bluuebunny/crossref_metadata_2025 huggingface dataset:
Experts by Experience: Qualitative Evaluation of Adolescent Participation in the Development of a Technological Intervention to Prevent Youth Suicide in Chile
Authors: Schilling Sara Hamilton , Carreño Alejandra , Tapia Eric , Mascayano Franco , Pitronello Romina , Santander Felipe , Jorquera María José , Burrone María Soledad , Alvarado Ruben Vladimir
Published: January 2021

Adolescent suicide is a pressing problem in Chile that has not yet been sufficiently addressed, as suicide rates have stagnated in recent years. One possible explanation could be linked to the adult-centered paradigm that continues to prevail in relation to adolescent health initiatives. In light of this, programs that seek to promote youth mental health should consider incorporating adolescents in the design process using participatory methodologies, to ensure that these initiatives are well-suited for the population. In line with this recommendation, a group of seven adolescents, 13 to 20 years of age, were incorporated into a research team to actively guide the design, development, and validation of a technology-based intervention, known as Project Clan, which was piloted to reduce adolescent suicide in schools in Chile. This group was known as the “Group of Experts,” in acknowledgment of their role as experts by experience on adolescence. A qualitative case study was conducted to explore their lived experiences, through semistructured individual in-depth interviews with six members of the group. Results showed that the adolescents had a high level of interest in mental health and had experienced problems of their own or accompanied friends who were struggling, which motivated their participation in the study. They had a critical view of the previous interventions they had received through educational institutions and valued their role in the promotion of their peers' mental health through the Group of Experts. They also highlighted the importance of creating tools that complement their daily lives and provide an alternative to existing social networks, by respecting their anonymity, providing a secure place for divulgation and self-expression, and facilitating access to professional support. We conclude that programs that address issues that affect adolescents should incorporate adolescents in the decision-making and design processes to ensure the acceptability and effectivity of their interventions.
Social Networking Addiction Among Hong Kong University Students: Its Health Consequences and Relationships With Parenting Behaviors
Authors: Yu Lu , Luo Tingyu
Published: January 2021

The use of social networking sites (SNSs) has been growing at a staggering rate, especially among university students. The present study investigated the prevalence of social networking addiction (SNA), its health consequences, and its relationships with parents' Internet-specific parenting behaviors in a sample of Hong Kong university students (N = 390). Adopting the 9-item social media disorder scale, 21.5% of the participating students met the criteria for SNA. Students with SNA showed longer sleeping latency, more sleep disturbance, poorer academic performance, lower levels of life satisfaction, and higher levels of depression than did students without SNA. Parental reactive restriction and limiting online behaviors of the participants were associated with higher risk of SNA. The findings suggest the severity of SNA and its negative consequences among Hong Kong university students. While parental behaviors limiting children's use of SNSs were found to increase the occurrence rate of SNA among university students, longitudinal studies are needed to further examine this causal relationship.
Self-Rated Healthy Life Expectancy Changes in Jiangxi Province of China by Gender and Urban–Rural Differences, 2013–2018
Authors: Liu Zhitao , Zheng Huilie , Wu Yuhang , Wang Shengwei , Liu Yong , Hu Songbo
Published: January 2021

Background: Globalization has brought about rapid economic and technological development, and life expectancy (LE) is constantly increasing. However, it is not clear whether an increase in LE will result in an increase in healthy life expectancy (HLE). This study evaluates trends in the self-rated healthy life expectancy (SRHLE) of residents aged 15 and older in Jiangxi Province of China from 2013 to 2018 and analyzes gender differences and urban–rural differences. This study provides a basis for the formulation of relevant public health policies.

Methods: Based on two National Health Services Survey databases of Jiangxi in 2013 and 2018 as well as infant mortality rates and under-5 mortality rates from the Health Commission of Jiangxi, the Sullivan method was used to calculate SRHLE. The changes in SRHLE were decomposed into health and mortality effects using the decomposition method.

Results: SRHLE decreased from 56.55 to 55.54 years and from 60.00 to 57.87 years for men and women aged 15 from 2013 to 2018, respectively. The SRHLE of women aged 15 was 3.45 and 2.34 years longer than that of men in 2013 and 2018, respectively. The SRHLE of urban men aged 15 was 2.9 and 4.46 years longer than that of rural men in 2013 and 2018, respectively, and that of urban women aged 15 was 3.28 and 5.57 years longer than that of rural women.

Conclusions: The decreased SRHLE indicated that the self-rated health (SRH) status of residents in Jiangxi has worsened, and it provided evidence for the expansion of morbidity, mainly due to the increased prevalence of chronic diseases and the improvement in residents' health awareness. Policy efforts are necessary to control the increased morbidity of chronic diseases and reduce gender and urban–rural differences in the quantity and quality of years lived.
Digital Articulation: Examining Text-Based Linguistic Performances in Mobile Communication Through Keystroke-Logging Analysis
Authors: Schneier Joel
Published: January 2021

This study examines how text-based mobile communication practices are performatively constructed as individuals compose messages key-by-key on virtual keyboards, and how thesesynchronous performances(Mobile interface theory: embodied space and locative media. New York, NY: Routledge) reflect the iterative process of constructing and maintaining interpersonal relationships. In doing so, this study reports on keystroke-logging analysis (see Writ. Commun. 30, 358–392) in order to observe how participants (N =10) composed text as part of everyday mobile communication for the period of one week, subsequently producing 179,996 individual keystroke log-file records. Participants used LogKey, a virtual keyboard application made exclusively for this study to run on the Android mobile operating system. Analysis of keystroke log-file data suggest that timing processes of composing text-messages may differ as participants messaged with different categories of interlocutors, composed on different communication applications, and composed paralinguistic features—such as variants ofLolandHahaThurlow and Brown, (Discourse Anal. Online, 2003, 1, 1); Tagg, (Discourse of text messaging. 2012, Bloomsbury, UK)—at different turn-taking positions. This evidence suggests that keystroke-logging methods may contribute to understanding of how individuals manage interpersonal relationships in real-time (Please reply! the replying norm in adolescent SMS communication,” in The inside text: social, cultural and design perspectives on SMS. (Norwell, MA: Springer), 53–73); (Beyond genre: closings and relational work in texting,” in Digital discourse: language in the new media. (Oxford: Oxford University Press), 67–85), and suggests future direction for methodologically studying linguistic performances as part of text-based mobile communication.
The Discrepancy Between Simulation and Observation of Electric Fields in Collisionless Shocks
Authors: Wilson Lynn B. , Chen Li-Jen , Roytershteyn Vadim
Published: January 2021

Recent time series observations of electric fields within collisionless shocks have shown that the fluctuating, electrostatic fields can be in excess of one hundred times that of the quasi-static electric fields. That is, the largest amplitude electric fields occur at high frequencies, not low. In contrast, many if not most kinetic simulations show the opposite, where the quasi-static electric fields dominate, unless they are specifically tailored to examine small-scale instabilities. Further, the shock ramp thickness is often observed to fall between the electron and ion scales while many simulations tend to produce ramp thicknesses at least at or above ion scales. This raises numerous questions about the role of small-scale instabilities and about the ability to directly compare simulations with observations.
Towards Interactive Analytics over RDF Graphs
Authors: Papadaki Maria-Evangelia , Spyratos Nicolas , Tzitzikas Yannis
Published: January 2021

The continuous accumulation of multi-dimensional data and the development of Semantic Web and Linked Data published in the Resource Description Framework (RDF) bring new requirements for data analytics tools. Such tools should take into account the special features of RDF graphs, exploit the semantics of RDF and support flexible aggregate queries. In this paper, we present an approach for applying analytics to RDF data based on a high-level functional query language, called HIFUN. According to that language, each analytical query is considered to be a well-formed expression of a functional algebra and its definition is independent of the nature and structure of the data. In this paper, we investigate how HIFUN can be used for easing the formulation of analytic queries over RDF data. We detail the applicability of HIFUN over RDF, as well as the transformations of data that may be required, we introduce the translation rules of HIFUN queries to SPARQL and we describe a first implementation of the proposed model.
Toward ATM Resiliency: A Deep CNN to Predict Number of Delayed Flights and ATFM Delay
Authors: Sanaei Rasoul , Pinto Brian Alphonse , Gollnick Volker
Published: January 2021

The European Air Traffic Management Network (EATMN) is comprised of various stakeholders and actors. Accordingly, the operations within EATMN are planned up to six months ahead of target date (tactical phase). However, stochastic events and the built-in operational flexibility (robustness), along with other factors, result in demand and capacity imbalances that lead to delayed flights. The size of the EATMN and its complexity challenge the prediction of the total network delay using analytical methods or optimization approaches. We face this challenge by proposing a deep convolutional neural network (DCNN), which takes capacity regulations as the input. DCNN architecture successfully improves the prediction results by 50 percent (compared to random forest as the baseline model). In fact, the trained model on 2016 and 2017 data is able to predict 2018 with a mean absolute percentage error of 22% and 14% for the delay and delayed traffic, respectively. This study presents a method to provide more accurate situational awareness, which is a must for the topic of network resiliency.
Crop Diversification in Viticulture with Aromatic Plants: Effects of Intercropping on Grapevine Productivity in a Steep-Slope Vineyard in the Mosel Area, Germany
Authors: Dittrich Felix , Iserloh Thomas , Treseler Cord-Henrich , Hüppi Roman , Ogan Sophie , Seeger Manuel , Thiele-Bruhn Sören
Published: January 2021

The effects of intercropping grapevine with aromatic plants are investigated using a multi-disciplinary approach. Selected results are presented that address the extent to which crop diversification by intercropping impacts grapevine yield and must quality, as well as soil water and mineral nutrients (NO3-N, NH4-N, plant-available K and P). The experimental field was a commercial steep-slope vineyard with shallow soils characterized by a high presence of coarse rock fragments in the Mosel area of Germany. The field experiment was set up as randomized block design. Rows were either cultivated with Riesling (Vitis vinifera L.) as a monocrop or intercropped with Origanum vulgare or Thymus vulgaris. Regarding soil moisture and nutrient levels, the topsoil (0–0.1 m) was more affected by intercropping than the subsoil (0.1–0.3 m). Gravimetric moisture was consistently lower in the intercropped topsoil. While NO3-N was almost unaffected by crop diversification, NH4-N, K, and P were uniformly reduced in topsoil. Significant differences in grapevine yield and must quality were dominantly attributable to climate variables, rather than to the treatments. Yield stabilization due to intercropping with thyme and oregano seems possible with sufficient rainfall or by irrigation. The long-term effects of intercropping on grapevine growth need further monitoring.
Impact of Climate Warming on Cotton Growth and Yields in China and Pakistan: A Regional Perspective
Authors: Arshad Adnan , Raza Muhammad Ali , Zhang Yue , Zhang Lizhen , Wang Xuejiao , Ahmed Mukhtar , Habib-ur-Rehman Muhammad
Published: January 2021

Year to year change in weather poses serious threats to agriculture globally, especially in developing countries. Global climate models simulate an increase in global temperature between 2.9 to 5.5 °C till 2060, and crop production is highly vulnerable to climate warming trends. Extreme temperature causes a significant reduction in crop yields by negatively regulating the crop phenology. Therefore, to evaluate warming impact on cotton (Gossypium hirsutum L.) production and management practices, we quantified agrometeorological data of 30 years by applying multiple crop modelling tools to compute the expected rise in temperature, impact of crop phenology, yield loss, provision of agrometeorology-services, agronomic technologies, and adaptation to climate-smart agriculture. Model projections of 15 agrometeorology stations showed that the growing duration of the sowing-boll opening and sowing-harvesting stages was reduced by 2.30 to 5.66 days decade−1 and 4.23 days decade−1, respectively, in Pakistan. Temperature rise in China also advanced the planting dates, sowing emergence, 3–5 leaves, budding anthesis, full-bloom, cleft-boll, boll-opening, and boll-opening filling by 24.4, 26.2, 24.8, 23.3, 22.6, 15.8, 14.6, 5.4, 2.9, and 8.0 days. Furthermore, present findings exhibited that the warming effect of sowing-harvest time was observed 2.16 days premature, and delayed for 8.2, 2.4, and 5.3 days in the 1970s, 1980s, and 1990s in China. APSIM-cotton quantification revealed that the sowing, emergence, flowering, and maturity stages were negatively correlated with temperature −2.03, −1.93, −1.09, and −0.42 days °C−1 on average, respectively. This study also provided insight into the adaptation of smart and better cotton by improving agrotechnological services.
Combined Acidification and Solar Drying of Pig Slurries for Nutrient Recovery and Controlled Atmospheric Emissions
Authors: Prenafeta-Boldú Francesc X. , Fernández Belén , Viñas Marc , Noguerol Joan , Soler Joan , Illa Josep
Published: January 2021

The solar drying of pig slurries was tested in a pilot-scale greenhouse (10 m2 footprint), operated with forced ventilation under low and high solar irradiation in Mediterranean conditions. Gaseous emissions were prevented through slurry acidification and by the biofiltration of exhaust gases. Air relative humidity and temperature in and out the greenhouse, as well as the weight of a slurry sample, were monitored online to command the ventilation regime. Daily average drying rate values ranged from 0.3 to 2.8 kg m−2 d−1 and displayed a direct dependency with solar radiation until the pig slurry lost a 60% of its initial weight, with a solar energy efficiency of about 26%. Upon further drying, the water content from pig slurries stabilized at around 10%. Mass balances between the initial slurry and dried product were closed for total solids and organic matter, but the recovery of nutrients ranged from 69% to 81%, apparently because of precipitation and incrustation phenomena. The NPK composition of the final product was 4.3–2.5–3.8 and fulfilled current regulations for solid organic fertilizers. Operational costs of the drying process and fertilizing quality parameters were also discussed.
Multiparametric Study of Antioxidant Effect on Ram Sperm Cryopreservation—From Field Trials to Research Bench
Authors: Riesco Marta F. , Alvarez Mercedes , Anel-Lopez Luis , Neila-Montero Marta , Palacin-Martinez Cristina , Montes-Garrido Rafael , Boixo Juan Carlos , de Paz Paulino , Anel Luis
Published: January 2021

The optimization of sperm cryopreservation protocols in ram is a feasible tool to reinforce artificial insemination technologies considering the desirable application of sperm by vaginal/cervical or transcervical deposition. Cryopreservation provokes different types of damage on spermatozoa and many of these detrimental effects are triggered by redox deregulation. For this reason, the antioxidant supplementation in sperm cryopreservation protocols to decrease reactive oxygen species (ROS) levels and to equilibrate redox status has been widely employed in different species. Despite this, more fertility trials are necessary to provide the definitive tool to ensure the antioxidant effectiveness on sperm quality. For this reason, in this work, we performed a multiparametric analysis of some previously tested antioxidants (crocin, GSH and Trolox) on ram sperm cryopreservation from field trials to sperm quality analyses focused on new strategies to measure redox balance. Attending to fertility trial, Trolox supplementation registered an improvement concerning to fertility (when we considered high fertility males) and multiple lambing frequency and other complementary and descriptive data related to lambing performance such as prolificacy and fecundity. This positive effect was more evident in multiple lambing frequency when we considered low fertility males than in global male analysis. In vitro analyses of sperm quality confirmed in vivo trials registering a positive effect on sperm viability and redox balance. In this study, we provided the definitive evidence that the role of trolox on redox balance maintenance has a direct effect on fertility parameters, such as prolificacy. The effectiveness of antioxidant treatments was tested, for the first time in ovine species, using an integrative and multiparametric approach combining in vivo and in vitro analyses and novel approaches, such as RedoxSYS. These types of strategies should be applied to improve sperm conservation methods and optimize AI technologies upgrading the correlation between in vitro and in vivo analyses.
Welfare Issues on Israeli Dairy Farms: Attitudes and Awareness of Farm Workers and Veterinary Practitioners
Authors: Weyl-Feinstein Sarah , Lavon Yaniv , Yaffa Kan Noa , Weiss-Bakal Meytal , Shmueli Ayelet , Ben-Dov Dganit , Malka Hillel , Faktor Gilad , Honig Hen
Published: January 2021

Attitudes toward practical dairy cow welfare issues were evaluated based on a questionnaire answered by 500 dairy farm workers and 27 veterinary practitioners. Primarily, the effect of demographic characteristics on attitudes toward cattle welfare was tested. Professionally, five themes were identified: effect of welfare awareness on productivity, knowledge of cattle’s senses and social structure, effects of man–animal interactions on milk yield, pain perception and prevention, and knowledge transfer from veterinary practitioners to farm workers. Farms with a higher welfare awareness score also had higher annual milk yield, with an annual mean difference of 1000 L of milk per cow between farms with higher and lower awareness scores. Veterinary practitioners showed high awareness of cows’ social structure, senses, and pain perception. Farm workers were aware of the influence of man–animal interactions during milking and stress effects on milk yield, and the possible effect of man’s behavior on heifers and cows. Practitioners and farm workers had different views regarding pain perception, mostly involving mutilation procedures. All veterinary practitioners advocated the use of pain alleviation in painful procedures, but only some of them instructed the farm workers to administer it. The survey results emphasize the variation in welfare knowledge and practical applications across farms, and the interest of both the animals and their managers to improve applied knowledge of best practice.
Relationship between Range Use and Fearfulness in Free-Range Hens from Different Rearing Enrichments
Authors: Bari Md Saiful , Allen Simon S. , Mesken Jarrod , Cohen-Barnhouse Andrew M. , Campbell Dana L. M.
Published: January 2021

Inconsistency between the environments of indoor pullet rearing and adult outdoor housing may increase the fearfulness in free-range hens. Rearing enrichments and/or range use may reduce adult fearfulness. Hy-Line Brown® chicks (n = 1700) were reared inside across 16 weeks with three enrichment treatments: weekly changing novel objects, custom-designed perching/navigation structures, or no additional enrichments. Pullets were transferred to a free-range system at 16 weeks of age, with range access provided from 25 weeks. At 62 weeks, 135 hens were selected from the three rearing treatments and two ranging groups (indoor: no ranging and outdoor: daily ranging) based on individual radio-frequency identification tracking. Individual behavioural tests of tonic immobility, emergence, open field, and novel object (pen level) were carried out on hens. Spectrograms of vocalisations were analysed for the open field test, as well as computer vision tracking of hen locomotion. The results showed few effects of rearing treatments, with outdoor rangers less fearful than indoor hens. The latency to step in the open field test negatively correlated with hen feather coverage. These results show that individual variation in ranging behaviours is present even following rearing enrichment treatments, and subsequent range use might be an indicator of bird fearfulness.
Management and Feeding Strategies in Early Life to Increase Piglet Performance and Welfare around Weaning: A Review
Authors: Blavi Laia , Solà-Oriol David , Llonch Pol , López-Vergé Sergi , Martín-Orúe Susana María , Pérez José Francisco
Published: January 2021

The performance of piglets in nurseries may vary depending on body weight, age at weaning, management, and pathogenic load in the pig facilities. The early events in a pig’s life are very important and may have long lasting consequences, since growth lag involves a significant cost to the system due to reduced market weights and increased barn occupancy. The present review evidences that there are several strategies that can be used to improve the performance and welfare of pigs at weaning. A complex set of early management and dietary strategies have been explored in sows and suckling piglets for achieving optimum and efficient growth of piglets after weaning. The management strategies studied to improve development and animal welfare include: (1) improving sow housing during gestation, (2) reducing pain during farrowing, (3) facilitating an early and sufficient colostrum intake, (4) promoting an early social interaction between litters, and (5) providing complementary feed during lactation. Dietary strategies for sows and suckling piglets aim to: (1) enhance fetal growth (arginine, folate, betaine, vitamin B12, carnitine, chromium, and zinc), (2) increase colostrum and milk production (DL-methionine, DL-2-hydroxy-4-methylthiobutanoic acid, arginine, L-carnitine, tryptophan, valine, vitamin E, and phytogenic actives), (3) modulate sows’ oxidative and inflammation status (polyunsaturated fatty acids, vitamin E, selenium, phytogenic actives, and spray dried plasma), (4) allow early microbial colonization (probiotics), or (5) supply conditionally essential nutrients (nucleotides, glutamate, glutamine, threonine, and tryptophan).
Developing a Simulated Online Model That Integrates GNSS, Accelerometer and Weather Data to Detect Parturition Events in Grazing Sheep: A Machine Learning Approach
Authors: Fogarty Eloise S. , Swain David L. , Cronin Greg M. , Moraes Luis E. , Bailey Derek W. , Trotter Mark
Published: January 2021

In the current study, a simulated online parturition detection model is developed and reported. Using a machine learning (ML)-based approach, the model incorporates data from Global Navigation Satellite System (GNSS) tracking collars, accelerometer ear tags and local weather data, with the aim of detecting parturition events in pasture-based sheep. The specific objectives were two-fold: (i) determine which sensor systems and features provide the most useful information for lambing detection; (ii) evaluate how these data might be integrated using ML classification to alert to a parturition event as it occurs. Two independent field trials were conducted during the 2017 and 2018 lambing seasons in New Zealand, with the data from each used for ML training and independent validation, respectively. Based on objective (i), four features were identified as exerting the greatest importance for lambing detection: mean distance to peers (MDP), MDP compared to the flock mean (MDP.Mean), closest peer (CP) and posture change (PC). Using these four features, the final ML was able to detect 27% and 55% of lambing events within ±3 h of birth with no prior false positives. If the model sensitivity was manipulated such that earlier false positives were permissible, this detection increased to 91% and 82% depending on the requirement for a single alert, or two consecutive alerts occurring. To identify the potential causes of model failure, the data of three animals were investigated further. Lambing detection appeared to rely on increased social isolation behaviour in addition to increased PC behaviour. The results of the study support the use of integrated sensor data for ML-based detection of parturition events in grazing sheep. This is the first known application of ML classification for the detection of lambing in pasture-based sheep. Application of this knowledge could have significant impacts on the ability to remotely monitor animals in commercial situations, with a logical extension of the information for remote monitoring of animal welfare.
Detection and Characterization of Viral Pathogens Associated with Reproductive Failure in Wild Boars in Central Italy
Authors: Pacini Maria Irene , Forzan Mario , Cilia Giovanni , Bertelloni Fabrizio , Fratini Filippo , Mazzei Maurizio
Published: January 2021

Wild boar and domestic swine share several pathogens, including viruses responsible for reproductive failures, representing an important sanitary and economic risk for the swine industry. Among them, suid herpesvirus 1 (SuHV-1), porcine circovirus 2 (PCV2) and porcine parvovirus 1 (PPV1) are widely diffused in the wild boar population. Unfortunately, little is known about their pathogenetic mechanisms and impact on the reproductive parameters of wild animals. This study aims to investigate the presence of viruses responsible for reproductive failure in pregnant wild boar sows and their foetuses. The investigation was conducted on 46 pregnant wild boar and their foetuses by molecular analysis; a phylogenetic study was performed on the positive samples. All of the investigated pathogens were identified in sows, while only herpesvirus and circovirus were detected in the tissues of their foetuses. Phylogenetic analysis revealed that the viral sequences obtained from the positive wild boars were closely related to those previously identified in domestic swine belonging to the same study areas. The results suggest that SuHV-1 and PCV2 can infect wild boar foetuses, with a possible impact on wild boar reproductive performance. Moreover, our data highlight the importance of continuous monitoring of swine pathogens circulating in wild environments, so as to carry out adequate sanitary actions.
Acknowledgment to Reviewers of Antioxidants in 2020
Authors:   Antioxidants Editorial Office
Published: January 2021

Peer review is the driving force of journal development, and reviewers are gatekeepers who ensure that Antioxidants maintains its standards for the high quality of its published papers [...]
Novel and Converging Ways of NOX2 and SOD3 in Trafficking and Redox Signaling in Macrophages
Authors: Petersen Steen Vang , Poulsen Nanna Bach , Linneberg Matthiesen Cecilie , Vilhardt Frederik
Published: January 2021

Macrophages and related tissue macrophage populations use the classical NADPH oxidase (NOX2) for the regulated production of superoxide and derived oxidants for pathogen combat and redox signaling. With an emphasis on macrophages, we discuss how sorting into secretory storage vesicles, agonist-responsive membrane trafficking, and segregation into sphingolipid and cholesterol-enriched microdomains (lipid rafts) determine the subcellular distribution and spatial organization of NOX2 and superoxide dismutase-3 (SOD3). We discuss how inflammatory activation of macrophages, in part through small GTPase Rab27A/B regulation of the secretory compartments, mediates the coalescence of these two proteins on the cell surface to deliver a focalized hydrogen peroxide output. In interplay with membrane-embedded oxidant transporters and redox sensitive target proteins, this arrangement allows for the autocrine and paracrine signaling, which govern macrophage activation states and transcriptional programs. By discussing examples of autocrine and paracrine redox signaling, we highlight why formation of spatiotemporal microenvironments where produced superoxide is rapidly converted to hydrogen peroxide and conveyed immediately to reach redox targets in proximal vicinity is required for efficient redox signaling. Finally, we discuss the recent discovery of macrophage-derived exosomes as vehicles of NOX2 holoenzyme export to other cells.
TQ-6, a Novel Ruthenium Derivative Compound, Possesses Potent Free Radical Scavenging Activity in Macrophages and Rats
Authors: Hung Kao-Wei , Chang Chao-Chien , Jayakumar Thanasekaran , Velusamy Marappan , Hsia Chih-Wei , Trang Nguyen Thi Thu , Chou Duen-Suey , Hsieh Cheng-Ying , Hsia Chih-Hsuan
Published: January 2021

Reactive oxygen species (ROS) play major role in inducing inflammation and related diseases. Our previous studies have revealed that the ruthenium (II)-compound, [Ru(η6-cymene)2-(1H-benzoimidazol-2-yl)-quinoline Cl]BF4 (TQ-6), inhibits hydroxyl radical (OH•) formation in human platelets. TQ-6 also have protective effect against induced inflammation in macrophages and hepatic injury in mice through NF-κB signaling. However, the free radical formation inhibitory mechanism of TQ-6 in macrophages is unclear. Therefore, this study detected the antioxidative ability of TQ-6 in both a cell-free system and in LPS-induced macrophages through electron spin resonance (ESR) spectrometry. TQ-6 reduced 1,1-diphenyl-2-picrylhydrazyl (DPPH), galvinoxyl, and superoxide radicals in a cell-free system and OH• formation in macrophages. Additionally, TQ-6 activated the nuclear factor erythroid 2-related factor 2 (Nrf2) signaling pathway and upregulated the antioxidant protein heme oxygenase-1 (HO-1) to elevate anti-inflammatory activity in LPS-induced macrophage cells and inhibited carrageenan-induced paw edema in a rat model. Therefore, TQ-6 may prevent oxidative stress and also act as an effective therapeutic agent for the treatment of oxidant-related diseases.
Model-Based Fiber Diameter Determination Approach to Fine Particulate Matter Fraction (PM2.5) Removal in HVAC Systems
Authors: Drąg Marlena
Published: January 2021

Particulate Matter (PM) is a general term to classify air pollutants consisting of airborne particles. The particles vary in composition and size, and the sizes of particles range from 2.5 µm (PM2.5) to 10 µm (PM10). Anthropogenic activity (e.g., industrial processes or fuel/waste combustion) stands as the main emission source of PM. Due to the fact that indoor PM penetrates from the outside to indoor air, Heating, Ventilation, and Air-Conditioning (HVAC) filtration systems may play a significant role in decreasing air pollution indoors. The section of the respiratory tract affected by particulate matter depends on the particle size. The smaller the fraction, the more deeply it can enter into lungs and bronchi, causing a series of health problems. Conventional electret air filters applied in HVAC systems are not able to efficiently remove PM2.5 (e.g., huge gaps between thick fibers and unintentional elimination of electrostatic effects). The electrospinning process allows for the production of fibers of diverse diameters, including ultrathin yarns. The following work presents the axial length scale χχ  estimation method for the given conditions and experimental results. According to this approach, it is possible to find out what parameters should be used to produce materials at certain fiber diameters and to capture fine particulate matter fractions (PM2.5). This research refers to poly(acrylonitrile) (PAN) fibers. The most important advantages, limitations, and challenges of the presented methodology are detected and discussed in this work.
Effects of a Hydraulic Series Connection and Flow Direction on Electricity Generation in a Stack Connected with Different Volume MFCs
Authors: Yu Jaecheul
Published: January 2021

Three microbial fuel cells (MFCs) with different volumes (S-, M-, and L-MFCs) were operated at individual flow (phase I) and serially connected flow modes (phase II for forward flow and phase III for reverse flow) at the same flow rate. The three MFCs showed different voltages and power generation according to the hydraulic and electric connection modes. The M- and L-MFCs showed a similar voltage at hydraulic series-forward flow mode (phase II). The principal component analysis (PCA) and Pearson correlation showed that voltage generation and power density were affected by volume, hydraulic retention time (HRT), chemical oxygen demand (COD) loading rate, removed COD, and internal resistances. When they were connected electrically in series and parallel, the stack showed relatively lower voltage loss (28–30%) compared to the voltage losses of the other stacks (43–94%). These results suggest an easy way to connect MFCs with different volumes can be a new option to avoid voltage reversal and minimize energy loss.
Classification of Objects by Shape Applied to Amber Gemstone Classification
Authors: Ostreika Armantas , Pivoras Marius , Misevičius Alfonsas , Skersys Tomas , Paulauskas Linas
Published: January 2021

To properly and quickly evaluate an object’s shape, in a manner that is suitable for real-time applications, a set of parameters has been created and the shape parametric description (SPD) has been elaborated. This solution is focused on the classification of amber gemstones according to shape. To improve the results obtained by SPD, the most popular machine learning classification algorithms were applied and tested. The proposed method (i.e., SPD) achieved the fastest classification, requiring the least computational resources, while providing an accuracy of approximately 80%. The best results were achieved when the SPD parameters were used in a feedforward neural network (FFNN), and an accuracy of 91.5% was obtained, while the time required for the computations remained in a range that is acceptable for real-time applications.
An Efficient Palette Generation Method for Color Image Quantization
Authors: Huang Shu-Chien
Published: January 2021

This article describes an efficient method to generate a color palette for color image quantization. The method consists of two stages. In the first stage, the initial palette is generated. Initially, the color palette is an empty set. First, the N colors are generated according to the data distribution of the input image in the RGB (Red, Green, Blue) color space. Then, one color is selected from the N colors and this color is added to the initial palette, and the step is repeated until the color number of the initial palette is equal to K. In the second stage, the quantized image is generated using the fast K-means algorithm. There are many sampling rates used in this study. For each sampled pixel, a fast searching method is employed to efficiently determine the closest color in the palette. Experimental results show that the high-quality quantized images can be generated by the proposed method. When the sampling rate equals 0.125, the computation time of the proposed method is less than 0.3 s for all cases.
Information Technologies in Complex Socio-Technical Systems Based on Functional Variability: A Case Study on HVAC Maintenance Work Orders
Authors: de Souza Ivenio , Rosa Ana , Vidal Mario , Najjar Mohammad , Hammad Ahmed , Haddad Assed
Published: January 2021

Information technology (IT) systems are known to promote improvements in quality and productivity of the work environments of complex and adaptive socio-technical systems that span hardware, community and software aspects. Systems development lies in eliciting and specifying requirements. However, current requirements of elicitation techniques are limited to correctly understanding the complexity involved in socio-technical systems. Therefore, approaches based on Resilience Engineering can provide concepts and methods for a better understanding of socio-technical systems’ functioning. This study aims to increase the application of the Functional Resonance Analysis Method (FRAM) in the requirements elicitation process. Specifically, understanding variability and its role in enhancing the requirements elicitation and specification process for the design/redesign of IT systems in complex socio-technical systems deployed in building maintenance is the main goal. This study proposes the merging of human factors and ergonomics (HFE) and Resilience Engineering concepts with Software Engineering. A case study was performed with workers to produce requirements specifications for work order issuing activity. This case study indicates the usefulness of the proposed approach for the specification of functional requirements to redesign the IT system examined. FRAM enables inferences to be made from hidden or fuzzy situations that are often not expressed by system users or are not detected by the system designer.
Influence of Biomechanical Parameters on Performance in Elite Triathletes along 29 Weeks of Training
Authors: Olaya-Cuartero Javier , Cejuela Roberto
Published: January 2021

The purpose of the study was to assess how the modification of biomechanical parameters influences the performance of elite triathletes. Four elite international triathletes participated in this study. The anthropometric method ISAK was used to estimate the triathlete’s body composition. For the physiological and biomechanical parameters, a running test (RT) was performed on an outdoor track, with the participants wearing the Stryd Summit Footpod (Stryd, Boulder, CO, USA). The pre-test took place in the last week of an adaptation mesocycle; then, after 29 weeks of training, the triathletes performed the post-test. A within-subject repeated measures design was used to assess changes in the anthropometric, physiological and biomechanical parameters. Pearson correlations (r) were applied to determine the relationship between the performance at different intensities (VT1, VT2 and MAS) and the biomechanical parameters. Concerning the anthropometric characteristics, significant differences were found in the summation (Σ) of skinfold (8.1 cm); as a consequence, the % fat mass was reduced (1.2%). Significant differences were found in the physiological values (VO2 and % VO2max), speed and biomechanical parameters, such as step length normalized, to the specific physiological intensity of the short-distance triathlon, the VT2. Therefore, performance improvement in the running segment could not only be explained by physiological changes, but also by biomechanical parameters changes.
Predicting Implicit User Preferences with Multimodal Feature Fusion for Similar User Recommendation in Social Media
Authors: Wang Jenq-Haur , Wu Yen-Tsang , Wang Long
Published: January 2021

In social networks, users can easily share information and express their opinions. Given the huge amount of data posted by many users, it is difficult to search for relevant information. In addition to individual posts, it would be useful if we can recommend groups of people with similar interests. Past studies on user preference learning focused on single-modal features such as review contents or demographic information of users. However, such information is usually not easy to obtain in most social media without explicit user feedback. In this paper, we propose a multimodal feature fusion approach to implicit user preference prediction which combines text and image features from user posts for recommending similar users in social media. First, we use the convolutional neural network (CNN) and TextCNN models to extract image and text features, respectively. Then, these features are combined using early and late fusion methods as a representation of user preferences. Lastly, a list of users with the most similar preferences are recommended. The experimental results on real-world Instagram data show that the best performance can be achieved when we apply late fusion of individual classification results for images and texts, with the best average top-k accuracy of 0.491. This validates the effectiveness of utilizing deep learning methods for fusing multimodal features to represent social user preferences. Further investigation is needed to verify the performance in different types of social media.
Rail Diagnostics Based on Ultrasonic Guided Waves: An Overview
Authors: Bombarda Davide , Vitetta Giorgio Matteo , Ferrante Giovanni
Published: January 2021

Rail tracks undergo massive stresses that can affect their structural integrity and produce rail breakage. The last phenomenon represents a serious concern for railway management authorities, since it may cause derailments and, consequently, losses of rolling stock material and lives. Therefore, the activities of track maintenance and inspection are of paramount importance. In recent years, the use of various technologies for monitoring rails and the detection of their defects has been investigated; however, despite the important progresses in this field, substantial research efforts are still required to achieve higher scanning speeds and improve the reliability of diagnostic procedures. It is expected that, in the near future, an important role in track maintenance and inspection will be played by the ultrasonic guided wave technology. In this manuscript, its use in rail track monitoring is investigated in detail; moreover, both of the main strategies investigated in the technical literature are taken into consideration. The first strategy consists of the installation of the monitoring instrumentation on board a moving test vehicle that scans the track below while running. The second strategy, instead, is based on distributing the instrumentation throughout the entire rail network, so that continuous monitoring in quasi-real-time can be obtained. In our analysis of the proposed solutions, the prototypes and the employed methods are described.
Time Domain Spherical Harmonic Processing with Open Spherical Microphones Recording
Authors: Sun Huiyuan , Abhayapala Thushara D. , Samarasinghe Prasanga N.
Published: January 2021

Spherical harmonic analysis has been a widely used approach for spatial audio processing in recent years. Among all applications that benefit from spatial processing, spatial Active Noise Control (ANC) remains unique with its requirement for open spherical microphone arrays to record the residual sound field throughout the continuous region. Ideally, a low delay spherical harmonic recording algorithm for open spherical microphone arrays is desired for real-time spatial ANC systems. Currently, frequency domain algorithms for spherical harmonic decomposition of microphone array recordings are applied in a spatial ANC system. However, a Short Time Fourier Transform is required, which introduces undesirable system delay for ANC systems. In this paper, we develop a time domain spherical harmonic decomposition algorithm for the application of spatial audio recording mainly with benefit to ANC with an open spherical microphone array. Microphone signals are processed by a series of pre-designed finite impulse response (FIR) filters to obtain a set of time domain spherical harmonic coefficients. The time domain coefficients contain the continuous spatial information of the residual sound field. We corroborate the time domain algorithm with a numerical simulation of a fourth order system, and show the proposed method to have lower delay than existing approaches.
Adequacy of Near Real-Time Satellite Precipitation Products in Driving Flood Discharge Simulation in the Fuji River Basin, Japan
Authors: Zhou Li , Rasmy Mohamed , Takeuchi Kuniyoshi , Koike Toshio , Selvarajah Hemakanth , Ao Tianqi
Published: January 2021

Flood management is an important topic worldwide. Precipitation is the most crucial factor in reducing flood-related risks and damages. However, its adequate quality and sufficient quantity are not met in many parts of the world. Currently, near real-time satellite precipitation products (NRT SPPs) have great potential to supplement the gauge rainfall. However, NRT SPPs have several biases that require corrections before application. As a result, this study investigated two statistical bias correction methods with different parameters for the NRT SPPs and evaluated the adequacy of its application in the Fuji River basin. We employed Global Satellite Mapping of Precipitation (GSMaP)-NRT and Integrated Multi-satellitE Retrievals for GPM (IMERG)-Early for NRT SPPs as well as BTOP model (Block-wise use of the TOPMODEL (Topographic-based hydrologic model)) for flood runoff simulation. The results showed that the corrected SPPs by the 10-day ratio based bias correction method are consistent with the gauge data at the watershed scale. Compared with the original SPPs, the corrected SPPs improved the flood discharge simulation considerably. GSMaP-NRT and IMERG-Early have the potential for hourly river-flow simulation on a basin or large scale after bias correction. These findings can provide references for the applications of NRT SPPs in other basins for flood monitoring and early warning applications. It is necessary to investigate the impact of number of ground observation and their distribution patterns on bias correction and hydrological simulation efficiency, which is the future direction of this study.
On the Use of Parsing for Named Entity Recognition
Authors: Alonso Miguel A. , Gómez-Rodríguez Carlos , Vilares Jesús
Published: January 2021

Parsing is a core natural language processing technique that can be used to obtain the structure underlying sentences in human languages. Named entity recognition (NER) is the task of identifying the entities that appear in a text. NER is a challenging natural language processing task that is essential to extract knowledge from texts in multiple domains, ranging from financial to medical. It is intuitive that the structure of a text can be helpful to determine whether or not a certain portion of it is an entity and if so, to establish its concrete limits. However, parsing has been a relatively little-used technique in NER systems, since most of them have chosen to consider shallow approaches to deal with text. In this work, we study the characteristics of NER, a task that is far from being solved despite its long history; we analyze the latest advances in parsing that make its use advisable in NER settings; we review the different approaches to NER that make use of syntactic information; and we propose a new way of using parsing in NER based on casting parsing itself as a sequence labeling task.