bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancement of cyclic spectral coherence map by statistical testing approach—application to bearing faults diagnosis in electric motors
Authors: Michalak Anna , Hebda-Sobkowicz Justyna , Wodecki Jacek , Szabat Krzysztof , Wolkiewicz Marcin , Weisse Sebastien , Valire Jerome , Zimroz Radosław , Wyłomańska Agnieszka
Published: November 2024

Efficiency of fault detection in rolling element bearings is heavily influenced by the quality of data. In controlled environments, such as test rigs designed for bearing diagnostics, data quality is relatively good. Similarly, diagnosing bearings that support shafts in industrial machinery is relatively straightforward. However, diagnosing bearings in electric motors presents greater complexity due to the influence of additional cyclic components on vibration signals. These extra components, originating from mechanical or electrical sources, complicate frequency-based analysis. This paper proposes a novel approach for diagnosing bearings in electric motors, utilizing statistical analysis within the bi-frequency domain through a cyclostationary framework. The method involves applying a statistical testing procedure to individual pixels on the cyclic spectral coherence (CSC) map. The statistical significance of these pixels is assessed based on quantiles of CSC maps obtained from a dataset representing a healthy bearing. This process results in an enhanced or cleaned CSC map, facilitating the identification of fault-related components. Consequently, this approach enables the detection of defects in electric motor bearings, even when additional signal components unrelated to the defect, but characteristic of a healthy bearing, are present.
A novel TCN-GRU based open set method for unknown damage diagnosis
Authors: Li Zhiyong , Wang Zhiyong , Wang Jinrui , Han Shanling
Published: November 2024

In the aerospace and high-speed rail industries, carbon fiber reinforced polymer (CFRP) has seen widespread application. CFRP plates and connectors in operation are often subjected to impacts that can cause damage. The unpredictable nature of the impacts introduces uncertainties in both the location and extent of the damage, posing significant challenges to traditional supervised learning models, which often struggle with missed detections or misclassifications when identifying unknown damages. To address the issue, a deep learning model based on temporal convolutional network-gated recurrent unit (TCN-GRU) is proposed. TCN extracts features from the raw time domain signals, and GRU selectively retains the significant features and completes sequence modeling. A center loss function is incorporated into the fully connected layer to improve the effects of intra-class aggregation and inter-class separation. An unknown detection module is introduced to realize the identification and classification of unknown damages based on a predefined threshold. The experimental results indicate that the proposed method can achieve effective unknown damage diagnosis in the open set case. This study provides a feasible solution for open set unknown damage diagnosis in CFRP plates and connectors.
A sEMG-based gesture recognition framework for cross-time tasks
Authors: Zhang Xingguo , Li Tengfei , Zhang Yue , Sun Maoxun , Zhang Cheng , Zhou Jie
Published: November 2024

In the practical application of action pattern recognition based on surface electromyography (sEMG) signals, the electrode displacement and the time-varying characteristics of the signals during cross-time signal acquisition can reduce the classification accuracy. This study designs a 12 d forearm sEMG signal cross-time acquisition experiment, introduces time span into the dataset, and proposes a cross-time gesture recognition framework based on deep convolutional neural networks (CNN) with sEMG signals. In the cross-validation of single-day analysis, recognition rates using multiple CNN modules exceed 90%. However, the average recognition rate for cross-day analysis is only 59.0%. The classification performance of the framework is significantly improved in the multi-day analysis by gradually increasing the number of training days. In particular, 97.4% accuracy is achieved in the cross-time recognition task by using a specific configuration of DenseNet as the network module and extracting features with one-dimensional (1D) convolution on signal fragments. Compared to the method of extracting short-time Fourier transform image features as input using two-dimensional convolution, the training method of extracting signal features using 1D convolution reduces the time consumed to about 1%, which is advantageous in terms of model performance.
Ignition mechanism of a dual trigger electrode hollow cathode
Authors: Luo Zihao , Zhang Guangchuan , Hao Guanghui , Zhang Zhongkai , Tianlang Yi , Ren Junxue , Wang Yibai , Zhang Zun , Wang Weizong , Tang Haibin
Published: November 2024

Hollow cathodes serve as the electron source for thrusters and are critical elements of the electric propulsion system. To overcome the limitations of the small orifice blockage in the discharge path of the conventional hollow cathode on the ignition performance, a dual trigger electrode heater-based cathode with a sub-millimeter columnar bias electrode inserted into the emitter cavity is proposed. Both experiments and simulations indicate that the dual trigger electrode cathode provides faster ignition time and self-healing ability from poisoning. A coupled plasma-thermal model reveals the ignition mechanism from the discharge process, power deposition, and ion sputtering. The electric field penetration induced by the inner electrode enhances the energy injection of emitted electrons and internal ohmic heating to establish an efficient discharge from upstream to downstream. Primary ignition of the inner electrode enhances the power deposition on the emitter with ion bombardment dominated, raising the emitter temperature rapidly by 150 K from 1173 K in the preheating phase to accelerate the electrode switching. Energetic ions during the primary ignition perform explosive scanning sputtering of the emitter, uniformly cleaning the tungstate layer from the emitter surface and allowing the cathode to self-heal from poisoning, as verified by destructive environmental tests.
Modeling thermal and buckling behavior in electrothermal bimorphs
Authors: Hussein Hussein , Tanguy Quentin A A , Lakkis Issam , Fariborzi Hossein , Majumdar Arka , Böhringer Karl F
Published: November 2024

Buckling is a structural phenomenon that can induce significant motion with minimal input variation. Electrothermal bimorphs, with their simple input and compact design, can leverage out-of-plane buckling motion for a broad range of applications. This paper presents the development of analytical electrothermal and structural models for such bimorphs. The electrothermal model calculates the temperature distribution within the bimorph caused by electrothermal heating, providing a 2D explicit analytical expression for estimating temperature along the bimorph’s length and cross-section. Nonhomogeneous heating leads to varying strains, which induce axial forces and moments along the bimorph’s neutral plane, varying with thermal expansion. The structural model derives the governing equation of deformation for the bimorph by analyzing internal strains and stresses resulting from deformation, electrothermal heating, and residual stresses. An analytical solution for deflection is obtained, incorporating infinite sums of heating and buckling modes, with closed-form equivalent expressions when possible. The bimorph’s behavior under different scenarios of residual stresses and electrothermal heating is elucidated based on the analytical model. Comparisons with finite element simulations demonstrated excellent agreement, highlighting the high accuracy of the proposed models.
Solar-powered thermo-pneumatic actuators for passively controlled adaptive shading
Authors: Louis Rafaela , Shea Kristina
Published: November 2024

The operational energy demand of buildings plays a significant role in global energy consumption. Especially, the energy required for cooling is predicted to rise due to climate change. Adaptive shading is a promising approach to save operational energy in buildings. State-of-the-art adaptive shading systems employ both active and passive actuation as well as control strategies, to lower energy consumption while maintaining the thermal and visual comfort of building occupants. However, both approaches still must overcome challenges that hinder widespread adoption. Active systems need motors and pumps, dedicated power supplies, and control electronics. These components make the systems heavy and complex to maintain and repair. Passive systems work without dedicated power supplies and control electronics but can face limitations based on the active materials used, e.g. material degradation, toxicity, narrow response windows, and unknown performance in varying conditions. This work presents a solar-powered, thermo-pneumatic actuator for use in adaptive shading applications that works without specialized active materials, electronic actuation and controls. The actuator incorporates elastic bellows to transform the thermal expansion of air into motion and adapts to changes in irradiance. The actuator is built as a functional prototype and its performance in different irradiance scenarios is evaluated. The actuator is capable of considerable motion, moving a rotational mechanism close to 90° powered by an irradiance of 1000 W m−2. The actuator response is sensitive enough to react to hourly changes in irradiance as well as to a simulated solar cycle. The paper concludes with the presentation of a shading device concept incorporating the actuator to highlight its potential for use in adaptive shading applications to reduce operational energy in buildings.
Direct moment estimation of intensity distribution of magnetic fields with quantum sensing network
Authors: Kasai Hiroto , Takeuchi Yuki , Matsuzaki Yuichiro , Tokura Yasuhiro
Published: November 2024

A quantum sensing network is used to simultaneously detect and measure physical quantities, such as magnetic fields, at different locations. However, there is a risk that the measurement data is leaked to the third party during the communication. Many theoretical and experimental efforts have been made to realize a secure quantum sensing network where a high level of security is guaranteed. In this paper, we propose a protocol to estimate statistical quantities of the target fields at different places without knowing individual value of the target fields. We generate an entanglement between L quantum sensors, let the quantum sensor interact with local fields, and perform specific measurements on them. By calculating the quantum Fisher information to estimate the individual value of the magnetic fields, we show that we cannot obtain any information of the value of the individual fields in the limit of large L. On the other hand, in our protocol, we can estimate theoretically any moment of the field distribution by measuring a specific observable and evaluated relative uncertainty of kth (

k
=
1
,
2
,
3
,
4

) order moment. Our results are a significant step towards using a quantum sensing network with security inbuilt.
Cementite with substitutional Nb atoms based on first-principles calculations
Authors: Zhang Junxiang , Gu Shangjun , Wang Jie , Wei Fulong , Xie Xiang , Yang Hui , You Jingtian , Li Changrong
Published: November 2024

Cementite is the strengthening phase in pearlite, and its mechanical properties determine the strength of the pearlite. A crystal model of niobium-substituted Fe3C was constructed. The stability, charge density, and elastic constants of the model were calculated, and the effects of niobium (Nb) substitution on the properties of Fe3C were discussed. FeNb8d
2 C is the most stable Nb-substituted structure. The reaction energy of FeNb8d
2 C is −0.796 eV, with a magnetic moment of 0.07 μB/f.u. At the Fermi level, the DOS of FeNb8d
2 C is 4.24, displaying metallic properties. Nb substitution enhances the symmetry of the DOS in Fe3C. The covalent bonding in FeNb8d
2 C, predominantly consisting of σ and π bonds, is formed by the hybridization of Nb 3 d states and C 2p states. FeNb8d
2 C is mechanical stability. It exhibits the strongest resistance to linear compression along the [100] direction and the highest shear deformation resistance along the (010) plane. Nb substitution increases the toughness of Fe3C, enhances isotropy on the (010) plane, and improves the resistance to linear compression along the [010] direction.
Six-scroll chaos within the dynamics of the Thomas chaotic system and application to biomedical data encryption
Authors: Boya Bertrand Frederick Boui A , Nanfak Arnaud , Ngono Joseph Mvogo , Klimentyevna Babenko Lyudmila , Nkapkop Jean de Dieu , Effa Joseph Yves
Published: November 2024

In this paper, the influence of non-monotonic nonlinearity within the dynamics of the Thomas model is studied. The system presents various six-scroll chaos over a wide range of parameter values through in-depth analysis using conventional nonlinear analysis tools. The new model also reveals multistability with an elegant configuration of up to nine periodic states. An electronic analog version of the model is designed and then simulated using PSPICE software to verify the physical implementation of the model. A novel biomedical image encryption scheme based on the six-scroll chaos system, Arnold transform and diffusion operation is proposed and its security is analyzed using statistical testing and key space analysis. The results demonstrate the effectiveness of the proposed system in providing secure and efficient encryption of digital images.
Wideband compact 3-dB microstrip power divider for L- and S-band applications
Authors: Demir Kübra , İmeci Şehabeddin Taha , Tütüncü Bilal
Published: November 2024

This paper presents the analysis, design, built and testing of a new compact 3 dB power divider operating across a wideband frequency range, with a 2.56 GHz center frequency. The proposed divider, consisting of three ports, is constructed using an FR4 substrate, with overall dimensions of 45 × 40 × 1 mm3. The frequencies with the best S21 and S31 results are recorded with a magnitude of −3.04 dB at 2.56 GHz. The simulated input match (S11) displays nearly −30 dB at 2.56 GHz, with a −10 dB bandwidth extending from 1 to 4 GHz, resulting in a total bandwidth of 3 GHz. Hence, the proposed power divider emerges as a strong candidate for applications in both the L- and S-bands. The measured data exhibit strong agreement with the simulation results. The originality of this study lies in achieving high performance within such compact dimensions at an affordable cost, thereby eliminating the complexity that can lead to manufacturing errors. Additionally, it is demonstrated through a comparative table that the proposed power divider exhibits superiority over similar ones found in the literature.
A novel chirp-based 2D hyperchaotic map for enhanced image encryption
Authors: Demirtaş Mehmet , Altunkaya Sabri
Published: November 2024

This paper presents a novel image encryption algorithm based on a newly proposed two-dimensional hyperchaotic map derived from the chirp signal. Performance evaluations of the proposed map include bifurcation analysis, phase portrait visualization, sensitivity to initial conditions, Lyapunov exponent calculations, entropy measurements, and NIST tests. These evaluations confirm the map’s strong randomness and broad chaotic behavior. The proposed encryption algorithm utilizes the high sensitivity to initial conditions and wide chaotic range of the hyperchaotic map to enhance security. The algorithm achieves a high degree of confusion and diffusion through bit-level manipulation, chaotic permutation, and randomized row-column diffusion processes. As a result, it can effectively encrypt images of any size, whether color or grayscale. Comprehensive security evaluations, such as key analysis, histogram analysis, Shannon entropy analysis, correlation analysis, differential analysis, and robustness analysis, confirm the algorithm’s resilience against a wide range of cryptographic attacks. Thus, the proposed algorithm offers a promising solution for secure image transmission.
Reexamination of the realtime protection for user privacy in practical quantum private query
Authors: Wei Chun-Yan , Cai Xiao-Qiu , Wang Tian-Yin
Published: November 2024

Quantum private query (QPQ) is the quantum version for symmetrically private information retrieval. However, the user privacy in QPQ is generally guarded in the delayed and cheat-sensitive way. That is, the dishonest database holder Bob’s cheating to elicit user privacy can only be discovered after the protocol is finished (when the user finds some errors in the retrieved database item). Such delayed detection may cause very unpleasant results for the user Alice in real-life applications. Without the realtime conscious of privacy leaking, Alice may make faulty decisions according to the received faulty item and suffer great loss. Worse yet, it is difficult for Alice to accuse a dishonest database to any one else though she can detect the cheating. Current efforts to protect user privacy in realtime in existing QPQ protocols mainly use two techniques, i.e. adding an honesty checking on the database or allowing the user to reorder the qubits. We reexamine these two kinds of QPQ protocols and find neither of them can work very well. We give concrete cheating strategies for both participants and show that honesty checking of inner participant should be dealt more carefully in for example the choosing of checking qubits. Finally, we give an idea to realize realtime detection of dishonest database in QPQ of blocks (i.e. multi-bit database items).
Theory of epigenetic switching due to stochastic histone mark loss during DNA replication
Authors: Movilla Miangolarra Ander , Howard Martin
Published: November 2024

How much information does a cell inherit from its ancestors beyond its genetic sequence? What are the epigenetic mechanisms that allow this? Despite the rise in available epigenetic data, how such information is inherited through the cell cycle is still not fully understood. Often, epigenetic marks can display bistable behaviour and their bistable state is transmitted to daughter cells through the cell cycle, providing the cell with a form of memory. However, loss-of-memory events also take place, where a daughter cell switches epigenetic state (with respect to the mother cell). Here, we develop a framework to compute these epigenetic switching rates, for the case when they are driven by DNA replication, i.e. the frequency of loss-of-memory events due to replication. We consider the dynamics of histone modifications during the cell cycle deterministically, except at DNA replication, where nucleosomes are randomly distributed between the two daughter DNA strands, which is therefore implemented stochastically. This hybrid stochastic-deterministic approach enables an analytic derivation of the replication-driven switching rate. While retaining great simplicity, this framework can explain experimental switching rate data, establishing its biological importance as a framework to quantitatively study epigenetic inheritance.
Noncommutativity and its role in constant-roll inflation models with non-minimal coupling constrained by swampland conjectures
Authors: Gashti Saeed Noori , Alipour Mohammad Reza , Afshar Mohammad Ali S. , Sadeghi Jafar
Published: November 2024

In this paper, using Hamiltonian formalism, we obtain solutions for constant-roll inflation according to the noncommutativity and the non-minimal coupling field of the Lagrangian. We consider three different types of couplings: power-law, exponential, and logarithmic. Subsequently, by plotting some figures, we study the effects of these coupling in constant-roll inflation with noncommutative parameters. We identify and specify the permissible regions of each case of the swampland conjecture and determine the best model. We find that the exponential, logarithmic, and power-law couplings with

agree with the dS swampland conjecture. These couplings provide similar results in both cases, some of which are compatible and some incompatible with the dS swampland conjectures. Moreover,

is more compatible than

, and the consistency value in the second boundary condition is much higher than in the first. The order of better compatibility of couplings with the swampland conjecture is ranked as follows: exponential non-minimal coupling, logarithmic non-minimal coupling, and power-law non-minimal coupling. For each type of coupling, we calculate the values of the scalar spectral index

and the tensor-to-scalar ratio r for two different potentials and compare them with the observational data from Planck 2018. We also determine the range of the free parameters

of the further refining de Sitter swampland conjecture (FRDSSC) that make the model consistent with the conjecture. We find that the model satisfies the FRDSSC for all types of couplings and both potentials, with some constraints on the parameters.
Stability of sputtered iridium oxide neural microelectrodes under kilohertz frequency pulsed stimulation
Authors: Maeng Jimin , Frederick Rebecca A , Dousti Behnoush , Ansari Ifra I , Joshi-Imre Alexandra , Cogan Stuart F , Deku Felix
Published: November 2024

Objective. Kilohertz (kHz) frequency stimulation has gained attention as a neuromodulation therapy in spinal cord and in peripheral nerve block applications, mainly for treating chronic pain. Yet, few studies have investigated the effects of high-frequency stimulation on the performance of the electrode materials. In this work, we assess the electrochemical characteristics and stability of sputtered iridium oxide film (SIROF) microelectrodes under kHz frequency pulsed electrical stimulation. Approach. SIROF microelectrodes were subjected to 1.5–10 kHz pulsing at charge densities of 250–1000 μC cm−2 (25–100 nC phase−1), under monopolar and bipolar configurations, in buffered saline solution. The electrochemical behavior as well as the long-term stability of the pulsed electrodes was evaluated by voltage transient, cyclic voltammetry, and electrochemical impedance spectroscopy measurements. Main results. Electrode polarization was more pronounced at higher stimulation frequencies in both monopolar and bipolar configurations. Bipolar stimulation resulted in an overall higher level of polarization than monopolar stimulation with the same parameters. In all tested pulsing conditions, except one, the maximum cathodal and anodal potential excursions stayed within the water window of iridium oxide (−0.6–0.8 V vs Ag|AgCl). Additionally, these SIROF microelectrodes showed little or no changes in the electrochemical performance under continuous current pulsing at frequencies up to 10 kHz for more than 109 pulses. Significance. Our results suggest that 10 000 μm2 SIROF microelectrodes can deliver high-frequency neural stimulation up to 10 kHz in buffered saline at charge densities between 250 and 1000 μC cm−2 (25–100 nC phase−1).
Exploring the integration of a global AI model with traditional data assimilation in weather forecasting
Authors: Xu Hongxiong , Duan Yihong , Xu Xiangde
Published: November 2024

Recent advancements in artificial intelligence (AI) have profoundly transformed weather forecasting, challenging traditional reliance on numerical weather prediction (NWP) models. Despite notable progress, AI models still depend heavily on traditional NWP systems to generate analysis fields, a dependency that increases computational demands and might limit forecast accuracy. This study explored the integration of gridpoint statistical interpolation (GSI) with the Pangu-Weather AI forecasting model (GSI-Pangu), and assessed the potential for AI models to autonomously generate forecasts by leveraging mature data assimilation (DA) systems. Our experiments commenced by adopting ERA5 reanalysis data for the initial cycle, and then involved assimilation of simulated observations in subsequent cycles, spanning a month-long period. In our experiments, ERA5 reanalysis data were used exclusively to initialize the first forecast cycle, after which simulated observations were assimilated in subsequent cycles throughout the month-long period. Results demonstrated notable enhancements in forecast accuracy, with reductions in the root mean square error across various atmospheric variables compared with the results of a control experiment without DA. Additionally, the results highlighted GSI-Pangu’s ability to predict large-scale circulation patterns of extreme precipitation events, together with its effectiveness in driving regional models to accurately forecast precipitation intensity and distribution. Successful implementation of GSI within the Pangu-Weather framework underscores the transformative potential of hybrid forecasting systems, which merge conventional meteorological techniques with AI innovations, thereby facilitating accelerated adoption of AI in weather forecasting.
Soil properties regulating water constraint by dominating ecosystem water demand in water-limited ecosystems
Authors: Zhu Xinrong , Wang Liming , Wu Lu
Published: November 2024

The influence of soil properties on soil water uptake and usage by vegetation remains inadequately understood. Prior studies predominantly correlated soil properties with wilting points and field water capacity; however, our novel framework investigates how soil properties drive ecosystem-level constraints on vegetation growth through soil water. In this study, a new paradigm was introduced for understanding the relationship between vegetation growth and soil moisture, characterized by a critical soil moisture (CSM) threshold that delineates the transition of vegetation into a moisture-limited state. This threshold declines sufficiently with soil desiccation. Our results highlight the pivotal role of soil properties in modulating this CSM threshold to meet the water demands of vegetation growth at the ecosystem-level. Globally, the regulation by soil properties ranges on the CSM threshold ranges from −0.18 cm3 cm−3 to +0.16 cm3 cm−3. The positive effect of soil properties in lowering this threshold for vegetation water demand significantly mitigated water constraints, thereby enhancing the vegetation growth. Notably, sandy soil textures were found to positively affect the lowering of CSM threshold in water-limited ecosystems. Our study provides valuable insights into the intricate role of soil properties in shaping global vegetation growth and proposes a new conceptual framework for their incorporation into the earth system models.
Planar scanning probe microscopy enables vector magnetic field imaging at the nanoscale
Authors: Weinbrenner Paul , Quellmalz Patricia , Giese Christian , Flacke Luis , Müller Manuel , Althammer Matthias , Geprägs Stephan , Gross Rudolf , Reinhard Friedemann
Published: November 2024

Planar scanning probe microscopy is a recently emerging alternative approach to tip-based scanning probe imaging. It can scan an extended planar sensor, such as a polished bulk diamond doped with magnetic-field-sensitive nitrogen-vacancy (NV) centers, in nanometer-scale proximity of a planar sample. So far, this technique has been limited to optical near-field microscopy and has required nanofabrication of the sample of interest. Here we extend this technique to magnetometry using NV centers and present a modification that removes the need for sample-side nanofabrication. We harness this new ability to perform a hitherto infeasible measurement - direct imaging of the three-dimensional vector magnetic field of magnetic vortices in a thin film magnetic heterostructure, based on repeated scanning with NV centers with different orientations within the same scanning probe. Our result opens the door to quantum sensing using multiple qubits within the same scanning probe, a prerequisite for the use of entanglement-enhanced and massively parallel schemes.
Driving superconducting qubits into chaos
Authors: Chávez-Carlos Jorge , Prado Reynoso Miguel A , Cortiñas Rodrigo G , García-Mata Ignacio , Batista Victor S , Pérez-Bernal Francisco , Wisniacki Diego A , Santos Lea F
Published: November 2024

Kerr parametric oscillators are potential building blocks for fault-tolerant quantum computers. They can stabilize Kerr-cat qubits, which offer advantages toward the encoding and manipulation of error-protected quantum information. The recent realization of Kerr-cat qubits made use of the nonlinearity of transmon superconducting circuits and a squeezing drive. Increasing nonlinearities can enable faster gate times, but, as shown here, can also induce chaos and melt the qubit away. We determine the region of validity of the Kerr-cat qubit and discuss how its disintegration could be experimentally detected. The danger zone for parametric quantum computation is also a potential playground for investigating quantum chaos with driven superconducting circuits.
Rural development drives temporal turnover in plant diversity in a China’s scenic area
Authors: Zhang Jia , Li Weicheng , Yang Guofu , Wang Yue , Ji Xinxin , Zhang Xiaojian , Lu Yijun
Published: November 2024

Rural development has the potential to improve the well-being of villagers, but it may also impact local plant diversity. In addition, plant diversity differs across various subareas of rural development efforts in scenic areas, reflecting variations along the center-periphery gradient. To explore the relationship between economic development, plant diversity, and villagers’ well-being in villages within scenic areas during the rural development process, this study analyzed plant species data and satellite remote sensing images between 1984 and 2021, focusing on changes in land-use types in the Hangzhou West Lake Scenic Area and their impacts on plant diversity in the central, middle, and peripheral scenic areas. The results indicated that the area of rural construction land decreased, compared to 1984, while other land use types showed varying degrees of increase. Specifically, part of the forest in the peripheral scenic area was transformed into tea fields, resulting in an observable increase in the overall area of tea field. Moreover, the number of plant species decreased along the center-periphery gradient of the scenic spot. The greatest differences in the number of plant species and increases in the number of invasive plants were found in the peripheral scenic area, reflecting the greater impact of rural development in this region. Additionally, the number of rare and endangered plant species increased the most in the central scenic area in recent years, which was related to the use of urban green space to protect such plants. Ellenberg’s ecological indicator values (EIVs) indicated an increase in the number of species preferring shady locations and acidic soils in the scenic areas. The changes in land use and production and business activity strategies in the villages of the West Lake Scenic Area improved the villagers’ well-being, and the resulting factors such as the introduction of non-indigenous plants and environmental filtering changed local plant diversity. Therefore, the administrators should carefully consider the trade-off between conserving biodiversity and enhancing the well-being of the local villagers. The findings offer evidence of how different economic development models over time can influence rural biodiversity and villagers’ well-being, providing a reference for sustainable development in scenic spot villages.
Density matrix emulation of quantum recurrent neural networks for multivariate time series prediction
Authors: Viqueira J D , Faílde D , Juane M M , Gómez A , Mera D
Published: November 2024

Quantum recurrent neural networks (QRNNs) are robust candidates for modelling and predicting future values in multivariate time series. However, the effective implementation of some QRNN models is limited by the need for mid-circuit measurements. Those increase the requirements for quantum hardware, which in the current noisy intermediate-scale quantum era does not allow reliable computations. Emulation arises as the main near-term alternative to explore the potential of QRNNs, but existing quantum emulators are not dedicated to circuits with multiple intermediate measurements. In this context, we design a specific emulation method that relies on density matrix formalism. Using a compact tensor notation, we provide the mathematical formulation of the operator-sum representation involved. This allows us to show how the present and past information from a time series is transmitted through the circuit, and how to reduce the computational cost in every time step of the emulated network. In addition, we derive the analytical gradient and the Hessian of the network outputs with respect to its trainable parameters, which are needed when the outputs have stochastic noise due to hardware errors and a finite number of circuit shots (sampling). We finally test the presented methods using a hardware-efficient ansatz and four diverse datasets that include univariate and multivariate time series, with and without sampling noise. In addition, we compare the model with other existing quantum and classical approaches. Our results show how QRNNs can be trained with numerical and analytical gradients to make accurate predictions of future values by capturing non-trivial patterns of input series with different complexities.
Affordability of healthy and water-saving dietary patterns in The Gambia
Authors: Felix Jyoti , Scheelbeek Pauline FD , Hadida Genevieve , Bose Indira , Jallow Bakary , Murray Kris A , Prentice Andrew M , Green Rosemary , Ali Zakari
Published: November 2024

Dietary modification has the potential to improve nutritional status and reduce environmental impacts of the food system. However, for many countries, the optimal composition of locally contextualized healthy and sustainable diets is unknown. The Gambia is vulnerable to climate-change-induced future water scarcity which may affect crop yields and the ability to supply healthy diets. This study identifies potential shifts in Gambian diets that could make diets healthier and reduce the associated agricultural water footprint (WF), and assesses the cost and affordability implications of such dietary changes. Gambian Integrated Household Survey (IHS) food consumption data was combined with market prices, food expenditure and agricultural WF data. Current dietary patterns were compared with World Health Organization (WHO) dietary guidelines and optimized using linear programming to identify least-cost diets that met nutrition recommendations and reduced agricultural water use. Optimization scenarios explored the maximum reduction in green water use that could be achieved with ‘culturally-acceptable’ dietary shifts, and the magnitude of shifts required to maintain green water use at current levels. On average, current diets provide adequate energy and have appropriate macronutrient composition. However, only 14% of households consume enough fruit and vegetables (F&Vs), and consumption of added sugars exceeds recommendations. With ‘culturally-acceptable’ changes in consumption, agricultural water use could decrease by 10%–13% or increase by 9%, depending on the baseline dietary pattern. Extreme dietary shifts will be required to maintain water use at 2015 levels with projected population growth. To meet WHO recommendations, dietary costs would increase by 43% compared to the current baseline. Healthy and green water-saving diets would require 48%–63% of average household expenditure to purchase, which is unaffordable for almost half of the population. F&Vs alone account for 31%–40% of the cost of optimized diets compared to 12% of current diets. Dietary modification has the potential to improve the nutritional quality of Gambian diets while reducing agricultural water use, but the required changes are likely to be unaffordable for a large proportion of the population. Improving availability and affordability of nutritious foods—particularly F&Vs—will be crucial for the accessibility of healthy and sustainable diets in the Gambian population.
Constructing Victimhood
Authors: Lawther Cheryl
Published: November 2024

This book seeks to go ‘beyond innocence and guilt’ to expand the criminological, victimological, and transitional justice imagination with regard to who we ‘see’ as victims, what we ‘hear’ as experiences of victimisation, and who makes these determinations. The book argues that the construction, reproduction, and politicisation of victimhood is structured not only by notions of innocence and guilt and the existence of complex victims, but by larger questions concerning the existence of hierarchies of victimhood, the exercise of voice and agency, the role of silence and the silencing of certain variants of victimhood, the presence of victimhood in the physical landscape, and the haunting impact of unresolved legacies of violent conflict. By failing to cast the transitional justice gaze more widely, this book argues that it is not only the ‘voices in the cracks’ that will be collapsed but entire experiences of victimhood and victimisation. Moreover, if transitional justice is to live up to its claims of being ‘victim-centred’, widening its conceptual and practical boundaries to recognise the multiple and overlapping variables that construct and reproduce understandings of victimhood is essential. Pursing this line of enquiry, this book aims to make a step-change in the understanding of victimhood in post-conflict and transitional contexts.
Victimhood, Silence, and Denial
Authors: Lawther Cheryl
Published: November 2024

Chapter 6 uncouples the role of silence and silencing in the construction, politicisation, and reproduction of victimhood. The starting point for this chapter is the argument that silence is both a social construction and a form of communication (Winter 2010). It is also inherently political. Privileging notions of ‘silence as dignity’, ‘silence as protection’, and ‘silence as fear’, the first part of the chapter focuses on the dynamics of silence and the existence of cultures of silence after conflict-related loss. In contrast, the second part of the chapter examines the silencing of gender-based victimhood. Through the themes of ‘Silence and the Conditions of Conflict’ and ‘Silence and the Self-Imagination’, this part of the chapter interrogates the silencing that can occur at the intersection of the specific conditions of a conflict, the operation of the state and its criminal justice system, and the self-imagination of non-state armed groups.
Moving forward from Cockcroft-Gault creatinine clearance to race-free estimated glomerular filtration rate to improve medication-related decision-making in adults across healthcare settings: A consensus of the National Kidney Foundation Workgroup for Implementation of Race-Free eGFR-Based Medication-Related Decisions
Authors: St. Peter Wendy L , Bzowyckyj Andrew S , Anderson-Haag Tracy , Awdishu Linda , Blackman Michael , Bland Andrew , Chan Ethan , Chmielewski Christine , Delgado Cynthia , Eyler Rachel , Foster Charles , Hudson Joanna , Kane-Gill Sandra L , Kliethermes Mary Ann , Le Tuan , Madabushi Rajanikanth , Martin Brianna , Miller W Greg , Neumiller Joshua J , Philbrick Ann M , Roberts Glenda , Schandorf Venita , Webb Andrew J , Wu Dennis , Nolin Thomas D ,   Written on behalf of the National Kidney Foundation Workgroup for Implementation of Race-Free eGFR-Based Medication-Related Decisions
Published: November 2024

Purpose

The goals of this paper are to (1) provide evidence and expert consensus to support a unified approach to estimating kidney filtration in adults with stable kidney function using race-free estimated glomerular filtration rate (eGFR) in place of Cockcroft-Gault estimated creatinine clearance (C-G eCrCL) for medical and medication-related decisions, and (2) demonstrate how adjusting eGFR results for an individual’s body surface area (BSA) when it is higher or lower than 1.73 m2 will improve results for medication-related decisions.

C-G eCrCL is predominantly used by US pharmacists to determine eGFR for the purposes of medication-related decisions, even though more accurate eGFR equations exist. Several driving factors make it the ideal time to shift clinical practice from using C-G eCrCL to eGFR. These factors include the following: (1) 2024 Food and Drug Administration (FDA) guidance for industry recommends eGFR over C-G eCrCL to evaluate the impact on pharmacokinetics in patients with impaired kidney function; (2) a joint National Kidney Foundation (NKF) and American Society of Nephrology task force recommends 3 race-free Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) eGFR equations for medical and medication-related decision-making; (3) the almost ubiquitous use of standardized serum creatinine assay methods in US clinical laboratories; and (4) increasing availability and use of serum cystatin C for eGFR assessment. This publication guides practitioners through the rationale for using race-free eGFR equations for medication-related decisions and how to implement this practice change.

Conclusion

The NKF Workgroup for Implementation of Race-Free eGFR-Based Medication-Related Decisions suggests that health systems, health settings, clinical laboratories, electronic health record systems, compendia and data vendors, and healthcare practitioners involved with medication-related decision-making transition away from C-G eCrCL and towards the race-free eGFR equations for more accurate assessment of kidney filtration and consistency in medication and medical decision-making across the US.
Examining Preparedness and Onboarding for Social Work Practice in Schools
Authors: Cox Tory Lynn , Fitzgerald Terence , Alvarez Michelle
Published: November 2024

This article highlights a research study investigating how school social workers (SSWers) are prepared during their MSW programs to work in various school settings. A survey was completed by 175 SSWers at the School Social Work Association of America 2019 National Conference. The results suggest that survey participants deemed insufficient the level of school social work (SSW) preparedness received at degree-granting institutions. For example, 38 percent of respondents did not take an SSW course, 49 percent did not intern in a school setting, and 85 percent would have benefited from additional SSW courses. Further, the respondents discussed numerous areas of improvement to be addressed by SSW preparation programs and employment settings, including preparation for the political environment of schools and more intensive onboarding and mentoring in their first years of service. The evidence also points to the fortitude of SSWers to persevere in their educational settings. In response to the survey results, the study researchers organized an edited book titled The Art of Becoming Indispensable: What School Social Workers Need to Know in Their First Three Years of Practice. Limitations and implications for SSW practice are discussed as well.
Genomic prediction of heterosis, inbreeding control, and mate allocation in outbred diploid and tetraploid populations
Authors: Endelman Jeffrey B
Published: November 2024

Breeders have long appreciated the need to balance selection for short-term genetic gain with maintaining genetic variance for long-term gain. For outbred populations, the method called optimum contribution selection (OCS) chooses parental contributions to maximize the average breeding value at a prescribed inbreeding rate. With optimum mate allocation (OMA), the contribution of each mating is optimized, which allows for specific combining ability due to dominance. To enable OCS and OMA in polyploid species, new theoretical results were derived to (1) predict midparent heterosis due to dominance and (2) control inbreeding in a population of arbitrary ploidy. A new convex optimization framework for OMA, named COMA, was developed and released as public software. Under stochastic simulation of a genomic selection program, COMA maintained a target inbreeding rate of 0.5% using either pedigree or genomic IBD (identity-by-descent) kinship. Significantly more genetic gain was realized with pedigree kinship, which is consistent with previous studies showing the selective advantage of an individual under OCS is dominated by its Mendelian sampling term. Despite the higher accuracy (+0.2–0.3) when predicting mate performance with OMA compared with OCS, there was little long-term gain advantage. The sparsity of the COMA mating design and flexibility to incorporate mating constraints offer practical incentives over OCS. In a potato breeding case study with 170 candidates, the optimal solution at 0.5% inbreeding involved 43 parents but only 43 of the 903 possible matings.
‘Ice sheet conservation’ and international discord: governing (potential) glacial geoengineering in Antarctica
Authors: Flamm Patrick , Shibata Akiho
Published: November 2024

Should current unmitigated emissions continue, there is a growing chance of collapse of the West Antarctic Ice Sheet, one of the planetary climate tipping points at greatest risk of being crossed. Such a collapse would subject the world to an increase of several metres in average global sea-level rise over just a few centuries. In this context, there is an academic debate about the potential of supporting glacial stability through artificial infrastructures such as an undersea ‘curtain’. However, this ‘ice sheet conservation’ would come with significant yet unforeseeable technical and environmental risks. Moreover, in this debate governance risks have been either neglected or understated. We argue that the proposed infrastructures could negatively implicate the ‘peaceful purposes only’ obligation enshrined in the Antarctic Treaty. By affecting contentious areas of Antarctic geopolitics, such as authority, sovereignty and security, there is a significant risk that the project would make the Antarctic ‘the scene or object of international discord’. Even if the ice curtain idea were to be technically feasible and environmentally harmless, it would still create significant political and legal challenges for the current governance arrangements in the Antarctic.
Implementation of a rule-based algorithm to find patients eligible for cancer clinical trials
Authors: Bickell Nina A , May Benjamin , Havrylchuk Ihor , John Jimmy , Lin Sylvia , Tao Ariana , Yagnik Radhi , Tatonetti Nicholas P
Published: November 2024

Objective

To explore implementing regular expressions (RegEx) to streamline patient identification and classification for matching to clinical trials.

Materials and Methods

To prepare approaches needed to match patients to relevant cancer clinical trials, we combined NCI’s Clinical Trials Search API to extract high-level eligibility criteria, including cancer type, stage, receptor/biomarker status, with similar data of patients with appointments in the upcoming week. Using RegEx, we prospectively identified all patients with breast, liver, or lung cancers at treatment decision points at 2 Cancer Centers’ and 2 community hospitals’, classified their cancer type, stage, and receptor/biomarker status. We evaluated accuracy using RegEx against manual reviews.

Results

Algorithm accuracy to identify patients at treatment decision points revealed 92% True Negative and 53% True Positive rate. Staging accuracy varied from 67% to 95%, and receptor/biomarker status accuracy from 76% to 86%.

Discussion and Conclusion

Using RegEx significantly reduced the number of patients requiring manual review, demonstrating a reduction in manual labor and potential biases, which can improve efficiency and inclusivity of clinical trial enrollment processes, especially in resource limited or data sensitive environments.

Trial Registration

NCT05146297