bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Indian white shrimp (Penaeus indicus) rearing technique at Balai Besar Perikanan Budidaya Air Payau (BBPBAP) Jepara
Authors: Firdausy A M A , Mutoharoh R , Anggraini N , Yudhistira A , Samara S H
Published: September 2024

Indian white shrimp is one of the important fishery commodities with high economic value after banana prawns (Penaeus merguiensis) in the northern coastal waters of Central Java Province. This shrimp needs to be more developed since its aquaculture technique was not quite as well-known as in other shrimps such as P. vannamei or P. monodon. This study aimed to unveil the techniques for rearing white shrimp and its influencing factors. The method in this research used active participation and descriptive methods. The data collection method used was from primary and secondary data. Both primary data were FCR (Feed Conversion Rate), ABW (Average Body Weight), ADG (Average Daily Growth), and water quality parameters while the secondary data were literature review and staff information. The results showed that the FCR values in the three pools were high (1: 5.5, 2: 24.57, 3: 10.36). For growth parameters, the ABW values for the three ponds were 29.57, 20.00, and 23.91 while the final ADG values were 0.53, 0.14, and 0.52 respectively. It can be concluded that the enlargement activity of Indian white shrimp needs to be improved due to high FCR value and fluctuating water quality. Higher FCR value would reduce the feed efficiency so that a lot of feed was given to the shrimps but their growth is less than optimal. The Enlargement activities at Jepara should use feed with a minimum protein content of 33% by the protein requirements of Indian white shrimp so that it can support gonad maturity. Additionally, it is necessary to rearrange the pond size to conform to the standard size (2000-5000 m2), as well as manage water quality through daily siphoning so that the water quality remains optimal.
Study of the diesel fuel drop vaporization and combustion at a hydrogen-diesel fuel dual fuelled diesel engine
Authors: Cernat A , Pana C , Negurescu N , Nutu C
Published: September 2024

The present paper shows the analysis of the results of the theoretical model developed by authors for diesel fuel drops vaporization study, air-diesel fuel-hydrogen mixture forming estimation and diesel fuel drops combustion in the presence of air-hydrogen mixtures set in the cylinder before the start of conventional fuel injection. The model is applied to a single cylinder diesel engine fuelled with diesel fuel and hydrogen, in dual mode by diesel gas method, at the engine speed of 900 rev/min. For a diesel fuel drop the vaporization speed, mixture formation speed, combustion speed, flame radius are presented and analysed. At hydrogen use, the cyclic amount of diesel fuel is reduced and the vaporization duration of the diesel fuel drop is reduced comparative to classic fuelling. At dual fuelling, the combustion of the burning of air-hydrogen mixtures in the vicinity of diesel droplets leads to reduced vaporization time, with 43%, an increased vaporization rate, with 26.9% and an accelerated formation of the mixture between diesel fuel and air-hydrogen mixture. Further, the combustion speed increase with 6.9%, the combustion time is decreased with 6% and the flame radius increase with 6.7%.
A calculation algorithm for the heater of a Stirling engine
Authors: Mitran T. , Craciun D. , Rus A. , Dragomir G. , Chira D.
Published: September 2024

The paper presents a calculation algorithm for the heater of a Stirling engine. In the current context of the energy crisis, Stirling engines can be used to produce mechanical work from renewable energy sources. The heat exchangers are one of the key elements regarding the efficiency of a Stirling engine. So, a calculation algorithm for the heater of a Stirling engine can be used for the dimensioning of this component, according to the requirements for the functioning of the system. To validate this algorithm, a dedicated program for the calculation of the heat exchangers based on the finite element analyse was used.
Conversion of a small size passenger car to hydrogen fueling: simulation of full load performance
Authors: Irimescu A , Vaglieco B M , Merola S S , Zollo V , De Marinis R
Published: September 2024

Hydrogen offers a valid choice when considering zero emissions transport. This alternative fuel is well suited for spark ignition (SI) engines and it can be implemented with relatively minor changes in terms of added components. Initial evaluations of feasibility with respect to available space for the fuel tank revealed that it is possible to convert a small size passenger car to hydrogen fueling and maintain a range comparable to the fully electric alternative. Peak power assessment showed that additional boosting was required compared to gasoline operation, close to the limit of compressor surge. As a result, the present study extended the engine speed range so as to evaluate full load performance levels that can be obtained when using hydrogen. 0D/1D simulation was applied for simulating power unit output as well as related control parameters. A dedicated laminar flame speed sub-model was implemented for including fuel chemistry effects. Predicted combustion phasing showed the required changes in ignition timing when switching fuels and revealed that the engine could be operated close to stoichiometry when using hydrogen. A reduction of torque was calculated at low engine speed, even if peak power ratings were practically the same as with gasoline fueling.
CFD simulation of the interaction between water droplets on the GDL of a low temperature PEM FC in conditions of air cross-flow
Authors: Antetomaso C , Merola S S , Irimescu A , Vaglieco B M , Micco S Di , Jannelli E , Scarpati G , Simeoni E
Published: September 2024

Droplet dynamics in low temperature proton exchange membrane fuel cells (LT-PEMFCs) are significantly important with respect to water management and removal. Three main phenomena are linked to water generation/transport in a LT-PEMFC: H2O production on the cathode side, electro-osmotic drag (anode to cathode) and back diffusion (cathode to anode). The excess/lack of water, depending on membrane humidity, strongly affects LT-PEMFC performance, involving its instability. In this work CFD simulation of droplets was performed when they were deposited in tandem on the gas diffusion layer (GDL) and subjected to 15 m/s parallel air flow. The volume of fluid (VOF) method was adopted and droplets with diameters that range from 0.3 mm to 0.8 mm were considered. Simulations demonstrate that deformations, oscillations and sliding of droplets were affected by their relative size and position. Results can contribute to define predictive models of water droplet dynamics on the GDL surface and their detachment towards the FC gas channel.
Simulation of the Parameters of a Lithium-ion Battery that Equips an Electric Vehicle
Authors: Ancuța A A , Voloacă Ș , Frățilă G , Danciu G
Published: September 2024

The evolution in the field of electric vehicles is strongly influenced by the performances of the electricity storage sources. Thus the paper proposes to present some theoretical aspects related to the operation of lithium-ion batteries and factors that may influence their state of charge and of course the vehicle autonomy, as well as a simulation model to determine the variation of the main parameters of the battery when it is connected to a velocity variation profile according to WLTC and UDDS cycles. For this we want to show the influence of the discharge current on the battery over time. So, to realize the study the velocity variation over time for the two mentioned cycles will be converted into the current variation and the battery will be connected to this signal.
Experimental for depicting the influence upon gaseous emissions of an Otto engine by using hydrogen as fuel addition
Authors: Suciu C M , Igreț S V , Ionel I
Published: September 2024

Due to the higher pollution restrictions implemented globally upon the internal combustion engines, for new but also older vehicles, suitable solutions must be found, for solving major, attested incriminations concerning pollution. The present research focuses on the possibility of the reduction of the emission concentration values emitted by a classic Otto spark ignition engine (Otto ICE), by adding hydrogen to the normal used fuel (gasoline). The hydrogen is generated via a water electrolytic conversion technology, applied, in symbiosis with the internal combustion engine and it is known as hydrogen air (HHA). The hydrogen quantity, as resulted from the HHA generating process and fuelled into the engine, represents 10% (by volume) of the total volume of the intake capacity. Being directly correlated to the stoichiometric ratio used to create the fuel mixture, the intake of hydrogen is finally controlled; therefore, the total calorific power of the new fuel mixtures is increasing by approximate 30%. All the measurements have been achieved in a lab using certified and approved gas analyzers and measurement instruments. The novelty of the research consists of (i) presenting results of measurements with the gas analyzer, one at an engine speed of 800 RPM and the second at 2000 RPM using only gasoline as fuel (normal or standard fuel); (ii) concluding of comparative measurements at the same engine speeds, but with addition of hydrogen in the fuel mixture. Since carbon dioxide makes up the vast majority of greenhouse emissions, the results indicate also a more reduced CO2 concentration in the exhaust. One presents that the electrolytic convertor is capable of producing 1800 litters of HHO gas from 1 litre of water. By upgrading the oxyhydrogen system, one succeeded to produce more HHO gas and replacing the amount of conventional fuel. As conclusions one demonstrated that lower emission values can be obtained with the addition of hydrogen air (HHA).
The emission of off-road vehicles and their reduction options
Authors: Bíró N , Kiss P , Szőllősi D
Published: September 2024

The reduction of harmful emissions is a popular topic in both scientific and public circles. Contrary to popular belief, emissions from transport are only a small part of global emissions. As shown in the figure, the average of the EU 27 countries attributes only 15% of emissions from transport. From common perspective, vehicles with internal combustion, including diesel engines, will soon be replaced by alternative drivetrains. However at least at the commercial and off-road transportation, the diesel technology it is not so easy, and also the environmental reasons are questionable. Although the local emissions of electric vehicles are zero, their global emissions are, according to some research, more significant than their counterparts with internal combustion engines. The total electricity produced in the world in 2016 was about 25 PWh, two-thirds of which came from fossil energy carriers, which seriously damages the ecosystem, so it cannot be labelled as green energy.
Study on the efficiency of Battery Electric Vehicle
Authors: Chiver O , Burnete N , Şugar I R , Neamt L
Published: September 2024

The paper deals with aspects that influence the efficiency of electric vehicles and, respectively, their efficiency compared to hybrid or ICE vehicles. Different driving cycles are considered, especially referring to driving on the highway, or urban driving with repeated starts and stops, with average speed relatively low, and the acceleration not too high. Besides these, a comparison will be made between the situations in which the BEV has one speed or two speeds, since the weight of the vehicle is greater in the latter case. Then a hybrid and a conventional model will be tested for the same driving cycles and the same vehicle body.
Influence of Dual Fueling on the Performance of a Compression Ignition Engine
Authors: Izvorean S , Stoica V , Lelea D
Published: September 2024

The diesel engine although offering a high efficiency and low fuel consumption is slowly being marginalized regarding thermal engines due to high pollutant like NOx and smoke particles. Although there are alternative propulsion systems, they are not proper for industrial use. For this reason, we need to find a solution to improve this engine and to obtain lower emissions and a higher efficiency.

In this paper we propose a solution that can improve the efficiency and reduce the pollutants produced by diesel engine, using a secondary fuel. The idea is to inject the secondary fuel in the intake manifold of the engine, creating a mix between the air and the fuel. This mixture will fill the cylinders and a pilot injection will be used to ignite the content of the cylinder and to provide the additional fuel needed to obtain the targeted performance, while maintaining the emissions at a minimum.

In this scope an experimental test bench with a diesel engine, equipped with a secondary injection system was created. The secondary fuel is injected, in the intake manifold, separately than the main diesel fuel, via a single point injection system. The entire system was created in the laboratory and is driven with a in house software solution that allows us to control every aspect of the engine such as timing, injection duration, fuel pressure and so on. As a result of the experiment, was observed that the engine performance is not diminished. The NOx emission presents a decrease in the same operating conditions. The smoke opacity is reduced significantly and the HC emissions present a slight increase for the same conditions
The influence of warning lights on the truck cabins on aerodynamic performance
Authors: Vieru E M , Iozsa M D , Ilea L , Frățilă G
Published: September 2024

In recent development of goods transportation by road, there has been a growing interest in truck aerodynamics as a consequence of increased desire to reduce fuel consumption and emissions. Commercial vehicles have undergone continuous modifications in terms of body design (cabin) and trailers or semi-trailers. There have been and still are areas that disrupt air flow and can be optimized for an improved aerodynamic performance. As part of this areas, the paper will study the influence of beacon lights and light ramps positioned on cabin roof for European type trucks (tractor units). These warning equipment’s are imposed by transportation laws, reason for which eliminating them for achieving described purpose is not an option. In this context, the reduction of aerodynamic coefficient (Cd) can be pursued by analysing and optimizing the dimensions, shape and position for warning lights, in order to reduce the magnitude level of swirling effect. Different configurations of these elements will be tested and their impact in terms of air flow on the truck body will be analysed, with focus on roof area. The study will be done by simulating the interaction between airflow and truck in a virtual aerodynamic wind tunnel. The results will be analysed with the help of parameters like velocities, streamlines and pressures from a theoretical and experimental point of view to find the most viable option for each of the presented elements. The CFD (computational fluid dynamics) numerical simulations for chosen tests will be performed at a speed of 110 km/h considering that it is an often-encountered speed for trucks and also that aerodynamic phenomenology can be BETTER observed. By analysing the results obtained from the performed CFD simulations, the best positions and shapes for the beacon and ramp lights are desired to be identified. The paper conclusions will contain best configurations of warning lights and emissions improvement.
The electric transmission stress behaviour investigation while being used for a middle-class road vehicle
Authors: Visan F , Croitorescu V
Published: September 2024

The paper presents the design for an electric transmission used for a middle-class road vehicle. The transmission gears are designed, calculated and virtually developed. A middle-class road vehicle is chosen for virtual implementation. The geometrical models for the gears are designed and developed. The transmission integration into the chosen vehicles is defined. The stress behaviour for the transmission is investigated following different torque performances demands. Different materials for the gears are considered.
Research regarding the simulation of the autonomy for the electric vehicles in the case of the WLTC test cycle
Authors: Minzatu Corneliu , Nişulescu Valentin , Bancă Gheorghe , Toma Marius , Renţea Cristian
Published: September 2024

In current mainstream research, energy consumption and autonomy are just a few of the the major objectives anticipated for electric road vehicles. The production of electric vehicles is continuously expanding, offering to the market a large variety of constructive variants in order to satisfy the requirements for their exploitation. Also, in the current energy context, it is expected from the electric car manufacturers, to deliver high quality models which can be characterized as the actual alternatives to actual existing solutions equipped with an internal combustion engine. Under these circumstances, the continuous research it is a high priority for everyone electric vehicle producers, where simulation on the computer is basically not absent as a go-between step prior to the validation of the final draft proposals. According to these assumptions, in the first part of the article you will find the AMESim simulation platform points, where it describes the model made with it and the simulated test cycle. In the second part of the article, as a consequence of the simulation of the experimental electric vehicle, are highlighted some aspects of the autonomy behaviour in the case of simulation on the World-wide harmonized Light duty Test Cycle (WLTC), for all four speed zones specific to it.
Study of Alternatives to Manufacturing of Long Pipes with Many Holes
Authors: Poiana DI , Ionel I , Vasilescu M , Vetreş I
Published: September 2024

In industrial manufacturing, certain long, thin-walled pipe-type parts that have many holes arranged along their longitudinal axis are required. In the automotive industry, such thin-walled long pipe parts are needed for body frames, for heavier component supports, for protection bars, etc. Frequent cases are encountered, for example, in the manufacture of modular shelves for storage. In these cases, long pipes, up to 6 meters long, with thin walls are used. Such long thin-walled pipes, which have many holes arranged along them, sometimes even equally spaced between them, are frequently made with a manufacturing technology that has several characteristic steps: 1) making holes in sheet metal strips, 2) bending the strips and welding them lengthwise, resulting in perforated pipes having a rectangular or square section. In this paper, two variants of obtaining pipes with holes arranged along the length of the pipe, but which are obtained from laminated pipes with thin walls of rectangular section, are proposed and analyzed. The characteristics of obtaining holes in these pipes are presented and the advantages and disadvantages of the proposed solutions are analyzed. The finite element method was also used for the analysis using SolidWorks software.
Weather and road environment’s influence on multi-vehicle crashes in Romania
Authors: Drosu A , Cofaru C , Slaff C
Published: September 2024

The aim of this paper is to assess the weather and road environment’s influence on Multi Vehicle Crashes (MVC) in Romania. In order to capture the real effect of these factors, the road accidents recorded between the months of November and March of each year from 2013 to 2018 are analysed, as this is the period of each year when most of the meteorological phenomena relevant to our research are present. The analysed data set contains complex records of a number of 8,538 accidents which are assessed at the highly disaggregation level (individual), a type of analysis which is rarely found in the road safety studies. A Binary Multiple Logistic Regression (BMLR) is employed for explanatory purposes in order to estimate the probability of MVC. Road accidents that involve at least 3 vehicles are declared as MVC and the probability of their occurrence is labelled as “1”. The rest of the crashes in the data set are assigned the value “0” of the probability. The results of this research show that the highways have the highest risk of a MCV occurring as the odds values show and the sleet is the weather phenomena which highly increase the probability of having a MCV. These risk factors should be further researched in connection with other variables that relate to the driver and weather characteristics.
The integrated methodology for assessing the safety of the road network infrastructure in Romania.
Authors: Dimitriu C I , Bujor C R
Published: September 2024

Romania has the highest road fatality rate in the EU and the lowest perception of road quality. This study presents the implementation of a preliminary procedure and tools provided by the European Commission for the safety assessment of the DN2-E85 road infrastructure, which covers 472.23 km. This road was selected due to the high number of road deaths between 2017 and 2022. The research focuses on the application of both proactive and reactive methodologies as required by Directive (EU) 2019/1936, which requires full road network safety assessments by 2024, with subsequent assessments every five years. The proactive methodology assesses the built-in road safety of the road infrastructure based on design parameters, while the reactive methodology is based on historical data on accidents and traffic flows. The integration of these methodologies allows the classification of road segments into five risk levels. Preliminary results indicate that approximately 59% of the length of the DN2-E85 road is classified as “very high priority”, highlighting significant safety deficiencies, which require actions to immediately improve traffic safety. This study highlights the need for systematic road infrastructure safety assessments and prioritisation of high-risk segments to reduce road fatalities and improve overall road safety. The findings serve as crucial information for road safety auditors and the Romanian Road Authority - ARR, supporting the identification of high-risk areas and the allocation of resources to improve safety. In addition, this research provides a basic basis for future adaptations of road infrastructure safety assessment guidelines, considering the specific characteristics of national and county roads. By aligning with EU directives and national standards, the study aims to increase road safety and reduce the incidence of serious accidents in Romania. The insights gained from this research are essential for developing effective road safety strategies and implementing remedial measures that address the most dangerous segments of the road network.
Enhancing tribological properties of pump shafts through shot peening: a study of surface roughness, hardness and performance comparison with heat treatment
Authors: Iyyadurai Jenish , Singh Ravindra Pratap , Arockiasamy Felix Sahayaraj , Mohanavel V , Kannan Sathish , Giri Jayant , Alarfaj Abdullah A
Published: September 2024

This research employed Shot Peening (SP) to enhance the tribological behavior of the En-31 pump shaft material. The study compared the effects of varying peening pressures (2.5, 3, 3.5, and 5 bar) and shot sizes (S110 and S230) on surface roughness, hardness, and tribological behavior. Surface roughness was quantified using profilometry to assess the impact of shot peening on the topography of AISI 4140 steel, while hardness testing evaluated the enhancement in surface hardness post-treatment, correlating with the induced compressive residual stresses. Additionally, wear analysis conducted through tribological testing determined the effectiveness of shot peening and plasma nitriding in improving wear resistance under operational conditions. The results shown highest hardness of 12.5% was achieved at a pressure of 4 bar with the S230 shot material, while the surface roughness increased by over 75% under the same conditions. The 3.5 bar peening process produced the most significant improvements based on fractographic analysis.
Cleanroom-free fabrication of flexible capacitive pressure sensors using paintable silver electrodes on stationery paper and random microstructured polydimethylsiloxane dielectric layer
Authors: Farman Mohd , Prajesh Rahul , Panwar Deepak Kumar , Kaur Maninder , Thouti Eshwar
Published: September 2024

In this work, we propose a facile, low-cost, and cleanroom-free approach for fabricating flexible capacitive pressure sensors based on paintable Ag electrodes on stationery paper substrates (Ag–paper electrodes) and a random microstructured polydimethylsiloxane (PDMS) dielectric layer transferred from emery paper. COMSOL Multiphysics simulations and experimental investigations suggest that the pressure sensor with random microstructured PDMS dielectric layer performs better than the sensor with ordered micropyramidal dielectric layer. The developed Ag–paper electrode and random microstructured PDMS dielectric layer-based pressure sensors are workable in a wide pressure range (up to 630 kPa) and exhibit a high sensitivity of 0.132 kPa−1 up to 1 kPa, low hysteresis (6.6%) with loading–unloading of ∼500 kPa pressure, high stability during a ∼5250 cyclic test, and the ability to sense a low pressure of ∼27 Pa. The developed sensor also successfully transduces arterial pulse wave forms when it is properly attached to the wrist. Using the proposed process, a flexible capacitive pressure sensor matrix of 4 × 4 array is also successfully developed for single- and multiple-point pressure mapping with minimal cross-talk. The proposed sensor process is simple and inexpensive to implement, and offers spatial pressure mapping for e-skin applications.
A qubit-efficient variational selected configuration-interaction method
Authors: Yoffe Daniel , Entin Noga , Natan Amir , Makmal Adi
Published: September 2024

Finding the ground-state energy of molecules is an important and challenging computational problem for which quantum computing can potentially find efficient solutions. The variational quantum eigensolver (VQE) is a quantum algorithm that tackles the molecular groundstate problem and is regarded as one of the flagships of quantum computing. Yet, to date, only very small molecules were computed via VQE, due to high noise levels in current quantum devices. Here we present an alternative variational quantum scheme that requires significantly less qubits than VQE. The reduction in the qubit number allows for shallower circuits to be sufficient, rendering the method more resistant to noise. The proposed algorithm, termed variational quantum selected-configuration-interaction (VQ-SCI), is based on: (a) representing the target groundstate as a superposition of Slater determinant configurations, encoded directly upon the quantum computational basis states; and (b) selecting a-priory only the most dominant configurations. This is demonstrated through a set of groundstate calculations of the H2, LiH, BeH2, H2O, NH3 and C2H4 molecules in the sto-3g basis set, performed on IBM quantum devices. We show that the VQ-SCI reaches the full configuration interaction energy within chemical accuracy using the lowest number of qubits reported to date. Moreover, when the SCI matrix is generated ‘on the fly’, the VQ-SCI requires exponentially less memory than classical SCI methods. This offers a potential remedy to a severe memory bottleneck problem in classical SCI calculations. Finally, the proposed scheme is general and can be straightforwardly applied for finding the groundstate of any Hermitian matrix, outside the chemical context.
Controlling and monitoring laser-mediated localized synthesis of silver nanoparticles within gold nanoapertures
Authors: Pillanagrovi Jayakumar , Dutta-Gupta Shourya
Published: September 2024

Photoreduction of metallic nanoparticles can be used for localized and deterministic synthesis of nanostructures required for various applications. Specifically, in-situ photoreduction of silver nanoparticles (AgNPs) is a facile fabrication route that enables the fabrication of nanoplasmonic substrates. In the present work, we demonstrate an approach to fabricate hybrid plasmonic substrates using in-situ photoreduction of AgNPs within gold nanoapertures (NAs). The approach involves the top-down approach to fabricate NAs followed by a site-specific synthesis of AgNPs within the NAs. Furthermore, we use dark-field imaging to monitor and understand the photoreduction within the gold NAs in real time. We demonstrate that a careful selection of experiment parameters aid to synthesize the AgNPs within NAs and the scattered light intensity can be used to map the characteristics of the formed AgNPs. The illumination time, laser power and AgNO3 concentration can be used to tune the AgNPs characteristics. The demonstrated strategy for realizing hybrid plasmonic substrates can be used for the fabrication of substrates for SERS based sensors, enhancing fluorescence of molecules, and photocatalytic applications.
Anderson impurity mechanism for a multi-level model in δ-Pu
Authors: Muñoz Alexander R , Jones Travis E
Published: September 2024

Electronic correlations and spin–orbit interactions in plutonium create variations in the bonding behavior of each of its allotropes. In δ-Pu, the 5f electrons lie at the tipping point between itinerant and localized behavior which has made the use of mixed-level models successful in describing its mechanical properties. The mechanism for the emergence of a mixed-level model has not yet been understood. We use a series of density functional theory approximations to understand the interactions that create a mixed-level description of δ-Pu which leads to accurate physical properties. With the intersite interactions present in the hybrid functional, we show that a single 5f electron engages in orbital-selective bonding that can be understood with an Anderson impurity picture. The Anderson model gives us a mechanism to understand how the bonding in δ-Pu evolves as a function of the interactions in the material such that we obtain both the accuracy and physics of the multi-level models from ab initio theory.
Experimental investigation on sustainable machining of monel using vegetable oils as cutting fluids and machine learning-based surface roughness prediction
Authors: M Ganesh , Arunkumar N , Siva M , Leo G M Lionus
Published: September 2024

The material processing industry is anticipated to mitigate environmental degradation. The protocols established by the International Organisation for Standardisation were adhered to. As a result, it would be prudent to investigate the feasibility of minimizing the use of synthetic cutting fluids from the machining process. This study discusses an environmentally-friendly machining technique for turning nickel-based alloy Monel-500, which evaluates four different cooling conditions: dry machining, flood machining, Co-MQL (coconut oil), and Rb-MQL (Rice Bran Oil). These conditions were tested by experimenting with various machining parameters to investigate four aspects of the turning process: surface finish,cutting temperature, tool wear and chip morphology. Rice bran oil is considered eco-friendly compared to synthetic cutting fluids, and employing it in minimum quantity is economical and helps improve the machined workpiece’s surface finish. The investigation has been further extended by applying machine learning algorithms to predict surface roughness, utilising two logical regressions implemented in Python. Among the two machine learning approaches, the random forest regression technique has demonstrated superior results, achieving a prediction accuracy of 99.8%. Consequently, a decision tree has been developed using this regression model to predict the surface roughness. The structured analysis of the decision tree provides more accurate conclusions, offering flexibility in adjusting parameters and expanding options for operation. As a result, the decision tree approach enables the efficient utilisation of production resources and enhances production capacity by making informed choices about cooling methods during the turning process. Rb-MQL has performed better in all aspects than the other three cooling conditions. When comparing machining under dry conditions, flood cooling, Co-MQL, and Rb-MQL (rice bran oil) reduce the tooltip temperature by 39.5%,25.45 and 24.11%, respectively. Rb-MQL reduced surface roughness by 28.23%,43.59 and 60.49% in contrast with machining under dry, flood, and Co-MQL.
Enhanced fault classification in inverter-fed transmission lines using deep learning
Authors: Etukuri Suresh , Siva M , Varma B R K
Published: September 2024

The conventional power transmission system with synchronous generators is protected with phase angle-based approach that decides which type of faut is occurred on the transmission line system. However, the phase angle-based fault classification method is no longer applicable for systems that have integrated Inverter Based Resources (IBR). The control technology employed for grid integration of renewable sources controls the fault current magnitude depending upon Grid code requirements which results in mal operation of relay. A new fault classification scheme is proposed in this paper which aims at precise faulty phase selection using deep learning techniques. Deep learning techniques have gained significance in the field of protection because of the big data availability from Phasor Measurement Units (PMU’s). This paper describes a new approach of fault classification for systems connected to renewables with the application of Long Short-Term Memory (LSTM) Deep learning network.
Mapping causal pathways with structural modes fingerprint for perovskite oxides
Authors: Ghosh Ayana , Ghosh Saurabh
Published: September 2024

Causality is innate to the determination of the fundamental mechanism controlling any physical phenomena. However, combining causality within the standard practices of computational modelling to understand structure-functionality connections is extremely rare. This work proposes a fingerprint based on key structural modes for ABO3-type perovskite oxides and its derivatives, combined with causal models, for predicting Kohn–Sham energies. Our study of causal models captures the inherent coupling between structural modes such as rotation, tilt and antiferroelectric displacements, responsible for phase transition, polarization, magnetization and metal–insulator transition, exhibited by these materials. Although developed for modelling specific functionality, this method is universally applicable to derive other functionalities and even different material classes while tracking hidden causal mechanisms via structural distortions.
Development and deployment of data-driven turbulence model for three-dimensional complex configurations
Authors: Sun Xuxiang , Liu Yilang , Zhang Weiwei , Wang Yongzhong , Zou Jingyuan , Han Zhengrong , Su Yun
Published: September 2024

In recent years, the synergy between artificial intelligence and turbulence big data has given rise to a new data-driven paradigm in turbulence research. Data-driven turbulence modeling has emerged as one of the forefront directions in fluid mechanics. Most existing studies focus on feature construction, selection, and the development of modeling frameworks, often overlooking the practical deployment and application of trained models. This paper examines the entire process from model construction to real-world deployment, using data-driven turbulence modeling for high Reynolds number flows over complex three-dimensional configurations as a case study. Key stages include data generation, input-output feature construction, model training, model compilation and optimization, deployment, and validation. We successfully implemented the entire workflow in a heterogeneous supercomputing environment and, through mixed programming techniques, integrated the resulting turbulence model into the Platform for Hybrid Engineering Simulation of Flows (PHengLEI) open-source software framework. This allowed for mixed-precision simulations, with the main equations solved in double precision and the turbulence model in half precision. The new computational framework was validated through large-scale parallel numerical simulations on grids with tens of millions of elements for three-dimensional complex configurations. The results highlight the efficiency of our model deployment, with overall computational efficiency improving by 13.35% and the turbulence model’s solution speed increasing by approximately 3.9 times. The accuracy of the computations was also confirmed, with the average relative error in the lift and drag coefficients calculated by the data-driven turbulence model within 3%. Across various computing nodes, the relative error in the computed aerodynamic coefficients remained within 1%, demonstrating the framework’s scalability. Notably, our contributions have been incorporated as a case study in the latest PHengLEI open-source project5

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https://forge.osredm.com/PHengLEI/PHengLEI-TestCases/tree/master/Y02_ThreeD_M6_Unstruct_Branch_Ascend.

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Clinical bioinformatics desiderata for molecular tumor boards
Authors: Pallocca Matteo , Betti Martina , Baldinelli Sara , Palombo Ramona , Bucci Gabriele , Mazzarella Luca , Tonon Giovanni , Ciliberto Gennaro
Published: September 2024

Clinical Bioinformatics is a knowledge framework required to interpret data of medical interest via computational methods. This area became of dramatic importance in precision oncology, fueled by cancer genomic profiling: most definitions of Molecular Tumor Boards require the presence of bioinformaticians. However, all available literature remained rather vague on what are the specific needs in terms of digital tools and expertise to tackle and interpret genomics data to assign novel targeted or biomarker-driven targeted therapies to cancer patients. To fill this gap, in this article, we present a catalog of software families and human skills required for the tumor board bioinformatician, with specific examples of real-world applications associated with each element presented.
An efficient protocol for the extraction of pigment-free active polyphenol oxidase and soluble proteins from plant cells
Authors: Yuzuak Seyit , Xie De-Yu
Published: September 2024

The elimination of brownish pigments from plant protein extracts has been a challenge in plant biochemistry studies. Although numerous approaches have been developed to reduce pigments for enzyme assays, none has been able to completely remove pigments from plant protein extracts for biochemical studies. A simple and effective protocol was developed to completely remove pigments from plant protein extracts. Proteins were extracted from red anthocyanin-rich transgenic and greenish wild-type tobacco cells cultured on agar-solidified Murashige and Skoog medium. Protein extracts from these cells were brownish or dark due to the pigments. Four approaches were comparatively tested to show that the diethylaminoethyl (DEAE)-Sephadex anion exchange gel column was effective in completely removing pigments to obtain transparent pigment-free protein extracts. A Millipore Amicon® Ultra 10K cut-off filter unit was used to effectively desalt proteins. Moreover, the removal of pigments significantly improved the measurement accuracy of total soluble proteins. Furthermore, enzymatic assays using catechol as a substrate coupled with high-performance liquid chromatography analysis demonstrated that the pigment-free proteins not only showed polyphenol oxidase (PPO) activity but also enhanced the catalytic activity of PPO. Taken together, this protocol is effective for extracting pigment-free plant proteins for plant biochemistry studies. A simple and effective protocol was successfully developed to not only completely and effectively remove anthocyanin and polyphenolics-derived quinone pigments from plant protein extracts but also to decrease the effects of pigments on the measurement accuracy of total soluble proteins. This robust protocol will enhance plant biochemical studies using pigment-free native proteins, which in turn increase their reliability and sensitivity.
The poster boys of aspirational labor: parables of success and failure in The Viral Fever’s web shows
Authors: Guha Suryansu
Published: September 2024

Aspirational labor has been understood by scholars based in the Global North to encapsulate a form of labor undertaken by social media content creators that is mostly uncompensated for, but is, nonetheless, integral to the functioning of its economy. While this dominant theorization of aspirational labor is sometimes helpful for explaining the precarity of digital media labor in countries of the Global South, its uncritical application could also be severely limiting. I undertake a close textual analysis of select web shows created by the entertainment brand and YouTube content creators The Viral Fever (TVF) to demonstrate how it would be imprecise to see them as just victims of an exploitative economy. My article shows how TVF web shows consistently imagine elaborate cinematic narratives that valorize and embody the neoliberal values of aspiration and individual growth that in turn is complicit in the machinations of platform economy’s extractive affordances.
Atypical gelatinous tumour of the eyelid in a 58-year-old woman
Authors: Fleischmann-Caruso Delphine , Kaspi Mathilde , Habougit Cyril , Karpathiou Georgia , Garcin Thibaud
Published: September 2024

The patient presented with a malignant tumour that was a slow-growing, painless lesion on the lower eyelid. The main differential diagnoses are cutaneous metastasis of adenocarcinoma and sebaceous carcinoma of the eyelid. They must be ruled out. As immunohistochemistry does not always provide a definitive diagnosis, an extended investigation must be carried out.
GRNet: a graph reasoning network for enhanced multi-modal learning in scene text recognition
Authors: Jia Zeguang , Wang Jianming , Jin Rize
Published: September 2024

Recent advancements in scene text recognition have predominantly focused on leveraging textual semantics. However, an over-reliance on linguistic priors can impede a model’s ability to handle irregular text scenes, including non-standard word usage, occlusions, severe distortions, or stretching. The key challenges lie in effectively localizing occlusions, perceiving multi-scale text, and inferring text based on scene context. To address these challenges and enhance visual capabilities, we introduce the Graph Reasoning Model (GRM). The GRM employs a novel feature fusion method to align spatial context information across different scales, beginning with a feature aggregation stage that extracts rich spatial contextual information from various feature maps. Visual reasoning representations are then obtained through graph convolution. We integrate the GRM module with a language model to form a two-stream architecture called GRNet. This architecture combines pure visual predictions with joint visual-linguistic predictions to produce the final recognition results. Additionally, we propose a dynamic iteration refinement for the language model to prevent over-correction of prediction results, ensuring a balanced contribution from both visual and linguistic cues. Extensive experiments demonstrate that GRNet achieves state-of-the-art average recognition accuracy across six mainstream benchmarks. These results highlight the efficacy of our multi-modal approach in scene text recognition, particularly in challenging scenarios where visual reasoning plays a crucial role.
Implications of myocardial strain in primary mitral regurgitation—a cardiovascular magnetic resonance study
Authors: Romano Simone , Kitkungvan Danai , Nguyen Duc T , El-Tallawi Carlos , Graviss Edward A , Farzaneh-Far Afshin , Shah Dipan J
Published: September 2024

Aims

Chronic primary mitral regurgitation (MR) results in progressive left ventricular (LV) remodelling. Abnormal myocardial deformation (strain) can be present despite preserved ejection fraction (EF). Cardiovascular magnetic resonance (CMR) feature-tracking techniques allow assessment of global longitudinal strain (GLS) from routine cine images. The aim of this study is to evaluate the prognostic value of CMR feature tracking–derived GLS in patients with primary MR.

Methods and results

Consecutive patients undergoing CMR for chronic MR from January 2012 to June 2018 were enrolled. Patients with LVEF <50% were excluded. The composite primary outcome aiming to detect decompensation related to MR comprised (i) referral for mitral surgery owing to symptoms or LV systolic dysfunction or (ii) cardiovascular death. The secondary outcome was all-cause death. A total of 422 patients were followed for a median of 2.7 years, and the primary endpoint was met in 93 patients (34 patients reported symptoms at baseline). At multivariable analysis, GLS≥ −16.6% was associated with primary outcome [hazard ratio (HR) 1.90, P = 0.01]. In moderate MR cohort, patients with GLS≥ −16.6% had worse event-free survival, whereas there was no significant difference in mild or severe MR groups. GLS≥ −16.0% remained associated with all-cause death after adjusting for other covariates including the MR severity (HR 2.24, P = 0.02).

Conclusion

In patients with primary MR with preserved systolic function, GLS was associated with our composite outcomes and all-cause death. GLS may serve as a marker of cardiac dysfunction in the patients with primary MR with preserved systolic function allowing identification of patients likely to decompensate during observation.
Fabrication of a three-dimensional scaffold-free trachea with horseshoe-shaped hyaline cartilage
Authors: Uchida Fumitake , Matsumoto Keitaro , Nishimuta Masato , Matsumoto Takamune , Oishi Kaido , Hara Ryosuke , Machino Ryusuke , Taniguchi Daisuke , Oyama Shosaburo , Moriyama Masaaki , Tomoshige Koichi , Doi Ryoichiro , Obata Tomohiro , Miyazaki Takuro , Nonaka Takashi , Nakayama Koichi , Nagayasu Takeshi
Published: September 2024

OBJECTIVES

Tracheal regeneration is challenging owing to its unique anatomy and low blood supply. Most tracheal regeneration applications require scaffolds. Herein, we developed bio-three-dimensional-printed scaffold-free artificial tracheas.

METHODS

We fabricated bio-three-dimensional-printed artificial tracheas. Their anterior surface comprised hyaline cartilage differentiated from mesenchymal stem cells, and their posterior surface comprised smooth muscle. Human bone marrow-derived mesenchymal stem cells were cultured and differentiated into chondrocytes using fibroblast growth factor-2 and transforming growth factor-beta-3. Initially, horseshoe-shaped spheroids were printed to cover the anterior surface of the artificial trachea, followed by the application of human bronchial smooth muscle cells for the posterior surface. After a 3-week maturing process, the artificial trachea was subjected to histological and immunohistochemical analyses.

RESULTS

The anterior surface of the artificial trachea comprised well-differentiated hyaline cartilage from human bone marrow-derived mesenchymal stem cells. Immunohistochemistry revealed that the smooth muscle expressed α-smooth muscle actin and smooth muscle myosin heavy chain 11.

CONCLUSIONS

A bio-three-dimensional-printed scaffold-free artificial trachea comprising different tissues at the front and back was successfully fabricated.