bluuebunny/crossref_metadata_2025 huggingface dataset:
A Low-Cost High-Performance Montgomery Modular Multiplier Based on Pipeline Interleaving for IoT Devices
Authors: Li Hongshuo , Ren Shiwei , Wang Weijiang , Zhang Jingqi , Wang Xiaohua
Published: July 2023

Modular multiplication is a crucial operation in public-key cryptography systems such as RSA and ECC. In this study, we analyze and improve the iteration steps of the classic Montgomery modular multiplication (MMM) algorithm and propose an interleaved pipeline (IP) structure, which meets the high-performance and low-cost requirements for Internet of Things devices. Compared to the classic pipeline structure, the IP does not require a multiplexing processing element (PE), which helps shorten the data path of intermediate results. We further introduce a disruption in the critical path to complete an iterative step of the MMM algorithm in two clock cycles. Our proposed hardware architecture is implemented on Xilinx Virtex-7 Series FPGA, using DSP48E1, to realize the multiplier. The implemented results show that the modular multiplication of 1024 bits by 2048 bits requires 1.03 μs and 2.13 μs, respectively. Moreover, our area–time–product analysis reveals a favorable outcome compared to the state-of-the-art designs across a 1024-bit and 2048-bit modulus.
MSTPose: Learning-Enriched Visual Information with Multi-Scale Transformers for Human Pose Estimation
Authors: Wu Chengyu , Wei Xin , Li Shaohua , Zhan Ao
Published: July 2023

Human pose estimation is a complex detection task in which the network needs to capture the rich information contained in the images. In this paper, we propose MSTPose (Multi-Scale Transformer for human Pose estimation). Specifically, MSTPose leverages a high-resolution convolution neural network (CNN) to extract texture information from images. For the feature maps from three different scales produced by the backbone network, each branch performs the coordinate attention operations. The feature maps are then spatially and channel-wise flattened, combined with keypoint tokens generated through random initialization, and fed into a parallel Transformer structure to learn spatial dependencies between features. As the Transformer outputs one-dimensional sequential features, the mainstream two-dimensional heatmap method is abandoned in favor of one-dimensional coordinate vector regression. The experiments show that MSTPose outperforms other CNN-based pose estimation models and demonstrates clear advantages over CNN + Transformer networks of similar types.
Inductive Sintering of Silver Micro Particles for Bonding of Microelectronic Components
Authors: Rochala Patrick , Hofmann Christian , Kroll Martin , Panhale Sushant , Javed Rezan , Hiller Karla
Published: July 2023

In this article, an efficient die-bonding technology based on silver sintering due to induction heating is presented. By using this technology, the heat for the sintering reaction is locally limited to the bonding area and heating of the entire power module is avoided. Furthermore, the sintering reaction is promoted due to current flow between the silver particles, and the sintering time is drastically reduced. Next to the experimental trials presented in this paper, finite element (FE) simulation methods were applied to develop a suitable induction coil geometry for the bonding of a diode to a direct bonded copper (DBC) substrate. Additional heating and sintering tests verified the reliability of the simulation model as well as the technological approach. Diodes were successfully bonded during the experiments and were analyzed by means of scanning electron microscopy (SEM) and function tests to qualify the inductive bonding technology. The results presented in this paper demonstrate that induction heating has high potential for cost-effective production in the field of die attach and can drastically increase the output in power-electronics production.
Research Progress in Failure Mechanism and Health State Evaluation Index System of Welded IGBT Power Modules
Authors: Kang Yongqiang , Dang Luzhi , Yang Lei , Wang Zhaoyun , Meng Yu , Li Shuaibing , Sun Yapeng , Wang Youyun , Dong Haiying
Published: July 2023

As the performance requirements of insulated gate bipolar transistors (IGBTs) in various fields of power electronic systems are increasing, the IGBT power module package structure, aging mechanism analysis, and selection of health state characteristic parameters are of great significance to ensure the normal operation of power systems. At present, research on the aging failure of welded IGBT modules is relatively comprehensive and can be divided into chip aging failure and package aging failure according to their failure parts. However, there is some research on the relationship between aging failure and the characteristic quantity of power modules, but no definite system has been formed. Therefore, in this paper, the packaging structure of the solder-type IGBT modules and the aging mechanism caused by different aging reasons were summarized. Moreover, the health status monitoring of solder-type IGBT modules from the junction temperature, bonding line, solder layer, and package insulation aging health status monitoring and its quantitative assessment research progress was analyzed in detail. Also, the health state evaluation index system of the solder-type IGBT modules was completed on the basis of voltage, current, thermal, insulation parameters, and other characteristic quantities. Finally, based on the analysis of domestic and international research problems, the development trend and direction of the condition monitoring technology of solder-type IGBT modules is foreseen. The research on condition monitoring for welded IGBT module technology has a certain significance.
Joint Optimization of Computation, Communication and Caching in D2D-Assisted Caching-Enhanced MEC System
Authors: Ge Jiaqi , Xu Gaochao , Zhang Yang , Lu Jianchao , Chen Haihua , Meng Xiangyu
Published: July 2023

In the era of intelligent applications, Mobile Edge Computing (MEC) is emerging as a promising technology that provides abundant resources for mobile devices. However, establishing a direct connection to the MEC server is not always feasible for certain devices. This paper introduces a novel Device-to-Device (D2D)-assisted system to address this challenge. The system leverages idle helper devices to execute and offload tasks to the MEC server, thereby enhancing resource utilization and reducing offload time. To further minimize offloading time for latency-sensitive tasks, this paper incorporates edge caching. The problem is formulated by jointly optimizing computation, communication and caching, and a novel Joint Multiple Decision Optimization Algorithm (JMDOA) is proposed to solve the minimum-energy-consumption problem. Specifically, the JMDOA algorithm decomposes the integer-mixed non-convex optimization problem into two subproblems based on distinct properties of discrete variables. These subproblems are solved separately and optimized iteratively, ensuring convergence to a suboptimal solution. Simulations demonstrate the effectiveness and superiority of JMDOA, exhibiting lower energy consumption and reduced time compared to other baseline algorithms, approaching the optimum. This work contributes to the field by presenting a novel approach to optimizing resource allocation in MEC systems, with potential implications for the future development of intelligent applications.
Advanced Misinformation Detection: A Bi-LSTM Model Optimized by Genetic Algorithms
Authors: Al Bataineh Ali , Reyes Valeria , Olukanni Toluwani , Khalaf Majd , Vibho Amrutaa , Pedyuk Rodion
Published: July 2023

The proliferation of misinformation, as insidious and pervasive as water, presents an unprecedented challenge to public discourse and comprehension. Often propagated to further specific ideologies or political objectives, misinformation not only misleads the populace but also fuels online advertising revenue generation. As such, the urgent need to pinpoint and eliminate misinformation from digital platforms has never been more critical. In response to this dilemma, this paper proposes a solution built on the backbone of massive data generation in today’s digital landscape. By leveraging advanced technologies, such as AI-driven systems with deep learning models and natural language processing capabilities, we can monitor and analyze an extensive scope of social media data. This, in turn, facilitates the identification of misinformation across multiple platforms and alerts users to potential propaganda. Central to our study is the development of misinformation classifiers based on a deep bi-directional long short-term memory (Bi-LSTM) model. This model is further enhanced by employing a genetic algorithm (GA), which automates the search for an optimal neural architecture, thereby significantly impacting the training behavior of the deep learning algorithm and the performance of the model being trained. To validate our approach, we compared the efficacy of our proposed model with nine traditional machine learning algorithms and a deep learning model rooted in long short-term memory (LSTM). The results affirmed the superiority of our GA-tuned Bi-LSTM model, which outperformed all other models in detecting misinformation with remarkable accuracy. Our intention with this paper is not to present our model as a comprehensive solution to misinformation but rather as a technological tool that can aid in the process, supplementing and bolstering the existing methodologies in the field of misinformation detection.
Deep Learning-Based Attack Detection and Classification in Android Devices
Authors: Gómez Alfonso , Muñoz Antonio
Published: July 2023

The increasing proliferation of Androidbased devices, which currently dominate the market with a staggering 72% global market share, has made them a prime target for attackers. Consequently, the detection of Android malware has emerged as a critical research area. Both academia and industry have explored various approaches to develop robust and efficient solutions for Android malware detection and classification, yet it remains an ongoing challenge. In this study, we present a supervised learning technique that demonstrates promising results in Android malware detection. The key to our approach lies in the creation of a comprehensive labeled dataset, comprising over 18,000 samples classified into five distinct categories: Adware, Banking, SMS, Riskware, and Benign applications. The effectiveness of our proposed model is validated using well-established datasets such as CICMalDroid2020, CICMalDroid2017, and CICAndMal2017. Comparing our results with state-of-the-art techniques in terms of precision, recall, efficiency, and other relevant factors, our approach outperforms other semi-supervised methods in specific parameters. However, we acknowledge that our model does not exhibit significant deviations when compared to alternative approaches concerning certain aspects. Overall, our research contributes to the ongoing efforts in the development of advanced techniques for Android malware detection and classification. We believe that our findings will inspire further investigations, leading to enhanced security measures and protection for Android devices in the face of evolving threats.
Analysis of the Complex Three-Dimensional Flow Structure in the Circulation Pump of the Flow-Making System Based on Delayed Detached Eddy Simulation
Authors: Li Zhong , Ding Lei , Gong Weifeng , Ni Dan , Ma Cunzhi , Sun Yanna
Published: July 2023

As the core component of the flow-making system, the circulating pump has differences in its internal flow structure under different operating conditions, which affects the flow quality of the environmental simulation test area and the authenticity of marine environmental simulation. To explore the internal flow characteristics and outlet evolution characteristics of the circulating pump, this paper uses the DDES (delayed detached eddy simulation) method for numerical simulation. This paper combines BVF (boundary vorticity flow) diagnosis and the limit streamline method to analyze the evolution characteristics of the unstable flow area on the blade surface; it uses the Q criterion to identify the vortex structure inside the pump and analyze its evolution and development laws. Additionally, a quantitative analysis of the flow state of the circulating pump using flow uniformity indexes is performed. The results show that the surface of impeller blades is uniform under 1.0 QN. At 0.7 QN, the evolution process of the blade suction surface BVF is periodic, with a corresponding period of about 2/9 T (0.02 s). At 1.0 QN, the strength and scale of the separated vortices inside the guide vanes are minimized compared to other flow rates, and the scale and strength of the vortices show a decreasing trend along the outer normal direction. The evolution period of the separation vortex on the pressure surface of the guide vane is about 1/3 T (0.033 s) under 1.1 QN and the evolution period of the suction surface of the guide vane is about 2/3 T (0.067 s) under 0.7 QN. The flow uniformity indexes value downstream of the pump outlet under 1.0 QN are very close to the ideal value; with a corresponding value of Ϛi = 0.023, θ¯ = 89.94°, γ = 0.95, λ = 97.9%, the outflow can be approximately regarded as axial uniform flow. The research results can provide theoretical support for the further optimization design of circulating pumps and lay the foundation for the implementation of real systems.
Common Architectures and Devices for Current Source Inverter in Motor-Drive Applications: A Comprehensive Review
Authors: Fidone Giovanni Luca , Migliazza Giovanni , Carfagna Emilio , Benatti Dario , Immovilli Fabio , Buticchi Giampaolo , Lorenzani Emilio
Published: July 2023

When compared to the much more common voltage-source inverter (VSI), the current-source inverter (CSI) is rarely used for variable speed drive applications, due to its disadvantages: the need of a constant DC-link current, typically realized with a front-end converter, and the need for reverse-voltage blocking (RVB) devices, typically implemented with in-series diodes. This limits the overall efficiency of the architecture. This paper investigates latest progress of the CSI research, with the aim of demonstrating why CSI could come back in the near future. Different architectures based on modern wide-bandgap (WBG) switches are analyzed, with an emphasis on why CSI can be advantageous compared to VSI.
Study of Nitrogen Compound Migration during the Pyrolysis of Longkou Oil Shale with Thermal Bitumen as the Intermediate
Authors: Shi Jian , Yue Changtao , Hou Jili , Huang Jiayu , Cao Yali , Li Weimin , Li Shuyuan
Published: July 2023

Oil shale is an unconventional energy resource with high nitrogen content. In this study, XPS, GC–MS and ESI FT-ICR MS were carried out to investigate the nitrogen compound migration during pyrolysis, with thermal bitumen as the intermediate. The results showed that the yield of thermal bitumen was highest when the reaction temperature was 380 °C. In the process of pyrolysis, amines and some nitrides generate ammonia gas due to the hydrogen transfer process, or they generate low-grade amines, which subsequently dissolve in pyrolysis water due to bond breakage during the pyrolysis process. As determined by GC–MS analyses, the basic components in shale oil are mainly quinoline compounds. Benzocarbazole and dibenzocarbazole compounds, such as C1-benzocarbazoles, C2-benzocarbazoles and C3-benzocarbazoles, were detected via ESI FT-ICR MS in thermal bitumen.
Research on the Relationship between Pore Structure and the Compressive Strength of Oil-Well Cement
Authors: Zheng Guanyi , Sun Jinfei , Guo Xiaoyang , Li Zaoyuan
Published: July 2023

The integrity of wellbore cement is an important guarantee for the long-term safety and effectiveness of carbon dioxide geological storage. During the process of CO2 capture, utilization, and storage, construction factors will cause changes in temperature and pressure distribution, leading to changes in the pore structure of cement and a decline in compressive strength, which can easily cause the failure of cement ring integrity. To provide theoretical guidance and analysis methods for evaluating the mechanism of cement strength performance degradation and optimizing injection parameters, in this study, we conducted the following research based on relevant studies: (1) The fracture theory was revised based on the characteristic factors of oil-well cement; (2) a pore structure model was established to analyze the failure process of cement, clarifying the relationship between pore structure and the compressive strength of cement; (3) the parameters of the pore structure model were determined and analyzed, considering the influence of cement content and total porosity on the model, and finally, the regression parameter K value was determined to be 1600. This article can provide a useful reference for the research on the failure of cement rings in the CO2 injection process and other related studies.
A Surrogate Model of the Butler-Volmer Equation for the Prediction of Thermodynamic Losses of Solid Oxide Fuel Cell Electrode
Authors: Buchaniec Szymon , Gnatowski Marek , Hasegawa Hiroshi , Brus Grzegorz
Published: July 2023

Solid oxide fuel cells are becoming increasingly important in various applications, from households to large-scale power plants. However, these electrochemical energy conversion devices have complex behavior that is difficult to understand and optimize. A numerical simulation is a primary tool for analysis and optimization-design. One of the most significant challenges in this field is improving microscale transport phenomena and electrode reaction models. Two main categories of simulation are black-box and white-box models. The former requires large experimental datasets and lacks physical constraints, while the latter inherits the inaccuracy of typical electrochemical reaction models. Here we show a micro-scale artificial neural network-supported numerical simulation that allows for overcoming those issues. In our research, we substituted one equation in the system, an electrochemical model, with an artificial neural network prediction. The data-driven prediction is constrained and must satisfy all reminded balance equations in the system. The results show that the proposed model can simulate an anode-electrode’s thermodynamic losses with improved accuracy compared with the classical approach. The coefficient of determination R2 for the proposed model was equal to 0.8810 for 800 °C, 0.8720 for 900 °C, and 0.8436 for 1000 °C. The findings open a way for improving the accuracy and computational complexity of electrochemical models in solid oxide fuel cell simulations.
Evaluation Method of Internal Resistance for Repurposing Using Middle and Large-Sized Batteries
Authors: Lim Min-Gyu , Jung Jae-Beom , Kim Nam-Hyun , Kim Ji-Myung , Shen Jian , Rho Dae-Seok
Published: July 2023

The number of used batteries is expected to dramatically increase in the near future due to the expansion of the electric vehicle (EV) market globally. Accordingly, the Korean government has improved the supporting structures for the recycling system for used batteries, and in particular, in the field of repurposing, various studies are being conducted with a focus on effective evaluation methods that can secure the performance and safety of batteries after use. The repurposing of used batteries is mostly adapted in the field of energy storage systems for normally used EV batteries and a total inspection before repurposing is required due to battery characteristics that can vary depending on the operational environments of and accidents involving medium- and large-sized batteries for EVs and energy storage systems (ESSs) that have been occurring continuously for the past few years. Therefore, this paper investigates the operating mechanisms of the internal resistance test method and implements a test device for middle- and large-sized cells and packs. Based on the proposed test method, the internal resistance of nickel manganese cobalt (NMC)-type commercial large batteries is analyzed according to the SOC (state of charge), SOH (state of health), ambient temperature, and connection degradation of batteries. The distribution degrees of the alternative current (AC) internal resistance (IR) and direct current (DC) internal resistance (IR) measurement methods under state of health (SOH) test conditions are about 7% and 50%. It was found that the DC IR measurement method is more effective in diagnosing battery cell degradation. The distribution degree of DC IR measurements for the degraded connection condition shows an increase of less than 1% regardless of the state of charge (SOC), while the distribution degree of the AC IR measurements shows an increase of up to 319%, indicating that the AC IR method is more effective than the DC IR method in identifying connection degradation. It is confirmed that the proposed method is effective in internal resistance measurement and safety evaluations for the repurposing of batteries.
A Multi-Agent Reinforcement Learning Method for Cooperative Secondary Voltage Control of Microgrids
Authors: Wang Tianhao , Ma Shiqian , Tang Zhuo , Xiang Tianchun , Mu Chaoxu , Jin Yao
Published: July 2023

This paper proposes a novel cooperative voltage control strategy for an isolated microgrid based on the multi-agent advantage actor-critic (MA2C) algorithm. The proposed method facilitates the collaborative operation of a distributed energy system (DES) by adopting an attention mechanism to adaptively boost information processing effectiveness through the assignment of importance scores. Additionally, the algorithm we propose, executed through a centralized training and decentralized execution framework, implements secondary control and effectively restores voltage deviation. The introduction of an attention mechanism alleviates the burden of information transmission. Finally, we illustrate the effectiveness of the proposed method through a DES consisting of six energy nodes.
Influence of the Type of Receiver on Electrical Energy Losses in Power Grids
Authors: Kłosowski Zbigniew , Mazur Łukasz
Published: July 2023

The development of power electronics, including high-efficiency power supply systems, changes the structure of perception of the types of electrical energy receivers connected to the power grid at each supply voltage level. In the past, the dominant type of receivers were constant impedance devices. Currently, more and more devices have power supplies, which are most often constant power receivers. The construction and technological diversity of receivers allows mixed receivers, which are a combination of constant power and constant impedance receivers, to be distinguished. Therefore, there is a need to determine the impact of the type of electrical energy receivers on the power grid, both in the context of the operation of a single receiver and in the case of a branched power grid with a high penetration of distributed generation. This article will discuss the impact of the type of electrical energy receivers on the operation of the power grid, with particular emphasis on the issue of electrical energy losses at changing voltages. To determine the impact of receivers, simulation studies were performed based on two case stages: the first is a fragment of a low-voltage power grid in a household that supplies a heating device, which is analyzed as a different type of receiver; the second is a fragment of a low-voltage power grid with various types of consumers and photovoltaic installations. The research was carried out on the basis of the mathematical model of the low-voltage power network developed by the authors using the electric multipole method and Newton’s method. The obtained results show that the type of receiver may have an impact on electrical energy losses.
Hybrid Maximum Power Extraction Methods for Photovoltaic Systems: A Comprehensive Review
Authors: Liu Haoming , Khan Muhammad Yasir Ali , Yuan Xiaoling
Published: July 2023

To efficiently and accurately track the Global Maximum Power Point (GMPP) of the PV system under Varying Environmental Conditions (VECs), numerous hybrid Maximum Power Point Tracking (MPPT) techniques were developed. In this research work, different hybrid MPPT techniques are categorized into three types: a combination of conventional algorithms, a combination of soft computing algorithms, and a combination of conventional and soft computing algorithms are discussed in detail. Particularly, about 90 hybrid MPPT techniques are presented, and their key specifications, such as accuracy, speed, cost, complexity, etc., are summarized. Along with these specifications, numerous other parameters, such as the PV panel’s location, season, tilt, orientation, etc., are also discussed, which makes its selection easier according to the requirements. This research work is organized in such a manner that it provides a valuable path for energy engineers and researchers to select an appropriate MPPT technique based on the projects’ limitations and objectives.
Mining Technologies Innovative Development II: The Overview
Authors: Zhironkin Sergey , Szurgacz Dawid
Published: July 2023

Dear colleagues—readers and authors of Energies journal, we present the Special Issue “Mining Technologies Innovative Development II”, which continues the previous issue, developing the ideas of sustainable mining of fossil energy sources, concentrating around the innovative modernization of the mineral resource sector in the context of achieving sustainable development goals [...]
Pyrolysis of Energy Cane Bagasse: Investigating Kinetics, Thermodynamics, and Effect of Temperature on Volatile Products
Authors: Liborio Denisson O. , Gonzalez Juan F. , Arias Santiago , Mumbach Guilherme D. , Alves Jose Luiz F. , da Silva Jean C. G. , Silva Jose Marcos F. , Barbosa Celmy M. B. M. , Carvalho Florival R. , Soares Ricardo R. , Simões Diogo A. , Pacheco Jose Geraldo A.
Published: July 2023

Energy cane is a genotype derived from species of sugarcane (Saccharum officinarum and Saccharum spontaneum) with a lower sucrose content and higher fiber content for bioenergy purposes. It is a rustic plant that demands less fertile soils that do not compete with food crops. In this work, an analysis of energy cane bagasse pyrolysis products was performed, assessing the effect of reaction temperature and kinetic and thermodynamic parameters. Anhydrosugars, such as D-allose, were the primary compounds derived from the decomposition of energy cane at 500 °C. Methyl vinyl ketone and acetic acid were favored at 550 and 600 °C. At 650 °C, methyl glyoxal, acetaldehyde and hydrocarbons were favored. Among the hydrocarbons observed, butane, toluene and olefins such as 1-decene, 1-undecene, 1-tridecene and 1-tetradecene were the most produced. The Friedman isoconversional method was able to determine the average activation energies in the ranges 113.7−149.4, 119.9−168.0, 149.3−196.4 and 170.1−2913.9 kJ mol−1 for the decomposition of, respectively, pseudo-extractives, pseudo-hemicellulose, pseudo-cellulose and pseudo-lignin. The thermodynamic parameters of activation were determined within the ranges of 131.0 to 507.6 kJ mol−1 for ΔH, 153.7 to 215.2 kJ mol−1 for ΔG and −35.5 to 508.8 J mol−1 K−1 for ΔS. This study is very encouraging for the cultivation and use of high-fiber-content energy cane bagasse, after sucrose extraction, to produce biofuels as an alternative to the current method of conversion into electricity by low-efficiency burning.
Power Quality Analysis for Light-Duty Electric Vehicles: A Case Study in Malta
Authors: Scicluna Kris , Azzopardi Brian , Spiteri Kurt
Published: July 2023

This paper presents a power quality analysis for multiple electric vehicle charging stations of the AC-Level 2 type in a real-life case study. The data was collected with a power quality analyzer that measured the main distribution system feeding nine 7 kW charging stations in a commercial site with light-duty vehicles in Malta, Europe. The relevance of this study to the specific case of Malta is accentuated by the topological challenges of the country; high density of road vehicles, with 18,000 vehicles for each square kilometer; and ambitious targets of reaching carbon neutrality by 2050. Data were collected over six days on an actual charging system with real-life charging patterns. Various results are presented in this paper, including three-phase system voltages and currents, individual harmonic voltage and current components, total harmonic distortion and total current demand distortion. These measurements were compared with standardized thresholds for low-voltage equipment used in public spaces, mainly as stated in IEEE 519-2014.
Bioactive Compounds and Antioxidant Activity in Seeds of Bred Lines of Common Bean Developed from Interspecific Crosses
Authors: Suárez Juan Carlos , Polanía-Hincapié Paola Andrea , Saldarriaga Sebastian , Ramón-Triana Vivian Yorlady , Urban Milan O. , Beebe Stephen E. , Rao Idupulapati M.
Published: July 2023

Knowledge is limited about the level of bioactive compounds and antioxidant activity of seeds from bred lines of common beans developed from interspecific crosses using four different Phaseolus species (P. vulgaris L., P. coccineus L., P. acutifolius A. Gray. Gray., and P. dumosus). In this study, differences in the nutritional quality of seeds among 112 bean genotypes were evaluated by measuring the levels of phenolic compounds, pigments, antioxidant activity, and sugars. The bean genotypes were grown under high temperatures and acid soil conditions in the Amazon region of Colombia. Five typology groups of bean genotypes were identified based on the level of bioactive compounds and their functional capacity: (1) highly bioactive and functional (HBF); (2) moderately bioactive and functional (MBF); (3) moderate antioxidant content with pigment influence (MACP); (4) moderately antinutritional with limited antioxidant potential (MALAP); and (5) antinutritional, low bioactive, and functional (ALBF). We developed a nutritional quality index (NQI) with values ranging from 0 to 1 based on the nutritional and anti-nutritional balance of each genotype and the higher values of the NQI of a genotype indicating greater nutritional quality. We found three interspecific bred lines (SER 212, SER 213, and RRA 81), with NQI values higher than 0.8. These three lines belong to the typology group of HBF. The superior nutritional quality of these three interspecific bred lines is attributed to a greater level of bioactive compounds and antioxidant capacity. These three bred lines may serve as useful parents to develop nutritionally superior and stress-resilient beans from bean breeding programs. Further research is needed to explore the role of testa color in improving the nutritional quality of seeds of common bean genotypes grown under different climatic conditions.
The Comparative Effect of Lactic Acid Fermentation and Germination on the Levels of Neurotoxin, Anti-Nutrients, and Nutritional Attributes of Sweet Blue Pea (Lathyrus sativus L.)
Authors: Arshad Nimra , Akhtar Saeed , Ismail Tariq , Saeed Wisha , Qamar Muhammad , Özogul Fatih , Bartkiene Elena , Rocha João Miguel
Published: July 2023

Grass pea (Lathyrus sativus L.), an indigenous legume of the subcontinental region, is a promising source of protein and other nutrients of health significance. Contrarily, a high amount of β-N-oxalyl-l-α,β-diaminopropionic acid (β-ODAP) and other anti-nutrients limits its wider acceptability as healthier substitute to protein of animal and plant origin. This study was aimed at investigating the effect of different processing techniques, viz. soaking, boiling, germination, and fermentation, to improve the nutrient-delivering potential of grass pea lentil and to mitigate its anti-nutrient and toxicant burden. The results presented the significant (p < 0.05) effect of germination on increasing the protein and fiber content of L. sativus from 22.6 to 30.7% and 15.1 to 19.4%, respectively. Likewise, germination reduced the total carbohydrate content of the grass pea from 59.1 to 46%. The highest rate of reduction in phytic acid (91%) and β-ODAP (37%) were observed in germinated grass pea powder, whereas fermentation anticipated an 89% reduction in tannin content. The lactic acid fermentation of grass pea increased the concentration of calcium, iron, and zinc from 4020 to 5100 mg/100 g, 3.97 to 4.35 mg/100 g, and 3.52 to 4.97 mg/100 g, respectively. The results suggest that fermentation and germination significantly (p < 0.05) improve the concentration of essential amino acids including threonine, leucine, histidine, tryptophan, and lysine in L. sativus powder. This study proposes lactic acid fermentation and germination as safer techniques to improve the nutrient-delivering potential of L. sativus and suggests processed powders of the legume as a cost-effective alternative to existing plant proteins.
Effect of Storage Time on the Physical, Chemical, and Rheological Properties of Blueberry Jam: Experimental Measurements and Artificial Neural Network Simulation
Authors: Guimarães Daniela Helena Pelegrine , Ferreira Ana Lúcia Gabas , Arce Pedro Felipe
Published: July 2023

Reversible data hiding (RDH) is crucial in modern data security, ensuring confidentiality and tamper-proofness in various industries like copyright protection, medical imaging, and digital forensics. As technology advances, RDH techniques become essential, but the trade-off between embedding capacity and visual quality must be heeded. In this paper, the relative correlation between the pixel’s local complexity and its directional prediction error is employed to enhance an efficient RDH without using a location map. An embedding process based on multiple cumulative peak region localization (MCPRL) is proposed to hide information in the 3D-directional prediction error histogram with a lower local complexity value and avoid the underflow/overflow problems. The carrier image is divided into three color channels, and then each channel is split into two non-overlapping sets: blank and shadow. Two half-directional prediction errors (the blank set and the shadow set) are constructed to generate a full-directional prediction error for each color channel belonging to the host image. The local complexity value and directional prediction error are critical metrics in the proposed embedding process to improve security and robustness. By utilizing these metrics to construct a 3D stego-Blank Set, the 3D stego-shadow Set will be subsequently constructed using the 3D blank set. The proposed technique outperforms other state-of-the-art techniques in terms of embedding capacity, image quality, and robustness against attacks without an extra location map. The experimental results illustrate the effectiveness of the proposed method for various 3D RDH techniques.
Regulatory Effects Mediated by Enteromorpha prolifera Polysaccharide and Its Zn(II) Complex on Hypoglycemic Activity in High-Sugar High-Fat Diet-Fed Mice
Authors: Li Liyan , Li Yuanyuan , Wang Peng
Published: July 2023

In order to investigate and develop functional foods of marine origin with hypoglycemic activity, Enteromorpha prolifera polysaccharide–Zn(II) (EZ) complex was first prepared by marine resourced E. prolifera polysaccharide (EP) and ZnSO4 and their anti-diabetes activities against high-sugar and high-fat-induced diabetic mice were evaluated. The detailed structural characterization of EZ was elucidated by UV-Vis spectroscopy, infrared spectroscopy, and monosaccharide composition determination. The pharmacological research suggests that EZ has a potent hypoglycemic effect on high-sugar and high-fat-induced diabetic mice by inhibiting insulin resistance, improving dyslipidemia, decreasing inflammatory status, repairing pancreas damage, as well as activating the IRS/PI3K/AKT signaling pathway and regulating GLUT2 gene expression. At the same time, microbiota analysis indicates that a high dose of EZ could enhance the abundance of dominant species, such as Staphylococcaceae, Planococcaceae, Muribaculaceae, Aerococcaceae, and Lacrobacillaceae, in intestinal microbiota distribution. Thus, EZ could be considered as a potential candidate for developing an ingredient of functional foods for Zn(II) supplements with hypoglycemic activity.
Characteristics of Unripened Cow Milk Curd Cheese Enriched with Raspberry (Rubus idaeus), Blueberry (Vaccinium myrtillus) and Elderberry (Sambucus nigra) Industry By-Products
Authors: Starkute Vytaute , Lukseviciute Justina , Klupsaite Dovile , Mockus Ernestas , Klementaviciute Jolita , Rocha João Miguel , Özogul Fatih , Ruzauskas Modestas , Viskelis Pranas , Bartkiene Elena
Published: July 2023

The aim of this study was to apply raspberry (Ras), blueberry (Blu) and elderberry (Eld) industry by-products (BIB) for unripened cow milk curd cheese (U-CC) enrichment. Firstly, antimicrobial properties of the BIBs were tested, and the effects of the immobilization in agar technology on BIB properties were evaluated. Further, non-immobilized (NI) and agar-immobilized (AI) BIBs were applied for U-CC enrichment, and their influence on U-CC parameters were analyzed. It was established that the tested BIBs possess desirable antimicrobial (raspberry BIB inhibited 7 out of 10 tested pathogens) and antioxidant activities (the highest total phenolic compounds (TPC) content was displayed by NI elderberry BIB 143.6 mg GAE/100 g). The addition of BIBs to U-CC increased TPC content and DPPH− (2,2-diphenyl-1-picrylhydrazyl)-radical scavenging activity of the U-CC (the highest TPC content was found in C-RaNI 184.5 mg/100 g, and strong positive correlation between TPC and DPPH− of the U-CC was found, r = 0.658). The predominant fatty acid group in U-CC was saturated fatty acids (SFA); however, the lowest content of SFA was unfolded in C-EldAI samples (in comparison with C, on average, by 1.6 times lower). The highest biogenic amine content was attained in C-EldAI (104.1 mg/kg). In total, 43 volatile compounds (VC) were identified in U-CC, and, in all cases, a broader spectrum of VCs was observed in U-CC enriched with BIBs. After 10 days of storage, the highest enterobacteria number was in C-BluNI (1.88 log10 CFU/g). All U-CC showed similar overall acceptability (on average, 8.34 points); however, the highest intensity of the emotion “happy” was expressed by testing C-EldNI. Finally, the BIBs are prospective ingredients for U-CC enrichment in a sustainable manner and improved nutritional traits.
Sleep-Enhancing Effect of Water Extract from Jujube (Zizyphus jujuba Mill.) Seeds Fermented by Lactobacillus brevis L32
Authors: Bae Gi Yeon , Ahn Yejin , Hong Ki-Bae , Jung Eun-Jin , Suh Hyung Joo , Jo Kyungae
Published: July 2023

Although Ziziphus jujuba Mill (jujube) is used in folk medicine for hypnotic sedative, anxiolytic, and many other purposes, to date, only a few studies have revealed its sleep-promoting effects and related mechanisms. Currently, drugs used for the treatment of sleep disorders have various side effects, so it is essential to develop safe natural materials. Therefore, we evaluated the sleep-enhancing activity and mechanism of action of an aqueous extract of jujube seeds (ZW) fermented with Lactobacillus brevis L-32 in rodent models. The starch contained in ZW was removed by enzymatic degradation and fermented with L. brevis to obtain a fermented product (ZW-FM) with a high γ-aminobutyric acid (GABA) content. To evaluate the sleep-promoting effect of ZW-FM, pentobarbital-induced sleep tests were performed on ICR mice, and electroencephalography analysis was undertaken in Sprague Dawley rats. Additionally, the awakening relief effects of ZW-FM were confirmed in a caffeine-induced insomnia model. Finally, the mechanism of sleep enhancement by ZW-FM was analyzed using GABA receptor type A (GABAA) antagonists. The ZW-FM-treated groups (100 and 150 mg/kg) showed increased sleep time, especially the δ-wave time during non-rapid eye movement (NREM) sleep. In addition, the 150 mg/kg ZW-FM treatment group showed decreased sleep latency and increased sleep time in the insomnia model. In particular, NREM sleep time was increased and REM sleep time, which was increased by caffeine treatment, was decreased by ZW-FM treatment. ZW-FM-induced sleep increase was inhibited by the GABAA receptor antagonists picrotoxin, bicuculline, and flumazenil, confirming that the increase was the result of a GABAergic mechanism. These results strongly suggest that the increased GABA in water extract from jujube seeds fermented by L. brevis acts as a sleep-promoting compound and that the sleep-promoting activity is related to GABAA receptor binding.
Thermal Characterisation and Isoconversional Kinetic Analysis of Osmotically Dried Pork Meat Proteins Longissimus dorsi
Authors: Ostojić Sanja , Micić Darko , Zlatanović Snežana , Lončar Biljana , Filipović Vladimir , Pezo Lato
Published: July 2023

The kinetic properties and thermal characteristics of fresh pork meat proteins (Longissimus dorsi), as well as osmotically dehydrated meat proteins, were investigated using differential scanning calorimetry. Two isoconversional kinetical methods, namely the differential Friedman and integral Ortega methods, were employed to analyze the data. The obtained kinetic triplet, activation energy, pre-exponential factor, and extent of conversion, has been discussed. The resulting activation energy for proteins of fresh meat ranges between 751 kJmol−1 for myosin, 152 kJmol−1 for collagen and sarcoplasmic proteins, and 331 kJmol−1 for actin at a conversion degree of 0.1 to 0.9. For osmotically dried pork meat proteins, the values range from 307 kJmol−1 for myosin 272 kJmol−1 for collagen and sarcoplasmic proteins, and 334.83 kJmol−1 for actin at a conversion degree from 0.1 to 0.9. The proteins of the dry meat obtained by osmotic dehydration in molasses could be described as partly unfolded as they retain the characteristic protein denaturation transition. Concerning the decrease in enthalpies of proteins denaturation, thermodynamic destabilization of dried meat proteins occurred. On the contrary, dried meat proteins were thermally stabilized with respect to increase in the temperatures of denaturation. Knowledge of the nature of meat protein denaturation of each kind of meat product is one of the necessary tools for developing the technology of meat product processing and to achieve desired quality and nutritional value. The kinetic analysis of meat protein denaturation is appropriate because protein denaturation gives rise to changes in meat texture during processing and directly affects the quality of product.
Influence of Flow Rate, Particle Size, and Temperature on Espresso Extraction Kinetics
Authors: Schmieder Benedikt K. L. , Pannusch Verena B. , Vannieuwenhuyse Lara , Briesen Heiko , Minceva Mirjana
Published: July 2023

Brewing espresso coffee (EC) is considered a craft and, by some, even an art. Therefore, in this study, we systematically investigated the influence of coffee grinding, water flow rate, and temperature on the extraction kinetics of representative EC components, employing a central composite experimental design. The extraction kinetics of trigonelline, caffeine, 5-caffeoylquinic acid (5-CQA), and Total Dissolved Solids (TDS) were determined by collecting and analyzing ten consecutive fractions during the EC brewing process. From the extraction kinetics, the component masses in the cup were calculated for Ristretto, Espresso, and Espresso Lungo. The analysis of the studied parameters revealed that flow rate had the strongest effect on the component mass in the cup. The intensity of the flow rate influence was more pronounced at finer grindings and higher water temperatures. Overall, the observed influences were minor compared to changes resulting from differences in total extracted EC mass.
Discrete q-Exponential Limit Order Cancellation Time Distribution
Authors: Gontis Vygintas
Published: July 2023

Modeling financial markets based on empirical data poses challenges in selecting the most appropriate models. Despite the abundance of empirical data available, researchers often face difficulties in identifying the best fitting model. Long-range memory and self-similarity estimators, commonly used for this purpose, can yield inconsistent parameter values, as they are tailored to specific time series models. In our previous work, we explored order disbalance time series from the broader perspective of fractional L’evy stable motion, revealing a stable anti-correlation in the financial market order flow. However, a more detailed analysis of empirical data indicates the need for a more specific order flow model that incorporates the power-law distribution of limit order cancellation times. When considering a series in event time, the limit order cancellation times follow a discrete probability mass function derived from the Tsallis q-exponential distribution. The combination of power-law distributions for limit order volumes and cancellation times introduces a novel approach to modeling order disbalance in the financial markets. Moreover, this proposed model has the potential to serve as an example for modeling opinion dynamics in social systems. By tailoring the model to incorporate the unique statistical properties of financial market data, we can improve the accuracy of our predictions and gain deeper insights into the dynamics of these complex systems.
U-Pb Zircon Geochronology of Detrital and Ash Fall Deposits of the Southern Paraná Basin: A Contribution for Provenance, Tectonic Evolution, and the Paleogeography of the SW Gondwana
Authors: Philipp Ruy Paulo , Faccini Ubiratan Ferrucio , Schultz Cesar Leandro , Zvirtes Gustavo , Bruckmann Matheus Philippe , Lavina Ernesto , Cagliari Joice , Jelinek Andrea Ritter , Netto Renata Guimarães , Viana Adriano Roessler , Basei Miguel Angelo Stipp
Published: July 2023

Zircon U-Pb geochronology was applied to investigate the provenance, depositional ages, and paleogeography of the southwestern Gondwana in detrital and ash fall sediments from Carboniferous to Jurassic succession of the southern Paraná Basin. Four detrital age populations suggest provenance from local and distal sources located to the south, southeast, and southwest: (i) Archean to Paleoproterozoic zircons from the Rio de La Plata Craton, Nico Peres and Taquarembó terranes; (ii) Grenvillian zircons from the basement of the Gondwanides and Namaqua–Natal belts; (iii) Neoproterozoic grains from the Don Feliciano Belt; and (iv) Phanerozoic populations from Paleozoic orogenic belts and related foreland systems in Argentina, as well as eroded units of the Paraná Basin. The paleogeographic reconstruction indicates an evolution in three distinct stages: (1) a gulf open to the Panthalassa Ocean during the Carboniferous; (2) an epicontinental sea with the rise of the Gondwanides Orogeny during the Permian; and (3) continental deposits controlled by an intra-plate graben system during the Triassic. Permian–Triassic volcanogenic zircons provide constrained maximum depositional ages and attested persistent volcanism, related to the Choiyoi magmatism and effects of the climate change episodes. During the Triassic, the extensional graben system recorded the uplift of the basement through regional northwest and northeast fault systems, and the recycling of Permian zircons, modifying source-to-sink relationships.