Digital Commons Network^™

Abalones At Risk: A Global Red List Assessment Of Haliotis In A Changing Climate, Howard Peters, Gina M. Ralph, Laura Rogers-Bennett

Biological Sciences Faculty Publications

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There is increasing awareness that marine invertebrates such as abalones are at risk from the combined stressors of fishing and climate change. Abalones are an important marine fishery resource and of cultural importance to Indigenous and non-Indigenous people. A highly priced marine delicacy, they are inherently vulnerable: individuals are slow-growing and long-lived and successful reproduction requires dense assemblages. However, their global conservation status is poorly understood. Using IUCN Red List methodology, we assessed the extinction risk to all 54 species of abalone (genus Haliotis). Of the 21 fished commercially for human consumption either now and/or in the past, 15 …

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State Of Coastal And Marine Resources: Sablayan, Occidental Mindoro, Ma Celina J. Añonuevo, Jemelyn Grace P. Baldisimo, Denmark B. Racamara, Mary Joyce P. Velos, Joseph Benedict T. Garcia, Frederico B. Sabban, Joey P. Cabasan, Rhea Mae Luciano, Darryl Anthony Valiño, Lovely Joy Heyres, Hazel O. Arceo

Biological Sciences Faculty Publications

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[Introduction] Sablayan, situated on the western side of Mindoro Island facing the WPS (12.8564° N, 120.9101° E), is a first-class municipality in the province of Occidental Mindoro with a total land area of 2,188.8km² that is divided into 22 barangays, nine of which are along the coast. The coastline stretches for 115 km, with municipal waters covering approximately 750,000 km² (LGU-Sablayan 2008).

The Apo Reef Natural Park, one of its most prominent features, is located approximately 33 km off the coast (Figure 2.9-1) The Apo Reef Natural Park is a protected coral reef system under presidential proclamation 868 (1996) encompassing …

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State Of Coastal And Marine Resources: Lian, Batangas, Joseph Benedict T. Garcia, Mary Joyce P. Velos, Jemelyn Grace P. Baldisimo, Joey P. Cabasan, Ma Celina J. Añonuevo, Denmark B. Recamara, Hazel O. Arceo

Biological Sciences Faculty Publications

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[Introduction] Lian (13.9852° N, 120.6545° E) is a third-class municipality in the northwestern part of the province of Batangas. It is bounded on the north by the municipality of Nasugbu, on the east by the municipalities of Tuy and Balayan, on the west by the WPS, and on the south by the municipality of Catatagan (Figure 2.7-1). It has a total land area of 76.80km² that is divided into 19 barangays, six of which are coastal and two are integrated coastal barangays (LGU-Lian 2013). Its total population is 56,280 individuals in 15,991 households as of 2020 (PSA 2020).

The main …

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Advancing Household Robotics: Deep Interactive Reinforcement Learning For Efficient Training And Enhanced Performance, Arpita Soni, Sujatha Alla, Suresh Dodda, Hemanth Volikatla

Engineering Management & Systems Engineering Faculty Publications

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The market for domestic robots—made to perform household chore, is growing as these robots relieve people of everyday responsibilities. Domestic robots are generally welcomed for their role in easing human labour, in contrast to industrial robots, which are frequently criticised for displacing human workers. But before these robots can carry out domestic chores, they need to become proficient in a number of minor activities, such as recognizing their surroundings, making decisions, and picking up on human behaviours. Reinforcement learning, or RL, has emerged as a key robotics technology that enables robots to interact with their environment and learn how to …

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Improving Neuropathological Analysis With Aβgan: Addressing Morphology Imbalance For Efficient Alzheimer's Disease Diagnosis, Sujatha Alla, Prasanthi Chidipudi, Nagesh Bheesetty, Vedvikash Reddy Velur, Joshit Mohanty, Puneeth Bheesetty, Marisha Jmukhadze, Narendra Lakshmana Gowda, Sai Gireesh Komaragiri

Engineering Management & Systems Engineering Faculty Publications

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Histopathologists are experiencing a digital revolution in their field thanks to the digitization of Whole Slide Images (WSIs), which are microscope slides of tissue that can measure gigapixels in size. With so much high resolution data at their disposal, computer vision techniques can now be used to automate laboratory processes, create visual standards, and increase analysis throughput, all of which reduce the workload of pathologists [1]. The "gold" standard in neuropathology, particularly for Alzheimer's Disease- is pathological diagnosis made by looking at White Matter Inclusions (WSIs) in brain tissue. Semi-quantitative scoring in accordance with the standards established by the Consortium …

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An Analysis Of The Essential Understandings In Elementary Geometry And A Comparison To The Common Core Standards With Teaching Implications, Helen Crompton, Sarah Ferguson

STEMPS Faculty Publications

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Geometry and spatial reasoning form the foundations of learning in mathematics. However, geometry is a subject often ignored by curriculum writers and teachers until high school, leading to students lacking in critical skills in geometric reasoning. As the United States moves into a new curriculum epoch, heralding the commencement of the national common core standards (CCS), one could question if CCS in geometry align with the essential understandings children need to be successful geometric thinkers. This paper begins with an examination of the essential understandings of geometric reasoning leading to an interpretation and critique of the elementary geometry CCS. Finally, …

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Uncertainty Quantification In Large Language Models Through Convex Hull Analysis, Ferhat Ozgur Catak, Murat Kuzlu

Engineering Technology Faculty Publications

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Uncertainty quantification approaches have been more critical in large language models (LLMs), particularly high-risk applications requiring reliable outputs. However, traditional methods for uncertainty quantification, such as probabilistic models and ensemble techniques, face challenges when applied to the complex and high-dimensional nature of LLM-generated outputs. This study proposes a novel geometric approach to uncertainty quantification using convex hull analysis. The proposed method leverages the spatial properties of response embeddings to measure the dispersion and variability of model outputs. The prompts are categorized into three types, i.e., ’easy’, ’moderate’, and ’confusing’, to generate multiple responses using different LLMs at varying temperature settings. …

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On The Modes Of Nanosecond Pulsed Plasmas For Combustion Ignition Of Quiescent Ch₄-Air Mixtures, Chunqi Jiang, Akash C. Dhotre, Meimei Lai, Sayan Biswas, James R. Macdonald, Isaac W. Ekoto

Bioelectrics Publications

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The effect of transient plasma modes on ignition kernel development are discussed here for a quiescent CH₄-air combustion model system. A 10 ns high-voltage pulse was applied to a pin-to-pin electrode in lean fuel-air mixtures at room temperature and atmospheric pressure. High-impedance streamer, transient spark and low-impedance spark discharges were identified based on pulse waveforms of voltage and current. A sustained ignition kernel expansion was observed when the plasma discharge transitioned into a transient spark or spark discharge. The minimum ignition energy was obtained at the transient spark mode, which has less than a third of the energy …

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A Benchmark Framework For Data Visualization And Explainable Ai (Xai), Murat Kuzlu, Gokcen Ozdemir, Umut Ozdemir

Engineering Technology Faculty Publications

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This research introduces a benchmark framework, called EDUMX, designed for machine learning (ML)- based forecasting and XAI tasks, leveraging the Streamlit open-source Python library. The framework offers a comprehensive suite of functionalities, including data loading, feature selection, relationship analysis, data preprocessing, model selection, metric evaluation, training, and real-time monitoring. Users can easily upload data in diverse formats, explore relationships between variables, preprocess data using various techniques, and assess the performance of the ML model using customizable metrics. With its user-friendly interface, this framework offers invaluable insights for forecasting tasks in various domains, catering to the evolving needs of predictive analytics. …

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From Carnival Games To Plastic Filters: Preparing Elementary Preservice Teachers To Teach Engineering, Jennifer Kidd, Pilar Pazos, Kristie Gutierrez, Danielle Rhemer, Stacie Ringleb, Krishna Kaipa, Isaac Kumi, Orlando Ayala, Francisco Cima

Teaching & Learning Faculty Publications

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Preservice teachers (PSTs) in an educational foundations course were tasked with leading elementary students in an engineering design challenge. In order to explore different approaches for helping the PSTs develop competence in engineering education, two implementation methods were tested. In Spring 2022, PSTs collaborated with undergraduate engineering students to develop carnival-themed design challenge lessons. In Fall 2022, PSTs worked with their PST classmates to teach a professionally prepared engineering lesson focused on designing plastic filters. PSTs’ knowledge of engineering and engineering pedagogy were compared across the two semesters using an exploratory approach. Both groups showed increases in engineering knowledge and …

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Snow Spheres And Ice Cubes, John Adam

Mathematics & Statistics Faculty Publications

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This article, titled "Snow spheres and ice cubes," discusses the melting of snowballs and ice cubes. It explains that in standard calculus textbooks, it is shown that a snowball melting at a rate proportional to its surface area will have its radius decrease at a constant rate, assuming it remains spherical as it melts. The article then poses several questions related to this concept, including the proportion of a smaller snow sphere that remains when half of a larger one has melted, the value of p for which the smaller sphere first melts, and the volume reduction factor for cubes …

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Preface, Mohamed Mahdi Tekitek, Manfred Krafczyk, Li-Shi Luo

Mathematics & Statistics Faculty Publications

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[Introduction] Matter, conceptually classified into fluids and solids, can be completely described by the microscopic physics of its constituent atoms or molecules. However, for most engineering applications, a macroscopic or continuum description has usually been sufficient due to the large disparity between the spatial and temporal scales relevant to these applications and the scales of the underlying molecular dynamics. In this case, the microscopic physics merely determines material properties such as the viscosity of a fluid or the elastic constants of a solid. These material properties cannot be derived within the macroscopic framework, but the qualitative nature of the macroscopic …

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Towards Trust And Reputation As A Service In Society 5.0, Stephan Olariu, Ravi Mukkamala, Meshari Aljohani

Computer Science Faculty Publications

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Our paper was inspired by the recent Society 5.0 initiative of the Japanese Government which seeks to create a sustainable human-centric society by putting to work recent advances in technology. One of the key challenges in implementing Society 5.0 is providing trusted and secure services for everyone to use. Motivated by this challenge, this paper makes three contributions that we summarize as follows: Our first main contribution is to propose a novel blockchain and smart contract-based trust and reputation service design to reduce the uncertainty associated with buyer feedback in marketplaces that we expect to see in Society 5.0. Our …

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An Objective Assessment Of Neuromotor Control Using A Smartphone App After Repeated Subconcussive Blast Exposure, Charlend K. Howard, Masahiro Yamada, Marcia Dovel, Rie Leverett, Alexander Hill, Kenneth A. Manlapaz, David O. Keyser, Rene S. Hernandez, Sheilah S. Rowe, Walter S. Carr, Michael S. Roy, Christopher K. Rhea

Rehabilitation Sciences Faculty Publications

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Subconcussive blast exposure has been shown to alter neurological functioning. However, the extent to which neurological dysfunction persists after blast exposure is unknown. This longitudinal study examined the potential short- and long-term effects of repeated subconcussive blast exposure on neuromotor performance from heavy weapons training in military personnel. A total of 214 participants were assessed; 137 were exposed to repeated subconcussive blasts and 77 were not exposed to blasts (controls). Participants completed a short stepping-in-place task while an Android smartphone app placed on their thigh recorded movement kinematics. We showed acute suppression of neuromotor variability 6 h after subconcussive blast …

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Sub-Band Backdoor Attack In Remote Sensing Imagery, Kazi Aminul Islam, Hongyi Wu, Chunsheng Xin, Rui Ning, Liuwan Zhu, Jiang Li

Electrical & Computer Engineering Faculty Publications

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Remote sensing datasets usually have a wide range of spatial and spectral resolutions. They provide unique advantages in surveillance systems, and many government organizations use remote sensing multispectral imagery to monitor security-critical infrastructures or targets. Artificial Intelligence (AI) has advanced rapidly in recent years and has been widely applied to remote image analysis, achieving state-of-the-art (SOTA) performance. However, AI models are vulnerable and can be easily deceived or poisoned. A malicious user may poison an AI model by creating a stealthy backdoor. A backdoored AI model performs well on clean data but behaves abnormally when a planted trigger appears in …

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Adversarial Training Based Domain Adaptation Of Skin Cancer Images, Syed Qasim Gilani, Muhammad Umair, Maryam Naqvi, Oge Marques, Hee-Cheol Kim

Electrical & Computer Engineering Faculty Publications

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Skin lesion datasets used in the research are highly imbalanced; Generative Adversarial Networks can generate synthetic skin lesion images to solve the class imbalance problem, but it can result in bias and domain shift. Domain shifts in skin lesion datasets can also occur if different instruments or imaging resolutions are used to capture skin lesion images. The deep learning models may not perform well in the presence of bias and domain shift in skin lesion datasets. This work presents a domain adaptation algorithm-based methodology for mitigating the effects of domain shift and bias in skin lesion datasets. Six experiments were …

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Ethical Decision-Making In Older Drivers During Critical Driving Situations: An Online Experiment, Amandeep Singh, Sarah Yahoodik, Yovela Murzello, Samuel Petkac, Yusuke Yamani, Siby Samuel

Psychology Faculty Publications

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The present study examined the impact of aging on ethical decision-making in simulated critical driving scenarios. 204 participants from North America, grouped into two age groups (18–30 years and 65 years and above), were asked to decide whether their simulated automated vehicle should stay in or change from the current lane in scenarios mimicking the Trolley Problem. Each participant viewed a video clip rendered by the driving simulator at Old Dominion University and pressed the space-bar if they decided to intervene in the control of the simulated automated vehicle in an online experiment. Bayesian hierarchical models were used to analyze …

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Leveraging Machine Learning To Study How Temperature Scores Predict Pre-Term Birth Status, Erich Seamon, Jennifer A. Mattera, Sarah A. Keim, Esther M. Leerkes, Jennifer L. Rennels, Andrea J. Kayl, Kristy M. Kulhanek, Darcia Narvaez, Sarah M. Sanborn, Jennifer B. Grandits, Christine Dunkel Schetter, Mary Coussons-Read, Amanda R. Tarullo, Sarah J. Schoppe-Sullivan, Mariah E. Thomason, Julie M. Braungart-Rieker, Julie C. Lumeng, Shannon N. Lenze, Lisa M. Christian, Darby E. Saxbe, Laura R. Stroud, Christina M. Rodriguez, Stephanie Anzaman-Frasca

Psychology Faculty Publications

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Background

Preterm birth (birth at <37 completed weeks gestation) is a significant public heatlh concern worldwide. Important health, and developmental consequences of preterm birth include altered temperament development, with greater dysregulation and distress proneness.

Aims

The present study leveraged advanced quantitative techniques, namely machine learning approaches, to discern the contribution of narrowly defined and broadband temperament dimensions to birth status classification (full-term vs. preterm). Along with contributing to the literature addressing temperament of infants born preterm, the present study serves as a methodological demonstration of these innovative statistical techniques.

Study design

This study represents a metanalysis conducted with multiple samples (N = 19) including preterm (n = 201) children and (n = 402) born at term, with data combined across investigations to perform classification analyses.

Subjects …

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Urban Flood Extent Segmentation And Evaluation From Real-World Surveillance Camera Images Using Deep Convolutional Neural Network, Yidi Wang, Yawen Shen, Behrouz Salahshour, Mecit Cetin, Khan Iftekharuddin, Navid Tahvildari, Guoping Huang, Devin K. Harris, Kwame Ampofo, Jonathan L. Goodall

Civil & Environmental Engineering Faculty Publications

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This study explores the use of Deep Convolutional Neural Network (DCNN) for semantic segmentation of flood images. Imagery datasets of urban flooding were used to train two DCNN-based models, and camera images were used to test the application of the models with real-world data. Validation results show that both models extracted flood extent with a mean F1-score over 0.9. The factors that affected the performance included still water surface with specular reflection, wet road surface, and low illumination. In testing, reduced visibility during a storm and raindrops on surveillance cameras were major problems that affected the segmentation of flood extent. …

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Small-Strain Site Response Of Soft Soils In The Sacramento-San Joaquin Delta Region Of California Conditioned On Vₛ₃₀ And Mhvsr, Tristan E. Buckreis, Jonathan P. Stewart, Scott J. Brandenberg, Pengfei Wang

Civil & Environmental Engineering Faculty Publications

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Sites located in the Sacramento-San Joaquin Delta region of California typically have peaty-organic soils near the ground surface, which are characteristically soft, with shear wave velocities as low as 30 m/s. These unusually soft geotechnical conditions, which are outside the range of applicability of existing ergodic site amplification models, can be anticipated to produce significant site effects during earthquake shaking. We evaluate site response for 36 seismic stations in the Delta region using non-ergodic methods with low-amplitude ground motion data. We model first-order site effects using a period-dependent relation conditioned on the 30 m time-averaged shear wave velocity (V …

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A Review On Biochar As An Adsorbent For Pb(Ii) Removal From Water, Pushpita Kumkum, Sandeep Kumar

Civil & Environmental Engineering Faculty Publications

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Heavy metal contamination in drinking water is a growing concern due to its severe health effects on humans. Among the many metals, lead (Pb), which is a toxic and harmful element, has the most widespread global distribution. Pb pollution is a major problem of water pollution in developing countries and nations. The most common sources of lead in drinking water are lead pipes, faucets, and plumbing fixtures. Adsorption is the most efficient method for metal removal, and activated carbon has been used widely in many applications as an effective adsorbent, but its high production costs have created the necessity for …

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Investigating The Viability Of Low Frequency Mhvsr Estimates Using Deep Shear Wave Velocity Profile, T. Mai, C. C. Nweke, P. Wang, F. J. Ornelas

Civil & Environmental Engineering Faculty Publications

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Site response describes the alterations of seismic energy due to its interaction with subsurface geological interfaces and structures, which is usually estimated by one dimensional (1D) ground response analysis (GRA). However, 1D GRA requires subsurface information (e.g., shear wave velocity profile), which makes it not widely applicable, particularly for the sites where subsurface information is unavailable. Alternatively, the microtremor horizontal-to-vertical spectral ratio (mHVSR) from three-component recordings of ambient noise on the ground surface is easily measured and is believed to have the potential for site response prediction (the peaks in mHVSR are strongly associated with the site resonant frequencies). However,the …

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Contribution Of High Turbidity To Tidal Dynamics In A Curved Channel In Zhoushan Islands, China, Li Li, Fangzhou Shen, Zhiguo He, Gangfeng Ma, Jiachen Wang, Kailong Huangfu

Civil & Environmental Engineering Faculty Publications

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The curved tidal channel, Luotou Deep-water Navigational Channel, is the main channel of the Ningbo Zhoushan Port, which is ranked first in the world. Tidal dynamics in the channel are spatially and temporally asymmetric. In this study, the three-dimensional tidal dynamics in the channel were analyzed using field data and simulated using FVCOM. The results show that the tides in the channel flood/ebb along the northern/southern bank near the bottom/surface layer and these asymmetries are due to the imbalanced Coriolis force, centrifugal force, sea-level gradient, and density gradient. Residual current velocity peaks (0.7 m/s) in the middle of the channel …

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Electrospun Pt-Tio₂ Nanofibers Doped With Hpa For Catalytic Hydrodeoxygenation, Amos Taiswa, Randy L. Maglinao, Jessica M. Andriolo, Sandeep Kumar, Jack L. Skinner

Civil & Environmental Engineering Faculty Publications

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Electrospinning is utilized to fabricate catalytic nanofiber scaffold for biocrude upgrading in hydrodeoxygenation (HDO) following computational studies suggesting the need for nano-catalysts for efficient HDO conversion and selectivity. Here, Pt-TiO₂ nanofibers are fabricated through electrospinning, followed by wet impregnation with a heteropoly acid (HPA), tungstosilicic acid. Intensive heat treatments were incorporated during and after processes to obtain a HPA doped Pt-TiO₂ nano-catalyst. Catalytic HDO was performed in a batch reactor with phenol as the raw biocrude dissolved in hexadecane. The HPA doped Pt-TiO₂ catalyst demonstrated promising HDO performance of 37.2% conversion and a 78.9% selectivity to oxygen …

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Modeling Coupled Driving Behavior During Lane Change: A Multi-Agent Transformer Reinforcement Learning Approach, Hongyu Guo, Mehdi Keyvan-Ekbatani, Kun Xie

Civil & Environmental Engineering Faculty Publications

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In a lane change (LC) scenario, the lane change vehicle interacts with surrounding vehicles. The interactions not only affect their driving behaviors but also influence the traffic flow. This study aims to model the coupled behavior of the lane changer and the follower in the target lane during LC. Large-scale real-world connected vehicle (CV) data from the Safety Pilot Model Deployment (SPMD) program are used to extract LCs and study vehicle interactions. A multi-agent Transformer-based deep deterministic policy gradient (MA-TDDPG) method is proposed to model the coupled behaviors during LC. The multi-agent framework can handle the multiple agents’ behaviors with …

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A General Framework For Modeling Subregional Path Effects, T. E. Buckreis, P. Wang, S. J. Brandenberg, J. P. Stewart

Civil & Environmental Engineering Faculty Publications

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Next Generation Attenuation (NGA) West2 ground motion models (GMMs) include regional path adjustments for broad jurisdictional regions, which necessarily averages spatially variable path effects within those regions. We extend that framework to account for systematic variations in attenuation within subregions defined in consideration of geologic differences. In recent years, cell-based methods which systematically account for spatial variations by summing the attenuation effects over a fine discretization of uniform-rectangular cells (e.g., Dawood and Rodriquez-Marek 2013; Kuehn et al. 2019) have been shown to be an effective alternative to regionalization and a step towards modelling non-ergodic path effects. The main drawbacks of …

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Integrating Climatological-Hydrodynamic Modeling And Paleohurricane Records To Assess Storm Surge Risk, Amirhosein Begmohammadi, Christine Y. Blackshaw, Ning Lin, Avantika Gori, Elizabeth Wallace, Kerry Emanuel, Jeffrey P. Donnelly

OES Faculty Publications

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Sediment cores from blue holes have emerged as a promising tool for extending the record of long-term tropical cyclone (TC) activity. However, interpreting this archive is challenging because storm surge depends on many parameters including TC intensity, track, and size. In this study, we use climatological-hydrodynamic modeling to interpret paleohurricane sediment records between 1851 and 2016 and assess the storm surge risk for Long Island in The Bahamas. As the historical TC data from 1988 to 2016 is too limited to estimate the surge risk for this area, we use historical event attribution in paleorecords paired with synthetic storm modeling …

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Last Millennium Hurricane Activity Linked To Endogenous Climate Variability, Wenchang Yang, Elizabeth Wallace, Gabriel A. Vecchi, Jeffrey P. Donnelly, Julien Emile-Geay, Gregory J. Hakim, Larry W. Horowitz, Richard M. Sullivan, Robert Tardif, Peter J. Van Hengstum, Tyler S. Winkler

OES Faculty Publications

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Despite increased Atlantic hurricane risk, projected trends in hurricane frequency in the warming climate are still highly uncertain, mainly due to short instrumental record that limits our understanding of hurricane activity and its relationship to climate. Here we extend the record to the last millennium using two independent estimates: a reconstruction from sedimentary paleohurricane records and a statistical model of hurricane activity using sea surface temperatures (SSTs). We find statistically significant agreement between the two estimates and the late 20th century hurricane frequency is within the range seen over the past millennium. Numerical simulations using a hurricane-permitting climate model suggest …

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Integrating Climatological-Hydrodynamic Modeling And Paleohurricane Records To Assess Storm Surge Risk, Amirhosein Begmohammadi, Christine Y. Blackshaw, Ning Lin, Avantika Gori, Elizabeth Wallace, Kerry Emanuel, Jeffrey P. Donnelly

OES Faculty Publications

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Sediment cores from blue holes have emerged as a promising tool for extending the record of long-term tropical cyclone (TC) activity. However, interpreting this archive is challenging because storm surge depends on many parameters including TC intensity, track, and size. In this study, we use climatological-hydrodynamic modeling to interpret paleohurricane sediment records between 1851 and 2016 and assess the storm surge risk for Long Island in The Bahamas. As the historical TC data from 1988 to 2016 is too limited to estimate the surge risk for this area, we use historical event attribution in paleorecords paired with synthetic storm modeling …

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Re-Evaluating Hydrogen Sulfide As A Sink For Cadmium And Zinc In The Oxic To Suboxic Upper Water Column Of The Pacific Ocean, N. R. Buckley, E. E. Black, J. A. Kenyon, N. T. Lanning, M. Sieber, T. M. Conway, J. N. Fitzsimmons, G. A. Cutter

OES Faculty Publications

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Hydrogen sulfide is produced by heterotrophic bacteria in anoxic waters and via carbonyl sulfide hydrolysis and phytoplankton emissions under oxic conditions. Apparent losses of dissolved cadmium (dCd) and zinc (dZn) in oxygen minimum zones (OMZs) of the Atlantic and Pacific Oceans have been attributed to metal-sulfide precipitation formed via dissimilatory sulfate reduction. It has also been argued that such a removal process could be a globally important sink for dCd and dZn. However, our studies from the North Pacific OMZ show that dissolved and particulate sulfide concentrations are insufficient to support the removal of dCd via precipitation. In contrast, apparent …

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