Functional Requirements Research Articles

Ranking Magnetic Colloid Performance for Magnetic Particle Imaging and Magnetic Particle Hyperthermia

AbstractMagnetic particle imaging (MPI) is an emerging modality that can address longstanding technological challenges encountered with magnetic particle hyperthermia (MPH) cancer therapy. MPI is a tracer technology compatible with MPH for which magnetic nanoparticles (MNPs) provide signal for MPI and heat for MPH. Identifying whether a specific MNP formulation is suitable for both modalities is essential for clinical implementation. Current models predict that functional requirements of each modality impose conflicting demands on nanoparticle magnetic properties. This objective here is to develop a measurement and ranking scheme based on end‐use performance to streamline evaluation of candidate MNP formulations. The measured MPI point‐spread function (PSF) and specific loss power (SLP) is combined to generate a single numerical value for comparison on a relative ranking scale, or figure of merit (FoM). 12 aqueous iron‐containing formulations are evaluated, including FDA‐approved (parenteral) iron‐containing colloids. MNPs with high (Synomag‐D70: 123.4), medium (Synomag‐D50: 63.2), and low (NanoXact: 0.147) FoM values are selected for in vivo validation of the selection scheme in subcutaneous 4T1 tumors. Results demonstrate that the proposed ranking accurately assessed the relative performance of MNPs for MPI and MPH. Data demonstrated that image quality and tumor temperature rise increased with FoM ranking, validating predictions. It isshown that the MPI signal correlated with MNP concentration in tissue. Computational heat transfer models anchored on tumor MPI data harmonized with experimental results to within an average of 2 °C when MNP content estimated from MPI data is included. Computational studies emphasized the importance of post‐injection MNP quantitation and MPI spatial resolution.

Applications for Semantic 3D Streetspace Models and Their Requirements—A Review and Look at the Road Ahead

In addition to geometric accuracy, topological information, appearance and georeferenced data, semantic capabilities are key strengths of digital 3D city models. This provides the foundation for a growing number of use cases, far beyond visualization. While these use cases mostly focused on models of buildings or the terrain so far, the increasing availability of data on roads and other transportation infrastructure opened up a range of emerging use cases in the field of semantic 3D streetspace models. While there are already a number of implemented examples, there is also a potential for new use cases not yet established in the field of 3D city modeling, which benefit from detailed representations of roads and their environment. To ensure clarity in our discussions, we introduce an unambiguous distinction between the terms `application domain’, `use case’, `functionality’ and `software application’. Based on these definitions, use cases are categorized according to their primary application domain and discussed with respect to relevant literature and required functionalities. Furthermore, requirements of functionalities towards semantic 3D streetspace models are determined and evaluated in detail with regard to geometric, semantic, topological, temporal and visual aspects. This article aims to give an overview on use cases in the context of semantic 3D streetspace models and to present requirements of respective functionalities, in order to provide insight for researchers, municipalities, companies, data providers, mapping agencies and other stakeholders interested in creating and using a digital twin of the streetspace.

A Design Study on Commercial Cleaning Robots Based on Kano–QFD

In the post-pandemic era, public space safety has emerged as a central public concern. As global public health awareness rose, traditional manual cleaning methods were increasingly inadequate for large-scale and high-standard cleaning requirements. Therefore, the design of a commercial cleaning robot that combined cleaning efficiency, environmental performance, and sustainability was essential to meet evolving societal demands. This paper systematically gathered and analyzed commercial cleaning robot functional requirements through a comprehensive investigation. According to the Kano model, functional requirements were categorized by attributes and their importance was quantified. Subsequently, using the QFD model, the design requirements for commercial cleaning robots were determined, and their significance weights were established. This identified the key design requirements. The results of this study indicated that the integration of the Kano and QFD models provided a novel perspective for the design of functional integration in commercial cleaning robots. Furthermore, it provided a practical methodological framework for addressing similar issues in the future.

Density gradient structure foams prepared by novel two-step foaming strategy: Performance, simulation and optimization

Functional gradient foam materials play a crucial role in meeting the diverse performance and functionality requirements of modern engineering. Density gradients enable the distribution of mechanical, dielectric, and optical properties within materials, exhibiting a gradient representation. However, creating density gradients within foams poses a significant challenge, especially for semi-crystalline polymers. The paper proposed a novel two-step foaming method for preparing polypropylene (PP) foams with density gradient structure (DGS). Initially, a pre-foaming process was conducted to prepare PP pre-foams with uniform structure (US) at low temperatures, followed by a secondary foaming process on partially saturated PP pre-foams to fabricate PP DGS foams. By adjusting the duration of partial saturation time, PP foams with various DGS can be achieved. Compared with the commonly used one-step foaming method and uniform foaming method in the literature, the DGS foams prepared by the two-step foaming method exhibit not only a significant enhancement in mechanical property but also achieve the lowest thermal conductivity, while maintaining comparable and outstanding sound insulation performance. Finally, a comprehensive evaluation model using COMSOL Multiphysics was developed for the DGS foams, providing insights for optimizing foam performance through process enhancements.

A novel framework for automated warehouse layout generation.

Optimizing warehouse layouts is crucial due to its significant impact on efficiency and productivity. We present an AI-driven framework for automated warehouse layout generation. This framework employs constrained beam search to derive optimal layouts within given spatial parameters, adhering to all functional requirements. The feasibility of the generated layouts is verified based on criteria such as item accessibility, required minimum clearances, and aisle connectivity. A scoring function is then used to evaluate the feasible layouts considering the number of storage locations, access points, and accessibility costs. We demonstrate our method's ability to produce feasible, optimal layouts for a variety of warehouse dimensions and shapes, diverse door placements, and interconnections. This approach, currently being prepared for deployment, will enable human designers to rapidly explore and confirm options, facilitating the selection of the most appropriate layout for their use-case.

From data silos to seamless integration and coordination: a data-asset centric approach to smart hospital facility management

PurposeExisting hospital building operations involve numerous information technology applications and complex building systems; therefore, an intelligent facility management (FM) platform is required to ensure their continuous operation. To address the persistent issues of data silos, inefficient data interoperability, and workflow incoordination that have been identified in the current body of FM practice and literature, the present study develops a data-asset (DA) centric FM platform specifically designed for hospital buildings.Design/methodology/approachThis study proposes a semi-customized approach to develop the DA-centric FM platform for hospital buildings. To elucidate the precise function requirements of the hospital FM platform, focus group interviews are employed. By seamlessly integrating the as-built BIM model, IoT sensor data and FM workflow data, the BIM-based DA model with a data transfer mechanism is developed. The development of the FM platform with function modules in a case study is guided by a five-tier architecture and the coordination theory (CT). The case study provides an in-depth introduction to the applications of DA management, space management and maintenance management modules.FindingsThe capabilities of the developed DA-centric hospital FM platform are validated through the case application and user satisfaction survey, which assess data quality, automation level, operation efficiency, flexibility and functionality. For hospital FM activities, this DA-centric FM platform realizes data integration and seamless transformation, optimizes workflow coordination and enhances operation performance.Originality/valueThe initial scholarly contribution is the establishment of the BIM-based DA model, which serves as the data middle platform for continuous data integration, transmission and sharing within the FM platform. Subsequently, under the guidance of the CT, the business process of function modules is designed, improving the intra-module and inter-module workflow coordination. The developed DA-centric FM system along with its performance benchmarking application, assists facility managers and decision-makers in implementing smart operations for hospital buildings and achieving the management goals of safety, efficiency, energy savings and convenience.

Rotor-Through-Coils Toroidal-Flux Reluctance E-Motor for Aviation

Electrification of aviation propulsion is in progress. New electric motor architectures — beyond axial and radial fluxes — may be required to unlock its full potential in meeting the demanding functional requirements (in terms of power, weight and efficiency) and certification requirements (from airworthiness authorities) set for airborne operating engine. This article presents a new class of toroidal-flux reluctance electric motors, where the rotor travells inside the coils — the Rotor-Through-Coils (RTC) Reluctance E-Motor. Extensive finite element magnetic model analysis was conducted (including motor operational characteristics assessment), following from an existing validated approach. The power delivered by five series-mounted motors rivales fuel-injected engines powering existing acrobat airplanes, including similar dimensions. A further important advantage will follow in a sequel publication showing the substantial advantage of this motor architecture to be entirely and effeciently air-cooled (like high pressure turbines already do in turbofans), removing the added complexity, weight, cost and certification issues implied in using onboard liquid coolants.

Development aspects of cable cutter cartridge for helicopter application

This research work emphasizes on the development aspects of a cartridge cable cutter for helicopter application. This cartridge is used to rescue hoist system during emergency for helicopter application under adverse conditions. It is an electrically initiated cartridge in which two electrical squibs are used with specified current and voltage. As the cartridge is initiated, the squib gets incandescent and initiates an explosive train. A cartridge cable cutter is a propellant actuated device (PAD) that generates hot combustion gases having high temperature and pressure on burning of gun powder and propellant inside the cartridge case. The cable cutter cartridge under study is filled with energetic materials (EM) such as propellants and gun powder. It releases the energy very quickly which acts on the projectile i.e. the cutter in actual system. A projectile velocity measurement was carried out using Doppler RADAR (radio detection and ranging). To assess the projectile velocity is the unique design feature in armament field. It is responsible for the measurement of the projectile velocity at the muzzle end of velocity test rig (VTR). The minimum and maximum projectile velocities were experimentally measured in between 70 ms−1 and 150 ms−1. The projectile velocity measurement is an evaluation methodology as performance parameter of this cartridge. The cartridge under study has been developed meeting structural, functional and mechanical requirements. The cartridge has undergone various exhaustive qualification tests during development phase. The cartridge was thus designed, qualified and validated through rigorous development trials. The main objective of this article is to address development aspects of the cartridge cable cutter for helicopter application. In conclusion, after successful design, development and qualification trials, the cartridge was found to meet all the functional and operational requirements considering the end use.

Cultural Sensitivity and Social Well-Being in Embassy Architecture: Educational Approaches and Design Strategies

Over the past two decades, the expanding environmental and ecological crises highlight the need to broaden the concept of sustainability to encompass support for cultural sensitivity and social well-being. This study explores the role of architectural education in fostering cultural sensitivity and social well-being in embassy architecture within a framework of environment–behavior studies. It starts from the premise that the architectural values of a culture are deeply rooted in the relationship between the users, architecture, and surrounding environment. State-sponsored architectural works (e.g., embassies, consulates, cultural centers) built outside the country are viewed as symbolic representations of a nation’s diplomatic and cultural influence. These architectural typologies hold a unique potential to act as bridges for cross-cultural dialogue and foster a collective sense of global citizenship. In order to develop and assess the teaching curriculum, a specific assignment was given to master’s students of the Faculty of Architecture, University of Belgrade, with the aim to explore how engineering education can be adopted to motivate students toward sustainable attitudes and design solutions. While traditional diplomatic architecture emphasizes inward-facing, fortress-like design strategies, establishing physical and symbolic barriers between the embassy’s territory and the surrounding context, this research advocates for a more holistic approach oriented toward cultural sustainability, openness, and integration within an urban context. Key findings highlight creative solutions for balancing cultural representation with functional requirements while prioritizing community engagement, environmental responsibility, and user well-being. By demonstrating the two distinctive architectural strategies, this study contributes to the culturally responsive embassy design within the broader context of sustainable architectural education.

KAWANKULINER: PERSONALISED FOOD RECOMMENDATION APP USING BMR AND TDEE FOR OPTIMAL DAILY NUTRITION

People often have difficulty in determining the type of food that is suitable for the composition of their body. This is due to the many types of food available, as well as the lack of information about the nutritional content of each type of food. By fulfilling the daily calorie and macro-nutrient needs required by the body, its metabolism can be maintained, preventing various health problems such as malnutrition. Based on the results of the Basic Health Research in 2018 malnutrition is one of the most serious problems in Indonesia. Several studies related to calculating calorie estimates using the BMR approach with the utilization of technology have been conducted.However, these studies were limited to only displaying the amount of daily calorie needs that were not accompanied by what foods were needed to meet these daily needs. The purpose of this research is to build an app to help individuals understand their daily calorie needs based on their Basal Metabolic Rate (BMR) and total daily expenditure energy (TDEE), using smart scale to provide body composition information and spoonacular API to provide food recommendations that match their energy needs and give them recipes on how to make their food meanwhile waterfall model is used as a software development method. The test results show that the app meets the functional and usability requirements well, with a high accuracy rate of 99.86% for calories, protein, fat, and carbohydrates. In terms of user response, 13 respondents had a very positive response, and considered the app useful for making it easier to get information about their calorie and macro-nutrient needs, as well as provide food recommendations based on their daily needs.

Research on Medical Device Software Based on Artificial Intelligence and Machine Learning Technologies

With the rapid development of Artificial Intelligence (AI) and Machine Learning (ML) technologies, new opportunities for innovation and application in medical device software have emerged. This paper explores the current research on medical device software based on AI and ML, analyzing the practical applications and outcomes of these technologies in the medical field. First, the basic concepts of AI and ML and their significance in medical devices are introduced. Then, an in-depth analysis of the functional requirements of medical device software, user experience, and relevant regulations is provided. Next, the paper discusses the specific applications of AI and ML in data processing, model training, and software implementation, showcasing their practical effects through case studies. Finally, the paper summarizes the current technical challenges and future opportunities, hoping to provide insights for further development in the medical device industry.

Worker-centered evaluation and redesign of manufacturing tasks for ergonomics improvement using axiomatic design principles

Humans are considered the most valuable resource in manufacturing systems thanks to their craftsmanship, dexterity, and autonomy significantly affecting productivity, quality, and the overall company competitiveness. This paper introduces the SAGE (Systematic Approach to Generating Ergonomic Manufacturing tasks) methodology, a structured approach based on Axiomatic Design principles to integrate Human Factors evaluation early in the operations design phase and redesign manufacturing tasks to improve operators well-being. The primary objective is to mitigate discomfort and safety risks that often lead to musculoskeletal disorders, absenteeism, and production delays. SAGE provides a comprehensive framework for assessing ergonomic aspects of manufacturing tasks and identifying the need for redesign. It offers a detailed set of Functional Requirements (FRs) for reference, assesses FR satisfaction, evaluates task complexity using the Independence Axiom, and examines the intensity of FR satisfaction through the Information Axiom. The methodology includes specific implementation guidelines, ensuring its applicability across diverse manufacturing contexts. Its effectiveness is demonstrated through a large-scale parts assembly case study inspired by the bus and coach industrial sector, where a production engineer evaluated a windows assembly task and identified ergonomic design interventions. A comparative analysis with other relevant methods is finally presented, highlighting the approach's effectiveness.

Research on Decoupling Duty Cycle Optimization Control Method of a Multiport Converter for Dual-Port Direct Drive Wave Power Generation System

Dual-port direct drive wave energy power generation systems (DP-DDWEPGS) have received widespread attention due to their smooth and zero-free output power, compared to single-port direct drive wave energy power generation systems (SP-DDWEPGS) which have the disadvantage of large out-put power fluctuations. To further enhance the performance of the DP-DDWEPGS, optimal power capture control is proposed to achieve maximum power point tracking. Meanwhile, a multiport converter is applied to the DP-DDWEPGS to solve the problem caused by an excessive number of switching devices in the overall system converter. The multiport converter fulfills all the functional requirements of the DP-DDWEPGS while reducing the number of switching devices. However, switch multiplexing of the multiport converter also introduces coupling relationships between each port and the wave force exhibits time-varying characteristics, necessitating advanced control methods with superior fast-tracking capability. Therefore, in this paper, a decoupling duty cycle optimization model predictive control for DP-DDWEPGS is proposed. Based on the characteristics of switching multiplexing, NSC finite control set model predictive control (FCS-MPC) decouples the current prediction and the cost function, reduces the number of candidate voltage vectors in each operation, and shortens the operation time by 70%. To address the issues of high ripple value and increased error due to decoupling in FCS-MPC, duty cycle optimization control is added, greatly reducing the fluctuations in electromagnetic force and power of the permanent magnet linear generator (PMLG). Based on the established simulation model, the feasibility and superiority of the multiport converter and decoupling duty cycle optimization model predictive current control method are verified.

Studying Dynamical and Hydraulic Characteristics of the Hydraulically Suspended Passive Shutdown Subassembly (HS-PSS) and Validating with a Prototypic Test Sample

The pool-type demonstrative China Fast Reactor 600 (CFR-600) adopted a series of improved safety designs, among which the hydraulic suspended passive shutdown subassembly (HS-PSS) is employed for inherent safety enhancement, especially suitable against unprotected loss of flow accident (ULOF). In this article, functional requirements for HS-PSS design in hydro-dynamic aspects are proposed, with the corresponding performance indicators discussed. To address these functional requirements, qualitative analysis on the equilibrium solution properties of the nonlinear dynamical model equation of the hydraulic moving body (HMB) in the HS-PSS are conducted, which leads to the determination of an applicable design parameter domain of the HMB for its practical design from the broad range of structural and parametric design options available for HS-PSS. Furtherly, hydraulically characterizing and modeling the constituent paths and consequent fluid network, hydraulic characteristics of the HS-PSS, as well as the coupled hydro-dynamic motion behaviors of the HMB for suspension and dropping states, were simulated and test-validated. Considering the HS-PSS hydro-dynamic behaviors, key indicators such as critical flowrate, drop time, hydraulic self-tightening performance, as well as the hydraulic characteristics curve are for fulfilling the functional requirements. Meanwhile, through sensitivity study of some structural parameters‘ impact on hydraulic characteristics, some most sensible structural parameters for adjusting and optimizing detailed design are observed. The work is quite significant in supporting the conceptual design of the HS-PSS as well as its engineering improvement.

Dimensional Synthesis of the Compliant Mechanism Using the Parametric Fuzzy Form of the Freudenstein Equation

The dimensional synthesis of compliant mechanisms (CMs) leverages the flexibility of their components to achieve precise motion and functionality. This study introduces a novel approach using the parametric fuzzy form of the Freudenstein equation with triangular fuzzy numbers (TFNs) to address the complexities and uncertainties inherent in CM design. By integrating fuzzy logic with advanced computational techniques such as Newton’s method, the proposed methodology offers a robust framework for synthesizing CMs that can adapt to varying conditions. This approach enables the creation of flexible links modeled as fuzzy regions, allowing for optimized performance and reliability across a range of operational scenarios. Numerical examples illustrate the practical application and efficacy of the proposed methods, highlighting significant improvements in the design and synthesis of CMs. The integration of fuzzy logic in the synthesis process not only enhances the resilience of the mechanisms but also paves the way for future advancements in the field. This study demonstrates the potential of fuzzy logic principles in optimizing CM designs, ensuring they meet specific functional requirements with high precision.

The conserved genetic program of male germ cells uncovers ancient regulators of human spermatogenesis.

Male germ cells share a common origin across animal species, therefore they likely retain a conserved genetic program that defines their cellular identity. However, the unique evolutionary dynamics of male germ cells coupled with their widespread leaky transcription pose significant obstacles to the identification of the core spermatogenic program. Through network analysis of the spermatocyte transcriptome of vertebrate and invertebrate species, we describe the conserved evolutionary origin of metazoan male germ cells at the molecular level. We estimate the average functional requirement of a metazoan male germ cell to correspond to the expression of approximately 10,000 protein-coding genes, a third of which defines a genetic scaffold of deeply conserved genes that has been retained throughout evolution. Such scaffold contains a set of 79 functional associations between 104 gene expression regulators that represent a core component of the conserved genetic program of metazoan spermatogenesis. By genetically interfering with the acquisition and maintenance of male germ cell identity, we uncover 161 previously unknown spermatogenesis genes and three new potential genetic causes of human infertility. These findings emphasize the importance of evolutionary history on human reproductive disease and establish a cross-species analytical pipeline that can be repurposed to other cell types and pathologies.

Dynamics and experimental study of a novel proportional directional valve with displacement feedback groove controlled by high-speed switching valves

The intelligence of hydraulic roof support is an important guarantee for unmanned fully mechanized coal mining face. The water-based medium proportional directional valve is the main factor that restricts the intelligent realization of support system. The support control valve needs to meet the 2/3 (two-position three-way) structure, taking into account both manual and electro-hydraulic control functions. The current water-based proportional valve does not satisfy the structural or functional demands of the support system. In this paper, a novel 2/3 water-based proportional directional valve is presented based on the displacement-flow feedback principle, which has two control modes: manual on-off control and electro-hydraulic proportional control. The proportional valve comprises two main valve spools and two pilot valves. The pilot valve is composed of a 2/3 on-off valve with manual operation capability and a high-speed switching valve group controlled by PWM (Pulse Width Modulation). The mathematical model of the proportional valve is established, and the experimental system is built to verify the characteristics of proportional valve. The proportional valve can meet the special functional requirements of the support. In the proportional control mode, the adjustment of spool displacement is regulated through the modulation of PWM duty ratio, resulting in effective control performance of the proportional valve. Furthermore, the discontinuous flow of the high-speed switching valve causes the pressure fluctuation of the pilot hydraulic bridge. Increasing the carrier frequency of PWM can reduce the amplitude of control chamber pressure and spool displacement fluctuation. The findings of the study can offer valuable insights for the continued advancement and enhancement of water-based proportional valves used in hydraulic roof support systems.

All-Ferroelectric Spiking Neural Networks via Morphotropic Phase Boundary Neurons.

Artificial neurons and synapses are crucial for efficiently implementing spiking neural networks (SNNs) in hardware. The distinct functional requirements of artificial neurons and synapses present significant challenges in the implementation of area- and energy-efficient SNNs. This study reports an all-ferroelectric SNN system through co-optimization of material properties and device configurations using wafer-scale atomic layer deposition. For the first time, a double-gate (DG) morphotropic phase boundary-based thin-film transistor (MPBTFT) is utilized for a leaky integrate-and-fire (LIF) neuron. The DG MPBTFT-based LIF neuron eliminates the need for capacitors and reset circuits, thereby enhancing area and energy efficiency. The DG configuration demonstrates various neuronal functions with high reliability. Co-optimizing materials and devices significantly enhance the performance and functional versatility of artificial neurons and synapses. Meticulous material engineering facilitates the seamless co-integration of DG MPBTFT-based neurons, ferroelectric thin-film transistor (TFT)-based synapses, and normal TFTs on a single wafer. All-ferroelectric SNN systems achieved a high classification accuracy of 94.9%, thereby highlighting the potential of DG MPBTFT-based LIF neurons for advanced neuromorphic computing.

Functional genomics screens reveal a role for TBC1D24 and SV2B in antibody-dependent enhancement of dengue virus infection.

Under some conditions, dengue virus (DENV) can hijack IgG antibodies to facilitate its uptake into target cells expressing Fc gamma receptors (FcgR)-a process known as antibody-dependent enhancement (ADE) of infection. Beyond a requirement for FcgR, host dependency factors for this unusual IgG-mediated infection route remain unknown. To identify cellular factors exclusively required for ADE, here, we performed CRISPR knockout (KO) screens in an in vitro system poorly permissive to infection in the absence of IgG antibodies. Validating our approach, a top hit was FcgRIIa, which facilitates the binding and internalization of IgG-bound DENV but is not required for canonical infection. Additionally, we identified host factors with no previously described role in DENV infection, including TBC1D24 and SV2B, which have known functions in regulated secretion. Using genetic knockout and trans-complemented cells, we validated a functional requirement for these host factors in ADE assays performed with monoclonal antibodies and polyclonal sera in multiple cell lines and using all four DENV serotypes. We show that knockout of TBC1D24 or SV2B impaired the binding of IgG-DENV complexes to cells without affecting FcgRIIa expression levels. Thus, we identify cellular factors beyond FcgR that promote efficient ADE of DENV infection. Our findings represent a first step toward advancing fundamental knowledge behind the biology of a non-canonical infection route implicated in disease.IMPORTANCEAntibodies can paradoxically enhance rather than inhibit dengue virus (DENV) infection in some cases. To advance knowledge of the functional requirements of antibody-dependent enhancement (ADE) of infection beyond existing descriptive studies, we performed a genome-scale CRISPR knockout (KO) screen in an optimized in vitro system permissive to efficient DENV infection only in the presence of IgG. In addition to FcgRIIa, a known receptor that facilitates IgG-mediated uptake of IgG-bound, but not naked DENV particles, our screens identified TBC1D24 and SV2B, cellular factors with no known role in DENV infection. We validated a functional role for TBC1D24 and SV2B in mediating ADE of all four DENV serotypes in different cell lines and using various antibodies. Thus, we identify cellular factors beyond Fc gamma receptors that promote ADE mechanisms. This study represents a first step toward advancing fundamental knowledge beyond a poorly understood non-canonical viral entry mechanism.

Long-Term Outcomes in Antibody-Negative Autoimmune Encephalitis: A Retrospective Study.

To characterize the long-term outcomes of patients with "possible only" or "probable" autoimmune encephalitis (AE). Despite comprising one-third of AE cases, antibody-negative cases lacking typical AE-defining features are understudied. We conducted a retrospective analysis of adult patients evaluated at a tertiary center neuroimmunology practice from 2006 to 2020, meeting diagnostic criteria for "possible only" or "probable but antibody-negative" AE, with at least one year of follow-up. All patients underwent neural antibody testing. Forty-five patients (median age, 61 years [range, 20-88]; female, 21 [47%]) were included, with a median follow-up of 36 months (range, 12-174). A change in diagnosis was noted in six additional patients, who were excluded from further analysis, with only two receiving a non-autoimmune diagnosis during follow-up. The majority (41/45 [91%]) presented with significant disability (modified Rankin Scale [mRS] ≥3) at baseline. CSF was inflammatory in 20/44 (45%) and MRI was abnormal in 21/45 (47%). Unclassified neural-specific IgG staining on tissue-based assay was detected in five (11%). Two cases (4%) had a paraneoplastic cause. The median time from onset to immunotherapy initiation was two months (range, 0-21), resulting in at least partial improvement in all 44 (98%) treated cases. Clinical relapses occurred in 14/45 (31%). At last follow-up, the most common symptoms were memory dysfunction (31/45 [69%]), attention deficits (17/45 [38%]), gait instability (13/45 [29%]), and visuospatial dysfunction (10/45 [22%]). Most patients achieved independence (median mRS, 2 [range, 0-6]); however, 11 patients had poor neurological outcome (mRS ≥3). Higher mRS score and gait assistance requirement at three months were predictive of poor outcome (P ≤0.01). Despite significant disability at initial stages, patients with antibody-negative but clinically presumed AE show potential for improvement with immunotherapy, highlighting the importance of early intervention. Early functional status and gait assistance requirements may assist in predicting long-term prognosis.