bluuebunny/crossref_metadata_2025 huggingface dataset:
A Study of The Sound Absorption Properties of Layered Composites on Chicken Feather Fibers
Authors: Artayani Meldawati , Kusno Asniawaty , Mulyadi Rosady , Jamala Nurul
Published: March 2024

Biocomposites made from animal fibers have now been developed into alternative materials for room acoustics. This study presents a material study on the sound absorption ability of chicken feather fiber composites made experimentally by layered methods of various matrix compositions. Testing the absorbability of material sound using an Impedance tube or Kundt tube method (ISO 10543-2), at a frequency of 200 Hz to 1600 Hz (Medium Sounds). The results revealed that chicken feather fiber composites (CFFC) performed well in sound absorption when using a matrix made from starch. Chicken feather fiber composites (CFFC) perform well in the medium to high-frequency range and can be recommended as indoor sound-absorbing materials.
Monitoring of cooling tower water pumps using Arduino data acquisition device
Authors: Lee Zhiyung Joshua , Anas Md Rezali Khairil , As’arry Azizan
Published: March 2024

Investing equipment to monitor the condition of assets through vibration can be expensive. Recent development of alternative microcontrollers has enabled researchers to study its potential to replace expensive equipment for monitoring purposes. This study aimed to investigate the potential of alternative microcontrollers to be used as devices to monitor the condition of water pumps. An internet of things (IoT) device was developed that can measure vibration and be applied to monitor water pumps. The vibration data was obtained when the pumps were operated and sent to the condition-based monitoring system (CBMS) database via Wi-Fi network. The vibration data was observed, and current and future condition was identified through vibration analysis.
Z-Freq Hybrid: Signal Analysis Based Car Air Conditioning Compressor Monitoring Technique Using Accelerometer and Piezo-Film Sensor
Authors: Othman MNB. , Nuawi M.Z. , Ngatiman N.A. , Yusri M.Y.
Published: March 2024

The efficiency and performance of car air conditioning systems rely heavily on adequately functioning the compressor and its associated components. There are many ways to detect an unfunctioning compressor and one of them is through vibration. Disfunctioning compressors could lead to discomfort, fatigue, stress and fogging windows, especially in long-distance driving. Thus, researchers focus on detecting the nonfunctioning car air conditioning compressor early. This paper introduced a new enhanced statistical method, namely Z-freq Hybrid. Z-freq Hybrid was based on a Z-notch frequency domain filter with a combination input of two different types of sensors introduced to detect functioning compressors. Data were recorded at various compressor speeds using an accelerometer and piezo film sensor with Signal Express 2015 software. The acceleration (m/s2) and voltage (mV) data were analyzed to find the combination degree of scattering data in a Z-freq Hybrid chart. The analyzed data show that the Z-freq Hybrid coefficient increases as the compressor’s speed increases. Then, the value dropped significantly when the compressor was dysfunctional. In conclusion, a Z-freq Hybrid can be employed to detect abnormalities and irregular vibration patterns, which may indicate the impending failure of a compressor.
Research on intelligent control system of permanent magnet motor for high-speed flywheel energy storage system based on deep learning
Authors: Kang Changfeng , Li Keyan
Published: March 2024

With the continuous development of society, more and more people pay attention to energy issues, and the realization of energy storage has become a hot research direction today. Despite advancements, the control system of the high-speed flywheel energy storage system’s permanent magnet motor still encounters issues in effectively regulating the magnetic suspension bearing and motor speed. In addressing this issue, a technical solution involves the implementation of an intelligent control system for the high-speed flywheel energy storage system’s permanent magnet motor, utilizing deep learning principles. This innovative approach employs deep neural networks to model, optimize, and regulate the flywheel energy storage system. The essence of flywheel energy storage lies in the conversion of electrical energy into mechanical energy, followed by its reconversion into electrical energy during output. It has the advantages of high energy density, high power density, long cycle life, fast charging and discharging, maintenance-free and environmental protection. A permanent magnet motor is a motor that uses permanent magnets to generate a magnetic field. It has the characteristics of high efficiency, high power density, and low rotor loss. It remains the most widely utilized motor in flywheel energy storage systems. An intelligent control system is characterized by its use of artificial intelligence technology to adapt, self-learn, and self-organize complex systems. This system is distinguished by its robust nonlinear processing capabilities and resilience to faults. The high-speed flywheel energy storage system permanent magnet motor intelligent control system based on deep learning can improve the performance, efficiency and reliability of the flywheel energy storage system, reduce costs and risks, and is suitable for electric vehicles, rail transit, power grid frequency regulation and other fields. In this paper, the convolutional neural network and PSO algorithm are used to obtain the PSNN neural network structure to predict the speed of the motor, so as to achieve its control. And the reliability of the structure is verified by experiments.
Research on mine ventilation network solution and collaborative control technology
Authors: Chang Weifeng , He Min
Published: March 2024

With the development of intelligent ventilation system in domestic coal mines, the demand for ventilation network solving software is becoming more and more intense. Aiming at the problem that the traditional ventilation network solution algorithm is difficult to meet the increasingly complex ventilation system solution needs of domestic mines, and the lack of functions of the collaborative control of ventilation equipment and facilities, this paper uses theoretical analysis combined with mine reality to study the relevant theories and algorithms in the field of ventilation network solution and collaborative control at home and abroad, and optimizes the network solution and collaborative control related algorithms such as iterative calculation of ventilation network, identification and stability analysis of angle-linked wind network, natural wind pressure calculation, local fan collaborative control, and collaborative control of damper and wind window. Provide theoretical guidance for future network solution software development.
Design and Simulation of Hydraulic Integrated Valve based on SLM Technology
Authors: Liang Keshan , Tang Li , Zhang Qingbiao , Cao Yujun
Published: March 2024

Intelligent robots put forward the need for miniaturization and integration of hydraulic systems. Based on SLM technology, this paper designs a hydraulic integrated valve, integrates flow channels, adapters and other facilities on the valve body, replaces the original linear movement scheme with a rotating spool scheme, studies parameters such as runner diameter and minimum wall thickness, and simulates and analyzes the flow performance of liquid when the main control runner and a single valve work. The results show that the integrated valve has the advantages of light weight, small size and good performance.
Effects of Pore Distribution on Mechanical Properties of Selective Laser Melted Inconel-718
Authors: Gao Kairan , Liu Yue
Published: March 2024

In recent years, Selective Laser Melting (SLM) technology has made significant advancements, offering high precision and near-net shaping capabilities that are widely applicable in aerospace, mechanical, and electrical industries. Inconel-718, known for its exceptional high-temperature corrosion resistance, fatigue endurance, and wear resistance, has found extensive use in aerospace applications such as gas turbine disks, rocket engines, and spacecraft components. However, the presence of porous defects in SLM-manufactured metal parts is inevitable, and these pores significantly affect the mechanical properties of the materials. While contemporary studies have focused on the influence of individual or a limited number of pores, the impact of pore distribution has been largely overlooked. This oversight leads to reduced prediction accuracy and hampers the practical implementation of SLM technology. Therefore, this paper specifically investigates the impact of pore distribution on the performance of SLM-manufactured metal materials, using Inconel-718 as an example. The study establishes simulation experiment models to explore diverse pore distribution patterns, including spatial position distribution models and spatial quantity distribution models. The Finite Element Method (FEM) model utilizes the Johnson-Cook constitutive model, and the pores are equivalently modelled as two-dimensional plane ellipses. Uniaxial tension simulations are performed to analyze the mechanical behavior of the materials. The results demonstrate that the mechanical properties of SLM-fabricated Inconel-718 are significantly influenced by the spatial position distribution, spatial quantity distribution, and spatial orientation distribution of the pores. Under different spatial position distributions, materials with more pores parallel to the stretching direction exhibit poorer mechanical performance due to earlier and more significant stress concentration. Under different spatial quantity distributions, materials with a higher pore density and smaller pore spacing show worse mechanical performance due to earlier and more severe stress concentration. Under different spatial orientation distributions, materials with a larger angle between the pore’s major axis and the stretching direction exhibit worse mechanical performance due to enhanced stress and earlier and more severe stress concentration. Overall, this study highlights the importance of considering pore distribution in SLM-manufactured metal materials, providing insights into the impact of spatial position, quantity, and orientation distributions on the mechanical properties of Inconel-718.
Research on the influence of heat release from cement hydration on the mechanical properties of casing
Authors: Li Xu , Tian Ming , Shen Biao , Yang Chuan , Huang Qian , Koxmak Sayyara
Published: March 2024

In order to study the influence of cement hydration heat release on the mechanical properties of casing, this paper calculates the wellbore temperature and pressure field based on the mathematical model of steady-state heat conduction of casing-cement ring-formation rock, establishes a mathematical model for the mechanical evaluation of cement hydration heat release and casing interaction, and performs finite element calculation and experimental simulation of the effect of cement hydration heat release on casing loss, and the results show that the results show: Along the axial direction of the wellbore, the maximum stress on the entire cement ring occurs in the lower position of the cement ring, and the maximum deformation on the casing occurs in the middle position. The axial stress variation range of the middle part of the casing is 50MPa, and the strain is 0.12%; The axial stress variation range of the outer ring is 235MPa, and the strain is 0.09%; The circumferential stress of the middle part varies from 500MPa to 0.255%. It is found that the stress and strain in the middle part of cement sheath are large, and yield is prone to occur. Under the action of cement hydration heat release, the long-axis elliptical deformation of (7.15∼31.8) mm occurs in the casing, that is, a large ovality is produced, which weakens the collapse strength of the casing. Two repeated tests showed that under the cement hydration heat release condition at the casing loss position, the temperature change of 60°C caused the increase of axial force of casing column and the increase of annular air pressure, which caused the non-uniform deformation of casing under the composite load of external extrusion and compression axial force.
Numerical Simulation of wind load on Inflated Membrane Structure
Authors: Li Weiqun , Shi Xiaojun , Xu Yangfan , Zhang Changrong , Li Yang , Yang Wenchao , Zheng Yitong , Peng Jianjun
Published: March 2024

The fluid-structure interaction (FSI) program were used to simulate the condition that inflated membrane structure transport process in incoming flow. A comparison between the results from numerical simulation and from the ground simulation test was used to validate the computational method. Due to the analysis of flow field and membrane structure’s deformation, the law of force variation of inflated membrane structure during FSI was discussed, and the causes of deformation instability in FSI problems were preliminary discussed. Possible ways to reduce the sensitivity of envelope deformation caused by constraint position were explored, and the effect of this improved method on the surface stress of the envelope was investigated.
Tunnel environment noise suppression by SVD-DSW method
Authors: Yue Yonggao , Zeng Jing , Wu Zhiyuan , Zhang Shang , Deng Lijuan
Published: March 2024

There is strong random noise in seismic records of tunnel seismic advance detection, which makes it difficult to obtain the underground lithology information in front of tunnel face accurately. Aiming at the problem that random noise is difficult to suppress in tunnel environment, a method of SVD-DSW is proposed in our research. Different from the directional seismic wave method, the proposed method is to stack the target signal after leveling. Then, the target signal with stronger coherence is extracted by singular value decomposition and target signal reconstruction, and finally reverse correct the extracted coherent signal to get the target signal. Simulation results and field data analysis show that the SVD-ICA theoretical approach is feasible for improving the SNR of the target signal in three-component seismogram, which is of great significance to increase detection range and resolution of tunnel seismic advance prediction.
The study of thermoelectric energy and mechanical properties by modifying carbon fiber fabric
Authors: Chen Qianyu
Published: March 2024

With the acceleration of global industrialisation, the scarcity and depletion of the world’s energy resources has become a problem that no country can ignore. It is a serious obstacle to the long-term stable development of society. Exploring and developing new energy sources has become the trend of global energy development. In this paper, hydrogen peroxide is used to treat carbon fibre materials. In addition, the thermoelectric reinforcing agent Bi2Te3 is doped into carbon fibre film materials by electrochemical deposition for the purpose of measuring the Seebeck coefficient and electrical conductivity. Technical abbreviations will be explained at the first use. By investigating how changes in the surface structure of carbon fibre fabrics and the addition of bismuth telluride affect their thermoelectric properties, this study establishes a framework for improving the thermoelectric capabilities of carbon fibre fabrics. Experimental results show that carbon fiber fabric treated with H2O2 have excellent thermoelectric and mechanical properties.
Vector Control Simulation of Permanent Magnet Synchronous Linear Motor
Authors: Dai Chunming , Wang Mian , Zhao Fenggang
Published: March 2024

Compared with rotating motor, linear motor can “directly” obtain linear motion, which eliminates the intermediate transformation link and can directly drive the equipment requiring linear motion. It is applicable to rotating motor mature control strategy can be better for linear motor control research. Its development and application of linear motor has great significance. In this thesis, starting from the weakening characteristics of permanent magnet synchronous linear motor, through the MATLAB simulation and comparative analysis of different control signals (SPWM and SVPWM) of vector control strategy, the conclusion that vector control strategy can effectively control ideal linear motor is obtained, which lays a foundation for further improving the control strategy to control non-ideal linear motor.
Study on the Selection of Power Cable Rejuvenation Fluids Based on Relative Diffusion Coefficients
Authors: Tao Xiantao , Deng Kai , Zhang Fei , Ren Ang , Su Fei , Liu Xiao , Gong Hui , Qin Zihang , Chu Fanwu
Published: March 2024

The present work presents and formulates a method for calculating the relative diffusion coefficient of rejuvenation fluid in injection cable rejuvenation technology, and the permeability characteristics of rejuvenation fluid in polyethylene insulation materials are calculated and compared. The main components of the rejuvenation fluid such as (Phenylmethyl-dimethoxysilane) PMDMS, (Diphenyldimethoxysilane) DPDMS and (Trimethylmethoxysilane) TMMS, and the catalysts such as (Tetra-isopropyl titanate) TIPT and (Tetra-isobutyl titanate) TIBT were analysed in depth. The article uses theoretical calculation method, combined with Helmroth and Limm-Hollifield models, to calculate the diffusion coefficients and relative diffusion coefficients of these compounds in polyethylene. Through comparative analysis of theoretical calculations, the optimal parameters for evaluating the permeability characteristics of rejuvenation fluids were determined. The research results show that TMMS has the best permeability characteristics in polyethylene, followed by PMDMS and DPDMS. In the catalyst, TIPT has better permeability characteristics than TIBT. And when selecting the composite formula for cable rejuvenation fluid, it is more convenient to use the relative diffusion coefficient as an index of diffusion characteristics. This research provides important theoretical basis and practical guidance for the formulation selection of cable rejuvenation fluids.
Comparative Study on the Ampacity of 500 kV Single-Core and Three-Core Submarine Cable
Authors: Tao Xiantao , Liu Hao , Wang Lei , Zhai Haoqi , Ni Yulin , Hou Junping , Zhang Shize , Luo Zhengjun , Chen Nan , Ye Gang
Published: March 2024

Submarine cable is an important equipment for data communication and power transmission in power systems, which has a complex laying environment. According to its structure, submarine cables can be divided into two types, single-core cables and three-core cables. In practical engineering, cable selection is crucial to ensure the safe and stable operation of the cable and reduce the cost. The present work compares the ampacity of 500 kV single-core cable and three-core cable with the same conductor cross-section area under certain laying conditions. And the temperature rise situation of the three-core cable and the single-core cable is compared under the application of the same current. The results reveals that the ampacity of the three-core cable is less than one-core cable under certain laying situations. And the maximum ampacity reduction of the three-core cable is 28.96%. Furthermore, the highest temperature rise point of the three-core cable is the air section of the J-tube, and the maximum temperature reaches 130.07°C.
Analysis of Calculation of Artificial Neutral Point Resistance for Open-circuit Testing
Authors: Fang Xiang
Published: March 2024

This article focuses on the artificial neutral point device with ZN connection (ZN type connection refers to the way that the primary winding adopts a zigzag connection and the neutral point is led out). In the process of breaking test, the arc energy is an important criterion. For three-phase four-wire transformers, the test loop can be built by connecting the N-pole with a pure resistance. However, for three-phase transformers, the loop needs to be built through the artificial neutral point. By analyzing the calculation and actual test data, the calculation method for the artificial neutral point resistance used in the experiment is clarified. It is confirmed that the resistance of the artificial neutral point will not change with the change of input voltage, making the calculation of expected fault current more accurate in daily use.
Research on Steel Cage Hoisting Equipment in Electric Power Construction
Authors: Qiu Haoci , Wu Fenqian , Chen Weiyu , Liu Ruijun , Wang Chao
Published: March 2024

In the process of electric power construction, the form of bored pile bottom foundation is widely used. However, if the method of segmental lifting of steel cage is adopted, it will bring a series of problems. First of all, the combination welding of the two main bars will become very difficult, and its welding strength is difficult to be guaranteed. Second, the welding process takes too long, which may lead to an increased risk of hole collapse. These problems will not only affect the efficiency and quality of power construction, but also threaten the safety of construction personnel. Therefore, in order to solve these problems, it is very important to improve the safety and reliability of the overall lifting process of the steel cage. This paper will introduce the research on the whole lifting of steel cage in power construction in detail, in order to provide useful reference for related projects and help the steady development of national power industry.
Multi-level Storage Characteristics of MoSe2 Resistive Random Access Memory
Authors: Dong Pengfan , Jian Jiaying , feng Hao , Geng Mingtao , Dang Bo , Gao Qian , Xu Junfeng , Zhu Man , Liu Xing
Published: March 2024

Resistive Random Access Memory (RRAM) is a type of non-volatile memory (NVM) device that stores information by switching between high and low resistance values. It has attracted widespread attention due to its promising potential for miniaturization. In this study, molybdenum diselenide (MoSe2) was successfully synthesized via the hydrothermal method, and the RRAM was fabricated with MoSe2 as the resistance change layer. Furthermore, the MoSe2 samples were characterized by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The results demonstrate that the prepared MoSe2 forms flower-like nanospheres assembled by nanosheets, with a particle size is about 200 nm. In addition, RRAM has a low operating voltage (< 1V), a high OFF/ON-state resistance ratio (> 102), a good endurance (103 cycles), and its resistance switching mechanism is dominated by the trap-controlled space charge limited current (SCLC) mechanism in the high resistance state (HRS) and by the ohmic mechanism in the low resistance state (LRS). Furthermore, multi-level storage is achieved by adjusting the compliance currents (Icc) and the stop voltage (Vstop).
Research on Black Start Control technology of Energy Storage Power Station Based on VSG All Vanadium Flow Battery
Authors: Xie Bing , Xu Baofeng , Liu Zhili , Sun Guangyu , Yang Bin , Wang Xiaodong
Published: March 2024

To reduce the losses caused by large-scale power outages in the power system, a stable control technology for the black start process of a 100 megawatt all vanadium flow battery energy storage power station is proposed. Firstly, a model is constructed for the liquid flow battery energy storage power station, and in order to improve the system capacity, four unit level power stations are processed in parallel. Secondly, based on the energy storage of all vanadium flow batteries, the traditional voltage and frequency stability control technology has been improved to address the characteristics of low inertia and damping in power electronic interfaces. The improved VSG strategy has been applied to the overall control of a hundred megawatt level flow battery energy storage power station, solving the voltage and frequency instability problems caused by load shocks and fluctuations. Finally, stable control of multiple parallel machines during the self starting process of the liquid flow battery energy storage power station was achieved, avoiding the occurrence of multiple machine circulation and uneven power distribution problems during the self starting process.
Performance Simulation Analysis of Synchronous Hydraulic System for Variable-Diameter Threshing Drum
Authors: San Yunlong , Yang Huimin , Chen Yifei , Wang Xuenong , Niu Changhe , Liu Yanbin
Published: March 2024

To meet the requirement that the traditional combine harvester can adjust the threshing gap in real time according to different working conditions, a hydraulic driven variable-diameter threshing drum and a synchronous hydraulic system were developed in the early stage. However, the performance of synchronous hydraulic system has not been studied in detail. Therefore, AMESim software was used to simulate and analyze the synchronous hydraulic system to verify its feasibility in this study. The results showed that the synchronization error of synchronous hydraulic system was less than 0.02 mm. When the hydraulic system was self-locking, the position fluctuation of the piston rod of hydraulic cylinder was less than 0.06 mm. When the hydraulic cylinder did not work, the logic valve effectively ensured that the hydraulic oil could directly return to the oil tank, resulting in the minimum energy loss of the system. The flow control valve could regulate the flow rate of the hydraulic system, causing the adjusting speed of the drum diameter can be adjusted. The hydraulic system pressure was determined to be 8 Mpa.
Failure Analysis of Header Flange Cracking in Propane Dehydrogenation Unit
Authors: Lu Xianjin , Yu Ting , Chen Yanbin , Chen Mao , An Zhicong
Published: March 2024

The boiler fault of propane dehydrogenation unit is investigated by macroscopic inspections, mechanical properties testing, chemical composition analysis, metallographic microstructure, X-ray diffraction (XRD), Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS). The experiments confirm the reason for cracks occurrence of SA182-F347H boiler that the stress corrosion cracking occurs. The sulfur injected into the device reacts with the flange metal to produce sulfide corrosion products. The improper control of flange manufacturing process and the operating temperature in the sensitized range lead to the sensitization of flange materials and reduce the corrosion resistance. During the equipment shutdown, the sulfide corrosion products on the surface of the flange reacted with air and water to form polysulfuric acid, and causing stress corrosion cracking and leakage of the sensitized F347H stainless steel flange.
RFSoC-based front-end electronics for pulse detection
Authors: Axani S.N. , Futagi S. , Garcia M. , Grant C. , Hosokawa K. , Ieki S. , Inoue K. , Ishidoshiro K. , Kawada N. , Matsumoto Y. , Nakahata T. , Nakamura K. , Shouji R. , Song H. , Winslow L.A.
Published: March 2024

Radiation measurement relies on pulse detection, which can
be performed using various configurations of high-speed
analog-to-digital converters (ADCs) and field-programmable gate
arrays (FPGAs). For optimal power consumption, design simplicity,
system flexibility, and the availability of DSP slices, we consider
the Radio Frequency System-on-Chip (RFSoC) to be a more suitable
option than traditional setups. To this end, we have developed
custom RFSoC-based electronics and verified its feasibility. The
ADCs on RFSoC exhibit a flat frequency response of 1–125 MHz. The
root-mean-square (RMS) noise level is 2.1 ADC without any digital
signal processing. The digital signal processing improves the RMS
noise level to 0.8 ADC (input equivalent
40 μVrms). Baseline correction via digital
signal processing can effectively prevent photomultiplier overshoot
after a large pulse. Crosstalk between all channels is less than
-55 dB. The measured data transfer speed can support up to
32 kHz trigger rates (corresponding to 750 Mbps). Overall, our
RFSoC-based electronics are highly suitable for pulse detection, and
after some modifications, they will be employed in the Kamioka
Liquid Scintillator Anti-Neutrino Detector (KamLAND).
Measuring cell proliferation in bioprinting research
Authors: Schweinitzer Sophie , Kadousaraei Masoumeh Jahani , Aydin Mehmet Serhat , Mustafa Kamal , Rashad Ahmad
Published: March 2024

Tissue-like constructs, intended for application in tissue engineering and regenerative medicine, can be produced by three-dimensional (3D) bioprinting of cells in hydrogels. It is essential that the viability and proliferation of the encapsulated cells can be reliably determined. Methods currently used to evaluate cell proliferation, such as quantification of DNA and measurement of metabolic activity, have been developed for application in 2D cultures and might not be suitable for bioinks. In this study, human fibroblasts were either cast or printed in gelatin methacryloyl (GelMA) or sodium alginate hydrogels and cell proliferation was assessed by AlamarBlue, PicoGreen and visual cell counts. Comparison of data extrapolated from standard curves generated from 2D cultures and 3D hydrogels showed potential inaccuracies. Moreover, there were pronounced discrepancies in cell numbers obtained from these assays; the different bioinks strongly influenced the outcomes. Overall, the results indicate that more than one method should be applied for better assessment of cell proliferation in bioinks.
Adipose tissue reconstruction facilitated with low immunogenicity decellularized adipose tissue scaffolds
Authors: Yang Xun , Jin Lijuan , Xu Miaomiao , Liu Xiao , Tan Zhikai , Liu Lijun
Published: March 2024

There is currently an urgent need to develop engineered scaffolds to support new adipose tissue formation and facilitate long-term maintenance of function and defect repair to further generate prospective bioactive filler materials capable of fulfilling surgical needs. Herein, adipose regeneration methods were optimized and decellularized adipose tissue (DAT) scaffolds with good biocompatibility were fabricated. Adipose-like tissues were reconstructed using the DAT and 3T3-L1 preadipocytes, which have certain differentiation potential, and the regenerative effects of the engineered adipose tissues in vitro and in vivo were explored. The method improved the efficiency of adipose removal from tissues, and significantly shortened the time for degreasing. Thus, the DAT not only provided a suitable space for cell growth but also promoted the proliferation, migration, and differentiation of preadipocytes within it. Following implantation of the constructed adipose tissues in vivo, the DAT showed gradual degradation and integration with surrounding tissues, accompanied by the generation of new adipose tissue analogs. Overall, the combination of adipose-derived extracellular matrix and preadipocytes for adipose tissue reconstruction will be of benefit in the artificial construction of biomimetic implant structures for adipose tissue reconstruction, providing a practical guideline for the initial integration of adipose tissue engineering into clinical medicine.
Large multi-decade beaver ponding changes in the subarctic Hudson Bay Lowlands, Canada observed using satellite remote sensing
Authors: Fraser Robert H , Olthof Ian , Berezanski Dean
Published: March 2024

Beavers strongly impact hydrology and ecosystems through their widespread dam building that creates ponds and wetlands. Monitoring the relative abundance of beavers and their waterbodies is needed to assess these effects and factors influencing population levels. However, the ability to do this over vast, remote regions is limited with conventional aerial or field-based surveying. To address this challenge, we developed a satellite remote sensing method to track beaver ponding changes over multiple decades and applied it to a 5127 km2 region of the coastal Hudson Bay Lowlands in Manitoba, Canada. Annual, sub-pixel surface water mapping using 30 m resolution Landsat satellite data, combined with a spatial database of beaver dams, permitted the mapping of 37 year (1985–2021) beaver ponding dynamics. We identified 1714 beaver dams and 1085 beaver pond complexes covering 31 km2, indicating that beavers have an important influence on stream hydrology in this high subarctic landscape. The total area of ponding decreased by 53% from 1986–1989 and by 80% by 1995, and then gradually recovered to initial levels by 2015. The early, steep drop in beaver ponding corresponded to a 13% decline in regional surface water area, while a similar wetness decline during 2015–2018 resulted in little change in beaver ponding. We suggest that strong beaver ponding dynamics were likely caused by the interaction between streamflow levels and beaver populations living near their northern range limit and cold tolerance. The pond mapping method can be applied to other regions if the long-term distribution of beaver dams is known, and ponds are large enough to be identified using a Landsat sub-pixel approach.
Synergistic effects of cold rolling and age hardening on the hardness and tensile characteristics of AA6061 hybrid composites
Authors: Sadanand Ramakrishna Vikas , Sharma Sathyashankara , Prabhu P R
Published: March 2024

The present study involves the fabrication of aluminium alloy 6061 matrix hybrid composites with varying weight fractions of silica sand and copper particles by employing the conventional stir casting method. The combined influence of age hardening (AH) and low temperature thermomechanical treatment (LTMT) on the hardness and tensile properties of AA6061 hybrid composites was investigated. The uniform dispersion of the particles in the matrix was confirmed by microstructure analysis and the improvement of Brinell hardness values. The composites exhibited higher tensile strength and hardness than the base alloy. Both AH and LTMT enhanced the properties of the hybrid composites and a comparison between them revealed the best results for LTMT hybrid composites. The LTMT hybrid composite with 3 wt% silica sand and 3 wt% copper (3S3C) subjected to 12% rolling deformation and aged at 100 °C had the highest hardness and tensile strength of 144.26 HV and 290 MPa respectively. The hardness and tensile strength of AA6061-3S3C hybrid composite subjected to LTMT in peak aged condition showed an improvement of 125 and 97% respectively when compared with those of AA6061 alloy. Fracture surface analysis of the thermomechanical treated composites in peak aged condition showed a mixed mode of failure dominant with the ductile fracture.
Generation of stable Gaussian cluster states in optomechanical systems with multifrequency drives
Authors: Yazdi Nahid , Zippilli Stefano , Vitali David
Published: March 2024

We show how to dissipatively stabilize the quantum state of N mechanical resonators in an optomechanical system, where the resonators interact by radiation pressure with N optical modes, which are driven by properly selected multifrequency drives. We analyze the performance of this approach for the stationary preparation of Gaussian cluster states.
Open code and data are not enough: understandability as design goal for energy system models
Authors: Pfenninger Stefan
Published: March 2024

Energy system models do not represent natural processes but are assumption-laden representations of complex engineered systems, making validation practically impossible. Post-normal science argues that in such cases, it is important to communicate embedded values and uncertainties, rather than establishing whether a model is ‘true’ or ‘correct’. Here, we examine how open energy modelling can achieve this aim by thinking about what ‘a model’ is and how it can be broken up into manageable parts. Collaboration on such building blocks—whether they are primarily code or primarily data—could become a bigger focus area for the energy modelling community. This collaboration may also include harmonisation and intercomparison of building blocks, rather than full models themselves. The aim is understandability, which will make life easier for modellers themselves (by making it easier to develop and apply problem-specific models) as well as for users far away from the modelling process (by making it easier to understand what is qualitatively happening in a model—without putting undue burden on the modellers to document every detail).
Training quantum Boltzmann machines with the β-variational quantum eigensolver
Authors: Huijgen Onno , Coopmans Luuk , Najafi Peyman , Benedetti Marcello , Kappen Hilbert J
Published: March 2024

The quantum Boltzmann machine (QBM) is a generative machine learning model for both classical data and quantum states. Training the QBM consists of minimizing the relative entropy from the model to the target state. This requires QBM expectation values which are computationally intractable for large models in general. It is therefore important to develop heuristic training methods that work well in practice. In this work, we study a heuristic method characterized by a nested loop: the inner loop trains the β-variational quantum eigensolver (β-VQE) by Liu et al (2021 Mach. Learn.: Sci. Technol.
2 025011) to approximate the QBM expectation values; the outer loop trains the QBM to minimize the relative entropy to the target. We show that low-rank representations obtained by β-VQE provide an efficient way to learn low-rank target states, such as classical data and low-temperature quantum tomography. We test the method on both classical and quantum target data with numerical simulations of up to 10 qubits. For the cases considered here, the obtained QBMs can model the target to high fidelity. We implement a trained model on a physical quantum device. The approach offers a valuable route towards variationally training QBMs on near-term quantum devices.
A method for quantifying the generalization capabilities of generative models for solving Ising models
Authors: Ma Qunlong , Ma Zhi , Gao Ming
Published: March 2024

For Ising models with complex energy landscapes, whether the ground state can be found by neural networks depends heavily on the Hamming distance between the training datasets and the ground state. Despite the fact that various recently proposed generative models have shown good performance in solving Ising models, there is no adequate discussion on how to quantify their generalization capabilities. Here we design a Hamming distance regularizer in the framework of a class of generative models, variational autoregressive networks (VANs), to quantify the generalization capabilities of various network architectures combined with VAN. The regularizer can control the size of the overlaps between the ground state and the training datasets generated by networks, which, together with the success rates of finding the ground state, form a quantitative metric to quantify their generalization capabilities. We conduct numerical experiments on several prototypical network architectures combined with VAN, including feed-forward neural networks, recurrent neural networks, and graph neural networks, to quantify their generalization capabilities when solving Ising models. Moreover, considering the fact that the quantification of the generalization capabilities of networks on small-scale problems can be used to predict their relative performance on large-scale problems, our method is of great significance for assisting in the Neural Architecture Search field of searching for the optimal network architectures when solving large-scale Ising models.
The Self: A Very Short Introduction
Authors: Schechtman Marya
Published: March 2024

The Self: A Very Short Introduction uses insights from philosophy, psychology, psychiatry, and popular thought to consider some of the most compelling and puzzling questions about the self, including questions about what kind of object a self is if it is an object at all, what it means to be oneself and why it is important, what kinds of changes the self can and cannot survive, whether a self can be separated from its body, whether more than one self can exist in a single body, and what role engagement with the environment and with other selves plays in constituting and maintaining the self. These investigations yield a complex, multi-dimensional picture of the self as a subject and agent embedded in and interacting with a natural and social world.
Divided and distressed selves
Authors: Schechtman Marya
Published: March 2024

This chapter considers what can be learned by reflection on a handful of psychiatric and neurological cases in which selfhood seems to be compromised. Cases include “split brain” cases (corpus callosotomy), dissociative identity disorder, depersonalization and derealization, the phenomenon of inserted thought as a symptom of schizophrenia, and alienation from one’s body, including the phenomenon of hemisphere neglect. Each of these cases involves a form of fragmentation or compartmentalization that challenges the integrity of the self but does not seem to completely undermine it. Lessons learned include the importance of affect in constituting the unity of self-experience, as well as the role of embodiment and agency in a unified self. These lessons point to a new way of thinking about the basic unity of consciousness that is typically taken to constitute a self, as well as suggesting that this unity may be less complete than we usually take it to be even in typical cases.
Embodied, social selves
Authors: Schechtman Marya
Published: March 2024

This chapter offers sustained examination of some of the major arguments for the claim that selves are inherently dependent on embodiment and/or embeddedness in a social context. Topics include theories that place the origins of selfhood in immunological response or neurological self-modeling, as well as phenomenological arguments that the experiencing subject emerges only in conjunction with consciousness of an experienced environment. Various positions on the social constitution of the self are also explored, including performative views of the self and accounts that see individual selves as abstractions from a broader community, without which they could not exist. The connections between the many different insights into the self generated in this and earlier chapters are discussed, revealing multiple ways in which subjective experience, embodiment, and social context work together to constitute and maintain the self. This suggests the value of a multi-dimensional approach that sees the self as a dynamic subject and agent, living a life filled with experiences, choices, emotions, activities, and relationships.
Achieving Joint Attention and Understanding of Task Responsibilities in Synchronous Hybrid L2 Classroom Group Work
Authors: Jakonen Teppo , Jauni Heidi , Sert Olcay
Published: March 2024

This article addresses the need to better understand interactional asymmetries, challenges, and solutions in implementing synchronous hybrid language teaching. We investigate video-recorded peer interactions in a higher education language teaching context in which a student uses a telepresence robot, a remotely moveable videoconferencing tool, to participate in small-group task work in L2 English together with students who are physically located in the language classroom. Drawing on multimodal conversation analysis, we examine how the geographically dispersed peer group achieves, maintains, and repairs their joint attention on task-relevant learning materials as they are accomplishing a task, and how this kind of referential interactional work enables their co-operation as a group. Based on the analysis, we argue that in synchronous hybrid learning there is a need to reflexively adjust interactional practices to secure an intersubjective understanding of learning tasks and their progressivity. The findings also suggest that sensory and interactional asymmetries should be taken into account when developing and implementing synchronous hybrid learning environments that aim at equality of opportunities regardless of the participation mode.
Utility of a Short-Form Phonemic Fluency Task
Authors: Kaufman Jack R , Fatima Hudaisa , Lacritz Laura H , Cullum C Munro
Published: March 2024

Objective

to establish a proof-of-concept and ascertain the reliability of an abbreviated 30-second (30s) phonemic fluency measure as a cognitive screening tool in older adults.

Methods

in all, 201 English-speaking individuals with normal cognition (NC; n = 119) or cognitive impairment (CI; mild CI or dementia; n = 82) were administered a standard 60s phonemic fluency task (FAS/CFL) with discrete 30s intervals denoted.

Results

for all letters, 30s trial scores significantly predicted 60s scores for the same letter, R2 = .7–.9, F(1, 200) = 850–915, p < .001. As with 60s total scores, 30s cumulative scores (for all three trials) were significantly different between NC and CI groups (p < .001). Receiver operating characteristic analyses showed that 30s total scores distinguished NC and CI groups as effectively (AUC = .675) as 60s total scores (AUC = .658).

Conclusions

these findings support the utility and reliability of a short-form phonemic fluency paradigm, as 30s performance reliably predicted 60s/trial totals and was equally accurate in distinguishing impaired/non-impaired groups.
GPCR-IPL score: multilevel featurization of GPCR–ligand interaction patterns and prediction of ligand functions from selectivity to biased activation
Authors: Kumar Surendra , Teli Mahesh K , Kim Mi-hyun
Published: March 2024

G-protein-coupled receptors (GPCRs) mediate diverse cell signaling cascades after recognizing extracellular ligands. Despite the successful history of known GPCR drugs, a lack of mechanistic insight into GPCR challenges both the deorphanization of some GPCRs and optimization of the structure–activity relationship of their ligands. Notably, replacing a small substituent on a GPCR ligand can significantly alter extracellular GPCR–ligand interaction patterns and motion of transmembrane helices in turn to occur post-binding events of the ligand. In this study, we designed 3D multilevel features to describe the extracellular interaction patterns. Subsequently, these 3D features were utilized to predict the post-binding events that result from conformational dynamics from the extracellular to intracellular areas. To understand the adaptability of GPCR ligands, we collected the conformational information of flexible residues during binding and performed molecular featurization on a broad range of GPCR–ligand complexes. As a result, we developed GPCR–ligand interaction patterns, binding pockets, and ligand features as score (GPCR-IPL score) for predicting the functional selectivity of GPCR ligands (agonism versus antagonism), using the multilevel features of (1) zoomed-out ‘residue level’ (for flexible transmembrane helices of GPCRs), (2) zoomed-in ‘pocket level’ (for sophisticated mode of action) and (3) ‘atom level’ (for the conformational adaptability of GPCR ligands). GPCR-IPL score demonstrated reliable performance, achieving area under the receiver operating characteristic of 0.938 and area under the precision-recall curve of 0.907 (available in gpcr-ipl-score.onrender.com). Furthermore, we used the molecular features to predict the biased activation of downstream signaling (Gi/o, Gq/11, Gs and β-arrestin) as well as the functional selectivity. The resulting models are interpreted and applied to out-of-set validation with three scenarios including the identification of a new MRGPRX antagonist.