bluuebunny/crossref_metadata_2025 huggingface dataset:
Soft-Switching Full-Bridge Topology with AC Distribution Solution in Power Converters’ Auxiliary Power Supplies
Authors: Musumeci Salvatore , Stella Fausto , Mandrile Fabio , Armando Eric , Fratta Antonino
Published: March 2022

The auxiliary power supply in a power converter is a key topic in the optimization of the converter’s low-voltage electronic circuit performance. In this article, a low-voltage DC-AC soft-switching full-bridge topology, with an innovative, driven technique to achieve a zero-voltage transition, is presented and discussed. The full-bridge converter drives a high-frequency transformer (called the main transformer) that on the secondary side, distributes an AC voltage and current to the several electronic circuit’s supplies. Every power supply is composed of an HF transformer (called load transformer) that converts the AC secondary voltage of the main transformer to the voltage and current levels requested by the electronic circuit. In this paper, the operating conditions are first investigated by several simulation results. Furthermore, an actual DC-DC power converter is used as a workbench for an experimental investigation of the effectiveness of the proposed auxiliary DC-AC soft-switching topology, and the AC distribution approach, to realize the several points of load power supply requested. Finally, the advantages and drawbacks of this auxiliary power supply solution are critically discussed, providing guidelines for the power converter designer.
The Use of Convolutional Neural Networks and Digital Camera Images in Cataract Detection
Authors: Lai Chi-Ju , Pai Ping-Feng , Marvin Marvin , Hung Hsiao-Han , Wang Si-Han , Chen Din-Nan
Published: March 2022

Cataract is one of the major causes of blindness in the world. Its early detection and treatment could greatly reduce the risk of deterioration and blindness. Instruments commonly used to detect cataracts are slit lamps and fundus cameras, which are highly expensive and require domain knowledge. Thus, the problem is that the lack of professional ophthalmologists could result in the delay of cataract detection, where medical treatment is inevitable. Therefore, this study aimed to design a convolutional neural network (CNN) with digital camera images (CNNDCI) system to detect cataracts efficiently and effectively. The designed CNNDCI system can perform the cataract identification process accurately in a user-friendly manner using smartphones to collect digital images. In addition, the existing numerical results provided by the literature were used to demonstrate the performance of the proposed CNNDCI system for cataract detection. Numerical results revealed that the designed CNNDCI system could identify cataracts effectively with satisfying accuracy. Thus, this study concluded that the presented CNNDCI architecture is a feasible and promising alternative for cataract detection.
A Corpus-Based Sentence Classifier for Entity–Relationship Modelling
Authors: Šuman Sabrina , Čandrlić Sanja , Jakupović Alen
Published: March 2022

Automated creation of a conceptual data model based on user requirements expressed in the textual form of a natural language is a challenging research area. The complexity of natural language requires deep insight into the semantics buried in words, expressions, and string patterns. For the purpose of natural language processing, we created a corpus of business descriptions and an adherent lexicon containing all the words in the corpus. Thus, it was possible to define rules for the automatic translation of business descriptions into the entity–relationship (ER) data model. However, since the translation rules could not always lead to accurate translations, we created an additional classification process layer—a classifier which assigns to each input sentence some of the defined ER method classes. The classifier represents a formalized knowledge of the four data modelling experts. This rule-based classification process is based on the extraction of ER information from a given sentence. After the detailed description, the classification process itself was evaluated and tested using the standard multiclass performance measures: recall, precision and accuracy. The accuracy in the learning phase was 96.77% and in the testing phase 95.79%.
Does Chinese Foreign Direct Investment (FDI) Stimulate Economic Growth in Pakistan? An Application of the Autoregressive Distributed Lag (ARDL Bounds) Testing Approach
Authors: Ahmad Muhammad Salman , Szczepankiewicz Elżbieta Izabela , Yonghong Dai , Ullah Farid , Ullah Ihsan , Loopesco Windham Eugene
Published: March 2022

The objective of this paper is to ascertain the impact of Chinese FDI on economic growth in Pakistan. This study documents the exploration of the determinants of economic growth in Pakistan by emphasizing the significant role played by Chinese FDI and investments in renewable energy in particular. This paper employs time series data analysis to examine the relationship between GDP and Chinese FDI, inflation, trade openness, exchange rates, interest rates, remittances, and renewable energy consumption from 1990 to 2019. The study involved performing the ARDL bounds test, and it was determined that the dependent and independent variables are linked in the long term. Furthermore, the error correction model is negative and noteworthy, which checks the long-run relationship between variables. According to the findings of the autoregressive distributed lag (ARDL) model, Chinese FDI has a substantial favorable effect on Pakistan’s economic growth. Furthermore, renewable energy usage has a long-term favorable and significant association with Pakistan’s economic growth. This study established that FDI, and particularly renewable energy, will stimulate the economic growth of Pakistan. Our research has substantial policy implications, especially when it comes to the relationship between FDI and renewable energy.
Investigations into the Combined Effect of Mahua Biodiesel Blends and Biogas in a Dual Fuel Engine
Authors: Kshatriya Anmol , Tiwari Prabhatkumar , M Sreekanth , Yunus Khan T. , Abdul Khadar Shaik , Mansour Mohamed , M Feroskhan
Published: March 2022

Rapid depletion of conventional fuel sources has led to the use of alternative fuels and implementation of variant engine technologies to reduce deleterious emissions being released and deliver thermal energy for numerous applications. This research aims to study the usage of mahua methyl ester in a single-cylinder 4-stroke CI engine, optimized to operate in the dual fuel mode. Performance, combustion and emission characteristics are recorded and compared with diesel with the sole aim of finding the blend that provides adequate performance and diminishing emissions. To this effect, the percentage of mahua biodiesel blend, load, biogas flow rate and methane fraction are varied. The experimentation is conducted using three mahua biodiesel blend variants namely B10, B20 and B30. Gaseous fuel comprising biogas (CH4 and CO2 in ratio of 3:2) and methane (CH4) are incorporated in the dual fuel condition at 8 litre per minute (lpm) and 12 lpm. B20 blend demonstrated better performance and emission characteristics. The addition of biodiesel (B20) showed more than 5% improvement in brake thermal efficiency. Additionally, comparing with normal diesel mode, B20 showed lower CO (0.061%) and NOx (615 ppm) emissions. In the dual fuel condition, methane and biogas are effective in reducing the NOx emissions, but with a negative repercussion of extortionately elevated HC and CO emissions. The best combination is deduced to be B20 mahua biodiesel at 8 lpm of biogas flow rate in the dual fuel mode due to better performance and emission characteristics.
Evolutionary Game Analysis of Co-Opetition Strategy in Energy Big Data Ecosystem under Government Intervention
Authors: Bao A-Ru-Han , Liu Yao , Dong Jun , Chen Zheng-Peng , Chen Zhen-Jie , Wu Chen
Published: March 2022

This study discusses how to facilitate the barrier-free circulation of energy big data among multiple entities and how to balance the energy big data ecosystem under government supervision using dynamic game theory. First, we define the related concepts and summarize the recent studies and developments of energy big data. Second, evolutionary game theory is applied to examine the interaction mechanism of complex behaviors between power grid enterprises and third-party enterprises in the energy big data ecosystem, with and without the supervision of government. Finally, a sensitivity analysis is conducted on the main factors affecting co-opetition, such as the initial participation willingness, distribution of benefits, free-riding behavior, government funding, and punitive liquidated damages. The results show that both government supervision measures and the participants’ own will have an impact on the stable evolution of the energy big data ecosystem in the dynamic evolution process, and the effect of parameter changes on the evolution is more significant under the state of no government supervision. In addition, the effectiveness of the developed model in this work is verified by simulated analysis. The present model can provide an important reference for overall planning and efficient operation of the energy big data ecosystem.
Voltage Fluctuations and Flicker in Prosumer PV Installation
Authors: Łowczowski Krzysztof , Nadolny Zbigniew
Published: March 2022

In this paper, we present problems connected with voltage fluctuations in low-voltage networks caused by small PV sources installed in an LV network. For the purpose of analysis, high-resolution data gathered at the output of real PV sources for 4 months in 2 locations are used. Data are processed to analyze the impact of different network parameters on voltage fluctuations and voltage flicker. The resulting values of flicker and fluctuations are given so the assessment of the impact of PV sources can be made before the connection of new sources to the power grid. Moreover, the methodology of analysis is presented in detail so the impact of similar PV sources on voltage could be analyzed. Finally, general conclusions connected with measurement, analysis, and mitigation are given.
Forest Total and Component Above-Ground Biomass (AGB) Estimation through C- and L-band Polarimetric SAR Data
Authors: Zeng Peng , Zhang Wangfei , Li Yun , Shi Jianmin , Wang Zhanhui
Published: March 2022

Forest biomass plays an essential role in forest carbon reservoir studies, biodiversity protection, forest management, and climate change mitigation actions. Synthetic Aperture Radar (SAR), especially the polarimetric SAR with the capability of identifying different aspects of forest structure, shows great potential in the accurate estimation of total and component forest above-ground biomass (AGB), including stem, bark, branch, and leaf biomass. This study aims to fully explore the potential of polarimetric parameters at the C- and L-bands to achieve high estimation accuracy and improve the estimation of AGB saturation levels. In this study, the backscattering coefficients at different polarimetric channels and polarimetric parameters extracted from Freeman2, Yamaguchi3, H-A-Alpha, and Target Scattering Vector Model (TSVM) decomposition methods were optimized by a random forest algorithm, first, and then inputted into linear regression models to estimate the total forest AGB and biomass components of two test sites in China. The results showed that polarimetric observations had great potential in total and component AGB estimation in the two test sites; the best performances were for leaves at test site I, with R2 = 0.637 and RMSE = 1.27 t/hm2. The estimation of biomass components at both test sites showed obvious saturation phenomenon estimation according to their scatter plots. The results obtained at both test sites demonstrated the potential of polarimetric parameters in total and component biomass estimation.
Reforestation Opportunities in Indonesia: Mitigating Climate Change and Achieving Sustainable Development Goals
Authors: Basuki Imam , Adinugroho Wahyu Catur , Utomo Nugroho Adi , Syaugi Ahmad , Tryanto Dede Hendry , Krisnawati Haruni , Cook-Patton Susan C. , Novita Nisa
Published: March 2022

Reforestation in the tropics is highlighted as an important intervention to mitigate climate change globally because of its potential for high CO2 removal rates, ranging from 4.5 to 40.7 t CO2e ha−1 yr−1 during the first 20 years of tree growth. Reforestation is critical to meeting emissions’ targets of the Paris Climate Agreement, as well as achieving Indonesia’s Nationally Determined Contribution (NDC) targets. Increasing carbon stocks through forest and land rehabilitation activities (RHL) is one of the Ministry of Environment and Forestry (MoEF) five main strategies for reducing greenhouse gas (GHG) emissions from the land sector. This study focuses on reforestation opportunities to support Indonesia’s NDC in reducing GHG emissions by 2030. We identified unproductive areas of land (shrub, open land) with highly degraded conditions as potential areas for reforestation. Based on Indonesian data of land cover change, we found that reforestation activities during 2019–2030 (11 years) under a realistic, ambitious and very ambitious scenario may remove carbon up to −0.25 GtCO2e (equal to −23 MtCO2e yr−1), −1.3 GtCO2e (equal to −124 MtCO2e yr−1) and −2.7 GtCO2e (equal to −247 MtCO2e yr−1), respectively. Based on international data of land cover change (Hansen et al. 2013), reforestation activities during 2019–2030, under a realistic, ambitious, and very ambitious scenario, have the opportunities to remove −17 MtCO2e yr−1, −118 MtCO2e yr−1, and −241 MtCO2e yr−1, respectively. This study demonstrates that ambitious and very ambitious scenarios of reforestation activities can significantly contribute to Indonesia’s forestry-related NDC in 2030 by reducing the Indonesia Business As Usual (BAU) emissions up to 17% and 35%.
Toward Blockchain Realization
Authors: Hsueh Chih-Wen , Chin Chi-Ting
Published: March 2022

Since FinTech was stimulated by the invention of blockchain, without the full realization of blockchain technologies in the following years, FinTech has not been fully realized. We discuss some myths and reasons for why blockchain technologies were not fully realized. The lack of distributed synchronization might be the most difficult challenge such that the trust provided by blockchain is not good enough for public use. We propose a mathematical solution with a new consensus mechanism based on general Proof-of-Work mining, called Proof-of-PowerTimestamp, to reach distributed synchronization and reduce power consumption to less than one billionth of Bitcoin. We also discuss related issues toward blockchain realization once the distributed synchronization and energy consumption problems are solved. Since the issues are mostly interdisciplinary or multidisciplinary, researchers are invited to cooperate to help blockchain realization as soon as possible.
Current Advances in Immunoassays for the Detection of β2-Agonists
Authors: Ouyang Shuyu , Yu Shuting , Le Yingying
Published: March 2022

β2-agonists are a group of synthetic phenylethanolamine compounds which are traditionally used for treating bronchospasm. These compounds can also increase skeletal muscle mass and decrease body fat. The illegal use of β2-agonists in food-producing animals results in residue of β2-agonists in edible tissues and causes adverse health effects in humans. Thus, the detection of β2-agonists at trace level in complex sample matrices is of great importance for monitoring the abuse of β2-agonists. Many methods have been developed to detect β2-agonists. Among them, a variety of antigen–antibody interaction-based techniques have been established to detect β2-agonists in various samples, including animal feed, urine, serum, milk, tissues and hair. In this review, we summarized current achievement in the extraction of β2-agonists from testing samples and detection of β2-agonists using immunological techniques. Future perspectives were briefly discussed.
Comparison Study of an Optimized Ultrasound-Based Method versus an Optimized Conventional Method for Agar Extraction, and Protein Co-Extraction, from Gelidium sesquipedale
Authors: Gómez Barrio Laura Pilar , Cabral Eduarda Melo , Zhao Ming , Álvarez García Carlos , Senthamaraikannan Ramsankar , Padamati Ramesh Babu , Tiwari Uma , Curtin James Francis , Tiwari Brijesh Kumar
Published: March 2022

Agar is a hydrocolloid found in red seaweeds, which has been of industrial interest over the last century due to its multiple applications in the food, cosmetic, and medical fields. This polysaccharide, extracted by boiling for several hours, is released from the cell wall of red seaweeds. However, the environmental impact coming from the long processing time and the energy required to reach the targeted processing temperature needs to be reduced. In this study, a response surface methodology was employed to optimize both conventional extraction and ultrasound-assisted extractions. Two different models were successfully obtained (R2 = 0.8773 and R2 = 0.7436, respectively). Additionally, a further re-extraction confirmed that more agar could be extracted. Protein was also successfully co-extracted in the seaweed residues. Optimized conditions were obtained for both the extractions and the re-extraction of the two methods (CE: 6 h, 100 °C; and UAE: 1 h, 100% power). Finally, FT-IR characterization demonstrated that the extracts had a similar spectrum to the commercial agar. Compared to commercial samples, the low gel strength of the agar extracts shows that these extracts might have novel and different potential applications.
Generalized Fractional Integrals Involving Product of a Generalized Mittag–Leffler Function and Two H-Functions
Authors: Singh Prakash , Jain Shilpi , Agarwal Praveen
Published: March 2022

The objective of this research is to obtain some fractional integral formulas concerning products of the generalized Mittag–Leffler function and two H-functions. The resulting integral formulas are described in terms of the H-function of several variables. Moreover, we give some illustrative examples for the efficiency of the general approach of our results.
Immediate Dentin Sealing for Adhesive Cementation of Indirect Restorations: A Systematic Review and Meta-Analysis
Authors: Hardan Louis , Devoto Walter , Bourgi Rim , Cuevas-Suárez Carlos Enrique , Lukomska-Szymanska Monika , Fernández-Barrera Miguel Ángel , Cornejo-Ríos Elizabeth , Monteiro Paulo , Zarow Maciej , Jakubowicz Natalia , Mancino Davide , Haikel Youssef , Kharouf Naji
Published: March 2022

Immediate dentin sealing (IDS) involves applying an adhesive system to dentin directly after tooth preparation, before impression. This was considered an alternate to delayed dentin sealing (DDS), a technique in which hybridization is performed following the provisional phase and just before the indirect restoration luting procedure. This study aimed to compare the bond strength of restorations to dentin of the IDS and the DDS techniques throughout a systematic review and meta-analysis. The following PICOS framework was used: population, indirect restorations; intervention, IDS; control, DDS; outcomes, bond strength; and study design, in vitro studies. PubMed (MedLine), The Cochrane Library, ISI Web of Science, Scielo, Scopus, and Embase were screened up to January 2022 by two reviewers (L.H. and R.B.). In vitro papers studying the bond strength to human dentin of the IDS technique compared to the DDS technique were considered. Meta-analyses were carried out by using a software program (Review Manager v5.4.1; The Cochrane Collaboration). Comparisons were made by considering the adhesive used for bonding (two-step etch-and-rinse, three step etch-and-rinse, one-step self-etch, two-step self-etch, and universal adhesives). A total of 3717 papers were retrieved in all databases. After full-text assessment, 22 potentially eligible studies were examined for qualitative analysis, leaving a total of 21 articles for the meta-analysis. For the immediate bond strength, regardless of the adhesive strategy used, the IDS technique improved the bond strength of restorations to the dentin (p < 0.001). Taking into account the subgroup analysis, it seems that the use of the IDS technique with a two-step etch-and-rinse or a one-step self-etch adhesive system does not represent any advantage over the DDS technique (p = 0.07, p = 0.15). On the other hand, for the aged bond strength, regardless of the adhesive strategy used, the IDS technique improved the bond strength of restorations to the dentin (p = 0.001). The subgroups analysis shows that this improvement is observed only when a three-step etch-and-rinse adhesive system (p < 0.001) or when a combination of an adhesive system plus a layer of flowable resin (p = 0.01) is used. The in vitro evidence suggests that the use of the IDS technique improves the bond strength of dentin to resin-based restorations regardless of the adhesive strategy used. The use of a three-step etch-and-rinse adhesive system or the combination of an adhesive system plus a layer of flowable resin seems to considerably enhance the bond strength in the long term.
Revised Rainfall Threshold in the Indonesian Landslide Early Warning System
Authors: Yuniawan Ragil Andika , Rifa’i Ahmad , Faris Fikri , Subiyantoro Andy , Satyaningsih Ratna , Hidayah Alidina Nurul , Hidayat Rokhmat , Mushthofa Akhyar , Ridwan Banata Wachid , Priangga Eka , Muntohar Agus Setyo , Jetten Victor G. , Westen Cees J. van , Bout Bastian V. den , Sutanto Samuel J.
Published: March 2022

Landslides are one of the most disastrous natural hazards that frequently occur in Indonesia. In 2017, Balai Sabo developed an Indonesia Landslide Early Warning System (ILEWS) by utilizing a single rainfall threshold for an entire nation, leading to inaccuracy in landslide predictions. The study aimed to improve the accuracy of the system by updating the rainfall threshold. We analyzed 420 landslide events in Java with the 1-day and 3-day effective antecedent rainfall for each landslide event. Rainfall data were obtained from the Global Precipitation Measurement (GPM), which is also used in the ILEWS. We propose four methods to derive the thresholds: the first is the existing threshold applied in the Balai Sabo ILEWS, the second and third use the average and minimum values of rainfall that trigger landslides, respectively, and the fourth uses the minimum value of rainfall that induces major landslides. We used receiver operating characteristic (ROC) analysis to evaluate the predictability of the rainfall thresholds. The fourth method showed the best results compared with the others, and this method provided a good prediction of landslide events with a low error value. The chosen threshold was then applied in the Balai Sabo-ILEWS.
Data-Driven Geothermal Reservoir Modeling: Estimating Permeability Distributions by Machine Learning
Authors: Suzuki Anna , Fukui Ken-ichi , Onodera Shinya , Ishizaki Junichi , Hashida Toshiyuki
Published: March 2022

Numerical modeling for geothermal reservoir engineering is a crucial process to evaluate the performance of the reservoir and to develop strategies for the future development. The governing equations in the geothermal reservoir models consist of several constitutive parameters, and each parameter is given to a large number of simulation grids. Thus, the combinations of parameters we need to estimate are almost limitless. Although several inverse analysis algorithms have been developed, determining the constitutive parameters in the reservoir model is still a matter of trial-and-error estimation in actual practice, and is largely based on the experience of the analyst. There are several parameters which control the hydrothermal processes in the geothermal reservoir modeling. In this study, as an initial challenge, we focus on permeability, which is one of the most important parameters for the modeling. We propose a machine-learning-based method to estimate permeability distributions using measurable data. A large number of learning data were prepared by a geothermal reservoir simulator capable of calculating pressure and temperature distributions in the natural state with different permeability distributions. Several machine learning algorithms (i.e., linear regression, ridge regression, Lasso regression, support vector regression (SVR), multilayer perceptron (MLP), random forest, gradient boosting, and the k-nearest neighbor algorithm) were applied to learn the relationship between the permeability and the pressure and temperature distributions. By comparing the feature importance and the scores of estimations, random forest using pressure differences as feature variables provided the best estimation (the training score of 0.979 and the test score of 0.789). Since it was learned independently of the grids and locations, this model is expected to be generalized. It was also found that estimation is possible to some extent, even for different heat source conditions. This study is a successful demonstration of the first step in achieving the goal of new data-driven geothermal reservoir engineering, which will be developed and enhanced with the knowledge of information science.
Lucía Puenzo: Readings from the Margins of a Literary Film Universe
Authors: García-Reyes David , Gallardo Marta
Published: March 2022

The writer and director Lucía Puenzo expresses herself in two different languages: literary prose and cinematographic narrative. Her work is characterised by a single ethical and aesthetic commitment. She highlights sensitive contemporary issues such as identity, gender, sexuality, marginality and the family, but also ethical concerns around eugenics, migration, exclusion and dangerous social elements. The paper looks at the differences between the novels XXY, El niño pez (The Fish Child) and Wakolda (The German Doctor) and their corresponding films, highlighting Puenzo’s stylistic and aesthetic constants. The notion of identity, the notion of family and different historical perspectives and their representations are analysed in her literary works and their subsequent adaptations in films. A comparative analysis of the literary and film texts help us to see how plotlines have been transposed, observing the differences and the reasons for these differences. She keeps her two creative sides separate and makes significant changes as she adapts the literary original to the film script. Her audiovisual approach is to reduce the plotlines and issues shown in the originals. The value of Puenzo’s artistic production is making visible characters who are on the edges or are socially marginalised, favouring their acceptance and integration in the society.
Alexithymia and Athletic Performance: Beneficial or Deleterious, Both Sides of the Medal? A Systematic Review
Authors: Proença Lopes Catarina , Allado Edem , Poussel Mathias , Essadek Aziz , Hamroun Aghilès , Chenuel Bruno
Published: March 2022

Background: Numerous studies have been published on alexithymia among athletes in the last decades. The objective, here, is to provide a critical review on alexithymia in sport and identify elements demonstrating that alexithymic athletes can attain a competitive advantage. Methods: The Center for Reviews and Dissemination guidelines were used. The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines served as the template for reporting the present systematic review. We searched PubMed, Embase, Science Direct, and PsycINFO, without language or date restrictions. Results: Within 72 eligible studies, 23 articles fulfilling the selection criteria were included in the review. Alexithymia is associated with various pathologies and considered to be counter-performing. However, despite considerable suspicion of an advantageous performance effect of alexithymia, there is a lack of data to quantify this effect. Studies identified are heterogeneous (different scales of measurement of alexithymia used or outcomes, different sports), that do not allow us to conclude on an observed causal relationship, because the studies are mostly observational. Conclusion: This systematic review opens a new search field on alexithymia, as possibly promoting performance.
Platanus hybrida’s Phenolic Profile, Antioxidant Power, and Antibacterial Activity against Methicillin-Resistant Staphylococcus aureus (MRSA)
Authors: Ribeiro Jessica , Silva Vanessa , Aires Alfredo , Carvalho Rosa , Barros Lillian , Gaivão Isabel , Igrejas Gilberto , Poeta Patrícia
Published: March 2022

Methicillin-resistant S. aureus (MRSA) are a threat to public health as they frequently reveal a multidrug-resistant pattern. Researchers all over the world are on an urgent hunt for new treatments to help fight infections before antibiotics become obsolete, and some natural alternatives, such as polyphenols, have already exhibited therapeutic properties. Therefore, this study aimed to determine the phenolic profile, antioxidant capacity, and antimicrobial activity against MRSA of the leaf, fruit, and stem bark extracts of Platanus hybrida. The polyphenols were extracted with a water/ethanol (20:80) mixture and the methodology included HPLC-DAD, DPPH, FRAP, and CuPRAC. To address this issue from a One Health perspective, the Kirby–Bauer disc diffusion method was performed against nine MRSA strains from three different sources (livestock, wild animals, and humans). Fourteen phenolics were identified and the leaf extract showed the highest phenolic content, followed by the fruit extract. The leaf extract also showed the highest antioxidant capacity while the fruit extract had the lowest antioxidant capacity. Both leaf and fruit extracts inhibited the growth of strains from all sources, while the stem bark extract did not inhibit the growth of human strains. This work highlights the complex chemical composition and the antioxidative and antimicrobial potential of extracts derived from P. hydrida.
COVID-19 and the Endocrine System: A Review of the Current Information and Misinformation
Authors: Mirza Samir Ahmed , Sheikh Abdul Ahad Ehsan , Barbera Michaela , Ijaz Zainab , Javaid Muhammad Ali , Shekhar Rahul , Pal Suman , Sheikh Abu Baker
Published: March 2022

Coronavirus disease 2019 (COVID-19) infection primarily involves the respiratory system but has many noteworthy extra pulmonary manifestations as well. We write this review to highlight the basis of some pathophysiological mechanisms of COVID-19 infection-induced endocrine dysfunction. Different scientific databases and institutional websites were searched to collect and consolidate the most up-to-date data relating to COVID-19 infection and endocrine systems. Hypopituitarism, central diabetes insipidus, SIADH, thyroid abnormalities, hyperglycemia, adrenal insufficiency, orchitis and alteration in sperm morphology have been reported in case reports of patients with COVID-19 infection. Data focusing on COVID-19 vaccination was also searched to summarize the effect, if any, on the endocrine system. Endocrinopathies noted post COVID-19 vaccination, including cases of adrenal hemorrhage, new onset Type II Diabetes Mellitus and subacute thyroiditis, are also discussed in this review. This review calls attention to the misinformation relating to COVID-19 vaccination with supposed endocrine effects such as infertility and problems with pregnancy. Rebutting these misconceptions can help increase compliance and maximize COVID-19 vaccination to the public.
Feasibility and Efficacy of Telehealth-Based Resistance Exercise Training in Adolescents with Cystic Fibrosis and Glucose Intolerance
Authors: Holmes Clifton J. , Racette Susan B. , Symonds Leslie , Arbeláez Ana Maria , Cao Chao , Granados Andrea
Published: March 2022

The aims of this study were to (1) determine the feasibility of a home-based resistance exercise training (RET) program in patients with cystic fibrosis and impaired glucose tolerance using virtual personal training and (2) observe the effects completion of the RET program had on glucose metabolism, pulmonary function, body composition, and physical fitness. The feasibility of the program was defined as 80% compliance. Ten participants (15.80 ± 2.20 yr, 25.1 ± 7.4 kg/m2) began a home-based resistance training program consisting of 36 sessions supervised via online videoconferencing. Compliance scores of 78.9% (all participants) and 81.8% (without one outlier) were observed. A significant increase was observed in 2-h C-peptide levels (2.1 ng/mL; p = 0.04), with a moderate decrease in fasting glucose (−5.2 mg/dL; p = 0.11) and a moderate increase in 2-h insulin (35.0 U/mL; p = 0.10). A small decrease in the fat percentage (−1.3%; p = 0.03) was observed in addition to increases in fat-free mass (1.5 kg; p = 0.01) and the fat-free mass index (0.4; p = 0.01). Small, yet statistically significant increases were observed in V̇O2peak (0.1 L/min p = 0.01), V̇CO2peak (0.1 L/min; p = 0.01), and ventilation (5.3 L/min; p = 0.04). Telehealth-based RET is feasible in adolescents with CF and impaired glucose tolerance and elicits small yet favorable changes in insulin secretion, body composition, and exercise capacity.
A New Combined Air Quality and Heat Index in Relation to Mortality in Monterrey, Mexico
Authors: Fever Shayna K. , Kahl Jonathan D. W. , Kalkbrenner Amy E. , Cerón Bretón Rosa M. , Cerón Bretón Julia G.
Published: March 2022

The negative synergistic effects of air pollution and sensible heat on public health have been noted in numerous studies. While separate, simplified, and public-facing indices have been developed to communicate the risks of unhealthful levels of air pollution and extreme heat, a combined index containing elements of both has rarely been investigated. Utilizing air quality, meteorology, and mortality data in Monterrey, Mexico, we investigated whether the association between the air quality index (AQI) and mortality was improved by considering elements of the heat index (HI). We created combined indices featuring additive, multiplicative, and either/or formulations and evaluated their relationship to mortality. Results showed increased associations with mortality for models employing indices that combined the AQI and the HI in an additive or multiplicative manner, with increases in the interquartile relative risk of 3–5% over that resulting from models employing the AQI alone.
The Analysis of the Relationship between the Quality of Life Level and Expectations of Patients with Cardiovascular Diseases under the Home Care of Primary Care Nurses
Authors: Szlenk-Czyczerska Elżbieta , Guzek Marika , Bielska Dorota Emilia , Ławnik Anna , Polański Piotr , Kurpas Donata
Published: March 2022

The World Health Organization defines quality of life as a person’s perception of his or her life situation in relation to the culture and value system in which he or she lives, in relation to and with respect to his or her functioning assumptions, expectations, and standards set by environmental conditions. Meeting the expectations of patients with CVD is one of the factors that positively influences their health status and leads to better diagnostic and treatment outcomes. The aim of this study was to answer three main questions related to patients with chronic cardiovascular disease: (1) What is their quality of life? (2) Are patients’ expectations about the quality of care provided by primary health care physicians/nurses met (and at what level)? (3) Is there a correlation between patients’ quality of life and their expectations of primary health care physicians/nurses? The study involved 193 Polish CVD patients who were cared for at home by a family nurse practitioner working in primary health care facilities. Data were collected from March 2016 to January 2017. The WHOQOL-BREF Quality of Life Questionnaire and the Author Interview Questionnaire were used for the study. Data analysis was based on the Spearman correlation coefficient test. There was a statistically significant association between patients’ expectations of the physician regarding information about the course of the disease and quality of life in the following domains: environmental r = 0.20, p = 0.006, psychological: r = 0.18, p = 0.015, physical: r = 0.18, p = 0.013, and social: r = 0.16, p = 0.025. Patients who did not expect the nurse to be courteous, understanding, or interested were found to have higher quality of life scores in psychological (r = −0.17, p = 0.023) and physical (r = −0.15, p = 0.044) domains. There was a statistically significant relationship between expectations of care from nurses regarding intimacy during care activities and the level of satisfaction with one’s own health (r = −0.15, p = 0.038) and quality of life (r = −0.14, p = 0.045), as well as quality of life in the domains of physical (r = 0.21, p = 0.004), social (r = 0.19, p = 0.010), and psychological (r = 0.16, p = 0.024). There is a need to define the expectations of patients with chronic cardiovascular disease in primary care, as lack of expectations of a physician/nurse continues to be associated with lower quality of life in all domains.
Symptoms of the Eruption of Permanent Teeth
Authors: Sobkowska Łucja , Sobkowska Julia , Dudek Damian , Grabarek Beniamin Oskar , Czajka-Jakubowska Agata , Przystańska Agnieszka
Published: March 2022

This prospective study examined a population of 520 urban and rural children aged 5 to 9 years. Every 2–4 weeks, the clinical symptoms accompanying primary tooth replacement such as a cough, a runny nose, pain, and body temperature were assessed in each child’s medical records. The authors were able to show in a statistically significant manner that the frequency, time, and type of cough were strongly related to the type of erupting teeth (p < 0.001 for each relationship). A cough dependent on the type of erupting teeth was observed in 86% to 92% of the examined children, with a morning bronchial cough being connected with an eruption of the lower teeth, and an eruption of the upper teeth producing an all-day pharyngeal cough caused by mucus secretions dripping down the back of the throat. A statistically significant relationship was also confirmed between the type of erupting teeth and the incidence of a runny nose (p < 0.001), the frequency of a runny nose (p < 0.001), and the time when runny nose symptoms occurred (p < 0.001). This study shows that the period when primary dentition is replaced with permanent teeth in children is characterized by a physiological cough and a runny nose.
Healthcare Leadership Perspectives on Supporting Frontline Workers in Health Center Settings during the Pandemic
Authors: Alvarez Carmen , Sims Holly , Grant Kimesha , Walczak Jessica , Lipman Paula Darby , Marsteller Jill A. , Cooper Lisa A. ,   on behalf of RICH LIFE Project Investigators
Published: March 2022

Throughout the COVID-19 pandemic much attention has been given to addressing the needs of hospital-based healthcare professionals delivering critical inpatient care. At the same time, other groups of essential frontline healthcare workers have continued to serve low-income and underserved populations whose healthcare and nonmedical needs did not cease, and in many cases were exacerbated by factors associated with the pandemic shutdown. As these same factors also potentially impacted well-being and effectiveness of frontline healthcare workers, we sought to understand the organizational-level responses to the pandemic, including the support and preparation for frontline workers. As part of a larger study focused on reducing health disparities in hypertension, we conducted semi-structured individual interviews with 14 leaders from healthcare and health services organizations to explore how these organizations responded to accommodate frontline workers’ needs. Findings from our sample show that healthcare and health service organizations made a range of major and timely modifications to clinic operations intended to address the needs of both employees and patients and strove to ensure continued patient services as much as possible. Nevertheless, our findings underscore the need for more attention and resources to support healthcare workers in primary care settings especially during emergencies such as COVID-19.
The Effects of Action Observation Therapy as a Rehabilitation Tool in Parkinson’s Disease Patients: A Systematic Review
Authors: Giannakopoulos Ioannis , Karanika Panagiota , Papaxanthis Charalambos , Tsaklis Panagiotis
Published: March 2022

During Action Observation (AO), patients observe human movements that they then try to imitate physically. Until now, few studies have investigated the effectiveness of it in Parkinson’s disease (PD). However, due to the diversity of interventions, it is unclear how the dose and characteristics can affect its efficiency. We investigated the AO protocols used in PD, by discussing the intervention features and the outcome measures in relation to their efficacy. A search was conducted through MEDLINE, Scopus, Cochrane, and WoS until November 2021, for RCTs with AO interventions. Participant’s characteristics, treatment features, outcome measures, and main results were extracted from each study. Results were gathered into a quantitative synthesis (MD and 95% CI) for each time point. Seven studies were included in the review, with 227 participants and a mean PEDro score of 6.7. These studies reported positive effects of AO in PD patients, mainly on walking ability and typical motor signs of PD like freezing of gait. However, disagreements among authors exist, mainly due to the heterogeneity of the intervention features. In overall, AO improves functional abilities and motor control in PD patients, with the intervention dose and the characteristics of the stimulus playing a decisive role in its efficacy.
Cost-Effectiveness of Routine Third Trimester Ultrasound Screening for Fetal Growth Restriction Compared to Care as Usual in Low-Risk Pregnancies: A Pragmatic Nationwide Stepped-Wedge Cluster-Randomized Trial in The Netherlands (the IRIS Study)
Authors: Henrichs Jens , de Jonge Ank , Westerneng Myrte , Verfaille Viki , Franx Arie , van der Horst Henriëtte E. , Bosmans Judith E. ,   on behalf of the IRIS Study Group
Published: March 2022

Routine third trimester ultrasonography is increasingly used to screen for fetal growth restriction. However, evidence regarding its cost-effectiveness is lacking. We aimed to evaluate the cost-effectiveness of routine third trimester ultrasonography to reduce adverse perinatal outcomes compared to usual care (selective ultrasonography). An economic evaluation alongside a stepped-wedge cluster-randomized trial was conducted. Via 60 midwifery practices 12,974 Dutch women aged ≥16 years with low-risk pregnancies were enrolled at 22.8 (SD = 2.4) weeks’ gestation. All practices provided usual care. At 3, 7, and 10 months a third of the practices were randomized to the intervention strategy providing routine ultrasonography at 28–30 and 34–36 weeks’ gestation and usual care. The primary clinical outcome was a dichotomous composite measure of 12 severe adverse perinatal outcomes (SAPO) up to one week postpartum. Information on perinatal care and societal costs was derived from Netherlands Perinatal Registry, hospital records and a survey. Cost-effectiveness analyses revealed no significant differences in SAPO and healthcare and societal costs between the intervention strategy (n = 7026) and usual care (n = 5948). Cost-effectiveness acceptability curves showed that the probability of cost-effectiveness was never higher than 0.6 for all possible ceiling ratios. Adding routine third trimester ultrasonography to usual care is not cost-effective in reducing SAPO.
Building the Momentum for A Stronger Pharmaceutical System in Africa
Authors: Ussai Silvia , Chillotti Caterina , Stochino Erminia , Deidda Arianna , Ambu Giovanni , Anania Lorenzo , Boccalini Alberto , Colombo Flavia , Ferrari Alessandra , Pala Daniele , Puddu Enrica , Rapallo Giulia , Pistis Marco
Published: March 2022

Despite impressive progress, nearly two billion people worldwide have no access to essential medicines. The COVID-19 pandemic revealed Africa’s vulnerability due to its reliance on imports for most vaccines, medicines, and other health product needs. The vaccine manufacturing is complex and requires massive financial investments, with global, regional, and national regulatory structures introducing consistent and urgent reforms to assure the quality and safety of medicines. In 2020, there were approximately 600 pharmaceutical manufacturers in Africa, 80% of which were concentrated in eight countries: Egypt, Algeria, Morocco, Tunisia, Nigeria, Ghana, Kenya, and South Africa. Only 4 countries had more than 50 manufacturers, while 22 countries had no local production. Out of the 600, around 25% were multinational companies. Africa is equally affected by modest scaled capacities substantially engaging in packaging and labelling, and occasionally fill and finish steps, facing criticalities in terms of solvent domestic markets. This article discusses the challenges in the development of a local pharmaceutical manufacturing in Africa and reflects on the importance of the momentum for strengthening the local medical production capacity in the continent as a critical opportunity for advancing universal health coverage (UHC).
Young People’s Voices and Science for Overcoming Toxic Relationships Represented in Sex Education
Authors: Villarejo-Carballido Beatriz , Pulido Cristina M. , Zubiri-Esnaola Harkaitz , Oliver Esther
Published: March 2022

The scientific literature has presented evidence of how fiction series impact the socialisation of young people’s relationships. However, there is a gap in the evidence on how dialogic interactions overcome the negative impact of the fiction series on the socialisation of toxic relationships. This research analyses dialogic interactions based on scientific evidence related to toxic relationships that contribute to overcoming this type of relationship. First, we developed a communicative content analysis of eight episodes of one of the most-watched fiction series by young people, Sex Education. After that, we conducted four communicative interviews with the young audience to collect their voices about the impact of these toxic relationships represented in this fiction series in their daily conversations. The results indicate that in such cases, there is a need to promote dialogic interactions about this fiction series, focusing the dialogue on which type of masculinity develops a toxic relationship and which, on the contrary, promotes healthy relationships.
Healthy Behavior and Environmental Behavior Correlate with Bicycle Commuting
Authors: Liu Qiang , Yamada Toshiaki , Liu Hang , Lin Li , Fang Qiaoling
Published: March 2022

Previous studies have identified that environmental awareness correlates with the choice of bicycle travel. However, few studies have considered the relationships with different types of healthy behaviors and environmental behaviors. This study examined the relationships between several healthy and environmental behaviors and the choice of bicycle commute using survey data. A total of 803 residents participated in this questionnaire survey. Using factor analysis, we constructed latent factors of healthy behaviors and environmental behaviors. Using a binary logistic regression model, we examined the relationship between latent factors and cycling usage, controlling for demographic characteristics. Factor analysis revealed three latent factors of healthy behaviors: “healthy diet”, “avoiding tobacco or overdrinking”, and “physical activity”. The latent factors of environmental behaviors were as follows: “household behavior” and “purchasing behavior”. The results showed that “avoiding tobacco or overdrinking”, “physical activity” and “purchasing behavior” correlated positively with bicycle commuting. Differences were also observed in relation to demographic characteristics.