bluuebunny/crossref_metadata_2025 huggingface dataset:
The ORIGIN Space Instrument for Detecting Biosignatures and Habitability Indicators on a Venus Life Finder Mission
Authors: Ligterink Niels F. W. , Kipfer Kristina A. , Gruchola Salome , Boeren Nikita J. , Keresztes Schmidt Peter , de Koning Coenraad P. , Tulej Marek , Wurz Peter , Riedo Andreas
Published: June 2022

Recent and past observations of chemical and physical peculiarities in the atmosphere of Venus have renewed speculations about the existence of life in its clouds. To find signs of Venusian life, a dedicated astrobiological space exploration mission is required, and for this reason the Venus Life Finder mission is currently being prepared. A Venus Life Finder mission will require dedicated and specialized instruments to hunt for biosignatures and habitability indicators. In this contribution, we present the ORIGIN space instrument, a laser desorption/laser ablation ionization mass spectrometer. This instrument is designed to detect large, non-volatile molecules, specifically biomolecules such as amino acids and lipids. At the same time, it can also be used in ablation mode for elemental composition analysis. Recent studies with this space prototype instrument of amino acids, polycyclic aromatic hydrocarbons, lipids, salts, metals, sulphur isotopes, and microbial elemental composition are discussed in the context of studies of biosignatures and habitability indicators in Venus’s atmosphere. The implementation of the ORIGIN instrument into a Venus Life Finder mission is discussed, emphasizing the low weight and low power consumption of the instrument. An instrument design and sample handling system are presented that make optimal use of the capabilities of this instrument. ORIGIN is a highly versatile instrument with proven capabilities to investigate and potentially resolve many of the outstanding questions about the atmosphere of Venus and the presence of life in its clouds.
Food Production in the Context of Global Developmental Challenges
Authors: Daszkiewicz Tomasz
Published: June 2022

The article presents a synthetic analysis of the most pressing challenges associated with food security in the context of changes induced by global development and the generated problems. The study demonstrated that a more effective model of food production and management is needed to counteract anthropogenic pressure on the natural environment and excessive exploitation of limited resources caused by rapid population growth. Policies aiming to increase the efficiency of production and conversion of raw materials into finished food products of plant and animal origin (including feed conversion into high-energy and high-protein foods), promote the use of novel protein sources for feed and food production, and prevent excessive food consumption and waste are needed. At present and in the future, demographic, social, environmental, and geopolitical factors as well as the availability of natural resources should be taken into account by world leaders who should act together, with solidarity, to provide food to countries suffering from food shortage. Adequate food availability, including both physical and financial access to food, cannot be guaranteed without a holistic approach to global food security.
Effectiveness of Species- and Trichothecene-Specific Primers in Monitoring Fusarium graminearum Species Complex in Small Grain–Pea Intercropping Systems
Authors: Župunski Vesna , Jevtić Radivoje , Grčak Milosav , Lalošević Mirjana , Orbović Branka , Živanov Dalibor , Knežević Desimir
Published: June 2022

Tracking the distribution of Fusarium species and the detection of changes in toxin production provides epidemiological information that is essential for Fusarium head blight (FHB) management. Members of Fusarium graminearum species complex (FGSC) were characterized using species and trichothecene-specific primers. Associations between members of the FGSC, cereal crop species (wheat, rye, triticale, and oat), seeding time (winter and spring), type of cultivation (monocrop and intercrop) and chemotype grouping were investigated with multiple correspondence analysis and multiple regression modeling. We found that triticale and oat were more related to isolates classified into F. graminearum s. lato than with other isolates. In contrast, wheat and rye were more associated with F. graminearum s. stricto. Cereal crop species affected the frequencies of F. graminearum s. stricto (p = 0.003) and F. graminearum s. lato (p = 0.08) and unidentified isolates with morphological characteristics like those of FGSC members (p = 0.02). The effectiveness of species-specific primers was 60.3% (Fg16F/R) and 76.2% (FgrF/FgcR), and the effectiveness of primer sets for the trichothecene genotyping of the Tri5 and Tri3 genes was 100% and 90.6%, respectively. The decrease in Fusarium-damaged kernel values in the wheat–pea intercropping system indicated that intercropping systems have the potential to control FHB.
Development and Validation of Alternative Palm-Derived Substrates for Seedling Production
Authors: Gomis María Pilar , Pérez-Murcia María Dolores , Barber Xavier , Martínez-Sabater Encarnación , Moral Raúl , Bustamante María Ángeles
Published: June 2022

The constraints associated with peat use in horticulture has led to a search for alternative materials for their use as growing media. The organic materials derived from palm trees (composted or not) can constitute an alternative due to their ligneous and fibrous character, similar to coir fiber. This work studies the feasibility of using several palm-tree-derived (Phoenix dactylifera L.) organic materials as growing media ingredients for the transplant production of lettuce (Lactuca sativa L. var. Senna). For this, the following substrates were studied: five mixtures for each palm-derived material (palm trunks and leaves and composts derived from palm trunk and leaves), in the proportions of 20%, 40%, 60%, 80%, and 100% by volume, mixed with coir fiber. Coir fiber at the proportion 100% was used as the control treatment. Physical, physico-chemical, and chemical analyses were conducted on the substrates, and the germination and morphological parameters of the seedlings were examined. Chemometric tools, such as random forest (RF) and hierarchical cluster analysis (HCA) were also used to evaluate the data obtained. The type and proportion of material used in the growing media principally affected the parameters studied in the lettuce seedlings. The substrates with a percentage of compost lower than 60% showed behavior closer to that observed in the growing media with 100% coir fiber and with the mixture of coir fiber and palm leaves or trunks at all proportions.
Identification and Genetic Mapping of Potential QTLs Conferring Heat Tolerance in Cotton (Gossypium hirsutum L.) by Using Micro Satellite Marker’s Approach
Authors: Rani Shazia , Baber Muhammad , Naqqash Tahir , Malik Saeed Ahmad
Published: June 2022

High-temperature stress can cause serious abiotic damage that limits the yield and quality of cotton plants. Heat Tolerance (HT) during the different developmental stages of cotton can guarantee a high yield under heat stress. HT is a complex trait that is regulated by multiple quantitative trait loci (QTLs). In this study, the F2 population derived from a cross between MNH-886, a heat-tolerant cultivar, and MNH-814, a heat-sensitive variety, was used to map HT QTLs during different morphological stages in cotton. A genetic map covering 4402.7 cm, with 175 marker loci and 26 linkage groups, was constructed by using this F2 population (94 individuals). This population was evaluated for different 23 morpho-physiological HT contributing traits QTL analysis via composite interval mapping detected 17 QTLs: three QTLs each for Total Number of Sympodes (TNS), Length of Bract (LOB), and Length of Staminal-column (LOS); two QTLs for First Sympodial Node Height (FSH), and one QTL each for Sympodial Node Height (SNH), Percent Boll set on second position along Sympodia (PBS), Total Number of Nodes (TNN), Number of Bolls (NOB), Total Number of Buds (TNB), and Length of Petal (LOP). Individually, the QTLs accounted for 7.76%–36.62% of phenotypic variation. QTLs identified linked with heat tolerance traits can facilitate marker-assisted breeding for heat tolerance in cotton.
Dystocia in the Standardbred Mare: A Retrospective Study from 2004 to 2020
Authors: Lanci Aliai , Perina Francesca , Donadoni André , Castagnetti Carolina , Mariella Jole
Published: June 2022

Dystocia as a prolonged stage II parturition (>30 min) was associated with a higher risk of complications. The hypothesis of the study was that any type of dystocia could affect the foal’s health, even when the stage II was <30 min. Clinical reports on 222 Standardbred mares and their foals hospitalized at the Veterinary Teaching Hospital of the University of Bologna from 2004 to 2020 were reviewed. Mares were divided into the Eutocia Group (165, eutocic delivery) and the Dystocia Group (57, dystocic delivery). The incidence of dystocia was 4.9%. Stage II was longer in the Dystocia Group (median 20 min) than in the Eutocia Group (median 12 min). All occurrences of dystocia were retrospectively classified into three categories of severity: mild, moderate and severe dystocia. The occurrence of postpartum complications in mares and neonatal diseases and failure of passive transfer of immunity in foals was higher in the Dystocia Group. Foal venous lactatemia and serum creatine kinase were significantly higher in the Dystocia Group (median 3.9 mmol/L; 262 UI/L respectively) than in the Eutocia Group (median 3.1 mmol/L; 187 UI/L respectively). The APGAR score was lower in the Dystocia Group (median 8) than in the Eutocia Group (median 10) and significantly lower in severe dystocia (median 3). The duration of stage II should not be considered the only parameter of dystocia in mares: even a rapid resolution of dystocia could pose health risks to the foal and the mare.
Fasciolosis—An Increasing Challenge in the Sheep Industry
Authors: Stuen Snorre , Ersdal Cecilie
Published: June 2022

The liver fluke Fasciola hepatica may cause severe infection in several mammalian species, including sheep and humans. Fasciolosis is a parasitic disease occurring worldwide in temperate climates and involves intermediate lymnaeid snails as vectors, in Europe the pond snail Galba truncatula in particular. In the sheep industry, the disease is a serious welfare and health problem. Fasciolosis is usually classified as acute, subacute or chronic according to the number and stage of flukes present in the liver, but with a considerable overlap. Acute disease, associated with a large number of migrating larvae, often results in sudden death due to acute and massive hemorrhage, while chronic fasciolosis is characterized by anemia, hypoalbuminaemia and weight loss. The management of fasciolosis is an increasing challenge in the sheep industry. Early diagnostic tests are limited. Protective immunity against liver flukes in sheep is low or lacking, and vaccines are not yet available. Treatment and control possibilities are challenging, and resistance to flukicide drugs is increasing. In addition, climate change with warmer and more humid weather will have a substantial effect on the establishment of both flukes and snails and will most likely increase the future distribution of F. hepatica.
Reply to Semin et al. Can Humans Discriminate Horse ‘Fear’ Chemosignals from Control Chemosignals? Comment on “Sabiniewicz et al. A Preliminary Investigation of Interspecific Chemosensory Communication of Emotions: Can Humans (Homo sapiens) Recognise Fear- and Non-Fear Body Odour from Horses (Equus ferus caballus). Animals 2021, 11, 3499”
Authors: Sabiniewicz Agnieszka , Białek Michał , Tarnowska Karolina , Świątek Robert , Dobrowolska Małgorzata , Sorokowski Piotr
Published: June 2022

Whereas several recent studies demonstrated that some animal species are able to recognize human emotions based on information from body odor [...]
Hereditary Basis of Coat Color and Excellent Feed Conversion Rate of Red Angus Cattle by Next-Generation Sequencing Data
Authors: He Yongmeng , Huang Yongfu , Wang Shizhi , Zhang Lupei , Gao Huijiang , Zhao Yongju , E Guangxin
Published: June 2022

Angus cattle have made remarkable contributions to the livestock industry worldwide as a commercial meat-type breed. Some evidence supported that Angus cattle with different coat colors have different feed-to-meat ratios, and the genetic basis of their coat color is inconclusive. Here, genome-wide association study was performed to investigate the genetic divergence of black and red Angus cattle with 63 public genome sequencing data. General linear model analysis was used to identify genomic regions with potential candidate variant/genes that contribute to coat color and feed conversion rate. Results showed that six single nucleotide polymorphisms (SNPs) and two insertion–deletions, which were annotated in five genes (ZCCHC14, ANKRD11, FANCA, MC1R, and LOC532875 [AFG3-like protein 1]), considerably diverged between black and red Angus cattle. The strongest associated loci, namely, missense mutation CHIR18_14705671 (c.296T > C) and frameshift mutation CHIR18_12999497 (c.310G>-), were located in MC1R. Three consecutive strongly associated SNPs were also identified and located in FANCA, which is widely involved in the Fanconi anemia pathway. Several SNPs of highly associated SNPs was notably enriched in ZCCHC14 and ANKRD11, which are related to myofiber growth and muscle development. This study provides a basis for the use of potential genetic markers to be used in future breeding programs to improve cattle selection in terms of coat color and meat phenotype. This study is also helpful to understand the hereditary basis of different coat colors and meat phenotypes. However, the putative candidate genes or markers identified in this study require further investigation to confirm their phenotypic causality and potential effective genetic relationships.
Characterization of β-Lactamases and Multidrug Resistance Mechanisms in Enterobacterales from Hospital Effluents and Wastewater Treatment Plant
Authors: Mutuku Christopher , Melegh Szilvia , Kovacs Krisztina , Urban Peter , Virág Eszter , Heninger Reka , Herczeg Robert , Sonnevend Ágnes , Gyenesei Attila , Fekete Csaba , Gazdag Zoltan
Published: June 2022

Antimicrobials in wastewater promote the emergence of antibiotic resistance, facilitated by selective pressure and transfer of resistant genes. Enteric bacteria belonging to Escherichia coli, Klebsiella pneumoniae, Klebsiella oxytoca, Enterobacter cloacae, and Citrobacter species (n = 126) from hospital effluents and proximate wastewater treatment plant were assayed for susceptibility to four antimicrobial classes. The β-lactamase encoding genes harbored in plasmids were genotyped and the plasmids were sequenced. A multidrug resistance phenotype was found in 72% (n = 58) of E. coli isolates, 70% (n = 43) of Klebsiella species isolates, and 40% (n = 25) of Enterobacter and Citrobacter species. Moreover, 86% (n = 50) of E. coli, 77% (n = 33) of Klebsiella species, and 25% (n = 4) of Citrobacter species isolates phenotypically expressed extended spectrum β-lactamase. Regarding ESBL genes, blaCTX-M-27 and blaTEM-1 were found in E. coli, while Klebsiella species harbored blaCTX-M-15, blaCTX-M-30, or blaSHV-12. Genes coding for aminoglycoside modifying enzymes, adenylyltransferases (aadA1, aadA5), phosphotransferases (aph(6)-1d, aph(3″)-Ib), acetyltransferases (aac(3)-IIa), (aac(6)-Ib), sulfonamide/trimethoprim resistant dihydropteroate synthase (sul), dihydrofolate reductase (dfrA), and quinolone resistance protein (qnrB1) were also identified. Monitoring wastewater from human sources for acquired resistance in clinically important bacteria may provide a cheaper alternative in regions facing challenges that limit clinical surveillance.
Computational Development of Inhibitors of Plasmid-Borne Bacterial Dihydrofolate Reductase
Authors: Silva Pedro J.
Published: June 2022

Resistance to trimethoprim and other antibiotics targeting dihydrofolate reductase may arise in bacteria harboring an atypical, plasmid-encoded, homotetrameric dihydrofolate reductase, called R67 DHFR. Although developing inhibitors to this enzyme may be expected to be promising drugs to fight trimethoprim-resistant strains, there is a paucity of reports describing the development of such molecules. In this manuscript, we describe the design of promising lead compounds to target R67 DHFR. Density-functional calculations were first used to identify the modifications of the pterin core that yielded derivatives likely to bind the enzyme and not susceptible to being acted upon by it. These unreactive molecules were then docked to the active site, and the stability of the docking poses of the best candidates was analyzed through triplicate molecular dynamics simulations, and compared to the binding stability of the enzyme–substrate complex. Molecule 32 ([6-(methoxymethyl)-4-oxo-3,7-dihydro-4H-pyrano[2,3-d]pyrimidin-2-yl]methyl-guanidinium) was shown by this methodology to afford extremely stable binding towards R67 DHFR and to prevent simultaneous binding to the substrate. Additional docking and molecular dynamics simulations further showed that this candidate also binds strongly to the canonical prokaryotic dihydrofolate reductase and to human DHFR, and is therefore likely to be useful to the development of chemotherapeutic agents and of dual-acting antibiotics that target the two types of bacterial dihydrofolate reductase.
Epidemiology, Clinical Characteristics, Risk Factors, and Outcomes of Candidemia in a Large Tertiary Teaching Hospital in Western China: A Retrospective 5-Year Study from 2016 to 2020
Authors: Hou Jie , Deng Jin , Liu Ya , Zhang Weili , Wu Siying , Liao Quanfeng , Ma Ying , Kang Mei
Published: June 2022

The aim of this study was to investigate the current status of candidemia and evaluate the clinical characteristics, risk factors and outcomes among different species. We conducted a retrospective study by univariate and multivariate analysis between Candida albicans and non-albicans Candida (NAC) species in a Chinese national medical center from 2016 to 2020. Among the 259 episodes, C. albicans (38.6%) was the leading species, followed by C. tropicalis (24.3%), C. parapsilosis (20.5%), and C. glabrata (12.4%). Most C. albicans and C. parapsilosis were susceptible to nine tested antifungal agents, whereas C. tropicalis showed 30.2~65.9% resistance/non-wild-type to four azoles with great cross-resistance, indicating that fluconazole should not be used for empirical antifungal treatment. In multivariable models, the factor related to an increased risk of NAC was glucocorticoid exposure, whereas gastrointestinal hemorrhage and thoracoabdominal drainage catheters were associated with an increased risk in C. albicans. Subgroup analysis revealed leukemia and lymphoma, as well as glucocorticoid exposure, to be factors independently associated with C. tropicalis in comparison with C. albicans candidemia. No significant differences in 7-day mortality or 30-day mortality were observed between C. albicans and NAC. This study may provide useful information with respect to choosing empirical antifungal agents and exploring differences in molecular mechanisms.
Antioxidant Therapy in Cancer: Rationale and Progress
Authors: Luo Maochao , Zhou Li , Huang Zhao , Li Bowen , Nice Edouard C. , Xu Jia , Huang Canhua
Published: June 2022

Cancer is characterized by increased oxidative stress, an imbalance between reactive oxygen species (ROS) and antioxidants. Enhanced ROS accumulation, as a result of metabolic disturbances and signaling aberrations, can promote carcinogenesis and malignant progression by inducing gene mutations and activating pro-oncogenic signaling, providing a possible rationale for targeting oxidative stress in cancer treatment. While numerous antioxidants have demonstrated therapeutic potential, their clinical efficacy in cancer remains unproven. Here, we review the rationale for, and recent advances in, pre-clinical and clinical research on antioxidant therapy in cancer, including targeting ROS with nonenzymatic antioxidants, such as NRF2 activators, vitamins, N-acetylcysteine and GSH esters, or targeting ROS with enzymatic antioxidants, such as NOX inhibitors and SOD mimics. In addition, we will offer insights into prospective therapeutic options for improving the effectiveness of antioxidant therapy, which may expand its applications in clinical cancer treatment.
Antioxidant Properties of Cerium Oxide Nanoparticles Prevent Retinal Neovascular Alterations In Vitro and In Vivo
Authors: Tisi Annamaria , Pulcini Fanny , Carozza Giulia , Mattei Vincenzo , Flati Vincenzo , Passacantando Maurizio , Antognelli Cinzia , Maccarone Rita , Delle Monache Simona
Published: June 2022

In this study, we investigated whether cerium oxide nanoparticles (CeO2-NPs), a promising antioxidant nanomaterial, may contrast retinal vascular alterations induced by oxidative damage in vitro and in vivo. For the in vivo experiments, the light damage (LD) animal model of Age-Related Macular Degeneration (AMD) was used and the CeO2-NPs were intravitreally injected. CeO2-NPs significantly decreased vascular endothelial growth factor (VEGF) protein levels, reduced neovascularization in the deep retinal plexus, and inhibited choroidal sprouting into the photoreceptor layer. The in vitro experiments were performed on human retinal pigment epithelial (ARPE-19) cells challenged with H2O2; we demonstrated that CeO2-NPs reverted H2O2-induced oxidative stress-dependent effects on this cell model. We further investigated the RPE–endothelial cells interaction under oxidative stress conditions in the presence or absence of CeO2-NPs through two experimental paradigms: (i) treatment of human umbilical vein endothelial cells (HUVECs) with conditioned media from ARPE-19 cells, and (ii) coculture of ARPE-19 and HUVECs. In both experimental conditions, CeO2-NPs were able to revert the detrimental effect of H2O2 on angiogenesis in vitro by realigning the level of tubule formation to that of the control. Altogether, our results indicate, for the first time, that CeO2-NPs can counteract retinal neovascularization and may be a new therapeutic strategy for the treatment of wet AMD.
Biochemical Marker Assessment of Chronic Carbamazepine Exposure at Environmentally Relevant Concentrations in Juvenile Common Carp (Cyprinus carpio)
Authors: Liang Xinyue , Csenki Zsolt , Ivánovics Bence , Bock Illés , Csorbai Balázs , Molnár József , Vásárhelyi Erna , Griffitts Jeffrey , Ferincz Árpád , Urbányi Béla , Ács András
Published: June 2022

Worldwide, the anticonvulsant drug carbamazepine (CBZ) is the most frequently identified pharmaceutical residue detected in rivers. Reported chronic effects of CBZ in non-target freshwater organisms, particularly fish, include oxidative stress and damage to liver tissues. Studies on CBZ effects in fish are mostly limited to zebrafish and rainbow trout studies. Furthermore, there are only a few chronic CBZ studies using near environmental concentrations. In this study, we provide data on subacute effects of CBZ exposure (28 days) to common carp (Cyprinus carpio), employing a set of biochemical markers of damage and exposure. CBZ was found to induce a significant change in the hepatic antioxidant status of fish subjected to 5 µg/L. Moreover, with increasing concentrations, enzymatic and non-enzymatic biomarkers of oxidative defence (catalase (CAT), superoxide dismutase (SOD), glutathione reductase (GR), DNA strand breaks)), toxicant biotransformation (ethoxyresorufin-o-demethylase (EROD), glutathione-S-transferase (GST)), and organ and tissue damage (lactate dehydrogenase (LDH), cetylcholinesterase (AChE)) were altered. The AChE, LDH, and lipid peroxidation (LPO) results indicate the occurrence of apoptotic process activation and tissue damage after 28 days of exposure to CBZ. These findings suggest significant adverse effects of CBZ exposure to common carp at concentrations often found in surface waters.
Jakarta Pandemic to Endemic Transition: Forecasting COVID-19 Using NNAR and LSTM
Authors: Pontoh Resa Septiani , Toharudin Toni , Ruchjana Budi Nurani , Gumelar Farhat , Putri Fariza Alamanda , Agisya Muhammad Naufal , Caraka Rezzy Eko
Published: June 2022

In December 2021, the latest COVID-19 variant, Omicron, was confirmed in Indonesia. Unlike the Delta variant, the number of deaths in the Omicron type did not increase significantly and remained constant, even though the cases increased significantly. It is hoped that Indonesia will declare COVID-19 endemic. Jakarta is the capital of Indonesia and the first city where the new COVID-19 virus emerged. Therefore, we are trying to model COVID-19 cases in Jakarta and predict future cases to see if endemic conditions are identified. We applied Neural Network Auto-Regressive (NNAR) and Long Short-Term Memory (LSTM) methods. It is found that the NNAR forecast better for positive confirmed cases with an R-squared 0.939 and the LSTM forecast better for cases of death with an R-squared 0.9337. The forecasting results for the next 7 days reveal that positive confirmed cases of COVID-19 in Jakarta will increase slightly. In addition, the death cases experienced a very small increase, only one new case. According to the results of this study, it can be concluded that COVID-19 in Jakarta will enter an endemic phase in Jakarta, with no substantial increase in cases and a low mortality rate.
Iterative Annotation of Biomedical NER Corpora with Deep Neural Networks and Knowledge Bases
Authors: Silvestri Stefano , Gargiulo Francesco , Ciampi Mario
Published: June 2022

The large availability of clinical natural language documents, such as clinical narratives or diagnoses, requires the definition of smart automatic systems for their processing and analysis, but the lack of annotated corpora in the biomedical domain, especially in languages different from English, makes it difficult to exploit the state-of-art machine-learning systems to extract information from such kinds of documents. For these reasons, healthcare professionals lose big opportunities that can arise from the analysis of this data. In this paper, we propose a methodology to reduce the manual efforts needed to annotate a biomedical named entity recognition (B-NER) corpus, exploiting both active learning and distant supervision, respectively based on deep learning models (e.g., Bi-LSTM, word2vec FastText, ELMo and BERT) and biomedical knowledge bases, in order to speed up the annotation task and limit class imbalance issues. We assessed this approach by creating an Italian-language electronic health record corpus annotated with biomedical domain entities in a small fraction of the time required for a fully manual annotation. The obtained corpus was used to train a B-NER deep neural network whose performances are comparable with the state of the art, with an F1-Score equal to 0.9661 and 0.8875 on two test sets.
The Impact of Using Mobile Phones on Gait Characteristics: A Narrative Review
Authors: Tan Yuanyuan , Sun Yuliang , Lang Chungang , Wen Yi
Published: June 2022

The aim of this study was to summarize the research status and reveal the impact of mobile phone use on gait characteristics by reviewing the existing studies in terms of research status, participants, independent variables, dependent variables, main findings, etc. Twenty-nine studies which investigated the impact of using mobile phones on gait characteristics were identified through a literature search. The majority of these studies examined the effects of mobile phone use on gait characteristics in young people. The preliminary results showed that walking while using a mobile phone has significant impacts on gait. It can decrease gait velocity, cadence, step length and stride length, along with significantly increasing step width, step time and double support time. The results varied among different mobile phone usage, which resulted from the different motor and mental demands. Additionally, age and environment could affect the results as well. As well as the kinematic characteristics, we suggest that kinetic and EMG analysis are conducted in future studies.
DriNet: Dynamic Backdoor Attack against Automatic Speech Recognization Models
Authors: Ye Jianbin , Liu Xiaoyuan , You Zheng , Li Guowei , Liu Bo
Published: June 2022

Automatic speech recognition (ASR) is popular in our daily lives (e.g., via voice assistants or voice input). Once its security attributes are destroyed, it poses as a severe threat to a user’s life and ‘property safety’. Prior research has demonstrated that ASR systems are vulnerable to backdoor attacks. A model embedded with a backdoor behaves normally on clean samples yet misclassifies malicious samples that contain triggers. Existing backdoor attacks have mostly been conducted in the image domain. However, they can not be applied in the audio domain because of poor transferability. This paper proposes a dynamic backdoor attack method against ASR models, named DriNet. Significantly, we designed a dynamic trigger generation network to craft a variety of audio triggers. It is trained jointly with the discriminative model incorporated with an attack success rate on poisoned samples and accuracy on clean samples. We demonstrate that DriNet achieves an attack success rate of 86.4% when infecting only 0.5% of the training set without reducing its accuracy. DriNet can still achieve comparable attack performance to backdoor attacks using static triggers, further enjoying richer attack patterns. We further evaluated DriNet’s resistance to a current state-of-the-art defense mechanism. The anomaly index of DriNet is more than 37.4% smaller than that of BadNets method. The triggers generated by DriNet are hard reverse, keeping DriNet from the detectors.
Switching Neural Network Control for Underactuated Spacecraft Formation Reconfiguration in Elliptic Orbits
Authors: Yu Jinlong , Li Zhi , Jia Lu , Zhang Yasheng
Published: June 2022

A switching neural network control scheme, consisting of the adaptive neural network controller and sliding mode controller, is proposed for underactuated formation reconfiguration in elliptic orbits with the loss of either the radial or in-track thrust. By using the inherent coupling of system states, the switching neural network technique is then adopted to estimate the unmatched disturbances and design the underactuated controller to achieve underactuated formation reconfiguration with high precision. The adaptive neural network controller works in the active region, and the disturbances composed of linearization errors and external perturbations are approximated by radial basis function neural networks. The adaptive sliding mode controller works outside the active region, and the upper bound of the approximation errors is estimated by the adaptation law. The stability of the closed-loop control system is proved via the Lyapunov-based approach. The numerical simulation results have demonstrated the rapid, high-precision and robust performance of the proposed controller compared with the linear sliding mode controller.
Pixel Resolution Imaging in Parallel Phase-Shifting Digital Holography
Authors: Wang Yue , Meng Haoran , Liu Xinyue , Liu Jiahao , Cui Xu
Published: June 2022

Parallel phase-shifting digital holography (PPSDH) employing a polarization image sensor can suppress zero-order and twin-image noise through a single exposure, achieve instantaneous measurement of complex-valued dynamic objects, and have broad applications in the areas of biomedicine, etc. To improve the imaging resolution of PPSDH, we propose an oversampled super-pixel image reconstruction method, which can be expressed as the implementation of nearest-neighbor interpolation to replace blank pixels in sparse sub-phase-shift holograms. We found experimentally that the maximum spatial lateral resolution of the reconstructed image based on the existing super-pixel method, B-spline, bicubic, bilinear, and the proposed nearest-neighbor interpolation was 12.4 µm, 11.4 µm, 9.8 µm, 8.8 µm, and 7.8 µm, respectively. The main reason for not reaching the ideal value of 6.9 µm was the inherent residual zero-order and twin-image noise, which needs to be removed in the future.
Tri-Band Bidirectional Antenna for 2.4/5 GHz WLAN and Ku-Band Applications
Authors: Lamultree Suthasinee , Thanamalapong Wutthipong , Dentri Sitthichai , Phongcharoenpanich Chuwong
Published: June 2022

A compact tri-band, low profile, and lightweight antenna is proposed for 2.4/5 GHz WLAN and Ku-band applications. The antenna geometry was a radiating rectangular patch surrounded by a wide circular slot with an inverted-L strip connected to one side of the slot. It was mounted on a copper layer of a single side FR4 substrate with a dielectric constant of 4.3 and a height of 1.6 mm. It was fed by a 50-Ω coplanar waveguide. This design was very compact (40 × 40 × 1.6 mm3). Simulated and actual measurements of an antenna setup in the laboratory verified that the antenna’s bidirectional radiation pattern completely covered the three transmission bands: 2.4–2.485 GHz, 5.15–5.825 GHz and 13.4–17.7 GHz with less than 10-dB return loss and maximum gains of 2.35 dBi, 4.41 dBi and 4.71 dBi, respectively. Wireless communication for the self-navigated vehicle, for one example, is fully supported by this single antenna.
In Vitro Assessment of Antiproliferative Activity and Cytotoxicity Modulation of Capsicum chinense By-Product Extracts
Authors: Chel-Guerrero Lilian Dolores , Scampicchio Matteo , Ferrentino Giovanna , Rodríguez-Buenfil Ingrid Mayanín , Fragoso-Serrano Mabel
Published: June 2022

Capsicum chinense J., also known locally as habanero pepper, is a medicinal herb known for its pharmacological properties. Its properties are attributed to the capsaicinoids and polyphenols found in its fruit and polyphenols in its by-products. The anticancer potential of C. chinense by-products remains unexplored. This study aimed to evaluate the antiproliferative activity and modulation of the cytotoxicity of extracts obtained from C. chinense by-products of plants grown on black and red soils of Yucatan, Mexico. Dry by-product extracts were obtained using maceration, a Soxhlet, and supercritical fluid extraction. In vitro antiproliferative activity and cytotoxicity modulation were evaluated by the sulforhodamine B method. The extract of leaves of plants grown on black soil obtained by maceration displayed selective high cytotoxicity against colorectal cancer cells, IC50 HCT–15 = 16.23 ± 2.89 µg mL−1. The leaf and stem extracts of plants grown on red soil obtained by maceration potentiated the vinblastine’s effect against parental breast cancer cells, MCF–7/Sens, with a reversion factor of 362.50-fold. Additionally, the extract of stems from plants grown on black soil obtained by supercritical fluid extraction and all the by-product extracts from plants grown on black soil obtained through maceration increased the effect of vinblastine against MCF–7/Vin+ with a reversion factor from 5.06- to 7.78-fold. These results highlight the anticancer potential of C. chinense by-products.
Artificial Intelligence in the Construction Industry: Main Development Trajectories and Future Outlook
Authors: Chen Hsiu-Ping , Ying Kuo-Ching
Published: June 2022

Recent developments in artificial intelligence (AI) have greatly influenced progress in various industries. While the complexity of the construction industry makes it an essential and potential area for AI applications, there has been no analysis conducted on the main development paths for the applications of AI technologies in the construction industry. To fill this gap, this study applied the main path analysis method to investigate the evolution of AI technologies in the construction industry. This study analyzed 587 articles published between 1989 and 2021 to identify the main development trajectories of AI technologies in the construction industry and to suggest possible directions in which AI technologies can be further applied to promote progress in architectural design, engineering design, and construction services.
A Network-Based Model for Optimization of Container Location Assignment at Inland Terminals
Authors: Rožić Tomislav , Ivanković Božidar , Bajor Ivona , Starčević Martin
Published: June 2022

The development of inland terminals helps seaports mitigate inevitable storage capacity problems, extending their gravitational field and strengthening their competitive advantage. Optimizing the container storage, efficiency, and productivity of seaports and inland terminals is becoming increasingly important. The present paper develops a network-based mathematical model to optimize the location assignment of inbound containers at inland terminals. The model’s assumptions are based on the analysis of criteria at representative European inland terminals, and the model aims to reduce unproductive manipulations. The present study is one of the few to develop a single model that integrates all important criteria for container location assignment, including a container’s dimensions, its occupancy, cargo type, the container’s owner, and distance to the final user. These criteria are important for the terminal operator so that they can determine container locations in a way that minimizes unproductive manipulations. Data from a single inland terminal were used to validate the model within the FlexSim CT simulation environment. Our results suggest that the model can reduce unproductive manipulations and associated costs at inland terminals.
Cavitation Erosion Characteristics for Different Metal Surface and Influencing Factors in Water Flowing System
Authors: He Jie , Liu Xiumei , Li Beibei , Zhai Jixing , Song Jiaqing
Published: June 2022

The impact of cavitation erosion behavior on different metals in a water flowing system was investigated experimentally. A flowing system of water was built and a transparent observation window is designed to capture the cavitation flow. Erosion tests were carried out on red copper, brass, pure aluminum, and an aluminum alloy. The cavitation behaviors are presented by the weight loss and cavitation erosion rate, and related changes in the topography of the metal surface are also discussed. The variation in the cavitation erosion on metallic specimens with increasing time could be divided into three stages: rising stage, stable stage, and attenuation stage. The pure aluminum material had the lowest yield strength, and suffered the most severe cavitation erosion while brass had the highest yield strength and good mechanical properties, which suffered the least cavitation erosion. Furthermore, the roughness of the material surface was also one of the important factors affecting the cavitation erosion rate. The weight loss of milling specimens with higher surface roughness was slightly lower than that of grinding. The high roughness of the metallic surface increased the pressure loss along the flow path and the suppressed cavitation strength. This work provides an experimental reference for the anti-cavitation ability improvement in metal materials and promotes an understanding of the related mechanism.
The Investigation of Shallow Structures at the Meishan Fault Zone with Ambient Noise Tomography Using a Dense Array Data
Authors: Wu Wei-Jhe , Su Chien-Min , Chen Chau-Huei
Published: June 2022

Seismic monitoring relies on seismography. However, the high cost of seismic equipment has presented a challenge to increasing the density of seismic networks in previous decades. Due to the large station spacing and inferior coverage of stations, this situation has led to a loss of detail in many research results. Along with the improvement of technology, the problem of increasing the density of seismographic observations is no longer an impossible issue. This makes it feasible to deploy a dense seismic network for monitoring earthquakes. This study deployed a linear dense array across the Meishan Fault in west-southern Taiwan for the purpose of analyzing the shallow fault zone structure. While the 1906 Meishan earthquake occurred in a period when historic records were available, the surficial geology surveys of the Meishan Fault are challenging because farming and construction engineering have obscured the outcrop. Early surveys of the Meishan Fault were mainly seismic surveys. In recent decades, over thirty profiles have been completed. However, the reflection seismic records had poor signal-to-noise ratios because the Meishan Fault is buried under thick sediments. Thus, the shallow structure of the Meishan Fault is still not known in detail. This study applied double-beamforming tomography to a dense seismic array to obtain high-resolution images of the Meishan Fault zone. The result shows that there is a south-dipping interface near the fault trace as indicated by the Central Geological Survey of Taiwan. In addition, we observed velocity transitions of perturbation profiles that may be caused by a branch fault, the Chentsoliao Fault. This study demonstrates that the ambient noise double beamforming method is an effective tool for imaging the detailed shallow structure along with the dense seismic array.
Architectural Experiment Design of Solar Energy Harvesting: A Kinetic Façade System for Educational Facilities
Authors: Choi Ho Soon
Published: June 2022

This study proposes an architectural design for renewable energy production to increase energy independence in the architectural field. Among natural energy sources, solar panels that can be applied to building façades have been developed to use solar energy. To maximize renewable energy generation, solar panels can be adjusted according to the optimal tilt for each month. They can be attached to and detached from the building façade and installed on an existing building elevation. Thus, it is possible to increase the energy independence of old buildings. The solar panel developed in this study increases energy independence and presents a creative “kinetic façade,” in which solar panels move each month according to the optimal tilt angle.
Factors Influencing YouTube as a Learning Tool and Its Influence on Academic Achievement in a Bilingual Environment Using Extended Information Adoption Model (IAM) with ML Prediction—Jordan Case Study
Authors: Abu-Taieh Evon , AlHadid Issam , Masa’deh Ra’ed , Alkhawaldeh Rami S. , Khwaldeh Sufian , Alrowwad Ala’aldin
Published: June 2022

YouTube usage as a learning tool is evident among students. Hence, the goal of this study is to examine the various factors that influence the use of YouTube as a learning tool, which influences academic achievement in a bilingual academic context. Using survey data from 704 YouTube users from Jordan’s bilingual academic institutes, the research model was empirically validated. Using Amos 20, structural equation modeling (SEM) was performed to assess the study hypotheses. SEM permits concurrent checking of the direct and indirect effects of all hypotheses. Confirmatory factor analysis (CFA) was used to validate the instrument items’ properties in addition to machine learning methods: ANN, SMO, the bagging reduced error pruning tree (RepTree), and random forest. The empirical results offer several key findings: academic achievement (AA) is influenced by the information adoption (IA) of YouTube as a learning tool. Information adoption (IA) is influenced by information usefulness (IU). Source credibility (SC) and information quality (IQ) both influence information usefulness (IU), while information language (IL) does not. Information quality (IQ) is influenced by intrinsic, contextual, and accessibility information quality. This study adds to the literature by empirically testing and theorizing the effects of YouTube as a learning tool on the academic achievement of Jordanian university students who are studying in bilingual surroundings.
Full-Body Motion Capture-Based Virtual Reality Multi-Remote Collaboration System
Authors: Ha Eunchong , Byeon Gongkyu , Yu Sunjin
Published: June 2022

Various realistic collaboration technologies have emerged in the context of the COVID-19 pandemic. However, as existing virtual reality (VR) collaboration systems generally employ an inverse kinematic method using a head-mounted display and controller, the user and character cannot be accurately matched. Accordingly, the immersion level of the VR experience is low. In this study, we propose a VR remote collaboration system that uses motion capture to improve immersion. The system uses a VR character in which a user wearing motion capture equipment performs the same operations as the user. Nevertheless, an error can occur in the virtual environment when the sizes of the actual motion capture user and virtual character are different. To reduce this error, a technique for synchronizing the size of the character according to the user’s body was implemented and tested. The experimental results show that the error between the heights of the test subject and virtual character was 0.465 cm on average. To verify that the implementation of the motion-capture-based VR remote collaboration system is possible, we confirm that three motion-capture users can collaborate remotely using a photon server.
SSA-CAE-Based Abnormal Data Classification Method in Edge Intelligence Device of CNC Machine
Authors: Kim Donghyun , Oh Seokju , Lee Jeahyeong , Jeong Jongpil
Published: June 2022

Smart factories and big data are important factors in the Fourth Industrial Revolution. Smart factories aim for automation and integration; however, the most important part is the application of data. Despite extensive research on the maintenance and quality management of big data-based production equipment, industrial data gathered for analysis contain more normal data than abnormal data. In addition, a significant amount of energy is expended in the data pre-processing process to analyze the acquired data. Therefore, to maintain production equipment and quality management, data classification technology that allows easy data analysis by classifying abnormal data into normal data is required. In this paper, we propose an abnormal data classification architecture for cycle data sets gathered from production facilities through SSA-CAE along with data storage methods for each product unit. SSA-CAE is a hybrid technique that combines singular spectrum analysis (SSA) techniques that are effective in reducing noise in time series data with convolutional auto encoder (CAE) that have performed well in time series.