bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of Lachancea thermotolerans on Chemical Composition and Sensory Profiles of Viognier Wines
Authors: Hranilovic Ana , Albertin Warren , Capone Dimitra L. , Gallo Adelaide , Grbin Paul R. , Danner Lukas , Bastian Susan E. P. , Masneuf-Pomarede Isabelle , Coulon Joana , Bely Marina , Jiranek Vladimir
Published: May 2022

Viognier is a warm climate grape variety prone to loss of acidity and accumulation of excessive sugars. The yeast Lachancea thermotolerans can improve the stability and balance of such wines due to the partial conversion of sugars to lactic acid during alcoholic fermentation. This study compared the performance of five L. thermotolerans strains in co-inoculations and sequential inoculations with Saccharomyces cerevisiae in high sugar/pH Viognier fermentations. The results highlighted the dichotomy between the non-acidified and the bio-acidified L. thermotolerans treatments, with either comparable or up to 0.5 units lower pH relative to the S. cerevisiae control. Significant differences were detected in a range of flavour-active yeast volatile metabolites. The perceived acidity mirrored the modulations in wine pH/TA, as confirmed via “Rate-All-That-Apply” sensory analysis. Despite major variations in the volatile composition and acidity alike, the varietal aromatic expression (i.e., stone fruit aroma/flavour) remained conserved between the treatments.
Public Perspectives on Exposure Notification Apps: A Patient and Citizen Co-Designed Study
Authors: Osmanlliu Esli , Paquette Jesseca , Rodriguez Duarte Maria Alejandra , Bédard Sylvain , de Marcellis-Warin Nathalie , Zhegu Majlinda , Régis Catherine , Bouthillier Marie-Eve , Grenier Annie-Danielle , Lewis Paul , Pomey Marie-Pascale
Published: May 2022

Canada deployed a digital exposure notification app (COVID Alert) as a strategy to support manual contact tracing. Our aims are to (1) assess the use, knowledge, and concerns of the COVID Alert app, (2) identify predictors of app downloads, and (3) develop strategies to promote social acceptability. A 36-item questionnaire was co-designed by 12 citizens and patients partnered with 16 academic researchers and was distributed in the province of Québec, Canada, from May 27 to 28 June 2021. Of 959 respondents, 43% had downloaded the app. Messaging from government sources constituted the largest influence on app download. Infrequent social contacts and perceived app inefficacy were the main reasons not to download the app. Cybersecurity, data confidentiality, loss of privacy, and geolocation were the most frequent concerns. Nearly half of the respondents inaccurately believed that the app used geolocation. Most respondents supported citizen involvement in app development. The identified predictors for app uptake included nine characteristics. In conclusion, this project highlights four key themes on how to promote the social acceptability of such tools: (1) improved communication and explanation of key app characteristics, (2) design features that incentivize adoption, (3) inclusive socio-technical features, and (4) upstream public partnership in development and deployment.
Task-Rate-Related Neural Dynamics Using Wireless EEG to Assist Diagnosis and Intervention Planning for Preschoolers with ADHD Exhibiting Heterogeneous Cognitive Proficiency
Authors: Chen I-Chun , Chen Chia-Ling , Chang Chih-Hao , Fan Zuo-Cian , Chang Yang , Lin Cheng-Hsiu , Ko Li-Wei
Published: May 2022

This study used a wireless EEG system to investigate neural dynamics in preschoolers with ADHD who exhibited varying cognitive proficiency pertaining to working memory and processing speed abilities. Preschoolers with ADHD exhibiting high cognitive proficiency (ADHD-H, n = 24), those with ADHD exhibiting low cognitive proficiency (ADHD-L, n = 18), and preschoolers with typical development (TD, n = 31) underwent the Conners’ Kiddie Continuous Performance Test and wireless EEG recording under different conditions (rest, slow-rate, and fast-rate task). In the slow-rate task condition, compared with the TD group, the ADHD-H group manifested higher delta and lower beta power in the central region, while the ADHD-L group manifested higher parietal delta power. In the fast-rate task condition, in the parietal region, ADHD-L manifested higher delta power than those in the other two groups (ADHD-H and TD); additionally, ADHD-L manifested higher theta as well as lower alpha and beta power than those with ADHD-H. Unlike those in the TD group, the delta power of both ADHD groups was enhanced in shifting from rest to task conditions. These findings suggest that task-rate-related neural dynamics contain specific neural biomarkers to assist clinical planning for ADHD in preschoolers with heterogeneous cognitive proficiency. The novel wireless EEG system used was convenient and highly suitable for clinical application.
Cone-Beam Navigation Can Reduce the Radiation Exposure and Save Fusion Length-Dependent Operation Time in Comparison to Conventional Fluoroscopy in Pedicle-Screw-Based Lumbar Interbody Fusion
Authors: Rohe Sebastian , Strube Patrick , Hölzl Alexander , Böhle Sabrina , Zippelius Timo , Lindemann Chris
Published: May 2022

This study investigates the advantages and disadvantages of cone-beam-based navigated standardized posterior lumbar interbody fusion surgery (PLIF), regarding the radiation exposure and perioperative time management, compared to the use of fluoroscopy. Patients treated receiving an elective one- to three-level PLIF were retrospectively enrolled in the study. The surgery time, preparation time, operation room time, and effective dose (mSv) were analyzed for comparison of the radiation exposure and time consumption between cone-beam and fluoroscopy; Results: 214 patients were included (108 cone-beam navigated, and 106 traditional fluoroscopies). Using cone-beam navigation, reductions in the effective dose (2.23 ± 1.96 mSv vs. 3.39 ± 2.32 mSv, p = 0.002) and mean surgery time of 30 min (143.62 ± 43.87 min vs. 171.10 ± 48.91 min, p < 0.001) were demonstrated, which leveled out the extended preparation time of 7–8 min (37.25 ± 9.99 min vs. 29.65 ± 7.69 min, p < 0.001). These effects were fusion length dependent and demonstrated additional benefits in multisegmental surgeries. The cone-beam navigation system led to a reduction in the perioperative time requirements and radiation exposure. Furthermore, the controversially discussed longer preparation time when using cone-beam navigation was amortized by a shortened surgery time, especially in multilevel surgery.
Personalized Care and Treatment Compliance in Chronic Conditions
Authors: Fernandes Júlio Belo , Teixeira Fábio , Godinho Catarina
Published: May 2022

Chronic diseases are commonly defined as conditions that last one year or more and require ongoing medical attention, limit activities of daily living, or both [...]
Novel Thienyl-Based Tyrosine Kinase Inhibitors for the Treatment of Hepatocellular Carcinoma
Authors: Ma Andi , Biersack Bernhard , Goehringer Nils , Nitzsche Bianca , Höpfner Michael
Published: May 2022

New medical treatments are urgently needed for advanced hepatocellular carcinoma (HCC). Recently, we showed the anticancer effects of novel thiophene-based kinase inhibitors. In this study, we further characterized the antineoplastic effects and modes of action of the two most promising inhibitors, Thio-Iva and Thio-Dam, and compared their effects with the clinically relevant multi-kinase inhibitor, sorafenib, in HCC cells. Crystal violet staining and real-time cell growth monitoring showed pronounced antiproliferative effects in Huh-7 and SNU-449 cells with IC50 values in the (sub-)micromolar range. Long-term incubation experiments revealed the reduced clonogenicity of Thio-Iva and Thio-Dam-treated HCC cells. LDH-release tests excluded cytotoxicity as an unspecific mode of action of the inhibitors, while flow cytometry analysis revealed a dose-dependent and pronounced G2/M phase cell cycle arrest and cyclin B1 suppression. Additionally, mitochondria-driven apoptosis was observed through the cytosolic increase of reactive oxygen species, a concomitant PARP cleavage, and caspase-3 induction. Both compounds were found to effectively inhibit the capillary tube formation of endothelial EA.hy926 cells in vitro, pointing towards additional antiangiogenic effects. Antiangiogenic and antineoplastic effects were confirmed in vivo by CAM assays. In summary, the thienyl-acrylonitrile derivatives, Thio-Iva and Thio-Dam, exert significant antineoplastic and antiangiogenic effects in HCC cells.
Improved Coffee Management by Farmers in State Forest Plantations in Indonesia: An Experimental Platform
Authors: Rowe Rebecca L. , Prayogo Cahyo , Oakley Simon , Hairiah Kurniatun , van Noordwijk Meine , Wicaksono Karuniawan Puji , Kurniawan Syahrul , Fitch Alice , Cahyono Edi Dwi , Suprayogo Didik , McNamara Niall P.
Published: May 2022

The Indonesian state forest managers have accepted farmer-managed coffee agroforestry in their estates as part of their social forestry program. Access by local farming communities to state-owned plantation forestry supports public motivation to maintain forest cover. However, balancing the expectations and needs of forest managers with those of the local farming communities is not easy. Coffee yields in Indonesia are lower than those of neighboring countries, suggesting that there is scope for improvement. Here we describe an experimental research platform developed through an international collaboration between the Universitas Brawijaya (UB), the UK Centre for Ecology and Hydrology (UKCEH), and smallholder coffee farmers to explore options for improving pine-coffee agroforestry systems within existing regulations. Located in a former state-owned pine production forest on the slopes of the stratovolcano, Mount Arjuna, in the Malang Regency of East Java, the research platform has seven instrumented research plots (40 × 60 m2), where agronomic practices can be trialed. The aim of the platform is to support the development of sustainable agronomic practices to improve the profitability of coffee agroforestry and thus the livelihood of low-income rural communities. Current trials are focused on improving coffee yields and include pine canopy trimming, fertilizers, and coffee pruning trials, with links to the development of socio-economic and environmental models. Whilst it is too early to assess the full impacts on yields, a survey of farmers demonstrated a positive attitude to canopy pruning, although with some concern over labor cost. The initial ecosystem modelling has highlighted the benefits of coffee agroforestry in balancing environmental and economic benefits. Here we provide a detailed description of the site, the current trials, and the modelling work, with the hope of highlighting opportunities for future collaboration and innovation.
Severe Drought Monitoring by Remote Sensing Methods and Its Impact on Wetlands Birds Assemblages in Nuntași and Tuzla Lakes (Danube Delta Biosphere Reserve)
Authors: Jitariu Vasile , Dorosencu Alexandru , Ichim Pavel , Ion Constantin
Published: May 2022

The present paper aims to highlight the impact of the partial or total drying of the Nuntași and Tuzla lakes (from the Danube Delta Biosphere Reserve) as a result of intense drought phenomena on groups of waterfowl that are encountered in this region. Our analysis combined satellite remote sensing techniques with bird observations that were made monthly during the analyzed period, corroborated with the meteorological context of the time interval that was taken into account. The results of the satellite image processing show a partial drying in 2013 and a total drying in 2020 of the Nuntași and Tuzla lakes, which were caused by both natural factors (drought) and anthropogenic factors (inadequate management of the area—e.g.,: communication channels with surrounding lakes are clogged). These situations have led to repercussions for groups of birds, which behave differently depending on their ecology. Pelicans and swans are the most affected birds, they leave the area in the absence of water, whereas gulls and terns are not affected by the decrease in the water surface, they even increase their numbers in such conditions. Our study also shows that from 2010 to 2020 the largest numbers of birds (total numbers of birds), with the exception of pelicans, were recorded in 2013 and 2020, more precisely in the years when the water surface decreased considerably. Another important feature of this paper involves highlighting how fragile an ecosystem can be in the context of climate change, but also how important it is to involve human society in maintaining the adequate conditions for an ecosystem that is part of one of the most important biodiversity hotspots on the planet, the Danube Delta Biosphere Reserve.
Multifunction Land Use to Promote Energy Communities in Mediterranean Region: Cases of Egypt and Italy
Authors: Abouaiana Ahmed , Battisti Alessandra
Published: May 2022

Mediterranean rural settlements suffer from numerous environmental challenges, specifically the annual decrease of the farmlands, climate change threats, and growing resource consumption and demand, such as energy, the core of development. Rural areas play a significant role in achieving food security and sustainable development. Therefore, this paper promotes the energy community and agrivoltaic key concepts as pillars to show how buildings and farms’ land uses positively impact the ecosystem. The study focused on Egypt and Italy as representatives of the entire region. Two rural settlements with the same characteristics representing typical agriculture-based patterns have been selected: Lasaifar Albalad, representing 339 villages in the Delta Region, northern Egypt, and Pontinia, representing rural typologies of the 1930s in the Lazio Region, central Italy. Then, two focus groups with versatile stakeholders were conducted. The results showed the juxtaposition of the key concepts and national rural and agricultural policies and fostered a novel approach between Egypt and Italy. The study presented the first analysis of both contexts. The focus groups promoted the ideas, led to a better understanding of the implementation possibilities, raised awareness, improved social acceptance, and highlighted the significant barriers. It paved the way for a further study (micro-scale on-ground practices) to be planned and implemented soon.
Self-Consistent Parameterization of DNA Residues for the Non-Polarizable AMBER Force Fields
Authors: Schneider Amelia L. , Albrecht Amanda V. , Huang Kenneth , Germann Markus W. , Poon Gregory M. K.
Published: May 2022

Fixed-charge (non-polarizable) forcefields are accurate and computationally efficient tools for modeling the molecular dynamics of nucleic acid polymers, particularly DNA, well into the µs timescale. The continued utility of these forcefields depends in part on expanding the residue set in step with advancing nucleic acid chemistry and biology. A key step in parameterizing new residues is charge derivation which is self-consistent with the existing residues. As atomic charges are derived by fitting against molecular electrostatic potentials, appropriate structural models are critical. Benchmarking against the existing charge set used in current AMBER nucleic acid forcefields, we report that quantum mechanical models of deoxynucleosides, even at a high level of theory, are not optimal structures for charge derivation. Instead, structures from molecular mechanics minimization yield charges with up to 6-fold lower RMS deviation from the published values, due to the choice of such an approach in the derivation of the original charge set. We present a contemporary protocol for rendering self-consistent charges as well as optimized charges for a panel of nine non-canonical residues that will permit comparison with literature as well as studying the dynamics of novel DNA polymers.
Perfusion Visualization during Ileal J-Pouch Formation—A Proposal for the Standardization of Intraoperative Imaging with Indocyanine Green Near-Infrared Fluorescence and a Postoperative Follow-Up in IBD Surgery
Authors: Lobbes Leonard A. , Berns Susanne , Warschkow René , Schmidt Leonard R. , Schineis Christian , Strobel Rahel M. , Lauscher Johannes C. , Beyer Katharina , Weixler Benjamin
Published: May 2022

Background: An anastomotic leak (AL) after a restorative proctocolectomy and an ileal J-pouch increases morbidity and the risk of pouch failure. Thus, a perfusion assessment during J-pouch formation is crucial. While indocyanine green near-infrared fluorescence (ICG-NIRF) has shown potential to reduce ALs, its suitability in a restorative proctocolectomy remains unclear. We aimed to develop a standardized approach for investigating ICG-NIRF and ALs in pouch surgery. Methods: Patients undergoing a restorative proctocolectomy with an ileal J-pouch for ulcerative colitis at an IBD-referral-center were included in a prospective study in which an AL within 30 postoperative days was the primary outcome. Intraoperatively, standardized perfusion visualization with ICG-NIRF was performed and video recorded for postoperative analysis at three time points. Quantitative clinical and technical variables (secondary outcome) were correlated with the primary outcome by descriptive analysis and logistic regression. A novel definition and grading of AL of the J-pouch was applied. A postoperative pouchoscopy was routinely performed to screen for AL. Results: Intraoperative ICG-NIRF-visualization and its postoperative visual analysis in 25 patients did not indicate an AL. The anastomotic site after pouch formation appeared completely fluorescent with a strong fluorescence signal (category 2) in all cases of ALs (4 of 25). Anastomotic site was not changed. ICG-NIRF visualization was reproducible and standardized. Logistic regression identified a two-stage approach vs. a three-stage approach (Odds ratio (OR) = 20.00, 95% confidence interval [CI] = 1.37–580.18, p = 0.029) as a risk factor for ALs. Conclusion: We present a standardized, comparable approach of ICG-NIRF visualization in pouch surgery. Our data indicate that the visual interpretation of ICG-NIRF alone may not detect ALs of the pouch in all cases—quantifiable, objective methods of interpretation may be required in the future.
MegaD: Deep Learning for Rapid and Accurate Disease Status Prediction of Metagenomic Samples
Authors: Mreyoud Yassin , Song Myoungkyu , Lim Jihun , Ahn Tae-Hyuk
Published: May 2022

The diversity within different microbiome communities that drive biogeochemical processes influences many different phenotypes. Analyses of these communities and their diversity by countless microbiome projects have revealed an important role of metagenomics in understanding the complex relation between microbes and their environments. This relationship can be understood in the context of microbiome composition of specific known environments. These compositions can then be used as a template for predicting the status of similar environments. Machine learning has been applied as a key component to this predictive task. Several analysis tools have already been published utilizing machine learning methods for metagenomic analysis. Despite the previously proposed machine learning models, the performance of deep neural networks is still under-researched. Given the nature of metagenomic data, deep neural networks could provide a strong boost to growth in the prediction accuracy in metagenomic analysis applications. To meet this urgent demand, we present a deep learning based tool that utilizes a deep neural network implementation for phenotypic prediction of unknown metagenomic samples. (1) First, our tool takes as input taxonomic profiles from 16S or WGS sequencing data. (2) Second, given the samples, our tool builds a model based on a deep neural network by computing multi-level classification. (3) Lastly, given the model, our tool classifies an unknown sample with its unlabeled taxonomic profile. In the benchmark experiments, we deduced that an analysis method facilitating a deep neural network such as our tool can show promising results in increasing the prediction accuracy on several samples compared to other machine learning models.
Appetite in Palliative Cancer Patients and Its Association with Albumin, CRP and Quality of Life in Men and Women—Cross-Sectional Data from the Palliative D-Study
Authors: Goodrose-Flores Charlotte , Bonn Stephanie , Klasson Caritha , Helde Frankling Maria , Trolle Lagerros Ylva , Björkhem-Bergman Linda
Published: May 2022

Albumin is an important biochemical marker in palliative cancer care, used for assessment of nutritional status, disease severity and prognosis. Our primary aim was to investigate sex differences in the association between appetite and albumin levels in palliative cancer patients. We also aimed to study associations between appetite and C-reactive protein (CRP), Quality of Life (QoL), pain and fatigue. In the Palliative D-cohort, consisting of 266 men and 264 women, we found a correlation between appetite and albumin; low appetite, measured with the Edmonton Symptom Assessment System, correlated significantly with low albumin in men: (r = −0.33, p < 0.001), but not in women (r = −0.03, p = 0.65). In a regression analysis adjusted for confounding factors, results were similar. Lower appetite was correlated with higher CRP in men (r = 0.27, p < 0.001), but not in women (r = 0.12, p = 0.05). Appetite was correlated with QoL, fatigue and pain in both men and women; those with a low appetite had a low QoL and high fatigue- and pain-scores (p < 0.001). In conclusion, our results indicated possible sex differences in the associations between appetite and albumin, and between appetite and CRP, in palliative care patients. Understanding these associations could provide additional value for clinical practice.
N-Methyl-D-Aspartate (NMDA) Receptors in the Prelimbic Cortex Are Required for Short- and Long-Term Memory Formation in Trace Fear Conditioning
Authors: Park Eui-Ho , Kim Nam-Soo , Lee Yeon-Kyung , Choi June-Seek
Published: May 2022

Accumulating evidence suggests that the medial prefrontal cortex (mPFC) has been implicated in the acquisition of fear memory during trace fear conditioning in which a conditional stimulus (CS) is paired with an aversive unconditional stimulus (UCS) separated by a temporal gap (trace interval, TI). However, little is known about the role of the prefrontal cortex for short- and long-term trace fear memory formation. Thus, we investigated how the prelimbic (PL) subregion within mPFC in rats contributes to short- and long-term trace fear memory formation using electrolytic lesions and d,l,-2-amino-5-phosphonovaleric acid (APV), an N-methyl-D-aspartate receptor (NMDAR) antagonist infusions into PL. In experiment 1, pre-conditioning lesions of PL impaired freezing to the CS as well as TI during the acquisition and retrieval sessions, indicating that PL is critically involved in trace fear memory formation. In experiment 2, temporary blockade of NMDA receptors in PL impaired the acquisition, but not the expression of short- and long-term trace fear memory. In addition, the inactivation of NMDAR in PL had little effect on locomotor activity, pre-pulse inhibition (PPI), or shock sensitivity. Taken together, these results suggest that NMDA receptor-mediated neurotransmission in PL is required for the acquisition of trace fear memory.
Customer Perception on Last-Mile Delivery Services Using Kansei Engineering and Conjoint Analysis: A Case Study of Indonesian Logistics Providers
Authors: Restuputri Dian Palupi , Fridawati Ayun , Masudin Ilyas
Published: May 2022

Background: This article identifies the preferences of the customer of logistics services in Indonesia using the Kansei engineering and conjoint analysis methods. The Conjoint Analysis aims to establish utility scores that represent factors in logistics services. Methods: In this study, 100 respondents from several cities in East Java, Indonesia, are selected to fill out the formal questionnaire. At the same time, 30 respondents are chosen to determine the attributes and level attributes. The analysis to determine attributes, level attributes, and formal questionnaires are assisted by SPSS 25. Sixteen stimuli are generated in this study to be used for a formal questionnaire. In this study, Kansei is used to provide a different perspective to describe the customer service, Including six attributes: delivery services, delivery speed, courier attitude, order information, condition of goods, and warehouse locations. Results: The results show that customers’ most preferred attributes are based on the condition of undamaged objects, and the attitude of the courier is vital for users in this study. Conclusions: The most considered instruments by the customer, such as delivery services, delivery speed, courier attitude, order information, condition of goods, and warehouse location.
Stress Distribution on Various Implant-Retained Bar Overdentures
Authors: Kümbüloğlu Övül , Koyuncu Beril , Yerlioğlu Gözde , Al-Haj Husain Nadin , Özcan Mutlu
Published: May 2022

The purpose of this study was to evaluate the effects of various fabrication techniques and materials used in implant-supported mandibular overdentures with a Hader bar attachment over added stress distribution. Three-dimensional geometric solid models, consisting of two implants (3.3 mm × 12 mm) placed at the bone level on both mandibular canine regions and a Hader bar structure, were prepared. Model 1 simulated a bar retentive system made from Titanium Grade 5 material by Computer Numerical Control (CNC) milling technique without using any converting adapter/multi-unit element on the implants, while Model 2 simulated the same configuration, but with converting adapters on the implants. Model 3 simulated a bar retentive system made from Cobalt-Chromium material, made by using conventional casting technique with converting adapters on the implants. Static loads of 100 Newton were applied on test models from horizontal, vertical and oblique directions. ANSYS R15.0 Workbench Software was used to compare Von Mises stress distribution and minimum/maximum principal stress values, and the results were evaluated by using Finite Element Analysis method. As a result, the highest stress distribution values under static loading in three different directions were obtained in Model 1. Stress was observed intensely around the necks of the implants and the surrounding cortical bone areas in all models. In scope of the results obtained, using converting adapters on implants has been considered to decrease transmission of forces onto implants and surrounding bone structures, thus providing a better stress distribution. It has also been observed that the type of material used for bar fabrication has no significant influence on stress values in those models where converting adapters were used.
Influence of Inertial Vlasov Foundation Parameters on the Dynamic Response of the Bernoulli—Euler Beam Subjected to A Group of Moving Forces—Analytical Approach
Authors: Ataman Magdalena , Szcześniak Wacław
Published: May 2022

The subject of this study is the vibration of the Bernoulli–Euler beam on a three-parameter inertial foundation caused by a group of moving forces. The solution to the problem is obtained analytically. The influence of deformable foundation properties on the dynamic response of the beam in the case of forced vibration and the case of free vibration after the load has left the beam is analysed. The influence of velocity on the dynamic response of the beam is also investigated in both cases. The results can be used as a benchmark for calculating more complex engineering structures under moving loads caused by road or railroad vehicles. The results of the investigation are presented in the figures. It is evident that the coefficient determining the foundation inertia has a significant influence on the dynamic deflection of the beam. Taking shear into account in the Vlasov foundation model has little effect on the dynamic deflections of the beam. The equivalent damping number introduced into the Kelvin–Voigt model takes into account the structure damping and mass damping of the beam.
Physicochemical Characterization of Novel Epoxidized Vegetable Oil from Chia Seed Oil
Authors: Dominguez-Candela Ivan , Lerma-Canto Alejandro , Cardona Salvador Cayetano , Lora Jaime , Fombuena Vicent
Published: May 2022

In this study, a novel epoxidized vegetable oil (EVO) from chia seed oil (CSO) has been obtained, with the aim to be employed in a great variety of green products related to the polymeric industry, as plasticizers and compatibilizers. Previous to the epoxidation process characterization, the fatty acid (FA) composition of CSO was analyzed using gas chromatography (GC). Epoxidation of CSO has been performed using peracetic acid formed in situ with hydrogen peroxide and acetic acid, applying sulfuric acid as catalyst. The effects of key parameters as temperature (60, 70, and 75 °C), the molar ratio of hydrogen peroxide:double bond (H2O2:DB) (0.75:1.0 and 1.50:1.0), and reaction time (0–8 h) were evaluated to obtain the highest relative oxirane oxygen yield (Yoo). The evaluation of the epoxidation process was carried out through iodine value (IV), oxirane oxygen content (Oo), epoxy equivalent weight (EEW), and selectivity (S). The main functional groups were identified by means of FTIR and 1H NMR spectroscopy. Physical properties were compared in the different assays. The study of different parameters showed that the best epoxidation conditions were carried out at 75 °C and H2O2:DB (1.50:1), obtaining an Oo value of 8.26% and an EEW of 193 (g·eq−1). These high values, even higher than those obtained for commercial epoxidized oils such as soybean or linseed oil, show the potential of the chemical modification of chia seed oil to be used in the development of biopolymers.
Surface Engineering of Nanomaterials with Polymers, Biomolecules, and Small Ligands for Nanomedicine
Authors: Díez-Pascual Ana M.
Published: May 2022

Nanomedicine is a speedily growing area of medical research that is focused on developing nanomaterials for the prevention, diagnosis, and treatment of diseases. Nanomaterials with unique physicochemical properties have recently attracted a lot of attention since they offer a lot of potential in biomedical research. Novel generations of engineered nanostructures, also known as designed and functionalized nanomaterials, have opened up new possibilities in the applications of biomedical approaches such as biological imaging, biomolecular sensing, medical devices, drug delivery, and therapy. Polymers, natural biomolecules, or synthetic ligands can interact physically or chemically with nanomaterials to functionalize them for targeted uses. This paper reviews current research in nanotechnology, with a focus on nanomaterial functionalization for medical applications. Firstly, a brief overview of the different types of nanomaterials and the strategies for their surface functionalization is offered. Secondly, different types of functionalized nanomaterials are reviewed. Then, their potential cytotoxicity and cost-effectiveness are discussed. Finally, their use in diverse fields is examined in detail, including cancer treatment, tissue engineering, drug/gene delivery, and medical implants.
The Advancement of Neutron-Shielding Materials for the Transportation and Storage of Spent Nuclear Fuel
Authors: Qi Zhengdong , Yang Zhong , Li Jianping , Guo Yongchun , Yang Guichun , Yu Yang , Zhang Jiachen
Published: May 2022

In this paper, the mechanism of neutron absorption and common reinforced particles is introduced, and recent research progress on different types of neutron-shielding materials (borated stainless steels, B/Al Alloy, B4C/Al composites, polymer-based composites, and shielding concrete) for transportation and wet or dry storage of spent fuel is elaborated, and critical performance is summarized and compared. In particular, the most widely studied and used borated stainless steel and B4C/Al composite neutron-absorption materials in the field of spent fuel are discussed at length. The problems and solutions in the preparation and application of different types of neutron-shielding materials for spent fuel transportation and storage are discussed, and their research priorities and development trends are proposed.
Effect of Current Density Ramping on the Growth Rate and Structure of AA2024-T3
Authors: Totaro Peter , Khusid Boris
Published: May 2022

The presented study successfully demonstrated advantages of multistep anodization of AA2024—T3. Coating properties and morphology were studied in detail for five anodization processes: a conventional Base process with a constant applied current density and processes with current density applied in one (OS1 and OS2) and five (MS1 and MS2) steps at different magnitudes during the ramp period. Due to lower oxygen infusion, processes MS1 and MS2 produced a more intact coating with reduced porosity and enhanced abrasion resistance and hardness. The presented results clearly demonstrate that starting anodization at a low voltage and then slowly ramping current density will form coatings with a higher aluminum/oxygen ratio and enhanced properties over a shorter period of processing.
Optimal Synthesis of Loader Drive Mechanisms: A Group Robust Decision-Making Rule Generation Approach
Authors: Petrović Goran , Pavlović Jovan , Madić Miloš , Marinković Dragan
Published: May 2022

The objective of this paper is to present a novel, hybrid group multi-criteria decision approach that can be used to evaluate alternatives for the optimal synthesis of loader drive mechanisms. In most product design engineering groups, experts have expertise in different areas and robust decision-making is necessary to integrate a number of opposing opinions, attitudes, and solutions. This study presents the application of an integrated approach for decision-making, i.e., the generation of a robust decision-making rule for group decision-making (RDMR-G) by combining different multi-criteria decision-making (MCDM) methods and Taguchi’s robust quality engineering principles. The basic idea behind this article was to create an approach that enables the comprehensive and robust consideration of expert opinions given the existence of numerous objective and subjective methods for determining the criteria weights, which are crucial to the final ranking of alternatives in any decision-making problem. In order to set the optimal configuration of a loader drive mechanism, five experts, all with a high level of experience and knowledge in this field, considered twenty-six different kinematic chain construction solutions, i.e., alternatives, and evaluated them with respect to six criteria. The obtained results and rankings provided by each expert and each criteria weighting method were compared using Kendall’s τb and Spearman’s ρ tests. As an example, this paper demonstrates the practical application of a RDMR-G approach and in doing so contributes to the literature in the fields of product design engineering and decision-making.
The Key Role of 3D Printing Technologies in the Further Development of Electrical Machines
Authors: Szabó Loránd , Fodor Dénes
Published: May 2022

There is a strong general demand for the permanent improvement of electrical machines. Nowadays, these are at their near maximum potential, and even small further improvements can only be achieved with great effort and high cost. The single solution should be a paradigm shift in their development, by using radically new approaches to topology, materials, and fabrication. Therefore, the application of diverse 3D printing techniques for advanced fabrication in this field is inevitable. Therefore, these new approaches are receiving a great deal of attention among electrical machines designers. In the paper, the possible applications of these new fabrication technologies in the field of electrical machines are surveyed. The focus is set on emphasizing the advancement over the traditional manufacturing approaches.
Missing Data Estimation in Temporal Multilayer Position-Aware Graph Neural Network (TMP-GNN)
Authors: Najafi Bahareh , Parsaeefard Saeedeh , Leon-Garcia Alberto
Published: May 2022

GNNs have been proven to perform highly effectively in various node-level, edge-level, and graph-level prediction tasks in several domains. Existing approaches mainly focus on static graphs. However, many graphs change over time and their edge may disappear, or the node/edge attribute may alter from one time to the other. It is essential to consider such evolution in the representation learning of nodes in time-varying graphs. In this paper, we propose a Temporal Multilayer Position-Aware Graph Neural Network (TMP-GNN), a node embedding approach for dynamic graphs that incorporates the interdependence of temporal relations into embedding computation. We evaluate the performance of TMP-GNN on two different representations of temporal multilayered graphs. The performance is assessed against the most popular GNNs on a node-level prediction task. Then, we incorporate TMP-GNN into a deep learning framework to estimate missing data and compare the performance with their corresponding competent GNNs from our former experiment, and a baseline method. Experimental results on four real-world datasets yield up to 58% lower ROCAUC for the pair-wise node classification task, and 96% lower MAE in missing feature estimation, particularly for graphs with a relatively high number of nodes and lower mean degree of connectivity.
Estimating the Best Time to View Cherry Blossoms Using Time-Series Forecasting Method
Authors: Horikawa Tomonari , Takahashi Munenori , Endo Masaki , Ohno Shigeyoshi , Hirota Masaharu , Ishikawa Hiroshi
Published: May 2022

In recent years, tourist information collection using the internet has become common. Tourists are increasingly using internet resources to obtain tourist information. Social network service (SNS) users share tourist information of various kinds. Twitter, one SNS, has been used for many studies. We are pursuing research supporting a method using Twitter to help tourists obtain information: estimates of the best time to view cherry blossoms. Earlier studies have proposed a low-cost moving average method using geotagged tweets related to location information. Geotagged tweets are helpful as social sensors for real-time estimation and for the acquisition of local tourist information because the information can reflect real-world situations. Earlier studies have used weighted moving averages, indicating that a person can estimate the best time to view cherry blossoms in each prefecture. This study proposes a time-series prediction method using SNS data and machine learning as a new method for estimating the best times for viewing for a certain period. Combining the time-series forecasting method and the low-cost moving average method yields an estimate of the best time to view cherry blossoms. This report describes results confirming the usefulness of the proposed method by experimentation with estimation of the best time to view beautiful cherry blossoms in each prefecture and municipality.
The Utility of Receiver Operating Characteristic Curve in Educational Assessment: Performance Prediction
Authors: Han Hyunsuk
Published: May 2022

When examinees are classified into groups based on scores from educational assessment, two indices are widely used to gauge the psychometric quality of the classifications: accuracy and consistency. The two indices take correct classifications into consideration while overlooking incorrect ones, where unbalanced class distribution threatens the validity of results from the accuracy and consistency indices. The single values produced from the two indices also fail to address the inconsistent accuracy of the classifier across different cut score locations. The current study proposed the concept of classification quality, which utilizes the receiver operating characteristics (ROC) graph to comprehensively evaluate the performance of classifiers. The ROC graph illustrates the tradeoff between benefits (true positive rate) and costs (false positive rate) in classification. In this article, a simulation study was conducted to demonstrate how to generate and interpret ROC graphs in educational assessment and the benefits of using ROC graphs to interpret classification quality. The results show that ROC graphs provide an efficient approach to (a) visualize the fluctuating performance of scoring classifiers, (b) address the unbalanced class distribution issue inherent in the accuracy and consistency indices, and (c) produce more accurate estimation of the classification results.
Condition Number and Clustering-Based Efficiency Improvement of Reduced-Order Solvers for Contact Problems Using Lagrange Multipliers
Authors: Le Berre Simon , Ramière Isabelle , Fauque Jules , Ryckelynck David
Published: May 2022

This paper focuses on reduced-order modeling for contact mechanics problems treated by Lagrange multipliers. The high nonlinearity of the dual solutions lead to poor classical data compression. A hyper-reduction approach based on a reduced integration domain (RID) is considered. The dual reduced basis is the restriction to the RID of the full-order dual basis, which ensures the hyper-reduced model to respect the non-linearity constraints. However, the verification of the solvability condition, associated with the well-posedness of the solution, may induce an extension of the primal reduced basis without guaranteeing accurate dual forces. We highlight the strong link between the condition number of the projected contact rigidity matrix and the precision of the dual reduced solutions. Two efficient strategies of enrichment of the primal POD reduced basis are then introduced. However, for large parametric variation of the contact zone, the reachable dual precision may remain limited. A clustering strategy on the parametric space is then proposed in order to deal with piece-wise low-rank approximations. On each cluster, a local accurate hyper-reduced model is built thanks to the enrichment strategies. The overall solution is then deeply improved while preserving an interesting compression of both primal and dual bases.
Causal Interactions in Agile Application Development
Authors: Gudas Saulius , Noreika Karolis
Published: May 2022

The Agile approach and tools are popular for the management of Enterprise Application Software (EAS) development. This article focuses on the issue of inconsistency between strategic business objectives and the functionality of the software developed. Agile management tools lack the functionality of EAS project activities coordination. This article aims to rethink Agile project management using the causal modelling approach. A causal model of Agile project management using a management transaction (MT) concept was developed. The notion of the space of processes was used to identify the MTs location along the axes of aggregation, generalization, and time and to formalize their interaction specifications. Taxonomy of the coordination meta-types and types was developed using the identifiers of the MTs. The modified Agile activities hierarchy was developed, and vertical and horizontal causal interactions between Agile activities were identified. This modified Agile management model helps to consistently track the integrity of EAS project content. Complexity indicators were introduced to evaluate the EAS project complexity and their average and normalized values are presented. Additional attributes in the Agile management tool Jira are proposed. Monitoring mismatch between strategic business objectives and development activities content helps to improve the success of EAS projects delivery.
Relaxation Oscillations and Dynamical Properties in a Time Delay Slow–Fast Predator–Prey Model with a Piecewise Smooth Functional Response
Authors: Qian Youhua , Peng Yuhui , Wang Yufeng , Lin Bingwen
Published: May 2022

In the past few decades, the predator–prey model has played an important role in the dynamic behavior of populations. Many scholars have studied the stability of the predator–prey system. Due to the complex influence of time delay on the dynamic behavior of systems, time-delay systems have garnered wide interest. In this paper, a classical piecewise smooth slow–fast predator–prey model is considered. The dynamic properties of the system are analyzed by linearization. The existence and uniqueness of the relaxation oscillation are then proven through the geometric singular perturbation theory and entry–exit function. Finally, a stable limit cycle is obtained. A numerical simulation verifies our results for the systems and shows the effectiveness of the method in dealing with time delays.
Weighted Hermite–Hadamard-Type Inequalities by Identities Related to Generalizations of Steffensen’s Inequality
Authors: Pečarić Josip , Perušić Pribanić Anamarija , Smoljak Kalamir Ksenija
Published: May 2022

In this paper, we obtain some new weighted Hermite–Hadamard-type inequalities for (n+2)−convex functions by utilizing generalizations of Steffensen’s inequality via Taylor’s formula.
Hadamard Product of Certain Multivalent Analytic Functions with Positive Real Parts
Authors: Lashin Abdel Moneim Y. , Aouf Mohamed K.
Published: May 2022

This paper aims to provide sufficient conditions for starlikeness and convexity of Hadamard product (convolution) of certain multivalent analytic functions with positive real parts. Moreover, the starlikeness conditions for a certain integral operator and other convolution results are also considered.
Representing 3/2-Institutions as Stratified Institutions
Authors: Diaconescu Răzvan
Published: May 2022

On the one hand, the extension of ordinary institution theory, known as the theory of stratified institutions, is a general axiomatic approach to model theories where the satisfaction is parameterized by states of the models. On the other hand, the theory of 3/2-institutions is an extension of ordinary institution theory that accommodates the partiality of the signature morphisms and its syntactic and semantic effects. The latter extension is motivated by applications to conceptual blending and software evolution. In this paper, we develop a general representation theorem of 3/2-institutions as stratified institutions. This enables a transfer of conceptual infrastructure from stratified to 3/2-institutions. We provide some examples in this direction.
Multi-Objective Optimal Sizing of HRES under Multiple Scenarios with Undetermined Probability
Authors: Li Kaiwen , Song Yuanming , Wang Rui
Published: May 2022

In recent years, technologies for renewable energy utilization have been booming. Hybrid renewable energy systems (HRESs), integrating multiple energy sources to mitigate the unstable, unpredictable, and intermittent characteristics of a single renewable energy source, have become increasingly popular. However, due to the inherent intermittency and uncertainty of renewable energies, the impact of uncertain factors on the capacity optimization of HRESs needs to be considered. In the traditional scenario-based planning method, when dealing with uncertain factors, the probability corresponding to the scenario is difficult to determine. Furthermore, when applying the robust optimization method, it is difficult to fully use existing data to describe uncertain parameters in the form of intervals. To tackle these difficulties, this study proposes a probability undetermined scenario-based sizing model (PUSS model) for stand-alone HRES configuration optimization and a multi-objective evolutionary algorithm as the problem solver. The solution set obtained by the method covers multiple possible values of scenario probability combinations and can provide decision-makers with an overview of alternatives for HRES sizing under different power supply pressures. Based on the real environment data and load data of a certain place, the proposed model and algorithm are applied to sizing a typical HRES comprising wind generators, solar photovoltaic panels, energy-storage devices, and diesel generators. The experimental results show that the proposed PUSS method is both effective and efficient.