Digital Commons Network^™

Brain-Adapter: Enhancing Neurological Disorder Analysis With Adapter-Tuning Multimodal Large Language Models, Jing Zhang, Xiaowei Yu, Yanjun Lyu, Lu Zhang, Tong Chen, Chao Cao, Yan Zhuang, Minheng Chen, Tianming Liu, Dajiang Zhu

Computer Science Faculty Research & Creative Works

Understanding brain disorders is crucial for accurate clinical diagnosis and treatment. Recent advances in Multimodal Large Language Models (MLLMs) offer a promising approach to interpreting medical images with the support of text descriptions. However, previous research has primarily focused on 2D medical images, leaving richer spatial information of 3D images under-explored, and single-modality-based methods are limited by overlooking the critical clinical information contained in other modalities. To address this issue, this paper proposes Brain-Adapter, a novel approach that incorporates an extra bottleneck layer to learn new knowledge and instill it into the original pre-trained knowledge. The major idea is to …

Exploring The Trade-Offs: Unified Large Language Models Vs Local Fine-Tuned Models For Highly-Specific Radiology Nli Task, Zihao Wu, Lu Zhang, Chao Cao, Xiaowei Yu, Zhengliang Liu, Lin Zhao, Yiwei Li, Haixing Dai, Chong Ma, Gang Li, Wei Liu, Quanzheng Li, Dinggang Shen, Xiang Li, Dajiang Zhu, Tianming Liu

Computer Science Faculty Research & Creative Works

Recently, ChatGPT and GPT-4 have emerged and gained immense global attention due to their unparalleled performance in language processing. Despite demonstrating impressive capability in various open-domain tasks, their adequacy in highly specific fields like radiology remains untested. Radiology presents unique linguistic phenomena distinct from open-domain data due to its specificity and complexity. Assessing the performance of large language models (LLMs) in such specific domains is crucial not only for a thorough evaluation of their overall performance but also for providing valuable insights into future model design directions: whether model design should be generic or domain specific. To this end, in …

Pregnancy And Postpartum Effects Of Electronic Cigarettes On Maternal Health And Vascular Function In The Fourth Trimester, Amber Mills, Duaa Dakhlallah, Anand Ranpara, W. Travis Goldsmith, Paul D. Chantler, Yue-Wern Huang, Jonathan Boyd, I. Mark Olfert

Biological Sciences Faculty Research & Creative Works

Pregnancy is a vulnerable time with significant cardiovascular changes that can lead to adverse outcomes, which can extend into the postpartum window. Exposure to emissions from electronic cigarettes (Ecig), commonly known as "vaping," has an adverse impact on cardiovascular function during pregnancy and post-natal life of offspring, but the postpartum effects on maternal health are poorly understood. We used a Sprague Dawley rat model, where pregnant dams are exposed to Ecigs between gestational day (GD)2-GD21 to examine postpartum consequences. Litter and dam health were monitored during the weaning period, and maternal vascular and endocrine function were assessed after weaning. Exposure …

On The Sharpness Of A Korn’S Inequality For Piecewise H1 Space And Its Applications, Qingguo Hong, Young Ju Lee, Jinchao Xu

Mathematics and Statistics Faculty Research & Creative Works

In this paper, we investigate the sharpness of a Korn's inequality for piecewise H1 space and its applications. We first revisit a Korn's inequality for the piecewise H1 space based on general polygonal or polyhedral decompositions of the domain. We express the Korn's inequality with minimal jump terms. Then we prove that such minimal jump conditions are sharp for achieving the Korn's inequality. The sharpness of the Korn's inequality and explicitly given minimal conditions can be used to test whether any given finite element spaces satisfy Korn's inequality, immediately as well as to build or modify nonconforming finite elements for …

Estimation And Model Misspecification For Recurrent Event Data With Covariates Under Measurement Errors, Ravinath Alahakoon, Gideon K.D. Zamba, Xuerong Meggie Wen, Akim Adekpedjou

Mathematics and Statistics Faculty Research & Creative Works

For subject i, we monitor an event that can occur multiple times over a random observation window [0, (Formula presented.)). At each recurrence, p concomitant variables, (Formula presented.), associated to the event recurrence are recorded—a subset ((Formula presented.)) of which is measured with errors. To circumvent the problem of bias and consistency associated with parameter estimation in the presence of measurement errors, we propose inference for corrected estimating equations with well-behaved roots under an additive measurement errors model. We show that estimation is essentially unbiased under the corrected profile likelihood for recurrent events, in comparison to biased estimations under a …

Multi-Valued Variational Inequalities For Variable Exponent Double Phase Problems: Comparison And Extremality Results, Siegfried Carl, Vy Khoi Le, Patrick Winkert

Mathematics and Statistics Faculty Research & Creative Works

We prove existence and comparison results for multi-valued variational inequalities in a bounded domain Ω of the form (Formula presented.) where A:W1,H(Ω)→W1,H(Ω)∗ given by (Formula presented.) for u∈W1,H(Ω), is the double phase operator with variable exponents and W1,H(Ω) is the associated Musielak–Orlicz Sobolev space. First, an existence result is proved under some weak coercivity condition. Our main focus aims at the treatment of the problem under consideration when coercivity fails. To this end we establish the method of sub–super-solution for the multi-valued variational inequality in the space W1, H(Ω) based on appropriately defined sub- and super-solutions, which yields the existence …

Pervasive Sensing To Correlate Vehicle Driving Behavior With City-Scale Traffic Dynamics, Debasree Das, Shameek Bhattacharjee, Sandip Chakraborty, Bivas Mitra, Sajal K. Das

Computer Science Faculty Research & Creative Works

Individual driving behavior is a pivotal element that shapes the overall traffic dynamics in a city. In this work, we study and analyze the complex web of relationships between individual driving behaviors and their impact on the overall traffic dynamics of a smart city with two primary objectives: first, understanding the spatial interaction between individual vehicles and their impact on each other, and second, finding anomalous driving behaviors, which lead to congestion and traffic incidents. Specifically, we introduce an overarching modular framework investigating human factors of driver characteristics, vehicle attributes, geographical terrain surrounding the road infrastructure, and environmental conditions. Analyzing …

Performance And Economic Evaluation Of Asphalt-Based High Friction Surface Treatment (Hfst) Applications, Alireza Roshan, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

High Friction Surface Treatments (HFSTs) are recognized for enhancing friction between tires and road surfaces, with reduced road accidents being a key benefit. Epoxy-based HFSTs, though widely used, come with challenges like compatibility issues with existing pavements, higher installation and removal costs, and reduced durability tied to substrate quality. Recently, state agencies have increasingly focused on developing asphalt-based alternative binders for HFST applications as highlighted in the National Cooperative Highway Research Program (NCHRP) RFP #NCHRP 10-145. This study introduces asphalt-based HFSTs as an alternative to traditional epoxy-based treatments. Various aggregate types were examined for friction performance and the effect of …

Existence Results For A Discrete Fractional Boundary Value Problem, David Barilla, Martin Bohner, Giuseppe Caristi, Shapour Heidarkhani, Shahin Moradi

Mathematics and Statistics Faculty Research & Creative Works

In this study, we investigate the existence of at least one solution and the existence of an infinite number of solutions for a discrete fractional boundary value problem. Requiring an algebraic condition on the nonlinear term for small values of the parameter and requiring an additional asymptotical behavior of the potential at zero, we investigate the existence of at least one nontrivial solution for the problem. Moreover, under suitable assumptions on the oscillatory behavior of the nonlinearity at infinity, for exact collections of the parameter, we discuss the existence of a sequence of solutions for the problem. We also present …

Analyzing Micrometeoroid And Orbital Debris Shield Performance For Sample Return Spacecraft, William P. Schonberg, Michael Squire

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Sample-return missions typically seek to collect and return samples from extraterrestrial locations to Earth for analysis. The return of samples from certain locations in the solar system represents a potential hazard to Earth's biosphere from foreign microorganisms. One way this could occur would be a break-up of the returning capsule during entry (which would disperse the samples through the air) due to undetected damage to the capsule thermal protection system (TPS). As a result, missions that plan to return payloads from some destinations are likely to have certain design requirements for the TPS surrounding their returning capsules, which may include …

Class-Wise Histogram Matching-Based Domain Adaptation In Deep Learning-Based Bridge Element Segmentation, Tarutal Ghosh Mondal, Zhenhua Shi, Haibin Zhang, Genda Chen

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study focused on the problem of domain shift in deep learning-based bridge element segmentation. The impracticability of accounting for all possible variabilities vis-à-vis structural shape, size, color, texture, illumination, and other operational conditions in the training process leads to the deterioration in the model performance when applied to test data from novel unseen domains. In such situations, rebuilding the model with labeled training data from the target domain becomes prohibitively expensive and time-consuming in many practical cases. Recent advancements in unsupervised domain adaptation techniques are known to provide viable solutions to this problem. However, it was observed in this …

Challenges In Numerical Simulation Of Frost Heave, Antai Dong, Xiong Zhang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Frost heave of soil extensively exists in northern regions and poses a significant threat to infrastructure in cold regions. Despite over a century of research, challenges persist in numerically simulating frost heave. This study addresses two key issues: (1) What is the primary driving force for liquid water transfer during the freezing process? (2) How can we correctly represent unfrozen water content? Critical insights are derived from the theoretical analysis of coupled hydrothermal migration during soil freezing processes, followed by a case simulation using COMSOL Multiphysics. It concludes that of the water content gradient, suction gradient, and hydraulic gradient, only …

Floquet Theory For First-Order Delay Equations And An Application To Height Stabilization Of A Drone’S Flight, Martin Bohner, Alexander Domoshnitsky, Oleg Kupervasser, Alex Sitkin

Mathematics and Statistics Faculty Research & Creative Works

In this paper, we proposed a version of the Floquet theory for delay differential equations. We demonstrated that very natural assumptions for control in technical applications can lead us to a one-dimensional fundamental system. This approach allowed researchers to work with classical methods used in the case of ordinary differential equations. On this basis, new original unexpected results on the exponential stability were proposed. For example, in the equation x' (4)+a(t)x(t—-T(7)) = 0, t € [0, co), we avoided the assumption on the smallness of the product sup,j9,.) 41 SUP;< {9,00) TD) < 3/2 for asymptotic stability. We obtained that in the case of w-periodic coefficient and delay, the fact that the period w was situated in a corresponding interval can lead to exponential stability. We then applied our new tests of stability to the stabilization of a drone's flight, where smallness of the noted above product could not be achieved from a technical point of view. For an equation with periodic coefficient and delay, we got a formula of the solution's representation on the semiaxis.

A Unified Concept Of Periodicity On Any Time Scale And Applications, Martin Bohner, Jaqueline G. Mesquita, Sabrina H. Streipert

Mathematics and Statistics Faculty Research & Creative Works

We introduce a novel definition of periodicity on arbitrary time scales, dependent on a strictly increasing and differentiable function. This removes the commonly used and restrictive assumption of a periodic time scale to define periodic functions. Our new definition furthermore allows for a wider class of functions to be studied using the theory of periodic systems. After providing crucial properties of these periodic functions, such as the translation invariance of integrals of periodic functions, we apply the concept of this new periodicity to linear dynamic equations. We provide necessary and sufficient conditions for a linear dynamic equation to have such …

Hydraulic Connectivity And Hydrochemistry Influence Microbial Community Structure In Agriculturally Affected Alluvial Aquifers In The Midwestern United States, Hunter W. Schroer, Kendra Markland, Fangqiong Ling, Craig L. Just

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Alluvial aquifers can provide ecosystem services and drinking water but much remains unknown about human effects on aquifer microbiomes. Therefore, we used amplicon sequencing and hydro chemical characterization to pair microbial communities with environmental conditions across 37 alluvial aquifer wells. The study region spanned eastern Iowa and southern Minnesota (USA) and contained a combination of drinking water and monitoring wells. In terms of microbial ecology, dominant phyla across the wells included Proteobacteria, Bacteroidota, Patescibacteria, Planctomycetota, and Nitrospirota. Tritium, an indicator of infiltration and surface water influence, was the highest correlated variable with the Shannon index (α-diversity) by the Spearman rank …

Forecasting State-Level Construction Labor Earnings For Enhanced Project Cost Control: An Econometric And Deep-Learning Analysis Of The Leading Economic Indicators, Ahmed Shiha, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

As a major input to several work packages, the labor element constitutes a critical component for successful performance of construction projects. Localized labor shortages, fundamental changes in prevailing wage laws, and historical shifts in the unionization rates of construction workers impair the adequate estimation of construction labor costs in diverse labor market dynamics. Meanwhile, existing studies have utilized national-level indicators to study the trends of construction labor costs, but the relationship between the multifaceted local economic factors and state-level construction labor costs remains understudied. This paper fills such a knowledge gap. A three-stage methodology is adopted: (1) data collection of …

Enhanced Kneser-Type Oscillation Criteria For Second-Order Functional Quasilinear Dynamic Equations On Time Scales, Taher S. Hassan, Elvan Akın, Bassant M. El-Matary, Ioan Lucian Popa, Mouataz Billah Mesmouli, Ismoil Odinaev, Akbar Ali

Mathematics and Statistics Faculty Research & Creative Works

This work presents new Kneser-type oscillation criteria for second-order quasilinear functional dynamic equations defined on arbitrary unbounded above time scales. Our approach employs the Riccati transformation technique in conjunction with the integral averaging method. The results show a significant improvement over recent Kneser-type oscillation criteria. We provided several illustrative examples to highlight the importance of our findings.

An Improved Table Method For Coded Target Identification With Application To Photogrammetric Analysis Of Soil Specimen During Triaxial Testing, Xiaolong Xia, Xiong Zhang, Sara Fayek, Zhaozheng Yin

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Accurate and efficient recognition and identification of coded targets are of great importance in coded target-based photogrammetry. Recently, a deep learning-based method has been utilized to recognize the coded targets. Then, a table method has been developed to decode the coded targets, identify falsely identified coded targets, and recover missing coded targets. This method takes advantage of the geometric arrangement of the coded targets. In this paper, an improved table method has been developed to improve the coded targets recognition and identification results. Blob analysis, instead of deep learning, is utilized to recognize coded targets. Then, the RANSAC algorithm was …

Using Telemetry To Assess Operator Effects On Hydraulic Shovel Energy Efficiency. Part Ii: Assessing Operator Effects, Noah Adekunle Aluko, Kwame Awuah-Offei

Mining Engineering Faculty Research & Creative Works

In this second part of a two-part series, this study investigates whether operator practices significantly affect the energy efficiency of hydraulic shovels, using detailed telemetry data. Rather than assuming this relationship, the research systematically tests it through a combination of statistical and regression analyses. First, Welch's and Kruskal–Wallis ANOVA confirm that operators differ significantly in their energy efficiency (p = 0.0000). Next, correlation analysis links parameters identified in Part I to energy per unit loading rate, and difference regression analysis determines which parameters most strongly influence efficiency variations. The results show that differences in payloads are the primary driver of …

Understanding The Usefulness Of Self-Escape Technologies In Underground Mining: Perspectives Of Metal/Nonmetal Miners, Eugene A. Gyawu, Kwame Awuah-Offei, D. A. Baker

Mining Engineering Faculty Research & Creative Works

Research on mine self-escape often focuses on coal mining, while perspectives from underground metal/nonmetal miners remain understudied despite their distinct emergency response challenges and unique operating environments. Using a scenario-based survey approach, this study evaluated underground metal/nonmetal miners' perceptions of the usefulness of 18 hypothetical self-escape interventions and how these perceptions are influenced by worker characteristics. Employment type was the strongest predictor of usefulness ratings, with hourly employees rating several self-escape interventions significantly higher than salaried employees, including those related to improving self-contained self-rescuers (SCSRs) and tethered guidance systems. The data suggested potential trends where perceived usefulness increased with more …

Cracking The Code: Harnessing Serpentinization-Driven Micro-Crack Networks For Hydrogen Generation And Subsurface Resource Recovery, U. Mutlu, G. Boitnott, A. Lisjak, J. Ha, O. Mahabadi, P. Connolly, B. N. Tunnell, T. Sherizadeh, S. Nowak, J. E. Olson

Mining Engineering Faculty Research & Creative Works

This study focuses on simulating volume-increasing processes caused by natural hydrogen-generating serpentinization, a reaction in which olivine and pyroxene typically transform into serpentine minerals. The volume increase leads to crack propagation along grain interfaces and new crack generation within unreacted crystals (aka grains). The interplay between thermo-hydro-mechanicalchemical (THMC) conditions plays a critical role in the initiation, propagation, and coalescence of various fracture surfaces, which enhances permeability and can accelerate serpentinization and hydrogen production rates. In the scenarios considered, chemical reactions between formation brine and reactive minerals result in volumetric expansion, generating stress and promoting the propagation of micro-cracks. Our results …

A New Formulation Of Hardy-Type Dynamic Inequalities On Time Scales, Martin Bohner, Irena Jadlovská, Ahmed I. Saied

Mathematics and Statistics Faculty Research & Creative Works

In this paper, we introduce a novel formulation of dynamic Hardy-type inequalities on a time scale, motivated by a recently established convexity approach in the Haar measure. The classical Hardy inequality is refined so that the classical Lebesgue-measure constant is replaced by the sharp constant 1. We obtain time-scale analogues on finite intervals with best constants, and, for nonincreasing and nondecreasing functions, reversed inequalities with explicit weights described by incomplete β-functions. To establish our results, we employ two distinct time scales and apply the chain rule, together with the substitution rule, the derivative of inverse functions, and Fubini's theorem for …

Active Phytoextraction Of Toluene Shifts The Microbiome And Enhances Degradation Capacity In Hybrid Poplar, Michael Benisrael, Dasiel Obregon, Philipp Wanner, Jeremy Fernandes, Joel G. Burken, Ramon Aravena, Beth L. Parker, Elizabeth A. Haack, David T. Tsao, Kari E. Dunfield

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Hybrid poplars are widely recognized for their effectiveness in remediating subsurface aromatic hydrocarbon contaminants, including benzene, toluene, ethylbenzene, and xylene isomers (BTEX). While BTEX compounds are frequently found in the transpiration streams of poplars at contaminated sites, the microbial dynamics within these trees, particularly in response to hydrocarbon exposure, remain underexplored. This study utilized high-throughput amplicon sequencing to investigate the trunk microbiome in hybrid poplars at a field-scale toluene phytoremediation site. Across the plant growth season (spring to late summer), we observed a significant seasonal increase in bacterial diversity and richness, particularly in trees located in areas with the highest …

Remenet: A Memory-Enhanced Gan Model For Intrusion Detection In Transportation Cyber-Physical Systems, Xin Wang, Lianbo Ma, Sajal K. Das, Zhonghua Liu

Computer Science Faculty Research & Creative Works

Ensuring the safety and reliability of Transportation Cyber-Physical Systems (T-CPS) is critical. However, the increasing interconnectedness of T-CPS exposes them to sophisticated cyberattacks, necessitating robust intrusion detection systems (IDS) to safeguard against evolving threats. This paper aims to enhance the security of T-CPS by addressing two key challenges: effective anomaly detection and handling imbalanced datasets in intrusion detection tasks. In this paper, we propose ReMeNet (Reconstruction Memory Network), a novel intrusion detection model that combines a memory module with a GAN-based architecture to enhance anomaly detection and data reconstruction. To address the challenge of imbalanced datasets, we incorporate a Vector …

Isolation And Characterization Of A Halophilic, Extremely Acidophilic, Iron-Oxidizing Bacterium, Connor Crites

Masters Theses

This thesis describes the isolation and characterization of a halophilic iron- oxidizing bacterium from sediments obtained from Lake Magic; an extremely acidic, saline lake located in Western Australia. The purpose for the isolation of novel, halotolerant/halophilic iron-oxidizing bacteria is to aid in metal-mining bioleaching operations. Currently used iron- and sulfur-oxidizing bacteria are extremely sensitive to chloride, which restricts their use in these industries.

A singular bacterial morphology was isolated from Lake Magic sediments that was roundly-rod shaped, 1-2 um in length, and stained Gram-negative. This organism was able to grow in a modified medium (DSM14174) using ferrous sulfate as an …

Auto-Tuning And Applications Of Transient Voltage Suppressor Models In Full-Wave Simulations, Daniel Peter Szanto

Masters Theses

System efficient electrostatic design (SEED) combines full-wave geometry information with SPICE models of non-linear protection devices, typically transient voltage suppression (TVS) diodes, to allow optimization and validation of electrostatic design (ESD) protection early in the design process. TVS models have previously been developed which may be used in SPICE simulation tools like Keysight ADS, but these models could not be used directly in full-wave simulation tools like CST Studio. A process was developed for converting existing ADS models of TVS devices to a form that can be used within a CST full wave/SPICE hybrid simulation. Three TVS models were converted …

Fast Demodulation Of Ofdr-Based Distributed Sensing Based On Enhanced Buneman Frequency Estimation, Zhaopeng Zhang, Bo Liu, Xiao Liu, Caiyun Li, Osamah Alsalman, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

Aiming at realizing high-efficiency distributed strain sensing through optical frequency domain reflectometry (OFDR), this paper introduces a fast demodulation algorithm to determine strain-induced spectral shifts from coarse Rayleigh backscattering (RBS) cross-correlation spectra. The proposed approach employs an enhanced Buneman frequency estimation (BFE) algorithm, enabling direct spectral shift analysis across coarse signals. By applying this algorithm, the need for dense interpolation in the conventional cross-correlation demodulation process - typically required for a finer spectral sampling interval but at the cost of demodulation efficiency - can be eliminated. Both theoretical analysis and experimental investigation reveal the equivalence of the BFE and conventional …

Ms-Yolo: Infrared Object Detection For Edge Deployment Via Mobilenetv4 And Slideloss, Jiali Zhang, Thomas S. White, Haoliang Zhang, Wenqing Hu, Donald C. Wunsch, Jian Liu

Mathematics and Statistics Faculty Research & Creative Works

Infrared imaging has emerged as a robust solution for urban object detection under low-light and adverse weather conditions, offering significant advantages over traditional visible-light cameras. However, challenges such as class imbalance, thermal noise, and computational constraints can significantly hinder model performance in practical settings. To address these issues, we evaluate multiple YOLO variants on the FLIR ADAS V2 dataset, ultimately selecting YOLOv8 as our baseline due to its balanced accuracy and efficiency. Building on this foundation, we present MS-YOLO (MobileNetv4 and SlideLoss based on YOLO), which replaces YOLOv8's CSPDarknet backbone with the more efficient MobileNetV4, reducing computational overhead by 1.5% …

A New Deep Decoder Type Cascaded Feedforward Neural Network For Critical Heat Flux Prediction In Power Reactors, Rehan Zubair Khalid, Atta Ullah, Asifullah Khan, Mansoor Hameed Inayat, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

Critical Heat Flux (CHF) is a fundamental parameter for ensuring the performance, reliability, safety, and economic viability of water-cooled nuclear reactors. Despite its significance, the absence of a deterministic theory for CHF prediction poses a substantial challenge in thermal engineering. Consequently, various experimental and numerical models have been developed, yet no universally accepted model comprehensively addresses the wide range of flow conditions encountered in practical applications. The accurate prediction of CHF remains a complex and critical task. This work introduces a novel Deep Decoder Type Cascaded feedforward Neural Network (DD-CFNN) to predict CHF across a broad spectrum of operating conditions. …

Optimizing Acid Mist Suppression: Unraveling Surfactant Effects On Bubble Formation And Bursting Dynamics In Copper Electrowinning, Ashish Kakoria, Mirza Muhammad Zaid, Aamir Iqbal, Ellen Amoako Afful, Guang Xu

Mining Engineering Faculty Research & Creative Works

The working mechanism of surfactant to reduce acid mist in copper electrowinning system is not well understood. Most of the studies are based on the surface tension reduction phenomenon but this is not the only function that causes acid mist reduction. In this paper, we investigated the effect of different surfactants on a bubble's residence time, terminal velocity, flow regime, and bursting dynamics using a high-speed camera. We have evaluated five different surfactants and found that the presence of surfactants reduces the terminal velocity, bubble diameter, and increases the residence time of the bubble in electrolyte. Especially for FC-1100, the …