bluuebunny/crossref_metadata_2025 huggingface dataset:
“Don’t Bring Me a Dog…I’ll Just Keep It”: Understanding Unplanned Dog Acquisitions Amongst a Sample of Dog Owners Attending Canine Health and Welfare Community Events in the United Kingdom
Authors: Holland Katrina E. , Mead Rebecca , Casey Rachel A. , Upjohn Melissa M. , Christley Robert M.
Published: February 2021

Understanding the factors that result in people becoming dog owners is key to developing messaging around responsible acquisition and providing appropriate support for prospective owners to ensure a strong dog–owner bond and optimise dog welfare. This qualitative study investigated factors that influence pet dog acquisition. Semi-structured interviews were conducted with 142 sets of dog owners/caretakers at 23 Dogs Trust community events. Interviews focused on the motivations and influences that impacted how people acquired their dogs. Transcribed interviews and notes were thematically analysed. Two acquisition types were reported, that each accounted for half of our interviewees’ experiences: planned and unplanned. Whilst planned acquisitions involved an intentional search for a dog, unplanned acquisitions occurred following an unexpected and unsought opportunity to acquire one. Unplanned acquisitions frequently involved a participant’s family or friends, people happening upon a dog in need, or dogs received as gifts. Motivations for deciding to take the dog included emotional attachments and a desire to help a vulnerable animal. Many reported making the decision to acquire the dog without hesitation and without conducting any pre-acquisition research. These findings present valuable insights for designers of interventions promoting responsible acquisition and ownership, because there is minimal opportunity to deliver messaging with these unplanned acquisitions. Additionally, these findings may guide future research to develop more complete understandings of the acquisition process. Further studies are required to understand the prevalence of unplanned acquisitions.
Friend or Foe? Impacts of Dietary Xylans, Xylooligosaccharides, and Xylanases on Intestinal Health and Growth Performance of Monogastric Animals
Authors: Baker Jonathan T. , Duarte Marcos E. , Holanda Debora M. , Kim Sung Woo
Published: February 2021

This paper discusses the structural difference and role of xylan, procedures involved in the production of xylooligosaccharides (XOS), and their implementation into animal feeds. Xylan is non-starch polysaccharides that share a β-(1-4)-linked xylopyranose backbone as a common feature. Due to the myriad of residues that can be substituted on the polymers within the xylan family, more anti-nutritional factors are associated with certain types of xylan than others. XOS are sugar oligomers extracted from xylan-containing lignocellulosic materials, such as crop residues, wood, and herbaceous biomass, that possess prebiotic effects. XOS can also be produced in the intestine of monogastric animals to some extent when exogenous enzymes, such as xylanase, are added to the feed. Xylanase supplementation is a common practice within both swine and poultry production to reduce intestinal viscosity and improve digestive utilization of nutrients. The efficacy of xylanase supplementation varies widely due a number of factors, one of which being the presence of xylanase inhibitors present in common feedstuffs. The use of prebiotics in animal feeding is gaining popularity as producers look to accelerate growth rate, enhance intestinal health, and improve other production parameters in an attempt to provide a safe and sustainable food product. Available research on the impact of xylan, XOS, as well as xylanase on the growth and health of swine and poultry, is also summarized. The response to xylanase supplementation in swine and poultry feeds is highly variable and whether the benefits are a result of nutrient release from NSP, reduction in digesta viscosity, production of short chain xylooligosaccharides or a combination of these is still in question. XOS supplementation seems to benefit both swine and poultry at various stages of production, as well as varying levels of XOS purity and degree of polymerization; however, further research is needed to elucidate the ideal dosage, purity, and degree of polymerization needed to confer benefits on intestinal health and performance in each respective species.
A Cow–Calf Farming System Fully Adapted to Elevation and Harsh Conditions in Andorra (Europe)
Authors: Armengol Ramon , Bassols Marta , Fraile Lorenzo
Published: February 2021

The use of natural resources is an important topic to optimize the efficiency of cattle production. The purpose of this work is to describe the project of the Bruna d’Andorra; a local cow breed under an extensive cow–calf system in Andorra (Europe), as an example of local farming and marketing of its meat products in an area with adverse environmental conditions. This breed is located in Andorra, a microstate that consists predominantly of rugged mountains and harsh weather conditions. The cow–calf Bruna d’Andorra extensive system is thoroughly described and productive and reproductive performance, compiled over 21 years (2000–2020), has been analyzed by years with the Chi-square test or ANOVA to compare proportions or means, respectively, and regression analysis was used to decipher evolution across years. The results show a population with a census large and stable enough to avoid inbreeding. Moreover, a sustained improvement of the productive performance and maternal fitness has been observed along the studied period for Bruna d’Andorra. The work concludes that local breeds can achieve sustainable animal production, especially when farmers, public administration and commercial circuits in the area agree to cooperate on such projects. The study also concludes that the Bruna d’Andorra cow breed can still improve in meat and reproductive performance.
Nocturnal One-Hour Lighting Stimulates Gonadal Development and Lowers Fat Deposition in Male Mule Ducks
Authors: Ju Tz-Chuen , Tsao Kai-Chien , Liu Tzu-Yu , Yang Shyi-Kuen
Published: February 2021

In this study, the effects of a nocturnal light pulse on body weight, organ mass, gonadal function, and plasma levels of metabolites were determined in male mule ducks. In total, 32 15-week-old mule ducks were randomly allocated to either Group C (control group) or L+ (lighting group). Group C was exposed to the natural photoperiod, whereas Group L+ was provided with a 1-h lighting over 20:00–21:00 every day, in addition to the natural photoperiod. At the end of the 42-day experiment, Group L+ had significantly lower relative weights (% of live weight) of the digestive tract and abdominal fat and higher relative weights of the breast meat and testes than Group C. Moreover, Group L+ had significantly higher plasma testosterone and lower plasma glucose levels. However, no between-group differences were observed in the triacylglycerol and uric acid levels. Histological examination demonstrated that the seminiferous tubule diameter was larger in Group L+ than in Group C. Moreover, the meiosis stage in spermatogenesis had begun in Group L+ but not in Group C. In conclusion, the supplemented 1-h lighting at 20:00 stimulated gonadal development and function and reduced fat deposition.
Identification of Individual Zebrafish (Danio rerio): A Refined Protocol for VIE Tagging Whilst Considering Animal Welfare and the Principles of the 3Rs
Authors: Rácz Anita , Allan Brooke , Dwyer Toni , Thambithurai Davide , Crespel Amélie , Killen Shaun S.
Published: February 2021

In aquatic ecology, studies have commonly employed a tagging technique known as visible implant elastomer (VIE). This method has not been widely adopted by the zebrafish research community and also lacks refinement with regard to animal welfare. The current paper introduces a new VIE tagging protocol, with the aim of improving existing tagging techniques by placing particular emphasis on the Three Rs. To improve animal welfare and fish survival, we added the use of an analgesic compound (lidocaine) through the marking procedure, followed by after-treatment with antiseptics (melaleuca, aloe vera, and PVP-I as active ingredients) to improve tissue regeneration and healing. The newly improved protocol has been quantitatively evaluated on different populations and age groups of zebrafish. This study will be useful to the scientific zebrafish community and to the wider field including biologist and aquarists, especially in consideration of animal welfare, where tagging techniques are considered as a potential noxious stimulus for fish.
Effects of Rumen-Protected Niacin on Dry Matter Intake, Milk Production, Apparent Total Tract Digestibility, and Faecal Bacterial Community in Multiparous Holstein Dairy Cow during the Postpartum Period
Authors: Gaowa Naren , Zhang Xiaoming , Li Huanxu , Wang Yajing , Zhang Jun , Hao Yangyi , Cao Zhijun , Li Shengli
Published: February 2021

Extensive studies about rumen-protected niacin (RPN) supplementation on dairy cows in early-lactation have been done, but the effects of RPN on changes in dry matter intake (DMI), milk production, feed digestibility, and fecal bacterial community were conflicting. The aim of this study was to investigate them affected by RPN in postpartum cows. Multiparous Holstein dairy cows (n = 12, parity = 3.5 ± 0.5, body weights = 740 ± 28 kg) were divided into two groups supplemented with either 0 (CON) or 20 g/d RPN (RPN). Our results showed that RPN supplementation increased DMI and milk production of cows during the first three weeks after calving (p < 0.05). The concentrations of neuropeptide Y and orexin A were significantly higher in RPN group than that in the CON group during postpartum period (p < 0.05). The apparent total-tract digestibility of nutrients was similar between the CON and RPN groups at 2 weeks after calving (p > 0.05). The 16S rRNA gene sequencing analysis showed that RPN had no impact on the alpha and beta diversity, although 4 genera were changed in cow feces at 14 days after calving. Overall, 20 g/d RPN added to the diet could improve DMI and milk yield up to two weeks after calving with little influence on feed digestibility.
blaNDM and mcr-1 to mcr-5 Gene Distribution Characteristics in Gut Specimens from Different Regions of China
Authors: Lv Dongyue , Duan Ran , Fan Rong , Mu Hui , Liang Junrong , Xiao Meng , He Zhaokai , Qin Shuai , Yang Jinchuan , Jing Huaiqi , Wang Zhaoguo , Wang Xin
Published: February 2021

Antibiotic resistance has become a global public health concern. To determine the distribution characteristics of mcr and blaNDM in China, gene screening was conducted directly from gut specimens sourced from livestock and poultry, poultry environments, human diarrhea patients, and wild animals from 10 regions, between 2010–2020. The positive rate was 5.09% (356/6991) for mcr and 0.41% (29/6991) for blaNDM, as detected in gut specimens from seven regions, throughout 2010 to 2019, but not detected in 2020. The detection rate of mcr showed significant differences among various sources: livestock and poultry (14.81%) > diarrhea patients (1.43%) > wild animals (0.36%). The detection rate of blaNDM was also higher in livestock and poultry (0.88%) than in diarrhea patients (0.17%), and this was undetected in wildlife. This is consistent with the relatively high detection rate of multiple mcr genotypes in livestock and poultry. All instances of coexistence of the mcr-1 and blaNDM genes, as well as coexistence of mcr genotypes within single specimens, and most new mcr subtypes came from livestock, and poultry environments. Our study indicates that the emergence of mcr and blaNDM genes in China is closely related to the selective pressure of carbapenem and polymyxin. The gene-based strategy is proposed to identify more resistance genes of concern, possibly providing guidance for the prevention and control of antimicrobial resistance dissemination.
Editorial for the Special Issue: “Honey Bee Products as an Alternative or Complement to Classical Antibiotics”
Authors: Szweda Piotr
Published: February 2021

Based on World Health Organization reports, the resistance of bacteria to well-known antibiotics is becoming a major global health challenge [...]
Static Osteogenesis versus Dynamic Osteogenesis: A Comparison between Two Different Types of Bone Formation
Authors: Ferretti Marzia , Palumbo Carla
Published: February 2021

In contrary to what has traditionally been believed, bone formation can occur through two different types of osteogenesis: static (SO) and dynamic (DO) osteogenesis, which are thus named because the former is characterized by pluristratified cords of unexpectedly stationary osteoblasts which differentiate at a fairly constant distance from the blood capillaries and transform into osteocytes without moving from the onset site, while the latter is distinguished by the well-known typical monostratified laminae of movable osteoblasts. The two types of osteogenesis differ in multiple aspects from both structural and functional viewpoints. Besides osteoblast arrangement, polarization, and motion, SO and DO differ in terms of time of occurrence (first SO and later DO), conditioning factors to which they are sensitive (endothelial-derived cytokines or mechanical loading, respectively), distribution of osteocytes to which they give rise (haphazard or ordered in planes, respectively), the collagen texture resulting from the different deposition types (woven or lamellar, respectively), the mechanical properties of the bone they form (poor for SO due to the high cellularity and woven texture and good for DO since osteocytes are located in more suitable conditions to perceive loading), and finally the functions of each, i.e., SO provides a preliminary rigid scaffold on which DO can take place, while DO produces bone tissue according to mechanical/metabolic needs.
A Model-Based SHM Strategy for Gears—Development of a Hybrid FEM-Analytical Approach to Investigate the Effects of Surface Fatigue on the Vibrational Spectra of a Back-to-Back Test Rig
Authors: Concli Franco , Pierri Ludovico , Sbarufatti Claudio
Published: February 2021

Transmissions are extensively employed in mechanical gearboxes when power conversion is required. Being able to provide specific maintenance is a crucial factor for both economics and reliability. However, although periodic transmission maintenance increases the systems’ longevity, it cannot prevent or predict sporadic major failures. In this context, structural health monitoring (SHM) represents a possible solution. Identifying variations of a specific measurable signal and correlating them with the type of damage or its location and severity may help assess the component condition and establish the need for maintenance operation. However, the collection of sufficient experimental examples for damage identification may be not convenient for big gearboxes, for which destructive experiments are too expensive, thus paving the way to model-based approaches, based on a numerical estimation of damage-related features. In this work, an SHM approach was developed based on signals from numerical simulations. To validate the approach with experimental measurements, a back-to-back test rig was used as a reference. Several types and severities of damages were simulated with an innovative hybrid analytical–numerical approach that allowed a significant reduction of the computational effort. The vibrational spectra that characterized the different damage conditions were processed through artificial neural networks (ANN) trained with numerical data and used to predict the presence, location, and severity of the damage.
Surface Modification of Glass Textile for the Reinforcement of a Cement-Based Composite: A Review
Authors: Bompadre Francesca , Donnini Jacopo
Published: February 2021

The mechanical properties of cement-based composites reinforced with glass textile are strongly affected by the low ability of the inorganic matrix to penetrate within the single filaments, and by the low durability of the fibers in an alkaline environment. Over the last decades, different studies have investigated the possibility to improve the mechanical properties and the durability of this class of composites by modifying the surface of the reinforcement, mainly using different types of organic or inorganic coatings. Although different solutions have been proposed, the feasibility of applying these techniques strictly depend on the final application of the composite. This review aims to give an overview of the different methods that have been proposed in the literature and to highlight advantages and drawbacks.
A Conceptual Blueprint for Making Neuromusculoskeletal Models Clinically Useful
Authors: Fregly Benjamin J.
Published: February 2021

The ultimate goal of most neuromusculoskeletal modeling research is to improve the treatment of movement impairments. However, even though neuromusculoskeletal models have become more realistic anatomically, physiologically, and neurologically over the past 25 years, they have yet to make a positive impact on the design of clinical treatments for movement impairments. Such impairments are caused by common conditions such as stroke, osteoarthritis, Parkinson’s disease, spinal cord injury, cerebral palsy, limb amputation, and even cancer. The lack of clinical impact is somewhat surprising given that comparable computational technology has transformed the design of airplanes, automobiles, and other commercial products over the same time period. This paper provides the author’s personal perspective for how neuromusculoskeletal models can become clinically useful. First, the paper motivates the potential value of neuromusculoskeletal models for clinical treatment design. Next, it highlights five challenges to achieving clinical utility and provides suggestions for how to overcome them. After that, it describes clinical, technical, collaboration, and practical needs that must be addressed for neuromusculoskeletal models to fulfill their clinical potential, along with recommendations for meeting them. Finally, it discusses how more complex modeling and experimental methods could enhance neuromusculoskeletal model fidelity, personalization, and utilization. The author hopes that these ideas will provide a conceptual blueprint that will help the neuromusculoskeletal modeling research community work toward clinical utility.
A Regularized Mixture of Linear Experts for Quality Prediction in Multimode and Multiphase Industrial Processes
Authors: Souza Francisco , Mendes Jérôme , Araújo Rui
Published: February 2021

This paper proposes the use of a regularized mixture of linear experts (MoLE) for predictive modeling in multimode-multiphase industrial processes. For this purpose, different regularized MoLE were evaluated, namely, through the elastic net (EN), Lasso, and ridge regression (RR) penalties. Their performances were compared when trained with different numbers of samples, and in comparison to other nonlinear predictive models. The models were evaluated on real multiphase polymerization process data. The Lasso penalty provided the best performance among all regularizers for MoLE, even when trained with a small number of samples.
Realization of Agile Methods in Established Processes: Challenges and Barriers
Authors: Lugnet Johan , Ericson Åsa , Larsson Andreas
Published: February 2021

This paper presents an explorative study and the results of 17 interviews with informants from different companies. Its purpose is to identify the challenges associated with implementing agile methods along with the established procedures for early design. The study exemplifies project leaders’ experiences and implementation efforts. As leaders of design projects, they have proposed the use of a new method that involves teams engaging in testing and evaluation, which aids in the understanding and introduction of change initiatives. The challenges that are identified are as follows: (1) a lack of approval not only from top managers but also from critical peers; (2) an unprepared organization that did not allow teamwork; and (3) a lack of specific company success factors to support new methods.
Assessment of Cold Ironing and LNG as Mitigation Tools of Short Sea Shipping Emissions in Port: A Spanish Case Study
Authors: Martínez-López Alba , Romero Alejandro , Orosa José A.
Published: February 2021

By the end of 2025 European ports are required to provide (Directive 2014/94/EU) facilities to ensure the Liquefied Natural Gas (LNG) use and on-shore electricity supply for vessels (Cold Ironing—CI). Even though this involves considerable port investment, many uncertainties about CI and LNG performance exist because their application depends on vessel operators’ willingness. Additionally, lag times for CI connection/disconnection along with methane emissions from LNG undermine their feasibility for Short Sea Shipping (SSS). Since, among the SSS aims are the reduction in berthing times and its effectiveness for-inter-islands’ traffic where, land electricity grids are frequently dependent on the fuel burning generation by penalizing the CI performance. This paper introduces a calculation method to evaluate the pollution savings in monetary terms by CI and LNG use in SSS. The method is applied to three European routes by testing the environmental performance of two fleets: feeder and Ro-Pax vessels. The results show that feeders reach higher environmental improvements by using port mitigation than Ro-Pax vessels. Additionally, the need for ensuring the sustainability of on-shore grids before the CI implementation was evinced, especially in insularity frameworks, where the environmental benefits from LNG use proved to be more effective.
Effects of Carbon Doping and Annealing Temperature on Magnetic MnAl Powders and MnAl Polymeric Composites
Authors: Thongsamrit Wannisa , Charoensuk Thanida , Saetang Panissa , Jantaratana Pongsakorn , Ruttanapun Chesta , Sirisathitkul Chitnarong
Published: February 2021

Process parameters leading to magnetic polymer composites, an essential ingredient in the additive manufacturing of rare-earth-free magnets, are investigated. The induction melting of manganese (Mn) and aluminum (Al), and subsequent annealing at 450, 500, or 550 °C for 20 min, gave rise to ferromagnetic τ–MnAl phase, as well as other phases. The nonmagnetic Al4C3 and oxide phases were then removed by the magnetic separation. Magnetic powders from the magnetic separation were incorporated in polylactic acid (PLA) matrix via a solution route. The remanent magnetization as high as 4.3 emu/g in the powder form was reduced to 2.3–2.6 emu/g in the composites. The reduction in coercivity was minimal, and the largest value of 814 Oe was obtained when the powder annealed at 450 °C was loaded in the composite. The phase composition and hence magnetic properties were even more sensitive to the carbon (C) doping. Interestingly, the addition of 3% C led to coercivity as high as 1445 Oe in MnAl–C powders without further annealing. The enhanced coercivity was attributed to the domain wall pinning by the AlMn3C phase, and magnetizations are likely increased by this phase.
Optimization of Reinforced Concrete Sections under Compression and Biaxial Bending by Using a Parallel Firefly Algorithm
Authors: Sánchez-Olivares Gregorio , Tomás Antonio
Published: February 2021

A simple formulation for the optimal design of reinforced concrete sections under compression and biaxial bending was established in a previous work by the authors. In that work, it was found that the formulation produced satisfactory results when used together with three algorithms that belong to the nature-inspired meta-heuristic algorithm group. However, despite the favorable results obtained, the necessary calculation times were extensive in all the cases. In order to solve this problem, the authors implemented a parallel calculation strategy in the algorithm that gave better results in the previous work. It was possible to verify, through two examples, that this strategy reduces calculation times as more processes are used in parallel, and that the adjustments made in the algorithm favor reaching designs close to the global optimum independently of the number of parallel processes adopted.
Current Filaments in Asymmetric Surface Dielectric Barrier Discharge
Authors: Piferi Cecilia , Barni Ruggero , Roman H. Eduardo , Riccardi Claudia
Published: February 2021

In this study, we examine the statistical properties of asymmetric surface dielectric barrier discharges (SDBD) produced by applying a periodic high voltage between two conducting displaced electrodes, located at the opposite sides of a flat dielectric panel. Here, the asymmetry refers to the fact that the lower electrode is fully covered with an insulating material, while the upper one, glued onto the dielectric surface, is otherwise left exposed to the air. Such a configuration allows the formation of a thin layer of plasma above the insulating surface. A single cycle signal consists of two well-separated half-cycle patterns, denoted as forward and backward strokes, corresponding to positive and negative voltages, respectively. They display a quite complex discharge pattern constituted by a sequence of individual peaks (bursts) of varying current and time duration. Specifically, we find that backward stroke bursts carry a positive mean charge Q≃0.3 nC and mean current I≃35 mA, with a mean duration τ≃15 ns, while forward stroke bursts have a negative mean charge Q≃−0.1 nC, a mean current I≃−20 mA, and a mean duration τ≃11 ns. The statistical analysis suggests that power injection can be tailored to produce the active agents in the plasma needed for a particular application. We also determined discharge spatial correlation patterns from measurements of the associated stimulated optical emission. The optical excitations occur as a result of the ionizing effect of the electromagnetic waves which ignite the discharge, followed by the electric current flow. In particular, we point out that one of the phases of the discharge is compatible with a cathode directed streamer phenomenon (backward stroke), while the mechanism acting for a forward stroke has a different structure.
Emulating Software-Defined Disaggregated Optical Networks in a Containerized Framework
Authors: Moreno-Muro Francisco-Javier , Garrich Miquel , Iglesias-Castreño Ignacio , Zahir Safaa , Pavón-Mariño Pablo
Published: February 2021

Telecom operators’ infrastructure is undergoing high pressure to keep the pace with the traffic demand generated by the societal need of remote communications, bandwidth-hungry applications, and the fulfilment of 5G requirements. Software-defined networking (SDN) entered in scene decoupling the data-plane forwarding actions from the control-plane decisions, hence boosting network programmability and innovation. Optical networks are also capitalizing on SDN benefits jointly with a disaggregation trend that holds the promise of overcoming traditional vendor-locked island limitations. In this work, we present our framework for disaggregated optical networks that leverages on SDN and container-based management for a realistic emulation of deployment scenarios. Our proposal relies on Kubernetes for the containers’ control and management, while employing the NETCONF protocol for the interaction with the light-weight software entities, i.e., agents, which govern the emulated optical devices. Remarkably, our agents’ structure relies on components that offer high versatility for accommodating the wide variety of components and systems in the optical domain. We showcase our proposal with the emulation of an 18-node European topology employing Cassini-compliant optical models, i.e., a state-of-the-art optical transponder proposed in the Telecom Infrastructure Project. The combination of our versatile framework based on containerized entities, the automatic creation of agents and the optical-layer characteristics represents a novel approach suitable for operationally complex carrier-grade transport infrastructure with SDN-based disaggregated optical systems.
Green Treatment of Cyanide Tailings Using a “Filter Press BackWash–Chemical Precipitation–Gaseous Membrane Absorption” Method
Authors: Yan Jingmin , Wang Yanhua , Tu Yubo , Han Peiwei , Liu Xiang , Ye Shufeng
Published: February 2021

Based on a “filter press backwash–chemical precipitation–gaseous membrane absorption” process, treatment of harmless cyanide tailings was conducted using cyanide tailings from a gold smelting enterprises (Yunnan Province, China) as the research object. The effects of air-drying time, backwash water parameters, initial pH of acidification, NaHS dosage, cyanide-containing water flow rate, and gaseous membrane stages on the process were investigated. Chemical composition, X-ray diffraction, and X-ray photoelectron spectroscopy analyses of the copper products were carried out. Results showed that the copper content in the copper product was 54.56%, and the chemical composition was mainly CuSCN, CuS, Cu2S, and CaSO4. Five cycles of experiments were carried out under optimal conditions; the results showed that the process can make the treated cyanide tailings meet the requirements of the technical specification for pollution control of cyanide leaching residue in the gold industry (TSPC) standard for storage in a tailings pond and a have certain stability. The average recovery rate of copper and total cyanide in elution water was 97.8% and 99.89%, respectively, and the average removal rate of thiocyanate was 94.09%.
Improvement for Convolutional Neural Networks in Image Classification Using Long Skip Connection
Authors: Hoang Hong Hai , Trinh Hoang Hieu
Published: February 2021

In this paper, we examine and research the effect of long skip connection on convolutional neural networks (CNNs) for the tasks of image (surface defect) classification. The standard popular models only apply short skip connection inside blocks (layers with the same size). We apply the long version of residual connection on several proposed models, which aims to reuse the lost spatial knowledge from the layers close to input. For some models, Depthwise Separable Convolution is used rather than traditional convolution in order to reduce both count of parameters and floating-point operations per second (FLOPs). Comparative experiments of the newly upgraded models and some popular models have been carried out on different datasets including Bamboo strips datasets and a reduced version of ImageNet. The modified version of DenseNet 121 (we call MDenseNet 121) achieves higher validation accuracy while it has about 75% of weights and FLOPs in comparison to the original DenseNet 121.
Description and Evaluation of the Fine Particulate Matter Forecasts in the NCAR Regional Air Quality Forecasting System
Authors: Kumar Rajesh , Bhardwaj Piyush , Pfister Gabriele , Drews Carl , Honomichl Shawn , D’Attilo Garth
Published: February 2021

This paper describes a quasi-operational regional air quality forecasting system for the contiguous United States (CONUS) developed at the National Center for Atmospheric Research (NCAR) to support air quality decision-making, field campaign planning, early identification of model errors and biases, and support the atmospheric science community in their research. This system aims to complement the operational air quality forecasts produced by the National Oceanic and Atmospheric Administration (NOAA), not to replace them. A publicly available information dissemination system has been established that displays various air quality products, including a near-real-time evaluation of the model forecasts. Here, we report the performance of our air quality forecasting system in simulating meteorology and fine particulate matter (PM2.5) for the first year after our system started, i.e., 1 June 2019 to 31 May 2020. Our system shows excellent skill in capturing hourly to daily variations in temperature, surface pressure, relative humidity, water vapor mixing ratios, and wind direction but shows relatively larger errors in wind speed. The model also captures the seasonal cycle of surface PM2.5 very well in different regions and for different types of sites (urban, suburban, and rural) in the CONUS with a mean bias smaller than 1 µg m−3. The skill of the air quality forecasts remains fairly stable between the first and second days of the forecasts. Our air quality forecast products are publicly available at a NCAR webpage. We invite the community to use our forecasting products for their research, as input for urban scale (<4 km), air quality forecasts, or the co-development of customized products, just to name a few applications.
Downscaling and Evaluation of Seasonal Climate Data for the European Power Sector
Authors: Ostermöller Jennifer , Lorenz Philip , Fröhlich Kristina , Kreienkamp Frank , Früh Barbara
Published: February 2021

Within the Clim2Power project, two case studies focus on seasonal variations of the hydropower production in the river basins of the Danube (Germany/Austria) and the Douro (Portugal). To deliver spatially highly resolved climate data as an input for the hydrological models, the forecasts of the German Climate Forecast System (GCFS2.0) need to be downscaled. The statistical-empirical method EPISODES is used in this approach. It is adapted to the seasonal data, which consists of ensemble hindcasts and forecasts. Beside this, the two case study regions need specific configurations of the statistical model, providing appropriate predictors for the meteorological variables. This paper describes the technical details of the adaptation of the EPISODES method for the needs of Clim2Power. We analyse the hindcast skill of the downscaled hindcasts of all four seasons for the two variables near-surface (2 m) temperature and precipitation, and conclude that on the average the skill is conserved compared to the global model. This means that the seasonal information is available at a higher spatial resolution without losing skill. Furthermore, the output of the statistical downscaling is nearly bias-free, which is, beside the higher spatial resolution, an added value for the climate service.
Agricultural and Forestry Land and Labor Use under Long-Term Climate Change in Chile
Authors: Melo Oscar , Foster William
Published: February 2021

The appropriate design of land-use and rural employment policies depends upon the anticipated performance of the farm sector in the context of expected climate changes, especially with respect to land allocations to potential activities. Concerns over the possible net benefits of land-use changes are particularly acute in lower- and middle-income countries, where agriculture tends to be important in employment, income generation and foreign-exchange earnings. This paper presents an analysis of the expected impacts on land use in Chile of projected climate-change scenarios in 2040 and 2070. We developed a farmland allocation model with associated labor employment at the municipal level driven by expected relative net incomes per hectare, constructed from local average per-hectare yields, regional average output prices and per-hectare production cost estimates. The sensitivities of cropland allocations to relative net-income changes were estimated using historical land allocations at the municipal level derived from the last two Chilean Agricultural Censuses. The results show that the impacts of climate changes will be mitigated by land-use adaptation, the main export-earning crops tending to move south; in aggregate, agricultural employment will decrease in all the climate-change scenarios; forestry and agriculture would likely suffer a loss in net-income generation under severe climate-change scenarios.
Associations between Space Weather Events and the Incidence of Acute Myocardial Infarction and Deaths from Ischemic Heart Disease
Authors: Vaičiulis Vidmantas , Venclovienė Jonė , Tamošiūnas Abdonas , Kiznys Deivydas , Lukšienė Dalia , Krančiukaitė-Butylkinienė Daina , Radišauskas Ričardas
Published: February 2021

The effects of charged solar particles hitting the Earth’s magnetosphere are often harmful and can be dangerous to the human organism. The aim of this study was to analyze the associations of geomagnetic storms (GSs) and other space weather events (solar proton events (SPEs), solar flares (SFs), high-speed solar wind (HSSW), interplanetary coronal mass ejections (ICMEs) and stream interaction regions (SIRs)) with morbidity from acute myocardial infarction (AMI) and mortality from ischemic heart diseases (IHDs) during the period 2000–2015 in Kaunas (Lithuania). In 2000–2015, 12,330 AMI events (men/women n = 6942/5388) and 3742 deaths from IHD (men/women n = 2480/1262) were registered. The results showed that a higher risk of AMI and deaths from IHD were related to the period of 3 days before GS—a day after GS, and a stronger effect was observed during the spring–autumn period. The strongest effect of HSSW was observed on the day of the event. We found significant associations between the risk of AMI and death from IHD and the occurrence of SFs during GSs. We also found a statistically significant increase in rate ratios (RRs) for all AMIs and deaths from IHD between the second and fourth days of the period of ICMEs.
Fixed Points of Some Asymptotically Regular Multivalued Mappings Satisfying a Kannan-Type Condition
Authors: Debnath Pradip , Mitrović Zoran D. , Srivastava Hari Mohan
Published: February 2021

In this paper, we establish some existence of fixed-point results for some asymptotically regular multivalued mappings satisfying Kannan-type contractive condition without assuming compactness of the underlying metric space or continuity of the mapping.
Automatic Defects Segmentation and Identification by Deep Learning Algorithm with Pulsed Thermography: Synthetic and Experimental Data
Authors: Fang Qiang , Ibarra-Castanedo Clemente , Maldague Xavier
Published: February 2021

In quality evaluation (QE) of the industrial production field, infrared thermography (IRT) is one of the most crucial techniques used for evaluating composite materials due to the properties of low cost, fast inspection of large surfaces, and safety. The application of deep neural networks tends to be a prominent direction in IRT Non-Destructive Testing (NDT). During the training of the neural network, the Achilles heel is the necessity of a large database. The collection of huge amounts of training data is the high expense task. In NDT with deep learning, synthetic data contributing to training in infrared thermography remains relatively unexplored. In this paper, synthetic data from the standard Finite Element Models are combined with experimental data to build repositories with Mask Region based Convolutional Neural Networks (Mask-RCNN) to strengthen the neural network, learning the essential features of objects of interest and achieving defect segmentation automatically. These results indicate the possibility of adapting inexpensive synthetic data merging with a certain amount of the experimental database for training the neural networks in order to achieve the compelling performance from a limited collection of the annotated experimental data of a real-world practical thermography experiment.
Microbial Interactions as Drivers of a Nitrification Process in a Chemostat
Authors: Ugalde-Salas Pablo , Ramírez C. Héctor , Harmand Jérôme , Desmond-Le Quéméner Elie
Published: February 2021

This article deals with the inclusion of microbial ecology measurements such as abundances of operational taxonomic units in bioprocess modelling. The first part presents the mathematical analysis of a model that may be framed within the class of Lotka–Volterra models fitted to experimental data in a chemostat setting where a nitrification process was operated for over 500 days. The limitations and the insights of such an approach are discussed. In the second part, the use of an optimal tracking technique (developed within the framework of control theory) for the integration of data from genetic sequencing in chemostat models is presented. The optimal tracking revisits the data used in the aforementioned chemostat setting. The resulting model is an explanatory model, not a predictive one, it is able to reconstruct the different forms of nitrogen in the reactor by using the abundances of the operational taxonomic units, providing some insights into the growth rate of microbes in a complex community.
Variation of Passive Biomechanical Properties of the Small Intestine along Its Length: Microstructure-Based Characterization
Authors: Sokolis Dimitrios P.
Published: February 2021

Multiaxial testing of the small intestinal wall is critical for understanding its biomechanical properties and defining material models, but limited data and material models are available. The aim of the present study was to develop a microstructure-based material model for the small intestine and test whether there was a significant variation in the passive biomechanical properties along the length of the organ. Rat tissue was cut into eight segments that underwent inflation/extension testing, and their nonlinearly hyper-elastic and anisotropic response was characterized by a fiber-reinforced model. Extensive parametric analysis showed a non-significant contribution to the model of the isotropic matrix and circumferential-fiber family, leading also to severe over-parameterization. Such issues were not apparent with the reduced neo-Hookean and (axial and diagonal)-fiber family model, that provided equally accurate fitting results. Absence from the model of either the axial or diagonal-fiber families led to ill representations of the force- and pressure-diameter data, respectively. The primary direction of anisotropy, designated by the estimated orientation angle of diagonal-fiber families, was about 35° to the axial direction, corroborating prior microscopic observations of submucosal collagen-fiber orientation. The estimated model parameters varied across and within the duodenum, jejunum, and ileum, corroborating histologically assessed segmental differences in layer thicknesses.
A Novel Approach to Design and Evaluate BNCT Neutron Beams Combining Physical, Radiobiological, and Dosimetric Figures of Merit
Authors: Postuma Ian , González Sara , Herrera Maria S , Provenzano Lucas , Ferrarini Michele , Magni Chiara , Protti Nicoletta , Fatemi Setareh , Vercesi Valerio , Battistoni Giuseppe , Anselmi Tamburini Umberto , Hao Liu Yuan , Kankaanranta Leena , Koivunoro Hanna , Altieri Saverio , Bortolussi Silva
Published: February 2021

(1) Background:The quality of neutron beams for Boron Neutron Capture Therapy (BNCT) is currently defined by its physical characteristics in air. Recommendations exist to define whether a designed beam is useful for clinical treatment. This work presents a new way to evaluate neutron beams based on their clinical performance and on their safety, employing radiobiological quantities. (2) Methods: The case study is a neutron beam for deep-seated tumors from a 5 MeV proton beam coupled to a beryllium target. Physical Figures of Merit were used to design five beams; however, they did not allow a clear ranking of their quality in terms of therapeutic potential. The latter was then evaluated based on in-phantom dose distributions and on the calculation of the Uncomplicated Tumor Control Probability (UTCP). The safety of the beams was also evaluated calculating the in-patient out-of-beam dosimetry. (3) Results: All the beams ensured a UTCP comparable to the one of a clinical beam in phantom; the safety criterion allowed to choose the best candidate. When this was tested in the treatment planning of a real patient treated in Finland, the UTCP was still comparable to the one of the clinical beam. (4) Conclusions: Even when standard physical recommendations are not met, radiobiological and dosimetric criteria demonstrate to be a valid tool to select an effective and safe beam for patient treatment.
Emerging Roles of Metallothioneins in Beta Cell Pathophysiology: Beyond and above Metal Homeostasis and Antioxidant Response
Authors: Bensellam Mohammed , Laybutt D. Ross , Jonas Jean-Christophe
Published: February 2021

Metallothioneins (MTs) are low molecular weight, cysteine-rich, metal-binding proteins whose precise biological roles have not been fully characterized. Existing evidence implicated MTs in heavy metal detoxification, metal ion homeostasis and antioxidant defense. MTs were thus categorized as protective effectors that contribute to cellular homeostasis and survival. This view has, however, been challenged by emerging evidence in different medical fields revealing novel pathophysiological roles of MTs, including inflammatory bowel disease, neurodegenerative disorders, carcinogenesis and diabetes. In the present focused review, we discuss the evidence for the role of MTs in pancreatic beta-cell biology and insulin secretion. We highlight the pattern of specific isoforms of MT gene expression in rodents and human beta-cells. We then discuss the mechanisms involved in the regulation of MTs in islets under physiological and pathological conditions, particularly type 2 diabetes, and analyze the evidence revealing adaptive and negative roles of MTs in beta-cells and the potential mechanisms involved. Finally, we underscore the unsettled questions in the field and propose some future research directions.
Syndecans and Pancreatic Ductal Adenocarcinoma
Authors: Betriu Nausika , Bertran-Mas Juan , Andreeva Anna , Semino Carlos E.
Published: February 2021

Pancreatic Ductal Adenocarcinoma (PDAC) is a fatal disease with poor prognosis because patients rarely express symptoms in initial stages, which prevents early detection and diagnosis. Syndecans, a subfamily of proteoglycans, are involved in many physiological processes including cell proliferation, adhesion, and migration. Syndecans are physiologically found in many cell types and their interactions with other macromolecules enhance many pathways. In particular, extracellular matrix components, growth factors, and integrins collect the majority of syndecans associations acting as biochemical, physical, and mechanical transducers. Syndecans are transmembrane glycoproteins, but occasionally their extracellular domain can be released from the cell surface by the action of matrix metalloproteinases, converting them into soluble molecules that are capable of binding distant molecules such as extracellular matrix (ECM) components, growth factor receptors, and integrins from other cells. In this review, we explore the role of syndecans in tumorigenesis as well as their potential as therapeutic targets. Finally, this work reviews the contribution of syndecan-1 and syndecan-2 in PDAC progression and illustrates its potential to be targeted in future treatments for this devastating disease.
Simulating Metaphyseal Fracture Healing in the Distal Radius
Authors: Engelhardt Lucas , Niemeyer Frank , Christen Patrik , Müller Ralph , Stock Kerstin , Blauth Michael , Urban Karsten , Ignatius Anita , Simon Ulrich
Published: February 2021

Simulating diaphyseal fracture healing via numerical models has been investigated for a long time. It is apparent from in vivo studies that metaphyseal fracture healing should follow similar biomechanical rules although the speed and healing pattern might differ. To investigate this hypothesis, a pre-existing, well-established diaphyseal fracture healing model was extended to study metaphyseal bone healing. Clinical data of distal radius fractures were compared to corresponding geometrically patient-specific fracture healing simulations. The numerical model, was able to predict a realistic fracture healing process in a wide variety of radius geometries. Endochondral and mainly intramembranous ossification was predicted in the fractured area without callus formation. The model, therefore, appears appropriate to study metaphyseal bone healing under differing mechanical conditions and metaphyseal fractures in different bones and fracture types. Nevertheless, the outlined model was conducted in a simplified rotational symmetric case. Further studies may extend the model to a three-dimensional representation to investigate complex fracture shapes. This will help to optimize clinical treatments of radial fractures, medical implant design and foster biomechanical research in metaphyseal fracture healing.