bluuebunny/crossref_metadata_2025 huggingface dataset:
Imidacloprid Pesticide Causes Unexpectedly Severe Bioelement Deficiencies and Imbalance in Honey Bees Even at Sublethal Doses
Authors: Paleolog Jerzy , Wilde Jerzy , Gancarz Marek , Wiącek Dariusz , Nawrocka Agnieszka , Strachecka Aneta
Published: February 2023

Pesticides impair honeybee health in many ways. Imidacloprid (IMD) is a pesticide used worldwide. No information exists on how IMD impact the bees’ body bioelement balance, which is essential for bee health. We hypothesized that IMD disturbs this balance and fed the bees (in field conditions) with diets containing 0 ppb (control), 5 ppb (sublethal considered field-relevant), and 200 ppb (adverse) doses of IMD. IMD severely reduced the levels of K, Na, Ca, and Mg (electrolytic) and of Fe, Mo, Mn, Co, Cu, Ni, Se, and Zn, while those of Sn, V, and Cr (enzymatic) were increased. Levels of P, S, Ti, Al, Li, and Sr were also decreased, while only the B content (physiologically essential) was increased. The increase in Tl, Pb, and As levels (toxic) was alarming. Generally, IMD, even in sublethal doses, unexpectedly led to severe bioelement malnutrition in 69% of bioelements and to a stoichiometric mismatch in the remaining ones. This points to the IMD-dependent bioelement disturbance as another, yet unaccounted for, essential metabolic element which can interfere with apian health. Consequently, there is a need for developing methods of bioelement supplementation of the honey bee diet for better preventing bee colony decline and protecting apian health status when faced with pesticides.
Hair Follicle Development and Cashmere Traits in Albas Goat Kids
Authors: Diao Xiaogao , Yao Lingyun , Wang Xinhui , Li Sen , Qin Jiaxin , Yang Lu , He Liwen , Zhang Wei
Published: February 2023

The objectives of this trial were to study the growth and development of hair follicles and cashmere traits in cashmere goats and to provide a theoretical basis for the regulation of secondary hair follicle development and the scientific breeding selection of cashmere goats. Twelve single-fetal female kids were selected as research objects. A long-term tracking plan was created to regularly determine their growth performance, cashmere performance, and hair follicle traits. The results showed no significant difference in live weight after the first and second combing. The cashmere yield and unit yield of the first combing were significantly higher than those of the second combing (p < 0.05). Sections of hair follicles showed that the primary hair follicles are almost fully developed by 1 month, and the secondary hair follicles are fully developed by 5–6 months after birth. The primary hair follicle density (PFD) and secondary hair follicle density (SFD) were highest at birth and decreased within 1 month; and SFD was stable at 5–6 months of age. The change of MSFD took a maximum time of 2 to 3 months. The S:P increase reached its peak at 6 months. BMP4 expression increased with time. FGF2, FGF21 and BMP7 were higher at 3 months old than at the other two-time points. In conclusion, this study determined the total development time of primary and secondary hair follicles from morphology and speculated that FGF2, FGF21, and BMP7 may play a regulatory role in developing secondary hair follicles. Therefore, the period from birth to 6 months of age was the best time to regulate secondary hair follicle development in cashmere goats kids. The traits of the hair follicle and cashmere at 6 months of age could be breeding selection indicators for cashmere goats.
Anatomical Description of Loggerhead Turtle (Caretta caretta) and Green Iguana (Iguana iguana) Skull by Three-Dimensional Computed Tomography Reconstruction and Maximum Intensity Projection Images
Authors: Mohamad Jose Raduan Jaber , González-Rodríguez Eligia , Arencibia Alberto , Déniz Soraya , Carrascosa Conrado , Encinoso Mario
Published: February 2023

The growing interest in reptiles has posed a challenge to veterinary clinicians due to the lack of a standardized system to perform anatomical studies similar to those used for dogs and cats. In this paper, we have attempted to describe, employing computed tomography and subsequent three-dimensional reconstructions, the normal anatomical features that comprise the skulls of two species of reptiles: the loggerhead turtle (Caretta caretta) and the green iguana (Iguana iguana). Computed tomography (CT) and subsequent image processing allowed the identification of the bony structures that comprise the head of these species. As a result, and based on previous articles, we propose the most significant anatomical differences and similarities between these species.
Comparison of Placental HSD17B1 Expression and Its Regulation in Various Mammalian Species
Authors: Yazawa Takashi , Islam Mohammad Sayful , Imamichi Yoshitaka , Watanabe Hiroyuki , Yaegashi Kazuhide , Ida Takanori , Sato Takahiro , Kitano Takeshi , Matsuzaki Shigenori , Umezawa Akihiro , Muranishi Yuki
Published: February 2023

During mammalian gestation, large amounts of progesterone are produced by the placenta and circulate for the maintenance of pregnancy. In contrast, primary plasma estrogens are different between species. To account for this difference, we compared the expression of ovarian and placental steroidogenic genes in various mammalian species (mouse, guinea pig, porcine, ovine, bovine, and human). Consistent with the ability to synthesize progesterone, CYP11A1/Cyp11a1, and bi-functional HSD3B/Hsd3b genes were expressed in all species. CYP17A1/Cyp17a1 was expressed in the placenta of all species, excluding humans. CYP19A/Cyp19a1 was expressed in all placental estrogen-producing species, whereas estradiol-producing HSD17B1 was only strongly expressed in the human placenta. The promoter region of HSD17B1 in various species possesses a well-conserved SP1 site that was activated in human placental cell line JEG-3 cells. However, DNA methylation analyses in the ovine placenta showed that the SP1-site in the promoter region of HSD17B1 was completely methylated. These results indicate that epigenetic regulation of HSD17B1 expression is important for species-specific placental sex steroid production. Because human HSD17B1 showed strong activity for the conversion of androstenedione into testosterone, similar to HSD17B1/Hsd17b1 in other species, we also discuss the biological significance of human placental HSD17B1 based on the symptoms of aromatase-deficient patients.
Genetic Diversity and Trends of Ancestral and New Inbreeding in German Sheep Breeds by Pedigree Data
Authors: Justinski Cathrin , Wilkens Jens , Distl Ottmar
Published: February 2023

In Germany, many autochthonous sheep breeds have developed, adapted to mountain, heath, moorland, or other marginal sites, but breeds imported from other countries have also contributed to the domestic breeds, particularly improving wool and meat quality. Selective breeding and the intense use of rams may risk losing genetic diversity and increasing rates of inbreeding. On the other hand, breeds with a low number of founder animals and only regional popularity may not leave their endangered status, as the number of breeders interested in the breed is limited. The objective of the present study was to determine demographic measures of genetic diversity and recent as well as ancestral trends of inbreeding in all autochthonous German sheep breeds and sheep of all breeding directions, including wool, meat, and milk. We used pedigree data from 1,435,562 sheep of 35 different breeds and a reference population of 981,093 sheep, born from 2010 to 2020. The mean number of equivalent generations, founders, effective founders, effective ancestors, and effective founder genomes were 5.77, 1669, 123.2, 63.5, and 33.0, respectively. Genetic drift accounted for 69% of the loss of genetic diversity, while loss due to unequal founder contributions was 31%. The mean inbreeding coefficient, individual rate of inbreeding (∆Fi), and realized effective population size across breeds were 0.031, 0.0074, and 91.4, respectively, with a significantly decreasing trend in ∆Fi in 11/35 breeds. New inbreeding, according to Kalinowski, contributed to 71.8% of individual inbreeding, but ancestral inbreeding coefficients showed an increasing trend in all breeds. In conclusion, in our study, all but one of the mountain-stone sheep breeds and the country sheep breed Wald were the most vulnerable populations, with Ne < 50. The next most endangered breeds are exotic, country, and heath breeds, with average Ne of 66, 83, and 89, respectively. The wool, meat, and milk breeds showed the highest genetic diversity, with average Ne of 158, 120, and 111, respectively. The results of our study should help strengthen conservation program efforts for the most endangered sheep breeds and maintain a high genetic diversity in all sheep breeds.
Susceptibility to SARS-CoV-2 and MERS-CoV in Beagle Dogs
Authors: Lyoo Kwang-Soo , Yeo Yoon-Hwan , Lee Sung-Geun , Yeom Minjoo , Lee Joo-Yeon , Kim Kyung-Chang , Song Daesub
Published: February 2023

The coronavirus disease 19 (COVID-19) pandemic, caused by the severe acute respiratory syndrome, coronavirus 2 (SARS-CoV-2), has resulted in unprecedented challenges to healthcare worldwide. In particular, the anthroponotic transmission of human coronaviruses has become a common concern among pet owners. Here, we experimentally inoculated beagle dogs with SARS-CoV-2 or Middle East respiratory syndrome (MERS-CoV) to compare their susceptibility to and the pathogenicity of these viruses. The dogs in this study exhibited weight loss and increased body temperatures and shed the viruses in their nasal secretions, feces, and urine. Pathologic changes were observed in the lungs of the dogs inoculated with SARS-CoV-2 or MERS-CoV. Additionally, clinical characteristics of SARS-CoV-2, such as increased lactate dehydrogenase levels, were identified in the current study.
Effect of Clindamycin on Intestinal Microbiome and Miltefosine Pharmacology in Hamsters Infected with Leishmania infantum
Authors: Olías-Molero Ana Isabel , Botías Pedro , Cuquerella Montserrat , García-Cantalejo Jesús , Barcia Emilia , Torrado Susana , Torrado Juan José , Alunda José María
Published: February 2023

Visceral leishmaniasis (VL), a vector-borne parasitic disease caused by Leishmania donovani and L. infantum (Kinetoplastida), affects humans and dogs, being fatal unless treated. Miltefosine (MIL) is the only oral medication for VL and is considered a first choice drug when resistance to antimonials is present. Comorbidity and comedication are common in many affected patients but the relationship between microbiome composition, drugs administered and their pharmacology is still unknown. To explore the effect of clindamycin on the intestinal microbiome and the availability and distribution of MIL in target organs, Syrian hamsters (120–140 g) were inoculated with L. infantum (108 promastigotes/animal). Infection was maintained for 16 weeks, and the animals were treated with MIL (7 days, 5 mg/kg/day), clindamycin (1 mg/kg, single dose) + MIL (7 days, 5 mg/kg/day) or kept untreated. Infection was monitored by ELISA and fecal samples (16 wpi, 18 wpi, end point) were analyzed to determine the 16S metagenomic composition (OTUs) of the microbiome. MIL levels were determined by LC-MS/MS in plasma (24 h after the last treatment; end point) and target organs (spleen, liver) (end point). MIL did not significantly affect the composition of intestinal microbiome, but clindamycin provoked a transient albeit significant modification of the relative abundance of 45% of the genera, including Ruminococcaceae UCG-014, Ruminococcus 2; Bacteroides and (Eubacterium) ruminantium group, besides its effect on less abundant phyla and families. Intestinal dysbiosis in the antibiotic-treated animals was associated with significantly lower levels of MIL in plasma, though not in target organs at the end of the experiment. No clear relationship between microbiome composition (OTUs) and pharmacological parameters was found.
Prevalence of Antimicrobial Resistance and Clonal Relationship in ESBL/AmpC-Producing Proteus mirabilis Isolated from Meat Products and Community-Acquired Urinary Tract Infection (UTI-CA) in Southern Brazil
Authors: Sanches Matheus Silva , Silva Luana Carvalho , Silva Caroline Rodrigues da , Montini Victor Hugo , Oliva Bruno Henrique Dias de , Guidone Gustavo Henrique Migliorini , Nogueira Mara Corrêa Lelles , Menck-Costa Maísa Fabiana , Kobayashi Renata Katsuko Takayama , Vespero Eliana Carolina , Rocha Sergio Paulo Dejato
Published: February 2023

The present study aimed to evaluate the prevalence of antimicrobial resistance and clonal relationships in Proteus mirabilis isolated from chicken meat, beef, pork, and community-acquired urinary tract infections (UTI-CA). Chicken meat isolates showed the highest multidrug resistance (MDR), followed by those from pork and UTI-CA, whereas beef had relatively few MDR strains. All sources had strains that carried blaCTX-M-65, whereas blaCTX-M-2 and blaCMY-2 were only detected in chicken meat and UTI-CA isolates. This indicates that chicken meat should be considered an important risk factor for the spread of P. mirabilis carrying ESBL and AmpC. Furthermore, ESBL/AmpC producing strains were resistant to a greater number of antimicrobials and possessed more resistance genes than non-producing strains. In addition, the antimicrobial resistance genes qnrD, aac(6′)-Ib-cr, sul1, sul2, fosA3, cmlA, and floR were also found. Molecular typing showed a genetic similarity between chicken meat and UTI-CA isolates, including some strains with 100% similarity, indicating that chicken can be a source of P. mirabilis causing UTI-CA. It was concluded that meat, especially chicken meat, can be an important source of dissemination of multidrug-resistant P. mirabilis in the community.
Structure, Activation, and Regulation of NOX2: At the Crossroad between the Innate Immunity and Oxidative Stress-Mediated Pathologies
Authors: Nocella Cristina , D’Amico Alessandra , Cammisotto Vittoria , Bartimoccia Simona , Castellani Valentina , Loffredo Lorenzo , Marini Leonardo , Ferrara Giulia , Testa Matteo , Motta Giulio , Benazzi Beatrice , Zara Fabio , Frati Giacomo , Sciarretta Sebastiano , Pignatelli Pasquale , Violi Francesco , Carnevale Roberto , Group Smile
Published: February 2023

Nicotinamide adenine dinucleotide phosphate (NADPH) oxidase (NOX) is a multisubunit enzyme complex that participates in the generation of superoxide or hydrogen peroxide (H2O2) and plays a key role in several biological functions. Among seven known NOX isoforms, NOX2 was the first identified in phagocytes but is also expressed in several other cell types including endothelial cells, platelets, microglia, neurons, and muscle cells. NOX2 has been assigned multiple roles in regulating many aspects of innate and adaptive immunity, and human and mouse models of NOX2 genetic deletion highlighted this key role. On the other side, NOX2 hyperactivation is involved in the pathogenesis of several diseases with different etiologies but all are characterized by an increase in oxidative stress and inflammatory process. From this point of view, the modulation of NOX2 represents an important therapeutic strategy aimed at reducing the damage associated with its hyperactivation. Although pharmacological strategies to selectively modulate NOX2 are implemented thanks to new biotechnologies, this field of research remains to be explored. Therefore, in this review, we analyzed the role of NOX2 at the crossroads between immunity and pathologies mediated by its hyperactivation. We described (1) the mechanisms of activation and regulation, (2) human, mouse, and cellular models studied to understand the role of NOX2 as an enzyme of innate immunity, (3) some of the pathologies associated with its hyperactivation, and (4) the inhibitory strategies, with reference to the most recent discoveries.
Bio-Based Nano-Enabled Cosmetic Formulations for the Treatment of Cutibacterium acnes-Associated Skin Infections
Authors: Ivanova Kristina , Ramon Eva , Ivanova Aleksandra , Sanchez-Gomez Susana , Tzanov Tzanko
Published: February 2023

Acne is a common chronic skin condition with serious physical and psychosocial consequences. In some cases, the appearance of pimples, whiteheads, or blackheads on the face, neck, and back may lead to scarring, disfiguring, depression, frustration, and anxiety in patients. Current treatments rely on antibiotics to eradicate Cutibacterium acnes (C. acnes), the bacterium responsible for this skin condition. However, these approaches do not scavenge the reactive oxidative species (ROS) generated during disease development and raise concerns about the increase in antimicrobial resistance. In this study, an environmentally friendly and cost-effective self-assembly nanoencapsulation technology based on zein, a bio-based hydrophobic protein, was employed to produce multifunctional essential oil (EO)-loaded nanocapsules (NCs) with superior antioxidant and bactericidal activity toward C. acnes. The NCs displayed “smart” release of the active cargo only under the conditions that were conducive to acne proliferation on skin. Once incorporated into creams, the EO-loaded NCs led to a complete inhibition of C. acnes and demonstrated the capacity to scavenge ROS, thus preventing damage to human skin cells. The in vitro permeation studies revealed that the nanoformulated EO was able to penetrate through the epidermis, indicating its potential for the treatment of skin diseases, such as acne.
3D Printing of Functional Strawberry Snacks: Food Design, Texture, Antioxidant Bioactive Compounds, and Microbial Stability
Authors: Bebek Markovinović Anica , Putnik Predrag , Bosiljkov Tomislav , Kostelac Deni , Frece Jadranka , Markov Ksenija , Žigolić Adrijana , Kaurinović Jelena , Pavlić Branimir , Duralija Boris , Zavadlav Sandra , Bursać Kovačević Danijela
Published: February 2023

3D printing technology (3DP) as additive manufacturing is an innovative design technology that can meet the individual nutritional and sensory needs of consumers. Therefore, the aim of this work was to apply 3DP in the production of a strawberry-based functional product with the addition of two hydrocolloids (corn and wheat starch) in three proportions (10, 15 and 20%) and to investigate the influence of 3DP process parameters on physico-chemical and textural properties, as well as the bioactive and antioxidant potential and microbiological stability, with(out) the addition of natural antimicrobial agents. Starch type had a significant effect on all tested bioactive compounds, as well as on starch content, except for total phenolic and hydroxycinnamic acid contents. Considering the content of bioactive compounds and antioxidant capacity, program 2 proved to be more suitable than program 1. All samples exhibited good textural properties, a high degree of stability and minimal geometric deviations. Regarding microbiological safety, no pathogenic bacteria were found in the 3DP samples during storage. The 3DP sample with added citral at a concentration of 75 mg L−1 showed the best microbiological quality. Ultimately, 3DP can be successfully used for the production of new strawberry-based functional products.
Nanoemulsion Composed of α-Tocopherol Succinate and Dequalinium Shows Mitochondria-Targeting and Anticancer Effects
Authors: Thuy Le Thi , Lee Seulgi , Dongquoc Viet , Choi Joon Sig
Published: February 2023

Targeted drugs have been used to treat mitochondrial dysfunction-related diseases, including metabolic disorders and cancer; however, targeting and penetrating intracellular organelles remains a challenge. Dominant targeting approaches for therapeutic delivery are detailed in many nanoemulsion studies and show the tremendous potential of targeted delivery to inhibit cancer cell growth. Dequalinium (DQA) and α-tocopherol succinate (α-TOS) are good agents for targeting mitochondria. In this study, we aimed to develop a mitochondria-targeting emulsion, using DQA and α-TOS (DTOS), for cancer treatment. DTOS emulsions of 150–170 nm in diameter were formulated using homogenization. DQA and α-TOS were used as bifunctional agents (surfactants) to stabilize the nanoemulsion and anticancer drugs. Various molar ratios of DQA and α-TOS were tested to determine the optimal condition, and DTOS 5-5 was selected for further study. The DTOS emulsion showed improved stability, as evidenced by its ability to remain stable for three years at room temperature. This stability, combined with its effective targeting of mitochondria, led to inhibition of 71.5% of HeLa cells after 24 h. The DTOS emulsion effectively inhibited spheroid growth in the 3D model, as well as prevented the growth of HeLa cells grafted onto zebrafish larvae. These results highlight the DTOS emulsion’s promising potential for mitochondria-targeting and cancer treatment.
Childhood Uveitic Glaucoma: Complex Management in a Fragile Population
Authors: Iannucci Valeria , Manni Priscilla , Mecarelli Giulia , Giammaria Sara , Giovannetti Francesca , Lambiase Alessandro , Bruscolini Alice
Published: February 2023

Uveitic glaucoma (UG) is a potentially blinding complication of intraocular inflammation and is one of the most common causes of secondary glaucoma in pediatric ophthalmology. Overall management of UG is often challenging and requires a multidisciplinary assessment and careful follow-up. The overlap with steroid-induced glaucoma (SIG) is quite common, as well as the failure of medical and surgical therapy; nevertheless, few recent papers have dealt with this topic. We review the features and the clinical approach to UG in childhood, discussing the treatments available in the pediatric population.
A Kitchen Standard Dress Detection Method Based on the YOLOv5s Embedded Model
Authors: Zhou Ziyun , Zhou Chengjiang , Pan Anning , Zhang Fuqing , Dong Chaoqun , Liu Xuedong , Zhai Xiangshuai , Wang Haitao
Published: February 2023

In order to quickly and accurately detect whether a chef is wearing a hat and mask, a kitchen standard dress detection method based on the YOLOv5s embedded model is proposed. Firstly, a complete kitchen scene dataset was constructed, and the introduction of images for the wearing of masks and hats allows for the low reliability problem caused by a single detection object to be effectively avoided. Secondly, the embedded detection system based on Jetson Xavier NX was introduced into kitchen standard dress detection for the first time, which accurately realizes real-time detection and early warning of non-standard dress. Among them, the combination of YOLOv5 and DeepStream SDK effectively improved the accuracy and effectiveness of standard dress detection in the complex kitchen background. Multiple sets of experiments show that the detection system based on YOLOv5s has the highest average accuracy of 0.857 and the fastest speed of 31.42 FPS. Therefore, the proposed detection method provided strong technical support for kitchen hygiene and food safety.
Support Vector Machine (SVM) Application for Uniaxial Compression Strength (UCS) Prediction: A Case Study for Maragheh Limestone
Authors: Cemiloglu Ahmed , Zhu Licai , Arslan Sibel , Xu Jinxia , Yuan Xiaofeng , Azarafza Mohammad , Derakhshani Reza
Published: February 2023

The geomechanical properties of rock materials, such as uniaxial compression strength (UCS), are the main requirements for geo-engineering design and construction. A proper understanding of UCS has a significant impression on the safe design of different foundations on rocks. So, applying fast and reliable approaches to predict UCS based on limited data can be an efficient alternative to regular traditional fitting curves. In order to improve the prediction accuracy of UCS, the presented study attempted to utilize the support vector machine (SVM) algorithm. Multiple training and testing datasets were prepared for the UCS predictions based on a total of 120 samples recorded on limestone from the Maragheh region, northwest Iran, which were used to achieve a high precision rate for UCS prediction. The models were validated using a confusion matrix, loss functions, and error tables (MAE, MSE, and RMSE). In addition, 24 samples were tested (20% of the primary dataset) and used for the model justifications. Referring to the results of the study, the SVM (accuracy = 0.91/precision = 0.86) showed good agreement with the actual data, and the estimated coefficient of determination (R2) reached 0.967, showing that the model’s performance was impressively better than that of traditional fitting curves.
Adaptive Backstepping Axial Position Tracking Control of Autonomous Undersea Vehicles with Deferred Output Constraint
Authors: Zhang Yuntao , Xu Ouguan
Published: February 2023

In this paper, an adaptive backstepping control scheme is proposed to solve the the surge motion tracking control problem of an autonomous undersea vehicle (AUV) with system constraint. First, an initial rectification reference signal is constructed for the subsequent implementation of deferred output constraint and making the control input smaller and smoother in the early stage of system operation. Second, a barrier Lyapunov function is adopted for developing an output-constrained state feedback adaptive controller. Then, on the basis of coordinate transformation and estimating the derivative of surge displacement by a linear and nonlinear combined differentiator, we develop an output feedback adaptive backstepping control scheme for AUVs whose velocity signals are unmeasurable. We also carried out a comparative numerical simulation with traditional adaptive control to verify the feasibility of the proposed control strategy.
A Systematic Literature Review on Urban Resilience Enabled with Asset and Disaster Risk Management Approaches and GIS-Based Decision Support Tools
Authors: Rezvani Seyed MHS , Falcão Maria João , Komljenovic Dragan , de Almeida Nuno Marques
Published: February 2023

Urban Resilience (UR) enables cities and communities to optimally withstand disruptions and recover to their pre-disruption state. There is an increasing number of interdisciplinary studies focusing on conceptual frameworks and/or tools seeking to enable more efficient decision-making processes that lead to higher levels of UR. This paper presents a systematic review of 68 Scopus-indexed journal papers published between 2011 and 2022 that focus on UR. The papers covered in this study fit three categories: literature reviews, conceptual models, and analytical models. The results of the review show that the major areas of discussion in UR publications include climate change, disaster risk assessment and management, Geographic Information Systems (GIS), urban and transportation infrastructure, decision making and disaster management, community and disaster resilience, and green infrastructure and sustainable development. The main research gaps identified include: a lack of a common resilience definition and multidisciplinary analysis, a need for a unified scalable and adoptable UR model, margin for an increased application of GIS-based multidimensional tools, stochastic analysis of virtual cities, and scenario simulations to support decision making processes. The systematic literature review undertaken in this paper suggests that these identified gaps can be addressed with the aid of asset and disaster risk management methods combined with GIS-based decision-making tools towards significantly improving UR.
Low-Complexity Data-Reuse RLS Algorithm for Stereophonic Acoustic Echo Cancellation
Authors: Fîciu Ionuț-Dorinel , Stanciu Cristian-Lucian , Paleologu Constantin , Benesty Jacob
Published: February 2023

Stereophonic audio devices employ two loudspeakers and two microphones in order to create a bidirectional sound effect. In this context, the stereophonic acoustic echo cancellation (SAEC) setup requires the estimation of four echo paths, each one corresponding to a loudspeaker-to-microphone pair. The widely linear (WL) model was proposed in recent literature in order to simplify the handling of the SAEC mathematical model. Moreover, low complexity recursive least- squares (RLS) adaptive algorithms were developed within the WL framework and successfully tested for SAEC scenarios. This paper proposes to apply a data-reuse (DR) approach for the combination between the RLS algorithm and the dichotomous coordinate descent (DCD) iterative method. The resulting WL-DR-RLS-DCD algorithm inherits the convergence properties of the RLS family and requires an amount of mathematical operations attractive for practical implementations. Simulation results show that the DR approach improves the tracking capabilities of the RLS-DCD algorithm, with an acceptable surplus in terms of computational workload.
Assessing the Features of Tomato Pomace Powder in Suspensions
Authors: Begliţa Victoria , Ungureanu-Iuga Mădălina , Mironeasa Silvia
Published: February 2023

The aim of this work was to investigate the physicochemical characteristics of dried tomato pomace and the viscoelastic behavior of suspensions obtained by the rehydration of dry, grinded tomato pomace and sieved with a particle size < 120 µm. Investigated systems comprised of three different dry tomato pomace powder (TP) concentrations (15, 20 and 25%) heat-treated at two temperatures (60 °C and 95 °C) corresponding to the “cold-break” and “hot-break”, during 30 min. The dynamic rheological properties and color parameters of the suspensions formulated were evaluated. The water activity, water absorption index, water retention capacity, pectin content and color parameters assessed revealed good properties of the dry tomato pomace powder (TP) to develop new products. Tomato pomace suspensions with different concentrations processed at different temperatures caused significant changes in rheological behavior. The viscoelastic properties of the TP suspension showed a much stiffer structure at 25% TP, processed at 90 °C. Instrumental color parameters a* and b* increased, while lightness (L*) decreased with concentration and temperature increase. These results could be useful to select the adequate concentration of TP to achieve a desired consistency of the product during processing with positive effects on quality parameters of the finite product.
MDFULog: Multi-Feature Deep Fusion of Unstable Log Anomaly Detection Model
Authors: Li Min , Sun Mengjie , Li Gang , Han Delong , Zhou Mingle
Published: February 2023

Effective log anomaly detection can help operators locate and solve problems quickly, ensure the rapid recovery of the system, and reduce economic losses. However, recent log anomaly detection studies have shown some drawbacks, such as concept drift, noise problems, and fuzzy feature relation extraction, which cause data instability and abnormal misjudgment, leading to significant performance degradation. This paper proposes a multi-feature deep fusion of an unstable log anomaly detection model (MDFULog) for the above problems. The MDFULog model uses a novel log resolution method to eliminate the dynamic interference caused by noise. This paper proposes a feature enhancement mechanism that fully uses the correlation between semantic information, time information, and sequence features to detect various types of log exceptions. The introduced semantic feature extraction model based on Bert preserves the semantics of log messages and maps them to log vectors, effectively eliminating worker randomness and noise injection caused by log template updates. An Informer anomaly detection classification model is proposed to extract practical information from a global perspective and predict outliers quickly and accurately. Experiments were conducted on HDFS, OpenStack, and unstable datasets, showing that the anomaly detection method in this paper performs significantly better than available algorithms.
VR as an Innovative Learning Tool in Sports Education
Authors: Geisen Mai , Fox Alexandra , Klatt Stefanie
Published: February 2023

Testing and application of suitable learning tools and methods can facilitate learning environments conducive to skill acquisition for the target group. This also applies to sports education at school level, including extracurricular activities. On the one hand, traditional learning methods are still effective in sports education; on the other hand, keeping up with societal and technological developments, new learning strategies are continuously being researched to complement existing pedagogical tools. An innovative tool that has been increasingly used in various fields of application in recent years is Virtual Reality (VR) as part of the Extended Reality (XR) domain. It enables learning in immersive and specifically designed learning environments and is particularly suitable for learning in (sports-)motor contexts due to its flexible use. In our study, we test a VR-based rotation task in an extracurricular dance class with the objective of supporting the crucial didactic, collaborative, and perceptual components of dance training in educational contexts. We conducted feedback sessions with the students and used direct observation to examine their behavioural actions. Based on the qualitative content analysis of the written feedback and the overview from the observations, we can identify integrative potentials of this innovative tool in sports education, especially extracurricular dance classes.
Interactive Multifactorial Evolutionary Optimization Algorithm with Multidimensional Preference Surrogate Models for Personalized Recommendation
Authors: Wu Weidong , Sun Xiaoyan , Man Guangyi , Li Shuai , Bao Lin
Published: February 2023

Interactive evolutionary algorithms (IEAs) coupled with a data-driven user surrogate model (USM) have recently been proposed for enhancing personalized recommendation performance. Since the USM relies on only one model to describe the full range of user preferences, existing USM-based IEAs have not investigated how knowledge migrates between preference models to improve the diversity and novelty of recommendations. Motivated by this, an interactive multifactorial evolutionary optimization algorithm with multidimensional preference user surrogate models is proposed here to perform a multi-view optimization for personalized recommendation. Firstly, multidimensional preference user surrogate models (MPUSMs), partial-MPUSMs, and probability models of MPUSMs are constructed to approximate the different perceptions of preferences and serve for population evolution. Next, a modified multifactorial evolutionary algorithm is used for the first time in the IEAs domain to recommend diverse and novel items for multiple preferences. It includes initialization and diversification management of a population with skill factors, recommendation lists of preference grading and interactive model management of inheriting previous information. Comprehensive comparison studies in the Amazon dataset show that the proposed models and algorithm facilitate the mining of knowledge between preferences. Eventually, at the cost of losing only about 5% of the Hit Ratio and Average Precision, the Individual Diversity is improved by 54.02%, the Self-system Diversity by 3.7%, the Surprise Degree by 2.69%, and the Preference Mining Degree by 16.05%.
A Multi-Stage Deep Reinforcement Learning with Search-Based Optimization for Air–Ground Unmanned System Navigation
Authors: Chen Xiaohui , Qi Yuhua , Yin Yizhen , Chen Yidong , Liu Li , Chen Hongbo
Published: February 2023

An important challenge for air–ground unmanned systems achieving autonomy is navigation, which is essential for them to accomplish various tasks in unknown environments. This paper proposes an end-to-end framework for solving air–ground unmanned system navigation using deep reinforcement learning (DRL) while optimizing by using a priori information from search-based path planning methods, which we call search-based optimizing DRL (SO-DRL) for the air–ground unmanned system. SO-DRL enables agents, i.e., an unmanned aerial vehicle (UAV) or an unmanned ground vehicle (UGV) to move to a given target in a completely unknown environment using only Lidar, without additional mapping or global planning. Our framework is equipped with Deep Deterministic Policy Gradient (DDPG), an actor–critic-based reinforcement learning algorithm, to input the agents’ state and laser scan measurements into the network and map them to continuous motion control. SO-DRL draws on current excellent search-based algorithms to demonstrate path planning and calculate rewards for its behavior. The demonstrated strategies are replayed in an experienced pool along with the autonomously trained strategies according to their priority. We use a multi-stage training approach based on course learning to train SO-DRL on the 3D simulator Gazebo and verify the robustness and success of the algorithm using new test environments for path planning in unknown environments. The experimental results show that SO-DRL can achieve faster algorithm convergence and a higher success rate. We piggybacked SO-DRL directly onto a real air–ground unmanned system, and SO-DRL can guide a UAV or UGV for navigation without adjusting any networks.
Application of a Fractional Instantaneous Unit Hydrograph in the TOPMODEL: A Case Study in Chengcun Basin, China
Authors: Xiang Xin , Ao Tianqi , Li Xiaodong
Published: February 2023

The movement of water flow usually has history and path dependence. Fractional calculus is very suitable for describing the process with memory and hereditary properties. In this study, the order of the differential equation in the Nash confluence system was extended from integer order to fractional order. On the basis of the Laplace transform, the fractional instantaneous unit hydrograph was obtained, which was used to describe the long-term memory of the basin confluence system. Furthermore, the enhanced TOPMODEL (FTOP) model was obtained by applying the fractional instantaneous unit hydrograph as the surface runoff calculation. Taking Chengcun Basin in China as an example, the FTOP model was used to simulate the daily runoff and 22 floods from 1989 to 1996. The simulation results were compared with two original TOPMODEL models (the NTOP and ITOP models). The results show that in the daily runoff simulation, the Nash–Sutcliffe efficiency (NSE), relative error (RE), and root mean square error (RMSE) of the FTOP model were 0.82, −11.14%, and 15.25 m3/s, respectively, being slightly better than the other two TOPMODEL models. According to the hydrologic frequency curve, the measured daily runoff was divided into different flow levels. It was found that the FTOP model can improve the simulation effect of the medium-flow (frequency between 10% and 50%) and low-flow (frequency more than 50%) sections to a certain extent. In the flood simulation, the average runoff depth relative error (RDRE), peak discharge relative error (PDRE), peak occurrence time error (POTE), and NSE of 22 floods were 1.99%, 14.06%, −1.27, and 0.88, respectively, indicating that the simulation effect had been improved. Especially in NSE, the improvement was more prominent, meaning that the FTOP model can better simulate the flooding process. However, the flood peak and runoff depth simulation effect were not significantly improved. These conclusions indicate that the confluence method using the fractional instantaneous unit hydrograph as the TOPMODEL model can improve the simulation effect.
Deep Learning-Based Graffiti Detection: A Study Using Images from the Streets of Lisbon
Authors: Fogaça Joana , Brandão Tomás , Ferreira João C.
Published: February 2023

This research work comes from a real problem from Lisbon City Council that was interested in developing a system that automatically detects in real-time illegal graffiti present throughout the city of Lisbon by using cars equipped with cameras. This system would allow a more efficient and faster identification and clean-up of the illegal graffiti constantly being produced, with a georeferenced position. We contribute also a city graffiti database to share among the scientific community. Images were provided and collected from different sources that included illegal graffiti, images with graffiti considered street art, and images without graffiti. A pipeline was then developed that, first, classifies the image with one of the following labels: illegal graffiti, street art, or no graffiti. Then, if it is illegal graffiti, another model was trained to detect the coordinates of graffiti on an image. Pre-processing, data augmentation, and transfer learning techniques were used to train the models. Regarding the classification model, an overall accuracy of 81.4% and F1-scores of 86%, 81%, and 66% were obtained for the classes of street art, illegal graffiti, and image without graffiti, respectively. As for the graffiti detection model, an Intersection over Union (IoU) of 70.3% was obtained for the test set.
On the Interplay between Machine Learning, Population Pharmacokinetics, and Bioequivalence to Introduce Average Slope as a New Measure for Absorption Rate
Authors: Karalis Vangelis D.
Published: February 2023

The scientific basis for demonstrating bioequivalence between two drug products relies on the comparison of their extent and rate of absorption. For the absorption extent, the area under the C-t curve (AUCt) is used without a doubt. For absorption rate, the maximum observed plasma concentration (Cmax) is still suggested by the authorities, despite the numerous concerns. In this study, the concept of average slope (AS) is introduced as a metric to express the absorption rate of drugs. Principal component analysis and random forest models were applied to actual and simulated two × two crossover bioequivalence studies to show that AS expresses the appropriate properties for characterizing absorption rate. Several absorption kinetics (slow, typical, fast) and sampling schemes (sparse, typical, dense) were simulated. The two machine learning algorithms, applied to all these scenarios, proved the desired properties of AS while showing the non-desired performances of other metrics currently used or proposed in the literature. The estimation of AS does not require any assumptions, models, or transformations and is as simple as that of AUCt. A modified version of AS, termed “weighted AS”, is also introduced in order to place emphasis on early time points where the C-t profile describes more clearly the absorption process.
Aqueous Extracts of Four Medicinal Plants and Their Allelopathic Effects on Germination and Seedlings: Their Morphometric Characteristics of Three Horticultural Plant Species
Authors: Erhatić Renata , Horvat Dijana , Zorić Zoran , Repajić Maja , Jović Tanja , Herceg Martina , Habuš Matea , Srečec Siniša
Published: February 2023

Allelopathy is a biological phenomenon of synthesizing and excreting compounds that can affect the growth of various organisms, i.e., plant species. The aim of this work was to investigate the possible allelopathic influence of aqueous extracts, obtained from plant species chia (Salvia hispanica L.), black cumin (Nigella sativa L.), wormwood (Artemisia absinthium L.), and nettle (Urtica dioica L.), on the seed germination growth and morphometric characteristics of pepper (Capsicum annuum L.), spinach (Spinacia oleracea L.) and lettuce (Lactuca sativa L.) seedlings in laboratory conditions. Pepper, spinach, and lettuce seedlings were treated with aqueous extracts of chia, nettle, wormwood, and black cumin of different concentrations (2.5, 5 and 10%, respectively). The aqueous extracts were prepared according to the method developed by Norsworthy and the qualitative and quantitative analysis of phenolic compounds in aqueous extracts were performed using ultra-performance liquid chromatography electrospray ionization tandem mass spectrometry (UPLC-ESI-MS/MS). Phytochemical composition of chia aqueous extracts showed the highest content (above the 1 mg L−1) of epicatechin, quinic acid, caffeic acid, esculetin and cinnamic acid in the comparison with others from the total of 19 detected chemical compounds. In aqueous extracts of black cumin, there were six compounds detected in content above 1 mg L−1, i.e., epicatechin, quinic acid, caffeic acid, esculetin, cinnamic acid, and kaempferol. The same compounds were the most abundant in wormwood extracts, along with gallic acid. Epicatechin and esculetin were only two compounds detected in aqueous extract of nettle in concentration higher than 1 mg L−1. According to the results of this study, only the treatment of spinach seeds with chia aqueous extract in concentration of 2.5% before germination stimulates the germination of spinach seeds, and wormwood herbs and chia extracts in concentrations of 2.5 and 5% stimulate the germination of lettuce seeds and the growth of hypocotyl and radicle length of developed seedlings. The treatment of pepper and lettuce seeds with aqueous extract of nettle in concentration of 10% completely inhibited seed germination.
A 1 × 2 Two-Dimensional Slanted Grating Based on Double-Layer Cylindrical Structure
Authors: Chen Yuda , Wang Jin , Wang Yihan , Li Xingxue , Jin Ge , Zhou Changhe
Published: February 2023

Diffraction gratings play an increasingly important role in various planar optical systems, such as near-eye display systems for virtual reality (VR) and augmented reality (AR). The slanted gratings have more advantages than other elements. A 1 × 2 transmission two-dimensional (2D) slanted grating based on a double-layer cylindrical structure was proposed in this paper. In the initial phase of this study, this kind of grating was proposed and designed. We used rigorous coupled-wave analysis (RCWA) and simulated annealing algorithm (SA) to optimize the grating parameters. The effects of the grating geometric parameters on the diffraction efficiency were investigated using rigorous coupled-wave analysis (RCWA). The simulated annealing algorithm (SA) optimization results show that the diffraction efficiency of the (0, −1) and (−1, 0) order exceed 35% under normal incidence in the range of 429–468 nm wavelength for TE and TM polarization. Meanwhile, the total diffraction efficiency can reach up to 78%. In the last section, we discuss the tolerances for the grating parameters to ensure high quality manufacturing processes. The total effective efficiency is greater than 75% when the MgF2 thickness is from 300 nm to 350 nm and the SiO2 thickness is from 525 nm to 550 nm. Moreover, the grating period has a 53 nm fabrication tolerance, and the slanted angle has a 8.8-degree fabrication tolerance. The relatively large tolerances ensure that it is easy to fabricate the two-dimensional slanted grating and to achieve the targeted objectives. The proposed 2D slanted grating can be applied to 2D exit pupil expansion, which is of great importance in AR/VR applications.
A Powerful Predicting Model for Financial Statement Fraud Based on Optimized XGBoost Ensemble Learning Technique
Authors: Ali Amal Al , Khedr Ahmed M. , El-Bannany Magdi , Kanakkayil Sakeena
Published: February 2023

This study aims to develop a better Financial Statement Fraud (FSF) detection model by utilizing data from publicly available financial statements of firms in the MENA region. We develop an FSF model using a powerful ensemble technique, the XGBoost (eXtreme Gradient Boosting) algorithm, that helps to identify fraud in a set of sample companies drawn from the Middle East and North Africa (MENA) region. The issue of class imbalance in the dataset is addressed by applying the Synthetic Minority Oversampling Technique (SMOTE) algorithm. We use different Machine Learning techniques in Python to predict FSF, and our empirical findings show that the XGBoost algorithm outperformed the other algorithms in this study, namely, Logistic Regression (LR), Decision Tree (DT), Support Vector Machine (SVM), AdaBoost, and Random Forest (RF). We then optimize the XGBoost algorithm to obtain the best result, with a final accuracy of 96.05% in the detection of FSF.