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Alphafold Database Debiasing For Robust Inverse Folding Jul 2025

Alphafold Database Debiasing For Robust Inverse Folding

Defensive Publications Series

The AlphaFold Protein Structure Database (AFDB) offers unparalleled structural coverage at near-experimental accuracy, positioning it as a valuable resource for data-driven protein design. However, its direct use in training deep models that are sensitive to fine-grained atomic geometry—such as inverse folding—exposes a critical limitation. Comparative analysis of structural feature distributions reveals that AFDB structures exhibit distinct statistical regularities, reflecting a systematic geometric bias that deviates from the conformational diversity found in experimentally determined structures from the Protein Data Bank (PDB). While AFDB structures are cleaner and more idealized, PDB structures capture the intrinsic variability and physical realism essential for generalization …


Contextual Explanation Of Local Differences On Digital Map User Interface, Florian Hartmann, Matthew Sharifi Jul 2025

Contextual Explanation Of Local Differences On Digital Map User Interface, Florian Hartmann, Matthew Sharifi

Defensive Publications Series

Different regions of the world have different regulations, e.g., related to driving, parking, etc. as well as different social norms, e.g., tipping, acceptable use of a mobile device on public transport, etc. Such differences can trip up travelers when they are in unfamiliar locations. This disclosure describes techniques to automatically determine via offline processing by a large language model (LLM). The differences are stored in a database and are used to surface proactive contextual alerts to users at appropriate times by explaining relevant differences between rules or norms at their current location and their typical location. The LLM can be …


Implicit Graph Neural Networks With Flexible Propagation Operators Jul 2025

Implicit Graph Neural Networks With Flexible Propagation Operators

Defensive Publications Series

Due to the capability to capture high-order information of nodes and reduce memory consumption, implicit graph neural networks have become an explored hotspot in recent years. However, these implicit graph neural networks are limited by the static topology, which makes it difficult to handle heterophilic graph-structured data. Furthermore, the existing methods inspired by optimization objectives are limited by the explicit structure of graph neural networks, which makes it difficult to set an appropriate number of network layers to solve optimization problems. To address these issues, we propose an implicit graph neural network with flexible propagation operators in this paper. From …


Balanced Graphformer: Enhancing Graph Transformers With Localized Training Against Over-Globalization Jul 2025

Balanced Graphformer: Enhancing Graph Transformers With Localized Training Against Over-Globalization

Defensive Publications Series

As Transformers gain traction in graph machine learning, the issue of "over-globalization" has emerged, where their global attention mechanisms excessively emphasize distant vertices, potentially diluting vital local information. This is particularly detrimental in graphs where local neighborhoods hold significant predictive value. Existing methods often lack flexibility in local processing or fail to effectively integrate local and global contexts. This paper introduces BalancedGraphFormer, a novel framework designed to localize graph transformer training. It integrates a dedicated local module with a complementary global module. The local module captures fine-grained neighborhood patterns, while the global module integrates broader context without overshadowing local details. …


Datacenter Planning And Rack Placement Optimization Using Reinforcement Learning, Na Jul 2025

Datacenter Planning And Rack Placement Optimization Using Reinforcement Learning, Na

Defensive Publications Series

This disclosure describes the use of reinforcement-learning (RL) techniques to optimize datacenter planning and rack placement. An RL agent operates within a state space that includes physical infrastructure (rack space, power, cooling, network), resource availability (machine inventory, backup power), constraints (emissions, workload demands), etc. The RL agent takes actions such as allocating capacity and placing machines. A reward function guides the agent towards optimal solutions by rewarding utilization, balancing load, achieving compliance with service-level objectives, and penalizing resource stranding and costs. RL algorithms balance exploration and exploitation, adapt to dynamic environments, and scale to large datacenters. Advantages of the described …


Robust Graph Learning Through Spatial-Spectral Synergy Against Structural Attacks Jul 2025

Robust Graph Learning Through Spatial-Spectral Synergy Against Structural Attacks

Defensive Publications Series

Graph Convolutional Networks (GCNs) are powerful tools for learning from graph data but exhibit significant vulnerability to adversarial structural attacks that manipulate node connections. While various defense strategies focusing independently on the spatial or spectral domains exist, they often fail to leverage the complementary strengths of both perspectives. This paper introduces the Spatial- Spectral Graph Convolutional Network (S²-GCN), a novel framework designed to enhance GCN robustness against structural attacks by synergistically combining spatial and spectral defense mechanisms. S²-GCN comprises two core GCN-based modules operating in parallel. The spectral module utilizes a graph structure derived from learnable low-frequency spectral components, adaptively …


Learning Resilient Graph Structures In Heterophilic Settings Jul 2025

Learning Resilient Graph Structures In Heterophilic Settings

Defensive Publications Series

Graphs provide a fundamental way to model relationships between entities and are central to numerous machine learning tasks. Standard graph-based methods often assume the provided graph structure is both accurate and complete. However, real-world graphs frequently suffer from noise and sparsity, negatively impacting downstream tasks like node classification and clustering. While graph representation learning has advanced significantly, many methods implicitly assume graph homophily (connections predominantly between nodes of the same class), struggling when faced with heterophily (connections predominantly between different classes). This paper introduces a novel method, Resilient Graph Learning for Heterophily (RGLH), designed to learn high-quality graph structures directly …


Halo: Heterophily-Aware Label-Free Ordering For Unsupervised Graph Fraud Detection Jul 2025

Halo: Heterophily-Aware Label-Free Ordering For Unsupervised Graph Fraud Detection

Defensive Publications Series

Graph fraud detection (GFD) has rapidly advanced in protecting online services by identifying malicious fraudsters. Recent supervised GFD research highlights that heterophilic connections between fraudsters and users can greatly impact detection performance, since fraudsters tend to camouflage themselves by building more connections to benign users. Despite the promising performance of supervised GFD methods, the reliance on labels limits their applications to unsupervised scenarios; Additionally, accurately capturing complex and diverse heterophily patterns without labels poses a further challenge. To fill the gap, we propose a Heterophily-guided Unsupervised Graph fraud dEtection approach (HUGE) for unsupervised GFD, which contains two essential components: a …


Biochar-Based Filtration And Barrier Systems For Urban Stormwater Treatment, Krishna R. Reddy Jul 2025

Biochar-Based Filtration And Barrier Systems For Urban Stormwater Treatment, Krishna R. Reddy

Stormwater Drainage Conference

Conference that deals a wide range of issues dealing with stormwater drainage. Professor Krishna Reddy of University of Illinois Chicago presented an invited talk titled "Biochar-Based Filtration and Barrier Systems for Urban Stormwater Treatment"


The Tax Adviser, Volume 11, Number 2, February 1980, American Institute Of Certified Public Accountants Jul 2025

The Tax Adviser, Volume 11, Number 2, February 1980, American Institute Of Certified Public Accountants

Tax Adviser

No abstract provided.


Author Index, 12 Months Ended January 1980, American Institute Of Certified Public Accountants Jul 2025

Author Index, 12 Months Ended January 1980, American Institute Of Certified Public Accountants

Tax Adviser

No abstract provided.


Tax Trends, E. S. Linett Jul 2025

Tax Trends, E. S. Linett

Tax Adviser

No abstract provided.


Spotlight, Robert F. Manning Jul 2025

Spotlight, Robert F. Manning

Tax Adviser

No abstract provided.


Accountant-Advisor In Treasury’S Office Of Tax Legislative Counsel, Kenneth F. Thomas, William R. Stromsem Jul 2025

Accountant-Advisor In Treasury’S Office Of Tax Legislative Counsel, Kenneth F. Thomas, William R. Stromsem

Tax Adviser

No abstract provided.


Common Stock Bailouts: A Planning Device For The Close Corporation, Michael C. Gallagher Jul 2025

Common Stock Bailouts: A Planning Device For The Close Corporation, Michael C. Gallagher

Tax Adviser

No abstract provided.


Tax Clinic, Steve Braun Jul 2025

Tax Clinic, Steve Braun

Tax Adviser

No abstract provided.


How To Obtain An Investment Credit For Rehabilitated Buildings, Philip W. Sandler Jul 2025

How To Obtain An Investment Credit For Rehabilitated Buildings, Philip W. Sandler

Tax Adviser

No abstract provided.


Estate Planning: Lifetime Gifts—A Quantitative Approach, Roger A. Pies, Daniel S. Goldberg Jul 2025

Estate Planning: Lifetime Gifts—A Quantitative Approach, Roger A. Pies, Daniel S. Goldberg

Tax Adviser

No abstract provided.


Charitable Remainder Trusts And Pooled Income Funds—Using Computer Simulation To Rank The Benefits, Anna C. Fowler Jul 2025

Charitable Remainder Trusts And Pooled Income Funds—Using Computer Simulation To Rank The Benefits, Anna C. Fowler

Tax Adviser

No abstract provided.


The Tax Adviser, Volume 11, Number 1, January 1980, American Institute Of Certified Public Accountants Jul 2025

The Tax Adviser, Volume 11, Number 1, January 1980, American Institute Of Certified Public Accountants

Tax Adviser

No abstract provided.


Author Index, 12 Months Ended December 1979, American Institute Of Certified Public Accountants Jul 2025

Author Index, 12 Months Ended December 1979, American Institute Of Certified Public Accountants

Tax Adviser

No abstract provided.


Subject Index, 12 Months Ended December 1979, American Institute Of Certified Public Accountants Jul 2025

Subject Index, 12 Months Ended December 1979, American Institute Of Certified Public Accountants

Tax Adviser

No abstract provided.


Tax Trends, E. S. Linett Jul 2025

Tax Trends, E. S. Linett

Tax Adviser

No abstract provided.


Design Of A Simplified Biomimetic Autonomous Entertainment Robot, Jessica E. Morris, Shanny May Ruiz, Morgan Snyder, Hannah Guild, Gabriel Cardona-Tous Jul 2025

Design Of A Simplified Biomimetic Autonomous Entertainment Robot, Jessica E. Morris, Shanny May Ruiz, Morgan Snyder, Hannah Guild, Gabriel Cardona-Tous

Graduate Scholarship and Creative Works

The advancement of technology has paved the way for robots with the purpose of entertainment to become more popular. However, the exploration of biomimetic actions as a factor of entertainment is majorly limited to the mimicry of young domesticated animals such as puppies and kittens, with some notable exceptions. However, there is a wide range of possibilities for robotics that mimic animals marketed as pets, outside of the common examples. This work seeks to explore the opportunity for autonomous systems with entertainment driven and expressive actions in the family of Testudines (turtles and tortoises), an undomesticated species, but still often …


A Neuromorphic Spike-Based System For Real-Time Behavioral Anomaly Detection In Saas And Self-Hosted Environments, Marcel Witt Jul 2025

A Neuromorphic Spike-Based System For Real-Time Behavioral Anomaly Detection In Saas And Self-Hosted Environments, Marcel Witt

Defensive Publications Series

This publication introduces NeuraSentry™, a neuromorphic anomaly detection framework inspired by biological spike-based learning and synaptic plasticity. It combines competitive vector detectors, temporal spike traces, and retroactive learning signals to detect evolving behavioral fraud and insider threats in both SaaS and on-premise systems. Key innovations include sparse activation using cosine similarity, HDBSCAN-based meta-neuron clustering, and delayed reward modulation modeled after dopamine and serotonin systems. NeuraSentry delivers adaptive, explainable, and scalable behavioral threat detection, without relying on labeled training data or fixed rules. This work establishes prior art to prevent overly broad patents in the field of neuromorphic security analytics.


Functional Handle Taper And Nesting Mold For Dispenser - Compatible Cutlery, Northstar Maintenance Management Inc. Dba Compostitall.Com Jul 2025

Functional Handle Taper And Nesting Mold For Dispenser - Compatible Cutlery, Northstar Maintenance Management Inc. Dba Compostitall.Com

Defensive Publications Series

This publication discloses the functional geometry of a tapered handle for compostable cutlery that enables consistent stacking and dispensing in tab-compatible or gravity-fed dispensers. This design has been in commercial use since approximately 2017 and is currently offered under the Forever Free brand. No claim of original invention is made; this disclosure is intended to serve as prior art.


Context-Aware Chatbot For Contextual Link Retrieval And Team Collaboration, Harish Murthy Jul 2025

Context-Aware Chatbot For Contextual Link Retrieval And Team Collaboration, Harish Murthy

Defensive Publications Series

Members of a team often individually bookmark or maintain knowledge assets, e.g., documents, meeting notes, etc. Sharing links to such assets and disseminating their contents within the team can become unwieldy, especially as the size of the team and the volume of assets grow. This disclosure describes techniques that enable individuals within a team to register certain mnemonics within a chat room or messaging app, such that when prompted with a mnemonic, a link to a contextually relevant asset is surfaced. In the case of chat rooms, context is derived from the chat room from which the query originated. In …


Key Management Server Driven Adaptive Client-Side Caching Of Cryptographic Keys, Himanshu Kishna Srivastava Mr. Jul 2025

Key Management Server Driven Adaptive Client-Side Caching Of Cryptographic Keys, Himanshu Kishna Srivastava Mr.

Defensive Publications Series

In conventional cryptographic systems, encryption keys are typically retrieved from a centralized key management server (KMS). To reduce latency and improve performance, clients often cache these keys locally. While this caching mechanism enhances efficiency. However, this approach also introduces several security challenges e.g. cached keys may become outdated or exposed to unauthorized access, and clients generally lack a reliable mechanism to detect when a key has been updated or revoked by the KMS. Moreover, because each client may implement its own caching logic—governing how long keys are stored, when they are refreshed, or how they are secured—this results in inconsistent …


Spotlight, Robert F. Manning Jul 2025

Spotlight, Robert F. Manning

Tax Adviser

No abstract provided.


Tax Clinic, William T. Diss Jul 2025

Tax Clinic, William T. Diss

Tax Adviser

No abstract provided.