bluuebunny/crossref_metadata_2025 huggingface dataset:
Lightweight Machine Learning Method for Real-Time Espresso Analysis
Authors: Choi Jintak , Lee Seungeun , Kang Kyungtae , Suh Hyojoong
Published: February 2024

Coffee crema plays a crucial role in assessing the quality of espresso. In recent years, in response to the rising labor costs, aging population, remote security/authentication needs, civic awareness, and the growing preference for non-face-to-face interactions, robot cafes have emerged. While some people seek sentiment and premium coffee, there are also many who desire quick and affordable options. To align with the trends of this era, there is a need for lightweight artificial intelligence algorithms for easy and quick decision making, as well as monitoring the extraction process in these automated cafes. However, the application of these technologies to actual coffee machines has been limited. In this study, we propose an innovative real-time coffee crema control system that integrates lightweight machine learning algorithms. We employ the GrabCut algorithm to segment the crema region from the rest of the image and use a clustering algorithm to determine the optimal brewing conditions for each cup of espresso based on the characteristics of the crema extracted. Our results demonstrate that our approach can accurately analyze coffee crema in real time. This research proposes a promising direction by leveraging computer vision and machine learning technologies to enhance the efficiency and consistency of coffee brewing. Such an approach enables the prediction of component replacement timing in coffee machines, such as the replacement of water filters, and provides administrators with Before Service. This could lead to the development of fully automated artificial intelligence coffee making systems in the future.
A Si IGBT/SiC MOSFET Hybrid Isolated Bidirectional DC–DC Converter for Reducing Losses and Costs of DC Solid State Transformer
Authors: Huang Jun , Wang Yu , Li Zhenfeng , Zhu Hongbo , Li Kai
Published: February 2024

The DC solid state transformer (DCSST) is a crucial component for connecting buses of different voltage levels in the DC distribution grid. This paper proposes a Si IGBT/SiC MOSFET hybrid isolated bidirectional DC–DC converter and an optimized modulation strategy (OMS) to reduce the losses and costs of DCSST. Based on the analysis of topology and operating principles, a duty-cycle modulation strategy is proposed and the converter is modeled by the time domain analysis (TDA) method. Through the analysis of switching characteristics, an optimization problem is established, which aims to reduce the conduction losses of switches while ensuring zero-voltage switching (ZVS) for all switches and low-current turn-off for IGBTs simultaneously. The optimization problem is solved by the augmented Lagrangian genetic algorithm (ALGA), and the OMS for the proposed converter is deduced. Finally, a 2 kW experimental prototype with the primary voltage of 405–495 V and the secondary voltage of 150 V is built to verify the effectiveness of the proposed topology and OMS. The switching costs of the proposed converter is reduced by 27.3% and the efficiency is improved by up to 4.04% compared to the existing method.
A Digital Twin Platform Integrating Process Parameter Simulation Solution for Intelligent Manufacturing
Authors: Wang Haoran , Yang Zuoqing , Zhang Quan , Sun Qilei , Lim Enggee
Published: February 2024

The present work aims to develop a digital twin system typical of intelligent manufacturing applications, which has integrated visualization technologies, as well as the process parameter simulation solution. The application under consideration is a typical machining process, with a gantry machine tool controlled by Siemens Programmable Logic Controller(PLC) S7-1200. With the establishment of dual-directional data communication between the physical machine tool and its virtual counterpart based on TCP/IP protocol, real-time visualization, monitoring, and control of the entire working process can be achieved. Furthermore, we integrated with the digital twin system as a solution for real-time process parameter simulation based on finite element modeling (FEM), which enables the real-time monitoring of necessary process parameters, e.g., surface deformation, during the machining process. A preliminary experiment was conducted to validate our proposed digital twin system, and the results demonstrated that our proposed method has satisfactory performance in terms of both control and monitoring of the traditional machining process, and synchronization between the physical and virtual models is also proven to be positive with minimal latency.
Perceptual Image Quality Prediction: Are Contrastive Language–Image Pretraining (CLIP) Visual Features Effective?
Authors: Onuoha Chibuike , Flaherty Jean , Cong Thang Truong
Published: February 2024

In recent studies, the Contrastive Language–Image Pretraining (CLIP) model has showcased remarkable versatility in downstream tasks, ranging from image captioning and question-answering reasoning to image–text similarity rating, etc. In this paper, we investigate the effectiveness of CLIP visual features in predicting perceptual image quality. CLIP is also compared with competitive large multimodal models (LMMs) for this task. In contrast to previous studies, the results show that CLIP and other LMMs do not always provide the best performance. Interestingly, our evaluation experiment reveals that combining visual features from CLIP or other LMMs with some simple distortion features can significantly enhance their performance. In some cases, the improvements are even more than 10%, while the prediction accuracy surpasses 90%.
An Experimental Electronic Board ADF339 for Analog and FPGA-Based Digital Filtration of Measurement Signals
Authors: Pałczyński Cezary , Olejnik Paweł
Published: February 2024

This work introduces and examines a new programmable electronic system, Board ADF339, designed for filtering analog measurement signals of low frequencies. The system operates in a mixed mode in collaboration with a digital controller implemented on the myRIO-1900 FPGA module. It enables the digital selection of the type and frequency settings of the UAF42 integrated circuit. In the technical implementation section, electronic filter and phase shifter circuit diagrams are presented, along with the digital counterpart of the analog filter. Tests of this system were conducted on signals generated using a function generator, which was followed by the filtration of signals occurring in real laboratory setups. A series of real responses from three different laboratory systems and a measurement system utilizing LabVIEW FPGA virtual instruments are demonstrated. After computing SNR indicators for noisy waveforms, the application scope and usability of the board are highlighted.
Intrusion Detection System for Autonomous Vehicles Using Non-Tree Based Machine Learning Algorithms
Authors: Anthony Cynthia , Elgenaidi Walid , Rao Muzaffar
Published: February 2024

This research work highlights significant achievements in the domain of intrusion detection systems (IDSs) for autonomous vehicles, which are crucial in enhancing their safety, reliability, and cybersecurity. This study introduces an approach that leverages non-tree-based machine learning algorithms, such as K-nearest neighbors and ensemble learning, to develop an IDS tailored for autonomous vehicles. These algorithms were employed because of their ability to process complex and large datasets with less likeliness for overfitting, their scalability, and their ability to adapt to changing conditions in real time. These algorithms effectively handle imbalanced data, enhancing the detection accuracy of both normal and intrusive instances. The IDS’s performance was validated through the utilization of three real-world datasets, CAN intrusion, CICIDS2017, and NSL-KDD, where the proposed non-tree-based IDS (NTB-MTH-IDS) was measured with the standard measurement metrics: accuracy, precision, F1-score, and recall, including specificity and sensitivity. Notably, the results indicate that K-nearest neighbors and stacking, as part of NTB-MTH-IDS, has an accuracy of 99.00%, 98.57%, and 97.57%, and F1-scores of 99.00%, 98.79%, and 97.54% in the CICIDS2017, NSL-KDD, and CAN datasets, respectively. The results of this research can lead to establishing a robust intrusion detection framework, thereby ensuring the safety and reliability of autonomous vehicles. Through this achievement, road users, passengers, and pedestrians are safeguarded against the consequences of potential cyber threats.
Multicriteria Machine Learning Model Assessment—Residuum Analysis Review
Authors: Kaniuka Jan , Ostrysz Jakub , Groszyk Maciej , Bieniek Krzysztof , Cyperski Szymon , Domański Paweł D.
Published: February 2024

The use of machine learning (ML) and its applications is one of the leading research areas nowadays. Neural networks have recently gained enormous popularity and many works in various fields use them in the hope of improving previous results. The application of the artificial intelligence (AI) methods and the rationale for this decision is one issue, but the assessment of such a model is a completely different matter. People mostly use mean square error or less often mean absolute error in the absolute or percentage versions. One should remember that an error does not equal an error and a single value does not provide enough knowledge about the causes of some behavior. Proper interpretation of the results is crucial. It leads to further model improvement. It might be challenging, but allows us to obtain better and more robust solutions, which ultimately solve real-life problems. The ML model assessment is the multicriteria task. A single measure delivers only a fraction of the picture. This paper aims at filling that research gap. Commonly used integral measures are compared with alternative measures like factors of the Gaussian and non-Gaussian statistics, robust statistical estimators, tail index and the fractional order. The proposed methodology delivers new single-criteria indexes or the multicriteria approach, which extend the statistical concept of the moment ratio diagram (MRD) into the index ratio diagram (IRD). The proposed approach is validated using real data from the Full Truck Load cost estimation example. It compares 35 different ML regression algorithms applied to that task. The analysis gives an insight into the properties of the selected methods, enables their comparison and homogeneity analysis and ultimately leads towards constructive suggestions for their eventual proper use. The paper proposes new indexes and concludes that correct selection of the residuum analysis methodology makes the assessment and the ML regression credible.
Real-Time Object Detection and Tracking Based on Embedded Edge Devices for Local Dynamic Map Generation
Authors: Choi Kyoungtaek , Moon Jongwon , Jung Ho Gi , Suhr Jae Kyu
Published: February 2024

This paper proposes a camera system designed for local dynamic map (LDM) generation, capable of simultaneously performing object detection, tracking, and 3D position estimation. This paper focuses on improving existing approaches to better suit our application, rather than proposing novel methods. We modified the detection head of YOLOv4 to enhance the detection performance for small objects and to predict fiducial points for 3D position estimation. The modified detector, compared to YOLOv4, shows an improvement of approximately 5% mAP on the Visdrone2019 dataset and around 3% mAP on our database. We also proposed a tracker based on DeepSORT. Unlike DeepSORT, which applies a feature extraction network for each detected object, the proposed tracker applies a feature extraction network once for the entire image. To increase the resolution of feature maps, the tracker integrates the feature aggregation network (FAN) structure into the DeepSORT network. The difference in multiple objects tracking accuracy (MOTA) between the proposed tracker and DeepSORT is minimal at 0.3%. However, the proposed tracker has a consistent computational load, regardless of the number of detected objects, because it extracts a feature map once for the entire image. This characteristic makes it suitable for embedded edge devices. The proposed methods have been implemented on a system on chip (SoC), Qualcomm QCS605, using network pruning and quantization. This enables the entire process to be executed at 10 Hz on this edge device.
Error Analysis and Condition Estimation of the Pyramidal Form of the Lucas-Kanade Method in Optical Flow
Authors: Winkler Joab R.
Published: February 2024

Optical flow is the apparent motion of the brightness patterns in an image. The pyramidal form of the Lucas-Kanade (LK) method is frequently used for its computation but experiments have shown that the method has deficiencies. Problems arise because of numerical issues in the least squares (LS) problem minAx−b22, A∈Rm×2 and m≫2, which must be solved many times. Numerical properties of the solution x0=A†b = (ATA)−1ATb of the LS problem are considered and it is shown that the property m≫2 has implications for the error and stability of x0. In particular, it can be assumed that b has components that lie in the column space (range) R(A) of A, and the space that is orthogonal to R(A), from which it follows that the upper bound of the condition number of x0 is inversely proportional to cosθ, where θ is the angle between b and its component that lies in R(A). It is shown that the maximum values of this condition number, other condition numbers and the errors in the solutions of the LS problems increase as the pyramid is descended from the top level (coarsest image) to the base (finest image), such that the optical flow computed at the base of the pyramid may be computationally unreliable. The extension of these results to the problem of total least squares is addressed by considering the stability of the optical flow vectors when there are errors in A and b. Examples of the computation of the optical flow demonstrate the theoretical results, and the implications of these results for extended forms of the LK method are discussed.
Ontology-Based Data Observatory for Formal Knowledge Representation of UXO Using Advanced Semantic Web Technologies
Authors: Horvat Marko , Krtalić Andrija , Akagić Amila , Mekterović Igor
Published: February 2024

As landmines and other unexploded ordnances (UXOs) present a great risk to civilians and infrastructure, humanitarian demining is an essential component of any post-conflict reconstruction. This paper introduces the Minefield Observatory, a novel web-based datastore service that semantically integrates diverse data in humanitarian demining to comprehensively and formally describe suspected minefields. Because of the high heterogeneity and isolation of the available minefield datasets, extracting relevant information to determine the optimal course of demining efforts is time-consuming, labor-intensive and requires highly specialized knowledge. Data consolidation and artificial intelligence techniques are used to convert unstructured data sources and store them in an ontology-based knowledge database that can be efficiently accessed through a Semantic Web application serving as the Minefield Observatory user interface. The MINEONT+ ontology was developed to integrate diverse mine scene information obtained through non-technical surveys and remote sensing, such as aerial and hyperspectral satellite imagery, indicators of mine presence and absence, contextual data, terrain analysis information, and battlefield reports. The Minefield Observatory uses the Microdata API to embed this dataset into dynamic HTML5 content, allowing seamless usage in a user-centric web tool. A use-case example was provided demonstrating the viability of the proposed approach.
Prediction Enhancement of Metasurface Absorber Design Using Adaptive Cascaded Deep Learning (ACDL) Model
Authors: Ajmi Haitham Al , Bait-Suwailam Mohammed M. , Khriji Lazhar , Al-Lawati Hassan
Published: February 2024

This paper presents a customized adaptive cascaded deep learning (ACDL) model for the design and performance prediction of metasurface absorbers. A multi-resonant metasurface absorber structure is introduced, with 10 target-driven design parameters. The proposed deep learning model takes advantage of cascading several sub-deep neural network (DNN) layers with forward noise mitigation capabilities. The inherent appearance of sparse data is dealt with in this work by proposing a trained data-adaptive selection technique. On the basis of the findings, the prediction response is quite fast and accurate enough to retrieve the design parameters of the studied metasurface absorber with two patches of 4000- and 7000-sample datasets. The training loss taken from the second DNN of our proposed model showed logarithmic mean squared errors of 0.039 and 0.033 when using Keras and the adaptive method, respectively, with a dataset split of 4000. On the contrary, for a dataset split of 7000, the errors were 0.049 with Keras and 0.045 with the adaptive method. On the other hand, the validation loss was evaluated using the mean square error method, which resulted in a loss of 0.044 with the 4000-sample datasets split with the Keras method, while this was 0.020 with the adaptive method. When extending the dataset to 7000 samples, the validation loss with the Keras splitting method was 0.0073, while it was improved, reaching 0.006, with the proposed adaptive method, and achieved a prediction accuracy of 94%. This proposed deep learning model can be deployed in the design process and synthesis of multi-resonant metasurface absorber structures. The proposed model shows the advantages of making the design process more efficient in sparse dataset handling, being an efficient approach in multi-resonance metasurface data pre-processing, being less time consuming, and being computationally valuable.
Enhanced Anti-Inflammatory and Non-Alcoholic Fatty Liver Disease (NAFLD) Improvement Effects of Bacillus subtilis-Fermented Fagopyrum tataricum Gaertner
Authors: Park Chan-Hwi , Kang Hyun , Lee Sung-Gyu
Published: February 2024

In this study, we investigated the enhanced anti-inflammatory activity and the effects on non-alcoholic fatty liver disease (NAFLD) of fermented Fagopyrum tataricum (F. tataricum) Gaertner extract (FFT) through in vitro analysis. We utilized high-performance liquid chromatography (HPLC) to analyze the non-fermented F. tataricum Gaertner extract (NFT) and the marker components, rutin and quercetin in FFT, to confirm changes in composition due to fermentation. The anti-inflammatory activity of NFT and FFT was evaluated using a lipopolysaccharide (LPS)-induced RAW 264.7 cell inflammation model. Simultaneously, the NAFLD improvement effects were measured by evaluating lipid accumulation and the expression of lipid synthesis regulators in free fatty acid (FFA)-induced HepG2 cells. HPLC analysis confirmed an increase in rutin content after the fermentation of F. tataricum Gaertner. Upon treatment with NFT and FFT at a concentration of 400 μg/mL, LPS-induced nitric oxide (NO) production values in RAW 264.7 cells were reduced to 16.12 μM and 2.09 μM, respectively, indicating enhanced significant inhibition (p < 0.05) of NO production through fermentation. FFT demonstrated the significant inhibition (p < 0.05) of inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (COX-2) protein, and inflammatory cytokine mRNA expression through the nuclear factor kappa B (NF-κB) and mitogen-activated protein kinase (MAPK) pathways in LPS-induced RAW 264.7 cells. In FFA-induced HepG2 cells, FFT significant suppressed (p < 0.05) lipid accumulation and the expression of sterol regulatory element binding protein (SREBP)-1c, CCAAT/enhancer binding protein (C/EBP)α proteins, and acetyl-CoA carboxylase (ACC) mRNA. The results of this study suggest the potential utilization of FFT as a material for improving NAFLD.
Evaluation of Handheld Mobile Laser Scanner Systems for the Definition of Fuel Types in Structurally Complex Mediterranean Forest Stands
Authors: Hoffrén Raúl , Lamelas María Teresa , de la Riva Juan
Published: February 2024

The exposure of Mediterranean forests to large wildfires requires mechanisms to prevent and mitigate their negative effects on the territory and ecosystems. Fuel models synthesize the complexity and heterogeneity of forest fuels and allow for the understanding and modeling of fire behavior. However, it is sometimes challenging to define the fuel type in a structurally heterogeneous forest stand due to the mixture of characteristics from the different types and limitations of qualitative field observations and passive and active airborne remote sensing. This can impact the performance of classification models that rely on the in situ identification of fuel types as the ground truth, which can lead to a mistaken prediction of fuel types over larger areas in fire prediction models. In this study, a handheld mobile laser scanner (HMLS) system was used to assess its capability to define Prometheus fuel types in 43 forest plots in Aragón (NE Spain). The HMLS system captured the vertical and horizontal distribution of fuel at an extremely high resolution to derive high-density three-dimensional point clouds (average: 63,148 points/m2), which were discretized into voxels of 0.05 m3. The total number of voxels in each 5 cm height stratum was calculated to quantify the fuel volume in each stratum, providing the vertical distribution of fuels (m3/m2) for each plot at a centimetric scale. Additionally, the fuel volume was computed for each Prometheus height stratum (0.60, 2, and 4 m) in each plot. The Prometheus fuel types were satisfactorily identified in each plot and were compared with the fuel types estimated in the field. This led to the modification of the ground truth in 10 out of the 43 plots, resulting in errors being found in the field estimation between types FT2–FT3, FT5–FT6, and FT6–FT7. These results demonstrate the ability of the HMLS systems to capture fuel heterogeneity at centimetric scales for the definition of fuel types in the field in Mediterranean forests, making them powerful tools for fuel mapping, fire modeling, and ultimately for improving wildfire prevention and forest management.
The Effect of Artificial Substrate and Carbon Source Addition on Bacterial Diversity and Community Composition in Water in a Pond Polyculture System
Authors: Guo Kun , Shi Mumin , Huang Xiaoli , Luo Liang , Wang Shihui , Zhang Rui , Xu Wei , Ruan Guoliang , Zhao Zhigang
Published: February 2024

The use of artificial substrates and biofloc technology can favor fish culture and improve water quality. The aim of this study was to evaluate whether artificial substrates and carbon source additions modify the microbial activity of water bodies. The diversity and structure of microflora in the water after adding artificial substrates and carbon sources to the ponds were analyzed using high-throughput sequencing based on the V3-V4 region of 16S rRNA genes. The results showed that there was no difference in the richness and diversity of intestinal microflora between the control and experimental groups. Principal coordinate analysis (PCoA) and nonmetric multidimensional scaling (NMDS) showed that artificial substrate and carbon source addition changed the structure of the microflora. The results of a linear discriminant analysis (LDA) effect size (LefSe) indicated 11 biomarkers in the EGˍst group. Spearman correlation heatmap analysis showed that environmental factors affected the bacterial communities, and the results of a redundancy analysis indicated that chemical oxygen demand was a critical factor in controlling the bacterial communities in the water. These results provide an understanding of the effect of artificial substrate and carbon source addition on bacterial diversity and community composition in water.
Exploring Interrelationships between Colour, Composition, and Coagulation Traits of Milk from Cows, Goats, and Sheep
Authors: Garzón Ana , Perea José M. , Angón Elena , Ryan Eoin G. , Keane Orla M. , Caballero-Villalobos Javier
Published: February 2024

This study explores the interrelationships between the composition, coagulation, and colour of sheep, goat, and cow milk to identify their similarities and differences and to assess whether the relationships between the variables are common to all species or whether they emerge from species-specific relationships. For this purpose, 2400 individual milk samples were analysed. The differences and similarities between the species were determined using discriminant analysis and cluster analysis. The results show a clear differentiation between species. Sheep milk stands out for its cheesemaking capacity and shows similarities with goat milk in composition and coagulation. Nonetheless, colorimetry highlights a greater similarity between sheep and cow milk. Composition and colorimetry were more discriminating than coagulation, and the variables that differed the most were fat, protein, curd yield, lightness, and red–green balance. Using canonical correlation, the interrelationships between the different sets of variables were explored, revealing patterns of common variation and species-specific relationships. Colorimetric variables were closely related to milk solids in all species, while in sheep milk, an inverse relationship with lactose was also identified. Furthermore, a strong relationship was revealed for all species between colour and curd yield. This could be modelled and applied to estimate the technological value of milk, proving colorimetry as a useful tool for the dairy industry.
The Quality Evaluation of Highland Barley and Its Suitability for Chinese Traditional Tsampa Processing
Authors: Xia Hu , Yu Bo , Yang Yanting , Wan Yan , Zou Liang , Peng Lianxin , Lu Lidan , Ren Yuanhang
Published: February 2024

The physicochemical traits of highland barley prominently affect the quality of Tsampa. To find out the relevance between the physicochemical properties of raw material and the texture parameters of processed products, twenty-five physicochemical traits and ten quality parameters for seventy-six varieties of highland barley were measured and analyzed. The results showed that there was a significant difference between the physicochemical indexes for highland barleys of various colors. The dark highland barley generally has more fat, protein, total dietary fiber, phenolic, Mg, K, Ca, and Zn and less amylose, Fe, Cu, and Mo than light colored barley. Then, these highland barleys were made into Tsampa. A comprehensive quality evaluation model based on the color and texture parameters of Tsampa was established through principal component analysis. Then, cluster analysis was used to classify the tested samples into three edible quality grades predicated on the above evaluation model. At last, the regression analysis was applied to establish a Tsampa quality predictive model according to the physicochemical traits of the raw material. The results showed that amylose, protein, β-Glucan, and a* and b* could be used to predict the comprehensive quality of Tsampa. The predicted results indicated that 11 of 14 validated samples were consistent with the actual quality, and the accuracy was above 78.57%. Our study built the approach of the appropriate processing varieties evaluation. It may provide reference for processing specific highland barley.
Emulsification Characteristics of Insoluble Dietary Fibers from Pomelo Peel: Effects of Acetylation, Enzymatic Hydrolysis, and Wet Ball Milling
Authors: Yang Kuimin , Yao Jieqiong , Shi Kaixin , Yang Chenxi , Xu Yang , Zhang Peipei , Pan Siyi
Published: February 2024

To improve the application potential of pomelo peel insoluble dietary fiber (PIDF) in emulsion systems, acetylation (PIDF-A), cellulase hydrolysis (PIDF-E), and wet ball milling (PIDF-M) were investigated in this paper as methods to change the emulsification properties of PIDF. The impact of the methods on PIDF composition, structure, and physicochemical properties was also assessed. The results demonstrated that both acetylation modification and cellulase hydrolysis could significantly improve the emulsification properties of PIDF. The emulsions stabilized with PIDF-A and PIDF-E could be stably stored at 25 °C for 30 d without phase separation at particle concentrations above 0.8% (w/v) and had higher storage stability: The D4,3 increments of PIDF-A- and PIDF-E-stabilized emulsions were 0.98 μm and 0.49 μm, respectively, at particle concentrations of 1.2% (w/v), while the storage stability of PIDF-M-stabilized emulsion (5.29 μm) significantly decreased compared with that of PIDF (4.00 μm). Moreover, PIDF-A showed the highest water retention capacity (21.84 g/g), water swelling capacity (15.40 mL/g), oil retention capacity (4.67 g/g), and zeta potential absolute (29.0 mV) among the PIDFs. In conclusion, acetylation modification was a promising method to improve the emulsifying properties of insoluble polysaccharides.
The Pea Oligosaccharides Could Stimulate the In Vitro Proliferation of Beneficial Bacteria and Enhance Anti-Inflammatory Effects via the NF-κB Pathway
Authors: Cheng Yongxia , Zhao Ruoqi , Qiao Mingwu , Ma Yan , Li Tiange , Li Ning , Shen Yue , Huang Xianqing , Song Lianjun
Published: February 2024

The oligosaccharides extracted from the seeds of peas, specifically consisting of raffinose, stachyose, and verbascose, fall under the category of raffinose family oligosaccharides (RFOs). The effect of RFOs on intestinal microflora and the anti-inflammatory mechanism were investigated by in vitro fermentation and cell experiments. Firstly, mouse feces were fermented in vitro and different doses of RFOs (0~2%) were added to determine the changes in the representative bacterial community, PH, and short-chain fatty acids in the fermentation solution during the fermentation period. The probiotic index was used to evaluate the probiotic proliferation effect of RFOs and the optimal group was selected for 16S rRNA assay with blank group. Then, the effects of RFOs on the inflammatory response of macrophage RAW264.7 induced by LPS were studied. The activity of cells, the levels of NO, ROS, inflammatory factors, and the expression of NF-κB, p65, and iNOS proteins in related pathways were measured. The results demonstrated that RFOs exerted a stimulatory effect on the proliferation of beneficial bacteria while concurrently inhibiting the growth of harmful bacteria. Moreover, RFOs significantly enhanced the diversity of intestinal flora and reduced the ratio of Firmicutes-to-Bacteroides (F/B). Importantly, it was observed that RFOs effectively suppressed NO and ROS levels, as well as inflammatory cytokine release and expression of NF-κB, p65, and iNOS proteins. These findings highlight the potential of RFOs in promoting intestinal health and ameliorating intestinal inflammation.
Technological and Safety Characterization of Coagulase-Negative Staphylococci Isolated from Sardinian Fermented Sausage Made by Ovine Meat
Authors: Mangia Nicoletta P. , Cottu Michele , Aponte Maria , Murgia Marco A. , Mura Maria E. , Blaiotta Giuseppe
Published: February 2024

Ripened sheep sausages are widely consumed in Italy, particularly in Sardinia. Despite their driving role in flavor and color development, coagulase-negative staphylococci in these products have been rarely investigated. A total of 70 CoNS cultures isolated from Sardinian sheep sausages were characterized by rep-PCR and M13-RAPD typing and identified by 16S rDNA sequencing. S. xylosus and S. equorum accounted for more than 70% of the total isolates, whilst S. pasteuri (8.5%), S. succinus (2.8%), and S. haemolyticus (2.8%) were less represented. The genes encoding the synthesis of putrescine, tyramine, cadaverine, and histamine were evaluated by PCR. None of the strains hosted genes for decarboxylases, except one S. pasteuri strain that was potentially a tyramine-producer. Antibiotic resistance was evaluated, along with nitrate reductase, lipolytic, and proteolytic activity, in a pool of selected cultures. Resistance to the primary antibiotics was rather widespread. S. xylosus, S. equorum, and S. pasteuri strains were all resistant to amoxicillin and kanamycin. S. equorum strains were sensitive to all tested antibiotics. S. xylosus strains were all resistant to penicillin B. Conversely, all S. pasteuri strains were resistant to both ampicillin and penicillin B, and four out of five strains exhibited tetracycline resistance. The high variability in the production of sheep sausages makes the search for adjunct cultures of crucial relevance. According to this perspective, the characterization of the autochthonous CSN population represents the first step to approach a starter selection.
Investigating the Role of OrbF in Biofilm Biosynthesis and Regulation of Biofilm-Associated Genes in Bacillus cereus BC1
Authors: Sun Yang , Shuai Wenjing , Nie Lanmengya , Li Xiangfei , Jiang Ling
Published: February 2024

Bacillus cereus (B. cereus), a prevalent foodborne pathogen, constitutes a substantial risk to food safety due to its pronounced resilience under adverse environmental conditions such as elevated temperatures and ultraviolet radiation. This resilience can be attributed to its capacity for biofilm synthesis and sustained high viability. Our research aimed to elucidate the mechanisms governing biofilm biosynthesis in B. cereus. To this end, we constructed a 5088-mutant library of the B. cereus strain BC1 utilizing the transposon TnYLB-1. Systematic screening of this library yielded mutants exhibiting diminished biofilm formation capabilities. Twenty-four genes associated with the biofilm synthesis were identified by reverse PCR in these mutants, notably revealing a significant reduction in biofilm synthesis upon disruption of the orbF gene in B. cereus BC1. Comparative analysis between the wild type and orbF-deficient BC1 strains (BC1ΔorbF) indicated a marked downregulation (decreased by 11.7% to 96.7%) in the expression of genes implicated in biofilm formation, flagellar assembly, and bacterial chemotaxis in the BC1ΔorbF. Electrophoretic mobility shift assay (EMSA) further corroborated the role of OrbF, demonstrating its binding to the promoter region of the biofilm gene cluster, subsequently leading to the suppression of transcriptional activity of biofilm-associated genes in B. cereus BC1. Our findings underscore the pivotal role of orbF in biofilm biosynthesis in B. cereus, highlighting its potential as a target for strategies aimed at mitigating biofilm formation in this pathogen.
Determination of Aflatoxin B1 in Grains by Aptamer Affinity Column Enrichment and Purification Coupled with High Performance Liquid Chromatography Detection
Authors: Ji Cong , Sun Xinyang , Fang Yong , Li Peng
Published: February 2024

Aflatoxin B1 (AFB1) is a highly teratogenic and carcinogenic secondary metabolite produced by Aspergillus. It is commonly detected in agricultural products such as cereals, peanuts, corn, and feed. Grains have a complex composition. These complex components severely interfere with the effective extraction and separation of AFB1, and also cause problems such as matrix interference and instrument damage, thus posing a great challenge in the accurate analysis of AFB1. In this study, an aptamer affinity column for AFB1 analysis (AFB1-AAC) was prepared for the enrichment and purification of AFB1 from grain samples. AFB1-AAC with an AFB1-specific aptamer as the recognition element exhibited high affinity and specificity for AFB1. Grain samples were enriched and purified by AFB1-AAC, and subsequently analyzed by high performance liquid chromatography with post-column photochemical derivatization-fluorescence detection (HPLC-PCD-FLD). The average recoveries of AFB1 ranged from 88.7% to 99.1%, with relative standard deviations (RSDs) of 1.4–5.6% (n = 3) at the spiked levels of 5.0–20.0 μg kg−1. The limit of detection (LOD) for AFB1 (0.02 μg kg−1) was much below the maximum residue limits (MRLs) for AFB1. This novel method can be applied to the determination of AFB1 residues in peanut, corn, and rice.
Superluminal Motion and Jet Parameters in the Gamma-ray-Emitting Narrow-Line Seyfert 1 Galaxy TXS 1206+549
Authors: Kozák Bettina , Frey Sándor , Gabányi Krisztina Éva
Published: February 2024

Narrow-line Seyfert 1 (NLS1) galaxies are a peculiar subclass of active galactic nuclei (AGN). Among them, TXS 1206+549 belongs to a small group of radio-loud and γ-ray-emitting NLS1 galaxies. We focus on the radio properties of this galaxy by analysing archival, high-resolution, very long baseline interferometry (VLBI) imaging observations taken at 8 GHz frequency in six epochs between 1994 and 2018. Using the milliarcsecond-scale radio structure, we can resolve a core and a jet component whose angular separation increases by (0.055±0.006) mas yr−1. This corresponds to an apparent superluminal jet component motion of (3.5±0.4)c. From the core brightness temperature and the jet component proper motion, we determine the characteristic Doppler-boosting factor, the bulk Lorentz factor, and the jet viewing angle. We find no compelling evidence for a very closely aligned blazar-type jet. The parameters for TXS 1206+549 resemble those of radio-loud quasar jets with a moderate Lorentz factor (Γ≈4) and ϑ≈24∘ inclination to the line of sight.
COMPAR-EU Recommendations on Self-Management Interventions in Type 2 Diabetes Mellitus
Authors: Beltran Jessica , Valli Claudia , Medina-Aedo Melixa , Canelo-Aybar Carlos , Niño de Guzmán Ena , Song Yang , Orrego Carola , Ballester Marta , Suñol Rosa , Noordman Janneke , Heijmans Monique , Seitidis Georgios , Tsokani Sofia , Kontouli Katerina-Maria , Christogiannis Christos , Mavridis Dimitris , Graaf Gimon de , Groene Oliver , Grammatikopoulou Maria G. , Camalleres-Guillem Francisco , Perestelo-Perez Lilisbeth , McGloin Helen , Winkley Kirsty , Mueller Beate Sigrid , Saz-Parkinson Zuleika , Corcoy Rosa , Alonso-Coello Pablo
Published: February 2024

Self-management interventions (SMIs) offer a promising approach to actively engage patients in the management of their chronic diseases. Within the scope of the COMPAR-EU project, our goal is to provide evidence-based recommendations for the utilisation and implementation of SMIs in the care of adult individuals with type 2 diabetes mellitus (T2DM). A multidisciplinary panel of experts, utilising a core outcome set (COS), identified critical outcomes and established effect thresholds for each outcome. The panel formulated recommendations using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach, a transparent and rigorous framework for developing and presenting the best available evidence for the formulation of recommendations. All recommendations are based on systematic reviews (SR) of the effects and of values and preferences, a contextual analysis, and a cost-effectiveness analysis. The COMPAR-EU panel is in favour of using SMIs rather than usual care (UC) alone (conditional, very low certainty of the evidence). Furthermore, the panel specifically is in favour of using ten selected SMIs, rather than UC alone (conditional, low certainty of the evidence), mostly encompassing education, self-monitoring, and behavioural techniques. The panel acknowledges that, for most SMIs, moderate resource requirements exist, and cost-effectiveness analyses do not distinctly favour either the SMI or UC. Additionally, it recognises that SMIs are likely to enhance equity, deeming them acceptable and feasible for implementation.
NIMBYism and Strategies for Coping with Managing Protests during the Establishment of Community Mental Health Facilities in Taiwan: Insights from Frontline Healthcare Professionals
Authors: Yao Ching-Teng , Hong Hong , Li Chien-Hsun
Published: February 2024

Taiwanese community mental health facilities encounter opposition/resistance from residents, commonly known as “Not-In-My-Backyard” (NIMBYism). This study investigated NIMBYism during the establishment of such facilities and how they respond to such resistance. A qualitative study through semi-structured interviews was used to obtain purposively sampled data. Fifteen frontline healthcare professionals from community mental health facilities in Taiwan were interviewed individually, using an organizational analysis structure. Data were analyzed using qualitative content analysis. Two themes: “Reasons for Resident Resistance” and “Institutional Response Strategies”, two categories, and 11 subcategories emerged. The findings demonstrated the following: (1) Reasons behind residents’ resistance toward establishing community mental health facilities are diverse. (2) Communities lack understanding regarding people with mental disorders, leading to irrational beliefs. (3) Fear and negative perceptions toward people with mental disorders exist. (4) Strategies employed by the facilities include providing community services to foster amicable relationships, organizing community outreaches, training people with mental disorders within communities, nurturing neighborhood connections, establishing and sustaining friendships within communities, inviting residents to visit community mental health facilities or introducing the facilities to communities, and leveraging governmental support. The government should adopt regulations or laws to reduce discrimination, promote human rights, and legislate to demarcate the use of community land.
‘Misdiagnosed and Misunderstood’: Insights into Rarer Forms of Dementia through a Stepwise Approach to Co-Constructed Research Poetry
Authors: Camic Paul M. , Sullivan Mary Pat , Harding Emma , Gould Martha , Wilson Lawrence , Rossi-Harries Sam , Grillo Adetola , McKee-Jackson Roberta , Cox Susan M. , Stott Joshua , Brotherhood Emilie V. , Windle Gill , Crutch Sebastian J.
Published: February 2024

This study investigated co-constructed research poetry as a way to understand the lived experiences of people affected by rarer dementia and as a means to use poetry to convey those experiences to healthcare professionals. Using mixed methods, 71 people living with rarer dementia and care-partners (stakeholders) contributed to co-constructing 27 poems with professional poets; stakeholders’ verbatim words were analysed with descriptive qualitative analysis. Stakeholders were also surveyed and interviewed about their participation. Healthcare professionals (n = 93) were surveyed to elicit their responses to learning through poetry and its acceptability as a learning tool. Poems conveyed a shared narrative of different aspects of lived experience, often owing to atypical symptoms, misunderstandings by professionals, lack of support pathways, and a continuous struggle to adapt. Stakeholder surveys indicated it was a valuable experience to both co-create and respond to the poems, whilst group interviews revealed people’s experiences of the research poetry were characterised by reflection on lived experience, curiosity and exploration. Healthcare professionals’ responses reinforced poetry’s capacity to stimulate cognitive and affective learning specific to rare dementia support and prompt both empathy and critical thinking in practice. As the largest poetry-based study that we are aware of, this novel accessible approach of creating group poems yielded substantial information about the experiences and needs of those affected by rarer dementia and how poetry can contribute to healthcare education and training.
Improving Well-Being and Fostering Health-Oriented Leadership among Leaders in Small and Medium-Sized Enterprises (SMEs): A Systematic Review
Authors: Erschens Rebecca , Adam Sophia Helen , Schröpel Carla , Diebig Mathias , Rieger Monika A. , Gündel Harald , Zipfel Stephan , Junne Florian
Published: February 2024

Leaders of small and medium-sized enterprises (SMEs) are often confronted with specific burdens, which frequently result in increased levels of stress. Leadership behaviour, in turn, has a significant impact on employees’ health and performance. Using the Population, Intervention, Comparison, Outcome (PICO) method, we conducted a systematic literature search covering publications from 2002 to 2023 using PubMed, PsycInfo and Business Source Premier on stress-reducing and well-being-improving interventions for SME leaders. The Effective Public Health Practice Project (EPHPP) Quality Assessment Tool was used to assess the methodological quality and risk of bias of the included studies regarding selection bias, study design, confounders, blinding, data collection, withdrawal and drop-out. Of the 3150 identified publications, 6 were included after screening. The studies varied in content (cognitive behavioural therapy [CBT]-based, psychoeducation, and mixed interventions) and approach (individual- and organisation-centred). Not all of the examined interventions provided significant outcomes. However, CBT-based and individualised approaches showed a positive trend in reducing SME leaders’ psychosocial stress and improving their well-being. Despite the limited data, it can be concluded that such interventions are beneficial for leaders and their specific needs. Future research should focus on tailored approaches, derived from well-founded theories and integrative interventions addressing SME leaders.
Determinants of Continuance Intention to Use Hearing Aids among Older Adults in Tehran (Iran)
Authors: Jorbonyan Abdolhakim , Abolfathi Momtaz Yadollah , Foroughan Mahshid , Mehrkian Saeideh
Published: February 2024

The present study seeks to evaluate the factors determining the continuance intention to use hearing aids in older adults. This cross-sectional study was carried out in 2021. The technology post-acceptance model (PAM) framework was used to develop a model for the continuance intention to use hearing aids. In total, 300 hearing aid users aged ≥60 years, who were selected via a randomized stratified sampling method, completed the self-evaluation tools used in this study. With a mean age of 71.38 years (SD = 8), the participants comprised 50.7% and 49.3% females and males, respectively. The path analysis results showed that the continuance intention to use hearing aids was positively and significantly influenced by the actual use of hearing aids, the perceived benefits, satisfaction, confirmation, self-efficacy in using hearing aids, an extraverted personality trait, self-perceived hearing handicap, and perceived social support. The main results of the present study can help hearing care providers develop a better understanding of older users to design effective rehabilitation strategies and ensure their continuance intention to use hearing aids.