bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of matrix thermal properties on laser-induced plasma
Authors: Shan 单 Yuheng 宇恒 , Li 李 An 安 , Zhang 张 Xinyu 新宇 , Yi 易 Wen 文 , Zhang 张 Ying 颖 , Liu 刘 Xiaodong 晓东 , Liu 刘 Ruibin 瑞斌 
Published: July 2024

Abstract
The matrix thermal properties have an important impact on laser-induced plasma, as the thermal effect dominates the interaction between ns-pulsed laser and matter, especially in metals. We used a series of pure metals and aluminum alloys to measure plasma temperature and electron density through laser-induced breakdown spectroscopy, in order to investigate the effect of matrix thermal properties on laser-induced plasma. In pure metals, a significant negative linear correlation was observed between the matrix thermal storage coefficient and plasma temperature, while a weak correlation was observed with electron density. The results indicate that metals with low thermal conductivity or specific heat capacity require less laser energy for thermal diffusion or melting and evaporation, resulting in higher ablation rates and higher plasma temperatures. However, considering ionization energy, thermal effects may be a secondary factor affecting electron density. The experiment of aluminum alloy further confirms the influence of thermal conductivity on plasma temperature and its mechanism explanation.
Delayed-measurement one-way quantum computing on cloud quantum computer
Authors: Yang 杨 Zhi-Peng 智鹏 , Zhang 张 Yu-Ran 煜然 , Li 李 Fu-Li 福利 , Fan 范 Heng 桁 
Published: July 2024

Abstract
One-way quantum computation focuses on initially generating an entangled cluster state followed by a sequence of measurements with classical communication of their individual outcomes. Recently, a delayed-measurement approach has been applied to replace classical communication of individual measurement outcomes. In this work, by considering the delayed-measurement approach, we demonstrate a modified one-way CNOT gate using the on-cloud superconducting quantum computing platform: Quafu. The modified protocol for one-way quantum computing requires only three qubits rather than the four used in the standard protocol. Since this modified cluster state decreases the number of physical qubits required to implement one-way computation, both the scalability and complexity of the computing process are improved. Compared to previous work, this modified one-way CNOT gate is superior to the standard one in both fidelity and resource requirements. We have also numerically compared the behavior of standard and modified methods in large-scale one-way quantum computing. Our results suggest that in a noisy intermediate-scale quantum (NISQ) era, the modified method shows a significant advantage for one-way quantum computation.
Memristors-coupled neuron models with multiple firing patterns and homogeneous and heterogeneous multistability
Authors: Wang 王 Xuan 暄 , Banerjee Santo , Cao 曹 Yinghong 颖鸿 , Mou 牟 Jun 俊 
Published: July 2024

Abstract
Memristors are extensively used to estimate the external electromagnetic stimulation and synapses for neurons. In this paper, two distinct scenarios, i.e., an ideal memristor serves as external electromagnetic stimulation and a locally active memristor serves as a synapse, are formulated to investigate the impact of a memristor on a two-dimensional Hindmarsh–Rose neuron model. Numerical simulations show that the neuronal models in different scenarios have multiple burst firing patterns. The introduction of the memristor makes the neuronal model exhibit complex dynamical behaviors. Finally, the simulation circuit and DSP hardware implementation results validate the physical mechanism, as well as the reliability of the biological neuron model.
Accelerator beam phase space tomography using machine learning to account for variations in beamline components
Authors: Wolski A. , Botelho D. , Dunning D. , Pollard A.E. 
Published: July 2024

Abstract
We describe a technique for reconstruction of the
four-dimensional transverse phase space of a beam in an accelerator
beamline, taking into account the presence of unknown errors on the
strengths of magnets used in the data collection. Use of machine
learning allows rapid reconstruction of the phase-space distribution
while at the same time providing estimates of the magnet errors. The
technique is demonstrated using experimental data from CLARA, an
accelerator test facility at Daresbury Laboratory.
Winter climate preconditioning of summer vegetation extremes in the Northern Hemisphere
Authors: Anand Mohit , Hamed Raed , Linscheid Nora , Silva Patrícia S , Andre Julie , Zscheischler Jakob , Garry Freya K , Bastos Ana 
Published: July 2024

Abstract
The impact of the spring climate on the Northern Hemisphere’s summer vegetation activity and extremes has been extensively researched, but less attention has been devoted to whether and how the winter climate may additionally influence vegetation extremes in the summer. Here, we provide insights into the influence of winter temperature and precipitation on summer vegetation extremes in the Northern Hemisphere. To do this, we identify positive and negative extremes in the summer leaf area index (LAI, a proxy for vegetation activity) and assess winter effects on those extremes using logistic regression at the regional scale. Over a quarter of the regions in the Northern Hemisphere show strong winter climate preconditioning on summer LAI extremes, which is typically stronger for croplands than forests. In regions with strong winter preconditioning, the spring LAI mediates the link between winter climate and summer LAI extremes through the ecological memory in seasonal legacy effects. Our findings suggest that extremely low summer LAI in both croplands and forests is preconditioned by colder and drier winters, while extremely high summer LAI in forests is associated with warmer and wetter winters. For low summer LAI in croplands, warmer winters are associated with an increased likelihood of extremes in mid-latitude regions and a reduced likelihood in high-latitude regions. Consideration of winter preconditioning effects may improve our understanding of inter-annual variability of vegetation activity and support agricultural and land management practitioners in anticipating the detrimental effects of winter on crop yields and forest conditions.
Riboflavin overproduction from diverse feedstocks with engineered Corynebacterium glutamicum
Authors: Pérez-García Fernando , Brito Luciana Fernandes , Bakken Thea Isabel , Brautaset Trygve 
Published: July 2024

Abstract
Riboflavin overproduction by Corynebacterium glutamicum was achieved by screening synthetic operons, enabling fine-tuned expression of the riboflavin biosynthetic genes ribGCAH. The synthetic operons were designed by means of predicted translational initiation rates of each open reading frame, with the best-performing selection enabling riboflavin overproduction without negatively affecting cell growth. Overexpression of the fructose-1,6-bisphosphatase (fbp) and 5-phosphoribosyl 1-pyrophosphate aminotransferase (purF) encoding genes was then done to redirect the metabolic flux towards the riboflavin precursors. The resulting strain produced 8.3 g l−1 of riboflavin in glucose-based fed-batch fermentations, which is the highest reported riboflavin titer with C. glutamicum. Further genetic engineering enabled both xylose and mannitol utilization by C. glutamicum, and we demonstrated riboflavin overproduction with the xylose-rich feedstocks rice husk hydrolysate and spent sulfite liquor, and the mannitol-rich feedstock brown seaweed hydrolysate. Remarkably, rice husk hydrolysate provided 30% higher riboflavin yields compared to glucose in the bioreactors.
Embedded three-dimensional printing of thick pea-protein-enriched constructs for large, customized structured cell-based meat production
Authors: Ianovici Iris , Zagury Yedidya , Afik Noa , Hendel Moran , Lavon Neta , Levenberg Shulamit 
Published: July 2024

Abstract
Recent 3D-printing research showed the potential of using plant-protein-enriched inks to fabricate cultivated meat (CM) via agar-based support baths. However, for fabricating large, customized, structured, thick cellular constructs and further cultivation, improved 3D-printing capabilities and diffusion limit circumvention are warranted. The presented study harnesses advanced printing and thick tissue engineering concepts for such purpose. By improving bath composition and altering printing design and execution, large-scale, marbled, 0.5-cm-thick rib-eye shaped constructs were obtained. The constructs featured stable fibrous architectures comparable to those of structured-meat products. Customized multi-cellular constructs with distinct regions were produced as well. Furthermore, sustainable 1-cm-thick cellular constructs were carefully designed and produced, which successfully maintained cell viability and activity for 3 weeks, through the combined effects of void-incorporation and dynamic culturing. As large, geometrically complex construct fabrication suitable for long-term cellular cultivation was demonstrated, these findings hold great promise for advancing structured CM research.
Development of machine learning regression models for the prediction of tensile strength of friction stir processed AA8090/SiC surface composites
Authors: Adiga Karthik , Herbert Mervin A , Rao Shrikantha S , Shettigar Arun Kumar , Shrivathsa TV 
Published: July 2024

Abstract
Friction Stir Processing is a state-of-the-art technology for microstructure refinement, material property enhancement, and fabrication of surface composites. Machine learning approaches have garnered significant interest as prospective models for modeling various production systems. The present work aims to develop four machine learning models, namely linear regression, support vector regression, artificial neural network and extreme gradient boosting to predict the influence of FSP parameters such as tool rotational speed, tool traverse speed and groove width on ultimate tensile strength of friction stir processed AA8090/SiC surface composites. These models were developed through Python programming and the original dataset was divided into 80% for the training phase and 20% for the testing phase. The performance of the models was evaluated by root mean squared error, mean absolute error and R2. Based on the results and graphical visualization, it was observed that the XGBoost model outperformed other models with high accuracy in predicting UTS of AA8090/SiC surface composites.
A study on the effects of hybrid (SIC- PSSA) nano sized reinforcement on mechanical and tribological behaviour of Al alloy-based metal matrix composite produced by ultrasonic assisted stir casting
Authors: Tenali Nagaraju , Ganesan G , Ravindra Babu P 
Published: July 2024

Abstract
This study focuses on the effects of hybrid reinforcement consisting of nanosized particles of Palm Sprout Shell Ash (PSSA) and silicon carbide (SiC) on the mechanical and tribological properties of the Al-Cu-Mg alloy. Hybrid reinforced composites with different weight percentages of SiC and PSSA (0:0, 0:4, 1:3, 2:2, and 4:0 wt%) were prepared using the ultrasonic-assisted bottom-poured stir casting technique. Scanning electron microscopy (SEM) and energy-dispersive x-ray spectroscopy (EDS) were used to characterize the hybrid composite made of Al-Cu-Mg alloy. The optical and SEM microstructural analyses demonstrated an even distribution of SiC and PSSA nano size reinforcements within the matrix. The EDS analysis revealed SiC and PSSA reinforcement particles in the composite. The mechanical properties (tensile, flexural, and impact strength) and wear properties (wear rate and coefficient of friction) of the composites and alloys were evaluated according to the ASTM standards. The hybrid reinforced composites outperformed the base alloy. Among all composites, the 2:2 wt% SIC and PSSA hybrid reinforced composites exhibited a significant enhancement in both tensile and flexural strength, with a 29.15% and 27.64% increase in strength, respectively. However, the inclusion of these reinforcements led to a reduction in the ductility and impact strength of the Al-Cu-Mg alloy composite. The 0:4 wt% SiC- and PSSA-reinforced composites experienced the largest reductions in ductility and impact strength, with decreases of 47.67% and 3.56%, respectively. For the 2:2 wt% SiC and PSSA composites, these reductions were 23.64% and 3.16%, respectively. The SEM analysis of the fractured surfaces of the composites tested for mechanical properties revealed evidence of both ductile and brittle fracture mechanisms in the tensile, flexural, and impact tests. The wear behaviour of the prepared samples was evaluated, and all composites exhibited superior performance compared with the base alloy, demonstrating adhesive and abrasive wear mechanisms and varying friction coefficients. Among all the composites, the 2:2 wt% SiC- and PSSA-reinforced composites exhibited high wear resistance and a lower coefficient of friction than the other fabricated composites.
Investigating the occurrence and predictability of pitch angle scattering events at ADITYA-Upgrade tokamak with the electron cyclotron emission radiometer
Authors: SIJU Varsha , PANDYA Santosh P. , PATHAK S. K. , PATEL Ansh , NAGORA Umesh , PUROHIT Shishir , JHA Sameer , GUPTA M. K. , TAHILIANI K. , KUMAR R. , TANNA R. L. , GHOSH J. 
Published: July 2024

Abstract
This paper describes the experimental analysis and preliminary investigation of the predictability of pitch angle scattering (PAS) events through the electron cyclotron emission (ECE) radiometer signals at the ADITYA-Upgrade (ADITYA-U) tokamak. For low-density discharges at ADITYA-U, a sudden abnormal rise is observed in the ECE signature while other plasma parameters are unchanged. Investigations are done to understand this abrupt rise that is expected to occur due to PAS. The rise time is as fast as 100 μs with a single step and/or multiple step rise in ECE radiometer measurements. This event is known to limit the on-axis energy of runaway electrons. Being a repetitive event, the conditions of its repetitive occurrence can be investigated, thereby exploring the possibility of it being triggered and surveyed as an alternate runaway electron mitigation plan. Functional parameterization of such events with other discharge parameters is obtained and the possibility to trigger these events is discussed. PREDICT code is used to investigate the possible interpretations for the PAS occurrence through modeling and supporting the ECE observations. The trigger values so obtained experimentally are set as input criteria for PAS occurrence. Preliminary modeling investigations provide reliable consistency with the findings.
Emergence of noise-induced barren plateaus in arbitrary layered noise models
Authors: Schumann M , Wilhelm F K , Ciani A 
Published: July 2024

Abstract
In variational quantum algorithms the parameters of a parameterized quantum circuit are optimized in order to minimize a cost function that encodes the solution of the problem. The barren plateau phenomenon manifests as an exponentially vanishing dependence of the cost function with respect to the variational parameters, and thus hampers the optimization process. We discuss how, and in which sense, the phenomenon of noise-induced barren plateaus emerges in parameterized quantum circuits with a layered noise model. Previous results have shown the existence of noise-induced barren plateaus in the presence of local Pauli noise (Wang et al 2021 Nat. Commun.
12 6961). We extend these results analytically to arbitrary completely-positive trace preserving maps in two cases: (1) when a parameter-shift rule holds, (2) when the parameterized quantum circuit at each layer forms a unitary 2-design. The second example shows how highly expressive unitaries give rise not only to standard barren plateaus (McClean et al 2018 Nat. Commun.
9 4812), but also to noise-induced ones. In the second part of the paper, we study numerically the emergence of noise-induced barren plateaus in QAOA circuits focusing on the case of MaxCut problems on d-regular graphs and amplitude damping noise.
An experiment on using activated carbon to remove direct dyes from wastewater collected from the textile dyeing industry
Authors: Enad Huda Yousif 
Published: July 2024

Abstract
Environmentalists have been raising concerns about the concentration of dye in wastewater. A wide range of industries are the major contributors to increasing the percentage of dyes in wastewater, such as the food, paper, fabric, makeup, and textile sectors. This is really posing an issue for many organisms living in water. A range of biological, physical, and chemical techniques have been developed to eliminate dye from wastewater. Different treatment techniques are well known for their efficiency in colour removal since different industries utilise different dyes. Adsorption, filtering, and coagulation/flocculation are well-known methods for physical treatment. For biological treatment, the use of microbes and enzymes, in addition to biosorption and biodegradation, is well known for its efficiency. Furthermore, the chemical treatment used ozonation, photocatalysis, and electron transport. This research used an experimental method to test the efficiency of activated carbon (AC) created from sawdust as a dye remover from wastewater. Sawdust AC was chemically and physically treated, and it was characterised by XRD, BET, SEM, FTIR, and EDX, which revealed a significant up-taking capacity that reached 73% of direct blue, green, and orange dye from its surface. It was discovered that pH values of 3 and below are optimal for the adsorption of direct dyes onto sawdust carbon. The findings suggest that sawdust carbon might be used to remove colours from wastewater at a lower cost than commercial activated carbon.
A method: multi-scale calculation life of welded beams with residual stress
Authors: Shining Lyu , Wang Aihong , Gao Youshan , Wu Huijuan , Gao Ling 
Published: July 2024

Abstract
To improve the accuracy of the probability of life value calculation while ensuring computational efficiency, a study was conducted on the finite element probability of life calculation method for beam-shell coupling. On the basis of the finite element heat and stress coupling model of Type I welded beam, a fatigue fracture model of residual stress and cyclic load coupling was established. The probability of life calculation of beam-shell elements was theoretically derived, and the expression of the probability of life model was unified. The probability of life of Type I welded beam was calculated, and it was compared with the model of beam assumption and the full life test result. The results show that the computational efficiency of the beam-shell coupling model is higher than that of the shell element model. In addition, the probability of life calculation result obtained by the beam-shell coupling model is highly consistent with the experimental result in statistical terms, and it has higher accuracy at low stress levels than the calculation result of the beam element, with the relative error between the median of the calculation result and the experimental result being less than 10%.
Mobility and Temperature Sensitive Energy Efficient Routing (MTS-EER) protocol in a wireless body area network
Authors: Rawat Anil K , Singh Amandeep , Singh Manwinder 
Published: July 2024

Abstract
Sensor technology advancements have provided the platform to implement wireless body area networks, thanks to the nanosized sensor units capable of sensing, aggregating, and forwarding physiological information. The collected information is routed to the desired destination unit for data analysis and decision-making in remote healthcare. However, improving energy utilization remains a brain-teasing problem for the research community, especially considering imbalanced energy consumption and postural movements. Mobility contributes to disconnectivity issues, high energy drainage, and retransmission delays. In addition, the sensor node’s thermal level also poses a challenge in maintaining safer and reliable data transmission. To overcome these issues, a novel Mobility and Temperature Sensitive Energy-Efficient Routing ¬(MTS-EER) algorithm has been proposed that includes a two-step process. In step 1, an Intelligent Path Estimation Function (IPEF) is designed considering the sensor’s mobility, temperature, and energy level. IPEF depends on crucial parameters i.e.: - residual energy, signal-to-noise ratio (SNR), distance, total energy, and most importantly temperature of the sensor unit. The sensor node with the least IPEF is selected as the Cluster Head (CH). In step 2, an optimized and sustainable energy conservation model (OSECM) is implemented based on the Adaptive Transmission Power (ATP) and the Power Management Module (PMM). The ATP conserves the energy via intelligently varying the transmission power and PMM manages the sleep pattern of sensor nodes to yield a high network lifetime and efficient energy utilization. The algorithm includes a clustering approach with dual sink nodes to conserve energy and improve reliability. Finally, the results are compared with the recent state-of-the-art research work. The proposed algorithm provides better results considering residual energy, throughput, network lifetime, and end-to-end delay.
Theoretical and experiment optimization research of a frequency up-converted piezoelectric energy harvester based on impact and magnetic force
Authors: Cheng Qianju , Wang Qingmeng , Liu Zhi , Lv Zean 
Published: July 2024

Abstract
Harvesting environmental vibrations to power electronic components is an essential approach for addressing the power supply challenge in MEMS. However, conventional vibration energy harvesting systems frequently suffer from limited frequency bandwidth and high-frequency deficiencies. This paper proposes a novel up-frequency structure for piezoelectric vibration energy harvesting (VEH) that relies on both nonlinear magnetic force and piecewise linear force. The proposed VEH’s nonlinear dynamic characteristics are analyzed theoretically, and an experimental prototype machining and vibration test platform are constructed. Theoretical and experimental results are compared and analyzed by conducting basic experiments and key parameter optimization experiments. The research results demonstrate that the proposed VEH can efficiently harvest vibration energy in low-frequency and wide-band environments. Regarding the system parameters, higher vibration acceleration results in increased output voltage and wider working frequency bandwidth. Reducing the gap distance enhances piecewise linear vibration, which broadens the working frequency bandwidth. Furthermore, the proposed VEH’s ability to harvest low-frequency vibrations can be enhanced by reducing the magnet distance, thereby reducing the linear resonance frequency of the system. The findings of this study offer valuable insights for advancing the engineering application of MEMS self-power supply technology.