bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Increased Ionic Liquid Uptake via Thermal Annealing on Mechanical Properties of Polyimide-Poly(ethylene glycol) Segmented Block Copolymer Membranes
Authors: Ciftcioglu Gokcen A. , Frank Curtis W.
Published: April 2021

Proton exchange membranes (PEMs) suffer performance degradation under certain conditions—temperatures greater than 80 °C, relative humidity less than 50%, and water retention less than 22%. Novel materials are needed that have improved water retention, stability at higher temperatures, flexibility, conductivity, and the ability to function at low humidity. This work focuses on polyimide-poly(ethylene glycol) (PI-PEG) segmented block copolymer (SBC) membranes with high conductivity and mechanical strength. Membranes were prepared with one of two ionic liquids (ILs), either ethylammonium nitrate (EAN) or propylammonium nitrate (PAN), incorporated within the membrane structure to enhance the proton exchange capability. Ionic liquid uptake capacities were compared for two different temperatures, 25 and 60 °C. Then, conductivities were measured for a series of combinations of undoped or doped unannealed and undoped or doped annealed membranes. Stress and strain tests were performed for unannealed and thermally annealed undoped membranes. Later, these experiments were repeated for doped unannealed and thermally annealed. Mechanical and conductivity data were interpreted in the context of prior small angle X-ray scattering (SAXS) studies on similar materials. We have shown that varying the compositions of polyimide-poly(ethylene glycol) (PI-PEG) SBCs allowed the morphology in the system to be tuned. Since polyimides (PI) are made from the condensation of dianhydrides and diamines, this was accomplished using components having different functional groups. Dianhydrides having either fluorinated or oxygenated functional groups and diamines having either fluorinated or oxygenated diamines were used as well as mixtures of these species. Changing the morphology by creating macrophase separation elevated the IL uptake capacities, and in turn, increased their conductivities by a factor of three or more compared to Nafion 115. The stiffness of the membranes synthesized in this work was comparable to Nafion 115 and, thus, sufficient for practical applications.
Design of Hybrid PAH Nanoadsorbents by Surface Functionalization of ZrO2 Nanoparticles with Phosphonic Acids
Authors: Bou Orm Nadine , Gréa Thomas , Hamandi Marwa , Lambert Alexandre , Lafay Florent , Vulliet Emmanuelle , Daniele Stéphane
Published: April 2021

This study focuses on the preparation of innovative nanocomposite materials based on surface modification of commercial nano-ZrO2 optimized from Brønsted acid–base surface reactions. This surface modification was carried out by direct grafting of suitable phosphonic acids bearing a vinylic or phenylic substituent in aqueous solution. Different loading quantities of the anchoring organophosphorus compounds were applied for each materials synthesis. The resulting nanohybrids were thoroughly characterized by infrared spectroscopy (DRIFT), solid-state nuclear magnetic resonance (NMR), nitrogen adsorption-desorption (BET), thermogravimetric analysis (TG), and X-ray photoelectron spectroscopy (XPS), demonstrating the reliability and efficient tunability of the surface functionalization based on the starting Zr/P ratio. Our nanocomposite materials exhibited a high specific surface area as well as complex porosity networks with well-defined meso-pore. The as-prepared materials were investigated for the adsorption of a mixture of 16 polycyclic aromatic hydrocarbons (PAHs) at 200 ng·mL−1 in an aqueous solution. Adsorption kinetics experiments of each individual material were carried out on the prepared PAHs standard solution for a contact time of up to 6 h. Pretreatments of the adsorption test samples were performed by solid-phase extraction (SPE), and the resulting samples were analyzed using an ultrasensitive GC-orbitrap-MS system. The pseudo-first-order and the pseudo-second-order models were used to determine the kinetic data. The adsorption kinetics were best described and fitted by the pseudo-second-order kinetic model. The correlation between the nature of the substituent (vinylic or phenylic) and the parameters characterizing the adsorption process were found. In addition, an increase of PAHs adsorption rates with phosphonic acid loading was observed.
Sesquiterpene-Loaded Co-Polymer Hybrid Nanoparticle Effects on Human Mast Cell Surface Receptor Expression, Granule Contents, and Degranulation
Authors: Arizmendi Narcy , Qian Hui , Li Yiming , Kulka Marianna
Published: April 2021

Biodegradable polymeric nanoparticles (NPs) such as poly(lactic-co-glycolic acid) (PLGA) and polyvinyl alcohol (PVA) have been used as drug delivery systems for natural and synthetic compounds and are designed to control the loading and release of biodegradable materials to target cells, tissues, and organs. Eremophilane-type sesquiterpenes have anti-inflammatory properties but are lipophilic, cytotoxic, and not biocompatible with many cells. To determine whether biodegradable PLGA/PVA could improve the biocompatibility of sesquiterpenes, sesquiterpene-loaded NPs were synthesized and their effects on human mast cells (LAD2), the major effector cells of allergic inflammation, were determined. NPs composed of PLGA/PVA and two types of sesquiterpenes (fukinone, PLGA/PVA-21 and 10βH-8α,12-epidioxyeremophil-7(11)-en-8β-ol, PLGA/PVA-22) were produced using a microfluidic synthesis method. The NPs’ size distribution and morphology were evaluated by dynamic light scattering and cryogenic transmission electron microscopy (TEM). PLGA/PVA-21 and PLGA/PVA-22 were 60 to 70 nm and were readily internalized by LAD2 as shown by flow cytometry, fluorescence microscopy, and TEM. While unencapsulated sesquiterpenes decreased LAD2 cell viability by 20%, PLGA/PVA-21 and PLGA/PVA-22 did not alter LAD2 viability, showing that encapsulation improved the biocompatibility of the sesquiterpenes. PLGA/PVA-21 and PLGA/PVA-22 decreased the expression of genes encoding the subunits of the high affinity immunoglobulin E receptor (FcεR1α, FcεR1β, FcεR1γ) and the stem cell factor receptor (Kit,), suggesting that hybrid NPs could alter mast cell responses to antigens and shift their maturation. Similarly, PLGA/PVA-21 and PLGA/PVA-22 inhibited tryptase expression but had no effect on chymase expression, thereby promoting a shift to the tryptase-positive phenotype (MCT). Lastly, PLGA/PVA-21 and PLGA/PVA-22 inhibited mast cell degranulation when the LAD2 cells were activated by IgE crosslinking and FcεRI. Overall, our results suggest that PLGA/PVA-21 and PLGA/PVA-22 alter human mast cell phenotype and activation without modifying viability, making them a more biocompatible approach than treating cells with sesquiterpenes alone.
Associations between Age-Related Hearing Loss and DietaryAssessment Using Data from Korean National Health andNutrition Examination Survey
Authors: Choi Ji Eun , Ahn Jungmin , Moon Il Joon
Published: April 2021

Age-related hearing loss (ARHL) is a major and rapidly growing public health problem thatcauses disability, social isolation, and socioeconomic cost. Nutritional status is known to cause manyaging-related problems, and recent studies have suggested that there are interaction effects betweenARHL and dietary factors. We aimed to investigate the association between ARHL and dietaryassessment using data from the fifth Korean National Health and Nutrition Examination Survey,which is a nationwide cross-sectional survey that included 5201 participants aged≥50 years from2010 to 2012. All participants had normal findings on otoscopic examination and symmetric hearingthresholds of <15 dB between both sides. Nutritional survey data included food consumption andnutrient intake using the 24 h recall method. Data were analyzed using multiple regression modelswith complex sampling adjusted for confounding factors, such as age, sex, educational level, andhistory of diabetes. Higher intake of seeds and nuts, fruits, seaweed, and vitamin A were positivelyassociated with better hearing. Our findings suggest that dietary antioxidants or anti-inflammatoryfood may help reduce ARHL
Effect of Curcumin Nanoemulsions Stabilized with MAG and DAG-MCFAs in a Fructose-Induced Hepatic Steatosis Rat Model
Authors: Agame-Lagunes Beatriz , Grube-Pagola Peter , García-Varela Rebeca , Alexander-Aguilera Alfonso , García Hugo S.
Published: April 2021

Current changes in diet, characterized by an increase in the intake of sweetened beverages, are heavily related to metabolic disorders such as non-alcoholic fatty liver. This condition can produce simple steatosis and, in worse cases, potentially result in steatohepatitis, fibrosis, and cirrhosis, comparable to the damage caused by the consumption of more or less 20–30 g of alcohol per day. The main objective of this research was to evaluate the effect of curcumin (Curcuma longa) nanoemulsions, using mono- and diacylglycerides medium chain fatty acids as stabilizers in an in vivo hepatic steatosis rat model. Pathology was induced by providing 30% fructose intake in the drinking water. Globule sizes under 200 nm that were stable for 4 weeks were obtained; curcumin encapsulated in the nanoemulsion was >70%. The results revealed an improvement regarding body and liver weight in the animals treated with curcumin nanoemulsions. A decrease in total cholesterol, LDL, AST/ALT, and HDL in serum was observed; however, no apparent improvement regarding serum glucose or triacylglycerides values was noted. Histological analysis showed a significant decrease in the extent of steatosis, inflammation, and brown adipose tissue in the treated animals.
Structural Analysis of the Simultaneous Activation and Inhibition of γ-Secretase Activity in the Development of Drugs for Alzheimer’s Disease
Authors: Svedružić Željko M. , Vrbnjak Katarina , Martinović Manuel , Miletić Vedran
Published: April 2021

Significance: The majority of the drugs which target membrane-embedded protease γ-secretase show an unusual biphasic activation–inhibition dose-response in cells, model animals, and humans. Semagacestat and avagacestat are two biphasic drugs that can facilitate cognitive decline in patients with Alzheimer’s disease. Initial mechanistic studies showed that the biphasic drugs, and pathogenic mutations, can produce the same type of changes in γ-secretase activity. Results: DAPT, semagacestat LY-411,575, and avagacestat are four drugs that show different binding constants, and a biphasic activation–inhibition dose-response for amyloid-β-40 products in SH-SY5 cells. Multiscale molecular dynamics studies have shown that all four drugs bind to the most mobile parts in the presenilin structure, at different ends of the 29 Å long active site tunnel. The biphasic dose-response assays are a result of the modulation of γ-secretase activity by the concurrent binding of multiple drug molecules at each end of the active site tunnel. The drugs activate γ-secretase by facilitating the opening of the active site tunnel, when the rate-limiting step is the tunnel opening, and the formation of the enzyme–substrate complex. The drugs inhibit γ-secretase as uncompetitive inhibitors by binding next to the substrate, to dynamic enzyme structures which regulate processive catalysis. The drugs can modulate the production of different amyloid-β catalytic intermediates by penetration into the active site tunnel, to different depths, with different flexibility and different binding affinity. Conclusions: Biphasic drugs and pathogenic mutations can affect the same dynamic protein structures that control processive catalysis. Successful drug-design strategies must incorporate transient changes in the γ-secretase structure in the development of specific modulators of its catalytic activity.
Film-Forming Systems for the Delivery of DNDI-0690 to Treat Cutaneous Leishmaniasis
Authors: Van Bocxlaer Katrien , McArthur Kerri-Nicola , Harris Andy , Alavijeh Mo , Braillard Stéphanie , Mowbray Charles E. , Croft Simon L.
Published: April 2021

In cutaneous leishmaniasis (CL), parasites reside in the dermis, creating an opportunity for local drug administration potentially reducing adverse effects and improving treatment adherence compared to current therapies. Polymeric film-forming systems (FFSs) are directly applied to the skin and form a thin film as the solvent evaporates. In contrast to conventional topical dosage forms, FFSs strongly adhere to the skin, favouring sustained drug delivery to the affected site, reducing the need for frequent applications, and enhancing patient compliance. This study reports the first investigation of the use of film-forming systems for the delivery of DNDI-0690, a nitroimidazole compound with potent activity against CL-causing Leishmania species. A total of seven polymers with or without plasticiser were evaluated for drying time, stickiness, film-flexibility, and cosmetic attributes; three FFSs yielded a positive evaluation for all test parameters. The impact of each of these FFSs on the permeation of the model skin permeant hydrocortisone (hydrocortisone, 1% (w/v) across the Strat-M membrane was evaluated, and the formulations resulting in the highest and lowest permeation flux (Klucel LF with triethyl citrate and Eudragit RS with dibutyl sebacate, respectively) were selected as the FFS vehicle for DNDI-0690. The release and skin distribution of the drug upon application to Leishmania-infected and uninfected BALB/c mouse skin were examined using Franz diffusion cells followed by an evaluation of the efficacy of both DNDI-0690 FFSs (1% (w/v)) in an experimental CL model. Whereas the Eudragit film resulted in a higher permeation of DNDI-0690, the Klucel film was able to deposit four times more drug into the skin, where the parasite resides. Of the FFSs formulations, only the Eudragit system resulted in a reduced parasite load, but not reduced lesion size, when compared to the vehicle only control. Whereas drug delivery into the skin was successfully modulated using different FFS systems, the FFS systems selected were not effective for the topical application of DNDI-0690. The convenience and aesthetic of FFS systems alongside their ability to modulate drug delivery to and into the skin merit further investigation using other promising antileishmanial drugs.
A Review on Green Composites Based on Natural Fiber-Reinforced Polybutylene Succinate (PBS)
Authors: Mochane Mokgaotsa J. , Magagula Sifiso I. , Sefadi Jeremia S. , Mokhena Teboho C.
Published: April 2021

The need for utilization of environmentally friendly materials has emerged due to environmental pollution that is caused by non-biodegradable materials. The usage of non-biodegradable plastics has increased in the past decades in many industries, and, as a result, the generation of non-biodegradable plastic wastes has also increased. To solve the problem of non-biodegradable plastic wastes, there is need for fabrication of bio-based polymers to replace petroleum-based polymers and provide strategic plans to reduce the production cost of bioplastics. One of the emerging bioplastics in the market is poly (butylene succinate) (PBS) and it has been the biopolymer of choice due to its biodegradability and environmental friendliness. However, there are some disadvantages associated with PBS such as high cost, low gas barrier properties, and softness. To lower the cost of PBS and enhance its properties, natural lignocellulosic fibers are incorporated into the PBS matrix, to form environmentally friendly composites. Natural fiber-based biocomposites have emerged as materials of interest in important industries such as packaging, automobile, and construction. The bonding between the PBS and natural fibers is weak, which is a major problem for advanced applications of this system. As a result, this review paper discusses various methods that are employed for surface modification of the Fibers The paper provides an in-depth discussion on the preparation, modification, and morphology of the natural fiber-reinforced polybutylene succinate biocomposites. Furthermore, because the preparation as well as the modification of the fiber-reinforced biocomposites have an influence on the mechanical properties of the biocomposites, mechanical properties of the biocomposites are also discussed. The applications of the natural fiber/PBS biocomposites for different systems are also reported.
A Comprehensive Review on Optimal Welding Conditions for Friction Stir Welding of Thermoplastic Polymers and Their Composites
Authors: Iftikhar Syed Haris , Mourad Abdel-Hamid Ismail , Sheikh-Ahmad Jamal , Almaskari Fahad , Vincent S.
Published: April 2021

Friction stir welding (FSW) and friction stir spot welding (FSSW) techniques are becoming widely popular joining techniques because of their increasing potential applications in automotive, aerospace, and other structural industries. These techniques have not only successfully joined similar and dissimilar metal and polymer parts but have also successfully developed polymer-metallic hybrid joints. This study classifies the literature available on the FSW and FSSW of thermoplastic polymers and polymer composites on the basis of joining materials (similar or dissimilar), joint configurations, tooling conditions, medium conditions, and study types. It provides a state-of-the-art and detailed review of the experimental studies available on the FSW and FSSW between similar thermoplastics. The mechanical properties of FSW (butt- and lap-joint configurations) and FSSW weld joints depend on various factors. These factors include the welding process parameters (tool rotational speed, tool traverse speed, tool tilt angle, etc.), base material, tool geometry (pin and shoulder size, pin profile, etc.) and tool material, and medium conditions (submerged, non-submerged, heat-assisted tooling, cooling-assisted tooling). Because of the dependence on many factors, it is difficult to optimize the welding conditions to obtain a high-quality weld joint with superior mechanical properties. The general guidelines are established by reviewing the available literature. These guidelines, if followed, will help to achieve high-quality weld joints with least defects and superior mechanical properties. Apart from parametric-based studies, the statistical-based studies (e.g., analysis of variance (ANOVA)-based studies) are covered, which helps with the determination of the influential parameters that affect the FSW and FSSW weld joint strength. Also, the optimal ranges of the most influential process parameters for different thermoplastic materials are established. The current work on the development of general guidelines and determination of influential parameters and their operating ranges from published literature can help with designing smart future experimental studies for obtaining the global optimum welding conditions. The gaps in the available literature and recommendations for future studies are also discussed.
Emerging Biofabrication Techniques: A Review on Natural Polymers for Biomedical Applications
Authors: Puertas-Bartolomé María , Mora-Boza Ana , García-Fernández Luis
Published: April 2021

Natural polymers have been widely used for biomedical applications in recent decades. They offer the advantages of resembling the extracellular matrix of native tissues and retaining biochemical cues and properties necessary to enhance their biocompatibility, so they usually improve the cellular attachment and behavior and avoid immunological reactions. Moreover, they offer a rapid degradability through natural enzymatic or chemical processes. However, natural polymers present poor mechanical strength, which frequently makes the manipulation processes difficult. Recent advances in biofabrication, 3D printing, microfluidics, and cell-electrospinning allow the manufacturing of complex natural polymer matrixes with biophysical and structural properties similar to those of the extracellular matrix. In addition, these techniques offer the possibility of incorporating different cell lines into the fabrication process, a revolutionary strategy broadly explored in recent years to produce cell-laden scaffolds that can better mimic the properties of functional tissues. In this review, the use of 3D printing, microfluidics, and electrospinning approaches has been extensively investigated for the biofabrication of naturally derived polymer scaffolds with encapsulated cells intended for biomedical applications (e.g., cell therapies, bone and dental grafts, cardiovascular or musculoskeletal tissue regeneration, and wound healing).
Synergy between Low Earth Orbit (LEO)—MODIS and Geostationary Earth Orbit (GEO)—GOES Sensors for Sargassum Monitoring in the Atlantic Ocean
Authors: Minghelli Audrey , Chevalier Cristele , Descloitres Jacques , Berline Léo , Blanc Philippe , Chami Malik
Published: April 2021

Since 2011, massive stranding of the brown algae Sargassum has regularly affected the coastal waters of the West Caribbean, Brazil, and West Africa, leading to heavy environmental and socio-economic impacts. Ocean color remote sensing observations as performed by sun-synchronous satellite sensors such as MODIS (NASA), MERIS (ESA), or OLCI (ESA/Copernicus) are used to provide quantitative assessments of Sargassum coverage through the calculation of indices as the Alternative Floating Algae Index (AFAI). Sun-synchronous sensors usually provide at best one daytime observation per day of a given oceanic area. However, such a daily temporal revisit rate is not fully satisfactory to monitor the dynamics of Sargassum aggregation due to their potentially significant drift over the course of the day as a result of oceanic currents and sea surface wind stress. In addition, the sun glint and the presence of clouds limit the use of low earth orbit observations, especially in tropical zones. The high frequency sampling provided by geostationary sensors can be a relevant alternative approach in synergy with ocean color sun-synchronous sensors to increase the temporal resolution of the observations, thus allowing efficient monitoring of Sargassum dynamics. In this study, data acquired by a geostationary satellite sensor located at 36,000 km from Earth, namely GOES-16 (NASA/NOAA), which was primarily designed for meteorology applications, are analyzed to investigate the Sargassum dynamics. The results demonstrate that a GOES-16 hourly composite product is appropriate to identify Sargassum aggregations using an index commonly used for vegetation monitoring, namely NDVI (Normalized Difference Vegetation Index). It is also shown that GOES hourly observations can significantly improve the simulated drift obtained with a transport circulation model, which uses geostrophic current, wind, and waves. This study thus highlights the significant relevance of the effective synergy between sun-synchronous and geostationary satellite sensors for characterizing the Sargassum dynamics. Such a synergy could be summarized as follows: (i) A sun-synchronous sensor enables accurate Sargassum detection and quantitative estimates (e.g., fractional coverage) through AFAI Level-2 products while (ii) a geostationary sensor enables the determination of the displacement features of Sargassum aggregations (velocity, direction).
Inversion of Phytoplankton Pigment Vertical Profiles from Satellite Data Using Machine Learning
Authors: Puissant Agathe , El Hourany Roy , Charantonis Anastase Alexandre , Bowler Chris , Thiria Sylvie
Published: April 2021

Observing the vertical dynamic of phytoplankton in the water column is essential to understand the evolution of the ocean primary productivity under climate change and the efficiency of the CO2 biological pump. This is usually made through in-situ measurements. In this paper, we propose a machine learning methodology to infer the vertical distribution of phytoplankton pigments from surface satellite observations, allowing their global estimation with a high spatial and temporal resolution. After imputing missing values through iterative completion Self-Organizing Maps, smoothing and reducing the vertical distributions through principal component analysis, we used a Self-Organizing Map to cluster the reduced profiles with satellite observations. These referent vector clusters were then used to invert the vertical profiles of phytoplankton pigments. The methodology was trained and validated on the MAREDAT dataset and tested on the Tara Oceans dataset. The different regression coefficients R2 between observed and estimated vertical profiles of pigment concentration are, on average, greater than 0.7. We could expect to monitor the vertical distribution of phytoplankton types in the global ocean.
Hybrid Multisite Silicon Neural Probe with Integrated Flexible Connector for Interchangeable Packaging
Authors: Novais Ashley , Calaza Carlos , Fernandes José , Fonseca Helder , Monteiro Patricia , Gaspar João , Jacinto Luis
Published: April 2021

Multisite neural probes are a fundamental tool to study brain function. Hybrid silicon/polymer neural probes combine rigid silicon and flexible polymer parts into one single device and allow, for example, the precise integration of complex probe geometries, such as multishank designs, with flexible biocompatible cabling. Despite these advantages and benefiting from highly reproducible fabrication methods on both silicon and polymer substrates, they have not been widely available. This paper presents the development, fabrication, characterization, and in vivo electrophysiological assessment of a hybrid multisite multishank silicon probe with a monolithically integrated polyimide flexible interconnect cable. The fabrication process was optimized at wafer level, and several neural probes with 64 gold electrode sites equally distributed along 8 shanks with an integrated 8 µm thick highly flexible polyimide interconnect cable were produced. The monolithic integration of the polyimide cable in the same fabrication process removed the necessity of the postfabrication bonding of the cable to the probe. This is the highest electrode site density and thinnest flexible cable ever reported for a hybrid silicon/polymer probe. Additionally, to avoid the time-consuming bonding of the probe to definitive packaging, the flexible cable was designed to terminate in a connector pad that can mate with commercial zero-insertion force (ZIF) connectors for electronics interfacing. This allows great experimental flexibility because interchangeable packaging can be used according to experimental demands. High-density distributed in vivo electrophysiological recordings were obtained from the hybrid neural probes with low intrinsic noise and high signal-to-noise ratio (SNR).
Distributed Beamforming and Power Allocation for Heterogeneous Networks with MISO Interference Channel
Authors: Lee Kisong
Published: April 2021

To address the limitations of centralized resource allocation, i.e., high computational complexity and signaling overhead, a distributed beamforming and power allocation strategy is proposed for heterogeneous networks with multiple-input-single-output (MISO) interference channels. In the proposed scheme, each secondary user transceiver pair (SU TP) determines the beamforming vector and transmits power to maximize its own spectral efficiency (SE) while keeping the interference to the primary user below a predetermined threshold, and such resource management for each SU TP is updated iteratively without any information sharing until the strategies for all SU TPs converge. The simulation confirms that the proposed scheme can achieve a performance comparable to that of a centralized approach with a much lower computation time, e.g., less than 5% degradation in SE while improving computation time by more than 10 times.
U-Infuse: Democratization of Customizable Deep Learning for Object Detection
Authors: Shepley Andrew , Falzon Greg , Lawson Christopher , Meek Paul , Kwan Paul
Published: April 2021

Image data is one of the primary sources of ecological data used in biodiversity conservation and management worldwide. However, classifying and interpreting large numbers of images is time and resource expensive, particularly in the context of camera trapping. Deep learning models have been used to achieve this task but are often not suited to specific applications due to their inability to generalise to new environments and inconsistent performance. Models need to be developed for specific species cohorts and environments, but the technical skills required to achieve this are a key barrier to the accessibility of this technology to ecologists. Thus, there is a strong need to democratize access to deep learning technologies by providing an easy-to-use software application allowing non-technical users to train custom object detectors. U-Infuse addresses this issue by providing ecologists with the ability to train customised models using publicly available images and/or their own images without specific technical expertise. Auto-annotation and annotation editing functionalities minimize the constraints of manually annotating and pre-processing large numbers of images. U-Infuse is a free and open-source software solution that supports both multiclass and single class training and object detection, allowing ecologists to access deep learning technologies usually only available to computer scientists, on their own device, customised for their application, without sharing intellectual property or sensitive data. It provides ecological practitioners with the ability to (i) easily achieve object detection within a user-friendly GUI, generating a species distribution report, and other useful statistics, (ii) custom train deep learning models using publicly available and custom training data, (iii) achieve supervised auto-annotation of images for further training, with the benefit of editing annotations to ensure quality datasets. Broad adoption of U-Infuse by ecological practitioners will improve ecological image analysis and processing by allowing significantly more image data to be processed with minimal expenditure of time and resources, particularly for camera trap images. Ease of training and use of transfer learning means domain-specific models can be trained rapidly, and frequently updated without the need for computer science expertise, or data sharing, protecting intellectual property and privacy.
Artefact Detection in Impedance Pneumography Signals: A Machine Learning Approach
Authors: Moeyersons Jonathan , Morales John , Seeuws Nick , Van Hoof Chris , Hermeling Evelien , Groenendaal Willemijn , Willems Rik , Van Huffel Sabine , Varon Carolina
Published: April 2021

Impedance pneumography has been suggested as an ambulatory technique for the monitoring of respiratory diseases. However, its ambulatory nature makes the recordings more prone to noise sources. It is important that such noisy segments are identified and removed, since they could have a huge impact on the performance of data-driven decision support tools. In this study, we investigated the added value of machine learning algorithms to separate clean from noisy bio-impedance signals. We compared three approaches: a heuristic algorithm, a feature-based classification model (SVM) and a convolutional neural network (CNN). The dataset consists of 47 chronic obstructive pulmonary disease patients who performed an inspiratory threshold loading protocol. During this protocol, their respiration was recorded with a bio-impedance device and a spirometer, which served as a gold standard. Four annotators scored the signals for the presence of artefacts, based on the reference signal. We have shown that the accuracy of both machine learning approaches (SVM: 87.77 ± 2.64% and CNN: 87.20 ± 2.78%) is significantly higher, compared to the heuristic approach (84.69 ± 2.32%). Moreover, no significant differences could be observed between the two machine learning approaches. The feature-based and neural network model obtained a respective AUC of 92.77±2.95% and 92.51±1.74%. These findings show that a data-driven approach could be beneficial for the task of artefact detection in respiratory thoracic bio-impedance signals.
Validity and Reliability of Mobile Applications for Assessing Strength, Power, Velocity, and Change-of-Direction: A Systematic Review
Authors: Silva Rui , Rico-González Markel , Lima Ricardo , Akyildiz Zeki , Pino-Ortega José , Clemente Filipe Manuel
Published: April 2021

This systematic review aimed to (1) identify and summarize studies that have examined the validity of apps for measuring human strength, power, velocity, and change-of-direction, and (2) identify and summarize studies that have examined the reliability of apps for measuring human strength, power, velocity, and change-of-direction. A systematic review of Cochrane Library, EBSCO, PubMed, Scielo, Scopus, SPORTDiscus, and Web of Science databases was performed, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. From the 435 studies initially identified, 23 were fully reviewed, and their outcome measures were extracted and analyzed. In total, 11 mobile applications were analyzed and summarized for their validity and reliability to test movement velocity, movement time, movement displacement, power output, and workload. The present systematic review revealed that the tested apps are valid and reliable for measuring bar movement velocity during lower and upper body resistance exercises; however, systematic bias was detected with heavier loads.
Visibility Restoration: A Systematic Review and Meta-Analysis
Authors: Ngo Dat , Lee Seungmin , Ngo Tri Minh , Lee Gi-Dong , Kang Bongsoon
Published: April 2021

Image acquisition is a complex process that is affected by a wide variety of internal and environmental factors. Hence, visibility restoration is crucial for many high-level applications in photography and computer vision. This paper provides a systematic review and meta-analysis of visibility restoration algorithms with a focus on those that are pertinent to poor weather conditions. This paper starts with an introduction to optical image formation and then provides a comprehensive description of existing algorithms as well as a comparative evaluation. Subsequently, there is a thorough discussion on current difficulties that are worthy of a scientific effort. Moreover, this paper proposes a general framework for visibility restoration in hazy weather conditions while using haze-relevant features and maximum likelihood estimates. Finally, a discussion on the findings and future developments concludes this paper.
Multi-Objective Whale Optimization Algorithm for Computation Offloading Optimization in Mobile Edge Computing
Authors: Huang Mengxing , Zhai Qianhao , Chen Yinjie , Feng Siling , Shu Feng
Published: April 2021

Computation offloading is one of the most important problems in edge computing. Devices can transmit computation tasks to servers to be executed through computation offloading. However, not all the computation tasks can be offloaded to servers with the limitation of network conditions. Therefore, it is very important to decide quickly how many tasks should be executed on servers and how many should be executed locally. Only computation tasks that are properly offloaded can improve the Quality of Service (QoS). Some existing methods only focus on a single objection, and of the others some have high computational complexity. There still have no method that could balance the targets and complexity for universal application. In this study, a Multi-Objective Whale Optimization Algorithm (MOWOA) based on time and energy consumption is proposed to solve the optimal offloading mechanism of computation offloading in mobile edge computing. It is the first time that MOWOA has been applied in this area. For improving the quality of the solution set, crowding degrees are introduced and all solutions are sorted by crowding degrees. Additionally, an improved MOWOA (MOWOA2) by using the gravity reference point method is proposed to obtain better diversity of the solution set. Compared with some typical approaches, such as the Grid-Based Evolutionary Algorithm (GrEA), Cluster-Gradient-based Artificial Immune System Algorithm (CGbAIS), Non-dominated Sorting Genetic Algorithm III (NSGA-III), etc., the MOWOA2 performs better in terms of the quality of the final solutions.
SiLiF Neutron Counters to Monitor Nuclear Materials in the MICADO Project
Authors: Cosentino Luigi , Ducasse Quentin , Giuffrida Martina , Lo Meo Sergio , Longhitano Fabio , Marchetta Carmelo , Massara Antonio , Pappalardo Alfio , Passaro Giuseppe , Russo Salvatore , Finocchiaro Paolo
Published: April 2021

In the framework of the MICADO (Measurement and Instrumentation for Cleaning And Decommissioning Operations) European Union (EU) project, aimed at the full digitization of low- and intermediate-level radioactive waste management, a set of 32 solid state thermal neutron detectors named SiLiF has been built and characterized. MICADO encompasses a complete active and passive characterization of the radwaste drums with neutrons and gamma rays, followed by a longer-term monitoring phase. The SiLiF detectors are suitable for the monitoring of nuclear materials and can be used around radioactive waste drums possibly containing small quantities of actinides, as well as around spent fuel casks in interim storage or during transportation. Suitable polyethylene moderators can be exploited to better shape the detector response to the expected neutron spectrum, according to Monte Carlo simulations that were performed. These detectors were extensively tested with an AmBe neutron source, and the results show a quite uniform and reproducible behavior.
How to Improve Urban Intelligent Traffic? A Case Study Using Traffic Signal Timing Optimization Model Based on Swarm Intelligence Algorithm
Authors: Fu Xiancheng , Gao Hengqiang , Cai Hongjuan , Wang Zhihao , Chen Weiming
Published: April 2021

Traffic congestion is a major problem in today’s society, and the intersection, as an important hub of urban traffic, is one of the most common places to produce traffic congestion. To alleviate the phenomenon of congestion at urban traffic intersections and relieve the traffic pressure at intersections, this paper takes the traffic flow at intersections as the research object and adopts the swarm intelligent algorithm to establish an optimization model of intersection traffic signal timing, which takes the average delay time of vehicles, the average number of stops of vehicles and the traffic capacity as the evaluation indexes. This model adjusts the intersection traffic signal timing intelligence according to the real-time traffic flow and carries out simulation experiments with MATLAB. Compared with the traditional timing schemes, the average delay time of vehicles is reduced by 10.25%, the average number of stops of vehicles is reduced by 24.55%, and the total traffic capacity of the intersection is increased by 3.56%, which verifies that the scheme proposed in this paper is effective in relieving traffic congestion.
Impact of Regional Environmental Regulations on Taiwanese Investment in Mainland China
Authors: Yang Fang , Gan Qinfan
Published: April 2021

Based on the perspective of regional differences and decentralization, this article investigated the impact of environmental regulations on Taiwanese investment in mainland China from theoretical and empirical perspectives, and analyzed whether local governments are competing to lower environmental standards to attract Taiwanese investment so as to maintain their comparative advantages. This paper constructed a theoretical model through a two-stage game model. With the panel data of each province in Mainland China from 2006 to 2016, the theoretical propositions were empirically tested through the system GMM estimation method. The results show that the environmental regulation policies adopted by the local governments in the mainland have a significant inhibitory effect on the investment volume of Taiwan-funded enterprises, and the interaction between environmental regulations and local tax burden levels also has a negative effect on Taiwanese investment. Local governments have the motive to reduce environmental regulations to attract investment.
Sustainable Applications in Agriculture
Authors: Ruiz-Canales Antonio , García Manuel Ferrández-Villena
Published: April 2021

Recently, the European Commission identified the goal to achieve a double transition—ecological and digital—as one of the greatest challenges on the areas of the planet across various sectors of the society [...]
Improvement of Quality of Higher Education Institutions as a Basis for Improvement of Quality of Life
Authors: Lazić Zorica , Đorđević Aleksandar , Gazizulina Albina
Published: April 2021

This paper aims to propose a quality assessment model for higher education institutions in the technical–technological field and a system for decision support and optimal management strategies for quality improvement. Obtaining research results is based on surveying stakeholders in higher education and obtaining quantitative data regarding key performance indices. Quantitative data and the genetic algorithm method are applied to determine optimal management strategies for quality improvement. Quality in the higher education sector is among the current issues in the academic community. By monitoring and researching the higher education field and analysing the literature and the current situation in the system of higher education in developing countries, it can be concluded that there is no single way to assess the quality of higher education institutions. This knowledge was a good starting point for the research presented in this paper. Accordingly, the findings include developing a system for quality assessment and the ranking of higher education institutions. Additionally, evaluating the relevance of key performance indicators of higher education institutions differs from different stakeholder perspectives. However, it is possible to develop a system for decision support and the selection of the optimal strategy for improving the performance of study programs and higher education institutions with regard to quality. The practical implications include defining a decision support system that enables the adoption of optimal decisions by the management teams of higher education institutions to improve study programs and the performance of the higher education institutions. The presented system may enable the benchmarking, simulation, and verification of different scenarios for improving the quality and performance of higher education institutions. In this paper, the authors analysed the characteristics, benefits, and drawbacks of different ranking systems to develop and introduce a novel ranking system that suggests weights for the ranking criteria and different perspectives regarding new digital age requirements. The model was tested, and the results are presented to demonstrate the advantages of the developed model. The originality of the research lies in the presented novel model that can be made available to government institutions and serve as a basis for the overall ranking and evaluation of higher education institutions, with the possibility of developing a performance-based funding system. Additionally, other stakeholders can gain an insight into the performance of an institution in relation to their needs and goals.
Do Household Time, Risk, and Social Preferences Affect Home Energy Retrofit Decisions in Korea?
Authors: Kim Jihyo , Nam Suhyeon
Published: April 2021

Paying attention to impacts of behavioral factor on energy efficiency (EE) investments, this study attempts to identify preference characteristics affecting EE investments. We model households’ EE investments with time, risk, and social preferences, conduct a survey, and empirically examine the effects of the preference characteristics on home energy retrofit decisions in Korea. We find that the research hypotheses for risk and social preferences that we are derived from the model are supported while those for time preference are partially supported. The results are summarized as follows. First, respondents who discount the future more heavily are less likely to plan a home energy retrofit. Second, very risk-averse respondents are less likely to have experienced a home energy retrofit and very risk-seeking ones are more likely to plan a home energy retrofit. Third, those seriously concerned about environmental issues or who strongly respond to moral norms are likely to have experienced or plan a home energy retrofit.
Study on the Farmland Improvement Effect of Drainage Measures under Film Mulch with Drip Irrigation in Saline–Alkali Land in Arid Areas
Authors: Zhao Li , Heng Tong , Yang Lili , Xu Xuan , Feng Yue
Published: April 2021

Water scarcity and imbalances in irrigation and drainage are the main factors leading to soil salinization in arid areas. There is a recognized need for effective drainage measures to prevent and improve saline−alkali land. The principal objective of this project was to investigate the effects of drainage measures on soil desalination and farmland drainage in the process of improving saline–alkali soils; these measures included subsurface pipe drainage (SPD) and open ditch drainage (ODD). The results of the tests, conducted over two years, revealed that the soil desalination rate in the SPD test area was between 25.8% and 35.2%, the cotton emergence rate was 36.7%, and a 3.8 t hm−2 seed cotton yield could be obtained. The soil electrolytic conductivity (EC) decreased step by step over time, and the average annual decrease reached 10 dS m−1. The degree of soil salinization was reduced from a moderately saline soil level (8−15 dS m−1) to a weakly saline soil level (4–8 dS m−1). Thus, the phased goal of improving saline–alkali land was achieved. The soil desalination rate in the ODD test area was only 1/10 of the SPD area; high soil EC (9−12 dS m−1) and groundwater level (2–3 m) were the most limiting factors affecting cotton growth in the ODD test area. The current results show that the critical depth of groundwater level affecting farmland secondary salinization is 4 m. In order to improve the salt discharge standard, SPD technology should be used on the basis of ODD. For salt that has accumulated in the soil for a long time, the technical mode of drip irrigation and leaching, followed by SPD drainage, in combination with the current irrigation system can achieve the goal of sustainable agriculture development.
The Heterogeneity Research of the Impact of EPU on Environmental Pollution: Empirical Evidence Based on 15 Countries
Authors: Chen Ying , Shen Xiaoqian , Wang Li
Published: April 2021

While economic growth has been the main goal of countries around the world, environmental problems such as air pollution have also arisen. Since the increase in economic uncertainty is limiting production capacity and consumers’ marginal propensity to consume, which reduces CO2 emissions, economic policy uncertainty has become one of the most important factors affecting CO2 emissions. COVID-19 has demonstrated that economic policy uncertainty reduces the enthusiasm of market participants, which, in turn, reduces energy demand and CO2 emissions. In order to further study the impact of economic policy uncertainty on air pollution, this study uses a panel model to empirically test the data for a sample of 15 countries covering the period from 1997 to 2019. According to the empirical results, we find that the economic policy uncertainty has a significant negative impact on per capita CO2 emissions. That is, the higher the uncertainty of economic policy, the lower the per capita CO2 emissions of countries. What’s more, this negative effect is larger in emerging market countries than in advanced countries.