bluuebunny/crossref_metadata_2025 huggingface dataset:
Novel CPU cache architecture based on two-dimensional MTJ device with ferromagnetic Fe3GeTe2
Authors: Han Shaopu , Jiang Yanfeng
Published: January 2024

With the development of Artificial Intelligence (AI) in recent years, the fields of computer, biology, medicine, and aerospace have demanded higher requirements for the processing and storage of information. In this paper, a novel Magnetic Tunnel Junction (MTJ) based Spin-Orbital Torque Magnetic Random Access Memory (SOT-MRAM) composed of Fe3GeTe2 (FGT) is employed as a storage medium in the computer architecture. On the basis of the analysis of the fundamentals, model configuration, characteristics and performance advantages of the FGT based SOT device, a hybrid storage (L1, L2, Last Level Cache) is constructed, with FGT-SOT-MRAM, conventional SOT-MRAM and STT-MRAM replacing the original static random access memory (SRAM) in the novel triple-level CPU cache architecture. This can override the increasing leakage problem of SRAM, while opening up the application of two-dimensional van der Waals ferromagnets in computer systems at the L1 cache level. Meanwhile, an innovative cache optimization scheme is put forward for magnetic memory to better match the performance of FGT-SOT-MRAM to CPU. The simulation results demonstrate that the FGT-based MRAM can achieve up to 38.03% IPC optimization and 53.41% power optimization in the CPU cache system in contrast to the conventional ones.
Fabrication of compact circular ring antenna loaded with Gd-YIG ferrites: Photon–magnon interaction
Authors: Yadav Sheetal , Sharma Monika , Kuanr Bijoy K.
Published: January 2024

In telecommunications technology, transmitting and receiving signals is not possible without an integrated antenna. Recently, novel approaches of transmitting and receiving signals using advancement in quantum technology as “information coherent transfer” have been emphasized which overcomes the limitations of superconducting qubits. In the present investigation, a compact-sized circular-ring antenna was designed for a 12 GHz centre frequency. The antenna was topped with Gd(x)-doped YIG (x = 0.0, 0.1, 0.2, 0.3) thin disks to investigate its tunable operation over the tri-band (C to Ku) frequencies due to the photon–magnon coupling, which enables coherent qubit information transmission from an electromagnetic (EM) carrier to the magnons. The proposed prototype of the antenna is validated using HFSS simulation. To characterize the frequency tunability of the designed antenna, we measured the return loss (S11) via a vector network analyzer as a function of dc magnetic field. Different concentrations of Gd-doped YIG ferrites (Gdx-YIG) have been loaded on ring antennas to observe strong anti-crossing phenomena with the application of an external magnetic field. The designed antenna has a tunability of around 300% for a small applied magnetic field up to 3.7 kOe. The maximum gain of dual resonance antenna is 1.4 for higher magnetic field of 3.7 kOe. The highest efficiency and lowest bandwidth of 30% and 14% respectively, for Gd0.1-YIG disk are observed. The measured normal mode splitting spectrum as a function of bias magnetic field that gives the maximum coupling strength is 153 MHz for a Gd concentration of 0.1. For practical applications, such antennas are suitable for use in tunable tri-band or multi-band applications (C to Ku).
A method for positioning multiple weak magnetic target signals under the interference of strong magnetic sources
Authors: Zhang Shunyu , Qiu Jing , Song Hongrui , Li Mingyu , Sun Hexuan , Huang Shuanglong
Published: January 2024

When locating multiple magnetic targets, the interference between each magnetic dipole is often ignored, we propose a method to detect and locate multiple weak magnetic target signals under the interference of strong magnetic sources. First, under different burial depths, the influence of shallow magnetic sources and deep magnetic sources on each other was studied and the conclusion was drawn that shallow targets are less affected by deep targets, while deep targets have the opposite effect; and the normalized source strength (NSS) is introduced into the concept of magnetic inclination in the terrain field, this simultaneously utilizes the insensitivity of magnetic inclination to burial depth and the isotropy of NSS to amplify the signal characteristics of submerged deep targets, and initially obtains the horizontal position of the measured target; the idea of locating shallow targets first, removing the interference of shallow targets, and then locating deep targets is proposed, The results of positioning were fitted and optimized by moth Moth-Flame Optimization (MFO), and the accuracy of positioning was improved. In the simulation, compared with the total magnetic field intensity (TMI), the root mean square error (RMSE) of the positioning results of the three measured targets after using the proposed method is reduced from 0.2820, 0.1831 and 0.3972 to 0.0112, 0.0145 and 0.0326, the positioning error of deep target is greatly reduced, which proves the feasibility of the proposed method, in the actual experiment, the positioning accuracy of the deep measured magnetic source is also improved.
Estimating the location of the hook-wire used in breast-conserving surgery using a magnetometer
Authors: Debnath Oiendrila Bhowmik , Kuwahata Akihiro , Sunaga Yuki , Chikaki Shinichi , Kaneko Miki , Kusakabe Moriaki , Sekino Masaki
Published: January 2024

In the surgical treatment of nonpalpable breast lesions, such as in early-stage cancer, a hook-wire is inserted into the lesion as a marker to enable surgeons to excise the tissue, along with the hook-wire, with a good margin. However, a benchmark technique for intraoperatively determining whether the excised tissue has an appropriate margin around the lesion has not yet been established. In this study, a method for locating a ferromagnetic stainless steel hook-wire inside the excised tissue using a magnetometer is proposed. The magnetometer is placed around a phantom along with the hook-wire at varied locations to map the magnetic field distribution. The three-dimensional coordinates of hook-wire are obtained by executing an optimization algorithm. The experimental results indicate that the location of the hook-wire is successfully obtained. Based on the information regarding the margin around the hook-wire, the surgeon can immediately evaluate the risk of whether some cancer cells still remain in the body.
Embedding electronic perpetual motion into single-atom catalysts for persistent Fenton-like reactions
Authors: Chen Fei , Sun Yi-Jiao , Huang Xin-Tong , Bai Chang-Wei , Zhang Zhi-Quan , Duan Pi-Jun , Chen Xin-Jia , Yang Qi , Yu Han-Qing
Published: January 2024

In our quest to leverage the capabilities of the emerging single-atom catalysts (SACs) for wastewater purification, we confronted fundamental challenges related to electron scarcity and instability. Through meticulous theoretical calculations, we identified optimal placements for nitrogen vacancies (Nv) and iron (Fe) single-atom sites, uncovering a dual-site approach that significantly amplified visible-light absorption and charge transfer dynamics. Informed by these computational insights, we cleverly integrated Nv into the catalyst design to boost electron density around iron atoms, yielding a potent and flexible photoactivator for benign peracetic acid. This exceptional catalyst exhibited remarkable stability and effectively degraded various organic contaminants over 20 cycles with self-cleaning properties. Specifically, the Nv sites captured electrons, enabling their swift transfer to adjacent Fe sites under visible light irradiation. This mechanism accelerated the reduction of the formed “peracetic acid-catalyst” intermediate. Theoretical calculations were used to elucidate the synergistic interplay of dual mechanisms, illuminating increased adsorption and activation of reactive molecules. Furthermore, electron reduction pathways on the conduction band were elaborately explored, unveiling the production of reactive species that enhanced photocatalytic processes. A six-flux model and associated parameters were also applied to precisely optimize the photocatalytic process, providing invaluable insights for future photocatalyst design. Overall, this study offers a molecule-level insight into the rational design of robust SACs in a photo-Fenton-like system, with promising implications for wastewater treatment and other high-value applications.
An exploratory study of intonational variation in L1 and L2 English speakers’ pragmatic production of high imposition
requests and refusals
Authors: Kostromitina Maria
Published: January 2024

This exploratory study examined the intonational patterns and corresponding speech act strategies in L1 and L2
English speakers’ production of high imposition requests and refusals that were elicited using video-based multiple turn discourse
completion tasks (DCTs). The participants, 34 L1 American English speakers and 14 high-proficiency L2 English speakers, recorded
their oral responses to 10 multiple-turn video-based DCTs. Using Brazil’s (1997)
framework, the collected speech samples were analyzed for tone choices in each tone unit. Pragmatic strategies in the produced
speech acts were analyzed by adapting the existing coding frameworks (Beebe et al.,
1990; Blum-Kulka et al., 1989). The extracted tone choices and
lexico-mathematical strategies were compared between the two language groups. The results preliminarily revealed differences in
the use of tones by L1 and L2 English speakers in performing requests and refusals. Moreover, while the employed speech act
strategies were largely similar between the two speaker groups, the associated tone choices showed contrasting usage patterns.
Engineering Quantum Criticality for Quantum Dot Power Harvesting
Authors: Wang 王 Jin-Yi 金义 , Nian 年 Lei-Lei 磊磊 , Lü 吕 Jing-Tao 京涛
Published: January 2024

Coupling of quantum-dot circuits to microwave photons enables us to investigate photon-assisted quantum transport. Here, we revisit this typical circuit quantum electrodynamical setup by introducing the Kerr nonlinearity of photons. By exploiting quantum critical behavior, we propose a powerful scheme to control the power-harvesting efficiency in the microwave regime, where the driven-dissipative optical system acts as an energy pump. It drives electron transport against a load in the quantum-dot circuit. The energy transfer and, consequently, the harvesting efficiency are enhanced near the critical point. As the critical point moves towards to low input power, high efficiency within experimental parameters is achieved. Our results complement fundamental studies of photon-to-electron conversion at the nanoscale and provide practical guidance for designs of integrated photoelectric devices through quantum criticality.
Measuring gloss using spectral reflectance
Authors: Zarobila Clarence J , Nadal Maria E , Miller C Cameron
Published: January 2024

Gloss is historically measured at three angles of incidence, 20°, 60°, and 85°, using a light source filtered to replicate Illuminant C and a colored glass filter designed to reproduce the CIE 1931 photopic luminous efficiency function. Herein an alternate method that relies on the spectral reflectance of a gloss standard and the sample, both measured with a new reference gonio-spectrometer and in accordance with the geometries specified in internationally recognized standards, is presented. The spectral reflectance measured with the aid of a spectrometer is converted to luminous flux which is then used to calculate gloss. This alternate method eliminates the errors associated with the source actual spectral power distribution vs. that of Illuminant C, and the actual spectral transmittance of the colored glass filter used vs. the spectral distribution of the photopic luminous efficiency function. Gloss measurement results for a synthetic quartz sample, Suprasil 311, are presented. The measured values averaged over three reflectance measurements are 71.3 ± 1.2 (k = 2), 82.2 ± 0.9 (k = 2), and 98.1 ± 3.0 (k = 2), and these agree exceptionally well with the theoretical values of 71.3, 82.1, and 98.1 Gloss Units at 20°, 60°, and 85°, respectively. Components of uncertainty are discussed. In addition, a gloss scale is proposed. The components of the scale have been selected from readily available optical glass types for ease of fabrication and relatively low cost. They span a range from 4.4 to almost 170 Gloss Units for light at 20° angle of incidence.
Research on bearing ZC feature selection method based on DWCMI
Authors: Chen Qing , Liu Tao , Wu Xing
Published: January 2024

In light of the issues related to the omission of crucial features and the incorrect selection of redundant features in existing feature selection methods for zero-crossing features, this paper presents a feature selection method based on dynamic weights condition mutual information (DWCMI). In this method, the main factor of the objective function for feature evaluation is conditional mutual information, while also incorporating a complementary evaluation criterion based on conditional mutual information to address the issue of misselecting redundant features. By introducing a dynamic weight coefficient, we can accurately measure the importance of selected features by assessing their dynamic change in mutual information, thereby avoiding any oversight of crucial features. In the process of designing the algorithm, computational efficiency is improved by buffering and reusing previously calculated mutual information. This approach avoids the issue of repeatedly calculating the mutual information. The necessity, effectiveness, and high efficiency of the DWCMI method have been verified through simulation and experimentation.
Accuracy assessment of crystal orientation indexations by EBSD
Authors: Shi Qiwei , Loisnard Dominique , Li Yang , Chen Zhe , Wang Haowei , Roux Stéphane
Published: January 2024

Accuracy and uncertainty analyses are essential for every measurement technology. In crystal orientation indexation by electron backscatter diffraction (EBSD), a series of accuracy estimations have been made for the Hough transform and dictionary indexation methods. The mean angular deviation is a standard parameter to indicate orientation accuracy, but this criterion is indirect and closely related to the accuracy of the projection center coordinates. Precise known orientation relationships (OR) are necessary to evaluate orientation accuracy without the ground truth. The current work uses the natural crystal twins and hardware OR to assess the orientation accuracy directly. The accuracy level for different EBSD analysis methods is compared through four experimental data sets of varying pattern definitions and noise levels. It is found that the full pattern match (FPM) algorithms improve the accuracy as compared to Hough indexation, and the gain varies greatly between 14% for fast acquisitions and 20 times for high-quality patterns. Depending on the resolution and quality of diffraction patterns, FPM results in an accuracy of crystal orientation between 0.04° and 0.9°. Comparing the two FPM variants, matching the gradients of diffraction patterns performs better in the case of high-to-median quality acquisitions while matching the pattern itself is more accurate for more noisy and low-definition patterns.
Transfer learning rolling bearing fault diagnosis model based on deep feature decomposition and class-level alignment
Authors: Dong Jingchuan , Jiang Hongyu , Su Depeng , Gao Yubo , Chen Tao , Sheng Kai
Published: January 2024

Research on transfer learning in rolling bearing fault diagnosis can help overcome challenges such as different data distributions and limited fault samples. However, most existing methods still struggle to address the zero-shot cross-domain problem within the same equipment and the few-shot cross-machine problem. In response to these challenges, this paper introduces a transfer learning rolling bearing fault diagnosis model based on deep feature decomposition and class-level alignment. The model consists of two stages. In the first stage, the original vibration signals undergo continuous wavelet transform to obtain time–frequency diagram. Subsequently, a convolutional neural network extracts features from the diagram. The obtained deep features are decomposed into four types: uncertain features, domain-shared features, domain-specific features and category features. Multiple loss functions are then employed to remove extraneous features beyond the category features. In the second stage, category features are further extracted, and convolutional block attention module is introduced to further reduce the potential interference of unexcluded irrelevant information within the category features with classification results. Simultaneously applying a class-level alignment strategy effectively alleviates inter-domain class distribution discrepancies. Experimental validation was conducted on three distinct datasets, revealing a significant improvement in the classification performance of the proposed method over alternative methods. Furthermore, the model demonstrated robustness and noise resistance.
Density-controlled electrochemical synthesis of ZnO nanowire arrays using nanotextured cathode
Authors: Eom Hyeonjin , Hur Junyoung , Sung Sang-Keun , Jeong Jun-Ho , Park Inkyu
Published: January 2024

Zinc oxide (ZnO) nanowires fabricated via wet chemical synthesis on flexible polymer substrates are inherently unstable against mechanical bending stress because of their high density and weak adhesion to the substrate. We introduce a novel method for controlling the density of such ZnO nanowire arrays using a three-dimensional corrugated metal substrate. These metal substrates, featuring extruded and recessed patterns fabricated via nanoimprint lithography, were employed as cathodes during the electrochemical deposition of ZnO nanowire arrays. The ZnO nanowire arrays synthesized on the patterned metal thin film exhibited smaller diameters and lower densities compared to those on non-patterned metal films. This reduction in density can be attributed to aligned nucleation and limited growth on the patterned metal surface. Crucially, ZnO nanowires synthesized on patterned metal substrates displayed remarkable mechanical robustness against external forces, a direct consequence of their reduced density. In contrast, nanowires synthesized on non-patterned metal substrates were broken under mechanical bending. Detailed morphological analyses performed after mechanical bending tests confirm that ZnO nanowires synthesized on nanoimprinted metal electrodes exhibited enhanced mechanical characteristics compared to those on non-patterned metal electrodes. These findings clearly demonstrate the promise of utilizing density-controlled ZnO nanowires in piezoelectric devices.
An efficient modeling workflow for high-performance nanowire single-photon avalanche detector
Authors: Li Zhe , Tan Hark Hoe , Jagadish Chennupati , Fu Lan
Published: January 2024

Single-photon detector (SPD), an essential building block of the quantum communication system, plays a fundamental role in developing next-generation quantum technologies. In this work, we propose an efficient modeling workflow of nanowire SPDs utilizing avalanche breakdown at reverse-biased conditions. The proposed workflow is explored to maximize computational efficiency and balance time-consuming drift-diffusion simulation with fast script-based post-processing. Without excessive computational effort, we could predict a suite of key device performance metrics, including breakdown voltage, dark/light avalanche built-up time, photon detection efficiency, dark count rate, and the deterministic part of timing jitter due to device structures. Implementing the proposed workflow onto a single InP nanowire and comparing it to the extensively studied planar devices and superconducting nanowire SPDs, we showed the great potential of nanowire avalanche SPD to outperform their planar counterparts and obtain as superior performance as superconducting nanowires, i.e. achieve a high photon detection efficiency of 70% with a dark count rate less than 20 Hz at non-cryogenic temperature. The proposed workflow is not limited to single-nanowire or nanowire-based device modeling and can be readily extended to more complicated two-/three dimensional structures.
Two-dimensional reductions of the Whitham modulation system for the Kadomtsev–Petviashvili equation
Authors: Biondini Gino , Bivolcic Alexander J , Hoefer Mark A , Moro Antonio
Published: January 2024

Two-dimensional reductions of the Kadomtsev–Petviashvili(KP)–Whitham system, namely the overdetermined Whitham modulation system for five dependent variables that describe the periodic solutions of the KP equation, are studied and characterized. Three different reductions are considered corresponding to modulations that are independent of x, independent of y, and of t (i.e. stationary), respectively. Each of these reductions still describes dynamic, two-dimensional spatial configurations since the modulated cnoidal wave, generically, has a nonzero speed and a nonzero slope in the xy plane. In all three of these reductions, the integrability of the resulting systems of equations is proven, and various other properties are elucidated. Compatibility with conservation of waves yields a reduction in the number of dependent variables to two, three and four, respectively. As a byproduct of the stationary case, the Whitham modulation system for the classical Boussinesq equation is explicitly obtained.
A systematic review on automatic identification of insomnia
Authors: Ingle Manisha , Sharma Manish , Kumar Kamlesh , Kumar Prince , Bhurane Ankit , Elphick Heather , Joshi Deepak , Acharya U Rajendra
Published: January 2024

Background. Insomnia is a prevalent sleep disorder characterized by difficulties in initiating sleep or experiencing non-restorative sleep. It is a multifaceted condition that impacts both the quantity and quality of an individual’s sleep. Recent advancements in machine learning (ML), and deep learning (DL) have enabled automated sleep analysis using physiological signals. This has led to the development of technologies for more accurate detection of various sleep disorders, including insomnia. This paper explores the algorithms and techniques for automatic insomnia detection. Methods. We followed the recommendations given in the Preferred Reporting Items for systematic reviews and meta-analyses (PRISMA) during our process of content discovery. Our review encompasses research papers published between 2015 and 2023, with a specific emphasis on automating the identification of insomnia. From a selection of well-regarded journals, we included more than 30 publications dedicated to insomnia detection. In our analysis, we assessed the performance of various methods for detecting insomnia, considering different datasets and physiological signals. A common thread across all the papers we reviewed was the utilization of artificial intelligence (AI) models, trained and tested using annotated physiological signals. Upon closer examination, we identified the utilization of 15 distinct algorithms for this detection task. Results. The major goal of this research is to conduct a thorough study to categorize, compare, and assess the key traits of automated systems for identifying insomnia. Our analysis offers complete and in-depth information. The essential components under investigation in the automated technique include the data input source, objective, ML and DL network, training framework, and references to databases. We classified pertinent research studies based on ML and DL model perspectives, considering factors like learning structure and input data types. Conclusion. Based on our review of the studies featured in this paper, we have identified a notable research gap in the current methods for identifying insomnia and opportunities for future advancements in the automation of insomnia detection. While the current techniques have shown promising results, there is still room for improvement in terms of accuracy and reliability. Future developments in technology and machine learning algorithms could help address these limitations and enable more effective and efficient identification of insomnia.
Assessment of bioimpedance spectroscopy devices: a comparative study and error analysis of gold-plated copper electrodes
Authors: Mussnig Sebastian , Krenn Simon , Hecking Manfred , Wabel Peter
Published: January 2024

Objective. Bioimpedance spectroscopy (BIS) is a non-invasive diagnostic tool to derive fluid volume compartments from frequency dependent voltage drops in alternating currents by extrapolating to the extracellular resistance (R
0) and intracellular resistance (R
i). Here we tested whether a novel BIS device with reusable and adhesive single-use electrodes produces results which are (in various body positions) equivalent to an established system employing only single-use adhesive electrodes. Approach. Two BIS devices (‘Cella’ and the ‘Body Composition Monitor’ [BCM]) were compared using four dedicated resistance testboxes and by measuring 40 healthy volunteers. In
vivo comparisons included supine wrist-to-ankle (WA) reference measurements and wrist-to-wrist (WW) measurements with pre-gelled silver/silver-chloride (Ag/AgCl) electrodes and WW measurements with reusable gold-plated copper electrodes. Main results. Coefficient of variation were <1% for all testbox measurements with both BIS devices. Accuracy was within ±1% of true resistance variability, a threshold which was only exceeded by the Cella device for all resistances in a testbox designed with a low R
0/R
i ratio. In
vivo, WA-BIS differed significantly between BIS devices (p < 0.001). Reusable WW electrodes exhibited larger resistances than WW-BIS with Ag/AgCl electrodes (R
0: 738.36 and 628.69 Ω; R
i: 1508.18 and 1390 Ω) and the relative error varied from 7.6% to 31.1% (R
0) and −15.6% to 37.3% (R
i). Significance. Both BIS devices produced equivalent resistances measurements but different estimates of body composition both in
silico and in WA setups in
vivo, suggesting that the devices should not be used interchangeably. Employing WW reusable electrodes as opposed to WA and WW measurement setups with pre-gelled Ag/AgCl electrodes seems to be associated with measurement variations that are too large for safe clinical use. We recommend further investigations of measurement errors originating from electrode material and current path.
Characterization of a functionally graded material produced using a new designed blender
Authors: Rahmani Kaveh , Majzoobi G H , Das R
Published: January 2024

One of the techniques widely used for fabrication of FGMs (Functionally Graded Materials) is powder metallurgy. However, producing a FGM with smooth gradient in its constituents mixture has remained a challenge yet to be met. The purpose of this research is design and manufacturing a blender for producing a functionally graded material with smooth gradient of its constituent materials. The blender was used to mix magnesium and titanium dioxide to produce Magnesium/titanium dioxide FGMs. The powder mixture was then compacted by Instron, drop hammer, and split Hopkinson bar at 600 °C. The microstructure and relative density of the functionally graded samples fabricated at different strain rates were studied in this work. SEM images clearly demonstrated a continuous and functional distribution of Mg and TiO2 particles in the produced FGM samples. It was also shown that increasing the compaction loading rate resulted in a higher relative density in the FGM samples. The maximum relative density (92%) was observed for the samples produced by Hopkinson bar. This level of density was 7% and 17% higher than the densities of the samples fabricated using drop hammer and Instron, respectively. The improvement of relative density in dynamic compaction methods is attributed to the increased compaction pressure and process being adiabatic.
Study of optical and structural properties of CZTS thin films using copper capping layer and sulfurization to correct stoichiometry
Authors: Bhale Devendra , Bute Arundhati , Tokas R B , Phatak Rohan , Vishwanadh B , Sharma R K , Biswas Arup , Bhattacharyya Dibyendu , Maiti Namita
Published: January 2024

Non-toxic, environment friendly and low cost Cu2ZnSnS4 (CZTS) thin films were deposited on sodalime glass substrates by radio frequency magnetron sputter deposition technique. Stoichiometry analysis revealed that the as-deposited films were Cu deficient. Hence, Cu capping layer was deposited, to study its’ effect on optical and structural properties of the films. These films were subsequently sulfurized in a quartz setup. Ultimately, stoichiometric CZTS films with improved Cu content up to 27.4% were obtained. The kesterite CZTS phase was identified in the samples using x-ray diffraction measurements. The morphological studies revealed that, grain size varies as a function of the thickness of Cu capping layer. The formation of undesired Cu2S and ZnS phases were also observed in the film with Cu content above and below the optimum range. Optical bandgap (Eg) of the films could also be optimized by controlling the Cu content in the film. An optimal Cu content between 24% and 26% was found to be appropriate for achieving a desired bandgap within a range of 1.55 to 1.4 eV, suitable for application in thin film solar cells. The CZTS films with corrected stoichiometry have a charge carrier density in the rage of ∼1021 cm−3, which are much better than values reported so far in the literature.
Calorimetry measurement for energy balance and energy distribution in WEST for L-mode plasmas
Authors: Gaspar J. , Gerardin J. , Corre Y. , Daumas J. , Fedorczak N. , Lamaison V. , Bourdelle C. , Ciraolo G. , Ekedahl A. , Gallo A. , Rivals N. , Tsitrone E. ,   the WEST Team
Published: January 2024

This paper presents the energy balance of 602 pulses from four different experimental campaigns for the WEST tokamak. Different magnetic configurations have been studied, with lower single null (LSN) and upper single null (USN) configuration with deuterium or helium plasmas. The energy balance is closed with an imbalance of about 5% of the total injected energy for most of the campaigns and for different magnetic configurations. The distribution over the whole machine is shown, with the outer first wall receiving most of the energy due to its large surface area with about 30% of the total heat load, and the divertor with 25% due to the heat loads deposited by the convected power in the scrape-off layer (SOL). Finally, the tomography inversion of the bolometry measurement allows us to disentangle the contribution of the radiated and convected power in the energy absorbed by each type of plasma-facing component. We show that in the USN configuration about 63% of the available energy in the SOL is deposited in the upper divertor (UDIV) through convected heat loads, while in LSN this value is spread over the lower divertor with 45% and the baffle and UDIV with about 10% for both.
The effectiveness of enhanced Moringa oleifera leaves extract powder (MOLEP) in beef patties as a fortification on a well-done cooking method
Authors: Swastike W , Kartikasari L R , Nuhriawangsa A M P , Barido F H , Hertanto B S
Published: January 2024

Fast food like patties has become more popular with the lifestyle changes. However after the pandemic, consumers have shown an increased interest in functional foods that not only provide essential nutrients but also possess potential health-promoting properties. The tree that is rich in nutrition and also has health benefits is Moringa oleifera called the “miracle tree”. The cooking method used when serving will also help to keep you safe and will have an impact on beef patties quality. This study investigates the effectiveness of enhanced Moringa oleifera leaves powder in beef patties on the well-done cooking method. The ingredients used in this study were beef ground meat, Moringa oleifera leaves extract powder (MOLEP), tapioca meal, seasonings, salt, sugar, egg whites, and cold water. The commercial beef meat that used as a raw material of beef patties with the ratio of MOLEP as fortification are 0 (P0), 1 (P1), 2 (P2), 3 (P2), and 4% (P4). The data were analyzed using analysis of variance (ANOVA). The results of the analysis showed that there was a significant difference (P<0.05) in the pH value after cooking, diameter patties after cooking, Springiness, Water holding capacity, and also cooking loss. The general conclusion of this research are The general conclusion of this research is that MOLEP can be applied and enhanced into beef patties as a fortification but not more than 0,3%. Enhancement of MOLEP in beef patties can inhibit the shrinkage of the product when it is cooked in a well-done cooking method.
Improving cross-subject classification performance of motor imagery signals: a data augmentation-focused deep learning framework
Authors: Ozelbas Enes , Tülay Emine Elif , Ozekes Serhat
Published: January 2024

Motor imagery brain-computer interfaces (MI-BCIs) have gained a lot of attention in recent years thanks to their potential to enhance rehabilitation and control of prosthetic devices for individuals with motor disabilities. However, accurate classification of motor imagery signals remains a challenging task due to the high inter-subject variability and non-stationarity in the electroencephalogram (EEG) data. In the context of MI-BCIs, with limited data availability, the acquisition of EEG data can be difficult. In this study, several data augmentation techniques have been compared with the proposed data augmentation technique adaptive cross-subject segment replacement (ACSSR). This technique, in conjunction with the proposed deep learning framework, allows for a combination of similar subject pairs to take advantage of one another and boost the classification performance of MI-BCIs. The proposed framework features a multi-domain feature extractor based on common spatial patterns with a sliding window and a parallel two-branch convolutional neural network. The performance of the proposed methodology has been evaluated on the multi-class BCI Competition IV Dataset 2a through repeated 10-fold cross-validation. Experimental results indicated that the implementation of the ACSSR method (80.47%) in the proposed framework has led to a considerable improvement in the classification performance compared to the classification without data augmentation (77.63%), and other fundamental data augmentation techniques used in the literature. The study contributes to the advancements for the development of effective MI-BCIs by showcasing the ability of the ACSSR method to address the challenges in motor imagery signal classification tasks.
Briefing: How a mutiny became a(nother) coup: The politics of counterinsurgency and international military partnerships in Niger
Authors: McCullough Aoife , Sandor Adam
Published: January 2024

This briefing explores the factors that led to the consolidated position of the Nigerien Security and Defence forces in support of the coup d’état launched the night of 26th July 2023. The initial blockade of the former President’s palace by the head of the Presidential Guard and 350 of its members looked like a mutiny. However, instead of moving swiftly to end the blockade, commanders from across the security forces appeared on national television that night to announce a coup. We show how dominant theories that have been used to explain the coup’s (unlikely) success, including those relying on patrimonialism and coups as intra-military coordination games, do not adequately explain the support for the coup across rank and file, and the direction the coup took once announced. We argue that this coup cannot be fully explained without considering how the coup leaders advanced powerful ideological messages to garner support. By making the coup about ‘correcting’ the government’s counter-insurgency strategy and regaining Niger’s sovereignty through the removal of French counter-terrorism troops from the country, members of the military believed that everyone else would support the coup, thus making it less likely that they would resist the coup leaders.
Development of the lyrics-based deep learning algorithm for identifying alcohol-related words (LYDIA)
Authors: Bonela Abraham Albert , He Zhen , Luxford Dan-Anderson , Riordan Benjamin , Kuntsche Emmanuel
Published: January 2024

Background

Music is an integral part of our lives and is often played in public places like restaurants. People exposed to music that contained alcohol-related lyrics in a bar scenario consumed significantly more alcohol than those exposed to music with less alcohol-related lyrics. Existing methods to quantify alcohol exposure in song lyrics have used manual annotation that is burdensome and time intensive. In this paper, we aim to build a deep learning algorithm (LYDIA) that can automatically detect and identify alcohol exposure and its context in song lyrics.

Methods

We identified 673 potentially alcohol-related words including brand names, urban slang, and beverage names. We collected all the lyrics from the Billboard’s top-100 songs from 1959 to 2020 (N = 6110). We developed an annotation tool to annotate both the alcohol-relation of the word (alcohol, non-alcohol, or unsure) and the context (positive, negative, or neutral) of the word in the song lyrics.

Results

LYDIA achieved an accuracy of 86.6% in identifying the alcohol-relation of the word, and 72.9% in identifying its context. LYDIA can distinguish with an accuracy of 97.24% between the words that have positive and negative relation to alcohol; and with an accuracy of 98.37% between the positive and negative context.

Conclusion

LYDIA can automatically identify alcohol exposure and its context in song lyrics, which will allow for the swift analysis of future lyrics and can be used to help raise awareness about the amount of alcohol in music.

Highlights Developed a deep learning algorithm (LYDIA) to identify alcohol words in songs. LYDIA achieved an accuracy of 86.6% in identifying alcohol-relation of the words. LYDIA’s accuracy in identifying positive, negative, or neutral context was 72.9%. LYDIA can automatically provide evidence of alcohol in millions of songs. This can raise awareness of harms of listening to songs with alcohol words.
Meeting-makers make meaning: alcoholics anonymous participation and personal meaningfulness
Authors: Thompson Benjamin L , Maleki Nasim , Kelly John F , Oscar-Berman Marlene
Published: January 2024

Aims

The central aim of this study was to determine whether intentional, voluntary alcoholics anonymous (AA) participation showed any independent association with affect, over and above that which has been observed in association with other recovery-related behaviors, such as abstinence, among individuals with a history of alcohol use disorder. Additionally, we sought to determine the nature of the affective changes associated with specific dimensions of AA participation (i.e. meeting  attendance, fellowship  involvement, 12-step  work).

Methods

Thirty abstinent alcohol use disorder individuals were recruited and evaluated. Multivariate linear regressions were used to examine associations between dimensions of AA participation, measured using the Multidimensional Mutual-Help Assessment Scale and standardized measures of affective experiences, including the Profile of Mood States, Subjective Happiness Scale, and the Twelve Promises Scale.

Results and Conclusions

Increase in AA participation was associated with higher positive affective experiences. These associations were observed independently with AA meeting  attendance and fellowship  involvement, but not 12-step work. This study’s findings suggest that greater AA meeting  attendance and fellowship  involvement are correlated with enhancements in the meta-emotional experience of personal meaningfulness. This study extends evidence on AA-related changes by considering affective improvements as a primary clinical outcome, thereby laying the foundation for subsequent, more comprehensive research into the relationship between dimensions of AA participation and recovery-related affective changes.
Near extinct Argyreia versicolor and rare Argyreia mekongensis are dependent on carpenter bee pollinators
Authors: Jirabanjongjit Awapa , Traiperm Paweena , Rattanamanee Chakkrapong , Stewart Alyssa B
Published: January 2024

Argyreia versicolor and Argyreia mekongensis are extremely rare plant species. The former had not been seen for nearly 100 years until two individuals were found in Thailand in 2018, and only a handful of populations are known for the latter. The aims of this study were to examine the breeding systems of A. versicolor and A. mekongensis using pollination experiments and to determine their potential pollinators via floral observations. Our controlled pollination experiments uncovered the self-incompatibility of both species. Pollinator censuses indicated that females of two carpenter bee species, Xylocopa aestuans and Xylocopa latipes, were the predominant floral visitors for both Argyreia species. Our observations confirmed a harmonious match between the floral shape of both Argyreia species and the body sizes of these pollinators, ensuring effective pollen transfer and validating their role as putative pollinators. In line with the high frequency of pollinator visits observed, our controlled pollination experiments found no evidence of pollen limitation under field conditions. The findings of this study hold significance for the conservation of these endangered species, yet the situation is dire for A. versicolor, with one of the two individuals under study recently lost. Hence, it is crucial to intensify monitoring efforts for the species, aiming to identify additional individuals for potential inclusion in an ex-situ conservation program. Simultaneously, safeguarding the habitat of these plant species and their pollinators will be critical.
Element recycling in arsoles
Authors: Takahara Chisa , Iwasaki Suzuka , Miyake Yusuke , Yumura Takashi , Imoto Hiroaki , Naka Kensuke
Published: January 2024

The incorporation of heteroatoms serves as a potent tool for the development of advanced materials, and arsenic (As) has recently become increasingly popular in the field of conjugated molecules. However, the potential toxicity of As-containing materials upon disposal remains a concern. In this study, we propose a chemical recycling approach for the As in arsoles. The oxidative ring-opening reaction of arsoles proceeds efficiently under ultraviolet irradiation, leading to the production of phenylarsonic acid, a precursor of arsoles.
Differential effects of specific emotions on spatial decision-making: evidence from cross-frequency functionally independent brain networks
Authors: Zhao Yanyan , Wang Danli , Wang Xinyuan , Jin Qiao , Gao Xuange
Published: January 2024

Emotions significantly shape the way humans make decisions. However, the underlying neural mechanisms of this influence remain elusive. In this study, we designed an experiment to investigate how emotions (specifically happiness, fear, and sadness) impact spatial decision-making, utilizing EEG data. To address the inherent limitations of sensor-level investigations previously conducted, we employed standard low-resolution brain electromagnetic tomography and functional independent component analysis to analyze the EEG data at the cortical source level. Our findings showed that across various spectral-spatial networks, positive emotion activated the decision-making network in the left middle temporal gyrus and inferior temporal gyrus, in contrast to negative emotions. We also identified the common spectral-spatial networks and observed significant differences in network strength across emotions. These insights further revealed the important role of the gamma-band prefrontal network. Our research provides a basis for deciphering the roles of brain networks in the impact of emotions on decision-making.
Neural correlates tracking different aspects of the emerging representation of novel visual categories
Authors: Jellinek Sára , Fiser József
Published: January 2024

Current studies investigating electroencephalogram correlates associated with categorization of sensory stimuli (P300 event-related potential, alpha event-related desynchronization, theta event-related synchronization) typically use an oddball paradigm with few, familiar, highly distinct stimuli providing limited insight about the aspects of categorization (e.g. difficulty, membership, uncertainty) that the correlates are linked to. Using a more complex task, we investigated whether such more specific links could be established between correlates and learning and how these links change during the emergence of new categories. In our study, participants learned to categorize novel stimuli varying continuously on multiple integral feature dimensions, while electroencephalogram was recorded from the beginning of the learning process. While there was no significant P300 event-related potential modulation, both alpha event-related desynchronization and theta event-related synchronization followed a characteristic trajectory in proportion with the gradual acquisition of the two categories. Moreover, the two correlates were modulated by different aspects of categorization, alpha event-related desynchronization by the difficulty of the task, whereas the magnitude of theta -related synchronization by the identity and possibly the strength of category membership. Thus, neural signals commonly related to categorization are appropriate for tracking both the dynamic emergence of internal representation of categories, and different meaningful aspects of the categorization process.
Cognitive stimulation as a mechanism linking socioeconomic status and neural function supporting working memory: a longitudinal fMRI study
Authors: Lurie Lucy A , Rosen Maya L , Weissman David G , Machlin Laura , Lengua Lilliana , Sheridan Margaret A , McLaughlin Katie A
Published: January 2024

Childhood experiences of low socioeconomic status are associated with alterations in neural function in the frontoparietal network and ventral visual stream, which may drive differences in working memory. However, the specific features of low socioeconomic status environments that contribute to these disparities remain poorly understood. Here, we examined experiences of cognitive deprivation (i.e. decreased variety and complexity of experience), as opposed to experiences of threat (i.e. violence exposure), as a potential mechanism through which family income contributes to alterations in neural activation during working memory. As part of a longitudinal study, 148 youth between aged 10 and 13 years completed a visuospatial working memory fMRI task. Early childhood low income, chronicity of low income in early childhood, and current income-to-needs were associated with task-related activation in the ventral visual stream and frontoparietal network. The association of family income with decreased activation in the lateral occipital cortex and intraparietal sulcus during working memory was mediated by experiences of cognitive deprivation. Surprisingly, however, family income and deprivation were not significantly related to working memory performance, and only deprivation was associated with academic achievement in this sample. Taken together, these findings suggest that early life low income and associated cognitive deprivation are important factors in neural function supporting working memory.