bluuebunny/crossref_metadata_2025 huggingface dataset:
Work-Related Physical Discomfort and Ergonomics Among Speech-Language Pathologists Performing Flexible Endoscopic Evaluations of Swallowing
Authors: Keltz Andrew , Leydon Ciara , Vernarelli Jacqueline A. , Livecchi Danielle , Lerner Michael Z.
Published: December 2024

Purpose:

Flexible endoscopic evaluation of swallowing (FEES) is a common component of a comprehensive dysphagia assessment. Endoscopy-related musculoskeletal symptoms resulting from clinician, environment, or equipment factors have been reported among health care professionals. The purpose of this work was to uncover the prevalence and nature of physical discomfort among speech-language pathologists (SLPs) who perform FEES. Investigators also explored SLPs' strategies to reduce endoscopy-related discomfort and their perceived benefit of ergonomics training.

Method:

A survey was distributed electronically to SLPs to gather information about demographics, work environment, FEES practice, ergonomics, and physical discomfort. Data were analyzed using logistic regression and Spearman rank correlations.

Results:

One hundred sixty SLPs who conduct FEES completed the survey. The majority of participants (73%) experienced physical discomfort, at least sometimes, when performing FEES, most notably in the shoulder, back, and neck. Participants who reported suboptimal ergonomics demonstrated fivefold increased odds of experiencing discomfort, indicating insight into physical challenges. Participants with fewer years of experience, less frequent ability to achieve optimal positioning, and increased frequency of physical discomfort were more likely to anticipate benefit from training.

Conclusions:

Physical discomfort was common and was not predicted by demographics, work environment, years of FEES practice, or dose. Further studies are needed to identify factors that predict discomfort and strategies to support comfort and well-being.
Research on influence of double energy absorptions on dynamic volt‐ampere characteristics of metal oxide varistors
Authors: Long Chen , Wu Yifei , Wu Yi , Rong Mingzhe , Xiao Yu , Bai Yunfan
Published: December 2024

Metal oxide varistors (MOVs) are extensively employed in DC circuit breakers (DCCBs) to suppress overvoltage, dissipate energy and build up voltage after interruption. Despite their widespread use, the performance of MOVs under short‐time, double energy absorption conditions is not well understood, posing a challenge to their application in open‐close‐open (OCO) operations of DCCBs. In this paper, a MOV double energy absorption test platform is established to investigate the deviation in volt‐ampere characteristic. The Fréchet distance is proposed as the criterion for assessing the similarity of MOV dynamic volt‐ampere characteristics, and the influencing factors are studied. It is observed that a 15% increase in the absorption of rated energy may result in roughly 20‐unit rise in the Fréchet distance. Furthermore, the deviation in volt‐ampere characteristics during the second pulse is found to be independent of the time interval, affirming that the OCO operation within 300 ms constitutes an adiabatic process. The excursion of the volt‐ampere characteristics is dominated by the energy and remains unaffected by the peak current of the initial pulse. These findings lay the foundation for the subsequent MOV dynamic characteristic balance test and model modification.
ELoran signal message recognition algorithm based on GTCN‐transformer
Authors: Zhang Kai , Yang Fan , Wang Weidong , Wang Bingqian
Published: December 2024

The Enhanced Long Range Navigation (eLoran) system serves as a crucial backup to the Global Navigation Satellite System (GNSS), leveraging advantages, such as low signal frequency, high transmitter power, and stable propagation distance. However, the prevailing demodulation techniques employed by the eLoran system, which are largely based on conventional digital signal processing, are susceptible to substantial inaccuracies when confronted with intense interference and complex environmental conditions. This paper introduces a novel GTCN‐Transformer network designed for the specific task of recognising message in eLoran pulse group signal. The network is constructed by enhancing the architecture of Temporal Convolutional Networks (TCN) and integrating the Transformer mechanism. In order to extract significant features from the pulse group signal, a sequence dataset was obtained by using cepstral analysis. Subsequently, the GTCN‐Transformer network is deployed to recognise the message contained within the eLoran pulse group signal. The experimental results demonstrate that the GTCN‐Transformer network achieves a recognition accuracy of over 95% for eLoran signal message information when the SNR exceeds 10 dB, even in the presence of sky‐wave and cross‐interference signals. Moreover, a comparative analysis with recurrent neural network (RNN) reveals that the GTCN‐Transformer network outperforms these architectures in terms of recognition accuracy.
A Bayesian approach to the halo galaxy – supermassive black hole connection through cosmic time
Authors: Boettner C. , Trebitsch M. , Dayal P.
Published: December 2024

Aims. The evolution of dark matter halos, galaxies, and supermassive black holes are deeply interdependent. We study whether this co-evolution can be qualitatively understood by connecting the evolution of a dark matter structure with simple empirical prescriptions for baryonic processes.

Methods. We established expressions for the (star-forming) galaxy stellar mass function, galaxy UV luminosity function, active black hole mass function, and quasar bolometric luminosity function by assuming a direct and physically motivated relationship between the properties of galaxies and supermassive black holes, and the mass of their host halo. We calibrated the baryonic prescriptions using a fully Bayesian approach to reproduce observed population statistics. The derived parameterisations were then utilised to investigate the connection between galaxy and black hole characteristics and how these characteristics change with redshift.

Results. The galaxy stellar mass – UV luminosity relation, black hole mass – stellar mass relation, black hole mass – AGN luminosity relation, and redshift evolution of these quantities obtained from the model are qualitatively consistent with observations. Based on these results, we present upper limits on the expected number of sources for z = 5 up to z = 15 for scheduled JWST and Euclid surveys, thus showcasing that empirical models can offer qualitative predictions at a high redshift in a fast, easy, and flexible manner that complements more computationally expensive approaches.
Analytical ray-tracing of synchrotron emission around accreting black holes
Authors: Veledina Alexandra , Pélissier Matthieu
Published: December 2024

Polarimetric images of accreting black holes encode important information about laws of strong gravity and relativistic motions of matter. Recent advancements in instrumentation have enabled such studies of two objects: the supermassive black holes M87* and Sagittarius A*. Light coming from these sources is produced by a synchrotron mechanism whose polarization is directly linked to magnetic field lines, and propagates toward the observer in a curved spacetime. We studied the distortions of the gas image by employing the analytical ray-tracing technique for polarized light ARTPOL, which is adapted for the case of synchrotron emission. We derived analytical expressions for fast conversion of the intensity or flux, polarization degree, and polarization angle from the local coordinates to those of the observer. We placed an emphasis on the nonzero matter elevation above the equatorial plane and noncircular matter motions. Applications of the developed formalism include static polarimetric imaging of the black hole vicinity and dynamic polarimetric signatures of matter close to the compact object.
Aqueous Mixtures of Deep Eutectic Solvents: Tuning the Reaction Medium and Photocatalyst for Highly Selective Amine Oxidation
Authors: Kare Varsha S. , Tiwari Shraeddha S.
Published: December 2024

Harvesting light as a source of energy for driving chemical processes is an important aspect of tacking the looming energy crisis. The challenge lies in making the process sustainable while retaining the efficiency and selectivity. In this work, deep eutectic solvents and their aqueous mixtures are used to replace acetonitrile as the reaction medium for the photocatalyzed amine oxidation. It is observed that the use of deep eutectic solvents as reaction media leads to >90% conversion but presents issues with efficient workup due to high viscosity. The use of water a cosolvent mitigates the issue. Further modification of the catalyst surface with alizarin enables the use of higher water content (in a 1:1 ratio) and leads to high conversion (>90%) at one-tenth of irradiation intensity. The high yield and selectivity eliminate the need for tedious purification steps to isolate the product. Control experiments indicate cooperative contributions by TiO2, 2,2,6,6-tetramethylpiperidin-1-yl)oxyl (TEMPO), and alizarin as mechanistic factors responsible for the enhanced reactivity.
Current trend and future research agenda for technological innovation in higher education institutions
Authors: Arviansyah Muhammad Rifqi , Azis Yudi , Sondari Mery Citra , Harsanto Budi
Published: December 2024

Technological innovation is significantly impacting Higher Education Institutions (HEI). In the Google Scholar database, over 3 million literature are available, but only a few articles discuss the review of technological innovation, especially in the HEI context. Therefore, this research aims to determine current trends and future opportunities using a planning-search-data organisation and analysis procedure. Descriptive and bibliometric analyses are conducted with a scoping review of 662 documents from the Scopus electronic database. The result shows that the research trend in this area is uptrend. Most of the literature discusses engineering education, e-learning, and educational innovation. Future research should be conducted in the areas of learning, technology development, intellectual capital, and technological innovation impact.
Relaxation of one-dimensional spin systems in a transverse variable magnetic field
Authors: Zaslavskii O. B. , Tsukernik V. M.
Published: December 2024

A semiinfinite X-Y chain is considered with an impurity at the end which interacts with a transverse magnetic field. It is shown that by using a unitary transformation that includes a nonlinear canonical transformation of Fermi operators, such a system will reduce to the model of an ideal Fermi gas. The evolution of the impurity spin with time is investigated for a jump-like change in the transverse field. It is shown that the nature of the relaxation depends on the presence of a discrete level and its closeness to the edge of the continuous spectrum. The switching on and switching off of the field are analyzed. The evolution of the total spin in time is considered for an Ising chain on which a transverse circularly polarized field acts.
Investigation of the voltage distribution in a film in a dynamic mixed state
Authors: Dmitrenko I. M. , Volotskaya V. G. , Sivakov A. G.
Published: December 2024

The voltage distribution along Sn and Al films, located in a perpendicular magnetic field, is investigated. It is shown that in the region of the dynamic mixed state (I < I*), the voltage is uniformly distributed along the film. The appearance of a stepped structure on the I-V curves for I ≥ I* is related to the formation of local regions with a voltage drop in the film, whose characteristic size ˄ ∼ 2lE.The results obtained confirm the results obtained by I. M. Dmitrenko et al. [Fiz. Nizk. Temp. 7, 383 (1981)].
Pseudopotential calculation of the electron-phonon interaction function in metallic microbridges
Authors: Shustov G. R. , Kulik I. O.
Published: December 2024

The Brovman-Kagan-Kholas pseudopotential is used to calculate the electron-phonon interaction functions G(ω)=α^2(ω)F(ω) in the alkali metals Na and K. The functions obtained are in satisfactory agreement with the point-contact spectra (i.e., the d2V/ dI2-versus-V curves) of these metals. The anisotropy of the G-function is determined. This is, however, found to have a relatively small magnitude.
Influence of vortex-lattice melting on the resistive properties of a superconducting thin-film transformer
Authors: Glazman L. I. , Fogel' N. Ya.
Published: December 2024

The current-voltage curve of a transformer (the dependence of the secondary voltage V2 on the transport current I1 in the primary circuit) has been calculated for two-dimensional vortex-lattice melting. It is shown that even in the critical temperature range the I-V curve loses its root singularity characteristic of a transformer operating in the standard mode. When the lattice is completely melted, the maximum of the V2(I1) curve shifts to higher currents while V2 is much lower than the primary voltage V1, at any value of I1. All of this makes it possible to study vortex-lattice melting using a superconducting transformer. We compare our calculated I-V curve with that obtained experimentally by Tarenkov et al.8
A technology-enabled collaborative learning model (Project ECHO) to upskill primary care providers in best practice pain care
Authors: De Morgan Simone , Walker Pippy , Blyth Fiona M. , Daly Anne , Burke Anne L. J. , Nicholas Michael K.
Published: December 2024

Background The South Australian (SA) Chronic Pain Extension for Community Healthcare Outcomes (ECHO) Network was established to upskill primary care providers in best practice pain care aligned to a patient-centred, biopsychosocial approach using didactic and case-based virtual mentoring sessions. The aims of this study were to assess: (a) participation, satisfaction (relevance, satisfaction with format and content, perceptions of the mentorship environment), learning (perceived knowledge gain, change in attitudes), competence (self-confidence) and performance (intention to change practice, perceived practice change) of the ECHO Network clinician participants; and (b) self-perceived barriers at the clinical, service and system level to applying the learnings. Methods A mixed methods, participatory evaluation approach was undertaken. Data sources included analysis of program records (learning needs assessment, enrolment survey data, program participation data and online surveys of healthcare professionals including a satisfaction survey after each ECHO session (n = 106 across the ECHO series of 10 sessions; average response rate = 46%), a case presenters survey (n = 7, response rate = 78%) and an outcome survey after all 10 ECHO sessions (n = 11, response rate = 25%). Results Forty-four healthcare professionals participated in the ECHO Network from a range of career stages and professional disciplines (half were general practitioners). One-third of participants practised in regional SA. Participants reported that the ECHO sessions met their learning needs (average = 99% across the series), were relevant to practice (average = 99% across the series), enabled them to learn about the multidisciplinary and biopsychosocial approach to pain care (average = 97% across the series) and provided positive mentorship (average = 96% across the series). Key learnings for participants were the importance of validating the patient experience and incorporating psychological and social approaches into pain care. More than one-third of participants (average = 42% across the series) identified barriers to applying the learnings such as limited time during a consultation and difficulty in forming a multidisciplinary team. Conclusions The ECHO Network model was found to be an acceptable and effective interdisciplinary education model for upskilling primary care providers in best practice pain care aligned to a patient-centred, biopsychosocial approach to pain managment. However, participants perceived barriers to translating this knowledge into practice at the clinical, service and system levels.
Metapopulation heterogeneities in host mobility, productivity, and immunocompetency always increase virulence and infectiousness
Authors: Sato Masato , Dieckmann Ulf , Sasaki Akira
Published: December 2024

The epidemiology and evolution of diseases unfold in populations that are rarely homogeneous. Instead, hosts infected by pathogens often form metapopulations, in which local populations connected by the movement of hosts experience different demographic and epidemiological conditions. Here, we develop a general theory of the evolution of pathogens in heterogeneous metapopulations. We reveal the following key insights into the evolution of pathogen virulence and infectiousness: (1) When the mobility (movement rate), productivity (birth rate and carrying capacity), or immunocompetency (immunity-loss rate) differ among local populations, this variance always increases pathogen virulence and infectiousness (2) The increment of pathogen virulence caused by such heterogeneity is approximately proportional to the variance of the corresponding heterogeneous local conditions (3) This increment can be expressed as the covariance between the local selection pressures and the local reproductive values experienced by the pathogen (4) The reason why heterogeneity always increases pathogen virulence is explained by the positive correlation of local selection pressures with reproductive values (5) Combinations of multiple independent heterogeneities further increase virulence and infectiousness, even more so when their covariances are positive. Our key findings robustly hold for different epidemiological frameworks – including SI, SIS, SIR, and SIRS models, with both density- and frequency-dependent transmission as well as with superinfection. They provide insights into the risks of growing pathogen infectiousness in a world in which heterogeneity – caused, e.g., by the concentration of human populations in urban areas – is rising.
Mantle oxidation by sulfur drives the formation of giant gold deposits in subduction zones
Authors: He Deng-Yang , Qiu Kun-Feng , Simon Adam C. , Pokrovski Gleb S. , Yu Hao-Cheng , Connolly James A. D. , Li Shan-Shan , Turner Simon , Wang Qing-Fei , Yang Meng-Fan , Deng Jun
Published: December 2024

Oxidation of the sub-arc mantle driven by slab-derived fluids has been hypothesized to contribute to the formation of gold deposits in magmatic arc environments that host the majority of metal resources on Earth. However, the mechanism by which the infiltration of slab-derived fluids into the mantle wedge changes its oxidation state and affects Au enrichment remains poorly understood. Here, we present the results of a numerical model that demonstrates that slab-derived fluids introduce large amounts of sulfate (S
6+
) into the overlying mantle wedge that increase its oxygen fugacity by up to 3 to 4 log units relative to the pristine mantle. Our model predicts that as much as 1 wt.% of the total dissolved sulfur in slab-derived fluids reacting with mantle rocks is present as the trisulfur radical ion, S
3
–
. This sulfur ligand stabilizes the aqueous Au(HS)S
3
–
complex, which can transport Au concentrations of several grams per cubic meter of fluid. Such concentrations are more than three orders of magnitude higher than the average abundance of Au in the mantle. Our data thus demonstrate that an aqueous fluid phase can extract 10 to 100 times more Au than in a fluid-absent rock-melt system during mantle partial melting at redox conditions close to the sulfide-sulfate boundary. We conclude that oxidation by slab-derived fluids is the primary cause of Au mobility and enrichment in the mantle wedge and that aqueous fluid-assisted mantle melting is a prerequisite for formation of Au-rich magmatic hydrothermal and orogenic gold systems in subduction zone settings.
Perceived memory credibility: The role of details
Authors: Nadel Lynn , Simon Katharine C.
Published: December 2024

The sharing of personal memories is a unique aspect of the human experience. Humans communicate to provide information, to influence, or even to amuse. How do we distinguish between credible and noncredible narratives? Forensic science has identified race, age, and detail quantity as influential. We do not know how the nature of narrated details impacts believability. We report two studies investigating how detail composition influences credibility ratings using definitions of details suggested by Levine et al. (2002). Internal details are directly connected to the episodic aspects of the memory, while external details refer to semantic facts or depictions not directly related to the main event. A total of 825 participants rated narratives that varied detail number and type for perceived credibility or saliency. Episodic memory details enhanced credibility more than semantic memory details. In addition, within episodic memories, person-related details enhanced credibility more than non-person-related details. Our results suggest a lens through which to view the credibility of what we hear and read.
Language learning, desire, and global power dynamics
Authors: Ishige Aika
Published: December 2024

Drawing on the concepts of desire from applied linguistics and Deleuzian perspectives, this study investigates the desires encapsulated in a Japanese woman’s English learning sojourn in the Philippines. Data were collected using an open-ended questionnaire and through two semi-structured interviews. The participant’s retrospective narrative provides insight into her perceptions of the Philippines compared to Canada. While previous research has primarily examined the sociolinguistic aspects of studying abroad in the Philippines, the current study expands this focus to encompass other dimensions, such as material factors. The findings illuminate how the Philippines, as a study-abroad destination, is experienced and remembered by students. Further, the findings unveil the participant’s ambivalent yet irresistible akogare for the West. The marginal desirability of the Philippines as a study-abroad destination represents how the historically and economically constituted global hierarchies of power have been reproduced in the discourse and practice of transnational English learning.
An introduction to conducting responsible and reproducible agricultural research
Authors: Sichinga-Ligowe Ivy , Joy Edward J.M. , Manzeke-Kangara M. Grace , Pino Loreto , Rivero M. Jordana , Devkota Mina , Broadley Martin R. , Haefele Stephan M. , McGrath Steve P.
Published: December 2024

This article aims to provide researchers with introductory guidance to good practices in the design, conduct and reporting of agricultural research. This narrative review considers issues related to research co-design, ethics and integrity, equity, diversity and inclusion, reproducibility and (meta)data reporting. Aspects for researchers to consider are highlighted, and relevant resources are identified, including academic papers and research funder guidance.
Spinoptics in the Schwarzschild spacetime
Authors: Frolov Valeri P.
Published: December 2024

We study spinoptics equations in the Schwarzschild spacetime. We demonstrate that using the
explicit and hidden symmetries of this metric one can explicitly solve the equations for complex null tetrad associated with null rays representing photon's and graviton's motion. This allows one to integrate the spinoptics equations both for the electromagnetic and gravitational waves. It is shown that the main effect of the interaction of the spin of these fields with the spacetime curvature is the tilt of the asymptotic planes of the massless particle orbit. The corresponding tilting angle is calculated. It is shown that this angle grows when a null ray passes in the vicinity of the circular null orbit located at r=3M.
Probabilistic Modeling of Ship Collision in The Lombok Strait, Indonesia: A Bayesian Network Approach
Authors: Ratih Iis Dewi , Artana Ketut Buda , Kuswanto Heri , Pratiwi Emmy , Zaki Athaya Raihan
Published: December 2024

Ship collisions are a type of maritime accident that can result in significant losses due to their direct impact on the structural integrity of the vessels involved. Collisions can occur between two or more ships crashing into each other. Such accidents can cause severe damage, threatening the safety of passengers and crew on all vessels involved, and generally result in greater losses than single-ship accidents. According to KNKT (National Transportation Safety Committee of the Republic of Indonesia) investigations, ship collisions occurred in the Lombok Strait from 2007 to 2019. The Lombok Strait is part of ALKI (Indonesian Archipelagic Sea Lanes) II, which connects Australia and East Asia. Therefore, assessing the frequency of collisions in these waters is necessary to determine the prevalence of such incidents. If the rate is high, efforts can be made to minimize risks and ensure safety in the shipping lanes, particularly in ALKI. A Bayesian Network can provide information about the likelihood of ship collisions, facilitating decision-making to prevent or mitigate the risks posed by such incidents. The model’s formation involves calculating the formed structure’s prior, conditional, and joint probability of the formed structure. Thus, conclusions were drawn based on the model’s predictions of ship collision chances in Indonesia, yielding an accuracy rate of 96.97%, a specificity of 90.00%, and a sensitivity of 100%. Based on Bayesian Network analysis and modeling, the causal probability values for the Lombok Strait are as follows: Pc Head-on, Pc Overtaking, and Pc Crossing are 2.85 x 10^-4, 1.03 x 10^-5, and 6.24 x 10^-5, respectively. Based on the Bayesian Network modeling results, the frequency of ship collisions in the Lombok Strait for each type of collision are 0.000026 collisions/year, 0.0000031 collisions/year, and 0.0000015 collisions/year, respectively.
Green finance, environmental taxation, and green innovation: unraveling their influence on the growth- quality nexus in China—a provincial perspective
Authors: Qamruzzaman Md
Published: December 2024

China’s fast industrialization and urbanization have led to impressive economic growth and caused severe environmental degradation, resulting in increased CO2 emissions. These emissions have increased by leaps and bounds with China’s rapid industrialization and urbanization. The case for sustainable development is compelling and has unleashed a search for green investments and technological innovations to meet the challenge. This study is motivated by the significant need to understand the effects of green finance, technological innovations, and environmental taxes on China’s economic growth and environmental sustainability. Furthermore, it tries to investigate how these elements may help make the model more sustainable and not endanger the developmental achievements of the country. For this purpose, we employed a comprehensive econometric approach through longitudinal data, and different models included Two-step GMM, Two-step system-GMM, and CS-ARDL. These methodologies portray various ways green investments, green technological innovation, tax, urbanization, inflows of FDI, and industrial structure intersect to influence environmental and economic outcomes in China. The results reflect a strong negative correlation with green investments made with CO2 emissions, proving that high investments in green technologies and practices effectively reduce carbon outputs. The study also underlined regional disparities and technological innovations in green. The study, therefore, recommends more efforts by Chinese policymakers on green finance and investment, standardization, and the rise in environmental standards across the country; enhanced efforts in further bringing down CO2 emissions through ecological taxes and incentives; and collective efforts with strong governmental support for research and development in low-carbon technologies that can help place China on a sustainable economic path.
Fuel starvation in automotive PEMFC stacks: stack current and bipolar plate resistance
Authors: Nissen Jens , Boye Jan-Peter , Schrievers Max , Schwämmlein Jan Nicolas , Hölzle Markus
Published: December 2024

Fuel cells are a viable option to reduce CO2 emissions of the heavy-duty transportation sector. However, under certain operation conditions, individual cells in the fuel cell stack may suffer from an undersupply of hydrogen, called fuel gross starvation (FGS). The voltage of affected cells is then reversed, enabling subsidiary reactions to gain the necessary current. These reactions are known to cause oxidation of the carbon in the anode catalyst layer, leading to performance degradation. This study demonstrates that FGS situations may furthermore cause a detrimental overheating behavior at high stack current. The behavior of two different 20-cell fuel cell stacks is investigated towards fuel starvation of one contained cell. One stack used carbon bipolar plates (BPs) with a comparatively high electric sheet resistance. The other stack used a modified BP which contained a copper-inlay, resulting in low electric sheet resistance. The behavior of the intentionally fuel starved cell was inspected in form of locally resolved current density, temperature and cell voltage. Additionally, the voltage of all other cells was simultaneously measured at the fuel inlet and outlet. At low stack currents, the fuel starved cell showed well comparable local behavior for both stack types. Significant differences occurred with increasing stack current. A spatially equal negative voltage was observed for the fuel starved cell when incorporated in the stack with a copper-inlay in the BP. A very high heat generation resulted from this condition, and detrimental effects of overheating were observed. In contrast, the fuel starved cell showed an intense variation of the local voltage when incorporated in the stack with only carbon-based BPs. The fuel outlet region of this cell hereby obtained a negative voltage, but the fuel inlet region maintained a positive voltage. This phenomenon allowed the fuel starved cell to counter-act an excessive heat production.
Latest advancements in smart grid technologies and their transformative role in shaping the power systems of tomorrow: an overview
Authors: Al-Shetwi Ali Q , Hannan M A , Al-Masri Hussein M K , Sujod Muhamad Zahim
Published: December 2024

Against the backdrop of a global shift towards renewable energy sources (RES) and the increasing complexity of modern power grids, smart grids (SGs) emerge as a critical solution for enhancing efficiency, reliability, and sustainability. This paper reviews a total of 177 key references published between 2014 and 2024, providing a comprehensive analysis of the most recent advancements in SG technologies and their pivotal role in shaping the future of power systems. The research explores the multifaceted components of SGs, encompassing intelligent sensing, communication technologies, home energy management systems, demand-side management, smart metering, smart electric vehicle charging, smart lighting, the Internet of Things, and the integration of big data, while investigating their role in enhancing the power grid in a smart and digitally integrated manner. The paper also discusses the SG features that have developed and improved the transmission and distribution networks, as well as the ancillary services on a grid-scale introduced through digitization. In addition, the status of the investment in SG is highlighted. The electrification of the global economy, driven by the urgent need to integrate RES, prompted an 8% increase in electricity grid investment in 2022. Additionally, digital technology investments for the grid constituted 19% of the total grid investment in the same year. SGs stand at the forefront of this transformation, playing a central role in facilitating the integration of variable RES, implementing digital technologies, smart devices, and optimizing power systems for diverse sectors. Despite substantial progress, some challenges persist that need further attention to ensure the seamless integration of SG technologies. The findings underscore the pivotal role of SGs in enhancing energy efficiency, effectively managing distributed energy resources, and strengthening the resilience of power systems. In conclusion, the recent advancements in SGs mark a transformative era for the power sector. However, to fully unlock their potential, it is essential to address the key challenges that hinder their seamless integration. Accordingly, these challenges are outlined to guide future research in developing innovative solutions that further optimize and advance the capabilities of SGs.
Supply-side challenges and research needs on the road to 100% zero-emissions vehicle sales
Authors: Jenn Alan , Chakraborty Amrita , Hardman Scott , Hoogland Kelly , Sugihara Claire , Tal Gil , Helveston John , Rich Jeppe , Jochem Patrick , Plötz Patrick , Sprei Frances , Williams Brett , Axsen Jonn , Figenbaum Erik , Pontes Jose , Refa Nazir
Published: December 2024

In this review paper, we delve into the supply-side challenges and considerations for transitioning to 100% zero-emission vehicles (ZEVs), weaving together an analysis of batteries, vehicle production, charging infrastructure, and relevant supply-side policies. We begin by examining the innovations and environmental impacts of lithium mining and recycling, highlighting the need for robust frameworks to ensure sustainable battery production. Our exploration of vehicle production reveals important issues regarding labor dynamics and global competitiveness. Our investigation into charging infrastructure reveals complexities in deployment models and access, reflecting broader societal and economic considerations. Lastly, a critical evaluation of policies across various jurisdictions provides insights into the effectiveness and potential improvements needed to support the ZEV transition. We emphasize the need for coordinated efforts and further research, particularly in areas such as end-of-life considerations for batteries and the alignment of international production standards. Our findings contribute to a comprehensive understanding of the supply-side landscape for ZEVs and underscore the essential research directions to ensure a responsible and successful electrification of the transportation system.
Accurate path tracing of a tracked robot: a modified PID approach with slip compensation
Authors: Deshmukh Deepak , Kumutham Anand Ronald , Pratihar Dilip Kumar , Deb Alok Kanti
Published: December 2024

The tracked robot functioning in unstructured and dynamic off-road environments poses significant challenges, necessitating sophisticated mathematical modeling. This paper explores the precise path-tracking capabilities of tracked robots in the presence of external disturbances. This study presents a model-based control method for tracked robots, using a modified PID controller. Genetic algorithms optimizes the control parameters to enhance tracking performance. The dynamic model of the robot has been implemented with kinematic backstepping to ensure velocity and position control. Considering the importance of accurately representing real-world scenarios, the mathematical model includes the robot dynamics, factoring in the influence of external disturbances and slippage, which increases the accuracy of the proposed control system. The output of the proposed controller was compared with the classical PID control technique on the basis of various performance indicators such as Integral Absolute Error (IAE), Integral Square Error (ISE), and sensitivity to disturbances. Simulation studies using MATLAB Simulink demonstrated the effectiveness of the proposed approach by enabling tracked robots to follow a desired path in complex terrain accurately. The developed controller was deployed on the experimental setup, and the trajectory tracking test was performed in indoor laboratory conditions. Experimental results show the robust performance and reliability of the modified PID controller, which provides precise path tracking while maintaining the reference robot's velocities.
Are queries and keys always relevant? A case study on transformer wave functions
Authors: Rende Riccardo , Loris Viteritti Luciano
Published: December 2024

The dot product attention mechanism, originally designed for natural language processing tasks, is a cornerstone of modern Transformers. It adeptly captures semantic relationships between word pairs in sentences by computing a similarity overlap between queries and keys. In this work, we explore the suitability of Transformers, focusing on their attention mechanisms, in the specific domain of the parametrization of variational wave functions to approximate ground states of quantum many-body spin Hamiltonians. Specifically, we perform numerical simulations on the two-dimensional J
1–J
2 Heisenberg model, a common benchmark in the field of quantum many-body systems on lattice. By comparing the performance of standard attention mechanisms with a simplified version that excludes queries and keys, relying solely on positions, we achieve competitive results while reducing computational cost and parameter usage. Furthermore, through the analysis of the attention maps generated by standard attention mechanisms, we show that the attention weights become effectively input-independent at the end of the optimization. We support the numerical results with analytical calculations, providing physical insights of why queries and keys should be, in principle, omitted from the attention mechanism when studying large systems.
Toward a process-oriented understanding of water in the climate system: recent insights from stable isotopes
Authors: Bailey Adriana , Noone David , Dee Sylvia , Nusbaumer Jesse , Conroy Jessica , Stevenson Samantha , Atwood Alyssa
Published: December 2024

Describing the processes that regulate the flows and exchanges of water within the atmosphere and between the atmosphere and Earth’s surface is critical for understanding environmental change and predicting Earth’s future accurately. The heavy-to-light hydrogen and oxygen isotope ratios of water provide a useful lens through which to evaluate these processes due to their innate sensitivity to evaporation, condensation, and mixing. In this review, we examine how isotopic information advances our understanding about the origin and transport history of moisture in the atmosphere and about convective processes—including cloud mixing and detrainment, precipitation formation, and rain evaporation. Moreover, we discuss how isotopic data can be used to benchmark numerical simulations across a range of scales and improve predictive skill through data assimilation techniques. This synthesis of work illustrates that, when paired with air mass thermodynamic properties that are commonly measured and modeled (such as specific humidity and temperature), water’s isotope ratios help shed light on moist processes that help set the climate state.
Evaluation of historical precipitation interannual variability in CMIP6 over the United States
Authors: Harp Ryan D , Taguela Thierry N , Akinsanola Akintomide A , Horton Daniel E
Published: December 2024

Interannual precipitation variability profoundly influences society via its effects on agriculture, water resources, infrastructure, and disaster risks. In this study, we use daily in situ precipitation observations from the global historical climatology network-daily (GHCN-D) to assess the ability of 21 Coupled Model Intercomparison Project Phase 6 (CMIP6) models, including the 50-member fifth-generation Canadian Earth System Model single model initial-condition large ensemble (CanESM5_SMILE), to realistically simulate historical interannual precipitation variability trends within 17 regions of the contiguous United States (CONUS). We assess how accurately the CMIP6 simulations align with observational data across annual, summer, and winter periods, focusing on four key hydrometeorological metrics, including interannual precipitation variability, relative interannual precipitation variability (coefficient of variation), annual mean precipitation, and annual wet day frequency. Our findings reveal that CMIP6 ensemble members generally reproduce the spatial patterns of observed trends in annual mean precipitation. In most regions, models agree well with the signs of observed changes in annual mean precipitation, though discrepancies in trend magnitude are evident. Further, observed trends in winter mean precipitation broadly exhibit a spatial pattern similar to that of the observed annual mean. However, analysis of the CanESM5_SMILE shows that trends in precipitation variability may primarily be the result of model-simulated internal variability, suggesting caution in interpreting multi-model single-realization ensemble results. Challenges in accurately simulating interannual precipitation variability underscore the need for ongoing model refinement and validation to enhance climate projections, especially in regions vulnerable to extreme precipitation events.
Decarbonization and technology cost drivers: considerations for potential future thermoelectric water use in the power sector
Authors: Cohen Stuart , Valdez Raquel , Tidwell Vincent , Khanal Saroj , Gunda Thushara
Published: December 2024

The power sector is currently undergoing significant changes, driven by a combination of factors, including decarbonization and technology innovation. This study aims to assess implications of these drivers on U.S. power sector technology futures and the associated water and environmental implications for cooling thermoelectric power plants. Specifically, we evaluate four decarbonization scenarios for the contiguous United States that vary in assumptions concerning demand growth and technology costs, with technology costs driving alternative outcomes that prioritize either technologies that require low amounts of water (such as wind, solar, and battery) or high amounts of water (such as nuclear and carbon capture and storage). These scenarios are executed in a power sector capacity expansion model and compared to two reference scenarios that assume status quo with policy and cost drivers. Our analysis indicates that future U.S. thermoelectric water withdrawals could decrease by 25%–60%, but water consumption could more than triple in some scenarios. These changes are driven by a combination of retirement of some power facilities, shifts in cooling technologies, and new technology deployment. The water use patterns vary across the United States, with the eastern regions demonstrating a lot more variability in water consumption across scenarios than western regions. However, local concerns can influence these possible investments, since increased water consumption can exacerbate water scarcity, leading to conflicts among competing users and affecting regional social, environmental, and economic dynamics. Future work should consider possible costs associated with alternate water sources, as well as improve the representation of water constraints within simulations. Inclusion of extreme events and alternate modeling platforms (e.g. production cost modeling and resource adequacy) may also be warranted to further stress test the robustness of these possible technology futures. Such assessments will be critical for ensuring decarbonization and other infrastructure-oriented investments lead to a reliable and resilient power grid.
Ligand identification in CryoEM and X-ray maps using deep learning
Authors: Karolczak Jacek , Przybyłowska Anna , Szewczyk Konrad , Taisner Witold , Heumann John M , Stowell Michael H B , Nowicki Michał , Brzezinski Dariusz
Published: December 2024

Motivation

Accurately identifying ligands plays a crucial role in the process of structure-guided drug design. Based on density maps from X-ray diffraction or cryogenic-sample electron microscopy (cryoEM), scientists verify whether small-molecule ligands bind to active sites of interest. However, the interpretation of density maps is challenging, and cognitive bias can sometimes mislead investigators into modeling fictitious compounds. Ligand identification can be aided by automatic methods, but existing approaches are available only for X-ray diffraction and are based on iterative fitting or feature-engineered machine learning rather than end-to-end deep learning.

Results

Here, we propose to identify ligands using a deep-learning approach that treats density maps as 3D point clouds. We show that the proposed model is on par with existing machine learning methods for X-ray crystallography while also being applicable to cryoEM density maps. Our study demonstrates that electron density map fragments can aid the training of models that can later be applied to cryoEM structures but also highlights challenges associated with the standardization of electron microscopy maps and the quality assessment of cryoEM ligands.

Availability and implementation

Code and model weights are available on GitHub at https://github.com/jkarolczak/ligands-classification. An accompanying ChimeraX bundle is available at https://github.com/wtaisner/chimerax-ligand-recognizer.
A deficiency screen identifies genomic regions critical for sperm head–tail connection
Authors: Galletta Brian J , Konstantinidou Parthena , Haase Astrid D , Rusan Nasser M
Published: December 2024

The Sperm Neck provides a stable connection between the sperm head and tail, which is critical for fertility in species with flagellated sperm. Within the Sperm Neck, the Head–Tail Coupling Apparatus serves as the critical link between the nucleus (head) and the axoneme (tail) via the centriole. To identify regions of the Drosophila melanogaster genome that contain genetic elements that influence Head–Tail Coupling Apparatus formation, we undertook a 2 part screen using the Drosophila Deficiency kit. For this screen, we utilized a sensitized genetic background that overexpresses the pericentriolar material regulatory protein Pericentrin-Like Protein. We had previously shown that Pericentrin-Like Protein overexpression disrupts the head–tail connection in some spermatids, but not to a degree sufficient to reduce fertility. In the first step of the screen, we tested for deficiencies that in combination with Pericentrin-Like Protein overexpression causes a reduction in fertility. We ultimately identified 11 regions of the genome that resulted in an enhanced fertility defect when combined with Pericentrin-Like Protein overexpression. In the second step of the screen, we tested these deficiencies for their ability to enhance the head–tail connection defect caused by Pericentrin-Like Protein overexpression, finding 6 genomic regions. We then tested smaller deficiencies to narrow the region of the genome that contained these enhancers and examined the expression patterns of the genes within these deficiencies using publicly available datasets of Drosophila tissue RNAseq and Drosophila testes snRNAseq. In total, our analysis suggests that some deficiencies may contain single genes that influence Head–Tail Coupling Apparatus formation or fertility, while other deficiencies appear to be genomic regions rich in testis-expressed genes that might affect the Head–Tail Coupling Apparatus through complex, multigene interactions.