bluuebunny/crossref_metadata_2025 huggingface dataset:
Parkin as a Molecular Bridge Linking Alzheimer’s and Parkinson’s Diseases?
Authors: Checler Frédéric , Alves da Costa Cristine
Published: April 2022

Alzheimer’s (AD) and Parkinson’s (PD) diseases are two distinct age-related pathologies that are characterized by various common dysfunctions. They are referred to as proteinopathies characterized by ubiquitinated protein accumulation and aggregation. This accumulation is mainly due to altered lysosomal and proteasomal clearing processes and is generally accompanied by ER stress disturbance, autophagic and mitophagic defects, mitochondrial structure and function alterations and enhanced neuronal cell death. Genetic approaches aimed at identifying molecular triggers responsible for familial forms of AD or PD have helped to understand the etiology of their sporadic counterparts. It appears that several proteins thought to contribute to one of these pathologies are also likely to contribute to the other. One such protein is parkin (PK). Here, we will briefly describe anatomical lesions and genetic advances linked to AD and PD as well as the main cellular processes commonly affected in these pathologies. Further, we will focus on current studies suggesting that PK could well participate in AD and thereby act as a molecular bridge between these two pathologies. In particular, we will focus on the transcription factor function of PK and its newly described transcriptional targets that are directly related to AD- and PD-linked cellular defects.
Enhancement of Methane Catalysis Rates in Methylosinus trichosporium OB3b
Authors: Samanta Dipayan , Govil Tanvi , Saxena Priya , Gadhamshetty Venkata , Krumholz Lee R. , Salem David R. , Sani Rajesh K.
Published: April 2022

Particulate methane monooxygenase (pMMO), a membrane-bound enzyme having three subunits (α, β, and γ) and copper-containing centers, is found in most of the methanotrophs that selectively catalyze the oxidation of methane into methanol. Active sites in the pMMO of Methylosinus trichosporium OB3b were determined by docking the modeled structure with ethylbenzene, toluene, 1,3-dibutadiene, and trichloroethylene. The docking energy between the modeled pMMO structure and ethylbenzene, toluene, 1,3-dibutadiene, and trichloroethylene was −5.2, −5.7, −4.2, and −3.8 kcal/mol, respectively, suggesting the existence of more than one active site within the monomeric subunits due to the presence of multiple binding sites within the pMMO monomer. The evaluation of tunnels and cavities of the active sites and the docking results showed that each active site is specific to the radius of the substrate. To increase the catalysis rates of methane in the pMMO of M. trichosporium OB3b, selected amino acid residues interacting at the binding site of ethylbenzene, toluene, 1,3-dibutadiene, and trichloroethylene were mutated. Based on screening the strain energy, docking energy, and physiochemical properties, five mutants were downselected, B:Leu31Ser, B:Phe96Gly, B:Phe92Thr, B:Trp106Ala, and B:Tyr110Phe, which showed the docking energy of −6.3, −6.7, −6.3, −6.5, and −6.5 kcal/mol, respectively, as compared to the wild type (−5.2 kcal/mol) with ethylbenzene. These results suggest that these five mutants would likely increase methane oxidation rates compared to wild-type pMMO.
Plasmonic Metal Nanoparticles Hybridized with 2D Nanomaterials for SERS Detection: A Review
Authors: Serafinelli Caterina , Fantoni Alessandro , Alegria Elisabete C. B. A. , Vieira Manuela
Published: April 2022

In SERS analysis, the specificity of molecular fingerprints is combined with potential single-molecule sensitivity so that is an attractive tool to detect molecules in trace amounts. Although several substrates have been widely used from early on, there are still some problems such as the difficulties to bind some molecules to the substrate. With the development of nanotechnology, an increasing interest has been focused on plasmonic metal nanoparticles hybridized with (2D) nanomaterials due to their unique properties. More frequently, the excellent properties of the hybrids compounds have been used to improve the drawbacks of the SERS platforms in order to create a system with outstanding properties. In this review, the physics and working principles of SERS will be provided along with the properties of differently shaped metal nanoparticles. After that, an overview on how the hybrid compounds can be engineered to obtain the SERS platform with unique properties will be given.
Multiplex Digital Quantification of β-Lactamase Genes in Antibiotic-Resistant Bacteria by Counting Gold Nanoparticle Labels on Silicon Microchips
Authors: Presnova Galina V. , Presnov Denis E. , Filippova Anna A. , Tsiniaikin Ilia I. , Ulyashova Mariya M. , Rubtsova Maya Yu.
Published: April 2022

Digital quantification based on counting of individual molecules is a promising approach for different biomedical applications due to its enhanced sensitivity. Here, we present a method for the digital detection of nucleic acids (DNA and RNA) on silicon microchips based on the counting of gold nanoparticles (GNPs) in DNA duplexes by scanning electron microscopy (SEM). Biotin-labeled DNA is hybridized with capture oligonucleotide probes immobilized on the microchips. Then biotin is revealed by a streptavidin–GNP conjugate followed by the detection of GNPs. Sharp images of each nanoparticle allow the visualization of hybridization results on a single-molecule level. The technique was shown to provide highly sensitive quantification of both short oligonucleotide and long double-strand DNA sequences up to 800 bp. The lowest limit of detection of 0.04 pM was determined for short 19-mer oligonucleotide. The method’s applicability was demonstrated for the multiplex quantification of several β-lactamase genes responsible for the development of bacterial resistance against β-lactam antibiotics. Determination of nucleic acids is effective for both specific DNA in lysates and mRNA in transcripts. The method is also characterized by high selectivity for single-nucleotide polymorphism discrimination. The proposed principle of digital quantification is a perspective for studying the mechanisms of bacterial antibiotic resistance and bacterial response to drugs.
It Takes a Village: Using Network Science to Identify the Effect of Individual Differences in Bilingual Experience for Theory of Mind
Authors: Navarro Ester , DeLuca Vincent , Rossi Eleonora
Published: April 2022

An increasing amount of research has examined the effects of bilingualism on performance in theory of mind (ToM) tasks. Bilinguals outperform monolinguals in ToM when comparing groups. However, it is unclear what aspects of the bilingual experience contribute to this effect in a dynamic construct like ToM. To date, bilingualism has been conceptualized as a dichotic skill that is distinct from monolingualism, obscuring nuances in the degree that different bilingual experience affects cognition. The current study used a combination of network science, cognitive, and linguistic behavioral measurements to explore the factors that influence perspective-taking ToM based on participants’ current and previous experience with language, as well as their family networks’ experience with language. The results suggest that some aspects of the bilingual experience predict task performance, but not others, and these predictors align with the two-system theory of ToM. Overall, the findings provide evidence for the extent to which individual differences in bilingualism are related to different cognitive outcomes.
Does the Type of Smartphone Usage Behavior Influence Problematic Smartphone Use and the Related Stress Perception?
Authors: Wickord Lea-Christin , Quaiser-Pohl Claudia Michaela
Published: April 2022

Problematic smartphone use (PSU) is defined as the inability to control the time spent on smartphones, which has long-term negative impacts on daily life. The use-and-gratifications approach is applied to smartphones and describes the extent to which users devote themselves to smartphones to obtain gratifications. These gratifications can be represented in the types of use (process, social, and habitual). This study examines the associations between PSU and the different types of use and their effects on perceived stress and self-perceived PSU. N = 108 subjects participated (65 women, 41 men, 2 diverse, mean age = 31.8; range 17–70). They completed the Mobile Phone Problem Use Scale (MPPUS-19), Perceived Stress Scale (PSS-10), a questionnaire on types of use, and a self-created scale for self-perceived PSU. Multiple linear regressions and correlations were calculated and show a relationship between PSU and perceived stress. All three types of use were shown to be predictors of PSU. For stress perception, only process use is a predictor. Both PSU and stress perception are predictors of the self-perceived PSU. Both stress and PSU interact with each other, and the different types of use determine how stressful smartphone use is perceived to be.
Economic and Social Interactions in Business Students during COVID-19 Confinement: Relationship with Sleep Disturbance
Authors: García Inmaculada Jimeno , Garvey Anne Marie
Published: April 2022

The objective of the study was to observe the effect of sleep on students in the first week (Point 1) of strict confinement and to analyze its evolution after one and two months (Point 2) of strict confinement during COVID-19. The evolution of sleep, in association with affected income status, family relations, and the death or infection of a family member or friend by COVID-19 was examined. Students responded to a survey that included questions relating to sleep quality and general well-being from the European Quality of Life Survey (EQLS). Sleep disturbance increased over strict confinement but was substantially more and with greater intensity in the case of students not living with family members. The results show that loss of family income, loss of a family member or friend, and having a friend or family member infected affected sleep quality negatively at Point 1. However, at Point 2, confinement itself affected students sleep, as well as the variables analyzed. Domestic harmony was a positive correlation for better sleep health. The study is important for managing coping policies and diagnosis.
Adjusted CT Image-Based Radiomic Features Combined with Immune Genomic Expression Achieve Accurate Prognostic Classification and Identification of Therapeutic Targets in Stage III Colorectal Cancer
Authors: Huang Yi-Ching , Tsai Yi-Shan , Li Chung-I , Chan Ren-Hao , Yeh Yu-Min , Chen Po-Chuan , Shen Meng-Ru , Lin Peng-Chan
Published: April 2022

To evaluate whether adjusted computed tomography (CT) scan image-based radiomics combined with immune genomic expression can achieve accurate stratification of cancer recurrence and identify potential therapeutic targets in stage III colorectal cancer (CRC), this cohort study enrolled 71 patients with postoperative stage III CRC. Based on preoperative CT scans, radiomic features were extracted and selected to build pixel image data using covariate-adjusted tensor classification in the high-dimension (CATCH) model. The differentially expressed RNA genes, as radiomic covariates, were identified by cancer recurrence. Predictive models were built using the pixel image and immune genomic expression factors, and the area under the curve (AUC) and F1 score were used to evaluate their performance. Significantly adjusted radiomic features were selected to predict recurrence. The association between the significantly adjusted radiomic features and immune gene expression was also investigated. Overall, 1037 radiomic features were converted into 33 × 32-pixel image data. Thirty differentially expressed genes were identified. We performed 100 iterations of 3-fold cross-validation to evaluate the performance of the CATCH model, which showed a high sensitivity of 0.66 and an F1 score of 0.69. The area under the curve (AUC) was 0.56. Overall, ten adjusted radiomic features were significantly associated with cancer recurrence in the CATCH model. All of these methods are texture-associated radiomics. Compared with non-adjusted radiomics, 7 out of 10 adjusted radiomic features influenced recurrence-free survival. The adjusted radiomic features were positively associated with PECAM1, PRDM1, AIF1, IL10, ISG20, and TLR8 expression. We provide individualized cancer therapeutic strategies based on adjusted radiomic features in recurrent stage III CRC. Adjusted CT scan image-based radiomics with immune genomic expression covariates using the CATCH model can efficiently predict cancer recurrence. The correlation between adjusted radiomic features and immune genomic expression can provide biological relevance and individualized therapeutic targets.
Predictors of Recurrence in Patients with Papillary Thyroid Carcinoma: Does Male Sex Matter?
Authors: Kim Hyeji , Kwon Hyungju , Moon Byung-In
Published: April 2022

Male patients with papillary thyroid carcinoma (PTC) usually have aggressive clinicopathological features, including large tumor size and lymph node metastasis; however, it is unclear whether male sex increases the risk of recurrence. Here, we evaluated the effect of sex on disease-free survival (DFS) of patients with PTC. Between 2009 and 2016, 1252 patients who underwent total thyroidectomy for PTC were enrolled; 157 (12.5%) were male and 1095 (87.5%) were female. With a mean follow-up of 6.6 years, five-year DFS rates were comparable between male and female patients (94.9% vs. 96.9%; p = 0.616) after adjusting for potential confounders. Multivariate Cox regression analysis also demonstrated that male sex was not an independent risk factor for recurrence (HR 1.982, 95% CI 0.831–4.726). Subgroup analyses further indicated that both male and female sex—in terms of their associations with five-year DFS—were comparable with other variables, including age < 55 years (94.5% vs. 97.3%; p = 0.520) and tumor size > 1 cm (91.9% vs. 97.0%; p = 0.243). In conclusion, male sex was not associated with the risk of recurrence in patients with PTC. Male patients do not always require aggressive treatment and follow-up approaches.
Histone Deacetylase Inhibitors Impair Glioblastoma Cell Motility and Proliferation
Authors: Rampazzo Elena , Manfreda Lorenzo , Bresolin Silvia , Cani Alice , Mariotto Elena , Bortolozzi Roberta , Della Puppa Alessandro , Viola Giampietro , Persano Luca
Published: April 2022

Despite being subjected to high-dose chemo and radiotherapy, glioblastoma (GBM) patients still encounter almost inevitable relapse, due to the capability of tumor cells to disseminate and invade normal brain tissues. Moreover, the presence of a cancer stem cell (CSC) subpopulation, already demonstrated to better resist and evade treatments, further frustrates potential therapeutic approaches. In this context, we previously demonstrated that GBM is characterized by a tightly-regulated balance between the β-catenin cofactors TCF1 and TCF4, with high levels of TCF4 responsible for sustaining CSC in these tumors; thus, supporting their aggressive features. Since histone deacetylase inhibitors (HDI) have been reported to strongly reduce TCF4 levels in colon cancer cells, we hypothesized that they could also exert a similar therapeutic action in GBM. Here, we treated primary GBM cultures with Trichostatin-A and Vorinostat, demonstrating their ability to strongly suppress the Wnt-dependent pathways; thus, promoting CSC differentiation and concomitantly impairing GBM cell viability and proliferation. More interestingly, analysis of their molecular effects suggested a prominent HDI action against GBM cell motility/migration, which we demonstrated to rely on the inhibition of the RhoA-GTPase and interferon intracellular cascades. Our results suggest HDI as potential therapeutic agents in GBM, through their action on multiple cancer hallmarks.
Deletion of Hnrnpk Gene Causes Infertility in Male Mice by Disrupting Spermatogenesis
Authors: Xu Haixia , Guo Jiahua , Wu Wei , Han Qiu , Huang Yueru , Wang Yaling , Li Cencen , Cheng Xiaofang , Zhang Pengpeng , Xu Yongjie
Published: April 2022

HnRNPK is a heterogeneous nuclear ribonucleoprotein (hnRNP) that has been firmly implicated in transcriptional and post-transcriptional regulation. However, the molecular mechanisms by which hnRNPK orchestrates transcriptional or post-transcriptional regulation are not well understood due to early embryonic lethality in homozygous knockout mice, especially in a tissue-specific context. Strikingly, in this study, we demonstrated that hnRNPK is strongly expressed in the mouse testis and mainly localizes to the nucleus in spermatogonia, spermatocytes, and round spermatids, suggesting an important role for hnRNPK in spermatogenesis. Using a male germ cell-specific hnRNPK-depleted mouse model, we found that it is critical for testicular development and male fertility. The initiation of meiosis of following spermatogenesis was not affected in Hnrnpk cKO mice, while most germ cells were arrested at the pachytene stage of the meiosis and no mature sperm were detected in epididymides. The further RNA-seq analysis of Hnrnpk cKO mice testis revealed that the deletion of hnRNPK disturbed the expression of genes involved in male reproductive development, among which the meiosis genes were significantly affected, and Hnrnpk cKO spermatocytes failed to complete the meiotic prophase. Together, these results identify hnRNPK as an essential regulator of spermatogenesis and male fertility.
Sarcopenia in Children with Solid Organ Tumors: An Instrumental Era
Authors: Ritz Annika , Lurz Eberhard , Berger Michael
Published: April 2022

Sarcopenia has recently been studied in both adults and children and was found to be a prognostic marker for adverse outcome in a variety of patient groups. Our research showed that sarcopenia is a relevant marker in predicting outcome in children with solid organ tumors, such as hepatoblastoma and neuroblastoma. This was especially true in very ill, high-risk groups. Children with cancer have a higher likelihood of ongoing loss of skeletal muscle mass due to a mismatch in energy intake and expenditure. Additionally, the effects of cancer therapy, hormonal alterations, chronic inflammation, multi-organ dysfunction, and a hypermetabolic state all contribute to a loss of skeletal muscle mass. Sarcopenia seems to be able to pinpoint this waste to a high degree in a new and objective way, making it an additional tool in predicting and improving outcome in children. This article focuses on the current state of sarcopenia in children with solid organ tumors. It details the pathophysiological mechanisms behind sarcopenia, highlighting the technical features of the available methods for measuring muscle mass, strength, and function, including artificial intelligence (AI)-based techniques. It also reviews the latest research on sarcopenia in children, focusing on children with solid organ tumors.
Mass Spectrometry for Neurobiomarker Discovery: The Relevance of Post-Translational Modifications
Authors: Azevedo Rita , Jacquemin Chloé , Villain Nicolas , Fenaille François , Lamari Foudil , Becher François
Published: April 2022

Neurodegenerative diseases are incurable, heterogeneous, and age-dependent disorders that challenge modern medicine. A deeper understanding of the pathogenesis underlying neurodegenerative diseases is necessary to solve the unmet need for new diagnostic biomarkers and disease-modifying therapy and reduce these diseases’ burden. Specifically, post-translational modifications (PTMs) play a significant role in neurodegeneration. Due to its proximity to the brain parenchyma, cerebrospinal fluid (CSF) has long been used as an indirect way to measure changes in the brain. Mass spectrometry (MS) analysis in neurodegenerative diseases focusing on PTMs and in the context of biomarker discovery has improved and opened venues for analyzing more complex matrices such as brain tissue and blood. Notably, phosphorylated tau protein, truncated α-synuclein, APP and TDP-43, and many other modifications were extensively characterized by MS. Great potential is underlying specific pathological PTM-signatures for clinical application. This review focuses on PTM-modified proteins involved in neurodegenerative diseases and highlights the most important and recent breakthroughs in MS-based biomarker discovery.
Microstructure and Mechanical Properties of Co-Sputtering (Mo, Hf)N Coatings
Authors: Hsu Shu-Yu , Wu Fan-Bean
Published: April 2022

This work focused on the microstructure and mechanical properties of (Mo, Hf)N coatings deposited by radio frequency reactive magnetron co-sputtering technique with input power modulation. The coating characteristics, including indentation hardness, modulus, and tribological behavior, were discussed in terms of deposition parameter, composition, phase, and microstructure. The (Mo, Hf)N thin films were fabricated at a fixed Ar/N2 inlet gas ratio of 12/8 sccm/sccm and modulated input powers. The input power of Mo was fixed at 150 W, while that of the Hf target was managed from 25 to 200 W. The deposition rate and the Hf content of the (Mo, Hf)N coatings increased with input power. The (Mo, Hf)N ternary nitride coatings showed a polycrystalline microstructure with B1-MoN(111), β-Mo2N (112), γ-Mo2N(111), (200), and MoN2(200) phases in X-ray diffraction patterns as input power modulation were 150/25 to 150/100 W/W. The multiple phase microstructure feature and detail crystal development were demonstrated through transmission electron microscopy. According to nanoindentation and wear test results, ternary (Mo, Hf)N coatings represented more improved mechanical characteristics than the MoN and HfN binary nitride films. The 150/100 W/W deposited (Mo, Hf)N coating exhibited a highest hardness of 22.5 GPa when Hf content was at 5.6 at.%. The superior anti-wear behavior of this film with least wear damage was observed as well. The multiphase and solid-solution strengthening of the (Mo, Hf)N coatings, i.e., a microstructure feature of mixed B1-MoN, β-Mo2N, γ-Mo2N, and MoN2 phases and Hf doping in MoN, were the responsible for the superior mechanical and tribological behavior for the (Mo, Hf)N coatings.
Superpixel-Oriented Label Distribution Learning for Skin Lesion Segmentation
Authors: Zhou Qiaoer , He Tingting , Zou Yuanwen
Published: April 2022

Lesion segmentation is a critical task in skin cancer analysis and detection. When developing deep learning-based segmentation methods, we need a large number of human-annotated labels to serve as ground truth for model-supervised learning. Due to the complexity of dermatological images and the subjective differences of different dermatologists in decision-making, the labels in the segmentation target boundary region are prone to produce uncertain labels or error labels. These labels may lead to unsatisfactory performance of dermoscopy segmentation. In addition, the model trained by the errored one-hot label may be overconfident, which can lead to arbitrary prediction and model overfitting. In this paper, a superpixel-oriented label distribution learning method is proposed. The superpixels formed by the simple linear iterative cluster (SLIC) algorithm combine one-hot labels constraint and define a distance function to convert it into a soft probability distribution. Referring to the model structure of knowledge distillation, after Superpixel-oriented label distribution learning, we get soft labels with structural prior information. Then the soft labels are transferred as new knowledge to the lesion segmentation network for training. Ours method on ISIC 2018 datasets achieves an Dice coefficient reaching 84%, sensitivity 79.6%, precision 80.4%, improved by 19.3%, 8.6% and 2.5% respectively in comparison with the results of U-Net. We also evaluate our method on the tasks of skin lesion segmentation via several general neural network architectures. The experiments show that ours method improves the performance of network image segmentation and can be easily integrated into most existing deep learning architectures.
Using the SARIMA Model to Forecast the Fourth Global Wave of Cumulative Deaths from COVID-19: Evidence from 12 Hard-Hit Big Countries
Authors: Perone Gaetano
Published: April 2022

The COVID-19 pandemic is a serious threat to all of us. It has caused an unprecedented shock to the world’s economy, and it has interrupted the lives and livelihood of millions of people. In the last two years, a large body of literature has attempted to forecast the main dimensions of the COVID-19 outbreak using a wide set of models. In this paper, I forecast the short- to mid-term cumulative deaths from COVID-19 in 12 hard-hit big countries around the world as of 20 August 2021. The data used in the analysis were extracted from the Our World in Data COVID-19 dataset. Both non-seasonal and seasonal autoregressive integrated moving averages (ARIMA and SARIMA) were estimated. The analysis showed that: (i) ARIMA/SARIMA forecasts were sufficiently accurate in both the training and test set by always outperforming the simple alternative forecasting techniques chosen as benchmarks (Mean, Naïve, and Seasonal Naïve); (ii) SARIMA models outperformed ARIMA models in 46 out 48 metrics (in forecasting future values), i.e., on 95.8% of all the considered forecast accuracy measures (mean absolute error [MAE], mean absolute percentage error [MAPE], mean absolute scaled error [MASE], and the root mean squared error [RMSE]), suggesting a clear seasonal pattern in the data; and (iii) the forecasted values from SARIMA models fitted very well the observed (real-time) data for the period 21 August 2021–19 September 2021 for almost all the countries analyzed. This article shows that SARIMA can be safely used for both the short- and medium-term predictions of COVID-19 deaths. Thus, this approach can help government authorities to monitor and manage the huge pressure that COVID-19 is exerting on national healthcare systems.
Transversal Competences and Employability of University Students: Converging towards Service-Learning
Authors: Rego Miguel A. Santos , Sáez-Gambín Daniel , González-Geraldo José Luis , García-Romero David
Published: April 2022

We are living in times of great transformations within the field of education and the labor market. These changes are connected and have to do with an expanded knowledge society, whose implications reach the levels of employability in times of uncertainty. Within this framework, the main purpose of our study is to perform a theoretical analysis and an empirical approach to the influence that transversal competences (soft skills) may have on the degree of employability of university students. We have identified some of those competences and we have tested them with a sample of 83 employers and 1249 students using a Likert scale. Our results show the interest of employers in the mastery of transversal competences and inequalities in terms of students’ perception thereof. We did not find any significant differences between students starting their degree and those who were about to complete it. However, we did find differences between the students who participated in experiential activities and those who did not, in favor of the former. Due to the importance of experiential learning in our results, we dedicate our discussion to theoretically exploring whether the pedagogical approach of Service-Learning (SL) might contribute to a better connection between transversal competences and employability.
Securing Drug Distribution Systems from Tampering Using Blockchain
Authors: Humayun Mamoona , Jhanjhi Noor Zaman , Niazi Mahmood , Amsaad Fathi , Masood Isma
Published: April 2022

The purpose of this study is to overcome coordination flaws and enhance end-to-end security in the drug distribution market (DDM). One of the major issues in drug market coordination management is the absence of a centralized monitoring system to provide adequate market control and offer real-time prices, availability, and authentication data. Further, tampering is another serious issue affecting the DDM, and as a consequence, there is a significant global market for counterfeit drugs. This vast counterfeit drug business presents a security risk to the distribution system. This study presents a blockchain-based solution to challenges such as coordination failure, secure drug delivery, and pharmaceutical authenticity. To optimize the drug distribution process (DDP), a framework for drug distribution is presented. The proposed framework is evaluated using mathematical modeling and a real-life case study. According to our results, the proposed technique helps to maintain market equilibrium by guaranteeing that there is adequate demand while maintaining supply. Using the suggested framework, massive data created by the medication supply chain would be appropriately handled, allowing market forces to be better regulated and no manufactured shortages to inflate medicine prices. The proposed framework calls for the Drug Regulatory Authority (DRA) to authenticate users on blockchain and to monitor end-to-end DDP. Using the proposed framework, big data generated through drug supply chain will be properly managed; thus, market forces will be better controlled, and no artificial shortages will be generated to raise drug costs.
Leakage Current Stability Analysis for Subthreshold SRAM
Authors: Bai Na , Hu Zhiqiang , Wang Yi , Xu Yaohua
Published: April 2022

Low-power memories typically operate in the subthreshold region of the device; however, as the supply voltage continues to decrease, the impact of leakage current on SRAM stability becomes more significant. The traditional method of measuring static noise tolerance only considers the effect of voltage, and the measurement results are not accurate enough. Therefore, this paper proposes a leakage-current-based stability analysis that provides better metrics, reads current noise tolerance (RINM) and writes current noise tolerance (WINM) to measure the stability of subthreshold SRAMs. Both currents and voltages were taken into account. The results demonstrate that the method is more accurate than the conventional method under subthreshold levels.
The Impact of Thermo-Modernization and Forecast Regulation on the Reduction of Thermal Energy Consumption and Reduction of Pollutant Emissions into the Atmosphere on the Example of Prefabricated Buildings
Authors: Piotrowska-Woroniak Joanna , Cieśliński Krzysztof , Woroniak Grzegorz , Bielskus Jonas
Published: April 2022

The paper presents an assessment of thermal energy consumption for heating in 10 buildings made in the OWT-67N prefabricated large-panel technology from 1983 to 1986. The work covers the years 2002–2020 in three periods: before and after thermal modernization and after the use of an innovative weather prediction heating system control in buildings. The analysis made it possible to assess the impact of carrying out a deep thermal modernization, and then installing a modern forecast regulation system in terms of reducing heat energy consumption for central heating purposes, as well as reducing greenhouse gas emissions, such as CO2, SOx, NOx, CO and benzo(a)pyrene, into the atmosphere. The implementation of deep thermal modernization in buildings allowed for savings of 19.8–35% of thermal energy consumption for heating. The use of additional regulation based on prediction saved from 4.8 to 23.5%, except for one building BU10, where there was an increase in final energy consumption by 2.1%. Replacing the weather regulation in heating stations with the forecast regulation additionally reduced the emission of pollutants by 11.1%, compared to the reduction of pollutants achieved as a result of the thermal modernization of buildings alone, amounting to an average of 29.7%.
Feature Selection in Energy Consumption of Solar Catamaran INER 1 on Galapagos Island
Authors: Moya Marcelo , Martínez-Gómez Javier , Urresta Esteban , Cordovez-Dammer Martín
Published: April 2022

Maritime passenger transport in the Galapagos Islands–Itabaca Channel is based on boats with combustion engines that consume an annual average of 4200 gallons of fuel and produce about 38 tons of CO2 per year. The operation of the solar catamaran “INER 1” electric propulsion (PV) is a renewable and sustainable model for passenger shipping in the Galapagos Islands. In this regard, the detailed study of the relationship between the variability of solar radiation, the abrupt change of tides due to changes in wind speed and direction, and the increase in tourists, according to dry and wet seasons, cause high energy consumption. The boats must absorb energy from the electrical grid of the islands; this energy is from renewable (solar and wind) and, mostly, of fossil origin so identifying the source of the energy absorbed by the boats is essential. The aim of this study was to select the most influential attributes in the operation of the solar catamaran “INER 1” in the Galapagos Islands. The methodology for knowledge discovery in the databases was determined by selecting attributes that combine environmental, social, and energy variables affecting the energy performance of the solar catamaran. The energy consumption of the boats features a direct relationship with the attributes defined in this research as: (1) Energ (energy used), (2) Tur (tourists and residents), (3) Fotov (PV park), (4) Glrad (global radiation), (5) date (date and time), (6) Term9 (thermo-electric 9). Considering the six best attributes filtered by the proposed algorithms, 4.95% in the mean squared error parameter and a 98.94% accuracy in the classification and prediction of the energy consumed by boats were obtained.
Polar Voltage Space Vectors of the Six-Phase Two-Level VSI
Authors: Iwaszkiewicz Jan , Muc Adam , Bielecka Agata
Published: April 2022

The paper recommends polar voltage space vectors of the six-phase and two-level inverter as a useful mathematical tool for vector control of the inverter. The inverter model is described using three mathematical tools: analytic expressions, voltage state, and space vectors. The analytic formulas allow for the determination of elementary physical inverter quantities: current and voltage. The state voltage vectors make it easy to define phase voltage distribution in every possible state of the inverter and voltage space vectors are the most important tool used for inverters’ control. The space vectors are defined using the standard voltage space vector transformation, while the state vectors are denoted by binary numbers and determine all voltage states of the inverter. The proposed notation system and vectors’ marking seem to be extremely useful in specifying the inverter states. This system certifies a deep correlation between the space and state vectors as they are described using the same digits. The properties of the system were confirmed during the simulation tests. Some examples of the inverter vector control based on polar voltage space vectors prove that the proposed solution is a useful mathematical tool and may be in fact suitable in designing inverter control algorithms. The simulation experiment described in this paper shows that the assumed control strategy allows for a significant reduction in the amount of switching compared to PWM. At the same time, the adopted vector strategy allows for the obtaining of a very favorable value of the current THD coefficient while maintaining the RMS values of the currents.
Predicting the Average Compression Strength of CLT by Using the Average Density or Compressive Strength of Lamina
Authors: Tian Zhaopeng , Gong Yingchun , Xu Junhua , Li Mingyue , Wang Zhaohui , Ren Haiqing
Published: April 2022

The compressive strength in the major direction of cross-laminated timber CLT is the key to supporting the building load when CLT is used as load-bearing walls in high-rise wood structures. This study mainly aims to present a model for predicting the average compressive strength of CLT and promoting the utilization of CLT made out of planted larch. The densities and compressive strengths of lamina specimens and CLT samples with widths of 89 and 178 mm were evaluated, and their relationship was analyzed to build a prediction model by using Monte Carlo simulation. The results reveal that the average density of the lamina and CLT were about equal, whereas the average compressive strength of the CLT was just about 72% of that of the lamina. Width exerted no significant effect on the average compressive strength of the CLT, but homogenization caused the wider CLT to have a smaller variation than that of the lamina. The average compressive strength of the lamina could be calculated by using the average density of lamina multiply by 103.10, and the average compressive strength of the CLT could be calculated according to the compression strength of lamina in major and minor direction, therefore, a new prediction model is determined to predict the average compression strength of CLT by using the average density of lamina or CLT, the average compression strength of CLT made in this study is about 74.23 times of the average density of the lamina. The results presented in this study can be used to predict the average compressive strength of CLT by using the average density of lamina and provide a fundamental basis for supporting the utilization of CLT as load-bearing walls.
Natural Pectin-Based Edible Composite Coatings with Antifungal Properties to Control Green Mold and Reduce Losses of ‘Valencia’ Oranges
Authors: Alvarez María Victoria , Palou Lluís , Taberner Verònica , Fernández-Catalán Asunción , Argente-Sanchis Maricruz , Pitta Eleni , Pérez-Gago María Bernardita
Published: April 2022

Novel pectin-based, antifungal, edible coatings (ECs) were formulated by the addition of natural extracts or essential oils (EOs), and their ability to control green mold (GM), caused by Penicillium digitatum, and preserve postharvest quality of ‘Valencia’ oranges was evaluated. Satureja montana, Cinnamomum zeylanicum (CN), Commiphora myrrha (MY) EOs, eugenol (EU), geraniol (GE), vanillin, and propolis extract were selected as the most effective antifungal agents against P. digitatum in in vitro assays. Pectin-beeswax edible coatings amended with these antifungals were applied to artificially inoculated oranges to evaluate GM control. ECs containing GE (2 g/kg), EU (4 and 8 g/kg), and MY EO (15 g/kg) reduced disease incidence by up to 58% after 8 days of incubation at 20 °C, while CN (8 g/kg) effectively reduced disease severity. Moreover, ECs formulated with EU (8 g/kg) and GE (2 g/kg) were the most effective on artificially inoculated cold-stored oranges, with GM incidence reductions of 56 and 48% after 4 weeks at 5 °C. Furthermore, ECs containing EU and MY reduced weight loss and maintained sensory and physicochemical quality after 8 weeks at 5 °C followed by 7 days at 20 °C. Overall, ECs with EU were the most promising and could be a good natural, safe, and eco-friendly commercial treatment for preserving orange postharvest quality.
MicroRNA-132-3p, Downregulated in Myeloid Angiogenic Cells from Hereditary Hemorrhagic Telangiectasia Patients, Is Enriched in the TGFβ and PI3K/AKT Signalling Pathways
Authors: Cannavicci Anthony , Zhang Qiuwang , Faughnan Marie E. , Kutryk Michael J. B.
Published: April 2022

Background. Hereditary hemorrhagic telangiectasia (HHT) is a rare, autosomal dominant genetic disorder characterized by life-threatening vascular dysplasia. Myeloid angiogenic cells (MACs), alternatively called early endothelial progenitor cells or circulating angiogenic cells, do not directly incorporate into developing blood vessels, but augment angiogenesis in a paracrine manner. MAC dysfunction has been reported in HHT. MicroRNAs (miRNAs) regulate cellular function by modulating gene expression post-transcriptionally. To date, the role of miRNAs in HHT MAC dysfunction has not been documented. Objective. The goal of this study was to comparatively profile miRNAs in HHT patient and control MACs to identify dysregulated miRNAs that may be responsible for the observed MAC dysfunction in HHT. Methodology/Results. Twenty-three dysregulated miRNAs (twenty-one upregulated and two downregulated) in HHT MACs were identified with a TaqMan miRNA microarray. Pathway enrichment analysis showed that the dysregulated miRNAs were significantly enriched in pathways involved in HHT pathogenesis, such as the transforming growth factor β (TGFβ), phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT), and Hippo signalling pathways. Furthermore, miR-132-3p was determined to be significantly reduced in HHT MACs compared with controls by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Bioinformatic analysis revealed that miR-132-3p is significantly enriched in the TGFβ and PI3K/AKT signalling pathways, targeting SMAD4, an effector of the TGFβ signalling pathway and RASA1, a negative regulator of the PI3K/AKT signalling pathway, respectively. Conclusion. MiRNA dysregulation, specifically reduced expression of miR-132-3p, in HHT MACs was identified. The dysregulated miRNAs are significantly enriched in the TGFβ, PI3K/AKT, and Hippo signalling pathways. These data suggest that alteration in miRNA expression may impair these pathways and contribute to MAC dysfunction in HHT.
A Cohort Study on the Effect of Parental Mind-Mindedness in Parent−Child Interaction Therapy
Authors: Meynen Merlijn , Colonnesi Cristina , Abrahamse Mariëlle E. , Hein Irma , Stams Geert-Jan J. M. , Lindauer Ramón J. L. L.
Published: April 2022

Parent−child interaction therapy (PCIT) is a short-term, evidence-based intervention for caregivers with children aged between 2 and 7 who exhibit behavioral problems. PCIT is effective, but has a high attrition rate ranging from 27% to 69%. We hypothesize that a low level of parental mind-mindedness—the parent’s propensity to treat the child as an intentional agent with its own thoughts and emotions—might contribute to premature attrition or cause families to profit less from treatment. To test these hypotheses, we performed a retrospective cohort study in a time-limited, home-based PCIT sample (n = 19) and in a clinic-based PCIT sample (n = 25), to investigate whether parents with a medium-high level of mind-mindedness differ from parents with a medium-low level of mind-mindedness in the outcome measures of PCIT (child’s behavioral problems, parenting skills and stress and mothers’ anxious and depressed symptoms). Furthermore, we examined if mind-mindedness was related to attrition and (for clinic-based PCIT only) number of sessions. Repeated measures ANOVA showed that mothers with a medium-high level of mind-mindedness displayed more improvement in two parenting skills benefiting a positive parent−child interaction. Furthermore, we found a group effect of mind-mindedness in the PCIT-home sample, with mothers with a medium-high level of mind-mindedness showing better results on most outcome measures. Our findings suggest that adding a mind-mindedness improving intervention prior to or during PCIT could benefit mothers with a medium to low level of mind-mindedness.
Door-to-Door Transportation Services for Reduced Mobility Population: A Descriptive Analytics of the City of Barcelona
Authors: Portell Laura , Morera Sergi , Ramalhinho Helena
Published: April 2022

A central issue in modern cities is providing inclusive transportation services for people with reduced mobility. In particular, Barcelona is offering a public door-to-door pickup transportation service complementary to the adapted regular public transport. In this work, we apply descriptive analytics to provide a detailed picture of the service by introducing and analyzing a new dataset related to this transportation service. We highlight some of the main problems of the service by processing the data associated with the users and the trips. We also suggest ideas for improving the service. Finally, we propose a trip assignment system based on priorities related to the user or trip characteristics that could improve the quality of the service.
Study on the Co-Benefits of Air Pollution Control and Carbon Reduction in the Yellow River Basin: An Assessment Based on a Spatial Econometric Model
Authors: Cai Zhongyao , Yang Xiaohui , Lin Huaxing , Yang Xinyu , Jiang Ping
Published: April 2022

To assess the green and low-carbon development of the Yellow River Basin (YRB) in China, this study utilizes an evaluation index system based on the framework of driving force, pressure, state, impacts, response, and management, and it measured the comprehensive scores of the co-benefits of carbon reduction and air pollution control in the YRB. The global Moran index was used to analyze the spatial correlation characteristics of co-benefits, and a generalized spatial measurement model was constructed to demonstrate their spatial spillover effects. The results show that the co-benefits steadily increased every year. The co-benefits had a significant positive spatial correlation and showed a development trend of “up–down–up”. According to the spillover effect test, the economic development level, education level, and intensity of environmental regulations had significant positive effects, while the level of urbanization and foreign investment had significant negative effects. Considering these results and the aim of promoting green and low-carbon development, clear detection of the spatial spillover characteristics of the co-benefits should be prioritized, followed by an understanding of the spatial transmission mechanism of carbon and air pollutant emission and transfer. Policy recommendations are also proposed including upgrading industrial structure, focusing on the development of modern services and high-tech industry, and strictly implementing the industrial environment access system.
Returning to Work after the COVID-19 Pandemic Earthquake: A Systematic Review
Authors: Garzillo Elpidio Maria , Cioffi Arcangelo , Carta Angela , Monaco Maria Grazia Lourdes
Published: April 2022

Background: The ongoing SARS-CoV-2 pandemic has disrupted life and work habits and has produced landmark changes worldwide. This systematic review aimed to analyse the management of Return to Work (RTW) by work organisations following the virus spread. Methods: A selection of 2477 papers, using string research on PubMed, Embase, Web of Science and Scopus from January 2020 to October 2021, were analysed. Results: Fifty-one articles were finally included, and the results obtained were discussed from three different points of view. Twenty articles concerning ‘Remodelling of Work Organization’ proposed some model strategies for resumption to work. Twenty-one papers, including ‘Clinical Evaluation of Workers’, mostly explored the psychosocial impact of returned workers. Finally, twelve articles explored the best ‘Testing Strategies related to RTW’. Despite the heterogeneity of included articles, several interesting approaches have emerged in managing RTW. Conclusions: The reported experiences could help to develop an RTW model for COVID-19 and future pandemics.