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At least 433 records · Page 24

Dendritic cells focus CTL responses toward highly conserved and topologically important HIV-1 epitopes

During early HIV-1 infection, immunodominant T cell responses to highly variable epitopes lead to the establishment of immune escape virus variants. Here we assessed a type 1-polarized monocyte-derived dendritic cell (MDC1)-based approach to selectively elicit cytotoxic T lymphocyte (CTL) responses against highly conserved and topologically important HIV-1 epitopes in HIV-1-infected individuals from the Thailand RV254/SEARCH 010 cohort who initiated antiretroviral therapy (ART) during early infection (Fiebig stages I-IV). Autologous MDC1 were used as antigen presenting cells to induce in vitro CTL responses against HIV-1 Gag, Pol, Env, and Nef as determined by flow cytometry and ELISpot assay. Ultra-conserved or topologically important antigens were respectively identified using the Epigraph tool and a structure-based network analysis approach and compared to overlapping peptides spanning the Gag proteome. MDC1 presenting either the overlapping Gag, Epigraph, or Network 14-21mer peptide pools consistently activated and expanded HIV-1-specific T cells to epitopes identified at the 9-13mer peptide level. Interestingly, some CTL responses occurred outside known or expected HLA associations, providing evidence of new HLA-associated CTL epitopes. Comparative analyses demonstrated more sequence conservation among Epigraph antigens but a higher magnitude of CTL responses to Network and Gag peptide groups. Importantly, CTL responses against topologically constrained Gag epitopes contained in both the Network and Gag peptide pools were selectively enhanced in the Network pool-initiated cultures. Our study supports the use of MDC1 as a therapeutic strategy to induce and focus CTL responses toward putative fitness-constrained regions of HIV-1 to prevent immune escape and control HIV-1 infection.

60 APPLIED LIFE SCIENCES↗

Farmer characteristics and decision-making: A model for bioenergy crop adoption

We report the commercial development of biofuels and bioproducts depends on whether renewable biomass feedstock is available while not directly competing with the production of food. Farmers are one of the most important stakeholders in the biofuel supply chain and confront a range of uncertainties while entering the bioenergy market. Their decision-making process is extremely complex and rarely purely rational. Modeling farmer behavior requires considering a wide range of individual-level factors, socio-temporal dynamics, institutional settings, and their interactions. These characteristics make agent-based modeling a suitable framework for evaluating such systems. We developed a model to simulate farmer bioenergy crop adoption behavior across a 50-county study region in Nebraska, Kansas, and Colorado. The analysis considers adoption decisions for two bioenergy feedstocks, crop residues and energy crops. We examine the influence of individual and farm characteristics, market structure, social networks, and media influence on farmer adoption decisions. Our results indicate that different factors can have varied impacts on the speed of adoption for the crop residues and energy crops. Identifying levers that have the most impact on grower adoption can inform the design of interventions both from policy and private sector standpoints with important implications for the future the bioenergy industry.

09 BIOMASS FUELS↗

Protein–Protein Interaction Networks Derived from Classical and Machine Learning-Based Natural Language Processing Tools

The study of protein-protein interactions (PPIs) provides insight into various biological mechanisms, including the binding of antibodies to antigens, enzymes to inhibitors or promoters, and receptors to ligands. Recent studies of PPIs have led to significant biological breakthroughs. For example, the study of PPIs involved in the human:SARS-CoV-2 viral infection mechanism aided in the development of the SARS-CoV-2 vaccines. Though several databases exist for the manual curation of PPI networks, text mining methods have been routinely demonstrated as useful alternatives for newly studied or understudied species where databases are incomplete. Here, the relationship extraction (RE) performance of several open-source classical text processing, machine learning (ML)-based natural language processing (NLP), and large language model (LLM)-based NLP tools were compared. Overall, our results indicated that networks derived from classical methods tend to have high true positive rates at the expense of having overconnected-networks, ML-based NLP methods have lower true positive rates but networks with the closest structures to the target network, and LLM-based NLP methods tend to exist in-between the two other approaches, with variable performances. Finally, the selection of a specific NLP approach should be tied to the needs of a study and text availability, as models varied in performance due to the amount of text provided.

59 BASIC BIOLOGICAL SCIENCES↗

Electronic Configurational Transformation of Network Modifiers in Aluminate Glass above Megabar Pressures

Electronic responses of glasses under extreme pressures differ from those of crystalline analogs. Their distinct electronic environments are found in network formers with well-defined, covalent-bonded coordination environments (e.g., [4] Si and [4] Al) and in network modifiers with more disordered, ionic-bonded configurations (e.g., [5,6,7] Ca). Deciphering the evolution of the bonding environment of network modifier cations upon compression provides atomic insights into the pressure-driven hardening and transport properties of glasses. Despite the importance, in contrast to extensive efforts to uncover how network formers behave under pressure, considerable structural disorder around network modifiers makes it challenging to probe their electronic bonding environments under compression. Our understanding of the evolution of network modifiers above megabars is currently absent. Here, we report a discovery of highly densified electronic configurations of network modifier Ca in aluminate glass under extreme compression via the first inelastic X-ray scattering at the Ca L-edge up to 140 GPa. As evidenced by the prominent pressure-driven increases in electronic dispersion and delocalization, densified calcium environments are characterized by a decreased average Ca–O distance, the formation of highly coordinated calcium, a broader distribution of topological variables, and a greater distortion of Ca polyhedra above megabars. The spectral features for the Ca environments reveal significant electronic and bonding modifications, including pressure-driven increases in the ligand field interaction, the covalence characteristic of the Ca–O bond, and the electron–hole Coulomb interaction. These densification paths identify the electronic adaptation of network modifiers above megabars, shedding light on the origins of enhanced electron transport and the electron-storing capacity of glasses under pressure.

amorphous materials↗

Layered supramolecular hydrogels from thioglycosides

Low molecular weight hydrogels are made of small molecules that aggregate via noncovalent interactions. Here, comprehensive characterization of the physical and chemical properties of hydrogels made from thioglycolipids of the disaccharides lactose and cellobiose with simple alkyl chains is reported. While thiolactoside hydrogels are robust, thiocellobioside gels are metastable, precipitating over time into fibrous crystals that can be entangled to create pseudo-hydrogels. Rheology confirms the viscoelastic solid nature of these hydrogels with storage moduli ranging from 10–600 kPa. Additionally, thiolactoside hydrogels are thixotropic which is a desirable property for many potential applications. Freeze-fracture electron microscopy of xerogels shows layers of stacked sheets that are entangled into networks. These structures are unique compared to the fibers or ribbons typically reported for hydrogels. Differential scanning calorimetry provides gel-to-liquid phase transition temperatures ranging from 30 to 80 °C. Prodan fluorescence spectroscopy allows assignment of phase transitions in the gels and other lyotropic phases of high concentration samples. Phase diagrams are estimated for all hydrogels at 1–10 wt% from 5 to ≥ 80 °C. In conclusion, these hydrogels represent a series of interesting materials with unique properties that make them attractive for numerous potential applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Generating synthetic occupants for use in building performance simulation

Occupant behaviour simulation frameworks can employ synthetic populations to characterize occupancy and behavioural patterns in buildings based on observed demographic data at a certain geographical location. For buildings, very few synthetic occupant populations have been generated. This paper uses a Bayesian Networks (BN) structural learning approach to synthesize populations of occupants in a multi-family housing case study. Two additional cases of office occupants and senior housing residents are considered as a cross-case comparison. Furthermore, we draw upon the extended version of drivers-needs-actions-systems (DNAS) framework to guide the selection of variables and data imputation. Our results show that the BN approach is powerful in learning the structure of data sets. The synthetic data sets successfully match the joint distributions of the underlying combined data sets. Experiments on the multi-family housing particularly show better performance than the office and senior housing cases.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Deep Learning–Assisted Multiobjective Optimization of Geological CO 2 Storage Performance under Geomechanical Risks

In geological CO 2 storage, designing the optimal well control strategy for CO 2 injection to maximize CO 2 storage while minimizing the associated geomechanical risks is not trivial. This challenge arises due to pressure buildup, CO 2 plume migration, the highly nonlinear nature of geomechanical responses to rock-fluid interaction, and the high computational cost associated with coupled flow and geomechanics simulations. In this paper, we introduce a novel optimization framework to address these challenges. The optimization problem is formulated as follows: maximize total CO 2 storage while minimizing geomechanical risks by adjusting the injection schedules within bounded constraints. The geomechanical risks are primarily driven by injection-induced pressure build-up, which is characterized by ground displacement and the induced microseismicity. We used the Fourier neural operator (FNO)-based deep learning model to construct surrogate models, replacing the time-consuming coupled flow and geomechanics simulations for evaluating the aforementioned objective functions. The developed surrogate models have been incorporated into a multiobjective optimization framework through a genetic algorithm to reduce the computational burden. The proposed optimization framework reduces the computational cost from approximately 2,400 hours, when using objective function evaluations based on physics-based simulations, to around 20 minutes. A set of Pareto-optimal solutions of the proposed workflow yields nontrivial optimal decisions, reducing the microseismicity potential and the vertical displacement. This Pareto front highlights the optimal trade-offs between CO 2 storage amount, safety, and ground displacement, emphasizing the need for careful optimization and management of injection strategies to achieve a balanced outcome. The novelty of this work is twofold. First, we demonstrate the importance of incorporating the minimization of the geomechanical risks as objective functions into the CO 2 storage optimization workflow to mitigate the potential risk of induced microseismicity and ground displacement. Second, we leverage the FNO-based surrogate models to optimize a real-field CO 2 storage operation.

42 ENGINEERING↗

Designing a Comprehensive IDS Strategy for a Zero Trust Architecture Environment

Zero Trust Architecture or ZTA is a cybersecurity model for enterprises to structure their networked resources around to maintain total security externally and internally. In a Zero Trust environment, no part of the network is considered "trustworthy" and thus should be scrutinized and monitored extensively as is done in traditional "Trust But Verify" schemes at the network's perimeter. In this way, Zero Trust Architecture is a superior model for securing access to networked resources at the enterprise level. Fermilab, in pursuit of a better security posture, has decided to embrace this model of architecture for its network. Attaining this goal requires tremendous infrastructural, policy, and procedural adjustments that will affect all the lab's personnel and resources.

D'Antonio, Lucas↗

Associative programming language and virtual associative access manager

APL provides convenient associative data manipulation functions in a high level language. Six statements were added to PL/1 via a preprocessor: CREATE, INSERT, FIND, FOR EACH, REMOVE, and DELETE. They allow complete control of all data base operations. During execution, data base management programs perform the functions required to support the APL language. VAAM is the data base management system designed to support the APL language. APL/VAAM is used by CADANCE, an interactive graphic computer system. VAAM is designed to support heavily referenced files. Virtual memory files, which utilize the paging mechanism of the operating system, are used. VAAM supports a full network data structure. The two basic blocks in a VAAM file are entities and sets. Entities are the basic information element and correspond to PL/1 based structures defined by the user. Sets contain the relationship information and are implemented as arrays.

Carol Price↗

Theory of electromagnetic transmission structures. I - Relativistic foundation and network formalisms

A new theorem on a class of four-dimensional skew-symmetric tensors is demonstrated. Coupled with the relativistic covariant form of Maxwell's equations, this theorem consolidates the classifications of guided waves by combining the three types - TE, TM, TEM - under a uniform condition applied to the generating four-potential which is Lorentz invariant. Each type corresponds to a potential of which a pair of the four components vanishes in a particular frame. Through appropriate normalization conditions, the resulting time-domain equations for the field amplitudes are readily reduced to modified telegraphist equations, which in turn lead to distributed network representations for each of the three types. The ambiguity of distributed network formalisms in general is elucidated and the concept of network parameter densities such as traditionally employed in TEM transmission line theory is questioned.

Gabriel, G. J.↗

Sub-T/g/ annealing studies of advanced epoxy-matrix graphite-fiber-reinforced composites

Annealing at temperatures below the glass transition temperature (sub-T/g/ annealing) in structural epoxy network glasses is found to affect long-term mechanical properties of symmetrically (+ or - 45 deg) reinforced 16-lamina graphite/epoxy composites. Post-cured specimens of Thornel 300 graphite/Narmco 5208 epoxy are sub-T(g) annealed at 140 C for about 10, 100, 1000, 10,000, and 100,000 min with a prior quenching above T(g). The ultimate tensile strength, strain-to-break, and static toughness of the composite materials are found to decrease as a function of sub-T(g) annealing time, while no weight loss is observed. Time-dependent changes in properties are explained by a physical aging concept based on free-volume decreases in the nonequilibrium glassy state of network epoxies, and results imply that changes in composite properties may occur with the service time.

Kong, E. S. W.↗

MSAT network architecture

The Mobile Satellite (MSAT) communications system will support mobile voice and data services using circuit switched and packet switched facilities with interconnection to the public switched telephone network and private networks. Control of the satellite network will reside in a Network Control System (NCS) which is being designed to be extremely flexible to provide for the operation of the system initially with one multi-beam satellite, but with capability to add additional satellites which may have other beam configurations. The architecture of the NCS is described. The signalling system must be capable of supporting the protocols for the assignment of circuits for mobile public telephone and private network calls as well as identifying packet data networks. The structure of a straw-man signalling system is discussed.

Davies, N. G.↗

Software For Graphical Representation Of A Network

System Visualization Tool (SVT) computer program developed to provide systems engineers with means of graphically representing networks. Generates diagrams illustrating structures and states of networks defined by users. Provides systems engineers powerful tool simplifing analysis of requirements and testing and maintenance of complex software-controlled systems. Employs visual models supporting analysis of chronological sequences of requirements, simulation data, and related software functions. Applied to pneumatic, hydraulic, and propellant-distribution networks. Used to define and view arbitrary configurations of such major hardware components of system as propellant tanks, valves, propellant lines, and engines. Also graphically displays status of each component. Advantage of SVT: utilizes visual cues to represent configuration of each component within network. Written in Turbo Pascal(R), version 5.0.

Mcallister, R. William↗