bluuebunny/crossref_metadata_2025 huggingface dataset:
Breast Cancer Diagnosis Using Extended-Wavelength–Diffuse Reflectance Spectroscopy (EW-DRS)—Proof of Concept in Ex Vivo Breast Specimens Using Machine Learning
Authors: Chaudhry Nadia , Albinsson John , Cinthio Magnus , Kröll Stefan , Malmsjö Malin , Rydén Lisa , Sheikh Rafi , Reistad Nina , Zackrisson Sophia
Published: September 2023

This study aims to investigate the feasibility of using diffuse reflectance spectroscopy (DRS) to distinguish malignant breast tissue from adjacent healthy tissue, and to evaluate if an extended-wavelength range (450–1550 nm) has an advantage over the standard wavelength range (450–900 nm). Multivariate statistics and machine learning algorithms, either linear discriminant analysis (LDA) or support vector machine (SVM) are used to distinguish the two tissue types in breast specimens (total or partial mastectomy) from 23 female patients with primary breast cancer. EW-DRS has a sensitivity of 94% and specificity of 91% as compared to a sensitivity of 40% and specificity of 71% using the standard wavelength range. The results suggest that DRS can discriminate between malignant and healthy breast tissue, with improved outcomes using an extended wavelength. It is also possible to construct a simple analytical model to improve the diagnostic performance of the DRS technique.
Determinant Factors of M&As in Emerging Economies: The Impact of Financial Performance in Romanian Minority Acquisitions
Authors: Maha Liviu-George , Aevoae George-Marian , Viorică Elena-Daniela , Dicu Roxana-Manuela
Published: September 2023

The paper aims at describing two dimensions of acquirers’ behaviour when purchasing minority shares in Romanian listed target companies, based on a sample of 710 Romanian minority acquisitions. The first dimension regards the acquirer’s decision to invest a certain amount, being influenced by the profitability of the target company The relationship was found to be positive and significant. To test the model further, a sample of 308 transactions was used, after excluding the transactions involving primary sector and blue-chip target companies. The second dimension focuses on the amount of purchased stake, which leads to either financial gains or the takeover intention, under the influence of the target company’s operational profit. The results show a positive and significant relationship for the small stakes and a non-significant one for the high stakes.
Rotation of 3D Anatomy Models Is Associated with Underperformance of Students with Low Visual-Spatial Abilities: A Two-Center Randomized Crossover Trial
Authors: Leeuwen Bo S. van , Dollé Anna E. D. , Vernooij Johannes C. M. , Hierck Beerend P. , Salvatori Daniela C. F.
Published: September 2023

Virtual 3D models can be an animal-free alternative to cadaveric dissection to learn spatial anatomy. The aim of this study was to investigate if the learning outcome differs when studying 3D models with a 360° rotatable interactive monoscopic 3-dimensional (iM3D) or an interactive monoscopic 2-dimensional (iM2D) visualization, and whether the level of visual-spatial ability (VSA) influences learning outcome. A two-center randomized crossover trial was conducted during the Laboratory Animals Science Course (March 2021–March 2022). Participants studied a 3D rat model using iM3D and iM2D. VSA was assessed by a 24-item mental rotation test and learning outcome by two knowledge tests. Data from 69 out of 111 recruited participants were analyzed using linear regression. Participants with low VSA performed significantly worse compared to participants with medium or high VSA when using iM3D, but equally well when using iM2D. When VSA level was disregarded, participants performed equally well with both visualizations. Rotation in iM3D requires the student to construct a mental 3D image from multiple views. This presumably increases cognitive load, especially for students with low VSA who might become cognitively overloaded. Future research could focus on adapting the visualization technique to students’ personal needs and abilities.
MASA: Multi-Application Scheduling Algorithm for Heterogeneous Resource Platform
Authors: Peng Quan , Wang Shan
Published: September 2023

Heterogeneous architecture-based systems-on-chip enable the development of flexible and powerful multifunctional RF systems. In complex and dynamic environments where applications arrive continuously and stochastically, real-time scheduling of multiple applications to appropriate processor resources is crucial for fully utilizing the heterogeneous SoC’s resource potential. However, heterogeneous resource-scheduling algorithms still face many problems in practical situations, including generalized abstraction of applications and heterogeneous resources, resource allocation, efficient scheduling of multiple applications in complex mission scenarios, and how to ensure the effectiveness combining with real-world applications of scheduling algorithms. Therefore, in this paper, we design the Multi-Application Scheduling Algorithm, named MASA, which is a two-phase scheduler architecture based on Deep Reinforcement Learning. The algorithm is made up of neural network scheduler-based task prioritization for dynamic encoding of applications and heuristic scheduler-based task mapping for solving the processor resource allocation problem. In order to achieve stable and fast training of the network scheduler based on the actor–critic strategy, we propose optimization methods for the training of MASA: reward dynamic alignment (RDA), earlier termination of the initial episodes, and asynchronous multi-agent training. The performance of the MASA is tested with classic directed acyclic graph and six real-world application datasets, respectively. Experimental results show that MASA outperforms other neural scheduling algorithms and heuristics, and ablation experiments illustrate how these training optimizations improve the network’s capacity.
Power Injection and Free Resonance Decoupled Wireless Power Transfer System with Double-Switch
Authors: Wu Wei , Luo Daqing , Tang Zhe , Hong Jianfeng , Yang Junjie
Published: September 2023

This article presents a type of power injection and free resonance decoupled wireless power transfer (WPT) system, the double-switch independent power injection and free resonance wireless power transfer (IPIFR-WPT) system working in CCM. Based on the stroboscopic mapping model, the theoretical results show that the operation point of the proposed WPT system is determined by itself instead of the switching control strategy. Specifically, once the voltage on the primary capacitance does not decrease to the input voltage in the free-resonance process, the diode in series would not turn on and the system would not switch to the power injection process. Therefore, there is a wide soft-switching margin to ensure the system operating in soft-switching states. Another characteristic of the proposed WPT system is the monotonicity between output power and operation cycle, which presents a simple power control method. And since the soft-switching margin may have intersection under dynamic coupling coefficient, the proposed system maintains soft-switching states with a fixed switching strategy and presents advantage to resist the dynamic change of coupling coefficient. All the characteristics of the proposed WPT system mentioned above have been verified in both theory and experiment.
High-Resistance Grounding Fault Detection and Line Selection in Resonant Grounding Distribution Network
Authors: Yang Dong , Lu Baopeng , Lu Huaiwei
Published: September 2023

The detection and selection of fault lines in resonant grounding distribution networks pose challenges due to the lack of sufficient state parameters and data. This paper proposes an approach to overcome these limitations by reconstructing the initial criterion for fault occurrence and fault line selection. Firstly, a combination of 15% of the traditional phase voltage and the sum of the zero-sequence voltage gradient is suggested as the initial criterion for fault occurrence. This improves the speed of the line selection device. Additionally, the transient process of high-resistance grounding in a resonant grounding system is analyzed based on the impedance characteristics of high- and low-frequency lines. The line selection criterion is then established by comparing the current and voltage derivative waveforms on high- and low-frequency lines. To verify the effectiveness of the proposed method, simulations are conducted. The results demonstrate that this method can effectively handle high-resistance grounding faults under complex conditions while meeting the required speed for line selection.
A Capacitorless LDO Regulator with Fast Feedback Loop and Damping-Factor-Control Frequency Compensation
Authors: Ning Yongkai , Guo Jiangfei , Jia Yangchen , Li Duosheng , Guo Guiliang
Published: September 2023

A fast feedback loop (FFL) based on comparators is proposed in this paper. The FFL improves the transient response characteristics of the output-capacitorless low-dropout (OCL-LDO) regulator. When the load current switches between 1 mA and 100 mA with 1 μs edge time, the overshoot and undershoot are 33 mV and 37 mV, respectively, and recovery time is 1.2 μs and 1.6 μs, respectively. A damping-factor-control (DFC) frequency compensation circuit is used to ensure the stability of the OCL-LDO, and the simulation results show that the phase margin exceeds 50 degree in the entire load variation range. This design is based on 180 nm process, and the area of the chip is 0.068 mm2 (without pads). A band-gap reference circuit is also designed in this work; its output voltage is 1.2 V and its temperature coefficient is 7.96 ppm/∘C. The input voltage range of the proposed OCL-LDO is 2.5 V to 5 V with a linear regulation rate of 0.128 mV/V and a load regulation rate of 0.0017 mV/mA. In addition, the load range of the proposed OCL-LDO is 0 mA to 100 mA, and the minimum required external capacitance is 0 F. The power supply rejection ratio (PSRR) is −46 dB @ 1 kHz.
Circuit Design of 3- and 4-Bit Flash Analog-to-Digital Converters Based on Memristors
Authors: Dai Guangzhen , Du Xingyan , Xie Wenxin , Ni Tianming , Han Mingjun , Wu Daohua
Published: September 2023

Given its advantageous power- and area-efficiency characteristics and its compatibility with traditional CMOS technology, the memristor has emerged as a promising candidate for low-power applications. To leverage these capacities, a new edge-triggered DFF was proposed, feeding back the master latches’ output to the input of the memristor-based NOR two-stage inverse-phase memristor-based master–slave DFF. Then, a 3-bit flash ADC was designed using the new DFF and simulated to demonstrate its feasibility and correctness. Additionally, a 4-bit flash ADC was implemented and utilized to sample an analog signal, resulting in a correct digital signal. Herein, the 50 nm BSIM4 models were applied. The 3- and 4-bit flash ADCs, respectively, consumed 1.33 mw and 5.84 mw power at a 1 V supply with delay times of 17.8 ns and 70 ns. Compared with previous work, the new 4-bit flash ADC has fewer transistors and smaller power consumption, with about a 25.57% reduction according to the 90 nm process.
Hardware and Software Implementation of the Embedded Controlling System for the TuMag Camera
Authors: Rodríguez Valido Manuel , Orozco Suárez David , Hernández Exposito David , Magdaleno Castelló Eduardo , Ruiz Cobo Basilio
Published: September 2023

The main objective of this paper is to present the design and implementation of an embedded controlling system for the Tunable Magnetograph (TuMag) instrument camera sensor and test-bench software application for camera laboratory characterization. The TuMag camera is based on a new scientific sensor GPIXEL SENSE400 device family equipped with an FPGA. The camera sensor has an active area of 2048 × 2048 pixels and reaches a frame rate of up to 48 frames per second. The embedded controlling system was implemented on an Artix 7 FPGA, which oversees controlling the image sensor through a configuration interface. It controls the read-out of the sensor data and the communication of commands with the host device. The camera has a standard CoaXPress communication interface of up to 3125 Gbps. The FPGA embedded control system allows bit, word, and serial channel calibration and the modification of several parameters, such as the region of interest (RoI) size, exposition time, hardware or software trigger, single or continuous acquisition modes, sensor gain, and adjustment of the black level offset and exposition time. In addition, the firmware has a temperature controller, voltage level monitoring, and an enable–disable power sensor. In addition, the test-bench software application is a library developed in Python 3.7. It is a wrapper for the standard GeniCan commercial frame grabber interpreter. This wrapper permits the improvement of the interaction and interface between the user and the hardware in the camera calibration. The test-bench software application permits the reduction of costs and the transport risk of the TuMag camera between different laboratories. All TuMag embedded control systems and test-bench software application functionalities were successfully tested according to scientific requirements.
Enhancing CNNs Performance on Object Recognition Tasks with Gabor Initialization
Authors: Rivas Pablo , Rai Mehang
Published: September 2023

The use of Gabor filters in image processing has been well-established, and these filters are recognized for their exceptional feature extraction capabilities. These filters are usually applied through convolution. While convolutional neural networks (CNNs) are designed to learn optimal filters, little research exists regarding any advantages of initializing CNNs with Gabor filters. In this study, the performance of CNNs initialized with Gabor filters is compared to traditional CNNs with random initialization on six object recognition datasets. The results indicated that the Gabor-initialized CNNs outperformed the traditional CNNs in terms of accuracy, area under the curve, minimum loss, and convergence speed. A statistical analysis was performed to validate the performance of the classifiers, and the results showed that the Gabor classifiers outperformed the baseline classifiers. The findings of this study provide robust evidence in favor of using Gabor-based methods for initializing the receptive fields of CNN architectures.
A Fog-Based Privacy-Preserving Federated Learning System for Smart Healthcare Applications
Authors: Butt Maryum , Tariq Noshina , Ashraf Muhammad , Alsagri Hatoon S. , Moqurrab Syed Atif , Alhakbani Haya Abdullah A. , Alduraywish Yousef A.
Published: September 2023

During the COVID-19 pandemic, the urgency of effective testing strategies had never been more apparent. The fusion of Artificial Intelligence (AI) and Machine Learning (ML) models, particularly within medical imaging (e.g., chest X-rays), holds promise in smart healthcare systems. Deep Learning (DL), a subset of AI, has exhibited prowess in enhancing classification accuracy, a crucial aspect in expediting COVID-19 diagnosis. However, the journey to harness DL’s potential is rife with challenges: notably, the intricate landscape of medical data privacy. Striking a balance between utilizing patient data for insights while upholding privacy is formidable. Federated Learning (FL) emerges as a solution by enabling collaborative model training across decentralized data sources, thus bypassing data centralization and preserving data privacy. This study presents a tailored, collaborative FL architecture for COVID-19 screening via chest X-ray images. Designed to facilitate cooperation among medical institutions, the framework ensures patient data remain localized, eliminating the need for direct data sharing. Addressing imbalanced and non-identically distributed data, the architecture is a robust solution. Implementation entails localized and fog-computing-based FL models. Localized models utilize Convolutional Neural Networks (CNNs) on institution-specific datasets, while the FL model, refined iteratively, takes precedence in the final classification. Intriguingly, the global FL model, fortified by fog computing, emerges as the frontrunner in classification after weight refinement, surpassing local models. Validation within the COLAB platform gauges the model’s performance through metrics such as accuracy, precision, recall, and F1-score. Remarkably, the proposed model excels across these metrics, solidifying its efficacy. This research navigates the confluence of AI, FL, and medical imaging, unveiling insights that could reshape healthcare delivery. The study enriches scientific discourse by addressing data privacy in collaborative learning and carries potential implications for enhanced patient care.
An Indoor Tags Position Perception Method Based on GWO–MLP Algorithm for RFID Robot
Authors: Wang Honggang , Zhang Yu , Li Sicheng , Huang Qinyan , Pan Ruoyu , Pang Shengli , Yang Jingfeng
Published: September 2023

This paper proposes a tag position perception method for scenarios such as package retrieval in unmanned warehouses and book management in libraries. This method can accurately predict the distribution of tag space positions in real–time during RFID robot inventory. Firstly, the signal strength (RSSI) and speed of identification (SoI) are used as features. The grey wolf optimization multi–layer perceptron neural network model (GWO–MLP) is employed to predict the distance of tag groups. Secondly, a tag orientation prediction algorithm is designed to estimate the orientation of the tag groups. Finally, the periodicity of the phase is determined by the characteristic of RSSI attenuation as the tag–to–antenna distance increases, solving the problem of position ambiguity caused by phase periodicity. The experiment has shown that this method achieves a high accuracy rate of 96.67% and 97% in predicting the distance and orientation of tag groups, respectively. The average error in distance perception for the single tag is less than 3 cm, enabling precise perception of RFID tag positions. This method facilitates more efficient operation management and accurate item traceability.
Flavor Characteristics of Navel Orange Wine Fermented by Saccharomyces cerevisiae SC-125 and Angel Yeast SY
Authors: Zhang Yingyue , Ye Hong , Zou Yuting , He Zihan , Xu Bitao , Wang Su , Peng Chuanning , Zhou Xuerui , Zhang Qing , Xiang Wenliang , Cai Ting , Tang Jie
Published: September 2023

This research utilized Jintang navel oranges as the primary raw material, and employed two distinct yeast strains, Saccharomyces cerevisiae SC-125 and Angel yeast SY, for a dual fermentation approach. Employing single-strain fermentation as the control, this study aims to ascertain the physicochemical markers, alterations in organic acids and amino acids, alongside the antioxidant properties throughout the fermentation process, all within an optimized environment. The characterization of flavor compounds in the navel orange wines subjected to diverse yeast strains and mixed fermentation was conducted using headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry (HP-SPME/GC-MS). This method facilitated the identification of flavor compound types and concentrations. Moreover, electronic sensory systems including electronic noses and electronic eyes were harnessed to discern distinctions among various navel orange wines. Through these techniques, the research aimed to elucidate the variances induced by different yeast strains during both individual and mixed fermentation processes, shedding light on their impacts on the ultimate quality of navel orange wines.
Fermentative Production of L-Theanine in Escherichia coli via the Construction of an Adenosine Triphosphate Regeneration System
Authors: Cao Ruiqi , Hu Shunyang , Lu Yao , Wang Wei , Fu Zhongdan , Cheng Jie
Published: September 2023

Theanine is a non-protein amino acid that is highly represented in tea plants and is one of the delicious ingredients in tea. In recent years, the global market demand for theanine has continued to rise, and the industry has developed rapidly. Here, we designed and constructed a promising pathway in Escherichia coli to produce L-theanine. This biosynthesis pathway employs four enzymes to achieve the production of L-theanine. This route involves the co-expression of four functional enzymes: γ-glutamylmethylamide synthetase (GMAS) from Methyloversatilis universalis, polyphosphate kinase (PPK) from E. coli, alanine transaminase from Bacillus subtilis (BsAld), and alanine decarboxylase from Camellia sinensis (CsAlaDC). Polyphosphate kinase from Escherichia coli was overexpressed in E. coli FD02, constructing an ATP regeneration system that increased the titer of L-theanine by 13.4% compared to E. coli FD01. A titer of 334 mg/L of L-theanine was produced via engineering strain FD03 in shake flasks. Moreover, glutamine permease from Saccharomyces cereviside (GNP1) was overexpressed in E. coli FD04, and the L-theanine titer increased by 14.7%. Finally, 2.9 g/L of L-theanine was obtained via FD04 in a 1 L bioreactor. In addition, the molecular docking results indicated that L-glutamate could bind to the hydrophobic cavity of GMAS due to the formation of hydrogen bonds and hydrophobic interactions with the surrounding amino acid residues.
Detecting Japanese Eels (Anguilla japonica) and Revealing Their Distribution in Taiwanese Rivers by Environmental DNA Analysis
Authors: Hsu Hsiang-Yi , Wu Kai-Jen , Han Yu-San
Published: September 2023

The Japanese eel (Anguilla japonica) is the most prevalent freshwater eel species in Taiwan. However, its population has undergone a significant decline in recent decades due to factors such as overfishing, habitat destruction, and the effects of climate change. Urgent action is needed to conserve this species. Before implementing conservation measures, it is imperative to ascertain the distribution of Japanese eels in Taiwan’s rivers. This study’s primary objective was to assess the effectiveness of eDNA analysis as a method for detecting Japanese eels. To achieve this goal, we compared eDNA analysis data with results obtained from electrofishing, with the Fengshan and Shimen Rivers serving as our designated test sites. Additionally, we collected water samples from 34 other rivers across Taiwan to comprehensively assess the species’ wider distribution using eDNA analysis. Our findings demonstrated eDNA analysis’s viability for detecting Japanese eels. Of the 36 rivers tested, Japanese eel DNA was detected in samples from 21 rivers, scattered across northern, eastern, southern, and western Taiwan, with no specific concentration in any region. We also noted reduced detectability of Japanese eel DNA in highly polluted rivers, indicating that river pollution may have a potential impact on their population. In the future, expanding eDNA analysis to more rivers could identify additional rivers that Japanese eels inhabit. Subsequently, resource management and conservation efforts can be focused on these identified habitats. Furthermore, developing advanced eDNA-based methods for estimating the abundance or biomass of Japanese eels could enhance the flexibility of management and conservation measures.
Implications of Warming on the Morphometric and Reproductive Traits of the Green Crab, Carcinus maenas
Authors: Monteiro João N. , Bueno-Pardo Juan , Pinto Miguel , Pardal Miguel A. , Martinho Filipe , Leitão Francisco
Published: September 2023

Understanding the relationship between environmental temperature and the biological traits of organisms is fundamental to inferring the potential impacts of climate change. In the case of marine poikilotherm species, seawater temperature is one of the main driving forces of biological processes, with consequences at higher levels of organization such as population and ecosystem. In this study, we analysed differences in maximum carapace width (CWmax), size at maturation, relative size at maturation, and duration of the reproductive season for the green crab (Carcinus maenas) along a temperature gradient. An extensive review of bibliographic data was performed on studies published between 1962 and 2020, gathering C. maenas data from 55 different populations, spread over 20 degrees of latitude and 14.2 °C of sea surface temperature (SST). In addition, green crab data were collected at five different lagoons and estuaries along the continental Portuguese coast. The relationship between average SST and CWmax, age of maturation, reduction of size at maturation, and duration of egg bearing was analysed to understand the role of SST in driving variation in these C. maenas characteristics across a latitudinal gradient. There was a significant relationship between SST and CWmax for males and SST and CW of females at maturation, respectively. The results extrapolate for each local projected temperature increase caused by climate change and suggest an effect on the morphometric and reproductive traits of C. maenas across regions. These changes comprise an overall reduction in C. maenas body size, an enlargement of the reproductive season, a shortening in the duration of larval developmental time, and a decrease in the relative size of crabs at maturation. Secondary consequences on the fecundity and connectivity of populations are discussed.
Adulteration Detection of Pork in Mutton Using Smart Phone with the CBAM-Invert-ResNet and Multiple Parts Feature Fusion
Authors: Bai Zongxiu , Zhu Rongguang , He Dongyu , Wang Shichang , Huang Zhongtao
Published: September 2023

To achieve accurate detection the content of multiple parts pork adulterated in mutton under the effect of mutton flavor essence and colorant by RGB images, the improved CBAM-Invert-ResNet50 network based on the attention mechanism and the inversion residual was used to detect the content of pork from the back, front leg, and hind leg in adulterated mutton. The deep features of different parts extracted by the CBAM-Invert-ResNet50 were fused by feature, stitched, and combined with transfer learning, and the content of pork from mixed parts in adulterated mutton was detected. The results showed that the R2 of the CBAM-Invert-ResNet50 for the back, front leg, and hind leg datasets were 0.9373, 0.8876, and 0.9055, respectively, and the RMSE values were 0.0268 g·g−1, 0.0378 g·g−1, and 0.0316 g·g−1, respectively. The R2 and RMSE of the mixed dataset were 0.9264 and 0.0290 g·g−1, respectively. When the features of different parts were fused, the R2 and RMSE of the CBAM-Invert-ResNet50 for the mixed dataset were 0.9589 and 0.0220 g·g−1, respectively. Compared with the model built before feature fusion, the R2 of the mixed dataset increased by 0.0325, and the RMSE decreased by 0.0070 g·g−1. The above results indicated that the CBAM-Invert-ResNet50 model could effectively detect the content of pork from different parts in adulterated mutton as additives. Feature fusion combined with transfer learning can effectively improve the detection accuracy for the content of mixed parts of pork in adulterated mutton. The results of this study can provide technical support and a basis for maintaining the mutton market order and protecting mutton food safety supervision.
Multi-Faceted Bioactivity Assessment of an Exopolysaccharide from Limosilactobacillus fermentum NCDC400: Antioxidant, Antibacterial, and Immunomodulatory Proficiencies
Authors: Kumari Manorama , Haranahalli Nataraj Basavaprabhu , Prasad Writdhama G. , Ali Syed Azmal , Behare Pradip V.
Published: September 2023

Exopolysaccharides (EPS) are acknowledged for their diverse functional and technological properties. This study presents the characterization of EPS400, an acidic exopolysaccharide sourced from the native probiotic Limosilactobacillus fermentum NCDC400. Notably, this strain has demonstrated previous capabilities in enhancing dairy food texture and displaying in vivo hypocholesterolemic activity. Our investigation aimed to unveil EPS400′s potential biological roles, encompassing antioxidant, antibacterial, and immunomodulatory activities. The results underscore EPS400′s prowess in scavenging radicals, including the 2,2-diphenyl-1-picrylhydrazyl radical, 2,2′-azino-di-(3-ethylbenzthiazoline sulfonic acid) radical, superoxide radical, hydroxyl radical, and chelating activity targeting the ferrous ion. Furthermore, EPS400 displayed substantial antibacterial effectiveness against prevalent food spoilage bacteria such as Pseudomonas aeruginosa NCDC105 and Micrococcus luteus. Remarkably, EPS400 exhibited the ability to modulate cytokine production, downregulating pro-inflammatory cytokines TNF-α, IL-1β, IL-6, and nitric oxide, while concurrently promoting the release of anti-inflammatory cytokine IL-10 within lipopolysaccharide-activated murine primary macrophages. Additionally, EPS400 significantly (p ≤ 0.05) enhanced the phagocytic potential of macrophages. Collectively, our findings spotlight EPS400 as a promising contender endowed with significant antioxidant, antibacterial, and immunomodulatory attributes. These characteristics propose EPS400 as a potential pharmaceutical or bioactive component, with potential applications in the realm of functional food development.
Bio-Mapping of Microbial Indicators and Pathogen Quantitative Loads in Commercial Broiler Processing Facilities in South America
Authors: Vargas David A. , Betancourt-Barszcz Gabriela K. , Chávez-Velado Daniela R. , Sánchez Angelica , Bueno López Rossy , Sanchez-Plata Marcos X.
Published: September 2023

A bio-mapping study was conducted with the aim of creating a microbiological baseline on indicator organisms and pathogens in commercial broiler processing facilities located in a country in South America. Whole chicken carcass and wing rinses were collected from five stages of the poultry processing line: live receiving (LR), rehanger (R), post-evisceration (PE), post-chilling (PC), and wings (W). Rinses (n = 150) were enumerated using the MicroSnap™ system for total viable counts (TVC) and Enterobacteriaceae (EB), while the BAX®-System-SalQuant® and BAX®-System-CampyQuant™ were used for Salmonella and Campylobacter, respectively. TVC and EB were significantly different between stages at the processing line (p < 0.01). There was a significant reduction from LR to PC for both microbial indicators. TVC and EB counts increased significantly from PC to W. Salmonella counts at PC were significantly different from the other stages at the processing line (p = 0.03). Campylobacter counts were significantly higher than the other stages at PC (p < 0.01). The development of bio-mapping baselines with microbial indicators showed consistent reduction up to the post-chilling stage, followed by an increase at the wings sampling location. The quantification of pathogens demonstrates that prevalence analysis as a sole measurement of food safety is not sufficient to evaluate the performance of processing operations and sanitary dressing procedures in commercial processing facilities.
Films Based on Biopolymers Incorporated with Active Compounds Encapsulated in Emulsions: Properties and Potential Applications—A Review
Authors: Reis Camily Aparecida , Gomes Andresa , do Amaral Sobral Paulo José
Published: September 2023

The rising consumer demand for safer, healthier, and fresher-like food has led to the emergence of new concepts in food packaging. In addition, the growing concern about environmental issues has increased the search for materials derived from non-petroleum sources and biodegradable options. Thus, active films based on biopolymers loaded with natural active compounds have great potential to be used as food packaging. However, several lipophilic active compounds are difficult to incorporate into aqueous film-forming solutions based on polysaccharides or proteins, and the hydrophilic active compounds require protection against oxidation. One way to incorporate these active compounds into film matrices is to encapsulate them in emulsions, such as microemulsions, nanoemulsions, Pickering emulsions, or double emulsions. However, emulsion characteristics can influence the properties of active films, such as mechanical, barrier, and optical properties. This review addresses the advantages of using emulsions to encapsulate active compounds before their incorporation into biopolymeric matrices, the main characteristics of these emulsions (emulsion type, droplet size, and emulsifier nature), and their influence on active film properties. Furthermore, we review the recent applications of the emulsion-charged active films in food systems.
Contamination of Honeybee (Apis mellifera L.) Royal Jelly by Pesticides and Sample Preparation Methods for Its Determination: A Critical Appraisal
Authors: Fuente-Ballesteros Adrián , Brugnerotto Patricia , Nguyen Vinh Dinh , Costa Ana C. O. , Bernal José , Ares Ana M.
Published: September 2023

Pesticides can easily enter the food chain, harming bee populations and ecosystems. Exposure of beehive products to various contaminants has been identified as one of the factors contributing to the decline in bee populations, and multiple food alerts have been reported. Despite this fact, royal jelly, a valuable bee product with nutritional and functional properties, has received less attention in this context. Pesticide residues of different chemical class can contaminate royal jelly when foraging bees collect pollen or nectar from pesticide-treated flowers, or in some cases, due to its frequent and inappropriate use in the treatment of mites in beehives. To monitor this issue and also make it more reliable, it is crucial to develop effective sample preparation methods for extracting pesticides from royal jelly for subsequent analysis. In this context, this review provides information about sample preparation methods (solid-phase extraction, solvent extraction, and QuEChERS—quick, easy, cheap, effective, rugged and safe) and analytical methods that have been validated or improved to extract and analyze pesticides, respectively, in royal jelly samples of different origins. Finally, future perspectives are discussed. With this background, we aim to provide data that can guide future research related to this topic.
A New Approach to Determining the Network Fractality with Application to Robot-Laser-Hardened Surfaces of Materials
Authors: Babič Matej , Marinković Dragan
Published: September 2023

A new method to determine a fractal network in chaotic systems is presented together with its application to the microstructure recognition of robot-laser-hardened (RLH) steels under various angles of a laser beam. The method is based on fractal geometry. An experimental investigation was conducted by investigating the effect of several process parameters on the final microstructures of material that has been heat-treated. The influences of the surface temperature, laser speed, and different orientation angles of the laser beam on the microstructural geometry of the treated surfaces were considered. The fractal network of the microstructures of robot-laser-hardened specimens was used to describe how the geometry was changed during the heat treatment of materials. In order to predict the fractal network of robot-laser-hardened specimens, we used a method based on intelligent systems, namely genetic programming (GP) and a convolutional neural network (CNN). The proposed GP model achieved a prediction accuracy of 98.4%, while the proposed CNN model reached 96.5%. The performed analyses demonstrate that the angles of the robot laser cell have a noticeable effect on the final microstructures. The specimen laser-hardened under the conditions of 4 mm/s, 1000 °C, and an impact angle of the laser beam equal to 75° presented the maximum fractal network. The minimum fractal network was observed for the specimen before the robot-laser-hardening process.
Development and Effects of Mobile-Application-Based Parenting Support Program for Premature Infants’ Mothers
Authors: Ahn Hye Young , Ko Hyun Jeong , Jo Hee Jee
Published: September 2023

Background: Premature infants are separated from their parents after birth and are admitted to the neonatal intensive care unit. Separation of babies from mothers causes various problems. Therefore, as the number of premature infants increases every year, educational programs to continuously support baby care are needed. Methods: In this study, a nonequivalent control group non-synchronized design was employed. The subjects of the study were 52 mothers of premature infants (16 in the app-based program group, 18 in the electronic document group, and 18 in the control group) using a portal site for parents from February to April 2023. The app-based program and electronic document group followed a parenting support program for two weeks. Results: There were significant differences in maternal confidence between the app-based, electronic document, and control groups (F = 7.354, p = 0.002). Conclusions: Providing necessary information and emotional support through professional counseling centers’ app-based programs for premature infants’ mothers, and providing interaction through member community bulletin boards, are proposed to form an effective educational program.
Oral Health Strategies: Surveying the Present to Plan the Future of Community-Based Learning
Authors: Veiga Nélio Jorge , Couto Patrícia , Correia Patrícia , Mello-Moura Anna Carolina Volpi , Lopes Pedro Campos , Correia Maria José
Published: September 2023

Introduction: Oral health literacy relates to the capacity of individuals to acquire, understand and to act upon oral health information to make appropriate health decisions. This scientific review’s main goal is to analyze the strategies that improve oral health literacy within the community, specifically oriented to a community-based learning model focused on the most vulnerable risk groups in society. Materials and Methods: The current review is based on the literature on oral health literacy within community-based learning strategies. The present review selected scientific studies by searching MEDLINE and related databases, such as Web of Science and PUBMED, and by consulting existing bibliographies. Results: Based on the application of the inclusion criteria to the abstracts, 45 publications were retrieved which explicitly dealt with the definitions of oral health literacy, community-based learning, and service learning. Several studies have demonstrated that health consumers with low health literacy fail to understand the available health information. Therefore, innovative oral health literacy strategies should be undertaken. Service learning is an example of an educational approach where the student learns specific soft skills in the classroom and collaborates directly with an agency or institution and engages in reflection activities to deepen their understanding of what is being taught. Conclusions: One of the main strategies used to incorporate the oral health professional in social responsibility and direct contact in the community is through experiencing community-based learning projects. The future graduate must be an educator capable of educating patients in order to themselves acquire high-level skills in oral health literacy.
Prevalence of Reproductive Health Issues among US Female Law Enforcement Officers
Authors: Kehler Ainslie , Jahnke Sara , Kukić Filip , Streetman Aspen E. , Heinrich Katie M.
Published: September 2023

Reproductive health is a considerable concern among US female law enforcement officers (LEOs). Miscarriage and preterm birth rates are significantly higher in women firefighters than published US averages. Since law enforcement and firefighting share occupational conditions and practices, adverse birth outcomes were hypothesized to be greater in female law enforcement officers (LEOs) than the US averages. Occupational hazards may place pregnant LEOs at a higher risk for complicated pregnancies and adverse birth outcomes. This study quantified pregnancy outcomes in female LEOs using a cross-sectional survey and compared them to US averages and large prospective studies. The participants (N = 162, 72.2% aged 31–49, 85.2% Caucasian) averaged 2.5 ± 1.4 pregnancies. Stress (59.1%) and shiftwork (59.8%) were the most common reported exposures. Miscarriage and preterm birth rates were 19.1% and 16.4%, respectively. Miscarriages were significantly greater among participants compared to prospective studies [χ2 (1, N = 911,971) = 20.51, p < 0.001]. Female LEOs of childbearing age should receive education about potential reproductive health hazards and take precautions against them. Moreover, policymakers, human resources, and healthcare providers should understand how law enforcement work might affect maternal health.
The Effect of Fracture Patterns, Pinning Configuration, Surgeon Experience and Subspecialty on Short-Term Radiological Outcomes of Pediatric Supracondylar Humeral Fractures Treated in the Prone Position: A Case-Series
Authors: Vescio Andrea , Carlisi Giovanni , Macrì Vincenzo Roberto , Sanzo Francesco , Gigliotti Giuseppe , Riccelli Daria Anna , Tedesco Giuseppe , Mercurio Michele , Galasso Olimpio , Gasparini Giorgio , Jackson Garrett R. , Chahla Jorge , Familiari Filippo
Published: September 2023

Background: The most common treatment modality for supracondylar humerus fractures (SCHFs) in children is closed reduction and percutaneous pinning (CRPP). Nonetheless, debate persists regarding the optimal technique used. Therefore, the purpose of our study was to investigate the impact of surgeon experience, surgeon subspecialty and pin configuration on short-term radiological outcomes following CRPP of displaced SCHFs. Methods: Patients less than 14 years of age who underwent CRPP for displaced SCHFs in the prone position between January 2018 and December 2022 were analyzed. Patients were separated into subgroups based on fracture type (low vs. high sagittal), pin configuration (lateral, cross, other), number and configuration of K-wires and first operator surgical experience. The following outcome measurements were collected: postoperative Baumann angle (BA), Shaft-Condylar angle (SCA), surgical duration (SD), duration of radiation exposure (DRE) and number of clinical and radiological follow-ups (FU). Results: A total of 44 patients with a mean age of 6 ± 2.5 years were included in the final analysis. The mean post-operative BA and SCA were 74.8° ± 4.9° and 37.7° ± 10.2°, respectively. No significant differences were found in the post-operative Baumann’s angle or SCA among the subgroups. Regarding secondary outcomes, no differences were found among each subgroup regarding SD, DRE and FUs. Conclusion: Short-term radiological outcomes following the treatment of SCHFs treated in the prone position are not affected by fracture patterns and pinning configuration, regardless of the surgeon’s years of experience or subspecialty.
Application of AHP-ICM and AHP-EWM in Collapse Disaster Risk Mapping in Huinan County
Authors: Lu Zengkang , Yu Chenglong , Liu Huanan , Zhang Jiquan , Zhang Yichen , Wang Jie , Chen Yanan
Published: September 2023

Collapses are one of the most common geological disasters in mountainous areas, which easily damage buildings and infrastructures and bring huge property losses to people’s production and life. This paper uses Huinan County as the study area, and with the help of a geographic information system (GIS) based on the formation principle of natural disaster risk, the information content method (ICM), the analytical hierarchy process (AHP), and the analytical hierarchy process–information content method (AHP-ICM) model are applied to hazard mapping, and the analytical hierarchy process-entropy weight method (AHP-EWM) model is applied to exposure, vulnerability and emergency responses, and recovery capability mapping. A risk mapping model for collapse disasters was also constructed using these four elements. Firstly, an inventory map of 52 landslides was compiled using remote sensing interpretation, field verification, and comprehensive previous survey data. Then, the study area mapping units were delineated using the curvature watershed method in the slope unit, and 21 indicators were used to draw the collapse disaster risk zoning map by considering the four elements of geological disaster risk. The prediction accuracy of the three hazard mapping models was verified using the receiver operating characteristic (ROC) curve, and the area under the curve (AUC) results of the AHP, ICM, and AHP-ICM models were 80%, 85.7%, and 87.4%, respectively. After a comprehensive comparison, the AHP-ICM model is the best of the three models in terms of collapse hazard mapping, and it was applied to collapse risk mapping with the AHP-EWM model to produce a reasonable and reliable collapse risk zoning map, which provides a basis for collapse management and decision making.
Flow-Data-Based Global Spatial Autocorrelation Measurements for Evaluating Spatial Interactions
Authors: Sun Shuai , Zhang Haiping
Published: September 2023

Spatial autocorrelation analysis is essential for understanding the distribution patterns of spatial flow data. Existing methods focus mainly on the origins and destinations of flow units and the relationships between them. These methods measure the autocorrelation of gravity or the positional and directional autocorrelations of flow units that are treated as objects. However, the intrinsic complexity of actual flow data necessitates the consideration of not only gravity, positional, and directional autocorrelations but also the autocorrelations of the variables of interest. This study proposes a global spatial autocorrelation method to measure the variables of interest of flow data. This method mainly consists of three steps. First, the proximity constraints of the origin and destination of a flow unit are defined to ensure similarity of flow units in terms of direction, distance, and position. This undertaking aims to determine the neighborhood of flow units and generate their adjacent matrices. Second, a spatial autocorrelation measurement model for flow data is constructed on the basis of the adjacent matrix generated. Artificial data sets are also employed to test the validity of the model. Finally, the proposed method is applied to the flow data analysis of population migration in central and eastern China to prove the practical application value of the model. The proposed method is universal and can be generalized to the global spatial autocorrelation analysis of any type of flow data.
An Agent-Based Simulation Platform for a Safe Election: From Design to Simulation
Authors: Barenji Ali V. , Montreuil Benoit , Babalou Sevda , Nazzal Dima , Benaben Frederick , DeMillo Richard
Published: September 2023

Managing the logistics and safety of an election system, from delivering voting machines to the right locations at the right time to ensuring that voting lines remain reasonable in length is a complex problem due to the scarcity of resources, especially human poll workers, and the impact of human behavior and disrupting events on the performance of this critical system. These complexities grew with the need for physical distancing during the COVID-19 pandemic coinciding with multiple key national elections, including the 2020 general presidential election in the USA. In this paper, we propose a digital clone platform leveraging agent-based simulation to model and experiment with resource allocation decisions and voter turnout fluctuations and facilitate “what-if” scenario testing of any election. As a use case, we consider three different concurrent polling location problems, namely, resource allocation, polling layout, and management. The main aim is to reduce voter waiting time and provide visibility of different scenarios for polling and state-level managers. We explain the proposed simulation platform based on Fulton County for the 2020 presidential US election. Fulton County had 238 polling locations in 2020, which provided publicly available voter turnout data. The developed platform realistically models at the county level and at specific locations, suggesting the possible allocation of finite resources among locations in the county and the configuration of each location, accounting for physical, legal, and technical constraints. Multiple realistic scenarios were developed and embedded into the simulation platform to evaluate and verify the different systems. The system performance and key attributes of the election system, such as waiting time, resource utilization, and layout safety, were tested and validated.