bluuebunny/crossref_metadata_2025 huggingface dataset:
Decomposing Cognitive Processes in the mPFC During Self-Thinking
Authors: Levorsen Marie , Aoki Ryuta , Sedikides Constantine , Izuma Keise
Published: November 2024

Past cognitive neuroscience research has demonstrated that thinking about both the self and other activate the medial prefrontal cortex (mPFC), a central hub of the default mode network. The mPFC is also implicated in other cognitive processes, such as introspection and autobiographical memory, rendering elusive its exact role during thinking about the self. Specifically, it is unclear whether the same cognitive process explains the common mPFC involvement or distinct processes are responsible for the mPFC activation overlap. In this preregistered functional magnetic resonance imaging study, we investigated whether and to what extent mPFC activation patterns during self-reference judgment could be explained by activation patterns during the tasks of other-reference judgment, introspection, and autobiographical memory. Multi-voxel pattern analysis showed that only in the mPFC were neural responses both concurrently different and similar across tasks. Furthermore, multiple regression and variance partitioning analyses indicated that each task (i.e., other-reference, introspection, memory) uniquely and jointly explained significant variance in mPFC activation during self-reference. These findings suggest that the self-reference task involves multiple cognitive processes shared with other tasks, and the mPFC is the unique place where necessary information is gathered and integrated for judgments based on internally constructed representations.
From naïve pluripotency to human neural organoids through a three-dimensional morphogenetic continuum
Authors: Laterza Cecilia , Cesare Elisa , Stuart Hannah T. , D’Ercole Martina , Gesualdo Alessia , La Barbera Maria Grazia , Brignani Sara , Ribecco Carmela , Polli Roberta , Frison Roberta , Angiolillo Silvia , Maset Andrea , Gagliano Onelia , Cacchiarelli Davide , Briscoe James , Tanaka Elly M. , Murgia Alessandra , Elvassore Nicola
Published: November 2024

Human central nervous system (CNS) development involves complex transitions from pluripotency to regionalised neural tissues. The early phases of this process are inaccessible in humans but can potentially be modelledin vitrousing brain organoids, including to study neurodevelopmental disorders. However, current methods are based on post-implantation-like human pluripotent stem cells (hPSCs), which exhibit a hypermethylated state and show epigenetic memory retention. Here we developed a 3D model of human CNS development, starting from naïve human induced PSCs (hiPSCs), which exhibit a hypomethylated pre-implantation-like state of pluripotency and develop into 3D neuroepithelial cysts in a timely morphogenetic continuum. Upon treatment with appropriate signalling cues, naïve-derived neuroepithelial cysts can be specified toward different axial identities. Extended culture of anterior-specified organoids results in forebrain-like structures containing both dorsal and ventral neural precursors as well as mature neurons, exhibiting appropriate cellular diversity and functional properties. We applied this system to model Fragile X Syndrome (FXS), an epigenetically regulated neurodevelopmental disorder. We found that FXS patient-derived naïve hiPSCs, initially demethylated at theFmr1locus, gradually underwent remethylation during organoid development. In addition,Fmr1silencing started much earlier than can be detected by pre-natal analysis, and is concomitant with the development of mosaicisms. Our approach provides a new platform for studying human CNS development, including early epigenetic events and regional patterning, demonstrating the potential of naïve hiPSC-derived organoids for modelling neurodevelopmental disorders with complex epigenetic regulation.

Highlights

- single naïve hiPSCs differentiate into 3D neuroepithelial cysts in a timely morphogenetic continuum

- signalling cues at appropriate developmental transitions can direct naïve hiPSC- derived organoids to different regional identities of the human CNS

- naïve hiPSC-derived forebrain organoids display cellular complexity representing both dorsal and ventral identities

- forebrain organoids from Fragile X Syndrome patients recapitulate the genetic instability and epigenetic dysregulation ofFmr1locus.
Computational analysis of morphological changes inLactiplantibacillus plantarumunder acidic stress
Authors: Venugopal Athira , Steinberg Doron , Moyal Ora , Yonnasi Shira , Glaicher Noga , Gitelman Eliraz , Shemesh Moshe , Amitay Moshe
Published: November 2024

Cell shape and size often define characteristics of individual or communities of microorganisms in changing environments. Hence, characterizing cell morphology using computational image analysis can aid in the accurate identification of bacterial responses to these changes. Modifications in cell morphology ofLactiplantibacillus plantarumwere determined in response to acidic stress, specifically during growth stage of the cells at pH 3.5 compared to pH 6.5.

Consequently, we developed a computational method to sort, detect, analyze, and measure bacterial size in a single-species culture. We applied a deep learning methodology composed of object detection followed by image classification to measure the bacterial cell dimensions of the pre-identified cells.

The results of our computational analysis show a significant change in cell morphology in response to alteration of environmental pH. Specifically, we found that the cell was dramatically elongated at low pH, while the width was not altered. Those changes could be attributed to modifications in membrane properties, for instance increased cell membrane fluidity in acidic pH.

Integration of deep learning with microbial microscopic imaging is an advanced methodology for studying cellular structures. These trained models and scripts can be applied to other microbes and cells and are publicly available at:https://github.com/OraMoyal26/bacteria_dimensions/tree/main
Sequence specificity of an essential nuclear localization sequence in Mcm3
Authors: Wang Ziyi , Zhang Yun Jing , Zhang Qian-yi , Bilsborrow Kate , Leslie Matthew , Suhandynata Raymond T. , Zhou Huilin
Published: November 2024

Proteins with nuclear localization sequences (NLSs) are directed into the cell nucleus through interactions between the NLS and importin proteins. NLSs are generally short motifs rich in basic amino acids; however, identifying NLSs can be challenging due to the lack of a universally conserved sequence. In this study, we characterized the sequence specificity of an essential and conserved NLS in Mcm3, a subunit of the replicative DNA helicase. Through mutagenesis and AlphaFold 3 (AF3) modeling, we demonstrate that the precise positioning of basic residues within the NLS is critical for nuclear transport of Mcm3 through optimal interactions with importin. Disrupting these interactions impairs the nuclear import of Mcm3, resulting in defective chromatin loading of MCM and poor cell growth. Our results provide a structure-guided framework for predicting and analyzing monopartite NLSs, which, despite lacking a single consensus sequence, retain key characteristics shared between the NLSs of Mcm3 and the SV40 large T antigen.

Author Summary

Transporting proteins into and out of the cell nucleus is essential for chromosome-associated activities. Nuclear localization sequences (NLSs), short motifs rich in basic amino acids, are commonly found in nuclear proteins. NLSs work by interacting with importin, a key transport receptor responsible for recognizing and guiding NLS-containing proteins through the nuclear pore complex into the nucleus. Other than being rich in basic amino acids, NLSs generally lack a discernible consensus sequence, raising questions about how they specifically control nuclear transport through their interactions with importins. Through a detailed mutagenesis study of a conserved and essential NLS in Mcm3, a subunit of the replicative DNA helicase, we demonstrate that the use of AlphaFold 3 (AF3), alongside genetic, biochemical, and cell biological analyses, define key contacts between Mcm3’s NLS and importin that are required for nuclear import of Mcm3.
Unveiling novel mechanisms of strobilurin resistance in the cacao pathogenMoniliophthora perniciosa
Authors: Prado P.F.V. , Mendes C.V.C. , Pires B.A. , Fiorin G.L. , Mieczkowski P. , Pereira G.A.G. , Teixeira P.J.P.L. , Thomazella D.P.T.
Published: November 2024

Witches’ broom disease (WBD) is a major constraint for cacao production in the Americas. The severe socioeconomic impact of WBD encouraged the evaluation of different control strategies, including the use of strobilurin fungicides. These molecules inhibit mitochondrial respiration, thus impairing ATP generation and leading to oxidative stress. These chemicals, however, have proven ineffective against the WBD pathogenMoniliophthora perniciosa. Here, we demonstrate thatM. perniciosatolerates high concentrations of strobilurins underin vitroconditions and highlight a set of molecular alterations that correlate with strobilurin tolerance in this fungus. Short-term exposure ofM. perniciosato the commercial strobilurin azoxystrobin led to the up-regulation of genes encoding enzymes of the glyoxylate cycle, gluconeogenesis, and fatty acid and amino acid catabolism, indicating that the fungal metabolism is remodeled to compensate for reduced ATP production. Furthermore, cell division, ribosome biogenesis, and sterol metabolism were repressed, which agrees with the impaired mycelial growth on azoxystrobin. Genes associated with cellular detoxification and response to oxidative stress (e.g., cytochrome P450s, membrane transporters and glutathione s-transferases) were strongly induced by the drug and represent potential strategies used by the pathogen to mitigate the toxic effects of the fungicide. Remarkably, exposure ofM. perniciosato azoxystrobin resulted in the spontaneous generation of a mutant with increased resistance to strobilurin. Comparative genomics and transcriptomics revealed alterations that may explain the resistance phenotype, including a large deletion in a putative transcriptional regulator and significant changes in the mutant transcriptome. Overall, this work provides important advances towards a comprehensive understanding of the molecular basis of strobilurin resistance in a tropical fungal pathogen. This is a fundamental step to efficiently employ these fungicides in agriculture and to prevent the emergence of strobilurin resistance.
Identification and characterization of substrate- and product-selective nylon hydrolases
Authors: Drufva Erin E. , Cahill John F. , Saint-Vincent Patricia M.B. , Williams Alexis N. , Bocharova Vera , Capra Nikolas , Meilleur Flora , Carper Dana L. , Bourgery Célestin , Miyazaki Kaito , Yonemura Maina , Shiraishi Yuki , Parks Jerry M. , Zhou Muchu , Dishner Isaiah T. , Foster Jeffrey C. , Koehler Stephen J. , Valentino Hannah R. , Sedova Ada , Kertesz Vilmos , Vasileva Delyana P. , Hochanadel Leah H. , Figg C. Adrian , Negoro Seiji , Kato Dai-ichiro , Chen Serena H. , Michener Joshua K.
Published: November 2024

Enzymes have evolved to rapidly and selectively hydrolyze diverse natural and anthropogenic polymers, but only a limited group of related enzymes have been shown to hydrolyze synthetic polyamides. In this work, we synthesized and characterized a panel of 95 diverse enzymes from the N-terminal nucleophile hydrolase superfamily with 30-50% pairwise amino acid identity. We found that nearly 40% of the enzymes had substantial nylon hydrolase activity, in many cases comparable to that of the best-characterized nylon hydrolase, NylC. There was no relationship between phylogeny and activity, nor any evidence of prior selection for nylon hydrolase activity. Several newly-identified hydrolases showed significant substrate selectivity, generating up to 20-fold higher product titers with Nylon 6,6 versus Nylon 6. Finally, we determined the crystal structure and oligomerization state of a Nylon 6,6-selective hydrolase to elucidate structural factors that could affect activity and selectivity. These new enzymes provide insights into the widespread potential for nylon hydrolase evolution and opportunities for analysis and engineering of improved hydrolases.

Significance

Nylons are common industrial polyamides with few recycling options. As an alternative to mechanical or chemical recycling, enzymes may provide a selective and energy-efficient route to deconstruct nylons from mixed waste. Several nylon hydrolases have been identified, most notably NylC, but these enzymes are all closely related and demonstrated similar activity and substrate range. In this work, we investigated a diverse set of enzymes and showed that nylon hydrolase activity is common, providing new insights into the evolution of microbial nylon hydrolysis. Unlike NylC, several enzymes demonstrated unprecedented substrate selectivity, preferentially hydrolyzing Nylon 6,6 compared to Nylon 6. These enzymes can be used to understand substrate selectivity in nylon hydrolysis and to engineer enzymes for nylon recycling from mixed waste.
Spontaneous Brain Dynamics Associated With Acceleration Of Long-term Functional Connectome In Postnatal Development
Authors: Ma Liang , Shultz Sarah , Fu Zening , Seraji Masoud , Iraji Armin , Calhoun Vince
Published: November 2024

The first six postnatal months are a critical period for brain development, marked by rapid changes in functional neural circuits. However, long-term changes in neonatal functional connectome lacks an interpretive imaging indicator for the future development due to the non-linearity characteristics. In this study, we introduce an approach to extract intrinsic brain states from short-term brain dynamics to study the long-term (longitudinal) development. We found a high association (r=0.460) between the co-activated pattern of specific brain state and the acceleration pattern of non-linear development of static functional connectome. The fractional occupancy, self-sustaining probability of this short-term state share the similar age tendency with the long-term change rate within the majority of the function connectome. These findings suggest that short-term brain dynamics could serve as potential biomarkers for predicting the long-term development of functional connectome.
Leaf size determines damage- and herbivore-induced volatile emissions in maize
Authors: Waterman Jamie M. , Cofer Tristan M. , Von Laue Ophélie M. , Mateo Pierre , Wang Lei , Erb Matthias
Published: November 2024

Stress-induced plant volatiles play an important role in mediating ecological interactions between plants and their environment. The timing and location of the inflicted damage is known to influence the quality and quantity of induced volatile emissions. However, how leaf characteristics and herbivore feeding behavior interact to shape volatile emissions is not well understood. Using a high-throughput volatile profiling system with high temporal resolution, we examined how mechanical damage and herbivore feeding on different leaves shapes plant-level volatile emission patterns in maize. We then tested feeding patterns and resulting consequences on volatile emissions with two generalist herbivores (Spodoptera exiguaandSpodoptera littoralis), and assessed whether feeding preferences are associated with enhanced herbivore performance. We found maize seedlings emit more volatiles when larger leaves are damaged. Larger leaves emitted more volatiles locally, which was the determining factor for higher plant-level emissions. Surprisingly, bothS. exiguaandS. littoralispreferentially consumed larger leaves, and thus maximize plant volatile emission without apparent growth benefits. Together, these findings provide an ecophysiological and behavioral mechanism for plant volatile emission patterns, with potentially important implications for volatile-mediated plant-environment interactions.
SingleMAPTknock-in mouse models of frontotemporal dementia for sharing with the neurodegenerative research community
Authors: Morito Takahiro , Qi Mohan , Kamano Naoko , Sasaguri Hiroki , Bez Sumi , Foiani Martha , Duff Keren , Benner Seico , Endo Toshihiro , Hama Hiroshi , Kurokawa Hiroshi , Miyawaki Atushi , Mizuma Hiroshi , Sahara Naruhiko , Shimojo Masafumi , Higuchi Makoto , Saido Takaomi C. , Watamura Naoto
Published: November 2024

We recently reported development of humanMAPTknock-in mice that carry single or double pathogenic mutations of frontotemporal dementia. However, it takes more than 14 months for the line with the most aggressive phenotypes to exhibit tau pathology without forming high-order tau oligomers, along with concomitant abnormal behavior. We thus generatedMAPTknock-in mice carrying triple mutations, among which theMAPTP301S;Int10+3;S320Fline exhibited robust pathology starting earlier than 6 months. Tau accumulation took place mainly in the thalamus, hypothalamus, amygdala and entorhinal cortex, but less so in the hippocampus, leading to synaptic loss, atrophy and behavioral abnormalities. CrossbreedingMAPTP301S;Int10+3;S320FwithAppknock-in miceAppNL-G-Fresulted in the manifestation of tau pathology in the hippocampus and cortex. These mutant mice will be valuable tools for understanding the mechanisms of frontotemporal dementia, Alzheimer’s disease and other tauopathies.
Bone Morphogenetic Protein signaling pathway – ethanol interactions disrupt palate formation independent ofgata3
Authors: Lovely C. Ben
Published: November 2024

Fetal Alcohol Spectrum Disorders (FASD) describes a wide array of neurological defects and craniofacial malformations, associated with ethanol teratogenicity. While there is growing evidence for a genetic component to FASD, little is known of the genes underlying these ethanol-induced defects. Along with timing and dosage, genetic predispositions may help explain the variability within FASD. From a screen for gene-ethanol interactions, we found that mutants for Bmp signaling components are ethanol-sensitive leading to defects in the zebrafish palate. Loss of Bmp signaling results in reductions ingata3expression in the maxillary domain of the neural crest in the 1st pharyngeal arch, leading to palate defects while upregulation of humanGATA3rescues these defects. Here, we show that ethanol-treated Bmp mutants exhibit misshaped and/or broken trabeculae. Surprisingly, up regulation ofGATA3does not rescue ethanol-induced palate defects andgata3expression was not altered in ethanol-treated Bmp mutants or dorsomorphin-treated larvae. Timing of ethanol sensitivity shows that Bmp mutants are ethanol sensitive from 10-18 hours post-fertilization (hpf), prior to Bmp’s regulation ofgata3in palate formation. This is consistent with our previous work with dorsomorphin-dependent knock down of Bmp signaling from 10-18 hpf disrupting endoderm formation and subsequent jaw development. Overall, this suggests that ethanol disrupts Bmp-dependent palate development independent of and earlier than the role ofgata3in palate formation by disrupting epithelial development. Ultimately, these data demonstrate that zebrafish is a useful model to identify and characterize gene-ethanol interactions and this work will directly inform our understanding of FASD.

Highlights

Bmp pathway mutants are ethanol sensitive resulting in palate defects.

Ethanol disrupts Bmp-dependent palate development independent ofgata3.

Timing of ethanol sensitivity suggests ethanol disrupts Bmp-dependent epithelial morphogenesis.
Quantum limits of superconducting-photonic links and their extension to millimeter waves
Authors: Multani Kevin K.S. , Jiang Wentao , Nanni Emilio A. , Safavi-Naeini Amir H.
Published: November 2024

Photonic addressing of superconducting circuits has been proposed to overcome wiring complexity and heat-load challenges. However, such superconducting-photonic links suffer from an efficiency-noise trade-off that limits scalability. This trade-off arises because increasing power conversion efficiency entails reducing optical power, which makes the converted signal susceptible to shot noise. We analyze this trade-off and find that the laser-driven qubit gate infidelity scales inversely with the number of photons used. While methods such as nonlinear detection or squeezed light could mitigate this effect, we consider generating higher-frequency electrical signals, such as millimeter waves (100 GHz), using laser light. At these higher frequencies, circuits have higher operating temperatures and cooling power budgets and alleviate constraints posed by the trade-off. Therefore, we demonstrate an optically driven cryogenic millimeter-wave source with a maximum power efficiency of 8×10−5 that can generate a maximum of 0.7μW of 80 GHz power, with a 1200-thermal-photon equivalent of added noise at 4K. Using this source, we perform frequency-domain spectroscopy of superconducting NbTiN resonators at 80–90 GHz. Our results show a promising approach to lessen the efficiency-noise constraints on superconducting-photonic links, while leveraging the benefits of photonic signal delivery. Further optimization of power efficiency and noise at high frequencies could make scalable photonic control of superconducting qubits viable at temperatures exceeding 1K.

Published by the American Physical Society
2024
Dark sector tunneling field potentials for a dark big bang
Authors: Casey Richard , Ilie Cosmin
Published: November 2024

All of the significant evidence for dark matter observed thus far has been through its gravitational interactions. After 40 years of direct detection experiments, the parameter space for weakly interacting massive particles (WIMPs) as dark matter candidates is rapidly approaching the neutrino floor. Moreover, there have been no signs of WIMPs in any particle production experiments so far. In this light, we consider a dark sector that is strongly decoupled from the visible sector, interacting exclusively through gravity. In this model, proposed by Freese and Winkler [Dark matter and gravitational waves from a dark big bang, ], dark matter can be produced through a first-order phase transition in the dark sector dubbed “the dark big bang.” We fully determine the allowed region of parameter space for the tunneling potential that leads to the realization of a dark big bang and is consistent with all experimental bounds available.

Published by the American Physical Society
2024
Machine learning potential for the Cu-W system
Authors: Liyanage Manura , Turlo Vladyslav , Curtin W. A.
Published: November 2024

Combining the excellent thermal and electrical properties of Cu with the high abrasion resistance and thermal stability of W, Cu-W nanoparticle-reinforced metal matrix composites and nano-multilayers are finding applications as brazing fillers and shielding material for plasma and radiation. Due to the large lattice mismatch between fcc Cu and bcc W, these systems have complex interfaces that are beyond the scales suitable for methods, thus motivating the development of chemically accurate interatomic potentials. Here, a neural network potential (NNP) for Cu-W is developed within the Behler-Parrinello framework using a curated training dataset that captures metallurgically relevant local atomic environments. The Cu-W NNP accurately predicts (i) the metallurgical properties (elasticity, stacking faults, dislocations, thermodynamic behavior) in elemental Cu and W, (ii) energies and structures of Cu-W intermetallics and solid solutions, and (iii) a range of fcc Cu/bcc W interfaces, and exhibits physically reasonable behavior for solid W/liquid Cu systems. As will be demonstrated in forthcoming work, this near accurate NNP can be applied to understand complex phenomena involving interface-driven processes and properties in Cu-W composites.

Published by the American Physical Society
2024
Protocol for nearly deterministic parity projection on two photonic qubits
Authors: Liu Chenxu , Frantzeskakis Rafail , Economou Sophia E. , Barnes Edwin
Published: November 2024

Photonic parity projection plays an important role in photonic quantum information processing. Nondestructive parity projections normally require high-fidelity controlled-Z gates between photonic and matter qubits, which can be experimentally demanding. In this paper, we propose a nearly deterministic parity projection protocol on two photonic qubits which only requires stable matter-photon controlled-phase gates. We also demonstrate that our protocol can tolerate moderate Gaussian phase errors in the controlled-phase gates as well as Pauli errors on the matter qubits. The fact that our protocol does not require perfect controlled-Z gates makes it more amenable to experimental implementation. Although we focus on photonic qubits, our protocol can be applied to any physical system or circuit with imperfect controlled-Z gates. Our protocol also provides a new optimization space for parity projection operations on various physical platforms, which is potentially beneficial for achieving high-fidelity parity projection operations.

Published by the American Physical Society
2024
Emergent topological quasiparticle kinetics in constricted nanomagnets
Authors: Guo J. , Hill D. , Lauter V. , Stingaciu L. , Zolnierczuk P. , Ullrich C. A. , Singh D. K.
Published: November 2024

The ubiquitous domain wall kinetics under magnetic field or current application describes the dynamic properties in nanostructured magnets. However, when the geometrical size of a nanomagnetic system is constricted to the limiting domain wall length scale, the competing energetics between anisotropy, exchange, and dipolar interactions can cause emergent kinetics due to quasiparticle relaxation, similar to bulk magnets of atomic origin. This paper presents a joint experimental and theoretical study to support this argument: constricted nanomagnets, made of antiferromagnetic and paramagnetic neodymium thin film with honeycomb motif, reveal fast kinetic events at picosecond timescales due to the relaxation of topological quasiparticles that persist to low temperature in the absence of any external stimuli. This discovery is especially important considering the fact that paramagnets or antiferromagnets have no net magnetization. Yet, the kinetics in neodymium nanostructures is quantitatively similar to that found in ferromagnetic counterparts and only varies with the thickness of the specimen. This suggests that a universal, topological quasiparticle-mediated dynamical behavior can be prevalent in nanoscopic magnets, irrespective of the nature of the underlying magnetic material.

Published by the American Physical Society
2024
Entanglement fractalization
Authors: Zhou Yao , Ye Peng
Published: November 2024

We numerically explore the interplay of fractal geometry and quantum entanglement by analyzing the von Neumann entropy (known as entanglement entropy) and the entanglement contour in the scaling limit. Adopting quadratic fermionic models on Sierpinski carpet, we uncover intriguing findings. For gapless ground states exhibiting a finite density of states at the chemical potential, we reveal a super-area law characterized by the presence of a logarithmic correction for area law in the scaling of entanglement entropy. This extends the well-established super-area law observed on translationally invariant Euclidean lattices where the Gioev-Klich-Widom conjecture regarding the asymptotic behavior of Toeplitz matrices holds significant influence. Furthermore, different from the fractal structure of the lattice, we observe the emergence of a self-similar and universal pattern termed an “entanglement fractal” in the entanglement contour data as we approach the scaling limit. Remarkably, this pattern bears resemblance to intricate Chinese paper-cutting designs. We provide general rules to artificially generate this fractal, offering insights into the universal scaling of entanglement entropy. Meanwhile, as the direct consequence of the entanglement fractal and beyond a single scaling behavior of entanglement contour in translation-invariant systems, we identify two distinct scaling behaviors in the entanglement contour of fractal systems. For gapped ground states, we observe that the entanglement entropy adheres to a generalized area law, with its dependence on the Hausdorff dimension of the boundary between complementary subsystems.

Published by the American Physical Society
2024
Local Density Approximation for Excited States
Authors: Gould Tim , Pittalis Stefano
Published: November 2024

The ground state of an homogeneous electron gas is a paradigmatic state that has been used to model and predict the electronic structure of matter at equilibrium for nearly a century. For half a century, it has been successfully used to predict ground states of quantum systems via the local density approximation (LDA) of density functional theory (DFT), and systematic improvements in the form of generalized gradient approximations and evolution thereon. Here, we introduce the LDA for excited states by considering a particular class of nonthermal ensemble states of the homogeneous electron gas. These states find sound foundation and application in ensemble DFT—a generalization of DFT that can deal with ground and excited states on equal footing. The ensemble LDA is shown to successfully predict difficult low-lying excitations in atoms and molecules for which approximations based on local spin density approximation and time-dependent LDA fail.

Published by the American Physical Society
2024
Protein Design by Integrating Machine Learning and Quantum-Encoded Optimization
Authors: Panizza Veronica , Hauke Philipp , Micheletti Cristian , Faccioli Pietro
Published: November 2024

The protein design problem involves finding polypeptide sequences folding into a given three-dimensional structure. Its rigorous algorithmic solution is computationally demanding, involving a nested search in sequence and structure spaces. Structure searches can now be bypassed thanks to recent machine-learning breakthroughs, which have enabled accurate and rapid structure predictions. Similarly, sequence searches might be entirely transformed by the advent of quantum annealing machines and by the required new encodings of the search problem, which could be performative even on classical machines. In this work, we introduce a general protein design scheme where algorithmic and technological advancements in machine learning and quantum-inspired algorithms can be integrated, and an optimal physics-based scoring function is iteratively learned. In this first proof-of-concept application, we apply the iterative method to a lattice protein model amenable to exhaustive benchmarks, finding that it can rapidly learn a physics-based scoring function and achieve promising design performances. Strikingly, our quantum-inspired reformulation outperforms conventional sequence optimization even when adopted on classical machines. The scheme is general and can be extended, e.g., to encompass off-lattice models, and it can integrate progress on various computational platforms, thus representing a new paradigm approach for protein design.

Published by the American Physical Society
2024
Exploring the views and experiences of professionals using PBS and emotional development assessment for individuals with an intellectual disability: a case study
Authors: McCarthy Freya Elizabeth Rose , Simpson Stephanie Jane
Published: November 2024

Purpose

The purpose of this paper was to investigate the utility of including emotional development (ED) assessment into a Positive Behaviour Support (PBS) approach in clinical practice with a patient with an intellectual disability (ID) and challenging behaviour.

Design/methodology/approach

Interviews were conducted with four staff involved in the care of the patient. The interviews were transcribed and analysed using thematic analysis and three reflective sessions were completed with the lead psychologist of the service.

Findings

Using thematic analysis, four themes were identified: getting everyone around the table: a collaborative approach, complementary approaches: a feedback loop, helping to make sense of the individual and ensuring a voice for service users.

Research limitations/implications

This was a case study selected from routine clinical practice and as such generalisability may be limited. This case study was designed as an exploration of the potential benefits of incorporating ED alongside PBS for ID and provides a basis for future research.

Practical implications

This study highlights the value of integration of ED assessment for people with ID and challenging behaviour within a healthcare team.

Originality/value

There is a lack of literature relating to ED and challenging behaviour within an ID population, particularly exploring ED within a PBS framework. This study provides a starting point for exploring how practice can be improved through incorporating ED assessment for individuals with ID and challenging behaviour.
Bending analysis of viscoelastic plates according to the Reissner’s theory using meshless local Petrov–Galerkin method and hereditary integral formulation
Authors: Monnerat Daniel Dias , Santiago José Antonio Fontes , Telles José Claudio de Faria , Cezario Flavio , Riobom Neto Carlos Gouveia , Costa Edmundo Guimarães de Araújo
Published: November 2024

Purpose

The purpose of this study is to apply the Meshless Local Petrov–Galerkin (MLPG) method to solve the bending problems of linear viscoelastic plates, considering Reissner’s theory.

Design/methodology/approach

The weak formulation for the set of equations that govern Reissner’s plate theory is implemented in conjunction with the integral formulation applied to viscoelastic constitutive expressions. A meshless method based on the Moving Least Squares (MLS) approximation is considered in the numerical implementation. The final equation system is assembled by adopting simple and efficient schemes for numerical integration, considering a simplified formulation through centralization of the local interpolation domains and Gaussian quadrature at the same field point. The results obtained are compared with available solutions to demonstrate the efficiency of the proposed formulation.

Findings

The hereditary integral approach proved to be the most general way to analyze the viscoelastic problem, especially when applied together with the modified scheme for numerical integration. In addition, the variable changing technique is demonstrated to be an efficient formulation for solving shear-locking effects in thin plate problems.

Originality/value

The differential of the present study is related to the manner in which the properties of linear viscoelastic materials are considered in the formulation. Although most authors consider this point through the application of the correspondence principle, the present study works with a hereditary integral formulation. In addition, the variable changing technique is applied to solve the shear-locking effects, and an alternative approximation technique is considered to speed up the numerical integration process.
Optimising Malaysia’s power mix for a sustainable future: a multi-scenario modelling approach
Authors: Woo Wing Thye , Leong Yuen Yoong , Low Wai Sern , Liew Jin Soong , Lee Chean Chung
Published: November 2024

Purpose

This study employs advanced modelling to assess the effectiveness of Malaysia’s current energy policies in achieving a low-carbon future. By optimising a 100% renewable energy mix, including energy storage, the research identifies pathways to decarbonise the power sector while minimising costs. These findings will inform the development of future policies.

Design/methodology/approach

This study employs the Stockholm Environment Institute-developed Low Emissions Analysis Platform (LEAP) and Next Energy Modeling system for Optimization (NEMO) to construct and optimise a comprehensive Malaysian power sector model. The model encompasses both electricity supply, including diverse electricity generation sources and demand across key sectors. Three scenarios – existing policy, optimised existing policy and more ambitious policy (near-zero emissions) – are analysed.

Findings

Solar photovoltaic (PV) is the dominant technology, but realising its full potential requires significant grid upgrades. While natural gas expansion underpins Malaysia’s decarbonisation strategy, solar and storage offer a cleaner and potentially cost-effective alternative. Rapid technological advancements in clean energy increase stranded asset risk for new gas power plants. Malaysia’s abundant bioenergy resources need more tapping. This can contribute to decarbonisation and rural development. Transitioning to a fully renewable grid necessitates substantial investments in energy storage and grid infrastructure. While falling battery costs and regional interconnection can mitigate costs, careful consideration of potential disruptions and cost fluctuations is essential for resilience.

Research limitations/implications

Energy sector modelling results are inherently dependent on input assumptions, such as future technology costs, resource availability and fossil fuel prices. These factors can be highly uncertain. While this study did not conduct sensitivity analyses to explore how variations in these assumptions might affect the results (e.g. cost variations across scenarios, technology mix fluctuations), the core findings provide valuable insights into potential decarbonisation pathways for Malaysia’s power sector. Future studies could build upon this work by incorporating sensitivity analyses to provide a more comprehensive understanding of how key results might change under a wider range of future possibilities.

Originality/value

This study co-optimises a 100% renewable energy mix for Malaysia, incorporating a comprehensive range of renewable resources, battery and pumped hydro storage. The research also provides a unique perspective on the interplay of philosophical underpinnings, psychological maturity and energy policy.
Financial education and budgeting behavior among college students: extending the theory of planned behavior
Authors: Tan Xiawei , Xiao Jing Jian , Meng Kexin , Xu Jiuping
Published: November 2024

Purpose

This study examines the association between financial education and budgeting behavior among college students. Under the guidance of the extended theory of planned behavior, we use a comprehensive measure of budgeting behavior and explore mediating factors between financial education and budgeting behavior.

Design/methodology/approach

Financial education was measured by both frequency and intensity of taking courses in finance and economics in college. Data from a sample of college students across China were analyzed using structural equation modeling and serial mediation analysis to explore the mediating roles of attitudes, subjective norms, perceived control and budgeting intentions in this relationship between financial education and budgeting behavior.

Findings

Budgeting intentions alone did not mediate the relationship between financial education and budgeting behavior. However, the serial mediation involving attitudes, subjective norms and budgeting intentions was significant.

Practical implications

The findings of this study have significant implications for financial educators, universities, governments and families. Financial educators should prioritize budgeting in curricula and aim to enhance students’ budgeting attitudes and intentions. Universities should enhance their financial education offerings, while governments and families should foster supportive environments and positive norms and attitudes around budgeting.

Originality/value

This research contributes a nuanced measurement of budgeting, analyzes the link between financial education and budgeting behavior among college students and highlights the roles of various components of the theory of planned behavior. It extends the theory by identifying how financial attitudes, subjective norms and budgeting intentions mediate the relationship between financial education and budgeting behavior.
Consumer impatience in the e-commerce home delivery context: a consumer-centric supply chain perspective for time-based competition
Authors: Paluzzi Haley , Chen Haozhe , Howe Michael , Daugherty Patricia J. , Tokar Travis
Published: November 2024

Purpose

This paper aims to introduce the concept of consumer impatience, empirically explore how it relates to time-based logistics performance (delivery speed and delivery timeliness) and discuss its impact on consumer satisfaction. This research argues that gaining insights related to delivery performance from a consumer’s perspective can help the development of more effective time-based logistics strategies for e-commerce home deliveries.

Design/methodology/approach

Hypotheses in this study are developed using attribution theory and tested with empirical data collected through an online behavioral consumer experiment. Middle-range theorizing is used to develop an understanding of the mechanisms that impact the relationship between time-based logistics performance and consumer satisfaction.

Findings

Findings indicate that consumer impatience with delivery speed and delivery timeliness play an essential role in the relationship between time-based delivery performance and consumer satisfaction. Issues with delivery timeliness are shown to have a more negative impact on consumer satisfaction than issues with delivery speed, while delivery communication is demonstrated to have a positive relationship with consumer satisfaction.

Originality/value

This empirical study adds to existing time-based competition literature by taking a consumer-centric perspective and bringing a largely overlooked but critical concept – consumer impatience – into the logistics and supply chain management setting. Middle-range theorizing allows for a conceptualized understanding of consumers’ delivery experiences that can help companies develop proactive actions in their time-based competition initiatives.
LLMSARec: large language model with semantic alignment for Web service recommendation
Authors: Feng Shangjie , Cao Buqing , Xie Ziming , Fu Zhongxiang , Peng Zhenlian , Kang Guosheng
Published: November 2024

Purpose

With the continuous increase in Web services, efficient identification of Web services that meet developers’ needs and understanding their relationships remains a challenge. Previous research has improved recommendation effectiveness by using correlations between Web services through graph neural networks (GNNs), while it has not fully leveraged service descriptions, limiting the depth and diversity of learning. To this end, a Web services recommendation method called LLMSARec, based on Large Language Model and semantic alignment, is proposed. This study aims to extract potential semantic information from services and learn deeper relationships between services.

Design/methodology/approach

This method consists of two core modules: profile generation and maximizing mutual information. The profile generation module uses LLM to analyze the descriptions of services, infer and construct service profiles. Concurrently, it uses LLM as text encoders to encode inferred service profiles for enhanced service representation learning. The maximizing mutual information model aims to align the semantic features of the services text inferred by LLM with structural semantic features of the services captured by GNNs, thus achieving a more comprehensive representation of services. The aligned representation serves as an input for the model to identify services with superior matching accuracy, thereby enhancing the service recommendation capability.

Findings

Experimental comparisons and analyses were conducted on the Programmable Web platform data set, and the results demonstrated that the effectiveness of Web service recommendations can be significantly improved by using LLMSARec.

Originality/value

In this study, the authors propose a Web service recommendation approach based on Large Language Model and semantic alignment. By extracting latent semantic information from services and effectively aligning semantic features with structural features, new representations can be generated to significantly enhance recommendation accuracy.
An integrated optimization strategy for mission planning and control resource allocation for long-endurance unmanned aerial vehicle
Authors: Li Kai , Zhu Cheng , Wang Jianjiang , Gao Junhui
Published: November 2024

Purpose

With burgeoning interest in the low-altitude economy, applications of long-endurance unmanned aerial vehicles (LE-UAVs) have increased in remote logistics distribution. Given LE-UAVs’ advantages of wide coverage, strong versatility and low cost, in addition to logistics distribution, they are widely used in military reconnaissance, communication relay, disaster monitoring and other activities. With limited autonomous intelligence, LE-UAVs require regular periodic and non-periodic control from ground control resources (GCRs) during flights and mission execution. However, the lack of GCRs significantly restricts the applications of LE-UAVs in parallel.

Design/methodology/approach

We consider the constraints of GCRs, investigating an integrated optimization problem of multi-LE-UAV mission planning and GCR allocation (Multi-U&G IOP). The problem integrates GCR allocation into traditional multi-UAV cooperative mission planning. The coupling decision of mission planning and GCR allocation enlarges the decision space and adds complexities to the problem’s structure. Through characterizing the problem, this study establishes a mixed integer linear programming (MILP) model for the integrated optimization problem. To solve the problem, we develop a three-stage iterative optimization algorithm combining a hybrid genetic algorithm with local search-variable neighborhood decent, heuristic conflict elimination and post-optimization of GCR allocation.

Findings

Numerical experimental results show that our developed algorithm can solve the problem efficiently and exceeds the solution performance of the solver CPLEX. For small-scale instances, our algorithm can obtain optimal solutions in less time than CPLEX. For large-scale instances, our algorithm produces better results in one hour than CPLEX does. Implementing our approach allows efficient coordination of multiple UAVs, enabling faster mission completion with a minimal number of GCRs.

Originality/value

Drawing on the interplay between LE-UAVs and GCRs and considering the practical applications of LE-UAVs, we propose the Multi-U&G IOP problem. We formulate this problem as a MILP model aiming to minimize the maximum task completion time (makespan). Furthermore, we present a relaxation model for this problem. To efficiently address the MILP model, we develop a three-stage iterative optimization algorithm. Subsequently, we verify the efficacy of our algorithm through extensive experimentation across various scenarios.
Opportunities for peace and non violence in the Papua New Guinea Highlands
Authors: Forsyth Miranda
Published: November 2024

Purpose

This paper aims to synthesise the literature addressing opportunities for intervention and peacemaking in the Highlands of Papua New Guinea (PNG). It shows that peacebuilding in PNG is actively practised in a variety of different forms and by a range of actors. It relies heavily on local champions and coalitions working together with “bits of the state” in inventive but, ultimately, highly vulnerable ways. It argues that the way forward is to better understand how the multiple resources in and beyond the state can be networked more effectively to engineer peace at many different levels, from the clan to the nation state.

Design/methodology/approach

The paper is based on a thorough review of the scholarly and grey literature concerning peacebuilding and conflict resolution in PNG over the past 30 years.

Findings

The key insight is that peacemaking and non-violence interventions in PNG need to be understood as requiring three different categories of treatment: quick, short interventions; ongoing, slow peacebuilding; and development of community wellness to preventatively stave off violence through increased community cohesion.

Originality/value

The paper is the basis of original research.