through the pistil to deliver sperm cells to female gametes for double fertilization. We used tomato as amodel fruit croptodeterminehowhigh temperature affects the pollen tube growthphase, takingadvantage of cultivars noted for fruit production in exceptionally hot growing seasons. We found that exposure to high temperature solely during the pollen tube growth phase limits fruit biomass and seed set more significantly in thermosensitive cultivars than in thermotolerant cultivars. Importantly, we found that pollen tubes from the thermotolerantTamaulipas cultivar have enhanced growth in vivo and in vitro under high temperature. Analysis of the pollen tube transcriptome’s response to high temperature allowed us to define two responsemodes (enhanced induction of stress responses and higher basal levels of growth pathways repressed by heat stress) associated with reproductive thermotolerance. Importantly, we define key components of the pollen tube stress response, identifyingenhancedreactive oxygenspecies (ROS)homeostasis andpollen tubecallose synthesis and deposition as important components of reproductive thermotolerance in Tamaulipas. Our work identifies the pollen tube growth phase as a viable target to enhance reproductive thermotolerance and delineates key pathways that are altered in crop varieties capable of fruiting under high-temperature conditions. 

Abstract Key messagePollen tubes from closely related species and mutants lacking pollen tube MYB transcription factors are able to initiate FER/LRE-dependent synergid cell calcium oscillations. AbstractReproductive isolation leads to the evolution of new species; however, the molecular mechanisms that maintain reproductive barriers between sympatric species are not well defined. In flowering plants, sperm cells are immotile and are delivered to female gametes by the pollen grain. After landing on the stigmatic surface, the pollen grain germinates a polarized extension, the pollen tube, into floral tissue. After growing via polar extension to the female gametes and shuttling its cargo of sperm cells through its cytoplasm, the pollen tube signals its arrival and identity to synergid cells that flank the egg. If signaling is successful, the pollen tube and receptive synergid cell burst, and sperm cells are released for fusion with female gametes. To better understand cell–cell recognition during reproduction and how reproductive barriers are maintained between closely related species, pollen tube-initiated synergid cell calcium ion dynamics were examined during interspecific crosses. It was observed that interspecific pollen tubes successfully trigger synergid cell calcium oscillations—a hallmark of reproductive success—but signaling fails downstream of key signaling genes and sperm are not released. This work further defines pollen tube–synergid cell signaling as a critical block to interspecific hybridization and suggests that the FERONIA/LORELEI signaling mechanism plays multiple parallel roles during pollen tube reception.