bluuebunny/crossref_metadata_2025 huggingface dataset:
Pharmacovigilance in High-Income Countries: Current Developments and a Review of Literature
Authors: Khan Muhammad Akhtar Abbas , Hamid Saima , Babar Zaheer-Ud-Din
Published: January 2023

The world bank has classified 80 economies based on their Gross National Income (GNI) per capita as High-Income. European Medicines Agency (EMA), Food and Drug Administration (FDA), and Pharmaceuticals and Medical Devices Agency (PMDA) are the major regulatory stakeholders driving global pharmacovigilance regulations. The purpose of this article is to describe pharmacovigilance systems and processes in high-income countries, particularly those that are also members of the International Conference on Harmonization (ICH). All high-income countries are members of the WHO PIDM. The income level of a country has a direct relationship with medicine safety measures. All ten pioneering members of the Uppsala monitoring centre are from high-income countries and were the first responders after the thalidomide tragedy by making drug evaluation committees, introducing the ADR reporting forms and taking safety measures. Despite access to the VigiBase, some countries have separate databases for managing and analyzing data like Canada Vigilance online database, FDA Adverse Event Reporting System, the French pharmacovigilance database and European Union’s system Eudravigilance. All high-income countries have robust pharmacovigilance systems. USFDA and EMA are the world leaders in the field of pharmacovigilance. Most high-income countries follow EMA guidelines. Medicine safety is directly influenced by a country’s income level.
The Poetics of Physics
Authors: Jeynes Chris , Parker Michael C. , Barker Margaret
Published: January 2023

Physics has been thought to truly represent reality since at least Galileo, and the foundations of physics are always established using philosophical ideas. In particular, the elegant naming of physical entities is usually very influential in the acceptance of physical theories. We here demonstrate (using current developments in thermodynamics as an example) that both the epistemology and the ontology of physics ultimately rest on poetic language. What we understand depends essentially on the language we use. We wish to establish our knowledge securely, but strictly speaking this is impossible using only analytic language. Knowledge of the meanings of things must use a natural language designed to express meaning, that is, poetic language. Although the world is really there, and although we can indeed know it truly, this knowledge is never either complete or certain but ultimately must rest on intuition. Reading a recently discovered artefact with a palaeo-Hebrew inscription as from the first century, we demonstrate from it that this ontological understanding long predates the Hellenic period. Poetic language is primary, both logically and temporally.
Tunable Plasmonic Perfect Absorber for Hot Electron Photodetection in Gold-Coated Silicon Nanopillars
Authors: Sun Tangyou , Song Wenke , Qin Zubin , Guo Wenjing , Wangyang Peihua , Zhou Zhiping , Deng Yanrong
Published: January 2023

Infrared detection technology has important applications in laser ranging, imaging, night vision, and other fields. Furthermore, recent studies have proven that hot carriers which are generated by surface plasmon decay can be exploited for photodetection to get beyond semiconductors’ bandgap restriction. In this study, silicon nanopillars (NPs) and gold film at the top and bottom of silicon nanopillars were designed to generate surface plasmon resonance and Fabry–Perot resonance to achieve perfect absorption. The absorption was calculated using the Finite Difference Time Domain (FDTD) method, and factors’ effects on resonance wavelength and absorption were examined. Here we demonstrate how this perfect absorber can be used to achieve near-unity optical absorption using ultrathin plasmonic nanostructures with thicknesses of 15 nm, smaller than the hot electron diffusion length. Further study revealed that the resonance wavelength can be redshifted to the mid-infrared band (e.g., 3.75 μm) by increasing the value of the structure parameters. These results demonstrate a success in the study of polarization insensitivity, detection band adjustable, and efficient perfect absorption infrared photodetectors.
Morpho-Physiological and Biochemical Responses of Field Pea Genotypes under Terminal Heat Stress
Authors: Sharma Vijay , Singh Chandra Mohan , Chugh Vishal , Kamaluddin Kamaluddin , Prajapati Pawan Kumar , Mishra Anuj , Kaushik Prashant , Dhanda Parmdeep Singh , Yadav Alpa , Satyendra Satyendra
Published: January 2023

Field pea is one of the important short-duration cool season pulse crops which contributes significantly towards food and nutritional security. Two heat-susceptible (HS) and two heat-tolerant (HT) genotypes were selected from the previous study for further characterization. A significant variation was observed for morpho-physiological traits studied. Principal component analysis explained that first two principal components, i.e., PC1 and PC2 showed 76.5% of the total variance in optimal condition, whereas 91.2% of the total variance was covered by the first two PCs in heat stress environment. The seed yield per plant determined significant and positive association with superoxide dismutase and number of seeds per pod under optimal conditions, whereas under heat stress condition, it was positively associated with number of effective pods per plant, biological yield per plant, proline, pod length, number of seeds per pod, superoxide dismutase, and peroxidase. The significant reduction was noticed in the susceptible genotypes, whereas tolerant genotypes showed stable and non-significant reduction in chlorophyll content. Further, minimum cell damage and higher hydrogen peroxide production was noticed in the susceptible genotypes. In addition, the biochemical characterization of HS and HT genotypes revealed that the higher expression of peroxidase, superoxide dismutase, and catalase modulates the tolerant responses in HT genotypes. These genotypes were further used in developing heat-tolerant field pea genotypes.
Assessment of Morphological, Anatomical and Palynological Variation in the Medicinal Plant Disporopsis longifolia Craib (Asparagaceae) for Botanical Quality Control
Authors: Sarapan Anuwat , Hodkinson Trevor R. , Suwanphakdee Chalermpol
Published: January 2023

Disporopsis longifolia Craib is an Asian medicinal plant belonging to the Asparagaceae family. The plants are well known for their steroidal saponins and phenolic compounds and are traditionally used as tonics for back pain, bellyache, cough, diabetes, asthma, pneumonia and rheumatism. However, they are challenging to identify to species level using morphology. This raises a serious concern for their medicinal applications where botanical quality control is essential. The most appropriate morphological, anatomical and pollen characters for species diagnosis were therefore determined. Synonyms were identified and lectotypification provided. The morphological characters were described from 76 fresh and dried specimens to include a broad range of materials from differing habitats and locations. Paraffin and peeling methods were applied for anatomical studies of leaves and stems and a modified acetolysis method was undertaken for pollen morphology. This paper compares the new character data to published data from other species in the genus, namely D. aspersa, D. fuscopicta, D. jinfushanensis, D. pernyi and D. undulata. This is the first report of such anatomical and pollen morphology characters for D. longifolia. The results provide accurate morphological, anatomical and palynological characters for quality control and are best applied in combination with each other.
Rice Phytoalexins: Half a Century of Amazing Discoveries; Part I: Distribution, Biosynthesis, Chemical Synthesis, and Biological Activities
Authors: Valletta Alessio , Iozia Lorenzo Maria , Fattorini Laura , Leonelli Francesca
Published: January 2023

Cultivated rice is a staple food for more than half of the world’s population, providing approximately 20% of the world’s food energy needs. A broad spectrum of pathogenic microorganisms causes rice diseases leading to huge yield losses worldwide. Wild and cultivated rice species are known to possess a wide variety of antimicrobial secondary metabolites, known as phytoalexins, which are part of their active defense mechanisms. These compounds are biosynthesized transiently by rice in response to pathogens and certain abiotic stresses. Rice phytoalexins have been intensively studied for over half a century, both for their biological role and their potential application in agronomic and pharmaceutical fields. In recent decades, the growing interest of the research community, combined with advances in chemical, biological, and biomolecular investigation methods, has led to a notable acceleration in the growth of knowledge on rice phytoalexins. This review provides an overview of the knowledge gained in recent decades on the diversity, distribution, biosynthesis, chemical synthesis, and bioactivity of rice phytoalexins, with particular attention to the most recent advances in this research field.
Ecological Impacts of Exotic Species on Native Seed Dispersal Systems: A Systematic Review
Authors: Cordero Sebastián , Gálvez Francisca , Fontúrbel Francisco E.
Published: January 2023

Exotic species are one of the main threats to biodiversity, leading to alterations in the structure and functioning of natural ecosystems. However, they can sometimes also provide ecological services, such as seed dispersal. Therefore, we assessed the ecological impacts of exotic species on native dispersal systems and the mechanisms underlying the disruption of mutualistic plant–disperser interactions. Exotic species negatively affect dispersal mutualisms by (i) altering dispersal behavior and visitation rates of native dispersers, (ii) predating native dispersers, (iii) transmitting forest pathogens, and (iv) predating seeds. Conversely, positive impacts include the dispersal of native plants, forest regeneration, and native habitat restoration via (i) increasing the visitation rates of frugivorous birds, (ii) facilitating the colonization and establishment of native forest trees, (iii) enhancing forest species seedling survival, and (iv) facilitating seed rain and seedling recruitment of early and late successional native plants. The reviewed studies provide similar results in some cases and opposite results in others, even within the same taxa. In almost all cases, exotic species cause negative impacts, although sometimes they are necessary to ensure native species’ persistence. Therefore, exotic species management requires a comprehensive understanding of their ecological roles, since the resulting effects rely on the complexity of native–exotic species interactions.
Metabolomics as a Potential Chemotaxonomical Tool: Application on the Selected Euphorbia Species Growing Wild in Serbia
Authors: Sofrenić Ivana , Anđelković Boban , Gođevac Dejan , Ivanović Stefan , Simić Katarina , Ljujić Jovana , Tešević Vele , Milosavljević Slobodan
Published: January 2023

Chemotaxonomy presents various challenges that need to be overcome in order to obtain valid and reliable results. Individual genetic and environmental variations can give a false picture and lead to wrong conclusions. Applying a holistic approach, based on multivariate data analysis, these challenges can be overcome. Thus, a metabolomics approach has to be optimized depending on the subject of research. We used 1H NMR-based metabolomics as a potential chemotaxonomic tool on the selected Euphorbia species growing wild in Serbia. Principal components analysis (PCA), soft independent modeling by class analogy (SIMCA) and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) were used to analyze obtained NMR data in order to reveal chemotaxonomic biomarkers. The standard protocol for plant metabolomics was optimized aiming to extract more specific metabolites, which are characteristic for the Euphorbia genus. The obtained models were validated, which revealed that variables unique for each species were associated with certain classes of molecules according to literature data. In E. salicifolia, acacetin-7-O-glycoside (not found before in the species) was detected, and the structure of the aglycone part was solved based on 2D NMR data. In the presented paper, we have shown that metabolomics can be successfully used in Euphorbia chemotaxonomy.
Influence of Nitrogen on Grapevine Susceptibility to Downy Mildew
Authors: Marcianò Demetrio , Ricciardi Valentina , Maddalena Giuliana , Massafra Annamaria , Marone Fassolo Elena , Masiero Simona , Bianco Piero Attilio , Failla Osvaldo , De Lorenzis Gabriella , Toffolatti Silvia Laura
Published: January 2023

Downy mildew, caused by the obligate parasite Plasmopara viticola, is one of the most important threats to viticulture. The exploitation of resistant and susceptibility traits of grapevine is one of the most promising ways to increase the sustainability of disease management. Nitrogen (N) fertilization is known for influencing disease severity in the open field, but no information is available on its effect on plant-pathogen interaction. A previous RNAseq study showed that several genes of N metabolism are differentially regulated in grapevine upon P. viticola inoculation, and could be involved in susceptibility or resistance to the pathogen. The aim of this study was to evaluate if N fertilization influences: (i) the foliar leaf content and photosynthetic activity of the plant, (ii) P. viticola infectivity, and (iii) the expression of the candidate susceptibility/resistance genes. Results showed that N level positively correlated with P. viticola infectivity, confirming that particular attention should be taken in vineyard to the fertilization, but did not influence the expression of the candidate genes. Therefore, these genes are manipulated by the pathogen and can be exploited for developing new, environmentally friendly disease management tools, such as dsRNAs, to silence the susceptibility genes or breeding for resistance.
Extracellular CahB1 from Sodalinema gerasimenkoae IPPAS B-353 Acts as a Functional Carboxysomal β-Carbonic Anhydrase in Synechocystis sp. PCC6803
Authors: Minagawa Jun , Dann Marcel
Published: January 2023

Cyanobacteria mostly rely on the active uptake of hydrated CO2 (i.e., bicarbonate ions) from the surrounding media to fuel their inorganic carbon assimilation. The dehydration of bicarbonate in close vicinity of RuBisCO is achieved through the activity of carboxysomal carbonic anhydrase (CA) enzymes. Simultaneously, many cyanobacterial genomes encode extracellular α- and β-class CAs (EcaA, EcaB) whose exact physiological role remains largely unknown. To date, the CahB1 enzyme of Sodalinema gerasimenkoae (formerly Microcoleus/Coleofasciculus chthonoplastes) remains the sole described active extracellular β-CA in cyanobacteria, but its molecular features strongly suggest it to be a carboxysomal rather than a secreted protein. Upon expression of CahB1 in Synechocystis sp. PCC6803, we found that its expression complemented the loss of endogenous CcaA. Moreover, CahB1 was found to localize to a carboxysome-harboring and CA-active cell fraction. Our data suggest that CahB1 retains all crucial properties of a cellular carboxysomal CA and that the secretion mechanism and/or the machinations of the Sodalinema gerasimenkoae carboxysome are different from those of Synechocystis.
Changes in Fatty Acid Content in Solanum spp. Fruits during Ripening
Authors: Staveckienė Jūratė , Kulaitienė Jurgita , Levickienė Dovilė , Vaitkevičienė Nijolė
Published: January 2023

This study aimed to determine the effects of the ripening stage and species on the contents of saturated (SFA), monounsaturated (MUFA), and polyunsaturated (PUFA) fatty acids in Solanum spp. fruits. A two-factor field experiment with four different Solanum spp. species (S. nigrum, S. melanocerasum, S. retroflexum, and S. villosum) and three ripening stages was conducted over two growing seasons (2020–2021). The fatty acid composition of the Solanum fruits was characterized using gas chromatography with a flame ionization detection. The results show that PUFAs are the dominant type of fatty acid in Solanum fruits, followed by MUFAs and SFAs. Overall, the highest PUFA contents were observed in S. nigrum fruits in the ripening stage I, and the highest MUFA and SFA contents were observed in S. melanocerasum fruits during ripening stages I and II, respectively.
Applications of Metabolomics for the Elucidation of Abiotic Stress Tolerance in Plants: A Special Focus on Osmotic Stress and Heavy Metal Toxicity
Authors: Mashabela Manamele Dannies , Masamba Priscilla , Kappo Abidemi Paul
Published: January 2023

Plants undergo metabolic perturbations under various abiotic stress conditions; due to their sessile nature, the metabolic network of plants requires continuous reconfigurations in response to environmental stimuli to maintain homeostasis and combat stress. The comprehensive analysis of these metabolic features will thus give an overview of plant metabolic responses and strategies applied to mitigate the deleterious effects of stress conditions at a biochemical level. In recent years, the adoption of metabolomics studies has gained significant attention due to the growing technological advances in analytical biochemistry (plant metabolomics). The complexity of the plant biochemical landscape requires sophisticated, advanced analytical methods. As such, technological advancements in the field of metabolomics have been realized, aided much by the development and refinement of separatory techniques, including liquid and gas chromatography (LC and GC), often hyphenated to state-of-the-art detection instruments such as mass spectrometry (MS) or nuclear resonance magnetic (NMR) spectroscopy. Significant advances and developments in these techniques are briefly highlighted in this review. The enormous progress made thus far also comes with the dawn of the Internet of Things (IoT) and technology housed in machine learning (ML)-based computational tools for data acquisition, mining, and analysis in the 4IR era allowing for broader metabolic coverage and biological interpretation of the cellular status of plants under varying environmental conditions. Thus, scientists can paint a holistic and comprehensive roadmap and predictive models for metabolite-guided crop improvement. The current review outlines the application of metabolomics and related technological advances in elucidating plant responses to abiotic stress, mainly focusing on heavy metal toxicity and subsequent osmotic stress tolerance.
Genetic Variation of Zinc and Iron Concentration in Normal, Provitamin A and Quality Protein Maize under Stress and Non-Stress Conditions
Authors: Goredema-Matongera Nakai , Ndhlela Thokozile , van Biljon Angeline , Kamutando Casper N. , Cairns Jill E. , Baudron Frederic , Labuschagne Maryke
Published: January 2023

The negative impacts of zinc (Zn) and iron (Fe) deficiency due to over-reliance on monotonous cereal-based diets are well-documented. Increasing micronutrient densities in maize is currently among top breeders’ priorities. Here, 77 single-cross Zn-enhanced hybrids with normal, provitamin A and quality protein maize genetic backgrounds were evaluated together with seven checks for grain Zn and Fe concentration and agronomic traits under optimum, low nitrogen (N) and managed drought conditions. Results showed a fairly wide variability for grain Zn (10.7–57.8 mg kg−1) and Fe (7.1–58.4 mg kg−1) concentration amongst the hybrids, across management conditions. Notable differences in Zn concentration were observed between the Zn-enhanced quality protein maize (QPM) (31.5 mg kg−1), Zn-enhanced provitamin A maize (28.5 mg kg−1), Zn-enhanced normal maize (26.0 mg kg−1) and checks (22.9 mg kg−1). Although checks showed the lowest micronutrient concentration, they were superior in grain yield (GY) performance, followed by Zn-enhanced normal hybrids. Genotypes grown optimally had higher micronutrient concentrations than those grown under stress. Genotype × environment interaction (G × E) was significant (p ≤ 0.01) for GY, grain Zn and Fe concentration, hence micronutrient-rich varieties could be developed for specific environments. Furthermore, correlation between grain Zn and Fe was positive and highly significant (r = 0.97; p ≤ 0.01) suggesting the possibility of improving these traits simultaneously. However, the negative correlation between GY and grain Zn (r = −0.44; p ≤ 0.01) and between GY and grain Fe concentration (r = −0.43; p ≤ 0.01) was significant but of moderate magnitude, suggesting slight dilution effects. Therefore, development of high yielding and micronutrient-dense maize cultivars is possible, which could reduce the highly prevalent micronutrient deficiency in sub-Saharan Africa (SSA).
Marginal Micro-Seal and Tensile Bond Strength of a Biopolymer Hybrid Layer Coupled with Dental Prosthesis Using a Primerless-Wet System
Authors: Piemjai Morakot , Waleepitackdej Onusa , Garcia-Godoy Franklin
Published: January 2023

The aim of this study is to compare the marginal seal and tensile bond strength (TBS) of prostheses fixed to enamel-dentin using different adhesive systems. Resin-composite inlays directly fabricated from Class V cavities of extracted human molars/premolars and mini-dumbbell-shaped specimens of bonded enamel-dentin were prepared for microleakage and tensile tests, respectively. Four adhesive systems were used: primerless-wet (1-1 etching for 10-, 30-, or 60-s, and 4-META/MMA-TBB), primer-moist (All-Bond2 + Duolink or Single-Bond2 + RelyX ARC), self-etch (AQ-Bond + Metafil FLO), and dry (Super-Bond C&B) bonding. Dye penetration distance and TBS data were recorded. Failure modes and characteristics of the tooth-resin interface were examined on the fractured specimens. All specimens in 10-, 30-, and 60-s etching primerless-wet, Super-Bond, and AQ-Bond had a microleakage-free tooth-resin interface. Primer-moist groups showed microleakage at the cementum/dentin-resin margin/interface. Significantly higher TBSs (p < 0.05) were recorded in primer-less-wet and Super-Bond groups with the consistent hybridized biopolymer layer after the chemical challenge and mixed failure in tooth structure, luting-resin, and at the PMMA-rod interface. There was no correlation between microleakage and TBS data (p = −0.148). A 1–3 µm hybrid layer created in the 10–60 s primerless-wet technique, producing complete micro-seal and higher tensile strength than enamel and cured 4-META/MMA-TBB, may enhance clinical performances like Super-Bond C&B, the sustainable luting resin.
Plasticized Mechanical Recycled PLA Films Reinforced with Microbial Cellulose Particles Obtained from Kombucha Fermented in Yerba Mate Waste
Authors: Agüero Ángel , Corral Perianes Esther , Abarca de las Muelas Sara Soledad , Lascano Diego , de la Fuente García-Soto María del Mar , Peltzer Mercedes Ana , Balart Rafael , Arrieta Marina Patricia
Published: January 2023

In this study, yerba mate waste (YMW) was used to produce a kombucha beverage, and the obtained microbial cellulose produced as a byproduct (KMW) was used to reinforce a mechanically recycled poly(lactic acid) (r-PLA) matrix. Microbial cellulosic particles were also produced in pristine yerba mate for comparison (KMN). To simulate the revalorization of the industrial PLA products rejected during the production line, PLA was subjected to three extrusion cycles, and the resultant pellets (r3-PLA) were then plasticized with 15 wt.% of acetyl tributyl citrate ester (ATBC) to obtain optically transparent and flexible films by the solvent casting method. The plasticized r3-PLA-ATBC matrix was then loaded with KMW and KMN in 1 and 3 wt.%. The use of plasticizer allowed a good dispersion of microbial cellulose particles into the r3-PLA matrix, allowing us to obtain flexible and transparent films which showed good structural and mechanical performance. Additionally, the obtained films showed antioxidant properties, as was proven by release analyses conducted in direct contact with a fatty food simulant. The results suggest the potential interest of these recycled and biobased materials, which are obtained from the revalorization of food waste, for their industrial application in food packaging and agricultural films.
Assessment of the Dimensionless Groups-Based Scale-Up of Gas–Solid Fluidized Beds
Authors: Zaid Faraj M. , Al-Rubaye Haider , Aljuwaya Thaar M. , Al-Dahhan Muthanna H.
Published: January 2023

The most common scale-up approach for gas–solids fluidized beds is based on matching the governing dimensionless parameters. In the literature, this approach has been validated only by means of measuring global parameters between different sizes of fluidized beds. However, such global measurements are not sufficient to depict all the interplaying hydrodynamic phenomena and hence verify the scale-up relationships. Therefore, to assess this approach, an advanced gas–solids optical probe and pressure transducer measurement techniques have been applied to quantify local hydrodynamic parameters in two different sized fluidized beds. Four different sets of experimental conditions were designed and conducted to examine the assessment of the scaling approach with matched and mismatched dimensionless groups between the two beds. The results indicated that the reported dimensionless groups are not adequate for achieving similarity between the two gas–solids fluidized beds in terms of solids holdup, gas holdup, particle velocity, mass flux, and pressure fluctuation. This finding demonstrates the importance of local measurements of the hydrodynamic parameters of fluidized beds in order to evaluate scale-up relationships. Finally, the results further advance the understanding of the gas–solids fluidized beds and present deeper insight into their solids dynamics.
Parallel Walking-Worker Flexible Assembly Lines for High-Mix Low-Volume Demand
Authors: Miqueo Adrian , Yagüe-Fabra José A. , Torralba Marta , Oliveros María-José , Tosello Guido
Published: January 2023

Demand trends towards mass customization drive the need for increasingly productive and flexible assembly operations. Walking-worker assembly lines can present advantages over fixed-worker systems. This article presents a multiproduct parallel walking-worker assembly line with shared automated stations, and evaluates its operational performance compared to semiautomated and manual fixed-worker lines. Simulation models were used to set up increasingly challenging scenarios based on an industrial case study. The results revealed that semiautomated parallel walking-worker lines could achieve greater productivity (+30%) than fixed-worker lines under high-mix low-volume demand conditions.
Research on Gas Concentration Prediction Based on the ARIMA-LSTM Combination Model
Authors: Li Chuan , Fang Xinqiu , Yan Zhenguo , Huang Yuxin , Liang Minfu
Published: January 2023

The current single gas prediction model is not sufficient for identifying and processing all the characteristics of mine gas concentration time series data. This paper proposes an ARIMA-LSTM combined forecasting model based on the autoregressive integrated moving average (ARIMA) model and the long short-term memory (LSTM) recurrent neural network. In the ARIMA-LSTM model, the ARIMA model is used to process the historical data of gas time series and obtain the corresponding linear prediction results and residual series. The LSTM model is used in further analysis of the residual series, predicting the nonlinear factors in the residual series. The prediction results of the combined model are compared separately with those of the two single models. Finally, RMSE, MAPE and R2 are used to evaluate the prediction accuracy of the three models. The results of the study show that the metrics of the combined ARIMA-LSTM model are R2 = 0.9825, MAPE = 0.0124 and RMSE = 0.083. The combined model has the highest prediction accuracy and the lowest error and is more suitable for the predictive analysis of gas data. By comparing the prediction results of a single model and the combined model on gas time series data, the applicability, validity and scientificity of the combined model proposed in this paper are verified, which is of great importance to accurate prediction and early warning of underground gas danger in coal mines.
Performance Analysis of a Hybrid of Solar Photovoltaic, Genset, and Hydro of a Rural-Based Power Mini-Grid: Case Study of Kisiizi Hydro Power Mini-Grid, Uganda
Authors: Cartland Richard , Sendegeya Al-Mas , Hakizimana Jean de Dieu Khan
Published: January 2023

The power sector in Uganda has increased steadily, focusing majorly on rural electrification to increase the proportion of the rural population accessing electricity using grid extension and isolated mini-grid approaches. Hydropower mini-grids implemented in rural communities have issues regarding system failures leading to shutdowns and load shedding. A study on an existing isolated hydropower mini-grid was made to find the possible causes. A review of published articles and reports, and an analysis of enrollment patterns, energy sales, and load demand was carried out. A field survey with a guided questionnaire to collect information about real energy demand data was carried out. The performance of the system was accomplished through simulation using HOMER pro × 64 software. The findings from the study show a reduction in customer enrollment, a reduction in energy sales, and a reasonable number of system shutdowns. Hybridization of the existing hydropower was modeled with different options. The hybrid system proposed indicates that, when implemented, it would reduce fuel consumption from 222 to 23.2 L/day and emissions from 82.5 to 8.3 kg/year on average and increases system reliability. Simulated values of NPC, LCOE, and operating costs are appreciable. Despite mini-grid shortfalls, there is notably improved livelihood due to improved social and economic services.
Study of Explosion Characteristics and Mechanism of Sucrose Dust
Authors: Liang Siting , Li Xiaoquan , Jiang Juju , Zhong Yuankun , Sun Yunjie , Jiang Zhong , Yang Lei , Hao Peng
Published: January 2023

In order to investigate the explosion mechanism of sucrose in the air atmosphere, the explosion intensity under different ignition delay times (IDT), powder input pressures (PIP), and concentrations were studied using a 20L-sphere. The sucrose particles were analyzed in a synchronized thermal analyzer (STA) and scanning electron microscope (SEM). The results are as follows: 1. The DSC curve has two endothermic peaks and one exothermic peak, respectively at T = 180.5 ℃, 510.2 ℃ and 582.6 ℃. 2. The explosion intensity varies with the experiment conditions. The maximum explosion pressure (Pmax) appears when IDT = 90 ms, PIP = 1.5 MPa and concentration = 625 g/m3. 3. The explosive mechanism is a homogeneous combustion mechanism based on particle surface pyrolysis and volatilization. Because of the decomposition, H2, CO, furfural, and other flammable gas-phase products are released, then surface burn appears, which leads to the crystal rupture on account of thermal imbalance, resulting in multiple flame points and a chain explosion. As the temperature of the 20L-sphere rises, more explosive products are released, which causes a rapidly expanding explosion and eventually forms the explosion. This paper can be used as a reference for the prevention of explosion accidents in sucrose production processing.
Comparative Performance of Machine-Learning and Deep-Learning Algorithms in Predicting Gas–Liquid Flow Regimes
Authors: Hafsa Noor , Rushd Sayeed , Yousuf Hazzaz
Published: January 2023

Gas–liquid flow is a significant phenomenon in various engineering applications, such as in nuclear reactors, power plants, chemical industries, and petroleum industries. The prediction of the flow patterns is of great importance for designing and analyzing the operations of two-phase pipeline systems. The traditional numerical and empirical methods that have been used for the prediction are known to result in a high inaccuracy for scale-up processes. That is why various artificial intelligence-based (AI-based) methodologies are being applied, at present, to predict the gas–liquid flow regimes. We focused in the current study on a thorough comparative analysis of machine learning (ML) and deep learning (DL) in predicting the flow regimes with the application of a diverse set of ML and DL frameworks to a database comprising 11,837 data points, which were collected from thirteen independent experiments. During the pre-processing, the big data analysis was performed to analyze the correlations among the parameters and extract important features. The comparative analysis of the AI-based models’ performances was conducted using precision, recall, F1-score, accuracy, Cohen’s kappa, and receiver operating characteristics curves. The extreme gradient boosting method was identified as the optimum model for predicting the two-phase flow regimes in inclined or horizontal pipelines.
Multimode Wind Tunnel Flow Field System Monitoring Based on KPLS
Authors: Guo Jin , Zhang Ran , Cui Xiaochun , Ma Weitong , Zhao Luping
Published: January 2023

In a wind tunnel process, Mach number is the most important parameter. However, it is difficult to measure directly, especially in the multimode operation process, leading to difficulty in process monitoring. Thus, it is necessary to measure the Mach number indirectly by utilizing data-driven methods, and based on which, to monitor the operation status of the wind tunnel process. In this paper, therefore, a multimode wind tunnel flow field system monitoring strategy is proposed. Since the wind tunnel system is a strongly nonlinear system, the kernel partial least squares method, which can efficiently handle the nonlinear regression problem, is utilized. Firstly, the Mach number is predicted utilizing the kernel partial least squares method. Secondly, process monitoring statistics, i.e., the Hotelling T2 statistic and the square prediction error, the SPE statistic, and their control limits, are proposed to be applied to monitor the wind tunnel process on the basis of the prediction of the Mach number. Finally, the Mach number prediction and monitoring strategy are applied to a real process, where mode analysis and division is necessary. After mode division, the single-mode and multimode processes are modeled and predicted, respectively, and both the single-mode and multimode processes are monitored online. Satisfactory results were achieved compared with those of the partial least squares method.
Religious Grammar of the Welfare State in Poland
Authors: Fel Stanisław , Michaluk Kamil
Published: January 2023

Religion is one of the factors that determine what welfare state model is chosen by a country. Poland is interesting in this respect because it has a fairly religiously homogenous society that looked for solutions to reconcile free market economy and social security after 1989. This country, where 95% of people are Catholics, opted for a non-obvious economic model that was far removed from Catholic social teaching. However, the Catholic Church continues to play an important role. The goal of this article is to describe the religious grammar of the welfare state in Poland. We analyse three issues that are crucial here: (1) the disagreement between the impact of primary ideologies (Pole–Catholic’s narrative) and secondary ideologies (contemporary socioeconomic trends); (2) the social functioning of the Catholic Church in relation to growing secularisation in Poland (muted vibrancy); (3) the role of the Church in the achievement of goals supporting social security in Poland.
Design and Construction of Hybrid Autonomous Underwater Glider for Underwater Research
Authors: Siregar Simon , Trilaksono Bambang Riyanto , Hidayat Egi Muhammad Idris , Kartidjo Muljowidodo , Habibullah Natsir , Zulkarnain Muhammad Fikri , Setiawan Handi Nugroho
Published: January 2023

The main goal of this paper was to design and construct a hybrid autonomous underwater glider (HAUG) with a torpedo shape, a size of 230 cm in length and 24 cm in diameter. The control, navigation, and guidance system were executed simultaneously using a Udoo X86 minicomputer as the main server and three BeagleBone Black single-board computers as the clients. The simulations showed a controlled horizontal speed of 0.5 m/s in AUV mode and 0.39 to 0.51 m/s in glide mode with a pitch angle between 14.13∘ and 26.89∘. In addition, the field experiments under limited space showed the proposed HAUG had comparable results with the simulation, with a horizontal speed in AUV mode of 1 m/s and in glide mode of around 0.2 m/s. Moreover, the energy consumption with an assumption of three cycles of gliding motion per hour was 51.63 watts/h, which enabled the HAUG to perform a mission for 44.74 h. The proposed HAUG was designed to hold pressure up to 200 m under water and to perform underwater applications such as search and rescue, mapping, surveillance, monitoring, and maintenance.
Editorial for the Special Issue “Understanding Biosphere–Atmosphere Interactions with Remote Sensing”
Authors: Krishnan Praveena , Wang Shusen
Published: January 2023

The terrestrial biosphere interacts with the free atmosphere through the exchange of momentum, energy and mass [...]
Spatial and Temporal Sampling Properties of a Large GNSS-R Satellite Constellation
Authors: Winkelried Jack , Ruf Christopher , Gleason Scott
Published: January 2023

Using large constellations of smallsats, mission designers can improve sampling density and coverage. We develop performance metrics that characterize key sampling properties for applications in numerical weather prediction and optimize orbit design parameters of the constellation with respect to those metrics. Orbits are defined by a set of Keplerian elements, and the relationship between those elements and the spatial and temporal coverage metrics are examined in order to maximize global and zonal (latitude-dependent) coverage. Additional optimization is performed by dividing a constellation into multiple orbit planes. An iterative method can be applied to this design process to compare the performance of current and previous designs. The main objective of this work is the design of optimized configurations of satellites in low Earth orbiting constellations to maximize the spatial and temporal sampling and coverage provided by its sensors. The key innovations developed are a new cost function which measures the temporal sampling properties of a satellite constellation, and the use of it together with existing cost functions for spatial sampling to design satellite constellations that optimize performance with respect to both performance metrics.
Rapid Spaceborne Mapping of Wildfire Retardant Drops for Active Wildfire Management
Authors: Tagestad Jerry D. , Saltiel Troy M. , Coleman André M.
Published: January 2023

Aerial application of fire retardant is a critical tool for managing wildland fire spread. Retardant applications are carefully planned to maximize fire line effectiveness, improve firefighter safety, protect high-value resources and assets, and limit environmental impact. However, topography, wind, visibility, and aircraft orientation can lead to differences between planned drop locations and the actual placement of the retardant. Information on the precise placement and areal extent of the dropped retardant can provide wildland fire managers with key information to (1) adaptively manage event resources, (2) assess the effectiveness of retardant slowing or stopping fire spread, (3) document location in relation to ecologically sensitive areas; and perform or validate cost-accounting for drop services. This study uses Sentinel-2 satellite data and commonly used machine learning classifiers to test an automated approach for detecting and mapping retardant application. We show that a multiclass model (retardant, burned, unburned, and cloud artifact classes) outperforms a single-class retardant model and that image differencing (post-application minus pre-application) outperforms single-image models. Compared to the random forest and support vector machine, the gradient boosting model performed the best with an overall accuracy of 0.88 and an F1 Score of 0.76 for fire retardant, though results were comparable for all three models. Our approach maps the full areal extent of the dropped retardant within minutes of image availability, rather than linear representations currently mapped by aerial GPS surveys. The development of this capability allows for the rapid assessment of retardant effectiveness and documentation of placement in relation to sensitive environments.
Comparison of Three Different Random Forest Approaches to Retrieve Daily High-Resolution Snow Cover Maps from MODIS and Sentinel-2 in a Mountain Area, Gran Paradiso National Park (NW Alps)
Authors: Richiardi Chiara , Siniscalco Consolata , Adamo Maria
Published: January 2023

In the Alpine environment, snow plays a key role in many processes involving ecosystems, biogeochemical cycles, and human wellbeing. Due to the inaccessibility of mountain areas and the high spatial and temporal heterogeneity of the snowpack, satellite spatio-temporal data without gaps offer a unique opportunity to monitor snow on a fine scale. In this study, we present a random forest approach within three different workflows to combine MODIS and Sentinel-2 snow products to retrieve daily gap-free snow cover maps at 20 m resolution. The three workflows differ in terms of the type of ingested snow products and, consequently, in the type of random forest used. The required inputs are the MODIS/Terra Snow Cover Daily L3 Global dataset at 500 m and the Sentinel-2 snow dataset at 20 m, automatically retrieved through the recently developed revised-Let It Snow workflow, from which the selected inputs are, alternatively, the Snow Cover Extent (SCE) map or the Normalized Difference Snow Index (NDSI) map, and a Digital Elevation Model (DEM) of consistent resolution with Sentinel-2 imagery. The algorithm is based on two steps, the first to fill the gaps of the MODIS snow dataset and the second to downscale the data and obtain the high resolution daily snow time series. The workflow is applied to a case study in Gran Paradiso National Park. The proposed study represents a first attempt to use the revised-Let It Snow with the purpose of extracting temporal parameters of snow. The validation was achieved by comparison with both an independent dataset of Sentinel-2 to assess the spatial accuracy, including the snowline elevation prediction, and the algorithm’s performance through the different topographic conditions, and with in-situ data collected by meteorological stations, to assess temporal accuracy, with a focus on seasonal snow phenology parameters. Results show that all of the approaches provide robust time series (overall accuracies of A1 = 93.4%, and A2 and A3 = 92.6% against Sentinel-2, and A1 = 93.1%, A2 = 93.7%, and A3 = 93.6% against weather stations), but the first approach requires about one fifth of the computational resources needed for the other two. The proposed workflow is fully automatic and requires input data that are readily and globally available, and promises to be easily reproducible in other study areas to obtain high-resolution daily time series, which is crucial for understanding snow-driven processes at a fine scale, such as vegetation dynamics after snowmelt.
An Integrated Optical Circuit Architecture for Inverse-Designed Silicon Photonic Components
Authors: Gostimirovic Dusan , Soref Richard
Published: January 2023

In this work, we demonstrate a compact toolkit of inverse-designed, topologically optimized silicon photonic devices that are arranged in a “plug-and-play” fashion to realize many different photonic integrated circuits, both passive and active, each with a small footprint. The silicon-on-insulator 1550-nm toolkit contains a 2 × 2 3-dB splitter/combiner, a 2 × 2 waveguide crossover, and a 2 × 2 all-forward add–drop resonator. The resonator can become a 2 × 2 electro-optical crossbar switch by means of the thermo-optical effect, phase-change cladding, or free-carrier injection. For each of the ten circuits demonstrated in this work, the toolkit of photonic devices enables the compact circuit to achieve low insertion loss and low crosstalk. By adopting the sophisticated inverse-design approach, the design structure, shape, and sizing of each individual device can be made more flexible to better suit the architecture of the greater circuit. For a compact architecture, we present a unified, parallel waveguide circuit framework into which the devices are designed to fit seamlessly, thus enabling low-complexity circuit design.
Relationship between Repeated Sprint Ability, Countermovement Jump and Thermography in Elite Football Players
Authors: Majano Carlos , García-Unanue Jorge , Hernandez-Martin Antonio , Sánchez-Sánchez Javier , Gallardo Leonor , Felipe Jose Luis
Published: January 2023

Football is a very demanding sport which requires players to exert maximum effort, producing fatigue and eventually injuries. Thermography can be used to detect fatigue and prevent its consequences through thermal asymmetries in the bilateral body areas; however, its adequacy for elite footballers has not been widely studied. Therefore, the objective of the present investigation was to determine the suitability of thermography to detect fatigue in male football players. For this reason, twenty participants were gathered into a pair of subgroups (low [<0.2 °C] vs. high thermal asymmetry [≥0.2 °C]) based on a thermography session of the lower limbs (thighs, calves, and hamstrings). After the thermography session, players performed CMJs before and after an RSA test (6 × 30 m/20″). A mixed two-way analysis of variance and Bonferroni post hoc pairwise comparisons were undertaken to analyse the results. No significant differences (p > 0.05) were found in any of the RSA test variables between low and high thermal asymmetry groups for thighs and calves. On the other hand, the low thermal asymmetry hamstring group reported a smaller percentage difference in sprints for the first sprint (%Diff) and a larger percentage difference in sprints two and three with respect to the best sprint (%Best). For CMJs, the low thermal asymmetry hamstring group reported significantly higher values post-RSA test, indicating better performance. Accordingly, thermography can provide information about performance in CMJ and RSA tests through hamstring asymmetries over 0.2 °C. Meanwhile, larger asymmetries than 0.2 °C in calves and thighs do not seem to be related to performance in these tests; therefore, coaches should consider if it is optimal to align players with high hamstring asymmetries.
Survey of Explainable AI Techniques in Healthcare
Authors: Chaddad Ahmad , Peng Jihao , Xu Jian , Bouridane Ahmed
Published: January 2023

Artificial intelligence (AI) with deep learning models has been widely applied in numerous domains, including medical imaging and healthcare tasks. In the medical field, any judgment or decision is fraught with risk. A doctor will carefully judge whether a patient is sick before forming a reasonable explanation based on the patient’s symptoms and/or an examination. Therefore, to be a viable and accepted tool, AI needs to mimic human judgment and interpretation skills. Specifically, explainable AI (XAI) aims to explain the information behind the black-box model of deep learning that reveals how the decisions are made. This paper provides a survey of the most recent XAI techniques used in healthcare and related medical imaging applications. We summarize and categorize the XAI types, and highlight the algorithms used to increase interpretability in medical imaging topics. In addition, we focus on the challenging XAI problems in medical applications and provide guidelines to develop better interpretations of deep learning models using XAI concepts in medical image and text analysis. Furthermore, this survey provides future directions to guide developers and researchers for future prospective investigations on clinical topics, particularly on applications with medical imaging.