bluuebunny/crossref_metadata_2025 huggingface dataset:
Psychosocial Wellbeing among Patients with Breast Cancer during COVID-19
Authors: Maculaitis Martine C. , Liu Xianchen , Berk Alexandra , Massa Angelina , Weiss Marisa C. , Kurosky Samantha K. , Li Benjamin , McRoy Lynn
Published: March 2023

The impact of coronavirus disease 2019 (COVID-19) on the wellbeing of breast cancer (BC) patients is not well understood. This study described psychosocial problems among these patients in the United States (US) during the COVID-19 pandemic. Data were collected from BC patients via an online self-report survey between 30 March–6 July 2021 to assess the prevalence of COVID-19 diagnosis history and potential depression, health-related quality of life, COVID-related stress, and financial toxicity. Patients with early-stage (eBC) and metastatic (mBC) disease were compared. Of 669 patients included in the analysis, the prevalence of COVID-19 diagnosis history (10.9% versus 7.7%) and potential depression (33.7% versus 28.3%) were higher in mBC than eBC patients. Patients with eBC (versus mBC) had higher scores on nearly all Functional Assessment of Cancer Therapy-Breast scales (all, p < 0.001). For the Psychological Impact of Cancer subscales measuring negative coping strategies, the emotional distress score was the highest (9.1 ± 1.8) in the overall sample. Comprehensive Score for Financial Toxicity scores were higher in eBC than in mBC patients (24.2 ± 11.3 vs. 21.3 ± 10.2, p < 0.001). Overall, the COVID-19-related stress score was highest for danger/contamination fears (8.2 ± 5.6). In conclusion, impairments to psychosocial wellbeing among patients during the pandemic were observed, particularly financial toxicity and poor mental health and emotional functioning, with greater problems among mBC patients.
Prostate Cancer Metastasis to Stomach: A Case Report and Review of Literature
Authors: Moshref Leena , Abidullah Mohammad , Czaykowski Piotr , Chowdhury Amitava , Wightman Robert , Hebbard Pamela
Published: March 2023

Metastatic prostate cancer is a common diagnosis with a protracted but terminal course. Gastrointestinal (GI) tract involvement is extremely rare, and reportedly portends a poor prognosis. It can present years after the initial prostate cancer diagnosis. Only fifteen cases of prostate cancer metastasis to the stomach have been reported in the literature. We report a case of a 72-year-old man with metastatic castration-resistant prostate cancer and extensive bony involvement. He presented a decade after the diagnosis of prostate cancer with signs of heartburn; a gastric biopsy was initially believed to represent primary gastric carcinoma, but subsequently a diagnosis of prostate cancer metastatic to the stomach was confirmed. This case highlights the importance of the provision of a pertinent clinical history and clinical differential diagnosis at the time of submission of surgical pathology specimens, as well as highlighting the need to have a low index of suspicion to pursue additional pathologic markers whenever a presumed second adenocarcinoma is noted in the context of a patient having a history of current or prior advanced-stage adenocarcinoma of another site. The correct diagnosis can shield the patient from the morbidity of inappropriate surgical or medical management.
The Clinical Significance of Incidental GIT Uptake on PET/CT: Radiologic, Endoscopic, and Pathologic Correlation
Authors: Hosni Mohammad N. , Kassas Mutaz , Itani Mohamad I. , Rahal Mahmoud A. , Al-Zakleet Safaa , El-Jebai Malak , Abi-Ghanem Alain S. , Moukaddam Hicham , Haidar Mohamad , Vinjamuri Sobhan , Shaib Yasser H.
Published: March 2023

Incidental gastrointestinal tract (GIT) [18F]-Fluorodeoxyglucose (FDG) uptake in positron emission technology/computed tomography (PET/CT) is an unexpected and often complicated finding for clinicians. This retrospective study reviewed 8991 charts of patients who underwent PET/CT: 440 patients had incidental GIT uptake, of which 80 underwent endoscopy. Patient characteristics, imaging parameters, and endoscopic findings were studied. Of the 80 patients, 31 had cancer/pre-cancer lesions (16 carcinomas; 15 pre-malignant polyps). Compared to patients with benign/absent lesions, patients with cancer/pre-cancer lesions were significantly older (p = 0.01), underwent PET/CT for primary evaluation/staging of cancer (p = 0.03), had focal GIT uptake (p = 0.04), and had lower GIT uptake (p = 0.004). Among patients with focal uptake, an SUVmax of 9.2 had the highest sensitivity (0.76) and specificity (0.885) in detecting cancer/pre-cancerous lesions. Lower GIT uptake was most common in the sigmoid colon, and upper GIT uptake was most frequent in the stomach. In a bivariate analysis, predictors of cancer/pre-cancer were older age, PET/CT indicated for primary evaluation, focal uptake, uptake in the lower GIT, and higher SUVmax. Further endoscopic investigation is warranted for patients with incidental GIT uptake, especially in the elderly or those presenting for primary evaluation with PET/CT, with the following findings on imaging: lower GIT uptake, focal uptake, or high SUVmax.
Automatic Classification of Particles in the Urine Sediment Test with the Developed Artificial Intelligence-Based Hybrid Model
Authors: Yildirim Muhammed , Bingol Harun , Cengil Emine , Aslan Serpil , Baykara Muhammet
Published: March 2023

Urine sediment examination is one of the main tests used in the diagnosis of many diseases. Thanks to this test, many diseases can be detected in advance. Examining the results of this test is an intensive and time-consuming process. Therefore, it is very important to automatically interpret the urine sediment test results using computer-aided systems. In this study, a data set consisting of eight classes was used. The data set used in the study consists of 8509 particle images obtained by examining the particles in the urine sediment. A hybrid model based on textural and Convolutional Neural Networks (CNN) was developed to classify the images in the related data set. The features obtained using textural-based methods and the features obtained from CNN-based architectures were combined after optimizing using the Minimum Redundancy Maximum Relevance (mRMR) method. In this way, we aimed to extract different features of the same image. This increased the performance of the proposed model. The CNN-based ResNet50 architecture and textural-based Local Binary Pattern (LBP) method were used for feature extraction. Finally, the optimized and combined feature map was classified at different machine learning classifiers. In order to compare the performance of the model proposed in the study, results were also obtained from different CNN architectures. A high accuracy value of 96.0% was obtained in the proposed model.
Notions of Completeness in the EPR Discussion
Authors: Krizek Gerd Christian , Mairhofer Lukas
Published: March 2023

We explore the different notions of completeness applied in the EPR discussion following and amending the thorough analysis of Arthur Fine. To this aim, we propose a classification scheme for scientific theories that provides a methodology for analyzing the different levels at which interpretive approaches come into play. This allows us to contrast several concepts of completeness that operate on specific levels of the theory. We introduce the notion of theory completeness and compare it with the established notions of Born completeness, Schrödinger completeness and bijective completeness. We relate these notions to the recent concept of ψ-completeness and predictable completeness. The paper shows that the EPR argument contains conflicting versions of completeness. The confusion of these notions led to misunderstandings in the EPR debate and hindered its progress. Their clarification will thus contribute to recent debates on interpretational issues of quantum mechanics. Finally, we discuss the connection between the EPR paper and the Einstein–Rosen paper with regard to the question of completeness.
Adaptive Bit-Labeling Design for Probabilistic Shaping Based on Residual Source Redundancy
Authors: Chen Chen , Chen Qiwang , Liu Sanya , Zhou Lin
Published: March 2023

By using the residual source redundancy to achieve the shaping gain, a joint source-channel coded modulation (JSCCM) system has been proposed as a new solution for probabilistic amplitude shaping (PAS). However, the source and channel codes in the JSCCM system should be designed specifically for a given source probability to ensure optimal PAS performance, which is undesirable for systems with dynamically changing source probabilities. In this paper, we propose a new shaping scheme by optimizing the bit-labeling of the JSCCM system. Instead of the conventional fixed labeling, the proposed bit-labelings are adaptively designed according to the source probability and the source code. Since it is simple to switch between different labelings according to the source probability and the source code, the proposed design can be considered as a promising low complexity alternative to obtain the shaping gain for sources with different probabilities. Numerical results show that the proposed bit-labelings can significantly improve the bit-error rate (BER) performance of the JSCCM system.
ECG Signal Denoising Method Based on Disentangled Autoencoder
Authors: Lin Haicai , Liu Ruixia , Liu Zhaoyang
Published: March 2023

The electrocardiogram (ECG) is widely used in medicine because it can provide basic information about different types of heart disease. However, ECG data are usually disturbed by various types of noise, which can lead to errors in diagnosis by doctors. To address this problem, this study proposes a method for denoising ECG based on disentangled autoencoders. A disentangled autoencoder is an improved autoencoder suitable for denoising ECG data. In our proposed method, we use a disentangled autoencoder model based on a fully convolutional neural network to effectively separate the clean ECG data from the noise. Unlike conventional autoencoders, we disentangle the features of the coding hidden layer to separate the signal-coding features from the noise-coding features. We performed simulation experiments on the MIT-BIH Arrhythmia Database and found that the algorithm had better noise reduction results when dealing with four different types of noise. In particular, using our method, the average improved signal-to-noise ratios for the three noises in the MIT-BIH Noise Stress Test Database were 27.45 db for baseline wander, 25.72 db for muscle artefacts, and 29.91 db for electrode motion artefacts. Compared to a denoising autoencoder based on a fully convolutional neural network (FCN), the signal-to-noise ratio was improved by an average of 12.57%. We can conclude that the model has scientific validity. At the same time, our noise reduction method can effectively remove noise while preserving the important information conveyed by the original signal.
Attention-Enhanced Lightweight One-Stage Detection Algorithm for Small Objects
Authors: Jia Nan , Wei Zongkang , Li Bangyu
Published: March 2023

The majority of object detection algorithms based on convolutional neural network are focused on larger objects. In order to improve the accuracy and efficiency of small object detection, a novel lightweight object detection algorithm with attention enhancement is proposed in this paper. The network part of the proposed algorithm is based on a single-stage framework and takes MobileNetV3-Large as a backbone. The representation of shallower scale features in the scale fusion module is enhanced by introducing an additional injection path from the backbone and a detection head specially responsible for detecting small objects is added. Instead of pooling operators, dilated convolution with hierarchical aggregation is used to reduce the effect of background pixels on the accuracy of small object locations. To improve the efficacy of merging, the spatial and channel weights of scale features are modified adaptively. Last but not least, to improve the representation of small objects in the training datasets, the Consistent Mixed Cropping method is also proposed. The small labels of standard datasets are expanded with the self-collected samples for the training of the algorithm network. According to the test results and visualization on the 64-Bit Extended (X86-64) platform and embedded Advanced RISC Machine (ARM) platform, we find that the average accuracy (mAP) of the proposed algorithm is 4.6% higher than YOLOv4 algorithm, which achieves better small object detection performance than YOLOv4 algorithm, and the computational complexity is only 12% of YOLOv4 algorithm.
No-Reference Image Quality Assessment Using the Statistics of Global and Local Image Features
Authors: Varga Domonkos
Published: March 2023

Methods of image quality assessment are widely used for ranking computer vision algorithms or controlling the perceptual quality of video and streaming applications. The ever-increasing number of digital images has encouraged the research in this field at an accelerated pace in recent decades. After the appearance of convolutional neural networks, many researchers have paid attention to different deep architectures to devise no-reference image quality assessment algorithms. However, many systems still rely on handcrafted features to ensure interpretability and restrict the consumption of resources. In this study, our efforts are focused on creating a quality-aware feature vector containing information about both global and local image features. Specifically, the research results of visual physiology indicate that the human visual system first quickly and automatically creates a global perception before gradually focusing on certain local areas to judge the quality of an image. Specifically, a broad spectrum of statistics extracted from global and local image features is utilized to represent the quality-aware aspects of a digital image from various points of view. The experimental results demonstrate that our method’s predicted quality ratings relate strongly with the subjective quality ratings. In particular, the introduced algorithm was compared with 16 other well-known advanced methods and outperformed them by a large margin on 9 accepted benchmark datasets in the literature: CLIVE, KonIQ-10k, SPAQ, BIQ2021, TID2008, TID2013, MDID, KADID-10k, and GFIQA-20k, which are considered de facto standards and generally accepted in image quality assessment.
Video Saliency Object Detection with Motion Quality Compensation
Authors: Wang Hengsen , Chen Chenglizhao , Li Linfeng , Peng Chong
Published: March 2023

Video saliency object detection is one of the classic research problems in computer vision, yet existing works rarely focus on the impact of input quality on model performance. As optical flow is a key input for video saliency detection models, its quality significantly affects model performance. Traditional optical flow models only calculate the optical flow between two consecutive video frames, ignoring the motion state of objects over a period of time, leading to low-quality optical flow and reduced performance of video saliency object detection models. Therefore, this paper proposes a new optical flow model that improves the quality of optical flow by expanding the flow perception range and uses high-quality optical flow to enhance the performance of video saliency object detection models. Experimental results on the datasets show that the proposed optical flow model can significantly improve optical flow quality, with the S-M values on the DAVSOD dataset increasing by about 39%, 49%, and 44% compared to optical flow models such as PWCNet, SpyNet, and LFNet. In addition, experiments that fine-tuning the benchmark model LIMS demonstrate that improving input quality can further improve model performance.
Accuracy Maps of Weigh-In-Motion Systems for Direct Enforcement
Authors: Gajda Janusz , Burnos Piotr , Sroka Ryszard , Daniol Mateusz
Published: March 2023

The need to protect road infrastructure and the environment, as well as to increase the safety of road users and to ensure fair conditions of competition in road transport, requires an increase in the efficiency of the elimination of overloaded vehicles from road traffic. The replacement of “manual” vehicle control (carried out by inspectors of the relevant services) by automatic control can ensure that these are highly effective. Such control can be implemented directly on the basis of weighing results obtained from weigh-in-motion (WIM) systems. The high sensitivity of WIM systems to various interfering factors is an obstacle to the full implementation of this goal. This paper presents a concept for accuracy maps determined for direct enforcement WIM systems. The use of such maps allows for the minimization of the probability of an error consisting in classifying a normative vehicle as an overloaded one.
Human Activity Recognition Based on Two-Channel Residual–GRU–ECA Module with Two Types of Sensors
Authors: Wang Xun , Shang Jie
Published: March 2023

With the thriving development of sensor technology and pervasive computing, sensor-based human activity recognition (HAR) has become more and more widely used in healthcare, sports, health monitoring, and human interaction with smart devices. Inertial sensors were one of the most commonly used sensors in HAR. In recent years, the demand for comfort and flexibility in wearable devices has gradually increased, and with the continuous development and advancement of flexible electronics technology, attempts to incorporate stretch sensors into HAR have begun. In this paper, we propose a two-channel network model based on residual blocks, an efficient channel attention module (ECA), and a gated recurrent unit (GRU) that is capable of the long-term sequence modeling of data, efficiently extracting spatial–temporal features, and performing activity classification. A dataset named IS-Data was designed and collected from six subjects wearing stretch sensors and inertial sensors while performing six daily activities. We conducted experiments using IS-Data and a public dataset called w-HAR to validate the feasibility of using stretch sensors in human action recognition and to investigate the effectiveness of combining flexible and inertial data in human activity recognition, and our proposed method showed superior performance and good generalization performance when compared with the state-of-the-art methods.
Chinese Brand Identity Management Based on Never-Ending Learning and Knowledge Graphs
Authors: Li Dalin , Wang Yijin , Wang Guansu , Lu Jiadong , Zhu Yong , Bella Gábor , Liang Yanchun
Published: March 2023

Brand identity (BI) refers to the individual characteristics of an enterprise or a certain brand in the market and in the mind of the public. It reflects the evaluation and recognition of the public on the brand and is the core of the market strategy. Successful BI management can bring great business value. Nowadays, the BI management methods based on Internet, big data, and AI are widely adopted. However, they are also confronted with problems, such as accuracy, effectiveness, and sustainability, especially for the Chinese BI. Our work applies the knowledge graph (KG) and never-ending learning (NEL) for exploring efficient Chinese BI management methods. We adapt the NEL framework for the sustainability. In order to improve the accuracy and effectiveness, we express the BI knowledge with KGs and propose two methods in the subsystem components of NEL: (1) the BI evaluation model based on KG and two-dimensional bag-of-words; (2) the Apriori based on KG. In the knowledge integrator of NEL, we propose the synonym KGs for suppressing the concept duplication and drift. The experimental results show that our method reached high consistency with the experts of BI management and the industry reports.
Mobile Broadband Adoption, Performance Measurements and Methodology: A Review
Authors: Umoh Vincent , Ekpe Unwana , Davidson Innocent , Akpan Joseph
Published: March 2023

Mobile broadband (MBB) penetration has deepened globally over the last twenty years. This is largely due to the adoption of smart devices, improved mobile communications network coverage, and the perpetual drive to develop ever faster mobile and wireless communication technologies. However, information on the quality of service (QoS) delivered by MBB operators to the end users remains an issue of concern. This has driven independent researchers and mobile communication industry regulators to develop methodologies for independent and unbiased evaluation of the QoS offered by MBB networks. This paper provides a detailed review of MBB adoption and penetration across several regions of the world. It also includes the existing methodologies for evaluating the performance of MBB systems as experienced by the end user. Specifically, methodologies such as the drive and walk tests, crowd-sourced mobile device-based methods and the software applications they employ, and the dedicated measurement testbeds are reviewed. Based on this, the challenges of adopting each of the methods are discussed in order to make a case for the development of more robust, partially autonomous and scalable MBB measurement platforms for the future.
A Critical Review on the Status and Progress of Microalgae Cultivation in Outdoor Photobioreactors Conducted over 35 Years (1986–2021)
Authors: Sarker Nilay Kumar , Kaparaju Prasad
Published: March 2023

Microalgae, a renewable bio-resource, are considered a potential value-added commodity and a tool to combat climate change. Microalgal research has received worldwide attention recently. Different perspectives have been explored, but cultivation in outdoor photobioreactors (PBRs) is still a less explored field. This review summarizes the studies conducted on the microalgae cultivated in outdoor PBRs only. The locations, algal strains, PBRs, and cultivation media used in these studies were identified and tabulated. Different aspects of outdoor algal cultivation in PBRs, such as temperature control, light intensity control, photosynthetic efficiency (PE), the outdoor adaptation of strains, PBR designs, and algal growth and biochemical composition variation from the weather, were studied and reviewed. A brief review of downstream processes and environmental and economic impacts was also conducted. This review summarizes what has been carried out in this field so far and will help researchers to determine what further work needs to be conducted and in which direction to proceed.
The Double Lanes Cell Transmission Model of Mixed Traffic Flow in Urban Intelligent Network
Authors: Tian Wenjing , Ma Jien , Qiu Lin , Wang Xiang , Lin Zhenzhi , Luo Chao , Li Yao , Fang Youtong
Published: March 2023

The connected and autonomous vehicle (CAV) is promised to ease congestion in the future with the rapid development of related technologies in recent years. To explore the characteristics of mixed-traffic flow and the dynamic transmission mechanism, this paper firstly detailed the car-following model of different vehicle types, establishing the fundamental diagram of the mixed-traffic flow through considering the different penetration rates and fleet size of CAV. Secondly, this paper constructed the lane-changing judgment mechanism based on the random utility theory. Finally, the paper proposed a lane-level dynamic cell transmission process, combined with a lane-changing strategy and cell transmission model. The effectiveness and feasibility of the model are verified using simulation analysis. This model makes a systematic, theoretical analysis from the perspective of the internal operation mechanism of traffic flow, and the lane-level traffic strategy provides a theoretical basis for balancing urban lane distribution and intelligent traffic management and control.
Different Control Techniques of Permanent Magnet Synchronous Motor with Fuzzy Logic for Electric Vehicles: Analysis, Modelling, and Comparison
Authors: Kakouche Khoudir , Oubelaid Adel , Mezani Smail , Rekioua Djamila , Rekioua Toufik
Published: March 2023

This paper presents a detailed analysis and comparative study of three torque control methodologies with fuzzy logic, namely direct torque control (DTC), fuzzy direct torque control (FDTC), and model predictive direct torque control (MPDTC), for PMSM control applied to an electric vehicle. The three control strategies are designed and developed to control torque in order to achieve vehicle requirements, such as minimum torque and flux ripples, fast dynamic response, and maximum efficiency. To enhance the performance and efficiency of the overall drive, a bidirectional DC/DC buck-boost converter is connected to the Li-ion battery. In addition, a fuzzy logic controller (FLC) is used in the outer loop to control the speed of the PMSM. As a result, the tuning difficulty of the conventional proportional-integral (PI) controller is avoided and the dynamic speed response is improved. Simulation results obtained from the three control techniques establish that the proposed system via the MPDTC technique reduces the torque ripples, flux ripples, reduces the THD of the PMSM current, and achieves a faster transient response. Additionally, the MPTDC technique enabled the electric vehicle to cover the longest distance, with approximately 110.72 km in a charging cycle. The real-time simulation is developed using the RT LAB simulator, and the obtained results confirm the superiority of the MPDTC technique over conventional DTC and FDTC techniques.
In-Wheel Motor Drive Systems for Electric Vehicles: State of the Art, Challenges, and Future Trends
Authors: Deepak Kritika , Frikha Mohamed Amine , Benômar Yassine , El Baghdadi Mohamed , Hegazy Omar
Published: March 2023

Recently, there has been significant attention given to the electrification of transportation due to concerns about fossil fuel depletion and environmental pollution. Conventional drive systems typically include a clutch, reduction gear, and mechanical differential, which results in power loss, noise, vibration, and additional maintenance. However, in-wheel motor drive technology eliminates the need for these components, providing benefits such as higher system efficiency, improved wheel control, and increased passenger comfort. This article offers a comprehensive review of the technology and development of in-wheel motor drives. It begins with an overview of in-wheel motor drives in electric vehicles, followed by an exploration of the types of electric motors suitable for in-wheel motor drives. The paper then presents an industrial state of the art of in-wheel motors, comparing them with conventional motor drives, and reviews the implemented power electronics, control system, and cooling systems. Finally, the paper concludes by providing an outlook on the challenges and future trends of in-wheel drive systems.
Techno-Economic Analysis of Rooftop Photovoltaic System under Different Scenarios in China University Campuses
Authors: Zhu Xingyu , Lv Yuexia , Bi Jinpeng , Jiang Mingkun , Su Yancai , Du Tingting
Published: March 2023

The expansively unutilized rooftop spaces in the university campuses can provide an excellent opportunity for the installation of solar photovoltaic systems to achieve renewable electricity generation and carbon dioxide reduction. Based on available rooftop areas and local solar radiation situations, technical potential and economic benefits of rooftop photovoltaic system under seven scenarios were carried out for three university campuses located in different solar zones in China. The potential capacity of photovoltaic installations on building’s flat rooftops in Tibet University, Qinghai University, and Qilu University of Technology reaches 11,291 kW, 9102 kW, and 3821 kW, corresponding to the maximum annual power generation of 28.19 GWh, 18.03 GWh, and 5.36 GWh, respectively. From the perspective of economic analysis, PV systems installed in “full self-consumption” mode are superior to those installed in “full-feed-into-grid” mode for all three study cases. The highest return on investment of PV systems installed on flat and pitched rooftops can be achieved at 208% and 204%, respectively, in Tibet University. The payback period for PV systems installed on flat rooftops is 1 year in Tibet University, and less than 8 years for both Qinghai University and Qilu University of Technology, respectively. Results reveal that rooftop photovoltaic systems can significantly help the universities to move towards sustainability.
Ecological Evaluation of the Sustainability of City Forests
Authors: Cvejić Milijana , Joksimović Marko , Tomićević-Dubljević Jelena , Rakonjac Ljubinko , Medarević Milan , Malinić Vladimir
Published: March 2023

The Košutnjak forest in the city of Belgrade, Serbia, with an area of 259 ha, provides ecological and social benefits to its inhabitants, but its composition has changed in the last 20 years: forest areas have decreased, people have become irresponsible towards the forest and forest soil, and forest degradation is evident. The question is whether the forest has the potential to regenerate and survive. The horizontal assessment of attributes was carried out using data from the official forest database of the administrative unit “Košutnjak (2007–2016)”, which, in conjunction with the basic forest, defines indicators of change, stability, and self-renewal, which assume sustainability and can be a useful tool for sustainable forest management. The attributes and indicators are processed on a three-level alphanumeric scale in Microsoft Excel, and the data collected and analyzed are mapped using ArcGis 9.3. The ability of forests to survive without human intervention was evaluated using the EEFS method of ecological assessment of forest sustainability, which was used for the first time in this study. The results showed that forest change was significant, stability was medium, and self-renewal was low on most sections, so forest sustainability was rated as unlikely. The EEFS method used provided results that can form the basis for a forest management strategy in the city and a platform for the long-term monitoring of forest condition.
Assessing Forest Biodiversity: A Novel Index to Consider Ecosystem, Species, and Genetic Diversity
Authors: Ette Jana-Sophie , Sallmannshofer Markus , Geburek Thomas
Published: March 2023

Rates of biodiversity loss remain high, threatening the life support system upon which all human life depends. In a case study, a novel biodiversity composite index (BCI) in line with the Convention on Biological Diversity is established in Tyrol, Austria, based on available national forest inventory and forest typing data. Indicators are referenced by ecological modeling, protected areas, and unmanaged forests using a machine learning approach. Our case study displays an average biodiversity rating of 57% out of 100% for Tyrolean forests. The respective rating for ecosystem diversity is 49%; for genetic diversity, 53%; and for species diversity, 71%. Coniferous forest types are in a more favorable state of preservation than deciduous and mixed forests. The BCI approach is transferable to Central European areas with forest typing. Our objective is to support the conservation of biodiversity and provide guidance to regional forest policy. BCI is useful to set restoration priorities, reach conservation targets, raise effectiveness of financial resources spent on biodiversity conservation, and enhance Sustainable Forest Management.
Effects of External Resistance, New Electrode Material, and Catholyte Type on the Energy Generation and Performance of Dual-Chamber Microbial Fuel Cells
Authors: López Zavala Miguel Ángel , Cámara Gutiérrez Iris Cassandra
Published: March 2023

In this study, the effects of an external resistance, new electrode material, and non-conventional catholyte on the energy generation and performance of a dual-chamber MFC were evaluated. Ten different resistances (15 Ω–220 kΩ), hydrophilically-treated graphene and graphite electrodes, and a 0.1 M HCl solution as a catholyte were assessed. The results showed that greater energy generation and power density were achieved at an external resistance of 2 kΩ and internal resistance between 2 and 5 kΩ on average; meanwhile, the greatest coulombic efficiency was obtained at the lowest external resistance evaluated (15 Ω). Therefore, it is recommended to operate the MFCs at the external resistance between 2 and 5 kΩ to ensure the maximum power generation of the dual chamber MFCs. Regarding the two electrode materials evaluated as an anode and cathode, hydrophilically-treated graphene was found to be a much better material to enhance the energy production and performance of the MFC system; therefore, its use is suggested in experimental and practical applications. On the other hand, the use of HCl as a catholyte enhanced the performance of MFC (constant and steady potential and greater coulombic efficiency) in most cases.
Resampling Imbalanced Network Intrusion Datasets to Identify Rare Attacks
Authors: Bagui Sikha , Mink Dustin , Bagui Subhash , Subramaniam Sakthivel , Wallace Daniel
Published: March 2023

This study, focusing on identifying rare attacks in imbalanced network intrusion datasets, explored the effect of using different ratios of oversampled to undersampled data for binary classification. Two designs were compared: random undersampling before splitting the training and testing data and random undersampling after splitting the training and testing data. This study also examines how oversampling/undersampling ratios affect random forest classification rates in datasets with minority dataor rare attacks. The results suggest that random undersampling before splitting gives better classification rates; however, random undersampling after oversampling with BSMOTE allows for the use of lower ratios of oversampled data.
Optimization of Artemia Feed Regimes for Larval Giant Kōkopu (Galaxias argenteus)
Authors: McKay William , Jeffs Andrew
Published: March 2023

Optimizing the initial live feed is critical to success in fish larviculture in terms of both larval health and productivity. It is also vitally important due to the significant cost of provisioning live feeds. Glaxiids are high-value diadromous fish species found in parts of the Southern Hemisphere, which are wild-harvested and sold for human consumption in their larval form. In the emerging aquaculture of galaxiids, the live feed makes up a great proportion of the production cycle and is therefore a significant factor in achieving the economic viability of their production. In New Zealand, the endemic galaxiid species giant kōkopu (Galaxias argenteus) is considered suitable for aquaculture; however, little is known of their larval-feeding requirements. This study compares the growth performance and survival of giant kōkopu larvae over a four-week period when fed different proportions of first-molt Artemia nauplii (instar-I) and enriched, second-molt-onward Artemia (instar-II+) for different durations. The larvae in the treatment group which received the greatest proportion of Instar-I Artemia for the longest duration had the lowest mean wet weight and survival, leading to the production of the lowest total biomass of fish larvae when compared to the other feed treatments. The feed treatment that received only instar-II+ Artemia achieved an equally best total productivity. While the treatment fed a partial initial duration of mixed instar-I and instar-II+ Artemia achieved the same total productivity, the individual larvae were heavier and their body length was longer. The latter feed treatment appears to offer the best balance between the availability of feed particles in the optimum size range and a higher level of digestibility given that instar-I Artemia had higher levels of highly unsaturated fatty acids and polyunsaturated fatty acids.
Comment on Hu et al. Determination of 2-Pentanol Enantiomers via Chiral GC-MS and Its Sensory Evaluation in Baijiu. Foods 2022, 11, 2584
Authors: Frański Rafał
Published: March 2023

Recently, Hu et al. have published a very interesting paper concerning the GC-MS analysis of 2-pentanol enantiomers in four types of Baijiu, a strong alcoholic beverage, which is of importance to Chinese social culture [...]
Reply to Frański, R. Comment on “Hu et al. Determination of 2-Pentanol Enantiomers via Chiral GC-MS and Its Sensory Evaluation in Baijiu. Foods 2022, 11, 2584”
Authors: Hu Lisha , Dai Yifeng
Published: March 2023

The comments [...]
1H NMR Reveals the Mechanism of Potassium Lactate on Proteolysis and Taste Metabolites of Rugao Ham
Authors: Cai Xin , Liao Renyong , Pan Daodong , Xia Qiang , Wang Ying , Geng Fang , Zhou Changyu , Cao Jinxuan
Published: March 2023

To deepen the understanding of the effect of potassium lactate on the taste of Rugao ham, proteolysis index, enzyme activities and protein degradation of Rugao ham salted with potassium lactate (0%, 0.5%, 1%, 2%) were investigated. Metabolites of Rugao ham were identified by 1H nuclear magnetic resonance (NMR) spectroscopy and the metabolic pathways of the key metabolites were enriched by the Kyoto Encyclopedia of Genes and Genomes (KEGG); the relationship between taste and metabolites was assessed by partial least square discriminant analysis (PLS-DA). The hams with 2% potassium lactate showed lower cathepsin B and L activities, and higher aminopeptidase activities than that of the control group. The contents of free amino acids and organic acids significantly increased from the control to the treatment of 2% potassium lactate. PLS-DA further demonstrated that aspartate, glutamate, alanine, serine, threonine, acetate, lactate, succinate, carnosine, β-glucose and glycerol were the key metabolites to improve the taste of Rugao ham in the treatment of 2% potassium lactate. Metabolic pathways analysis further demonstrated that amino acids metabolism was the main pathway for the taste development of Rugao ham.
Quality Control of Jinhua Ham from the Influence between Proteases Activities and Processing Parameters: A Review
Authors: Hu Shiqi , Xu Xinglian , Zhang Wangang , Li Chunbao , Zhou Guanghong
Published: March 2023

Endogenous proteases are significant for Jinhua ham quality. Protein degradation affects the chemical traits, texture and the formation of flavor substances. Protease activities are affected by different process parameters, such as processing temperature, maturation time, salt content and the drying rate. They affect ham quality, which can be controlled by process parameters. The influences of key factors on Jinhua ham quality are briefly summarized, which can provide a theoretical basis for the selection of specific parameters in dry-cured ham processing. Furthermore, some suggestions are proposed for correcting and improving the flavor and textural defects of ham, yet the effectiveness depends on the operating conditions. The determination of enzyme activity is not real-time and unsupervised at the moment. Future research will focus on the determination of the actual endogenous protease activity and the quantitative relationship between the enzyme activity and main processing parameters.
Effects of Protein Components on the Chemical Composition and Sensory Properties of Millet Huangjiu (Chinese Millet Wine)
Authors: Zhou Chenguang , Zhou Yaojie , Liu Tianrui , Li Bin , Hu Yuqian , Zhai Xiaodong , Zuo Min , Liu Siyao , Yang Zhen
Published: March 2023

Millet Huangjiu is a national alcoholic beverage in China. The quality of Chinese millet Huangjiu is significantly influenced by the protein components in the raw materials of millet. Therefore, in this study, the impact of different protein components on the quality of millet Huangjiu was investigated by adding exogenous proteins glutelin and albumin either individually or in combination. The study commenced with the determination of the oenological parameters of different millet Huangjiu samples, followed by the assessment of free amino acids and organic acids. In addition, the volatile profiles of millet Huangjiu were characterized by employing HS-SPME-GC/MS. Finally, a sensory evaluation was conducted to evaluate the overall aroma profiles of millet Huangjiu. The results showed that adding glutelin significantly increased the contents of total soluble solids, amino acid nitrogen, and ethanol in millet Huangjiu by 32.2%, 41.5%, and 17.7%, respectively. Furthermore, the fortification of the fermentation substrate with glutelin protein was found to significantly enhance the umami (aspartic and glutamic acids) and sweet-tasting (alanine and proline) amino acids in the final product. Gas chromatography-quadrupole mass spectrometry coupled with multivariate statistical analysis revealed distinct impacts of protein composition on the volatile organic compound (VOC) profiles of millet Huangjiu. Excessive glutelin led to an over-accumulation of alcohol aroma, while the addition of albumin protein proved to be a viable approach for enhancing the ester and fruity fragrances. Sensory analysis suggested that the proper amount of protein fortification using a Glu + Alb combination could enhance the sensory attributes of millet Huangjiu while maintaining its unique flavor characteristics. These findings suggest that reasonable adjustment of the glutelin and albumin contents in millet could effectively regulate the chemical composition and improve the sensory quality of millet Huangjiu.
Development of a Rapid and Non-Destructive Method for the Detection of Water Addition in Octopus Species (Octopus vulgaris and Eledone cirrhosa) Using Time Domain Reflectometry (TDR)
Authors: Teixeira Bárbara , Vieira Helena , Martins Sandra , Mendes Rogério
Published: March 2023

Consumer expectations regarding the quality of octopus are often frustrated and dissatisfaction is frequent, namely due to the excessive reduction in weight after cooking. Therefore, a rapid and non-destructive method based in time domain reflectometry (TDR) was developed for the control of water added to octopus (Octopus vulgaris and Eledone cirrhosa). O. vulgaris had significant higher values of moisture content, moisture/protein ratio, and cooking loss than E. cirrhosa. Immersion in freshwater increased the weight of O. vulgaris in ca. 32% after 32 h, and of E. cirrhosa in ca. 21% after 36 h, and cooking losses increased about 13.9% and 26.1%, respectively. The results reveal how consumers can be misled by abusive water addition. Changes in electrical conductivity and TDR curves were linked with the increasing incorporation of water and dilution effect of salts from octopus muscle. TDR technology and linear discriminant analysis were combined to detect added water in octopus. The classification model developed was cross-validated and 98.6% of samples were correctly classified. The method can be used to proof the authenticity of octopus (O. vulgaris and E. cirrhosa) or to detect fraudulent practices regarding added water.
Prevention of Chilling Injury in Pomegranates Revisited: Pre- and Post-Harvest Factors, Mode of Actions, and Technologies Involved
Authors: Maghoumi Mahshad , Amodio Maria Luisa , Cisneros-Zevallos Luis , Colelli Giancarlo
Published: March 2023

The storage life of pomegranate fruit (Punica granatum L.) is limited by decay, chilling injury, weight loss, and husk scald. In particular, chilling injury (CI) limits pomegranate long-term storage at chilling temperatures. CI manifests as skin browning that expands randomly with surface spots, albedo brown discoloration, and changes in aril colors from red to brown discoloration during handling or storage (6–8 weeks) at <5–7 °C. Since CI symptoms affect external and internal appearance, it significantly reduces pomegranate fruit marketability. Several postharvest treatments have been proposed to prevent CI, including atmospheric modifications (MA), heat treatments (HT), coatings, use of polyamines (PAs), salicylic acid (SA), jasmonates (JA), melatonin and glycine betaine (GB), among others. There is no complete understanding of the etiology and biochemistry of CI, however, a hypothetical model proposed herein indicates that oxidative stress plays a key role, which alters cell membrane functionality and integrity and alters protein/enzyme biosynthesis associated with chilling injury symptoms. This review discusses the hypothesized mechanism of CI based on recent research, its association to postharvest treatments, and their possible targets. It also indicates that the proposed mode of action model can be used to combine treatments in a hurdle synergistic or additive approach or as the basis for novel technological developments.
Dietary Dried Jujube Fruit Powder (DJFP) Supplementation Improves Growth Performance, Antioxidant Stability, and Meat Composition in Broilers
Authors: Yang Chao , Zhu Xijin , Liu Wenyu , Huang Jie , Xie Zhijun , Yang Farong , Zhang Li , Wei Yuming
Published: March 2023

Nowadays, broiler production is faced with great challenges due to intensive culture modes, and chickens are more susceptible to oxidative stress. Consequently, synthetic antioxidants have been used to reduce this process, but their use has shown potential health risks. Thus, the use of natural ingredients has been suggested as a strategy to prevent oxidative stress. This study investigated how dietary dried jujube fruit powder (DJFP) supplementation influences the growth performance, antioxidant stability, meat composition, and nutritional quality of Cobb broilers. A total of 360 unsexed broilers (1-day-old) were randomly assigned to treatments that varied in DJFP levels: a basal diet without DJFP (control) and diets supplemented with 50 g/kg DJFP (P1), 100 g/kg DJFP (P2), and 150 g/kg DJFP (P3), with 9 replicates per treatment (90 broilers/treatment or 10 broilers/replicate). The results demonstrated improvement in the growth performance of broilers in terms of body weight (BW), body weight gain (WG), average daily body weight gain (ADG), average daily feed intake (ADFI), and feed conversion ratio (FCR) following dietary DJFP supplementation. In addition, the antioxidant stabilities in the DJFP-treated broilers were improved and inhibited the production of lipid oxidation products compared with the control, with those in the P2 group showing the most marked effect. Moreover, dietary DJFP supplementation significantly increased (p < 0.05) the activity of antioxidant enzymes in broilers. Furthermore, the breast meat of the broilers displayed an increased protein content with a simultaneous reduction in the fat content after DJFP treatment (p < 0.05). Essential amino acid levels were higher in the DJFP-supplemented groups (p < 0.05). The sum of saturated fatty acids was lower, and that of monounsaturated fatty acids (MUFAs) and the polyunsaturated fatty acid/saturated fatty acid ratio (PUFA/SFA) were higher in the DJFP-supplemented groups (p < 0.05). Together, these results indicate that up to 100 g/kg of dietary DJFP supplementation can enhance the growth performance and antioxidant capacity, meat composition, and amino acid and fatty acid composition in broiler breast meat. In conclusion, dietary DJFP supplementation is a healthy alternative to the use of synthetic antioxidants in broiler production, especially in regions rich in jujube resources.